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opentelemetry-python-contrib-0.66b2/README.md 0000664 0000000 0000000 00000027630 15270700723 0021034 0 ustar 00root root 0000000 0000000 ---
Getting Started
•
API Documentation
•
Getting In Touch (GitHub Discussions)
Contributing
•
Instrumentations
---
# OpenTelemetry Python Contrib
The Python auto-instrumentation libraries for [OpenTelemetry](https://opentelemetry.io/) (per [OTEP 0001](https://github.com/open-telemetry/oteps/blob/main/text/0001-telemetry-without-manual-instrumentation.md))
## Index
* [Installation](#installation)
* [Releasing](#releasing)
* [Releasing a package as `1.0` stable](#releasing-a-package-as-10-stable)
* [Semantic Convention status of instrumentations](#semantic-convention-status-of-instrumentations)
* [Contributing](#contributing)
* [Thanks to all the people who already contributed](#thanks-to-all-the-people-who-already-contributed)
## Installation
This repository includes installable packages for each instrumented library. Libraries that produce telemetry data should only depend on `opentelemetry-api`,
and defer the choice of the SDK to the application developer. Applications may
depend on `opentelemetry-sdk` or another package that implements the API.
**Please note** that these libraries are currently in _beta_, and shouldn't
generally be used in production environments.
Unless explicitly stated otherwise, any instrumentation here for a particular library is not developed or maintained by the authors of such library.
The
[`instrumentation/`](https://github.com/open-telemetry/opentelemetry-python-contrib/tree/main/instrumentation)
directory includes OpenTelemetry instrumentation packages, which can be installed
separately as:
```sh
pip install opentelemetry-instrumentation-{integration}
```
To install the development versions of these packages instead, clone or fork
this repo and do an [editable
install](https://pip.pypa.io/en/stable/topics/local-project-installs/#editable-installs):
```sh
pip install -e ./instrumentation/opentelemetry-instrumentation-{integration}
```
## Releasing
Maintainers release new versions of the packages in `opentelemetry-python-contrib` on a monthly cadence. See [releases](https://github.com/open-telemetry/opentelemetry-python-contrib/releases) for all previous releases.
Contributions that enhance OTel for Python are welcome to be hosted upstream for the benefit of group collaboration. Maintainers will look for things like good documentation, good unit tests, and in general their own confidence when deciding to release a package with the stability guarantees that are implied with a `1.0` release.
To resolve this, members of the community are encouraged to commit to becoming a CODEOWNER for packages in `-contrib` that they feel experienced enough to maintain. CODEOWNERS can then follow the checklist below to release `-contrib` packages as 1.0 stable:
### Releasing a package as `1.0` stable
To release a package as `1.0` stable, the package:
- SHOULD have a CODEOWNER. To become one, submit an issue and explain why you meet the responsibilities found in [CODEOWNERS](.github/CODEOWNERS).
- MUST have unit tests that cover all supported versions of the instrumented library.
- e.g. Instrumentation packages might use different techniques to instrument different major versions of python packages
- MUST have clear documentation for non-obvious usages of the package
- e.g. If an instrumentation package uses flags, a token as context, or parameters that are not typical of the `BaseInstrumentor` class, these are documented
- After the release of `1.0`, a CODEOWNER may no longer feel like they have the bandwidth to meet the responsibilities of maintaining the package. That's not a problem at all, life happens! However, if that is the case, we ask that the CODEOWNER please raise an issue indicating that they would like to be removed as a CODEOWNER so that they don't get pinged on future PRs. Ultimately, we hope to use that issue to find a new CODEOWNER.
## Semantic Convention status of instrumentations
In our efforts to maintain optimal user experience and prevent breaking changes for transitioning into stable semantic conventions, OpenTelemetry Python is adopting the semantic convention migration plan for several instrumentations. Currently this plan is only being adopted for [HTTP-related instrumentations](https://github.com/open-telemetry/semantic-conventions/blob/main/docs/non-normative/http-migration.md), but will eventually cover all types. Please refer to the `semconv status` column of the [instrumentation README](instrumentation/README.md) of the current status of instrumentations' semantic conventions. The possible values are `development`, `stable` and `migration` referring to [status](https://github.com/open-telemetry/opentelemetry-specification/blob/v1.31.0/specification/document-status.md#lifecycle-status) of that particular semantic convention. `Migration` refers to an instrumentation that currently supports the migration plan.
## Contributing
See [CONTRIBUTING.md](CONTRIBUTING.md)
We meet weekly on Thursday at 9AM PT. The meeting is subject to change depending on contributors' availability. Check the [OpenTelemetry community calendar](https://calendar.google.com/calendar/embed?src=c_2bf73e3b6b530da4babd444e72b76a6ad893a5c3f43cf40467abc7a9a897f977%40group.calendar.google.com) for specific dates and for the Zoom link.
Meeting notes are available as a public [Google doc](https://docs.google.com/document/d/18w8zOBm_mbety0OqlPwxc7dvnfu641EgmrO4AdJef0U/edit?tab=t.0).
The meeting is open for all to join. We invite everyone to join our meeting, regardless of your experience level. Whether you're a seasoned OpenTelemetry developer, just starting your journey, or simply curious about the work we do, you're more than welcome to participate!
### Maintainers
- [Aaron Abbott](https://github.com/aabmass), Google
- [Emídio Neto](https://github.com/emdneto), Independent
- [Leighton Chen](https://github.com/lzchen), Microsoft
- [Lukas Hering](https://github.com/herin049), Oracle
- [Riccardo Magliocchetti](https://github.com/xrmx), Elastic
For more information about the maintainer role, see the [community repository](https://github.com/open-telemetry/community/blob/main/guides/contributor/membership.md#maintainer).
### Approvers
- [Diego Hurtado](https://github.com/ocelotl), Dash0
- [Dylan Russell](https://github.com/dylanrussell), Google
- [Héctor Hernández](https://github.com/hectorhdzg), Microsoft
- [Keith Decker](https://github.com/keith-decker), Cisco/Splunk
- [Liudmila Molkova](https://github.com/lmolkova), Google
- [Mike Goldsmith](https://github.com/MikeGoldsmith), Honeycomb
- [Pablo Collins](https://github.com/pmcollins), Splunk
- [Srikanth Chekuri](https://github.com/srikanthccv), signoz.io
- [Tammy Baylis](https://github.com/tammy-baylis-swi), SolarWinds
For more information about the approver role, see the [community repository](https://github.com/open-telemetry/community/blob/main/guides/contributor/membership.md#approver).
### Emeritus
- [Alex Boten](https://github.com/codeboten), Maintainer
- [Ashutosh Goel](https://github.com/ashu658), Approver
- [Jeremy Voss](https://github.com/jeremydvoss), Approver
- [Nathaniel Ruiz Nowell](https://github.com/NathanielRN), Approver
- [Nikolay Sokolik](https://github.com/nikosokolik), Approver
- [Nikolay Sokolik](https://github.com/oxeye-nikolay), Approver
- [Owais Lone](https://github.com/owais), Maintainer
- [Owais Lone](https://github.com/owais), Approver
- [Sanket Mehta](https://github.com/sanketmehta28), Approver
- [Shalev Roda](https://github.com/shalevr), Maintainer
- [Shalev Roda](https://github.com/shalevr), Approver
- [Yusuke Tsutsumi](https://github.com/toumorokoshi), Maintainer
For more information about the emeritus role, see the [community repository](https://github.com/open-telemetry/community/blob/main/guides/contributor/membership.md#emeritus-maintainerapprovertriager).
### Thanks to all of our contributors!
opentelemetry-python-contrib-0.66b2/RELEASING.md 0000664 0000000 0000000 00000023433 15270700723 0021405 0 ustar 00root root 0000000 0000000 # Release instructions
## Preparing a new major or minor release
* Run the [Prepare release branch workflow](https://github.com/open-telemetry/opentelemetry-python-contrib/actions/workflows/prepare-release-branch.yml).
* Press the "Run workflow" button, and leave the default branch `main` selected.
* If making a pre-release of stable components (e.g. release candidate),
enter the pre-release version number, e.g. `1.9.0rc2`.
(otherwise the workflow will pick up the version from `main` and just remove the `.dev` suffix).
* Review the two pull requests that it creates.
(one is targeted to the release branch and one is targeted to `main`).
* The builds will fail for the release PR because of validation rules. Follow the [release workflow](https://github.com/open-telemetry/opentelemetry-python/blob/main/RELEASING.md) for the core repo up until this same point.
* Close and reopen the PR so that the workflow will take into account the label automation we have in place
* Merge the release PR.
* Merge the PR to main (this can be done separately from [making the release](#making-the-release))
### Preparing a major or minor release for individual package
> [!NOTE]
> Per-package major or minor release is supported for the following packages only:
> - opentelemetry-opamp-client
> - opentelemetry-propagator-aws-xray
> - opentelemetry-resource-detector-azure
> - opentelemetry-resourcedetector-gcp
> - opentelemetry-sdk-extension-aws
> - opentelemetry-instrumentation-valkey-py
> - opentelemetry-util-genai
>
> These libraries are also excluded from the general release.
>
> The deprecated GenAI instrumentations listed under [Releasing individual package](#releasing-individual-package)
> are intentionally absent here: they no longer get major or minor releases from this repository, only
> patch releases from their existing `package-release/` branches.
Package release preparation is handled by the [`[Package] Prepare release`](./.github/workflows/package-prepare-release.yml) workflow that allows
to pick a specific package to release. It follows the same versioning strategy and process as the general release.
Long-term package release branch follows `package-release/{package-name}/v{major}.{minor}.x` (or `package-release/{package-name}/v{major}.{minor}bx`) naming pattern.
The workflow will create two pull requests, one against the `main` and one against the `package-release/` branch; both should be merged in order to proceed with the release.
To keep the process lightweight, it's OK to approve the PRs you generate and merge without additional reviews.
## Preparing a new patch release
### Backporting
Creating manual backports of pull request(s) requires the `backport` label to be added in order to have a green CI.
To use the workflow to backport pull request(s) to the release branch:
* Run the [Backport workflow](https://github.com/open-telemetry/opentelemetry-python-contrib/actions/workflows/backport.yml).
* Press the "Run workflow" button, then select the release branch from the dropdown list,
e.g. `release/v1.9.x`, then enter the pull request number that you want to backport,
then click the "Run workflow" button below that.
* Add the label `backport` to the generated pull request.
* In case label automation doesn't work, just close and reopen the PR so that the workflow will take into account the label automation we have in place.
* Review and merge the backport pull request that it generates.
### Preparing a patch release
* Run the [Prepare patch release workflow](https://github.com/open-telemetry/opentelemetry-python-contrib/actions/workflows/prepare-patch-release.yml).
* Press the "Run workflow" button, then select the release branch from the dropdown list,
e.g. `release/v1.9.x`, and click the "Run workflow" button below that.
* Review and merge the pull request that it creates for updating the version.
* Note: If you are doing a patch release in `-contrib` repo, you should also do an equivalent patch release in `-core` repo (even if there's no fix to release), otherwise tests in CI will fail.
### Preparing a patch release for individual package
> [!NOTE]
> Per-package release is supported only for packages included in the corresponding workflow. Libraries that support per-package release are currently
> excluded from the general patch release.
Per-package patch release preparation is handled by the [`[Package] Prepare patch release`](./.github/workflows/package-prepare-patch-release.yml) workflow that allows
to pick a specific package to release.
The workflow can only be run against long-term release branch such as `package-release/{package-name}/v{major}.{minor}.x` or `package-release/{package-name}/v{major}.{minor}bx`.
The workflow will create a pull request that should be merged in order to proceed with the release.
## Making the release
* Run the [Release workflow](https://github.com/open-telemetry/opentelemetry-python-contrib/actions/workflows/release.yml).
* Press the "Run workflow" button, then select the release branch from the dropdown list,
e.g. `release/v1.9.x`, and click the "Run workflow" button below that.
* This workflow will publish the artifacts and publish a GitHub release with release notes based on the change log.
* Review and merge the pull request that it creates for updating the change log in main
(note that if this is not a patch release then the change log on main may already be up-to-date,
in which case no pull request will be created).
* Verify that a new [Github release](https://github.com/open-telemetry/opentelemetry-python-contrib/releases) has been created and that the CHANGELOGs look correct.
### Releasing individual package
> [!NOTE]
> Per-package patch release is supported for the following packages only:
> - opentelemetry-opamp-client
> - opentelemetry-propagator-aws-xray
> - opentelemetry-resource-detector-azure
> - opentelemetry-resourcedetector-gcp
> - opentelemetry-sdk-extension-aws
> - opentelemetry-instrumentation-openai-v2
> - opentelemetry-instrumentation-openai-agents-v2
> - opentelemetry-instrumentation-vertexai
> - opentelemetry-instrumentation-valkey-py
> - opentelemetry-util-genai
>
> These libraries are also excluded from the general patch release.
Per-package release is handled by the [`[Package] Release`](./.github/workflows/package-release.yml) workflow that allows
to pick a specific package to release.
The workflow can only be run against long-term release branch such as `package-release/{package-name}/v{major}.{minor}.x` or `package-release/{package-name}/v{major}.{minor}bx`.
## After the release
* Check PyPI
* This should be handled automatically on release by the [publish action](https://github.com/open-telemetry/opentelemetry-python-contrib/blob/main/.github/workflows/release.yml).
* Check the [action logs](https://github.com/open-telemetry/opentelemetry-python-contrib/actions/workflows/release.yml) to make sure packages have been uploaded to PyPI
* Check the release history (e.g. https://pypi.org/project/opentelemetry-instrumentation/#history) on PyPI
* If for some reason the action failed, see [Publish failed](#publish-failed) below
## Notes about version numbering for stable components
* The version number for stable components in the `main` branch is always `X.Y.0.dev`,
where `X.Y.0` represents the next minor release.
* When the release branch is created, you can opt to make a "pre-release", e.g. `X.Y.0rc2`.
* If you ARE NOT making a "pre-release":
* A "long-term" release branch will be created, e.g. `release/v1.9.x-0.21bx` (notice the wildcard x's).
Later on, after the initial release, you can backport PRs to a "long-term" release branch and make patch releases
from it.
* The version number for stable components in the release branch will be bumped to remove the `.dev`,
e.g. `X.Y.0`.
* The version number for stable components in the `main` branch will be bumped to the next version,
e.g. `X.{Y+1}.0.dev`.
* If you ARE making a "pre-release":
* A "short-term" release branch will be created, e.g. `release/v1.9.0rc2-0.21b0` (notice the precise version with no
wildcard x's). "Short-term" release branches do not support backports or patch releases after the initial release.
* The version number for stable components in the `main` branch will not be bumped, e.g. it will remain `X.Y.0.dev`
since the next minor release will still be `X.Y.0`.
## Notes about version numbering for unstable components
* The version number for unstable components in the `main` branch is always `0.Yb0.dev`,
where `0.Yb0` represents the next minor release.
* _Question: Is "b" (beta) redundant on "0." releases, or is this a python thing? I'm wondering if we can change it to `0.Y.0` to match up with the practice in js and go repos._
* Unstable components do not need "pre-releases", and so whether or not you are making a "pre-release" of stable
components:
* The version number for unstable components in the release branch will be bumped to remove the `.dev`,
e.g. `0.Yb0`.
* The version number for unstable components in the `main` branch will be bumped to the next version,
e.g. `0.{Y+1}b0.dev`.
## Releasing dev version of new packages to claim namespace
When a contribution introduces a new package, in order to mitigate name-squatting incidents, release the current development version of the new package under the `opentelemetry` user to simply claim the namespace. This should be done shortly after the PR that introduced this package has been merged into `main`.
## Troubleshooting
### Publish failed
If for some reason the action failed, do it manually:
- Switch to the release branch (important so we don't publish packages with "dev" versions)
- Build distributions with `./scripts/build.sh`
- Delete distributions we don't want to push (e.g. `testutil`)
- Push to PyPI as `twine upload --skip-existing --verbose dist/*`
- Double check PyPI!
opentelemetry-python-contrib-0.66b2/_template/ 0000775 0000000 0000000 00000000000 15270700723 0021517 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/_template/README.rst 0000664 0000000 0000000 00000001220 15270700723 0023201 0 ustar 00root root 0000000 0000000 OpenTelemetry Instrumentation
==========================================
|pypi|
.. |pypi| image:: https://badge.fury.io/py/opentelemetry-instrumentation-.svg
:target: https://pypi.org/project/opentelemetry-instrumentation-/
This library allows tracing requests made by the library.
Installation
------------
::
pip install opentelemetry-instrumentation-
References
----------
* `OpenTelemetry REPLACE ME/ Tracing `_
* `OpenTelemetry Project `_
opentelemetry-python-contrib-0.66b2/_template/autodoc_entry.rst 0000664 0000000 0000000 00000000355 15270700723 0025133 0 ustar 00root root 0000000 0000000 .. include:: ../../../instrumentation/opentelemetry-instrumentation-/README.rst
:end-before: References
.. automodule:: opentelemetry.instrumentation.
:members:
:undoc-members:
:show-inheritance:
opentelemetry-python-contrib-0.66b2/_template/pyproject.toml 0000664 0000000 0000000 00000003607 15270700723 0024441 0 ustar 00root root 0000000 0000000 [build-system]
requires = ["hatchling"]
build-backend = "hatchling.build"
[project]
# opentelemetry-instrumentation plus the name of the library being instrument e.g
# name = "opentelemetry-instrumentation-sqlalchemy"
name = ""
dynamic = ["version"]
# a description of the instrumentation e.g
# description = "SQLAlchemy tracing for OpenTelemetry"
description = ""
readme = "README.rst"
license = "Apache-2.0"
requires-python = ">=3.10"
authors = [
{ name = "OpenTelemetry Authors", email = "cncf-opentelemetry-contributors@lists.cncf.io" },
]
classifiers = [
"Development Status :: 4 - Beta",
"Intended Audience :: Developers",
"License :: OSI Approved :: Apache Software License",
"Programming Language :: Python",
"Programming Language :: Python :: 3",
"Programming Language :: Python :: 3.10",
"Programming Language :: Python :: 3.11",
"Programming Language :: Python :: 3.12",
"Programming Language :: Python :: 3.13",
"Programming Language :: Python :: 3.14",
]
dependencies = [
"opentelemetry-api ~= 1.12",
]
[project.entry-points.opentelemetry_instrumentor]
# REPLACE ME: the entrypoint for the instrumentor e.g
# sqlalchemy = "opentelemetry.instrumentation.sqlalchemy:SQLAlchemyInstrumentor"
REPLACE_ME = "opentelemetry.instrumentation."
[project.urls]
# url of the instrumentation e.g
# Homepage = "https://github.com/open-telemetry/opentelemetry-python-contrib/instrumentation/opentelemetry-instrumentation-sqlalchemy"
Homepage = ""
Repository = "https://github.com/open-telemetry/opentelemetry-python-contrib"
[tool.hatch.version]
# REPLACE ME: the path to the version file e.g
# "src/opentelemetry/instrumentation/sqlalchemy/version.py"
path = "src/opentelemetry/instrumentation//version.py"
[tool.hatch.build.targets.sdist]
include = [
"/src",
"/tests",
]
[tool.hatch.build.targets.wheel]
packages = ["src/opentelemetry"]
opentelemetry-python-contrib-0.66b2/_template/version.py 0000664 0000000 0000000 00000000144 15270700723 0023555 0 ustar 00root root 0000000 0000000 # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
__version__ = "0.66b2"
opentelemetry-python-contrib-0.66b2/dev-requirements.txt 0000664 0000000 0000000 00000000516 15270700723 0023607 0 ustar 00root root 0000000 0000000 pylint==4.0.5
pyright==v1.1.404
sphinx==7.1.2
sphinx-rtd-theme==2.0.0rc4
sphinx-autodoc-typehints==1.25.2
pytest==7.4.4
pytest-cov==4.1.0
readme-renderer==42.0
bleach==4.1.0 # transient dependency for readme-renderer
markupsafe>=2.0.1
codespell==2.1.0
requests==2.33.1
ruamel.yaml==0.17.21
flaky==3.7.0
pre-commit==3.7.0
ruff==0.16.1
opentelemetry-python-contrib-0.66b2/docs-requirements.txt 0000664 0000000 0000000 00000002160 15270700723 0023756 0 ustar 00root root 0000000 0000000 sphinx==7.1.2
sphinx-rtd-theme==2.0.0rc4
sphinx-autodoc-typehints==1.25.2
# Required to avoid breakages for pyramid and cassandra packages
setuptools<82.0.0
# Required by opentelemetry-instrumentation
fastapi>=0.65.2
pymemcache~=1.3
# Required by conf
django>=2.2
# Require by opentelemetry-util-genai
fsspec>=2025.9.0
# Required by instrumentation and exporter packages
aio_pika~=7.2.0
aiohttp~=3.13
aiokafka~=0.11.0
aiopg>=0.13.0,<1.3.0
asyncpg>=0.12.0
asyncclick~=8.0
botocore~=1.0
boto3~=1.0
cassandra-driver~=3.25
celery>=4.0
confluent-kafka>= 1.8.2,< 3.0.0
flask~=2.0
falcon~=2.0
grpcio~=1.27
httpx>=0.18.0
httpx2~=2.12
kafka-python>=2.0,<3.0
mysql-connector-python~=8.0
mysqlclient~=2.1.1
openai >= 1.26.0
psutil>=5
psycopg~=3.1.17
pika>=0.12.0
pymongo~=4.6.3
PyMySQL~=1.1.1
pymssql~=2.3.2
pyramid>=1.7
redis>=2.6
remoulade[limits]>=5.0.0 ; python_version >= "3.12"
remoulade>=0.50.0 ; python_version < "3.12"
sqlalchemy>=1.0
starlette~=0.50
structlog>=21.1
tornado>=5.1.1
tortoise-orm>=0.17.0
wrapt~=2.1
# required by opamp
uuid_utils
protobuf>=5.0,< 7.0
# indirect dependency pins
markupsafe==2.0.1
itsdangerous==2.0.1
opentelemetry-python-contrib-0.66b2/docs/ 0000775 0000000 0000000 00000000000 15270700723 0020475 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/docs/Makefile 0000664 0000000 0000000 00000001105 15270700723 0022132 0 ustar 00root root 0000000 0000000 # Minimal makefile for Sphinx documentation
#
# You can set these variables from the command line.
SPHINXOPTS =
SPHINXBUILD = sphinx-build
SOURCEDIR = .
BUILDDIR = _build
# Put it first so that "make" without argument is like "make help".
help:
@$(SPHINXBUILD) -M help "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O)
.PHONY: help Makefile
# Catch-all target: route all unknown targets to Sphinx using the new
# "make mode" option. $(O) is meant as a shortcut for $(SPHINXOPTS).
%: Makefile
@$(SPHINXBUILD) -M $@ "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O)
opentelemetry-python-contrib-0.66b2/docs/conf.py 0000664 0000000 0000000 00000015524 15270700723 0022003 0 ustar 00root root 0000000 0000000 # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
# Configuration file for the Sphinx documentation builder.
#
# This file only contains a selection of the most common options. For a full
# list see the documentation:
# http://www.sphinx-doc.org/en/master/config
# -- Path setup --------------------------------------------------------------
# If extensions (or modules to document with autodoc) are in another directory,
# add these directories to sys.path here. If the directory is relative to the
# documentation root, use os.path.abspath to make it absolute, like shown here.
import os
import sys
from configparser import ConfigParser
from os import listdir
from os.path import isdir, join
# configure django to avoid the following exception:
# django.core.exceptions.ImproperlyConfigured: Requested settings, but settings
# are not configured. You must either define the environment variable
# DJANGO_SETTINGS_MODULE or call settings.configure() before accessing settings.
from django.conf import settings
settings.configure()
source_dirs = []
exp = "../exporter"
exp_dirs = [os.path.abspath("/".join([exp, f, "src"])) for f in listdir(exp) if isdir(join(exp, f))]
instr = "../instrumentation"
instr_dirs = [os.path.abspath("/".join([instr, f, "src"])) for f in listdir(instr) if isdir(join(instr, f))]
instr_genai = "../instrumentation-genai"
instr_genai_dirs = [
os.path.abspath("/".join([instr_genai, f, "src"])) for f in listdir(instr_genai) if isdir(join(instr_genai, f))
]
prop = "../propagator"
prop_dirs = [os.path.abspath("/".join([prop, f, "src"])) for f in listdir(prop) if isdir(join(prop, f))]
sdk_ext = "../sdk-extension"
sdk_ext_dirs = [os.path.abspath("/".join([sdk_ext, f, "src"])) for f in listdir(sdk_ext) if isdir(join(sdk_ext, f))]
resource = "../resource"
resource_dirs = [os.path.abspath("/".join([resource, f, "src"])) for f in listdir(resource) if isdir(join(resource, f))]
util = "../util"
util_dirs = [os.path.abspath("/".join([util, f, "src"])) for f in listdir(util) if isdir(join(util, f))]
opamp = "../opamp"
opamp_dirs = [os.path.abspath("/".join([opamp, f, "src"])) for f in listdir(opamp) if isdir(join(opamp, f))]
sys.path[:0] = (
exp_dirs + instr_dirs + instr_genai_dirs + sdk_ext_dirs + prop_dirs + resource_dirs + util_dirs + opamp_dirs
)
# -- Project information -----------------------------------------------------
project = "OpenTelemetry Python Contrib"
copyright = "OpenTelemetry Authors" # pylint: disable=redefined-builtin
author = "OpenTelemetry Authors"
# -- General configuration ---------------------------------------------------
# Easy automatic cross-references for `code in backticks`
default_role = "any"
# Add any Sphinx extension module names here, as strings. They can be
# extensions coming with Sphinx (named 'sphinx.ext.*') or your custom
# ones.
extensions = [
# API doc generation
"sphinx.ext.autodoc",
# Support for google-style docstrings
"sphinx.ext.napoleon",
# Infer types from hints instead of docstrings
"sphinx_autodoc_typehints",
# Add links to source from generated docs
"sphinx.ext.viewcode",
# Link to other sphinx docs
"sphinx.ext.intersphinx",
# Add a .nojekyll file to the generated HTML docs
# https://help.github.com/en/articles/files-that-start-with-an-underscore-are-missing
"sphinx.ext.githubpages",
# Support external links to different versions in the Github repo
"sphinx.ext.extlinks",
]
intersphinx_mapping = {
"python": ("https://docs.python.org/3/", None),
"psycopg": ("https://www.psycopg.org/psycopg3/docs/", None),
"psycopg2": ("https://www.psycopg.org/docs/", None),
"opentracing": (
"https://opentracing-python.readthedocs.io/en/latest/",
None,
),
"aiohttp": ("https://docs.aiohttp.org/en/stable/", None),
"wrapt": ("https://wrapt.readthedocs.io/en/latest/", None),
"pymongo": ("https://pymongo.readthedocs.io/en/stable/", None),
"opentelemetry": (
"https://opentelemetry-python.readthedocs.io/en/latest/",
None,
),
"redis": ("https://redis.readthedocs.io/en/latest/", None),
"fsspec": ("https://filesystem-spec.readthedocs.io/en/latest/", None),
}
# http://www.sphinx-doc.org/en/master/config.html#confval-nitpicky
# Sphinx will warn about all references where the target cannot be found.
nitpicky = True
# Sphinx does not recognize generic type TypeVars
# Container supposedly were fixed, but does not work
# https://github.com/sphinx-doc/sphinx/pull/3744
nitpick_ignore = [
(
"py:class",
"opamp_pb2.RemoteConfigStatus",
),
(
"py:class",
"opamp_pb2.EffectiveConfig",
),
(
"py:class",
"opamp_pb2.AgentRemoteConfig",
),
]
cfg = ConfigParser()
cfg.read("./nitpick-exceptions.ini")
mcfg = cfg["default"]
def getlistcfg(strval):
return [val.strip() for line in strval.split("\n") for val in line.split(",") if val.strip()]
ignore_categories = [
"py-class",
"py-func",
"py-exc",
"py-obj",
"py-data",
"any",
]
for category in ignore_categories:
if category in mcfg:
items = getlistcfg(mcfg[category])
for item in items:
nitpick_ignore.append((category.replace("-", ":"), item))
# Add any paths that contain templates here, relative to this directory.
templates_path = ["_templates"]
# List of patterns, relative to source directory, that match files and
# directories to ignore when looking for source files.
# This pattern also affects html_static_path and html_extra_path.
exclude_patterns = ["_build", "Thumbs.db", ".DS_Store"]
autodoc_default_options = {
"members": True,
"undoc-members": True,
"show-inheritance": True,
"member-order": "bysource",
}
# -- Options for HTML output -------------------------------------------------
# The theme to use for HTML and HTML Help pages. See the documentation for
# a list of builtin themes.
#
html_theme = "sphinx_rtd_theme"
# Add any paths that contain custom static files (such as style sheets) here,
# relative to this directory. They are copied after the builtin static files,
# so a file named "default.css" will overwrite the builtin "default.css".
html_static_path = []
# Support external links to specific versions of the files in the Github repo
branch = os.environ.get("READTHEDOCS_VERSION")
if branch is None or branch == "latest":
branch = "main"
REPO = "open-telemetry/opentelemetry-python-contrib/"
scm_raw_web = "https://raw.githubusercontent.com/" + REPO + branch
scm_web = "https://github.com/" + REPO + "blob/" + branch
# Store variables in the epilogue so they are globally available.
rst_epilog = f"""
.. |SCM_WEB| replace:: {scm_web}
.. |SCM_RAW_WEB| replace:: {scm_raw_web}
.. |SCM_BRANCH| replace:: {branch}
"""
# used to have links to repo files
extlinks = {
"scm_raw_web": (scm_raw_web + "/%s", "scm_raw_web"),
"scm_web": (scm_web + "/%s", "scm_web"),
}
opentelemetry-python-contrib-0.66b2/docs/index.rst 0000664 0000000 0000000 00000006121 15270700723 0022336 0 ustar 00root root 0000000 0000000 OpenTelemetry-Python-Contrib
============================
Complimentary instrumentation and vendor-specific packages for use with the
Python `OpenTelemetry `_ client.
.. image:: https://img.shields.io/badge/slack-chat-green.svg
:target: https://cloud-native.slack.com/archives/C01PD4HUVBL
:alt: Slack Chat
**Please note** that this library is currently in _beta_, and shouldn't
generally be used in production environments.
Installation
------------
There are several complimentary packages available on PyPI which can be
installed separately via pip:
.. code-block:: sh
pip install opentelemetry-exporter-{exporter}
pip install opentelemetry-instrumentation-{instrumentation}
pip install opentelemetry-sdk-extension-{sdk-extension}
A complete list of packages can be found at the
`Contrib repo instrumentation `_
and `Contrib repo exporter `_ directories.
Extensions
----------
Visit `OpenTelemetry Registry `_ to
find a lot of related projects like exporters, instrumentation libraries, tracer
implementations, resource, etc.
Installing Cutting Edge Packages
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
While the project is pre-1.0, there may be significant functionality that
has not yet been released to PyPI. In that situation, you may want to
install the packages directly from the repo. This can be done by cloning the
repository and doing an `editable
install `_:
.. code-block:: sh
git clone https://github.com/open-telemetry/opentelemetry-python-contrib.git
cd opentelemetry-python-contrib
pip install -e ./instrumentation/opentelemetry-instrumentation-flask
pip install -e ./instrumentation/opentelemetry-instrumentation-botocore
pip install -e ./sdk-extension/opentelemetry-sdk-extension-aws
pip install -e ./resource/opentelemetry-resource-detector-containerid
.. toctree::
:maxdepth: 2
:caption: OpenTelemetry Instrumentations
:name: Instrumentations
:glob:
instrumentation/**
.. toctree::
:maxdepth: 2
:caption: OpenTelemetry Generative AI Instrumentations
:name: Generative AI Instrumentations
:glob:
instrumentation-genai/**
.. toctree::
:maxdepth: 2
:caption: OpenTelemetry Propagators
:name: Propagators
:glob:
propagator/**
.. toctree::
:maxdepth: 2
:caption: OpenTelemetry Performance
:name: Performance
:glob:
performance/**
.. toctree::
:maxdepth: 2
:caption: OpenTelemetry SDK Extensions
:name: SDK Extensions
:glob:
sdk-extension/**
.. toctree::
:maxdepth: 2
:caption: OpenTelemetry Resource Detectors
:name: Resource Detectors
:glob:
resource/**
.. toctree::
:maxdepth: 2
:caption: OpAMP
:name: OpAMP
:glob:
opamp/**
Indices and tables
------------------
* :ref:`genindex`
* :ref:`modindex`
* :ref:`search`
opentelemetry-python-contrib-0.66b2/docs/instrumentation-genai/ 0000775 0000000 0000000 00000000000 15270700723 0025021 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/docs/instrumentation-genai/openai.rst 0000664 0000000 0000000 00000000316 15270700723 0027026 0 ustar 00root root 0000000 0000000 OpenTelemetry Python - OpenAI Instrumentation
=============================================
.. automodule:: opentelemetry.instrumentation.openai_v2
:members:
:undoc-members:
:show-inheritance:
opentelemetry-python-contrib-0.66b2/docs/instrumentation-genai/util.rst 0000664 0000000 0000000 00000001274 15270700723 0026534 0 ustar 00root root 0000000 0000000 OpenTelemetry Python - GenAI Util
=================================
.. automodule:: opentelemetry.util.genai
:members:
:undoc-members:
:show-inheritance:
.. automodule:: opentelemetry.util.genai.utils
:members:
:undoc-members:
:show-inheritance:
.. automodule:: opentelemetry.util.genai.types
:members:
:undoc-members:
:show-inheritance:
.. automodule:: opentelemetry.util.genai.environment_variables
:members:
:undoc-members:
:show-inheritance:
.. automodule:: opentelemetry.util.genai.completion_hook
:members:
:undoc-members:
:show-inheritance:
.. automodule:: opentelemetry.util.genai._upload
:members:
:show-inheritance:
opentelemetry-python-contrib-0.66b2/docs/instrumentation/ 0000775 0000000 0000000 00000000000 15270700723 0023740 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/docs/instrumentation/aio_pika/ 0000775 0000000 0000000 00000000000 15270700723 0025514 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/docs/instrumentation/aio_pika/aio_pika.rst 0000664 0000000 0000000 00000000305 15270700723 0030020 0 ustar 00root root 0000000 0000000 OpenTelemetry aio pika Instrumentation
============================================
.. automodule:: opentelemetry.instrumentation.aio_pika
:members:
:undoc-members:
:show-inheritance:
opentelemetry-python-contrib-0.66b2/docs/instrumentation/aiohttp_client/ 0000775 0000000 0000000 00000000000 15270700723 0026746 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/docs/instrumentation/aiohttp_client/aiohttp_client.rst 0000664 0000000 0000000 00000000321 15270700723 0032502 0 ustar 00root root 0000000 0000000 OpenTelemetry aiohttp client Instrumentation
============================================
.. automodule:: opentelemetry.instrumentation.aiohttp_client
:members:
:undoc-members:
:show-inheritance:
opentelemetry-python-contrib-0.66b2/docs/instrumentation/aiohttp_server/ 0000775 0000000 0000000 00000000000 15270700723 0026776 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/docs/instrumentation/aiohttp_server/aiohttp_server.rst 0000664 0000000 0000000 00000000361 15270700723 0032566 0 ustar 00root root 0000000 0000000 .. include:: ../../../instrumentation/opentelemetry-instrumentation-aiohttp-server/README.rst
:end-before: References
.. automodule:: opentelemetry.instrumentation.aiohttp_server
:members:
:undoc-members:
:show-inheritance:
opentelemetry-python-contrib-0.66b2/docs/instrumentation/aiokafka/ 0000775 0000000 0000000 00000000000 15270700723 0025506 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/docs/instrumentation/aiokafka/aiokafka.rst 0000664 0000000 0000000 00000000356 15270700723 0030012 0 ustar 00root root 0000000 0000000 .. include:: ../../../instrumentation/opentelemetry-instrumentation-aiokafka/README.rst
:end-before: References
API
---
.. automodule:: opentelemetry.instrumentation.aiokafka
:members:
:undoc-members:
:show-inheritance:
opentelemetry-python-contrib-0.66b2/docs/instrumentation/aiopg/ 0000775 0000000 0000000 00000000000 15270700723 0025037 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/docs/instrumentation/aiopg/aiopg.rst 0000664 0000000 0000000 00000000266 15270700723 0026674 0 ustar 00root root 0000000 0000000 OpenTelemetry aiopg Instrumentation
===================================
.. automodule:: opentelemetry.instrumentation.aiopg
:members:
:undoc-members:
:show-inheritance:
opentelemetry-python-contrib-0.66b2/docs/instrumentation/asgi/ 0000775 0000000 0000000 00000000000 15270700723 0024663 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/docs/instrumentation/asgi/asgi.rst 0000664 0000000 0000000 00000000312 15270700723 0026334 0 ustar 00root root 0000000 0000000 .. include:: ../../../instrumentation/opentelemetry-instrumentation-asgi/README.rst
API
---
.. automodule:: opentelemetry.instrumentation.asgi
:members:
:undoc-members:
:show-inheritance:
opentelemetry-python-contrib-0.66b2/docs/instrumentation/asyncclick/ 0000775 0000000 0000000 00000000000 15270700723 0026063 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/docs/instrumentation/asyncclick/asyncclick.rst 0000664 0000000 0000000 00000000351 15270700723 0030737 0 ustar 00root root 0000000 0000000 .. include:: ../../../instrumentation/opentelemetry-instrumentation-asyncclick/README.rst
:end-before: References
.. automodule:: opentelemetry.instrumentation.asyncclick
:members:
:undoc-members:
:show-inheritance:
opentelemetry-python-contrib-0.66b2/docs/instrumentation/asyncio/ 0000775 0000000 0000000 00000000000 15270700723 0025405 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/docs/instrumentation/asyncio/asyncio.rst 0000664 0000000 0000000 00000000513 15270700723 0027603 0 ustar 00root root 0000000 0000000 OpenTelemetry asyncio Instrumentation
==============================================
.. automodule:: opentelemetry.instrumentation.asyncio
:members:
:undoc-members:
:show-inheritance:
.. automodule:: opentelemetry.instrumentation.asyncio.environment_variables
:members:
:undoc-members:
:show-inheritance:
opentelemetry-python-contrib-0.66b2/docs/instrumentation/asyncpg/ 0000775 0000000 0000000 00000000000 15270700723 0025404 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/docs/instrumentation/asyncpg/asyncpg.rst 0000664 0000000 0000000 00000000335 15270700723 0027603 0 ustar 00root root 0000000 0000000 OpenTelemetry asyncpg Instrumentation
=====================================
Module contents
---------------
.. automodule:: opentelemetry.instrumentation.asyncpg
:members:
:undoc-members:
:show-inheritance:
opentelemetry-python-contrib-0.66b2/docs/instrumentation/aws_lambda/ 0000775 0000000 0000000 00000000000 15270700723 0026032 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/docs/instrumentation/aws_lambda/aws_lambda.rst 0000664 0000000 0000000 00000000305 15270700723 0030654 0 ustar 00root root 0000000 0000000 OpenTelemetry AWS lambda Instrumentation
==========================================
.. automodule:: opentelemetry.instrumentation.aws_lambda
:members:
:undoc-members:
:show-inheritance:
opentelemetry-python-contrib-0.66b2/docs/instrumentation/base/ 0000775 0000000 0000000 00000000000 15270700723 0024652 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/docs/instrumentation/base/instrumentation.rst 0000664 0000000 0000000 00000000424 15270700723 0030647 0 ustar 00root root 0000000 0000000 .. include:: ../../../opentelemetry-instrumentation/README.rst
:end-before: References
API
---
.. automodule:: opentelemetry.instrumentation
:members:
:undoc-members:
:show-inheritance:
Submodules
----------
.. toctree::
:maxdepth: 1
instrumentor
opentelemetry-python-contrib-0.66b2/docs/instrumentation/base/instrumentor.rst 0000664 0000000 0000000 00000000333 15270700723 0030154 0 ustar 00root root 0000000 0000000 opentelemetry.instrumentation.instrumentor package
==================================================
.. automodule:: opentelemetry.instrumentation.instrumentor
:members:
:undoc-members:
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opentelemetry-python-contrib-0.66b2/docs/instrumentation/boto3sqs/ 0000775 0000000 0000000 00000000000 15270700723 0025515 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/docs/instrumentation/boto3sqs/boto3sqs.rst 0000664 0000000 0000000 00000000311 15270700723 0030017 0 ustar 00root root 0000000 0000000 .. include:: ../../../instrumentation/opentelemetry-instrumentation-boto3sqs/README.rst
.. automodule:: opentelemetry.instrumentation.boto3sqs
:members:
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opentelemetry-python-contrib-0.66b2/docs/instrumentation/botocore/ 0000775 0000000 0000000 00000000000 15270700723 0025554 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/docs/instrumentation/botocore/botocore.rst 0000664 0000000 0000000 00000000277 15270700723 0030130 0 ustar 00root root 0000000 0000000 OpenTelemetry Botocore Instrumentation
======================================
.. automodule:: opentelemetry.instrumentation.botocore
:members:
:undoc-members:
:show-inheritance:
opentelemetry-python-contrib-0.66b2/docs/instrumentation/cassandra/ 0000775 0000000 0000000 00000000000 15270700723 0025677 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/docs/instrumentation/cassandra/cassandra.rst 0000664 0000000 0000000 00000000302 15270700723 0030363 0 ustar 00root root 0000000 0000000 OpenTelemetry Cassandra Instrumentation
=======================================
.. automodule:: opentelemetry.instrumentation.cassandra
:members:
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opentelemetry-python-contrib-0.66b2/docs/instrumentation/celery/ 0000775 0000000 0000000 00000000000 15270700723 0025223 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/docs/instrumentation/celery/celery.rst 0000664 0000000 0000000 00000000271 15270700723 0027240 0 ustar 00root root 0000000 0000000 OpenTelemetry Celery Instrumentation
====================================
.. automodule:: opentelemetry.instrumentation.celery
:members:
:undoc-members:
:show-inheritance:
opentelemetry-python-contrib-0.66b2/docs/instrumentation/click/ 0000775 0000000 0000000 00000000000 15270700723 0025025 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/docs/instrumentation/click/click.rst 0000664 0000000 0000000 00000000337 15270700723 0026647 0 ustar 00root root 0000000 0000000 .. include:: ../../../instrumentation/opentelemetry-instrumentation-click/README.rst
:end-before: References
.. automodule:: opentelemetry.instrumentation.click
:members:
:undoc-members:
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opentelemetry-python-contrib-0.66b2/docs/instrumentation/confluent_kafka/ 0000775 0000000 0000000 00000000000 15270700723 0027072 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/docs/instrumentation/confluent_kafka/confluent_kafka.rst 0000664 0000000 0000000 00000000345 15270700723 0032760 0 ustar 00root root 0000000 0000000 .. include:: ../../../instrumentation/opentelemetry-instrumentation-confluent-kafka/README.rst
.. automodule:: opentelemetry.instrumentation.confluent_kafka
:members:
:undoc-members:
:show-inheritance:
:noindex:
opentelemetry-python-contrib-0.66b2/docs/instrumentation/dbapi/ 0000775 0000000 0000000 00000000000 15270700723 0025017 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/docs/instrumentation/dbapi/dbapi.rst 0000664 0000000 0000000 00000000304 15270700723 0026625 0 ustar 00root root 0000000 0000000 OpenTelemetry Database API Instrumentation
==========================================
.. automodule:: opentelemetry.instrumentation.dbapi
:members:
:undoc-members:
:show-inheritance:
opentelemetry-python-contrib-0.66b2/docs/instrumentation/django/ 0000775 0000000 0000000 00000000000 15270700723 0025202 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/docs/instrumentation/django/django.rst 0000664 0000000 0000000 00000000271 15270700723 0027176 0 ustar 00root root 0000000 0000000 OpenTelemetry Django Instrumentation
====================================
.. automodule:: opentelemetry.instrumentation.django
:members:
:undoc-members:
:show-inheritance:
opentelemetry-python-contrib-0.66b2/docs/instrumentation/exceptions/ 0000775 0000000 0000000 00000000000 15270700723 0026121 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/docs/instrumentation/exceptions/exceptions.rst 0000664 0000000 0000000 00000000305 15270700723 0031032 0 ustar 00root root 0000000 0000000 OpenTelemetry Exceptions Instrumentation
========================================
.. automodule:: opentelemetry.instrumentation.exceptions
:members:
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:show-inheritance:
opentelemetry-python-contrib-0.66b2/docs/instrumentation/falcon/ 0000775 0000000 0000000 00000000000 15270700723 0025202 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/docs/instrumentation/falcon/falcon.rst 0000664 0000000 0000000 00000000271 15270700723 0027176 0 ustar 00root root 0000000 0000000 OpenTelemetry Falcon Instrumentation
====================================
.. automodule:: opentelemetry.instrumentation.falcon
:members:
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:show-inheritance:
opentelemetry-python-contrib-0.66b2/docs/instrumentation/fastapi/ 0000775 0000000 0000000 00000000000 15270700723 0025367 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/docs/instrumentation/fastapi/fastapi.rst 0000664 0000000 0000000 00000000317 15270700723 0027551 0 ustar 00root root 0000000 0000000 .. include:: ../../../instrumentation/opentelemetry-instrumentation-fastapi/README.rst
API
---
.. automodule:: opentelemetry.instrumentation.fastapi
:members:
:undoc-members:
:show-inheritance: opentelemetry-python-contrib-0.66b2/docs/instrumentation/flask/ 0000775 0000000 0000000 00000000000 15270700723 0025040 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/docs/instrumentation/flask/flask.rst 0000664 0000000 0000000 00000000266 15270700723 0026676 0 ustar 00root root 0000000 0000000 OpenTelemetry Flask Instrumentation
===================================
.. automodule:: opentelemetry.instrumentation.flask
:members:
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:show-inheritance:
opentelemetry-python-contrib-0.66b2/docs/instrumentation/grpc/ 0000775 0000000 0000000 00000000000 15270700723 0024673 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/docs/instrumentation/grpc/grpc.rst 0000664 0000000 0000000 00000000321 15270700723 0026354 0 ustar 00root root 0000000 0000000 OpenTelemetry gRPC Instrumentation
==================================
Module contents
---------------
.. automodule:: opentelemetry.instrumentation.grpc
:members:
:undoc-members:
:show-inheritance:
opentelemetry-python-contrib-0.66b2/docs/instrumentation/httpx/ 0000775 0000000 0000000 00000000000 15270700723 0025107 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/docs/instrumentation/httpx/httpx.rst 0000664 0000000 0000000 00000000400 15270700723 0027002 0 ustar 00root root 0000000 0000000 .. include:: ../../../instrumentation/opentelemetry-instrumentation-httpx/README.rst
:end-before: References
API
---
.. automodule:: opentelemetry.instrumentation.httpx
:members:
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:inherited-members:
opentelemetry-python-contrib-0.66b2/docs/instrumentation/jinja2/ 0000775 0000000 0000000 00000000000 15270700723 0025115 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/docs/instrumentation/jinja2/jinja2.rst 0000664 0000000 0000000 00000000271 15270700723 0027024 0 ustar 00root root 0000000 0000000 OpenTelemetry Jinja2 Instrumentation
====================================
.. automodule:: opentelemetry.instrumentation.jinja2
:members:
:undoc-members:
:show-inheritance:
opentelemetry-python-contrib-0.66b2/docs/instrumentation/kafka_python/ 0000775 0000000 0000000 00000000000 15270700723 0026416 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/docs/instrumentation/kafka_python/kafka_python.rst 0000664 0000000 0000000 00000000357 15270700723 0031633 0 ustar 00root root 0000000 0000000 .. include:: ../../../instrumentation/opentelemetry-instrumentation-kafka-python/README.rst
:end-before: References
API
---
.. automodule:: opentelemetry.instrumentation.kafka
:members:
:undoc-members:
:show-inheritance:
opentelemetry-python-contrib-0.66b2/docs/instrumentation/logging/ 0000775 0000000 0000000 00000000000 15270700723 0025366 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/docs/instrumentation/logging/logging.rst 0000664 0000000 0000000 00000000274 15270700723 0027551 0 ustar 00root root 0000000 0000000 OpenTelemetry Logging Instrumentation
=====================================
.. automodule:: opentelemetry.instrumentation.logging
:members:
:undoc-members:
:show-inheritance:
opentelemetry-python-contrib-0.66b2/docs/instrumentation/mysql/ 0000775 0000000 0000000 00000000000 15270700723 0025105 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/docs/instrumentation/mysql/mysql.rst 0000664 0000000 0000000 00000000266 15270700723 0027010 0 ustar 00root root 0000000 0000000 OpenTelemetry MySQL Instrumentation
===================================
.. automodule:: opentelemetry.instrumentation.mysql
:members:
:undoc-members:
:show-inheritance:
opentelemetry-python-contrib-0.66b2/docs/instrumentation/mysqlclient/ 0000775 0000000 0000000 00000000000 15270700723 0026304 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/docs/instrumentation/mysqlclient/mysqlclient.rst 0000664 0000000 0000000 00000000310 15270700723 0031374 0 ustar 00root root 0000000 0000000 OpenTelemetry mysqlclient Instrumentation
=========================================
.. automodule:: opentelemetry.instrumentation.mysqlclient
:members:
:undoc-members:
:show-inheritance:
opentelemetry-python-contrib-0.66b2/docs/instrumentation/pika/ 0000775 0000000 0000000 00000000000 15270700723 0024664 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/docs/instrumentation/pika/pika.rst 0000664 0000000 0000000 00000000266 15270700723 0026346 0 ustar 00root root 0000000 0000000 OpenTelemetry Pika Instrumentation
=====================================
.. automodule:: opentelemetry.instrumentation.pika
:members:
:undoc-members:
:show-inheritance:
opentelemetry-python-contrib-0.66b2/docs/instrumentation/psycopg/ 0000775 0000000 0000000 00000000000 15270700723 0025424 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/docs/instrumentation/psycopg/psycopg.rst 0000664 0000000 0000000 00000000274 15270700723 0027645 0 ustar 00root root 0000000 0000000 OpenTelemetry Psycopg Instrumentation
=====================================
.. automodule:: opentelemetry.instrumentation.psycopg
:members:
:undoc-members:
:show-inheritance:
opentelemetry-python-contrib-0.66b2/docs/instrumentation/psycopg2/ 0000775 0000000 0000000 00000000000 15270700723 0025506 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/docs/instrumentation/psycopg2/psycopg2.rst 0000664 0000000 0000000 00000000277 15270700723 0030014 0 ustar 00root root 0000000 0000000 OpenTelemetry Psycopg2 Instrumentation
======================================
.. automodule:: opentelemetry.instrumentation.psycopg2
:members:
:undoc-members:
:show-inheritance:
opentelemetry-python-contrib-0.66b2/docs/instrumentation/pymemcache/ 0000775 0000000 0000000 00000000000 15270700723 0026053 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/docs/instrumentation/pymemcache/pymemcache.rst 0000664 0000000 0000000 00000000305 15270700723 0030716 0 ustar 00root root 0000000 0000000 OpenTelemetry pymemcache Instrumentation
========================================
.. automodule:: opentelemetry.instrumentation.pymemcache
:members:
:undoc-members:
:show-inheritance:
opentelemetry-python-contrib-0.66b2/docs/instrumentation/pymongo/ 0000775 0000000 0000000 00000000000 15270700723 0025430 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/docs/instrumentation/pymongo/pymongo.rst 0000664 0000000 0000000 00000000274 15270700723 0027655 0 ustar 00root root 0000000 0000000 OpenTelemetry pymongo Instrumentation
=====================================
.. automodule:: opentelemetry.instrumentation.pymongo
:members:
:undoc-members:
:show-inheritance:
opentelemetry-python-contrib-0.66b2/docs/instrumentation/pymssql/ 0000775 0000000 0000000 00000000000 15270700723 0025450 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/docs/instrumentation/pymssql/pymssql.rst 0000664 0000000 0000000 00000000274 15270700723 0027715 0 ustar 00root root 0000000 0000000 OpenTelemetry pymssql Instrumentation
=====================================
.. automodule:: opentelemetry.instrumentation.pymssql
:members:
:undoc-members:
:show-inheritance:
opentelemetry-python-contrib-0.66b2/docs/instrumentation/pymysql/ 0000775 0000000 0000000 00000000000 15270700723 0025456 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/docs/instrumentation/pymysql/pymysql.rst 0000664 0000000 0000000 00000000274 15270700723 0027731 0 ustar 00root root 0000000 0000000 OpenTelemetry PyMySQL Instrumentation
=====================================
.. automodule:: opentelemetry.instrumentation.pymysql
:members:
:undoc-members:
:show-inheritance:
opentelemetry-python-contrib-0.66b2/docs/instrumentation/pyramid/ 0000775 0000000 0000000 00000000000 15270700723 0025405 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/docs/instrumentation/pyramid/pyramid.rst 0000664 0000000 0000000 00000000274 15270700723 0027607 0 ustar 00root root 0000000 0000000 OpenTelemetry Pyramid Instrumentation
=====================================
.. automodule:: opentelemetry.instrumentation.pyramid
:members:
:undoc-members:
:show-inheritance:
opentelemetry-python-contrib-0.66b2/docs/instrumentation/redis/ 0000775 0000000 0000000 00000000000 15270700723 0025046 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/docs/instrumentation/redis/redis.rst 0000664 0000000 0000000 00000000353 15270700723 0026707 0 ustar 00root root 0000000 0000000 .. include:: ../../../instrumentation/opentelemetry-instrumentation-redis/README.rst
:end-before: References
Usage
-----
.. automodule:: opentelemetry.instrumentation.redis
:members:
:undoc-members:
:show-inheritance: opentelemetry-python-contrib-0.66b2/docs/instrumentation/remoulade/ 0000775 0000000 0000000 00000000000 15270700723 0025715 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/docs/instrumentation/remoulade/remoulade.rst 0000664 0000000 0000000 00000000314 15270700723 0030422 0 ustar 00root root 0000000 0000000 .. include:: ../../../instrumentation/opentelemetry-instrumentation-remoulade/README.rst
.. automodule:: opentelemetry.instrumentation.remoulade
:members:
:undoc-members:
:show-inheritance:
opentelemetry-python-contrib-0.66b2/docs/instrumentation/requests/ 0000775 0000000 0000000 00000000000 15270700723 0025613 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/docs/instrumentation/requests/requests.rst 0000664 0000000 0000000 00000000277 15270700723 0030226 0 ustar 00root root 0000000 0000000 OpenTelemetry requests Instrumentation
======================================
.. automodule:: opentelemetry.instrumentation.requests
:members:
:undoc-members:
:show-inheritance:
opentelemetry-python-contrib-0.66b2/docs/instrumentation/sqlalchemy/ 0000775 0000000 0000000 00000000000 15270700723 0026102 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/docs/instrumentation/sqlalchemy/sqlalchemy.rst 0000664 0000000 0000000 00000000305 15270700723 0030774 0 ustar 00root root 0000000 0000000 OpenTelemetry SQLAlchemy Instrumentation
========================================
.. automodule:: opentelemetry.instrumentation.sqlalchemy
:members:
:undoc-members:
:show-inheritance:
opentelemetry-python-contrib-0.66b2/docs/instrumentation/sqlite3/ 0000775 0000000 0000000 00000000000 15270700723 0025324 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/docs/instrumentation/sqlite3/sqlite3.rst 0000664 0000000 0000000 00000000274 15270700723 0027445 0 ustar 00root root 0000000 0000000 OpenTelemetry SQLite3 Instrumentation
=====================================
.. automodule:: opentelemetry.instrumentation.sqlite3
:members:
:undoc-members:
:show-inheritance:
opentelemetry-python-contrib-0.66b2/docs/instrumentation/starlette/ 0000775 0000000 0000000 00000000000 15270700723 0025747 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/docs/instrumentation/starlette/starlette.rst 0000664 0000000 0000000 00000000323 15270700723 0030506 0 ustar 00root root 0000000 0000000 .. include:: ../../../instrumentation/opentelemetry-instrumentation-starlette/README.rst
API
---
.. automodule:: opentelemetry.instrumentation.starlette
:members:
:undoc-members:
:show-inheritance: opentelemetry-python-contrib-0.66b2/docs/instrumentation/structlog/ 0000775 0000000 0000000 00000000000 15270700723 0025766 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/docs/instrumentation/structlog/structlog.rst 0000664 0000000 0000000 00000000302 15270700723 0030541 0 ustar 00root root 0000000 0000000 OpenTelemetry Structlog Instrumentation
=======================================
.. automodule:: opentelemetry.instrumentation.structlog
:members:
:undoc-members:
:show-inheritance:
opentelemetry-python-contrib-0.66b2/docs/instrumentation/system_metrics/ 0000775 0000000 0000000 00000000000 15270700723 0027012 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/docs/instrumentation/system_metrics/system_metrics.rst 0000664 0000000 0000000 00000000536 15270700723 0032622 0 ustar 00root root 0000000 0000000 OpenTelemetry system metrics Instrumentation
============================================
.. automodule:: opentelemetry.instrumentation.system_metrics
:members:
:undoc-members:
:show-inheritance:
.. automodule:: opentelemetry.instrumentation.system_metrics.environment_variables
:members:
:undoc-members:
:show-inheritance:
opentelemetry-python-contrib-0.66b2/docs/instrumentation/threading/ 0000775 0000000 0000000 00000000000 15270700723 0025705 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/docs/instrumentation/threading/threading.rst 0000664 0000000 0000000 00000000302 15270700723 0030377 0 ustar 00root root 0000000 0000000 OpenTelemetry Threading Instrumentation
=======================================
.. automodule:: opentelemetry.instrumentation.threading
:members:
:undoc-members:
:show-inheritance:
opentelemetry-python-contrib-0.66b2/docs/instrumentation/tornado/ 0000775 0000000 0000000 00000000000 15270700723 0025406 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/docs/instrumentation/tornado/tornado.rst 0000664 0000000 0000000 00000000275 15270700723 0027612 0 ustar 00root root 0000000 0000000 OpenTelemetry Tornado Instrumentation
======================================
.. automodule:: opentelemetry.instrumentation.tornado
:members:
:undoc-members:
:show-inheritance:
opentelemetry-python-contrib-0.66b2/docs/instrumentation/tortoiseorm/ 0000775 0000000 0000000 00000000000 15270700723 0026326 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/docs/instrumentation/tortoiseorm/tortoiseorm.rst 0000664 0000000 0000000 00000000317 15270700723 0031447 0 ustar 00root root 0000000 0000000 .. include:: ../../../instrumentation/opentelemetry-instrumentation-tortoiseorm/README.rst
.. automodule:: opentelemetry.instrumentation.tortoiseorm
:members:
:undoc-members:
:show-inheritance:
opentelemetry-python-contrib-0.66b2/docs/instrumentation/urllib/ 0000775 0000000 0000000 00000000000 15270700723 0025231 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/docs/instrumentation/urllib/urllib3.rst 0000664 0000000 0000000 00000000301 15270700723 0027331 0 ustar 00root root 0000000 0000000 OpenTelemetry urllib Instrumentation
============================================
.. automodule:: opentelemetry.instrumentation.urllib
:members:
:undoc-members:
:show-inheritance:
opentelemetry-python-contrib-0.66b2/docs/instrumentation/urllib3/ 0000775 0000000 0000000 00000000000 15270700723 0025314 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/docs/instrumentation/urllib3/urllib3.rst 0000664 0000000 0000000 00000000303 15270700723 0027416 0 ustar 00root root 0000000 0000000 OpenTelemetry urllib3 Instrumentation
============================================
.. automodule:: opentelemetry.instrumentation.urllib3
:members:
:undoc-members:
:show-inheritance:
opentelemetry-python-contrib-0.66b2/docs/instrumentation/wsgi/ 0000775 0000000 0000000 00000000000 15270700723 0024711 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/docs/instrumentation/wsgi/wsgi.rst 0000664 0000000 0000000 00000000263 15270700723 0026415 0 ustar 00root root 0000000 0000000 OpenTelemetry WSGI Instrumentation
==================================
.. automodule:: opentelemetry.instrumentation.wsgi
:members:
:undoc-members:
:show-inheritance:
opentelemetry-python-contrib-0.66b2/docs/make.bat 0000664 0000000 0000000 00000001423 15270700723 0022102 0 ustar 00root root 0000000 0000000 @ECHO OFF
pushd %~dp0
REM Command file for Sphinx documentation
if "%SPHINXBUILD%" == "" (
set SPHINXBUILD=sphinx-build
)
set SOURCEDIR=.
set BUILDDIR=_build
if "%1" == "" goto help
%SPHINXBUILD% >NUL 2>NUL
if errorlevel 9009 (
echo.
echo.The 'sphinx-build' command was not found. Make sure you have Sphinx
echo.installed, then set the SPHINXBUILD environment variable to point
echo.to the full path of the 'sphinx-build' executable. Alternatively you
echo.may add the Sphinx directory to PATH.
echo.
echo.If you don't have Sphinx installed, grab it from
echo.http://sphinx-doc.org/
exit /b 1
)
%SPHINXBUILD% -M %1 %SOURCEDIR% %BUILDDIR% %SPHINXOPTS%
goto end
:help
%SPHINXBUILD% -M help %SOURCEDIR% %BUILDDIR% %SPHINXOPTS%
:end
popd
opentelemetry-python-contrib-0.66b2/docs/nitpick-exceptions.ini 0000664 0000000 0000000 00000005010 15270700723 0025012 0 ustar 00root root 0000000 0000000 [default]
py-class=
; TODO: Understand why sphinx is not able to find this local class
opentelemetry.propagators.textmap.CarrierT
opentelemetry.propagators.textmap.Setter
opentelemetry.propagators.textmap.Getter
opentelemetry.propagators.textmap.TextMapPropagator
; - AwsXRayPropagator
opentelemetry.propagators.textmap.DefaultGetter
; API
opentelemetry.propagators.textmap.Getter
; - AWSXRayPropagator
opentelemetry.sdk.trace.id_generator.IdGenerator
opentelemetry.instrumentation.confluent_kafka.ProxiedProducer
opentelemetry.instrumentation.confluent_kafka.ProxiedConsumer
opentelemetry.instrumentation.instrumentor.BaseInstrumentor
; - AwsXRayIdGenerator
TextMapPropagator
CarrierT
Setter
Getter
; - AwsXRayPropagator.extract
; httpx changes __module__ causing Sphinx to error and no Sphinx site is available
httpx.Client
httpx.AsyncClient
httpx.BaseTransport
httpx2.BaseTransport
openai.BaseTransport
httpx.AsyncBaseTransport
httpx2.AsyncBaseTransport
httpx.SyncByteStream
httpx.AsyncByteStream
httpx.Response
httpx.URL
httpx.Headers
aiohttp.web_request.Request
celery.worker.request.Request
yarl.URL
cimpl.Producer
cimpl.Consumer
func
Message
TopicPartition
callable
Consumer
confluent_kafka.Message
psycopg.Connection
psycopg.AsyncConnection
ObjectProxy
wrapt.proxies.ObjectProxy
_wrappers.ObjectProxy
fastapi.applications.FastAPI
starlette.applications.Starlette
_contextvars.Token
opentelemetry.instrumentation.httpx._SyncOpenTelemetryTransportBase
opentelemetry.instrumentation.httpx._AsyncOpenTelemetryTransportBase
opentelemetry.instrumentation.httpx._BaseHTTPXClientInstrumentor
any=
; API
opentelemetry.propagators.textmap.TextMapPropagator.fields
; - AWSXRayPropagator
TraceId
; - AwsXRayIdGenerator
TraceIdRatioBased
; - AwsXRayIdGenerator
; SDK
SpanProcessor
TracerProvider
; - AwsXRayIdGenerator
; Instrumentation
BaseInstrumentor
; - instrumentation.*
Setter
httpx
instrument
__iter__
list.__iter__
__getitem__
list.__getitem__
SQS.ReceiveMessage
py-obj=
opentelemetry.propagators.textmap.CarrierT
opentelemetry.instrumentation.dbapi.ConnectionT
opentelemetry.instrumentation.dbapi.CursorT
py-data=
typing.Union
typing.Optional
py-func=
poll
flush
Message.error
py-exc=
KafkaException
KafkaError
opentelemetry-python-contrib-0.66b2/docs/opamp/ 0000775 0000000 0000000 00000000000 15270700723 0021611 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/docs/opamp/client.rst 0000664 0000000 0000000 00000000247 15270700723 0023624 0 ustar 00root root 0000000 0000000 OpenTelemetry Python - OpAMP Client
===================================
.. automodule:: opentelemetry._opamp
:members:
:undoc-members:
:show-inheritance:
opentelemetry-python-contrib-0.66b2/docs/performance/ 0000775 0000000 0000000 00000000000 15270700723 0022776 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/docs/performance/benchmarks.rst 0000664 0000000 0000000 00000000657 15270700723 0025655 0 ustar 00root root 0000000 0000000 Performance Tests - Benchmarks
==============================
For instructions on running and writing benchmarks locally, see the
`Benchmarks section of CONTRIBUTING.md `_.
Live benchmark results are published at
`opentelemetry.io/docs/languages/python/benchmarks `_.
opentelemetry-python-contrib-0.66b2/docs/propagator/ 0000775 0000000 0000000 00000000000 15270700723 0022653 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/docs/propagator/aws/ 0000775 0000000 0000000 00000000000 15270700723 0023445 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/docs/propagator/aws/aws.rst 0000664 0000000 0000000 00000000277 15270700723 0024777 0 ustar 00root root 0000000 0000000 OpenTelemetry Python - AWS X-Ray Propagator
===========================================
.. automodule:: opentelemetry.propagators.aws
:members:
:undoc-members:
:show-inheritance: opentelemetry-python-contrib-0.66b2/docs/resource/ 0000775 0000000 0000000 00000000000 15270700723 0022324 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/docs/resource/container/ 0000775 0000000 0000000 00000000000 15270700723 0024306 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/docs/resource/container/container.rst 0000664 0000000 0000000 00000000346 15270700723 0027025 0 ustar 00root root 0000000 0000000 OpenTelemetry Python - Resource Detector for Containers
=======================================================
.. automodule:: opentelemetry.resource.detector.containerid
:members:
:undoc-members:
:show-inheritance:
opentelemetry-python-contrib-0.66b2/docs/sdk-extension/ 0000775 0000000 0000000 00000000000 15270700723 0023270 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/docs/sdk-extension/aws/ 0000775 0000000 0000000 00000000000 15270700723 0024062 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/docs/sdk-extension/aws/aws.rst 0000664 0000000 0000000 00000000330 15270700723 0025402 0 ustar 00root root 0000000 0000000 OpenTelemetry Python - AWS SDK Extension
========================================
.. automodule:: opentelemetry.sdk.extension.aws.trace.aws_xray_id_generator
:members:
:undoc-members:
:show-inheritance:
opentelemetry-python-contrib-0.66b2/eachdist.ini 0000664 0000000 0000000 00000003641 15270700723 0022036 0 ustar 00root root 0000000 0000000 # These will be sorted first in that order.
# All packages that are depended upon by others should be listed here.
[DEFAULT]
ignore=
_template
sortfirst=
opentelemetry-instrumentation
util/opentelemetry-util-http
instrumentation/opentelemetry-instrumentation-wsgi
instrumentation/opentelemetry-instrumentation-dbapi
instrumentation/opentelemetry-instrumentation-asgi
instrumentation/opentelemetry-instrumentation-botocore
instrumentation/*
exporter/*
ext/*
[stable]
version=1.45.2
packages=
opentelemetry-sdk
opentelemetry-proto
opentelemetry-propagator-jaeger
opentelemetry-propagator-b3
opentelemetry-exporter-zipkin-proto-http
opentelemetry-exporter-zipkin-json
opentelemetry-exporter-zipkin
opentelemetry-exporter-otlp-proto-grpc
opentelemetry-exporter-otlp
opentelemetry-exporter-jaeger-thrift
opentelemetry-exporter-jaeger-proto-grpc
opentelemetry-exporter-jaeger
opentelemetry-api
opentelemetry-exporter-credential-provider-gcp
[prerelease]
version=0.66b2
packages=
all
opentelemetry-semantic-conventions
opentelemetry-test-utils
opentelemetry-instrumentation
opentelemetry-contrib-instrumentations
opentelemetry-distro
opentelemetry-resource-detector-containerid
[exclude_release]
packages=
opentelemetry-opamp-client
opentelemetry-instrumentation-valkey-py
opentelemetry-propagator-aws-xray
opentelemetry-resource-detector-azure
opentelemetry-resourcedetector-gcp
opentelemetry-sdk-extension-aws
opentelemetry-propagator-aws-xray
opentelemetry-instrumentation-vertexai
opentelemetry-instrumentation-openai-v2
opentelemetry-instrumentation-openai-agents-v2
opentelemetry-instrumentation-test
opentelemetry-util-genai
[lintroots]
extraroots=examples/*,scripts/
subglob=*.py,tests/,test/,src/*,examples/*
[testroots]
extraroots=examples/*,tests/
subglob=tests/,test/
opentelemetry-python-contrib-0.66b2/exporter/ 0000775 0000000 0000000 00000000000 15270700723 0021415 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/exporter/opentelemetry-exporter-credential-provider-gcp/ 0000775 0000000 0000000 00000000000 15270700723 0032666 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/exporter/opentelemetry-exporter-credential-provider-gcp/LICENSE 0000664 0000000 0000000 00000026135 15270700723 0033702 0 ustar 00root root 0000000 0000000 Apache License
Version 2.0, January 2004
http://www.apache.org/licenses/
TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION
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"Licensor" shall mean the copyright owner or entity authorized by
the copyright owner that is granting the License.
"Legal Entity" shall mean the union of the acting entity and all
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"control" means (i) the power, direct or indirect, to cause the
direction or management of such entity, whether by contract or
otherwise, or (ii) ownership of fifty percent (50%) or more of the
outstanding shares, or (iii) beneficial ownership of such entity.
"You" (or "Your") shall mean an individual or Legal Entity
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"Source" form shall mean the preferred form for making modifications,
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"Object" form shall mean any form resulting from mechanical
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not limited to compiled object code, generated documentation,
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"Work" shall mean the work of authorship, whether in Source or
Object form, made available under the License, as indicated by a
copyright notice that is included in or attached to the work
(an example is provided in the Appendix below).
"Derivative Works" shall mean any work, whether in Source or Object
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"Contribution" shall mean any work of authorship, including
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README.rst 0000664 0000000 0000000 00000004354 15270700723 0034304 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/exporter/opentelemetry-exporter-credential-provider-gcp OpenTelemetry GCP Credential Provider for OTLP Exporters
========================================================
.. image:: https://badge.fury.io/py/opentelemetry-exporter-credential-provider-gcp.svg
:target: https://badge.fury.io/py/opentelemetry-exporter-credential-provider-gcp
.. image:: https://readthedocs.org/projects/google-cloud-opentelemetry/badge/?version=latest
:target: https://google-cloud-opentelemetry.readthedocs.io/en/latest/?badge=latest
:alt: Documentation Status
This library provides support for supplying your machine's Application Default Credentials (https://cloud.google.com/docs/authentication/application-default-credentials)
to the OTLP Exporters created automatically by OpenTelemetry Python's auto instrumentation.
These credentials authorize OTLP traces to be sent to `telemetry.googleapis.com`.
Currently `telemetry.googleapis.com` only supports OTLP traces, but eventually the endpoint will
support OTLP logs and metrics too.
To learn more about instrumentation and observability, including opinionated recommendations
for Google Cloud Observability, visit `Instrumentation and observability
`_.
For how to export trace data when you use manual instrumentation visit `Migrate from the Trace exporter to the OTLP endpoint
`_.
Installation
------------
.. code:: bash
pip install opentelemetry-exporter-credential-provider-gcp
Usage
-----
Your installed HTTP/GRPC OTLP Exporter must be at release `>=1.37` for this feature.
Set the following environment variables:
`export OTEL_RESOURCE_ATTRIBUTES="gcp.project_id="`
`export OTEL_EXPORTER_OTLP_TRACES_ENDPOINT="https://telemetry.googleapis.com:443/v1/traces"`
If you plan to have python auto instrumentation use the GRPC OTLP Exporter to send traces to Cloud Trace:
`export OTEL_PYTHON_EXPORTER_OTLP_GRPC_TRACES_CREDENTIAL_PROVIDER=gcp_grpc_credentials`
If you plan to have python auto instrumentation use the HTTP OTLP Exporter to send traces to Cloud Trace:
`export OTEL_PYTHON_EXPORTER_OTLP_HTTP_TRACES_CREDENTIAL_PROVIDER=gcp_http_credentials`
References
----------
* `OpenTelemetry Project `_
pyproject.toml 0000664 0000000 0000000 00000003171 15270700723 0035525 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/exporter/opentelemetry-exporter-credential-provider-gcp [build-system]
requires = ["hatchling"]
build-backend = "hatchling.build"
[project]
name = "opentelemetry-exporter-credential-provider-gcp"
dynamic = ["version"]
description = "GCP OTLP Exporter Credential Provider for OpenTelemetry"
readme = "README.rst"
license = "Apache-2.0"
requires-python = ">=3.10"
authors = [
{ name = "OpenTelemetry Authors", email = "cncf-opentelemetry-contributors@lists.cncf.io" },
]
classifiers = [
"Development Status :: 4 - Beta",
"Intended Audience :: Developers",
"License :: OSI Approved :: Apache Software License",
"Programming Language :: Python",
"Programming Language :: Python :: 3",
"Programming Language :: Python :: 3.10",
"Programming Language :: Python :: 3.11",
"Programming Language :: Python :: 3.12",
"Programming Language :: Python :: 3.13",
"Programming Language :: Python :: 3.14",
]
dependencies = [
"grpcio >= 1.67.0",
"google-auth >= 2.25",
"requests >= 2.7",
]
[project.entry-points.opentelemetry_otlp_credential_provider]
gcp_grpc_credentials = "opentelemetry.gcp_credential_provider:create_google_grpc_credentials"
gcp_http_credentials = "opentelemetry.gcp_credential_provider:create_google_authorized_session"
[project.urls]
Homepage = "https://github.com/open-telemetry/opentelemetry-python-contrib/tree/main/exporter/opentelemetry-exporter-credential-provider-gcp"
Repository = "https://github.com/open-telemetry/opentelemetry-python-contrib"
[tool.hatch.version]
path = "src/opentelemetry/gcp_credential_provider/version.py"
[tool.hatch.build.targets.sdist]
include = [
"/src",
"/tests",
]
[tool.hatch.build.targets.wheel]
packages = ["src/opentelemetry"]
opentelemetry-python-contrib-0.66b2/exporter/opentelemetry-exporter-credential-provider-gcp/src/ 0000775 0000000 0000000 00000000000 15270700723 0033455 5 ustar 00root root 0000000 0000000 opentelemetry/ 0000775 0000000 0000000 00000000000 15270700723 0036272 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/exporter/opentelemetry-exporter-credential-provider-gcp/src gcp_credential_provider/ 0000775 0000000 0000000 00000000000 15270700723 0043147 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/exporter/opentelemetry-exporter-credential-provider-gcp/src/opentelemetry __init__.py 0000664 0000000 0000000 00000001444 15270700723 0045263 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/exporter/opentelemetry-exporter-credential-provider-gcp/src/opentelemetry/gcp_credential_provider # Copyright 2025 Google LLC
# SPDX-License-Identifier: Apache-2.0
import google.auth
import grpc
import requests
from google.auth.transport.grpc import AuthMetadataPlugin
from google.auth.transport.requests import AuthorizedSession, Request
# pyright: reportUnknownMemberType=false, reportUnknownArgumentType=false, reportUnknownVariableType=false
def create_google_grpc_credentials() -> grpc.ChannelCredentials:
credentials, _ = google.auth.default()
return grpc.composite_channel_credentials(
grpc.ssl_channel_credentials(),
grpc.metadata_call_credentials(AuthMetadataPlugin(credentials=credentials, request=Request())),
)
def create_google_authorized_session() -> requests.Session:
credentials, _ = google.auth.default()
return AuthorizedSession(credentials)
version.py 0000664 0000000 0000000 00000000144 15270700723 0045205 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/exporter/opentelemetry-exporter-credential-provider-gcp/src/opentelemetry/gcp_credential_provider # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
__version__ = "0.66b2"
test-requirements.txt 0000664 0000000 0000000 00000000203 15270700723 0037043 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/exporter/opentelemetry-exporter-credential-provider-gcp pytest==7.4.4
opentelemetry-exporter-otlp-proto-http==1.37
opentelemetry-exporter-otlp-proto-common==1.37
opentelemetry-proto==1.37 opentelemetry-python-contrib-0.66b2/exporter/opentelemetry-exporter-credential-provider-gcp/tests/ 0000775 0000000 0000000 00000000000 15270700723 0034030 5 ustar 00root root 0000000 0000000 test_credential_provider.py 0000664 0000000 0000000 00000003060 15270700723 0041405 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/exporter/opentelemetry-exporter-credential-provider-gcp/tests # Copyright 2023 Google LLC
# SPDX-License-Identifier: Apache-2.0
from os import environ
from unittest import TestCase
from unittest.mock import MagicMock, patch
from google.auth.transport.requests import AuthorizedSession
from opentelemetry.exporter.otlp.proto.http.trace_exporter import (
OTLPSpanExporter,
)
from opentelemetry.sdk.environment_variables import (
_OTEL_PYTHON_EXPORTER_OTLP_GRPC_TRACES_CREDENTIAL_PROVIDER,
_OTEL_PYTHON_EXPORTER_OTLP_HTTP_TRACES_CREDENTIAL_PROVIDER,
)
# pyright: reportUnknownMemberType=false, reportUnknownVariableType=false, reportMissingImports=false, reportUntypedFunctionDecorator=false
class TestOTLPTraceAutoInstrumentGcpCredential(TestCase):
@patch("google.auth.default")
@patch.dict(
environ,
{
_OTEL_PYTHON_EXPORTER_OTLP_HTTP_TRACES_CREDENTIAL_PROVIDER: "gcp_http_credentials",
_OTEL_PYTHON_EXPORTER_OTLP_GRPC_TRACES_CREDENTIAL_PROVIDER: "gcp_grpc_credentials",
},
)
def test_loads_otlp_exporters_with_google_creds(self, mock_default: MagicMock): # pylint: disable=no-self-use
"""Test that OTel configuration internals can load the credentials from entrypoint by
name"""
mock_credentials = MagicMock()
mock_credentials.project_id = "test-project"
mock_default.return_value = (mock_credentials, "test-project")
http_exporter = OTLPSpanExporter()
assert isinstance(http_exporter._session, AuthorizedSession)
# Assert that google.auth.default was called
mock_default.assert_called_once()
opentelemetry-python-contrib-0.66b2/exporter/opentelemetry-exporter-prometheus-remote-write/ 0000775 0000000 0000000 00000000000 15270700723 0032771 5 ustar 00root root 0000000 0000000 README.rst 0000664 0000000 0000000 00000001675 15270700723 0034412 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/exporter/opentelemetry-exporter-prometheus-remote-write OpenTelemetry Prometheus Remote Write Exporter
==============================================
|pypi|
.. |pypi| image:: https://badge.fury.io/py/opentelemetry-exporter-prometheus-remote-write.svg
:target: https://pypi.org/project/opentelemetry-exporter-prometheus-remote-write/
This package contains an exporter to send metrics from the OpenTelemetry Python SDK directly to a Prometheus Remote Write integrated backend
(such as Cortex or Thanos) without having to run an instance of the Prometheus server.
Installation
------------
::
pip install opentelemetry-exporter-prometheus-remote-write
.. _OpenTelemetry: https://github.com/open-telemetry/opentelemetry-python/
.. _Prometheus Remote Write integrated backend: https://prometheus.io/docs/operating/integrations/
References
----------
* `OpenTelemetry Project `_
* `Prometheus Remote Write Integration `_
opentelemetry-python-contrib-0.66b2/exporter/opentelemetry-exporter-prometheus-remote-write/example/0000775 0000000 0000000 00000000000 15270700723 0034424 5 ustar 00root root 0000000 0000000 Dockerfile 0000664 0000000 0000000 00000000322 15270700723 0036334 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/exporter/opentelemetry-exporter-prometheus-remote-write/example FROM python:3.10
RUN apt-get update -y && apt-get install libsnappy-dev -y
WORKDIR /code
COPY . .
RUN pip install -e .
RUN pip install -r ./example/requirements.txt
CMD ["python", "./example/sampleapp.py"]
README.md 0000664 0000000 0000000 00000003745 15270700723 0035635 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/exporter/opentelemetry-exporter-prometheus-remote-write/example # Prometheus Remote Write Exporter Example
This example uses [Docker Compose](https://docs.docker.com/compose/) to set up:
1. A Python program that creates 5 instruments with 5 unique
aggregators and a randomized load generator
2. An instance of [Cortex](https://cortexmetrics.io/) to receive the metrics
data
3. An instance of [Grafana](https://grafana.com/) to visualizse the exported
data
## Requirements
* Have Docker Compose [installed](https://docs.docker.com/compose/install/)
*Users do not need to install Python as the app will be run in the Docker Container*
## Instructions
1. Run `docker-compose up -d` in the the `example/` directory
The `-d` flag causes all services to run in detached mode and frees up your
terminal session. This also causes no logs to show up. Users can attach themselves to the service's logs manually using `docker logs ${CONTAINER_ID} --follow`
2. Log into the Grafana instance at [http://localhost:3000](http://localhost:3000)
* login credentials are `username: admin` and `password: admin`
* There may be an additional screen on setting a new password. This can be skipped and is optional
3. Navigate to the `Data Sources` page
* Look for a gear icon on the left sidebar and select `Data Sources`
4. Add a new Prometheus Data Source
* Use `http://cortex:9009/api/prom` as the URL
* (OPTIONAl) set the scrape interval to `2s` to make updates appear quickly
* click `Save & Test`
5. Go to `Metrics Explore` to query metrics
* Look for a compass icon on the left sidebar
* click `Metrics` for a dropdown list of all the available metrics
* (OPTIONAL) Adjust time range by clicking the `Last 6 hours` button on the upper right side of the graph
* (OPTIONAL) Set up auto-refresh by selecting an option under the dropdown next to the refresh button on the upper right side of the graph
* Click the refresh button and data should show up on the graph
6. Shutdown the services when finished
* Run `docker-compose down` in the example directory
cortex-config.yml 0000664 0000000 0000000 00000005161 15270700723 0037642 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/exporter/opentelemetry-exporter-prometheus-remote-write/example # This Cortex Config is copied from the Cortex Project documentation
# Source: https://github.com/cortexproject/cortex/blob/master/docs/configuration/single-process-config.yaml
# Configuration for running Cortex in single-process mode.
# This configuration should not be used in production.
# It is only for getting started and development.
# Disable the requirement that every request to Cortex has a
# X-Scope-OrgID header. `fake` will be substituted in instead.
# pylint: skip-file
auth_enabled: false
server:
http_listen_port: 9009
# Configure the server to allow messages up to 100MB.
grpc_server_max_recv_msg_size: 104857600
grpc_server_max_send_msg_size: 104857600
grpc_server_max_concurrent_streams: 1000
distributor:
shard_by_all_labels: true
pool:
health_check_ingesters: true
ingester_client:
grpc_client_config:
# Configure the client to allow messages up to 100MB.
max_recv_msg_size: 104857600
max_send_msg_size: 104857600
use_gzip_compression: true
ingester:
# We want our ingesters to flush chunks at the same time to optimise
# deduplication opportunities.
spread_flushes: true
chunk_age_jitter: 0
walconfig:
wal_enabled: true
recover_from_wal: true
wal_dir: /tmp/cortex/wal
lifecycler:
# The address to advertise for this ingester. Will be autodiscovered by
# looking up address on eth0 or en0; can be specified if this fails.
# address: 127.0.0.1
# We want to start immediately and flush on shutdown.
join_after: 0
min_ready_duration: 0s
final_sleep: 0s
num_tokens: 512
tokens_file_path: /tmp/cortex/wal/tokens
# Use an in memory ring store, so we don't need to launch a Consul.
ring:
kvstore:
store: inmemory
replication_factor: 1
# Use local storage - BoltDB for the index, and the filesystem
# for the chunks.
schema:
configs:
- from: 2019-07-29
store: boltdb
object_store: filesystem
schema: v10
index:
prefix: index_
period: 1w
storage:
boltdb:
directory: /tmp/cortex/index
filesystem:
directory: /tmp/cortex/chunks
delete_store:
store: boltdb
purger:
object_store_type: filesystem
frontend_worker:
# Configure the frontend worker in the querier to match worker count
# to max_concurrent on the queriers.
match_max_concurrent: true
# Configure the ruler to scan the /tmp/cortex/rules directory for prometheus
# rules: https://prometheus.io/docs/prometheus/latest/configuration/recording_rules/#recording-rules
ruler:
enable_api: true
enable_sharding: false
storage:
type: local
local:
directory: /tmp/cortex/rules
docker-compose.yml 0000664 0000000 0000000 00000001731 15270700723 0040004 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/exporter/opentelemetry-exporter-prometheus-remote-write/example # Copyright The OpenTelemetry Authors
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
version: "3.8"
services:
cortex:
image: quay.io/cortexproject/cortex:v1.5.0
command:
- -config.file=./config/cortex-config.yml
volumes:
- ./cortex-config.yml:/config/cortex-config.yml:ro
ports:
- 9009:9009
grafana:
image: grafana/grafana:latest
ports:
- 3000:3000
sample_app:
build:
context: ../
dockerfile: ./example/Dockerfile
requirements.txt 0000664 0000000 0000000 00000000166 15270700723 0037634 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/exporter/opentelemetry-exporter-prometheus-remote-write/example psutil
protobuf>=3.13.0
requests>=2.25.0
python-snappy>=0.5.4
opentelemetry-api
opentelemetry-sdk
opentelemetry-proto
sampleapp.py 0000664 0000000 0000000 00000005223 15270700723 0036703 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/exporter/opentelemetry-exporter-prometheus-remote-write/example # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
import logging
import random
import sys
import time
from logging import INFO
import psutil
from opentelemetry import metrics
from opentelemetry.exporter.prometheus_remote_write import (
PrometheusRemoteWriteMetricsExporter,
)
from opentelemetry.metrics import Observation
from opentelemetry.sdk.metrics import MeterProvider
from opentelemetry.sdk.metrics.export import PeriodicExportingMetricReader
logging.basicConfig(stream=sys.stdout, level=logging.INFO)
logger = logging.getLogger(__name__)
testing_labels = {"environment": "testing"}
exporter = PrometheusRemoteWriteMetricsExporter(
endpoint="http://cortex:9009/api/prom/push",
headers={"X-Scope-Org-ID": "5"},
)
reader = PeriodicExportingMetricReader(exporter, 1000)
provider = MeterProvider(metric_readers=[reader])
metrics.set_meter_provider(provider)
meter = metrics.get_meter(__name__)
# Callback to gather cpu usage
def get_cpu_usage_callback(observer):
for number, percent in enumerate(psutil.cpu_percent(percpu=True)):
labels = {"cpu_number": str(number)}
yield Observation(percent, labels)
# Callback to gather RAM usage
def get_ram_usage_callback(observer):
ram_percent = psutil.virtual_memory().percent
yield Observation(ram_percent, {})
requests_counter = meter.create_counter(
name="requests",
description="number of requests",
unit="1",
)
request_min_max = meter.create_counter(
name="requests_min_max",
description="min max sum count of requests",
unit="1",
)
request_last_value = meter.create_counter(
name="requests_last_value",
description="last value number of requests",
unit="1",
)
requests_active = meter.create_up_down_counter(
name="requests_active",
description="number of active requests",
unit="1",
)
meter.create_observable_counter(
callbacks=[get_ram_usage_callback],
name="ram_usage",
description="ram usage",
unit="1",
)
meter.create_observable_up_down_counter(
callbacks=[get_cpu_usage_callback],
name="cpu_percent",
description="per-cpu usage",
unit="1",
)
request_latency = meter.create_histogram("request_latency")
# Load generator
num = random.randint(0, 1000)
while True:
# counters
requests_counter.add(num % 131 + 200, testing_labels)
request_min_max.add(num % 181 + 200, testing_labels)
request_last_value.add(num % 101 + 200, testing_labels)
# updown counter
requests_active.add(num % 7231 + 200, testing_labels)
request_latency.record(num % 92, testing_labels)
logger.log(level=INFO, msg="completed metrics collection cycle")
time.sleep(1)
num += 9791
opentelemetry-python-contrib-0.66b2/exporter/opentelemetry-exporter-prometheus-remote-write/proto/ 0000775 0000000 0000000 00000000000 15270700723 0034134 5 ustar 00root root 0000000 0000000 .gitignore 0000664 0000000 0000000 00000000016 15270700723 0036042 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/exporter/opentelemetry-exporter-prometheus-remote-write/proto opentelemetry
README.md 0000664 0000000 0000000 00000000342 15270700723 0035333 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/exporter/opentelemetry-exporter-prometheus-remote-write/proto ## Instructions
1. Install protobuf tools. Can use your package manager or download from [GitHub](https://github.com/protocolbuffers/protobuf/releases/tag/v26.0)
2. Run `generate-proto-py.sh` from inside the `proto/` directory generate-proto-py.sh 0000775 0000000 0000000 00000004132 15270700723 0037775 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/exporter/opentelemetry-exporter-prometheus-remote-write/proto #!/bin/bash
set -e
PROM_VERSION=v2.39.0
PROTO_VERSION=v1.3.2
# SRC_DIR is from protoc perspective. ie its the destination for our checkouts/clones
SRC_DIR=opentelemetry/exporter/prometheus_remote_write/gen/
#TODO:
# Check that black & protoc are installed properly
echo "Creating our destination directory"
mkdir -p ${SRC_DIR}/gogoproto
# Clone prometheus
echo "Grabbing Prometheus protobuf files"
git clone --filter=blob:none --sparse https://github.com/prometheus/prometheus.git
cd prometheus
git checkout ${PROM_VERSION}
git sparse-checkout set prompb
cd ..
# We also need gogo.proto which is in the protobuf Repo
# Could also try to pull this locally from the install location of protobuf
# but that will be harder in a platform agnostic way.
echo "Grabbing gogo.proto"
git clone --filter=blob:none --sparse https://github.com/gogo/protobuf.git
cd protobuf
git checkout ${PROTO_VERSION}
git sparse-checkout set /gogoproto/gogo.proto
cd ..
# Move the proto files into our structure
echo "Moving proto files to ${SRC_DIR}"
cp prometheus/prompb/remote.proto prometheus/prompb/types.proto ${SRC_DIR}
cp protobuf/gogoproto/gogo.proto ${SRC_DIR}/gogoproto/
# A bit of a hack, but we need to fix the imports to fit the python structure.
# using sed to find the 3 files and point them at each other using OUR structure
echo "Fixing imports"
sed -i 's/import "types.proto";/import "opentelemetry\/exporter\/prometheus_remote_write\/gen\/types.proto";/' ${SRC_DIR}/remote.proto
sed -i 's/import "gogoproto\/gogo.proto";/import "opentelemetry\/exporter\/prometheus_remote_write\/gen\/gogoproto\/gogo.proto";/' ${SRC_DIR}/remote.proto
sed -i 's/import "gogoproto\/gogo.proto";/import "opentelemetry\/exporter\/prometheus_remote_write\/gen\/gogoproto\/gogo.proto";/' ${SRC_DIR}/types.proto
# Cleanup the repos
echo "Removing clones..."
rm -rf protobuf prometheus
# Used libprotoc 26
echo "Compiling proto files to Python"
protoc -I . --python_out=../src ${SRC_DIR}/gogoproto/gogo.proto ${SRC_DIR}/remote.proto ${SRC_DIR}/types.proto
echo "Running formatting on the generated files"
../../../scripts/eachdist.py format --path $PWD/..
pyproject.toml 0000664 0000000 0000000 00000002716 15270700723 0035634 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/exporter/opentelemetry-exporter-prometheus-remote-write [build-system]
requires = ["hatchling"]
build-backend = "hatchling.build"
[project]
name = "opentelemetry-exporter-prometheus-remote-write"
dynamic = ["version"]
description = "Prometheus Remote Write Metrics Exporter for OpenTelemetry"
readme = "README.rst"
license = "Apache-2.0"
requires-python = ">=3.10"
authors = [
{ name = "OpenTelemetry Authors", email = "cncf-opentelemetry-contributors@lists.cncf.io" },
]
classifiers = [
"Development Status :: 4 - Beta",
"Intended Audience :: Developers",
"License :: OSI Approved :: Apache Software License",
"Programming Language :: Python",
"Programming Language :: Python :: 3",
"Programming Language :: Python :: 3.10",
"Programming Language :: Python :: 3.11",
"Programming Language :: Python :: 3.12",
"Programming Language :: Python :: 3.13",
"Programming Language :: Python :: 3.14",
]
dependencies = [
"protobuf >=5.26, <7.0",
"requests ~= 2.28",
"opentelemetry-api ~= 1.12",
"opentelemetry-sdk ~= 1.12",
"python-snappy ~= 0.6",
]
[project.urls]
Homepage = "https://github.com/open-telemetry/opentelemetry-python-contrib/tree/main/exporter/opentelemetry-exporter-prometheus-remote-write"
Repository = "https://github.com/open-telemetry/opentelemetry-python-contrib"
[tool.hatch.version]
path = "src/opentelemetry/exporter/prometheus_remote_write/version.py"
[tool.hatch.build.targets.sdist]
include = [
"/src",
"/tests",
]
[tool.hatch.build.targets.wheel]
packages = ["src/opentelemetry"]
opentelemetry-python-contrib-0.66b2/exporter/opentelemetry-exporter-prometheus-remote-write/src/ 0000775 0000000 0000000 00000000000 15270700723 0033560 5 ustar 00root root 0000000 0000000 opentelemetry/ 0000775 0000000 0000000 00000000000 15270700723 0036375 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/exporter/opentelemetry-exporter-prometheus-remote-write/src exporter/ 0000775 0000000 0000000 00000000000 15270700723 0040245 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/exporter/opentelemetry-exporter-prometheus-remote-write/src/opentelemetry prometheus_remote_write/ 0000775 0000000 0000000 00000000000 15270700723 0045225 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/exporter/opentelemetry-exporter-prometheus-remote-write/src/opentelemetry/exporter __init__.py 0000664 0000000 0000000 00000033124 15270700723 0047341 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/exporter/opentelemetry-exporter-prometheus-remote-write/src/opentelemetry/exporter/prometheus_remote_write # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
import logging
import re
from collections import defaultdict
from collections.abc import Mapping, Sequence
from itertools import chain
import requests
import snappy
from opentelemetry.exporter.prometheus_remote_write.gen.remote_pb2 import ( # pylint: disable=no-name-in-module
WriteRequest,
)
from opentelemetry.exporter.prometheus_remote_write.gen.types_pb2 import ( # pylint: disable=no-name-in-module
Label,
Sample,
TimeSeries,
)
from opentelemetry.sdk.metrics import (
Counter,
ObservableCounter,
ObservableGauge,
ObservableUpDownCounter,
UpDownCounter,
)
from opentelemetry.sdk.metrics import Histogram as ClientHistogram
from opentelemetry.sdk.metrics.export import (
AggregationTemporality,
Gauge,
Histogram,
Metric,
MetricExporter,
MetricExportResult,
MetricsData,
Sum,
)
logger = logging.getLogger(__name__)
PROMETHEUS_NAME_REGEX = re.compile(r"^\d|[^\w:]")
PROMETHEUS_LABEL_REGEX = re.compile(r"^\d|[^\w]")
UNDERSCORE_REGEX = re.compile(r"_+")
class PrometheusRemoteWriteMetricsExporter(MetricExporter):
"""
Prometheus remote write metric exporter for OpenTelemetry.
Args:
endpoint: url where data will be sent (Required)
basic_auth: username and password for authentication (Optional)
headers: additional headers for remote write request (Optional)
timeout: timeout for remote write requests in seconds, defaults to 30 (Optional)
proxies: dict mapping request proxy protocols to proxy urls (Optional)
tls_config: configuration for remote write TLS settings (Optional)
"""
def __init__(
self,
endpoint: str,
basic_auth: dict = None,
headers: dict = None,
timeout: int = 30,
tls_config: dict = None,
proxies: dict = None,
resources_as_labels: bool = True,
preferred_temporality: dict[type, AggregationTemporality] = None,
preferred_aggregation: dict = None,
):
self.endpoint = endpoint
self.basic_auth = basic_auth
self.headers = headers
self.timeout = timeout
self.tls_config = tls_config
self.proxies = proxies
self.resources_as_labels = resources_as_labels
if not preferred_temporality:
preferred_temporality = {
Counter: AggregationTemporality.CUMULATIVE,
UpDownCounter: AggregationTemporality.CUMULATIVE,
ClientHistogram: AggregationTemporality.CUMULATIVE,
ObservableCounter: AggregationTemporality.CUMULATIVE,
ObservableUpDownCounter: AggregationTemporality.CUMULATIVE,
ObservableGauge: AggregationTemporality.CUMULATIVE,
}
super().__init__(preferred_temporality, preferred_aggregation)
@property
def endpoint(self):
return self._endpoint
@endpoint.setter
def endpoint(self, endpoint: str):
if endpoint == "":
raise ValueError("endpoint required")
self._endpoint = endpoint
@property
def basic_auth(self):
return self._basic_auth
@basic_auth.setter
def basic_auth(self, basic_auth: dict):
if basic_auth:
if "username" not in basic_auth:
raise ValueError("username required in basic_auth")
if "password_file" in basic_auth:
if "password" in basic_auth:
raise ValueError("basic_auth cannot contain password and password_file")
with open( # pylint: disable=unspecified-encoding
basic_auth["password_file"]
) as file:
basic_auth["password"] = file.readline().strip()
elif "password" not in basic_auth:
raise ValueError("password required in basic_auth")
self._basic_auth = basic_auth
@property
def timeout(self):
return self._timeout
@timeout.setter
def timeout(self, timeout: int):
if timeout <= 0:
raise ValueError("timeout must be greater than 0")
self._timeout = timeout
@property
def tls_config(self):
return self._tls_config
@tls_config.setter
def tls_config(self, tls_config: dict):
if tls_config:
new_config = {}
if "ca_file" in tls_config:
new_config["ca_file"] = tls_config["ca_file"]
if "cert_file" in tls_config and "key_file" in tls_config:
new_config["cert_file"] = tls_config["cert_file"]
new_config["key_file"] = tls_config["key_file"]
elif "cert_file" in tls_config or "key_file" in tls_config:
raise ValueError("tls_config requires both cert_file and key_file")
if "insecure_skip_verify" in tls_config:
new_config["insecure_skip_verify"] = tls_config["insecure_skip_verify"]
self._tls_config = tls_config
@property
def proxies(self):
return self._proxies
@proxies.setter
def proxies(self, proxies: dict):
self._proxies = proxies
@property
def headers(self):
return self._headers
@headers.setter
def headers(self, headers: dict):
self._headers = headers
def export(
self,
metrics_data: MetricsData,
timeout_millis: float = 10_000,
**kwargs,
) -> MetricExportResult:
if not metrics_data:
return MetricExportResult.SUCCESS
timeseries = self._translate_data(metrics_data)
if not timeseries:
logger.error("All records contain unsupported aggregators, export aborted")
return MetricExportResult.FAILURE
message = self._build_message(timeseries)
headers = self._build_headers()
return self._send_message(message, headers)
def _translate_data(self, data: MetricsData) -> Sequence[TimeSeries]:
rw_timeseries = []
for resource_metrics in data.resource_metrics:
resource = resource_metrics.resource
# OTLP Data model suggests combining some attrs into job/instance
# Should we do that here?
if self.resources_as_labels:
resource_labels = [(n, str(v)) for n, v in resource.attributes.items()]
else:
resource_labels = []
# Scope name/version probably not too useful from a labeling perspective
for scope_metrics in resource_metrics.scope_metrics:
for metric in scope_metrics.metrics:
rw_timeseries.extend(self._parse_metric(metric, resource_labels))
return rw_timeseries
def _parse_metric(self, metric: Metric, resource_labels: Sequence) -> Sequence[TimeSeries]:
"""
Parses the Metric & lower objects, then converts the output into
OM TimeSeries. Returns a List of TimeSeries objects based on one Metric
"""
# Create the metric name, will be a label later
if metric.unit:
# Prom. naming guidelines add unit to the name
name = f"{metric.name}_{metric.unit}"
else:
name = metric.name
# datapoints have attributes associated with them. these would be sent
# to RW as different metrics: name & labels is a unique time series
sample_sets = defaultdict(list)
if isinstance(metric.data, (Gauge, Sum)):
for dp in metric.data.data_points:
attrs, sample = self._parse_data_point(dp, name)
sample_sets[attrs].append(sample)
elif isinstance(metric.data, Histogram):
for dp in metric.data.data_points:
dp_result = self._parse_histogram_data_point(dp, name)
for attrs, sample in dp_result:
sample_sets[attrs].append(sample)
else:
logger.warning("Unsupported Metric Type: %s", type(metric.data))
return []
return self._convert_to_timeseries(sample_sets, resource_labels)
def _convert_to_timeseries(
self, sample_sets: Mapping[tuple, Sequence], resource_labels: Sequence
) -> Sequence[TimeSeries]:
timeseries = []
for labels, samples in sample_sets.items():
ts = TimeSeries()
for label_name, label_value in sorted(chain(resource_labels, labels)):
# Previous implementation did not str() the names...
ts.labels.append(self._label(label_name, str(label_value)))
for value, timestamp in samples:
ts.samples.append(self._sample(value, timestamp))
timeseries.append(ts)
return timeseries
@staticmethod
def _sample(value: int, timestamp: int) -> Sample:
sample = Sample()
sample.value = value
sample.timestamp = timestamp
return sample
def _label(self, name: str, value: str) -> Label:
label = Label()
label.name = self._sanitize_string(name, "label")
label.value = value
return label
@staticmethod
def _sanitize_string(string: str, type_: str) -> str:
# I Think Prometheus requires names to NOT start with a number this
# would not catch that, but do cover the other cases. The naming rules
# don't explicit say this, but the supplied regex implies it.
# Got a little weird trying to do substitution with it, but can be
# fixed if we allow numeric beginnings to metric names
if type_ == "name":
sanitized = PROMETHEUS_NAME_REGEX.sub("_", string)
elif type_ == "label":
sanitized = PROMETHEUS_LABEL_REGEX.sub("_", string)
else:
raise TypeError(f"Unsupported string type: {type_}")
# Remove consecutive underscores
# TODO: Unfortunately this clobbbers __name__
# sanitized = UNDERSCORE_REGEX.sub("_",sanitized)
return sanitized
def _parse_histogram_data_point(self, data_point, name):
sample_attr_pairs = []
base_attrs = list(data_point.attributes.items())
timestamp = data_point.time_unix_nano // 1_000_000
def handle_bucket(value, bound=None, name_override=None):
# Metric Level attributes + the bucket boundary attribute + name
ts_attrs = base_attrs.copy()
ts_attrs.append(
(
"__name__",
self._sanitize_string(name_override or name, "name"),
)
)
if bound:
ts_attrs.append(("le", str(bound)))
# Value is count of values in each bucket
ts_sample = (value, timestamp)
return tuple(ts_attrs), ts_sample
for bound_pos, bound in enumerate(data_point.explicit_bounds):
sample_attr_pairs.append(handle_bucket(data_point.bucket_counts[bound_pos], bound))
# Add the last label for implicit +inf bucket
sample_attr_pairs.append(handle_bucket(data_point.bucket_counts[-1], bound="+Inf"))
# Lastly, add series for count & sum
sample_attr_pairs.append(handle_bucket(data_point.sum, name_override=f"{name}_sum"))
sample_attr_pairs.append(handle_bucket(data_point.count, name_override=f"{name}_count"))
return sample_attr_pairs
def _parse_data_point(self, data_point, name=None):
attrs = tuple(data_point.attributes.items()) + (("__name__", self._sanitize_string(name, "name")),)
sample = (data_point.value, (data_point.time_unix_nano // 1_000_000))
return attrs, sample
@staticmethod
def _build_message(timeseries: Sequence[TimeSeries]) -> bytes:
write_request = WriteRequest()
write_request.timeseries.extend(timeseries)
serialized_message = write_request.SerializeToString()
return snappy.compress(serialized_message)
def _build_headers(self) -> dict:
headers = {
"Content-Encoding": "snappy",
"Content-Type": "application/x-protobuf",
"X-Prometheus-Remote-Write-Version": "0.1.0",
}
if self.headers:
for header_name, header_value in self.headers.items():
headers[header_name] = header_value
return headers
def _send_message(self, message: bytes, headers: dict) -> MetricExportResult:
auth = None
if self.basic_auth:
auth = (self.basic_auth["username"], self.basic_auth["password"])
cert = None
verify = True
if self.tls_config:
if "ca_file" in self.tls_config:
verify = self.tls_config["ca_file"]
elif "insecure_skip_verify" in self.tls_config:
verify = self.tls_config["insecure_skip_verify"]
if "cert_file" in self.tls_config and "key_file" in self.tls_config:
cert = (
self.tls_config["cert_file"],
self.tls_config["key_file"],
)
try:
response = requests.post(
self.endpoint,
data=message,
headers=headers,
auth=auth,
timeout=self.timeout,
proxies=self.proxies,
cert=cert,
verify=verify,
)
if not response.ok:
response.raise_for_status()
except requests.exceptions.RequestException as err:
logger.error("Export POST request failed with reason: %s", err)
return MetricExportResult.FAILURE
return MetricExportResult.SUCCESS
def force_flush(self, timeout_millis: float = 10_000) -> bool:
return True
def shutdown(self, timeout_millis: float = 30_000, **kwargs) -> None:
pass
gen/ 0000775 0000000 0000000 00000000000 15270700723 0045776 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/exporter/opentelemetry-exporter-prometheus-remote-write/src/opentelemetry/exporter/prometheus_remote_write gogoproto/ 0000775 0000000 0000000 00000000000 15270700723 0050015 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/exporter/opentelemetry-exporter-prometheus-remote-write/src/opentelemetry/exporter/prometheus_remote_write/gen gogoproto/gogo_pb2.py 0000664 0000000 0000000 00000017252 15270700723 0052074 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/exporter/opentelemetry-exporter-prometheus-remote-write/src/opentelemetry/exporter/prometheus_remote_write/gen # -*- coding: utf-8 -*-
# Generated by the protocol buffer compiler. DO NOT EDIT!
# source: opentelemetry/exporter/prometheus_remote_write/gen/gogoproto/gogo.proto
# Protobuf Python Version: 5.26.0
"""Generated protocol buffer code."""
from google.protobuf import descriptor as _descriptor
from google.protobuf import descriptor_pool as _descriptor_pool
from google.protobuf import symbol_database as _symbol_database
from google.protobuf.internal import builder as _builder
# @@protoc_insertion_point(imports)
_sym_db = _symbol_database.Default()
from google.protobuf import descriptor_pb2 as google_dot_protobuf_dot_descriptor__pb2
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# @@protoc_insertion_point(module_scope)
remote_pb2.py 0000664 0000000 0000000 00000007260 15270700723 0050413 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/exporter/opentelemetry-exporter-prometheus-remote-write/src/opentelemetry/exporter/prometheus_remote_write/gen # -*- coding: utf-8 -*-
# Generated by the protocol buffer compiler. DO NOT EDIT!
# source: opentelemetry/exporter/prometheus_remote_write/gen/remote.proto
# Protobuf Python Version: 5.26.0
"""Generated protocol buffer code."""
from google.protobuf import descriptor as _descriptor
from google.protobuf import descriptor_pool as _descriptor_pool
from google.protobuf import symbol_database as _symbol_database
from google.protobuf.internal import builder as _builder
# @@protoc_insertion_point(imports)
_sym_db = _symbol_database.Default()
from opentelemetry.exporter.prometheus_remote_write.gen import types_pb2 as opentelemetry_dot_exporter_dot_prometheus__remote__write_dot_gen_dot_types__pb2
from opentelemetry.exporter.prometheus_remote_write.gen.gogoproto import gogo_pb2 as opentelemetry_dot_exporter_dot_prometheus__remote__write_dot_gen_dot_gogoproto_dot_gogo__pb2
DESCRIPTOR = _descriptor_pool.Default().AddSerializedFile(b'\n?opentelemetry/exporter/prometheus_remote_write/gen/remote.proto\x12\nprometheus\x1a>opentelemetry/exporter/prometheus_remote_write/gen/types.proto\x1aGopentelemetry/exporter/prometheus_remote_write/gen/gogoproto/gogo.proto\"z\n\x0cWriteRequest\x12\x30\n\ntimeseries\x18\x01 \x03(\x0b\x32\x16.prometheus.TimeSeriesB\x04\xc8\xde\x1f\x00\x12\x32\n\x08metadata\x18\x03 \x03(\x0b\x32\x1a.prometheus.MetricMetadataB\x04\xc8\xde\x1f\x00J\x04\x08\x02\x10\x03\"\xae\x01\n\x0bReadRequest\x12\"\n\x07queries\x18\x01 \x03(\x0b\x32\x11.prometheus.Query\x12\x45\n\x17\x61\x63\x63\x65pted_response_types\x18\x02 \x03(\x0e\x32$.prometheus.ReadRequest.ResponseType\"4\n\x0cResponseType\x12\x0b\n\x07SAMPLES\x10\x00\x12\x17\n\x13STREAMED_XOR_CHUNKS\x10\x01\"8\n\x0cReadResponse\x12(\n\x07results\x18\x01 \x03(\x0b\x32\x17.prometheus.QueryResult\"\x8f\x01\n\x05Query\x12\x1a\n\x12start_timestamp_ms\x18\x01 \x01(\x03\x12\x18\n\x10\x65nd_timestamp_ms\x18\x02 \x01(\x03\x12*\n\x08matchers\x18\x03 \x03(\x0b\x32\x18.prometheus.LabelMatcher\x12$\n\x05hints\x18\x04 \x01(\x0b\x32\x15.prometheus.ReadHints\"9\n\x0bQueryResult\x12*\n\ntimeseries\x18\x01 \x03(\x0b\x32\x16.prometheus.TimeSeries\"]\n\x13\x43hunkedReadResponse\x12\x31\n\x0e\x63hunked_series\x18\x01 \x03(\x0b\x32\x19.prometheus.ChunkedSeries\x12\x13\n\x0bquery_index\x18\x02 \x01(\x03\x42\x08Z\x06prompbb\x06proto3')
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_builder.BuildTopDescriptorsAndMessages(DESCRIPTOR, 'opentelemetry.exporter.prometheus_remote_write.gen.remote_pb2', _globals)
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_globals['_WRITEREQUEST'].fields_by_name['metadata']._loaded_options = None
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_globals['_QUERYRESULT']._serialized_start=721
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_globals['_CHUNKEDREADRESPONSE']._serialized_start=780
_globals['_CHUNKEDREADRESPONSE']._serialized_end=873
# @@protoc_insertion_point(module_scope)
types_pb2.py 0000664 0000000 0000000 00000013634 15270700723 0050266 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/exporter/opentelemetry-exporter-prometheus-remote-write/src/opentelemetry/exporter/prometheus_remote_write/gen # -*- coding: utf-8 -*-
# Generated by the protocol buffer compiler. DO NOT EDIT!
# source: opentelemetry/exporter/prometheus_remote_write/gen/types.proto
# Protobuf Python Version: 5.26.0
"""Generated protocol buffer code."""
from google.protobuf import descriptor as _descriptor
from google.protobuf import descriptor_pool as _descriptor_pool
from google.protobuf import symbol_database as _symbol_database
from google.protobuf.internal import builder as _builder
# @@protoc_insertion_point(imports)
_sym_db = _symbol_database.Default()
from opentelemetry.exporter.prometheus_remote_write.gen.gogoproto import gogo_pb2 as opentelemetry_dot_exporter_dot_prometheus__remote__write_dot_gen_dot_gogoproto_dot_gogo__pb2
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_builder.BuildMessageAndEnumDescriptors(DESCRIPTOR, _globals)
_builder.BuildTopDescriptorsAndMessages(DESCRIPTOR, 'opentelemetry.exporter.prometheus_remote_write.gen.types_pb2', _globals)
if not _descriptor._USE_C_DESCRIPTORS:
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_globals['_LABELS'].fields_by_name['labels']._loaded_options = None
_globals['_LABELS'].fields_by_name['labels']._serialized_options = b'\310\336\037\000'
_globals['_CHUNKEDSERIES'].fields_by_name['labels']._loaded_options = None
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_globals['_CHUNKEDSERIES'].fields_by_name['chunks']._loaded_options = None
_globals['_CHUNKEDSERIES'].fields_by_name['chunks']._serialized_options = b'\310\336\037\000'
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_globals['_LABEL']._serialized_end=715
_globals['_LABELS']._serialized_start=717
_globals['_LABELS']._serialized_end=766
_globals['_LABELMATCHER']._serialized_start=769
_globals['_LABELMATCHER']._serialized_end=899
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_globals['_LABELMATCHER_TYPE']._serialized_end=899
_globals['_READHINTS']._serialized_start=901
_globals['_READHINTS']._serialized_end=1025
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_globals['_CHUNK']._serialized_end=1167
_globals['_CHUNK_ENCODING']._serialized_start=1135
_globals['_CHUNK_ENCODING']._serialized_end=1167
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_globals['_CHUNKEDSERIES']._serialized_end=1266
# @@protoc_insertion_point(module_scope)
version.py 0000664 0000000 0000000 00000000144 15270700723 0047263 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/exporter/opentelemetry-exporter-prometheus-remote-write/src/opentelemetry/exporter/prometheus_remote_write # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
__version__ = "0.66b2"
test-requirements.txt 0000664 0000000 0000000 00000000572 15270700723 0037157 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/exporter/opentelemetry-exporter-prometheus-remote-write asgiref==3.8.1
certifi==2024.7.4
charset-normalizer==3.3.2
cramjam==2.11.0
Deprecated==1.2.14
idna==3.7
iniconfig==2.0.0
packaging==24.0
pluggy==1.6.0
protobuf==6.33.5
py-cpuinfo==9.0.0
pytest==7.4.4
python-snappy==0.7.1
requests==2.33.1
tomli==2.0.1
typing_extensions==4.12.2
urllib3==2.7.0
wrapt==1.16.0
zipp==3.19.2
-e exporter/opentelemetry-exporter-prometheus-remote-write
opentelemetry-python-contrib-0.66b2/exporter/opentelemetry-exporter-prometheus-remote-write/tests/ 0000775 0000000 0000000 00000000000 15270700723 0034133 5 ustar 00root root 0000000 0000000 __init__.py 0000664 0000000 0000000 00000000114 15270700723 0036161 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/exporter/opentelemetry-exporter-prometheus-remote-write/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
conftest.py 0000664 0000000 0000000 00000003053 15270700723 0036254 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/exporter/opentelemetry-exporter-prometheus-remote-write/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
import random
import pytest
import opentelemetry.test.metrictestutil as metric_util
# pylint: disable=no-name-in-module
from opentelemetry.exporter.prometheus_remote_write import (
PrometheusRemoteWriteMetricsExporter,
)
from opentelemetry.sdk.metrics.export import (
AggregationTemporality,
Histogram,
HistogramDataPoint,
Metric,
)
@pytest.fixture
def prom_rw():
return PrometheusRemoteWriteMetricsExporter("http://victoria:8428/api/v1/write")
@pytest.fixture
def metric(request):
if hasattr(request, "param"):
type_ = request.param
else:
type_ = random.choice(["gauge", "sum"])
if type_ == "gauge":
return metric_util._generate_gauge("test.gauge", random.randint(0, 100))
if type_ == "sum":
return metric_util._generate_sum("test.sum", random.randint(0, 9_999_999_999))
if type_ == "histogram":
return _generate_histogram("test_histogram")
raise ValueError(f"Unsupported metric type '{type_}'.")
def _generate_histogram(name):
dp = HistogramDataPoint(
attributes={"foo": "bar", "baz": 42},
start_time_unix_nano=1641946016139533244,
time_unix_nano=1641946016139533244,
count=5,
sum=420,
bucket_counts=[1, 4],
explicit_bounds=[10.0],
min=8,
max=80,
)
data = Histogram(
[dp],
AggregationTemporality.CUMULATIVE,
)
return Metric(
name,
"foo",
"tu",
data=data,
)
test_prometheus_remote_write_exporter.py 0000664 0000000 0000000 00000025661 15270700723 0044407 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/exporter/opentelemetry-exporter-prometheus-remote-write/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
import unittest
from unittest.mock import patch
import pytest
# pylint: disable=no-name-in-module
from opentelemetry.exporter.prometheus_remote_write import (
PrometheusRemoteWriteMetricsExporter,
)
from opentelemetry.exporter.prometheus_remote_write.gen.types_pb2 import ( # pylint: disable=E0611
Label,
Sample,
TimeSeries,
)
from opentelemetry.sdk.metrics.export import (
Histogram,
HistogramDataPoint,
MetricExportResult,
MetricsData,
NumberDataPoint,
ResourceMetrics,
ScopeMetrics,
)
from opentelemetry.sdk.resources import Resource
from opentelemetry.sdk.util.instrumentation import InstrumentationScope
@pytest.mark.parametrize(
"name,result",
[
("abc.124", "abc_124"),
(":abc", ":abc"),
("abc.name.hi", "abc_name_hi"),
("service.name...", "service_name___"),
("4hellowor:ld5∂©∑", "_hellowor:ld5___"),
],
)
def test_regex(name, result, prom_rw):
assert prom_rw._sanitize_string(name, "name") == result
def test_regex_invalid(prom_rw):
with pytest.raises(TypeError):
prom_rw("foo_bar", "A random type")
def test_parse_data_point(prom_rw):
attrs = {"Foo": "Bar", "Baz": 42}
timestamp = 1641946016139533244
value = 242.42
dp = NumberDataPoint(attrs, 0, timestamp, value)
name = "abc.123_42"
labels, sample = prom_rw._parse_data_point(dp, name)
name = "abc_123_42"
assert labels == (("Foo", "Bar"), ("Baz", 42), ("__name__", name))
assert sample == (value, timestamp // 1_000_000)
def test_parse_histogram_dp(prom_rw):
attrs = {"foo": "bar", "baz": 42}
timestamp = 1641946016139533244
bounds = [10.0, 20.0]
dp = HistogramDataPoint(
attributes=attrs,
start_time_unix_nano=1641946016139533244,
time_unix_nano=timestamp,
count=9,
sum=180,
bucket_counts=[1, 4, 4],
explicit_bounds=bounds,
min=8,
max=80,
)
name = "foo_histogram"
label_sample_pairs = prom_rw._parse_histogram_data_point(dp, name)
timestamp = timestamp // 1_000_000
bounds.append("+Inf")
for pos, bound in enumerate(bounds):
# We have to attributes, we kinda assume the bucket label is last...
assert ("le", str(bound)) == label_sample_pairs[pos][0][-1]
# Check and make sure we are putting the bucket counts in there
assert (dp.bucket_counts[pos], timestamp) == label_sample_pairs[pos][1]
# Last two are the sum & total count
assert ("__name__", f"{name}_sum") in label_sample_pairs[-2][0]
assert (dp.sum, timestamp) == label_sample_pairs[-2][1]
assert ("__name__", f"{name}_count") in label_sample_pairs[-1][0]
assert (dp.count, timestamp) == label_sample_pairs[-1][1]
@pytest.mark.parametrize(
"metric",
[
"gauge",
"sum",
"histogram",
],
indirect=["metric"],
)
def test_parse_metric(metric, prom_rw):
"""
Ensures output from parse_metrics are TimeSeries with expected data/size
"""
attributes = {
"service_name": "foo",
"bool_value": True,
}
assert len(metric.data.data_points) == 1, "We can only support a single datapoint in tests"
series = prom_rw._parse_metric(metric, tuple(attributes.items()))
timestamp = metric.data.data_points[0].time_unix_nano // 1_000_000
for single_series in series:
labels = str(single_series.labels)
# Its a bit easier to validate these stringified where we dont have to
# worry about ordering and protobuf TimeSeries object structure
# This doesn't guarantee the labels aren't mixed up, but our other
# test cases already do.
assert "__name__" in labels
assert prom_rw._sanitize_string(metric.name, "name") in labels
combined_attrs = list(attributes.items()) + list(metric.data.data_points[0].attributes.items())
for name, value in combined_attrs:
assert prom_rw._sanitize_string(name, "label") in labels
assert str(value) in labels
if isinstance(metric.data, Histogram):
values = [
metric.data.data_points[0].count,
metric.data.data_points[0].sum,
metric.data.data_points[0].bucket_counts[0],
metric.data.data_points[0].bucket_counts[1],
]
else:
values = [
metric.data.data_points[0].value,
]
for sample in single_series.samples:
assert sample.timestamp == timestamp
assert sample.value in values
def test_convert_to_timeseries(prom_rw):
resource_labels = (("service_name", "foo"), ("bool_value", True))
sample_sets = {
(("foo", "bar"), ("baz", 42), ("__name__", "test_histogram_tu")): [(1, 1641946016139)],
(("baz", "42"), ("foo", "bar")): [(4, 1641946016139)],
}
timeseries = prom_rw._convert_to_timeseries(sample_sets, resource_labels)
assert timeseries == [
TimeSeries(
labels=[
Label(name="__name__", value="test_histogram_tu"),
Label(name="baz", value="42"),
Label(name="bool_value", value="True"),
Label(name="foo", value="bar"),
Label(name="service_name", value="foo"),
],
samples=[Sample(value=1, timestamp=1641946016139)],
),
TimeSeries(
labels=[
Label(name="baz", value="42"),
Label(name="bool_value", value="True"),
Label(name="foo", value="bar"),
Label(name="service_name", value="foo"),
],
samples=[Sample(value=4, timestamp=1641946016139)],
),
]
class TestValidation(unittest.TestCase):
# Test cases to ensure exporter parameter validation works as intended
def test_valid_standard_param(self):
exporter = PrometheusRemoteWriteMetricsExporter(
endpoint="/prom/test_endpoint",
)
self.assertEqual(exporter.endpoint, "/prom/test_endpoint")
def test_valid_basic_auth_param(self):
exporter = PrometheusRemoteWriteMetricsExporter(
endpoint="/prom/test_endpoint",
basic_auth={
"username": "test_username",
"password": "test_password",
},
)
self.assertEqual(exporter.basic_auth["username"], "test_username")
self.assertEqual(exporter.basic_auth["password"], "test_password")
def test_invalid_no_endpoint_param(self):
with self.assertRaises(ValueError):
PrometheusRemoteWriteMetricsExporter("")
def test_invalid_no_username_param(self):
with self.assertRaises(ValueError):
PrometheusRemoteWriteMetricsExporter(
endpoint="/prom/test_endpoint",
basic_auth={"password": "test_password"},
)
def test_invalid_no_password_param(self):
with self.assertRaises(ValueError):
PrometheusRemoteWriteMetricsExporter(
endpoint="/prom/test_endpoint",
basic_auth={"username": "test_username"},
)
def test_invalid_conflicting_passwords_param(self):
with self.assertRaises(ValueError):
PrometheusRemoteWriteMetricsExporter(
endpoint="/prom/test_endpoint",
basic_auth={
"username": "test_username",
"password": "test_password",
"password_file": "test_file",
},
)
def test_invalid_timeout_param(self):
with self.assertRaises(ValueError):
PrometheusRemoteWriteMetricsExporter(endpoint="/prom/test_endpoint", timeout=0)
def test_valid_tls_config_param(self):
tls_config = {
"ca_file": "test_ca_file",
"cert_file": "test_cert_file",
"key_file": "test_key_file",
"insecure_skip_verify": True,
}
exporter = PrometheusRemoteWriteMetricsExporter(endpoint="/prom/test_endpoint", tls_config=tls_config)
self.assertEqual(exporter.tls_config["ca_file"], tls_config["ca_file"])
self.assertEqual(exporter.tls_config["cert_file"], tls_config["cert_file"])
self.assertEqual(exporter.tls_config["key_file"], tls_config["key_file"])
self.assertEqual(
exporter.tls_config["insecure_skip_verify"],
tls_config["insecure_skip_verify"],
)
# if cert_file is provided, then key_file must also be provided
def test_invalid_tls_config_cert_only_param(self):
tls_config = {"cert_file": "value"}
with self.assertRaises(ValueError):
PrometheusRemoteWriteMetricsExporter(endpoint="/prom/test_endpoint", tls_config=tls_config)
# if cert_file is provided, then key_file must also be provided
def test_invalid_tls_config_key_only_param(self):
tls_config = {"cert_file": "value"}
with self.assertRaises(ValueError):
PrometheusRemoteWriteMetricsExporter(endpoint="/prom/test_endpoint", tls_config=tls_config)
# Ensures export is successful with valid export_records and config
@patch("requests.post")
def test_valid_export(mock_post, prom_rw, metric):
mock_post.return_value.configure_mock(status_code=200)
# Assumed a "None" for Scope or Resource aren't valid, so build them here
scope = ScopeMetrics(InstrumentationScope(name="prom-rw-test"), [metric], None)
resource = ResourceMetrics(Resource({"service.name": "foo"}), [scope], None)
record = MetricsData([resource])
result = prom_rw.export(record)
assert result == MetricExportResult.SUCCESS
assert mock_post.call_count == 1
result = prom_rw.export([])
assert result == MetricExportResult.SUCCESS
def test_invalid_export(prom_rw):
record = MetricsData([])
result = prom_rw.export(record)
assert result == MetricExportResult.FAILURE
@patch("requests.post")
def test_valid_send_message(mock_post, prom_rw):
mock_post.return_value.configure_mock(ok=True)
result = prom_rw._send_message(b"", {})
assert mock_post.call_count == 1
assert result == MetricExportResult.SUCCESS
def test_invalid_send_message(prom_rw):
result = prom_rw._send_message(b"", {})
assert result == MetricExportResult.FAILURE
# Verifies that build_message calls snappy.compress and returns SerializedString
@patch("snappy.compress", return_value=b"")
def test_build_message(mock_compress, prom_rw):
message = prom_rw._build_message([TimeSeries()])
assert mock_compress.call_count == 1
assert isinstance(message, bytes)
# Ensure correct headers are added when valid config is provided
def test_build_headers(prom_rw):
prom_rw.headers = {"Custom Header": "test_header"}
headers = prom_rw._build_headers()
assert headers["Content-Encoding"] == "snappy"
assert headers["Content-Type"] == "application/x-protobuf"
assert headers["X-Prometheus-Remote-Write-Version"] == "0.1.0"
assert headers["Custom Header"] == "test_header"
opentelemetry-python-contrib-0.66b2/exporter/opentelemetry-exporter-richconsole/ 0000775 0000000 0000000 00000000000 15270700723 0030465 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/exporter/opentelemetry-exporter-richconsole/README.rst 0000664 0000000 0000000 00000001423 15270700723 0032154 0 ustar 00root root 0000000 0000000 OpenTelemetry Rich Console Exporter
===================================
|pypi|
.. |pypi| image:: https://badge.fury.io/py/opentelemetry-exporter-richconsole.svg
:target: https://pypi.org/project/opentelemetry-exporter-richconsole/
This library is a console exporter using the Rich tree view. When used with a batch span processor, the rich console exporter will show the trace as a
tree and all related spans as children within the tree, including properties.
Installation
------------
::
pip install opentelemetry-exporter-richconsole
.. _Rich: https://rich.readthedocs.io/
.. _OpenTelemetry: https://github.com/open-telemetry/opentelemetry-python/
References
----------
* `Rich `_
* `OpenTelemetry Project `_
opentelemetry-python-contrib-0.66b2/exporter/opentelemetry-exporter-richconsole/pyproject.toml 0000664 0000000 0000000 00000002617 15270700723 0033407 0 ustar 00root root 0000000 0000000 [build-system]
requires = ["hatchling"]
build-backend = "hatchling.build"
[project]
name = "opentelemetry-exporter-richconsole"
dynamic = ["version"]
description = "Rich Console Exporter for OpenTelemetry"
readme = "README.rst"
license = "Apache-2.0"
requires-python = ">=3.10"
authors = [
{ name = "OpenTelemetry Authors", email = "cncf-opentelemetry-contributors@lists.cncf.io" },
]
classifiers = [
"Development Status :: 4 - Beta",
"Intended Audience :: Developers",
"License :: OSI Approved :: Apache Software License",
"Programming Language :: Python",
"Programming Language :: Python :: 3",
"Programming Language :: Python :: 3.10",
"Programming Language :: Python :: 3.11",
"Programming Language :: Python :: 3.12",
"Programming Language :: Python :: 3.13",
"Programming Language :: Python :: 3.14",
]
dependencies = [
"opentelemetry-api ~= 1.12",
"opentelemetry-sdk ~= 1.12",
"opentelemetry-semantic-conventions == 0.66b2",
"rich>=10.0.0",
]
[project.urls]
Homepage = "https://github.com/open-telemetry/opentelemetry-python-contrib/tree/main/exporter/opentelemetry-exporter-richconsole"
Repository = "https://github.com/open-telemetry/opentelemetry-python-contrib"
[tool.hatch.version]
path = "src/opentelemetry/exporter/richconsole/version.py"
[tool.hatch.build.targets.sdist]
include = [
"/src",
"/tests",
]
[tool.hatch.build.targets.wheel]
packages = ["src/opentelemetry"]
opentelemetry-python-contrib-0.66b2/exporter/opentelemetry-exporter-richconsole/src/ 0000775 0000000 0000000 00000000000 15270700723 0031254 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/exporter/opentelemetry-exporter-richconsole/src/opentelemetry/ 0000775 0000000 0000000 00000000000 15270700723 0034150 5 ustar 00root root 0000000 0000000 exporter/ 0000775 0000000 0000000 00000000000 15270700723 0035741 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/exporter/opentelemetry-exporter-richconsole/src/opentelemetry richconsole/ 0000775 0000000 0000000 00000000000 15270700723 0040251 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/exporter/opentelemetry-exporter-richconsole/src/opentelemetry/exporter __init__.py 0000664 0000000 0000000 00000014115 15270700723 0042364 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/exporter/opentelemetry-exporter-richconsole/src/opentelemetry/exporter/richconsole # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
"""
The **OpenTelemetry Rich Console Exporter** provides a span exporter from a batch span processor
to print `OpenTelemetry`_ traces using `Rich`_.
Installation
------------
::
pip install opentelemetry-exporter-richconsole
Usage
-----
The Rich Console Exporter is a console exporter that prints a tree view onto stdout of the traces
with the related spans and properties as children of that tree. For the tree view, the Rich
Console Exporter should be used with a BatchSpanProcessor. If used within a SimpleSpanProcessor,
all spans will be printed in a list.
.. code:: python
from opentelemetry import trace
from opentelemetry.sdk.trace.export import BatchSpanProcessor
from opentelemetry.exporter.richconsole import RichConsoleSpanExporter
from opentelemetry.sdk.trace import TracerProvider
trace.set_tracer_provider(TracerProvider())
tracer = trace.get_tracer(__name__)
tracer.add_span_processor(BatchSpanProcessor(RichConsoleSpanExporter()))
API
---
.. _Rich: https://rich.readthedocs.io/
.. _OpenTelemetry: https://github.com/open-telemetry/opentelemetry-python/
"""
# pylint: disable=import-error
import datetime
import typing
from rich.console import Console
from rich.syntax import Syntax
from rich.text import Text
from rich.tree import Tree
import opentelemetry.trace
from opentelemetry.sdk.trace import ReadableSpan
from opentelemetry.sdk.trace.export import SpanExporter, SpanExportResult
from opentelemetry.semconv._incubating.attributes.db_attributes import (
DB_STATEMENT,
)
def _ns_to_time(nanoseconds):
ts = datetime.datetime.fromtimestamp(nanoseconds / 1e9, datetime.timezone.utc)
return ts.strftime("%H:%M:%S.%f")
def _child_to_tree(child: Tree, span: ReadableSpan, *, suppress_resource: bool):
child.add(Text.from_markup(f"[bold cyan]Kind :[/bold cyan] {span.kind.name}"))
_add_status(child, span)
_child_add_optional_attributes(child, span, suppress_resource=suppress_resource)
def _add_status(child: Tree, span: ReadableSpan):
if not span.status.is_unset:
if not span.status.is_ok:
child.add(Text.from_markup(f"[bold cyan]Status :[/bold cyan] [red]{span.status.status_code}[/red]"))
else:
child.add(Text.from_markup(f"[bold cyan]Status :[/bold cyan] {span.status.status_code}"))
if span.status.description:
child.add(Text.from_markup(f"[bold cyan]Description :[/bold cyan] {span.status.description}"))
def _child_add_optional_attributes(child: Tree, span: ReadableSpan, *, suppress_resource: bool):
if span.events:
events = child.add(label=Text.from_markup("[bold cyan]Events :[/bold cyan] "))
for event in span.events:
event_node = events.add(Text(event.name))
for key, val in event.attributes.items():
event_node.add(Text.from_markup(f"[bold cyan]{key} :[/bold cyan] {val}"))
if span.attributes:
attributes = child.add(label=Text.from_markup("[bold cyan]Attributes :[/bold cyan] "))
for attribute in span.attributes:
if attribute == DB_STATEMENT:
attributes.add(Text.from_markup(f"[bold cyan]{attribute} :[/bold cyan] "))
attributes.add(Syntax(span.attributes[attribute], "sql"))
else:
attributes.add(Text.from_markup(f"[bold cyan]{attribute} :[/bold cyan] {span.attributes[attribute]}"))
if span.resource and not suppress_resource:
resources = child.add(label=Text.from_markup("[bold cyan]Resources :[/bold cyan] "))
for resource in span.resource.attributes:
resources.add(Text.from_markup(f"[bold cyan]{resource} :[/bold cyan] {span.resource.attributes[resource]}"))
class RichConsoleSpanExporter(SpanExporter):
"""Implementation of :class:`SpanExporter` that prints spans to the
console.
Should be used within a BatchSpanProcessor
"""
def __init__(
self,
service_name: str | None = None,
suppress_resource: bool = False,
):
self.service_name = service_name
self.suppress_resource = suppress_resource
self.console = Console()
def export(self, spans: typing.Sequence[ReadableSpan]) -> SpanExportResult:
if not spans:
return SpanExportResult.SUCCESS
for tree in self.spans_to_tree(spans, suppress_resource=self.suppress_resource).values():
self.console.print(tree)
return SpanExportResult.SUCCESS
@staticmethod
def spans_to_tree(
spans: typing.Sequence[ReadableSpan],
*,
suppress_resource: bool = False,
) -> dict[str, Tree]:
trees = {}
parents = {}
spans = list(spans)
span_ids = {s.context.span_id for s in spans}
while spans:
for span in spans:
if not span.parent or span.parent.span_id not in span_ids:
trace_id = opentelemetry.trace.format_trace_id(span.context.trace_id)
tree = trees.setdefault(trace_id, Tree(label=f"Trace {trace_id}"))
child = tree.add(
label=Text.from_markup(
f"[blue][{_ns_to_time(span.start_time)}][/blue] [bold]{span.name}[/bold], span {opentelemetry.trace.format_span_id(span.context.span_id)}"
)
)
parents[span.context.span_id] = child
_child_to_tree(child, span, suppress_resource=suppress_resource)
spans.remove(span)
elif span.parent and span.parent.span_id in parents:
child = parents[span.parent.span_id].add(
label=Text.from_markup(
f"[blue][{_ns_to_time(span.start_time)}][/blue] [bold]{span.name}[/bold], span {opentelemetry.trace.format_span_id(span.context.span_id)}"
)
)
parents[span.context.span_id] = child
_child_to_tree(child, span, suppress_resource=suppress_resource)
spans.remove(span)
return trees
version.py 0000664 0000000 0000000 00000000144 15270700723 0042307 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/exporter/opentelemetry-exporter-richconsole/src/opentelemetry/exporter/richconsole # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
__version__ = "0.66b2"
test-requirements.txt 0000664 0000000 0000000 00000000506 15270700723 0034650 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/exporter/opentelemetry-exporter-richconsole asgiref==3.8.1
Deprecated==1.2.14
flaky==3.7.0
iniconfig==2.0.0
markdown-it-py==3.0.0
mdurl==0.1.2
packaging==24.0
pluggy==1.6.0
py-cpuinfo==9.0.0
Pygments==2.17.2
pytest==7.4.4
pytest-timeout==2.3.1
rich==13.7.1
tomli==2.0.1
typing_extensions==4.12.2
wrapt==1.16.0
zipp==3.19.2
-e exporter/opentelemetry-exporter-richconsole
opentelemetry-python-contrib-0.66b2/exporter/opentelemetry-exporter-richconsole/tests/ 0000775 0000000 0000000 00000000000 15270700723 0031627 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/exporter/opentelemetry-exporter-richconsole/tests/__init__.py 0000664 0000000 0000000 00000000000 15270700723 0033726 0 ustar 00root root 0000000 0000000 test_rich_exporter.py 0000664 0000000 0000000 00000007261 15270700723 0036044 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/exporter/opentelemetry-exporter-richconsole/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
import pytest
from rich.text import Text
from rich.tree import Tree
import opentelemetry.trace
from opentelemetry.exporter.richconsole import RichConsoleSpanExporter
from opentelemetry.sdk import trace
from opentelemetry.sdk.resources import Resource
from opentelemetry.sdk.trace.export import BatchSpanProcessor
@pytest.fixture(name="span_processor")
def fixture_span_processor():
exporter = RichConsoleSpanExporter()
span_processor = BatchSpanProcessor(exporter)
yield span_processor
span_processor.shutdown()
@pytest.fixture(name="tracer_provider")
def fixture_tracer_provider(span_processor):
tracer_provider = trace.TracerProvider()
tracer_provider.add_span_processor(span_processor)
yield tracer_provider
def test_span_exporter(tracer_provider, span_processor, capsys):
tracer = tracer_provider.get_tracer(__name__)
span = tracer.start_span("test_span")
span.set_attribute("key", "V4LuE")
span.end()
span_processor.force_flush()
captured = capsys.readouterr()
assert "V4LuE" in captured.out
def walk_tree(root: Tree) -> int:
# counts the amount of spans in a tree that contains a span
return sum(walk_tree(child) for child in root.children) + int("span" in root.label)
def test_multiple_traces(tracer_provider):
exporter = RichConsoleSpanExporter()
tracer = tracer_provider.get_tracer(__name__)
with tracer.start_as_current_span("parent_1") as parent_1:
with tracer.start_as_current_span("child_1") as child_1:
pass
with tracer.start_as_current_span("parent_2") as parent_2:
pass
trees = exporter.spans_to_tree((parent_2, parent_1, child_1))
# asserts that we have all traces
assert len(trees) == 2
traceid_1 = opentelemetry.trace.format_trace_id(parent_1.context.trace_id)
assert traceid_1 in trees
assert opentelemetry.trace.format_trace_id(parent_2.context.trace_id) in trees
# asserts that we have exactly the number of spans we exported
assert sum(walk_tree(tree) for tree in trees.values()) == 3
# assert that the relationship is correct
assert parent_1.name in trees[traceid_1].children[0].label
assert any(child_1.name in child.label for child in trees[traceid_1].children[0].children)
assert not any(parent_1.name in child.label for child in trees[traceid_1].children[0].children)
assert not any(parent_2.name in child.label for child in trees[traceid_1].children[0].children)
@pytest.mark.timeout(30)
def test_no_deadlock(tracer_provider):
# non-regression test for https://github.com/open-telemetry/opentelemetry-python-contrib/issues/3254
tracer = tracer_provider.get_tracer(__name__)
with tracer.start_as_current_span("parent"):
with tracer.start_as_current_span("child") as child:
pass
RichConsoleSpanExporter.spans_to_tree((child,))
def test_suppress_resource(span_processor):
attributes = {"resource.key": "resource.value"}
resource = Resource(attributes)
tracer_provider = trace.TracerProvider(resource=resource)
tracer_provider.add_span_processor(span_processor)
tracer = tracer_provider.get_tracer(__name__)
with tracer.start_as_current_span("parent") as parent:
with tracer.start_as_current_span("child") as child:
pass
trees = RichConsoleSpanExporter.spans_to_tree((parent, child), suppress_resource=True)
assert len(trees) == 1
nodes = [next(t for t in trees.values())]
for node in nodes:
label = node.label
if isinstance(label, Text):
label = label.plain
assert "resource" not in label.lower()
nodes.extend(node.children)
opentelemetry-python-contrib-0.66b2/gen-requirements.txt 0000664 0000000 0000000 00000000157 15270700723 0023603 0 ustar 00root root 0000000 0000000 -c dev-requirements.txt
astor==0.8.1
jinja2==3.1.6
markupsafe==2.0.1
ruff==0.16.1
requests
tomli
tomli_w
hatch
opentelemetry-python-contrib-0.66b2/instrumentation-genai/ 0000775 0000000 0000000 00000000000 15270700723 0024071 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/AGENTS.md 0000664 0000000 0000000 00000001260 15270700723 0025373 0 ustar 00root root 0000000 0000000 # GenAI Instrumentation — Agent and Contributor Guidelines
**GenAI instrumentations are no longer developed in this repository.** They live in
[opentelemetry-python-genai](https://github.com/open-telemetry/opentelemetry-python-genai),
which is where new instrumentations, features, and bug fixes go.
The packages still present under this directory are deprecated, receive security patches only,
and will be removed from this repository in the future.
Do not add instrumentations here, and do not fix bugs or add features to the ones that remain.
Send any such change to the `opentelemetry-python-genai` repo instead. Security patches are the
only changes accepted in this directory.
opentelemetry-python-contrib-0.66b2/instrumentation-genai/CLAUDE.md 0000777 0000000 0000000 00000000000 15270700723 0026646 2AGENTS.md ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/README.md 0000664 0000000 0000000 00000004327 15270700723 0025356 0 ustar 00root root 0000000 0000000
> [!WARNING]
> GenAI instrumentations have been moved to the
> [opentelemetry-python-genai](https://github.com/open-telemetry/opentelemetry-python-genai)
> repository, which is now their home for new development and releases. The copies that
> still live in this directory only receive security patches and will be removed from
> here in the future.
| Instrumentation | Supported Packages | Metrics support | Semconv status |
| --------------- | ------------------ | --------------- | -------------- |
| [opentelemetry-instrumentation-genai-anthropic](https://github.com/open-telemetry/opentelemetry-python-genai/tree/main/instrumentation/opentelemetry-instrumentation-genai-anthropic) | anthropic >= 0.16.0 | Yes | development
| [opentelemetry-instrumentation-genai-claude-agent-sdk](https://github.com/open-telemetry/opentelemetry-python-genai/tree/main/instrumentation/opentelemetry-instrumentation-genai-claude-agent-sdk) | claude-agent-sdk >= 0.1.14 | No | development
| [opentelemetry-instrumentation-google-genai](https://github.com/open-telemetry/opentelemetry-python-genai/tree/main/instrumentation/opentelemetry-instrumentation-google-genai) | google-genai >= 1.32.0 | No | development
| [opentelemetry-instrumentation-genai-langchain](https://github.com/open-telemetry/opentelemetry-python-genai/tree/main/instrumentation/opentelemetry-instrumentation-genai-langchain) | langchain >= 0.3.21 | Yes | development
| [opentelemetry-instrumentation-genai-openai-agents](https://github.com/open-telemetry/opentelemetry-python-genai/tree/main/instrumentation/opentelemetry-instrumentation-genai-openai-agents) | openai-agents >= 0.3.3 | No | development
| [opentelemetry-instrumentation-genai-openai](https://github.com/open-telemetry/opentelemetry-python-genai/tree/main/instrumentation/opentelemetry-instrumentation-genai-openai) | openai >= 1.26.0 | Yes | development
| [opentelemetry-instrumentation-vertexai](./opentelemetry-instrumentation-vertexai) | google-cloud-aiplatform >= 1.64 | No | development
| [opentelemetry-instrumentation-genai-weaviate-client](https://github.com/open-telemetry/opentelemetry-python-genai/tree/main/instrumentation/opentelemetry-instrumentation-genai-weaviate-client) | weaviate-client >= 3.0.0,<5.0.0 | No | development opentelemetry-instrumentation-openai-agents-v2/ 0000775 0000000 0000000 00000000000 15270700723 0035224 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai .gitignore 0000664 0000000 0000000 00000000116 15270700723 0037212 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-openai-agents-v2 examples/.env
examples/openai_agents_multi_agent_travel/.env
examples/**/.env
CHANGELOG.md 0000664 0000000 0000000 00000003041 15270700723 0037033 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-openai-agents-v2 # Changelog
All notable changes to this project will be documented in this file.
The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),
and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
## Unreleased
- Deprecate `opentelemetry-instrumentation-openai-agents-v2`. Use the
`opentelemetry-instrumentation-genai-openai-agents` package instead. This
package now only receives security patches.
- Align AgentSpanData test stubs and span processor with real OpenAI Agents SDK;
remove non-existent `operation`, `description`, `agent_id`, and `model` fields.
([#4229](https://github.com/open-telemetry/opentelemetry-python-contrib/pull/4229))
- Document official package metadata and README for the OpenAI Agents instrumentation.
([#3859](https://github.com/open-telemetry/opentelemetry-python-contrib/pull/3859))
- Populate instructions and tool definitions from Response obj.
([#4196](https://github.com/open-telemetry/opentelemetry-python-contrib/pull/4196))
## Version 0.1.0 (2025-10-15)
- Initial barebones package skeleton: minimal instrumentor stub, version module,
and packaging metadata/entry point.
([#3805](https://github.com/open-telemetry/opentelemetry-python-contrib/pull/3805))
- Implement OpenAI Agents span processing aligned with GenAI semantic conventions.
([#3817](https://github.com/open-telemetry/opentelemetry-python-contrib/pull/3817))
- Input and output according to GenAI spec.
([#3824](https://github.com/open-telemetry/opentelemetry-python-contrib/pull/3824))
LICENSE 0000664 0000000 0000000 00000026155 15270700723 0036242 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-openai-agents-v2 Apache License
Version 2.0, January 2004
http://www.apache.org/licenses/
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README.rst 0000664 0000000 0000000 00000011616 15270700723 0036720 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-openai-agents-v2 OpenTelemetry OpenAI Agents Instrumentation
===========================================
.. warning::
**This package is deprecated.** Use the
`opentelemetry-instrumentation-genai-openai-agents `_
package instead. ``opentelemetry-instrumentation-openai-agents-v2`` now only
receives security patches. Please
migrate by replacing it with ``opentelemetry-instrumentation-genai-openai-agents``:
.. code-block:: console
pip uninstall opentelemetry-instrumentation-openai-agents-v2
pip install opentelemetry-instrumentation-genai-openai-agents
The replacement package contains **breaking changes** relative to this one.
Review the
`CHANGELOG `_
before upgrading.
|pypi|
.. |pypi| image:: https://badge.fury.io/py/opentelemetry-instrumentation-openai-agents-v2.svg
:target: https://pypi.org/project/opentelemetry-instrumentation-openai-agents-v2/
This library provides the official OpenTelemetry instrumentation for the
`openai-agents SDK `_. It converts
the rich trace data emitted by the Agents runtime
into the GenAI semantic conventions, enriches spans with request/response payload
metadata, and records duration/token usage metrics.
Features
--------
* Generates spans for agents, tools, generations, guardrails, and handoffs using
the OpenTelemetry GenAI semantic conventions.
* Captures prompts, responses, tool arguments, and system instructions when content
capture is enabled.
* Publishes duration and token metrics for every operation.
* Supports environment overrides so you can configure agent metadata or disable
telemetry without code changes.
Installation
------------
If your application is already configured with OpenTelemetry, install the package
and its optional instruments:
.. code-block:: console
pip install opentelemetry-instrumentation-openai-agents-v2
pip install openai-agents
Usage
-----
Instrumentation automatically wires the Agents tracing processor into the SDK.
Configure OpenTelemetry as usual, then call :class:`OpenAIAgentsInstrumentor`.
.. code-block:: python
from agents import Agent, Runner, function_tool
from opentelemetry import trace
from opentelemetry.exporter.otlp.proto.grpc.trace_exporter import OTLPSpanExporter
from opentelemetry.instrumentation.openai_agents import OpenAIAgentsInstrumentor
from opentelemetry.sdk.trace import TracerProvider
from opentelemetry.sdk.trace.export import BatchSpanProcessor
def configure_otel() -> None:
provider = TracerProvider()
provider.add_span_processor(BatchSpanProcessor(OTLPSpanExporter()))
trace.set_tracer_provider(provider)
OpenAIAgentsInstrumentor().instrument(tracer_provider=provider)
@function_tool
def get_weather(city: str) -> str:
return f"The forecast for {city} is sunny with pleasant temperatures."
assistant = Agent(
name="Travel Concierge",
instructions="You are a concise travel concierge.",
tools=[get_weather],
)
result = Runner.run_sync(assistant, "I'm visiting Barcelona this weekend. How should I pack?")
print(result.final_output)
Configuration
-------------
The instrumentor exposes runtime toggles through keyword arguments and environment
variables:
* ``OTEL_INSTRUMENTATION_GENAI_CAPTURE_MESSAGE_CONTENT`` or
``OTEL_INSTRUMENTATION_OPENAI_AGENTS_CAPTURE_CONTENT`` – controls how much
message content is captured. Valid values map to
:class:`opentelemetry.instrumentation.openai_agents.ContentCaptureMode`
(``span_only``, ``event_only``, ``span_and_event``, ``no_content``).
* ``OTEL_INSTRUMENTATION_OPENAI_AGENTS_CAPTURE_METRICS`` – set to ``false`` to
disable duration/token metrics.
* ``OTEL_INSTRUMENTATION_OPENAI_AGENTS_SYSTEM`` – overrides the ``gen_ai.system``
attribute when your deployment is not the default OpenAI platform.
You can also override agent metadata directly when calling
``OpenAIAgentsInstrumentor().instrument(...)`` using ``agent_name``, ``agent_id``,
``agent_description``, ``base_url``, ``server_address``, and ``server_port``.
Examples
--------
The :mod:`examples` directory contains runnable scenarios, including:
* ``examples/manual`` – manual OpenTelemetry configuration for a single agent run.
* ``examples/content-capture`` – demonstrates span and event content capture.
* ``examples/zero-code`` – end-to-end setup using environment configuration only.
References
----------
* `OpenTelemetry Python Contrib `_
* `OpenTelemetry GenAI semantic conventions `_
* `OpenAI Agents SDK `_
examples/ 0000775 0000000 0000000 00000000000 15270700723 0037042 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-openai-agents-v2 content-capture/ 0000775 0000000 0000000 00000000000 15270700723 0042155 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-openai-agents-v2/examples .env.example 0000664 0000000 0000000 00000000522 15270700723 0044377 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-openai-agents-v2/examples/content-capture # Copy to .env and add values before running the sample.
# Required for OpenAI client (only used if you swap in a real OpenAI call)
OPENAI_API_KEY=
# Optional overrides for span attributes / exporters
OTEL_SERVICE_NAME=openai-agents-content-capture-demo
OTEL_EXPORTER_OTLP_ENDPOINT=http://localhost:4317
OTEL_EXPORTER_OTLP_PROTOCOL=grpc
README.md 0000664 0000000 0000000 00000002636 15270700723 0043443 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-openai-agents-v2/examples/content-capture # OpenAI Agents Content Capture Demo
This example exercises the `OpenAIAgentsInstrumentor` with message content
capture enabled, illustrating how prompts, responses, and tool payloads are
recorded on spans and span events.
> The demo uses the local tracing utilities from the `openai-agents`
> package—no outbound API calls are made.
## Prerequisites
1. Activate the repository virtual environment:
```bash
source ../../.venv/bin/activate
```
2. Copy `.env.example` to `.env` and provide any overrides you need (for example,
setting `OTEL_EXPORTER_OTLP_ENDPOINT`).
3. Ensure `openai-agents` is installed in the environment (it is included in
the shared development venv for this repository).
## Run the demo
```bash
python main.py
```
The script will:
- Configure the OpenTelemetry SDK with an OTLP exporter so spans reach your collector.
- Instrument the OpenAI Agents tracing hooks with content capture enabled.
- Simulate an agent invocation that performs a generation and a tool call.
- Print the resulting spans, attributes, and events (including JSON-encoded
prompts and responses) to stdout.
## Customisation tips
- Set `OTEL_SERVICE_NAME` before running to override the default service name.
- Adjust the OTLP exporter configuration (endpoint, protocol) through `.env`.
- Modify the prompts, tool payloads, or add additional spans in `run_workflow`
to explore different content capture scenarios.
main.py 0000664 0000000 0000000 00000007105 15270700723 0043456 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-openai-agents-v2/examples/content-capture # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
"""
Content capture demo for the OpenAI Agents instrumentation.
This script spins up the instrumentation with message capture enabled and
simulates an agent invocation plus a tool call using the tracing helpers from
the ``openai-agents`` package. Spans are exported to the console so you can
inspect captured prompts, responses, and tool payloads without making any
OpenAI API calls.
"""
from __future__ import annotations
import json
import os
from typing import Any
from agents.tracing import agent_span, function_span, generation_span, trace
from dotenv import load_dotenv
from opentelemetry.exporter.otlp.proto.grpc.trace_exporter import (
OTLPSpanExporter,
)
from opentelemetry.instrumentation.openai_agents import (
OpenAIAgentsInstrumentor,
)
from opentelemetry.sdk.resources import Resource
from opentelemetry.sdk.trace import TracerProvider
from opentelemetry.sdk.trace.export import BatchSpanProcessor
load_dotenv() # take environment variables from .env.
def configure_tracing() -> None:
"""Configure a tracer provider that exports spans via OTLP."""
resource = Resource.create(
{"service.name": os.environ.get("OTEL_SERVICE_NAME", "openai-agents-content-capture-demo")}
)
provider = TracerProvider(resource=resource)
provider.add_span_processor(BatchSpanProcessor(OTLPSpanExporter()))
# Instrument with explicit content capture mode to ensure prompts/responses are recorded.
OpenAIAgentsInstrumentor().instrument(
tracer_provider=provider,
capture_message_content="span_and_event",
system="openai",
agent_name="Travel Concierge",
base_url="https://api.openai.com/v1",
)
def dump(title: str, payload: Any) -> None:
"""Pretty-print helper used to show intermediate context."""
print(f"\n=== {title} ===")
print(json.dumps(payload, indent=2))
def run_workflow() -> None:
"""Simulate an agent workflow with a generation and a tool invocation."""
itinerary_prompt = [
{"role": "system", "content": "Plan high level travel itineraries."},
{
"role": "user",
"content": "I'm visiting Paris for 3 days in November.",
},
]
tool_args = {"city": "Paris", "date": "2025-11-12"}
tool_result = {
"forecast": "Mostly sunny, highs 15°C",
"packing_tips": ["light jacket", "comfortable shoes"],
}
with trace("travel-booking-workflow"):
with agent_span(name="travel_planner") as agent:
dump(
"Agent span started",
{"span_id": agent.span_id, "trace_id": agent.trace_id},
)
with generation_span(
input=itinerary_prompt,
output=[
{
"role": "assistant",
"content": ("Day 1 visit the Louvre, Day 2 tour Versailles, Day 3 explore Montmartre."),
}
],
model="gpt-4o-mini",
usage={
"input_tokens": 128,
"output_tokens": 96,
"total_tokens": 224,
},
):
pass
with function_span(
name="fetch_weather",
input=json.dumps(tool_args),
output=tool_result,
):
pass
print("\nWorkflow complete – spans exported to the configured OTLP endpoint.")
def main() -> None:
configure_tracing()
run_workflow()
if __name__ == "__main__":
main()
manual/ 0000775 0000000 0000000 00000000000 15270700723 0040317 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-openai-agents-v2/examples .env.example 0000664 0000000 0000000 00000000311 15270700723 0042535 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-openai-agents-v2/examples/manual # Copy to .env and add real values before running main.py
OPENAI_API_KEY=
OTEL_EXPORTER_OTLP_ENDPOINT=http://localhost:4317
OTEL_EXPORTER_OTLP_PROTOCOL=grpc
OTEL_SERVICE_NAME=openai-agents-manual-demo
README.rst 0000664 0000000 0000000 00000002700 15270700723 0042005 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-openai-agents-v2/examples/manual OpenTelemetry OpenAI Agents Instrumentation Example
===================================================
This example demonstrates how to manually configure the OpenTelemetry SDK
alongside the OpenAI Agents instrumentation.
Running `main.py `_ produces spans for the end-to-end agent run,
including tool invocations and model generations. Spans are exported through
OTLP/gRPC to the endpoint configured in the environment.
Setup
-----
1. Copy `.env.example <.env.example>`_ to `.env` and update it with your real
``OPENAI_API_KEY``. If your
OTLP collector is not reachable via ``http://localhost:4317``, adjust the
endpoint variables as needed.
2. Create a virtual environment and install the dependencies:
::
python3 -m venv .venv
source .venv/bin/activate
pip install "python-dotenv[cli]"
uv pip install -r requirements.txt --prerelease=allow
Run
---
Execute the sample with ``dotenv`` so the environment variables from ``.env``
are applied:
::
dotenv run -- python main.py
Ensure ``OPENAI_API_KEY`` is present in your environment (or ``.env`` file); the OpenAI client raises ``OpenAIError`` if the key is missing.
The script automatically loads environment variables from ``.env`` so running
``python main.py`` directly also works if the shell already has the required
values exported.
You should see the agent response printed to the console while spans export to
your configured observability backend.
main.py 0000664 0000000 0000000 00000003277 15270700723 0041626 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-openai-agents-v2/examples/manual # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
# pylint: skip-file
"""Manual OpenAI Agents instrumentation example."""
from __future__ import annotations
from agents import Agent, Runner, function_tool
from dotenv import load_dotenv
from opentelemetry import trace
from opentelemetry.exporter.otlp.proto.grpc.trace_exporter import (
OTLPSpanExporter,
)
from opentelemetry.instrumentation.openai_agents import (
OpenAIAgentsInstrumentor,
)
from opentelemetry.sdk.trace import TracerProvider
from opentelemetry.sdk.trace.export import BatchSpanProcessor
def configure_otel() -> None:
"""Configure the OpenTelemetry SDK for exporting spans."""
provider = TracerProvider()
provider.add_span_processor(BatchSpanProcessor(OTLPSpanExporter()))
trace.set_tracer_provider(provider)
OpenAIAgentsInstrumentor().instrument(tracer_provider=provider)
@function_tool
def get_weather(city: str) -> str:
"""Return a canned weather response for the requested city."""
return f"The forecast for {city} is sunny with pleasant temperatures."
def run_agent() -> None:
"""Create a simple agent and execute a single run."""
assistant = Agent(
name="Travel Concierge",
instructions=(
"You are a concise travel concierge. Use the weather tool when the traveler asks about local conditions."
),
tools=[get_weather],
)
result = Runner.run_sync(
assistant,
"I'm visiting Barcelona this weekend. How should I pack?",
)
print("Agent response:")
print(result.final_output)
def main() -> None:
load_dotenv()
configure_otel()
run_agent()
if __name__ == "__main__":
main()
requirements.txt 0000664 0000000 0000000 00000000254 15270700723 0043604 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-openai-agents-v2/examples/manual openai-agents~=0.3.3
python-dotenv~=1.0
opentelemetry-sdk~=1.36.0
opentelemetry-exporter-otlp-proto-grpc~=1.36.0
opentelemetry-instrumentation-openai-agents-v2~=0.1.0.dev
zero-code/ 0000775 0000000 0000000 00000000000 15270700723 0040731 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-openai-agents-v2/examples .env.example 0000664 0000000 0000000 00000000614 15270700723 0043155 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-openai-agents-v2/examples/zero-code # Update this with your real OpenAI API key
OPENAI_API_KEY=sk-YOUR_API_KEY
# Uncomment and adjust if you use a non-default OTLP collector endpoint
# OTEL_EXPORTER_OTLP_ENDPOINT=http://localhost:4317
# OTEL_EXPORTER_OTLP_PROTOCOL=grpc
OTEL_SERVICE_NAME=opentelemetry-python-openai-agents-zero-code
# Optionally override the agent name reported on spans
# OTEL_GENAI_AGENT_NAME=Travel Concierge
README.rst 0000664 0000000 0000000 00000002764 15270700723 0042431 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-openai-agents-v2/examples/zero-code OpenTelemetry OpenAI Agents Zero-Code Instrumentation Example
=============================================================
This example shows how to capture telemetry from OpenAI Agents without
changing your application code by using ``opentelemetry-instrument``.
When `main.py `_ is executed, spans describing the agent workflow are
exported to the configured OTLP endpoint. The spans include details such as the
operation name, tool usage, and token consumption (when available).
Setup
-----
1. Copy `.env.example <.env.example>`_ to `.env` and update it with your real
``OPENAI_API_KEY``. Adjust the
OTLP endpoint settings if your collector is not reachable via
``http://localhost:4317``.
2. Create a virtual environment and install the dependencies:
::
python3 -m venv .venv
source .venv/bin/activate
pip install "python-dotenv[cli]"
uv pip install -r requirements.txt --prerelease=allow
Run
---
Execute the sample via ``opentelemetry-instrument`` so the OpenAI Agents
instrumentation is activated automatically:
::
dotenv run -- opentelemetry-instrument python main.py
Ensure ``OPENAI_API_KEY`` is set in your shell or `.env`; the OpenAI client raises ``OpenAIError`` if the key is missing.
Because ``main.py`` invokes ``load_dotenv``, running ``python main.py`` directly
also works when the required environment variables are already exported.
You should see the agent response printed to the console while spans export to
your observability backend.
main.py 0000664 0000000 0000000 00000003426 15270700723 0042234 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-openai-agents-v2/examples/zero-code # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
"""Zero-code OpenAI Agents example."""
from __future__ import annotations
from agents import Agent, Runner, function_tool
from dotenv import load_dotenv
from opentelemetry import trace
from opentelemetry.exporter.otlp.proto.grpc.trace_exporter import (
OTLPSpanExporter,
)
from opentelemetry.instrumentation.openai_agents import (
OpenAIAgentsInstrumentor,
)
from opentelemetry.sdk.trace import TracerProvider
from opentelemetry.sdk.trace.export import BatchSpanProcessor
def configure_tracing() -> None:
"""Ensure tracing exports spans even without auto-instrumentation."""
current_provider = trace.get_tracer_provider()
if isinstance(current_provider, TracerProvider):
provider = current_provider
else:
provider = TracerProvider()
provider.add_span_processor(BatchSpanProcessor(OTLPSpanExporter()))
trace.set_tracer_provider(provider)
OpenAIAgentsInstrumentor().instrument(tracer_provider=provider)
@function_tool
def get_weather(city: str) -> str:
"""Return a canned weather response for the requested city."""
return f"The forecast for {city} is sunny with pleasant temperatures."
def run_agent() -> None:
assistant = Agent(
name="Travel Concierge",
instructions=(
"You are a concise travel concierge. Use the weather tool when the traveler asks about local conditions."
),
tools=[get_weather],
)
result = Runner.run_sync(
assistant,
"I'm visiting Barcelona this weekend. How should I pack?",
)
print("Agent response:")
print(result.final_output)
def main() -> None:
load_dotenv()
configure_tracing()
run_agent()
if __name__ == "__main__":
main()
requirements.txt 0000664 0000000 0000000 00000000311 15270700723 0044210 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-openai-agents-v2/examples/zero-code openai-agents~=0.3.3
python-dotenv~=1.0
opentelemetry-sdk~=1.36.0
opentelemetry-exporter-otlp-proto-grpc~=1.36.0
opentelemetry-distro~=0.57b0
opentelemetry-instrumentation-openai-agents-v2~=0.1.0.dev
pyproject.toml 0000664 0000000 0000000 00000003343 15270700723 0040143 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-openai-agents-v2 [build-system]
requires = ["hatchling"]
build-backend = "hatchling.build"
[project]
name = "opentelemetry-instrumentation-openai-agents-v2"
dynamic = ["version"]
description = "OpenTelemetry Official OpenAI Agents instrumentation"
readme = "README.rst"
license = "Apache-2.0"
requires-python = ">=3.10"
authors = [
{ name = "OpenTelemetry Authors", email = "cncf-opentelemetry-contributors@lists.cncf.io" },
]
classifiers = [
"Development Status :: 4 - Beta",
"Intended Audience :: Developers",
"License :: OSI Approved :: Apache Software License",
"Programming Language :: Python",
"Programming Language :: Python :: 3",
"Programming Language :: Python :: 3.10",
"Programming Language :: Python :: 3.11",
"Programming Language :: Python :: 3.12",
"Programming Language :: Python :: 3.13",
"Programming Language :: Python :: 3.14",
]
dependencies = [
"opentelemetry-api >= 1.40",
"opentelemetry-instrumentation >= 0.61b0",
"opentelemetry-semantic-conventions >= 0.61b0",
"opentelemetry-util-genai >= 0.4b0, < 0.6b0",
"typing-extensions >= 4.5.0",
]
[project.optional-dependencies]
instruments = [
"openai-agents >= 0.3.3",
]
[project.entry-points.opentelemetry_instrumentor]
openai_agents = "opentelemetry.instrumentation.openai_agents:OpenAIAgentsInstrumentor"
[project.urls]
Homepage = "https://github.com/open-telemetry/opentelemetry-python-contrib/tree/main/instrumentation-genai/opentelemetry-instrumentation-openai-agents-v2"
Repository = "https://github.com/open-telemetry/opentelemetry-python-contrib"
[tool.hatch.version]
path = "src/opentelemetry/instrumentation/openai_agents/version.py"
[tool.hatch.build.targets.sdist]
include = [
"/src",
]
[tool.hatch.build.targets.wheel]
packages = ["src/opentelemetry"]
src/ 0000775 0000000 0000000 00000000000 15270700723 0036013 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-openai-agents-v2 opentelemetry/ 0000775 0000000 0000000 00000000000 15270700723 0040707 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-openai-agents-v2/src instrumentation/ 0000775 0000000 0000000 00000000000 15270700723 0044152 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-openai-agents-v2/src/opentelemetry openai_agents/ 0000775 0000000 0000000 00000000000 15270700723 0046766 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-openai-agents-v2/src/opentelemetry/instrumentation __init__.py 0000664 0000000 0000000 00000016175 15270700723 0051111 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-openai-agents-v2/src/opentelemetry/instrumentation/openai_agents # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
"""OpenAI Agents instrumentation for OpenTelemetry."""
# pylint: disable=too-many-locals
from __future__ import annotations
import importlib
import logging
import os
from collections.abc import Collection
from typing import Any
from typing_extensions import deprecated
from opentelemetry.instrumentation.instrumentor import BaseInstrumentor
from opentelemetry.semconv._incubating.attributes import (
gen_ai_attributes as GenAI,
)
from opentelemetry.semconv.schemas import Schemas
from opentelemetry.trace import get_tracer
from .package import _instruments
from .span_processor import (
ContentCaptureMode,
GenAIEvaluationAttributes,
GenAIOperationName,
GenAIOutputType,
GenAIProvider,
GenAISemanticProcessor,
GenAIToolType,
)
__all__ = [
"GenAIEvaluationAttributes",
"GenAIOperationName",
"GenAIOutputType",
"GenAIProvider",
"GenAIToolType",
"OpenAIAgentsInstrumentor",
]
logger = logging.getLogger(__name__)
_CONTENT_CAPTURE_ENV = "OTEL_INSTRUMENTATION_GENAI_CAPTURE_MESSAGE_CONTENT"
_SYSTEM_OVERRIDE_ENV = "OTEL_INSTRUMENTATION_OPENAI_AGENTS_SYSTEM"
_CAPTURE_CONTENT_ENV = "OTEL_INSTRUMENTATION_OPENAI_AGENTS_CAPTURE_CONTENT"
_CAPTURE_METRICS_ENV = "OTEL_INSTRUMENTATION_OPENAI_AGENTS_CAPTURE_METRICS"
def _load_tracing_module(): # pragma: no cover - exercised via tests
return importlib.import_module("agents.tracing")
def _get_registered_processors(provider) -> list:
multi = getattr(provider, "_multi_processor", None)
processors = getattr(multi, "_processors", ())
return list(processors)
def _resolve_system(value: str | None) -> str:
if not value:
return GenAI.GenAiSystemValues.OPENAI.value
normalized = value.strip().lower()
for member in GenAI.GenAiSystemValues:
if normalized == member.value:
return member.value
if normalized == member.name.lower():
return member.value
return value
def _resolve_content_mode(value: Any) -> ContentCaptureMode:
if isinstance(value, ContentCaptureMode):
return value
if isinstance(value, bool):
return ContentCaptureMode.SPAN_AND_EVENT if value else ContentCaptureMode.NO_CONTENT
if value is None:
return ContentCaptureMode.SPAN_AND_EVENT
text = str(value).strip().lower()
if not text:
return ContentCaptureMode.SPAN_AND_EVENT
mapping = {
"span_only": ContentCaptureMode.SPAN_ONLY,
"span-only": ContentCaptureMode.SPAN_ONLY,
"span": ContentCaptureMode.SPAN_ONLY,
"event_only": ContentCaptureMode.EVENT_ONLY,
"event-only": ContentCaptureMode.EVENT_ONLY,
"event": ContentCaptureMode.EVENT_ONLY,
"span_and_event": ContentCaptureMode.SPAN_AND_EVENT,
"span-and-event": ContentCaptureMode.SPAN_AND_EVENT,
"span_and_events": ContentCaptureMode.SPAN_AND_EVENT,
"all": ContentCaptureMode.SPAN_AND_EVENT,
"true": ContentCaptureMode.SPAN_AND_EVENT,
"1": ContentCaptureMode.SPAN_AND_EVENT,
"yes": ContentCaptureMode.SPAN_AND_EVENT,
"no_content": ContentCaptureMode.NO_CONTENT,
"false": ContentCaptureMode.NO_CONTENT,
"0": ContentCaptureMode.NO_CONTENT,
"no": ContentCaptureMode.NO_CONTENT,
"none": ContentCaptureMode.NO_CONTENT,
}
return mapping.get(text, ContentCaptureMode.SPAN_AND_EVENT)
def _resolve_bool(value: Any, default: bool) -> bool:
if value is None:
return default
if isinstance(value, bool):
return value
text = str(value).strip().lower()
if text in {"true", "1", "yes", "on"}:
return True
if text in {"false", "0", "no", "off"}:
return False
return default
@deprecated(
"opentelemetry-instrumentation-openai-agents-v2 is deprecated. Use the "
"opentelemetry-instrumentation-genai-openai-agents package instead. This "
"package only receives security patches."
)
class OpenAIAgentsInstrumentor(BaseInstrumentor):
"""Instrumentation that bridges OpenAI Agents tracing to OpenTelemetry.
.. deprecated:: 0.2.0
Use the ``opentelemetry-instrumentation-genai-openai-agents`` package
instead. This package only receives security patches.
"""
def __init__(self) -> None:
super().__init__()
self._processor: GenAISemanticProcessor | None = None
def _instrument(self, **kwargs) -> None:
if self._processor is not None:
return
tracer_provider = kwargs.get("tracer_provider")
tracer = get_tracer(
__name__,
"",
tracer_provider,
schema_url=Schemas.V1_28_0.value,
)
system_override = kwargs.get("system") or os.getenv(_SYSTEM_OVERRIDE_ENV)
system = _resolve_system(system_override)
content_override = kwargs.get("capture_message_content")
if content_override is None:
content_override = os.getenv(_CONTENT_CAPTURE_ENV) or os.getenv(_CAPTURE_CONTENT_ENV)
content_mode = _resolve_content_mode(content_override)
metrics_override = kwargs.get("capture_metrics")
if metrics_override is None:
metrics_override = os.getenv(_CAPTURE_METRICS_ENV)
metrics_enabled = _resolve_bool(metrics_override, default=True)
agent_name = kwargs.get("agent_name")
agent_id = kwargs.get("agent_id")
agent_description = kwargs.get("agent_description")
base_url = kwargs.get("base_url")
server_address = kwargs.get("server_address")
server_port = kwargs.get("server_port")
processor = GenAISemanticProcessor(
tracer=tracer,
system_name=system,
include_sensitive_data=content_mode != ContentCaptureMode.NO_CONTENT,
content_mode=content_mode,
metrics_enabled=metrics_enabled,
agent_name=agent_name,
agent_id=agent_id,
agent_description=agent_description,
base_url=base_url,
server_address=server_address,
server_port=server_port,
agent_name_default="OpenAI Agent",
agent_id_default="agent",
agent_description_default="OpenAI Agents instrumentation",
base_url_default="https://api.openai.com",
server_address_default="api.openai.com",
server_port_default=443,
)
tracing = _load_tracing_module()
provider = tracing.get_trace_provider()
existing = _get_registered_processors(provider)
provider.set_processors([*existing, processor])
self._processor = processor
def _uninstrument(self, **kwargs) -> None:
if self._processor is None:
return
tracing = _load_tracing_module()
provider = tracing.get_trace_provider()
current = _get_registered_processors(provider)
filtered = [proc for proc in current if proc is not self._processor]
provider.set_processors(filtered)
try:
self._processor.shutdown()
finally:
self._processor = None
def instrumentation_dependencies(self) -> Collection[str]:
return _instruments
package.py 0000664 0000000 0000000 00000000222 15270700723 0050727 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-openai-agents-v2/src/opentelemetry/instrumentation/openai_agents # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
_instruments = ("openai-agents >= 0.3.3",)
_supports_metrics = False
span_processor.py 0000664 0000000 0000000 00000234342 15270700723 0052410 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-openai-agents-v2/src/opentelemetry/instrumentation/openai_agents # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
"""
GenAI Semantic Convention Trace Processor
This module implements a custom trace processor that enriches spans with
OpenTelemetry GenAI semantic conventions attributes following the
OpenInference processor pattern. It adds standardized attributes for
generative AI operations using iterator-based attribute extraction.
References:
- OpenTelemetry GenAI Semantic Conventions:
https://opentelemetry.io/docs/specs/semconv/gen-ai/gen-ai-spans/
- OpenInference Pattern: https://github.com/Arize-ai/openinference
"""
# pylint: disable=too-many-lines,invalid-name,too-many-locals,too-many-branches,too-many-statements,too-many-return-statements,too-many-nested-blocks,too-many-arguments,too-many-instance-attributes,broad-exception-caught,no-self-use,consider-iterating-dictionary,unused-variable,unnecessary-pass
from __future__ import annotations
import importlib
import logging
from collections.abc import Iterator, Sequence
from dataclasses import dataclass
from datetime import datetime, timezone
from enum import Enum
from typing import Any
from urllib.parse import urlparse
from opentelemetry.util.genai.utils import gen_ai_json_dumps
try:
from agents.tracing import Span, Trace, TracingProcessor
from agents.tracing.span_data import (
AgentSpanData,
FunctionSpanData,
GenerationSpanData,
GuardrailSpanData,
HandoffSpanData,
ResponseSpanData,
SpeechSpanData,
TranscriptionSpanData,
)
except ModuleNotFoundError: # pragma: no cover - test stubs
tracing_module = importlib.import_module("agents.tracing")
Span = tracing_module.Span
Trace = tracing_module.Trace
TracingProcessor = tracing_module.TracingProcessor
AgentSpanData = getattr(tracing_module, "AgentSpanData", Any) # type: ignore[assignment]
FunctionSpanData = getattr(tracing_module, "FunctionSpanData", Any) # type: ignore[assignment]
GenerationSpanData = getattr(tracing_module, "GenerationSpanData", Any) # type: ignore[assignment]
GuardrailSpanData = getattr(tracing_module, "GuardrailSpanData", Any) # type: ignore[assignment]
HandoffSpanData = getattr(tracing_module, "HandoffSpanData", Any) # type: ignore[assignment]
ResponseSpanData = getattr(tracing_module, "ResponseSpanData", Any) # type: ignore[assignment]
SpeechSpanData = getattr(tracing_module, "SpeechSpanData", Any) # type: ignore[assignment]
TranscriptionSpanData = getattr(tracing_module, "TranscriptionSpanData", Any) # type: ignore[assignment]
from opentelemetry.context import attach, detach
from opentelemetry.metrics import Histogram, get_meter
from opentelemetry.semconv._incubating.attributes import (
gen_ai_attributes as GenAIAttributes,
)
from opentelemetry.semconv._incubating.attributes import (
server_attributes as ServerAttributes,
)
from opentelemetry.trace import Span as OtelSpan
from opentelemetry.trace import (
SpanKind,
Status,
StatusCode,
Tracer,
set_span_in_context,
)
from opentelemetry.util.types import AttributeValue
# Import all semantic convention constants
# ---- GenAI semantic convention helpers (embedded from constants.py) ----
def _enum_values(enum_cls) -> dict[str, str]:
"""Return mapping of enum member name to value."""
return {member.name: member.value for member in enum_cls}
_PROVIDER_VALUES = _enum_values(GenAIAttributes.GenAiProviderNameValues)
class GenAIProvider:
OPENAI = _PROVIDER_VALUES["OPENAI"]
GCP_GEN_AI = _PROVIDER_VALUES["GCP_GEN_AI"]
GCP_VERTEX_AI = _PROVIDER_VALUES["GCP_VERTEX_AI"]
GCP_GEMINI = _PROVIDER_VALUES["GCP_GEMINI"]
ANTHROPIC = _PROVIDER_VALUES["ANTHROPIC"]
COHERE = _PROVIDER_VALUES["COHERE"]
AZURE_AI_INFERENCE = _PROVIDER_VALUES["AZURE_AI_INFERENCE"]
AZURE_AI_OPENAI = _PROVIDER_VALUES["AZURE_AI_OPENAI"]
IBM_WATSONX_AI = _PROVIDER_VALUES["IBM_WATSONX_AI"]
AWS_BEDROCK = _PROVIDER_VALUES["AWS_BEDROCK"]
PERPLEXITY = _PROVIDER_VALUES["PERPLEXITY"]
X_AI = _PROVIDER_VALUES["X_AI"]
DEEPSEEK = _PROVIDER_VALUES["DEEPSEEK"]
GROQ = _PROVIDER_VALUES["GROQ"]
MISTRAL_AI = _PROVIDER_VALUES["MISTRAL_AI"]
ALL = set(_PROVIDER_VALUES.values())
_OPERATION_VALUES = _enum_values(GenAIAttributes.GenAiOperationNameValues)
class GenAIOperationName:
CHAT = _OPERATION_VALUES["CHAT"]
GENERATE_CONTENT = _OPERATION_VALUES["GENERATE_CONTENT"]
TEXT_COMPLETION = _OPERATION_VALUES["TEXT_COMPLETION"]
EMBEDDINGS = _OPERATION_VALUES["EMBEDDINGS"]
CREATE_AGENT = _OPERATION_VALUES["CREATE_AGENT"]
INVOKE_AGENT = _OPERATION_VALUES["INVOKE_AGENT"]
EXECUTE_TOOL = _OPERATION_VALUES["EXECUTE_TOOL"]
# Operations below are not yet covered by the spec but remain for backwards compatibility
TRANSCRIPTION = "transcription"
SPEECH = "speech_generation"
GUARDRAIL = "guardrail_check"
HANDOFF = "agent_handoff"
RESPONSE = "response" # internal aggregator in current processor
CLASS_FALLBACK = {
"generationspan": CHAT,
"responsespan": RESPONSE,
"functionspan": EXECUTE_TOOL,
"agentspan": INVOKE_AGENT,
}
_OUTPUT_VALUES = _enum_values(GenAIAttributes.GenAiOutputTypeValues)
class GenAIOutputType:
TEXT = _OUTPUT_VALUES["TEXT"]
JSON = _OUTPUT_VALUES["JSON"]
IMAGE = _OUTPUT_VALUES["IMAGE"]
SPEECH = _OUTPUT_VALUES["SPEECH"]
class GenAIToolType:
FUNCTION = "function"
EXTENSION = "extension"
DATASTORE = "datastore"
ALL = {FUNCTION, EXTENSION, DATASTORE}
class GenAIEvaluationAttributes:
NAME = "gen_ai.evaluation.name"
SCORE_VALUE = "gen_ai.evaluation.score.value"
SCORE_LABEL = "gen_ai.evaluation.score.label"
EXPLANATION = "gen_ai.evaluation.explanation"
def _attr(name: str, fallback: str) -> str:
return getattr(GenAIAttributes, name, fallback)
GEN_AI_PROVIDER_NAME = _attr("GEN_AI_PROVIDER_NAME", "gen_ai.provider.name")
GEN_AI_OPERATION_NAME = _attr("GEN_AI_OPERATION_NAME", "gen_ai.operation.name")
GEN_AI_REQUEST_MODEL = _attr("GEN_AI_REQUEST_MODEL", "gen_ai.request.model")
GEN_AI_REQUEST_MAX_TOKENS = _attr("GEN_AI_REQUEST_MAX_TOKENS", "gen_ai.request.max_tokens")
GEN_AI_REQUEST_TEMPERATURE = _attr("GEN_AI_REQUEST_TEMPERATURE", "gen_ai.request.temperature")
GEN_AI_REQUEST_TOP_P = _attr("GEN_AI_REQUEST_TOP_P", "gen_ai.request.top_p")
GEN_AI_REQUEST_TOP_K = _attr("GEN_AI_REQUEST_TOP_K", "gen_ai.request.top_k")
GEN_AI_REQUEST_FREQUENCY_PENALTY = _attr("GEN_AI_REQUEST_FREQUENCY_PENALTY", "gen_ai.request.frequency_penalty")
GEN_AI_REQUEST_PRESENCE_PENALTY = _attr("GEN_AI_REQUEST_PRESENCE_PENALTY", "gen_ai.request.presence_penalty")
GEN_AI_REQUEST_CHOICE_COUNT = _attr("GEN_AI_REQUEST_CHOICE_COUNT", "gen_ai.request.choice.count")
GEN_AI_REQUEST_STOP_SEQUENCES = _attr("GEN_AI_REQUEST_STOP_SEQUENCES", "gen_ai.request.stop_sequences")
GEN_AI_REQUEST_ENCODING_FORMATS = _attr("GEN_AI_REQUEST_ENCODING_FORMATS", "gen_ai.request.encoding_formats")
GEN_AI_REQUEST_SEED = _attr("GEN_AI_REQUEST_SEED", "gen_ai.request.seed")
GEN_AI_RESPONSE_ID = _attr("GEN_AI_RESPONSE_ID", "gen_ai.response.id")
GEN_AI_RESPONSE_MODEL = _attr("GEN_AI_RESPONSE_MODEL", "gen_ai.response.model")
GEN_AI_RESPONSE_FINISH_REASONS = _attr("GEN_AI_RESPONSE_FINISH_REASONS", "gen_ai.response.finish_reasons")
GEN_AI_USAGE_INPUT_TOKENS = _attr("GEN_AI_USAGE_INPUT_TOKENS", "gen_ai.usage.input_tokens")
GEN_AI_USAGE_OUTPUT_TOKENS = _attr("GEN_AI_USAGE_OUTPUT_TOKENS", "gen_ai.usage.output_tokens")
GEN_AI_CONVERSATION_ID = _attr("GEN_AI_CONVERSATION_ID", "gen_ai.conversation.id")
GEN_AI_AGENT_ID = _attr("GEN_AI_AGENT_ID", "gen_ai.agent.id")
GEN_AI_AGENT_NAME = _attr("GEN_AI_AGENT_NAME", "gen_ai.agent.name")
GEN_AI_AGENT_DESCRIPTION = _attr("GEN_AI_AGENT_DESCRIPTION", "gen_ai.agent.description")
GEN_AI_TOOL_NAME = _attr("GEN_AI_TOOL_NAME", "gen_ai.tool.name")
GEN_AI_TOOL_TYPE = _attr("GEN_AI_TOOL_TYPE", "gen_ai.tool.type")
GEN_AI_TOOL_CALL_ID = _attr("GEN_AI_TOOL_CALL_ID", "gen_ai.tool.call.id")
GEN_AI_TOOL_DESCRIPTION = _attr("GEN_AI_TOOL_DESCRIPTION", "gen_ai.tool.description")
GEN_AI_OUTPUT_TYPE = _attr("GEN_AI_OUTPUT_TYPE", "gen_ai.output.type")
GEN_AI_SYSTEM_INSTRUCTIONS = _attr("GEN_AI_SYSTEM_INSTRUCTIONS", "gen_ai.system_instructions")
GEN_AI_INPUT_MESSAGES = _attr("GEN_AI_INPUT_MESSAGES", "gen_ai.input.messages")
GEN_AI_OUTPUT_MESSAGES = _attr("GEN_AI_OUTPUT_MESSAGES", "gen_ai.output.messages")
GEN_AI_DATA_SOURCE_ID = _attr("GEN_AI_DATA_SOURCE_ID", "gen_ai.data_source.id")
# The semantic conventions currently expose multiple usage token attributes; we retain the
# completion/prompt aliases for backwards compatibility where used.
GEN_AI_USAGE_PROMPT_TOKENS = _attr("GEN_AI_USAGE_PROMPT_TOKENS", "gen_ai.usage.prompt_tokens")
GEN_AI_USAGE_COMPLETION_TOKENS = _attr("GEN_AI_USAGE_COMPLETION_TOKENS", "gen_ai.usage.completion_tokens")
# Attributes not (yet) defined in the spec retain their literal values.
GEN_AI_TOOL_CALL_ARGUMENTS = "gen_ai.tool.call.arguments"
GEN_AI_TOOL_CALL_RESULT = "gen_ai.tool.call.result"
GEN_AI_TOOL_DEFINITIONS = "gen_ai.tool.definitions"
GEN_AI_ORCHESTRATOR_AGENT_DEFINITIONS = "gen_ai.orchestrator.agent.definitions"
GEN_AI_GUARDRAIL_NAME = "gen_ai.guardrail.name"
GEN_AI_GUARDRAIL_TRIGGERED = "gen_ai.guardrail.triggered"
GEN_AI_HANDOFF_FROM_AGENT = "gen_ai.handoff.from_agent"
GEN_AI_HANDOFF_TO_AGENT = "gen_ai.handoff.to_agent"
GEN_AI_EMBEDDINGS_DIMENSION_COUNT = "gen_ai.embeddings.dimension.count"
GEN_AI_TOKEN_TYPE = _attr("GEN_AI_TOKEN_TYPE", "gen_ai.token.type")
# ---- Normalization utilities (embedded from utils.py) ----
def normalize_provider(provider: str | None) -> str | None:
"""Normalize provider name to spec-compliant value."""
if not provider:
return None
normalized = provider.strip().lower()
if normalized in GenAIProvider.ALL:
return normalized
return provider # passthrough if unknown (forward compat)
def validate_tool_type(tool_type: str | None) -> str:
"""Validate and normalize tool type."""
if not tool_type:
return GenAIToolType.FUNCTION # default
normalized = tool_type.strip().lower()
return normalized if normalized in GenAIToolType.ALL else GenAIToolType.FUNCTION
def normalize_output_type(output_type: str | None) -> str:
"""Normalize output type to spec-compliant value."""
if not output_type:
return GenAIOutputType.TEXT # default
normalized = output_type.strip().lower()
base_map = {
"json_object": GenAIOutputType.JSON,
"jsonschema": GenAIOutputType.JSON,
"speech_audio": GenAIOutputType.SPEECH,
"audio_speech": GenAIOutputType.SPEECH,
"image_png": GenAIOutputType.IMAGE,
"function_arguments_json": GenAIOutputType.JSON,
"tool_call": GenAIOutputType.JSON,
"transcription_json": GenAIOutputType.JSON,
}
if normalized in base_map:
return base_map[normalized]
if normalized in {
GenAIOutputType.TEXT,
GenAIOutputType.JSON,
GenAIOutputType.IMAGE,
GenAIOutputType.SPEECH,
}:
return normalized
return GenAIOutputType.TEXT # default for unknown
# Legacy attributes removed
logger = logging.getLogger(__name__)
GEN_AI_SYSTEM_KEY = getattr(GenAIAttributes, "GEN_AI_SYSTEM", "gen_ai.system")
class ContentCaptureMode(Enum):
"""Controls whether sensitive content is recorded on spans, events, or both."""
NO_CONTENT = "no_content"
SPAN_ONLY = "span_only"
EVENT_ONLY = "event_only"
SPAN_AND_EVENT = "span_and_event"
@property
def capture_in_span(self) -> bool:
return self in (
ContentCaptureMode.SPAN_ONLY,
ContentCaptureMode.SPAN_AND_EVENT,
)
@property
def capture_in_event(self) -> bool:
return self in (
ContentCaptureMode.EVENT_ONLY,
ContentCaptureMode.SPAN_AND_EVENT,
)
@dataclass
class ContentPayload:
"""Container for normalized content associated with a span."""
input_messages: list[dict[str, Any]] | None = None
output_messages: list[dict[str, Any]] | None = None
system_instructions: list[dict[str, str]] | None = None
tool_arguments: Any = None
tool_result: Any = None
def _is_instance_of(value: Any, classes: Any) -> bool:
"""Safe isinstance that tolerates typing.Any placeholders."""
if not isinstance(classes, tuple):
classes = (classes,)
for cls in classes:
try:
if isinstance(value, cls):
return True
except TypeError:
continue
return False
def _infer_server_attributes(base_url: str | None) -> dict[str, Any]:
"""Return server.address / server.port attributes if base_url provided."""
out: dict[str, Any] = {}
if not base_url:
return out
try:
parsed = urlparse(base_url)
if parsed.hostname:
out[ServerAttributes.SERVER_ADDRESS] = parsed.hostname
if parsed.port:
out[ServerAttributes.SERVER_PORT] = parsed.port
except Exception:
return out
return out
def safe_json_dumps(obj: Any) -> str:
"""Safely convert object to JSON string (fallback to str)."""
try:
return gen_ai_json_dumps(obj)
except (TypeError, ValueError):
return str(obj)
def _as_utc_nano(dt: datetime) -> int:
"""Convert datetime to UTC nanoseconds timestamp."""
return int(dt.astimezone(timezone.utc).timestamp() * 1_000_000_000)
def _get_span_status(span: Span[Any]) -> Status:
"""Get OpenTelemetry span status from agent span."""
if error := getattr(span, "error", None):
return Status(
status_code=StatusCode.ERROR,
description=f"{error.get('message', '')}: {error.get('data', '')}",
)
return Status(StatusCode.OK)
def get_span_name(
operation_name: str,
model: str | None = None,
agent_name: str | None = None,
tool_name: str | None = None,
) -> str:
"""Generate spec-compliant span name based on operation type."""
base_name = operation_name
if operation_name in {
GenAIOperationName.CHAT,
GenAIOperationName.TEXT_COMPLETION,
GenAIOperationName.EMBEDDINGS,
GenAIOperationName.TRANSCRIPTION,
GenAIOperationName.SPEECH,
}:
return f"{base_name} {model}" if model else base_name
if operation_name == GenAIOperationName.CREATE_AGENT:
return f"{base_name} {agent_name}" if agent_name else base_name
if operation_name == GenAIOperationName.INVOKE_AGENT:
return f"{base_name} {agent_name}" if agent_name else base_name
if operation_name == GenAIOperationName.EXECUTE_TOOL:
return f"{base_name} {tool_name}" if tool_name else base_name
if operation_name == GenAIOperationName.HANDOFF:
return f"{base_name} {agent_name}" if agent_name else base_name
return base_name
class GenAISemanticProcessor(TracingProcessor):
"""Trace processor adding GenAI semantic convention attributes with metrics."""
# pylint: disable=too-many-positional-arguments
def __init__(
self,
tracer: Tracer | None = None,
system_name: str = "openai",
include_sensitive_data: bool = True,
content_mode: ContentCaptureMode = ContentCaptureMode.SPAN_AND_EVENT,
base_url: str | None = None,
agent_name: str | None = None,
agent_id: str | None = None,
agent_description: str | None = None,
server_address: str | None = None,
server_port: int | None = None,
metrics_enabled: bool = True,
agent_name_default: str | None = None,
agent_id_default: str | None = None,
agent_description_default: str | None = None,
base_url_default: str | None = None,
server_address_default: str | None = None,
server_port_default: int | None = None,
):
"""Initialize processor with metrics support.
Args:
tracer: Optional OpenTelemetry tracer
system_name: Provider name (openai/azure.ai.inference/etc.)
include_sensitive_data: Include model/tool IO when True
base_url: API endpoint for server.address/port
agent_name: Name of the agent (can be overridden by env var)
agent_id: ID of the agent (can be overridden by env var)
agent_description: Description of the agent (can be overridden by env var)
server_address: Server address (can be overridden by env var or base_url)
server_port: Server port (can be overridden by env var or base_url)
"""
self._tracer = tracer
self.system_name = normalize_provider(system_name) or system_name
self._content_mode = content_mode
self.include_sensitive_data = include_sensitive_data and (
content_mode.capture_in_span or content_mode.capture_in_event
)
effective_base_url = base_url or base_url_default
self.base_url = effective_base_url
# Agent information - prefer explicit overrides; otherwise defer to span data
self.agent_name = agent_name
self.agent_id = agent_id
self.agent_description = agent_description
self._agent_name_default = agent_name_default
self._agent_id_default = agent_id_default
self._agent_description_default = agent_description_default
# Server information - use init parameters, then base_url inference
self.server_address = server_address or server_address_default
resolved_port = server_port if server_port is not None else server_port_default
self.server_port = resolved_port
# If server info not provided, try to extract from base_url
if (not self.server_address or not self.server_port) and effective_base_url:
server_attrs = _infer_server_attributes(effective_base_url)
if not self.server_address:
self.server_address = server_attrs.get(ServerAttributes.SERVER_ADDRESS)
if not self.server_port:
self.server_port = server_attrs.get(ServerAttributes.SERVER_PORT)
# Content capture configuration
self._capture_messages = content_mode.capture_in_span or content_mode.capture_in_event
self._capture_system_instructions = True
self._capture_tool_definitions = True
# Span tracking
self._root_spans: dict[str, OtelSpan] = {}
self._otel_spans: dict[str, OtelSpan] = {}
self._tokens: dict[str, object] = {}
self._span_parents: dict[str, str | None] = {}
self._agent_content: dict[str, dict[str, list[Any]]] = {}
# Metrics configuration
self._metrics_enabled = metrics_enabled
self._meter = None
self._duration_histogram: Histogram | None = None
self._token_usage_histogram: Histogram | None = None
if self._metrics_enabled:
self._init_metrics()
def _get_server_attributes(self) -> dict[str, Any]:
"""Get server attributes from configured values."""
attrs = {}
if self.server_address:
attrs[ServerAttributes.SERVER_ADDRESS] = self.server_address
if self.server_port:
attrs[ServerAttributes.SERVER_PORT] = self.server_port
return attrs
def _init_metrics(self):
"""Initialize metric instruments."""
self._meter = get_meter("opentelemetry.instrumentation.openai_agents", "0.1.0")
# Operation duration histogram
self._duration_histogram = self._meter.create_histogram(
name="gen_ai.client.operation.duration",
description="GenAI operation duration",
unit="s",
)
# Token usage histogram
self._token_usage_histogram = self._meter.create_histogram(
name="gen_ai.client.token.usage",
description="Number of input and output tokens used",
unit="{token}",
)
def _record_metrics(self, span: Span[Any], attributes: dict[str, AttributeValue]) -> None:
"""Record metrics for the span."""
if not self._metrics_enabled or (self._duration_histogram is None and self._token_usage_histogram is None):
return
try:
# Calculate duration
duration = None
if hasattr(span, "started_at") and hasattr(span, "ended_at"):
try:
start = datetime.fromisoformat(span.started_at)
end = datetime.fromisoformat(span.ended_at)
duration = (end - start).total_seconds()
except Exception:
pass
# Build metric attributes
metric_attrs = {
GEN_AI_PROVIDER_NAME: attributes.get(GEN_AI_PROVIDER_NAME),
GEN_AI_OPERATION_NAME: attributes.get(GEN_AI_OPERATION_NAME),
GEN_AI_REQUEST_MODEL: (attributes.get(GEN_AI_REQUEST_MODEL) or attributes.get(GEN_AI_RESPONSE_MODEL)),
ServerAttributes.SERVER_ADDRESS: attributes.get(ServerAttributes.SERVER_ADDRESS),
ServerAttributes.SERVER_PORT: attributes.get(ServerAttributes.SERVER_PORT),
}
# Add error type if present
if error := getattr(span, "error", None):
error_type = error.get("type") or error.get("name")
if error_type:
metric_attrs["error.type"] = error_type
# Remove None values
metric_attrs = {k: v for k, v in metric_attrs.items() if v is not None}
# Record duration
if duration is not None and self._duration_histogram is not None:
self._duration_histogram.record(duration, metric_attrs)
# Record token usage
if self._token_usage_histogram:
input_tokens = attributes.get(GEN_AI_USAGE_INPUT_TOKENS)
if isinstance(input_tokens, (int, float)):
token_attrs = dict(metric_attrs)
token_attrs[GEN_AI_TOKEN_TYPE] = "input"
self._token_usage_histogram.record(input_tokens, token_attrs)
output_tokens = attributes.get(GEN_AI_USAGE_OUTPUT_TOKENS)
if isinstance(output_tokens, (int, float)):
token_attrs = dict(metric_attrs)
token_attrs[GEN_AI_TOKEN_TYPE] = "output"
self._token_usage_histogram.record(output_tokens, token_attrs)
except Exception as e:
logger.debug("Failed to record metrics: %s", e)
def _emit_content_events(
self,
span: Span[Any],
otel_span: OtelSpan,
payload: ContentPayload,
agent_content: dict[str, list[Any]] | None = None,
) -> None:
"""Intentionally skip emitting gen_ai.* events to avoid payload duplication."""
if not self.include_sensitive_data or not self._content_mode.capture_in_event or not otel_span.is_recording():
return
logger.debug(
"Event capture requested for span %s but is currently disabled",
getattr(span, "span_id", ""),
)
return
def _collect_system_instructions(self, messages: Sequence[Any] | None) -> list[dict[str, str]]:
"""Return system/ai role instructions as typed text objects.
Enforces format: [{"type": "text", "content": "..."}].
Handles message content that may be a string, list of parts,
or a dict with text/content fields.
"""
if not messages:
return []
out: list[dict[str, str]] = []
for m in messages:
if not isinstance(m, dict):
continue
role = m.get("role")
if role in {"system", "ai"}:
content = m.get("content")
out.extend(self._normalize_to_text_parts(content))
return out
def _normalize_to_text_parts(self, content: Any) -> list[dict[str, str]]:
"""Normalize arbitrary content into typed text parts.
- String -> [{type: text, content: }]
- List/Tuple -> map each item to a text part (string/dict supported)
- Dict -> use 'text' or 'content' field when available; else str(dict)
- Other -> str(value)
"""
parts: list[dict[str, str]] = []
if content is None:
return parts
if isinstance(content, str):
parts.append({"type": "text", "content": content})
return parts
if isinstance(content, (list, tuple)):
for item in content:
if isinstance(item, str):
parts.append({"type": "text", "content": item})
elif isinstance(item, dict):
txt = item.get("text") or item.get("content")
if isinstance(txt, str) and txt:
parts.append({"type": "text", "content": txt})
else:
parts.append({"type": "text", "content": str(item)})
else:
parts.append({"type": "text", "content": str(item)})
return parts
if isinstance(content, dict):
txt = content.get("text") or content.get("content")
if isinstance(txt, str) and txt:
parts.append({"type": "text", "content": txt})
else:
parts.append({"type": "text", "content": str(content)})
return parts
# Fallback for other types
parts.append({"type": "text", "content": str(content)})
return parts
def _redacted_text_parts(self) -> list[dict[str, str]]:
"""Return a single redacted text part for system instructions."""
return [{"type": "text", "content": "readacted"}]
def _normalize_messages_to_role_parts(self, messages: Sequence[Any] | None) -> list[dict[str, Any]]:
"""Normalize input messages to enforced role+parts schema.
Each message becomes: {"role": , "parts": [ {"type": ..., ...} ]}
Redaction: when include_sensitive_data is False, replace text content,
tool_call arguments, and tool_call_response result with "readacted".
"""
if not messages:
return []
normalized: list[dict[str, Any]] = []
for m in messages:
if not isinstance(m, dict):
# Fallback: treat as user text
normalized.append(
{
"role": "user",
"parts": [
{
"type": "text",
"content": "readacted" if not self.include_sensitive_data else str(m),
}
],
}
)
continue
role = m.get("role") or "user"
parts: list[dict[str, Any]] = []
# Existing parts array
if isinstance(m.get("parts"), (list, tuple)):
for p in m["parts"]:
if isinstance(p, dict):
ptype = p.get("type") or "text"
newp: dict[str, Any] = {"type": ptype}
if ptype == "text":
txt = p.get("content") or p.get("text")
newp["content"] = (
"readacted"
if not self.include_sensitive_data
else (txt if isinstance(txt, str) else str(p))
)
elif ptype == "tool_call":
newp["id"] = p.get("id")
newp["name"] = p.get("name")
args = p.get("arguments")
newp["arguments"] = "readacted" if not self.include_sensitive_data else args
elif ptype == "tool_call_response":
newp["id"] = p.get("id") or m.get("tool_call_id")
result = p.get("result") or p.get("content")
newp["result"] = "readacted" if not self.include_sensitive_data else result
else:
newp["content"] = "readacted" if not self.include_sensitive_data else str(p)
parts.append(newp)
else:
parts.append(
{
"type": "text",
"content": "readacted" if not self.include_sensitive_data else str(p),
}
)
# OpenAI content
content = m.get("content")
if isinstance(content, str):
parts.append(
{
"type": "text",
"content": "readacted" if not self.include_sensitive_data else content,
}
)
elif isinstance(content, (list, tuple)):
for item in content:
if isinstance(item, dict):
itype = item.get("type") or "text"
if itype == "text":
txt = item.get("text") or item.get("content")
parts.append(
{
"type": "text",
"content": "readacted"
if not self.include_sensitive_data
else (txt if isinstance(txt, str) else str(item)),
}
)
else:
# Fallback for other part types
parts.append(
{
"type": "text",
"content": "readacted" if not self.include_sensitive_data else str(item),
}
)
else:
parts.append(
{
"type": "text",
"content": "readacted" if not self.include_sensitive_data else str(item),
}
)
# Assistant tool_calls
if role == "assistant" and isinstance(m.get("tool_calls"), (list, tuple)):
for tc in m["tool_calls"]:
if not isinstance(tc, dict):
continue
p = {"type": "tool_call"}
p["id"] = tc.get("id")
fn = tc.get("function") or {}
if isinstance(fn, dict):
p["name"] = fn.get("name")
args = fn.get("arguments")
p["arguments"] = "readacted" if not self.include_sensitive_data else args
parts.append(p)
# Tool call response
if role in {"tool", "function"}:
p = {"type": "tool_call_response"}
p["id"] = m.get("tool_call_id") or m.get("id")
result = m.get("result") or m.get("content")
p["result"] = "readacted" if not self.include_sensitive_data else result
parts.append(p)
if parts:
normalized.append({"role": role, "parts": parts})
elif not self.include_sensitive_data:
normalized.append({"role": role, "parts": self._redacted_text_parts()})
return normalized
def _normalize_output_messages_to_role_parts(self, span_data: Any) -> list[dict[str, Any]]:
"""Normalize output messages to enforced role+parts schema.
Produces: [{"role": "assistant", "parts": [{"type": "text", "content": "..."}],
optional "finish_reason": "..." }]
"""
messages: list[dict[str, Any]] = []
parts: list[dict[str, Any]] = []
finish_reason: str | None = None
# Response span: prefer consolidated output_text
response = getattr(span_data, "response", None)
if response is not None:
# Collect text content
output_text = getattr(response, "output_text", None)
if isinstance(output_text, str) and output_text:
parts.append(
{
"type": "text",
"content": ("readacted" if not self.include_sensitive_data else output_text),
}
)
else:
output = getattr(response, "output", None)
if isinstance(output, Sequence):
for item in output:
# ResponseOutputMessage may have a string representation
txt = getattr(item, "content", None)
if isinstance(txt, str) and txt:
parts.append(
{
"type": "text",
"content": ("readacted" if not self.include_sensitive_data else txt),
}
)
else:
# Fallback: stringified
parts.append(
{
"type": "text",
"content": ("readacted" if not self.include_sensitive_data else str(item)),
}
)
# Capture finish_reason from parts when present
fr = getattr(item, "finish_reason", None)
if isinstance(fr, str) and not finish_reason:
finish_reason = fr
# Generation span: use span_data.output
if not parts:
output = getattr(span_data, "output", None)
if isinstance(output, Sequence):
for item in output:
if isinstance(item, dict):
if item.get("type") == "text":
txt = item.get("content") or item.get("text")
if isinstance(txt, str) and txt:
parts.append(
{
"type": "text",
"content": ("readacted" if not self.include_sensitive_data else txt),
}
)
elif "content" in item and isinstance(item["content"], str):
parts.append(
{
"type": "text",
"content": ("readacted" if not self.include_sensitive_data else item["content"]),
}
)
else:
parts.append(
{
"type": "text",
"content": ("readacted" if not self.include_sensitive_data else str(item)),
}
)
if not finish_reason and isinstance(item.get("finish_reason"), str):
finish_reason = item.get("finish_reason")
elif isinstance(item, str):
parts.append(
{
"type": "text",
"content": ("readacted" if not self.include_sensitive_data else item),
}
)
else:
parts.append(
{
"type": "text",
"content": ("readacted" if not self.include_sensitive_data else str(item)),
}
)
# Build assistant message
msg: dict[str, Any] = {"role": "assistant", "parts": parts}
if finish_reason:
msg["finish_reason"] = finish_reason
# Only include if there is content
if parts:
messages.append(msg)
return messages
def _build_content_payload(self, span: Span[Any]) -> ContentPayload:
"""Normalize content from span data for attribute/event capture."""
payload = ContentPayload()
span_data = getattr(span, "span_data", None)
if span_data is None or not self.include_sensitive_data:
return payload
capture_messages = self._capture_messages and (
self._content_mode.capture_in_span or self._content_mode.capture_in_event
)
capture_system = self._capture_system_instructions and (
self._content_mode.capture_in_span or self._content_mode.capture_in_event
)
capture_tools = self._content_mode.capture_in_span or (
self._content_mode.capture_in_event and _is_instance_of(span_data, FunctionSpanData)
)
if _is_instance_of(span_data, GenerationSpanData):
span_input = getattr(span_data, "input", None)
if capture_messages and span_input:
payload.input_messages = self._normalize_messages_to_role_parts(span_input)
if capture_system and span_input:
sys_instr = self._collect_system_instructions(span_input)
if sys_instr:
payload.system_instructions = sys_instr
if capture_messages and (getattr(span_data, "output", None) or getattr(span_data, "response", None)):
normalized_out = self._normalize_output_messages_to_role_parts(span_data)
if normalized_out:
payload.output_messages = normalized_out
elif _is_instance_of(span_data, ResponseSpanData):
span_input = getattr(span_data, "input", None)
response_obj = getattr(span_data, "response", None)
if capture_messages and span_input:
payload.input_messages = self._normalize_messages_to_role_parts(span_input)
if capture_system and response_obj and hasattr(response_obj, "instructions"):
payload.system_instructions = self._normalize_to_text_parts(response_obj.instructions)
if capture_system and span_input:
sys_instr = self._collect_system_instructions(span_input)
if sys_instr:
payload.system_instructions = sys_instr
if capture_messages:
normalized_out = self._normalize_output_messages_to_role_parts(span_data)
if normalized_out:
payload.output_messages = normalized_out
elif _is_instance_of(span_data, FunctionSpanData) and capture_tools:
def _serialize_tool_value(value: Any) -> str | None:
if value is None:
return None
if isinstance(value, (dict, list)):
return safe_json_dumps(value)
return str(value)
payload.tool_arguments = _serialize_tool_value(getattr(span_data, "input", None))
payload.tool_result = _serialize_tool_value(getattr(span_data, "output", None))
return payload
def _find_agent_parent_span_id(self, span_id: str | None) -> str | None:
"""Return nearest ancestor span id that represents an agent."""
current = span_id
visited: set[str] = set()
while current:
if current in visited:
break
visited.add(current)
if current in self._agent_content:
return current
current = self._span_parents.get(current)
return None
def _update_agent_aggregate(self, span: Span[Any], payload: ContentPayload) -> None:
"""Accumulate child span content for parent agent span."""
agent_id = self._find_agent_parent_span_id(span.parent_id)
if not agent_id:
return
entry = self._agent_content.setdefault(
agent_id,
{
"input_messages": [],
"output_messages": [],
"system_instructions": [],
"request_model": None,
},
)
if payload.input_messages:
entry["input_messages"] = self._merge_content_sequence(entry["input_messages"], payload.input_messages)
if payload.output_messages:
entry["output_messages"] = self._merge_content_sequence(entry["output_messages"], payload.output_messages)
if payload.system_instructions:
entry["system_instructions"] = self._merge_content_sequence(
entry["system_instructions"], payload.system_instructions
)
if not entry.get("request_model"):
model = getattr(span.span_data, "model", None)
if not model:
response_obj = getattr(span.span_data, "response", None)
model = getattr(response_obj, "model", None)
if model:
entry["request_model"] = model
def _infer_output_type(self, span_data: Any) -> str:
"""Infer gen_ai.output.type for multiple span kinds."""
if _is_instance_of(span_data, FunctionSpanData):
# Tool results are typically JSON
return GenAIOutputType.JSON
if _is_instance_of(span_data, TranscriptionSpanData):
return GenAIOutputType.TEXT
if _is_instance_of(span_data, SpeechSpanData):
return GenAIOutputType.SPEECH
if _is_instance_of(span_data, GuardrailSpanData):
return GenAIOutputType.TEXT
if _is_instance_of(span_data, HandoffSpanData):
return GenAIOutputType.TEXT
# Check for embeddings operation
if _is_instance_of(span_data, GenerationSpanData):
if hasattr(span_data, "embedding_dimension"):
return GenAIOutputType.TEXT # Embeddings are numeric but represented as text
# Generation/Response - check output structure
output = getattr(span_data, "output", None) or getattr(getattr(span_data, "response", None), "output", None)
if isinstance(output, Sequence) and output:
first = output[0]
if isinstance(first, dict):
item_type = first.get("type")
if isinstance(item_type, str):
normalized = item_type.strip().lower()
if normalized in {"image", "image_url"}:
return GenAIOutputType.IMAGE
if normalized in {"audio", "speech", "audio_url"}:
return GenAIOutputType.SPEECH
if normalized in {
"json",
"json_object",
"jsonschema",
"function_call",
"tool_call",
"tool_result",
}:
return GenAIOutputType.JSON
if normalized in {
"text",
"output_text",
"message",
"assistant",
}:
return GenAIOutputType.TEXT
# Conversation style payloads
if "role" in first:
parts = first.get("parts")
if isinstance(parts, Sequence) and parts:
# If all parts are textual (or missing explicit type), treat as text
textual = True
for part in parts:
if isinstance(part, dict):
part_type = str(part.get("type", "")).lower()
if part_type in {"image", "image_url"}:
return GenAIOutputType.IMAGE
if part_type in {
"audio",
"speech",
"audio_url",
}:
return GenAIOutputType.SPEECH
if part_type and part_type not in {
"text",
"output_text",
"assistant",
}:
textual = False
elif not isinstance(part, str):
textual = False
if textual:
return GenAIOutputType.TEXT
content_value = first.get("content")
if isinstance(content_value, str):
return GenAIOutputType.TEXT
# Detect structured data without explicit type
json_like_keys = {
"schema",
"properties",
"arguments",
"result",
"data",
"json",
"output_json",
}
if json_like_keys.intersection(first.keys()):
return GenAIOutputType.JSON
return GenAIOutputType.TEXT
@staticmethod
def _sanitize_usage_payload(usage: Any) -> None:
"""Remove non-spec usage fields (e.g., total tokens) in-place."""
if not usage:
return
if isinstance(usage, dict):
usage.pop("total_tokens", None)
return
if hasattr(usage, "total_tokens"):
try:
usage.total_tokens = None
except Exception: # pragma: no cover - defensive
try:
delattr(usage, "total_tokens")
except Exception: # pragma: no cover - defensive
pass
def _get_span_kind(self, span_data: Any) -> SpanKind:
"""Determine appropriate span kind based on span data type."""
if _is_instance_of(span_data, FunctionSpanData):
return SpanKind.INTERNAL # Tool execution is internal
if _is_instance_of(
span_data,
(
GenerationSpanData,
ResponseSpanData,
TranscriptionSpanData,
SpeechSpanData,
),
):
return SpanKind.CLIENT # API calls to model providers
if _is_instance_of(span_data, AgentSpanData):
return SpanKind.CLIENT
if _is_instance_of(span_data, (GuardrailSpanData, HandoffSpanData)):
return SpanKind.INTERNAL # Agent operations are internal
return SpanKind.INTERNAL
def on_trace_start(self, trace: Trace) -> None:
"""Create root span when trace starts."""
if self._tracer:
attributes = {
GEN_AI_PROVIDER_NAME: self.system_name,
GEN_AI_SYSTEM_KEY: self.system_name,
GEN_AI_OPERATION_NAME: GenAIOperationName.INVOKE_AGENT,
}
# Legacy emission removed
# Add configured agent and server attributes
if self.agent_name:
attributes[GEN_AI_AGENT_NAME] = self.agent_name
if self.agent_id:
attributes[GEN_AI_AGENT_ID] = self.agent_id
if self.agent_description:
attributes[GEN_AI_AGENT_DESCRIPTION] = self.agent_description
attributes.update(self._get_server_attributes())
otel_span = self._tracer.start_span(
name=trace.name,
attributes=attributes,
kind=SpanKind.SERVER, # Root span is typically server
)
self._root_spans[trace.trace_id] = otel_span
def on_trace_end(self, trace: Trace) -> None:
"""End root span when trace ends."""
if root_span := self._root_spans.pop(trace.trace_id, None):
if root_span.is_recording():
root_span.set_status(Status(StatusCode.OK))
root_span.end()
self._cleanup_spans_for_trace(trace.trace_id)
def on_span_start(self, span: Span[Any]) -> None:
"""Start child span for agent span."""
if not self._tracer or not span.started_at:
return
self._span_parents[span.span_id] = span.parent_id
if _is_instance_of(span.span_data, AgentSpanData) and span.span_id not in self._agent_content:
self._agent_content[span.span_id] = {
"input_messages": [],
"output_messages": [],
"system_instructions": [],
"request_model": None,
}
parent_span = self._otel_spans.get(span.parent_id) if span.parent_id else self._root_spans.get(span.trace_id)
context = set_span_in_context(parent_span) if parent_span else None
# Get operation details for span naming
operation_name = self._get_operation_name(span.span_data)
model = getattr(span.span_data, "model", None)
if model is None:
response_obj = getattr(span.span_data, "response", None)
model = getattr(response_obj, "model", None)
# Use configured agent name or get from span data
agent_name = self.agent_name
if not agent_name and _is_instance_of(span.span_data, AgentSpanData):
agent_name = getattr(span.span_data, "name", None)
if not agent_name:
agent_name = self._agent_name_default
tool_name = getattr(span.span_data, "name", None) if _is_instance_of(span.span_data, FunctionSpanData) else None
# Generate spec-compliant span name
span_name = get_span_name(operation_name, model, agent_name, tool_name)
attributes = {
GEN_AI_PROVIDER_NAME: self.system_name,
GEN_AI_SYSTEM_KEY: self.system_name,
GEN_AI_OPERATION_NAME: operation_name,
}
# Legacy emission removed
# Add configured agent and server attributes
agent_name_override = self.agent_name or self._agent_name_default
agent_id_override = self.agent_id or self._agent_id_default
agent_desc_override = self.agent_description or self._agent_description_default
if agent_name_override:
attributes[GEN_AI_AGENT_NAME] = agent_name_override
if agent_id_override:
attributes[GEN_AI_AGENT_ID] = agent_id_override
if agent_desc_override:
attributes[GEN_AI_AGENT_DESCRIPTION] = agent_desc_override
attributes.update(self._get_server_attributes())
otel_span = self._tracer.start_span(
name=span_name,
context=context,
attributes=attributes,
kind=self._get_span_kind(span.span_data),
)
self._otel_spans[span.span_id] = otel_span
self._tokens[span.span_id] = attach(set_span_in_context(otel_span))
def on_span_end(self, span: Span[Any]) -> None:
"""Finalize span with attributes, events, and metrics."""
if token := self._tokens.pop(span.span_id, None):
detach(token)
payload = self._build_content_payload(span)
self._update_agent_aggregate(span, payload)
agent_content = (
self._agent_content.get(span.span_id) if _is_instance_of(span.span_data, AgentSpanData) else None
)
if not (otel_span := self._otel_spans.pop(span.span_id, None)):
# Log attributes even without OTel span
try:
attributes = dict(self._extract_genai_attributes(span, payload, agent_content))
for key, value in attributes.items():
logger.debug("GenAI attr span %s: %s=%s", span.span_id, key, value)
except Exception as e:
logger.warning(
"Failed to extract attributes for span %s: %s",
span.span_id,
e,
)
if _is_instance_of(span.span_data, AgentSpanData):
self._agent_content.pop(span.span_id, None)
self._span_parents.pop(span.span_id, None)
return
try:
# Extract and set attributes
attributes: dict[str, AttributeValue] = {}
# Optimize for non-sampled spans to avoid heavy work
if not otel_span.is_recording():
otel_span.end()
return
for key, value in self._extract_genai_attributes(span, payload, agent_content):
otel_span.set_attribute(key, value)
attributes[key] = value
if _is_instance_of(span.span_data, (GenerationSpanData, ResponseSpanData)):
operation_name = attributes.get(GEN_AI_OPERATION_NAME)
model_for_name = attributes.get(GEN_AI_REQUEST_MODEL) or (attributes.get(GEN_AI_RESPONSE_MODEL))
if operation_name and model_for_name:
agent_name_for_name = attributes.get(GEN_AI_AGENT_NAME)
tool_name_for_name = attributes.get(GEN_AI_TOOL_NAME)
new_name = get_span_name(
operation_name,
model_for_name,
agent_name_for_name,
tool_name_for_name,
)
if new_name != otel_span.name:
otel_span.update_name(new_name)
# Emit span events for captured content when configured
self._emit_content_events(span, otel_span, payload, agent_content)
# Emit operation details event if configured
# Set error status if applicable
otel_span.set_status(status=_get_span_status(span))
if getattr(span, "error", None):
err_obj = span.error
err_type = err_obj.get("type") or err_obj.get("name")
if err_type:
otel_span.set_attribute("error.type", err_type)
# Record metrics before ending span
self._record_metrics(span, attributes)
# End the span
otel_span.end()
except Exception as e:
logger.warning("Failed to enrich span %s: %s", span.span_id, e)
otel_span.set_status(Status(StatusCode.ERROR, str(e)))
otel_span.end()
finally:
if _is_instance_of(span.span_data, AgentSpanData):
self._agent_content.pop(span.span_id, None)
self._span_parents.pop(span.span_id, None)
def shutdown(self) -> None:
"""Clean up resources on shutdown."""
for span_id, otel_span in list(self._otel_spans.items()):
otel_span.set_status(Status(StatusCode.ERROR, "Application shutdown"))
otel_span.end()
for trace_id, root_span in list(self._root_spans.items()):
root_span.set_status(Status(StatusCode.ERROR, "Application shutdown"))
root_span.end()
self._otel_spans.clear()
self._root_spans.clear()
self._tokens.clear()
self._span_parents.clear()
self._agent_content.clear()
def force_flush(self) -> None:
"""Force flush (no-op for this processor)."""
def _get_operation_name(self, span_data: Any) -> str:
"""Determine operation name from span data type."""
if _is_instance_of(span_data, GenerationSpanData):
# Check if it's embeddings
if hasattr(span_data, "embedding_dimension"):
return GenAIOperationName.EMBEDDINGS
# Check if it's chat or completion
if span_data.input:
first_input = span_data.input[0] if span_data.input else None
if isinstance(first_input, dict) and "role" in first_input:
return GenAIOperationName.CHAT
return GenAIOperationName.TEXT_COMPLETION
if _is_instance_of(span_data, AgentSpanData):
# The OpenAI Agents SDK AgentSpanData has no "operation" field;
# agent spans always represent invoke_agent.
return GenAIOperationName.INVOKE_AGENT
if _is_instance_of(span_data, FunctionSpanData):
return GenAIOperationName.EXECUTE_TOOL
if _is_instance_of(span_data, ResponseSpanData):
return GenAIOperationName.CHAT # Response typically from chat
if _is_instance_of(span_data, TranscriptionSpanData):
return GenAIOperationName.TRANSCRIPTION
if _is_instance_of(span_data, SpeechSpanData):
return GenAIOperationName.SPEECH
if _is_instance_of(span_data, GuardrailSpanData):
return GenAIOperationName.GUARDRAIL
if _is_instance_of(span_data, HandoffSpanData):
return GenAIOperationName.HANDOFF
return "unknown"
def _extract_genai_attributes(
self,
span: Span[Any],
payload: ContentPayload,
agent_content: dict[str, list[Any]] | None = None,
) -> Iterator[tuple[str, AttributeValue]]:
"""Yield (attr, value) pairs for GenAI semantic conventions."""
span_data = span.span_data
# Base attributes
yield GEN_AI_PROVIDER_NAME, self.system_name
yield GEN_AI_SYSTEM_KEY, self.system_name
# Legacy emission removed
# Add configured agent attributes (always include when set)
agent_name_override = self.agent_name or self._agent_name_default
agent_id_override = self.agent_id or self._agent_id_default
agent_desc_override = self.agent_description or self._agent_description_default
if agent_name_override:
yield GEN_AI_AGENT_NAME, agent_name_override
if agent_id_override:
yield GEN_AI_AGENT_ID, agent_id_override
if agent_desc_override:
yield GEN_AI_AGENT_DESCRIPTION, agent_desc_override
# Server attributes
for key, value in self._get_server_attributes().items():
yield key, value
# Process different span types
if _is_instance_of(span_data, GenerationSpanData):
yield from self._get_attributes_from_generation_span_data(span_data, payload)
elif _is_instance_of(span_data, AgentSpanData):
yield from self._get_attributes_from_agent_span_data(span_data, agent_content)
elif _is_instance_of(span_data, FunctionSpanData):
yield from self._get_attributes_from_function_span_data(span_data, payload)
elif _is_instance_of(span_data, ResponseSpanData):
yield from self._get_attributes_from_response_span_data(span_data, payload)
elif _is_instance_of(span_data, TranscriptionSpanData):
yield from self._get_attributes_from_transcription_span_data(span_data)
elif _is_instance_of(span_data, SpeechSpanData):
yield from self._get_attributes_from_speech_span_data(span_data)
elif _is_instance_of(span_data, GuardrailSpanData):
yield from self._get_attributes_from_guardrail_span_data(span_data)
elif _is_instance_of(span_data, HandoffSpanData):
yield from self._get_attributes_from_handoff_span_data(span_data)
def _get_attributes_from_generation_span_data(
self, span_data: GenerationSpanData, payload: ContentPayload
) -> Iterator[tuple[str, AttributeValue]]:
"""Extract attributes from generation span."""
# Operation name
operation_name = self._get_operation_name(span_data)
yield GEN_AI_OPERATION_NAME, operation_name
# Model information
if span_data.model:
yield GEN_AI_REQUEST_MODEL, span_data.model
# Check for embeddings-specific attributes
if hasattr(span_data, "embedding_dimension"):
yield (
GEN_AI_EMBEDDINGS_DIMENSION_COUNT,
span_data.embedding_dimension,
)
# Check for data source
if hasattr(span_data, "data_source_id"):
yield GEN_AI_DATA_SOURCE_ID, span_data.data_source_id
finish_reasons: list[Any] = []
if span_data.output:
for part in span_data.output:
if isinstance(part, dict):
fr = part.get("finish_reason") or part.get("stop_reason")
else:
fr = getattr(part, "finish_reason", None)
if fr:
finish_reasons.append(fr if isinstance(fr, str) else str(fr))
if finish_reasons:
yield GEN_AI_RESPONSE_FINISH_REASONS, finish_reasons
# Usage information
if span_data.usage:
usage = span_data.usage
self._sanitize_usage_payload(usage)
if "prompt_tokens" in usage or "input_tokens" in usage:
tokens = usage.get("prompt_tokens") or usage.get("input_tokens")
if tokens is not None:
yield GEN_AI_USAGE_INPUT_TOKENS, tokens
if "completion_tokens" in usage or "output_tokens" in usage:
tokens = usage.get("completion_tokens") or usage.get("output_tokens")
if tokens is not None:
yield GEN_AI_USAGE_OUTPUT_TOKENS, tokens
# Model configuration
if span_data.model_config:
mc = span_data.model_config
param_map = {
"temperature": GEN_AI_REQUEST_TEMPERATURE,
"top_p": GEN_AI_REQUEST_TOP_P,
"top_k": GEN_AI_REQUEST_TOP_K,
"max_tokens": GEN_AI_REQUEST_MAX_TOKENS,
"presence_penalty": GEN_AI_REQUEST_PRESENCE_PENALTY,
"frequency_penalty": GEN_AI_REQUEST_FREQUENCY_PENALTY,
"seed": GEN_AI_REQUEST_SEED,
"n": GEN_AI_REQUEST_CHOICE_COUNT,
"stop": GEN_AI_REQUEST_STOP_SEQUENCES,
"encoding_formats": GEN_AI_REQUEST_ENCODING_FORMATS,
}
for k, attr in param_map.items():
if hasattr(mc, "__contains__") and k in mc:
value = mc[k]
else:
value = getattr(mc, k, None)
if value is not None:
yield attr, value
if hasattr(mc, "get"):
base_url = mc.get("base_url") or mc.get("baseUrl") or mc.get("endpoint")
else:
base_url = (
getattr(mc, "base_url", None) or getattr(mc, "baseUrl", None) or getattr(mc, "endpoint", None)
)
for key, value in _infer_server_attributes(base_url).items():
yield key, value
# Sensitive data capture
if (
self.include_sensitive_data
and self._content_mode.capture_in_span
and self._capture_messages
and payload.input_messages
):
yield (
GEN_AI_INPUT_MESSAGES,
safe_json_dumps(payload.input_messages),
)
if (
self.include_sensitive_data
and self._content_mode.capture_in_span
and self._capture_system_instructions
and payload.system_instructions
):
yield (
GEN_AI_SYSTEM_INSTRUCTIONS,
safe_json_dumps(payload.system_instructions),
)
if (
self.include_sensitive_data
and self._content_mode.capture_in_span
and self._capture_messages
and payload.output_messages
):
yield (
GEN_AI_OUTPUT_MESSAGES,
safe_json_dumps(payload.output_messages),
)
# Output type
yield (
GEN_AI_OUTPUT_TYPE,
normalize_output_type(self._infer_output_type(span_data)),
)
def _merge_content_sequence(
self,
existing: list[Any],
incoming: Sequence[Any],
) -> list[Any]:
"""Merge normalized message/content lists without duplicating snapshots."""
if not incoming:
return existing
incoming_list = [self._clone_message(item) for item in incoming]
if self.include_sensitive_data:
filtered = [msg for msg in incoming_list if not self._is_placeholder_message(msg)]
if filtered:
incoming_list = filtered
if not existing:
return incoming_list
result = [self._clone_message(item) for item in existing]
for idx, new_msg in enumerate(incoming_list):
if idx < len(result):
if (
self.include_sensitive_data
and self._is_placeholder_message(new_msg)
and not self._is_placeholder_message(result[idx])
):
continue
if result[idx] != new_msg:
result[idx] = self._clone_message(new_msg)
else:
if self.include_sensitive_data and self._is_placeholder_message(new_msg):
if (
any(not self._is_placeholder_message(existing_msg) for existing_msg in result)
or new_msg in result
):
continue
result.append(self._clone_message(new_msg))
return result
def _clone_message(self, message: Any) -> Any:
if isinstance(message, dict):
return {
key: self._clone_message(value) if isinstance(value, (dict, list)) else value
for key, value in message.items()
}
if isinstance(message, list):
return [self._clone_message(item) for item in message]
return message
def _is_placeholder_message(self, message: Any) -> bool:
if not isinstance(message, dict):
return False
parts = message.get("parts")
if not isinstance(parts, list) or not parts:
return False
for part in parts:
if not isinstance(part, dict) or part.get("type") != "text" or part.get("content") != "readacted":
return False
return True
def _get_attributes_from_agent_span_data(
self,
span_data: AgentSpanData,
agent_content: dict[str, list[Any]] | None = None,
) -> Iterator[tuple[str, AttributeValue]]:
"""Extract attributes from agent span."""
yield GEN_AI_OPERATION_NAME, self._get_operation_name(span_data)
name = self.agent_name or getattr(span_data, "name", None) or self._agent_name_default
if name:
yield GEN_AI_AGENT_NAME, name
# agent_id and description are not available on the OpenAI Agents SDK
# AgentSpanData; only use user-configured overrides.
agent_id = self.agent_id or self._agent_id_default
if agent_id:
yield GEN_AI_AGENT_ID, agent_id
description = self.agent_description or self._agent_description_default
if description:
yield GEN_AI_AGENT_DESCRIPTION, description
# The OpenAI Agents SDK AgentSpanData has no "model" field; fall back to
# the model aggregated from child generation/response spans.
model = None
if agent_content:
model = agent_content.get("request_model")
if model:
yield GEN_AI_REQUEST_MODEL, model
if hasattr(span_data, "conversation_id") and span_data.conversation_id:
yield GEN_AI_CONVERSATION_ID, span_data.conversation_id
# Agent definitions
if self._capture_tool_definitions and hasattr(span_data, "agent_definitions"):
yield (
GEN_AI_ORCHESTRATOR_AGENT_DEFINITIONS,
safe_json_dumps(span_data.agent_definitions),
)
# System instructions from agent definitions
if self._capture_system_instructions and hasattr(span_data, "agent_definitions"):
try:
defs = span_data.agent_definitions
if isinstance(defs, (list, tuple)):
collected: list[dict[str, str]] = []
for d in defs:
if isinstance(d, dict):
msgs = d.get("messages") or d.get("system_messages")
if isinstance(msgs, (list, tuple)):
collected.extend(self._collect_system_instructions(msgs))
if collected:
yield (
GEN_AI_SYSTEM_INSTRUCTIONS,
safe_json_dumps(collected),
)
except Exception:
pass
if (
self.include_sensitive_data
and self._content_mode.capture_in_span
and self._capture_messages
and agent_content
):
if agent_content.get("input_messages"):
yield (
GEN_AI_INPUT_MESSAGES,
safe_json_dumps(agent_content["input_messages"]),
)
if agent_content.get("output_messages"):
yield (
GEN_AI_OUTPUT_MESSAGES,
safe_json_dumps(agent_content["output_messages"]),
)
if (
self.include_sensitive_data
and self._content_mode.capture_in_span
and self._capture_system_instructions
and agent_content
and agent_content.get("system_instructions")
):
yield (
GEN_AI_SYSTEM_INSTRUCTIONS,
safe_json_dumps(agent_content["system_instructions"]),
)
yield (
GEN_AI_OUTPUT_TYPE,
normalize_output_type(self._infer_output_type(span_data)),
)
def _get_attributes_from_function_span_data(
self, span_data: FunctionSpanData, payload: ContentPayload
) -> Iterator[tuple[str, AttributeValue]]:
"""Extract attributes from function/tool span."""
yield GEN_AI_OPERATION_NAME, GenAIOperationName.EXECUTE_TOOL
if span_data.name:
yield GEN_AI_TOOL_NAME, span_data.name
# Tool type - validate and normalize
tool_type = "function" # Default for function spans
if hasattr(span_data, "tool_type"):
tool_type = span_data.tool_type
yield GEN_AI_TOOL_TYPE, validate_tool_type(tool_type)
if hasattr(span_data, "call_id") and span_data.call_id:
yield GEN_AI_TOOL_CALL_ID, span_data.call_id
if hasattr(span_data, "description") and span_data.description:
yield GEN_AI_TOOL_DESCRIPTION, span_data.description
# Tool definitions
if self._capture_tool_definitions and hasattr(span_data, "tool_definitions"):
yield (
GEN_AI_TOOL_DEFINITIONS,
safe_json_dumps(span_data.tool_definitions),
)
# Tool input/output (sensitive)
if self.include_sensitive_data and self._content_mode.capture_in_span and payload.tool_arguments is not None:
yield GEN_AI_TOOL_CALL_ARGUMENTS, payload.tool_arguments
if self.include_sensitive_data and self._content_mode.capture_in_span and payload.tool_result is not None:
yield GEN_AI_TOOL_CALL_RESULT, payload.tool_result
yield (
GEN_AI_OUTPUT_TYPE,
normalize_output_type(self._infer_output_type(span_data)),
)
def _get_attributes_from_response_span_data(
self, span_data: ResponseSpanData, payload: ContentPayload
) -> Iterator[tuple[str, AttributeValue]]:
"""Extract attributes from response span."""
yield GEN_AI_OPERATION_NAME, GenAIOperationName.CHAT
# Response information
if span_data.response:
if hasattr(span_data.response, "id") and span_data.response.id:
yield GEN_AI_RESPONSE_ID, span_data.response.id
# Model from response
if hasattr(span_data.response, "model") and span_data.response.model:
yield GEN_AI_RESPONSE_MODEL, span_data.response.model
if not getattr(span_data, "model", None):
yield GEN_AI_REQUEST_MODEL, span_data.response.model
# Finish reasons
finish_reasons = []
if hasattr(span_data.response, "output") and span_data.response.output:
for part in span_data.response.output:
if isinstance(part, dict):
fr = part.get("finish_reason") or part.get("stop_reason")
else:
fr = getattr(part, "finish_reason", None)
if fr:
finish_reasons.append(fr)
if finish_reasons:
yield GEN_AI_RESPONSE_FINISH_REASONS, finish_reasons
# Usage from response
if hasattr(span_data.response, "usage") and span_data.response.usage:
usage = span_data.response.usage
self._sanitize_usage_payload(usage)
input_tokens = getattr(usage, "input_tokens", None)
if input_tokens is None:
input_tokens = getattr(usage, "prompt_tokens", None)
if input_tokens is not None:
yield GEN_AI_USAGE_INPUT_TOKENS, input_tokens
output_tokens = getattr(usage, "output_tokens", None)
if output_tokens is None:
output_tokens = getattr(usage, "completion_tokens", None)
if output_tokens is not None:
yield GEN_AI_USAGE_OUTPUT_TOKENS, output_tokens
# Tool definitions from response
if self._capture_tool_definitions and hasattr(span_data.response, "tools"):
yield (
GEN_AI_TOOL_DEFINITIONS,
safe_json_dumps(
list(
map(
lambda tool: tool.to_dict(),
span_data.response.tools,
)
)
),
)
# Input/output messages
if (
self.include_sensitive_data
and self._content_mode.capture_in_span
and self._capture_messages
and payload.input_messages
):
yield (
GEN_AI_INPUT_MESSAGES,
safe_json_dumps(payload.input_messages),
)
if (
self.include_sensitive_data
and self._content_mode.capture_in_span
and self._capture_system_instructions
and payload.system_instructions
):
yield (
GEN_AI_SYSTEM_INSTRUCTIONS,
safe_json_dumps(payload.system_instructions),
)
if (
self.include_sensitive_data
and self._content_mode.capture_in_span
and self._capture_messages
and payload.output_messages
):
yield (
GEN_AI_OUTPUT_MESSAGES,
safe_json_dumps(payload.output_messages),
)
yield (
GEN_AI_OUTPUT_TYPE,
normalize_output_type(self._infer_output_type(span_data)),
)
def _get_attributes_from_transcription_span_data(
self, span_data: TranscriptionSpanData
) -> Iterator[tuple[str, AttributeValue]]:
"""Extract attributes from transcription span."""
yield GEN_AI_OPERATION_NAME, GenAIOperationName.TRANSCRIPTION
if hasattr(span_data, "model") and span_data.model:
yield GEN_AI_REQUEST_MODEL, span_data.model
# Audio format
if hasattr(span_data, "format") and span_data.format:
yield "gen_ai.audio.input.format", span_data.format
# Transcript (sensitive)
if (
self.include_sensitive_data
and self._content_mode.capture_in_span
and self._capture_messages
and hasattr(span_data, "transcript")
):
yield "gen_ai.transcription.text", span_data.transcript
yield (
GEN_AI_OUTPUT_TYPE,
normalize_output_type(self._infer_output_type(span_data)),
)
def _get_attributes_from_speech_span_data(self, span_data: SpeechSpanData) -> Iterator[tuple[str, AttributeValue]]:
"""Extract attributes from speech span."""
yield GEN_AI_OPERATION_NAME, GenAIOperationName.SPEECH
if hasattr(span_data, "model") and span_data.model:
yield GEN_AI_REQUEST_MODEL, span_data.model
if hasattr(span_data, "voice") and span_data.voice:
yield "gen_ai.speech.voice", span_data.voice
if hasattr(span_data, "format") and span_data.format:
yield "gen_ai.audio.output.format", span_data.format
# Input text (sensitive)
if (
self.include_sensitive_data
and self._content_mode.capture_in_span
and self._capture_messages
and hasattr(span_data, "input_text")
):
yield "gen_ai.speech.input_text", span_data.input_text
yield (
GEN_AI_OUTPUT_TYPE,
normalize_output_type(self._infer_output_type(span_data)),
)
def _get_attributes_from_guardrail_span_data(
self, span_data: GuardrailSpanData
) -> Iterator[tuple[str, AttributeValue]]:
"""Extract attributes from guardrail span."""
yield GEN_AI_OPERATION_NAME, GenAIOperationName.GUARDRAIL
if span_data.name:
yield GEN_AI_GUARDRAIL_NAME, span_data.name
yield GEN_AI_GUARDRAIL_TRIGGERED, span_data.triggered
yield (
GEN_AI_OUTPUT_TYPE,
normalize_output_type(self._infer_output_type(span_data)),
)
def _get_attributes_from_handoff_span_data(
self, span_data: HandoffSpanData
) -> Iterator[tuple[str, AttributeValue]]:
"""Extract attributes from handoff span."""
yield GEN_AI_OPERATION_NAME, GenAIOperationName.HANDOFF
if span_data.from_agent:
yield GEN_AI_HANDOFF_FROM_AGENT, span_data.from_agent
if span_data.to_agent:
yield GEN_AI_HANDOFF_TO_AGENT, span_data.to_agent
yield (
GEN_AI_OUTPUT_TYPE,
normalize_output_type(self._infer_output_type(span_data)),
)
def _cleanup_spans_for_trace(self, trace_id: str) -> None:
"""Clean up spans for a trace to prevent memory leaks."""
spans_to_remove = [span_id for span_id in self._otel_spans.keys() if span_id.startswith(trace_id)]
for span_id in spans_to_remove:
if otel_span := self._otel_spans.pop(span_id, None):
otel_span.set_status(Status(StatusCode.ERROR, "Trace ended before span completion"))
otel_span.end()
self._tokens.pop(span_id, None)
__all__ = [
"ContentCaptureMode",
"ContentPayload",
"GenAIEvaluationAttributes",
"GenAIOperationName",
"GenAIOutputType",
"GenAIProvider",
"GenAISemanticProcessor",
"GenAIToolType",
"normalize_output_type",
"normalize_provider",
"validate_tool_type",
]
version.py 0000664 0000000 0000000 00000000147 15270700723 0051027 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-openai-agents-v2/src/opentelemetry/instrumentation/openai_agents # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
__version__ = "0.2.0.dev"
tests/ 0000775 0000000 0000000 00000000000 15270700723 0036366 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-openai-agents-v2 conftest.py 0000664 0000000 0000000 00000001202 15270700723 0040560 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-openai-agents-v2/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
from __future__ import annotations
import sys
from pathlib import Path
TESTS_ROOT = Path(__file__).resolve().parent
GENAI_ROOT = TESTS_ROOT.parent
REPO_ROOT = GENAI_ROOT.parent
PROJECT_ROOT = REPO_ROOT.parent
for path in (
PROJECT_ROOT / "opentelemetry-instrumentation" / "src",
GENAI_ROOT / "src",
PROJECT_ROOT / "util" / "opentelemetry-util-genai" / "src",
REPO_ROOT / "openai_agents_lib",
REPO_ROOT / "openai_lib",
TESTS_ROOT / "stubs",
):
path_str = str(path)
if path_str not in sys.path:
sys.path.insert(0, path_str)
requirements.latest.txt 0000664 0000000 0000000 00000003454 15270700723 0043153 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-openai-agents-v2/tests # Copyright The OpenTelemetry Authors
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ********************************
# WARNING: NOT HERMETIC !!!!!!!!!!
# ********************************
#
# This "requirements.txt" is installed in conjunction
# with multiple other dependencies in the top-level "tox.ini"
# file. In particular, please see:
#
# openai_agents-latest: {[testenv]test_deps}
# openai_agents-latest: -r {toxinidir}/instrumentation-genai/opentelemetry-instrumentation-openai-agents-v2/tests/requirements.latest.txt
#
# This provides additional dependencies, namely:
#
# opentelemetry-api
# opentelemetry-sdk
# opentelemetry-semantic-conventions
#
# ... with a "dev" version based on the latest distribution.
# This variant of the requirements aims to test the system using
# the newest supported version of external dependencies.
openai-agents==0.3.3
pydantic>=2.10,<3
httpx==0.27.2
Deprecated==1.2.14
importlib-metadata==6.11.0
packaging==24.0
pytest==7.4.4
pytest-asyncio==0.21.0
wrapt==1.16.0
# test with the latest version of opentelemetry-api, sdk, and semantic conventions
grpcio>=1.60.0; implementation_name != "pypy"
grpcio<1.60.0; implementation_name == "pypy"
-e opentelemetry-instrumentation
-e instrumentation-genai/opentelemetry-instrumentation-openai-agents-v2
-e util/opentelemetry-util-genai
requirements.oldest.txt 0000664 0000000 0000000 00000002644 15270700723 0043151 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-openai-agents-v2/tests # Copyright The OpenTelemetry Authors
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# This variant of the requirements aims to test the system using
# the oldest supported version of external dependencies.
openai-agents==0.3.3
pydantic>=2.10,<3
httpx==0.27.2
Deprecated==1.2.14
importlib-metadata==6.11.0
packaging==24.0
pytest==7.4.4
pytest-asyncio==0.21.0
wrapt==1.16.0
opentelemetry-exporter-otlp-proto-grpc~=1.30
opentelemetry-exporter-otlp-proto-http~=1.30
opentelemetry-api==1.40 # when updating, also update in pyproject.toml
opentelemetry-sdk==1.40 # when updating, also update in pyproject.toml
opentelemetry-semantic-conventions==0.61b0 # when updating, also update in pyproject.toml
opentelemetry-util-genai==0.4b.0 # when updating, also update in pyproject.toml
grpcio>=1.60.0; implementation_name != "pypy"
grpcio<1.60.0; implementation_name == "pypy"
-e instrumentation-genai/opentelemetry-instrumentation-openai-agents-v2
stubs/ 0000775 0000000 0000000 00000000000 15270700723 0037526 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-openai-agents-v2/tests agents/ 0000775 0000000 0000000 00000000000 15270700723 0041007 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-openai-agents-v2/tests/stubs __init__.py 0000664 0000000 0000000 00000000146 15270700723 0043121 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-openai-agents-v2/tests/stubs/agents # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
# Stub package for tests
tracing/ 0000775 0000000 0000000 00000000000 15270700723 0042436 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-openai-agents-v2/tests/stubs/agents __init__.py 0000664 0000000 0000000 00000013637 15270700723 0044561 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-openai-agents-v2/tests/stubs/agents/tracing # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
# pylint: skip-file
from __future__ import annotations
from collections.abc import Mapping, Sequence
from contextlib import contextmanager
from dataclasses import dataclass
from itertools import count
from typing import Any
from .processor_interface import TracingProcessor
from .spans import Span
from .traces import Trace
SPAN_TYPE_AGENT = "agent"
SPAN_TYPE_FUNCTION = "function"
SPAN_TYPE_GENERATION = "generation"
SPAN_TYPE_RESPONSE = "response"
__all__ = [
"AgentSpanData",
"FunctionSpanData",
"GenerationSpanData",
"ResponseSpanData",
"TraceProvider",
"agent_span",
"function_span",
"generation_span",
"get_trace_provider",
"response_span",
"set_trace_processors",
"trace",
]
@dataclass
class AgentSpanData:
name: str | None = None
handoffs: list[str] | None = None
tools: list[str] | None = None
output_type: str | None = None
@property
def type(self) -> str:
return SPAN_TYPE_AGENT
@dataclass
class FunctionSpanData:
name: str | None = None
input: Any = None
output: Any = None
@property
def type(self) -> str:
return SPAN_TYPE_FUNCTION
@dataclass
class GenerationSpanData:
input: Sequence[Mapping[str, Any]] | None = None
output: Sequence[Mapping[str, Any]] | None = None
model: str | None = None
model_config: Mapping[str, Any] | None = None
usage: Mapping[str, Any] | None = None
@property
def type(self) -> str:
return SPAN_TYPE_GENERATION
@dataclass
class ResponseSpanData:
response: Any = None
@property
def type(self) -> str:
return SPAN_TYPE_RESPONSE
class _ProcessorFanout(TracingProcessor):
def __init__(self) -> None:
self._processors: list[TracingProcessor] = []
def add_tracing_processor(self, processor: TracingProcessor) -> None:
self._processors.append(processor)
def set_processors(self, processors: list[TracingProcessor]) -> None:
self._processors = list(processors)
def on_trace_start(self, trace: Trace) -> None:
for processor in list(self._processors):
processor.on_trace_start(trace)
def on_trace_end(self, trace: Trace) -> None:
for processor in list(self._processors):
processor.on_trace_end(trace)
def on_span_start(self, span: Span) -> None:
for processor in list(self._processors):
processor.on_span_start(span)
def on_span_end(self, span: Span) -> None:
for processor in list(self._processors):
processor.on_span_end(span)
def shutdown(self) -> None:
for processor in list(self._processors):
processor.shutdown()
def force_flush(self) -> None:
for processor in list(self._processors):
processor.force_flush()
class TraceProvider:
def __init__(self) -> None:
self._multi_processor = _ProcessorFanout()
self._ids = count(1)
def register_processor(self, processor: TracingProcessor) -> None:
self._multi_processor.add_tracing_processor(processor)
def set_processors(self, processors: list[TracingProcessor]) -> None:
self._multi_processor.set_processors(processors)
def create_trace(
self,
name: str,
trace_id: str | None = None,
group_id: str | None = None,
metadata: Mapping[str, Any] | None = None,
disabled: bool = False,
) -> Trace:
trace_id = trace_id or f"trace_{next(self._ids)}"
return Trace(name, trace_id, self._multi_processor)
def create_span(
self,
span_data: Any,
span_id: str | None = None,
parent: Trace | Span | None = None,
disabled: bool = False,
) -> Span:
span_id = span_id or f"span_{next(self._ids)}"
if isinstance(parent, Span):
trace_id = parent.trace_id
parent_id = parent.span_id
elif isinstance(parent, Trace):
trace_id = parent.trace_id
parent_id = None
else:
trace_id = f"trace_{next(self._ids)}"
parent_id = None
return Span(trace_id, span_id, span_data, parent_id, self._multi_processor)
def shutdown(self) -> None:
self._multi_processor.shutdown()
_PROVIDER = TraceProvider()
_CURRENT_TRACE: Trace | None = None
def get_trace_provider() -> TraceProvider:
return _PROVIDER
def set_trace_processors(processors: list[TracingProcessor]) -> None:
_PROVIDER.set_processors(processors)
@contextmanager
def trace(name: str, **kwargs: Any):
global _CURRENT_TRACE
trace_obj = _PROVIDER.create_trace(name, **kwargs)
previous = _CURRENT_TRACE
_CURRENT_TRACE = trace_obj
trace_obj.start()
try:
yield trace_obj
finally:
trace_obj.finish()
_CURRENT_TRACE = previous
@contextmanager
def generation_span(**kwargs: Any):
data = GenerationSpanData(**kwargs)
span = _PROVIDER.create_span(data, parent=_CURRENT_TRACE)
span.start()
try:
yield span
finally:
span.finish()
@contextmanager
def agent_span(
name: str,
handoffs: list[str] | None = None,
tools: list[str] | None = None,
output_type: str | None = None,
**kwargs: Any,
):
data = AgentSpanData(name=name, handoffs=handoffs, tools=tools, output_type=output_type)
span = _PROVIDER.create_span(data, parent=_CURRENT_TRACE)
span.start()
try:
yield span
finally:
span.finish()
@contextmanager
def function_span(**kwargs: Any):
data = FunctionSpanData(**kwargs)
span = _PROVIDER.create_span(data, parent=_CURRENT_TRACE)
span.start()
try:
yield span
finally:
span.finish()
@contextmanager
def response_span(**kwargs: Any):
data = ResponseSpanData(**kwargs)
span = _PROVIDER.create_span(data, parent=_CURRENT_TRACE)
span.start()
try:
yield span
finally:
span.finish()
processor_interface.py 0000664 0000000 0000000 00000001116 15270700723 0047046 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-openai-agents-v2/tests/stubs/agents/tracing # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
from __future__ import annotations
class TracingProcessor:
def on_trace_start(self, trace): # pragma: no cover - stub
pass
def on_trace_end(self, trace): # pragma: no cover - stub
pass
def on_span_start(self, span): # pragma: no cover - stub
pass
def on_span_end(self, span): # pragma: no cover - stub
pass
def shutdown(self) -> None: # pragma: no cover - stub
pass
def force_flush(self) -> None: # pragma: no cover - stub
pass
spans.py 0000664 0000000 0000000 00000002210 15270700723 0044127 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-openai-agents-v2/tests/stubs/agents/tracing # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
from __future__ import annotations
from datetime import datetime
from typing import Any
class Span:
def __init__(
self,
trace_id: str,
span_id: str,
span_data: Any,
parent_id: str | None,
processor,
) -> None:
self.trace_id = trace_id
self.span_id = span_id
self.span_data = span_data
self.parent_id = parent_id
self.started_at: str | None = None
self.ended_at: str | None = None
self.error = None
self._processor = processor
def start(self) -> None:
if self.started_at is not None:
return
self.started_at = datetime.utcnow().isoformat() + "Z"
self._processor.on_span_start(self)
def finish(self) -> None:
if self.ended_at is not None:
return
self.ended_at = datetime.utcnow().isoformat() + "Z"
self._processor.on_span_end(self)
def __enter__(self) -> Span:
self.start()
return self
def __exit__(self, exc_type, exc, tb) -> None:
self.finish()
traces.py 0000664 0000000 0000000 00000001656 15270700723 0044301 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-openai-agents-v2/tests/stubs/agents/tracing # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
from __future__ import annotations
from datetime import datetime
class Trace:
def __init__(self, name: str, trace_id: str, processor) -> None:
self.name = name
self.trace_id = trace_id
self._processor = processor
self.started_at: str | None = None
self.ended_at: str | None = None
def start(self) -> None:
if self.started_at is not None:
return
self.started_at = datetime.utcnow().isoformat() + "Z"
self._processor.on_trace_start(self)
def finish(self) -> None:
if self.ended_at is not None:
return
self.ended_at = datetime.utcnow().isoformat() + "Z"
self._processor.on_trace_end(self)
def __enter__(self) -> Trace:
self.start()
return self
def __exit__(self, exc_type, exc, tb) -> None:
self.finish()
opentelemetry/ 0000775 0000000 0000000 00000000000 15270700723 0042422 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-openai-agents-v2/tests/stubs instrumentation/ 0000775 0000000 0000000 00000000000 15270700723 0045665 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-openai-agents-v2/tests/stubs/opentelemetry instrumentor.py 0000664 0000000 0000000 00000001377 15270700723 0051020 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-openai-agents-v2/tests/stubs/opentelemetry/instrumentation # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
# pylint: skip-file
from __future__ import annotations
from collections.abc import Collection
class BaseInstrumentor:
def __init__(self) -> None:
pass
def instrument(self, **kwargs) -> None:
self._instrument(**kwargs)
def uninstrument(self, **kwargs) -> None:
self._uninstrument(**kwargs)
# Subclasses override
def _instrument(self, **kwargs) -> None: # pragma: no cover - stub
raise NotImplementedError
def _uninstrument(self, **kwargs) -> None: # pragma: no cover - stub
raise NotImplementedError
def instrumentation_dependencies(
self,
) -> Collection[str]: # pragma: no cover
return []
wrapt.py 0000664 0000000 0000000 00000001107 15270700723 0041234 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-openai-agents-v2/tests/stubs # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
class ObjectProxy:
"""Minimal stand-in for wrapt.ObjectProxy used in tests."""
def __init__(self, wrapped):
self.__wrapped__ = wrapped
def __getattr__(self, item):
return getattr(self.__wrapped__, item)
def __setattr__(self, key, value):
if key == "__wrapped__":
super().__setattr__(key, value)
else:
setattr(self.__wrapped__, key, value)
def __call__(self, *args, **kwargs):
return self.__wrapped__(*args, **kwargs)
test_tracer.py 0000664 0000000 0000000 00000042347 15270700723 0041271 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-openai-agents-v2/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
# pylint: disable=wrong-import-position,wrong-import-order,import-error,no-name-in-module,unexpected-keyword-arg,no-value-for-parameter,redefined-outer-name
from __future__ import annotations
import json
import sys
from pathlib import Path
from types import SimpleNamespace
from typing import Any
TESTS_ROOT = Path(__file__).resolve().parent
stub_path = TESTS_ROOT / "stubs"
if str(stub_path) not in sys.path:
sys.path.insert(0, str(stub_path))
sys.modules.pop("agents", None)
sys.modules.pop("agents.tracing", None)
import agents.tracing as agents_tracing # noqa: E402
from agents.tracing import ( # noqa: E402
agent_span,
function_span,
generation_span,
response_span,
set_trace_processors,
trace,
)
from openai.types.responses import FunctionTool # noqa: E402
from opentelemetry.instrumentation.openai_agents import ( # noqa: E402
OpenAIAgentsInstrumentor,
)
from opentelemetry.instrumentation.openai_agents.span_processor import ( # noqa: E402
ContentPayload,
GenAISemanticProcessor,
)
from opentelemetry.sdk.trace import TracerProvider # noqa: E402
try:
from opentelemetry.sdk.trace.export import ( # type: ignore[attr-defined]
InMemorySpanExporter,
SimpleSpanProcessor,
)
except ImportError: # pragma: no cover - support older/newer SDK layouts
from opentelemetry.sdk.trace.export import (
SimpleSpanProcessor,
)
from opentelemetry.sdk.trace.export.in_memory_span_exporter import (
InMemorySpanExporter,
)
from opentelemetry.semconv._incubating.attributes import ( # noqa: E402
gen_ai_attributes as GenAI,
)
from opentelemetry.semconv._incubating.attributes import ( # noqa: E402
server_attributes as ServerAttributes,
)
from opentelemetry.trace import SpanKind # noqa: E402
GEN_AI_PROVIDER_NAME = GenAI.GEN_AI_PROVIDER_NAME
GEN_AI_INPUT_MESSAGES = getattr(GenAI, "GEN_AI_INPUT_MESSAGES", "gen_ai.input.messages")
GEN_AI_OUTPUT_MESSAGES = getattr(GenAI, "GEN_AI_OUTPUT_MESSAGES", "gen_ai.output.messages")
GEN_AI_TOOL_DEFINITIONS = getattr(GenAI, "GEN_AI_TOOL_DEFINITIONS", "gen_ai.tool.definitions")
def _instrument_with_provider(**instrument_kwargs):
set_trace_processors([])
provider = TracerProvider()
exporter = InMemorySpanExporter()
provider.add_span_processor(SimpleSpanProcessor(exporter))
instrumentor = OpenAIAgentsInstrumentor()
instrumentor.instrument(tracer_provider=provider, **instrument_kwargs)
return instrumentor, exporter
def test_generation_span_creates_client_span():
instrumentor, exporter = _instrument_with_provider()
try:
with trace("workflow"):
with generation_span(
input=[{"role": "user", "content": "hi"}],
model="gpt-4o-mini",
model_config={
"temperature": 0.2,
"base_url": "https://api.openai.com",
},
usage={"input_tokens": 12, "output_tokens": 3},
):
pass
spans = exporter.get_finished_spans()
client_span = next(span for span in spans if span.kind is SpanKind.CLIENT)
assert client_span.attributes[GEN_AI_PROVIDER_NAME] == "openai"
assert client_span.attributes[GenAI.GEN_AI_OPERATION_NAME] == "chat"
assert client_span.attributes[GenAI.GEN_AI_REQUEST_MODEL] == "gpt-4o-mini"
assert client_span.name == "chat gpt-4o-mini"
assert client_span.attributes[GenAI.GEN_AI_USAGE_INPUT_TOKENS] == 12
assert client_span.attributes[GenAI.GEN_AI_USAGE_OUTPUT_TOKENS] == 3
assert client_span.attributes[ServerAttributes.SERVER_ADDRESS] == "api.openai.com"
finally:
instrumentor.uninstrument()
exporter.clear()
def test_generation_span_without_roles_uses_text_completion():
instrumentor, exporter = _instrument_with_provider()
try:
with trace("workflow"):
with generation_span(
input=[{"content": "tell me a joke"}],
model="gpt-4o-mini",
model_config={"temperature": 0.7},
):
pass
spans = exporter.get_finished_spans()
completion_span = next(
span
for span in spans
if span.attributes[GenAI.GEN_AI_OPERATION_NAME] == GenAI.GenAiOperationNameValues.TEXT_COMPLETION.value
)
assert completion_span.kind is SpanKind.CLIENT
assert completion_span.name == "text_completion gpt-4o-mini"
assert completion_span.attributes[GenAI.GEN_AI_REQUEST_MODEL] == "gpt-4o-mini"
finally:
instrumentor.uninstrument()
exporter.clear()
def test_function_span_records_tool_attributes():
instrumentor, exporter = _instrument_with_provider()
try:
with trace("workflow"):
with function_span(name="fetch_weather", input='{"city": "Paris"}'):
pass
spans = exporter.get_finished_spans()
tool_span = next(span for span in spans if span.kind is SpanKind.INTERNAL)
assert tool_span.attributes[GenAI.GEN_AI_OPERATION_NAME] == "execute_tool"
assert tool_span.attributes[GenAI.GEN_AI_TOOL_NAME] == "fetch_weather"
assert tool_span.attributes[GenAI.GEN_AI_TOOL_TYPE] == "function"
assert tool_span.attributes[GEN_AI_PROVIDER_NAME] == "openai"
finally:
instrumentor.uninstrument()
exporter.clear()
def test_agent_invoke_span_records_attributes():
instrumentor, exporter = _instrument_with_provider()
try:
with trace("workflow"):
with agent_span(
name="support_bot",
handoffs=["escalation_bot"],
tools=["search"],
output_type="str",
):
pass
spans = exporter.get_finished_spans()
invoke_span = next(
span
for span in spans
if span.attributes[GenAI.GEN_AI_OPERATION_NAME] == GenAI.GenAiOperationNameValues.INVOKE_AGENT.value
)
assert invoke_span.kind is SpanKind.CLIENT
assert invoke_span.name == "invoke_agent support_bot"
assert invoke_span.attributes[GEN_AI_PROVIDER_NAME] == "openai"
assert invoke_span.attributes[GenAI.GEN_AI_AGENT_NAME] == "support_bot"
finally:
instrumentor.uninstrument()
exporter.clear()
def _placeholder_message() -> dict[str, Any]:
return {
"role": "user",
"parts": [{"type": "text", "content": "readacted"}],
}
def test_normalize_messages_skips_empty_when_sensitive_enabled():
processor = GenAISemanticProcessor(metrics_enabled=False)
normalized = processor._normalize_messages_to_role_parts([{"role": "user", "content": None}])
assert not normalized
def test_normalize_messages_emits_placeholder_when_sensitive_disabled():
processor = GenAISemanticProcessor(include_sensitive_data=False, metrics_enabled=False)
normalized = processor._normalize_messages_to_role_parts([{"role": "user", "content": None}])
assert normalized == [_placeholder_message()]
def test_agent_content_aggregation_skips_duplicate_snapshots():
processor = GenAISemanticProcessor(metrics_enabled=False)
agent_id = "agent-span"
processor._agent_content[agent_id] = {
"input_messages": [],
"output_messages": [],
"system_instructions": [],
}
payload = ContentPayload(
input_messages=[
{"role": "user", "parts": [{"type": "text", "content": "hello"}]},
{
"role": "user",
"parts": [{"type": "text", "content": "readacted"}],
},
]
)
processor._update_agent_aggregate(
SimpleNamespace(span_id="child-1", parent_id=agent_id, span_data=None),
payload,
)
processor._update_agent_aggregate(
SimpleNamespace(span_id="child-2", parent_id=agent_id, span_data=None),
payload,
)
aggregated = processor._agent_content[agent_id]["input_messages"]
assert aggregated == [{"role": "user", "parts": [{"type": "text", "content": "hello"}]}]
# ensure data copied rather than reused to prevent accidental mutation
assert aggregated is not payload.input_messages
def test_agent_content_aggregation_filters_placeholder_append_when_sensitive():
processor = GenAISemanticProcessor(metrics_enabled=False)
agent_id = "agent-span"
processor._agent_content[agent_id] = {
"input_messages": [],
"output_messages": [],
"system_instructions": [],
}
initial_payload = ContentPayload(input_messages=[{"role": "user", "parts": [{"type": "text", "content": "hello"}]}])
processor._update_agent_aggregate(
SimpleNamespace(span_id="child-1", parent_id=agent_id, span_data=None),
initial_payload,
)
placeholder_payload = ContentPayload(input_messages=[_placeholder_message()])
processor._update_agent_aggregate(
SimpleNamespace(span_id="child-2", parent_id=agent_id, span_data=None),
placeholder_payload,
)
aggregated = processor._agent_content[agent_id]["input_messages"]
assert aggregated == [{"role": "user", "parts": [{"type": "text", "content": "hello"}]}]
def test_agent_content_aggregation_retains_placeholder_when_sensitive_disabled():
processor = GenAISemanticProcessor(include_sensitive_data=False, metrics_enabled=False)
agent_id = "agent-span"
processor._agent_content[agent_id] = {
"input_messages": [],
"output_messages": [],
"system_instructions": [],
}
placeholder_payload = ContentPayload(input_messages=[_placeholder_message()])
processor._update_agent_aggregate(
SimpleNamespace(span_id="child-1", parent_id=agent_id, span_data=None),
placeholder_payload,
)
aggregated = processor._agent_content[agent_id]["input_messages"]
assert aggregated == [_placeholder_message()]
def test_agent_content_aggregation_appends_new_messages_once():
processor = GenAISemanticProcessor(metrics_enabled=False)
agent_id = "agent-span"
processor._agent_content[agent_id] = {
"input_messages": [],
"output_messages": [],
"system_instructions": [],
}
initial_payload = ContentPayload(input_messages=[{"role": "user", "parts": [{"type": "text", "content": "hello"}]}])
processor._update_agent_aggregate(
SimpleNamespace(span_id="child-1", parent_id=agent_id, span_data=None),
initial_payload,
)
extended_messages = [
{"role": "user", "parts": [{"type": "text", "content": "hello"}]},
{
"role": "assistant",
"parts": [{"type": "text", "content": "hi there"}],
},
]
extended_payload = ContentPayload(input_messages=extended_messages)
processor._update_agent_aggregate(
SimpleNamespace(span_id="child-2", parent_id=agent_id, span_data=None),
extended_payload,
)
aggregated = processor._agent_content[agent_id]["input_messages"]
assert aggregated == extended_messages
assert extended_payload.input_messages == extended_messages
def test_agent_span_collects_child_messages():
instrumentor, exporter = _instrument_with_provider()
try:
provider = agents_tracing.get_trace_provider()
with trace("workflow") as workflow:
agent_span_obj = provider.create_span(
agents_tracing.AgentSpanData(name="helper"),
parent=workflow,
)
agent_span_obj.start()
generation = agents_tracing.GenerationSpanData(
input=[{"role": "user", "content": "hi"}],
output=[{"type": "text", "content": "hello"}],
model="gpt-4o-mini",
)
gen_span = provider.create_span(generation, parent=agent_span_obj)
gen_span.start()
gen_span.finish()
agent_span_obj.finish()
spans = exporter.get_finished_spans()
agent_span = next(
span
for span in spans
if span.attributes.get(GenAI.GEN_AI_OPERATION_NAME) == GenAI.GenAiOperationNameValues.INVOKE_AGENT.value
)
prompt = json.loads(agent_span.attributes[GEN_AI_INPUT_MESSAGES])
completion = json.loads(agent_span.attributes[GEN_AI_OUTPUT_MESSAGES])
assert prompt == [
{
"role": "user",
"parts": [{"type": "text", "content": "hi"}],
}
]
assert completion == [
{
"role": "assistant",
"parts": [{"type": "text", "content": "hello"}],
}
]
assert not agent_span.events
finally:
instrumentor.uninstrument()
exporter.clear()
def test_agent_name_override_applied_to_agent_spans():
instrumentor, exporter = _instrument_with_provider(agent_name="Travel Concierge")
try:
with trace("workflow"):
with agent_span(name="support_bot"):
pass
spans = exporter.get_finished_spans()
agent_span_record = next(
span
for span in spans
if span.attributes[GenAI.GEN_AI_OPERATION_NAME] == GenAI.GenAiOperationNameValues.INVOKE_AGENT.value
)
assert agent_span_record.kind is SpanKind.CLIENT
assert agent_span_record.name == "invoke_agent Travel Concierge"
assert agent_span_record.attributes[GenAI.GEN_AI_AGENT_NAME] == "Travel Concierge"
finally:
instrumentor.uninstrument()
exporter.clear()
def test_capture_mode_can_be_disabled():
instrumentor, exporter = _instrument_with_provider(capture_message_content="no_content")
try:
with trace("workflow"):
with generation_span(
input=[{"role": "user", "content": "hi"}],
output=[{"role": "assistant", "content": "hello"}],
model="gpt-4o-mini",
):
pass
spans = exporter.get_finished_spans()
client_span = next(span for span in spans if span.kind is SpanKind.CLIENT)
assert GEN_AI_INPUT_MESSAGES not in client_span.attributes
assert GEN_AI_OUTPUT_MESSAGES not in client_span.attributes
for event in client_span.events:
assert GEN_AI_INPUT_MESSAGES not in event.attributes
assert GEN_AI_OUTPUT_MESSAGES not in event.attributes
finally:
instrumentor.uninstrument()
exporter.clear()
def test_response_span_records_response_attributes():
instrumentor, exporter = _instrument_with_provider()
class _Usage:
def __init__(self, input_tokens: int, output_tokens: int) -> None:
self.input_tokens = input_tokens
self.output_tokens = output_tokens
class _Response:
def __init__(self) -> None:
self.id = "resp-123"
self.instructions = "You are a helpful assistant."
self.model = "gpt-4o-mini"
self.usage = _Usage(42, 9)
self.tools = [
FunctionTool(
name="get_current_weather",
type="function",
description="Get the current weather in a given location",
parameters={
"type": "object",
"properties": {
"location": {
"title": "Location",
"type": "string",
},
},
"required": ["location"],
},
)
]
self.output = [{"finish_reason": "stop"}]
try:
with trace("workflow"):
with response_span(response=_Response()):
pass
spans = exporter.get_finished_spans()
response = next(
span
for span in spans
if span.attributes[GenAI.GEN_AI_OPERATION_NAME] == GenAI.GenAiOperationNameValues.CHAT.value
)
assert response.kind is SpanKind.CLIENT
assert response.name == "chat gpt-4o-mini"
assert response.attributes[GEN_AI_PROVIDER_NAME] == "openai"
assert response.attributes[GenAI.GEN_AI_RESPONSE_ID] == "resp-123"
assert response.attributes[GenAI.GEN_AI_RESPONSE_MODEL] == "gpt-4o-mini"
assert response.attributes[GenAI.GEN_AI_USAGE_INPUT_TOKENS] == 42
assert response.attributes[GenAI.GEN_AI_USAGE_OUTPUT_TOKENS] == 9
assert response.attributes[GenAI.GEN_AI_RESPONSE_FINISH_REASONS] == ("stop",)
system_instructions = json.loads(response.attributes[GenAI.GEN_AI_SYSTEM_INSTRUCTIONS])
assert system_instructions == [{"type": "text", "content": "You are a helpful assistant."}]
tool_definitions = json.loads(response.attributes[GEN_AI_TOOL_DEFINITIONS])
assert tool_definitions == [
{
"type": "function",
"name": "get_current_weather",
"description": "Get the current weather in a given location",
"parameters": {
"type": "object",
"properties": {
"location": {"title": "Location", "type": "string"},
},
"required": ["location"],
},
}
]
finally:
instrumentor.uninstrument()
exporter.clear()
test_z_instrumentor_behaviors.py 0000664 0000000 0000000 00000004206 15270700723 0045145 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-openai-agents-v2/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
# pylint: disable=wrong-import-position,wrong-import-order,import-error
from __future__ import annotations
import sys
from pathlib import Path
TESTS_ROOT = Path(__file__).resolve().parent
stub_path = TESTS_ROOT / "stubs"
if str(stub_path) not in sys.path:
sys.path.insert(0, str(stub_path))
from agents.tracing import ( # noqa: E402
get_trace_provider,
set_trace_processors,
)
from opentelemetry.instrumentation.openai_agents import ( # noqa: E402
OpenAIAgentsInstrumentor,
)
from opentelemetry.instrumentation.openai_agents.package import ( # noqa: E402
_instruments,
)
from opentelemetry.sdk.trace import TracerProvider # noqa: E402
def test_double_instrument_is_noop():
set_trace_processors([])
provider = TracerProvider()
instrumentor = OpenAIAgentsInstrumentor()
instrumentor.instrument(tracer_provider=provider)
trace_provider = get_trace_provider()
assert len(trace_provider._multi_processor._processors) == 1
instrumentor.instrument(tracer_provider=provider)
assert len(trace_provider._multi_processor._processors) == 1
instrumentor.uninstrument()
instrumentor.uninstrument()
set_trace_processors([])
def test_instrumentation_dependencies_exposed():
instrumentor = OpenAIAgentsInstrumentor()
assert instrumentor.instrumentation_dependencies() == _instruments
def test_default_agent_configuration():
set_trace_processors([])
provider = TracerProvider()
instrumentor = OpenAIAgentsInstrumentor()
try:
instrumentor.instrument(tracer_provider=provider)
processor = instrumentor._processor
assert processor is not None
assert processor._agent_name_default == "OpenAI Agent"
assert processor._agent_id_default == "agent"
assert processor._agent_description_default == "OpenAI Agents instrumentation"
assert processor.base_url == "https://api.openai.com"
assert processor.server_address == "api.openai.com"
assert processor.server_port == 443
finally:
instrumentor.uninstrument()
set_trace_processors([])
test_z_span_processor_unit.py 0000664 0000000 0000000 00000040153 15270700723 0044432 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-openai-agents-v2/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
# pylint: disable=wrong-import-position,wrong-import-order,import-error,no-name-in-module,unexpected-keyword-arg,no-value-for-parameter,redefined-outer-name,too-many-locals,too-many-statements,too-many-branches
from __future__ import annotations
import importlib
import json
from dataclasses import dataclass
from datetime import datetime, timezone
from enum import Enum
from types import SimpleNamespace
from typing import Any
import pytest
from agents.tracing import (
AgentSpanData,
FunctionSpanData,
GenerationSpanData,
ResponseSpanData,
)
import opentelemetry.semconv._incubating.attributes.gen_ai_attributes as _gen_ai_attributes
from opentelemetry.sdk.trace import TracerProvider
from opentelemetry.semconv._incubating.attributes import (
server_attributes as _server_attributes,
)
from opentelemetry.trace import SpanKind
from opentelemetry.trace.status import StatusCode
def _ensure_semconv_enums() -> None:
if not hasattr(_gen_ai_attributes, "GenAiProviderNameValues"):
class _GenAiProviderNameValues(Enum):
OPENAI = "openai"
GCP_GEN_AI = "gcp.gen_ai"
GCP_VERTEX_AI = "gcp.vertex_ai"
GCP_GEMINI = "gcp.gemini"
ANTHROPIC = "anthropic"
COHERE = "cohere"
AZURE_AI_INFERENCE = "azure.ai.inference"
AZURE_AI_OPENAI = "azure.ai.openai"
IBM_WATSONX_AI = "ibm.watsonx.ai"
AWS_BEDROCK = "aws.bedrock"
PERPLEXITY = "perplexity"
X_AI = "x.ai"
DEEPSEEK = "deepseek"
GROQ = "groq"
MISTRAL_AI = "mistral.ai"
class _GenAiOperationNameValues(Enum):
CHAT = "chat"
GENERATE_CONTENT = "generate_content"
TEXT_COMPLETION = "text_completion"
EMBEDDINGS = "embeddings"
CREATE_AGENT = "create_agent"
INVOKE_AGENT = "invoke_agent"
EXECUTE_TOOL = "execute_tool"
class _GenAiOutputTypeValues(Enum):
TEXT = "text"
JSON = "json"
IMAGE = "image"
SPEECH = "speech"
_gen_ai_attributes.GenAiProviderNameValues = _GenAiProviderNameValues
_gen_ai_attributes.GenAiOperationNameValues = _GenAiOperationNameValues
_gen_ai_attributes.GenAiOutputTypeValues = _GenAiOutputTypeValues
if not hasattr(_server_attributes, "SERVER_ADDRESS"):
_server_attributes.SERVER_ADDRESS = "server.address"
if not hasattr(_server_attributes, "SERVER_PORT"):
_server_attributes.SERVER_PORT = "server.port"
_ensure_semconv_enums()
ServerAttributes = _server_attributes
sp = importlib.import_module("opentelemetry.instrumentation.openai_agents.span_processor")
try:
from opentelemetry.sdk.trace.export import ( # type: ignore[attr-defined]
InMemorySpanExporter,
SimpleSpanProcessor,
)
except ImportError: # pragma: no cover
from opentelemetry.sdk.trace.export import SimpleSpanProcessor
from opentelemetry.sdk.trace.export.in_memory_span_exporter import (
InMemorySpanExporter,
)
def _collect(iterator) -> dict[str, Any]:
return dict(iterator)
@pytest.fixture
def processor_setup():
provider = TracerProvider()
exporter = InMemorySpanExporter()
provider.add_span_processor(SimpleSpanProcessor(exporter))
tracer = provider.get_tracer(__name__)
processor = sp.GenAISemanticProcessor(tracer=tracer, system_name="openai")
yield processor, exporter
processor.shutdown()
exporter.clear()
def test_time_helpers():
dt = datetime(2024, 1, 1, tzinfo=timezone.utc)
assert sp._as_utc_nano(dt) == 1704067200 * 1_000_000_000
class Fallback:
def __str__(self) -> str:
return "fallback"
assert sp.safe_json_dumps({"foo": "bar"}) == '{"foo":"bar"}'
assert sp.safe_json_dumps(Fallback()) == "fallback"
def test_infer_server_attributes_variants(monkeypatch):
assert sp._infer_server_attributes(None) == {}
assert sp._infer_server_attributes(123) == {}
attrs = sp._infer_server_attributes("https://api.example.com:8080/v1")
assert attrs[ServerAttributes.SERVER_ADDRESS] == "api.example.com"
assert attrs[ServerAttributes.SERVER_PORT] == 8080
def boom(_: str):
raise ValueError("unparsable url")
monkeypatch.setattr(sp, "urlparse", boom)
assert sp._infer_server_attributes("bad") == {}
def test_operation_and_span_naming(processor_setup):
processor, _ = processor_setup
generation = GenerationSpanData(input=[{"role": "user"}], model="gpt-4o")
assert processor._get_operation_name(generation) == sp.GenAIOperationName.CHAT
completion = GenerationSpanData(input=[])
assert processor._get_operation_name(completion) == sp.GenAIOperationName.TEXT_COMPLETION
embeddings = GenerationSpanData(input=None)
embeddings.embedding_dimension = 128
assert processor._get_operation_name(embeddings) == sp.GenAIOperationName.EMBEDDINGS
# AgentSpanData always maps to invoke_agent (no operation field in OpenAI Agents SDK)
agent_data = AgentSpanData(name="bot")
assert processor._get_operation_name(agent_data) == sp.GenAIOperationName.INVOKE_AGENT
agent_default = AgentSpanData()
assert processor._get_operation_name(agent_default) == sp.GenAIOperationName.INVOKE_AGENT
function_data = FunctionSpanData()
assert processor._get_operation_name(function_data) == sp.GenAIOperationName.EXECUTE_TOOL
response_data = ResponseSpanData()
assert processor._get_operation_name(response_data) == sp.GenAIOperationName.CHAT
class UnknownSpanData:
pass
unknown = UnknownSpanData()
assert processor._get_operation_name(unknown) == "unknown"
assert processor._get_span_kind(GenerationSpanData()) is SpanKind.CLIENT
assert processor._get_span_kind(FunctionSpanData()) is SpanKind.INTERNAL
assert sp.get_span_name(sp.GenAIOperationName.CHAT, model="gpt-4o") == "chat gpt-4o"
assert sp.get_span_name(sp.GenAIOperationName.EXECUTE_TOOL, tool_name="weather") == "execute_tool weather"
assert sp.get_span_name(sp.GenAIOperationName.INVOKE_AGENT, agent_name=None) == "invoke_agent"
assert sp.get_span_name(sp.GenAIOperationName.CREATE_AGENT, agent_name=None) == "create_agent"
def test_attribute_builders(processor_setup):
processor, _ = processor_setup
payload = sp.ContentPayload(
input_messages=[
{
"role": "user",
"parts": [{"type": "text", "content": "hi"}],
}
],
output_messages=[
{
"role": "assistant",
"parts": [{"type": "text", "content": "hello"}],
}
],
system_instructions=[{"type": "text", "content": "be helpful"}],
)
model_config = {
"base_url": "https://api.openai.com:443/v1",
"temperature": 0.2,
"top_p": 0.9,
"top_k": 3,
"frequency_penalty": 0.1,
"presence_penalty": 0.4,
"seed": 1234,
"n": 2,
"max_tokens": 128,
"stop": ["foo", None, "bar"],
}
generation_span = GenerationSpanData(
input=[{"role": "user"}],
output=[{"finish_reason": "stop"}],
model="gpt-4o",
model_config=model_config,
usage={
"prompt_tokens": 10,
"completion_tokens": 3,
"total_tokens": 13,
},
)
gen_attrs = _collect(processor._get_attributes_from_generation_span_data(generation_span, payload))
assert gen_attrs[sp.GEN_AI_REQUEST_MODEL] == "gpt-4o"
assert gen_attrs[sp.GEN_AI_REQUEST_MAX_TOKENS] == 128
assert gen_attrs[sp.GEN_AI_REQUEST_STOP_SEQUENCES] == [
"foo",
None,
"bar",
]
assert gen_attrs[ServerAttributes.SERVER_ADDRESS] == "api.openai.com"
assert gen_attrs[ServerAttributes.SERVER_PORT] == 443
assert gen_attrs[sp.GEN_AI_USAGE_INPUT_TOKENS] == 10
assert gen_attrs[sp.GEN_AI_USAGE_OUTPUT_TOKENS] == 3
assert gen_attrs[sp.GEN_AI_RESPONSE_FINISH_REASONS] == ["stop"]
assert json.loads(gen_attrs[sp.GEN_AI_INPUT_MESSAGES])[0]["role"] == "user"
assert json.loads(gen_attrs[sp.GEN_AI_OUTPUT_MESSAGES])[0]["role"] == "assistant"
assert json.loads(gen_attrs[sp.GEN_AI_SYSTEM_INSTRUCTIONS])[0]["content"] == "be helpful"
assert gen_attrs[sp.GEN_AI_OUTPUT_TYPE] == sp.GenAIOutputType.TEXT
class _Usage:
def __init__(self) -> None:
self.input_tokens = None
self.prompt_tokens = 7
self.output_tokens = None
self.completion_tokens = 2
self.total_tokens = 9
class _Response:
def __init__(self) -> None:
self.id = "resp-1"
self.model = "gpt-4o"
self.usage = _Usage()
self.output = [{"finish_reason": "stop"}]
response_span = ResponseSpanData(response=_Response())
response_attrs = _collect(processor._get_attributes_from_response_span_data(response_span, sp.ContentPayload()))
assert response_attrs[sp.GEN_AI_RESPONSE_ID] == "resp-1"
assert response_attrs[sp.GEN_AI_RESPONSE_MODEL] == "gpt-4o"
assert response_attrs[sp.GEN_AI_RESPONSE_FINISH_REASONS] == ["stop"]
assert response_attrs[sp.GEN_AI_USAGE_INPUT_TOKENS] == 7
assert response_attrs[sp.GEN_AI_USAGE_OUTPUT_TOKENS] == 2
assert response_attrs[sp.GEN_AI_OUTPUT_TYPE] == sp.GenAIOutputType.TEXT
agent_span = AgentSpanData(
name="helper",
output_type="json",
)
agent_attrs = _collect(processor._get_attributes_from_agent_span_data(agent_span, None))
assert agent_attrs[sp.GEN_AI_AGENT_NAME] == "helper"
assert sp.GEN_AI_AGENT_ID not in agent_attrs
assert sp.GEN_AI_REQUEST_MODEL not in agent_attrs
assert agent_attrs[sp.GEN_AI_OUTPUT_TYPE] == sp.GenAIOutputType.TEXT
# Fallback to aggregated model when span data lacks it
agent_span_no_model = AgentSpanData(
name="helper-2",
output_type="json",
)
agent_content = {
"input_messages": [],
"output_messages": [],
"system_instructions": [],
"request_model": "gpt-fallback",
}
agent_attrs_fallback = _collect(processor._get_attributes_from_agent_span_data(agent_span_no_model, agent_content))
assert agent_attrs_fallback[sp.GEN_AI_REQUEST_MODEL] == "gpt-fallback"
function_span = FunctionSpanData(name="lookup_weather")
function_span.tool_type = "extension"
function_span.call_id = "call-42"
function_span.description = "desc"
function_payload = sp.ContentPayload(
tool_arguments={"city": "seattle"},
tool_result={"temperature": 70},
)
function_attrs = _collect(processor._get_attributes_from_function_span_data(function_span, function_payload))
assert function_attrs[sp.GEN_AI_TOOL_NAME] == "lookup_weather"
assert function_attrs[sp.GEN_AI_TOOL_TYPE] == "extension"
assert function_attrs[sp.GEN_AI_TOOL_CALL_ID] == "call-42"
assert function_attrs[sp.GEN_AI_TOOL_DESCRIPTION] == "desc"
assert function_attrs[sp.GEN_AI_TOOL_CALL_ARGUMENTS] == {"city": "seattle"}
assert function_attrs[sp.GEN_AI_TOOL_CALL_RESULT] == {"temperature": 70}
assert function_attrs[sp.GEN_AI_OUTPUT_TYPE] == sp.GenAIOutputType.JSON
def test_extract_genai_attributes_unknown_type(processor_setup):
processor, _ = processor_setup
class UnknownSpanData:
pass
class StubSpan:
def __init__(self) -> None:
self.span_data = UnknownSpanData()
attrs = _collect(processor._extract_genai_attributes(StubSpan(), sp.ContentPayload(), None))
assert attrs[sp.GEN_AI_PROVIDER_NAME] == "openai"
assert attrs[sp.GEN_AI_SYSTEM_KEY] == "openai"
assert sp.GEN_AI_OPERATION_NAME not in attrs
def test_span_status_helper():
status = sp._get_span_status(SimpleNamespace(error={"message": "boom", "data": "bad"}))
assert status.status_code is StatusCode.ERROR
assert status.description == "boom: bad"
ok_status = sp._get_span_status(SimpleNamespace(error=None))
assert ok_status.status_code is StatusCode.OK
@dataclass
class FakeTrace:
name: str
trace_id: str
started_at: str | None = None
ended_at: str | None = None
@dataclass
class FakeSpan:
trace_id: str
span_id: str
span_data: Any
parent_id: str | None = None
started_at: str | None = None
ended_at: str | None = None
error: dict[str, Any] | None = None
def test_span_lifecycle_and_shutdown(processor_setup):
processor, exporter = processor_setup
trace = FakeTrace(
name="workflow",
trace_id="trace-1",
started_at="not-a-timestamp",
ended_at="2024-01-01T00:00:05Z",
)
processor.on_trace_start(trace)
parent_span = FakeSpan(
trace_id="trace-1",
span_id="span-1",
span_data=AgentSpanData(name="agent"),
started_at="2024-01-01T00:00:00Z",
ended_at="2024-01-01T00:00:02Z",
)
processor.on_span_start(parent_span)
missing_span = FakeSpan(
trace_id="trace-1",
span_id="missing",
span_data=FunctionSpanData(name="lookup"),
started_at="2024-01-01T00:00:01Z",
ended_at="2024-01-01T00:00:02Z",
)
processor.on_span_end(missing_span)
child_span = FakeSpan(
trace_id="trace-1",
span_id="span-2",
parent_id="span-1",
span_data=FunctionSpanData(name="lookup"),
started_at="2024-01-01T00:00:02Z",
ended_at="2024-01-01T00:00:03Z",
error={"message": "boom", "data": "bad"},
)
processor.on_span_start(child_span)
processor.on_span_end(child_span)
processor.on_span_end(parent_span)
processor.on_trace_end(trace)
linger_trace = FakeTrace(
name="linger",
trace_id="trace-2",
started_at="2024-01-01T00:00:06Z",
)
processor.on_trace_start(linger_trace)
linger_span = FakeSpan(
trace_id="trace-2",
span_id="span-3",
span_data=AgentSpanData(),
started_at="2024-01-01T00:00:06Z",
)
processor.on_span_start(linger_span)
assert processor.force_flush() is None
processor.shutdown()
finished = exporter.get_finished_spans()
statuses = {span.name: span.status for span in finished}
assert (
statuses["execute_tool lookup"].status_code is StatusCode.ERROR
and statuses["execute_tool lookup"].description == "boom: bad"
)
assert statuses["invoke_agent agent"].status_code is StatusCode.OK
assert statuses["workflow"].status_code is StatusCode.OK
assert (
statuses["invoke_agent"].status_code is StatusCode.ERROR
and statuses["invoke_agent"].description == "Application shutdown"
)
assert (
statuses["linger"].status_code is StatusCode.ERROR and statuses["linger"].description == "Application shutdown"
)
workflow_span = next(span for span in finished if span.name == "workflow")
assert workflow_span.attributes[sp.GEN_AI_OPERATION_NAME] == sp.GenAIOperationName.INVOKE_AGENT
def test_chat_span_renamed_with_model(processor_setup):
processor, exporter = processor_setup
trace = FakeTrace(name="workflow", trace_id="trace-rename")
processor.on_trace_start(trace)
agent = FakeSpan(
trace_id=trace.trace_id,
span_id="agent-span",
span_data=AgentSpanData(
name="Agent",
),
started_at="2025-01-01T00:00:00Z",
ended_at="2025-01-01T00:00:02Z",
)
processor.on_span_start(agent)
generation_data = GenerationSpanData(
input=[{"role": "user", "content": "question"}],
output=[{"finish_reason": "stop"}],
usage={"prompt_tokens": 1, "completion_tokens": 1},
)
generation_span = FakeSpan(
trace_id=trace.trace_id,
span_id="child-span",
parent_id=agent.span_id,
span_data=generation_data,
started_at="2025-01-01T00:00:00Z",
ended_at="2025-01-01T00:00:01Z",
)
processor.on_span_start(generation_span)
# Model becomes available before span end (e.g., once response arrives)
generation_data.model = "gpt-4o"
processor.on_span_end(generation_span)
processor.on_span_end(agent)
processor.on_trace_end(trace)
span_names = {span.name for span in exporter.get_finished_spans()}
assert "chat gpt-4o" in span_names
test_zz_coverage_improvements.py 0000664 0000000 0000000 00000077144 15270700723 0045142 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-openai-agents-v2/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
# pylint: disable=wrong-import-position,wrong-import-order,import-error,no-name-in-module,unexpected-keyword-arg,no-value-for-parameter,redefined-outer-name,too-many-locals,too-many-statements,protected-access,import-outside-toplevel,no-self-use,invalid-name
# ruff: noqa: PLC0415
"""
Tests for improving coverage of OpenAI Agents instrumentation.
This file targets uncovered lines identified in the coverage report:
- __init__.py: _resolve_system, _resolve_bool, _resolve_content_mode
- span_processor.py: normalization utilities, span data handlers, message normalization,
output type inference, metrics recording, and various edge cases.
NOTE: Imports are done inside functions to avoid module-level import conflicts
that can occur when pytest collects tests across multiple files.
"""
from __future__ import annotations
def _get_modules():
"""Lazy import to avoid module conflicts."""
import importlib
sp = importlib.import_module("opentelemetry.instrumentation.openai_agents.span_processor")
init_module = importlib.import_module("opentelemetry.instrumentation.openai_agents")
return sp, init_module
def _get_span_data_classes():
"""Lazy import span data classes."""
from agents.tracing import (
AgentSpanData,
FunctionSpanData,
GenerationSpanData,
ResponseSpanData,
)
return (
AgentSpanData,
FunctionSpanData,
GenerationSpanData,
ResponseSpanData,
)
def _get_otel_test_fixtures():
"""Get OpenTelemetry test fixtures."""
from opentelemetry.sdk.trace import TracerProvider
try:
from opentelemetry.sdk.trace.export import (
InMemorySpanExporter,
SimpleSpanProcessor,
)
except ImportError:
from opentelemetry.sdk.trace.export import SimpleSpanProcessor
from opentelemetry.sdk.trace.export.in_memory_span_exporter import (
InMemorySpanExporter,
)
return TracerProvider, InMemorySpanExporter, SimpleSpanProcessor
# ============================================================================
# Tests for __init__.py functions
# ============================================================================
class TestResolveSystem:
"""Tests for _resolve_system function."""
def test_resolve_system_returns_openai_for_none(self):
_, init_module = _get_modules()
result = init_module._resolve_system(None)
assert result == "openai"
def test_resolve_system_returns_openai_for_empty_string(self):
_, init_module = _get_modules()
result = init_module._resolve_system("")
assert result == "openai"
def test_resolve_system_matches_enum_value(self):
_, init_module = _get_modules()
result = init_module._resolve_system("openai")
assert result == "openai"
def test_resolve_system_matches_enum_name(self):
_, init_module = _get_modules()
result = init_module._resolve_system("OPENAI")
assert result == "openai"
def test_resolve_system_matches_enum_name_when_name_differs(self):
_, init_module = _get_modules()
from opentelemetry.semconv._incubating.attributes import (
gen_ai_attributes as GenAI,
)
candidate = next(
(member for member in GenAI.GenAiSystemValues if member.name.lower() != member.value),
None,
)
assert candidate is not None
assert init_module._resolve_system(candidate.name.lower()) == candidate.value
def test_resolve_system_matches_with_whitespace(self):
_, init_module = _get_modules()
result = init_module._resolve_system(" openai ")
assert result == "openai"
def test_resolve_system_returns_custom_value_when_not_found(self):
_, init_module = _get_modules()
result = init_module._resolve_system("custom_provider")
assert result == "custom_provider"
class TestResolveBool:
"""Tests for _resolve_bool function."""
def test_resolve_bool_returns_default_for_none(self):
_, init_module = _get_modules()
assert init_module._resolve_bool(None, True) is True
assert init_module._resolve_bool(None, False) is False
def test_resolve_bool_returns_value_for_bool(self):
_, init_module = _get_modules()
assert init_module._resolve_bool(True, False) is True
assert init_module._resolve_bool(False, True) is False
def test_resolve_bool_parses_true_strings(self):
_, init_module = _get_modules()
for value in ["true", "TRUE", "1", "yes", "on", " YES "]:
assert init_module._resolve_bool(value, False) is True, f"Failed for {value}"
def test_resolve_bool_parses_false_strings(self):
_, init_module = _get_modules()
for value in ["false", "FALSE", "0", "no", "off", " NO "]:
assert init_module._resolve_bool(value, True) is False, f"Failed for {value}"
def test_resolve_bool_returns_default_for_unknown(self):
_, init_module = _get_modules()
assert init_module._resolve_bool("maybe", True) is True
assert init_module._resolve_bool("maybe", False) is False
class TestResolveContentMode:
"""Tests for _resolve_content_mode function."""
def test_resolve_content_mode_returns_value_for_enum(self):
sp, init_module = _get_modules()
result = init_module._resolve_content_mode(sp.ContentCaptureMode.SPAN_ONLY)
assert result == sp.ContentCaptureMode.SPAN_ONLY
def test_resolve_content_mode_for_bool_true(self):
sp, init_module = _get_modules()
result = init_module._resolve_content_mode(True)
assert result == sp.ContentCaptureMode.SPAN_AND_EVENT
def test_resolve_content_mode_for_bool_false(self):
sp, init_module = _get_modules()
result = init_module._resolve_content_mode(False)
assert result == sp.ContentCaptureMode.NO_CONTENT
def test_resolve_content_mode_for_none(self):
sp, init_module = _get_modules()
result = init_module._resolve_content_mode(None)
assert result == sp.ContentCaptureMode.SPAN_AND_EVENT
def test_resolve_content_mode_for_empty_string(self):
sp, init_module = _get_modules()
result = init_module._resolve_content_mode("")
assert result == sp.ContentCaptureMode.SPAN_AND_EVENT
def test_resolve_content_mode_span_only_variants(self):
sp, init_module = _get_modules()
for value in ["span_only", "span-only", "span"]:
result = init_module._resolve_content_mode(value)
assert result == sp.ContentCaptureMode.SPAN_ONLY, f"Failed for {value}"
def test_resolve_content_mode_event_only_variants(self):
sp, init_module = _get_modules()
for value in ["event_only", "event-only", "event"]:
result = init_module._resolve_content_mode(value)
assert result == sp.ContentCaptureMode.EVENT_ONLY, f"Failed for {value}"
def test_resolve_content_mode_span_and_event_variants(self):
sp, init_module = _get_modules()
for value in [
"span_and_event",
"span-and-event",
"span_and_events",
"all",
"true",
"1",
"yes",
]:
result = init_module._resolve_content_mode(value)
assert result == sp.ContentCaptureMode.SPAN_AND_EVENT, f"Failed for {value}"
def test_resolve_content_mode_no_content_variants(self):
sp, init_module = _get_modules()
for value in ["no_content", "false", "0", "no", "none"]:
result = init_module._resolve_content_mode(value)
assert result == sp.ContentCaptureMode.NO_CONTENT, f"Failed for {value}"
# ============================================================================
# Tests for span_processor.py normalization utilities
# ============================================================================
class TestNormalizeProvider:
"""Tests for normalize_provider function."""
def test_normalize_provider_returns_none_for_none(self):
sp, _ = _get_modules()
assert sp.normalize_provider(None) is None
def test_normalize_provider_returns_none_for_empty(self):
sp, _ = _get_modules()
assert sp.normalize_provider("") is None
def test_normalize_provider_normalizes_valid_provider(self):
sp, _ = _get_modules()
result = sp.normalize_provider("OPENAI")
assert result == "openai"
def test_normalize_provider_passes_through_unknown(self):
sp, _ = _get_modules()
result = sp.normalize_provider("MyCustomProvider")
assert result == "MyCustomProvider"
class TestValidateToolType:
"""Tests for validate_tool_type function."""
def test_validate_tool_type_returns_default_for_none(self):
sp, _ = _get_modules()
assert sp.validate_tool_type(None) == "function"
def test_validate_tool_type_returns_default_for_empty(self):
sp, _ = _get_modules()
assert sp.validate_tool_type("") == "function"
def test_validate_tool_type_normalizes_valid_types(self):
sp, _ = _get_modules()
assert sp.validate_tool_type("FUNCTION") == "function"
assert sp.validate_tool_type("extension") == "extension"
assert sp.validate_tool_type("DATASTORE") == "datastore"
def test_validate_tool_type_returns_default_for_unknown(self):
sp, _ = _get_modules()
assert sp.validate_tool_type("unknown_type") == "function"
class TestNormalizeOutputType:
"""Tests for normalize_output_type function."""
def test_normalize_output_type_returns_text_for_none(self):
sp, _ = _get_modules()
assert sp.normalize_output_type(None) == "text"
def test_normalize_output_type_returns_text_for_empty(self):
sp, _ = _get_modules()
assert sp.normalize_output_type("") == "text"
def test_normalize_output_type_normalizes_known_types(self):
sp, _ = _get_modules()
assert sp.normalize_output_type("TEXT") == "text"
assert sp.normalize_output_type("json") == "json"
assert sp.normalize_output_type("image") == "image"
assert sp.normalize_output_type("speech") == "speech"
def test_normalize_output_type_handles_mappings(self):
sp, _ = _get_modules()
assert sp.normalize_output_type("json_object") == "json"
assert sp.normalize_output_type("jsonschema") == "json"
assert sp.normalize_output_type("speech_audio") == "speech"
assert sp.normalize_output_type("audio_speech") == "speech"
assert sp.normalize_output_type("image_png") == "image"
assert sp.normalize_output_type("function_arguments_json") == "json"
assert sp.normalize_output_type("tool_call") == "json"
assert sp.normalize_output_type("transcription_json") == "json"
def test_normalize_output_type_returns_text_for_unknown(self):
sp, _ = _get_modules()
assert sp.normalize_output_type("unknown_type") == "text"
# ============================================================================
# Tests for span naming and output type inference
# ============================================================================
class TestGetSpanName:
"""Tests for get_span_name function."""
def test_span_name_handoff(self):
sp, _ = _get_modules()
name = sp.get_span_name("agent_handoff", agent_name="target_agent")
assert name == "agent_handoff target_agent"
def test_span_name_handoff_no_agent(self):
sp, _ = _get_modules()
name = sp.get_span_name("agent_handoff")
assert name == "agent_handoff"
def test_span_name_transcription(self):
sp, _ = _get_modules()
name = sp.get_span_name("transcription", model="whisper-1")
assert name == "transcription whisper-1"
def test_span_name_speech(self):
sp, _ = _get_modules()
name = sp.get_span_name("speech_generation", model="tts-1")
assert name == "speech_generation tts-1"
def test_span_name_unknown_operation(self):
sp, _ = _get_modules()
name = sp.get_span_name("unknown_operation")
assert name == "unknown_operation"
class TestInferOutputType:
"""Tests for _infer_output_type method."""
def _make_processor(self):
sp, _ = _get_modules()
TracerProvider, _, _ = _get_otel_test_fixtures()
provider = TracerProvider()
tracer = provider.get_tracer(__name__)
return sp.GenAISemanticProcessor(tracer=tracer, system_name="openai", metrics_enabled=False)
def test_infer_output_type_function_span(self):
_, FunctionSpanData, _, _ = _get_span_data_classes()
processor = self._make_processor()
span_data = FunctionSpanData()
assert processor._infer_output_type(span_data) == "json"
def test_infer_output_type_embeddings(self):
_, _, GenerationSpanData, _ = _get_span_data_classes()
processor = self._make_processor()
span_data = GenerationSpanData()
span_data.embedding_dimension = 128
assert processor._infer_output_type(span_data) == "text"
def test_infer_output_type_image_output(self):
_, _, GenerationSpanData, _ = _get_span_data_classes()
processor = self._make_processor()
span_data = GenerationSpanData(output=[{"type": "image"}])
assert processor._infer_output_type(span_data) == "image"
def test_infer_output_type_audio_output(self):
_, _, GenerationSpanData, _ = _get_span_data_classes()
processor = self._make_processor()
span_data = GenerationSpanData(output=[{"type": "audio"}])
assert processor._infer_output_type(span_data) == "speech"
def test_infer_output_type_json_output(self):
_, _, GenerationSpanData, _ = _get_span_data_classes()
processor = self._make_processor()
span_data = GenerationSpanData(output=[{"type": "json_object"}])
assert processor._infer_output_type(span_data) == "json"
def test_infer_output_type_text_output(self):
_, _, GenerationSpanData, _ = _get_span_data_classes()
processor = self._make_processor()
span_data = GenerationSpanData(output=[{"type": "text"}])
assert processor._infer_output_type(span_data) == "text"
def test_infer_output_type_json_like_keys(self):
_, _, GenerationSpanData, _ = _get_span_data_classes()
processor = self._make_processor()
span_data = GenerationSpanData(output=[{"schema": {}, "properties": {}}])
assert processor._infer_output_type(span_data) == "json"
# ============================================================================
# Tests for content capture mode properties
# ============================================================================
class TestContentCaptureMode:
"""Tests for ContentCaptureMode properties."""
def test_capture_in_span(self):
sp, _ = _get_modules()
assert sp.ContentCaptureMode.NO_CONTENT.capture_in_span is False
assert sp.ContentCaptureMode.SPAN_ONLY.capture_in_span is True
assert sp.ContentCaptureMode.EVENT_ONLY.capture_in_span is False
assert sp.ContentCaptureMode.SPAN_AND_EVENT.capture_in_span is True
def test_capture_in_event(self):
sp, _ = _get_modules()
assert sp.ContentCaptureMode.NO_CONTENT.capture_in_event is False
assert sp.ContentCaptureMode.SPAN_ONLY.capture_in_event is False
assert sp.ContentCaptureMode.EVENT_ONLY.capture_in_event is True
assert sp.ContentCaptureMode.SPAN_AND_EVENT.capture_in_event is True
# ============================================================================
# Tests for sanitize usage payload
# ============================================================================
class TestSanitizeUsagePayload:
"""Tests for _sanitize_usage_payload method."""
def test_sanitize_dict_usage(self):
sp, _ = _get_modules()
usage = {"input_tokens": 10, "output_tokens": 5, "total_tokens": 15}
sp.GenAISemanticProcessor._sanitize_usage_payload(usage)
assert "total_tokens" not in usage
assert usage["input_tokens"] == 10
def test_sanitize_object_usage(self):
sp, _ = _get_modules()
class Usage:
def __init__(self):
self.input_tokens = 10
self.output_tokens = 5
self.total_tokens = 15
usage = Usage()
sp.GenAISemanticProcessor._sanitize_usage_payload(usage)
assert usage.total_tokens is None
def test_sanitize_none_usage(self):
sp, _ = _get_modules()
# Should not raise
sp.GenAISemanticProcessor._sanitize_usage_payload(None)
# ============================================================================
# Tests for message normalization
# ============================================================================
class TestNormalizeMessagesToRoleParts:
"""Tests for _normalize_messages_to_role_parts method."""
def _make_processor(self, sensitive=True):
sp, _ = _get_modules()
TracerProvider, _, _ = _get_otel_test_fixtures()
provider = TracerProvider()
tracer = provider.get_tracer(__name__)
return sp.GenAISemanticProcessor(
tracer=tracer,
system_name="openai",
include_sensitive_data=sensitive,
metrics_enabled=False,
)
def test_normalize_non_dict_message(self):
processor = self._make_processor()
messages = ["plain text message"]
normalized = processor._normalize_messages_to_role_parts(messages)
assert len(normalized) == 1
assert normalized[0]["role"] == "user"
assert normalized[0]["parts"][0]["type"] == "text"
def test_normalize_with_redaction(self):
processor = self._make_processor(sensitive=False)
messages = [{"role": "user", "content": "Secret message"}]
normalized = processor._normalize_messages_to_role_parts(messages)
assert normalized[0]["parts"][0]["content"] == "readacted"
def test_normalize_empty_messages_returns_empty_list(self):
processor = self._make_processor()
normalized = processor._normalize_messages_to_role_parts([])
assert normalized == []
def test_normalize_parts_tool_calls_and_tool_responses(self):
processor = self._make_processor(sensitive=False)
messages = [
{
"role": "assistant",
"parts": [
{"type": "text", "content": "hello"},
{
"type": "tool_call",
"id": "call_1",
"name": "weather",
"arguments": {"city": "Paris"},
},
{
"type": "tool_call_response",
"id": "call_1",
"result": {"temp": 70},
},
{"type": "weird", "payload": {"x": 1}},
123,
],
"content": [
{"type": "text", "text": "from-content"},
{"type": "image", "url": "http://example.com"},
"raw",
],
"tool_calls": [
{
"id": "call_2",
"function": {"name": "calc", "arguments": '{"x":1}'},
},
"not-dict",
],
},
{"role": "tool", "tool_call_id": "call_2", "content": {"x": 1}},
]
normalized = processor._normalize_messages_to_role_parts(messages)
assert normalized[0]["role"] == "assistant"
assistant_part_types = {p["type"] for p in normalized[0]["parts"]}
assert "tool_call" in assistant_part_types
assert "tool_call_response" in assistant_part_types
tool_call = next(p for p in normalized[0]["parts"] if p["type"] == "tool_call")
assert tool_call["arguments"] == "readacted"
tool_response = next(p for p in normalized[0]["parts"] if p["type"] == "tool_call_response")
assert tool_response["result"] == "readacted"
assert normalized[1]["role"] == "tool"
assert normalized[1]["parts"][0]["type"] == "tool_call_response"
assert normalized[1]["parts"][0]["result"] == "readacted"
# ============================================================================
# Tests for helper functions
# ============================================================================
class TestHelperFunctions:
"""Tests for various helper functions."""
def test_is_instance_of_single_class(self):
sp, _ = _get_modules()
assert sp._is_instance_of("hello", str) is True
assert sp._is_instance_of(123, str) is False
def test_is_instance_of_tuple_classes(self):
sp, _ = _get_modules()
assert sp._is_instance_of("hello", (str, int)) is True
assert sp._is_instance_of(123, (str, int)) is True
assert sp._is_instance_of(3.14, (str, int)) is False
def test_span_status_helper(self):
from types import SimpleNamespace
from opentelemetry.trace.status import StatusCode
sp, _ = _get_modules()
status = sp._get_span_status(SimpleNamespace(error={"message": "boom", "data": "bad"}))
assert status.status_code is StatusCode.ERROR
assert status.description == "boom: bad"
ok_status = sp._get_span_status(SimpleNamespace(error=None))
assert ok_status.status_code is StatusCode.OK
# ============================================================================
# Tests for processor initialization and configuration
# ============================================================================
class TestProcessorConfiguration:
"""Tests for GenAISemanticProcessor configuration."""
def test_processor_with_metrics_disabled(self):
sp, _ = _get_modules()
TracerProvider, _, _ = _get_otel_test_fixtures()
provider = TracerProvider()
tracer = provider.get_tracer(__name__)
processor = sp.GenAISemanticProcessor(
tracer=tracer,
system_name="openai",
metrics_enabled=False,
)
assert processor._metrics_enabled is False
assert processor._duration_histogram is None
assert processor._token_usage_histogram is None
processor.shutdown()
def test_processor_with_custom_system_name(self):
sp, _ = _get_modules()
TracerProvider, _, _ = _get_otel_test_fixtures()
provider = TracerProvider()
tracer = provider.get_tracer(__name__)
processor = sp.GenAISemanticProcessor(
tracer=tracer,
system_name="azure.ai.inference",
metrics_enabled=False,
)
assert processor.system_name == "azure.ai.inference"
processor.shutdown()
def test_processor_force_flush_is_noop(self):
sp, _ = _get_modules()
TracerProvider, _, _ = _get_otel_test_fixtures()
provider = TracerProvider()
tracer = provider.get_tracer(__name__)
processor = sp.GenAISemanticProcessor(
tracer=tracer,
system_name="openai",
metrics_enabled=False,
)
# Should not raise
result = processor.force_flush()
assert result is None
processor.shutdown()
def test_processor_infers_server_from_base_url(self):
sp, _ = _get_modules()
TracerProvider, _, _ = _get_otel_test_fixtures()
provider = TracerProvider()
tracer = provider.get_tracer(__name__)
processor = sp.GenAISemanticProcessor(
tracer=tracer,
system_name="openai",
metrics_enabled=False,
base_url="https://api.example.com:8443/v1",
)
assert processor.server_address == "api.example.com"
assert processor.server_port == 8443
server_attrs = processor._get_server_attributes()
assert server_attrs[sp.ServerAttributes.SERVER_ADDRESS] == "api.example.com"
assert server_attrs[sp.ServerAttributes.SERVER_PORT] == 8443
processor.shutdown()
class TestRecordMetrics:
def test_record_metrics_noop_when_disabled(self):
sp, _ = _get_modules()
processor = sp.GenAISemanticProcessor(metrics_enabled=False)
processor._record_metrics(object(), {})
def test_record_metrics_records_duration_and_tokens(self):
from types import SimpleNamespace
sp, _ = _get_modules()
TracerProvider, _, _ = _get_otel_test_fixtures()
provider = TracerProvider()
tracer = provider.get_tracer(__name__)
class _Histogram:
def __init__(self) -> None:
self.records = []
def record(self, value, attributes) -> None:
self.records.append((value, attributes))
duration_histogram = _Histogram()
token_histogram = _Histogram()
processor = sp.GenAISemanticProcessor(tracer=tracer, system_name="openai", metrics_enabled=False)
processor._metrics_enabled = True
processor._duration_histogram = duration_histogram
processor._token_usage_histogram = token_histogram
span = SimpleNamespace(
started_at="2024-01-01T00:00:00+00:00",
ended_at="2024-01-01T00:00:02+00:00",
error={"type": "timeout"},
)
attributes = {
sp.GEN_AI_PROVIDER_NAME: "openai",
sp.GEN_AI_OPERATION_NAME: sp.GenAIOperationName.CHAT,
sp.GEN_AI_REQUEST_MODEL: "gpt-4o-mini",
sp.ServerAttributes.SERVER_ADDRESS: "api.example.com",
sp.ServerAttributes.SERVER_PORT: 443,
sp.GEN_AI_USAGE_INPUT_TOKENS: 2,
sp.GEN_AI_USAGE_OUTPUT_TOKENS: 3,
}
processor._record_metrics(span, attributes)
assert duration_histogram.records
duration_value, duration_attrs = duration_histogram.records[0]
assert duration_value == 2.0
assert duration_attrs["error.type"] == "timeout"
assert len(token_histogram.records) == 2
token_types = {token_attrs[sp.GEN_AI_TOKEN_TYPE] for _, token_attrs in token_histogram.records}
assert token_types == {"input", "output"}
def test_record_metrics_swallows_exceptions(self):
from types import SimpleNamespace
sp, _ = _get_modules()
TracerProvider, _, _ = _get_otel_test_fixtures()
provider = TracerProvider()
tracer = provider.get_tracer(__name__)
class _BoomHistogram:
def record(self, value, attributes) -> None:
raise RuntimeError("boom")
processor = sp.GenAISemanticProcessor(tracer=tracer, system_name="openai", metrics_enabled=False)
processor._metrics_enabled = True
processor._duration_histogram = _BoomHistogram()
span = SimpleNamespace(
started_at="2024-01-01T00:00:00+00:00",
ended_at="2024-01-01T00:00:02+00:00",
)
attributes = {
sp.GEN_AI_PROVIDER_NAME: "openai",
sp.GEN_AI_OPERATION_NAME: sp.GenAIOperationName.CHAT,
sp.GEN_AI_REQUEST_MODEL: "gpt-4o-mini",
}
processor._record_metrics(span, attributes)
class TestVersionModule:
def test_version_importable(self):
import importlib
version_module = importlib.import_module("opentelemetry.instrumentation.openai_agents.version")
assert isinstance(version_module.__version__, str)
assert version_module.__version__
# ============================================================================
# Tests for normalize_to_text_parts
# ============================================================================
class TestNormalizeToTextParts:
"""Tests for _normalize_to_text_parts method."""
def _make_processor(self):
sp, _ = _get_modules()
TracerProvider, _, _ = _get_otel_test_fixtures()
provider = TracerProvider()
tracer = provider.get_tracer(__name__)
return sp.GenAISemanticProcessor(tracer=tracer, system_name="openai", metrics_enabled=False)
def test_normalize_string_content(self):
processor = self._make_processor()
parts = processor._normalize_to_text_parts("Hello")
assert len(parts) == 1
assert parts[0] == {"type": "text", "content": "Hello"}
def test_normalize_list_content(self):
processor = self._make_processor()
parts = processor._normalize_to_text_parts(["Hello", "World"])
assert len(parts) == 2
assert parts[0]["content"] == "Hello"
assert parts[1]["content"] == "World"
def test_normalize_list_with_dict_missing_text_and_other_types(self):
processor = self._make_processor()
parts = processor._normalize_to_text_parts([{"nope": "missing"}, 123, "ok"])
assert [part["content"] for part in parts] == [
"{'nope': 'missing'}",
"123",
"ok",
]
def test_normalize_dict_content_with_text(self):
processor = self._make_processor()
parts = processor._normalize_to_text_parts({"text": "From text key"})
assert len(parts) == 1
assert parts[0]["content"] == "From text key"
def test_normalize_dict_without_text_or_content(self):
processor = self._make_processor()
parts = processor._normalize_to_text_parts({"nope": "missing"})
assert parts[0]["content"] == "{'nope': 'missing'}"
def test_normalize_none_content(self):
processor = self._make_processor()
parts = processor._normalize_to_text_parts(None)
assert parts == []
def test_normalize_other_type_content(self):
processor = self._make_processor()
parts = processor._normalize_to_text_parts(123)
assert len(parts) == 1
assert parts[0]["content"] == "123"
# ============================================================================
# Tests for collect_system_instructions
# ============================================================================
class TestCollectSystemInstructions:
"""Tests for _collect_system_instructions method."""
def _make_processor(self):
sp, _ = _get_modules()
TracerProvider, _, _ = _get_otel_test_fixtures()
provider = TracerProvider()
tracer = provider.get_tracer(__name__)
return sp.GenAISemanticProcessor(tracer=tracer, system_name="openai", metrics_enabled=False)
def test_collect_system_role_message(self):
processor = self._make_processor()
messages = [
{"role": "system", "content": "You are a helpful assistant."},
{"role": "user", "content": "Hello"},
]
collected = processor._collect_system_instructions(messages)
assert len(collected) == 1
assert collected[0]["type"] == "text"
assert collected[0]["content"] == "You are a helpful assistant."
def test_collect_ai_role_message(self):
processor = self._make_processor()
messages = [
{"role": "ai", "content": "AI assistant instructions."},
]
collected = processor._collect_system_instructions(messages)
assert len(collected) == 1
assert collected[0]["content"] == "AI assistant instructions."
def test_collect_empty_messages(self):
processor = self._make_processor()
collected = processor._collect_system_instructions([])
assert collected == []
def test_collect_none_messages(self):
processor = self._make_processor()
collected = processor._collect_system_instructions(None)
assert collected == []
def test_collect_skips_non_dict_messages(self):
processor = self._make_processor()
collected = processor._collect_system_instructions(["not-a-dict", {"role": "system", "content": "hi"}])
assert collected[0]["content"] == "hi"
opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-openai-v2/ 0000775 0000000 0000000 00000000000 15270700723 0034024 5 ustar 00root root 0000000 0000000 .changelog/ 0000775 0000000 0000000 00000000000 15270700723 0035752 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-openai-v2 .gitignore 0000664 0000000 0000000 00000000000 15270700723 0037730 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-openai-v2/.changelog 4500.changed 0000664 0000000 0000000 00000000127 15270700723 0037655 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-openai-v2/.changelog Refactor chat completion stream wrappers to use shared GenAI stream lifecycle helpers.
4554.changed 0000664 0000000 0000000 00000000245 15270700723 0037667 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-openai-v2/.changelog Pass tool definitions from `tools` kwarg to `InferenceInvocation.tool_definitions` so `gen_ai.tool.definitions` span attribute is populated on chat completion spans
4751.fixed 0000664 0000000 0000000 00000000347 15270700723 0037377 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-openai-v2/.changelog `opentelemetry-instrumentation-openai-v2`: await `AsyncStream.close` when closing an async streaming chat completion on the default semantic convention path so the underlying httpx response/connection is released instead of leaked
CHANGELOG.md 0000664 0000000 0000000 00000014070 15270700723 0035560 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-openai-v2 # Changelog
All notable changes to this project will be documented in this file.
The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),
and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
## Version 2.4b0 (2026-05-01)
- Migrate experimental path from deprecated `LLMInvocation` to `InferenceInvocation`,
using `handler.start_inference()` and `invocation.stop()`/`invocation.fail()` directly
([#4502](https://github.com/open-telemetry/opentelemetry-python-contrib/pull/4502))
- Use `create_duration_histogram` and `create_token_histogram` from
`opentelemetry-util-genai` instead of defining bucket boundaries locally
([#4501](https://github.com/open-telemetry/opentelemetry-python-contrib/pull/4501))
- Import `OTEL_INSTRUMENTATION_GENAI_CAPTURE_MESSAGE_CONTENT` from
`opentelemetry.util.genai.environment_variables` instead of re-defining it locally,
making `opentelemetry-util-genai` the single source of truth for this constant.
([#4455](https://github.com/open-telemetry/opentelemetry-python-contrib/pull/4455))
- Fix compatibility with wrapt 2.x by using positional arguments in `wrap_function_wrapper()` calls
([#4445](https://github.com/open-telemetry/opentelemetry-python-contrib/pull/4445))
- Fix `ChoiceBuffer` crash on streaming tool-call deltas with `arguments=None`
([#4350](https://github.com/open-telemetry/opentelemetry-python-contrib/pull/4350))
- Fix `StreamWrapper` missing `.headers` and other attributes when using `with_raw_response` streaming
([#4113](https://github.com/open-telemetry/opentelemetry-python-contrib/issues/4113))
- Add opt-in support for latest experimental semantic conventions (v1.37.0). Set
`OTEL_SEMCONV_STABILITY_OPT_IN` to `gen_ai_latest_experimental` to enable.
Add dependency on `opentelemetry-util-genai` pypi package.
([#3715](https://github.com/open-telemetry/opentelemetry-python-contrib/pull/3715))
- Add wrappers for OpenAI Responses API streams and response stream managers
([#4280](https://github.com/open-telemetry/opentelemetry-python-contrib/pull/4280))
- Add async wrappers for OpenAI Responses API streams and response stream managers
([#4325](https://github.com/open-telemetry/opentelemetry-python-contrib/pull/4325))
- Add strongly typed Responses API extractors with validation and content
extraction improvements
([#4337](https://github.com/open-telemetry/opentelemetry-python-contrib/pull/4337))
- Add instrumentation for OpenAI Responses API `create`
([#4474](https://github.com/open-telemetry/opentelemetry-python-contrib/pull/4474))
- Add completion hook support.
([#4315](https://github.com/open-telemetry/opentelemetry-python-contrib/pull/4315))
- Fix `response_format` handling: map `json_object`/`json_schema` to `json` output type.
([#4315](https://github.com/open-telemetry/opentelemetry-python-contrib/pull/4315))
- Skip attribute values with `openai.Omit` value.
([#4315](https://github.com/open-telemetry/opentelemetry-python-contrib/pull/4315))
- Default empty string for `gen_ai.request.model` attribute on missing model.
([#4494](https://github.com/open-telemetry/opentelemetry-python-contrib/pull/4494))
## Version 2.3b0 (2025-12-24)
- Fix `AttributeError` when handling `LegacyAPIResponse` (from `with_raw_response`)
([#4017](https://github.com/open-telemetry/opentelemetry-python-contrib/pull/4017))
- Add support for chat completions choice count and stop sequences span attributes
([#4028](https://github.com/open-telemetry/opentelemetry-python-contrib/pull/4028))
- Fix crash with streaming `with_raw_response`
([#4033](https://github.com/open-telemetry/opentelemetry-python-contrib/pull/4033))
- Bump to 1.30.0 semconv schema: `gen_ai.request.seed` instead of `gen_ai.openai.request.seed`
([#4036](https://github.com/open-telemetry/opentelemetry-python-contrib/pull/4036))
## Version 2.2b0 (2025-11-25)
- Fix service tier attribute names: use `GEN_AI_OPENAI_REQUEST_SERVICE_TIER` for request
attributes and `GEN_AI_OPENAI_RESPONSE_SERVICE_TIER` for response attributes.
([#3920](https://github.com/open-telemetry/opentelemetry-python-contrib/issues/3920))
- Added support for OpenAI embeddings instrumentation
([#3461](https://github.com/open-telemetry/opentelemetry-python-contrib/pull/3461))
- Record prompt and completion events regardless of span sampling decision.
([#3226](https://github.com/open-telemetry/opentelemetry-python-contrib/pull/3226))
- Filter out attributes with the value of NotGiven instances
([#3760](https://github.com/open-telemetry/opentelemetry-python-contrib/pull/3760))
- Migrate off the deprecated events API to use the logs API
([#3625](https://github.com/open-telemetry/opentelemetry-python-contrib/pull/3628))
## Version 2.1b0 (2025-01-18)
- Coerce openai response_format to semconv format
([#3073](https://github.com/open-telemetry/opentelemetry-python-contrib/pull/3073))
- Add example to `opentelemetry-instrumentation-openai-v2`
([#3006](https://github.com/open-telemetry/opentelemetry-python-contrib/pull/3006))
- Support for `AsyncOpenAI/AsyncCompletions` ([#2984](https://github.com/open-telemetry/opentelemetry-python-contrib/pull/2984))
- Add metrics ([#3180](https://github.com/open-telemetry/opentelemetry-python-contrib/pull/3180))
## Version 2.0b0 (2024-11-08)
- Use generic `OTEL_INSTRUMENTATION_GENAI_CAPTURE_MESSAGE_CONTENT` environment variable
to control if content of prompt, completion, and other messages is captured.
([#2947](https://github.com/open-telemetry/opentelemetry-python-contrib/pull/2947))
- Update OpenAI instrumentation to Semantic Conventions v1.28.0: add new attributes
and switch prompts and completions to log-based events.
([#2925](https://github.com/open-telemetry/opentelemetry-python-contrib/pull/2925))
- Initial OpenAI instrumentation
([#2759](https://github.com/open-telemetry/opentelemetry-python-contrib/pull/2759))
LICENSE 0000664 0000000 0000000 00000026135 15270700723 0034761 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-openai-v2 Apache License
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README.rst 0000664 0000000 0000000 00000015170 15270700723 0035440 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-openai-v2 OpenTelemetry OpenAI Instrumentation
====================================
.. warning::
**This package is deprecated.** Use the
`opentelemetry-instrumentation-genai-openai `_
package instead. ``opentelemetry-instrumentation-openai-v2`` now only
receives security patches. Please
migrate by replacing it with ``opentelemetry-instrumentation-genai-openai``:
.. code-block:: console
pip uninstall opentelemetry-instrumentation-openai-v2
pip install opentelemetry-instrumentation-genai-openai
The replacement package contains **breaking changes** relative to this one.
Review the
`CHANGELOG `_
before upgrading.
|pypi|
.. |pypi| image:: https://badge.fury.io/py/opentelemetry-instrumentation-openai-v2.svg
:target: https://pypi.org/project/opentelemetry-instrumentation-openai-v2/
This library allows tracing LLM requests and logging of messages made by the
`OpenAI Python API library `_. It also captures
the duration of the operations and the number of tokens used as metrics.
Many LLM platforms support the OpenAI SDK. This means systems such as the following are observable with this instrumentation when accessed using it:
.. list-table:: OpenAI Compatible Platforms
:widths: 40 25
:header-rows: 1
* - Name
- gen_ai.system
* - `Azure OpenAI `_
- ``azure.ai.openai``
* - `Gemini `_
- ``gemini``
* - `Perplexity `_
- ``perplexity``
* - `xAI `_ (Compatible with Anthropic)
- ``xai``
* - `DeepSeek `_
- ``deepseek``
* - `Groq `_
- ``groq``
* - `MistralAI `_
- ``mistral_ai``
Installation
------------
If your application is already instrumented with OpenTelemetry, add this
package to your requirements.
::
pip install opentelemetry-instrumentation-openai-v2
If you don't have an OpenAI application, yet, try our `examples `_
which only need a valid OpenAI API key.
Check out `zero-code example `_ for a quick start.
Usage
-----
This section describes how to set up OpenAI instrumentation if you're setting OpenTelemetry up manually.
Check out the `manual example `_ for more details.
Instrumenting all clients
*************************
When using the instrumentor, all clients will automatically trace OpenAI operations including chat completions and embeddings.
You can also optionally capture prompts and completions as log events.
Make sure to configure OpenTelemetry tracing, logging, and events to capture all telemetry emitted by the instrumentation.
.. code-block:: python
from opentelemetry.instrumentation.openai_v2 import OpenAIInstrumentor
OpenAIInstrumentor().instrument()
client = OpenAI()
# Chat completion example
response = client.chat.completions.create(
model="gpt-4o-mini",
messages=[
{"role": "user", "content": "Write a short poem on open telemetry."},
],
)
# Embeddings example
embedding_response = client.embeddings.create(
model="text-embedding-3-small",
input="Generate vector embeddings for this text"
)
Enabling message content
*************************
Message content such as the contents of the prompt, completion, function arguments and return values
are not captured by default. To capture message content as log events, set the environment variable
``OTEL_INSTRUMENTATION_GENAI_CAPTURE_MESSAGE_CONTENT`` to one of the following values:
- ``true`` - Legacy. Used to enable content capturing on ``gen_ai.{role}.message`` and ``gen_ai.choice`` events when
`latest experimental features <#enabling-the-latest-experimental-features>`_ are *not* enabled.
- ``span_only`` - Used to enable content capturing on *span* attributes when
`latest experimental features <#enabling-the-latest-experimental-features>`_ are enabled.
- ``event_only`` - Used to enable content capturing on *event* attributes when
`latest experimental features <#enabling-the-latest-experimental-features>`_ are enabled.
- ``span_and_event`` - Used to enable content capturing on both *span* and *event* attributes when
`latest experimental features <#enabling-the-latest-experimental-features>`_ are enabled.
Uploading prompts and completions
*********************************
To enable the built-in upload hook, set:
- ``OTEL_INSTRUMENTATION_GENAI_COMPLETION_HOOK=upload``
- ``OTEL_INSTRUMENTATION_GENAI_UPLOAD_BASE_PATH`` to an ``fsspec``-compatible URI/path
(e.g. ``/path/to/prompts`` or ``gs://my_bucket``).
Install the ``upload`` extra to pull in ``fsspec``::
pip install opentelemetry-util-genai[upload]
See the `opentelemetry-util-genai
`_
for additional options.
Enabling the latest experimental features
***********************************************
To enable the latest experimental features, set the environment variable
``OTEL_SEMCONV_STABILITY_OPT_IN`` to ``gen_ai_latest_experimental``. Or, if you use
``OTEL_SEMCONV_STABILITY_OPT_IN`` to enable other features, append ``,gen_ai_latest_experimental`` to its value.
Without this setting, OpenAI instrumentation aligns with `Semantic Conventions v1.30.0 `_
and would not capture additional details introduced in later versions.
.. note:: Generative AI semantic conventions are still evolving. The latest experimental features will introduce breaking changes in future releases.
Uninstrument
************
To uninstrument clients, call the uninstrument method:
.. code-block:: python
from opentelemetry.instrumentation.openai_v2 import OpenAIInstrumentor
OpenAIInstrumentor().instrument()
# ...
# Uninstrument all clients
OpenAIInstrumentor().uninstrument()
References
----------
* `OpenTelemetry OpenAI Instrumentation `_
* `OpenTelemetry Project `_
* `OpenTelemetry Python Examples `_
examples/ 0000775 0000000 0000000 00000000000 15270700723 0035563 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-openai-v2 embeddings/ 0000775 0000000 0000000 00000000000 15270700723 0037664 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-openai-v2/examples .env 0000664 0000000 0000000 00000001122 15270700723 0040451 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-openai-v2/examples/embeddings # Update this with your real OpenAI API key
OPENAI_API_KEY=sk-YOUR_API_KEY
# Uncomment to use Ollama instead of OpenAI
# OPENAI_BASE_URL=http://localhost:11434/v1
# OPENAI_API_KEY=unused
# CHAT_MODEL=qwen2.5:0.5b
# Uncomment and change to your OTLP endpoint
# OTEL_EXPORTER_OTLP_ENDPOINT=http://localhost:4317
# OTEL_EXPORTER_OTLP_PROTOCOL=grpc
OTEL_SERVICE_NAME=opentelemetry-python-openai
# Uncomment if your OTLP endpoint doesn't support logs
# OTEL_LOGS_EXPORTER=console
# Change to 'false' to hide prompt and completion content
OTEL_INSTRUMENTATION_GENAI_CAPTURE_MESSAGE_CONTENT=true
README.rst 0000664 0000000 0000000 00000002544 15270700723 0041360 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-openai-v2/examples/embeddings OpenTelemetry OpenAI Embeddings API Instrumentation Example
===========================================================
This is an example of how to instrument OpenAI Embeddings API calls with zero code changes,
using ``opentelemetry-instrument``.
When ``main.py`` is run, it exports traces and metrics to an OTLP
compatible endpoint. Traces include details such as the model used,
dimensions of embeddings, and the duration of the embedding request.
Metrics capture token usage and performance data.
Note: ``.env`` file configures additional environment variables:
- ``OTEL_INSTRUMENTATION_GENAI_CAPTURE_MESSAGE_CONTENT=true`` configures OpenAI instrumentation to capture content on events.
- ``OTEL_LOGS_EXPORTER=otlp`` to specify exporter type.
Setup
-----
Minimally, update the ``.env`` file with your ``OPENAI_API_KEY``. An
OTLP compatible endpoint should be listening for traces and logs on
http://localhost:4317. If not, update ``OTEL_EXPORTER_OTLP_ENDPOINT`` as well.
Next, set up a virtual environment like this:
::
python3 -m venv .venv
source .venv/bin/activate
pip install "python-dotenv[cli]"
pip install -r requirements.txt
Run
---
Run the example like this:
::
dotenv run -- opentelemetry-instrument python main.py
You should see embedding information printed while traces and metrics export to your
configured observability tool.
main.py 0000664 0000000 0000000 00000001572 15270700723 0041167 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-openai-v2/examples/embeddings # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
import os
from openai import OpenAI
def main():
client = OpenAI()
# Create embeddings with OpenAI API
embedding_response = client.embeddings.create(
model=os.getenv("EMBEDDING_MODEL", "text-embedding-3-small"),
input="OpenTelemetry provides observability for your applications.",
)
# Print embedding information
print(f"Model: {embedding_response.model}")
print(f"Dimensions: {len(embedding_response.data[0].embedding)}")
print(
f"Token usage - Prompt: {embedding_response.usage.prompt_tokens}, Total: {embedding_response.usage.total_tokens}"
)
# Print a sample of the embedding vector (first 5 dimensions)
print(f"Embedding sample (first 5 dimensions): {embedding_response.data[0].embedding[:5]}")
if __name__ == "__main__":
main()
requirements.txt 0000664 0000000 0000000 00000000245 15270700723 0043151 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-openai-v2/examples/embeddings openai~=1.57.3
opentelemetry-sdk~=1.36.0
opentelemetry-exporter-otlp-proto-grpc~=1.36.0
opentelemetry-distro~=0.57b0
opentelemetry-instrumentation-openai-v2~=2.2b0
manual/ 0000775 0000000 0000000 00000000000 15270700723 0037040 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-openai-v2/examples .env 0000664 0000000 0000000 00000003022 15270700723 0037626 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-openai-v2/examples/manual # Update this with your real OpenAI API key
OPENAI_API_KEY=sk-YOUR_API_KEY
# Uncomment to use Ollama instead of OpenAI
# OPENAI_BASE_URL=http://localhost:11434/v1
# OPENAI_API_KEY=unused
# CHAT_MODEL=qwen2.5:0.5b
# Uncomment and change to your OTLP endpoint
# OTEL_EXPORTER_OTLP_ENDPOINT=http://localhost:4317
# OTEL_EXPORTER_OTLP_PROTOCOL=grpc
OTEL_SERVICE_NAME=opentelemetry-python-openai
# Remove to hide prompt and completion content
# Possible values (case insensitive):
# - `span_only` - record content on span attibutes
# - `event_only` - record content on event attributes
# - `span_and_event` - record content on both span and event attributes
# - `true` - only used for backward compatibility when
# `gen_ai_latest_experimental` is not set in the
# `OTEL_SEMCONV_STABILITY_OPT_IN` environment variable.
# - everything else - don't record content on any signal
OTEL_INSTRUMENTATION_GENAI_CAPTURE_MESSAGE_CONTENT=span_only
# Enables latest and greatest features available in GenAI semantic conventions.
# Note: since conventions are still in development, using this flag would
# likely result in having breaking changes.
#
# Comment out if you want to use semantic conventions of version 1.30.0.
OTEL_SEMCONV_STABILITY_OPT_IN=gen_ai_latest_experimental
# Uncomment to upload prompts and responses to an fsspec-compatible
# destination instead of or in addition to recording them inline on spans/events.
# OTEL_INSTRUMENTATION_GENAI_COMPLETION_HOOK=upload
# OTEL_INSTRUMENTATION_GENAI_UPLOAD_BASE_PATH=/path/to/prompts
README.rst 0000664 0000000 0000000 00000004414 15270700723 0040532 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-openai-v2/examples/manual OpenTelemetry OpenAI Instrumentation Example
============================================
This is an example of how to instrument OpenAI calls when configuring OpenTelemetry SDK and Instrumentations manually.
When `main.py `_ is run, it exports traces and logs to an OTLP
compatible endpoint. Traces include details such as the model used and the
duration of the chat request. Logs capture the chat request and the generated
response, providing a comprehensive view of the performance and behavior of
your OpenAI requests.
Note: `.env <.env>`_ file configures additional environment variables:
- ``OTEL_INSTRUMENTATION_GENAI_CAPTURE_MESSAGE_CONTENT=span_only`` configures OpenAI instrumentation to capture prompt and completion contents on *span* attributes.
- ``OTEL_SEMCONV_STABILITY_OPT_IN=gen_ai_latest_experimental`` enables latest experimental features.
- ``OTEL_INSTRUMENTATION_GENAI_COMPLETION_HOOK`` (commented out) - uncomment along with ``OTEL_INSTRUMENTATION_GENAI_UPLOAD_BASE_PATH`` to upload prompts and completions to an ``fsspec``-compatible destination instead of recording them inline. Also uncomment the ``opentelemetry-util-genai[upload]`` line in `requirements.txt `_ and reinstall.
Setup
-----
Minimally, update the `.env <.env>`_ file with your ``OPENAI_API_KEY``. An
OTLP compatible endpoint should be listening for traces and logs on
http://localhost:4317. If not, update ``OTEL_EXPORTER_OTLP_ENDPOINT`` as well.
Next, set up a virtual environment like this:
::
python3 -m venv .venv
source .venv/bin/activate
pip install "python-dotenv[cli]"
pip install -r requirements.txt
Run
---
Run the example like this:
::
dotenv run -- python main.py
You should see a poem generated by OpenAI while traces and logs export to your
configured observability tool.
Custom completion hook
----------------------
`custom_hook.py `_ is a variant of ``main.py`` that passes a
custom ``CompletionHook`` implementation programmatically via
``OpenAIInstrumentor().instrument(completion_hook=...)``. The example hook
prints prompts and completions to stdout; real hooks typically forward content
to external storage and record reference URIs on the span/log_record.
Run it the same way:
::
dotenv run -- python custom_hook.py
custom_hook.py 0000664 0000000 0000000 00000005357 15270700723 0041756 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-openai-v2/examples/manual # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
# pylint: skip-file
"""Same as main.py, but instruments OpenAI with a custom CompletionHook
that prints prompts and completions to stdout.
Run with: dotenv run -- python custom_hook.py
"""
import os
from openai import OpenAI
from opentelemetry import _logs, metrics, trace
from opentelemetry.exporter.otlp.proto.grpc._log_exporter import (
OTLPLogExporter,
)
from opentelemetry.exporter.otlp.proto.grpc.metric_exporter import (
OTLPMetricExporter,
)
from opentelemetry.exporter.otlp.proto.grpc.trace_exporter import (
OTLPSpanExporter,
)
from opentelemetry.instrumentation.openai_v2 import OpenAIInstrumentor
from opentelemetry.sdk._logs import LoggerProvider
from opentelemetry.sdk._logs.export import BatchLogRecordProcessor
from opentelemetry.sdk.metrics import MeterProvider
from opentelemetry.sdk.metrics.export import PeriodicExportingMetricReader
from opentelemetry.sdk.trace import TracerProvider
from opentelemetry.sdk.trace.export import BatchSpanProcessor
from opentelemetry.util.genai.completion_hook import CompletionHook
from opentelemetry.util.genai.types import (
InputMessage,
MessagePart,
OutputMessage,
ToolDefinition,
)
class PrintCompletionHook(CompletionHook):
"""Minimal CompletionHook that prints inputs/outputs to stdout.
Real hooks typically forward content to external storage (object store,
database, etc.) and record reference URIs on the span/log_record.
"""
def on_completion(
self,
*,
inputs: list[InputMessage],
outputs: list[OutputMessage],
system_instruction: list[MessagePart],
tool_definitions: list[ToolDefinition] | None = None,
span=None,
log_record=None,
) -> None:
print(f"[hook] inputs: {inputs}")
print(f"[hook] outputs: {outputs}")
trace.set_tracer_provider(TracerProvider())
trace.get_tracer_provider().add_span_processor(BatchSpanProcessor(OTLPSpanExporter()))
_logs.set_logger_provider(LoggerProvider())
_logs.get_logger_provider().add_log_record_processor(BatchLogRecordProcessor(OTLPLogExporter()))
metrics.set_meter_provider(
MeterProvider(
metric_readers=[
PeriodicExportingMetricReader(OTLPMetricExporter()),
]
)
)
OpenAIInstrumentor().instrument(completion_hook=PrintCompletionHook())
def main():
client = OpenAI()
chat_completion = client.chat.completions.create(
model=os.getenv("CHAT_MODEL", "gpt-4o-mini"),
messages=[
{
"role": "user",
"content": "Write a short poem on OpenTelemetry.",
},
],
)
print(chat_completion.choices[0].message.content)
if __name__ == "__main__":
main()
main.py 0000664 0000000 0000000 00000003574 15270700723 0040347 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-openai-v2/examples/manual # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
# pylint: skip-file
import os
from openai import OpenAI
# NOTE: OpenTelemetry Python Logs API is in beta
from opentelemetry import _logs, metrics, trace
from opentelemetry.exporter.otlp.proto.grpc._log_exporter import (
OTLPLogExporter,
)
from opentelemetry.exporter.otlp.proto.grpc.metric_exporter import (
OTLPMetricExporter,
)
from opentelemetry.exporter.otlp.proto.grpc.trace_exporter import (
OTLPSpanExporter,
)
from opentelemetry.instrumentation.openai_v2 import OpenAIInstrumentor
from opentelemetry.sdk._logs import LoggerProvider
from opentelemetry.sdk._logs.export import BatchLogRecordProcessor
from opentelemetry.sdk.metrics import MeterProvider
from opentelemetry.sdk.metrics.export import PeriodicExportingMetricReader
from opentelemetry.sdk.trace import TracerProvider
from opentelemetry.sdk.trace.export import BatchSpanProcessor
# configure tracing
trace.set_tracer_provider(TracerProvider())
trace.get_tracer_provider().add_span_processor(BatchSpanProcessor(OTLPSpanExporter()))
# configure logging
_logs.set_logger_provider(LoggerProvider())
_logs.get_logger_provider().add_log_record_processor(BatchLogRecordProcessor(OTLPLogExporter()))
# configure metrics
metrics.set_meter_provider(
MeterProvider(
metric_readers=[
PeriodicExportingMetricReader(
OTLPMetricExporter(),
),
]
)
)
# instrument OpenAI
OpenAIInstrumentor().instrument()
def main():
client = OpenAI()
chat_completion = client.chat.completions.create(
model=os.getenv("CHAT_MODEL", "gpt-4o-mini"),
messages=[
{
"role": "user",
"content": "Write a short poem on OpenTelemetry.",
},
],
)
print(chat_completion.choices[0].message.content)
if __name__ == "__main__":
main()
requirements.txt 0000664 0000000 0000000 00000000463 15270700723 0042327 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-openai-v2/examples/manual openai~=1.57.3
opentelemetry-sdk~=1.36.0
opentelemetry-exporter-otlp-proto-grpc~=1.36.0
opentelemetry-instrumentation-openai-v2~=2.1b0
# Uncomment to enable the upload completion hook (pulls in fsspec).
# Required when OTEL_INSTRUMENTATION_GENAI_COMPLETION_HOOK=upload.
# opentelemetry-util-genai[upload]
zero-code/ 0000775 0000000 0000000 00000000000 15270700723 0037452 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-openai-v2/examples .env 0000664 0000000 0000000 00000003147 15270700723 0040250 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-openai-v2/examples/zero-code # Update this with your real OpenAI API key
OPENAI_API_KEY=sk-YOUR_API_KEY
# Uncomment to use Ollama instead of OpenAI
# OPENAI_BASE_URL=http://localhost:11434/v1
# OPENAI_API_KEY=unused
# CHAT_MODEL=qwen2.5:0.5b
# Uncomment and change to your OTLP endpoint
# OTEL_EXPORTER_OTLP_ENDPOINT=http://localhost:4317
# OTEL_EXPORTER_OTLP_PROTOCOL=grpc
OTEL_SERVICE_NAME=opentelemetry-python-openai
# Uncomment if your OTLP endpoint doesn't support logs
# OTEL_LOGS_EXPORTER=console
# Remove to hide prompt and completion content
# Possible values (case insensitive):
# - `span_only` - record content on span attibutes
# - `event_only` - record content on event attributes
# - `span_and_event` - record content on both span and event attributes
# - `true` - only used for backward compatibility when
# `gen_ai_latest_experimental` is not set in the
# `OTEL_SEMCONV_STABILITY_OPT_IN` environment variable.
# - everything else - don't record content on any signal
OTEL_INSTRUMENTATION_GENAI_CAPTURE_MESSAGE_CONTENT=span_only
# Enables latest and greatest features available in GenAI semantic conventions.
# Note: since conventions are still in development, using this flag would
# likely result in having breaking changes.
#
# Comment out if you want to use semantic conventions of version 1.30.0.
OTEL_SEMCONV_STABILITY_OPT_IN=gen_ai_latest_experimental
# Uncomment to upload prompts and responses to an fsspec-compatible
# destination instead of or in addition to recording them inline on spans/events.
# OTEL_INSTRUMENTATION_GENAI_COMPLETION_HOOK=upload
# OTEL_INSTRUMENTATION_GENAI_UPLOAD_BASE_PATH=/path/to/prompts
README.rst 0000664 0000000 0000000 00000003613 15270700723 0041144 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-openai-v2/examples/zero-code OpenTelemetry OpenAI Zero-Code Instrumentation Example
======================================================
This is an example of how to instrument OpenAI calls with zero code changes,
using `opentelemetry-instrument`.
When `main.py `_ is run, it exports traces and logs to an OTLP
compatible endpoint. Traces include details such as the model used and the
duration of the chat request. Logs capture the chat request and the generated
response, providing a comprehensive view of the performance and behavior of
your OpenAI requests.
Note: `.env <.env>`_ file configures additional environment variables:
- ``OTEL_INSTRUMENTATION_GENAI_CAPTURE_MESSAGE_CONTENT=span_only`` configures OpenAI instrumentation to capture prompt and completion contents on *span* attributes.
- ``OTEL_LOGS_EXPORTER=otlp`` to specify exporter type.
- ``OTEL_SEMCONV_STABILITY_OPT_IN=gen_ai_latest_experimental`` enables latest experimental features.
- ``OTEL_INSTRUMENTATION_GENAI_COMPLETION_HOOK`` (commented out) - uncomment along with ``OTEL_INSTRUMENTATION_GENAI_UPLOAD_BASE_PATH`` to upload prompts and completions to an ``fsspec``-compatible destination instead of recording them inline. Also uncomment the ``opentelemetry-util-genai[upload]`` line in `requirements.txt `_ and reinstall.
Setup
-----
Minimally, update the `.env <.env>`_ file with your ``OPENAI_API_KEY``. An
OTLP compatible endpoint should be listening for traces and logs on
http://localhost:4317. If not, update ``OTEL_EXPORTER_OTLP_ENDPOINT`` as well.
Next, set up a virtual environment like this:
::
python3 -m venv .venv
source .venv/bin/activate
pip install "python-dotenv[cli]"
pip install -r requirements.txt
Run
---
Run the example like this:
::
dotenv run -- opentelemetry-instrument python main.py
You should see a poem generated by OpenAI while traces and logs export to your
configured observability tool.
main.py 0000664 0000000 0000000 00000001004 15270700723 0040743 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-openai-v2/examples/zero-code # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
import os
from openai import OpenAI
def main():
client = OpenAI()
chat_completion = client.chat.completions.create(
model=os.getenv("CHAT_MODEL", "gpt-4o-mini"),
messages=[
{
"role": "user",
"content": "Write a short poem on OpenTelemetry.",
},
],
)
print(chat_completion.choices[0].message.content)
if __name__ == "__main__":
main()
requirements.txt 0000664 0000000 0000000 00000000520 15270700723 0042733 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-openai-v2/examples/zero-code openai~=1.57.3
opentelemetry-sdk~=1.36.0
opentelemetry-exporter-otlp-proto-grpc~=1.36.0
opentelemetry-distro~=0.57b0
opentelemetry-instrumentation-openai-v2~=2.1b0
# Uncomment to enable the upload completion hook (pulls in fsspec).
# Required when OTEL_INSTRUMENTATION_GENAI_COMPLETION_HOOK=upload.
# opentelemetry-util-genai[upload]
pyproject.toml 0000664 0000000 0000000 00000004600 15270700723 0036661 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-openai-v2 [build-system]
requires = ["hatchling"]
build-backend = "hatchling.build"
[project]
name = "opentelemetry-instrumentation-openai-v2"
dynamic = ["version"]
description = "OpenTelemetry Official OpenAI instrumentation"
readme = "README.rst"
license = "Apache-2.0"
requires-python = ">=3.10"
authors = [
{ name = "OpenTelemetry Authors", email = "cncf-opentelemetry-contributors@lists.cncf.io" },
]
classifiers = [
"Development Status :: 4 - Beta",
"Intended Audience :: Developers",
"License :: OSI Approved :: Apache Software License",
"Programming Language :: Python",
"Programming Language :: Python :: 3",
"Programming Language :: Python :: 3.10",
"Programming Language :: Python :: 3.11",
"Programming Language :: Python :: 3.12",
"Programming Language :: Python :: 3.13",
"Programming Language :: Python :: 3.14",
]
dependencies = [
"opentelemetry-api ~= 1.40",
"opentelemetry-instrumentation ~= 0.61b0",
"opentelemetry-semantic-conventions ~= 0.61b0",
"opentelemetry-util-genai > 0.4b0, < 0.6b0",
"typing-extensions >= 4.5.0",
]
[project.optional-dependencies]
instruments = ["openai >= 1.26.0"]
[project.entry-points.opentelemetry_instrumentor]
openai = "opentelemetry.instrumentation.openai_v2:OpenAIInstrumentor"
[project.urls]
Homepage = "https://github.com/open-telemetry/opentelemetry-python-contrib/tree/main/instrumentation-genai/opentelemetry-instrumentation-openai-v2"
Repository = "https://github.com/open-telemetry/opentelemetry-python-contrib"
[tool.hatch.version]
path = "src/opentelemetry/instrumentation/openai_v2/version.py"
[tool.hatch.build.targets.sdist]
include = ["/src", "/tests"]
[tool.hatch.build.targets.wheel]
packages = ["src/opentelemetry"]
[tool.towncrier]
directory = ".changelog"
filename = "CHANGELOG.md"
start_string = "\n"
template = "../../scripts/changelog_template.j2"
issue_format = "[#{issue}](https://github.com/open-telemetry/opentelemetry-python-contrib/pull/{issue})"
wrap = true
issue_pattern = "^(\\d+)"
[[tool.towncrier.type]]
directory = "added"
name = "Added"
showcontent = true
[[tool.towncrier.type]]
directory = "changed"
name = "Changed"
showcontent = true
[[tool.towncrier.type]]
directory = "deprecated"
name = "Deprecated"
showcontent = true
[[tool.towncrier.type]]
directory = "removed"
name = "Removed"
showcontent = true
[[tool.towncrier.type]]
directory = "fixed"
name = "Fixed"
showcontent = true
src/ 0000775 0000000 0000000 00000000000 15270700723 0034534 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-openai-v2 opentelemetry/ 0000775 0000000 0000000 00000000000 15270700723 0037430 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-openai-v2/src instrumentation/ 0000775 0000000 0000000 00000000000 15270700723 0042673 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-openai-v2/src/opentelemetry openai_v2/ 0000775 0000000 0000000 00000000000 15270700723 0044555 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-openai-v2/src/opentelemetry/instrumentation __init__.py 0000664 0000000 0000000 00000017475 15270700723 0046704 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-openai-v2/src/opentelemetry/instrumentation/openai_v2 # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
"""
OpenAI client instrumentation supporting `openai`, it can be enabled by
using ``OpenAIInstrumentor``.
.. _openai: https://pypi.org/project/openai/
Usage
-----
.. code:: python
from openai import OpenAI
from opentelemetry.instrumentation.openai_v2 import OpenAIInstrumentor
OpenAIInstrumentor().instrument()
client = OpenAI()
response = client.chat.completions.create(
model="gpt-4o-mini",
messages=[
{"role": "user", "content": "Write a short poem on open telemetry."},
],
)
Configuration
-------------
By default, the instrumentation aligns with `Semantic Conventions v1.30.0
`_
and does not capture prompt or completion content. Behavior is controlled
via environment variables:
- ``OTEL_SEMCONV_STABILITY_OPT_IN=gen_ai_latest_experimental`` - opt into the
latest GenAI semantic conventions. Required to access the newer attributes
and the ``span_only`` / ``event_only`` / ``span_and_event`` content modes.
Without this flag, the instrumentation stays on v1.30.0 conventions.
- ``OTEL_INSTRUMENTATION_GENAI_CAPTURE_MESSAGE_CONTENT`` - enable capture of
prompts, completions, tool arguments, and return values. Set to ``true``
on the legacy path, or one of ``span_only``, ``event_only``,
``span_and_event`` when experimental conventions are enabled.
- ``OTEL_INSTRUMENTATION_GENAI_COMPLETION_HOOK=upload`` together with
``OTEL_INSTRUMENTATION_GENAI_UPLOAD_BASE_PATH=`` - upload
prompts and completions to an ``fsspec``-compatible destination
(local filesystem, ``gs://``, ``s3://``, etc.) and record reference URIs as
``gen_ai.input.messages.ref`` / ``gen_ai.output.messages.ref`` attributes.
Inline content is not captured unless
``OTEL_INSTRUMENTATION_GENAI_CAPTURE_MESSAGE_CONTENT`` is also set.
See the `opentelemetry-util-genai README
`_
for the full list of GenAI configuration variables.
A custom ``CompletionHook`` implementation can also be passed programmatically::
OpenAIInstrumentor().instrument(completion_hook=my_hook)
When provided, this takes precedence over the hook resolved from
``OTEL_INSTRUMENTATION_GENAI_COMPLETION_HOOK``.
API
---
"""
from collections.abc import Collection
from importlib import import_module
from typing_extensions import deprecated
from wrapt import wrap_function_wrapper
from opentelemetry._logs import get_logger
from opentelemetry.instrumentation.instrumentor import BaseInstrumentor
from opentelemetry.instrumentation.openai_v2.package import _instruments
from opentelemetry.instrumentation.openai_v2.utils import is_content_enabled
from opentelemetry.instrumentation.utils import unwrap
from opentelemetry.metrics import get_meter
from opentelemetry.semconv.schemas import Schemas
from opentelemetry.trace import get_tracer
from opentelemetry.util.genai.completion_hook import load_completion_hook
from opentelemetry.util.genai.handler import (
TelemetryHandler,
)
from opentelemetry.util.genai.utils import is_experimental_mode
from .instruments import Instruments
from .patch import (
async_chat_completions_create_v_new,
async_chat_completions_create_v_old,
async_embeddings_create,
chat_completions_create_v_new,
chat_completions_create_v_old,
embeddings_create,
)
from .patch_responses import (
responses_create,
)
@deprecated(
"opentelemetry-instrumentation-openai-v2 is deprecated. Use the "
"opentelemetry-instrumentation-genai-openai package instead. This package "
"only receives security patches."
)
class OpenAIInstrumentor(BaseInstrumentor):
"""OpenTelemetry instrumentation for the OpenAI Python client.
.. deprecated:: 2.5b0
Use the ``opentelemetry-instrumentation-genai-openai`` package instead.
This package only receives security patches.
"""
def __init__(self):
self._meter = None
def instrumentation_dependencies(self) -> Collection[str]:
return _instruments
def _instrument(self, **kwargs):
"""Enable OpenAI instrumentation."""
latest_experimental_enabled = is_experimental_mode()
tracer_provider = kwargs.get("tracer_provider")
tracer = get_tracer(
__name__,
"",
tracer_provider,
schema_url=Schemas.V1_30_0.value, # only used on the legacy path
)
logger_provider = kwargs.get("logger_provider")
logger = get_logger(
__name__,
"",
logger_provider=logger_provider,
schema_url=Schemas.V1_30_0.value, # only used on the legacy path
)
meter_provider = kwargs.get("meter_provider")
self._meter = get_meter(
__name__,
"",
meter_provider,
schema_url=Schemas.V1_30_0.value, # only used on the legacy path
)
instruments = Instruments(self._meter)
handler = TelemetryHandler(
tracer_provider=tracer_provider,
meter_provider=meter_provider,
logger_provider=logger_provider,
completion_hook=kwargs.get("completion_hook") or load_completion_hook(),
)
wrap_function_wrapper(
"openai.resources.chat.completions",
"Completions.create",
(
chat_completions_create_v_new(handler)
if latest_experimental_enabled
else chat_completions_create_v_old(tracer, logger, instruments, is_content_enabled())
),
)
wrap_function_wrapper(
"openai.resources.chat.completions",
"AsyncCompletions.create",
(
async_chat_completions_create_v_new(handler)
if latest_experimental_enabled
else async_chat_completions_create_v_old(tracer, logger, instruments, is_content_enabled())
),
)
# Add instrumentation for the embeddings API
wrap_function_wrapper(
"openai.resources.embeddings",
"Embeddings.create",
embeddings_create(tracer, instruments, latest_experimental_enabled),
)
wrap_function_wrapper(
"openai.resources.embeddings",
"AsyncEmbeddings.create",
async_embeddings_create(tracer, instruments, latest_experimental_enabled),
)
responses_module = _get_responses_module()
# Responses instrumentation is intentionally limited to the latest
# experimental semconv path. Unlike chat completions, we do not carry
# a second legacy wrapper here; the current implementation is built on
# the inference handler lifecycle and would need a separate old-path
# implementation to support legacy semconv mode.
if responses_module is not None and latest_experimental_enabled:
wrap_function_wrapper(
"openai.resources.responses.responses",
"Responses.create",
responses_create(handler),
)
def _uninstrument(self, **kwargs):
import openai # pylint: disable=import-outside-toplevel # noqa: PLC0415
unwrap(openai.resources.chat.completions.Completions, "create")
unwrap(openai.resources.chat.completions.AsyncCompletions, "create")
unwrap(openai.resources.embeddings.Embeddings, "create")
unwrap(openai.resources.embeddings.AsyncEmbeddings, "create")
responses_module = _get_responses_module()
if responses_module is not None:
unwrap(responses_module.Responses, "create")
def _get_responses_module():
try:
return import_module("openai.resources.responses.responses")
except ImportError:
return None
chat_buffers.py 0000664 0000000 0000000 00000003135 15270700723 0047564 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-openai-v2/src/opentelemetry/instrumentation/openai_v2 # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
from __future__ import annotations
from openai.types.chat.chat_completion_chunk import ChoiceDeltaToolCall
class ToolCallBuffer:
def __init__(
self,
index: int,
tool_call_id: str | None,
function_name: str | None,
) -> None:
self.index: int = index
self.function_name: str | None = function_name
self.tool_call_id: str | None = tool_call_id
self.arguments: list[str] = []
def append_arguments(self, arguments: str | None) -> None:
if arguments is not None:
self.arguments.append(arguments)
class ChoiceBuffer:
def __init__(self, index: int) -> None:
self.index: int = index
self.finish_reason: str | None = None
self.text_content: list[str] = []
self.tool_calls_buffers: list[ToolCallBuffer | None] = []
def append_text_content(self, content: str) -> None:
self.text_content.append(content)
def append_tool_call(self, tool_call: ChoiceDeltaToolCall) -> None:
idx = tool_call.index
for _ in range(len(self.tool_calls_buffers), idx + 1):
self.tool_calls_buffers.append(None)
function = tool_call.function
buffer = self.tool_calls_buffers[idx]
if buffer is None:
buffer = ToolCallBuffer(
idx,
tool_call.id,
function.name if function else None,
)
self.tool_calls_buffers[idx] = buffer
if function:
buffer.append_arguments(function.arguments)
chat_wrappers.py 0000664 0000000 0000000 00000015560 15270700723 0050000 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-openai-v2/src/opentelemetry/instrumentation/openai_v2 # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
from __future__ import annotations
import json
from openai import AsyncStream, Stream
from openai.types.chat import ChatCompletionChunk
from opentelemetry.semconv._incubating.attributes import (
openai_attributes as OpenAIAttributes,
)
from opentelemetry.util.genai.invocation import InferenceInvocation
from opentelemetry.util.genai.stream import (
AsyncStreamWrapper,
SyncStreamWrapper,
)
from opentelemetry.util.genai.types import (
OutputMessage,
Text,
ToolCallRequest,
)
from .chat_buffers import ChoiceBuffer
class _ChatStreamMixin:
"""Chat-specific hooks shared by sync and async stream wrappers."""
_self_invocation: InferenceInvocation
_self_capture_content: bool
_self_choice_buffers: list[ChoiceBuffer]
_self_response_id: str | None
_self_response_model: str | None
_self_service_tier: str | None
_self_prompt_tokens: int | None
_self_completion_tokens: int | None
def _set_response_model(self, chunk: ChatCompletionChunk) -> None:
if self._self_response_model:
return
if chunk.model:
self._self_response_model = chunk.model
def _set_response_id(self, chunk: ChatCompletionChunk) -> None:
if self._self_response_id:
return
if chunk.id:
self._self_response_id = chunk.id
def _set_response_service_tier(self, chunk: ChatCompletionChunk) -> None:
if self._self_service_tier:
return
service_tier = getattr(chunk, "service_tier", None)
if service_tier:
self._self_service_tier = service_tier
def _build_streaming_response(self, chunk: ChatCompletionChunk) -> None:
if chunk.choices is None:
return
for choice in chunk.choices:
if not choice.delta:
continue
for idx in range(len(self._self_choice_buffers), choice.index + 1):
self._self_choice_buffers.append(ChoiceBuffer(idx))
if choice.finish_reason:
self._self_choice_buffers[choice.index].finish_reason = choice.finish_reason
if choice.delta.content is not None:
self._self_choice_buffers[choice.index].append_text_content(choice.delta.content)
if choice.delta.tool_calls is not None:
for tool_call in choice.delta.tool_calls:
self._self_choice_buffers[choice.index].append_tool_call(tool_call)
def _set_usage(self, chunk: ChatCompletionChunk) -> None:
usage = getattr(chunk, "usage", None)
if usage:
self._self_completion_tokens = usage.completion_tokens
self._self_prompt_tokens = usage.prompt_tokens
def _process_chunk(self, chunk: ChatCompletionChunk) -> None:
self._set_response_id(chunk)
self._set_response_model(chunk)
self._set_response_service_tier(chunk)
self._build_streaming_response(chunk)
self._set_usage(chunk)
def _set_output_messages(self) -> None:
if not self._self_capture_content: # optimization
return
output_messages = []
for choice in self._self_choice_buffers:
message = OutputMessage(
role="assistant",
finish_reason=choice.finish_reason or "error",
parts=[],
)
if choice.text_content:
message.parts.append(Text(content="".join(choice.text_content)))
if choice.tool_calls_buffers:
tool_calls = []
for tool_call in filter(None, choice.tool_calls_buffers):
arguments = None
arguments_str = "".join(tool_call.arguments)
if arguments_str:
try:
arguments = json.loads(arguments_str)
except json.JSONDecodeError:
arguments = arguments_str
tool_call_part = ToolCallRequest(
name=tool_call.function_name,
id=tool_call.tool_call_id,
arguments=arguments,
)
tool_calls.append(tool_call_part)
message.parts.extend(tool_calls)
output_messages.append(message)
self._self_invocation.output_messages = output_messages
def _on_stream_end(self) -> None:
self._cleanup()
def _on_stream_error(self, error: BaseException) -> None:
self._cleanup(error)
def parse(self) -> _ChatStreamMixin:
"""Called when using with_raw_response with stream=True."""
return self
def _cleanup(self, error: BaseException | None = None) -> None:
self._self_invocation.response_model_name = self._self_response_model
self._self_invocation.response_id = self._self_response_id
self._self_invocation.input_tokens = self._self_prompt_tokens
self._self_invocation.output_tokens = self._self_completion_tokens
finish_reasons = [choice.finish_reason for choice in self._self_choice_buffers if choice.finish_reason]
if finish_reasons:
self._self_invocation.finish_reasons = finish_reasons
if self._self_service_tier:
self._self_invocation.attributes.update(
{OpenAIAttributes.OPENAI_RESPONSE_SERVICE_TIER: self._self_service_tier},
)
self._set_output_messages()
if error:
self._self_invocation.fail(error)
else:
self._self_invocation.stop()
class ChatStreamWrapper(
_ChatStreamMixin,
SyncStreamWrapper[ChatCompletionChunk],
):
def __init__(
self,
stream: Stream[ChatCompletionChunk],
invocation: InferenceInvocation,
capture_content: bool,
) -> None:
super().__init__(stream)
self._self_invocation = invocation
self._self_choice_buffers = []
self._self_capture_content = capture_content
self._self_response_id = None
self._self_response_model = None
self._self_service_tier = None
self._self_prompt_tokens = None
self._self_completion_tokens = None
class AsyncChatStreamWrapper(
_ChatStreamMixin,
AsyncStreamWrapper[ChatCompletionChunk],
):
def __init__(
self,
stream: AsyncStream[ChatCompletionChunk],
invocation: InferenceInvocation,
capture_content: bool,
) -> None:
super().__init__(stream)
self._self_invocation = invocation
self._self_choice_buffers = []
self._self_capture_content = capture_content
self._self_response_id = None
self._self_response_model = None
self._self_service_tier = None
self._self_prompt_tokens = None
self._self_completion_tokens = None
__all__ = [
"AsyncChatStreamWrapper",
"ChatStreamWrapper",
]
instruments.py 0000664 0000000 0000000 00000000721 15270700723 0047522 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-openai-v2/src/opentelemetry/instrumentation/openai_v2 # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
from opentelemetry.metrics import Histogram, Meter
from opentelemetry.util.genai.instruments import (
create_duration_histogram,
create_token_histogram,
)
class Instruments:
def __init__(self, meter: Meter):
self.operation_duration_histogram: Histogram = create_duration_histogram(meter)
self.token_usage_histogram: Histogram = create_token_histogram(meter)
package.py 0000664 0000000 0000000 00000000215 15270700723 0046520 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-openai-v2/src/opentelemetry/instrumentation/openai_v2 # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
_instruments = ("openai >= 1.26.0",)
_supports_metrics = True
patch.py 0000664 0000000 0000000 00000063614 15270700723 0046240 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-openai-v2/src/opentelemetry/instrumentation/openai_v2 # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
from timeit import default_timer
from typing import Any
from openai import AsyncStream, Stream
from opentelemetry._logs import Logger, LogRecord
from opentelemetry.context import get_current
from opentelemetry.semconv._incubating.attributes import (
gen_ai_attributes as GenAIAttributes,
)
from opentelemetry.semconv._incubating.attributes import (
openai_attributes as OpenAIAttributes,
)
from opentelemetry.semconv._incubating.attributes import (
server_attributes as ServerAttributes,
)
from opentelemetry.trace import Span, SpanKind, Tracer
from opentelemetry.trace.propagation import set_span_in_context
from opentelemetry.util.genai.handler import TelemetryHandler
from opentelemetry.util.genai.invocation import InferenceInvocation
from opentelemetry.util.genai.types import (
Error,
)
from .chat_buffers import ChoiceBuffer
from .chat_wrappers import AsyncChatStreamWrapper, ChatStreamWrapper
from .instruments import Instruments
from .utils import (
_prepare_output_messages,
choice_to_event,
create_chat_invocation,
get_llm_request_attributes,
handle_span_exception,
is_streaming,
message_to_event,
set_span_attribute,
)
def chat_completions_create_v_old(
tracer: Tracer,
logger: Logger,
instruments: Instruments,
capture_content: bool,
):
"""Wrap the `create` method of the `ChatCompletion` class to trace it."""
def traced_method(wrapped, instance, args, kwargs):
span_attributes = {**get_llm_request_attributes(kwargs, instance, False)}
operation_name = span_attributes[GenAIAttributes.GEN_AI_OPERATION_NAME]
model = span_attributes.get(GenAIAttributes.GEN_AI_REQUEST_MODEL)
span_name = f"{operation_name} {model}" if model else operation_name
with tracer.start_as_current_span(
name=span_name,
kind=SpanKind.CLIENT,
attributes=span_attributes,
end_on_exit=False,
) as span:
for message in kwargs.get("messages", []):
logger.emit(message_to_event(message, capture_content))
start = default_timer()
result = None
error_type = None
try:
result = wrapped(*args, **kwargs)
if hasattr(result, "parse"):
# result is of type LegacyAPIResponse, call parse to get the actual response
parsed_result = result.parse()
else:
parsed_result = result
if is_streaming(kwargs):
return LegacyChatStreamWrapper(parsed_result, span, logger, capture_content)
if span.is_recording():
_set_response_attributes(span, parsed_result)
for choice in getattr(parsed_result, "choices", []):
logger.emit(choice_to_event(choice, capture_content))
span.end()
return result
except Exception as error:
error_type = type(error).__qualname__
handle_span_exception(span, error)
raise
finally:
duration = max((default_timer() - start), 0)
_record_metrics(
instruments,
duration,
result,
span_attributes,
error_type,
GenAIAttributes.GenAiOperationNameValues.CHAT.value,
)
return traced_method
def chat_completions_create_v_new(
handler: TelemetryHandler,
):
"""Wrap the `create` method of the `ChatCompletion` class to trace it."""
capture_content = handler.should_capture_content()
def traced_method(wrapped, instance, args, kwargs):
chat_invocation = create_chat_invocation(handler, kwargs, instance, capture_content=capture_content)
try:
result = wrapped(*args, **kwargs)
if hasattr(result, "parse"):
# result is of type LegacyAPIResponse, call parse to get the actual response
parsed_result = result.parse()
else:
parsed_result = result
if is_streaming(kwargs):
return ChatStreamWrapper(parsed_result, chat_invocation, capture_content)
_set_response_properties(chat_invocation, parsed_result, capture_content)
chat_invocation.stop()
return result
except Exception as error:
chat_invocation.fail(Error(type=type(error), message=str(error)))
raise
return traced_method
def async_chat_completions_create_v_old(
tracer: Tracer,
logger: Logger,
instruments: Instruments,
capture_content: bool,
):
"""Wrap the `create` method of the `AsyncChatCompletion` class to trace it."""
async def traced_method(wrapped, instance, args, kwargs):
span_attributes = {**get_llm_request_attributes(kwargs, instance, False)}
operation_name = span_attributes[GenAIAttributes.GEN_AI_OPERATION_NAME]
model = span_attributes.get(GenAIAttributes.GEN_AI_REQUEST_MODEL)
span_name = f"{operation_name} {model}" if model else operation_name
with tracer.start_as_current_span(
name=span_name,
kind=SpanKind.CLIENT,
attributes=span_attributes,
end_on_exit=False,
) as span:
for message in kwargs.get("messages", []):
logger.emit(message_to_event(message, capture_content))
start = default_timer()
result = None
error_type = None
try:
result = await wrapped(*args, **kwargs)
if hasattr(result, "parse"):
# result is of type LegacyAPIResponse, calling parse to get the actual response
parsed_result = result.parse()
else:
parsed_result = result
if is_streaming(kwargs):
return AsyncLegacyChatStreamWrapper(parsed_result, span, logger, capture_content)
if span.is_recording():
_set_response_attributes(span, parsed_result)
for choice in getattr(parsed_result, "choices", []):
logger.emit(choice_to_event(choice, capture_content))
span.end()
return result
except Exception as error:
error_type = type(error).__qualname__
handle_span_exception(span, error)
raise
finally:
duration = max((default_timer() - start), 0)
_record_metrics(
instruments,
duration,
result,
span_attributes,
error_type,
GenAIAttributes.GenAiOperationNameValues.CHAT.value,
)
return traced_method
def async_chat_completions_create_v_new(
handler: TelemetryHandler,
):
"""Wrap the `create` method of the `AsyncChatCompletion` class to trace it."""
capture_content = handler.should_capture_content()
async def traced_method(wrapped, instance, args, kwargs):
chat_invocation = create_chat_invocation(handler, kwargs, instance, capture_content=capture_content)
try:
result = await wrapped(*args, **kwargs)
if hasattr(result, "parse"):
# result is of type LegacyAPIResponse, calling parse to get the actual response
parsed_result = result.parse()
else:
parsed_result = result
if is_streaming(kwargs):
return AsyncChatStreamWrapper(parsed_result, chat_invocation, capture_content)
_set_response_properties(chat_invocation, parsed_result, capture_content)
chat_invocation.stop()
return result
except Exception as error:
chat_invocation.fail(Error(type=type(error), message=str(error)))
raise
return traced_method
def embeddings_create(
tracer: Tracer,
instruments: Instruments,
latest_experimental_enabled: bool,
):
"""Wrap the `create` method of the `Embeddings` class to trace it."""
def traced_method(wrapped, instance, args, kwargs):
span_attributes = get_llm_request_attributes(
kwargs,
instance,
latest_experimental_enabled,
GenAIAttributes.GenAiOperationNameValues.EMBEDDINGS.value,
)
span_name = _get_embeddings_span_name(span_attributes)
with tracer.start_as_current_span(
name=span_name,
kind=SpanKind.CLIENT,
attributes=span_attributes,
end_on_exit=True,
) as span:
start = default_timer()
result = None
error_type = None
try:
result = wrapped(*args, **kwargs)
if span.is_recording():
_set_embeddings_response_attributes(span, result)
return result
except Exception as error:
error_type = type(error).__qualname__
handle_span_exception(span, error)
raise
finally:
duration = max((default_timer() - start), 0)
_record_metrics(
instruments,
duration,
result,
span_attributes,
error_type,
GenAIAttributes.GenAiOperationNameValues.EMBEDDINGS.value,
)
return traced_method
def async_embeddings_create(
tracer: Tracer,
instruments: Instruments,
latest_experimental_enabled: bool,
):
"""Wrap the `create` method of the `AsyncEmbeddings` class to trace it."""
async def traced_method(wrapped, instance, args, kwargs):
span_attributes = get_llm_request_attributes(
kwargs,
instance,
latest_experimental_enabled,
GenAIAttributes.GenAiOperationNameValues.EMBEDDINGS.value,
)
span_name = _get_embeddings_span_name(span_attributes)
with tracer.start_as_current_span(
name=span_name,
kind=SpanKind.CLIENT,
attributes=span_attributes,
end_on_exit=True,
) as span:
start = default_timer()
result = None
error_type = None
try:
result = await wrapped(*args, **kwargs)
if span.is_recording():
_set_embeddings_response_attributes(span, result)
return result
except Exception as error:
error_type = type(error).__qualname__
handle_span_exception(span, error)
raise
finally:
duration = max((default_timer() - start), 0)
_record_metrics(
instruments,
duration,
result,
span_attributes,
error_type,
GenAIAttributes.GenAiOperationNameValues.EMBEDDINGS.value,
)
return traced_method
def _get_embeddings_span_name(span_attributes):
"""Get span name for embeddings operations."""
operation_name = span_attributes[GenAIAttributes.GEN_AI_OPERATION_NAME]
model = span_attributes.get(GenAIAttributes.GEN_AI_REQUEST_MODEL)
return f"{operation_name} {model}" if model else operation_name
def _record_metrics(
instruments: Instruments,
duration: float,
result,
request_attributes: dict,
error_type: str | None,
operation_name: str,
):
common_attributes = {
GenAIAttributes.GEN_AI_OPERATION_NAME: operation_name,
GenAIAttributes.GEN_AI_SYSTEM: GenAIAttributes.GenAiSystemValues.OPENAI.value,
GenAIAttributes.GEN_AI_REQUEST_MODEL: request_attributes[GenAIAttributes.GEN_AI_REQUEST_MODEL],
}
if "gen_ai.embeddings.dimension.count" in request_attributes:
common_attributes["gen_ai.embeddings.dimension.count"] = request_attributes["gen_ai.embeddings.dimension.count"]
if error_type:
common_attributes["error.type"] = error_type
if result and getattr(result, "model", None):
common_attributes[GenAIAttributes.GEN_AI_RESPONSE_MODEL] = result.model
if result and getattr(result, "service_tier", None):
common_attributes[GenAIAttributes.GEN_AI_OPENAI_RESPONSE_SERVICE_TIER] = result.service_tier
if result and getattr(result, "system_fingerprint", None):
common_attributes[GenAIAttributes.GEN_AI_OPENAI_RESPONSE_SYSTEM_FINGERPRINT] = result.system_fingerprint
if ServerAttributes.SERVER_ADDRESS in request_attributes:
common_attributes[ServerAttributes.SERVER_ADDRESS] = request_attributes[ServerAttributes.SERVER_ADDRESS]
if ServerAttributes.SERVER_PORT in request_attributes:
common_attributes[ServerAttributes.SERVER_PORT] = request_attributes[ServerAttributes.SERVER_PORT]
instruments.operation_duration_histogram.record(
duration,
attributes=common_attributes,
)
if result and getattr(result, "usage", None):
# Always record input tokens
input_attributes = {
**common_attributes,
GenAIAttributes.GEN_AI_TOKEN_TYPE: GenAIAttributes.GenAiTokenTypeValues.INPUT.value,
}
instruments.token_usage_histogram.record(
result.usage.prompt_tokens,
attributes=input_attributes,
)
# For embeddings, don't record output tokens as all tokens are input tokens
if operation_name != GenAIAttributes.GenAiOperationNameValues.EMBEDDINGS.value:
output_attributes = {
**common_attributes,
GenAIAttributes.GEN_AI_TOKEN_TYPE: GenAIAttributes.GenAiTokenTypeValues.COMPLETION.value,
}
instruments.token_usage_histogram.record(result.usage.completion_tokens, attributes=output_attributes)
def _set_response_attributes(span, result):
if getattr(result, "model", None):
set_span_attribute(span, GenAIAttributes.GEN_AI_RESPONSE_MODEL, result.model)
if getattr(result, "choices", None):
finish_reasons = []
for choice in result.choices:
finish_reasons.append(choice.finish_reason or "error")
set_span_attribute(
span,
GenAIAttributes.GEN_AI_RESPONSE_FINISH_REASONS,
finish_reasons,
)
if getattr(result, "id", None):
set_span_attribute(span, GenAIAttributes.GEN_AI_RESPONSE_ID, result.id)
if getattr(result, "service_tier", None):
set_span_attribute(
span,
GenAIAttributes.GEN_AI_OPENAI_RESPONSE_SERVICE_TIER,
result.service_tier,
)
# Get the usage
if getattr(result, "usage", None):
set_span_attribute(
span,
GenAIAttributes.GEN_AI_USAGE_INPUT_TOKENS,
result.usage.prompt_tokens,
)
set_span_attribute(
span,
GenAIAttributes.GEN_AI_USAGE_OUTPUT_TOKENS,
result.usage.completion_tokens,
)
def _set_response_properties(
chat_invocation: InferenceInvocation, result, capture_content: bool
) -> InferenceInvocation:
if getattr(result, "model", None):
chat_invocation.response_model_name = result.model
if getattr(result, "choices", None):
finish_reasons = []
for choice in result.choices:
finish_reasons.append(choice.finish_reason or "error")
chat_invocation.finish_reasons = finish_reasons
if capture_content: # optimization
chat_invocation.output_messages = _prepare_output_messages(result.choices)
if getattr(result, "id", None):
chat_invocation.response_id = result.id
if getattr(result, "service_tier", None):
chat_invocation.attributes.update(
{OpenAIAttributes.OPENAI_RESPONSE_SERVICE_TIER: result.service_tier},
)
chat_invocation.metric_attributes.update(
{OpenAIAttributes.OPENAI_RESPONSE_SERVICE_TIER: result.service_tier},
)
if getattr(result, "usage", None):
chat_invocation.input_tokens = result.usage.prompt_tokens
chat_invocation.output_tokens = result.usage.completion_tokens
if getattr(result, "system_fingerprint", None):
chat_invocation.attributes.update(
{OpenAIAttributes.OPENAI_RESPONSE_SYSTEM_FINGERPRINT: result.system_fingerprint},
)
chat_invocation.metric_attributes.update(
{OpenAIAttributes.OPENAI_RESPONSE_SYSTEM_FINGERPRINT: result.system_fingerprint},
)
return chat_invocation
def _set_embeddings_response_attributes(
span: Span,
result: Any,
):
set_span_attribute(span, GenAIAttributes.GEN_AI_RESPONSE_MODEL, result.model)
# Set embeddings dimensions if we can determine it from the response
if getattr(result, "data", None) and len(result.data) > 0:
first_embedding = result.data[0]
if getattr(first_embedding, "embedding", None):
set_span_attribute(
span,
"gen_ai.embeddings.dimension.count",
len(first_embedding.embedding),
)
# Get the usage
if getattr(result, "usage", None):
set_span_attribute(
span,
GenAIAttributes.GEN_AI_USAGE_INPUT_TOKENS,
result.usage.prompt_tokens,
)
# Don't set output tokens for embeddings as all tokens are input tokens
class BaseStreamWrapper:
response_id: str | None = None
response_model: str | None = None
service_tier: str | None = None
finish_reasons: list = []
prompt_tokens: int | None = 0
completion_tokens: int | None = 0
def __init__(
self,
stream: Stream,
capture_content: bool,
):
self.stream = stream
self.choice_buffers = []
self._started = False
self.capture_content = capture_content
self._setup()
def _setup(self):
if not self._started:
self._started = True
def cleanup(self, error: BaseException | None = None):
pass
def __enter__(self):
self._setup()
return self
def __exit__(self, exc_type, exc_val, exc_tb):
error = exc_val if exc_type else None
self.cleanup(error)
return False # Propagate the exception
async def __aenter__(self):
self._setup()
return self
async def __aexit__(self, exc_type, exc_val, exc_tb):
error = exc_val if exc_type else None
self.cleanup(error)
return False # Propagate the exception
def close(self):
self.stream.close()
self.cleanup()
def __iter__(self):
return self
def __aiter__(self):
return self
def __next__(self):
try:
chunk = next(self.stream)
self.process_chunk(chunk)
return chunk
except StopIteration:
self.cleanup()
raise
except Exception as error:
self.cleanup(error)
raise
async def __anext__(self):
try:
chunk = await self.stream.__anext__()
self.process_chunk(chunk)
return chunk
except StopAsyncIteration:
self.cleanup()
raise
except Exception as error:
self.cleanup(error)
raise
def set_response_model(self, chunk):
if self.response_model:
return
if getattr(chunk, "model", None):
self.response_model = chunk.model
def set_response_id(self, chunk):
if self.response_id:
return
if getattr(chunk, "id", None):
self.response_id = chunk.id
def set_response_service_tier(self, chunk):
if self.service_tier:
return
if getattr(chunk, "service_tier", None):
self.service_tier = chunk.service_tier
def build_streaming_response(self, chunk):
if getattr(chunk, "choices", None) is None:
return
choices = chunk.choices
for choice in choices:
if not choice.delta:
continue
# make sure we have enough choice buffers
for idx in range(len(self.choice_buffers), choice.index + 1):
self.choice_buffers.append(ChoiceBuffer(idx))
if choice.finish_reason:
self.choice_buffers[choice.index].finish_reason = choice.finish_reason
if choice.delta.content is not None:
self.choice_buffers[choice.index].append_text_content(choice.delta.content)
if choice.delta.tool_calls is not None:
for tool_call in choice.delta.tool_calls:
self.choice_buffers[choice.index].append_tool_call(tool_call)
def set_usage(self, chunk):
if getattr(chunk, "usage", None):
self.completion_tokens = chunk.usage.completion_tokens
self.prompt_tokens = chunk.usage.prompt_tokens
def process_chunk(self, chunk):
self.set_response_id(chunk)
self.set_response_model(chunk)
self.set_response_service_tier(chunk)
self.build_streaming_response(chunk)
self.set_usage(chunk)
def __getattr__(self, name):
return getattr(self.stream, name)
def parse(self):
"""Called when using with_raw_response with stream=True"""
return self
class LegacyChatStreamWrapper(BaseStreamWrapper):
span: Span
response_id: str | None = None
response_model: str | None = None
service_tier: str | None = None
finish_reasons: list = []
prompt_tokens: int | None = 0
completion_tokens: int | None = 0
def __init__(
self,
stream: Stream,
span: Span,
logger: Logger,
capture_content: bool,
):
super().__init__(stream, capture_content=capture_content)
self.span = span
self.logger = logger
def cleanup(self, error: BaseException | None = None):
if not self._started:
return
if self.span.is_recording():
if self.response_model:
set_span_attribute(
self.span,
GenAIAttributes.GEN_AI_RESPONSE_MODEL,
self.response_model,
)
if self.response_id:
set_span_attribute(
self.span,
GenAIAttributes.GEN_AI_RESPONSE_ID,
self.response_id,
)
set_span_attribute(
self.span,
GenAIAttributes.GEN_AI_USAGE_INPUT_TOKENS,
self.prompt_tokens,
)
set_span_attribute(
self.span,
GenAIAttributes.GEN_AI_USAGE_OUTPUT_TOKENS,
self.completion_tokens,
)
if self.service_tier:
set_span_attribute(
self.span,
GenAIAttributes.GEN_AI_OPENAI_RESPONSE_SERVICE_TIER,
self.service_tier,
)
set_span_attribute(
self.span,
GenAIAttributes.GEN_AI_RESPONSE_FINISH_REASONS,
self.finish_reasons,
)
for idx, choice in enumerate(self.choice_buffers):
message = {"role": "assistant"}
if self.capture_content and choice.text_content:
message["content"] = "".join(choice.text_content)
if choice.tool_calls_buffers:
tool_calls = []
for tool_call in filter(None, choice.tool_calls_buffers):
function = {"name": tool_call.function_name}
if self.capture_content:
function["arguments"] = "".join(tool_call.arguments)
tool_call_dict = {
"id": tool_call.tool_call_id,
"type": "function",
"function": function,
}
tool_calls.append(tool_call_dict)
message["tool_calls"] = tool_calls
body = {
"index": idx,
"finish_reason": choice.finish_reason or "error",
"message": message,
}
event_attributes = {GenAIAttributes.GEN_AI_SYSTEM: GenAIAttributes.GenAiSystemValues.OPENAI.value}
context = set_span_in_context(self.span, get_current())
self.logger.emit(
LogRecord(
event_name="gen_ai.choice",
attributes=event_attributes,
body=body,
context=context,
)
)
if error:
handle_span_exception(self.span, error)
else:
self.span.end()
self._started = False
class AsyncLegacyChatStreamWrapper(LegacyChatStreamWrapper):
"""Async variant of :class:`LegacyChatStreamWrapper`.
Wraps an ``openai.AsyncStream`` whose ``close`` is a coroutine. ``close``
and ``__aexit__`` are therefore overridden as awaitables so the underlying
``AsyncStream.close`` is awaited, releasing the httpx response/connection
instead of leaking it (and avoiding the ``coroutine ... was never awaited``
warning).
"""
stream: AsyncStream
async def close(self) -> None:
# Finalize the span even if the underlying close raises, and re-raise
# the original exception unmodified.
try:
await self.stream.close()
finally:
self.cleanup()
async def __aexit__(self, exc_type, exc_val, exc_tb):
# The wrapper replaces the underlying AsyncStream as the async context
# manager, so it must await AsyncStream.close on exit to release the
# httpx response/connection instead of leaking it.
error = exc_val if exc_type else None
try:
await self.stream.close()
finally:
self.cleanup(error)
return False # Propagate the exception
patch_responses.py 0000664 0000000 0000000 00000003207 15270700723 0050331 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-openai-v2/src/opentelemetry/instrumentation/openai_v2 # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
from __future__ import annotations
from opentelemetry.util.genai.handler import TelemetryHandler
from opentelemetry.util.genai.types import Error
from .response_extractors import (
apply_request_attributes,
extract_params,
get_inference_creation_kwargs,
set_invocation_response_attributes,
)
from .response_wrappers import ResponseStreamWrapper
from .utils import is_streaming
def responses_create(handler: TelemetryHandler):
"""Wrap the `create` method of the `Responses` class to trace it."""
capture_content = handler.should_capture_content()
def traced_method(wrapped, instance, args, kwargs):
params = extract_params(**kwargs)
invocation = handler.start_inference(**get_inference_creation_kwargs(params, instance))
apply_request_attributes(invocation, params, capture_content)
try:
result = wrapped(*args, **kwargs)
parsed_result = _get_response_stream_result(result)
if is_streaming(kwargs):
return ResponseStreamWrapper(
parsed_result,
invocation,
capture_content,
)
set_invocation_response_attributes(invocation, parsed_result, capture_content)
invocation.stop()
return result
except Exception as error:
invocation.fail(Error(type=type(error), message=str(error)))
raise
return traced_method
def _get_response_stream_result(result):
if hasattr(result, "parse"):
return result.parse()
return result
response_extractors.py 0000664 0000000 0000000 00000032316 15270700723 0051250 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-openai-v2/src/opentelemetry/instrumentation/openai_v2 # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
from __future__ import annotations
import json
from collections.abc import Mapping, Sequence
from dataclasses import dataclass
from typing import TYPE_CHECKING
from opentelemetry.semconv._incubating.attributes import (
gen_ai_attributes as GenAIAttributes,
)
from opentelemetry.semconv._incubating.attributes import (
openai_attributes as OpenAIAttributes,
)
from .utils import (
_openai_response_format_to_output_type,
get_server_address_and_port,
)
if TYPE_CHECKING:
from openai.types.responses.response import Response
from openai.types.responses.response_usage import ResponseUsage
from opentelemetry.util.genai.types import (
InputMessage,
OutputMessage,
Text,
)
try:
from openai.types.responses.response import Response
from openai.types.responses.response_function_tool_call import (
ResponseFunctionToolCall,
)
from openai.types.responses.response_output_message import (
ResponseOutputMessage,
)
from openai.types.responses.response_output_refusal import (
ResponseOutputRefusal,
)
from openai.types.responses.response_output_text import ResponseOutputText
from openai.types.responses.response_reasoning_item import (
ResponseReasoningItem,
)
from openai.types.responses.response_usage import ResponseUsage
except ImportError:
Response = None
ResponseFunctionToolCall = None
ResponseOutputMessage = None
ResponseOutputRefusal = None
ResponseOutputText = None
ResponseReasoningItem = None
ResponseUsage = None
try:
from opentelemetry.util.genai.types import (
InputMessage,
OutputMessage,
Reasoning,
Text,
)
from opentelemetry.util.genai.types import (
ToolCallRequest as ToolCall,
)
except ImportError:
InputMessage = None
OutputMessage = None
Reasoning = None
Text = None
ToolCall = None
@dataclass
class ResponseRequestParams:
model: str | None = None
instructions: str | None = None
input: str | Sequence[object] | None = None
max_output_tokens: int | None = None
service_tier: str | None = None
temperature: float | None = None
output_type: str | None = None
top_p: float | None = None
@dataclass
class UsageTokens:
input_tokens: int | None = None
output_tokens: int | None = None
cache_creation_input_tokens: int | None = None
cache_read_input_tokens: int | None = None
def _get_field(value: object, field_name: str) -> object | None:
if isinstance(value, Mapping):
return value.get(field_name)
return getattr(value, field_name, None)
def _get_sequence(value: object) -> Sequence[object]:
if isinstance(value, Sequence) and not isinstance(value, (str, bytes, bytearray)):
return value
return ()
def _get_int(value: object) -> int | None:
if isinstance(value, bool) or not isinstance(value, int):
return None
return value
def _get_float(value: object) -> float | None:
if isinstance(value, bool) or not isinstance(value, (int, float)):
return None
return float(value)
def _extract_output_type_from_value(text_config: object) -> str | None:
format_config = _get_field(text_config, "format")
if format_config is None:
return None
format_type = _get_field(format_config, "type")
if isinstance(format_type, str):
return _openai_response_format_to_output_type(format_type)
return None
def extract_params(
*,
model: str | None = None,
instructions: str | None = None,
input_items: str | Sequence[object] | None = None,
max_output_tokens: int | None = None,
service_tier: str | None = None,
temperature: float | None = None,
text: object | None = None,
top_p: float | None = None,
**_kwargs: object,
) -> ResponseRequestParams:
if input_items is None and "input" in _kwargs:
input_items = _kwargs["input"]
return ResponseRequestParams(
model=model if isinstance(model, str) else None,
instructions=instructions if isinstance(instructions, str) else None,
input=(
input_items
if isinstance(input_items, str)
or (isinstance(input_items, Sequence) and not isinstance(input_items, (str, bytes, bytearray)))
else None
),
max_output_tokens=_get_int(max_output_tokens),
service_tier=(service_tier if isinstance(service_tier, str) and service_tier != "auto" else None),
temperature=_get_float(temperature),
output_type=_extract_output_type_from_value(text),
top_p=_get_float(top_p),
)
def get_system_instruction(instructions: str | None) -> list[Text]:
if Text is None or instructions is None:
return []
return [Text(content=instructions)]
def get_input_messages(
input_value: str | Sequence[object] | None,
) -> list[InputMessage]:
if InputMessage is None or Text is None:
return []
if isinstance(input_value, str):
return [InputMessage(role="user", parts=[Text(content=input_value)])]
messages: list[InputMessage] = []
for item in _get_sequence(input_value):
role = _get_field(item, "role")
if not isinstance(role, str):
continue
content = _get_field(item, "content")
if isinstance(content, str):
messages.append(InputMessage(role=role, parts=[Text(content=content)]))
continue
parts = []
for part in _get_sequence(content):
text = _get_field(part, "text")
if isinstance(text, str):
parts.append(Text(content=text))
if parts:
messages.append(InputMessage(role=role, parts=parts))
return messages
def _extract_output_parts(content_blocks: Sequence[object]) -> list[Text]:
if Text is None or ResponseOutputText is None or ResponseOutputRefusal is None:
return []
parts: list[Text] = []
for block in content_blocks:
if isinstance(block, ResponseOutputText):
parts.append(Text(content=block.text))
elif isinstance(block, ResponseOutputRefusal):
parts.append(Text(content=block.refusal))
return parts
def _parse_tool_call_arguments(arguments: str | None) -> object:
if arguments is None:
return None
try:
return json.loads(arguments)
except (TypeError, ValueError):
return arguments
def _extract_reasoning_parts(
item: ResponseReasoningItem,
) -> list[Reasoning]:
if Reasoning is None:
return []
parts: list[Reasoning] = []
for block in item.summary:
if isinstance(block.text, str):
parts.append(Reasoning(content=block.text))
for block in item.content or []:
if getattr(block, "type", None) == "reasoning_text" and isinstance(getattr(block, "text", None), str):
parts.append(Reasoning(content=block.text))
return parts
def _finish_reason_from_status(status: str | None) -> str | None:
if status == "completed":
return "stop"
if status in {"failed", "cancelled", "incomplete"}:
return status
return None
def _response_types_available() -> bool:
return (
Response is not None
and ResponseOutputMessage is not None
and ResponseFunctionToolCall is not None
and ResponseReasoningItem is not None
)
def get_output_messages_from_response(
response: Response | None,
) -> list[OutputMessage]:
if not _response_types_available() or not isinstance(response, Response) or OutputMessage is None or Text is None:
return []
messages: list[OutputMessage] = []
for item in response.output:
if isinstance(item, ResponseOutputMessage):
finish_reason = _finish_reason_from_status(item.status)
if finish_reason is None:
continue
messages.append(
OutputMessage(
role=item.role,
parts=_extract_output_parts(item.content),
finish_reason=finish_reason,
)
)
continue
if isinstance(item, ResponseFunctionToolCall):
if ToolCall is None or item.status not in {
"completed",
"incomplete",
}:
continue
messages.append(
OutputMessage(
role="assistant",
parts=[
ToolCall(
id=item.call_id if item.call_id else item.id,
name=item.name,
arguments=_parse_tool_call_arguments(item.arguments),
)
],
finish_reason="tool_calls",
)
)
continue
if isinstance(item, ResponseReasoningItem):
finish_reason = _finish_reason_from_status(item.status)
if finish_reason is None:
continue
parts = _extract_reasoning_parts(item)
if parts:
messages.append(
OutputMessage(
role="assistant",
parts=parts,
finish_reason=finish_reason,
)
)
return messages
def extract_finish_reasons(response: Response | None) -> list[str]:
if (
Response is None
or ResponseOutputMessage is None
or ResponseFunctionToolCall is None
or not isinstance(response, Response)
):
return []
finish_reasons: list[str] = []
for item in response.output:
if isinstance(item, ResponseFunctionToolCall) and item.status in {
"completed",
"incomplete",
}:
finish_reasons.append("tool_calls")
continue
if not isinstance(item, ResponseOutputMessage):
continue
finish_reason = _finish_reason_from_status(item.status)
if finish_reason is not None:
finish_reasons.append(finish_reason)
return list(dict.fromkeys(finish_reasons))
def get_inference_creation_kwargs(
params: ResponseRequestParams,
client_instance: object,
) -> dict[str, object]:
address, port = get_server_address_and_port(client_instance)
creation_kwargs: dict[str, object] = {
"provider": GenAIAttributes.GenAiProviderNameValues.OPENAI.value,
}
if params.model is not None:
creation_kwargs["request_model"] = params.model
if address is not None:
creation_kwargs["server_address"] = address
if port is not None:
creation_kwargs["server_port"] = port
return creation_kwargs
def apply_request_attributes(
invocation,
params: ResponseRequestParams,
capture_content: bool,
) -> None:
invocation.temperature = params.temperature
invocation.top_p = params.top_p
invocation.max_tokens = params.max_output_tokens
if params.service_tier is not None:
invocation.attributes[OpenAIAttributes.OPENAI_REQUEST_SERVICE_TIER] = params.service_tier
if params.output_type is not None:
invocation.attributes[GenAIAttributes.GEN_AI_OUTPUT_TYPE] = params.output_type
if capture_content:
invocation.system_instruction = get_system_instruction(params.instructions)
invocation.input_messages = get_input_messages(params.input)
def extract_usage_tokens(usage: ResponseUsage | None) -> UsageTokens:
if ResponseUsage is None or usage is None or not isinstance(usage, ResponseUsage):
return UsageTokens()
details = usage.input_tokens_details
return UsageTokens(
input_tokens=usage.input_tokens,
output_tokens=usage.output_tokens,
# `cache_creation_input_tokens` is not present on every SDK version's
# input token details model, so keep this attribute access guarded for
# compatibility across the supported OpenAI range.
cache_creation_input_tokens=(
details.cache_creation_input_tokens
if details is not None and hasattr(details, "cache_creation_input_tokens")
else None
),
cache_read_input_tokens=(details.cached_tokens if details is not None else None),
)
def set_invocation_response_attributes(
invocation,
response: Response | None,
capture_content: bool,
) -> None:
if Response is None or not isinstance(response, Response):
return
invocation.response_model_name = response.model
invocation.response_id = response.id
if response.service_tier is not None:
invocation.attributes[OpenAIAttributes.OPENAI_RESPONSE_SERVICE_TIER] = response.service_tier
tokens = extract_usage_tokens(response.usage)
invocation.input_tokens = tokens.input_tokens
invocation.output_tokens = tokens.output_tokens
invocation.cache_creation_input_tokens = tokens.cache_creation_input_tokens
invocation.cache_read_input_tokens = tokens.cache_read_input_tokens
finish_reasons = extract_finish_reasons(response)
if finish_reasons:
invocation.finish_reasons = finish_reasons
if capture_content:
output_messages = get_output_messages_from_response(response)
if output_messages:
invocation.output_messages = output_messages
response_wrappers.py 0000664 0000000 0000000 00000032151 15270700723 0050712 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-openai-v2/src/opentelemetry/instrumentation/openai_v2 # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
"""Wrappers for OpenAI Responses API streams and stream managers."""
from __future__ import annotations
import logging
from collections.abc import Callable, Generator
from contextlib import AsyncExitStack, ExitStack, contextmanager
from types import TracebackType
from typing import TYPE_CHECKING, Generic, TypeVar
from opentelemetry.util.genai.types import Error
try:
from opentelemetry.instrumentation.openai_v2.response_extractors import ( # pylint: disable=no-name-in-module
set_invocation_response_attributes,
)
except ImportError:
set_invocation_response_attributes = None
if TYPE_CHECKING:
from openai.lib.streaming.responses._events import ( # pylint: disable=no-name-in-module
ResponseStreamEvent,
)
from openai.lib.streaming.responses._responses import (
AsyncResponseStream,
AsyncResponseStreamManager,
ResponseStream,
ResponseStreamManager,
) # pylint: disable=no-name-in-module
from openai.types.responses import ( # pylint: disable=no-name-in-module
ParsedResponse,
Response,
)
from opentelemetry.util.genai._invocation import GenAIInvocation
_logger = logging.getLogger(__name__)
TextFormatT = TypeVar("TextFormatT")
ResponseT = TypeVar("ResponseT")
def _set_response_attributes(
invocation: GenAIInvocation,
result: ParsedResponse[TextFormatT] | Response | None,
capture_content: bool,
) -> None:
if set_invocation_response_attributes is None:
return
set_invocation_response_attributes(invocation, result, capture_content)
def _get_stream_response(stream):
try:
return stream._response
except AttributeError:
try:
return stream.response
except AttributeError:
return None
class _ResponseProxy(Generic[ResponseT]):
def __init__(self, response: ResponseT, finalize: Callable[[], None]):
self._response = response
self._finalize = finalize
def close(self) -> None:
try:
self._response.close()
finally:
self._finalize()
def __getattr__(self, name: str):
return getattr(self._response, name)
class _AsyncResponseProxy(Generic[ResponseT]):
def __init__(self, response: ResponseT, finalize: Callable[[], None]):
self._response = response
self._finalize = finalize
async def aclose(self) -> None:
try:
await self._response.aclose()
finally:
self._finalize()
def __getattr__(self, name: str):
return getattr(self._response, name)
class ResponseStreamWrapper(Generic[TextFormatT]):
"""Wrapper for OpenAI Responses API stream objects.
Wraps ResponseStream from the OpenAI SDK:
https://github.com/openai/openai-python/blob/656e3cab4a18262a49b961d41293367e45ee71b9/src/openai/_streaming.py#L55
"""
def __init__(
self,
stream: ResponseStream[TextFormatT],
invocation: GenAIInvocation,
capture_content: bool,
):
self.stream = stream
self.invocation = invocation
self._capture_content = capture_content
self._finalized = False
def __enter__(self) -> ResponseStreamWrapper:
return self
def __exit__(
self,
exc_type: type[BaseException] | None,
exc_val: BaseException | None,
exc_tb: TracebackType | None,
) -> bool:
try:
if exc_type is not None:
self._fail(str(exc_val), type(exc_val) if exc_val else Exception)
finally:
self.close()
return False
def close(self) -> None:
try:
self.stream.close()
finally:
self._stop(None)
def __iter__(self) -> ResponseStreamWrapper:
return self
def __next__(self) -> ResponseStreamEvent[TextFormatT]:
try:
event = next(self.stream)
except StopIteration:
self._stop(None)
raise
except Exception as error:
self._fail(str(error), type(error))
raise
with self._safe_instrumentation("event processing"):
self.process_event(event)
return event
def get_final_response(self) -> ParsedResponse[TextFormatT]:
self.until_done()
return self.stream.get_final_response()
def until_done(self) -> ResponseStreamWrapper:
for _ in self:
pass
return self
def parse(self) -> ResponseStreamWrapper:
"""Called when using with_raw_response with stream=True."""
return self
# TODO: Replace __getattr__ passthrough with wrapt.ObjectProxy in a future
# cleanup once wrapt 2 typing support is available (wrapt PR #3903).
def __getattr__(self, name: str):
return getattr(self.stream, name)
@property
def response(self):
response = _get_stream_response(self.stream)
if response is None:
return None
return _ResponseProxy(response, lambda: self._stop(None))
def _stop(self, result: ParsedResponse[TextFormatT] | Response | None) -> None:
if self._finalized:
return
with self._safe_instrumentation("response attribute extraction"):
_set_response_attributes(self.invocation, result, self._capture_content)
with self._safe_instrumentation("inference.stop"):
self.invocation.stop()
self._finalized = True
def _fail(self, message: str, error_type: type[BaseException]) -> None:
if self._finalized:
return
with self._safe_instrumentation("inference.fail"):
self.invocation.fail(Error(message=message, type=error_type))
self._finalized = True
@staticmethod
@contextmanager
def _safe_instrumentation(context: str) -> Generator[None, None, None]:
try:
yield
except Exception: # pylint: disable=broad-exception-caught
_logger.debug(
"OpenAI responses instrumentation error during %s",
context,
exc_info=True,
stacklevel=2,
)
def process_event(self, event: ResponseStreamEvent[TextFormatT]) -> None:
event_type = event.type
response: ParsedResponse[TextFormatT] | Response | None = getattr(event, "response", None)
if response and not self.invocation.request_model:
model = response.model
if model:
self.invocation.request_model = model
if event_type == "response.completed":
self._stop(response)
return
if event_type in {"response.failed", "response.incomplete"}:
with self._safe_instrumentation("response attribute extraction"):
_set_response_attributes(self.invocation, response, self._capture_content)
self._fail(event_type, RuntimeError)
return
if event_type == "response.error":
error_type = getattr(event, "code", None) or "response.error"
message = getattr(event, "message", None) or error_type
self._fail(message, RuntimeError)
class ResponseStreamManagerWrapper(Generic[TextFormatT]):
"""Wrapper for OpenAI Responses API stream managers.
Wraps ResponseStreamManager from the OpenAI SDK:
https://github.com/openai/openai-python/blob/656e3cab4a18262a49b961d41293367e45ee71b9/src/openai/lib/streaming/responses/_responses.py#L95
"""
def __init__(
self,
manager: ResponseStreamManager[TextFormatT],
invocation,
capture_content: bool,
):
self._manager = manager
self._invocation = invocation
self._capture_content = capture_content
self._stream_wrapper: ResponseStreamWrapper[TextFormatT] | None = None
def __enter__(self) -> ResponseStreamWrapper[TextFormatT]:
stream = self._manager.__enter__()
self._stream_wrapper = ResponseStreamWrapper(
stream,
self._invocation,
self._capture_content,
)
return self._stream_wrapper
def __exit__(
self,
exc_type: type[BaseException] | None,
exc_val: BaseException | None,
exc_tb: TracebackType | None,
) -> bool:
suppressed = False
stream_wrapper = self._stream_wrapper
self._stream_wrapper = None
with ExitStack() as cleanup:
if stream_wrapper is not None:
def finalize_stream_wrapper() -> None:
if suppressed:
stream_wrapper.__exit__(None, None, None)
else:
stream_wrapper.__exit__(exc_type, exc_val, exc_tb)
cleanup.callback(finalize_stream_wrapper)
suppressed = self._manager.__exit__(exc_type, exc_val, exc_tb)
return suppressed
def parse(self) -> ResponseStreamManagerWrapper[TextFormatT]:
raise NotImplementedError("ResponseStreamManagerWrapper.parse() is not implemented")
# TODO: Replace __getattr__ passthrough with wrapt.ObjectProxy in a future
# cleanup once wrapt 2 typing support is available (wrapt PR #3903).
def __getattr__(self, name: str):
return getattr(self._manager, name)
class AsyncResponseStreamWrapper(ResponseStreamWrapper[TextFormatT]):
"""Wrapper for async OpenAI Responses API stream objects."""
stream: AsyncResponseStream[TextFormatT]
async def __aenter__(self) -> AsyncResponseStreamWrapper[TextFormatT]:
return self
async def __aexit__(
self,
exc_type: type[BaseException] | None,
exc_val: BaseException | None,
exc_tb: TracebackType | None,
) -> bool:
try:
if exc_type is not None:
self._fail(str(exc_val), type(exc_val) if exc_val else Exception)
finally:
await self.close()
return False
async def close(self) -> None:
try:
await self.stream.close()
finally:
self._stop(None)
def __aiter__(self) -> AsyncResponseStreamWrapper[TextFormatT]:
return self
async def __anext__(self) -> ResponseStreamEvent[TextFormatT]:
try:
event = await self.stream.__anext__()
except StopAsyncIteration:
self._stop(None)
raise
except Exception as error:
self._fail(str(error), type(error))
raise
with self._safe_instrumentation("event processing"):
self.process_event(event)
return event
async def get_final_response(self) -> ParsedResponse[TextFormatT]:
await self.until_done()
return await self.stream.get_final_response()
async def until_done(self) -> AsyncResponseStreamWrapper[TextFormatT]:
async for _ in self:
pass
return self
def parse(self) -> AsyncResponseStreamWrapper[TextFormatT]:
"""Called when using with_raw_response with stream=True."""
return self
@property
def response(self):
response = _get_stream_response(self.stream)
if response is None:
return None
return _AsyncResponseProxy(response, lambda: self._stop(None))
class AsyncResponseStreamManagerWrapper(Generic[TextFormatT]):
"""Wrapper for async OpenAI Responses API stream managers."""
def __init__(
self,
manager: AsyncResponseStreamManager[TextFormatT],
invocation,
capture_content: bool,
):
self._manager = manager
self._invocation = invocation
self._capture_content = capture_content
self._stream_wrapper: AsyncResponseStreamWrapper[TextFormatT] | None = None
async def __aenter__(self) -> AsyncResponseStreamWrapper[TextFormatT]:
stream = await self._manager.__aenter__()
self._stream_wrapper = AsyncResponseStreamWrapper(
stream,
self._invocation,
self._capture_content,
)
return self._stream_wrapper
async def __aexit__(
self,
exc_type: type[BaseException] | None,
exc_val: BaseException | None,
exc_tb: TracebackType | None,
) -> bool:
suppressed = False
stream_wrapper = self._stream_wrapper
self._stream_wrapper = None
async with AsyncExitStack() as cleanup:
if stream_wrapper is not None:
async def finalize_stream_wrapper() -> None:
if suppressed:
await stream_wrapper.__aexit__(None, None, None)
else:
await stream_wrapper.__aexit__(exc_type, exc_val, exc_tb)
cleanup.push_async_callback(finalize_stream_wrapper)
suppressed = await self._manager.__aexit__(exc_type, exc_val, exc_tb)
return suppressed
def parse(self) -> AsyncResponseStreamManagerWrapper[TextFormatT]:
raise NotImplementedError("AsyncResponseStreamManagerWrapper.parse() is not implemented")
# TODO: Replace __getattr__ passthrough with wrapt.ObjectProxy in a future
# cleanup once wrapt 2 typing support is available (wrapt PR #3903).
def __getattr__(self, name: str):
return getattr(self._manager, name)
utils.py 0000664 0000000 0000000 00000040666 15270700723 0046303 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-openai-v2/src/opentelemetry/instrumentation/openai_v2 # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
from __future__ import annotations
import json
from collections.abc import Iterable, Mapping
from os import environ
from typing import Any
from urllib.parse import urlparse
import openai
from httpx import URL
from openai import NotGiven
from opentelemetry._logs import LogRecord
from opentelemetry.semconv._incubating.attributes import (
gen_ai_attributes as GenAIAttributes,
)
from opentelemetry.semconv._incubating.attributes import (
openai_attributes as OpenAIAttributes,
)
from opentelemetry.semconv._incubating.attributes import (
server_attributes as ServerAttributes,
)
from opentelemetry.semconv.attributes import (
error_attributes as ErrorAttributes,
)
from opentelemetry.trace.status import Status, StatusCode
from opentelemetry.util.genai.environment_variables import (
OTEL_INSTRUMENTATION_GENAI_CAPTURE_MESSAGE_CONTENT,
)
from opentelemetry.util.genai.handler import TelemetryHandler
from opentelemetry.util.genai.invocation import InferenceInvocation
from opentelemetry.util.genai.types import (
FunctionToolDefinition,
InputMessage,
OutputMessage,
Text,
ToolCallRequest,
ToolCallResponse,
ToolDefinition,
)
_OpenAIOmit = getattr(openai, "Omit", None)
def is_content_enabled() -> bool:
capture_content = environ.get(OTEL_INSTRUMENTATION_GENAI_CAPTURE_MESSAGE_CONTENT, "false")
return capture_content.lower() == "true"
def extract_tool_calls(item, capture_content):
tool_calls = get_property_value(item, "tool_calls")
if tool_calls is None:
return None
calls = []
for tool_call in tool_calls:
tool_call_dict = {}
call_id = get_property_value(tool_call, "id")
if call_id:
tool_call_dict["id"] = call_id
tool_type = get_property_value(tool_call, "type")
if tool_type:
tool_call_dict["type"] = tool_type
func = get_property_value(tool_call, "function")
if func:
tool_call_dict["function"] = {}
name = get_property_value(func, "name")
if name:
tool_call_dict["function"]["name"] = name
arguments = get_property_value(func, "arguments")
if capture_content and arguments:
if isinstance(arguments, str):
arguments = arguments.replace("\n", "")
tool_call_dict["function"]["arguments"] = arguments
calls.append(tool_call_dict)
return calls
def get_server_address_and_port(
client_instance,
) -> tuple[str | None, int | None]:
base_client = getattr(client_instance, "_client", None)
base_url = getattr(base_client, "base_url", None)
if not base_url:
return None, None
address = None
port = None
if isinstance(base_url, URL):
address = base_url.host
port = base_url.port
elif isinstance(base_url, str):
url = urlparse(base_url)
address = url.hostname
port = url.port
if port == 443:
port = None
return address, port
def get_property_value(obj, property_name):
if isinstance(obj, dict):
return obj.get(property_name, None)
return getattr(obj, property_name, None)
def message_to_event(message, capture_content):
attributes = {GenAIAttributes.GEN_AI_SYSTEM: GenAIAttributes.GenAiSystemValues.OPENAI.value}
role = get_property_value(message, "role")
content = get_property_value(message, "content")
body = {}
if capture_content and content:
body["content"] = content
if role == "assistant":
tool_calls = extract_tool_calls(message, capture_content)
if tool_calls:
body = {"tool_calls": tool_calls}
elif role == "tool":
tool_call_id = get_property_value(message, "tool_call_id")
if tool_call_id:
body["id"] = tool_call_id
return LogRecord(
event_name=f"gen_ai.{role}.message",
attributes=attributes,
body=body if body else None,
)
def choice_to_event(choice, capture_content):
attributes = {GenAIAttributes.GEN_AI_SYSTEM: GenAIAttributes.GenAiSystemValues.OPENAI.value}
body = {
"index": choice.index,
"finish_reason": choice.finish_reason or "error",
}
if choice.message:
message = {"role": (choice.message.role if choice.message and choice.message.role else None)}
tool_calls = extract_tool_calls(choice.message, capture_content)
if tool_calls:
message["tool_calls"] = tool_calls
content = get_property_value(choice.message, "content")
if capture_content and content:
message["content"] = content
body["message"] = message
return LogRecord(
event_name="gen_ai.choice",
attributes=attributes,
body=body,
)
def set_span_attributes(span, attributes: dict):
for field, value in attributes.model_dump(by_alias=True).items():
set_span_attribute(span, field, value)
def set_span_attribute(span, name, value):
if non_numerical_value_is_set(value) is False:
return
span.set_attribute(name, value)
def is_streaming(kwargs):
return non_numerical_value_is_set(kwargs.get("stream"))
def non_numerical_value_is_set(value: bool | str | NotGiven | None):
return bool(value) and value_is_set(value)
def value_is_set(value):
if _OpenAIOmit is not None and isinstance(value, _OpenAIOmit):
return False
return value is not None and not isinstance(value, NotGiven)
def _openai_response_format_to_output_type(response_format_type: str) -> str:
if response_format_type in ("json_object", "json_schema"):
return GenAIAttributes.GenAiOutputTypeValues.JSON.value
return response_format_type
def get_llm_request_attributes(
kwargs,
client_instance,
latest_experimental_enabled,
operation_name=GenAIAttributes.GenAiOperationNameValues.CHAT.value,
):
# pylint: disable=too-many-branches,too-many-locals
attributes = {
GenAIAttributes.GEN_AI_OPERATION_NAME: operation_name,
}
model = kwargs.get("model")
if model:
attributes[GenAIAttributes.GEN_AI_REQUEST_MODEL] = model
if latest_experimental_enabled:
attributes.update(
{
GenAIAttributes.GEN_AI_PROVIDER_NAME: (GenAIAttributes.GenAiProviderNameValues.OPENAI.value),
}
)
else:
attributes.update(
{
GenAIAttributes.GEN_AI_SYSTEM: GenAIAttributes.GenAiProviderNameValues.OPENAI.value,
}
)
# Add chat-specific attributes only for chat operations
if operation_name == GenAIAttributes.GenAiOperationNameValues.CHAT.value:
attributes.update(
{
GenAIAttributes.GEN_AI_REQUEST_TEMPERATURE: kwargs.get("temperature"),
GenAIAttributes.GEN_AI_REQUEST_TOP_P: kwargs.get("p") or kwargs.get("top_p"),
GenAIAttributes.GEN_AI_REQUEST_MAX_TOKENS: kwargs.get("max_tokens"),
GenAIAttributes.GEN_AI_REQUEST_PRESENCE_PENALTY: kwargs.get("presence_penalty"),
GenAIAttributes.GEN_AI_REQUEST_FREQUENCY_PENALTY: kwargs.get("frequency_penalty"),
GenAIAttributes.GEN_AI_REQUEST_SEED: kwargs.get("seed"),
}
)
if (choice_count := kwargs.get("n")) is not None:
# Only add non default, meaningful values
if isinstance(choice_count, int) and choice_count != 1:
attributes[GenAIAttributes.GEN_AI_REQUEST_CHOICE_COUNT] = choice_count
if (stop_sequences := kwargs.get("stop")) is not None:
if isinstance(stop_sequences, str):
stop_sequences = [stop_sequences]
attributes[GenAIAttributes.GEN_AI_REQUEST_STOP_SEQUENCES] = stop_sequences
request_response_format_attr_key = (
GenAIAttributes.GEN_AI_OUTPUT_TYPE
if latest_experimental_enabled
else GenAIAttributes.GEN_AI_OPENAI_REQUEST_RESPONSE_FORMAT
)
if (response_format := kwargs.get("response_format")) is not None:
# response_format may be string or object with a string in the `type` key
if isinstance(response_format, Mapping):
if (response_format_type := response_format.get("type")) is not None:
attributes[request_response_format_attr_key] = response_format_type
elif isinstance(response_format, str):
attributes[request_response_format_attr_key] = response_format
# service_tier can be passed directly or in extra_body (in SDK 1.26.0 it's via extra_body)
service_tier = kwargs.get("service_tier")
if service_tier is None:
extra_body = kwargs.get("extra_body")
if isinstance(extra_body, Mapping):
service_tier = extra_body.get("service_tier")
request_service_tier_attr_key = (
OpenAIAttributes.OPENAI_REQUEST_SERVICE_TIER
if latest_experimental_enabled
else GenAIAttributes.GEN_AI_OPENAI_REQUEST_SERVICE_TIER
)
attributes[request_service_tier_attr_key] = service_tier if service_tier != "auto" else None
# Add embeddings-specific attributes
elif operation_name == GenAIAttributes.GenAiOperationNameValues.EMBEDDINGS.value:
# Add embedding dimensions if specified
if (dimensions := kwargs.get("dimensions")) is not None:
# TODO: move to GEN_AI_EMBEDDINGS_DIMENSION_COUNT when 1.39.0 is baseline
attributes["gen_ai.embeddings.dimension.count"] = dimensions
# Add encoding format if specified
if "encoding_format" in kwargs:
attributes[GenAIAttributes.GEN_AI_REQUEST_ENCODING_FORMATS] = [kwargs["encoding_format"]]
address, port = get_server_address_and_port(client_instance)
if address:
attributes[ServerAttributes.SERVER_ADDRESS] = address
if port:
attributes[ServerAttributes.SERVER_PORT] = port
# filter out values not set
return {k: v for k, v in attributes.items() if value_is_set(v)}
def create_chat_invocation(
handler: TelemetryHandler,
kwargs,
client_instance,
capture_content: bool,
) -> InferenceInvocation:
# pylint: disable=too-many-branches
address, port = get_server_address_and_port(client_instance)
invocation = handler.start_inference(
GenAIAttributes.GenAiProviderNameValues.OPENAI.value,
request_model=kwargs.get("model", ""),
server_address=address if address else None,
server_port=port if port else None,
)
invocation.temperature = get_value(kwargs.get("temperature"))
invocation.top_p = get_value(kwargs.get("p") or kwargs.get("top_p"))
invocation.max_tokens = get_value(kwargs.get("max_tokens"))
invocation.presence_penalty = get_value(kwargs.get("presence_penalty"))
invocation.frequency_penalty = get_value(kwargs.get("frequency_penalty"))
invocation.seed = get_value(kwargs.get("seed"))
if (stop_sequences := get_value(kwargs.get("stop"))) is not None:
if isinstance(stop_sequences, str):
stop_sequences = [stop_sequences]
invocation.stop_sequences = stop_sequences
if (choice_count := get_value(kwargs.get("n"))) is not None:
# Only add non default, meaningful values
if isinstance(choice_count, int) and choice_count != 1:
invocation.attributes[GenAIAttributes.GEN_AI_REQUEST_CHOICE_COUNT] = choice_count
if (response_format := get_value(kwargs.get("response_format"))) is not None:
# response_format may be string or object with a string in the `type` key
if isinstance(response_format, Mapping):
if (response_format_type := get_value(response_format.get("type"))) is not None:
invocation.attributes[GenAIAttributes.GEN_AI_OUTPUT_TYPE] = _openai_response_format_to_output_type(
response_format_type
)
elif isinstance(response_format, str):
invocation.attributes[GenAIAttributes.GEN_AI_OUTPUT_TYPE] = _openai_response_format_to_output_type(
response_format
)
# service_tier can be passed directly or in extra_body (in SDK 1.26.0 it's via extra_body)
service_tier = get_value(kwargs.get("service_tier"))
if service_tier is None:
extra_body = get_value(kwargs.get("extra_body"))
if isinstance(extra_body, Mapping):
service_tier = get_value(extra_body.get("service_tier"))
if service_tier is not None and service_tier != "auto":
invocation.attributes[OpenAIAttributes.OPENAI_REQUEST_SERVICE_TIER] = service_tier
if capture_content: # optimization
invocation.input_messages = _prepare_input_messages(kwargs.get("messages", []))
invocation.tool_definitions = _prepare_tool_definitions(kwargs.get("tools"))
return invocation
def get_value(v: Any):
if value_is_set(v):
return v
return None
def handle_span_exception(span, error: BaseException):
span.set_status(Status(StatusCode.ERROR, str(error)))
if span.is_recording():
span.set_attribute(ErrorAttributes.ERROR_TYPE, type(error).__qualname__)
span.end()
def _is_text_part(content: Any) -> bool:
return isinstance(content, str) or (
isinstance(content, Iterable) and all(isinstance(part, str) for part in content)
)
def _prepare_input_messages(messages) -> list[InputMessage]:
chat_messages = []
for message in messages:
role = get_property_value(message, "role")
chat_message = InputMessage(role=str(role), parts=[])
chat_messages.append(chat_message)
content = get_property_value(message, "content")
if role == "assistant":
tool_calls = get_property_value(message, "tool_calls")
if tool_calls:
chat_message.parts += extract_tool_calls_new(tool_calls)
if _is_text_part(content):
chat_message.parts.append(Text(content=str(content)))
elif role == "tool":
tool_call_id = get_property_value(message, "tool_call_id")
chat_message.parts.append(ToolCallResponse(id=tool_call_id, response=content))
else:
# system, developer, user, fallback
if _is_text_part(content):
chat_message.parts.append(Text(content=str(content)))
return chat_messages
def extract_tool_calls_new(tool_calls) -> list[ToolCallRequest]:
parts = []
for tool_call in tool_calls:
call_id = get_property_value(tool_call, "id")
func_name = ""
arguments = None
func = get_property_value(tool_call, "function")
if func:
func_name = get_property_value(func, "name") or ""
arguments_str = get_property_value(func, "arguments")
if arguments_str:
try:
arguments = json.loads(arguments_str)
except json.JSONDecodeError:
arguments = arguments_str
# TODO: support custom
parts.append(ToolCallRequest(id=call_id, name=func_name, arguments=arguments))
return parts
def _prepare_tool_definitions(tools) -> list[ToolDefinition] | None:
if not tools:
return None
definitions: list[ToolDefinition] = []
for tool in tools:
tool_type = get_property_value(tool, "type")
if tool_type == "function":
func = get_property_value(tool, "function")
if func:
definitions.append(
FunctionToolDefinition(
name=get_property_value(func, "name") or "",
description=get_property_value(func, "description"),
parameters=get_property_value(func, "parameters"),
)
)
return definitions
def _prepare_output_messages(choices) -> list[OutputMessage]:
output_messages = []
for choice in choices:
if choice.message:
parts = []
tool_calls = get_property_value(choice.message, "tool_calls")
if tool_calls:
parts += extract_tool_calls_new(tool_calls)
content = get_property_value(choice.message, "content")
if _is_text_part(content):
parts.append(Text(content=str(content)))
message = OutputMessage(
finish_reason=choice.finish_reason or "error",
role=(choice.message.role if choice.message and choice.message.role else ""),
parts=parts,
)
output_messages.append(message)
return output_messages
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# SPDX-License-Identifier: Apache-2.0
__version__ = "2.5b0.dev"
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If you need to record calls you need to export the `OPENAI_API_KEY` as environment variable.
Since tox blocks environment variables by default you need to override its configuration to let them pass:
```
export TOX_OVERRIDE=testenv.pass_env=OPENAI_API_KEY
```
We are not adding it to tox.ini because of security concerns.
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"text": "```bash\n#!/usr/bin/env bash\n\n# Usage:\n# ./transpose.sh '[1,2],[3,4],[5,6]'\n\ninput=\"$1\"\n\n# Extract rows into an array\nIFS='|' read -r -a rows <<< \"$(echo \"$input\" | sed 's/],\\[/]|[/g')\"\n\n# Remove leading/trailing brackets and split first row to get column count\nfirst_row=\"${rows[0]#[}\"\nfirst_row=\"${first_row%]}\"\nIFS=',' read -r -a first_vals <<< \"$first_row\"\ncols=\"${#first_vals[@]}\"\n\n# Build transpose\nresult=\"\"\nfor ((c=0; c InMemoryLogRecordExporter rename
try:
from opentelemetry.sdk._logs.export import ( # pylint: disable=no-name-in-module
InMemoryLogRecordExporter,
SimpleLogRecordProcessor,
)
except ImportError:
# Fallback to old name for compatibility with older SDK versions
from opentelemetry.sdk._logs.export import (
InMemoryLogExporter as InMemoryLogRecordExporter,
)
from opentelemetry.sdk._logs.export import (
SimpleLogRecordProcessor,
)
from opentelemetry.sdk.metrics import (
MeterProvider,
)
from opentelemetry.sdk.metrics.export import (
InMemoryMetricReader,
)
from opentelemetry.sdk.trace import TracerProvider
from opentelemetry.sdk.trace.export import SimpleSpanProcessor
from opentelemetry.sdk.trace.export.in_memory_span_exporter import (
InMemorySpanExporter,
)
from opentelemetry.sdk.trace.sampling import ALWAYS_OFF
@pytest.fixture(scope="function", name="span_exporter")
def fixture_span_exporter():
exporter = InMemorySpanExporter()
yield exporter
@pytest.fixture(scope="function", name="log_exporter")
def fixture_log_exporter():
exporter = InMemoryLogRecordExporter()
yield exporter
@pytest.fixture(scope="function", name="metric_reader")
def fixture_metric_reader():
exporter = InMemoryMetricReader()
yield exporter
@pytest.fixture(scope="function", name="tracer_provider")
def fixture_tracer_provider(span_exporter):
provider = TracerProvider()
provider.add_span_processor(SimpleSpanProcessor(span_exporter))
return provider
@pytest.fixture(scope="function", name="logger_provider")
def fixture_logger_provider(log_exporter):
provider = LoggerProvider()
provider.add_log_record_processor(SimpleLogRecordProcessor(log_exporter))
return provider
@pytest.fixture(scope="function", name="meter_provider")
def fixture_meter_provider(metric_reader):
meter_provider = MeterProvider(
metric_readers=[metric_reader],
)
return meter_provider
@pytest.fixture(autouse=True)
def environment():
if not os.getenv("OPENAI_API_KEY"):
os.environ["OPENAI_API_KEY"] = "test_openai_api_key"
@pytest.fixture
def openai_client():
return OpenAI()
@pytest.fixture
def async_openai_client():
return AsyncOpenAI()
@pytest.fixture(scope="module")
def vcr_config():
return {
"filter_headers": [
("cookie", "test_cookie"),
("authorization", "Bearer test_openai_api_key"),
("openai-organization", "test_openai_org_id"),
("openai-project", "test_openai_project_id"),
],
"decode_compressed_response": True,
"before_record_response": scrub_response_headers,
}
@pytest.fixture(
scope="function",
params=[(True, "span_only"), (False, "True")],
name="content_mode",
)
def fixture_content_mode(request):
# returns tuple: (latest_experimental_enabled: bool, content_mode: str)
# we don't test (True, "event_only"), (True, "span_and_event") because it's util's
# responsibility
return request.param
@pytest.fixture(scope="function")
def instrument_no_content(
tracer_provider,
logger_provider,
meter_provider,
content_mode,
):
_OpenTelemetrySemanticConventionStability._initialized = False
latest_experimental_enabled, _ = content_mode
os.environ.update(
{OTEL_SEMCONV_STABILITY_OPT_IN: "gen_ai_latest_experimental" if latest_experimental_enabled else ""}
)
instrumentor = OpenAIInstrumentor()
instrumentor.instrument(
tracer_provider=tracer_provider,
logger_provider=logger_provider,
meter_provider=meter_provider,
)
yield instrumentor
os.environ.pop(OTEL_INSTRUMENTATION_GENAI_CAPTURE_MESSAGE_CONTENT, None)
os.environ.pop(OTEL_SEMCONV_STABILITY_OPT_IN, None)
instrumentor.uninstrument()
@pytest.fixture(scope="function")
def instrument_with_content(tracer_provider, logger_provider, meter_provider, content_mode):
_OpenTelemetrySemanticConventionStability._initialized = False
latest_experimental_enabled, content_mode_value = content_mode
os.environ.update({OTEL_INSTRUMENTATION_GENAI_CAPTURE_MESSAGE_CONTENT: content_mode_value})
os.environ.update(
{OTEL_SEMCONV_STABILITY_OPT_IN: "gen_ai_latest_experimental" if latest_experimental_enabled else ""}
)
instrumentor = OpenAIInstrumentor()
instrumentor.instrument(
tracer_provider=tracer_provider,
logger_provider=logger_provider,
meter_provider=meter_provider,
)
yield instrumentor
os.environ.pop(OTEL_INSTRUMENTATION_GENAI_CAPTURE_MESSAGE_CONTENT, None)
os.environ.pop(OTEL_SEMCONV_STABILITY_OPT_IN, None)
instrumentor.uninstrument()
@pytest.fixture(scope="function")
def instrument_with_content_unsampled(span_exporter, logger_provider, meter_provider, content_mode):
_OpenTelemetrySemanticConventionStability._initialized = False
latest_experimental_enabled, content_mode_value = content_mode
os.environ.update({OTEL_INSTRUMENTATION_GENAI_CAPTURE_MESSAGE_CONTENT: content_mode_value})
os.environ.update(
{OTEL_SEMCONV_STABILITY_OPT_IN: "gen_ai_latest_experimental" if latest_experimental_enabled else ""}
)
tracer_provider = TracerProvider(sampler=ALWAYS_OFF)
tracer_provider.add_span_processor(SimpleSpanProcessor(span_exporter))
instrumentor = OpenAIInstrumentor()
instrumentor.instrument(
tracer_provider=tracer_provider,
logger_provider=logger_provider,
meter_provider=meter_provider,
)
yield instrumentor
os.environ.pop(OTEL_INSTRUMENTATION_GENAI_CAPTURE_MESSAGE_CONTENT, None)
os.environ.pop(OTEL_SEMCONV_STABILITY_OPT_IN, None)
instrumentor.uninstrument()
@pytest.fixture(scope="function")
def instrument_event_only(tracer_provider, logger_provider, meter_provider):
_OpenTelemetrySemanticConventionStability._initialized = False
os.environ.update(
{
OTEL_INSTRUMENTATION_GENAI_CAPTURE_MESSAGE_CONTENT: "event_only",
OTEL_SEMCONV_STABILITY_OPT_IN: "gen_ai_latest_experimental",
}
)
instrumentor = OpenAIInstrumentor()
instrumentor.instrument(
tracer_provider=tracer_provider,
logger_provider=logger_provider,
meter_provider=meter_provider,
)
yield instrumentor
os.environ.pop(OTEL_INSTRUMENTATION_GENAI_CAPTURE_MESSAGE_CONTENT, None)
os.environ.pop(OTEL_SEMCONV_STABILITY_OPT_IN, None)
instrumentor.uninstrument()
class LiteralBlockScalar(str):
"""Formats the string as a literal block scalar, preserving whitespace and
without interpreting escape characters"""
def literal_block_scalar_presenter(dumper, data):
"""Represents a scalar string as a literal block, via '|' syntax"""
return dumper.represent_scalar("tag:yaml.org,2002:str", data, style="|")
yaml.add_representer(LiteralBlockScalar, literal_block_scalar_presenter)
def process_string_value(string_value):
"""Pretty-prints JSON or returns long strings as a LiteralBlockScalar"""
try:
json_data = json.loads(string_value)
return LiteralBlockScalar(json.dumps(json_data, indent=2))
except (ValueError, TypeError):
if len(string_value) > 80:
return LiteralBlockScalar(string_value)
return string_value
def convert_body_to_literal(data):
"""Searches the data for body strings, attempting to pretty-print JSON"""
if isinstance(data, dict):
for key, value in data.items():
# Handle response body case (e.g., response.body.string)
if key == "body" and isinstance(value, dict) and "string" in value:
value["string"] = process_string_value(value["string"])
# Handle request body case (e.g., request.body)
elif key == "body" and isinstance(value, str):
data[key] = process_string_value(value)
else:
convert_body_to_literal(value)
elif isinstance(data, list):
for idx, choice in enumerate(data):
data[idx] = convert_body_to_literal(choice)
return data
class PrettyPrintJSONBody:
"""This makes request and response body recordings more readable."""
@staticmethod
def serialize(cassette_dict):
cassette_dict = convert_body_to_literal(cassette_dict)
return yaml.dump(cassette_dict, default_flow_style=False, allow_unicode=True)
@staticmethod
def deserialize(cassette_string):
return yaml.load(cassette_string, Loader=yaml.Loader)
@pytest.fixture(scope="module", autouse=True)
def fixture_vcr(vcr):
vcr.register_serializer("yaml", PrettyPrintJSONBody)
return vcr
def scrub_response_headers(response):
"""
This scrubs sensitive response headers. Note they are case-sensitive!
"""
response["headers"]["openai-organization"] = "test_openai_org_id"
response["headers"]["Set-Cookie"] = "test_set_cookie"
return response
requirements.latest.txt 0000664 0000000 0000000 00000003365 15270700723 0041675 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-openai-v2/tests # Copyright The OpenTelemetry Authors
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ********************************
# WARNING: NOT HERMETIC !!!!!!!!!!
# ********************************
#
# This "requirements.txt" is installed in conjunction
# with multiple other dependencies in the top-level "tox.ini"
# file. In particular, please see:
#
# openai-latest: {[testenv]test_deps}
# openai-latest: -r {toxinidir}/instrumentation-genai/opentelemetry-instrumentation-openai-v2/tests/requirements.latest.txt
#
# This provides additional dependencies, namely:
#
# opentelemetry-api
# opentelemetry-sdk
# opentelemetry-semantic-conventions
#
# ... with a "dev" version based on the latest distribution.
# This variant of the requirements aims to test the system using
# the newest supported version of external dependencies.
openai==2.26.0
pydantic==2.12.5
httpx==0.27.2
# older jiter is required for PyPy < 3.11
jiter==0.11.1
Deprecated==1.3.1
importlib-metadata==6.11.0
packaging==24.0
pytest==7.4.4
pytest-vcr==1.0.2
pytest-asyncio==0.21.0
wrapt==2.1.2
# test with the latest version of opentelemetry-api, sdk, and semantic conventions
-e opentelemetry-instrumentation
-e instrumentation-genai/opentelemetry-instrumentation-openai-v2
-e util/opentelemetry-util-genai requirements.oldest.txt 0000664 0000000 0000000 00000002547 15270700723 0041674 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-openai-v2/tests # Copyright The OpenTelemetry Authors
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# This variant of the requirements aims to test the system using
# the oldest supported version of external dependencies.
openai==1.26.0
numpy==2.3.1 ; python_version >= "3.11"
numpy==2.1.0 ; python_version == "3.10"
numpy==2.0.0 ; python_version == "3.9"
pydantic==2.12.5
httpx==0.27.2
Deprecated==1.2.14
importlib-metadata==6.11.0
packaging==24.0
pytest==7.4.4
pytest-vcr==1.0.2
pytest-asyncio==0.21.0
wrapt==1.16.0
opentelemetry-exporter-otlp-proto-http~=1.30
opentelemetry-api==1.40 # when updating, also update in pyproject.toml
opentelemetry-sdk==1.40 # when updating, also update in pyproject.toml
opentelemetry-semantic-conventions==0.61b0 # when updating, also update in pyproject.toml
-e util/opentelemetry-util-genai
-e instrumentation-genai/opentelemetry-instrumentation-openai-v2
test_async_chat_completions.py 0000664 0000000 0000000 00000125750 15270700723 0043262 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-openai-v2/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
# pylint: disable=too-many-locals,too-many-lines
from unittest.mock import AsyncMock
import pytest
from openai import APIConnectionError, AsyncOpenAI, NotFoundError
from opentelemetry.instrumentation.openai_v2.patch import (
AsyncLegacyChatStreamWrapper,
)
from opentelemetry.semconv._incubating.attributes import (
error_attributes as ErrorAttributes,
)
from opentelemetry.semconv._incubating.attributes import (
gen_ai_attributes as GenAIAttributes,
)
from opentelemetry.semconv._incubating.attributes import (
openai_attributes as OpenAIAttributes,
)
from opentelemetry.semconv._incubating.attributes import (
server_attributes as ServerAttributes,
)
from opentelemetry.util.genai.utils import is_experimental_mode
from .test_utils import (
DEFAULT_MODEL,
EXPECTED_TOOL_DEFINITIONS,
USER_ONLY_EXPECTED_INPUT_MESSAGES,
USER_ONLY_PROMPT,
WEATHER_TOOL_EXPECTED_INPUT_MESSAGES,
WEATHER_TOOL_PROMPT,
assert_all_attributes,
assert_message_in_logs,
assert_messages_attribute,
format_simple_expected_output_message,
get_current_weather_tool_definition,
)
@pytest.mark.asyncio()
async def test_async_chat_completion_with_content(
span_exporter,
log_exporter,
async_openai_client,
instrument_with_content,
vcr,
):
latest_experimental_enabled = is_experimental_mode()
with vcr.use_cassette("test_async_chat_completion_with_content.yaml"):
response = await async_openai_client.chat.completions.create(
messages=USER_ONLY_PROMPT, model=DEFAULT_MODEL, stream=False
)
spans = span_exporter.get_finished_spans()
assert_all_attributes(
spans[0],
DEFAULT_MODEL,
latest_experimental_enabled,
response.id,
response.model,
response.usage.prompt_tokens,
response.usage.completion_tokens,
)
if latest_experimental_enabled:
assert_messages_attribute(
spans[0].attributes["gen_ai.input.messages"],
USER_ONLY_EXPECTED_INPUT_MESSAGES,
)
assert_messages_attribute(
spans[0].attributes["gen_ai.output.messages"],
format_simple_expected_output_message(response.choices[0].message.content),
)
else:
logs = log_exporter.get_finished_logs()
assert len(logs) == 2
user_message = {"content": USER_ONLY_PROMPT[0]["content"]}
assert_message_in_logs(logs[0], "gen_ai.user.message", user_message, spans[0])
choice_event = {
"index": 0,
"finish_reason": "stop",
"message": {
"role": "assistant",
"content": response.choices[0].message.content,
},
}
assert_message_in_logs(logs[1], "gen_ai.choice", choice_event, spans[0])
@pytest.mark.asyncio()
async def test_async_chat_completion_no_content(
span_exporter,
log_exporter,
async_openai_client,
instrument_no_content,
vcr,
):
latest_experimental_enabled = is_experimental_mode()
with vcr.use_cassette("test_async_chat_completion_no_content.yaml"):
response = await async_openai_client.chat.completions.create(
messages=USER_ONLY_PROMPT, model=DEFAULT_MODEL, stream=False
)
spans = span_exporter.get_finished_spans()
assert_all_attributes(
spans[0],
DEFAULT_MODEL,
latest_experimental_enabled,
response.id,
response.model,
response.usage.prompt_tokens,
response.usage.completion_tokens,
)
logs = log_exporter.get_finished_logs()
if latest_experimental_enabled:
assert len(logs) == 0
assert "gen_ai.input.messages" not in spans[0].attributes
assert "gen_ai.output.messages" not in spans[0].attributes
else:
assert len(logs) == 2
assert_message_in_logs(logs[0], "gen_ai.user.message", None, spans[0])
choice_event = {
"index": 0,
"finish_reason": "stop",
"message": {"role": "assistant"},
}
assert_message_in_logs(logs[1], "gen_ai.choice", choice_event, spans[0])
@pytest.mark.asyncio()
async def test_async_chat_completion_bad_endpoint(span_exporter, instrument_no_content):
latest_experimental_enabled = is_experimental_mode()
client = AsyncOpenAI(base_url="http://localhost:4242")
with pytest.raises(APIConnectionError):
await client.chat.completions.create(
messages=USER_ONLY_PROMPT,
model=DEFAULT_MODEL,
timeout=0.1,
)
spans = span_exporter.get_finished_spans()
assert_all_attributes(
spans[0],
DEFAULT_MODEL,
latest_experimental_enabled,
server_address="localhost",
)
assert 4242 == spans[0].attributes[ServerAttributes.SERVER_PORT]
assert "APIConnectionError" == spans[0].attributes[ErrorAttributes.ERROR_TYPE]
@pytest.mark.asyncio()
async def test_async_chat_completion_404(span_exporter, async_openai_client, instrument_no_content, vcr):
latest_experimental_enabled = is_experimental_mode()
llm_model_value = "this-model-does-not-exist"
with vcr.use_cassette("test_async_chat_completion_404.yaml"):
with pytest.raises(NotFoundError):
await async_openai_client.chat.completions.create(
messages=USER_ONLY_PROMPT,
model=llm_model_value,
)
spans = span_exporter.get_finished_spans()
assert_all_attributes(spans[0], llm_model_value, latest_experimental_enabled)
assert "NotFoundError" == spans[0].attributes[ErrorAttributes.ERROR_TYPE]
@pytest.mark.asyncio()
async def test_async_chat_completion_api_exception_propagates(async_openai_client, instrument_no_content, vcr):
with vcr.use_cassette("test_async_chat_completion_404.yaml"):
with pytest.raises(NotFoundError):
await async_openai_client.chat.completions.create(
messages=USER_ONLY_PROMPT,
model="this-model-does-not-exist",
)
@pytest.mark.asyncio()
async def test_async_chat_completion_extra_params(span_exporter, async_openai_client, instrument_no_content, vcr):
latest_experimental_enabled = is_experimental_mode()
with vcr.use_cassette("test_async_chat_completion_extra_params.yaml"):
response = await async_openai_client.chat.completions.create(
messages=USER_ONLY_PROMPT,
model=DEFAULT_MODEL,
seed=42,
temperature=0.5,
max_tokens=50,
stream=False,
extra_body={"service_tier": "default"},
response_format={"type": "text"},
)
spans = span_exporter.get_finished_spans()
assert_all_attributes(
spans[0],
DEFAULT_MODEL,
latest_experimental_enabled,
response.id,
response.model,
response.usage.prompt_tokens,
response.usage.completion_tokens,
request_service_tier="default",
response_service_tier=getattr(response, "service_tier", None),
)
assert spans[0].attributes[GenAIAttributes.GEN_AI_REQUEST_SEED] == 42
assert spans[0].attributes[GenAIAttributes.GEN_AI_REQUEST_TEMPERATURE] == 0.5
assert spans[0].attributes[GenAIAttributes.GEN_AI_REQUEST_MAX_TOKENS] == 50
request_service_tier_attr_key = (
OpenAIAttributes.OPENAI_REQUEST_SERVICE_TIER
if latest_experimental_enabled
else GenAIAttributes.GEN_AI_OPENAI_REQUEST_SERVICE_TIER
)
assert spans[0].attributes[request_service_tier_attr_key] == "default"
output_type_attr_key = (
GenAIAttributes.GEN_AI_OUTPUT_TYPE
if latest_experimental_enabled
else GenAIAttributes.GEN_AI_OPENAI_REQUEST_RESPONSE_FORMAT
)
assert spans[0].attributes[output_type_attr_key] == "text"
@pytest.mark.asyncio()
async def test_async_chat_completion_multiple_choices(
span_exporter,
log_exporter,
async_openai_client,
instrument_with_content,
vcr,
):
latest_experimental_enabled = is_experimental_mode()
with vcr.use_cassette("test_async_chat_completion_multiple_choices.yaml"):
response = await async_openai_client.chat.completions.create(
messages=USER_ONLY_PROMPT, model=DEFAULT_MODEL, n=2, stream=False
)
spans = span_exporter.get_finished_spans()
assert_all_attributes(
spans[0],
DEFAULT_MODEL,
latest_experimental_enabled,
response.id,
response.model,
response.usage.prompt_tokens,
response.usage.completion_tokens,
)
logs = log_exporter.get_finished_logs()
if latest_experimental_enabled:
expected_output_messages = [
{
"role": "assistant",
"parts": [
{
"type": "text",
"content": response.choices[0].message.content,
}
],
"finish_reason": "stop",
},
{
"role": "assistant",
"parts": [
{
"type": "text",
"content": response.choices[1].message.content,
}
],
"finish_reason": "stop",
},
]
assert_messages_attribute(
spans[0].attributes["gen_ai.output.messages"],
expected_output_messages,
)
else:
assert len(logs) == 3 # 1 user message + 2 choice messages
user_message = {"content": USER_ONLY_PROMPT[0]["content"]}
assert_message_in_logs(logs[0], "gen_ai.user.message", user_message, spans[0])
choice_event_0 = {
"index": 0,
"finish_reason": "stop",
"message": {
"role": "assistant",
"content": response.choices[0].message.content,
},
}
assert_message_in_logs(logs[1], "gen_ai.choice", choice_event_0, spans[0])
choice_event_1 = {
"index": 1,
"finish_reason": "stop",
"message": {
"role": "assistant",
"content": response.choices[1].message.content,
},
}
assert_message_in_logs(logs[2], "gen_ai.choice", choice_event_1, spans[0])
@pytest.mark.asyncio()
async def test_async_chat_completion_with_raw_response(
span_exporter,
log_exporter,
async_openai_client,
instrument_with_content,
vcr,
):
latest_experimental_enabled = is_experimental_mode()
with vcr.use_cassette("test_async_chat_completion_with_raw_response.yaml"):
response = await async_openai_client.chat.completions.with_raw_response.create(
messages=USER_ONLY_PROMPT,
model=DEFAULT_MODEL,
)
response = response.parse()
spans = span_exporter.get_finished_spans()
assert_all_attributes(
spans[0],
DEFAULT_MODEL,
latest_experimental_enabled,
response.id,
response.model,
response.usage.prompt_tokens,
response.usage.completion_tokens,
)
logs = log_exporter.get_finished_logs()
if latest_experimental_enabled:
assert_messages_attribute(
spans[0].attributes["gen_ai.input.messages"],
USER_ONLY_EXPECTED_INPUT_MESSAGES,
)
assert_messages_attribute(
spans[0].attributes["gen_ai.output.messages"],
format_simple_expected_output_message(response.choices[0].message.content),
)
else:
assert len(logs) == 2
user_message = {"content": USER_ONLY_PROMPT[0]["content"]}
assert_message_in_logs(logs[0], "gen_ai.user.message", user_message, spans[0])
choice_event = {
"index": 0,
"finish_reason": "stop",
"message": {
"role": "assistant",
"content": response.choices[0].message.content,
},
}
assert_message_in_logs(logs[1], "gen_ai.choice", choice_event, spans[0])
@pytest.mark.asyncio()
async def test_chat_completion_with_raw_response_streaming(
span_exporter,
log_exporter,
async_openai_client,
instrument_with_content,
vcr,
):
latest_experimental_enabled = is_experimental_mode()
with vcr.use_cassette("test_chat_completion_with_raw_response_streaming.yaml"):
raw_response = await async_openai_client.chat.completions.with_raw_response.create(
messages=USER_ONLY_PROMPT,
model=DEFAULT_MODEL,
stream=True,
stream_options={"include_usage": True},
)
response = raw_response.parse()
message_content = ""
response_stream_usage = None
response_stream_model = None
response_stream_id = None
async for chunk in response:
if chunk.choices:
message_content += chunk.choices[0].delta.content or ""
# get the last chunk
if getattr(chunk, "usage", None):
response_stream_usage = chunk.usage
response_stream_model = chunk.model
response_stream_id = chunk.id
spans = span_exporter.get_finished_spans()
assert_all_attributes(
spans[0],
DEFAULT_MODEL,
latest_experimental_enabled,
response_stream_id,
response_stream_model,
response_stream_usage.prompt_tokens,
response_stream_usage.completion_tokens,
response_service_tier="default",
)
logs = log_exporter.get_finished_logs()
if latest_experimental_enabled:
assert len(logs) == 0
assert_messages_attribute(
spans[0].attributes["gen_ai.input.messages"],
USER_ONLY_EXPECTED_INPUT_MESSAGES,
)
assert_messages_attribute(
spans[0].attributes["gen_ai.output.messages"],
format_simple_expected_output_message(message_content),
)
else:
assert len(logs) == 2
user_message = {"content": USER_ONLY_PROMPT[0]["content"]}
assert_message_in_logs(logs[0], "gen_ai.user.message", user_message, spans[0])
choice_event = {
"index": 0,
"finish_reason": "stop",
"message": {
"role": "assistant",
"content": message_content,
},
}
assert_message_in_logs(logs[1], "gen_ai.choice", choice_event, spans[0])
@pytest.mark.asyncio()
async def test_async_chat_completion_tool_calls_with_content(
span_exporter,
log_exporter,
async_openai_client,
instrument_with_content,
vcr,
):
with vcr.use_cassette("test_async_chat_completion_tool_calls_with_content.yaml"):
await chat_completion_tool_call(
span_exporter,
log_exporter,
async_openai_client,
True,
is_experimental_mode(),
)
@pytest.mark.asyncio()
async def test_async_chat_completion_tool_calls_no_content(
span_exporter,
log_exporter,
async_openai_client,
instrument_no_content,
vcr,
):
with vcr.use_cassette("test_async_chat_completion_tool_calls_no_content.yaml"):
await chat_completion_tool_call(
span_exporter,
log_exporter,
async_openai_client,
False,
is_experimental_mode(),
)
async def chat_completion_tool_call(
span_exporter,
log_exporter,
async_openai_client,
expect_content,
latest_experimental_enabled,
):
# pylint: disable=too-many-statements
messages_value = WEATHER_TOOL_PROMPT.copy()
response_0 = await async_openai_client.chat.completions.create(
messages=messages_value,
model=DEFAULT_MODEL,
tool_choice="auto",
tools=[get_current_weather_tool_definition()],
)
# sanity check
assert "tool_calls" in response_0.choices[0].finish_reason
# final request
messages_value.append(
{
"role": "assistant",
"tool_calls": response_0.choices[0].message.to_dict()["tool_calls"],
}
)
tool_call_result_0 = {
"role": "tool",
"content": "50 degrees and raining",
"tool_call_id": response_0.choices[0].message.tool_calls[0].id,
}
tool_call_result_1 = {
"role": "tool",
"content": "70 degrees and sunny",
"tool_call_id": response_0.choices[0].message.tool_calls[1].id,
}
messages_value.append(tool_call_result_0)
messages_value.append(tool_call_result_1)
response_1 = await async_openai_client.chat.completions.create(messages=messages_value, model=DEFAULT_MODEL)
# sanity check
assert "stop" in response_1.choices[0].finish_reason
# validate both calls
spans = span_exporter.get_finished_spans()
assert len(spans) == 2
assert_all_attributes(
spans[0],
DEFAULT_MODEL,
latest_experimental_enabled,
response_0.id,
response_0.model,
response_0.usage.prompt_tokens,
response_0.usage.completion_tokens,
)
assert_all_attributes(
spans[1],
DEFAULT_MODEL,
latest_experimental_enabled,
response_1.id,
response_1.model,
response_1.usage.prompt_tokens,
response_1.usage.completion_tokens,
)
logs = log_exporter.get_finished_logs()
if latest_experimental_enabled:
if not expect_content:
pass
else:
# first call
assert_messages_attribute(
spans[0].attributes["gen_ai.input.messages"],
WEATHER_TOOL_EXPECTED_INPUT_MESSAGES,
)
first_output = [
{
"role": "assistant",
"parts": [
{
"type": "tool_call",
"id": response_0.choices[0].message.tool_calls[0].id,
"name": "get_current_weather",
"arguments": {"location": "Seattle, WA"},
},
{
"type": "tool_call",
"id": response_0.choices[0].message.tool_calls[1].id,
"name": "get_current_weather",
"arguments": {"location": "San Francisco, CA"},
},
],
"finish_reason": "tool_calls",
}
]
assert_messages_attribute(spans[0].attributes["gen_ai.output.messages"], first_output)
assert_messages_attribute(
spans[0].attributes["gen_ai.tool.definitions"],
EXPECTED_TOOL_DEFINITIONS,
)
assert "gen_ai.tool.definitions" not in spans[1].attributes
# second call
del first_output[0]["finish_reason"]
second_input = []
second_input += WEATHER_TOOL_EXPECTED_INPUT_MESSAGES.copy()
second_input += first_output
second_input += [
{
"role": "tool",
"parts": [
{
"type": "tool_call_response",
"id": response_0.choices[0].message.tool_calls[0].id,
"response": tool_call_result_0["content"],
}
],
},
{
"role": "tool",
"parts": [
{
"type": "tool_call_response",
"id": response_0.choices[0].message.tool_calls[1].id,
"response": tool_call_result_1["content"],
}
],
},
]
assert_messages_attribute(spans[1].attributes["gen_ai.input.messages"], second_input)
assert_messages_attribute(
spans[1].attributes["gen_ai.output.messages"],
[
{
"role": "assistant",
"parts": [
{
"type": "text",
"content": response_1.choices[0].message.content,
},
],
"finish_reason": "stop",
}
],
)
else:
assert len(logs) == 9 # 3 logs for first completion, 6 for second
# call one
system_message = {"content": messages_value[0]["content"]} if expect_content else None
assert_message_in_logs(logs[0], "gen_ai.system.message", system_message, spans[0])
user_message = {"content": messages_value[1]["content"]} if expect_content else None
assert_message_in_logs(logs[1], "gen_ai.user.message", user_message, spans[0])
function_call_0 = {"name": "get_current_weather"}
function_call_1 = {"name": "get_current_weather"}
if expect_content:
function_call_0["arguments"] = (
response_0.choices[0].message.tool_calls[0].function.arguments.replace("\n", "")
)
function_call_1["arguments"] = (
response_0.choices[0].message.tool_calls[1].function.arguments.replace("\n", "")
)
choice_event = {
"index": 0,
"finish_reason": "tool_calls",
"message": {
"role": "assistant",
"tool_calls": [
{
"id": response_0.choices[0].message.tool_calls[0].id,
"type": "function",
"function": function_call_0,
},
{
"id": response_0.choices[0].message.tool_calls[1].id,
"type": "function",
"function": function_call_1,
},
],
},
}
assert_message_in_logs(logs[2], "gen_ai.choice", choice_event, spans[0])
# call two
system_message = {"content": messages_value[0]["content"]} if expect_content else None
assert_message_in_logs(logs[3], "gen_ai.system.message", system_message, spans[1])
user_message = {"content": messages_value[1]["content"]} if expect_content else None
assert_message_in_logs(logs[4], "gen_ai.user.message", user_message, spans[1])
assistant_tool_call = {"tool_calls": messages_value[2]["tool_calls"]}
if not expect_content:
assistant_tool_call["tool_calls"][0]["function"]["arguments"] = None
assistant_tool_call["tool_calls"][1]["function"]["arguments"] = None
assert_message_in_logs(logs[5], "gen_ai.assistant.message", assistant_tool_call, spans[1])
tool_message_0 = {
"id": tool_call_result_0["tool_call_id"],
"content": tool_call_result_0["content"] if expect_content else None,
}
assert_message_in_logs(logs[6], "gen_ai.tool.message", tool_message_0, spans[1])
tool_message_1 = {
"id": tool_call_result_1["tool_call_id"],
"content": tool_call_result_1["content"] if expect_content else None,
}
assert_message_in_logs(logs[7], "gen_ai.tool.message", tool_message_1, spans[1])
message = {
"role": "assistant",
"content": response_1.choices[0].message.content if expect_content else None,
}
choice = {
"index": 0,
"finish_reason": "stop",
"message": message,
}
assert_message_in_logs(logs[8], "gen_ai.choice", choice, spans[1])
@pytest.mark.asyncio()
async def test_async_chat_completion_streaming(
span_exporter,
log_exporter,
async_openai_client,
instrument_with_content,
vcr,
):
latest_experimental_enabled = is_experimental_mode()
llm_model_value = "gpt-4"
kwargs = {
"model": llm_model_value,
"messages": USER_ONLY_PROMPT,
"stream": True,
"stream_options": {"include_usage": True},
}
response_stream_usage = None
response_stream_model = None
response_stream_id = None
response_stream_result = ""
with vcr.use_cassette("test_async_chat_completion_streaming.yaml"):
response = await async_openai_client.chat.completions.create(**kwargs)
async for chunk in response:
if chunk.choices:
response_stream_result += chunk.choices[0].delta.content or ""
# get the last chunk
if getattr(chunk, "usage", None):
response_stream_usage = chunk.usage
response_stream_model = chunk.model
response_stream_id = chunk.id
spans = span_exporter.get_finished_spans()
assert_all_attributes(
spans[0],
llm_model_value,
latest_experimental_enabled,
response_stream_id,
response_stream_model,
response_stream_usage.prompt_tokens,
response_stream_usage.completion_tokens,
)
logs = log_exporter.get_finished_logs()
if latest_experimental_enabled:
assert_messages_attribute(
spans[0].attributes["gen_ai.input.messages"],
USER_ONLY_EXPECTED_INPUT_MESSAGES,
)
assert_messages_attribute(
spans[0].attributes["gen_ai.output.messages"],
format_simple_expected_output_message(response_stream_result),
)
else:
assert len(logs) == 2
user_message = {"content": "Say this is a test"}
assert_message_in_logs(logs[0], "gen_ai.user.message", user_message, spans[0])
choice_event = {
"index": 0,
"finish_reason": "stop",
"message": {
"role": "assistant",
"content": response_stream_result,
},
}
assert_message_in_logs(logs[1], "gen_ai.choice", choice_event, spans[0])
@pytest.mark.asyncio()
async def test_async_chat_completion_streaming_user_exception_propagates(
span_exporter,
async_openai_client,
instrument_with_content,
vcr,
):
latest_experimental_enabled = is_experimental_mode()
llm_model_value = "gpt-4"
kwargs = {
"model": llm_model_value,
"messages": USER_ONLY_PROMPT,
"stream": True,
"stream_options": {"include_usage": True},
}
response_stream_model = None
response_stream_id = None
with vcr.use_cassette("test_async_chat_completion_streaming.yaml"):
response = await async_openai_client.chat.completions.create(**kwargs)
with pytest.raises(RuntimeError, match="user failure"):
async with response:
async for chunk in response:
response_stream_model = chunk.model
response_stream_id = chunk.id
raise RuntimeError("user failure")
spans = span_exporter.get_finished_spans()
assert_all_attributes(
spans[0],
llm_model_value,
latest_experimental_enabled,
response_stream_id,
response_stream_model,
)
assert "RuntimeError" == spans[0].attributes[ErrorAttributes.ERROR_TYPE]
@pytest.mark.asyncio()
async def test_async_chat_completion_streaming_not_complete(
span_exporter,
log_exporter,
async_openai_client,
instrument_with_content,
vcr,
):
latest_experimental_enabled = is_experimental_mode()
kwargs = {
"model": DEFAULT_MODEL,
"messages": USER_ONLY_PROMPT,
"stream": True,
}
response_stream_model = None
response_stream_id = None
response_stream_result = ""
with vcr.use_cassette("test_async_chat_completion_streaming_not_complete.yaml"):
response = await async_openai_client.chat.completions.create(**kwargs)
idx = 0
async for chunk in response:
if chunk.choices:
response_stream_result += chunk.choices[0].delta.content or ""
if idx == 1:
# fake a stop
break
if chunk.model:
response_stream_model = chunk.model
if chunk.id:
response_stream_id = chunk.id
idx += 1
await response.close()
spans = span_exporter.get_finished_spans()
assert_all_attributes(
spans[0],
DEFAULT_MODEL,
latest_experimental_enabled,
response_stream_id,
response_stream_model,
)
logs = log_exporter.get_finished_logs()
if latest_experimental_enabled:
assert_messages_attribute(
spans[0].attributes["gen_ai.input.messages"],
USER_ONLY_EXPECTED_INPUT_MESSAGES,
)
assert_messages_attribute(
spans[0].attributes["gen_ai.output.messages"],
format_simple_expected_output_message(response_stream_result, finish_reason="error"),
)
else:
assert len(logs) == 2
user_message = {"content": "Say this is a test"}
assert_message_in_logs(logs[0], "gen_ai.user.message", user_message, spans[0])
choice_event = {
"index": 0,
"finish_reason": "error",
"message": {
"role": "assistant",
"content": response_stream_result,
},
}
assert_message_in_logs(logs[1], "gen_ai.choice", choice_event, spans[0])
@pytest.mark.asyncio()
async def test_async_chat_completion_streaming_close_awaits_underlying_stream(
span_exporter,
async_openai_client,
instrument_with_content,
vcr,
):
# Closing the legacy async stream wrapper must await the underlying
# AsyncStream.close so the httpx response/connection is released instead of
# leaking.
# https://github.com/open-telemetry/opentelemetry-python-contrib/issues/4710
if is_experimental_mode():
pytest.skip("legacy stream wrapper only")
kwargs = {
"model": DEFAULT_MODEL,
"messages": USER_ONLY_PROMPT,
"stream": True,
}
with vcr.use_cassette("test_async_chat_completion_streaming_not_complete.yaml"):
response = await async_openai_client.chat.completions.create(**kwargs)
assert isinstance(response, AsyncLegacyChatStreamWrapper)
async for _ in response:
# consume one chunk, then exit early (mirrors cancellation)
break
# Wrap the real close so the underlying connection is still released
# while asserting it was awaited.
underlying_close = AsyncMock(wraps=response.stream.close)
response.stream.close = underlying_close
# close() must be awaitable and must await the underlying stream close.
await response.close()
underlying_close.assert_awaited_once()
spans = span_exporter.get_finished_spans()
assert len(spans) == 1
@pytest.mark.asyncio()
async def test_async_chat_completion_streaming_context_manager_awaits_close(
span_exporter,
async_openai_client,
instrument_with_content,
vcr,
):
# Exiting the legacy async stream wrapper as an async context manager must
# await the underlying AsyncStream.close so the httpx response/connection is
# released instead of leaking.
# https://github.com/open-telemetry/opentelemetry-python-contrib/issues/4710
if is_experimental_mode():
pytest.skip("legacy stream wrapper only")
kwargs = {
"model": DEFAULT_MODEL,
"messages": USER_ONLY_PROMPT,
"stream": True,
}
with vcr.use_cassette("test_async_chat_completion_streaming_not_complete.yaml"):
response = await async_openai_client.chat.completions.create(**kwargs)
assert isinstance(response, AsyncLegacyChatStreamWrapper)
# Wrap the real close so the underlying connection is still released
# while asserting it was awaited.
underlying_close = AsyncMock(wraps=response.stream.close)
response.stream.close = underlying_close
async with response:
async for _ in response:
# consume one chunk, then exit early
break
underlying_close.assert_awaited_once()
spans = span_exporter.get_finished_spans()
assert len(spans) == 1
@pytest.mark.asyncio()
async def test_async_chat_completion_multiple_choices_streaming(
span_exporter,
log_exporter,
async_openai_client,
instrument_with_content,
vcr,
):
latest_experimental_enabled = is_experimental_mode()
messages_value = WEATHER_TOOL_PROMPT.copy()
with vcr.use_cassette("test_async_chat_completion_multiple_choices_streaming.yaml"):
response_0 = await async_openai_client.chat.completions.create(
messages=messages_value,
model=DEFAULT_MODEL,
n=2,
stream=True,
stream_options={"include_usage": True},
)
response_stream_usage = None
response_stream_model = None
response_stream_id = None
# two strings for each choice
response_stream_result = ["", ""]
finish_reasons = ["", ""]
async for chunk in response_0:
if chunk.choices:
for choice in chunk.choices:
response_stream_result[choice.index] += choice.delta.content or ""
if choice.finish_reason:
finish_reasons[choice.index] = choice.finish_reason
# get the last chunk
if getattr(chunk, "usage", None):
response_stream_usage = chunk.usage
response_stream_model = chunk.model
response_stream_id = chunk.id
# sanity check
assert "stop" == finish_reasons[0]
spans = span_exporter.get_finished_spans()
assert_all_attributes(
spans[0],
DEFAULT_MODEL,
latest_experimental_enabled,
response_stream_id,
response_stream_model,
response_stream_usage.prompt_tokens,
response_stream_usage.completion_tokens,
)
logs = log_exporter.get_finished_logs()
if latest_experimental_enabled:
expected_output_messages = [
{
"role": "assistant",
"parts": [
{
"type": "text",
"content": "".join(response_stream_result[0]),
}
],
"finish_reason": "stop",
},
{
"role": "assistant",
"parts": [
{
"type": "text",
"content": "".join(response_stream_result[1]),
}
],
"finish_reason": "stop",
},
]
assert_messages_attribute(
spans[0].attributes["gen_ai.input.messages"],
WEATHER_TOOL_EXPECTED_INPUT_MESSAGES,
)
assert_messages_attribute(
spans[0].attributes["gen_ai.output.messages"],
expected_output_messages,
)
else:
assert len(logs) == 4
system_message = {"content": messages_value[0]["content"]}
assert_message_in_logs(logs[0], "gen_ai.system.message", system_message, spans[0])
user_message = {"content": "What's the weather in Seattle and San Francisco today?"}
assert_message_in_logs(logs[1], "gen_ai.user.message", user_message, spans[0])
choice_event_0 = {
"index": 0,
"finish_reason": "stop",
"message": {
"role": "assistant",
"content": "".join(response_stream_result[0]),
},
}
assert_message_in_logs(logs[2], "gen_ai.choice", choice_event_0, spans[0])
choice_event_1 = {
"index": 1,
"finish_reason": "stop",
"message": {
"role": "assistant",
"content": "".join(response_stream_result[1]),
},
}
assert_message_in_logs(logs[3], "gen_ai.choice", choice_event_1, spans[0])
@pytest.mark.asyncio()
async def test_async_chat_completion_multiple_tools_streaming_with_content(
span_exporter,
log_exporter,
async_openai_client,
instrument_with_content,
vcr,
):
with vcr.use_cassette("test_async_chat_completion_multiple_tools_streaming_with_content.yaml"):
await async_chat_completion_multiple_tools_streaming(
span_exporter,
log_exporter,
async_openai_client,
True,
is_experimental_mode(),
)
@pytest.mark.asyncio()
async def test_async_chat_completion_multiple_tools_streaming_no_content(
span_exporter,
log_exporter,
async_openai_client,
instrument_no_content,
vcr,
):
with vcr.use_cassette("test_async_chat_completion_multiple_tools_streaming_no_content.yaml"):
await async_chat_completion_multiple_tools_streaming(
span_exporter,
log_exporter,
async_openai_client,
False,
is_experimental_mode(),
)
@pytest.mark.asyncio()
async def test_async_chat_completion_streaming_unsampled(
span_exporter,
log_exporter,
async_openai_client,
instrument_with_content_unsampled,
vcr,
):
latest_experimental_enabled = is_experimental_mode()
kwargs = {
"model": DEFAULT_MODEL,
"messages": USER_ONLY_PROMPT,
"stream": True,
"stream_options": {"include_usage": True},
}
response_stream_result = ""
with vcr.use_cassette("test_async_chat_completion_streaming_unsampled.yaml"):
response = await async_openai_client.chat.completions.create(**kwargs)
async for chunk in response:
if chunk.choices:
response_stream_result += chunk.choices[0].delta.content or ""
spans = span_exporter.get_finished_spans()
assert len(spans) == 0
logs = log_exporter.get_finished_logs()
if not latest_experimental_enabled:
assert len(logs) == 2
user_message = {"content": "Say this is a test"}
assert_message_in_logs(logs[0], "gen_ai.user.message", user_message, None)
choice_event = {
"index": 0,
"finish_reason": "stop",
"message": {
"role": "assistant",
"content": response_stream_result,
},
}
assert_message_in_logs(logs[1], "gen_ai.choice", choice_event, None)
assert logs[0].log_record.trace_id is not None
assert logs[0].log_record.span_id is not None
assert not logs[0].log_record.trace_flags.sampled
assert logs[0].log_record.trace_id == logs[1].log_record.trace_id
assert logs[0].log_record.span_id == logs[1].log_record.span_id
assert logs[0].log_record.trace_flags == logs[1].log_record.trace_flags
async def async_chat_completion_multiple_tools_streaming(
span_exporter,
log_exporter,
async_openai_client,
expect_content,
latest_experimental_enabled,
):
messages_value = WEATHER_TOOL_PROMPT.copy()
response = await async_openai_client.chat.completions.create(
messages=messages_value,
model=DEFAULT_MODEL,
tool_choice="auto",
tools=[get_current_weather_tool_definition()],
stream=True,
stream_options={"include_usage": True},
)
finish_reason = None
response_stream_usage = None
response_stream_model = None
response_stream_id = None
# two tools
tool_names = ["", ""]
tool_call_ids = ["", ""]
tool_args = ["", ""]
async for chunk in response:
if chunk.choices:
if chunk.choices[0].finish_reason:
finish_reason = chunk.choices[0].finish_reason
for tool_call in chunk.choices[0].delta.tool_calls or []:
t_idx = tool_call.index
if tool_call.id:
tool_call_ids[t_idx] = tool_call.id
if tool_call.function:
if tool_call.function.arguments:
tool_args[t_idx] += tool_call.function.arguments
if tool_call.function.name:
tool_names[t_idx] = tool_call.function.name
# get the last chunk
if getattr(chunk, "usage", None):
response_stream_usage = chunk.usage
response_stream_model = chunk.model
response_stream_id = chunk.id
# sanity check
assert "tool_calls" == finish_reason
spans = span_exporter.get_finished_spans()
assert_all_attributes(
spans[0],
DEFAULT_MODEL,
latest_experimental_enabled,
response_stream_id,
response_stream_model,
response_stream_usage.prompt_tokens,
response_stream_usage.completion_tokens,
)
logs = log_exporter.get_finished_logs()
if latest_experimental_enabled:
if expect_content:
# first call
assert_messages_attribute(
spans[0].attributes["gen_ai.input.messages"],
WEATHER_TOOL_EXPECTED_INPUT_MESSAGES,
)
first_output = [
{
"role": "assistant",
"parts": [
{
"type": "tool_call",
"id": tool_call_ids[0],
"name": "get_current_weather",
"arguments": {"location": "Seattle, WA"},
},
{
"type": "tool_call",
"id": tool_call_ids[1],
"name": "get_current_weather",
"arguments": {"location": "San Francisco, CA"},
},
],
"finish_reason": "tool_calls",
}
]
assert_messages_attribute(spans[0].attributes["gen_ai.output.messages"], first_output)
assert_messages_attribute(
spans[0].attributes["gen_ai.tool.definitions"],
EXPECTED_TOOL_DEFINITIONS,
)
else:
assert len(logs) == 3
system_message = {"content": messages_value[0]["content"]} if expect_content else None
assert_message_in_logs(logs[0], "gen_ai.system.message", system_message, spans[0])
user_message = {"content": "What's the weather in Seattle and San Francisco today?"} if expect_content else None
assert_message_in_logs(logs[1], "gen_ai.user.message", user_message, spans[0])
choice_event = {
"index": 0,
"finish_reason": "tool_calls",
"message": {
"role": "assistant",
"tool_calls": [
{
"id": tool_call_ids[0],
"type": "function",
"function": {
"name": tool_names[0],
"arguments": (tool_args[0].replace("\n", "") if expect_content else None),
},
},
{
"id": tool_call_ids[1],
"type": "function",
"function": {
"name": tool_names[1],
"arguments": (tool_args[1].replace("\n", "") if expect_content else None),
},
},
],
},
}
assert_message_in_logs(logs[2], "gen_ai.choice", choice_event, spans[0])
test_async_embeddings.py 0000664 0000000 0000000 00000016722 15270700723 0042026 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-openai-v2/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
"""Unit tests for OpenAI Async Embeddings API instrumentation."""
import pytest
from openai import AsyncOpenAI, NotFoundError
from opentelemetry.semconv._incubating.attributes import (
error_attributes as ErrorAttributes,
)
from opentelemetry.semconv._incubating.attributes import (
gen_ai_attributes as GenAIAttributes,
)
from opentelemetry.semconv._incubating.metrics import gen_ai_metrics
from opentelemetry.util.genai.utils import is_experimental_mode
from .test_utils import (
DEFAULT_EMBEDDING_MODEL,
assert_all_attributes,
assert_embedding_attributes,
)
@pytest.mark.asyncio
async def test_async_embeddings_no_content(
span_exporter,
log_exporter,
async_openai_client,
instrument_no_content,
vcr,
):
"""Test creating embeddings asynchronously with content capture disabled"""
latest_experimental_enabled = is_experimental_mode()
input_text = "This is a test for async embeddings"
with vcr.use_cassette("test_async_embeddings_no_content.yaml"):
response = await async_openai_client.embeddings.create(
model=DEFAULT_EMBEDDING_MODEL,
input=input_text,
)
# Verify spans
spans = span_exporter.get_finished_spans()
assert len(spans) == 1
assert_embedding_attributes(
spans[0],
DEFAULT_EMBEDDING_MODEL,
latest_experimental_enabled,
response,
)
# No logs should be emitted when content capture is disabled
logs = log_exporter.get_finished_logs()
assert len(logs) == 0
@pytest.mark.asyncio
async def test_async_embeddings_with_dimensions(
span_exporter,
metric_reader,
async_openai_client,
instrument_no_content,
vcr,
):
"""Test creating embeddings asynchronously with custom dimensions"""
latest_experimental_enabled = is_experimental_mode()
input_text = "This is a test for async embeddings with dimensions"
dimensions = 512 # Using a smaller dimension than default
with vcr.use_cassette("test_async_embeddings_with_dimensions.yaml"):
response = await async_openai_client.embeddings.create(
model=DEFAULT_EMBEDDING_MODEL,
input=input_text,
dimensions=dimensions,
)
# Verify spans
spans = span_exporter.get_finished_spans()
assert len(spans) == 1
assert_embedding_attributes(
spans[0],
DEFAULT_EMBEDDING_MODEL,
latest_experimental_enabled,
response,
)
# Verify dimensions attribute is set correctly
assert spans[0].attributes["gen_ai.embeddings.dimension.count"] == dimensions
# Verify actual embedding dimensions match the requested dimensions
assert len(response.data[0].embedding) == dimensions
@pytest.mark.asyncio
async def test_async_embeddings_with_batch_input(
span_exporter,
metric_reader,
async_openai_client,
instrument_with_content,
vcr,
):
"""Test creating embeddings asynchronously with batch input"""
latest_experimental_enabled = is_experimental_mode()
input_texts = [
"This is the first test string for async embeddings",
"This is the second test string for async embeddings",
"This is the third test string for async embeddings",
]
with vcr.use_cassette("test_async_embeddings_with_batch_input.yaml"):
response = await async_openai_client.embeddings.create(
model=DEFAULT_EMBEDDING_MODEL,
input=input_texts,
)
# Verify spans
spans = span_exporter.get_finished_spans()
assert len(spans) == 1
assert_embedding_attributes(
spans[0],
DEFAULT_EMBEDDING_MODEL,
latest_experimental_enabled,
response,
)
# Verify results contain the same number of embeddings as input texts
assert len(response.data) == len(input_texts)
@pytest.mark.asyncio
async def test_async_embeddings_error_handling(span_exporter, metric_reader, instrument_no_content, vcr):
"""Test async embeddings error handling"""
latest_experimental_enabled = is_experimental_mode()
model_name = "non-existent-embedding-model"
input_text = "This is a test for async embeddings with error"
client = AsyncOpenAI()
with vcr.use_cassette("test_async_embeddings_error_handling.yaml"):
with pytest.raises(NotFoundError):
await client.embeddings.create(
model=model_name,
input=input_text,
)
# Verify spans
spans = span_exporter.get_finished_spans()
assert len(spans) == 1
assert_all_attributes(
spans[0],
model_name,
latest_experimental_enabled,
operation_name="embeddings",
)
assert "NotFoundError" == spans[0].attributes[ErrorAttributes.ERROR_TYPE]
@pytest.mark.asyncio
@pytest.mark.vcr()
async def test_async_embeddings_token_metrics(
span_exporter,
metric_reader,
async_openai_client,
instrument_no_content,
vcr,
):
"""Test that token usage metrics are correctly recorded for async embeddings"""
latest_experimental_enabled = is_experimental_mode()
input_text = "This is a test for async embeddings token metrics"
with vcr.use_cassette("test_async_embeddings_token_metrics.yaml"):
response = await async_openai_client.embeddings.create(
model=DEFAULT_EMBEDDING_MODEL,
input=input_text,
)
# Verify spans
spans = span_exporter.get_finished_spans()
assert len(spans) == 1
assert_embedding_attributes(
spans[0],
DEFAULT_EMBEDDING_MODEL,
latest_experimental_enabled,
response,
)
# Verify metrics
metrics = metric_reader.get_metrics_data().resource_metrics
assert len(metrics) == 1
metric_data = metrics[0].scope_metrics[0].metrics
# Verify token usage metric
token_metric = next(
(m for m in metric_data if m.name == gen_ai_metrics.GEN_AI_CLIENT_TOKEN_USAGE),
None,
)
assert token_metric is not None
# Find the input token data point
input_token_point = None
for point in token_metric.data.data_points:
if point.attributes[GenAIAttributes.GEN_AI_TOKEN_TYPE] == GenAIAttributes.GenAiTokenTypeValues.INPUT.value:
input_token_point = point
break
assert input_token_point is not None, "Input token metric not found"
# Verify the token counts match what was reported in the response
assert input_token_point.sum == response.usage.prompt_tokens
@pytest.mark.asyncio
async def test_async_embeddings_with_encoding_format(
span_exporter,
metric_reader,
async_openai_client,
instrument_no_content,
vcr,
):
"""Test creating embeddings with different encoding format"""
latest_experimental_enabled = is_experimental_mode()
input_text = "This is a test for embeddings with encoding format"
encoding_format = "base64"
with vcr.use_cassette("test_async_embeddings_with_encoding_format.yaml"):
response = await async_openai_client.embeddings.create(
model=DEFAULT_EMBEDDING_MODEL,
input=input_text,
encoding_format=encoding_format,
)
# Verify spans
spans = span_exporter.get_finished_spans()
assert len(spans) == 1
assert_embedding_attributes(
spans[0],
DEFAULT_EMBEDDING_MODEL,
latest_experimental_enabled,
response,
)
# Verify encoding_format attribute is set correctly
assert spans[0].attributes["gen_ai.request.encoding_formats"] == (encoding_format,)
test_chat_completions.py 0000664 0000000 0000000 00000137157 15270700723 0042071 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-openai-v2/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
# pylint: disable=too-many-locals,too-many-lines
import logging
import os
import pytest
from openai import (
NOT_GIVEN,
APIConnectionError,
NotFoundError,
OpenAI,
)
try:
from openai import not_given # pylint: disable=no-name-in-module
except ImportError:
not_given = NOT_GIVEN
from opentelemetry.semconv._incubating.attributes import (
error_attributes as ErrorAttributes,
)
from opentelemetry.semconv._incubating.attributes import (
gen_ai_attributes as GenAIAttributes,
)
from opentelemetry.semconv._incubating.attributes import (
openai_attributes as OpenAIAttributes,
)
from opentelemetry.semconv._incubating.attributes import (
server_attributes as ServerAttributes,
)
from opentelemetry.semconv._incubating.metrics import gen_ai_metrics
from opentelemetry.util.genai.utils import is_experimental_mode
from .test_utils import (
DEFAULT_MODEL,
EXPECTED_TOOL_DEFINITIONS,
USER_ONLY_EXPECTED_INPUT_MESSAGES,
USER_ONLY_PROMPT,
WEATHER_TOOL_EXPECTED_INPUT_MESSAGES,
WEATHER_TOOL_PROMPT,
assert_all_attributes,
assert_message_in_logs,
assert_messages_attribute,
format_simple_expected_output_message,
get_current_weather_tool_definition,
)
def test_chat_completion_with_content(span_exporter, log_exporter, openai_client, instrument_with_content, vcr):
latest_experimental_enabled = is_experimental_mode()
print(
f"latest_experimental_enabled={latest_experimental_enabled}, ENV_VAR={os.getenv('OTEL_SEMCONV_STABILITY_OPT_IN')}"
)
with vcr.use_cassette("test_chat_completion_with_content.yaml"):
response = openai_client.chat.completions.create(
messages=USER_ONLY_PROMPT,
model=DEFAULT_MODEL,
stream=False,
)
spans = span_exporter.get_finished_spans()
assert_all_attributes(
spans[0],
DEFAULT_MODEL,
latest_experimental_enabled,
response.id,
response.model,
response.usage.prompt_tokens,
response.usage.completion_tokens,
)
if latest_experimental_enabled:
assert_messages_attribute(
spans[0].attributes["gen_ai.input.messages"],
USER_ONLY_EXPECTED_INPUT_MESSAGES,
)
assert_messages_attribute(
spans[0].attributes["gen_ai.output.messages"],
format_simple_expected_output_message(response.choices[0].message.content),
)
else:
logs = log_exporter.get_finished_logs()
assert len(logs) == 2
user_message = {"content": USER_ONLY_PROMPT[0]["content"]}
assert_message_in_logs(logs[0], "gen_ai.user.message", user_message, spans[0])
choice_event = {
"index": 0,
"finish_reason": "stop",
"message": {
"role": "assistant",
"content": response.choices[0].message.content,
},
}
assert_message_in_logs(logs[1], "gen_ai.choice", choice_event, spans[0])
def test_chat_completion_handles_not_given(
span_exporter,
log_exporter,
openai_client,
instrument_no_content,
vcr,
caplog,
):
caplog.set_level(logging.WARNING)
latest_experimental_enabled = is_experimental_mode()
with vcr.use_cassette("test_chat_completion_handles_not_given.yaml"):
response = openai_client.chat.completions.create(
messages=USER_ONLY_PROMPT,
model=DEFAULT_MODEL,
stream=False,
top_p=NOT_GIVEN,
max_tokens=not_given,
)
(span,) = span_exporter.get_finished_spans()
assert_all_attributes(
span,
DEFAULT_MODEL,
latest_experimental_enabled,
response.id,
response.model,
response.usage.prompt_tokens,
response.usage.completion_tokens,
response_service_tier="default",
)
assert GenAIAttributes.GEN_AI_REQUEST_TOP_P not in span.attributes
assert GenAIAttributes.GEN_AI_REQUEST_MAX_TOKENS not in span.attributes
assert_no_invalid_type_warning(caplog)
def test_chat_completion_no_content(span_exporter, log_exporter, openai_client, instrument_no_content, vcr):
latest_experimental_enabled = is_experimental_mode()
with vcr.use_cassette("test_chat_completion_no_content.yaml"):
response = openai_client.chat.completions.create(messages=USER_ONLY_PROMPT, model=DEFAULT_MODEL, stream=False)
spans = span_exporter.get_finished_spans()
assert_all_attributes(
spans[0],
DEFAULT_MODEL,
latest_experimental_enabled,
response.id,
response.model,
response.usage.prompt_tokens,
response.usage.completion_tokens,
)
logs = log_exporter.get_finished_logs()
if latest_experimental_enabled:
assert len(logs) == 0
assert "gen_ai.input.messages" not in spans[0].attributes
assert "gen_ai.output.messages" not in spans[0].attributes
else:
assert len(logs) == 2
assert_message_in_logs(logs[0], "gen_ai.user.message", None, spans[0])
choice_event = {
"index": 0,
"finish_reason": "stop",
"message": {"role": "assistant"},
}
assert_message_in_logs(logs[1], "gen_ai.choice", choice_event, spans[0])
def test_chat_completion_bad_endpoint(span_exporter, metric_reader, instrument_no_content, vcr):
latest_experimental_enabled = is_experimental_mode()
client = OpenAI(base_url="http://localhost:4242")
with vcr.use_cassette("test_chat_completion_bad_endpoint.yaml"):
with pytest.raises(APIConnectionError):
client.chat.completions.create(
messages=USER_ONLY_PROMPT,
model=DEFAULT_MODEL,
timeout=0.1,
)
spans = span_exporter.get_finished_spans()
assert_all_attributes(
spans[0],
DEFAULT_MODEL,
latest_experimental_enabled,
server_address="localhost",
)
assert 4242 == spans[0].attributes[ServerAttributes.SERVER_PORT]
assert "APIConnectionError" == spans[0].attributes[ErrorAttributes.ERROR_TYPE]
metrics = metric_reader.get_metrics_data().resource_metrics
assert len(metrics) == 1
metric_data = metrics[0].scope_metrics[0].metrics
duration_metric = next(
(m for m in metric_data if m.name == gen_ai_metrics.GEN_AI_CLIENT_OPERATION_DURATION),
None,
)
assert duration_metric is not None
assert duration_metric.data.data_points[0].sum > 0
assert duration_metric.data.data_points[0].attributes[ErrorAttributes.ERROR_TYPE] == "APIConnectionError"
def test_chat_completion_404(span_exporter, openai_client, metric_reader, instrument_no_content, vcr):
latest_experimental_enabled = is_experimental_mode()
llm_model_value = "this-model-does-not-exist"
with vcr.use_cassette("test_chat_completion_404.yaml"):
with pytest.raises(NotFoundError):
openai_client.chat.completions.create(
messages=USER_ONLY_PROMPT,
model=llm_model_value,
)
spans = span_exporter.get_finished_spans()
assert_all_attributes(spans[0], llm_model_value, latest_experimental_enabled)
assert "NotFoundError" == spans[0].attributes[ErrorAttributes.ERROR_TYPE]
metrics = metric_reader.get_metrics_data().resource_metrics
assert len(metrics) == 1
metric_data = metrics[0].scope_metrics[0].metrics
duration_metric = next(
(m for m in metric_data if m.name == gen_ai_metrics.GEN_AI_CLIENT_OPERATION_DURATION),
None,
)
assert duration_metric is not None
assert duration_metric.data.data_points[0].sum > 0
assert duration_metric.data.data_points[0].attributes[ErrorAttributes.ERROR_TYPE] == "NotFoundError"
def test_chat_completion_api_exception_propagates(openai_client, instrument_no_content, vcr):
with vcr.use_cassette("test_chat_completion_404.yaml"):
with pytest.raises(NotFoundError):
openai_client.chat.completions.create(
messages=USER_ONLY_PROMPT,
model="this-model-does-not-exist",
)
def test_chat_completion_extra_params(span_exporter, openai_client, instrument_no_content, vcr):
latest_experimental_enabled = is_experimental_mode()
with vcr.use_cassette("test_chat_completion_extra_params.yaml"):
response = openai_client.chat.completions.create(
n=2,
messages=USER_ONLY_PROMPT,
model=DEFAULT_MODEL,
seed=42,
temperature=0.5,
max_tokens=50,
stream=False,
extra_body={"service_tier": "default"},
response_format={"type": "text"},
stop=["full", "stop"],
)
spans = span_exporter.get_finished_spans()
assert_all_attributes(
spans[0],
DEFAULT_MODEL,
latest_experimental_enabled,
response.id,
response.model,
response.usage.prompt_tokens,
response.usage.completion_tokens,
request_service_tier="default",
response_service_tier=getattr(response, "service_tier", None),
)
assert spans[0].attributes[GenAIAttributes.GEN_AI_REQUEST_SEED] == 42
assert spans[0].attributes[GenAIAttributes.GEN_AI_REQUEST_TEMPERATURE] == 0.5
assert spans[0].attributes[GenAIAttributes.GEN_AI_REQUEST_MAX_TOKENS] == 50
request_service_tier_attr_key = (
OpenAIAttributes.OPENAI_REQUEST_SERVICE_TIER
if latest_experimental_enabled
else GenAIAttributes.GEN_AI_OPENAI_REQUEST_SERVICE_TIER
)
assert spans[0].attributes[request_service_tier_attr_key] == "default"
output_type_attr_key = (
GenAIAttributes.GEN_AI_OUTPUT_TYPE
if latest_experimental_enabled
else GenAIAttributes.GEN_AI_OPENAI_REQUEST_RESPONSE_FORMAT
)
assert spans[0].attributes[output_type_attr_key] == "text"
assert spans[0].attributes[GenAIAttributes.GEN_AI_REQUEST_STOP_SEQUENCES] == ("full", "stop")
assert spans[0].attributes[GenAIAttributes.GEN_AI_REQUEST_CHOICE_COUNT] == 2
def test_chat_completion_n_1_is_not_reported(span_exporter, openai_client, instrument_no_content, vcr):
latest_experimental_enabled = is_experimental_mode()
with vcr.use_cassette("test_chat_completion_n_1_is_not_reported.yaml"):
response = openai_client.chat.completions.create(
n=1,
messages=USER_ONLY_PROMPT,
model=DEFAULT_MODEL,
)
spans = span_exporter.get_finished_spans()
assert_all_attributes(
spans[0],
DEFAULT_MODEL,
latest_experimental_enabled,
response.id,
response.model,
response.usage.prompt_tokens,
response.usage.completion_tokens,
response_service_tier=getattr(response, "service_tier", None),
)
assert GenAIAttributes.GEN_AI_REQUEST_CHOICE_COUNT not in spans[0].attributes
def test_chat_completion_handle_stop_sequences_as_string(span_exporter, openai_client, instrument_no_content, vcr):
latest_experimental_enabled = is_experimental_mode()
with vcr.use_cassette("test_chat_completion_handle_stop_sequences_as_string.yaml"):
response = openai_client.chat.completions.create(
messages=USER_ONLY_PROMPT,
model=DEFAULT_MODEL,
stop="stop",
)
spans = span_exporter.get_finished_spans()
assert_all_attributes(
spans[0],
DEFAULT_MODEL,
latest_experimental_enabled,
response.id,
response.model,
response.usage.prompt_tokens,
response.usage.completion_tokens,
response_service_tier=getattr(response, "service_tier", None),
)
assert spans[0].attributes[GenAIAttributes.GEN_AI_REQUEST_STOP_SEQUENCES] == ("stop",)
def test_chat_completion_multiple_choices(span_exporter, log_exporter, openai_client, instrument_with_content, vcr):
latest_experimental_enabled = is_experimental_mode()
with vcr.use_cassette("test_chat_completion_multiple_choices.yaml"):
response = openai_client.chat.completions.create(
messages=USER_ONLY_PROMPT, model=DEFAULT_MODEL, n=2, stream=False
)
spans = span_exporter.get_finished_spans()
assert_all_attributes(
spans[0],
DEFAULT_MODEL,
latest_experimental_enabled,
response.id,
response.model,
response.usage.prompt_tokens,
response.usage.completion_tokens,
)
assert spans[0].attributes[GenAIAttributes.GEN_AI_REQUEST_CHOICE_COUNT] == 2
logs = log_exporter.get_finished_logs()
if latest_experimental_enabled:
expected_output_messages = [
{
"role": "assistant",
"parts": [
{
"type": "text",
"content": response.choices[0].message.content,
}
],
"finish_reason": "stop",
},
{
"role": "assistant",
"parts": [
{
"type": "text",
"content": response.choices[1].message.content,
}
],
"finish_reason": "stop",
},
]
assert_messages_attribute(
spans[0].attributes["gen_ai.input.messages"],
USER_ONLY_EXPECTED_INPUT_MESSAGES,
)
assert_messages_attribute(
spans[0].attributes["gen_ai.output.messages"],
expected_output_messages,
)
else:
assert len(logs) == 3 # 1 user message + 2 choice messages
user_message = {"content": USER_ONLY_PROMPT[0]["content"]}
assert_message_in_logs(logs[0], "gen_ai.user.message", user_message, spans[0])
choice_event_0 = {
"index": 0,
"finish_reason": "stop",
"message": {
"role": "assistant",
"content": response.choices[0].message.content,
},
}
assert_message_in_logs(logs[1], "gen_ai.choice", choice_event_0, spans[0])
choice_event_1 = {
"index": 1,
"finish_reason": "stop",
"message": {
"role": "assistant",
"content": response.choices[1].message.content,
},
}
assert_message_in_logs(logs[2], "gen_ai.choice", choice_event_1, spans[0])
def test_chat_completion_with_raw_response(span_exporter, log_exporter, openai_client, instrument_with_content, vcr):
latest_experimental_enabled = is_experimental_mode()
with vcr.use_cassette("test_chat_completion_with_raw_response.yaml"):
response = openai_client.chat.completions.with_raw_response.create(
messages=USER_ONLY_PROMPT,
model=DEFAULT_MODEL,
)
response = response.parse()
spans = span_exporter.get_finished_spans()
assert_all_attributes(
spans[0],
DEFAULT_MODEL,
latest_experimental_enabled,
response.id,
response.model,
response.usage.prompt_tokens,
response.usage.completion_tokens,
)
if latest_experimental_enabled:
assert_messages_attribute(
spans[0].attributes["gen_ai.input.messages"],
USER_ONLY_EXPECTED_INPUT_MESSAGES,
)
assert_messages_attribute(
spans[0].attributes["gen_ai.output.messages"],
format_simple_expected_output_message(response.choices[0].message.content),
)
else:
logs = log_exporter.get_finished_logs()
assert len(logs) == 2
user_message = {"content": USER_ONLY_PROMPT[0]["content"]}
assert_message_in_logs(logs[0], "gen_ai.user.message", user_message, spans[0])
choice_event = {
"index": 0,
"finish_reason": "stop",
"message": {
"role": "assistant",
"content": response.choices[0].message.content,
},
}
assert_message_in_logs(logs[1], "gen_ai.choice", choice_event, spans[0])
def test_chat_completion_with_raw_response_streaming(
span_exporter, log_exporter, openai_client, instrument_with_content, vcr
):
latest_experimental_enabled = is_experimental_mode()
with vcr.use_cassette("test_chat_completion_with_raw_response_streaming.yaml"):
raw_response = openai_client.chat.completions.with_raw_response.create(
messages=USER_ONLY_PROMPT,
model=DEFAULT_MODEL,
stream=True,
stream_options={"include_usage": True},
)
response = raw_response.parse()
message_content = ""
response_stream_usage = None
response_stream_model = None
response_stream_id = None
for chunk in response:
if chunk.choices:
message_content += chunk.choices[0].delta.content or ""
# get the last chunk
if getattr(chunk, "usage", None):
response_stream_usage = chunk.usage
response_stream_model = chunk.model
response_stream_id = chunk.id
spans = span_exporter.get_finished_spans()
assert_all_attributes(
spans[0],
DEFAULT_MODEL,
latest_experimental_enabled,
response_stream_id,
response_stream_model,
response_stream_usage.prompt_tokens,
response_stream_usage.completion_tokens,
response_service_tier="default",
)
logs = log_exporter.get_finished_logs()
if latest_experimental_enabled:
assert len(logs) == 0
assert_messages_attribute(
spans[0].attributes["gen_ai.input.messages"],
USER_ONLY_EXPECTED_INPUT_MESSAGES,
)
assert_messages_attribute(
spans[0].attributes["gen_ai.output.messages"],
format_simple_expected_output_message(message_content),
)
else:
assert len(logs) == 2
user_message = {"content": USER_ONLY_PROMPT[0]["content"]}
assert_message_in_logs(logs[0], "gen_ai.user.message", user_message, spans[0])
choice_event = {
"index": 0,
"finish_reason": "stop",
"message": {
"role": "assistant",
"content": message_content,
},
}
assert_message_in_logs(logs[1], "gen_ai.choice", choice_event, spans[0])
def test_chat_completion_tool_calls_with_content(
span_exporter, log_exporter, openai_client, instrument_with_content, vcr
):
with vcr.use_cassette("test_chat_completion_tool_calls_with_content.yaml"):
chat_completion_tool_call(
span_exporter,
log_exporter,
openai_client,
True,
is_experimental_mode(),
)
def test_chat_completion_tool_calls_no_content(span_exporter, log_exporter, openai_client, instrument_no_content, vcr):
with vcr.use_cassette("test_chat_completion_tool_calls_no_content.yaml"):
chat_completion_tool_call(
span_exporter,
log_exporter,
openai_client,
False,
is_experimental_mode(),
)
def chat_completion_tool_call(
span_exporter,
log_exporter,
openai_client,
expect_content,
latest_experimental_enabled,
):
# pylint: disable=too-many-statements
messages_value = WEATHER_TOOL_PROMPT.copy()
response_0 = openai_client.chat.completions.create(
messages=messages_value,
model=DEFAULT_MODEL,
tool_choice="auto",
tools=[get_current_weather_tool_definition()],
)
# sanity check
assert "tool_calls" in response_0.choices[0].finish_reason
# final request
messages_value.append(
{
"role": "assistant",
"tool_calls": response_0.choices[0].message.to_dict()["tool_calls"],
}
)
tool_call_result_0 = {
"role": "tool",
"content": "50 degrees and raining",
"tool_call_id": response_0.choices[0].message.tool_calls[0].id,
}
tool_call_result_1 = {
"role": "tool",
"content": "70 degrees and sunny",
"tool_call_id": response_0.choices[0].message.tool_calls[1].id,
}
messages_value.append(tool_call_result_0)
messages_value.append(tool_call_result_1)
response_1 = openai_client.chat.completions.create(messages=messages_value, model=DEFAULT_MODEL)
# sanity check
assert "stop" in response_1.choices[0].finish_reason
# validate both calls
spans = span_exporter.get_finished_spans()
assert len(spans) == 2
assert_all_attributes(
spans[0],
DEFAULT_MODEL,
latest_experimental_enabled,
response_0.id,
response_0.model,
response_0.usage.prompt_tokens,
response_0.usage.completion_tokens,
)
assert_all_attributes(
spans[1],
DEFAULT_MODEL,
latest_experimental_enabled,
response_1.id,
response_1.model,
response_1.usage.prompt_tokens,
response_1.usage.completion_tokens,
)
logs = log_exporter.get_finished_logs()
if latest_experimental_enabled:
if not expect_content:
pass
else:
# first call
assert_messages_attribute(
spans[0].attributes["gen_ai.input.messages"],
WEATHER_TOOL_EXPECTED_INPUT_MESSAGES,
)
first_output = [
{
"role": "assistant",
"parts": [
{
"type": "tool_call",
"id": response_0.choices[0].message.tool_calls[0].id,
"name": "get_current_weather",
"arguments": {"location": "Seattle, WA"},
},
{
"type": "tool_call",
"id": response_0.choices[0].message.tool_calls[1].id,
"name": "get_current_weather",
"arguments": {"location": "San Francisco, CA"},
},
],
"finish_reason": "tool_calls",
}
]
assert_messages_attribute(spans[0].attributes["gen_ai.output.messages"], first_output)
assert_messages_attribute(
spans[0].attributes["gen_ai.tool.definitions"],
EXPECTED_TOOL_DEFINITIONS,
)
assert "gen_ai.tool.definitions" not in spans[1].attributes
# second call
del first_output[0]["finish_reason"]
second_input = []
second_input += WEATHER_TOOL_EXPECTED_INPUT_MESSAGES.copy()
second_input += first_output
second_input += [
{
"role": "tool",
"parts": [
{
"type": "tool_call_response",
"id": response_0.choices[0].message.tool_calls[0].id,
"response": tool_call_result_0["content"],
}
],
},
{
"role": "tool",
"parts": [
{
"type": "tool_call_response",
"id": response_0.choices[0].message.tool_calls[1].id,
"response": tool_call_result_1["content"],
}
],
},
]
assert_messages_attribute(spans[1].attributes["gen_ai.input.messages"], second_input)
assert_messages_attribute(
spans[1].attributes["gen_ai.output.messages"],
format_simple_expected_output_message(response_1.choices[0].message.content),
)
else:
assert len(logs) == 9 # 3 logs for first completion, 6 for second
# call one
system_message = {"content": messages_value[0]["content"]} if expect_content else None
assert_message_in_logs(logs[0], "gen_ai.system.message", system_message, spans[0])
user_message = {"content": messages_value[1]["content"]} if expect_content else None
assert_message_in_logs(logs[1], "gen_ai.user.message", user_message, spans[0])
function_call_0 = {"name": "get_current_weather"}
function_call_1 = {"name": "get_current_weather"}
if expect_content:
function_call_0["arguments"] = (
response_0.choices[0].message.tool_calls[0].function.arguments.replace("\n", "")
)
function_call_1["arguments"] = (
response_0.choices[0].message.tool_calls[1].function.arguments.replace("\n", "")
)
choice_event = {
"index": 0,
"finish_reason": "tool_calls",
"message": {
"role": "assistant",
"tool_calls": [
{
"id": response_0.choices[0].message.tool_calls[0].id,
"type": "function",
"function": function_call_0,
},
{
"id": response_0.choices[0].message.tool_calls[1].id,
"type": "function",
"function": function_call_1,
},
],
},
}
assert_message_in_logs(logs[2], "gen_ai.choice", choice_event, spans[0])
# call two
system_message = {"content": messages_value[0]["content"]} if expect_content else None
assert_message_in_logs(logs[3], "gen_ai.system.message", system_message, spans[1])
user_message = {"content": messages_value[1]["content"]} if expect_content else None
assert_message_in_logs(logs[4], "gen_ai.user.message", user_message, spans[1])
assistant_tool_call = {"tool_calls": messages_value[2]["tool_calls"]}
if not expect_content:
assistant_tool_call["tool_calls"][0]["function"]["arguments"] = None
assistant_tool_call["tool_calls"][1]["function"]["arguments"] = None
assert_message_in_logs(logs[5], "gen_ai.assistant.message", assistant_tool_call, spans[1])
tool_message_0 = {
"id": tool_call_result_0["tool_call_id"],
"content": tool_call_result_0["content"] if expect_content else None,
}
assert_message_in_logs(logs[6], "gen_ai.tool.message", tool_message_0, spans[1])
tool_message_1 = {
"id": tool_call_result_1["tool_call_id"],
"content": tool_call_result_1["content"] if expect_content else None,
}
assert_message_in_logs(logs[7], "gen_ai.tool.message", tool_message_1, spans[1])
message = {
"role": "assistant",
"content": response_1.choices[0].message.content if expect_content else None,
}
choice = {
"index": 0,
"finish_reason": "stop",
"message": message,
}
assert_message_in_logs(logs[8], "gen_ai.choice", choice, spans[1])
def test_chat_completion_streaming(span_exporter, log_exporter, openai_client, instrument_with_content, vcr):
latest_experimental_enabled = is_experimental_mode()
kwargs = {
"model": DEFAULT_MODEL,
"messages": USER_ONLY_PROMPT,
"stream": True,
"stream_options": {"include_usage": True},
}
response_stream_usage = None
response_stream_model = None
response_stream_id = None
response_stream_result = ""
with vcr.use_cassette("test_chat_completion_streaming.yaml"):
response = openai_client.chat.completions.create(**kwargs)
for chunk in response:
if chunk.choices:
response_stream_result += chunk.choices[0].delta.content or ""
# get the last chunk
if getattr(chunk, "usage", None):
response_stream_usage = chunk.usage
response_stream_model = chunk.model
response_stream_id = chunk.id
spans = span_exporter.get_finished_spans()
assert_all_attributes(
spans[0],
DEFAULT_MODEL,
latest_experimental_enabled,
response_stream_id,
response_stream_model,
response_stream_usage.prompt_tokens,
response_stream_usage.completion_tokens,
)
logs = log_exporter.get_finished_logs()
if latest_experimental_enabled:
assert_messages_attribute(
spans[0].attributes["gen_ai.input.messages"],
USER_ONLY_EXPECTED_INPUT_MESSAGES,
)
assert_messages_attribute(
spans[0].attributes["gen_ai.output.messages"],
format_simple_expected_output_message(response_stream_result),
)
else:
assert len(logs) == 2
user_message = {"content": "Say this is a test"}
assert_message_in_logs(logs[0], "gen_ai.user.message", user_message, spans[0])
choice_event = {
"index": 0,
"finish_reason": "stop",
"message": {
"role": "assistant",
"content": response_stream_result,
},
}
assert_message_in_logs(logs[1], "gen_ai.choice", choice_event, spans[0])
def test_chat_completion_streaming_user_exception_propagates(
span_exporter, openai_client, instrument_with_content, vcr
):
latest_experimental_enabled = is_experimental_mode()
kwargs = {
"model": DEFAULT_MODEL,
"messages": USER_ONLY_PROMPT,
"stream": True,
"stream_options": {"include_usage": True},
}
response_stream_model = None
response_stream_id = None
with vcr.use_cassette("test_chat_completion_streaming.yaml"):
response = openai_client.chat.completions.create(**kwargs)
with pytest.raises(RuntimeError, match="user failure"):
with response:
for chunk in response:
response_stream_model = chunk.model
response_stream_id = chunk.id
raise RuntimeError("user failure")
spans = span_exporter.get_finished_spans()
assert_all_attributes(
spans[0],
DEFAULT_MODEL,
latest_experimental_enabled,
response_stream_id,
response_stream_model,
)
assert "RuntimeError" == spans[0].attributes[ErrorAttributes.ERROR_TYPE]
def test_chat_completion_streaming_user_exception_wins_over_close_exception(
span_exporter, openai_client, instrument_with_content, vcr, monkeypatch
):
if not is_experimental_mode():
pytest.skip("new stream wrapper only")
kwargs = {
"model": DEFAULT_MODEL,
"messages": USER_ONLY_PROMPT,
"stream": True,
"stream_options": {"include_usage": True},
}
with vcr.use_cassette("test_chat_completion_streaming.yaml"):
response = openai_client.chat.completions.create(**kwargs)
original_close = response.__wrapped__.close
def close_raises():
original_close()
raise RuntimeError("close failure")
monkeypatch.setattr(response.__wrapped__, "close", close_raises)
with pytest.raises(RuntimeError, match="user failure"):
with response:
raise RuntimeError("user failure")
spans = span_exporter.get_finished_spans()
assert "RuntimeError" == spans[0].attributes[ErrorAttributes.ERROR_TYPE]
def test_chat_completion_streaming_close_exception_propagates_when_first(
span_exporter, openai_client, instrument_with_content, vcr, monkeypatch
):
if not is_experimental_mode():
pytest.skip("new stream wrapper only")
kwargs = {
"model": DEFAULT_MODEL,
"messages": USER_ONLY_PROMPT,
"stream": True,
"stream_options": {"include_usage": True},
}
with vcr.use_cassette("test_chat_completion_streaming.yaml"):
response = openai_client.chat.completions.create(**kwargs)
original_close = response.__wrapped__.close
def close_raises():
original_close()
raise RuntimeError("close failure")
monkeypatch.setattr(response.__wrapped__, "close", close_raises)
with pytest.raises(RuntimeError, match="close failure"):
response.close()
spans = span_exporter.get_finished_spans()
assert "RuntimeError" == spans[0].attributes[ErrorAttributes.ERROR_TYPE]
def test_chat_completion_streaming_instrumentation_finalize_errors_swallowed(
span_exporter, openai_client, instrument_with_content, vcr, monkeypatch
):
if not is_experimental_mode():
pytest.skip("new stream wrapper only")
kwargs = {
"model": DEFAULT_MODEL,
"messages": USER_ONLY_PROMPT,
"stream": True,
"stream_options": {"include_usage": True},
}
with vcr.use_cassette("test_chat_completion_streaming.yaml"):
response = openai_client.chat.completions.create(**kwargs)
def stop_raises():
raise RuntimeError("instrumentation failure")
monkeypatch.setattr(response, "_on_stream_end", stop_raises)
response.close()
assert span_exporter.get_finished_spans() == ()
def test_chat_completion_streaming_not_complete(
span_exporter, log_exporter, openai_client, instrument_with_content, vcr
):
latest_experimental_enabled = is_experimental_mode()
kwargs = {
"model": DEFAULT_MODEL,
"messages": USER_ONLY_PROMPT,
"stream": True,
}
response_stream_model = None
response_stream_id = None
response_stream_result = ""
with vcr.use_cassette("test_chat_completion_streaming_not_complete.yaml"):
response = openai_client.chat.completions.create(**kwargs)
for idx, chunk in enumerate(response):
if chunk.choices:
response_stream_result += chunk.choices[0].delta.content or ""
if idx == 1:
# fake a stop
break
if chunk.model:
response_stream_model = chunk.model
if chunk.id:
response_stream_id = chunk.id
response.close()
spans = span_exporter.get_finished_spans()
assert_all_attributes(
spans[0],
DEFAULT_MODEL,
latest_experimental_enabled,
response_stream_id,
response_stream_model,
)
logs = log_exporter.get_finished_logs()
if latest_experimental_enabled:
assert_messages_attribute(
spans[0].attributes["gen_ai.input.messages"],
USER_ONLY_EXPECTED_INPUT_MESSAGES,
)
assert_messages_attribute(
spans[0].attributes["gen_ai.output.messages"],
format_simple_expected_output_message(response_stream_result, finish_reason="error"),
)
else:
assert len(logs) == 2
user_message = {"content": "Say this is a test"}
assert_message_in_logs(logs[0], "gen_ai.user.message", user_message, spans[0])
choice_event = {
"index": 0,
"finish_reason": "error",
"message": {
"role": "assistant",
"content": response_stream_result,
},
}
assert_message_in_logs(logs[1], "gen_ai.choice", choice_event, spans[0])
def test_chat_completion_multiple_choices_streaming(
span_exporter, log_exporter, openai_client, instrument_with_content, vcr
):
latest_experimental_enabled = is_experimental_mode()
with vcr.use_cassette("test_chat_completion_multiple_choices_streaming.yaml"):
response_0 = openai_client.chat.completions.create(
messages=WEATHER_TOOL_PROMPT,
model=DEFAULT_MODEL,
n=2,
stream=True,
stream_options={"include_usage": True},
)
# two strings for each choice
response_stream_result = ["", ""]
finish_reasons = ["", ""]
response_stream_usage = None
response_stream_model = None
response_stream_id = None
for chunk in response_0:
if chunk.choices:
for choice in chunk.choices:
response_stream_result[choice.index] += choice.delta.content or ""
if choice.finish_reason:
finish_reasons[choice.index] = choice.finish_reason
# get the last chunk
if getattr(chunk, "usage", None):
response_stream_usage = chunk.usage
response_stream_model = chunk.model
response_stream_id = chunk.id
# sanity check
assert "stop" == finish_reasons[0]
spans = span_exporter.get_finished_spans()
assert_all_attributes(
spans[0],
DEFAULT_MODEL,
latest_experimental_enabled,
response_stream_id,
response_stream_model,
response_stream_usage.prompt_tokens,
response_stream_usage.completion_tokens,
)
logs = log_exporter.get_finished_logs()
if latest_experimental_enabled:
expected_output_messages = [
{
"role": "assistant",
"parts": [
{
"type": "text",
"content": "".join(response_stream_result[0]),
}
],
"finish_reason": "stop",
},
{
"role": "assistant",
"parts": [
{
"type": "text",
"content": "".join(response_stream_result[1]),
}
],
"finish_reason": "stop",
},
]
assert_messages_attribute(
spans[0].attributes["gen_ai.input.messages"],
WEATHER_TOOL_EXPECTED_INPUT_MESSAGES,
)
assert_messages_attribute(
spans[0].attributes["gen_ai.output.messages"],
expected_output_messages,
)
else:
assert len(logs) == 4
system_message = {"content": WEATHER_TOOL_PROMPT[0]["content"]}
assert_message_in_logs(logs[0], "gen_ai.system.message", system_message, spans[0])
user_message = {"content": "What's the weather in Seattle and San Francisco today?"}
assert_message_in_logs(logs[1], "gen_ai.user.message", user_message, spans[0])
choice_event_0 = {
"index": 0,
"finish_reason": "stop",
"message": {
"role": "assistant",
"content": "".join(response_stream_result[0]),
},
}
assert_message_in_logs(logs[2], "gen_ai.choice", choice_event_0, spans[0])
choice_event_1 = {
"index": 1,
"finish_reason": "stop",
"message": {
"role": "assistant",
"content": "".join(response_stream_result[1]),
},
}
assert_message_in_logs(logs[3], "gen_ai.choice", choice_event_1, spans[0])
def test_chat_completion_multiple_tools_streaming_with_content(
span_exporter, log_exporter, openai_client, instrument_with_content, vcr
):
with vcr.use_cassette("test_chat_completion_multiple_tools_streaming_with_content.yaml"):
chat_completion_multiple_tools_streaming(
span_exporter,
log_exporter,
openai_client,
True,
is_experimental_mode(),
)
def test_chat_completion_multiple_tools_streaming_no_content(
span_exporter, log_exporter, openai_client, instrument_no_content, vcr
):
with vcr.use_cassette("test_chat_completion_multiple_tools_streaming_no_content.yaml"):
chat_completion_multiple_tools_streaming(
span_exporter,
log_exporter,
openai_client,
False,
is_experimental_mode(),
)
def test_chat_completion_with_content_span_unsampled(
span_exporter,
log_exporter,
openai_client,
instrument_with_content_unsampled,
vcr,
):
latest_experimental_enabled = is_experimental_mode()
with vcr.use_cassette("test_chat_completion_with_content_span_unsampled.yaml"):
response = openai_client.chat.completions.create(messages=USER_ONLY_PROMPT, model=DEFAULT_MODEL, stream=False)
spans = span_exporter.get_finished_spans()
assert len(spans) == 0
logs = log_exporter.get_finished_logs()
if not latest_experimental_enabled:
assert len(logs) == 2
user_message = {"content": USER_ONLY_PROMPT[0]["content"]}
assert_message_in_logs(logs[0], "gen_ai.user.message", user_message, None)
choice_event = {
"index": 0,
"finish_reason": "stop",
"message": {
"role": "assistant",
"content": response.choices[0].message.content,
},
}
assert_message_in_logs(logs[1], "gen_ai.choice", choice_event, None)
assert logs[0].log_record.trace_id is not None
assert logs[0].log_record.span_id is not None
assert not logs[0].log_record.trace_flags.sampled
assert logs[0].log_record.trace_id == logs[1].log_record.trace_id
assert logs[0].log_record.span_id == logs[1].log_record.span_id
assert logs[0].log_record.trace_flags == logs[1].log_record.trace_flags
def test_chat_completion_with_context_manager_streaming(
span_exporter, log_exporter, openai_client, instrument_with_content, vcr
):
latest_experimental_enabled = is_experimental_mode()
with vcr.use_cassette("test_chat_completion_with_context_manager_streaming.yaml"):
with openai_client.chat.completions.create(
messages=USER_ONLY_PROMPT,
model=DEFAULT_MODEL,
stream=True,
stream_options={"include_usage": True},
) as response:
message_content = ""
response_stream_usage = None
response_stream_model = None
response_stream_id = None
for chunk in response:
if chunk.choices:
message_content += chunk.choices[0].delta.content or ""
# get the last chunk
if getattr(chunk, "usage", None):
response_stream_usage = chunk.usage
response_stream_model = chunk.model
response_stream_id = chunk.id
spans = span_exporter.get_finished_spans()
assert_all_attributes(
spans[0],
DEFAULT_MODEL,
latest_experimental_enabled,
response_stream_id,
response_stream_model,
response_stream_usage.prompt_tokens,
response_stream_usage.completion_tokens,
response_service_tier="default",
)
logs = log_exporter.get_finished_logs()
if latest_experimental_enabled:
assert len(logs) == 0
assert_messages_attribute(
spans[0].attributes["gen_ai.input.messages"],
USER_ONLY_EXPECTED_INPUT_MESSAGES,
)
assert_messages_attribute(
spans[0].attributes["gen_ai.output.messages"],
format_simple_expected_output_message(message_content),
)
else:
assert len(logs) == 2
user_message = {"content": USER_ONLY_PROMPT[0]["content"]}
assert_message_in_logs(logs[0], "gen_ai.user.message", user_message, spans[0])
choice_event = {
"index": 0,
"finish_reason": "stop",
"message": {
"role": "assistant",
"content": message_content,
},
}
assert_message_in_logs(logs[1], "gen_ai.choice", choice_event, spans[0])
def chat_completion_multiple_tools_streaming(
span_exporter,
log_exporter,
openai_client,
expect_content,
latest_experimental_enabled,
):
response = openai_client.chat.completions.create(
messages=WEATHER_TOOL_PROMPT,
model=DEFAULT_MODEL,
tool_choice="auto",
tools=[get_current_weather_tool_definition()],
stream=True,
stream_options={"include_usage": True},
)
finish_reason = None
response_stream_usage = None
response_stream_model = None
response_stream_id = None
# two tools
tool_names = ["", ""]
tool_call_ids = ["", ""]
tool_args = ["", ""]
for chunk in response:
if chunk.choices:
if chunk.choices[0].finish_reason:
finish_reason = chunk.choices[0].finish_reason
for tool_call in chunk.choices[0].delta.tool_calls or []:
t_idx = tool_call.index
if tool_call.id:
tool_call_ids[t_idx] = tool_call.id
if tool_call.function:
if tool_call.function.arguments:
tool_args[t_idx] += tool_call.function.arguments
if tool_call.function.name:
tool_names[t_idx] = tool_call.function.name
# get the last chunk
if getattr(chunk, "usage", None):
response_stream_usage = chunk.usage
response_stream_model = chunk.model
response_stream_id = chunk.id
# sanity check
assert "tool_calls" == finish_reason
spans = span_exporter.get_finished_spans()
assert_all_attributes(
spans[0],
DEFAULT_MODEL,
latest_experimental_enabled,
response_stream_id,
response_stream_model,
response_stream_usage.prompt_tokens,
response_stream_usage.completion_tokens,
)
logs = log_exporter.get_finished_logs()
if latest_experimental_enabled:
if expect_content:
# first call
assert_messages_attribute(
spans[0].attributes["gen_ai.input.messages"],
WEATHER_TOOL_EXPECTED_INPUT_MESSAGES,
)
first_output = [
{
"role": "assistant",
"parts": [
{
"type": "tool_call",
"id": tool_call_ids[0],
"name": "get_current_weather",
"arguments": {"location": "Seattle, WA"},
},
{
"type": "tool_call",
"id": tool_call_ids[1],
"name": "get_current_weather",
"arguments": {"location": "San Francisco, CA"},
},
],
"finish_reason": "tool_calls",
}
]
assert_messages_attribute(spans[0].attributes["gen_ai.output.messages"], first_output)
assert_messages_attribute(
spans[0].attributes["gen_ai.tool.definitions"],
EXPECTED_TOOL_DEFINITIONS,
)
else:
assert len(logs) == 3
system_message = {"content": WEATHER_TOOL_PROMPT[0]["content"]} if expect_content else None
assert_message_in_logs(logs[0], "gen_ai.system.message", system_message, spans[0])
user_message = {"content": "What's the weather in Seattle and San Francisco today?"} if expect_content else None
assert_message_in_logs(logs[1], "gen_ai.user.message", user_message, spans[0])
choice_event = {
"index": 0,
"finish_reason": "tool_calls",
"message": {
"role": "assistant",
"tool_calls": [
{
"id": tool_call_ids[0],
"type": "function",
"function": {
"name": tool_names[0],
"arguments": tool_args[0].replace("\n", "") if expect_content else None,
},
},
{
"id": tool_call_ids[1],
"type": "function",
"function": {
"name": tool_names[1],
"arguments": tool_args[1].replace("\n", "") if expect_content else None,
},
},
],
},
}
assert_message_in_logs(logs[2], "gen_ai.choice", choice_event, spans[0])
def assert_no_invalid_type_warning(caplog):
assert "Invalid type" not in caplog.text
test_chat_metrics.py 0000664 0000000 0000000 00000015703 15270700723 0041173 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-openai-v2/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
import pytest
from tests.test_utils import DEFAULT_MODEL, USER_ONLY_PROMPT
from opentelemetry.semconv._incubating.attributes import (
gen_ai_attributes as GenAIAttributes,
)
from opentelemetry.semconv._incubating.attributes import (
openai_attributes as OpenAIAttributes,
)
from opentelemetry.semconv._incubating.attributes import (
server_attributes as ServerAttributes,
)
from opentelemetry.semconv._incubating.metrics import gen_ai_metrics
from opentelemetry.util.genai.utils import is_experimental_mode
_DURATION_BUCKETS = (
0.01,
0.02,
0.04,
0.08,
0.16,
0.32,
0.64,
1.28,
2.56,
5.12,
10.24,
20.48,
40.96,
81.92,
)
_TOKEN_USAGE_BUCKETS = (
1,
4,
16,
64,
256,
1024,
4096,
16384,
65536,
262144,
1048576,
4194304,
16777216,
67108864,
)
def assert_all_metric_attributes(data_point, latest_experimental_enabled):
assert GenAIAttributes.GEN_AI_OPERATION_NAME in data_point.attributes
assert (
data_point.attributes[GenAIAttributes.GEN_AI_OPERATION_NAME]
== GenAIAttributes.GenAiOperationNameValues.CHAT.value
)
provider_name_attr_name = "gen_ai.provider.name" if latest_experimental_enabled else GenAIAttributes.GEN_AI_SYSTEM
assert provider_name_attr_name in data_point.attributes
assert data_point.attributes[provider_name_attr_name] == GenAIAttributes.GenAiSystemValues.OPENAI.value
assert GenAIAttributes.GEN_AI_REQUEST_MODEL in data_point.attributes
assert data_point.attributes[GenAIAttributes.GEN_AI_REQUEST_MODEL] == "gpt-4o-mini"
assert GenAIAttributes.GEN_AI_RESPONSE_MODEL in data_point.attributes
assert data_point.attributes[GenAIAttributes.GEN_AI_RESPONSE_MODEL] == "gpt-4o-mini-2024-07-18"
system_fingerprint_attr_key = (
OpenAIAttributes.OPENAI_RESPONSE_SYSTEM_FINGERPRINT
if latest_experimental_enabled
else GenAIAttributes.GEN_AI_OPENAI_RESPONSE_SYSTEM_FINGERPRINT
)
response_service_tier_attr_key = (
OpenAIAttributes.OPENAI_RESPONSE_SERVICE_TIER
if latest_experimental_enabled
else GenAIAttributes.GEN_AI_OPENAI_RESPONSE_SERVICE_TIER
)
request_service_tier_attr_key = (
OpenAIAttributes.OPENAI_REQUEST_SERVICE_TIER
if latest_experimental_enabled
else GenAIAttributes.GEN_AI_OPENAI_REQUEST_SERVICE_TIER
)
assert system_fingerprint_attr_key in data_point.attributes
assert data_point.attributes[system_fingerprint_attr_key] == "fp_0ba0d124f1"
assert request_service_tier_attr_key not in data_point.attributes
assert response_service_tier_attr_key in data_point.attributes
assert data_point.attributes[response_service_tier_attr_key] == "default"
assert data_point.attributes[ServerAttributes.SERVER_ADDRESS] == "api.openai.com"
def test_chat_completion_metrics(metric_reader, openai_client, instrument_with_content, vcr):
latest_experimental_enabled = is_experimental_mode()
with vcr.use_cassette("test_chat_completion_metrics.yaml"):
openai_client.chat.completions.create(messages=USER_ONLY_PROMPT, model=DEFAULT_MODEL, stream=False)
metrics = metric_reader.get_metrics_data().resource_metrics
assert len(metrics) == 1
metric_data = metrics[0].scope_metrics[0].metrics
assert len(metric_data) == 2
duration_metric = next(
(m for m in metric_data if m.name == gen_ai_metrics.GEN_AI_CLIENT_OPERATION_DURATION),
None,
)
assert duration_metric is not None
duration_point = duration_metric.data.data_points[0]
assert duration_point.sum > 0
assert_all_metric_attributes(duration_point, latest_experimental_enabled)
assert duration_point.explicit_bounds == _DURATION_BUCKETS
token_usage_metric = next(
(m for m in metric_data if m.name == gen_ai_metrics.GEN_AI_CLIENT_TOKEN_USAGE),
None,
)
assert token_usage_metric is not None
input_token_usage = next(
(
d
for d in token_usage_metric.data.data_points
if d.attributes[GenAIAttributes.GEN_AI_TOKEN_TYPE] == GenAIAttributes.GenAiTokenTypeValues.INPUT.value
),
None,
)
assert input_token_usage is not None
assert input_token_usage.sum == 12
assert input_token_usage.explicit_bounds == _TOKEN_USAGE_BUCKETS
assert input_token_usage.bucket_counts[2] == 1
assert_all_metric_attributes(input_token_usage, latest_experimental_enabled)
output_token_usage = next(
(
d
for d in token_usage_metric.data.data_points
if d.attributes[GenAIAttributes.GEN_AI_TOKEN_TYPE] == GenAIAttributes.GenAiTokenTypeValues.COMPLETION.value
),
None,
)
assert output_token_usage is not None
assert output_token_usage.sum == 5
# assert against buckets [1, 4, 16, 64, 256, 1024, 4096, 16384, 65536, 262144, 1048576, 4194304, 16777216, 67108864]
assert output_token_usage.bucket_counts[2] == 1
assert_all_metric_attributes(output_token_usage, latest_experimental_enabled)
@pytest.mark.asyncio()
async def test_async_chat_completion_metrics(metric_reader, async_openai_client, instrument_with_content, vcr):
latest_experimental_enabled = is_experimental_mode()
with vcr.use_cassette("test_async_chat_completion_metrics.yaml"):
await async_openai_client.chat.completions.create(messages=USER_ONLY_PROMPT, model=DEFAULT_MODEL, stream=False)
metrics = metric_reader.get_metrics_data().resource_metrics
assert len(metrics) == 1
metric_data = metrics[0].scope_metrics[0].metrics
assert len(metric_data) == 2
duration_metric = next(
(m for m in metric_data if m.name == gen_ai_metrics.GEN_AI_CLIENT_OPERATION_DURATION),
None,
)
assert duration_metric is not None
assert duration_metric.data.data_points[0].sum > 0
assert_all_metric_attributes(duration_metric.data.data_points[0], latest_experimental_enabled)
token_usage_metric = next(
(m for m in metric_data if m.name == gen_ai_metrics.GEN_AI_CLIENT_TOKEN_USAGE),
None,
)
assert token_usage_metric is not None
input_token_usage = next(
(
d
for d in token_usage_metric.data.data_points
if d.attributes[GenAIAttributes.GEN_AI_TOKEN_TYPE] == GenAIAttributes.GenAiTokenTypeValues.INPUT.value
),
None,
)
assert input_token_usage is not None
assert input_token_usage.sum == 12
assert_all_metric_attributes(input_token_usage, latest_experimental_enabled)
output_token_usage = next(
(
d
for d in token_usage_metric.data.data_points
if d.attributes[GenAIAttributes.GEN_AI_TOKEN_TYPE] == GenAIAttributes.GenAiTokenTypeValues.COMPLETION.value
),
None,
)
assert output_token_usage is not None
assert output_token_usage.sum == 12
assert_all_metric_attributes(output_token_usage, latest_experimental_enabled)
test_choice_buffer.py 0000664 0000000 0000000 00000011374 15270700723 0041311 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-openai-v2/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
"""Unit tests for ChoiceBuffer and ToolCallBuffer classes."""
from openai.types.chat.chat_completion_chunk import (
ChoiceDeltaToolCall,
ChoiceDeltaToolCallFunction,
)
from opentelemetry.instrumentation.openai_v2.chat_buffers import (
ChoiceBuffer,
ToolCallBuffer,
)
def test_toolcallbuffer_append_arguments_with_string():
buf = ToolCallBuffer(0, "call_1", "get_weather")
buf.append_arguments('{"city":')
buf.append_arguments(' "NYC"}')
assert "".join(buf.arguments) == '{"city": "NYC"}'
def test_toolcallbuffer_append_arguments_with_none_is_skipped():
"""Regression test for issue #4344.
Some OpenAI-compatible providers (vLLM, TGI, etc.) send
arguments=None on tool-call delta chunks instead of arguments="".
This must not crash when joining the arguments list.
"""
buf = ToolCallBuffer(0, "call_1", "get_weather")
buf.append_arguments(None)
buf.append_arguments('{"city": "NYC"}')
buf.append_arguments(None)
assert "".join(buf.arguments) == '{"city": "NYC"}'
def test_toolcallbuffer_append_arguments_all_none():
buf = ToolCallBuffer(0, "call_1", "get_weather")
buf.append_arguments(None)
buf.append_arguments(None)
assert "".join(buf.arguments) == ""
def test_toolcallbuffer_append_arguments_empty_string():
buf = ToolCallBuffer(0, "call_1", "get_weather")
buf.append_arguments("")
buf.append_arguments('{"city": "NYC"}')
assert "".join(buf.arguments) == '{"city": "NYC"}'
def test_choicebuffer_append_tool_call_with_none_arguments():
"""End-to-end regression test for issue #4344.
Simulates the exact scenario from the bug report where a provider
sends arguments=None on the first tool-call delta chunk.
"""
buf = ChoiceBuffer(0)
buf.append_tool_call(
ChoiceDeltaToolCall(
index=0,
id="call_1",
type="function",
function=ChoiceDeltaToolCallFunction(name="get_weather", arguments=None),
)
)
buf.append_tool_call(
ChoiceDeltaToolCall(
index=0,
function=ChoiceDeltaToolCallFunction(arguments='{"city": "NYC"}'),
)
)
# This must not raise TypeError
result = "".join(buf.tool_calls_buffers[0].arguments)
assert result == '{"city": "NYC"}'
def test_choicebuffer_append_tool_call_normal_flow():
"""Standard OpenAI flow where arguments="" on first delta."""
buf = ChoiceBuffer(0)
buf.append_tool_call(
ChoiceDeltaToolCall(
index=0,
id="call_1",
type="function",
function=ChoiceDeltaToolCallFunction(name="get_weather", arguments=""),
)
)
buf.append_tool_call(
ChoiceDeltaToolCall(
index=0,
function=ChoiceDeltaToolCallFunction(arguments='{"city": "NYC"}'),
)
)
result = "".join(buf.tool_calls_buffers[0].arguments)
assert result == '{"city": "NYC"}'
def test_choicebuffer_append_multiple_tool_calls_with_none_arguments():
"""Multiple tool calls where some have arguments=None."""
buf = ChoiceBuffer(0)
# First tool call
buf.append_tool_call(
ChoiceDeltaToolCall(
index=0,
id="call_1",
type="function",
function=ChoiceDeltaToolCallFunction(name="get_weather", arguments=None),
)
)
buf.append_tool_call(
ChoiceDeltaToolCall(
index=0,
function=ChoiceDeltaToolCallFunction(arguments='{"city": "NYC"}'),
)
)
# Second tool call
buf.append_tool_call(
ChoiceDeltaToolCall(
index=1,
id="call_2",
type="function",
function=ChoiceDeltaToolCallFunction(name="get_time", arguments=None),
)
)
buf.append_tool_call(
ChoiceDeltaToolCall(
index=1,
function=ChoiceDeltaToolCallFunction(arguments='{"tz": "EST"}'),
)
)
assert "".join(buf.tool_calls_buffers[0].arguments) == '{"city": "NYC"}'
assert "".join(buf.tool_calls_buffers[1].arguments) == '{"tz": "EST"}'
def test_choicebuffer_append_tool_call_with_none_function():
"""Handle delta chunks where function is None."""
buf = ChoiceBuffer(0)
buf.append_tool_call(
ChoiceDeltaToolCall(
index=0,
id="call_1",
type="function",
function=ChoiceDeltaToolCallFunction(name="get_weather", arguments='{"city": "NYC"}'),
)
)
# Subsequent delta with function=None should not crash
buf.append_tool_call(
ChoiceDeltaToolCall(
index=0,
function=None,
)
)
result = "".join(buf.tool_calls_buffers[0].arguments)
assert result == '{"city": "NYC"}'
test_completion_hook.py 0000664 0000000 0000000 00000007064 15270700723 0041720 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-openai-v2/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
import os
from unittest.mock import MagicMock, patch
from opentelemetry.instrumentation._semconv import (
OTEL_SEMCONV_STABILITY_OPT_IN,
_OpenTelemetrySemanticConventionStability,
)
from opentelemetry.instrumentation.openai_v2 import OpenAIInstrumentor
from opentelemetry.util.genai.environment_variables import (
OTEL_INSTRUMENTATION_GENAI_CAPTURE_MESSAGE_CONTENT,
)
from .test_utils import DEFAULT_MODEL, USER_ONLY_PROMPT
@patch.dict(
os.environ,
{OTEL_SEMCONV_STABILITY_OPT_IN: "gen_ai_latest_experimental"},
)
def test_custom_hook_is_called(
span_exporter,
log_exporter,
tracer_provider,
logger_provider,
meter_provider,
openai_client,
vcr,
):
"""A hook passed to instrument() is called after each chat completion."""
hook = MagicMock()
instrumentor = OpenAIInstrumentor()
_OpenTelemetrySemanticConventionStability._initialized = False
instrumentor.instrument(
tracer_provider=tracer_provider,
logger_provider=logger_provider,
meter_provider=meter_provider,
completion_hook=hook,
)
try:
with vcr.use_cassette("test_chat_completion_with_content.yaml"):
openai_client.chat.completions.create(
messages=USER_ONLY_PROMPT,
model=DEFAULT_MODEL,
stream=False,
)
finally:
instrumentor.uninstrument()
hook.on_completion.assert_called_once()
kwargs = hook.on_completion.call_args.kwargs
assert kwargs["inputs"]
assert kwargs["outputs"]
assert kwargs["span"] is not None
# Content goes to the hook only — not to span attributes or log records
spans = span_exporter.get_finished_spans()
assert len(spans) == 1
span_attrs = spans[0].attributes or {}
assert "gen_ai.input.messages" not in span_attrs
assert "gen_ai.output.messages" not in span_attrs
assert log_exporter.get_finished_logs() == ()
@patch.dict(
os.environ,
{
OTEL_SEMCONV_STABILITY_OPT_IN: "gen_ai_latest_experimental",
OTEL_INSTRUMENTATION_GENAI_CAPTURE_MESSAGE_CONTENT: "span_only",
},
)
def test_default_hook_loaded_from_env(
span_exporter,
tracer_provider,
logger_provider,
meter_provider,
openai_client,
vcr,
):
"""When no hook kwarg is given, load_completion_hook() provides the default."""
default_hook = MagicMock()
instrumentor = OpenAIInstrumentor()
with patch(
"opentelemetry.instrumentation.openai_v2.load_completion_hook",
return_value=default_hook,
):
instrumentor.instrument(
tracer_provider=tracer_provider,
logger_provider=logger_provider,
meter_provider=meter_provider,
# no completion_hook kwarg — should fall back to load_completion_hook()
)
try:
with vcr.use_cassette("test_chat_completion_with_content.yaml"):
openai_client.chat.completions.create(
messages=USER_ONLY_PROMPT,
model=DEFAULT_MODEL,
stream=False,
)
finally:
instrumentor.uninstrument()
default_hook.on_completion.assert_called_once()
kwargs = default_hook.on_completion.call_args.kwargs
assert kwargs["inputs"]
assert kwargs["outputs"]
assert kwargs["span"] is not None
spans = span_exporter.get_finished_spans()
assert len(spans) == 1
span_attrs = spans[0].attributes or {}
assert "gen_ai.input.messages" in span_attrs
assert "gen_ai.output.messages" in span_attrs
test_embeddings.py 0000664 0000000 0000000 00000026122 15270700723 0040624 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-openai-v2/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
"""Unit tests for OpenAI Embeddings API instrumentation."""
import pytest
from openai import (
NOT_GIVEN,
APIConnectionError,
NotFoundError,
OpenAI,
)
try:
from openai import not_given # pylint: disable=no-name-in-module
except ImportError:
not_given = NOT_GIVEN
from opentelemetry.semconv._incubating.attributes import (
error_attributes as ErrorAttributes,
)
from opentelemetry.semconv._incubating.attributes import (
gen_ai_attributes as GenAIAttributes,
)
from opentelemetry.semconv._incubating.attributes import (
server_attributes as ServerAttributes,
)
from opentelemetry.semconv._incubating.metrics import gen_ai_metrics
from opentelemetry.util.genai.utils import is_experimental_mode
from .test_utils import (
DEFAULT_EMBEDDING_MODEL,
assert_all_attributes,
assert_embedding_attributes,
)
def test_embeddings_no_content(span_exporter, log_exporter, openai_client, instrument_no_content, vcr):
"""Test creating embeddings with content capture disabled"""
latest_experimental_enabled = is_experimental_mode()
input_text = "This is a test for embeddings"
with vcr.use_cassette("test_embeddings_no_content.yaml"):
response = openai_client.embeddings.create(
model=DEFAULT_EMBEDDING_MODEL,
input=input_text,
)
# Verify spans
spans = span_exporter.get_finished_spans()
assert len(spans) == 1
assert_embedding_attributes(
spans[0],
DEFAULT_EMBEDDING_MODEL,
latest_experimental_enabled,
response,
)
# No logs should be emitted when content capture is disabled
logs = log_exporter.get_finished_logs()
assert len(logs) == 0
def test_embeddings_with_dimensions(span_exporter, metric_reader, openai_client, instrument_no_content, vcr):
"""Test creating embeddings with custom dimensions parameter"""
latest_experimental_enabled = is_experimental_mode()
input_text = "This is a test for embeddings with dimensions"
dimensions = 512 # Using a smaller dimension than default
with vcr.use_cassette("test_embeddings_with_dimensions.yaml"):
response = openai_client.embeddings.create(
model=DEFAULT_EMBEDDING_MODEL,
input=input_text,
dimensions=dimensions,
)
# Verify spans
spans = span_exporter.get_finished_spans()
assert len(spans) == 1
assert_embedding_attributes(
spans[0],
DEFAULT_EMBEDDING_MODEL,
latest_experimental_enabled,
response,
)
# Verify dimensions attribute is set correctly
assert spans[0].attributes["gen_ai.embeddings.dimension.count"] == dimensions
# Verify actual embedding dimensions match the requested dimensions
assert len(response.data[0].embedding) == dimensions
# Verify metrics
metrics = metric_reader.get_metrics_data().resource_metrics
assert len(metrics) == 1
metric_data = metrics[0].scope_metrics[0].metrics
duration_metric = next(
(m for m in metric_data if m.name == gen_ai_metrics.GEN_AI_CLIENT_OPERATION_DURATION),
None,
)
assert duration_metric is not None
# Verify the dimensions attribute is present in metrics
for point in duration_metric.data.data_points:
if "gen_ai.embeddings.dimension.count" in point.attributes:
assert point.attributes["gen_ai.embeddings.dimension.count"] == dimensions
break
else:
assert False, "Dimensions attribute not found in metrics"
def test_embeddings_with_batch_input(span_exporter, metric_reader, openai_client, instrument_with_content, vcr):
"""Test creating embeddings with batch input (list of strings)"""
latest_experimental_enabled = is_experimental_mode()
input_texts = [
"This is the first test string for embeddings",
"This is the second test string for embeddings",
"This is the third test string for embeddings",
]
with vcr.use_cassette("test_embeddings_with_batch_input.yaml"):
response = openai_client.embeddings.create(
model=DEFAULT_EMBEDDING_MODEL,
input=input_texts,
)
# Verify spans
spans = span_exporter.get_finished_spans()
assert len(spans) == 1
assert_embedding_attributes(
spans[0],
DEFAULT_EMBEDDING_MODEL,
latest_experimental_enabled,
response,
)
# Verify results contain the same number of embeddings as input texts
assert len(response.data) == len(input_texts)
def test_embeddings_with_encoding_format(span_exporter, metric_reader, openai_client, instrument_no_content, vcr):
"""Test creating embeddings with different encoding format"""
latest_experimental_enabled = is_experimental_mode()
input_text = "This is a test for embeddings with encoding format"
encoding_format = "base64"
with vcr.use_cassette("test_embeddings_with_encoding_format.yaml"):
response = openai_client.embeddings.create(
model=DEFAULT_EMBEDDING_MODEL,
input=input_text,
encoding_format=encoding_format,
)
# Verify spans
spans = span_exporter.get_finished_spans()
assert len(spans) == 1
assert_embedding_attributes(
spans[0],
DEFAULT_EMBEDDING_MODEL,
latest_experimental_enabled,
response,
)
# Verify encoding_format attribute is set correctly
assert spans[0].attributes["gen_ai.request.encoding_formats"] == (encoding_format,)
@pytest.mark.parametrize("not_given_value", [NOT_GIVEN, not_given])
def test_embeddings_with_not_given_values(
span_exporter,
metric_reader,
openai_client,
instrument_no_content,
not_given_value,
vcr,
):
"""Test creating embeddings with NOT_GIVEN and not_given values"""
latest_experimental_enabled = is_experimental_mode()
input_text = "This is a test for embeddings with encoding format"
with vcr.use_cassette("test_embeddings_with_not_given_values.yaml"):
response = openai_client.embeddings.create(
model=DEFAULT_EMBEDDING_MODEL,
input=input_text,
dimensions=not_given_value,
)
# Verify spans
spans = span_exporter.get_finished_spans()
assert len(spans) == 1
assert_embedding_attributes(
spans[0],
DEFAULT_EMBEDDING_MODEL,
latest_experimental_enabled,
response,
)
assert "gen_ai.request.dimensions" not in spans[0].attributes
def test_embeddings_bad_endpoint(span_exporter, metric_reader, instrument_no_content, vcr):
"""Test error handling for bad endpoint"""
latest_experimental_enabled = is_experimental_mode()
input_text = "This is a test for embeddings with bad endpoint"
client = OpenAI(base_url="http://localhost:4242")
with vcr.use_cassette("test_embeddings_bad_endpoint.yaml"):
with pytest.raises(APIConnectionError):
client.embeddings.create(
model=DEFAULT_EMBEDDING_MODEL,
input=input_text,
timeout=0.1,
)
# Verify spans
spans = span_exporter.get_finished_spans()
assert len(spans) == 1
assert_all_attributes(
spans[0],
DEFAULT_EMBEDDING_MODEL,
latest_experimental_enabled,
operation_name="embeddings",
server_address="localhost",
)
assert 4242 == spans[0].attributes[ServerAttributes.SERVER_PORT]
assert "APIConnectionError" == spans[0].attributes[ErrorAttributes.ERROR_TYPE]
# Verify metrics
metrics = metric_reader.get_metrics_data().resource_metrics
assert len(metrics) == 1
metric_data = metrics[0].scope_metrics[0].metrics
duration_metric = next(
(m for m in metric_data if m.name == gen_ai_metrics.GEN_AI_CLIENT_OPERATION_DURATION),
None,
)
assert duration_metric is not None
assert duration_metric.data.data_points[0].sum > 0
assert duration_metric.data.data_points[0].attributes[ErrorAttributes.ERROR_TYPE] == "APIConnectionError"
def test_embeddings_model_not_found(span_exporter, metric_reader, openai_client, instrument_no_content, vcr):
"""Test error handling for non-existent model"""
latest_experimental_enabled = is_experimental_mode()
model_name = "non-existent-embedding-model"
input_text = "This is a test for embeddings with bad model"
with vcr.use_cassette("test_embeddings_model_not_found.yaml"):
with pytest.raises(NotFoundError):
openai_client.embeddings.create(
model=model_name,
input=input_text,
)
# Verify spans
spans = span_exporter.get_finished_spans()
assert len(spans) == 1
assert_all_attributes(
spans[0],
model_name,
latest_experimental_enabled,
operation_name="embeddings",
)
assert "NotFoundError" == spans[0].attributes[ErrorAttributes.ERROR_TYPE]
# Verify metrics
metrics = metric_reader.get_metrics_data().resource_metrics
assert len(metrics) == 1
metric_data = metrics[0].scope_metrics[0].metrics
duration_metric = next(
(m for m in metric_data if m.name == gen_ai_metrics.GEN_AI_CLIENT_OPERATION_DURATION),
None,
)
assert duration_metric is not None
assert duration_metric.data.data_points[0].sum > 0
assert duration_metric.data.data_points[0].attributes[ErrorAttributes.ERROR_TYPE] == "NotFoundError"
def test_embeddings_token_metrics(span_exporter, metric_reader, openai_client, instrument_no_content, vcr):
"""Test that token usage metrics are correctly recorded"""
latest_experimental_enabled = is_experimental_mode()
input_text = "This is a test for embeddings token metrics"
with vcr.use_cassette("test_embeddings_token_metrics.yaml"):
response = openai_client.embeddings.create(
model=DEFAULT_EMBEDDING_MODEL,
input=input_text,
)
# Verify spans
spans = span_exporter.get_finished_spans()
assert len(spans) == 1
assert_embedding_attributes(
spans[0],
DEFAULT_EMBEDDING_MODEL,
latest_experimental_enabled,
response,
)
# Verify metrics
metrics = metric_reader.get_metrics_data().resource_metrics
assert len(metrics) == 1
metric_data = metrics[0].scope_metrics[0].metrics
# Verify operation duration metric
duration_metric = next(
(m for m in metric_data if m.name == gen_ai_metrics.GEN_AI_CLIENT_OPERATION_DURATION),
None,
)
assert duration_metric is not None
# Verify token usage metric
token_metric = next(
(m for m in metric_data if m.name == gen_ai_metrics.GEN_AI_CLIENT_TOKEN_USAGE),
None,
)
assert token_metric is not None
# Find the input token data point
input_token_point = None
for point in token_metric.data.data_points:
if point.attributes[GenAIAttributes.GEN_AI_TOKEN_TYPE] == GenAIAttributes.GenAiTokenTypeValues.INPUT.value:
input_token_point = point
break
assert input_token_point is not None, "Input token metric not found"
# Verify the token counts match what was reported in the response
assert input_token_point.sum == response.usage.prompt_tokens
test_request_attributes.py 0000664 0000000 0000000 00000006573 15270700723 0042471 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-openai-v2/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
"""Unit tests for get_llm_request_attributes and span name logic in utils.py."""
from types import SimpleNamespace
import pytest
from opentelemetry.instrumentation.openai_v2.patch import (
_get_embeddings_span_name,
)
from opentelemetry.instrumentation.openai_v2.utils import (
get_llm_request_attributes,
)
from opentelemetry.semconv._incubating.attributes import (
gen_ai_attributes as GenAIAttributes,
)
@pytest.fixture(autouse=True)
def fixture_vcr():
"""No VCR needed for these unit tests."""
yield
def _make_client(base_url=None):
return SimpleNamespace(_base_url=base_url)
def test_model_omitted_when_missing():
"""When 'model' is not in kwargs, GEN_AI_REQUEST_MODEL should be absent."""
attrs = get_llm_request_attributes(
kwargs={},
client_instance=_make_client(),
latest_experimental_enabled=False,
)
assert GenAIAttributes.GEN_AI_REQUEST_MODEL not in attrs
def test_model_omitted_when_missing_experimental():
"""Same as above but with latest_experimental_enabled=True."""
attrs = get_llm_request_attributes(
kwargs={},
client_instance=_make_client(),
latest_experimental_enabled=True,
)
assert GenAIAttributes.GEN_AI_REQUEST_MODEL not in attrs
def test_model_preserved_when_provided():
"""When 'model' is in kwargs, GEN_AI_REQUEST_MODEL should be set to its value."""
attrs = get_llm_request_attributes(
kwargs={"model": "gpt-4o-mini"},
client_instance=_make_client(),
latest_experimental_enabled=False,
)
assert attrs[GenAIAttributes.GEN_AI_REQUEST_MODEL] == "gpt-4o-mini"
def test_span_name_includes_model_when_present():
"""Span name should be '{operation} {model}' when model is provided."""
attrs = get_llm_request_attributes(
kwargs={"model": "gpt-4o"},
client_instance=_make_client(),
latest_experimental_enabled=False,
)
operation_name = attrs[GenAIAttributes.GEN_AI_OPERATION_NAME]
model = attrs.get(GenAIAttributes.GEN_AI_REQUEST_MODEL)
span_name = f"{operation_name} {model}" if model else operation_name
assert span_name == "chat gpt-4o"
def test_span_name_uses_operation_only_when_model_missing():
"""Span name should be just '{operation}' when model is not provided."""
attrs = get_llm_request_attributes(
kwargs={},
client_instance=_make_client(),
latest_experimental_enabled=False,
)
operation_name = attrs[GenAIAttributes.GEN_AI_OPERATION_NAME]
model = attrs.get(GenAIAttributes.GEN_AI_REQUEST_MODEL)
span_name = f"{operation_name} {model}" if model else operation_name
assert span_name == "chat"
def test_embeddings_span_name_includes_model():
"""Embeddings span name should be '{operation} {model}' when model is present."""
span_attributes = {
GenAIAttributes.GEN_AI_OPERATION_NAME: "embeddings",
GenAIAttributes.GEN_AI_REQUEST_MODEL: "text-embedding-3-small",
}
assert _get_embeddings_span_name(span_attributes) == "embeddings text-embedding-3-small"
def test_embeddings_span_name_without_model():
"""Embeddings span name should be just '{operation}' when model is absent."""
span_attributes = {
GenAIAttributes.GEN_AI_OPERATION_NAME: "embeddings",
}
assert _get_embeddings_span_name(span_attributes) == "embeddings"
test_response_extractors.py 0000664 0000000 0000000 00000025252 15270700723 0042642 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-openai-v2/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
from types import SimpleNamespace
from unittest import mock
import pytest
from opentelemetry.instrumentation.openai_v2 import response_extractors
from opentelemetry.semconv._incubating.attributes import (
openai_attributes as OpenAIAttributes,
)
from opentelemetry.util.genai.types import LLMInvocation
try:
# Responses types are not available in the oldest supported OpenAI SDK.
# pylint: disable-next=no-name-in-module
from openai.types.responses.response import Response
HAS_RESPONSES_TYPES = True
except ImportError:
Response = None
HAS_RESPONSES_TYPES = False
pytestmark = pytest.mark.skipif(
not HAS_RESPONSES_TYPES,
reason="Responses SDK types require a newer openai SDK",
)
@pytest.fixture(scope="module", name="loaded_module")
def _loaded_module_fixture():
return response_extractors
def _make_response(output=None, **overrides):
payload = {
"id": "resp_123",
"created_at": 0.0,
"model": "gpt-4.1",
"object": "response",
"output": output or [],
"parallel_tool_calls": False,
"tool_choice": "auto",
"tools": [],
"temperature": 1.0,
"top_p": 1.0,
"usage": {
"input_tokens": 11,
"input_tokens_details": {"cached_tokens": 0},
"output_tokens": 7,
"output_tokens_details": {"reasoning_tokens": 0},
"total_tokens": 18,
},
}
payload.update(overrides)
return Response.model_validate(payload)
def test_extract_system_instruction_returns_text_for_string(loaded_module):
params = loaded_module.extract_params(instructions="Be concise")
instructions = loaded_module.get_system_instruction(params.instructions)
assert [part.content for part in instructions] == ["Be concise"]
def test_extract_input_messages_supports_string_and_mixed_message_content(
loaded_module,
):
from_string = loaded_module.get_input_messages("Hello")
from_list = loaded_module.get_input_messages(
[
{"role": "user", "content": "First"},
SimpleNamespace(
role="assistant",
content=[
{"text": "Second"},
SimpleNamespace(text="Third"),
{"type": "input_image", "image_url": "ignored"},
],
),
{"role": None, "content": "ignored"},
]
)
assert [(msg.role, [part.content for part in msg.parts]) for msg in from_string] == [("user", ["Hello"])]
assert [(msg.role, [part.content for part in msg.parts]) for msg in from_list] == [
("user", ["First"]),
("assistant", ["Second", "Third"]),
]
def test_extract_output_messages_maps_parts_and_finish_reasons(loaded_module):
response = _make_response(
output=[
{
"id": "msg_1",
"type": "message",
"role": "assistant",
"status": "completed",
"content": [
{"type": "output_text", "text": "Done", "annotations": []},
{"type": "refusal", "refusal": "Cannot comply"},
],
},
{
"id": "msg_2",
"type": "message",
"role": "assistant",
"status": "incomplete",
"content": [
{
"type": "output_text",
"text": "Partial",
"annotations": [],
}
],
},
{
"id": "msg_3",
"type": "message",
"role": "assistant",
"status": "in_progress",
"content": [
{
"type": "output_text",
"text": "Pending",
"annotations": [],
}
],
},
{
"id": "fc_1",
"type": "function_call",
"status": "completed",
"name": "get_weather",
"call_id": "call_123",
"arguments": '{"city":"SF"}',
},
{
"id": "rs_1",
"type": "reasoning",
"status": "completed",
"summary": [{"type": "summary_text", "text": "Thought step"}],
"content": None,
},
]
)
messages = loaded_module.get_output_messages_from_response(response)
assert [(msg.role, msg.finish_reason) for msg in messages] == [
("assistant", "stop"),
("assistant", "incomplete"),
("assistant", "tool_calls"),
("assistant", "stop"),
]
assert [part.content for part in messages[0].parts] == [
"Done",
"Cannot comply",
]
assert [part.content for part in messages[1].parts] == ["Partial"]
assert messages[2].parts[0].type == "tool_call"
assert messages[2].parts[0].name == "get_weather"
assert messages[2].parts[0].arguments == {"city": "SF"}
assert messages[3].parts[0].type == "reasoning"
assert messages[3].parts[0].content == "Thought step"
def test_extract_finish_reasons_maps_terminal_message_and_tool_items(
loaded_module,
):
response = _make_response(
output=[
{
"id": "msg_1",
"type": "message",
"role": "assistant",
"status": "completed",
"content": [],
},
{
"id": "msg_2",
"type": "message",
"role": "assistant",
"status": "in_progress",
"content": [],
},
{
"id": "fc_1",
"type": "function_call",
"status": "incomplete",
"name": "tool",
"call_id": "call_1",
"arguments": "{}",
},
]
)
assert loaded_module.extract_finish_reasons(response) == [
"stop",
"tool_calls",
]
def test_extract_output_type_handles_text_format_mapping(loaded_module):
assert loaded_module.extract_params(text={"format": {"type": "json_schema"}}).output_type == "json"
assert loaded_module.extract_params(text={"format": {"type": "text"}}).output_type == "text"
assert (
loaded_module.extract_params(text=SimpleNamespace(format=SimpleNamespace(type="json_schema"))).output_type
== "json"
)
assert loaded_module.extract_params(text=SimpleNamespace(format=SimpleNamespace(type="text"))).output_type == "text"
assert loaded_module.extract_params(text={"format": "plain"}).output_type is None
assert loaded_module.extract_params(text="plain").output_type is None
def test_extractors_handle_missing_genai_types_import(loaded_module):
with (
mock.patch.object(loaded_module, "Text", None),
mock.patch.object(loaded_module, "InputMessage", None),
mock.patch.object(loaded_module, "OutputMessage", None),
):
assert loaded_module.get_system_instruction("hi") == []
assert loaded_module.get_input_messages("hi") == []
assert (
loaded_module.get_output_messages_from_response(
_make_response(
output=[
{
"id": "msg_1",
"type": "message",
"role": "assistant",
"status": "completed",
"content": [],
}
]
)
)
== []
)
def test_set_invocation_response_attributes_populates_usage_and_metadata(
loaded_module,
):
invocation = LLMInvocation(request_model="gpt-4o-mini")
result = _make_response(
service_tier="scale",
usage={
"input_tokens": 11,
"input_tokens_details": {
"cached_tokens": 3,
"cache_creation_input_tokens": 5,
},
"output_tokens": 7,
"output_tokens_details": {"reasoning_tokens": 0},
"total_tokens": 18,
},
)
loaded_module.set_invocation_response_attributes(invocation, result, capture_content=False)
assert invocation.response_model_name == "gpt-4.1"
assert invocation.response_id == "resp_123"
assert invocation.input_tokens == 11
assert invocation.output_tokens == 7
assert invocation.cache_read_input_tokens == 3
assert invocation.cache_creation_input_tokens == 5
assert invocation.attributes == {
OpenAIAttributes.OPENAI_RESPONSE_SERVICE_TIER: "scale",
}
def test_set_invocation_response_attributes_populates_output_messages(
loaded_module,
):
invocation = LLMInvocation(request_model="gpt-4o-mini")
result = _make_response(
output=[
{
"id": "msg_1",
"type": "message",
"role": "assistant",
"status": "completed",
"content": [{"type": "output_text", "text": "Done", "annotations": []}],
}
]
)
loaded_module.set_invocation_response_attributes(invocation, result, capture_content=True)
assert invocation.finish_reasons == ["stop"]
assert [(message.role, message.finish_reason) for message in invocation.output_messages] == [("assistant", "stop")]
assert [[part.content for part in message.parts] for message in invocation.output_messages] == [["Done"]]
def test_extractors_ignore_invalid_request_shapes_without_validation(
loaded_module,
):
params = loaded_module.extract_params(instructions=["not-a-string"], input=42, text={"format": {"type": 42}})
assert loaded_module.get_system_instruction(params.instructions) == []
assert loaded_module.get_input_messages(params.input) == []
assert params.output_type is None
def test_response_extractors_ignore_invalid_shapes_without_validation(
loaded_module,
):
invocation = LLMInvocation(request_model="gpt-4o-mini")
invalid_result = SimpleNamespace(output=42, usage=42)
assert loaded_module.get_output_messages_from_response(invalid_result) == []
assert loaded_module.extract_finish_reasons(invalid_result) == []
loaded_module.set_invocation_response_attributes(invocation, invalid_result, capture_content=True)
assert invocation.response_model_name is None
assert invocation.response_id is None
assert invocation.input_tokens is None
assert invocation.output_tokens is None
assert invocation.finish_reasons is None
assert not invocation.output_messages
assert not invocation.attributes
test_response_wrappers.py 0000664 0000000 0000000 00000030513 15270700723 0042303 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-openai-v2/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
from types import SimpleNamespace
import pytest
from opentelemetry.instrumentation.openai_v2.response_wrappers import (
AsyncResponseStreamManagerWrapper,
AsyncResponseStreamWrapper,
ResponseStreamManagerWrapper,
ResponseStreamWrapper,
)
class _FakeManager:
def __init__(self, stream, suppressed=False, exit_error=None):
self._stream = stream
self._suppressed = suppressed
self._exit_error = exit_error
self.exit_args = None
def __enter__(self):
return self._stream
def __exit__(self, exc_type, exc_val, exc_tb):
self.exit_args = (exc_type, exc_val, exc_tb)
if self._exit_error is not None:
raise self._exit_error
return self._suppressed
class _FakeAsyncManager:
def __init__(self, stream, suppressed=False, exit_error=None):
self._stream = stream
self._suppressed = suppressed
self._exit_error = exit_error
self.exit_args = None
async def __aenter__(self):
return self._stream
async def __aexit__(self, exc_type, exc_val, exc_tb):
self.exit_args = (exc_type, exc_val, exc_tb)
if self._exit_error is not None:
raise self._exit_error
return self._suppressed
def _noop_stop():
return None
def _noop_fail(error):
del error
def _make_wrapper(manager):
invocation = SimpleNamespace(
request_model=None,
stop=_noop_stop,
fail=_noop_fail,
)
return ResponseStreamManagerWrapper(
manager=manager,
invocation=invocation,
capture_content=False,
)
def _make_stream_wrapper(stream, invocation=None):
if invocation is None:
invocation = SimpleNamespace(
request_model=None,
stop=_noop_stop,
fail=_noop_fail,
)
return ResponseStreamWrapper(
stream=stream,
invocation=invocation,
capture_content=False,
)
def _make_async_manager_wrapper(manager):
invocation = SimpleNamespace(
request_model=None,
stop=_noop_stop,
fail=_noop_fail,
)
return AsyncResponseStreamManagerWrapper(
manager=manager,
invocation=invocation,
capture_content=False,
)
def _make_async_stream_wrapper(stream, invocation=None):
if invocation is None:
invocation = SimpleNamespace(
request_model=None,
stop=_noop_stop,
fail=_noop_fail,
)
return AsyncResponseStreamWrapper(
stream=stream,
invocation=invocation,
capture_content=False,
)
class _FakeStreamWrapper:
def __init__(self):
self.exit_args = None
def __exit__(self, exc_type, exc_val, exc_tb):
self.exit_args = (exc_type, exc_val, exc_tb)
return False
class _FakeAsyncStreamWrapper:
def __init__(self):
self.exit_args = None
async def __aexit__(self, exc_type, exc_val, exc_tb):
self.exit_args = (exc_type, exc_val, exc_tb)
return False
class _FakeAsyncResponse:
def __init__(self):
self.aclose_calls = 0
async def aclose(self):
self.aclose_calls += 1
class _FakeSyncResponse:
def __init__(self):
self.close_calls = 0
def close(self):
self.close_calls += 1
class _FakeAsyncStream:
def __init__(
self,
*,
events=None,
error=None,
final_response=None,
response=None,
):
self._events = list(events or [])
self._error = error
self._final_response = final_response
self._response = response
self.close_calls = 0
self.get_final_response_calls = 0
async def __anext__(self):
if self._events:
return self._events.pop(0)
if self._error is not None:
raise self._error
raise StopAsyncIteration
async def close(self):
self.close_calls += 1
async def get_final_response(self):
self.get_final_response_calls += 1
return self._final_response
def test_manager_exit_forwards_exception_to_stream_wrapper():
manager = _FakeManager(stream=SimpleNamespace(), suppressed=False)
wrapper = _make_wrapper(manager)
stream_wrapper = _FakeStreamWrapper()
wrapper._stream_wrapper = stream_wrapper
error = ValueError("boom")
result = wrapper.__exit__(ValueError, error, None)
assert result is False
assert manager.exit_args == (ValueError, error, None)
assert stream_wrapper.exit_args == (ValueError, error, None)
assert wrapper._stream_wrapper is None
def test_manager_exit_uses_none_exception_when_manager_suppresses():
manager = _FakeManager(stream=SimpleNamespace(), suppressed=True)
wrapper = _make_wrapper(manager)
stream_wrapper = _FakeStreamWrapper()
wrapper._stream_wrapper = stream_wrapper
error = RuntimeError("ignored")
result = wrapper.__exit__(RuntimeError, error, None)
assert result is True
assert manager.exit_args == (RuntimeError, error, None)
assert stream_wrapper.exit_args == (None, None, None)
assert wrapper._stream_wrapper is None
def test_manager_exit_still_finalizes_stream_wrapper_when_manager_raises():
manager_error = RuntimeError("manager failure")
manager = _FakeManager(stream=SimpleNamespace(), suppressed=False, exit_error=manager_error)
wrapper = _make_wrapper(manager)
stream_wrapper = _FakeStreamWrapper()
wrapper._stream_wrapper = stream_wrapper
error = ValueError("outer")
with pytest.raises(RuntimeError, match="manager failure"):
wrapper.__exit__(ValueError, error, None)
assert manager.exit_args == (ValueError, error, None)
assert stream_wrapper.exit_args == (ValueError, error, None)
assert wrapper._stream_wrapper is None
def test_stream_wrapper_response_falls_back_to_public_response_attr():
response = _FakeSyncResponse()
stream = SimpleNamespace(response=response)
wrapper = _make_stream_wrapper(stream)
stopped = []
wrapper._stop = stopped.append
wrapper.response.close()
assert response.close_calls == 1
assert stopped == [None]
@pytest.mark.asyncio
async def test_async_manager_exit_forwards_exception_to_stream_wrapper():
manager = _FakeAsyncManager(stream=SimpleNamespace(), suppressed=False)
wrapper = _make_async_manager_wrapper(manager)
stream_wrapper = _FakeAsyncStreamWrapper()
wrapper._stream_wrapper = stream_wrapper
error = ValueError("boom")
result = await wrapper.__aexit__(ValueError, error, None)
assert result is False
assert manager.exit_args == (ValueError, error, None)
assert stream_wrapper.exit_args == (ValueError, error, None)
assert wrapper._stream_wrapper is None
@pytest.mark.asyncio
async def test_async_manager_enter_constructs_async_stream_wrapper():
stream = _FakeAsyncStream()
manager = _FakeAsyncManager(stream=stream)
wrapper = _make_async_manager_wrapper(manager)
async with wrapper as result:
assert isinstance(result, AsyncResponseStreamWrapper)
assert result.stream is stream
assert wrapper._stream_wrapper is result
@pytest.mark.asyncio
async def test_async_manager_exit_uses_none_exception_when_manager_suppresses():
manager = _FakeAsyncManager(stream=SimpleNamespace(), suppressed=True)
wrapper = _make_async_manager_wrapper(manager)
stream_wrapper = _FakeAsyncStreamWrapper()
wrapper._stream_wrapper = stream_wrapper
error = RuntimeError("ignored")
result = await wrapper.__aexit__(RuntimeError, error, None)
assert result is True
assert manager.exit_args == (RuntimeError, error, None)
assert stream_wrapper.exit_args == (None, None, None)
assert wrapper._stream_wrapper is None
@pytest.mark.asyncio
async def test_async_manager_exit_still_finalizes_stream_wrapper_when_manager_raises():
manager_error = RuntimeError("manager failure")
manager = _FakeAsyncManager(stream=SimpleNamespace(), suppressed=False, exit_error=manager_error)
wrapper = _make_async_manager_wrapper(manager)
stream_wrapper = _FakeAsyncStreamWrapper()
wrapper._stream_wrapper = stream_wrapper
error = ValueError("outer")
with pytest.raises(RuntimeError, match="manager failure"):
await wrapper.__aexit__(ValueError, error, None)
assert manager.exit_args == (ValueError, error, None)
assert stream_wrapper.exit_args == (ValueError, error, None)
assert wrapper._stream_wrapper is None
@pytest.mark.asyncio
async def test_async_stream_wrapper_exit_closes_without_exception():
stream = _FakeAsyncStream()
wrapper = _make_async_stream_wrapper(stream)
stopped = []
wrapper._stop = stopped.append
result = await wrapper.__aexit__(None, None, None)
assert result is False
assert stream.close_calls == 1
assert stopped == [None]
@pytest.mark.asyncio
async def test_async_stream_wrapper_exit_fails_and_closes_on_exception():
stream = _FakeAsyncStream()
wrapper = _make_async_stream_wrapper(stream)
stopped = []
failures = []
def record_failure(message, error_type):
failures.append((message, error_type))
wrapper._stop = stopped.append
wrapper._fail = record_failure
error = ValueError("boom")
result = await wrapper.__aexit__(ValueError, error, None)
assert result is False
assert stream.close_calls == 1
assert stopped == [None]
assert failures == [("boom", ValueError)]
@pytest.mark.asyncio
async def test_async_stream_wrapper_close_closes_stream_and_stops():
stream = _FakeAsyncStream()
wrapper = _make_async_stream_wrapper(stream)
stopped = []
wrapper._stop = stopped.append
await wrapper.close()
assert stream.close_calls == 1
assert stopped == [None]
@pytest.mark.asyncio
async def test_async_stream_wrapper_processes_events_and_stops_on_completion():
event = SimpleNamespace(type="response.created")
stream = _FakeAsyncStream(events=[event])
wrapper = _make_async_stream_wrapper(stream)
processed = []
stopped = []
wrapper.process_event = processed.append
wrapper._stop = stopped.append
result = await anext(wrapper)
assert result is event
assert processed == [event]
with pytest.raises(StopAsyncIteration):
await anext(wrapper)
assert stopped == [None]
@pytest.mark.asyncio
async def test_async_stream_wrapper_until_done_consumes_stream():
events = [
SimpleNamespace(type="response.created"),
SimpleNamespace(type="response.in_progress"),
]
stream = _FakeAsyncStream(events=events)
wrapper = _make_async_stream_wrapper(stream)
processed = []
stopped = []
wrapper.process_event = processed.append
wrapper._stop = stopped.append
result = await wrapper.until_done()
assert result is wrapper
assert processed == events
assert stopped == [None]
@pytest.mark.asyncio
async def test_async_stream_wrapper_fails_and_reraises_stream_errors():
error = ValueError("boom")
stream = _FakeAsyncStream(error=error)
wrapper = _make_async_stream_wrapper(stream)
failures = []
def record_failure(message, error_type):
failures.append((message, error_type))
wrapper._fail = record_failure
with pytest.raises(ValueError, match="boom"):
await anext(wrapper)
assert failures == [("boom", ValueError)]
@pytest.mark.asyncio
async def test_async_stream_response_aclose_finalizes_wrapper():
response = _FakeAsyncResponse()
stream = _FakeAsyncStream(response=response)
wrapper = _make_async_stream_wrapper(stream)
stopped = []
wrapper._stop = stopped.append
await wrapper.response.aclose()
assert response.aclose_calls == 1
assert stopped == [None]
@pytest.mark.asyncio
async def test_async_stream_response_is_none_when_stream_has_no_response():
wrapper = _make_async_stream_wrapper(SimpleNamespace())
assert wrapper.response is None
@pytest.mark.asyncio
async def test_async_stream_get_final_response_waits_for_completion():
event = SimpleNamespace(type="response.in_progress")
final_response = SimpleNamespace(id="response_123")
stream = _FakeAsyncStream(events=[event], final_response=final_response)
wrapper = _make_async_stream_wrapper(stream)
wrapper.process_event = lambda current: current
result = await wrapper.get_final_response()
assert result is final_response
assert stream.get_final_response_calls == 1
test_responses.py 0000664 0000000 0000000 00000055140 15270700723 0040546 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-openai-v2/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
import inspect
import json
import pytest
from openai import APIConnectionError, BadRequestError, NotFoundError, OpenAI
from opentelemetry.instrumentation.openai_v2 import OpenAIInstrumentor
from opentelemetry.instrumentation.openai_v2.response_wrappers import (
ResponseStreamWrapper,
)
from opentelemetry.semconv._incubating.attributes import (
error_attributes as ErrorAttributes,
)
from opentelemetry.semconv._incubating.attributes import (
gen_ai_attributes as GenAIAttributes,
)
from opentelemetry.semconv._incubating.attributes import (
server_attributes as ServerAttributes,
)
from opentelemetry.util.genai.utils import is_experimental_mode
from .test_utils import (
DEFAULT_MODEL,
USER_ONLY_EXPECTED_INPUT_MESSAGES,
USER_ONLY_PROMPT,
assert_all_attributes,
assert_cache_attributes,
assert_messages_attribute,
format_simple_expected_output_message,
get_responses_weather_tool_definition,
)
try:
# Responses is not available in the oldest supported OpenAI SDK, so keep
# this import guarded. Pylint runs against the oldest dependency set and
# cannot resolve this optional module there.
# pylint: disable-next=no-name-in-module
from openai.resources.responses.responses import Responses as _Responses
HAS_RESPONSES_API = True
_create_params = set(inspect.signature(_Responses.create).parameters)
_has_tools_param = "tools" in _create_params
_has_reasoning_param = "reasoning" in _create_params
except ImportError:
HAS_RESPONSES_API = False
_has_tools_param = False
_has_reasoning_param = False
pytestmark = pytest.mark.skipif(not HAS_RESPONSES_API, reason="Responses API requires a newer openai SDK")
SYSTEM_INSTRUCTIONS = "You are a helpful assistant."
EXPECTED_SYSTEM_INSTRUCTIONS = [
{
"type": "text",
"content": SYSTEM_INSTRUCTIONS,
}
]
INVALID_MODEL = "this-model-does-not-exist"
REASONING_MODEL = "gpt-5.4"
REASONING_PROMPT = """
Write a bash script that takes a matrix represented as a string with
format '[1,2],[3,4],[5,6]' and prints the transpose in the same format.
"""
def _skip_if_not_latest():
if not is_experimental_mode():
pytest.skip("Responses create instrumentation only supports the latest experimental semconv path")
def _load_span_messages(span, attribute):
value = span.attributes.get(attribute)
assert value is not None
return json.loads(value)
def _assert_response_content(span, response, log_exporter):
assert_messages_attribute(
span.attributes[GenAIAttributes.GEN_AI_INPUT_MESSAGES],
USER_ONLY_EXPECTED_INPUT_MESSAGES,
)
assert json.loads(span.attributes[GenAIAttributes.GEN_AI_SYSTEM_INSTRUCTIONS]) == EXPECTED_SYSTEM_INSTRUCTIONS
assert_messages_attribute(
span.attributes[GenAIAttributes.GEN_AI_OUTPUT_MESSAGES],
format_simple_expected_output_message(response.output_text),
)
assert len(log_exporter.get_finished_logs()) == 0
def _assert_request_attrs(
span,
*,
temperature=None,
top_p=None,
max_tokens=None,
output_type=None,
):
if temperature is not None:
assert span.attributes[GenAIAttributes.GEN_AI_REQUEST_TEMPERATURE] == temperature
if top_p is not None:
assert span.attributes[GenAIAttributes.GEN_AI_REQUEST_TOP_P] == top_p
if max_tokens is not None:
assert span.attributes[GenAIAttributes.GEN_AI_REQUEST_MAX_TOKENS] == max_tokens
if output_type is not None:
assert span.attributes[GenAIAttributes.GEN_AI_OUTPUT_TYPE] == output_type
def _collect_completed_response(stream):
response = None
for event in stream:
if event.type == "response.completed":
response = event.response
assert response is not None
return response
def test_responses_uninstrument_removes_patching(span_exporter, tracer_provider, logger_provider, meter_provider):
instrumentor = OpenAIInstrumentor()
instrumentor.instrument(
tracer_provider=tracer_provider,
logger_provider=logger_provider,
meter_provider=meter_provider,
)
instrumentor.uninstrument()
assert len(span_exporter.get_finished_spans()) == 0
def test_responses_multiple_instrument_uninstrument_cycles(tracer_provider, logger_provider, meter_provider):
instrumentor = OpenAIInstrumentor()
instrumentor.instrument(
tracer_provider=tracer_provider,
logger_provider=logger_provider,
meter_provider=meter_provider,
)
instrumentor.uninstrument()
instrumentor.instrument(
tracer_provider=tracer_provider,
logger_provider=logger_provider,
meter_provider=meter_provider,
)
instrumentor.uninstrument()
instrumentor.instrument(
tracer_provider=tracer_provider,
logger_provider=logger_provider,
meter_provider=meter_provider,
)
instrumentor.uninstrument()
@pytest.mark.vcr()
def test_responses_create_basic(request, span_exporter, openai_client, instrument_no_content):
_skip_if_not_latest()
response = openai_client.responses.create(
model=DEFAULT_MODEL,
instructions=SYSTEM_INSTRUCTIONS,
input=USER_ONLY_PROMPT[0]["content"],
stream=False,
)
(span,) = span_exporter.get_finished_spans()
assert_all_attributes(
span,
DEFAULT_MODEL,
True,
response.id,
response.model,
response.usage.input_tokens,
response.usage.output_tokens,
response_service_tier=getattr(response, "service_tier", None),
)
assert span.attributes[GenAIAttributes.GEN_AI_RESPONSE_FINISH_REASONS] == ("stop",)
assert GenAIAttributes.GEN_AI_INPUT_MESSAGES not in span.attributes
assert GenAIAttributes.GEN_AI_OUTPUT_MESSAGES not in span.attributes
@pytest.mark.vcr()
def test_responses_create_captures_content(
request,
span_exporter,
log_exporter,
openai_client,
instrument_with_content,
):
_skip_if_not_latest()
response = openai_client.responses.create(
model=DEFAULT_MODEL,
instructions=SYSTEM_INSTRUCTIONS,
input=USER_ONLY_PROMPT[0]["content"],
stream=False,
text={"format": {"type": "text"}},
)
(span,) = span_exporter.get_finished_spans()
assert_all_attributes(
span,
DEFAULT_MODEL,
True,
response.id,
response.model,
response.usage.input_tokens,
response.usage.output_tokens,
response_service_tier=getattr(response, "service_tier", None),
)
_assert_response_content(span, response, log_exporter)
@pytest.mark.vcr()
def test_responses_create_with_all_params(request, span_exporter, openai_client, instrument_no_content):
_skip_if_not_latest()
response = openai_client.responses.create(
model=DEFAULT_MODEL,
instructions=SYSTEM_INSTRUCTIONS,
input=USER_ONLY_PROMPT[0]["content"],
max_output_tokens=50,
temperature=0.7,
top_p=0.9,
service_tier="default",
text={"format": {"type": "text"}},
)
(span,) = span_exporter.get_finished_spans()
assert_all_attributes(
span,
DEFAULT_MODEL,
True,
response.id,
response.model,
response.usage.input_tokens,
response.usage.output_tokens,
request_service_tier="default",
response_service_tier=getattr(response, "service_tier", None),
)
_assert_request_attrs(
span,
temperature=0.7,
top_p=0.9,
max_tokens=50,
output_type="text",
)
@pytest.mark.vcr()
def test_responses_create_token_usage(request, span_exporter, openai_client, instrument_no_content):
_skip_if_not_latest()
response = openai_client.responses.create(
model=DEFAULT_MODEL,
instructions=SYSTEM_INSTRUCTIONS,
input="Count to 5.",
)
(span,) = span_exporter.get_finished_spans()
assert span.attributes[GenAIAttributes.GEN_AI_USAGE_INPUT_TOKENS] == response.usage.input_tokens
assert span.attributes[GenAIAttributes.GEN_AI_USAGE_OUTPUT_TOKENS] == response.usage.output_tokens
@pytest.mark.vcr()
def test_responses_create_aggregates_cache_tokens(request, span_exporter, openai_client, instrument_no_content):
_skip_if_not_latest()
response = openai_client.responses.create(
model=DEFAULT_MODEL,
instructions=SYSTEM_INSTRUCTIONS,
input=USER_ONLY_PROMPT[0]["content"],
)
(span,) = span_exporter.get_finished_spans()
assert_cache_attributes(span, response.usage)
@pytest.mark.vcr()
def test_responses_create_stop_reason(request, span_exporter, openai_client, instrument_no_content):
_skip_if_not_latest()
openai_client.responses.create(
model=DEFAULT_MODEL,
instructions=SYSTEM_INSTRUCTIONS,
input="Say hi.",
)
(span,) = span_exporter.get_finished_spans()
assert span.attributes[GenAIAttributes.GEN_AI_RESPONSE_FINISH_REASONS] == ("stop",)
def test_responses_create_connection_error(span_exporter, instrument_no_content):
_skip_if_not_latest()
client = OpenAI(base_url="http://localhost:4242")
with pytest.raises(APIConnectionError):
client.responses.create( # pylint: disable=no-member
model=DEFAULT_MODEL,
input="Hello",
timeout=0.1,
)
(span,) = span_exporter.get_finished_spans()
assert span.attributes[GenAIAttributes.GEN_AI_REQUEST_MODEL] == DEFAULT_MODEL
assert span.attributes[ServerAttributes.SERVER_ADDRESS] == "localhost"
assert span.attributes[ServerAttributes.SERVER_PORT] == 4242
assert span.attributes[ErrorAttributes.ERROR_TYPE] == "APIConnectionError"
@pytest.mark.vcr()
def test_responses_create_api_error(request, span_exporter, openai_client, instrument_no_content):
_skip_if_not_latest()
with pytest.raises((BadRequestError, NotFoundError)) as exc_info:
openai_client.responses.create(
model=INVALID_MODEL,
input="Hello",
)
(span,) = span_exporter.get_finished_spans()
assert span.attributes[GenAIAttributes.GEN_AI_REQUEST_MODEL] == INVALID_MODEL
assert span.attributes[ErrorAttributes.ERROR_TYPE] == type(exc_info.value).__name__
@pytest.mark.vcr()
def test_responses_create_streaming(request, span_exporter, openai_client, instrument_no_content):
_skip_if_not_latest()
with openai_client.responses.create(
model=DEFAULT_MODEL,
instructions=SYSTEM_INSTRUCTIONS,
input=USER_ONLY_PROMPT[0]["content"],
service_tier="default",
stream=True,
) as stream:
response = _collect_completed_response(stream)
(span,) = span_exporter.get_finished_spans()
assert_all_attributes(
span,
DEFAULT_MODEL,
True,
response.id,
response.model,
response.usage.input_tokens,
response.usage.output_tokens,
request_service_tier="default",
response_service_tier=getattr(response, "service_tier", None),
)
@pytest.mark.vcr()
def test_responses_create_streaming_aggregates_cache_tokens(
request, span_exporter, openai_client, instrument_no_content
):
_skip_if_not_latest()
with openai_client.responses.create(
model=DEFAULT_MODEL,
instructions=SYSTEM_INSTRUCTIONS,
input=USER_ONLY_PROMPT[0]["content"],
stream=True,
) as stream:
response = _collect_completed_response(stream)
(span,) = span_exporter.get_finished_spans()
assert_cache_attributes(span, response.usage)
@pytest.mark.vcr()
def test_responses_create_streaming_captures_content(
request,
span_exporter,
log_exporter,
openai_client,
instrument_with_content,
):
_skip_if_not_latest()
with openai_client.responses.create(
model=DEFAULT_MODEL,
instructions=SYSTEM_INSTRUCTIONS,
input=USER_ONLY_PROMPT[0]["content"],
stream=True,
) as stream:
response = _collect_completed_response(stream)
(span,) = span_exporter.get_finished_spans()
assert_all_attributes(
span,
DEFAULT_MODEL,
True,
response.id,
response.model,
response.usage.input_tokens,
response.usage.output_tokens,
response_service_tier=getattr(response, "service_tier", None),
)
_assert_response_content(span, response, log_exporter)
@pytest.mark.vcr()
def test_responses_create_streaming_iteration(request, span_exporter, openai_client, instrument_no_content):
_skip_if_not_latest()
stream = openai_client.responses.create(
model=DEFAULT_MODEL,
instructions=SYSTEM_INSTRUCTIONS,
input="Say hi.",
stream=True,
)
events = list(stream)
assert len(events) > 0
(span,) = span_exporter.get_finished_spans()
assert span.attributes[GenAIAttributes.GEN_AI_REQUEST_MODEL] == DEFAULT_MODEL
assert GenAIAttributes.GEN_AI_RESPONSE_ID in span.attributes
assert GenAIAttributes.GEN_AI_RESPONSE_MODEL in span.attributes
assert span.attributes[GenAIAttributes.GEN_AI_RESPONSE_FINISH_REASONS] == ("stop",)
assert GenAIAttributes.GEN_AI_USAGE_INPUT_TOKENS in span.attributes
assert GenAIAttributes.GEN_AI_USAGE_OUTPUT_TOKENS in span.attributes
@pytest.mark.vcr()
def test_responses_create_streaming_delegates_response_attribute(request, openai_client, instrument_no_content):
_skip_if_not_latest()
stream = openai_client.responses.create(
model=DEFAULT_MODEL,
instructions=SYSTEM_INSTRUCTIONS,
input="Say hi.",
stream=True,
)
assert stream.response is not None
assert stream.response.status_code == 200
assert stream.response.headers.get("x-request-id") is not None
stream.close()
def test_responses_create_streaming_connection_error(span_exporter, instrument_no_content):
_skip_if_not_latest()
client = OpenAI(base_url="http://localhost:4242")
with pytest.raises(APIConnectionError):
client.responses.create( # pylint: disable=no-member
model=DEFAULT_MODEL,
input="Hello",
stream=True,
timeout=0.1,
)
(span,) = span_exporter.get_finished_spans()
assert span.attributes[GenAIAttributes.GEN_AI_REQUEST_MODEL] == DEFAULT_MODEL
assert span.attributes[ErrorAttributes.ERROR_TYPE] == "APIConnectionError"
@pytest.mark.vcr()
def test_responses_stream_wrapper_finalize_idempotent(request, span_exporter, openai_client, instrument_no_content):
_skip_if_not_latest()
stream = openai_client.responses.create(
model=DEFAULT_MODEL,
instructions=SYSTEM_INSTRUCTIONS,
input=USER_ONLY_PROMPT[0]["content"],
stream=True,
)
response = _collect_completed_response(stream)
stream.close()
spans = span_exporter.get_finished_spans()
assert len(spans) == 1
assert_all_attributes(
spans[0],
DEFAULT_MODEL,
True,
response.id,
response.model,
response.usage.input_tokens,
response.usage.output_tokens,
response_service_tier=getattr(response, "service_tier", None),
)
@pytest.mark.vcr()
def test_responses_create_stream_propagation_error(
request, span_exporter, openai_client, instrument_no_content, monkeypatch
):
_skip_if_not_latest()
stream = openai_client.responses.create(
model=DEFAULT_MODEL,
instructions=SYSTEM_INSTRUCTIONS,
input=USER_ONLY_PROMPT[0]["content"],
stream=True,
)
class ErrorInjectingStreamDelegate:
def __init__(self, inner):
self._inner = inner
self._count = 0
def __iter__(self):
return self
def __next__(self):
if self._count == 1:
raise ConnectionError("connection reset during stream")
self._count += 1
return next(self._inner)
def close(self):
return self._inner.close()
def __getattr__(self, name):
return getattr(self._inner, name)
monkeypatch.setattr(stream, "stream", ErrorInjectingStreamDelegate(stream.stream))
with pytest.raises(ConnectionError, match="connection reset during stream"):
with stream:
for _ in stream:
pass
(span,) = span_exporter.get_finished_spans()
assert span.attributes[GenAIAttributes.GEN_AI_REQUEST_MODEL] == DEFAULT_MODEL
assert span.attributes[ErrorAttributes.ERROR_TYPE] == "ConnectionError"
@pytest.mark.vcr()
def test_responses_create_streaming_user_exception(request, span_exporter, openai_client, instrument_no_content):
_skip_if_not_latest()
with pytest.raises(ValueError, match="User raised exception"):
with openai_client.responses.create(
model=DEFAULT_MODEL,
instructions=SYSTEM_INSTRUCTIONS,
input=USER_ONLY_PROMPT[0]["content"],
stream=True,
) as stream:
for _ in stream:
raise ValueError("User raised exception")
(span,) = span_exporter.get_finished_spans()
assert span.attributes[GenAIAttributes.GEN_AI_REQUEST_MODEL] == DEFAULT_MODEL
assert span.attributes[ErrorAttributes.ERROR_TYPE] == "ValueError"
@pytest.mark.vcr()
def test_responses_create_instrumentation_error_swallowed(
request, span_exporter, openai_client, instrument_no_content, monkeypatch
):
_skip_if_not_latest()
def exploding_process_event(self, event):
del self
del event
raise RuntimeError("instrumentation bug")
monkeypatch.setattr(ResponseStreamWrapper, "process_event", exploding_process_event)
with openai_client.responses.create(
model=DEFAULT_MODEL,
instructions=SYSTEM_INSTRUCTIONS,
input=USER_ONLY_PROMPT[0]["content"],
stream=True,
) as stream:
events = list(stream)
assert len(events) > 0
(span,) = span_exporter.get_finished_spans()
assert span.attributes[GenAIAttributes.GEN_AI_REQUEST_MODEL] == DEFAULT_MODEL
assert ErrorAttributes.ERROR_TYPE not in span.attributes
@pytest.mark.vcr()
@pytest.mark.skipif(
not _has_tools_param,
reason="openai SDK too old to support 'tools' parameter on Responses.create",
)
def test_responses_create_captures_tool_call_content(request, span_exporter, openai_client, instrument_with_content):
_skip_if_not_latest()
openai_client.responses.create(
model=DEFAULT_MODEL,
input="What's the weather in Seattle right now?",
tools=[get_responses_weather_tool_definition()],
tool_choice={"type": "function", "name": "get_current_weather"},
)
(span,) = span_exporter.get_finished_spans()
assert span.attributes[GenAIAttributes.GEN_AI_REQUEST_MODEL] == DEFAULT_MODEL
assert span.attributes[GenAIAttributes.GEN_AI_RESPONSE_FINISH_REASONS] == ("tool_calls",)
input_messages = _load_span_messages(span, GenAIAttributes.GEN_AI_INPUT_MESSAGES)
assert input_messages[0]["role"] == "user"
output_messages = _load_span_messages(span, GenAIAttributes.GEN_AI_OUTPUT_MESSAGES)
tool_call_parts = [
part for message in output_messages for part in message.get("parts", []) if part.get("type") == "tool_call"
]
assert len(tool_call_parts) > 0
assert tool_call_parts[0]["name"] == "get_current_weather"
assert "arguments" in tool_call_parts[0]
@pytest.mark.vcr()
@pytest.mark.skipif(
not _has_reasoning_param,
reason=("openai SDK too old to support 'reasoning' parameter on Responses.create"),
)
def test_responses_create_reports_reasoning_tokens(request, span_exporter, openai_client, instrument_with_content):
_skip_if_not_latest()
response = openai_client.responses.create(
model=REASONING_MODEL,
reasoning={"effort": "low"},
input=[
{
"role": "user",
"content": REASONING_PROMPT,
}
],
max_output_tokens=300,
timeout=30.0,
)
reasoning_tokens = getattr(
getattr(response.usage, "output_tokens_details", None),
"reasoning_tokens",
None,
)
assert reasoning_tokens is not None
assert reasoning_tokens > 0
spans = span_exporter.get_finished_spans()
assert len(spans) == 1
(span,) = spans
assert span.attributes[GenAIAttributes.GEN_AI_REQUEST_MODEL] == (REASONING_MODEL)
assert span.attributes[GenAIAttributes.GEN_AI_USAGE_INPUT_TOKENS] == response.usage.input_tokens
assert span.attributes[GenAIAttributes.GEN_AI_USAGE_OUTPUT_TOKENS] == response.usage.output_tokens
assert span.attributes[GenAIAttributes.GEN_AI_RESPONSE_FINISH_REASONS] == ("stop",)
output_messages = _load_span_messages(span, GenAIAttributes.GEN_AI_OUTPUT_MESSAGES)
assert len(output_messages) > 0
@pytest.mark.vcr()
def test_responses_create_with_content_span_unsampled(
request,
span_exporter,
log_exporter,
openai_client,
instrument_with_content_unsampled,
):
_skip_if_not_latest()
openai_client.responses.create(
model=DEFAULT_MODEL,
instructions=SYSTEM_INSTRUCTIONS,
input=USER_ONLY_PROMPT[0]["content"],
stream=False,
)
assert len(span_exporter.get_finished_spans()) == 0
assert len(log_exporter.get_finished_logs()) == 0
@pytest.mark.vcr()
def test_responses_create_with_content_shapes(
request,
span_exporter,
log_exporter,
openai_client,
instrument_with_content,
):
_skip_if_not_latest()
openai_client.responses.create(
model=DEFAULT_MODEL,
instructions=SYSTEM_INSTRUCTIONS,
input=USER_ONLY_PROMPT[0]["content"],
stream=False,
)
(span,) = span_exporter.get_finished_spans()
input_messages = _load_span_messages(span, GenAIAttributes.GEN_AI_INPUT_MESSAGES)
output_messages = _load_span_messages(span, GenAIAttributes.GEN_AI_OUTPUT_MESSAGES)
assert input_messages[0]["role"] == "user"
assert input_messages[0]["parts"][0]["type"] == "text"
assert output_messages[0]["role"] == "assistant"
assert output_messages[0]["parts"][0]["type"] == "text"
assert len(log_exporter.get_finished_logs()) == 0
@pytest.mark.vcr()
def test_responses_create_event_only_no_content_in_span(
request, span_exporter, log_exporter, openai_client, instrument_event_only
):
_skip_if_not_latest()
openai_client.responses.create(
model=DEFAULT_MODEL,
instructions=SYSTEM_INSTRUCTIONS,
input=USER_ONLY_PROMPT[0]["content"],
stream=False,
)
(span,) = span_exporter.get_finished_spans()
assert GenAIAttributes.GEN_AI_INPUT_MESSAGES not in span.attributes
assert GenAIAttributes.GEN_AI_OUTPUT_MESSAGES not in span.attributes
assert GenAIAttributes.GEN_AI_SYSTEM_INSTRUCTIONS not in span.attributes
logs = log_exporter.get_finished_logs()
assert len(logs) == 1
assert logs[0].log_record.event_name == "gen_ai.client.inference.operation.details"
test_utils.py 0000664 0000000 0000000 00000023223 15270700723 0037662 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-openai-v2/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
"""Shared test utilities for OpenAI instrumentation tests."""
import json
from typing import Any
from opentelemetry.sdk.trace import ReadableSpan
from opentelemetry.semconv._incubating.attributes import (
gen_ai_attributes as GenAIAttributes,
)
from opentelemetry.semconv._incubating.attributes import (
openai_attributes as OpenAIAttributes,
)
from opentelemetry.semconv._incubating.attributes import (
server_attributes as ServerAttributes,
)
DEFAULT_MODEL = "gpt-4o-mini"
DEFAULT_EMBEDDING_MODEL = "text-embedding-3-small"
GEN_AI_USAGE_CACHE_CREATION_INPUT_TOKENS = "gen_ai.usage.cache_creation.input_tokens"
GEN_AI_USAGE_CACHE_READ_INPUT_TOKENS = "gen_ai.usage.cache_read.input_tokens"
USER_ONLY_PROMPT = [{"role": "user", "content": "Say this is a test"}]
USER_ONLY_EXPECTED_INPUT_MESSAGES = [
{
"role": "user",
"parts": [
{
"type": "text",
"content": USER_ONLY_PROMPT[0]["content"],
}
],
}
]
WEATHER_TOOL_PROMPT = [
{"role": "system", "content": "You're a helpful assistant."},
{
"role": "user",
"content": "What's the weather in Seattle and San Francisco today?",
},
]
WEATHER_TOOL_EXPECTED_INPUT_MESSAGES = [
{
"role": "system",
"parts": [
{
"type": "text",
"content": WEATHER_TOOL_PROMPT[0]["content"],
}
],
},
{
"role": "user",
"parts": [
{
"type": "text",
"content": WEATHER_TOOL_PROMPT[1]["content"],
}
],
},
]
def _assert_optional_attribute(span, attribute_name, expected_value):
"""Helper to assert optional span attributes."""
if expected_value is not None:
assert expected_value == span.attributes[attribute_name]
else:
assert attribute_name not in span.attributes
def assert_all_attributes(
span: ReadableSpan,
request_model: str,
latest_experimental_enabled: bool,
response_id: str = None,
response_model: str = None,
input_tokens: int | None = None,
output_tokens: int | None = None,
operation_name: str = "chat",
server_address: str = "api.openai.com",
server_port: int = 443,
request_service_tier: str | None = None,
response_service_tier: str | None = None,
):
assert span.name == f"{operation_name} {request_model}"
assert operation_name == span.attributes[GenAIAttributes.GEN_AI_OPERATION_NAME]
provider_name_attr_name = "gen_ai.provider.name" if latest_experimental_enabled else GenAIAttributes.GEN_AI_SYSTEM
assert GenAIAttributes.GenAiProviderNameValues.OPENAI.value == span.attributes[provider_name_attr_name]
assert request_model == span.attributes[GenAIAttributes.GEN_AI_REQUEST_MODEL]
_assert_optional_attribute(span, GenAIAttributes.GEN_AI_RESPONSE_MODEL, response_model)
_assert_optional_attribute(span, GenAIAttributes.GEN_AI_RESPONSE_ID, response_id)
_assert_optional_attribute(span, GenAIAttributes.GEN_AI_USAGE_INPUT_TOKENS, input_tokens)
_assert_optional_attribute(span, GenAIAttributes.GEN_AI_USAGE_OUTPUT_TOKENS, output_tokens)
assert server_address == span.attributes[ServerAttributes.SERVER_ADDRESS]
if server_port != 443 and server_port > 0:
assert server_port == span.attributes[ServerAttributes.SERVER_PORT]
request_service_tier_attr_name = (
OpenAIAttributes.OPENAI_REQUEST_SERVICE_TIER
if latest_experimental_enabled
else GenAIAttributes.GEN_AI_OPENAI_REQUEST_SERVICE_TIER
)
_assert_optional_attribute(
span,
request_service_tier_attr_name,
request_service_tier,
)
response_service_tier_attr_name = (
OpenAIAttributes.OPENAI_RESPONSE_SERVICE_TIER
if latest_experimental_enabled
else GenAIAttributes.GEN_AI_OPENAI_RESPONSE_SERVICE_TIER
)
_assert_optional_attribute(
span,
response_service_tier_attr_name,
response_service_tier,
)
def assert_log_parent(log, span):
"""Assert that the log record has the correct parent span context"""
if span:
assert log.log_record.trace_id == span.get_span_context().trace_id
assert log.log_record.span_id == span.get_span_context().span_id
assert log.log_record.trace_flags == span.get_span_context().trace_flags
def get_current_weather_tool_definition():
return {
"type": "function",
"function": {
"name": "get_current_weather",
"description": "Get the current weather in a given location",
"parameters": {
"type": "object",
"properties": {
"location": {
"type": "string",
"description": "The city and state, e.g. Boston, MA",
},
},
"required": ["location"],
"additionalProperties": False,
},
},
}
def get_responses_weather_tool_definition():
return {
"type": "function",
"name": "get_current_weather",
"description": "Get the current weather in a given location",
"parameters": {
"type": "object",
"properties": {
"location": {
"type": "string",
"description": "The city and state, e.g. Boston, MA",
},
},
"required": ["location"],
"additionalProperties": False,
},
"strict": True,
}
EXPECTED_TOOL_DEFINITIONS = [
{
"type": "function",
"name": "get_current_weather",
"description": "Get the current weather in a given location",
"parameters": {
"type": "object",
"properties": {
"location": {
"type": "string",
"description": "The city and state, e.g. Boston, MA",
},
},
"required": ["location"],
"additionalProperties": False,
},
}
]
def remove_none_values(body):
"""Remove None values from a dictionary recursively"""
result = {}
for key, value in body.items():
if value is None:
continue
if isinstance(value, dict):
result[key] = remove_none_values(value)
elif isinstance(value, list):
result[key] = [remove_none_values(i) if isinstance(i, dict) else i for i in value]
else:
result[key] = value
return result
def assert_completion_attributes(
span: ReadableSpan,
request_model: str,
response: Any,
latest_experimental_enabled: bool,
operation_name: str = "chat",
server_address: str = "api.openai.com",
):
return assert_all_attributes(
span,
request_model,
latest_experimental_enabled,
response.id,
response.model,
response.usage.prompt_tokens,
response.usage.completion_tokens,
operation_name,
server_address,
)
def assert_messages_attribute(actual, expected):
assert json.loads(actual) == expected
def format_simple_expected_output_message(content: str, finish_reason: str = "stop"):
return [
{
"role": "assistant",
"parts": [
{
"type": "text",
"content": content,
}
],
"finish_reason": finish_reason,
}
]
def _get_usage_details(usage):
return getattr(usage, "input_tokens_details", None) or getattr(usage, "prompt_tokens_details", None)
def assert_cache_attributes(span, usage):
details = _get_usage_details(usage)
assert details is not None
cached_tokens = getattr(details, "cached_tokens", None)
if cached_tokens is None:
assert GEN_AI_USAGE_CACHE_READ_INPUT_TOKENS not in span.attributes
else:
assert span.attributes[GEN_AI_USAGE_CACHE_READ_INPUT_TOKENS] == cached_tokens
cache_creation = getattr(details, "cache_creation_input_tokens", None)
if cache_creation is None:
assert GEN_AI_USAGE_CACHE_CREATION_INPUT_TOKENS not in span.attributes
else:
assert span.attributes[GEN_AI_USAGE_CACHE_CREATION_INPUT_TOKENS] == cache_creation
def assert_message_in_logs(log, event_name, expected_content, parent_span):
assert log.log_record.event_name == event_name
assert log.log_record.attributes[GenAIAttributes.GEN_AI_SYSTEM] == GenAIAttributes.GenAiSystemValues.OPENAI.value
if not expected_content:
assert not log.log_record.body
else:
assert log.log_record.body
assert dict(log.log_record.body) == remove_none_values(expected_content)
assert_log_parent(log, parent_span)
def assert_embedding_attributes(
span: ReadableSpan,
request_model: str,
latest_experimental_enabled: bool,
response,
):
"""Assert that the span contains all required attributes for embeddings operation"""
# Use the common assertion function
assert_all_attributes(
span,
request_model,
latest_experimental_enabled,
response_id=None, # Embeddings don't have a response ID
response_model=response.model,
input_tokens=response.usage.prompt_tokens,
operation_name="embeddings",
server_address="api.openai.com",
)
# Assert embeddings-specific attributes
if hasattr(span, "attributes") and "gen_ai.embeddings.dimension.count" in span.attributes:
# If dimensions were specified, verify that they match the actual dimensions
assert span.attributes["gen_ai.embeddings.dimension.count"] == len(response.data[0].embedding)
opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-vertexai/ 0000775 0000000 0000000 00000000000 15270700723 0034053 5 ustar 00root root 0000000 0000000 CHANGELOG.md 0000664 0000000 0000000 00000006750 15270700723 0035615 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-vertexai # Changelog
> [!WARNING]
> This package is deprecated and will not be replaced — it only receives security patches and will be removed in the future.
> Google [deprecated the generative AI modules of the Vertex AI SDK](https://cloud.google.com/vertex-ai/generative-ai/docs/deprecations/genai-vertexai-sdk)
> that this package instruments.
All notable changes to this project will be documented in this file.
The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),
and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
## Unreleased
- Fix compatibility with wrapt 2.x by using positional arguments in `wrap_function_wrapper()` calls
([#4445](https://github.com/open-telemetry/opentelemetry-python-contrib/pull/4445))
## Version 2.2b0 (2025-12-19)
- Fix overwritten log attributes in vertexai instrumentation
([#3925](https://github.com/open-telemetry/opentelemetry-python-contrib/pull/3925))
- Add the `GEN_AI_OUTPUT_TYPE`, `GEN_AI_REQUEST_CHOICE_COUNT` and `GEN_AI_REQUEST_SEED` sem conv request attributes to events/spans generated in the stable instrumentation. This was added pre sem conv 1.36 so it should be in the stable instrumentation. See ([#4011](https://github.com/open-telemetry/opentelemetry-python-contrib/pull/4011)).
## Version 2.1b0 (2025-10-16)
- Update instrumentation to use the latest semantic convention changes made in https://github.com/open-telemetry/semantic-conventions/pull/2179.
Now only a single event and span (`gen_ai.client.inference.operation.details`) are used to capture prompt and response content. These changes are opt-in,
users will need to set the environment variable OTEL_SEMCONV_STABILITY_OPT_IN to `gen_ai_latest_experimental` to see them ([#3799](https://github.com/open-telemetry/opentelemetry-python-contrib/pull/3799)) and ([#3709](https://github.com/open-telemetry/opentelemetry-python-contrib/pull/3709)). Update instrumentation to call upload hook.
- Implement uninstrument for `opentelemetry-instrumentation-vertexai`
([#3328](https://github.com/open-telemetry/opentelemetry-python-contrib/pull/3328))
- VertexAI support for async calling
([#3386](https://github.com/open-telemetry/opentelemetry-python-contrib/pull/3386))
- Migrate off the deprecated events API to use the logs API
([#3625](https://github.com/open-telemetry/opentelemetry-python-contrib/pull/3626))
- Update `gen_ai_latest_experimental` instrumentation to record files being passed to the model
([#3840](https://github.com/open-telemetry/opentelemetry-python-contrib/pull/3840)).
## Version 2.0b0 (2025-02-24)
- Added Vertex AI spans for request parameters
([#3192](https://github.com/open-telemetry/opentelemetry-python-contrib/pull/3192))
- Initial VertexAI instrumentation
([#3123](https://github.com/open-telemetry/opentelemetry-python-contrib/pull/3123))
- Add server attributes to Vertex AI spans
([#3208](https://github.com/open-telemetry/opentelemetry-python-contrib/pull/3208))
- VertexAI emit user, system, and assistant events
([#3203](https://github.com/open-telemetry/opentelemetry-python-contrib/pull/3203))
- Add Vertex gen AI response attributes and `gen_ai.choice` events
([#3227](https://github.com/open-telemetry/opentelemetry-python-contrib/pull/3227))
- VertexAI stop serializing unset fields into event
([#3236](https://github.com/open-telemetry/opentelemetry-python-contrib/pull/3236))
- Vertex capture tool requests and responses
([#3255](https://github.com/open-telemetry/opentelemetry-python-contrib/pull/3255))
LICENSE 0000664 0000000 0000000 00000026135 15270700723 0035010 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-vertexai Apache License
Version 2.0, January 2004
http://www.apache.org/licenses/
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README.rst 0000664 0000000 0000000 00000005516 15270700723 0035472 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-vertexai OpenTelemetry VertexAI Instrumentation
======================================
.. warning::
This package is deprecated as part of the GenAI package migration. It is not
being migrated to the
`opentelemetry-python-genai `_
repository, and no replacement package is planned there.
|pypi|
.. |pypi| image:: https://badge.fury.io/py/opentelemetry-instrumentation-vertexai.svg
:target: https://pypi.org/project/opentelemetry-instrumentation-vertexai/
This library allows tracing LLM requests and logging of messages made by the
`VertexAI Python API library `_.
Installation
------------
If your application is already instrumented with OpenTelemetry, add this
package to your requirements.
::
pip install opentelemetry-instrumentation-vertexai
If you don't have an VertexAI application, yet, try our `examples `_.
Check out `zero-code example `_ for a quick start.
Usage
-----
This section describes how to set up VertexAI instrumentation if you're setting OpenTelemetry up manually.
Check out the `manual example `_ for more details.
Instrumenting all clients
*************************
When using the instrumentor, all clients will automatically trace VertexAI chat completion operations.
You can also optionally capture prompts and completions as log events.
Make sure to configure OpenTelemetry tracing, logging, and events to capture all telemetry emitted by the instrumentation.
.. code-block:: python
from opentelemetry.instrumentation.vertexai import VertexAIInstrumentor
from vertexai.generative_models import GenerativeModel
VertexAIInstrumentor().instrument()
vertexai.init()
model = GenerativeModel("gemini-1.5-flash-002")
response = model.generate_content("Write a short poem on OpenTelemetry.")
Enabling message content
*************************
Message content such as the contents of the prompt, completion, function arguments and return values
are not captured by default. To capture message content as log events, set the environment variable
`OTEL_INSTRUMENTATION_GENAI_CAPTURE_MESSAGE_CONTENT` to `true`.
Uninstrument
************
To uninstrument clients, call the uninstrument method:
.. code-block:: python
from opentelemetry.instrumentation.vertexai import VertexAIInstrumentor
VertexAIInstrumentor().instrument()
# ...
# Uninstrument all clients
VertexAIInstrumentor().uninstrument()
References
----------
* `OpenTelemetry VertexAI Instrumentation `_
* `OpenTelemetry Project `_
* `OpenTelemetry Python Examples `_
examples/ 0000775 0000000 0000000 00000000000 15270700723 0035612 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-vertexai manual/ 0000775 0000000 0000000 00000000000 15270700723 0037067 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-vertexai/examples .env 0000664 0000000 0000000 00000002012 15270700723 0037653 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-vertexai/examples/manual # Uncomment and change to your OTLP endpoint
# OTEL_EXPORTER_OTLP_ENDPOINT=http://localhost:4317
# OTEL_EXPORTER_OTLP_PROTOCOL=grpc
OTEL_SERVICE_NAME=opentelemetry-python-vertexai
# Change to 'false' to hide prompt and completion content
OTEL_INSTRUMENTATION_GENAI_CAPTURE_MESSAGE_CONTENT=true
# Alternatively set this env var to enable the latest semantic conventions:
OTEL_SEMCONV_STABILITY_OPT_IN=gen_ai_latest_experimental
# When using the latest experimental flag this env var controls which telemetry signals will have prompt and response content included in them.
# Choices are NO_CONTENT, SPAN_ONLY, EVENT_ONLY, SPAN_AND_EVENT.
OTEL_INSTRUMENTATION_GENAI_CAPTURE_MESSAGE_CONTENT=SPAN_AND_EVENT
# Optional hook that will upload prompt and response content to some external destination.
# For example fsspec.
OTEL_INSTRUMENTATION_GENAI_COMPLETION_HOOK = "upload"
# Required if using a completion hook. The path to upload content to for example gs://my_bucket.
OTEL_INSTRUMENTATION_GENAI_UPLOAD_BASE_PATH = "gs://my_bucket" README.rst 0000664 0000000 0000000 00000002423 15270700723 0040557 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-vertexai/examples/manual OpenTelemetry VertexAI Instrumentation Example
==============================================
This is an example of how to instrument VertexAI calls when configuring OpenTelemetry SDK and Instrumentations manually.
When `main.py `_ is run, it exports traces and logs to an OTLP
compatible endpoint. Traces include details such as the model used and the
duration of the chat request. Logs capture the chat request and the generated
response, providing a comprehensive view of the performance and behavior of
your VertexAI requests.
Note: `.env <.env>`_ file configures additional environment variables:
- `OTEL_INSTRUMENTATION_GENAI_CAPTURE_MESSAGE_CONTENT=true` configures
VertexAI instrumentation to capture prompt and completion contents on
events.
Setup
-----
An OTLP compatible endpoint should be listening for traces and logs on
http://localhost:4317. If not, update "OTEL_EXPORTER_OTLP_ENDPOINT" as well.
Next, set up a virtual environment like this:
::
python3 -m venv .venv
source .venv/bin/activate
pip install "python-dotenv[cli]"
pip install -r requirements.txt
Run
---
Run the example like this:
::
dotenv run -- python main.py
You should see a poem generated by VertexAI while traces and logs export to your
configured observability tool.
main.py 0000664 0000000 0000000 00000002546 15270700723 0040374 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-vertexai/examples/manual # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
# pylint: skip-file
import vertexai
from vertexai.generative_models import GenerativeModel
# NOTE: OpenTelemetry Python Logs and Events APIs are in beta
from opentelemetry import _logs, trace
from opentelemetry.exporter.otlp.proto.grpc._log_exporter import (
OTLPLogExporter,
)
from opentelemetry.exporter.otlp.proto.grpc.trace_exporter import (
OTLPSpanExporter,
)
from opentelemetry.instrumentation.vertexai import VertexAIInstrumentor
from opentelemetry.sdk._logs import LoggerProvider
from opentelemetry.sdk._logs.export import BatchLogRecordProcessor
from opentelemetry.sdk.trace import TracerProvider
from opentelemetry.sdk.trace.export import BatchSpanProcessor
# configure tracing
trace.set_tracer_provider(TracerProvider())
trace.get_tracer_provider().add_span_processor(BatchSpanProcessor(OTLPSpanExporter()))
# configure logging and events
_logs.set_logger_provider(LoggerProvider())
_logs.get_logger_provider().add_log_record_processor(BatchLogRecordProcessor(OTLPLogExporter()))
# instrument VertexAI
VertexAIInstrumentor().instrument()
def main():
vertexai.init()
model = GenerativeModel("gemini-1.5-flash-002")
chat_completion = model.generate_content("Write a short poem on OpenTelemetry.")
print(chat_completion.text)
if __name__ == "__main__":
main()
requirements.txt 0000664 0000000 0000000 00000000226 15270700723 0042353 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-vertexai/examples/manual google-cloud-aiplatform>=1.64
opentelemetry-sdk~=1.29.0
opentelemetry-exporter-otlp-proto-grpc~=1.29.0
opentelemetry-instrumentation-vertexai~=2.0b0
zero-code/ 0000775 0000000 0000000 00000000000 15270700723 0037501 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-vertexai/examples .env 0000664 0000000 0000000 00000002140 15270700723 0040267 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-vertexai/examples/zero-code # Uncomment and change to your OTLP endpoint
# OTEL_EXPORTER_OTLP_ENDPOINT=http://localhost:4317
# OTEL_EXPORTER_OTLP_PROTOCOL=grpc
OTEL_SERVICE_NAME=opentelemetry-python-vertexai
# Uncomment if your OTLP endpoint doesn't support logs
# OTEL_LOGS_EXPORTER=console
# Change to 'false' to hide prompt and completion content
OTEL_INSTRUMENTATION_GENAI_CAPTURE_MESSAGE_CONTENT=true
# Alternatively set this env var to enable the latest semantic conventions:
OTEL_SEMCONV_STABILITY_OPT_IN=gen_ai_latest_experimental
# When using the latest experimental flag this env var controls which telemetry signals will have prompt and response content included in them.
# Choices are NO_CONTENT, SPAN_ONLY, EVENT_ONLY, SPAN_AND_EVENT.
OTEL_INSTRUMENTATION_GENAI_CAPTURE_MESSAGE_CONTENT=SPAN_AND_EVENT
# Optional hook that will upload prompt and response content to some external destination.
# For example fsspec.
OTEL_INSTRUMENTATION_GENAI_COMPLETION_HOOK = "upload"
# Required if using a completion hook. The path to upload content to for example gs://my_bucket.
OTEL_INSTRUMENTATION_GENAI_UPLOAD_BASE_PATH = "gs://my_bucket"
README.rst 0000664 0000000 0000000 00000002102 15270700723 0041163 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-vertexai/examples/zero-code OpenTelemetry VertexAI Instrumentation Example
==============================================
This is an example of how to instrument VertexAI calls with zero code changes,
using `opentelemetry-instrument`.
When `main.py `_ is run, it exports traces and logs to an OTLP
compatible endpoint. Traces include details such as the model used and the
duration of the chat request. Logs capture the chat request and the generated
response, providing a comprehensive view of the performance and behavior of
your VertexAI requests.
Setup
-----
An OTLP compatible endpoint should be listening for traces and logs on http://localhost:4318.
If not, update "OTEL_EXPORTER_OTLP_ENDPOINT" as well.
Next, set up a virtual environment like this:
::
python3 -m venv .venv
source .venv/bin/activate
pip install "python-dotenv[cli]"
pip install -r requirements.txt
Run
---
Run the example like this:
::
dotenv run -- opentelemetry-instrument python main.py
You should see a poem generated by VertexAI while traces and logs export to your
configured observability tool.
main.py 0000664 0000000 0000000 00000000607 15270700723 0041002 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-vertexai/examples/zero-code # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
import vertexai
from vertexai.generative_models import GenerativeModel
def main():
vertexai.init()
model = GenerativeModel("gemini-1.5-flash-002")
chat_completion = model.generate_content("Write a short poem on OpenTelemetry.")
print(chat_completion.text)
if __name__ == "__main__":
main()
requirements.txt 0000664 0000000 0000000 00000000263 15270700723 0042766 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-vertexai/examples/zero-code google-cloud-aiplatform>=1.64
opentelemetry-sdk~=1.28.2
opentelemetry-exporter-otlp-proto-http~=1.28.2
opentelemetry-distro~=0.49b2
opentelemetry-instrumentation-vertexai~=2.0b0
pyproject.toml 0000664 0000000 0000000 00000003243 15270700723 0036712 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-vertexai [build-system]
requires = ["hatchling"]
build-backend = "hatchling.build"
[project]
name = "opentelemetry-instrumentation-vertexai"
dynamic = ["version"]
description = "OpenTelemetry Official VertexAI instrumentation"
readme = "README.rst"
license = "Apache-2.0"
requires-python = ">=3.10"
authors = [
{ name = "OpenTelemetry Authors", email = "cncf-opentelemetry-contributors@lists.cncf.io" },
]
classifiers = [
"Development Status :: 4 - Beta",
"Intended Audience :: Developers",
"License :: OSI Approved :: Apache Software License",
"Programming Language :: Python",
"Programming Language :: Python :: 3",
"Programming Language :: Python :: 3.10",
"Programming Language :: Python :: 3.11",
"Programming Language :: Python :: 3.12",
"Programming Language :: Python :: 3.13",
"Programming Language :: Python :: 3.14",
]
dependencies = [
"opentelemetry-api ~= 1.40",
"opentelemetry-instrumentation ~= 0.61b0",
"opentelemetry-semantic-conventions ~= 0.61b0",
"opentelemetry-util-genai >= 0.4b0, <0.5b0",
]
[project.optional-dependencies]
instruments = ["google-cloud-aiplatform >= 1.64"]
[project.entry-points.opentelemetry_instrumentor]
vertexai = "opentelemetry.instrumentation.vertexai:VertexAIInstrumentor"
[project.urls]
Homepage = "https://github.com/open-telemetry/opentelemetry-python-contrib/tree/main/instrumentation-genai/opentelemetry-instrumentation-vertexai"
Repository = "https://github.com/open-telemetry/opentelemetry-python-contrib"
[tool.hatch.version]
path = "src/opentelemetry/instrumentation/vertexai/version.py"
[tool.hatch.build.targets.sdist]
include = ["/src", "/tests"]
[tool.hatch.build.targets.wheel]
packages = ["src/opentelemetry"]
src/ 0000775 0000000 0000000 00000000000 15270700723 0034563 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-vertexai opentelemetry/ 0000775 0000000 0000000 00000000000 15270700723 0037457 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-vertexai/src instrumentation/ 0000775 0000000 0000000 00000000000 15270700723 0042722 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-vertexai/src/opentelemetry vertexai/ 0000775 0000000 0000000 00000000000 15270700723 0044551 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-vertexai/src/opentelemetry/instrumentation __init__.py 0000664 0000000 0000000 00000012541 15270700723 0046665 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-vertexai/src/opentelemetry/instrumentation/vertexai # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
"""
VertexAI client instrumentation supporting `google-cloud-aiplatform` SDK, it can be enabled by
using ``VertexAIInstrumentor``.
.. _vertexai: https://pypi.org/project/google-cloud-aiplatform/
Usage
-----
.. code:: python
import vertexai
from vertexai.generative_models import GenerativeModel
from opentelemetry.instrumentation.vertexai import VertexAIInstrumentor
VertexAIInstrumentor().instrument()
vertexai.init()
model = GenerativeModel("gemini-1.5-flash-002")
chat_completion = model.generate_content(
"Write a short poem on OpenTelemetry."
)
API
---
"""
from __future__ import annotations
from collections.abc import Collection
from typing import Any
from wrapt import (
wrap_function_wrapper, # type: ignore[reportUnknownVariableType]
)
from opentelemetry._logs import get_logger
from opentelemetry.instrumentation._semconv import (
_OpenTelemetrySemanticConventionStability,
_OpenTelemetryStabilitySignalType,
_StabilityMode,
)
from opentelemetry.instrumentation.instrumentor import BaseInstrumentor
from opentelemetry.instrumentation.utils import unwrap
from opentelemetry.instrumentation.vertexai.package import _instruments
from opentelemetry.instrumentation.vertexai.patch import MethodWrappers
from opentelemetry.instrumentation.vertexai.utils import is_content_enabled
from opentelemetry.semconv.schemas import Schemas
from opentelemetry.trace import get_tracer
from opentelemetry.util.genai.completion_hook import load_completion_hook
def _methods_to_wrap(
method_wrappers: MethodWrappers,
):
# This import is very slow, do it lazily in case instrument() is not called
# pylint: disable=import-outside-toplevel
from google.cloud.aiplatform_v1.services.prediction_service import ( # noqa: PLC0415
async_client,
client,
)
from google.cloud.aiplatform_v1beta1.services.prediction_service import ( # noqa: PLC0415
async_client as async_client_v1beta1,
)
from google.cloud.aiplatform_v1beta1.services.prediction_service import ( # noqa: PLC0415
client as client_v1beta1,
)
for client_class in (
client.PredictionServiceClient,
client_v1beta1.PredictionServiceClient,
):
yield (
client_class,
client_class.generate_content.__name__, # type: ignore[reportUnknownMemberType]
method_wrappers.generate_content,
)
for client_class in (
async_client.PredictionServiceAsyncClient,
async_client_v1beta1.PredictionServiceAsyncClient,
):
yield (
client_class,
client_class.generate_content.__name__, # type: ignore[reportUnknownMemberType]
method_wrappers.agenerate_content,
)
class VertexAIInstrumentor(BaseInstrumentor):
def __init__(self) -> None:
super().__init__()
self._methods_to_unwrap: list[tuple[Any, str]] = []
def instrumentation_dependencies(self) -> Collection[str]:
return _instruments
def _instrument(self, **kwargs: Any):
"""Enable VertexAI instrumentation."""
completion_hook = kwargs.get("completion_hook") or load_completion_hook()
sem_conv_opt_in_mode = _OpenTelemetrySemanticConventionStability._get_opentelemetry_stability_opt_in_mode(
_OpenTelemetryStabilitySignalType.GEN_AI,
)
tracer_provider = kwargs.get("tracer_provider")
schema = Schemas.V1_28_0.value if sem_conv_opt_in_mode == _StabilityMode.DEFAULT else Schemas.V1_36_0.value
tracer = get_tracer(
__name__,
"",
tracer_provider,
schema_url=schema,
)
logger_provider = kwargs.get("logger_provider")
logger = get_logger(
__name__,
"",
logger_provider=logger_provider,
schema_url=schema,
)
sem_conv_opt_in_mode = _OpenTelemetrySemanticConventionStability._get_opentelemetry_stability_opt_in_mode(
_OpenTelemetryStabilitySignalType.GEN_AI,
)
if sem_conv_opt_in_mode == _StabilityMode.DEFAULT:
# Type checker now knows sem_conv_opt_in_mode is a Literal[_StabilityMode.DEFAULT]
method_wrappers = MethodWrappers(
tracer,
logger,
is_content_enabled(sem_conv_opt_in_mode),
sem_conv_opt_in_mode,
completion_hook,
)
elif sem_conv_opt_in_mode == _StabilityMode.GEN_AI_LATEST_EXPERIMENTAL:
# Type checker now knows it's the other literal
method_wrappers = MethodWrappers(
tracer,
logger,
is_content_enabled(sem_conv_opt_in_mode),
sem_conv_opt_in_mode,
completion_hook,
)
else:
raise RuntimeError(f"{sem_conv_opt_in_mode} mode not supported")
for client_class, method_name, wrapper in _methods_to_wrap(method_wrappers):
wrap_function_wrapper(
client_class,
method_name,
wrapper,
)
self._methods_to_unwrap.append((client_class, method_name))
def _uninstrument(self, **kwargs: Any) -> None:
for client_class, method_name in self._methods_to_unwrap:
unwrap(client_class, method_name)
events.py 0000664 0000000 0000000 00000011245 15270700723 0046432 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-vertexai/src/opentelemetry/instrumentation/vertexai # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
# type: ignore[reportUnknownDeprecated]
"""
Factories for event types described in
https://github.com/open-telemetry/semantic-conventions/blob/main/docs/gen-ai/gen-ai-events.md#system-event.
Hopefully this code can be autogenerated by Weaver once Gen AI semantic conventions are
schematized in YAML and the Weaver tool supports it.
"""
from __future__ import annotations
from collections.abc import Iterable
from dataclasses import asdict, dataclass
from typing import Any, Literal
from opentelemetry._logs import LogRecord
from opentelemetry.semconv._incubating.attributes import gen_ai_attributes
from opentelemetry.util.types import AnyValue
def user_event(
*,
role: str = "user",
content: AnyValue = None,
) -> LogRecord:
"""Creates a User event
https://github.com/open-telemetry/semantic-conventions/blob/v1.28.0/docs/gen-ai/gen-ai-events.md#user-event
"""
body: dict[str, AnyValue] = {
"role": role,
}
if content is not None:
body["content"] = content
return LogRecord(
event_name="gen_ai.user.message",
attributes={
gen_ai_attributes.GEN_AI_SYSTEM: gen_ai_attributes.GenAiSystemValues.VERTEX_AI.value,
},
body=body,
)
def assistant_event(
*,
role: str = "assistant",
content: AnyValue = None,
) -> LogRecord:
"""Creates an Assistant event
https://github.com/open-telemetry/semantic-conventions/blob/v1.28.0/docs/gen-ai/gen-ai-events.md#assistant-event
"""
body: dict[str, AnyValue] = {
"role": role,
}
if content is not None:
body["content"] = content
return LogRecord(
event_name="gen_ai.assistant.message",
attributes={
gen_ai_attributes.GEN_AI_SYSTEM: gen_ai_attributes.GenAiSystemValues.VERTEX_AI.value,
},
body=body,
)
def system_event(
*,
role: str = "system",
content: AnyValue = None,
) -> LogRecord:
"""Creates a System event
https://github.com/open-telemetry/semantic-conventions/blob/v1.28.0/docs/gen-ai/gen-ai-events.md#system-event
"""
body: dict[str, AnyValue] = {
"role": role,
}
if content is not None:
body["content"] = content
return LogRecord(
event_name="gen_ai.system.message",
attributes={
gen_ai_attributes.GEN_AI_SYSTEM: gen_ai_attributes.GenAiSystemValues.VERTEX_AI.value,
},
body=body,
)
def tool_event(
*,
role: str | None,
id_: str,
content: AnyValue = None,
) -> LogRecord:
"""Creates a Tool message event
https://github.com/open-telemetry/semantic-conventions/blob/v1.28.0/docs/gen-ai/gen-ai-events.md#event-gen_aitoolmessage
"""
if not role:
role = "tool"
body: dict[str, AnyValue] = {
"role": role,
"id": id_,
}
if content is not None:
body["content"] = content
return LogRecord(
event_name="gen_ai.tool.message",
attributes={
gen_ai_attributes.GEN_AI_SYSTEM: gen_ai_attributes.GenAiSystemValues.VERTEX_AI.value,
},
body=body,
)
@dataclass
class ChoiceMessage:
"""The message field for a gen_ai.choice event"""
content: AnyValue = None
role: str = "assistant"
@dataclass
class ChoiceToolCall:
"""The tool_calls field for a gen_ai.choice event"""
@dataclass
class Function:
name: str
arguments: AnyValue = None
function: Function
id: str
type: Literal["function"] = "function"
FinishReason = Literal["content_filter", "error", "length", "stop", "tool_calls"]
def choice_event(
*,
finish_reason: FinishReason | str,
index: int,
message: ChoiceMessage,
tool_calls: Iterable[ChoiceToolCall] = (),
) -> LogRecord:
"""Creates a choice event, which describes the Gen AI response message.
https://github.com/open-telemetry/semantic-conventions/blob/v1.28.0/docs/gen-ai/gen-ai-events.md#event-gen_aichoice
"""
body: dict[str, AnyValue] = {
"finish_reason": finish_reason,
"index": index,
"message": _asdict_filter_nulls(message),
}
tool_calls_list = [_asdict_filter_nulls(tool_call) for tool_call in tool_calls]
if tool_calls_list:
body["tool_calls"] = tool_calls_list
return LogRecord(
event_name="gen_ai.choice",
attributes={
gen_ai_attributes.GEN_AI_SYSTEM: gen_ai_attributes.GenAiSystemValues.VERTEX_AI.value,
},
body=body,
)
def _asdict_filter_nulls(instance: Any) -> dict[str, AnyValue]:
return asdict(
instance,
dict_factory=lambda kvs: {k: v for (k, v) in kvs if v is not None},
)
package.py 0000664 0000000 0000000 00000000202 15270700723 0046510 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-vertexai/src/opentelemetry/instrumentation/vertexai # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
_instruments = ("google-cloud-aiplatform >= 1.64",)
patch.py 0000664 0000000 0000000 00000027700 15270700723 0046230 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-vertexai/src/opentelemetry/instrumentation/vertexai # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
from __future__ import annotations
from collections.abc import Awaitable, Callable, MutableSequence
from contextlib import contextmanager
from dataclasses import asdict
from typing import (
TYPE_CHECKING,
Any,
Literal,
cast,
overload,
)
from opentelemetry._logs import Logger, LogRecord
from opentelemetry.instrumentation._semconv import (
_StabilityMode,
)
from opentelemetry.instrumentation.vertexai.utils import (
GenerateContentParams,
_map_finish_reason,
convert_content_to_message_parts,
get_genai_request_attributes,
get_genai_response_attributes,
get_server_attributes,
get_span_name,
request_to_events,
response_to_events,
)
from opentelemetry.semconv._incubating.attributes import (
gen_ai_attributes as GenAI,
)
from opentelemetry.trace import SpanKind, Tracer
from opentelemetry.util.genai.completion_hook import CompletionHook
from opentelemetry.util.genai.types import (
ContentCapturingMode,
InputMessage,
OutputMessage,
)
from opentelemetry.util.genai.utils import gen_ai_json_dumps
if TYPE_CHECKING:
from google.cloud.aiplatform_v1.services.prediction_service import client
from google.cloud.aiplatform_v1.types import (
content,
prediction_service,
)
from google.cloud.aiplatform_v1beta1.services.prediction_service import (
client as client_v1beta1,
)
from google.cloud.aiplatform_v1beta1.types import (
content as content_v1beta1,
)
from google.cloud.aiplatform_v1beta1.types import (
prediction_service as prediction_service_v1beta1,
)
# Use parameter signature from
# https://github.com/googleapis/python-aiplatform/blob/v1.76.0/google/cloud/aiplatform_v1/services/prediction_service/client.py#L2088
# to handle named vs positional args robustly
def _extract_params(
request: prediction_service.GenerateContentRequest
| prediction_service_v1beta1.GenerateContentRequest
| dict[Any, Any]
| None = None,
*,
model: str | None = None,
contents: MutableSequence[content.Content] | MutableSequence[content_v1beta1.Content] | None = None,
**_kwargs: Any,
) -> GenerateContentParams:
# Request vs the named parameters are mututally exclusive or the RPC will fail
if not request:
return GenerateContentParams(
model=model or "",
contents=contents,
)
if isinstance(request, dict):
return GenerateContentParams(**request)
return GenerateContentParams(
model=request.model,
contents=request.contents,
system_instruction=request.system_instruction,
tools=request.tools,
tool_config=request.tool_config,
labels=request.labels,
safety_settings=request.safety_settings,
generation_config=request.generation_config,
)
# For details about GEN_AI_LATEST_EXPERIMENTAL stability mode see
# https://github.com/open-telemetry/semantic-conventions/blob/v1.37.0/docs/gen-ai/gen-ai-agent-spans.md?plain=1#L18-L37
class MethodWrappers:
@overload
def __init__(
self,
tracer: Tracer,
logger: Logger,
capture_content: ContentCapturingMode,
sem_conv_opt_in_mode: Literal[_StabilityMode.GEN_AI_LATEST_EXPERIMENTAL],
completion_hook: CompletionHook,
) -> None: ...
@overload
def __init__(
self,
tracer: Tracer,
logger: Logger,
capture_content: bool,
sem_conv_opt_in_mode: Literal[_StabilityMode.DEFAULT],
completion_hook: CompletionHook,
) -> None: ...
def __init__(
self,
tracer: Tracer,
logger: Logger,
capture_content: bool | ContentCapturingMode,
sem_conv_opt_in_mode: Literal[_StabilityMode.DEFAULT, _StabilityMode.GEN_AI_LATEST_EXPERIMENTAL],
completion_hook: CompletionHook,
) -> None:
self.tracer = tracer
self.logger = logger
self.capture_content = capture_content
self.sem_conv_opt_in_mode = sem_conv_opt_in_mode
self.completion_hook = completion_hook
@contextmanager
def _with_new_instrumentation(
self,
capture_content: ContentCapturingMode,
instance: client.PredictionServiceClient | client_v1beta1.PredictionServiceClient,
args: Any,
kwargs: Any,
):
params = _extract_params(*args, **kwargs)
request_attributes = get_genai_request_attributes(True, params)
with self.tracer.start_as_current_span(
name=f"{GenAI.GenAiOperationNameValues.CHAT.value} {request_attributes.get(GenAI.GEN_AI_REQUEST_MODEL, '')}".strip(), # pyright: ignore[reportDeprecated]
kind=SpanKind.CLIENT,
) as span:
def handle_response(
response: prediction_service.GenerateContentResponse
| prediction_service_v1beta1.GenerateContentResponse
| None,
) -> None:
attributes = (
get_server_attributes(instance.api_endpoint)
| request_attributes
| get_genai_response_attributes(response)
)
event = LogRecord(
event_name="gen_ai.client.inference.operation.details",
)
event.attributes = attributes.copy()
system_instructions, inputs, outputs = [], [], []
if params.system_instruction:
system_instructions = convert_content_to_message_parts(params.system_instruction)
if params.contents:
inputs = [
InputMessage(
role=content.role,
parts=convert_content_to_message_parts(content),
)
for content in params.contents
]
if response:
outputs = [
OutputMessage(
finish_reason=_map_finish_reason(candidate.finish_reason),
role=candidate.content.role,
parts=convert_content_to_message_parts(candidate.content),
)
for candidate in response.candidates
]
self.completion_hook.on_completion(
inputs=inputs,
outputs=outputs,
system_instruction=system_instructions,
span=span,
log_record=event,
)
content_attributes = {
k: [asdict(x) for x in v]
for k, v in [
(
GenAI.GEN_AI_SYSTEM_INSTRUCTIONS,
system_instructions,
),
(GenAI.GEN_AI_INPUT_MESSAGES, inputs),
(GenAI.GEN_AI_OUTPUT_MESSAGES, outputs),
]
if v
}
if span.is_recording():
span.set_attributes(attributes)
if capture_content in (
ContentCapturingMode.SPAN_AND_EVENT,
ContentCapturingMode.SPAN_ONLY,
):
span.set_attributes({k: gen_ai_json_dumps(v) for k, v in content_attributes.items()})
if capture_content in (
ContentCapturingMode.SPAN_AND_EVENT,
ContentCapturingMode.EVENT_ONLY,
):
event.attributes |= content_attributes
self.logger.emit(event)
yield handle_response
@contextmanager
def _with_default_instrumentation(
self,
capture_content: bool,
instance: client.PredictionServiceClient | client_v1beta1.PredictionServiceClient,
args: Any,
kwargs: Any,
):
params = _extract_params(*args, **kwargs)
api_endpoint: str = instance.api_endpoint
span_attributes = {
**get_genai_request_attributes(False, params),
**get_server_attributes(api_endpoint),
}
span_name = get_span_name(span_attributes)
with self.tracer.start_as_current_span(
name=span_name,
kind=SpanKind.CLIENT,
attributes=span_attributes,
) as span:
for event in request_to_events(params=params, capture_content=capture_content):
self.logger.emit(event)
# TODO: set error.type attribute
# https://github.com/open-telemetry/semantic-conventions/blob/main/docs/gen-ai/gen-ai-spans.md
def handle_response(
response: prediction_service.GenerateContentResponse
| prediction_service_v1beta1.GenerateContentResponse,
) -> None:
if span.is_recording():
# When streaming, this is called multiple times so attributes would be
# overwritten. In practice, it looks the API only returns the interesting
# attributes on the last streamed response. However, I couldn't find
# documentation for this and setting attributes shouldn't be too expensive.
span.set_attributes(get_genai_response_attributes(response))
for event in response_to_events(response=response, capture_content=capture_content):
self.logger.emit(event)
yield handle_response
def generate_content(
self,
wrapped: Callable[
...,
prediction_service.GenerateContentResponse | prediction_service_v1beta1.GenerateContentResponse,
],
instance: client.PredictionServiceClient | client_v1beta1.PredictionServiceClient,
args: Any,
kwargs: Any,
) -> prediction_service.GenerateContentResponse | prediction_service_v1beta1.GenerateContentResponse:
if self.sem_conv_opt_in_mode == _StabilityMode.DEFAULT:
capture_content_bool = cast(bool, self.capture_content)
with self._with_default_instrumentation(capture_content_bool, instance, args, kwargs) as handle_response:
response = wrapped(*args, **kwargs)
handle_response(response)
return response
else:
capture_content = cast(ContentCapturingMode, self.capture_content)
with self._with_new_instrumentation(capture_content, instance, args, kwargs) as handle_response:
response = None
try:
response = wrapped(*args, **kwargs)
return response
finally:
handle_response(response)
async def agenerate_content(
self,
wrapped: Callable[
...,
Awaitable[prediction_service.GenerateContentResponse | prediction_service_v1beta1.GenerateContentResponse],
],
instance: client.PredictionServiceClient | client_v1beta1.PredictionServiceClient,
args: Any,
kwargs: Any,
) -> prediction_service.GenerateContentResponse | prediction_service_v1beta1.GenerateContentResponse:
if self.sem_conv_opt_in_mode == _StabilityMode.DEFAULT:
capture_content_bool = cast(bool, self.capture_content)
with self._with_default_instrumentation(capture_content_bool, instance, args, kwargs) as handle_response:
response = await wrapped(*args, **kwargs)
handle_response(response)
return response
else:
capture_content = cast(ContentCapturingMode, self.capture_content)
with self._with_new_instrumentation(capture_content, instance, args, kwargs) as handle_response:
response = None
try:
response = await wrapped(*args, **kwargs)
return response
finally:
handle_response(response)
py.typed 0000664 0000000 0000000 00000000000 15270700723 0046236 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-vertexai/src/opentelemetry/instrumentation/vertexai utils.py 0000664 0000000 0000000 00000033517 15270700723 0046274 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-vertexai/src/opentelemetry/instrumentation/vertexai # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
# type: ignore[reportUnknownDeprecated]
from __future__ import annotations
import logging
import re
from collections.abc import Iterable, Mapping, Sequence
from dataclasses import dataclass
from os import environ
from typing import (
TYPE_CHECKING,
Literal,
cast,
overload,
)
from urllib.parse import urlparse
from google.protobuf import json_format
from opentelemetry._logs import LogRecord
from opentelemetry.instrumentation._semconv import (
_StabilityMode,
)
from opentelemetry.instrumentation.vertexai.events import (
ChoiceMessage,
ChoiceToolCall,
assistant_event,
choice_event,
system_event,
tool_event,
user_event,
)
from opentelemetry.semconv._incubating.attributes import (
gen_ai_attributes as GenAIAttributes,
)
from opentelemetry.semconv.attributes import server_attributes
from opentelemetry.util.genai.types import (
Blob,
ContentCapturingMode,
FinishReason,
MessagePart,
Text,
ToolCallRequest,
ToolCallResponse,
Uri,
)
from opentelemetry.util.genai.utils import get_content_capturing_mode
from opentelemetry.util.types import AnyValue, AttributeValue
if TYPE_CHECKING:
from google.cloud.aiplatform_v1.types import (
content,
prediction_service,
tool,
)
from google.cloud.aiplatform_v1beta1.types import (
content as content_v1beta1,
)
from google.cloud.aiplatform_v1beta1.types import (
prediction_service as prediction_service_v1beta1,
)
from google.cloud.aiplatform_v1beta1.types import (
tool as tool_v1beta1,
)
_MODEL = "model"
@dataclass(frozen=True)
class GenerateContentParams:
model: str
contents: Sequence[content.Content] | Sequence[content_v1beta1.Content] | None = None
system_instruction: content.Content | content_v1beta1.Content | None = None
tools: Sequence[tool.Tool] | Sequence[tool_v1beta1.Tool] | None = None
tool_config: tool.ToolConfig | tool_v1beta1.ToolConfig | None = None
labels: Mapping[str, str] | None = None
safety_settings: Sequence[content.SafetySetting] | Sequence[content_v1beta1.SafetySetting] | None = None
generation_config: content.GenerationConfig | content_v1beta1.GenerationConfig | None = None
def get_server_attributes(
endpoint: str,
) -> dict[str, AttributeValue]:
"""Get server.* attributes from the endpoint, which is a hostname with optional port e.g.
- ``us-central1-aiplatform.googleapis.com``
- ``us-central1-aiplatform.googleapis.com:5431``
"""
parsed = urlparse(f"scheme://{endpoint}")
if not parsed.hostname:
return {}
return {
server_attributes.SERVER_ADDRESS: parsed.hostname,
server_attributes.SERVER_PORT: parsed.port or 443,
}
def get_genai_request_attributes( # pylint: disable=too-many-branches
use_latest_semconvs: bool,
params: GenerateContentParams,
operation_name: GenAIAttributes.GenAiOperationNameValues = GenAIAttributes.GenAiOperationNameValues.CHAT,
):
model = _get_model_name(params.model)
generation_config = params.generation_config
attributes: dict[str, AttributeValue] = {
GenAIAttributes.GEN_AI_OPERATION_NAME: operation_name.value,
GenAIAttributes.GEN_AI_REQUEST_MODEL: model,
}
if not use_latest_semconvs:
attributes[GenAIAttributes.GEN_AI_SYSTEM] = GenAIAttributes.GenAiSystemValues.VERTEX_AI.value
if not generation_config:
return attributes
# Check for optional fields
# https://proto-plus-python.readthedocs.io/en/stable/fields.html#optional-fields
if "temperature" in generation_config:
attributes[GenAIAttributes.GEN_AI_REQUEST_TEMPERATURE] = generation_config.temperature
if "top_p" in generation_config:
# There is also a top_k parameter ( The maximum number of tokens to consider when sampling.),
# but no semconv yet exists for it.
attributes[GenAIAttributes.GEN_AI_REQUEST_TOP_P] = generation_config.top_p
if "max_output_tokens" in generation_config:
attributes[GenAIAttributes.GEN_AI_REQUEST_MAX_TOKENS] = generation_config.max_output_tokens
if "presence_penalty" in generation_config:
attributes[GenAIAttributes.GEN_AI_REQUEST_PRESENCE_PENALTY] = generation_config.presence_penalty
if "frequency_penalty" in generation_config:
attributes[GenAIAttributes.GEN_AI_REQUEST_FREQUENCY_PENALTY] = generation_config.frequency_penalty
if "stop_sequences" in generation_config:
attributes[GenAIAttributes.GEN_AI_REQUEST_STOP_SEQUENCES] = generation_config.stop_sequences
if "seed" in generation_config:
attributes[GenAIAttributes.GEN_AI_REQUEST_SEED] = generation_config.seed
if "candidate_count" in generation_config:
attributes[GenAIAttributes.GEN_AI_REQUEST_CHOICE_COUNT] = generation_config.candidate_count
if "response_mime_type" in generation_config:
if generation_config.response_mime_type == "text/plain":
attributes[GenAIAttributes.GEN_AI_OUTPUT_TYPE] = "text"
elif generation_config.response_mime_type == "application/json":
attributes[GenAIAttributes.GEN_AI_OUTPUT_TYPE] = "json"
else:
attributes[GenAIAttributes.GEN_AI_OUTPUT_TYPE] = generation_config.response_mime_type
return attributes
def get_genai_response_attributes(
response: prediction_service.GenerateContentResponse | prediction_service_v1beta1.GenerateContentResponse | None,
) -> dict[str, AttributeValue]:
if not response:
return {}
finish_reasons: list[str] = [_map_finish_reason(candidate.finish_reason) for candidate in response.candidates]
return {
GenAIAttributes.GEN_AI_RESPONSE_MODEL: response.model_version,
GenAIAttributes.GEN_AI_RESPONSE_FINISH_REASONS: finish_reasons,
GenAIAttributes.GEN_AI_USAGE_INPUT_TOKENS: response.usage_metadata.prompt_token_count,
GenAIAttributes.GEN_AI_USAGE_OUTPUT_TOKENS: response.usage_metadata.candidates_token_count,
}
_MODEL_STRIP_RE = re.compile(r"^projects/(.*)/locations/(.*)/publishers/google/models/")
def _get_model_name(model: str) -> str:
return _MODEL_STRIP_RE.sub("", model)
OTEL_INSTRUMENTATION_GENAI_CAPTURE_MESSAGE_CONTENT = "OTEL_INSTRUMENTATION_GENAI_CAPTURE_MESSAGE_CONTENT"
@overload
def is_content_enabled(
mode: Literal[_StabilityMode.GEN_AI_LATEST_EXPERIMENTAL],
) -> ContentCapturingMode: ...
@overload
def is_content_enabled(mode: Literal[_StabilityMode.DEFAULT]) -> bool: ...
def is_content_enabled(
mode: Literal[_StabilityMode.DEFAULT, _StabilityMode.GEN_AI_LATEST_EXPERIMENTAL],
) -> bool | ContentCapturingMode:
if mode == _StabilityMode.DEFAULT:
capture_content = environ.get(OTEL_INSTRUMENTATION_GENAI_CAPTURE_MESSAGE_CONTENT, "false")
return capture_content.lower() == "true"
return get_content_capturing_mode()
def get_span_name(span_attributes: Mapping[str, AttributeValue]) -> str:
name = span_attributes[GenAIAttributes.GEN_AI_OPERATION_NAME]
model = span_attributes[GenAIAttributes.GEN_AI_REQUEST_MODEL]
if not model:
return f"{name}"
return f"{name} {model}"
def request_to_events(*, params: GenerateContentParams, capture_content: bool) -> Iterable[LogRecord]:
# System message
if params.system_instruction:
request_content = _parts_to_any_value(
capture_content=capture_content,
parts=params.system_instruction.parts,
)
yield system_event(role=params.system_instruction.role, content=request_content)
for content in params.contents or []:
# Assistant message
if content.role == _MODEL:
request_content = _parts_to_any_value(capture_content=capture_content, parts=content.parts)
yield assistant_event(role=content.role, content=request_content)
continue
# Tool event
#
# Function call results can be parts inside of a user Content or in a separate Content
# entry without a role. That may cause duplication in a user event, see
# https://github.com/open-telemetry/opentelemetry-python-contrib/issues/3280
function_responses = [part.function_response for part in content.parts if "function_response" in part]
for idx, function_response in enumerate(function_responses):
yield tool_event(
id_=f"{function_response.name}_{idx}",
role=content.role,
content=json_format.MessageToDict(
function_response._pb.response # type: ignore[reportUnknownMemberType]
)
if capture_content
else None,
)
if len(function_responses) == len(content.parts):
# If the content only contained function responses, don't emit a user event
continue
request_content = _parts_to_any_value(capture_content=capture_content, parts=content.parts)
yield user_event(role=content.role, content=request_content)
def _modality_from_mime_type(mime_type: str) -> str:
"""Infer modality from MIME type prefix."""
if mime_type.startswith("image/"):
return "image"
if mime_type.startswith("video/"):
return "video"
if mime_type.startswith("audio/"):
return "audio"
return mime_type
def convert_content_to_message_parts(
content: content.Content | content_v1beta1.Content,
) -> list[MessagePart]:
parts: MessagePart = []
for idx, part in enumerate(content.parts):
if "function_response" in part:
part = part.function_response
parts.append(
ToolCallResponse(
id=f"{part.name}_{idx}",
response=json_format.MessageToDict(part._pb.response), # type: ignore[reportUnknownMemberType]
)
)
elif "function_call" in part:
part = part.function_call
parts.append(
ToolCallRequest(
id=f"{part.name}_{idx}",
name=part.name,
arguments=json_format.MessageToDict(
part._pb.args, # type: ignore[reportUnknownMemberType]
),
)
)
elif "text" in part:
parts.append(Text(content=part.text))
elif "inline_data" in part:
part = part.inline_data
mime_type = part.mime_type or ""
parts.append(
Blob(
mime_type=mime_type,
modality=_modality_from_mime_type(mime_type),
content=part.data or b"",
)
)
elif "file_data" in part:
part = part.file_data
mime_type = part.mime_type or ""
parts.append(
Uri(
mime_type=mime_type,
modality=_modality_from_mime_type(mime_type),
uri=part.file_uri or "",
)
)
else:
logging.warning("Unknown part dropped from telemetry %s", part)
return parts
def response_to_events(
*,
response: prediction_service.GenerateContentResponse | prediction_service_v1beta1.GenerateContentResponse,
capture_content: bool,
) -> Iterable[LogRecord]:
for candidate in response.candidates:
tool_calls = _extract_tool_calls(candidate=candidate, capture_content=capture_content)
# The original function_call Part is still duplicated in message, see
# https://github.com/open-telemetry/opentelemetry-python-contrib/issues/3280
yield choice_event(
finish_reason=_map_finish_reason(candidate.finish_reason),
index=candidate.index,
# default to "model" since Vertex uses that instead of assistant
message=ChoiceMessage(
role=candidate.content.role or _MODEL,
content=_parts_to_any_value(
capture_content=capture_content,
parts=candidate.content.parts,
),
),
tool_calls=tool_calls,
)
def _extract_tool_calls(
*,
candidate: content.Candidate | content_v1beta1.Candidate,
capture_content: bool,
) -> Iterable[ChoiceToolCall]:
for idx, part in enumerate(candidate.content.parts):
if "function_call" not in part:
continue
yield ChoiceToolCall(
# Make up an id with index since vertex expects the indices to line up instead of
# using ids.
id=f"{part.function_call.name}_{idx}",
function=ChoiceToolCall.Function(
name=part.function_call.name,
arguments=json_format.MessageToDict(
part.function_call._pb.args # type: ignore[reportUnknownMemberType]
)
if capture_content
else None,
),
)
def _parts_to_any_value(
*,
capture_content: bool,
parts: Sequence[content.Part] | Sequence[content_v1beta1.Part],
) -> list[dict[str, AnyValue]] | None:
if not capture_content:
return None
return [
cast(
"dict[str, AnyValue]",
type(part).to_dict( # type: ignore[reportUnknownMemberType]
part, always_print_fields_with_no_presence=False
),
)
for part in parts
]
def _map_finish_reason(
finish_reason: content.Candidate.FinishReason | content_v1beta1.Candidate.FinishReason,
) -> FinishReason | str:
EnumType = type(finish_reason) # pylint: disable=invalid-name
if finish_reason is EnumType.FINISH_REASON_UNSPECIFIED or finish_reason is EnumType.OTHER:
return "error"
if finish_reason is EnumType.STOP:
return "stop"
if finish_reason is EnumType.MAX_TOKENS:
return "length"
# If there is no 1:1 mapping to an OTel preferred enum value, use the exact vertex reason
return finish_reason.name
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# SPDX-License-Identifier: Apache-2.0
__version__ = "2.3b0.dev"
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conftest.py 0000664 0000000 0000000 00000030503 15270700723 0037336 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-vertexai/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
"""Unit tests configuration module."""
import asyncio
import json
import os
import re
from collections.abc import Callable, Generator, Mapping, MutableMapping
from typing import (
Any,
Concatenate,
Protocol,
TypeVar,
)
import pytest
import vertexai
import yaml
from google.auth.aio.credentials import (
AnonymousCredentials as AsyncAnonymousCredentials,
)
from google.auth.credentials import AnonymousCredentials
from google.cloud.aiplatform.initializer import _set_async_rest_credentials
from typing_extensions import ParamSpec
from vcr import VCR
from vcr.record_mode import RecordMode
from vcr.request import Request
from vertexai.generative_models import (
GenerativeModel,
)
from opentelemetry.instrumentation._semconv import (
OTEL_SEMCONV_STABILITY_OPT_IN,
_OpenTelemetrySemanticConventionStability,
)
from opentelemetry.instrumentation.vertexai import VertexAIInstrumentor
from opentelemetry.instrumentation.vertexai.utils import (
OTEL_INSTRUMENTATION_GENAI_CAPTURE_MESSAGE_CONTENT,
)
from opentelemetry.sdk._logs import LoggerProvider
# Backward compatibility for InMemoryLogExporter -> InMemoryLogRecordExporter rename
try:
from opentelemetry.sdk._logs.export import ( # pylint: disable=no-name-in-module
InMemoryLogRecordExporter,
SimpleLogRecordProcessor,
)
except ImportError:
# Fallback to old name for compatibility with older SDK versions
from opentelemetry.sdk._logs.export import (
InMemoryLogExporter as InMemoryLogRecordExporter,
)
from opentelemetry.sdk._logs.export import (
SimpleLogRecordProcessor,
)
from opentelemetry.sdk.metrics import (
MeterProvider,
)
from opentelemetry.sdk.metrics.export import (
InMemoryMetricReader,
)
from opentelemetry.sdk.trace import TracerProvider
from opentelemetry.sdk.trace.export import SimpleSpanProcessor
from opentelemetry.sdk.trace.export.in_memory_span_exporter import (
InMemorySpanExporter,
)
FAKE_PROJECT = "fake-project"
@pytest.fixture(scope="function", name="span_exporter")
def fixture_span_exporter():
exporter = InMemorySpanExporter()
yield exporter
@pytest.fixture(scope="function", name="log_exporter")
def fixture_log_exporter():
exporter = InMemoryLogRecordExporter()
yield exporter
@pytest.fixture(scope="function", name="metric_reader")
def fixture_metric_reader():
exporter = InMemoryMetricReader()
yield exporter
@pytest.fixture(scope="function", name="tracer_provider")
def fixture_tracer_provider(span_exporter):
provider = TracerProvider()
provider.add_span_processor(SimpleSpanProcessor(span_exporter))
return provider
@pytest.fixture(scope="function", name="logger_provider")
def fixture_logger_provider(log_exporter):
provider = LoggerProvider()
provider.add_log_record_processor(SimpleLogRecordProcessor(log_exporter))
return provider
@pytest.fixture(scope="function", name="meter_provider")
def fixture_meter_provider(metric_reader):
return MeterProvider(
metric_readers=[metric_reader],
)
@pytest.fixture(autouse=True)
def vertexai_init(vcr: VCR) -> None:
# When not recording (in CI), don't do any auth. That prevents trying to read application
# default credentials from the filesystem or metadata server and oauth token exchange. This
# is not the interesting part of our instrumentation to test.
credentials = None
project = None
if vcr.record_mode == RecordMode.NONE:
credentials = AnonymousCredentials()
project = FAKE_PROJECT
vertexai.init(api_transport="rest", credentials=credentials, project=project)
@pytest.fixture(scope="function")
def instrument_no_content(tracer_provider, logger_provider, meter_provider, request):
# Reset global state..
_OpenTelemetrySemanticConventionStability._initialized = False
os.environ.update({OTEL_SEMCONV_STABILITY_OPT_IN: "stable"})
os.environ.update({OTEL_INSTRUMENTATION_GENAI_CAPTURE_MESSAGE_CONTENT: "False"})
instrumentor = VertexAIInstrumentor()
instrumentor.instrument(
tracer_provider=tracer_provider,
logger_provider=logger_provider,
meter_provider=meter_provider,
)
yield instrumentor
os.environ.pop(OTEL_INSTRUMENTATION_GENAI_CAPTURE_MESSAGE_CONTENT, None)
if instrumentor.is_instrumented_by_opentelemetry:
instrumentor.uninstrument()
@pytest.fixture(scope="function")
def instrument_no_content_with_experimental_semconvs(tracer_provider, logger_provider, meter_provider, request):
# Reset global state..
_OpenTelemetrySemanticConventionStability._initialized = False
os.environ.update({OTEL_SEMCONV_STABILITY_OPT_IN: "gen_ai_latest_experimental"})
os.environ.update({OTEL_INSTRUMENTATION_GENAI_CAPTURE_MESSAGE_CONTENT: "NO_CONTENT"})
instrumentor = VertexAIInstrumentor()
instrumentor.instrument(
tracer_provider=tracer_provider,
logger_provider=logger_provider,
meter_provider=meter_provider,
)
yield instrumentor
os.environ.pop(OTEL_INSTRUMENTATION_GENAI_CAPTURE_MESSAGE_CONTENT, None)
if instrumentor.is_instrumented_by_opentelemetry:
instrumentor.uninstrument()
@pytest.fixture(scope="function")
def instrument_with_experimental_semconvs(tracer_provider, logger_provider, meter_provider):
# Reset global state..
_OpenTelemetrySemanticConventionStability._initialized = False
os.environ.update({OTEL_SEMCONV_STABILITY_OPT_IN: "gen_ai_latest_experimental"})
os.environ.update({OTEL_INSTRUMENTATION_GENAI_CAPTURE_MESSAGE_CONTENT: "SPAN_AND_EVENT"})
instrumentor = VertexAIInstrumentor()
instrumentor.instrument(
tracer_provider=tracer_provider,
logger_provider=logger_provider,
meter_provider=meter_provider,
)
yield instrumentor
os.environ.pop(OTEL_INSTRUMENTATION_GENAI_CAPTURE_MESSAGE_CONTENT, None)
if instrumentor.is_instrumented_by_opentelemetry:
instrumentor.uninstrument()
@pytest.fixture(scope="function")
def instrument_with_upload_hook(tracer_provider, logger_provider, meter_provider):
# Reset global state..
_OpenTelemetrySemanticConventionStability._initialized = False
os.environ.update(
{
OTEL_SEMCONV_STABILITY_OPT_IN: "gen_ai_latest_experimental",
"OTEL_INSTRUMENTATION_GENAI_COMPLETION_HOOK": "upload",
"OTEL_INSTRUMENTATION_GENAI_UPLOAD_BASE_PATH": "memory://",
OTEL_INSTRUMENTATION_GENAI_CAPTURE_MESSAGE_CONTENT: "SPAN_AND_EVENT",
}
)
instrumentor = VertexAIInstrumentor()
instrumentor.instrument(
tracer_provider=tracer_provider,
logger_provider=logger_provider,
meter_provider=meter_provider,
)
yield instrumentor
os.environ.pop(OTEL_INSTRUMENTATION_GENAI_CAPTURE_MESSAGE_CONTENT, None)
os.environ.pop("OTEL_INSTRUMENTATION_GENAI_COMPLETION_HOOK", None)
os.environ.pop("OTEL_INSTRUMENTATION_GENAI_UPLOAD_BASE_PATH", None)
if instrumentor.is_instrumented_by_opentelemetry:
instrumentor.uninstrument()
@pytest.fixture(scope="function")
def instrument_with_content(tracer_provider, logger_provider, meter_provider, request):
# Reset global state..
_OpenTelemetrySemanticConventionStability._initialized = False
os.environ.update({OTEL_SEMCONV_STABILITY_OPT_IN: "stable"})
os.environ.update({OTEL_INSTRUMENTATION_GENAI_CAPTURE_MESSAGE_CONTENT: "True"})
instrumentor = VertexAIInstrumentor()
instrumentor.instrument(
tracer_provider=tracer_provider,
logger_provider=logger_provider,
meter_provider=meter_provider,
)
yield instrumentor
os.environ.pop(OTEL_INSTRUMENTATION_GENAI_CAPTURE_MESSAGE_CONTENT, None)
if instrumentor.is_instrumented_by_opentelemetry:
instrumentor.uninstrument()
@pytest.fixture(scope="module")
def vcr_config():
filter_header_regexes = [
r"X-.*",
"Server",
"Date",
"Expires",
"Authorization",
]
def filter_headers(headers: Mapping[str, str]) -> Mapping[str, str]:
return {
key: val
for key, val in headers.items()
if not any(re.match(filter_re, key, re.IGNORECASE) for filter_re in filter_header_regexes)
}
def before_record_cb(request: Request):
request.headers = filter_headers(request.headers)
request.uri = re.sub(r"/projects/[^/]+/", "/projects/fake-project/", request.uri)
return request
def before_response_cb(response: MutableMapping[str, Any]):
response["headers"] = filter_headers(response["headers"])
return response
return {
"decode_compressed_response": True,
"before_record_request": before_record_cb,
"before_record_response": before_response_cb,
"ignore_hosts": ["oauth2.googleapis.com"],
}
class LiteralBlockScalar(str):
"""Formats the string as a literal block scalar, preserving whitespace and
without interpreting escape characters"""
def literal_block_scalar_presenter(dumper, data):
"""Represents a scalar string as a literal block, via '|' syntax"""
return dumper.represent_scalar("tag:yaml.org,2002:str", data, style="|")
yaml.add_representer(LiteralBlockScalar, literal_block_scalar_presenter)
def process_string_value(string_value):
"""Pretty-prints JSON or returns long strings as a LiteralBlockScalar"""
try:
json_data = json.loads(string_value)
return LiteralBlockScalar(json.dumps(json_data, indent=2))
except (ValueError, TypeError):
if len(string_value) > 80:
return LiteralBlockScalar(string_value)
return string_value
def convert_body_to_literal(data):
"""Searches the data for body strings, attempting to pretty-print JSON"""
if isinstance(data, dict):
for key, value in data.items():
# Handle response body case (e.g., response.body.string)
if key == "body" and isinstance(value, dict) and "string" in value:
value["string"] = process_string_value(value["string"])
# Handle request body case (e.g., request.body)
elif key == "body" and isinstance(value, str):
data[key] = process_string_value(value)
else:
convert_body_to_literal(value)
elif isinstance(data, list):
for idx, choice in enumerate(data):
data[idx] = convert_body_to_literal(choice)
return data
class PrettyPrintJSONBody:
"""This makes request and response body recordings more readable."""
@staticmethod
def serialize(cassette_dict):
cassette_dict = convert_body_to_literal(cassette_dict)
return yaml.dump(cassette_dict, default_flow_style=False, allow_unicode=True)
@staticmethod
def deserialize(cassette_string):
return yaml.load(cassette_string, Loader=yaml.Loader)
@pytest.fixture(scope="module", autouse=True)
def fixture_vcr(vcr):
vcr.register_serializer("yaml", PrettyPrintJSONBody)
return vcr
_P = ParamSpec("_P")
_R = TypeVar("_R")
def _copy_signature(
func_type: Callable[_P, _R],
) -> Callable[[Callable[..., Any]], Callable[Concatenate[GenerativeModel, _P], _R]]:
return lambda func: func
# Type annotation for fixture to make LSP work properly
class GenerateContentFixture(Protocol):
@_copy_signature(GenerativeModel.generate_content)
def __call__(self): ...
@pytest.fixture(
name="generate_content",
params=(
pytest.param(False, id="sync"),
pytest.param(True, id="async"),
),
)
def fixture_generate_content(
request: pytest.FixtureRequest,
vcr: VCR,
) -> Generator[GenerateContentFixture, None, None]:
"""This fixture parameterizes tests that use it to test calling both
GenerativeModel.generate_content() and GenerativeModel.generate_content_async().
"""
is_async: bool = request.param
if is_async:
# See
# https://github.com/googleapis/python-aiplatform/blob/cb0e5fedbf45cb0531c0b8611fb7fabdd1f57e56/google/cloud/aiplatform/initializer.py#L717-L729
_set_async_rest_credentials(credentials=AsyncAnonymousCredentials())
def wrapper(model: GenerativeModel, *args, **kwargs) -> None:
if is_async:
return asyncio.run(model.generate_content_async(*args, **kwargs))
return model.generate_content(*args, **kwargs)
with vcr.use_cassette(request.node.originalname, allow_playback_repeats=True):
yield wrapper
requirements.latest.txt 0000664 0000000 0000000 00000005201 15270700723 0041713 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-vertexai/tests # Copyright The OpenTelemetry Authors
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ********************************
# WARNING: NOT HERMETIC !!!!!!!!!!
# ********************************
#
# This "requirements.txt" is installed in conjunction
# with multiple other dependencies in the top-level "tox.ini"
# file. In particular, please see:
#
# vertexai-latest: {[testenv]test_deps}
# vertexai-latest: -r {toxinidir}/instrumentation-genai/opentelemetry-instrumentation-vertexai/tests/requirements.latest.txt
#
# This provides additional dependencies, namely:
#
# opentelemetry-api
# opentelemetry-sdk
# opentelemetry-semantic-conventions
#
# ... with a "dev" version based on the latest distribution.
# This variant of the requirements aims to test the system using
# the newest supported version of external dependencies.
annotated-types==0.7.0
asgiref==3.8.1
cachetools==5.5.0
certifi==2024.8.30
charset-normalizer==3.4.0
Deprecated==1.3.1
docstring_parser==0.16
exceptiongroup==1.2.2
google-api-core[grpc, async_rest]==2.23.0
google-auth[aiohttp]==2.45.0
google-cloud-aiplatform==1.79.0
google-cloud-bigquery==3.27.0
google-cloud-core==2.4.1
google-cloud-resource-manager==1.13.1
google-cloud-storage==2.19.0
google-crc32c==1.5.0
google-resumable-media==2.7.2
googleapis-common-protos==1.66.0
grpc-google-iam-v1==0.13.1
grpcio-status==1.68.1
idna==3.10
importlib_metadata==8.5.0
iniconfig==2.0.0
multidict==6.1.0
packaging==24.2
pluggy==1.6.0
propcache==0.2.0
proto-plus==1.25.0
protobuf==5.29.1
pyasn1==0.6.1
pyasn1_modules==0.4.1
pydantic==2.12.5
pytest==7.4.4
pytest-asyncio==0.21.0
pytest-vcr==1.0.2
python-dateutil==2.9.0.post0
PyYAML==6.0.2
requests==2.33.1
rsa==4.9
fsspec==2025.9.0
six==1.17.0
tomli==2.2.1
typing_extensions==4.14.1
urllib3==1.26.20
vcrpy==6.0.2
wrapt==2.1.2
yarl==1.15.2
zipp==3.20.2
grpcio>=1.75.1 ; python_version >= "3.14"
shapely==2.0.6 ; python_version < "3.10"
shapely==2.1.2 ; python_version >= "3.10"
# test with the latest version of opentelemetry-api, sdk, and semantic conventions
-e opentelemetry-instrumentation
-e instrumentation-genai/opentelemetry-instrumentation-vertexai[instruments]
-e util/opentelemetry-util-genai[upload]
requirements.oldest.txt 0000664 0000000 0000000 00000004072 15270700723 0041716 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-vertexai/tests # Copyright The OpenTelemetry Authors
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# This variant of the requirements aims to test the system using
# the oldest supported version of external dependencies.
annotated-types==0.7.0
cachetools==5.5.0
certifi==2024.8.30
charset-normalizer==3.4.0
Deprecated==1.2.14
docstring_parser==0.16
exceptiongroup==1.2.2
google-api-core[grpc, async_rest]==2.23.0
google-auth[aiohttp]==2.36.0
google-cloud-aiplatform==1.79.0
google-cloud-bigquery==3.27.0
google-cloud-core==2.4.1
google-cloud-resource-manager==1.13.1
google-cloud-storage==2.19.0
google-crc32c==1.5.0
google-resumable-media==2.7.2
googleapis-common-protos==1.66.0
grpc-google-iam-v1==0.13.1
grpcio-status==1.68.1
idna==3.10
importlib-metadata==6.11.0
iniconfig==2.0.0
multidict==6.1.0
packaging==24.0
pluggy==1.6.0
propcache==0.2.0
proto-plus==1.25.0
protobuf==5.29.1
pyasn1==0.6.1
pyasn1_modules==0.4.1
pydantic==2.12.5
pytest==7.4.4
pytest-asyncio==0.21.0
pytest-vcr==1.0.2
python-dateutil==2.9.0.post0
PyYAML==6.0.2
requests==2.33.1
rsa==4.9
six==1.17.0
tomli==2.2.1
typing_extensions==4.14.1
urllib3==1.26.20
vcrpy==6.0.2
wrapt==1.16.0
yarl==1.15.2
zipp==3.20.2
grpcio>=1.75.1 ; python_version >= "3.14"
shapely==2.0.6 ; python_version < "3.10"
shapely==2.1.2 ; python_version >= "3.10"
# when updating, also update in pyproject.toml
opentelemetry-api==1.40
opentelemetry-sdk==1.40
opentelemetry-semantic-conventions==0.61b0
opentelemetry-instrumentation==0.61b0
opentelemetry-util-genai[upload]==0.4b0
fsspec==2025.9.0
-e instrumentation-genai/opentelemetry-instrumentation-vertexai[instruments]
shared_test_utils.py 0000664 0000000 0000000 00000006420 15270700723 0041237 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-vertexai/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
from vertexai.generative_models import (
Content,
FunctionDeclaration,
GenerativeModel,
Part,
Tool,
)
def weather_tool() -> Tool:
# Adapted from https://cloud.google.com/vertex-ai/generative-ai/docs/multimodal/function-calling#parallel-samples
get_current_weather_func = FunctionDeclaration(
name="get_current_weather",
description="Get the current weather in a given location",
parameters={
"type": "object",
"properties": {
"location": {
"type": "string",
"description": "The location for which to get the weather. "
"It can be a city name, a city name and state, or a zip code. "
"Examples: 'San Francisco', 'San Francisco, CA', '95616', etc.",
},
},
},
)
return Tool(
function_declarations=[get_current_weather_func],
)
def ask_about_weather(generate_content: callable) -> None:
model = GenerativeModel("gemini-2.5-pro", tools=[weather_tool()])
# Model will respond asking for function calls
generate_content(
model,
[
# User asked about weather
Content(
role="user",
parts=[
Part.from_text("Get weather details in New Delhi and San Francisco?"),
],
),
],
)
def ask_about_weather_function_response(
generate_content: callable,
) -> None:
model = GenerativeModel("gemini-2.5-pro", tools=[weather_tool()])
generate_content(
model,
[
# User asked about weather
Content(
role="user",
parts=[
Part.from_text("Get weather details in New Delhi and San Francisco?"),
],
),
# Model requests two function calls
Content(
role="model",
parts=[
Part.from_dict(
{
"function_call": {
"name": "get_current_weather",
"args": {"location": "New Delhi"},
}
},
),
Part.from_dict(
{
"function_call": {
"name": "get_current_weather",
"args": {"location": "San Francisco"},
}
},
),
],
),
# User responds with function responses
Content(
role="user",
parts=[
Part.from_function_response(
name="get_current_weather",
response={"content": '{"temperature": 35, "unit": "C"}'},
),
Part.from_function_response(
name="get_current_weather",
response={"content": '{"temperature": 25, "unit": "C"}'},
),
],
),
],
)
test_chat_completions.py 0000664 0000000 0000000 00000033117 15270700723 0042107 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-vertexai/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
from __future__ import annotations
import pytest
from google.api_core.exceptions import BadRequest, NotFound
from vertexai.generative_models import (
Content,
GenerationConfig,
GenerativeModel,
Part,
)
from vertexai.preview.generative_models import (
GenerativeModel as PreviewGenerativeModel,
)
from opentelemetry.instrumentation.vertexai import VertexAIInstrumentor
# Backward compatibility for InMemoryLogExporter -> InMemoryLogRecordExporter rename
try:
from opentelemetry.sdk._logs._internal.export.in_memory_log_exporter import ( # pylint: disable=no-name-in-module
InMemoryLogRecordExporter,
)
except ImportError:
# Fallback to old name for compatibility with older SDK versions
from opentelemetry.sdk._logs._internal.export.in_memory_log_exporter import (
InMemoryLogExporter as InMemoryLogRecordExporter,
)
from opentelemetry.sdk.trace import ReadableSpan
from opentelemetry.sdk.trace.export.in_memory_span_exporter import (
InMemorySpanExporter,
)
from opentelemetry.trace import StatusCode
@pytest.mark.vcr()
def test_generate_content(
span_exporter: InMemorySpanExporter,
log_exporter: InMemoryLogRecordExporter,
generate_content: callable,
instrument_with_content: VertexAIInstrumentor,
):
model = GenerativeModel("gemini-2.5-pro")
generate_content(
model,
[
Content(
role="user",
parts=[
Part.from_text("Say this is a test"),
],
),
],
)
# Emits span
spans = span_exporter.get_finished_spans()
assert len(spans) == 1
assert spans[0].name == "chat gemini-2.5-pro"
assert dict(spans[0].attributes) == {
"gen_ai.operation.name": "chat",
"gen_ai.request.model": "gemini-2.5-pro",
"gen_ai.response.finish_reasons": ("stop",),
"gen_ai.response.model": "gemini-2.5-pro",
"gen_ai.system": "vertex_ai",
"gen_ai.usage.input_tokens": 5,
"gen_ai.usage.output_tokens": 5,
"server.address": "us-central1-aiplatform.googleapis.com",
"server.port": 443,
}
logs = log_exporter.get_finished_logs()
# Emits user and choice events
assert len(logs) == 2
user_log, choice_log = [log_data.log_record for log_data in logs]
span_context = spans[0].get_span_context()
assert user_log.trace_id == span_context.trace_id
assert user_log.span_id == span_context.span_id
assert user_log.trace_flags == span_context.trace_flags
assert user_log.attributes == {"gen_ai.system": "vertex_ai"}
assert user_log.event_name == "gen_ai.user.message"
assert user_log.body == {
"content": [{"text": "Say this is a test"}],
"role": "user",
}
assert choice_log.trace_id == span_context.trace_id
assert choice_log.span_id == span_context.span_id
assert choice_log.trace_flags == span_context.trace_flags
assert choice_log.attributes == {"gen_ai.system": "vertex_ai"}
assert choice_log.event_name == "gen_ai.choice"
assert choice_log.body == {
"finish_reason": "stop",
"index": 0,
"message": {
"content": [{"text": "This is a test."}],
"role": "model",
},
}
@pytest.mark.vcr()
def test_generate_content_without_events(
span_exporter: InMemorySpanExporter,
log_exporter: InMemoryLogRecordExporter,
generate_content: callable,
instrument_no_content: VertexAIInstrumentor,
):
model = GenerativeModel("gemini-2.5-pro")
generate_content(
model,
[
Content(role="user", parts=[Part.from_text("Say this is a test")]),
],
)
# Emits span
spans = span_exporter.get_finished_spans()
assert len(spans) == 1
assert spans[0].name == "chat gemini-2.5-pro"
assert dict(spans[0].attributes) == {
"gen_ai.operation.name": "chat",
"gen_ai.request.model": "gemini-2.5-pro",
"gen_ai.response.finish_reasons": ("stop",),
"gen_ai.response.model": "gemini-2.5-pro",
"gen_ai.system": "vertex_ai",
"gen_ai.usage.input_tokens": 5,
"gen_ai.usage.output_tokens": 5,
"server.address": "us-central1-aiplatform.googleapis.com",
"server.port": 443,
}
logs = log_exporter.get_finished_logs()
# Emits user and choice event without body.content
assert len(logs) == 2
user_log, choice_log = [log_data.log_record for log_data in logs]
assert user_log.attributes == {"gen_ai.system": "vertex_ai"}
assert user_log.event_name == "gen_ai.user.message"
assert user_log.body == {"role": "user"}
assert choice_log.attributes == {"gen_ai.system": "vertex_ai"}
assert choice_log.event_name == "gen_ai.choice"
assert choice_log.body == {
"finish_reason": "stop",
"index": 0,
"message": {"role": "model"},
}
@pytest.mark.vcr()
def test_generate_content_empty_model(
span_exporter: InMemorySpanExporter,
generate_content: callable,
instrument_with_content: VertexAIInstrumentor,
):
model = GenerativeModel("")
try:
generate_content(
model,
[Content(role="user", parts=[Part.from_text("Say this is a test")])],
)
except ValueError:
pass
spans = span_exporter.get_finished_spans()
assert len(spans) == 1
assert spans[0].name == "chat"
# Captures invalid params
assert dict(spans[0].attributes) == {
"gen_ai.operation.name": "chat",
"gen_ai.request.model": "",
"gen_ai.system": "vertex_ai",
"server.address": "us-central1-aiplatform.googleapis.com",
"server.port": 443,
}
assert_span_error(spans[0])
@pytest.mark.vcr()
def test_generate_content_missing_model(
span_exporter: InMemorySpanExporter,
generate_content: callable,
instrument_with_content: VertexAIInstrumentor,
):
model = GenerativeModel("gemini-does-not-exist")
try:
generate_content(
model,
[Content(role="user", parts=[Part.from_text("Say this is a test")])],
)
except NotFound:
pass
spans = span_exporter.get_finished_spans()
assert len(spans) == 1
assert spans[0].name == "chat gemini-does-not-exist"
# Captures invalid params
assert dict(spans[0].attributes) == {
"gen_ai.operation.name": "chat",
"gen_ai.request.model": "gemini-does-not-exist",
"gen_ai.system": "vertex_ai",
"server.address": "us-central1-aiplatform.googleapis.com",
"server.port": 443,
}
assert_span_error(spans[0])
@pytest.mark.vcr()
def test_generate_content_invalid_temperature(
span_exporter: InMemorySpanExporter,
generate_content: callable,
instrument_with_content: VertexAIInstrumentor,
):
model = GenerativeModel("gemini-2.5-pro")
try:
# Temperature out of range causes error
generate_content(
model,
[Content(role="user", parts=[Part.from_text("Say this is a test")])],
generation_config=GenerationConfig(temperature=1000),
)
except BadRequest:
pass
spans = span_exporter.get_finished_spans()
assert len(spans) == 1
assert spans[0].name == "chat gemini-2.5-pro"
assert dict(spans[0].attributes) == {
"gen_ai.operation.name": "chat",
"gen_ai.request.model": "gemini-2.5-pro",
"gen_ai.request.temperature": 1000.0,
"gen_ai.system": "vertex_ai",
"server.address": "us-central1-aiplatform.googleapis.com",
"server.port": 443,
}
assert_span_error(spans[0])
@pytest.mark.vcr()
def test_generate_content_invalid_role(
log_exporter: InMemoryLogRecordExporter,
generate_content: callable,
instrument_with_content: VertexAIInstrumentor,
):
model = GenerativeModel("gemini-2.5-pro")
try:
# Fails because role must be "user" or "model"
generate_content(
model,
[
Content(
role="invalid_role",
parts=[Part.from_text("Say this is a test")],
)
],
)
except BadRequest:
pass
# Emits the faulty content which caused the request to fail
logs = log_exporter.get_finished_logs()
assert len(logs) == 1
log = logs[0].log_record
assert log.attributes == {
"gen_ai.system": "vertex_ai",
}
assert log.event_name == "gen_ai.user.message"
assert log.body == {
"content": [{"text": "Say this is a test"}],
"role": "invalid_role",
}
@pytest.mark.vcr()
def test_generate_content_extra_params(
span_exporter,
instrument_no_content,
generate_content: callable,
):
generation_config = GenerationConfig(
top_k=2,
top_p=0.95,
temperature=0.2,
stop_sequences=["\n\n\n"],
max_output_tokens=5,
presence_penalty=-1.5,
frequency_penalty=1.0,
seed=12345,
)
model = GenerativeModel("gemini-2.5-pro")
generate_content(
model,
[
Content(role="user", parts=[Part.from_text("Say this is a test")]),
],
generation_config=generation_config,
)
spans = span_exporter.get_finished_spans()
assert len(spans) == 1
assert dict(spans[0].attributes) == {
"gen_ai.operation.name": "chat",
"gen_ai.request.frequency_penalty": 1.0,
"gen_ai.request.max_tokens": 5,
"gen_ai.request.seed": 12345,
"gen_ai.request.model": "gemini-2.5-pro",
"gen_ai.request.presence_penalty": -1.5,
"gen_ai.request.stop_sequences": ("\n\n\n",),
"gen_ai.request.temperature": 0.20000000298023224,
"gen_ai.request.top_p": 0.949999988079071,
"gen_ai.response.finish_reasons": ("length",),
"gen_ai.response.model": "gemini-2.5-pro",
"gen_ai.system": "vertex_ai",
"gen_ai.usage.input_tokens": 5,
"gen_ai.usage.output_tokens": 0,
"server.address": "us-central1-aiplatform.googleapis.com",
"server.port": 443,
}
def assert_span_error(span: ReadableSpan) -> None:
# Sets error status
assert span.status.status_code == StatusCode.ERROR
# TODO: check thate error.type is set
# https://github.com/open-telemetry/semantic-conventions/blob/main/docs/gen-ai/gen-ai-spans.md
# Records exception event
error_events = [e for e in span.events if e.name == "exception"]
assert error_events != []
@pytest.mark.vcr()
def test_generate_content_all_events(
log_exporter: InMemoryLogRecordExporter,
generate_content: callable,
instrument_with_content: VertexAIInstrumentor,
):
generate_content_all_input_events(
GenerativeModel(
"gemini-2.5-pro",
system_instruction=Part.from_text("You are a clever language model"),
),
log_exporter,
instrument_with_content,
)
@pytest.mark.vcr()
def test_preview_generate_content_all_input_events(
log_exporter: InMemoryLogRecordExporter,
generate_content: callable,
instrument_with_content: VertexAIInstrumentor,
):
generate_content_all_input_events(
PreviewGenerativeModel(
"gemini-2.5-pro",
system_instruction=Part.from_text("You are a clever language model"),
),
log_exporter,
instrument_with_content,
)
def generate_content_all_input_events(
model: GenerativeModel | PreviewGenerativeModel,
log_exporter: InMemoryLogRecordExporter,
instrument_with_content: VertexAIInstrumentor,
):
model.generate_content(
[
Content(role="user", parts=[Part.from_text("My name is OpenTelemetry")]),
Content(role="model", parts=[Part.from_text("Hello OpenTelemetry!")]),
Content(
role="user",
parts=[Part.from_text("Address me by name and say this is a test")],
),
],
generation_config=GenerationConfig(seed=12345, response_mime_type="text/plain"),
)
# Emits a system event, 2 users events, an assistant event, and the choice (response) event
logs = log_exporter.get_finished_logs()
assert len(logs) == 5
system_log, user_log1, assistant_log, user_log2, choice_log = [log_data.log_record for log_data in logs]
assert system_log.attributes == {"gen_ai.system": "vertex_ai"}
assert system_log.event_name == "gen_ai.system.message"
assert system_log.body == {
"content": [{"text": "You are a clever language model"}],
# The API only allows user and model, so system instruction is considered a user role
"role": "user",
}
assert user_log1.attributes == {"gen_ai.system": "vertex_ai"}
assert user_log1.event_name == "gen_ai.user.message"
assert user_log1.body == {
"content": [{"text": "My name is OpenTelemetry"}],
"role": "user",
}
assert assistant_log.attributes == {"gen_ai.system": "vertex_ai"}
assert assistant_log.event_name == "gen_ai.assistant.message"
assert assistant_log.body == {
"content": [{"text": "Hello OpenTelemetry!"}],
"role": "model",
}
assert user_log2.attributes == {"gen_ai.system": "vertex_ai"}
assert user_log2.event_name == "gen_ai.user.message"
assert user_log2.body == {
"content": [{"text": "Address me by name and say this is a test"}],
"role": "user",
}
assert choice_log.attributes == {"gen_ai.system": "vertex_ai"}
assert choice_log.event_name == "gen_ai.choice"
assert choice_log.body == {
"finish_reason": "stop",
"index": 0,
"message": {
"content": [{"text": "OpenTelemetry, this is a test."}],
"role": "model",
},
}
test_chat_completions_experimental.py 0000664 0000000 0000000 00000040500 15270700723 0044656 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-vertexai/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
from __future__ import annotations
import pytest
from google.api_core.exceptions import BadRequest, NotFound
from vertexai.generative_models import (
Content,
GenerationConfig,
GenerativeModel,
Image,
Part,
)
from vertexai.preview.generative_models import (
GenerativeModel as PreviewGenerativeModel,
)
from opentelemetry.instrumentation.vertexai import VertexAIInstrumentor
# Backward compatibility for InMemoryLogExporter -> InMemoryLogRecordExporter rename
try:
from opentelemetry.sdk._logs._internal.export.in_memory_log_exporter import ( # pylint: disable=no-name-in-module
InMemoryLogRecordExporter,
)
except ImportError:
# Fallback to old name for compatibility with older SDK versions
from opentelemetry.sdk._logs._internal.export.in_memory_log_exporter import (
InMemoryLogExporter as InMemoryLogRecordExporter,
)
from opentelemetry.sdk.trace import ReadableSpan
from opentelemetry.sdk.trace.export.in_memory_span_exporter import (
InMemorySpanExporter,
)
from opentelemetry.trace import StatusCode
@pytest.mark.vcr()
def test_generate_content_with_files(
span_exporter: InMemorySpanExporter,
log_exporter: InMemoryLogRecordExporter,
generate_content: callable,
instrument_with_experimental_semconvs: VertexAIInstrumentor,
):
model = GenerativeModel("gemini-2.5-pro")
generate_content(
model,
[
Content(
role="user",
parts=[
Part.from_text("Say this is a test"),
Part.from_uri(
mime_type="image/jpeg",
uri="https://images.pdimagearchive.org/collections/microscopic-delights/1lede-0021.jpg",
),
Part.from_image(
Image.from_bytes(
"iVBORw0KGgoAAAANSUhEUgAAAAUAAAAFCAYAAACNbyblAAAAHElEQVQI12P4//8/w38GIAXDIBKE0DHxgljNBAAO9TXL0Y4OHwAAAABJRU5ErkJggg=="
)
),
],
),
],
)
# Emits span
spans = span_exporter.get_finished_spans()
assert len(spans) == 1
assert spans[0].name == "chat gemini-2.5-pro"
assert dict(spans[0].attributes) == {
"gen_ai.operation.name": "chat",
"gen_ai.request.model": "gemini-2.5-pro",
"gen_ai.response.finish_reasons": ("stop",),
"gen_ai.response.model": "gemini-2.5-pro",
"gen_ai.usage.input_tokens": 521,
"gen_ai.usage.output_tokens": 5,
"server.address": "us-central1-aiplatform.googleapis.com",
"server.port": 443,
"gen_ai.input.messages": '[{"role":"user","parts":[{"content":"Say this is a test","type":"text"},{"mime_type":"image/jpeg","modality":"image","uri":"https://images.pdimagearchive.org/collections/microscopic-delights/1lede-0021.jpg","type":"uri"},{"mime_type":"image/jpeg","modality":"image","content":"iVBORw0KGgoAAAANSUhEUgAAAAUAAAAFCAYAAACNbyblAAAAHElEQVQI12P4//8/w38GIAXDIBKE0DHxgljNBAAO9TXL0Y4OHwAAAABJRU5ErkJggg==","type":"blob"}]}]',
"gen_ai.output.messages": '[{"role":"model","parts":[{"content":"This is a test.","type":"text"}],"finish_reason":"stop"}]',
}
logs = log_exporter.get_finished_logs()
assert len(logs) == 1
log = logs[0].log_record
assert log.attributes == {
"server.address": "us-central1-aiplatform.googleapis.com",
"server.port": 443,
"gen_ai.operation.name": "chat",
"gen_ai.request.model": "gemini-2.5-pro",
"gen_ai.response.model": "gemini-2.5-pro",
"gen_ai.response.finish_reasons": ("stop",),
"gen_ai.usage.input_tokens": 521,
"gen_ai.usage.output_tokens": 5,
"gen_ai.input.messages": (
{
"role": "user",
"parts": (
{"content": "Say this is a test", "type": "text"},
{
"mime_type": "image/jpeg",
"modality": "image",
"uri": "https://images.pdimagearchive.org/collections/microscopic-delights/1lede-0021.jpg",
"type": "uri",
},
{
"mime_type": "image/jpeg",
"modality": "image",
"content": b"\x89PNG\r\n\x1a\n\x00\x00\x00\rIHDR\x00\x00\x00\x05\x00\x00\x00\x05\x08\x06\x00\x00\x00\x8do&\xe5\x00\x00\x00\x1cIDAT\x08\xd7c\xf8\xff\xff?\xc3\x7f\x06 \x05\xc3 \x12\x84\xd01\xf1\x82X\xcd\x04\x00\x0e\xf55\xcb\xd1\x8e\x0e\x1f\x00\x00\x00\x00IEND\xaeB`\x82",
"type": "blob",
},
),
},
),
"gen_ai.output.messages": (
{
"role": "model",
"parts": ({"content": "This is a test.", "type": "text"},),
"finish_reason": "stop",
},
),
}
@pytest.mark.vcr()
def test_generate_content_without_events(
span_exporter: InMemorySpanExporter,
log_exporter: InMemoryLogRecordExporter,
generate_content: callable,
instrument_with_experimental_semconvs: VertexAIInstrumentor,
):
model = GenerativeModel("gemini-2.5-pro")
generate_content(
model,
[
Content(role="user", parts=[Part.from_text("Say this is a test")]),
],
)
# Emits span
spans = span_exporter.get_finished_spans()
assert len(spans) == 1
assert spans[0].name == "chat gemini-2.5-pro"
assert dict(spans[0].attributes) == {
"gen_ai.operation.name": "chat",
"gen_ai.output.messages": '[{"role":"model","parts":[{"content":"This is a test.","type":"text"}],"finish_reason":"stop"}]',
"gen_ai.input.messages": '[{"role":"user","parts":[{"content":"Say this is a test","type":"text"}]}]',
"gen_ai.request.model": "gemini-2.5-pro",
"gen_ai.response.finish_reasons": ("stop",),
"gen_ai.response.model": "gemini-2.5-pro",
"gen_ai.usage.input_tokens": 5,
"gen_ai.usage.output_tokens": 5,
"server.address": "us-central1-aiplatform.googleapis.com",
"server.port": 443,
}
logs = log_exporter.get_finished_logs()
assert len(logs) == 1
log = logs[0].log_record
print(log.attributes)
assert log.attributes == {
"gen_ai.operation.name": "chat",
"gen_ai.request.model": "gemini-2.5-pro",
"server.address": "us-central1-aiplatform.googleapis.com",
"server.port": 443,
"gen_ai.response.model": "gemini-2.5-pro",
"gen_ai.response.finish_reasons": ("stop",),
"gen_ai.usage.input_tokens": 5,
"gen_ai.usage.output_tokens": 5,
"gen_ai.input.messages": (
{
"role": "user",
"parts": ({"content": "Say this is a test", "type": "text"},),
},
),
"gen_ai.output.messages": (
{
"role": "model",
"parts": ({"content": "This is a test.", "type": "text"},),
"finish_reason": "stop",
},
),
}
@pytest.mark.vcr()
def test_generate_content_empty_model(
span_exporter: InMemorySpanExporter,
generate_content: callable,
instrument_with_experimental_semconvs: VertexAIInstrumentor,
):
model = GenerativeModel("")
try:
generate_content(
model,
[Content(role="user", parts=[Part.from_text("Say this is a test")])],
)
except ValueError:
pass
spans = span_exporter.get_finished_spans()
assert len(spans) == 1
assert spans[0].name == "chat"
# Captures invalid params
assert dict(spans[0].attributes) == {
"gen_ai.operation.name": "chat",
"gen_ai.request.model": "",
"server.address": "us-central1-aiplatform.googleapis.com",
"server.port": 443,
"gen_ai.input.messages": '[{"role":"user","parts":[{"content":"Say this is a test","type":"text"}]}]',
}
assert_span_error(spans[0])
@pytest.mark.vcr()
def test_generate_content_missing_model(
span_exporter: InMemorySpanExporter,
generate_content: callable,
instrument_with_experimental_semconvs: VertexAIInstrumentor,
):
model = GenerativeModel("gemini-does-not-exist")
try:
generate_content(
model,
[Content(role="user", parts=[Part.from_text("Say this is a test")])],
)
except NotFound:
pass
spans = span_exporter.get_finished_spans()
assert len(spans) == 1
assert spans[0].name == "chat gemini-does-not-exist"
# Captures invalid params
assert dict(spans[0].attributes) == {
"gen_ai.operation.name": "chat",
"gen_ai.request.model": "gemini-does-not-exist",
"server.address": "us-central1-aiplatform.googleapis.com",
"server.port": 443,
"gen_ai.input.messages": '[{"role":"user","parts":[{"content":"Say this is a test","type":"text"}]}]',
}
assert_span_error(spans[0])
@pytest.mark.vcr()
def test_generate_content_invalid_temperature(
span_exporter: InMemorySpanExporter,
generate_content: callable,
instrument_with_experimental_semconvs: VertexAIInstrumentor,
):
model = GenerativeModel("gemini-2.5-pro")
try:
# Temperature out of range causes error
generate_content(
model,
[Content(role="user", parts=[Part.from_text("Say this is a test")])],
generation_config=GenerationConfig(temperature=1000),
)
except BadRequest:
pass
spans = span_exporter.get_finished_spans()
assert len(spans) == 1
assert spans[0].name == "chat gemini-2.5-pro"
assert dict(spans[0].attributes) == {
"gen_ai.operation.name": "chat",
"gen_ai.request.model": "gemini-2.5-pro",
"gen_ai.request.temperature": 1000.0,
"server.address": "us-central1-aiplatform.googleapis.com",
"server.port": 443,
"gen_ai.input.messages": '[{"role":"user","parts":[{"content":"Say this is a test","type":"text"}]}]',
}
assert_span_error(spans[0])
@pytest.mark.vcr()
def test_generate_content_invalid_role(
log_exporter: InMemoryLogRecordExporter,
generate_content: callable,
instrument_with_experimental_semconvs: VertexAIInstrumentor,
):
model = GenerativeModel("gemini-2.5-pro")
try:
# Fails because role must be "user" or "model"
generate_content(
model,
[
Content(
role="invalid_role",
parts=[Part.from_text("Say this is a test")],
)
],
)
except BadRequest:
pass
# Emits the faulty content which caused the request to fail
logs = log_exporter.get_finished_logs()
assert len(logs) == 1
log = logs[0].log_record
assert log.attributes == {
"gen_ai.operation.name": "chat",
"gen_ai.request.model": "gemini-2.5-pro",
"server.address": "us-central1-aiplatform.googleapis.com",
"server.port": 443,
"gen_ai.input.messages": (
{
"role": "invalid_role",
"parts": ({"type": "text", "content": "Say this is a test"},),
},
),
}
@pytest.mark.vcr()
def test_generate_content_extra_params(
span_exporter,
instrument_no_content_with_experimental_semconvs,
generate_content: callable,
):
generation_config = GenerationConfig(
top_k=2,
top_p=0.95,
temperature=0.2,
stop_sequences=["\n\n\n"],
max_output_tokens=5,
presence_penalty=-1.5,
frequency_penalty=1.0,
seed=12345,
)
model = GenerativeModel("gemini-2.5-pro")
generate_content(
model,
[
Content(role="user", parts=[Part.from_text("Say this is a test")]),
],
generation_config=generation_config,
)
spans = span_exporter.get_finished_spans()
assert len(spans) == 1
assert dict(spans[0].attributes) == {
"gen_ai.operation.name": "chat",
"gen_ai.request.frequency_penalty": 1.0,
"gen_ai.request.max_tokens": 5,
"gen_ai.request.model": "gemini-2.5-pro",
"gen_ai.request.presence_penalty": -1.5,
"gen_ai.request.stop_sequences": ("\n\n\n",),
"gen_ai.request.temperature": 0.20000000298023224,
"gen_ai.request.top_p": 0.949999988079071,
"gen_ai.response.finish_reasons": ("length",),
"gen_ai.response.model": "gemini-2.5-pro",
"gen_ai.request.seed": 12345,
"gen_ai.usage.input_tokens": 5,
"gen_ai.usage.output_tokens": 0,
"server.address": "us-central1-aiplatform.googleapis.com",
"server.port": 443,
}
def assert_span_error(span: ReadableSpan) -> None:
# Sets error status
assert span.status.status_code == StatusCode.ERROR
# TODO: check thate error.type is set
# https://github.com/open-telemetry/semantic-conventions/blob/main/docs/gen-ai/gen-ai-spans.md
# Records exception event
error_events = [e for e in span.events if e.name == "exception"]
assert error_events != []
@pytest.mark.vcr()
def test_generate_content_all_events(
log_exporter: InMemoryLogRecordExporter,
generate_content: callable,
instrument_with_experimental_semconvs: VertexAIInstrumentor,
):
generate_content_all_input_events(
GenerativeModel(
"gemini-2.5-pro",
system_instruction=Part.from_text("You are a clever language model"),
),
log_exporter,
instrument_with_experimental_semconvs,
)
@pytest.mark.vcr()
def test_preview_generate_content_all_input_events(
log_exporter: InMemoryLogRecordExporter,
generate_content: callable,
instrument_with_experimental_semconvs: VertexAIInstrumentor,
):
generate_content_all_input_events(
PreviewGenerativeModel(
"gemini-2.5-pro",
system_instruction=Part.from_text("You are a clever language model"),
),
log_exporter,
instrument_with_experimental_semconvs,
)
def generate_content_all_input_events(
model: GenerativeModel | PreviewGenerativeModel,
log_exporter: InMemoryLogRecordExporter,
instrument_with_experimental_semconvs: VertexAIInstrumentor,
):
model.generate_content(
[
Content(role="user", parts=[Part.from_text("My name is OpenTelemetry")]),
Content(role="model", parts=[Part.from_text("Hello OpenTelemetry!")]),
Content(
role="user",
parts=[Part.from_text("Address me by name and say this is a test")],
),
],
generation_config=GenerationConfig(seed=12345, response_mime_type="text/plain"),
)
# Emits a single log.
logs = log_exporter.get_finished_logs()
assert len(logs) == 1
log = logs[0].log_record
assert log.attributes == {
"gen_ai.operation.name": "chat",
"gen_ai.request.model": "gemini-2.5-pro",
"gen_ai.request.seed": 12345,
"gen_ai.output.type": "text",
"server.address": "us-central1-aiplatform.googleapis.com",
"server.port": 443,
"gen_ai.response.model": "gemini-2.5-pro",
"gen_ai.response.finish_reasons": ("stop",),
"gen_ai.usage.input_tokens": 25,
"gen_ai.usage.output_tokens": 8,
"gen_ai.system_instructions": ({"type": "text", "content": "You are a clever language model"},),
"gen_ai.input.messages": (
{
"role": "user",
"parts": (
{
"type": "text",
"content": "My name is OpenTelemetry",
},
),
},
{
"role": "model",
"parts": ({"type": "text", "content": "Hello OpenTelemetry!"},),
},
{
"role": "user",
"parts": (
{
"type": "text",
"content": "Address me by name and say this is a test",
},
),
},
),
"gen_ai.output.messages": (
{
"role": "model",
"parts": (
{
"type": "text",
"content": "OpenTelemetry, this is a test.",
},
),
"finish_reason": "stop",
},
),
}
test_function_calling.py 0000664 0000000 0000000 00000023267 15270700723 0042077 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-vertexai/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
import pytest
from tests.shared_test_utils import (
ask_about_weather,
ask_about_weather_function_response,
)
from opentelemetry.instrumentation.vertexai import VertexAIInstrumentor
# Backward compatibility for InMemoryLogExporter -> InMemoryLogRecordExporter rename
try:
from opentelemetry.sdk._logs._internal.export.in_memory_log_exporter import ( # pylint: disable=no-name-in-module
InMemoryLogRecordExporter,
)
except ImportError:
# Fallback to old name for compatibility with older SDK versions
from opentelemetry.sdk._logs._internal.export.in_memory_log_exporter import (
InMemoryLogExporter as InMemoryLogRecordExporter,
)
from opentelemetry.sdk.trace.export.in_memory_span_exporter import (
InMemorySpanExporter,
)
@pytest.mark.vcr()
def test_function_call_choice(
span_exporter: InMemorySpanExporter,
log_exporter: InMemoryLogRecordExporter,
instrument_with_content: VertexAIInstrumentor,
generate_content: callable,
):
ask_about_weather(generate_content)
# Emits span
spans = span_exporter.get_finished_spans()
assert len(spans) == 1
assert spans[0].name == "chat gemini-2.5-pro"
assert dict(spans[0].attributes) == {
"gen_ai.operation.name": "chat",
"gen_ai.request.model": "gemini-2.5-pro",
"gen_ai.response.finish_reasons": ("stop",),
"gen_ai.response.model": "gemini-2.5-pro",
"gen_ai.system": "vertex_ai",
"gen_ai.usage.input_tokens": 74,
"gen_ai.usage.output_tokens": 16,
"server.address": "us-central1-aiplatform.googleapis.com",
"server.port": 443,
}
# Emits user and choice events
logs = log_exporter.get_finished_logs()
assert len(logs) == 2
user_log, choice_log = [log_data.log_record for log_data in logs]
assert user_log.attributes == {"gen_ai.system": "vertex_ai"}
assert user_log.event_name == "gen_ai.user.message"
assert user_log.body == {
"content": [{"text": "Get weather details in New Delhi and San Francisco?"}],
"role": "user",
}
assert choice_log.attributes == {"gen_ai.system": "vertex_ai"}
assert choice_log.event_name == "gen_ai.choice"
assert choice_log.body == {
"finish_reason": "stop",
"index": 0,
"message": {
"content": [
{
"function_call": {
"args": {"location": "New Delhi"},
"name": "get_current_weather",
}
},
{
"function_call": {
"args": {"location": "San Francisco"},
"name": "get_current_weather",
}
},
],
"role": "model",
},
"tool_calls": [
{
"function": {
"arguments": {"location": "New Delhi"},
"name": "get_current_weather",
},
"id": "get_current_weather_0",
"type": "function",
},
{
"function": {
"arguments": {"location": "San Francisco"},
"name": "get_current_weather",
},
"id": "get_current_weather_1",
"type": "function",
},
],
}
@pytest.mark.vcr()
def test_function_call_choice_no_content(
log_exporter: InMemoryLogRecordExporter,
instrument_no_content: VertexAIInstrumentor,
generate_content: callable,
):
ask_about_weather(generate_content)
# Emits user and choice events
logs = log_exporter.get_finished_logs()
assert len(logs) == 2
user_log, choice_log = [log_data.log_record for log_data in logs]
assert user_log.attributes == {"gen_ai.system": "vertex_ai"}
assert user_log.event_name == "gen_ai.user.message"
assert user_log.body == {
"role": "user",
}
assert choice_log.attributes == {"gen_ai.system": "vertex_ai"}
assert choice_log.event_name == "gen_ai.choice"
assert choice_log.body == {
"finish_reason": "stop",
"index": 0,
"message": {"role": "model"},
"tool_calls": [
{
"function": {"name": "get_current_weather"},
"id": "get_current_weather_0",
"type": "function",
},
{
"function": {"name": "get_current_weather"},
"id": "get_current_weather_1",
"type": "function",
},
],
}
@pytest.mark.vcr()
def test_tool_events(
span_exporter: InMemorySpanExporter,
log_exporter: InMemoryLogRecordExporter,
instrument_with_content: VertexAIInstrumentor,
generate_content: callable,
):
ask_about_weather_function_response(generate_content)
# Emits span
spans = span_exporter.get_finished_spans()
assert len(spans) == 1
assert spans[0].name == "chat gemini-2.5-pro"
assert dict(spans[0].attributes) == {
"gen_ai.operation.name": "chat",
"gen_ai.request.model": "gemini-2.5-pro",
"gen_ai.response.finish_reasons": ("stop",),
"gen_ai.response.model": "gemini-2.5-pro",
"gen_ai.system": "vertex_ai",
"gen_ai.usage.input_tokens": 128,
"gen_ai.usage.output_tokens": 26,
"server.address": "us-central1-aiplatform.googleapis.com",
"server.port": 443,
}
logs = log_exporter.get_finished_logs()
# Emits user, assistant, two tool, and choice events
assert len(logs) == 5
user_log, assistant_log, tool_log1, tool_log2, choice_log = [log_data.log_record for log_data in logs]
assert user_log.attributes == {"gen_ai.system": "vertex_ai"}
assert user_log.event_name == "gen_ai.user.message"
assert user_log.body == {
"content": [{"text": "Get weather details in New Delhi and San Francisco?"}],
"role": "user",
}
assert assistant_log.attributes == {"gen_ai.system": "vertex_ai"}
assert assistant_log.event_name == "gen_ai.assistant.message"
assert assistant_log.body == {
"role": "model",
"content": [
{
"function_call": {
"name": "get_current_weather",
"args": {"location": "New Delhi"},
}
},
{
"function_call": {
"name": "get_current_weather",
"args": {"location": "San Francisco"},
}
},
],
}
assert tool_log1.attributes == {"gen_ai.system": "vertex_ai"}
assert tool_log1.event_name == "gen_ai.tool.message"
assert tool_log1.body == {
"role": "user",
"id": "get_current_weather_0",
"content": {"content": '{"temperature": 35, "unit": "C"}'},
}
assert tool_log2.attributes == {"gen_ai.system": "vertex_ai"}
assert tool_log2.event_name == "gen_ai.tool.message"
assert tool_log2.body == {
"role": "user",
"id": "get_current_weather_1",
"content": {"content": '{"temperature": 25, "unit": "C"}'},
}
assert choice_log.attributes == {"gen_ai.system": "vertex_ai"}
assert choice_log.event_name == "gen_ai.choice"
assert choice_log.body == {
"finish_reason": "stop",
"index": 0,
"message": {
"content": [{"text": "The current temperature in New Delhi is 35°C, and in San Francisco, it is 25°C."}],
"role": "model",
},
}
@pytest.mark.vcr()
def test_tool_events_no_content(
span_exporter: InMemorySpanExporter,
log_exporter: InMemoryLogRecordExporter,
instrument_no_content: VertexAIInstrumentor,
generate_content: callable,
):
ask_about_weather_function_response(generate_content)
# Emits span
spans = span_exporter.get_finished_spans()
assert len(spans) == 1
assert spans[0].name == "chat gemini-2.5-pro"
assert dict(spans[0].attributes) == {
"gen_ai.operation.name": "chat",
"gen_ai.request.model": "gemini-2.5-pro",
"gen_ai.response.finish_reasons": ("stop",),
"gen_ai.response.model": "gemini-2.5-pro",
"gen_ai.system": "vertex_ai",
"gen_ai.usage.input_tokens": 128,
"gen_ai.usage.output_tokens": 22,
"server.address": "us-central1-aiplatform.googleapis.com",
"server.port": 443,
}
logs = log_exporter.get_finished_logs()
# Emits user, assistant, two tool, and choice events
assert len(logs) == 5
user_log, assistant_log, tool_log1, tool_log2, choice_log = [log_data.log_record for log_data in logs]
assert user_log.attributes == {"gen_ai.system": "vertex_ai"}
assert user_log.event_name == "gen_ai.user.message"
assert user_log.body == {"role": "user"}
assert assistant_log.attributes == {"gen_ai.system": "vertex_ai"}
assert assistant_log.event_name == "gen_ai.assistant.message"
assert assistant_log.body == {"role": "model"}
assert tool_log1.attributes == {
"gen_ai.system": "vertex_ai",
}
assert tool_log1.event_name == "gen_ai.tool.message"
assert tool_log1.body == {
"role": "user",
"id": "get_current_weather_0",
}
assert tool_log1.event_name == "gen_ai.tool.message"
assert tool_log2.attributes == {"gen_ai.system": "vertex_ai"}
assert tool_log2.body == {
"role": "user",
"id": "get_current_weather_1",
}
assert tool_log2.event_name == "gen_ai.tool.message"
assert choice_log.attributes == {"gen_ai.system": "vertex_ai"}
assert choice_log.event_name == "gen_ai.choice"
assert choice_log.body == {
"finish_reason": "stop",
"index": 0,
"message": {"role": "model"},
}
test_function_calling_experimental.py 0000664 0000000 0000000 00000032107 15270700723 0044645 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-vertexai/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
import json
import time
from typing import Any
import fsspec
import pytest
from tests.shared_test_utils import (
ask_about_weather,
ask_about_weather_function_response,
)
from opentelemetry.instrumentation.vertexai import VertexAIInstrumentor
# Backward compatibility for InMemoryLogExporter -> InMemoryLogRecordExporter rename
try:
from opentelemetry.sdk._logs._internal.export.in_memory_log_exporter import ( # pylint: disable=no-name-in-module
InMemoryLogRecordExporter,
)
except ImportError:
# Fallback to old name for compatibility with older SDK versions
from opentelemetry.sdk._logs._internal.export.in_memory_log_exporter import (
InMemoryLogExporter as InMemoryLogRecordExporter,
)
from opentelemetry.sdk.trace.export.in_memory_span_exporter import (
InMemorySpanExporter,
)
def test_function_call_choice(
span_exporter: InMemorySpanExporter,
log_exporter: InMemoryLogRecordExporter,
instrument_with_experimental_semconvs: VertexAIInstrumentor,
generate_content: callable,
):
ask_about_weather(generate_content)
# Emits span
spans = span_exporter.get_finished_spans()
assert len(spans) == 1
assert spans[0].name == "chat gemini-2.5-pro"
assert dict(spans[0].attributes) == {
"gen_ai.operation.name": "chat",
"gen_ai.request.model": "gemini-2.5-pro",
"gen_ai.response.finish_reasons": ("stop",),
"gen_ai.response.model": "gemini-2.5-pro",
"gen_ai.usage.input_tokens": 74,
"gen_ai.usage.output_tokens": 16,
"server.address": "us-central1-aiplatform.googleapis.com",
"gen_ai.input.messages": '[{"role":"user","parts":[{"content":"Get weather details in New Delhi and San Francisco?","type":"text"}]}]',
"gen_ai.output.messages": '[{"role":"model","parts":[{"arguments":{"location":"New Delhi"},"name":"get_current_weather","id":"get_current_weather_0","type":"tool_call"},{"arguments":{"location":"San Francisco"},"name":"get_current_weather","id":"get_current_weather_1","type":"tool_call"}],"finish_reason":"stop"}]',
"server.port": 443,
}
# Emits user and choice events
logs = log_exporter.get_finished_logs()
assert len(logs) == 1
log = logs[0].log_record
assert log.attributes == {
"gen_ai.operation.name": "chat",
"gen_ai.request.model": "gemini-2.5-pro",
"server.address": "us-central1-aiplatform.googleapis.com",
"server.port": 443,
"gen_ai.response.model": "gemini-2.5-pro",
"gen_ai.response.finish_reasons": ("stop",),
"gen_ai.usage.input_tokens": 74,
"gen_ai.usage.output_tokens": 16,
"gen_ai.input.messages": (
{
"role": "user",
"parts": (
{
"type": "text",
"content": "Get weather details in New Delhi and San Francisco?",
},
),
},
),
"gen_ai.output.messages": (
{
"role": "model",
"parts": (
{
"type": "tool_call",
"arguments": {"location": "New Delhi"},
"name": "get_current_weather",
"id": "get_current_weather_0",
},
{
"type": "tool_call",
"arguments": {"location": "San Francisco"},
"name": "get_current_weather",
"id": "get_current_weather_1",
},
),
"finish_reason": "stop",
},
),
}
@pytest.mark.vcr()
def test_function_call_choice_no_content(
log_exporter: InMemoryLogRecordExporter,
instrument_no_content_with_experimental_semconvs: VertexAIInstrumentor,
generate_content: callable,
):
ask_about_weather(generate_content)
# Emits user and choice events
logs = log_exporter.get_finished_logs()
assert len(logs) == 1
log = logs[0].log_record
assert log.attributes == {
"gen_ai.operation.name": "chat",
"gen_ai.request.model": "gemini-2.5-pro",
"server.address": "us-central1-aiplatform.googleapis.com",
"server.port": 443,
"gen_ai.response.model": "gemini-2.5-pro",
"gen_ai.response.finish_reasons": ("stop",),
"gen_ai.usage.input_tokens": 74,
"gen_ai.usage.output_tokens": 16,
}
@pytest.mark.vcr()
def test_tool_events(
span_exporter: InMemorySpanExporter,
log_exporter: InMemoryLogRecordExporter,
instrument_with_experimental_semconvs: VertexAIInstrumentor,
generate_content: callable,
):
ask_about_weather_function_response(generate_content)
# Emits span
spans = span_exporter.get_finished_spans()
assert len(spans) == 1
assert spans[0].name == "chat gemini-2.5-pro"
assert dict(spans[0].attributes) == {
"gen_ai.operation.name": "chat",
"gen_ai.request.model": "gemini-2.5-pro",
"gen_ai.response.finish_reasons": ("stop",),
"gen_ai.response.model": "gemini-2.5-pro",
"gen_ai.usage.input_tokens": 128,
"gen_ai.usage.output_tokens": 26,
"server.address": "us-central1-aiplatform.googleapis.com",
"server.port": 443,
"gen_ai.input.messages": '[{"role":"user","parts":[{"content":"Get weather details in New Delhi and San Francisco?","type":"text"}]},{"role":"model","parts":[{"arguments":{"location":"New Delhi"},"name":"get_current_weather","id":"get_current_weather_0","type":"tool_call"},{"arguments":{"location":"San Francisco"},"name":"get_current_weather","id":"get_current_weather_1","type":"tool_call"}]},{"role":"user","parts":[{"response":{"content":"{\\"temperature\\": 35, \\"unit\\": \\"C\\"}"},"id":"get_current_weather_0","type":"tool_call_response"},{"response":{"content":"{\\"temperature\\": 25, \\"unit\\": \\"C\\"}"},"id":"get_current_weather_1","type":"tool_call_response"}]}]',
"gen_ai.output.messages": '[{"role":"model","parts":[{"content":"The current temperature in New Delhi is 35\\u00b0C, and in San Francisco, it is 25\\u00b0C.","type":"text"}],"finish_reason":"stop"}]',
}
logs = log_exporter.get_finished_logs()
assert len(logs) == 1
log = logs[0].log_record
assert log.attributes == {
"gen_ai.operation.name": "chat",
"gen_ai.request.model": "gemini-2.5-pro",
"server.address": "us-central1-aiplatform.googleapis.com",
"server.port": 443,
"gen_ai.response.model": "gemini-2.5-pro",
"gen_ai.response.finish_reasons": ("stop",),
"gen_ai.usage.input_tokens": 128,
"gen_ai.usage.output_tokens": 26,
"gen_ai.input.messages": (
{
"role": "user",
"parts": (
{
"type": "text",
"content": "Get weather details in New Delhi and San Francisco?",
},
),
},
{
"role": "model",
"parts": (
{
"type": "tool_call",
"arguments": {"location": "New Delhi"},
"name": "get_current_weather",
"id": "get_current_weather_0",
},
{
"type": "tool_call",
"arguments": {"location": "San Francisco"},
"name": "get_current_weather",
"id": "get_current_weather_1",
},
),
},
{
"role": "user",
"parts": (
{
"type": "tool_call_response",
"response": {"content": '{"temperature": 35, "unit": "C"}'},
"id": "get_current_weather_0",
},
{
"type": "tool_call_response",
"response": {"content": '{"temperature": 25, "unit": "C"}'},
"id": "get_current_weather_1",
},
),
},
),
"gen_ai.output.messages": (
{
"role": "model",
"parts": (
{
"type": "text",
"content": "The current temperature in New Delhi is 35°C, and in San Francisco, it is 25°C.",
},
),
"finish_reason": "stop",
},
),
}
@pytest.mark.vcr()
def test_tool_events_no_content(
span_exporter: InMemorySpanExporter,
log_exporter: InMemoryLogRecordExporter,
instrument_no_content_with_experimental_semconvs: VertexAIInstrumentor,
generate_content: callable,
):
ask_about_weather_function_response(generate_content)
# Emits span
spans = span_exporter.get_finished_spans()
assert len(spans) == 1
assert spans[0].name == "chat gemini-2.5-pro"
assert dict(spans[0].attributes) == {
"gen_ai.operation.name": "chat",
"gen_ai.request.model": "gemini-2.5-pro",
"gen_ai.response.finish_reasons": ("stop",),
"gen_ai.response.model": "gemini-2.5-pro",
"gen_ai.usage.input_tokens": 128,
"gen_ai.usage.output_tokens": 22,
"server.address": "us-central1-aiplatform.googleapis.com",
"server.port": 443,
}
logs = log_exporter.get_finished_logs()
assert len(logs) == 1
log = logs[0].log_record
assert log.attributes == {
"gen_ai.operation.name": "chat",
"gen_ai.request.model": "gemini-2.5-pro",
"server.address": "us-central1-aiplatform.googleapis.com",
"server.port": 443,
"gen_ai.response.model": "gemini-2.5-pro",
"gen_ai.response.finish_reasons": ("stop",),
"gen_ai.usage.input_tokens": 128,
"gen_ai.usage.output_tokens": 22,
}
def assert_fsspec_equal(path: str, value: Any) -> None:
# Hide this function and its calls from traceback.
__tracebackhide__ = True # pylint: disable=unused-variable
with fsspec.open(path, "r") as file:
assert json.load(file) == value
@pytest.mark.vcr()
def test_tool_events_with_completion_hook(
span_exporter: InMemorySpanExporter,
log_exporter: InMemoryLogRecordExporter,
instrument_with_upload_hook: VertexAIInstrumentor,
generate_content: callable,
):
ask_about_weather_function_response(generate_content)
# Emits span
spans = span_exporter.get_finished_spans()
assert len(spans) == 1
logs = log_exporter.get_finished_logs()
assert len(logs) == 1
# File upload takes a few seconds sometimes.
time.sleep(3)
# Both log and span have the same reference attributes from upload hook
for key in "gen_ai.input.messages_ref", "gen_ai.output.messages_ref":
assert spans[0].attributes.get(key)
assert logs[0].log_record.attributes.get(key)
assert spans[0].attributes[key] == logs[0].log_record.attributes[key]
assert_fsspec_equal(
spans[0].attributes["gen_ai.output.messages_ref"],
[
{
"role": "model",
"parts": [
{
"content": "The weather in New Delhi is 35°C and in San Francisco is 25°C.",
"type": "text",
}
],
"finish_reason": "stop",
}
],
)
assert_fsspec_equal(
spans[0].attributes["gen_ai.input.messages_ref"],
[
{
"parts": [
{
"content": "Get weather details in New Delhi and San Francisco?",
"type": "text",
}
],
"role": "user",
},
{
"parts": [
{
"arguments": {"location": "New Delhi"},
"id": "get_current_weather_0",
"name": "get_current_weather",
"type": "tool_call",
},
{
"arguments": {"location": "San Francisco"},
"id": "get_current_weather_1",
"name": "get_current_weather",
"type": "tool_call",
},
],
"role": "model",
},
{
"parts": [
{
"id": "get_current_weather_0",
"response": {"content": '{"temperature": 35, "unit": "C"}'},
"type": "tool_call_response",
},
{
"id": "get_current_weather_1",
"response": {"content": '{"temperature": 25, "unit": "C"}'},
"type": "tool_call_response",
},
],
"role": "user",
},
],
)
test_instrumentor.py 0000664 0000000 0000000 00000001771 15270700723 0041326 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-vertexai/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
from __future__ import annotations
import pytest
from google.cloud.aiplatform_v1.services.prediction_service import client
from google.cloud.aiplatform_v1beta1.services.prediction_service import (
client as client_v1beta1,
)
from opentelemetry.instrumentation.vertexai import VertexAIInstrumentor
@pytest.fixture(
name="client_class",
params=[
pytest.param(client.PredictionServiceClient, id="v1"),
pytest.param(client_v1beta1.PredictionServiceClient, id="v1beta1"),
],
)
def fixture_client_class(request: pytest.FixtureRequest):
return request.param
def test_instruments(instrument_with_content: VertexAIInstrumentor, client_class):
assert hasattr(client_class.generate_content, "__wrapped__")
def test_uninstruments(instrument_with_content: VertexAIInstrumentor, client_class):
instrument_with_content.uninstrument()
assert not hasattr(client_class.generate_content, "__wrapped__")
test_utils.py 0000664 0000000 0000000 00000003041 15270700723 0037705 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation-genai/opentelemetry-instrumentation-vertexai/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
from google.cloud.aiplatform_v1.types import (
content,
)
from google.cloud.aiplatform_v1beta1.types import (
content as content_v1beta1,
)
from opentelemetry.instrumentation.vertexai.utils import (
_map_finish_reason,
get_server_attributes,
)
def test_get_server_attributes() -> None:
# without port
assert get_server_attributes("us-central1-aiplatform.googleapis.com") == {
"server.address": "us-central1-aiplatform.googleapis.com",
"server.port": 443,
}
# with port
assert get_server_attributes("us-central1-aiplatform.googleapis.com:5432") == {
"server.address": "us-central1-aiplatform.googleapis.com",
"server.port": 5432,
}
def test_map_finish_reason():
for Enum in (
content.Candidate.FinishReason,
content_v1beta1.Candidate.FinishReason,
):
for finish_reason, expect in [
# Handled mappings
(Enum.FINISH_REASON_UNSPECIFIED, "error"),
(Enum.OTHER, "error"),
(Enum.STOP, "stop"),
(Enum.MAX_TOKENS, "length"),
# Preserve vertex enum value
(Enum.BLOCKLIST, "BLOCKLIST"),
(Enum.MALFORMED_FUNCTION_CALL, "MALFORMED_FUNCTION_CALL"),
(Enum.PROHIBITED_CONTENT, "PROHIBITED_CONTENT"),
(Enum.RECITATION, "RECITATION"),
(Enum.SAFETY, "SAFETY"),
(Enum.SPII, "SPII"),
]:
assert _map_finish_reason(finish_reason) == expect
opentelemetry-python-contrib-0.66b2/instrumentation/ 0000775 0000000 0000000 00000000000 15270700723 0023010 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/README.md 0000664 0000000 0000000 00000014714 15270700723 0024276 0 ustar 00root root 0000000 0000000
| Instrumentation | Supported Packages | Metrics support | Semconv status |
| --------------- | ------------------ | --------------- | -------------- |
| [opentelemetry-instrumentation-aio-pika](./opentelemetry-instrumentation-aio-pika) | aio_pika >= 7.2.0, < 11.0.0 | No | development
| [opentelemetry-instrumentation-aiohttp-client](./opentelemetry-instrumentation-aiohttp-client) | aiohttp ~= 3.0 | Yes | migration
| [opentelemetry-instrumentation-aiohttp-server](./opentelemetry-instrumentation-aiohttp-server) | aiohttp ~= 3.0 | Yes | migration
| [opentelemetry-instrumentation-aiokafka](./opentelemetry-instrumentation-aiokafka) | aiokafka >= 0.8, < 1.0 | No | development
| [opentelemetry-instrumentation-aiopg](./opentelemetry-instrumentation-aiopg) | aiopg >= 0.13.0, < 2.0.0 | Yes | migration
| [opentelemetry-instrumentation-asgi](./opentelemetry-instrumentation-asgi) | asgiref ~= 3.0 | Yes | migration
| [opentelemetry-instrumentation-asyncclick](./opentelemetry-instrumentation-asyncclick) | asyncclick ~= 8.0 | No | development
| [opentelemetry-instrumentation-asyncio](./opentelemetry-instrumentation-asyncio) | asyncio | No | development
| [opentelemetry-instrumentation-asyncpg](./opentelemetry-instrumentation-asyncpg) | asyncpg >= 0.12.0 | No | migration
| [opentelemetry-instrumentation-aws-lambda](./opentelemetry-instrumentation-aws-lambda) | aws_lambda | No | development
| [opentelemetry-instrumentation-boto3sqs](./opentelemetry-instrumentation-boto3sqs) | boto3 ~= 1.0 | No | development
| [opentelemetry-instrumentation-botocore](./opentelemetry-instrumentation-botocore) | botocore~=1.0,aiobotocore>=2.0,<4.0 | No | development
| [opentelemetry-instrumentation-cassandra](./opentelemetry-instrumentation-cassandra) | cassandra-driver ~= 3.25,scylla-driver ~= 3.25 | No | migration
| [opentelemetry-instrumentation-celery](./opentelemetry-instrumentation-celery) | celery >= 4.0, < 6.0 | No | development
| [opentelemetry-instrumentation-click](./opentelemetry-instrumentation-click) | click >= 8.1.3, < 9.0.0 | No | development
| [opentelemetry-instrumentation-confluent-kafka](./opentelemetry-instrumentation-confluent-kafka) | confluent-kafka >= 1.8.2, < 3.0.0 | No | development
| [opentelemetry-instrumentation-dbapi](./opentelemetry-instrumentation-dbapi) | dbapi | No | migration
| [opentelemetry-instrumentation-django](./opentelemetry-instrumentation-django) | django >= 2.0 | Yes | development
| [opentelemetry-instrumentation-exceptions](./opentelemetry-instrumentation-exceptions) | exceptions | No | development
| [opentelemetry-instrumentation-falcon](./opentelemetry-instrumentation-falcon) | falcon >= 1.4.1, < 5.0.0 | Yes | migration
| [opentelemetry-instrumentation-fastapi](./opentelemetry-instrumentation-fastapi) | fastapi ~= 0.92 | Yes | migration
| [opentelemetry-instrumentation-flask](./opentelemetry-instrumentation-flask) | flask >= 1.0 | Yes | migration
| [opentelemetry-instrumentation-grpc](./opentelemetry-instrumentation-grpc) | grpcio >= 1.42.0 | No | development
| [opentelemetry-instrumentation-httpx](./opentelemetry-instrumentation-httpx) | httpx >= 0.18.0,httpx2 >= 2.0.0 | Yes | migration
| [opentelemetry-instrumentation-jinja2](./opentelemetry-instrumentation-jinja2) | jinja2 >= 2.7, < 4.0 | No | development
| [opentelemetry-instrumentation-kafka-python](./opentelemetry-instrumentation-kafka-python) | kafka-python >= 2.0, < 4.0 | No | development
| [opentelemetry-instrumentation-logging](./opentelemetry-instrumentation-logging) | logging | No | development
| [opentelemetry-instrumentation-mysql](./opentelemetry-instrumentation-mysql) | mysql-connector-python >= 8.0 | No | migration
| [opentelemetry-instrumentation-mysqlclient](./opentelemetry-instrumentation-mysqlclient) | mysqlclient < 3 | No | migration
| [opentelemetry-instrumentation-pika](./opentelemetry-instrumentation-pika) | pika >= 0.12.0 | No | development
| [opentelemetry-instrumentation-psycopg](./opentelemetry-instrumentation-psycopg) | psycopg >= 3.1.0 | No | migration
| [opentelemetry-instrumentation-psycopg2](./opentelemetry-instrumentation-psycopg2) | psycopg2 >= 2.7.3.1,psycopg2-binary >= 2.7.3.1 | No | migration
| [opentelemetry-instrumentation-pymemcache](./opentelemetry-instrumentation-pymemcache) | pymemcache >= 1.3.5, < 5 | No | migration
| [opentelemetry-instrumentation-pymongo](./opentelemetry-instrumentation-pymongo) | pymongo >= 3.1, < 5.0 | No | migration
| [opentelemetry-instrumentation-pymssql](./opentelemetry-instrumentation-pymssql) | pymssql >= 2.1.5, < 3 | No | migration
| [opentelemetry-instrumentation-pymysql](./opentelemetry-instrumentation-pymysql) | PyMySQL < 2 | No | migration
| [opentelemetry-instrumentation-pyramid](./opentelemetry-instrumentation-pyramid) | pyramid >= 1.7 | Yes | migration
| [opentelemetry-instrumentation-redis](./opentelemetry-instrumentation-redis) | redis >= 2.6 | No | migration
| [opentelemetry-instrumentation-remoulade](./opentelemetry-instrumentation-remoulade) | remoulade >= 0.50 | No | development
| [opentelemetry-instrumentation-requests](./opentelemetry-instrumentation-requests) | requests ~= 2.0 | Yes | migration
| [opentelemetry-instrumentation-sqlalchemy](./opentelemetry-instrumentation-sqlalchemy) | sqlalchemy >= 1.0.0, < 2.1.0 | Yes | migration
| [opentelemetry-instrumentation-sqlite3](./opentelemetry-instrumentation-sqlite3) | sqlite3 | No | migration
| [opentelemetry-instrumentation-starlette](./opentelemetry-instrumentation-starlette) | starlette >= 0.13 | Yes | development
| [opentelemetry-instrumentation-structlog](./opentelemetry-instrumentation-structlog) | structlog >= 21.1 | No | development
| [opentelemetry-instrumentation-system-metrics](./opentelemetry-instrumentation-system-metrics) | psutil >= 5 | No | development
| [opentelemetry-instrumentation-threading](./opentelemetry-instrumentation-threading) | threading | No | development
| [opentelemetry-instrumentation-tornado](./opentelemetry-instrumentation-tornado) | tornado >= 5.1.1 | Yes | migration
| [opentelemetry-instrumentation-tortoiseorm](./opentelemetry-instrumentation-tortoiseorm) | tortoise-orm >= 0.17.0 | No | migration
| [opentelemetry-instrumentation-urllib](./opentelemetry-instrumentation-urllib) | urllib | Yes | migration
| [opentelemetry-instrumentation-urllib3](./opentelemetry-instrumentation-urllib3) | urllib3 >= 1.0.0, < 3.0.0 | Yes | migration
| [opentelemetry-instrumentation-valkey-py](./opentelemetry-instrumentation-valkey-py) | valkey ~= 6.0 | Yes | development
| [opentelemetry-instrumentation-wsgi](./opentelemetry-instrumentation-wsgi) | wsgi | Yes | migration opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aio-pika/ 0000775 0000000 0000000 00000000000 15270700723 0032635 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aio-pika/LICENSE 0000664 0000000 0000000 00000026135 15270700723 0033651 0 ustar 00root root 0000000 0000000 Apache License
Version 2.0, January 2004
http://www.apache.org/licenses/
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README.rst 0000664 0000000 0000000 00000001353 15270700723 0034247 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aio-pika OpenTelemetry Aio-pika Instrumentation
======================================
|pypi|
.. |pypi| image:: https://badge.fury.io/py/opentelemetry-instrumentation-aio-pika.svg
:target: https://pypi.org/project/opentelemetry-instrumentation-aio-pika/
This library allows tracing requests made by the Aio-pika library.
Installation
------------
::
pip install opentelemetry-instrumentation-aio-pika
References
----------
* `OpenTelemetry Aio-pika instrumentation `_
* `OpenTelemetry Project `_
* `OpenTelemetry Python Examples `_
pyproject.toml 0000664 0000000 0000000 00000003210 15270700723 0035466 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aio-pika [build-system]
requires = ["hatchling"]
build-backend = "hatchling.build"
[project]
name = "opentelemetry-instrumentation-aio-pika"
dynamic = ["version"]
description = "OpenTelemetry Aio-pika instrumentation"
readme = "README.rst"
license = "Apache-2.0"
requires-python = ">=3.10"
authors = [
{ name = "OpenTelemetry Authors", email = "cncf-opentelemetry-contributors@lists.cncf.io" },
]
classifiers = [
"Development Status :: 4 - Beta",
"Intended Audience :: Developers",
"License :: OSI Approved :: Apache Software License",
"Programming Language :: Python",
"Programming Language :: Python :: 3",
"Programming Language :: Python :: 3.10",
"Programming Language :: Python :: 3.11",
"Programming Language :: Python :: 3.12",
"Programming Language :: Python :: 3.13",
"Programming Language :: Python :: 3.14",
]
dependencies = [
"opentelemetry-api ~= 1.5",
"opentelemetry-instrumentation == 0.66b2",
"opentelemetry-semantic-conventions == 0.66b2",
"wrapt >= 1.0.0, < 3.0.0",
]
[project.optional-dependencies]
instruments = [
"aio_pika >= 7.2.0, < 11.0.0",
]
[project.entry-points.opentelemetry_instrumentor]
aio-pika = "opentelemetry.instrumentation.aio_pika:AioPikaInstrumentor"
[project.urls]
Homepage = "https://github.com/open-telemetry/opentelemetry-python-contrib/tree/main/instrumentation/opentelemetry-instrumentation-aio-pika"
Repository = "https://github.com/open-telemetry/opentelemetry-python-contrib"
[tool.hatch.version]
path = "src/opentelemetry/instrumentation/aio_pika/version.py"
[tool.hatch.build.targets.sdist]
include = [
"/src",
"/tests",
]
[tool.hatch.build.targets.wheel]
packages = ["src/opentelemetry"]
opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aio-pika/src/ 0000775 0000000 0000000 00000000000 15270700723 0033424 5 ustar 00root root 0000000 0000000 opentelemetry/ 0000775 0000000 0000000 00000000000 15270700723 0036241 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aio-pika/src instrumentation/ 0000775 0000000 0000000 00000000000 15270700723 0041504 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aio-pika/src/opentelemetry aio_pika/ 0000775 0000000 0000000 00000000000 15270700723 0043260 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aio-pika/src/opentelemetry/instrumentation __init__.py 0000664 0000000 0000000 00000002014 15270700723 0045366 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aio-pika/src/opentelemetry/instrumentation/aio_pika # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
"""
Instrument aio_pika to trace RabbitMQ applications.
Usage
-----
Start broker backend
.. code-block:: python
docker run -p 5672:5672 rabbitmq
Run instrumented task
.. code-block:: python
import asyncio
from aio_pika import Message, connect
from opentelemetry.instrumentation.aio_pika import AioPikaInstrumentor
AioPikaInstrumentor().instrument()
async def main() -> None:
connection = await connect("amqp://guest:guest@localhost/")
async with connection:
channel = await connection.channel()
queue = await channel.declare_queue("hello")
await channel.default_exchange.publish(Message(b"Hello World!"), routing_key=queue.name)
if __name__ == "__main__":
asyncio.run(main())
API
---
"""
# pylint: disable=import-error
from .aio_pika_instrumentor import AioPikaInstrumentor
from .version import __version__
__all__ = ["AioPikaInstrumentor", "__version__"]
aio_pika_instrumentor.py 0000664 0000000 0000000 00000005015 15270700723 0050240 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aio-pika/src/opentelemetry/instrumentation/aio_pika # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
from collections.abc import Callable, Collection
from typing import Any
import wrapt
from aio_pika import Exchange, Queue
from aio_pika.abc import AbstractIncomingMessage
from opentelemetry import trace
from opentelemetry.instrumentation.aio_pika.callback_decorator import (
CallbackDecorator,
)
from opentelemetry.instrumentation.aio_pika.package import _instruments
from opentelemetry.instrumentation.aio_pika.publish_decorator import (
PublishDecorator,
)
from opentelemetry.instrumentation.aio_pika.version import __version__
from opentelemetry.instrumentation.instrumentor import BaseInstrumentor
from opentelemetry.instrumentation.utils import unwrap
from opentelemetry.trace import Tracer
_INSTRUMENTATION_MODULE_NAME = "opentelemetry.instrumentation.aio_pika"
class AioPikaInstrumentor(BaseInstrumentor):
@staticmethod
def _instrument_queue(tracer: Tracer):
async def wrapper(wrapped, instance, args, kwargs):
async def consume(
callback: Callable[[AbstractIncomingMessage], Any],
*fargs,
**fkwargs,
):
decorated_callback = CallbackDecorator(tracer, instance).decorate(callback)
return await wrapped(decorated_callback, *fargs, **fkwargs)
return await consume(*args, **kwargs)
wrapt.wrap_function_wrapper(Queue, "consume", wrapper)
@staticmethod
def _instrument_exchange(tracer: Tracer):
async def wrapper(wrapped, instance, args, kwargs):
decorated_publish = PublishDecorator(tracer, instance).decorate(wrapped)
return await decorated_publish(*args, **kwargs)
wrapt.wrap_function_wrapper(Exchange, "publish", wrapper)
def _instrument(self, **kwargs):
tracer_provider = kwargs.get("tracer_provider", None)
tracer = trace.get_tracer(
_INSTRUMENTATION_MODULE_NAME,
__version__,
tracer_provider,
schema_url="https://opentelemetry.io/schemas/1.11.0",
)
self._instrument_queue(tracer)
self._instrument_exchange(tracer)
@staticmethod
def _uninstrument_queue():
unwrap(Queue, "consume")
@staticmethod
def _uninstrument_exchange():
unwrap(Exchange, "publish")
def _uninstrument(self, **kwargs):
self._uninstrument_queue()
self._uninstrument_exchange()
def instrumentation_dependencies(self) -> Collection[str]:
return _instruments
callback_decorator.py 0000664 0000000 0000000 00000003531 15270700723 0047432 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aio-pika/src/opentelemetry/instrumentation/aio_pika # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
from collections.abc import Callable
from typing import Any
from aio_pika import Queue
from aio_pika.abc import AbstractIncomingMessage
from opentelemetry import context, propagate, trace
from opentelemetry.instrumentation.aio_pika.span_builder import SpanBuilder
from opentelemetry.instrumentation.utils import is_instrumentation_enabled
from opentelemetry.semconv.trace import MessagingOperationValues
from opentelemetry.trace import Span, Tracer
class CallbackDecorator:
def __init__(self, tracer: Tracer, queue: Queue):
self._tracer = tracer
self._queue = queue
def _get_span(self, message: AbstractIncomingMessage) -> Span | None:
builder = SpanBuilder(self._tracer)
builder.set_as_consumer()
builder.set_operation(MessagingOperationValues.RECEIVE)
builder.set_destination(message.exchange or message.routing_key)
builder.set_channel(self._queue.channel)
builder.set_message(message)
return builder.build()
def decorate(self, callback: Callable[[AbstractIncomingMessage], Any]) -> Callable[[AbstractIncomingMessage], Any]:
async def decorated(message: AbstractIncomingMessage):
if not is_instrumentation_enabled():
return await callback(message)
headers = message.headers or {}
ctx = propagate.extract(headers)
token = context.attach(ctx)
span = self._get_span(message)
if not span:
return await callback(message)
try:
with trace.use_span(span, end_on_exit=True):
return_value = await callback(message)
finally:
if token:
context.detach(token)
return return_value
return decorated
package.py 0000664 0000000 0000000 00000000265 15270700723 0045230 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aio-pika/src/opentelemetry/instrumentation/aio_pika # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
from collections.abc import Collection
_instruments: Collection[str] = ("aio_pika >= 7.2.0, < 11.0.0",)
publish_decorator.py 0000664 0000000 0000000 00000002744 15270700723 0047351 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aio-pika/src/opentelemetry/instrumentation/aio_pika # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
from collections.abc import Callable
import aiormq
from aio_pika import Exchange
from aio_pika.abc import AbstractMessage
from opentelemetry import propagate, trace
from opentelemetry.instrumentation.aio_pika.span_builder import SpanBuilder
from opentelemetry.trace import Span, Tracer
class PublishDecorator:
def __init__(self, tracer: Tracer, exchange: Exchange):
self._tracer = tracer
self._exchange = exchange
def _get_publish_span(self, message: AbstractMessage, routing_key: str) -> Span | None:
builder = SpanBuilder(self._tracer)
builder.set_as_producer()
builder.set_destination(f"{self._exchange.name},{routing_key}")
builder.set_channel(self._exchange.channel)
builder.set_message(message)
return builder.build()
def decorate(self, publish: Callable) -> Callable:
async def decorated_publish(
message: AbstractMessage, routing_key: str, **kwargs
) -> aiormq.abc.ConfirmationFrameType | None:
span = self._get_publish_span(message, routing_key)
if not span:
return await publish(message, routing_key, **kwargs)
with trace.use_span(span, end_on_exit=True):
propagate.inject(message.properties.headers)
return_value = await publish(message, routing_key, **kwargs)
return return_value
return decorated_publish
span_builder.py 0000664 0000000 0000000 00000006641 15270700723 0046310 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aio-pika/src/opentelemetry/instrumentation/aio_pika # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
from aio_pika.abc import AbstractChannel, AbstractMessage
from opentelemetry.instrumentation.utils import is_instrumentation_enabled
from opentelemetry.semconv._incubating.attributes.messaging_attributes import (
MESSAGING_MESSAGE_ID,
MESSAGING_OPERATION,
MESSAGING_SYSTEM,
)
from opentelemetry.semconv._incubating.attributes.net_attributes import (
NET_PEER_NAME,
NET_PEER_PORT,
)
from opentelemetry.semconv.trace import (
MessagingOperationValues,
SpanAttributes,
)
from opentelemetry.trace import Span, SpanKind, Tracer
_DEFAULT_ATTRIBUTES = {MESSAGING_SYSTEM: "rabbitmq"}
class SpanBuilder:
def __init__(self, tracer: Tracer):
self._tracer = tracer
self._attributes = _DEFAULT_ATTRIBUTES.copy()
self._operation: MessagingOperationValues = None
self._kind: SpanKind = None
self._destination: str = None
def set_as_producer(self):
self._kind = SpanKind.PRODUCER
def set_as_consumer(self):
self._kind = SpanKind.CONSUMER
def set_operation(self, operation: MessagingOperationValues):
self._operation = operation
def set_destination(self, destination: str):
self._destination = destination
# TODO: Update this implementation once the semantic conventions for messaging stabilize
# See: https://github.com/open-telemetry/semantic-conventions/blob/main/docs/registry/attributes/messaging.md
self._attributes[SpanAttributes.MESSAGING_DESTINATION] = destination
def set_channel(self, channel: AbstractChannel):
if hasattr(channel, "_connection"):
# aio_rmq 9.1 and above removed the connection attribute from the abstract listings
connection = channel._connection
else:
# aio_rmq 9.0.5 and below
connection = channel.connection
if hasattr(connection, "connection"):
# aio_rmq 7
url = connection.connection.url
else:
# aio_rmq 8
url = connection.url
self._attributes.update(
{
NET_PEER_NAME: url.host,
NET_PEER_PORT: url.port or 5672,
}
)
def set_message(self, message: AbstractMessage):
properties = message.properties
if properties.message_id:
self._attributes[MESSAGING_MESSAGE_ID] = properties.message_id
if properties.correlation_id:
self._attributes[SpanAttributes.MESSAGING_CONVERSATION_ID] = properties.correlation_id
def build(self) -> Span | None:
if not is_instrumentation_enabled():
return None
if self._operation:
self._attributes[MESSAGING_OPERATION] = self._operation.value
else:
# TODO: Update this implementation once the semantic conventions for messaging stabilize
# See: https://github.com/open-telemetry/semantic-conventions/blob/main/docs/registry/attributes/messaging.md
self._attributes[SpanAttributes.MESSAGING_TEMP_DESTINATION] = True
span = self._tracer.start_span(
self._generate_span_name(),
kind=self._kind,
attributes=self._attributes,
)
return span
def _generate_span_name(self) -> str:
operation_value = self._operation.value if self._operation else "send"
return f"{self._destination} {operation_value}"
version.py 0000664 0000000 0000000 00000000144 15270700723 0045316 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aio-pika/src/opentelemetry/instrumentation/aio_pika # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
__version__ = "0.66b2"
test-requirements-latest.txt 0000664 0000000 0000000 00000004441 15270700723 0040314 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aio-pika # This file was autogenerated by uv via the following command:
# uv pip compile --python 3.10 --universal --no-emit-package opentelemetry-api --no-emit-package opentelemetry-semantic-conventions -c dev-requirements.txt instrumentation/opentelemetry-instrumentation-aio-pika/test-requirements.in -o instrumentation/opentelemetry-instrumentation-aio-pika/test-requirements-latest.txt
-e instrumentation/opentelemetry-instrumentation-aio-pika
# via -r instrumentation/opentelemetry-instrumentation-aio-pika/test-requirements.in
-e opentelemetry-instrumentation
# via
# -r instrumentation/opentelemetry-instrumentation-aio-pika/test-requirements.in
# opentelemetry-instrumentation-aio-pika
aio-pika==9.6.2 ; python_full_version < '3.11'
# via -r instrumentation/opentelemetry-instrumentation-aio-pika/test-requirements.in
aio-pika==10.0.1 ; python_full_version >= '3.11'
# via -r instrumentation/opentelemetry-instrumentation-aio-pika/test-requirements.in
aiormq==6.9.4 ; python_full_version < '3.11'
# via aio-pika
aiormq==7.0.0 ; python_full_version >= '3.11'
# via aio-pika
colorama==0.4.6 ; sys_platform == 'win32'
# via pytest
exceptiongroup==1.3.1 ; python_full_version < '3.11'
# via
# aio-pika
# pytest
idna==3.19
# via yarl
iniconfig==2.3.0
# via pytest
multidict==6.7.1
# via yarl
packaging==26.3
# via
# opentelemetry-instrumentation
# pytest
pamqp==3.3.0 ; python_full_version < '3.11'
# via aiormq
pamqp==4.0.1 ; python_full_version >= '3.11'
# via aiormq
pluggy==1.6.0
# via pytest
propcache==0.5.2
# via yarl
pytest==7.4.4
# via
# -c dev-requirements.txt
# -r instrumentation/opentelemetry-instrumentation-aio-pika/test-requirements.in
tomli==2.4.1 ; python_full_version < '3.11'
# via pytest
typing-extensions==4.16.0
# via
# exceptiongroup
# multidict
# opentelemetry-api
# opentelemetry-semantic-conventions
wrapt==2.4.0
# via
# -r instrumentation/opentelemetry-instrumentation-aio-pika/test-requirements.in
# opentelemetry-instrumentation
# opentelemetry-instrumentation-aio-pika
yarl==1.24.5
# via
# aio-pika
# aiormq
# The following packages were excluded from the output:
# opentelemetry-api
# opentelemetry-semantic-conventions
test-requirements-oldest.txt 0000664 0000000 0000000 00000004003 15270700723 0040304 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aio-pika # This file was autogenerated by uv via the following command:
# uv pip compile --python 3.10 --resolution lowest-direct --universal --no-emit-package opentelemetry-api --no-emit-package opentelemetry-semantic-conventions -c dev-requirements.txt instrumentation/opentelemetry-instrumentation-aio-pika/test-requirements.in -o instrumentation/opentelemetry-instrumentation-aio-pika/test-requirements-oldest.txt
-e instrumentation/opentelemetry-instrumentation-aio-pika
# via -r instrumentation/opentelemetry-instrumentation-aio-pika/test-requirements.in
-e opentelemetry-instrumentation
# via
# -r instrumentation/opentelemetry-instrumentation-aio-pika/test-requirements.in
# opentelemetry-instrumentation-aio-pika
aio-pika==7.2.0
# via -r instrumentation/opentelemetry-instrumentation-aio-pika/test-requirements.in
aiormq==6.2.3
# via aio-pika
colorama==0.4.6 ; sys_platform == 'win32'
# via pytest
exceptiongroup==1.3.1 ; python_full_version < '3.11'
# via pytest
idna==3.19
# via yarl
iniconfig==2.3.0
# via pytest
multidict==6.8.0
# via yarl
packaging==18.0
# via
# opentelemetry-instrumentation
# pytest
pamqp==3.1.0
# via aiormq
pluggy==1.6.0
# via pytest
propcache==0.5.2
# via yarl
pyparsing==3.3.2
# via packaging
pytest==7.4.4
# via
# -c dev-requirements.txt
# -r instrumentation/opentelemetry-instrumentation-aio-pika/test-requirements.in
six==1.17.0
# via packaging
tomli==2.4.1 ; python_full_version < '3.11'
# via pytest
typing-extensions==4.16.0
# via
# exceptiongroup
# multidict
# opentelemetry-api
# opentelemetry-semantic-conventions
wrapt==1.16.0
# via
# -r instrumentation/opentelemetry-instrumentation-aio-pika/test-requirements.in
# opentelemetry-instrumentation
# opentelemetry-instrumentation-aio-pika
yarl==1.24.5
# via
# aio-pika
# aiormq
# The following packages were excluded from the output:
# opentelemetry-api
# opentelemetry-semantic-conventions
test-requirements.in 0000664 0000000 0000000 00000000240 15270700723 0036602 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aio-pika aio-pika >= 7.2.0, < 11.0.0
wrapt >= 1.16.0, < 3.0.0
pytest >= 7.4.4
-e opentelemetry-instrumentation
-e instrumentation/opentelemetry-instrumentation-aio-pika
opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aio-pika/tests/ 0000775 0000000 0000000 00000000000 15270700723 0033777 5 ustar 00root root 0000000 0000000 __init__.py 0000664 0000000 0000000 00000000000 15270700723 0036017 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aio-pika/tests consts.py 0000664 0000000 0000000 00000001737 15270700723 0035613 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aio-pika/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
from argparse import Namespace
from aio_pika import __version__ as aiopika_version
from yarl import URL
AIOPIKA_VERSION_INFO = tuple(int(v) for v in aiopika_version.split("."))
MESSAGE_ID = "meesage_id"
CORRELATION_ID = "correlation_id"
MESSAGING_SYSTEM_VALUE = "rabbitmq"
EXCHANGE_NAME = "exchange_name"
QUEUE_NAME = "queue_name"
ROUTING_KEY = "routing_key"
SERVER_HOST = "localhost"
SERVER_PORT = 1234
SERVER_USER = "guest"
SERVER_PASS = "guest"
SERVER_URL = URL(f"amqp://{SERVER_USER}:{SERVER_PASS}@{SERVER_HOST}:{SERVER_PORT}/")
CONNECTION_7 = Namespace(connection=Namespace(url=SERVER_URL))
CONNECTION_8 = Namespace(url=SERVER_URL)
CHANNEL_7 = Namespace(connection=CONNECTION_7, loop=None)
CHANNEL_8 = Namespace(connection=CONNECTION_8, loop=None)
MESSAGE = Namespace(
properties=Namespace(message_id=MESSAGE_ID, correlation_id=CORRELATION_ID, headers={}),
exchange=EXCHANGE_NAME,
headers={},
)
test_aio_pika_instrumentation.py 0000664 0000000 0000000 00000001354 15270700723 0042433 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aio-pika/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
from unittest import TestCase
import wrapt
from aio_pika import Exchange, Queue
from opentelemetry.instrumentation.aio_pika import AioPikaInstrumentor
class TestPika(TestCase):
def test_instrument_api(self) -> None:
instrumentation = AioPikaInstrumentor()
instrumentation.instrument()
self.assertTrue(isinstance(Queue.consume, wrapt.BoundFunctionWrapper))
self.assertTrue(isinstance(Exchange.publish, wrapt.BoundFunctionWrapper))
instrumentation.uninstrument()
self.assertFalse(isinstance(Queue.consume, wrapt.BoundFunctionWrapper))
self.assertFalse(isinstance(Exchange.publish, wrapt.BoundFunctionWrapper))
test_callback_decorator.py 0000664 0000000 0000000 00000007747 15270700723 0041146 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aio-pika/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
import asyncio
from unittest import TestCase, mock, skipIf
from aio_pika import Queue
from opentelemetry.instrumentation.aio_pika.callback_decorator import (
CallbackDecorator,
)
from opentelemetry.semconv._incubating.attributes.messaging_attributes import (
MESSAGING_MESSAGE_ID,
MESSAGING_OPERATION,
MESSAGING_SYSTEM,
)
from opentelemetry.semconv._incubating.attributes.net_attributes import (
NET_PEER_NAME,
NET_PEER_PORT,
)
from opentelemetry.semconv.trace import SpanAttributes
from opentelemetry.trace import SpanKind, get_tracer
from .consts import (
AIOPIKA_VERSION_INFO,
CHANNEL_7,
CHANNEL_8,
CORRELATION_ID,
EXCHANGE_NAME,
MESSAGE,
MESSAGE_ID,
MESSAGING_SYSTEM_VALUE,
QUEUE_NAME,
SERVER_HOST,
SERVER_PORT,
)
@skipIf(AIOPIKA_VERSION_INFO >= (8, 0), "Only for aio_pika 7")
class TestInstrumentedQueueAioRmq7(TestCase):
EXPECTED_ATTRIBUTES = {
MESSAGING_SYSTEM: MESSAGING_SYSTEM_VALUE,
SpanAttributes.MESSAGING_DESTINATION: EXCHANGE_NAME,
NET_PEER_NAME: SERVER_HOST,
NET_PEER_PORT: SERVER_PORT,
MESSAGING_MESSAGE_ID: MESSAGE_ID,
SpanAttributes.MESSAGING_CONVERSATION_ID: CORRELATION_ID,
MESSAGING_OPERATION: "receive",
}
def setUp(self):
self.tracer = get_tracer(__name__)
self.loop = asyncio.new_event_loop()
asyncio.set_event_loop(self.loop)
def test_get_callback_span(self):
queue = Queue(CHANNEL_7, QUEUE_NAME, False, False, False, None)
tracer = mock.MagicMock()
CallbackDecorator(tracer, queue)._get_span(MESSAGE)
tracer.start_span.assert_called_once_with(
f"{EXCHANGE_NAME} receive",
kind=SpanKind.CONSUMER,
attributes=self.EXPECTED_ATTRIBUTES,
)
def test_decorate_callback(self):
queue = Queue(CHANNEL_7, QUEUE_NAME, False, False, False, None)
callback = mock.MagicMock(return_value=asyncio.sleep(0))
with mock.patch.object(CallbackDecorator, "_get_span") as mocked_get_callback_span:
callback_decorator = CallbackDecorator(self.tracer, queue)
decorated_callback = callback_decorator.decorate(callback)
self.loop.run_until_complete(decorated_callback(MESSAGE))
mocked_get_callback_span.assert_called_once()
callback.assert_called_once_with(MESSAGE)
@skipIf(AIOPIKA_VERSION_INFO <= (8, 0), "Only for aio_pika 8")
class TestInstrumentedQueueAioRmq8(TestCase):
EXPECTED_ATTRIBUTES = {
MESSAGING_SYSTEM: MESSAGING_SYSTEM_VALUE,
SpanAttributes.MESSAGING_DESTINATION: EXCHANGE_NAME,
NET_PEER_NAME: SERVER_HOST,
NET_PEER_PORT: SERVER_PORT,
MESSAGING_MESSAGE_ID: MESSAGE_ID,
SpanAttributes.MESSAGING_CONVERSATION_ID: CORRELATION_ID,
MESSAGING_OPERATION: "receive",
}
def setUp(self):
self.tracer = get_tracer(__name__)
self.loop = asyncio.new_event_loop()
asyncio.set_event_loop(self.loop)
def test_get_callback_span(self):
queue = Queue(CHANNEL_8, QUEUE_NAME, False, False, False, None)
tracer = mock.MagicMock()
CallbackDecorator(tracer, queue)._get_span(MESSAGE)
tracer.start_span.assert_called_once_with(
f"{EXCHANGE_NAME} receive",
kind=SpanKind.CONSUMER,
attributes=self.EXPECTED_ATTRIBUTES,
)
def test_decorate_callback(self):
queue = Queue(CHANNEL_8, QUEUE_NAME, False, False, False, None)
callback = mock.MagicMock(return_value=asyncio.sleep(0))
with mock.patch.object(CallbackDecorator, "_get_span") as mocked_get_callback_span:
callback_decorator = CallbackDecorator(self.tracer, queue)
decorated_callback = callback_decorator.decorate(callback)
self.loop.run_until_complete(decorated_callback(MESSAGE))
mocked_get_callback_span.assert_called_once()
callback.assert_called_once_with(MESSAGE)
test_publish_decorator.py 0000664 0000000 0000000 00000015654 15270700723 0041054 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aio-pika/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
import asyncio
from unittest import TestCase, mock, skipIf
from unittest.mock import MagicMock
from aio_pika import Exchange, RobustExchange
from opentelemetry.instrumentation.aio_pika.publish_decorator import (
PublishDecorator,
)
from opentelemetry.semconv._incubating.attributes.messaging_attributes import (
MESSAGING_MESSAGE_ID,
MESSAGING_SYSTEM,
)
from opentelemetry.semconv._incubating.attributes.net_attributes import (
NET_PEER_NAME,
NET_PEER_PORT,
)
from opentelemetry.semconv.trace import SpanAttributes
from opentelemetry.trace import SpanKind, get_tracer
from .consts import (
AIOPIKA_VERSION_INFO,
CHANNEL_7,
CHANNEL_8,
CONNECTION_7,
CONNECTION_8,
CORRELATION_ID,
EXCHANGE_NAME,
MESSAGE,
MESSAGE_ID,
MESSAGING_SYSTEM_VALUE,
ROUTING_KEY,
SERVER_HOST,
SERVER_PORT,
)
@skipIf(AIOPIKA_VERSION_INFO >= (8, 0), "Only for aio_pika 7")
class TestInstrumentedExchangeAioRmq7(TestCase):
EXPECTED_ATTRIBUTES = {
MESSAGING_SYSTEM: MESSAGING_SYSTEM_VALUE,
SpanAttributes.MESSAGING_DESTINATION: f"{EXCHANGE_NAME},{ROUTING_KEY}",
NET_PEER_NAME: SERVER_HOST,
NET_PEER_PORT: SERVER_PORT,
MESSAGING_MESSAGE_ID: MESSAGE_ID,
SpanAttributes.MESSAGING_CONVERSATION_ID: CORRELATION_ID,
SpanAttributes.MESSAGING_TEMP_DESTINATION: True,
}
def setUp(self):
self.tracer = get_tracer(__name__)
self.loop = asyncio.new_event_loop()
asyncio.set_event_loop(self.loop)
def test_get_publish_span(self):
exchange = Exchange(CONNECTION_7, CHANNEL_7, EXCHANGE_NAME)
tracer = mock.MagicMock()
PublishDecorator(tracer, exchange)._get_publish_span(MESSAGE, ROUTING_KEY)
tracer.start_span.assert_called_once_with(
f"{EXCHANGE_NAME},{ROUTING_KEY} send",
kind=SpanKind.PRODUCER,
attributes=self.EXPECTED_ATTRIBUTES,
)
def _test_publish(self, exchange_type: type[Exchange]):
exchange = exchange_type(CONNECTION_7, CHANNEL_7, EXCHANGE_NAME)
with mock.patch.object(PublishDecorator, "_get_publish_span") as mock_get_publish_span:
with mock.patch.object(Exchange, "publish") as mock_publish:
decorated_publish = PublishDecorator(self.tracer, exchange).decorate(mock_publish)
self.loop.run_until_complete(decorated_publish(MESSAGE, ROUTING_KEY))
mock_publish.assert_called_once()
mock_get_publish_span.assert_called_once()
def test_publish(self):
self._test_publish(Exchange)
def test_robust_publish(self):
self._test_publish(RobustExchange)
def _test_publish_works_with_not_recording_span(self, exchange_type):
exchange = exchange_type(CONNECTION_7, CHANNEL_7, EXCHANGE_NAME)
with mock.patch.object(PublishDecorator, "_get_publish_span") as mock_get_publish_span:
mocked_not_recording_span = MagicMock()
mocked_not_recording_span.is_recording.return_value = False
mock_get_publish_span.return_value = mocked_not_recording_span
with mock.patch.object(Exchange, "publish") as mock_publish:
with mock.patch(
"opentelemetry.instrumentation.aio_pika.publish_decorator.propagate.inject"
) as mock_inject:
decorated_publish = PublishDecorator(self.tracer, exchange).decorate(mock_publish)
self.loop.run_until_complete(decorated_publish(MESSAGE, ROUTING_KEY))
mock_publish.assert_called_once()
mock_get_publish_span.assert_called_once()
mock_inject.assert_called_once()
def test_publish_works_with_not_recording_span(self):
self._test_publish_works_with_not_recording_span(Exchange)
def test_publish_works_with_not_recording_span_robust(self):
self._test_publish_works_with_not_recording_span(RobustExchange)
@skipIf(AIOPIKA_VERSION_INFO <= (8, 0), "Only for aio_pika 8")
class TestInstrumentedExchangeAioRmq8(TestCase):
EXPECTED_ATTRIBUTES = {
MESSAGING_SYSTEM: MESSAGING_SYSTEM_VALUE,
SpanAttributes.MESSAGING_DESTINATION: f"{EXCHANGE_NAME},{ROUTING_KEY}",
NET_PEER_NAME: SERVER_HOST,
NET_PEER_PORT: SERVER_PORT,
MESSAGING_MESSAGE_ID: MESSAGE_ID,
SpanAttributes.MESSAGING_CONVERSATION_ID: CORRELATION_ID,
SpanAttributes.MESSAGING_TEMP_DESTINATION: True,
}
def setUp(self):
self.tracer = get_tracer(__name__)
self.loop = asyncio.new_event_loop()
asyncio.set_event_loop(self.loop)
def test_get_publish_span(self):
exchange = Exchange(CHANNEL_8, EXCHANGE_NAME)
tracer = mock.MagicMock()
PublishDecorator(tracer, exchange)._get_publish_span(MESSAGE, ROUTING_KEY)
tracer.start_span.assert_called_once_with(
f"{EXCHANGE_NAME},{ROUTING_KEY} send",
kind=SpanKind.PRODUCER,
attributes=self.EXPECTED_ATTRIBUTES,
)
def _test_publish(self, exchange_type: type[Exchange]):
exchange = exchange_type(CONNECTION_8, CHANNEL_8, EXCHANGE_NAME)
with mock.patch.object(PublishDecorator, "_get_publish_span") as mock_get_publish_span:
with mock.patch.object(Exchange, "publish") as mock_publish:
decorated_publish = PublishDecorator(self.tracer, exchange).decorate(mock_publish)
self.loop.run_until_complete(decorated_publish(MESSAGE, ROUTING_KEY))
mock_publish.assert_called_once()
mock_get_publish_span.assert_called_once()
def test_publish(self):
self._test_publish(Exchange)
def test_robust_publish(self):
self._test_publish(RobustExchange)
def _test_publish_works_with_not_recording_span(self, exchange_type):
exchange = exchange_type(CONNECTION_7, CHANNEL_7, EXCHANGE_NAME)
with mock.patch.object(PublishDecorator, "_get_publish_span") as mock_get_publish_span:
mocked_not_recording_span = MagicMock()
mocked_not_recording_span.is_recording.return_value = False
mock_get_publish_span.return_value = mocked_not_recording_span
with mock.patch.object(Exchange, "publish") as mock_publish:
with mock.patch(
"opentelemetry.instrumentation.aio_pika.publish_decorator.propagate.inject"
) as mock_inject:
decorated_publish = PublishDecorator(self.tracer, exchange).decorate(mock_publish)
self.loop.run_until_complete(decorated_publish(MESSAGE, ROUTING_KEY))
mock_publish.assert_called_once()
mock_get_publish_span.assert_called_once()
mock_inject.assert_called_once()
def test_publish_works_with_not_recording_span(self):
self._test_publish_works_with_not_recording_span(Exchange)
def test_publish_works_with_not_recording_span_robust(self):
self._test_publish_works_with_not_recording_span(RobustExchange)
test_span_builder.py 0000664 0000000 0000000 00000000765 15270700723 0040010 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aio-pika/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
from unittest import TestCase
from opentelemetry.instrumentation.aio_pika.span_builder import SpanBuilder
from opentelemetry.trace import Span, get_tracer
class TestBuilder(TestCase):
def test_build(self):
builder = SpanBuilder(get_tracer(__name__))
builder.set_as_consumer()
builder.set_destination("destination")
span = builder.build()
self.assertTrue(isinstance(span, Span))
opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aiohttp-client/ 0000775 0000000 0000000 00000000000 15270700723 0034067 5 ustar 00root root 0000000 0000000 LICENSE 0000664 0000000 0000000 00000026135 15270700723 0035024 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aiohttp-client Apache License
Version 2.0, January 2004
http://www.apache.org/licenses/
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README.rst 0000664 0000000 0000000 00000001656 15270700723 0035507 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aiohttp-client OpenTelemetry aiohttp client Integration
========================================
|pypi|
.. |pypi| image:: https://badge.fury.io/py/opentelemetry-instrumentation-aiohttp-client.svg
:target: https://pypi.org/project/opentelemetry-instrumentation-aiohttp-client/
This library allows tracing HTTP requests made by the
`aiohttp client `_ library.
Installation
------------
::
pip install opentelemetry-instrumentation-aiohttp-client
References
----------
* `OpenTelemetry aiohttp client Instrumentation `_
* `aiohttp Tracing Reference `_
* `OpenTelemetry Project `_
* `OpenTelemetry Python Examples `_
pyproject.toml 0000664 0000000 0000000 00000003315 15270700723 0036726 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aiohttp-client [build-system]
requires = ["hatchling"]
build-backend = "hatchling.build"
[project]
name = "opentelemetry-instrumentation-aiohttp-client"
dynamic = ["version"]
description = "OpenTelemetry aiohttp client instrumentation"
readme = "README.rst"
license = "Apache-2.0"
requires-python = ">=3.10"
authors = [
{ name = "OpenTelemetry Authors", email = "cncf-opentelemetry-contributors@lists.cncf.io" },
]
classifiers = [
"Development Status :: 4 - Beta",
"Intended Audience :: Developers",
"License :: OSI Approved :: Apache Software License",
"Programming Language :: Python",
"Programming Language :: Python :: 3",
"Programming Language :: Python :: 3.10",
"Programming Language :: Python :: 3.11",
"Programming Language :: Python :: 3.12",
"Programming Language :: Python :: 3.13",
"Programming Language :: Python :: 3.14",
]
dependencies = [
"opentelemetry-api ~= 1.12",
"opentelemetry-instrumentation == 0.66b2",
"opentelemetry-semantic-conventions == 0.66b2",
"opentelemetry-util-http == 0.66b2",
"wrapt >= 1.0.0, < 3.0.0",
]
[project.optional-dependencies]
instruments = [
"aiohttp ~= 3.0",
]
[project.entry-points.opentelemetry_instrumentor]
aiohttp-client = "opentelemetry.instrumentation.aiohttp_client:AioHttpClientInstrumentor"
[project.urls]
Homepage = "https://github.com/open-telemetry/opentelemetry-python-contrib/tree/main/instrumentation/opentelemetry-instrumentation-aiohttp-client"
Repository = "https://github.com/open-telemetry/opentelemetry-python-contrib"
[tool.hatch.version]
path = "src/opentelemetry/instrumentation/aiohttp_client/version.py"
[tool.hatch.build.targets.sdist]
include = [
"/src",
"/tests",
]
[tool.hatch.build.targets.wheel]
packages = ["src/opentelemetry"]
src/ 0000775 0000000 0000000 00000000000 15270700723 0034577 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aiohttp-client opentelemetry/ 0000775 0000000 0000000 00000000000 15270700723 0037473 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aiohttp-client/src instrumentation/ 0000775 0000000 0000000 00000000000 15270700723 0042736 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aiohttp-client/src/opentelemetry aiohttp_client/ 0000775 0000000 0000000 00000000000 15270700723 0045744 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aiohttp-client/src/opentelemetry/instrumentation __init__.py 0000664 0000000 0000000 00000064346 15270700723 0050072 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aiohttp-client/src/opentelemetry/instrumentation/aiohttp_client # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
"""
The opentelemetry-instrumentation-aiohttp-client package allows tracing HTTP
requests made by the aiohttp client library.
Usage
-----
Explicitly instrumenting a single client session:
.. code:: python
import asyncio
import aiohttp
from opentelemetry.instrumentation.aiohttp_client import create_trace_config
import yarl
def strip_query_params(url: yarl.URL) -> str:
return str(url.with_query(None))
async def get(url):
async with aiohttp.ClientSession(trace_configs=[create_trace_config(
# Remove all query params from the URL attribute on the span.
url_filter=strip_query_params,
)]) as session:
async with session.get(url) as response:
await response.text()
asyncio.run(get("https://example.com"))
Instrumenting all client sessions:
.. code:: python
import asyncio
import aiohttp
from opentelemetry.instrumentation.aiohttp_client import (
AioHttpClientInstrumentor
)
# Enable instrumentation
AioHttpClientInstrumentor().instrument()
# Create a session and make an HTTP get request
async def get(url):
async with aiohttp.ClientSession() as session:
async with session.get(url) as response:
await response.text()
asyncio.run(get("https://example.com"))
Configuration
-------------
Request/Response hooks
**********************
Utilize request/response hooks to execute custom logic to be performed before/after performing a request.
.. code-block:: python
def request_hook(span: Span, params: aiohttp.TraceRequestStartParams):
if span and span.is_recording():
span.set_attribute("custom_user_attribute_from_request_hook", "some-value")
def response_hook(
span: Span,
params: typing.Union[
aiohttp.TraceRequestEndParams,
aiohttp.TraceRequestExceptionParams,
],
):
if span and span.is_recording():
span.set_attribute("custom_user_attribute_from_response_hook", "some-value")
AioHttpClientInstrumentor().instrument(request_hook=request_hook, response_hook=response_hook)
Exclude lists
*************
To exclude certain URLs from tracking, set the environment variable ``OTEL_PYTHON_AIOHTTP_CLIENT_EXCLUDED_URLS``
(or ``OTEL_PYTHON_EXCLUDED_URLS`` to cover all instrumentations) to a string of comma delimited regexes that match the
URLs.
For example,
::
export OTEL_PYTHON_AIOHTTP_CLIENT_EXCLUDED_URLS="client/.*/info,healthcheck"
will exclude requests such as ``https://site/client/123/info`` and ``https://site/xyz/healthcheck``.
Capture HTTP request and response headers
*****************************************
You can configure the agent to capture specified HTTP headers as span attributes, according to the
`semantic conventions `_.
Request headers
***************
To capture HTTP request headers as span attributes, set the environment variable
``OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_CLIENT_REQUEST`` to a comma delimited list of HTTP header names.
For example using the environment variable,
::
export OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_CLIENT_REQUEST="content-type,custom_request_header"
will extract ``content-type`` and ``custom_request_header`` from the request headers and add them as span attributes.
Request header names in aiohttp are case-insensitive. So, giving the header name as ``CUStom-Header`` in the environment
variable will capture the header named ``custom-header``.
Regular expressions may also be used to match multiple headers that correspond to the given pattern. For example:
::
export OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_CLIENT_REQUEST="Accept.*,X-.*"
Would match all request headers that start with ``Accept`` and ``X-``.
To capture all request headers, set ``OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_CLIENT_REQUEST`` to ``".*"``.
::
export OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_CLIENT_REQUEST=".*"
The name of the added span attribute will follow the format ``http.request.header.`` where ````
is the normalized HTTP header name (lowercase, with ``-`` replaced by ``_``). The value of the attribute will be a
single item list containing all the header values.
For example:
``http.request.header.custom_request_header = ["", ""]``
Response headers
****************
To capture HTTP response headers as span attributes, set the environment variable
``OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_CLIENT_RESPONSE`` to a comma delimited list of HTTP header names.
For example using the environment variable,
::
export OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_CLIENT_RESPONSE="content-type,custom_response_header"
will extract ``content-type`` and ``custom_response_header`` from the response headers and add them as span attributes.
Response header names in aiohttp are case-insensitive. So, giving the header name as ``CUStom-Header`` in the environment
variable will capture the header named ``custom-header``.
Regular expressions may also be used to match multiple headers that correspond to the given pattern. For example:
::
export OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_CLIENT_RESPONSE="Content.*,X-.*"
Would match all response headers that start with ``Content`` and ``X-``.
To capture all response headers, set ``OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_CLIENT_RESPONSE`` to ``".*"``.
::
export OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_CLIENT_RESPONSE=".*"
The name of the added span attribute will follow the format ``http.response.header.`` where ````
is the normalized HTTP header name (lowercase, with ``-`` replaced by ``_``). The value of the attribute will be a
list containing the header values.
For example:
``http.response.header.custom_response_header = ["", ""]``
Sanitizing headers
******************
In order to prevent storing sensitive data such as personally identifiable information (PII), session keys, passwords,
etc, set the environment variable ``OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SANITIZE_FIELDS``
to a comma delimited list of HTTP header names to be sanitized.
Regexes may be used, and all header names will be matched in a case-insensitive manner.
For example using the environment variable,
::
export OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SANITIZE_FIELDS=".*session.*,set-cookie"
will replace the value of headers such as ``session-id`` and ``set-cookie`` with ``[REDACTED]`` in the span.
Note:
The environment variable names used to capture HTTP headers are still experimental, and thus are subject to change.
API
---
"""
from __future__ import annotations
import types
import typing
from collections.abc import Callable, Collection
from timeit import default_timer
from typing import (
TYPE_CHECKING,
Any,
TypedDict,
cast,
)
from urllib.parse import urlparse
import aiohttp
import wrapt
import yarl
from opentelemetry import context as context_api
from opentelemetry import trace
from opentelemetry.instrumentation._semconv import (
HTTP_DURATION_HISTOGRAM_BUCKETS_NEW,
HTTP_DURATION_HISTOGRAM_BUCKETS_OLD,
_client_duration_attrs_new,
_client_duration_attrs_old,
_filter_semconv_duration_attrs,
_get_schema_url,
_OpenTelemetrySemanticConventionStability,
_OpenTelemetryStabilitySignalType,
_report_new,
_report_old,
_set_http_host_client,
_set_http_method,
_set_http_net_peer_name_client,
_set_http_peer_port_client,
_set_http_url,
_set_status,
_StabilityMode,
)
from opentelemetry.instrumentation.aiohttp_client.package import _instruments
from opentelemetry.instrumentation.aiohttp_client.version import __version__
from opentelemetry.instrumentation.instrumentor import BaseInstrumentor
from opentelemetry.instrumentation.utils import (
is_http_instrumentation_enabled,
unwrap,
)
from opentelemetry.metrics import MeterProvider, get_meter
from opentelemetry.propagate import inject
from opentelemetry.semconv.attributes.error_attributes import ERROR_TYPE
from opentelemetry.semconv.metrics import (
MetricInstruments, # type: ignore[reportDeprecated]
)
from opentelemetry.semconv.metrics.http_metrics import (
HTTP_CLIENT_REQUEST_DURATION,
)
from opentelemetry.trace import Span, SpanKind, TracerProvider, get_tracer
from opentelemetry.trace.status import Status, StatusCode
from opentelemetry.util.http import (
OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_CLIENT_REQUEST,
OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_CLIENT_RESPONSE,
OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SANITIZE_FIELDS,
get_custom_header_attributes,
get_custom_headers,
get_excluded_urls,
normalise_request_header_name,
normalise_response_header_name,
redact_url,
sanitize_method,
)
if TYPE_CHECKING:
from typing_extensions import Unpack
UrlFilterT = Callable[[yarl.URL], str] | None
RequestHookT = Callable[[Span, aiohttp.TraceRequestStartParams], None] | None
ResponseHookT = (
Callable[
[
Span,
aiohttp.TraceRequestEndParams | aiohttp.TraceRequestExceptionParams,
],
None,
]
| None
)
class ClientSessionInitKwargs(TypedDict, total=False):
trace_configs: typing.Sequence[aiohttp.TraceConfig]
class InstrumentKwargs(TypedDict, total=False):
tracer_provider: trace.TracerProvider
meter_provider: MeterProvider
url_filter: UrlFilterT
request_hook: RequestHookT
response_hook: ResponseHookT
trace_configs: typing.Sequence[aiohttp.TraceConfig]
class UninstrumentKwargs(TypedDict, total=False):
pass
def _get_span_name(method: str) -> str:
method = sanitize_method(method.strip())
if method == "_OTHER":
method = "HTTP"
return method
def _set_http_status_code_attribute(
span: Span,
status_code: int,
metric_attributes: dict[str, Any] | None = None,
sem_conv_opt_in_mode: _StabilityMode = _StabilityMode.DEFAULT,
):
status_code_str = str(status_code)
try:
status_code = int(status_code)
except ValueError:
status_code = -1
if metric_attributes is None:
metric_attributes = {}
# When we have durations we should set metrics only once
# Also the decision to include status code on a histogram should
# not be dependent on tracing decisions.
_set_status(
span,
metric_attributes,
status_code,
status_code_str,
server_span=False,
sem_conv_opt_in_mode=sem_conv_opt_in_mode,
)
# pylint: disable=too-many-locals
# pylint: disable=too-many-statements
def create_trace_config(
url_filter: UrlFilterT = None,
request_hook: RequestHookT = None,
response_hook: ResponseHookT = None,
tracer_provider: TracerProvider | None = None,
meter_provider: MeterProvider | None = None,
sem_conv_opt_in_mode: _StabilityMode = _StabilityMode.DEFAULT,
captured_request_headers: list[str] | None = None,
captured_response_headers: list[str] | None = None,
sensitive_headers: list[str] | None = None,
) -> aiohttp.TraceConfig:
"""Create an aiohttp-compatible trace configuration.
One span is created for the entire HTTP request, including initial
TCP/TLS setup if the connection doesn't exist.
By default the span name is set to the HTTP request method.
Example usage:
.. code:: python
import aiohttp
from opentelemetry.instrumentation.aiohttp_client import create_trace_config
async with aiohttp.ClientSession(trace_configs=[create_trace_config()]) as session:
async with session.get(url) as response:
await response.text()
:param url_filter: A callback to process the requested URL prior to adding
it as a span attribute. This can be useful to remove sensitive data
such as API keys or user personal information.
:param Callable request_hook: Optional callback that can modify span name and request params.
:param Callable response_hook: Optional callback that can modify span name and response params.
:param tracer_provider: optional TracerProvider from which to get a Tracer
:param meter_provider: optional Meter provider to use
:param captured_request_headers: List of HTTP request header regexes to capture as
span attributes. Header names matching these patterns will be added as span
attributes with the format ``http.request.header.``.
:param captured_response_headers: List of HTTP response header regexes to capture as
span attributes. Header names matching these patterns will be added as span
attributes with the format ``http.response.header.``.
:param sensitive_headers: List of HTTP header regexes whose values should be
sanitized (redacted) when captured. Header values matching these patterns
will be replaced with ``[REDACTED]``.
:return: An object suitable for use with :py:class:`aiohttp.ClientSession`.
:rtype: :py:class:`aiohttp.TraceConfig`
"""
# `aiohttp.TraceRequestStartParams` resolves to `aiohttp.tracing.TraceRequestStartParams`
# which doesn't exist in the aiohttp intersphinx inventory.
# Explicitly specify the type for the `request_hook` and `response_hook` param and rtype to work
# around this issue.
schema_url = _get_schema_url(sem_conv_opt_in_mode)
tracer = get_tracer(
__name__,
__version__,
tracer_provider,
schema_url=schema_url,
)
meter = get_meter(
__name__,
__version__,
meter_provider,
schema_url,
)
duration_histogram_old = None
if _report_old(sem_conv_opt_in_mode):
duration_histogram_old = meter.create_histogram(
name=MetricInstruments.HTTP_CLIENT_DURATION, # type: ignore[reportDeprecated]
unit="ms",
description="measures the duration of the outbound HTTP request",
explicit_bucket_boundaries_advisory=HTTP_DURATION_HISTOGRAM_BUCKETS_OLD,
)
duration_histogram_new = None
if _report_new(sem_conv_opt_in_mode):
duration_histogram_new = meter.create_histogram(
name=HTTP_CLIENT_REQUEST_DURATION,
unit="s",
description="Duration of HTTP client requests.",
explicit_bucket_boundaries_advisory=HTTP_DURATION_HISTOGRAM_BUCKETS_NEW,
)
excluded_urls = get_excluded_urls("AIOHTTP_CLIENT")
def _end_trace(trace_config_ctx: types.SimpleNamespace):
elapsed_time = max(default_timer() - trace_config_ctx.start_time, 0)
if trace_config_ctx.token:
context_api.detach(trace_config_ctx.token)
if trace_config_ctx.span:
trace_config_ctx.span.end()
if trace_config_ctx.duration_histogram_old is not None:
duration_attrs_old = cast(
dict[str, Any],
_filter_semconv_duration_attrs(
trace_config_ctx.metric_attributes,
_client_duration_attrs_old,
_client_duration_attrs_new,
_StabilityMode.DEFAULT,
),
)
trace_config_ctx.duration_histogram_old.record(
max(round(elapsed_time * 1000), 0),
attributes=duration_attrs_old,
)
if trace_config_ctx.duration_histogram_new is not None:
duration_attrs_new = cast(
dict[str, Any],
_filter_semconv_duration_attrs(
trace_config_ctx.metric_attributes,
_client_duration_attrs_old,
_client_duration_attrs_new,
_StabilityMode.HTTP,
),
)
trace_config_ctx.duration_histogram_new.record(elapsed_time, attributes=duration_attrs_new)
async def on_request_start(
_session: aiohttp.ClientSession,
trace_config_ctx: types.SimpleNamespace,
params: aiohttp.TraceRequestStartParams,
):
if not is_http_instrumentation_enabled() or trace_config_ctx.excluded_urls.url_disabled(str(params.url)):
return
trace_config_ctx.start_time = default_timer()
method = params.method
request_span_name = _get_span_name(method)
request_url = (
redact_url(cast(Callable[[yarl.URL], str], trace_config_ctx.url_filter)(params.url))
if callable(trace_config_ctx.url_filter)
else redact_url(str(params.url))
)
span_attributes: dict[str, Any] = {}
_set_http_method(
span_attributes,
method,
sanitize_method(method),
sem_conv_opt_in_mode,
)
_set_http_method(
trace_config_ctx.metric_attributes,
method,
sanitize_method(method),
sem_conv_opt_in_mode,
)
_set_http_url(span_attributes, request_url, sem_conv_opt_in_mode)
try:
parsed_url = urlparse(request_url)
if parsed_url.hostname:
_set_http_host_client(
trace_config_ctx.metric_attributes,
parsed_url.hostname,
sem_conv_opt_in_mode,
)
_set_http_net_peer_name_client(
trace_config_ctx.metric_attributes,
parsed_url.hostname,
sem_conv_opt_in_mode,
)
if _report_new(sem_conv_opt_in_mode):
_set_http_host_client(
span_attributes,
parsed_url.hostname,
sem_conv_opt_in_mode,
)
if parsed_url.port:
_set_http_peer_port_client(
trace_config_ctx.metric_attributes,
parsed_url.port,
sem_conv_opt_in_mode,
)
if _report_new(sem_conv_opt_in_mode):
_set_http_peer_port_client(span_attributes, parsed_url.port, sem_conv_opt_in_mode)
except ValueError:
pass
span_attributes.update(
get_custom_header_attributes(
{key: params.headers.getall(key) for key in params.headers.keys()},
captured_request_headers,
sensitive_headers,
normalise_request_header_name,
)
)
trace_config_ctx.span = trace_config_ctx.tracer.start_span(
request_span_name, kind=SpanKind.CLIENT, attributes=span_attributes
)
if callable(request_hook):
request_hook(trace_config_ctx.span, params)
trace_config_ctx.token = context_api.attach(trace.set_span_in_context(trace_config_ctx.span))
inject(params.headers)
async def on_request_end(
_session: aiohttp.ClientSession,
trace_config_ctx: types.SimpleNamespace,
params: aiohttp.TraceRequestEndParams,
):
if trace_config_ctx.span is None:
return
if callable(response_hook):
response_hook(trace_config_ctx.span, params)
_set_http_status_code_attribute(
trace_config_ctx.span,
params.response.status,
trace_config_ctx.metric_attributes,
sem_conv_opt_in_mode,
)
trace_config_ctx.span.set_attributes(
get_custom_header_attributes(
{key: params.response.headers.getall(key) for key in params.response.headers.keys()},
captured_response_headers,
sensitive_headers,
normalise_response_header_name,
)
)
_end_trace(trace_config_ctx)
async def on_request_exception(
_session: aiohttp.ClientSession,
trace_config_ctx: types.SimpleNamespace,
params: aiohttp.TraceRequestExceptionParams,
):
if trace_config_ctx.span is None:
return
if trace_config_ctx.span.is_recording() and params.exception:
exc_type = type(params.exception).__qualname__
if _report_new(sem_conv_opt_in_mode):
trace_config_ctx.span.set_attribute(ERROR_TYPE, exc_type)
trace_config_ctx.metric_attributes[ERROR_TYPE] = exc_type
trace_config_ctx.span.set_status(Status(StatusCode.ERROR, exc_type))
trace_config_ctx.span.record_exception(params.exception)
if callable(response_hook):
response_hook(trace_config_ctx.span, params)
_end_trace(trace_config_ctx)
def _trace_config_ctx_factory(**kwargs: Any) -> types.SimpleNamespace:
kwargs.setdefault("trace_request_ctx", {})
return types.SimpleNamespace(
tracer=tracer,
span=None,
token=None,
duration_histogram_old=duration_histogram_old,
duration_histogram_new=duration_histogram_new,
metric_attributes={},
url_filter=url_filter,
excluded_urls=excluded_urls,
start_time=0,
**kwargs,
)
trace_config = aiohttp.TraceConfig(
trace_config_ctx_factory=cast(type[types.SimpleNamespace], _trace_config_ctx_factory)
)
trace_config.on_request_start.append(on_request_start)
trace_config.on_request_end.append(on_request_end)
trace_config.on_request_exception.append(on_request_exception)
return trace_config
def _instrument(
tracer_provider: TracerProvider | None = None,
meter_provider: MeterProvider | None = None,
url_filter: UrlFilterT = None,
request_hook: RequestHookT = None,
response_hook: ResponseHookT = None,
trace_configs: typing.Sequence[aiohttp.TraceConfig] | None = None,
sem_conv_opt_in_mode: _StabilityMode = _StabilityMode.DEFAULT,
captured_request_headers: list[str] | None = None,
captured_response_headers: list[str] | None = None,
sensitive_headers: list[str] | None = None,
):
"""Enables tracing of all ClientSessions
When a ClientSession gets created a TraceConfig is automatically added to
the session's trace_configs.
"""
trace_configs = trace_configs or ()
# pylint:disable=unused-argument
def instrumented_init(
wrapped: Callable[..., None],
_instance: aiohttp.ClientSession,
args: tuple[Any, ...],
kwargs: ClientSessionInitKwargs,
):
client_trace_configs = list(kwargs.get("trace_configs") or [])
client_trace_configs.extend(trace_configs)
trace_config = create_trace_config(
url_filter=url_filter,
request_hook=request_hook,
response_hook=response_hook,
tracer_provider=tracer_provider,
meter_provider=meter_provider,
sem_conv_opt_in_mode=sem_conv_opt_in_mode,
captured_request_headers=captured_request_headers,
captured_response_headers=captured_response_headers,
sensitive_headers=sensitive_headers,
)
setattr(trace_config, "_is_instrumented_by_opentelemetry", True)
client_trace_configs.append(trace_config)
kwargs["trace_configs"] = client_trace_configs
return wrapped(*args, **kwargs)
wrapt.wrap_function_wrapper( # type: ignore[reportUnknownVariableType]
aiohttp.ClientSession, "__init__", instrumented_init
)
def _uninstrument():
"""Disables instrumenting for all newly created ClientSessions"""
unwrap(aiohttp.ClientSession, "__init__")
def _uninstrument_session(client_session: aiohttp.ClientSession):
"""Disables instrumentation for the given ClientSession"""
# pylint: disable=protected-access
trace_configs = client_session._trace_configs
client_session._trace_configs = [
trace_config for trace_config in trace_configs if not hasattr(trace_config, "_is_instrumented_by_opentelemetry")
]
class AioHttpClientInstrumentor(BaseInstrumentor):
"""An instrumentor for aiohttp client sessions
See `BaseInstrumentor`
"""
def instrumentation_dependencies(self) -> Collection[str]:
return _instruments
def _instrument(self, **kwargs: Unpack[InstrumentKwargs]):
"""Instruments aiohttp ClientSession
Args:
**kwargs: Optional arguments
``tracer_provider``: a TracerProvider, defaults to global
``meter_provider``: a MeterProvider, defaults to global
``url_filter``: A callback to process the requested URL prior to adding
it as a span attribute. This can be useful to remove sensitive data
such as API keys or user personal information.
``request_hook``: An optional callback that is invoked right after a span is created.
``response_hook``: An optional callback which is invoked right before the span is finished processing a response.
``trace_configs``: An optional list of aiohttp.TraceConfig items, allowing customize enrichment of spans
based on aiohttp events (see specification: https://docs.aiohttp.org/en/stable/tracing_reference.html)
"""
_OpenTelemetrySemanticConventionStability._initialize()
_sem_conv_opt_in_mode = _OpenTelemetrySemanticConventionStability._get_opentelemetry_stability_opt_in_mode(
_OpenTelemetryStabilitySignalType.HTTP,
)
_instrument(
tracer_provider=kwargs.get("tracer_provider"),
meter_provider=kwargs.get("meter_provider"),
url_filter=kwargs.get("url_filter"),
request_hook=kwargs.get("request_hook"),
response_hook=kwargs.get("response_hook"),
trace_configs=kwargs.get("trace_configs"),
sem_conv_opt_in_mode=_sem_conv_opt_in_mode,
captured_request_headers=get_custom_headers(OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_CLIENT_REQUEST),
captured_response_headers=get_custom_headers(OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_CLIENT_RESPONSE),
sensitive_headers=get_custom_headers(OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SANITIZE_FIELDS),
)
def _uninstrument(self, **kwargs: Unpack[UninstrumentKwargs]):
_uninstrument()
@staticmethod
def uninstrument_session(client_session: aiohttp.ClientSession):
"""Disables instrumentation for the given session"""
_uninstrument_session(client_session)
package.py 0000664 0000000 0000000 00000000252 15270700723 0047710 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aiohttp-client/src/opentelemetry/instrumentation/aiohttp_client # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
_instruments = ("aiohttp ~= 3.0",)
_supports_metrics = True
_semconv_status = "migration"
py.typed 0000664 0000000 0000000 00000000000 15270700723 0047431 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aiohttp-client/src/opentelemetry/instrumentation/aiohttp_client version.py 0000664 0000000 0000000 00000000144 15270700723 0050002 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aiohttp-client/src/opentelemetry/instrumentation/aiohttp_client # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
__version__ = "0.66b2"
test-requirements.txt 0000664 0000000 0000000 00000001162 15270700723 0040251 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aiohttp-client aiohttp==3.10.2
aiosignal==1.3.1
asgiref==3.8.1
async-timeout==4.0.3
blinker==1.7.0
certifi==2024.7.4
charset-normalizer==3.3.2
click==8.1.7
Deprecated==1.2.14
Flask==3.0.2
frozenlist==1.4.1
http_server_mock==1.7
idna==3.7
iniconfig==2.0.0
itsdangerous==2.1.2
Jinja2==3.1.6
MarkupSafe==2.1.5
multidict==6.0.5
packaging==24.0
pluggy==1.6.0
py-cpuinfo==9.0.0
pytest==7.4.4
requests==2.33.1
tomli==2.0.1
typing_extensions==4.12.2
urllib3==2.7.0
Werkzeug==3.0.6
wrapt==1.16.0
yarl==1.9.4
zipp==3.19.2
-e opentelemetry-instrumentation
-e util/opentelemetry-util-http
-e instrumentation/opentelemetry-instrumentation-aiohttp-client
tests/ 0000775 0000000 0000000 00000000000 15270700723 0035152 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aiohttp-client __init__.py 0000664 0000000 0000000 00000000000 15270700723 0037251 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aiohttp-client/tests test_aiohttp_client_integration.py 0000664 0000000 0000000 00000155624 15270700723 0044211 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aiohttp-client/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
# pylint: disable=too-many-lines
import asyncio
import contextlib
import os
import typing
import unittest
import urllib.parse
from http import HTTPStatus
from unittest import mock
import aiohttp
import aiohttp.test_utils
import yarl
from http_server_mock import HttpServerMock
from opentelemetry import trace as trace_api
from opentelemetry.instrumentation import aiohttp_client
from opentelemetry.instrumentation._semconv import (
HTTP_DURATION_HISTOGRAM_BUCKETS_NEW,
HTTP_DURATION_HISTOGRAM_BUCKETS_OLD,
OTEL_SEMCONV_STABILITY_OPT_IN,
_OpenTelemetrySemanticConventionStability,
_StabilityMode,
)
from opentelemetry.instrumentation.aiohttp_client import (
AioHttpClientInstrumentor,
)
from opentelemetry.instrumentation.utils import (
suppress_http_instrumentation,
suppress_instrumentation,
)
from opentelemetry.semconv._incubating.attributes.http_attributes import (
HTTP_HOST,
HTTP_METHOD,
HTTP_STATUS_CODE,
HTTP_URL,
)
from opentelemetry.semconv._incubating.attributes.net_attributes import (
NET_PEER_NAME,
NET_PEER_PORT,
)
from opentelemetry.semconv._incubating.attributes.server_attributes import (
SERVER_ADDRESS,
SERVER_PORT,
)
from opentelemetry.semconv.attributes.error_attributes import ERROR_TYPE
from opentelemetry.semconv.attributes.http_attributes import (
HTTP_REQUEST_METHOD,
HTTP_REQUEST_METHOD_ORIGINAL,
HTTP_RESPONSE_STATUS_CODE,
)
from opentelemetry.semconv.attributes.url_attributes import URL_FULL
from opentelemetry.test.test_base import TestBase
from opentelemetry.trace import Span, StatusCode
from opentelemetry.util._importlib_metadata import entry_points
def run_with_test_server(runnable: typing.Callable, url: str, handler: typing.Callable) -> tuple[str, int]:
async def do_request():
app = aiohttp.web.Application()
parsed_url = urllib.parse.urlparse(url)
app.add_routes([aiohttp.web.get(parsed_url.path, handler)])
app.add_routes([aiohttp.web.post(parsed_url.path, handler)])
app.add_routes([aiohttp.web.patch(parsed_url.path, handler)])
with contextlib.suppress(aiohttp.ClientError):
async with aiohttp.test_utils.TestServer(app) as server:
netloc = (server.host, server.port)
await server.start_server()
await runnable(server)
return netloc
return asyncio.run(do_request())
SCOPE = "opentelemetry.instrumentation.aiohttp_client"
# pylint: disable=too-many-public-methods
class TestAioHttpIntegration(TestBase):
_test_status_codes = (
(HTTPStatus.OK, StatusCode.UNSET),
(HTTPStatus.TEMPORARY_REDIRECT, StatusCode.UNSET),
(HTTPStatus.NOT_FOUND, StatusCode.ERROR),
(HTTPStatus.BAD_REQUEST, StatusCode.ERROR),
(HTTPStatus.SERVICE_UNAVAILABLE, StatusCode.ERROR),
(HTTPStatus.GATEWAY_TIMEOUT, StatusCode.ERROR),
)
def setUp(self):
super().setUp()
_OpenTelemetrySemanticConventionStability._initialized = False
def _assert_spans(self, spans, num_spans=1):
finished_spans = self.memory_exporter.get_finished_spans()
self.assertEqual(num_spans, len(finished_spans))
self.assertEqual(
[
(
span.name,
(span.status.status_code, span.status.description),
dict(span.attributes),
)
for span in finished_spans
],
spans,
)
def _assert_metrics(self, num_metrics: int = 1):
metrics = self.get_sorted_metrics(SCOPE)
self.assertEqual(len(metrics), num_metrics)
return metrics
def _assert_single_span(self):
"""Assert that exactly one span was created and return it."""
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(1, len(spans))
return spans[0]
@staticmethod
def _http_request(
trace_config,
url: str,
method: str = "GET",
status_code: int = HTTPStatus.OK,
request_handler: typing.Callable = None,
**kwargs,
) -> tuple[str, int]:
"""Helper to start an aiohttp test server and send an actual HTTP request to it."""
async def default_handler(request):
assert "traceparent" in request.headers
return aiohttp.web.Response(status=int(status_code))
async def client_request(server: aiohttp.test_utils.TestServer):
async with aiohttp.test_utils.TestClient(server, trace_configs=[trace_config]) as client:
await client.request(method, url, trace_request_ctx={}, **kwargs)
handler = request_handler or default_handler
return run_with_test_server(client_request, url, handler)
def test_status_codes(self):
index = 0
for status_code, span_status in self._test_status_codes:
with self.subTest(status_code=status_code):
path = "test-path?query=param#foobar"
host, port = self._http_request(
trace_config=aiohttp_client.create_trace_config(),
url=f"/{path}",
status_code=status_code,
)
url = f"http://{host}:{port}/{path}"
attributes = {
HTTP_METHOD: "GET",
HTTP_URL: url,
HTTP_STATUS_CODE: status_code,
}
spans = [("GET", (span_status, None), attributes)]
self._assert_spans(spans)
self.memory_exporter.clear()
metrics = self._assert_metrics(1)
duration_data_point = metrics[0].data.data_points[index]
self.assertEqual(
dict(duration_data_point.attributes),
{
HTTP_STATUS_CODE: status_code,
HTTP_METHOD: "GET",
HTTP_HOST: host,
NET_PEER_NAME: host,
NET_PEER_PORT: port,
},
)
self.assertEqual(
duration_data_point.explicit_bounds,
HTTP_DURATION_HISTOGRAM_BUCKETS_OLD,
)
index += 1
def test_status_codes_new_semconv(self):
index = 0
for status_code, span_status in self._test_status_codes:
with self.subTest(status_code=status_code):
path = "test-path?query=param#foobar"
host, port = self._http_request(
trace_config=aiohttp_client.create_trace_config(sem_conv_opt_in_mode=_StabilityMode.HTTP),
url=f"/{path}",
status_code=status_code,
)
url = f"http://{host}:{port}/{path}"
attributes = {
HTTP_REQUEST_METHOD: "GET",
URL_FULL: url,
HTTP_RESPONSE_STATUS_CODE: status_code,
SERVER_ADDRESS: host,
SERVER_PORT: port,
}
if status_code >= 400:
attributes[ERROR_TYPE] = str(status_code.value)
spans = [("GET", (span_status, None), attributes)]
self._assert_spans(spans)
self.memory_exporter.clear()
metrics = self._assert_metrics(1)
duration_data_point = metrics[0].data.data_points[index]
self.assertEqual(
duration_data_point.attributes.get(HTTP_RESPONSE_STATUS_CODE),
status_code,
)
self.assertEqual(
duration_data_point.attributes.get(HTTP_REQUEST_METHOD),
"GET",
)
if status_code >= 400:
self.assertEqual(
duration_data_point.attributes.get(ERROR_TYPE),
str(status_code.value),
)
self.assertEqual(
duration_data_point.explicit_bounds,
HTTP_DURATION_HISTOGRAM_BUCKETS_NEW,
)
index += 1
def test_status_codes_both_semconv(self):
index = 0
for status_code, span_status in self._test_status_codes:
with self.subTest(status_code=status_code):
path = "test-path?query=param#foobar"
host, port = self._http_request(
trace_config=aiohttp_client.create_trace_config(sem_conv_opt_in_mode=_StabilityMode.HTTP_DUP),
url=f"/{path}",
status_code=status_code,
)
url = f"http://{host}:{port}/{path}"
attributes = {
HTTP_REQUEST_METHOD: "GET",
HTTP_METHOD: "GET",
HTTP_HOST: host,
URL_FULL: url,
HTTP_URL: url,
HTTP_RESPONSE_STATUS_CODE: status_code,
HTTP_STATUS_CODE: status_code,
SERVER_ADDRESS: host,
SERVER_PORT: port,
NET_PEER_PORT: port,
}
if status_code >= 400:
attributes[ERROR_TYPE] = str(status_code.value)
spans = [("GET", (span_status, None), attributes)]
self._assert_spans(spans, 1)
self.memory_exporter.clear()
metrics = self._assert_metrics(2)
duration_data_point = metrics[0].data.data_points[index]
self.assertEqual(
duration_data_point.attributes.get(HTTP_STATUS_CODE),
status_code,
)
self.assertEqual(
duration_data_point.attributes.get(HTTP_METHOD),
"GET",
)
self.assertEqual(
duration_data_point.attributes.get(ERROR_TYPE),
None,
)
duration_data_point = metrics[1].data.data_points[index]
self.assertEqual(
duration_data_point.attributes.get(HTTP_RESPONSE_STATUS_CODE),
status_code,
)
self.assertEqual(
duration_data_point.attributes.get(HTTP_REQUEST_METHOD),
"GET",
)
if status_code >= 400:
self.assertEqual(
duration_data_point.attributes.get(ERROR_TYPE),
str(status_code.value),
)
index += 1
def test_metrics(self):
with self.subTest(status_code=200):
host, port = self._http_request(
trace_config=aiohttp_client.create_trace_config(),
url="/test-path?query=param#foobar",
status_code=200,
)
metrics = self._assert_metrics(1)
self.assertEqual(len(metrics[0].data.data_points), 1)
duration_data_point = metrics[0].data.data_points[0]
self.assertEqual(
dict(metrics[0].data.data_points[0].attributes),
{
HTTP_STATUS_CODE: 200,
HTTP_METHOD: "GET",
HTTP_HOST: host,
NET_PEER_NAME: host,
NET_PEER_PORT: port,
},
)
self.assertEqual(duration_data_point.count, 1)
self.assertTrue(duration_data_point.min > 0)
self.assertTrue(duration_data_point.max > 0)
self.assertTrue(duration_data_point.sum > 0)
def test_schema_url(self):
with self.subTest(status_code=200):
self._http_request(
trace_config=aiohttp_client.create_trace_config(),
url="/test-path?query=param#foobar",
status_code=200,
)
span = self.memory_exporter.get_finished_spans()[0]
self.assertEqual(
span.instrumentation_scope.schema_url,
"https://opentelemetry.io/schemas/1.11.0",
)
self.memory_exporter.clear()
def test_schema_url_new_semconv(self):
with self.subTest(status_code=200):
self._http_request(
trace_config=aiohttp_client.create_trace_config(sem_conv_opt_in_mode=_StabilityMode.HTTP),
url="/test-path?query=param#foobar",
status_code=200,
)
span = self.memory_exporter.get_finished_spans()[0]
self.assertEqual(
span.instrumentation_scope.schema_url,
"https://opentelemetry.io/schemas/1.21.0",
)
self.memory_exporter.clear()
def test_schema_url_both_semconv(self):
with self.subTest(status_code=200):
self._http_request(
trace_config=aiohttp_client.create_trace_config(sem_conv_opt_in_mode=_StabilityMode.HTTP_DUP),
url="/test-path?query=param#foobar",
status_code=200,
)
span = self.memory_exporter.get_finished_spans()[0]
self.assertEqual(
span.instrumentation_scope.schema_url,
"https://opentelemetry.io/schemas/1.21.0",
)
self.memory_exporter.clear()
def test_not_recording(self):
mock_tracer = mock.Mock()
mock_span = mock.Mock()
mock_span.is_recording.return_value = False
mock_tracer.start_span.return_value = mock_span
with mock.patch("opentelemetry.trace.get_tracer"):
# pylint: disable=W0612
self._http_request(
trace_config=aiohttp_client.create_trace_config(),
url="/test-path?query=param#foobar",
)
self.assertFalse(mock_span.is_recording())
self.assertTrue(mock_span.is_recording.called)
self.assertFalse(mock_span.set_attribute.called)
self.assertFalse(mock_span.set_status.called)
def test_hooks(self):
method = "PATCH"
path = "/some/path"
expected = "PATCH - /some/path"
def request_hook(span: Span, params: aiohttp.TraceRequestStartParams):
span.update_name(f"{params.method} - {params.url.path}")
def response_hook(
span: Span,
params: aiohttp.TraceRequestEndParams | aiohttp.TraceRequestExceptionParams,
):
span.set_attribute("response_hook_attr", "value")
host, port = self._http_request(
trace_config=aiohttp_client.create_trace_config(
request_hook=request_hook,
response_hook=response_hook,
),
method=method,
url=path,
status_code=HTTPStatus.OK,
)
for span in self.memory_exporter.get_finished_spans():
self.assertEqual(span.name, expected)
self.assertEqual(
(span.status.status_code, span.status.description),
(StatusCode.UNSET, None),
)
self.assertEqual(span.attributes[HTTP_METHOD], method)
self.assertEqual(
span.attributes[HTTP_URL],
f"http://{host}:{port}{path}",
)
self.assertEqual(span.attributes[HTTP_STATUS_CODE], HTTPStatus.OK)
self.assertIn("response_hook_attr", span.attributes)
self.assertEqual(span.attributes["response_hook_attr"], "value")
self.memory_exporter.clear()
def test_url_filter_option(self):
# Strips all query params from URL before adding as a span attribute.
def strip_query_params(url: yarl.URL) -> str:
return str(url.with_query(None))
host, port = self._http_request(
trace_config=aiohttp_client.create_trace_config(url_filter=strip_query_params),
url="/some/path?query=param&other=param2",
status_code=HTTPStatus.OK,
)
self._assert_spans(
[
(
"GET",
(StatusCode.UNSET, None),
{
HTTP_METHOD: "GET",
HTTP_URL: f"http://{host}:{port}/some/path",
HTTP_STATUS_CODE: int(HTTPStatus.OK),
},
)
]
)
def test_connection_errors(self):
trace_configs = [aiohttp_client.create_trace_config()]
for url, expected_status in (
("http://this-is-unknown.local/", StatusCode.ERROR),
("http://127.0.0.1:1/", StatusCode.ERROR),
):
with self.subTest(expected_status=expected_status):
async def do_request(url):
async with aiohttp.ClientSession(
trace_configs=trace_configs,
) as session:
async with session.get(url):
pass
with self.assertRaises(aiohttp.ClientConnectorError):
asyncio.run(do_request(url))
self._assert_spans(
[
(
"GET",
(expected_status, "ClientConnectorError"),
{
HTTP_METHOD: "GET",
HTTP_URL: url,
},
)
]
)
self.memory_exporter.clear()
def test_basic_exception(self):
async def request_handler(request):
assert "traceparent" in request.headers
host, port = self._http_request(
trace_config=aiohttp_client.create_trace_config(),
url="/test",
request_handler=request_handler,
)
span = self.memory_exporter.get_finished_spans()[0]
self.assertEqual(len(span.events), 1)
self.assertEqual(span.events[0].name, "exception")
self._assert_spans(
[
(
"GET",
(StatusCode.ERROR, "ServerDisconnectedError"),
{
HTTP_METHOD: "GET",
HTTP_URL: f"http://{host}:{port}/test",
},
)
]
)
metrics = self._assert_metrics(1)
duration_data_point = metrics[0].data.data_points[0]
self.assertEqual(
dict(duration_data_point.attributes),
{
HTTP_METHOD: "GET",
HTTP_HOST: host,
NET_PEER_NAME: host,
NET_PEER_PORT: port,
},
)
def test_basic_exception_new_semconv(self):
async def request_handler(request):
assert "traceparent" in request.headers
host, port = self._http_request(
trace_config=aiohttp_client.create_trace_config(sem_conv_opt_in_mode=_StabilityMode.HTTP),
url="/test",
request_handler=request_handler,
)
span = self.memory_exporter.get_finished_spans()[0]
self.assertEqual(len(span.events), 1)
self.assertEqual(span.events[0].name, "exception")
self._assert_spans(
[
(
"GET",
(StatusCode.ERROR, "ServerDisconnectedError"),
{
HTTP_REQUEST_METHOD: "GET",
URL_FULL: f"http://{host}:{port}/test",
ERROR_TYPE: "ServerDisconnectedError",
SERVER_ADDRESS: host,
SERVER_PORT: port,
},
)
]
)
metrics = self._assert_metrics(1)
duration_data_point = metrics[0].data.data_points[0]
self.assertEqual(
dict(duration_data_point.attributes),
{
HTTP_REQUEST_METHOD: "GET",
ERROR_TYPE: "ServerDisconnectedError",
SERVER_ADDRESS: host,
SERVER_PORT: port,
},
)
def test_basic_exception_both_semconv(self):
async def request_handler(request):
assert "traceparent" in request.headers
host, port = self._http_request(
trace_config=aiohttp_client.create_trace_config(sem_conv_opt_in_mode=_StabilityMode.HTTP_DUP),
url="/test",
request_handler=request_handler,
)
span = self.memory_exporter.get_finished_spans()[0]
self.assertEqual(len(span.events), 1)
self.assertEqual(span.events[0].name, "exception")
self._assert_spans(
[
(
"GET",
(StatusCode.ERROR, "ServerDisconnectedError"),
{
HTTP_REQUEST_METHOD: "GET",
URL_FULL: f"http://{host}:{port}/test",
ERROR_TYPE: "ServerDisconnectedError",
HTTP_METHOD: "GET",
HTTP_URL: f"http://{host}:{port}/test",
HTTP_HOST: host,
SERVER_ADDRESS: host,
SERVER_PORT: port,
NET_PEER_PORT: port,
},
)
]
)
metrics = self._assert_metrics(2)
duration_data_point = metrics[0].data.data_points[0]
self.assertEqual(
dict(duration_data_point.attributes),
{
HTTP_METHOD: "GET",
HTTP_HOST: host,
NET_PEER_NAME: host,
NET_PEER_PORT: port,
},
)
duration_data_point = metrics[1].data.data_points[0]
self.assertEqual(
dict(duration_data_point.attributes),
{
HTTP_REQUEST_METHOD: "GET",
ERROR_TYPE: "ServerDisconnectedError",
SERVER_ADDRESS: host,
SERVER_PORT: port,
},
)
def test_timeout(self):
async def request_handler(request):
await asyncio.sleep(1)
assert "traceparent" in request.headers
return aiohttp.web.Response()
host, port = self._http_request(
trace_config=aiohttp_client.create_trace_config(),
url="/test_timeout",
request_handler=request_handler,
timeout=aiohttp.ClientTimeout(sock_read=0.01),
)
self._assert_spans(
[
(
"GET",
(StatusCode.ERROR, "SocketTimeoutError"),
{
HTTP_METHOD: "GET",
HTTP_URL: f"http://{host}:{port}/test_timeout",
},
)
]
)
def test_too_many_redirects(self):
async def request_handler(request):
# Create a redirect loop.
location = request.url
assert "traceparent" in request.headers
raise aiohttp.web.HTTPFound(location=location)
host, port = self._http_request(
trace_config=aiohttp_client.create_trace_config(),
url="/test_too_many_redirects",
request_handler=request_handler,
max_redirects=2,
)
self._assert_spans(
[
(
"GET",
(StatusCode.ERROR, "TooManyRedirects"),
{
HTTP_METHOD: "GET",
HTTP_URL: f"http://{host}:{port}/test_too_many_redirects",
},
)
]
)
def test_nonstandard_http_method(self):
trace_configs = [aiohttp_client.create_trace_config()]
app = HttpServerMock("nonstandard_method")
@app.route("/status/200", methods=["NONSTANDARD"])
def index():
return ("", 405, {})
url = "http://localhost:5000/status/200"
with app.run("localhost", 5000):
with self.subTest(url=url):
async def do_request(url):
async with aiohttp.ClientSession(
trace_configs=trace_configs,
) as session:
async with session.request("NONSTANDARD", url):
pass
asyncio.run(do_request(url))
self._assert_spans(
[
(
"HTTP",
(StatusCode.ERROR, None),
{
HTTP_METHOD: "_OTHER",
HTTP_URL: url,
HTTP_STATUS_CODE: int(HTTPStatus.METHOD_NOT_ALLOWED),
},
)
]
)
self.memory_exporter.clear()
def test_nonstandard_http_method_new_semconv(self):
trace_configs = [aiohttp_client.create_trace_config(sem_conv_opt_in_mode=_StabilityMode.HTTP)]
app = HttpServerMock("nonstandard_method")
@app.route("/status/200", methods=["NONSTANDARD"])
def index():
return ("", 405, {})
url = "http://localhost:5000/status/200"
with app.run("localhost", 5000):
with self.subTest(url=url):
async def do_request(url):
async with aiohttp.ClientSession(
trace_configs=trace_configs,
) as session:
async with session.request("NONSTANDARD", url):
pass
asyncio.run(do_request(url))
self._assert_spans(
[
(
"HTTP",
(StatusCode.ERROR, None),
{
HTTP_REQUEST_METHOD: "_OTHER",
URL_FULL: url,
HTTP_RESPONSE_STATUS_CODE: int(HTTPStatus.METHOD_NOT_ALLOWED),
HTTP_REQUEST_METHOD_ORIGINAL: "NONSTANDARD",
ERROR_TYPE: "405",
SERVER_ADDRESS: "localhost",
SERVER_PORT: 5000,
},
)
]
)
self.memory_exporter.clear()
def test_remove_sensitive_params(self):
trace_configs = [aiohttp_client.create_trace_config()]
app = HttpServerMock("test_remove_sensitive_params")
@app.route("/status/200")
def index():
return "hello"
url = "http://username:password@localhost:5000/status/200?Signature=secret"
with app.run("localhost", 5000):
with self.subTest(url=url):
async def do_request(url):
async with aiohttp.ClientSession(
trace_configs=trace_configs,
) as session:
async with session.get(url):
pass
asyncio.run(do_request(url))
self._assert_spans(
[
(
"GET",
(StatusCode.UNSET, None),
{
HTTP_METHOD: "GET",
HTTP_URL: ("http://REDACTED:REDACTED@localhost:5000/status/200?Signature=REDACTED"),
HTTP_STATUS_CODE: int(HTTPStatus.OK),
},
)
]
)
self.memory_exporter.clear()
def test_ignores_excluded_urls(self):
async def request_handler(request):
assert "traceparent" not in request.headers
return aiohttp.web.Response(status=HTTPStatus.OK)
for env_var in (
"OTEL_PYTHON_AIOHTTP_CLIENT_EXCLUDED_URLS",
"OTEL_PYTHON_EXCLUDED_URLS",
):
with self.subTest(env_var=env_var):
with mock.patch.dict(os.environ, {env_var: "/some/path"}, clear=True):
self._http_request(
trace_config=aiohttp_client.create_trace_config(),
request_handler=request_handler,
url="/some/path?query=param&other=param2",
status_code=HTTPStatus.OK,
)
self._assert_spans([], 0)
self._assert_metrics(0)
def test_metric_attributes_isolation(self):
async def success_handler(request):
assert "traceparent" in request.headers
return aiohttp.web.Response(status=HTTPStatus.OK)
async def timeout_handler(request):
await asyncio.sleep(60)
assert "traceparent" in request.headers
return aiohttp.web.Response(status=HTTPStatus.OK)
trace_config: aiohttp.TraceConfig = aiohttp_client.create_trace_config()
success_host, success_port = self._http_request(
trace_config=trace_config,
url="/success",
request_handler=success_handler,
)
timeout_host, timeout_port = self._http_request(
trace_config=trace_config,
url="/timeout",
request_handler=timeout_handler,
timeout=aiohttp.ClientTimeout(sock_read=0.01),
)
metrics = self._assert_metrics(1)
duration_dp_attributes = [dict(dp.attributes) for dp in metrics[0].data.data_points]
self.assertEqual(
[
{
HTTP_METHOD: "GET",
HTTP_HOST: success_host,
HTTP_STATUS_CODE: int(HTTPStatus.OK),
NET_PEER_NAME: success_host,
NET_PEER_PORT: success_port,
},
{
HTTP_METHOD: "GET",
HTTP_HOST: timeout_host,
NET_PEER_NAME: timeout_host,
NET_PEER_PORT: timeout_port,
},
],
duration_dp_attributes,
)
def test_custom_request_headers_captured(self):
"""Test that specified request headers are captured as span attributes."""
trace_config = aiohttp_client.create_trace_config(
captured_request_headers=["X-Custom-Header", "X-Another-Header"]
)
self._http_request(
trace_config=trace_config,
url="/test-path",
status_code=200,
headers={
"X-Custom-Header": "custom-value",
"X-Another-Header": "another-value",
"X-Excluded-Header": "excluded-value",
},
)
span = self._assert_single_span()
self.assertEqual(
span.attributes["http.request.header.x_custom_header"],
("custom-value",),
)
self.assertEqual(
span.attributes["http.request.header.x_another_header"],
("another-value",),
)
self.assertNotIn("http.request.header.x_excluded_header", span.attributes)
def test_custom_response_headers_captured(self):
"""Test that specified response headers are captured as span attributes."""
trace_config = aiohttp_client.create_trace_config(
captured_response_headers=["X-Custom-Header", "X-Another-Header"]
)
def custom_handler(_request):
headers = {
"X-Custom-Header": "custom-value",
"X-Another-Header": "another-value",
"X-Excluded-Header": "excluded-value",
}
return aiohttp.web.Response(status=200, text="OK", headers=headers)
self._http_request(
trace_config=trace_config,
url="/test-path",
status_code=200,
request_handler=custom_handler,
)
span = self._assert_single_span()
self.assertEqual(
span.attributes["http.response.header.x_custom_header"],
("custom-value",),
)
self.assertEqual(
span.attributes["http.response.header.x_another_header"],
("another-value",),
)
self.assertNotIn("http.response.header.x_excluded_header", span.attributes)
def test_custom_headers_not_captured_when_not_configured(self):
"""Test that headers are not captured when env vars are not set."""
trace_config = aiohttp_client.create_trace_config()
def custom_handler(_request):
return aiohttp.web.Response(
status=200,
text="OK",
headers={"X-Response-Header": "response-value"},
)
self._http_request(
trace_config=trace_config,
url="/test-path",
status_code=200,
request_handler=custom_handler,
headers={"X-Request-Header": "request-value"},
)
span = self._assert_single_span()
self.assertNotIn("http.request.header.x_request_header", span.attributes)
self.assertNotIn("http.response.header.x_response_header", span.attributes)
def test_sensitive_headers_sanitized(self):
"""Test that sensitive header values are redacted."""
trace_config = aiohttp_client.create_trace_config(
captured_request_headers=["Authorization", "X-Api-Key"],
captured_response_headers=["Set-Cookie", "X-Secret"],
sensitive_headers=[
"Authorization",
"X-Api-Key",
"Set-Cookie",
"X-Secret",
],
)
def custom_handler(_request):
response_headers = {
"Set-Cookie": "session=abc123",
"X-Secret": "secret",
}
return aiohttp.web.Response(status=200, text="OK", headers=response_headers)
self._http_request(
trace_config=trace_config,
url="/test-path",
status_code=200,
request_handler=custom_handler,
headers={
"Authorization": "Bearer secret-token",
"X-Api-Key": "secret-key",
},
)
span = self._assert_single_span()
self.assertEqual(
span.attributes["http.request.header.authorization"],
("[REDACTED]",),
)
self.assertEqual(
span.attributes["http.request.header.x_api_key"],
("[REDACTED]",),
)
self.assertEqual(
span.attributes["http.response.header.set_cookie"],
("[REDACTED]",),
)
self.assertEqual(
span.attributes["http.response.header.x_secret"],
("[REDACTED]",),
)
def test_custom_headers_with_regex(self):
"""Test that header capture works with regex patterns."""
trace_config = aiohttp_client.create_trace_config(
captured_request_headers=["X-Custom-Request-.*"],
captured_response_headers=["X-Custom-Response-.*"],
)
def custom_handler(_request):
response_headers = {
"X-Custom-Response-A": "value-A",
"X-Custom-Response-B": "value-B",
"X-Other-Response-Header": "other-value",
}
return aiohttp.web.Response(status=200, text="OK", headers=response_headers)
self._http_request(
trace_config=trace_config,
url="/test-path",
status_code=200,
request_handler=custom_handler,
headers={
"X-Custom-Request-One": "value-one",
"X-Custom-Request-Two": "value-two",
"X-Other-Request-Header": "other-value",
},
)
span = self._assert_single_span()
self.assertEqual(
span.attributes["http.request.header.x_custom_request_one"],
("value-one",),
)
self.assertEqual(
span.attributes["http.request.header.x_custom_request_two"],
("value-two",),
)
self.assertNotIn("http.request.header.x_other_request_header", span.attributes)
self.assertEqual(
span.attributes["http.response.header.x_custom_response_a"],
("value-A",),
)
self.assertEqual(
span.attributes["http.response.header.x_custom_response_b"],
("value-B",),
)
self.assertNotIn("http.response.header.x_other_response_header", span.attributes)
def test_custom_headers_case_insensitive(self):
"""Test that header capture is case-insensitive."""
trace_config = aiohttp_client.create_trace_config(
captured_request_headers=["x-request-header"],
captured_response_headers=["x-response-header"],
)
def custom_handler(_request):
response_headers = {"X-ReSPoNse-HeaDER": "custom-value"}
return aiohttp.web.Response(status=200, text="OK", headers=response_headers)
self._http_request(
trace_config=trace_config,
url="/test-path",
status_code=200,
request_handler=custom_handler,
headers={"X-ReQuESt-HeaDER": "custom-value"},
)
span = self._assert_single_span()
self.assertEqual(
span.attributes["http.request.header.x_request_header"],
("custom-value",),
)
self.assertEqual(
span.attributes["http.response.header.x_response_header"],
("custom-value",),
)
def test_multi_value_request_headers(self):
"""Test that headers with multiple values are captured correctly."""
trace_config = aiohttp_client.create_trace_config(captured_request_headers=["X-Multi-Value"])
self._http_request(
trace_config=trace_config,
url="/test-path",
status_code=200,
headers=(("X-Multi-Value", "value1"), ("X-Multi-Value", "value2")),
)
span = self._assert_single_span()
self.assertEqual(
span.attributes["http.request.header.x_multi_value"],
("value1", "value2"),
)
def test_standard_http_headers_captured(self):
"""Test that standard HTTP headers can be captured."""
trace_config = aiohttp_client.create_trace_config(
captured_request_headers=["Content-Type", "Accept"],
captured_response_headers=["Content-Type", "Server"],
)
def custom_handler(_request):
response_headers = {
"Content-Type": "text/plain",
"Server": "TestServer/1.0",
}
return aiohttp.web.Response(status=200, body=b"OK", headers=response_headers)
self._http_request(
trace_config=trace_config,
url="/test-path",
status_code=200,
request_handler=custom_handler,
headers={
"Content-Type": "application/json",
"Accept": "application/json",
},
)
span = self._assert_single_span()
self.assertEqual(
span.attributes["http.request.header.content_type"],
("application/json",),
)
self.assertEqual(
span.attributes["http.request.header.accept"],
("application/json",),
)
self.assertEqual(
span.attributes["http.response.header.content_type"],
("text/plain",),
)
self.assertEqual(
span.attributes["http.response.header.server"],
("TestServer/1.0",),
)
def test_capture_all_request_headers(self):
"""Test that all request headers can be captured with .* pattern."""
trace_config = aiohttp_client.create_trace_config(captured_request_headers=[".*"])
def custom_handler(_request):
return aiohttp.web.Response(status=200, text="OK")
self._http_request(
trace_config=trace_config,
url="/test-path",
status_code=200,
request_handler=custom_handler,
headers={
"X-Header-One": "value1",
"X-Header-Two": "value2",
"X-Header-Three": "value3",
},
)
span = self._assert_single_span()
self.assertEqual(
span.attributes["http.request.header.x_header_one"],
("value1",),
)
self.assertEqual(
span.attributes["http.request.header.x_header_two"],
("value2",),
)
self.assertEqual(
span.attributes["http.request.header.x_header_three"],
("value3",),
)
def test_capture_all_response_headers(self):
"""Test that all response headers can be captured with .* pattern."""
trace_config = aiohttp_client.create_trace_config(captured_response_headers=[".*"])
def custom_handler(_request):
response_headers = {
"X-Response-One": "value1",
"X-Response-Two": "value2",
"X-Response-Three": "value3",
}
return aiohttp.web.Response(status=200, text="OK", headers=response_headers)
self._http_request(
trace_config=trace_config,
url="/test-path",
status_code=200,
request_handler=custom_handler,
)
span = self._assert_single_span()
self.assertEqual(
span.attributes["http.response.header.x_response_one"],
("value1",),
)
self.assertEqual(
span.attributes["http.response.header.x_response_two"],
("value2",),
)
self.assertEqual(
span.attributes["http.response.header.x_response_three"],
("value3",),
)
def test_sanitize_with_regex_pattern(self):
"""Test that sanitization works with regex patterns."""
trace_config = aiohttp_client.create_trace_config(
captured_request_headers=["X-Test.*"],
sensitive_headers=[".*secret.*"],
)
self._http_request(
trace_config=trace_config,
url="/test-path",
status_code=200,
headers={
"X-Test": "normal-value",
"X-Test-Secret": "secret-value",
},
)
span = self._assert_single_span()
self.assertEqual(
span.attributes["http.request.header.x_test"],
("normal-value",),
)
self.assertEqual(
span.attributes["http.request.header.x_test_secret"],
("[REDACTED]",),
)
class TestAioHttpClientInstrumentor(TestBase):
URL = "/test-path"
def setUp(self):
super().setUp()
AioHttpClientInstrumentor().instrument()
_OpenTelemetrySemanticConventionStability._initialized = False
def tearDown(self):
super().tearDown()
AioHttpClientInstrumentor().uninstrument()
@staticmethod
# pylint:disable=unused-argument
async def default_handler(request):
return aiohttp.web.Response(status=200)
@staticmethod
def get_default_request(url: str = URL):
async def default_request(server: aiohttp.test_utils.TestServer):
async with aiohttp.test_utils.TestClient(server) as session:
await session.get(url)
return default_request
def _assert_spans(self, num_spans: int):
finished_spans = self.memory_exporter.get_finished_spans()
self.assertEqual(num_spans, len(finished_spans))
if num_spans == 0:
return None
if num_spans == 1:
return finished_spans[0]
return finished_spans
def _assert_metrics(self, num_metrics: int = 1):
metrics = self.get_sorted_metrics(SCOPE)
self.assertEqual(len(metrics), num_metrics)
return metrics
def test_instrument(self):
host, port = run_with_test_server(self.get_default_request(), self.URL, self.default_handler)
span = self._assert_spans(1)
self.assertEqual("GET", span.name)
self.assertEqual("GET", span.attributes[HTTP_METHOD])
self.assertEqual(
f"http://{host}:{port}/test-path",
span.attributes[HTTP_URL],
)
self.assertEqual(200, span.attributes[HTTP_STATUS_CODE])
metrics = self._assert_metrics(1)
duration_data_point = metrics[0].data.data_points[0]
self.assertEqual(duration_data_point.count, 1)
self.assertEqual(
dict(duration_data_point.attributes),
{
HTTP_HOST: host,
HTTP_STATUS_CODE: 200,
HTTP_METHOD: "GET",
NET_PEER_NAME: host,
NET_PEER_PORT: port,
},
)
def test_instrument_new_semconv(self):
AioHttpClientInstrumentor().uninstrument()
with mock.patch.dict("os.environ", {OTEL_SEMCONV_STABILITY_OPT_IN: "http"}):
AioHttpClientInstrumentor().instrument()
host, port = run_with_test_server(self.get_default_request(), self.URL, self.default_handler)
span = self._assert_spans(1)
self.assertEqual("GET", span.name)
self.assertEqual("GET", span.attributes[HTTP_REQUEST_METHOD])
self.assertEqual(
f"http://{host}:{port}/test-path",
span.attributes[URL_FULL],
)
self.assertEqual(200, span.attributes[HTTP_RESPONSE_STATUS_CODE])
metrics = self._assert_metrics(1)
duration_data_point = metrics[0].data.data_points[0]
self.assertEqual(duration_data_point.count, 1)
self.assertEqual(
dict(duration_data_point.attributes),
{
HTTP_RESPONSE_STATUS_CODE: 200,
HTTP_REQUEST_METHOD: "GET",
SERVER_ADDRESS: host,
SERVER_PORT: port,
},
)
def test_instrument_both_semconv(self):
AioHttpClientInstrumentor().uninstrument()
with mock.patch.dict("os.environ", {OTEL_SEMCONV_STABILITY_OPT_IN: "http/dup"}):
AioHttpClientInstrumentor().instrument()
host, port = run_with_test_server(self.get_default_request(), self.URL, self.default_handler)
url = f"http://{host}:{port}/test-path"
span = self._assert_spans(1)
self.assertEqual("GET", span.name)
self.assertEqual(
dict(span.attributes),
{
HTTP_REQUEST_METHOD: "GET",
HTTP_METHOD: "GET",
HTTP_HOST: host,
URL_FULL: url,
HTTP_URL: url,
HTTP_RESPONSE_STATUS_CODE: 200,
HTTP_STATUS_CODE: 200,
SERVER_ADDRESS: host,
SERVER_PORT: port,
NET_PEER_PORT: port,
},
)
metrics = self._assert_metrics(2)
duration_data_point = metrics[0].data.data_points[0]
self.assertEqual(duration_data_point.count, 1)
self.assertEqual(
dict(duration_data_point.attributes),
{
HTTP_STATUS_CODE: 200,
HTTP_METHOD: "GET",
HTTP_HOST: host,
NET_PEER_NAME: host,
NET_PEER_PORT: port,
},
)
duration_data_point = metrics[1].data.data_points[0]
self.assertEqual(duration_data_point.count, 1)
self.assertEqual(
dict(duration_data_point.attributes),
{
HTTP_RESPONSE_STATUS_CODE: 200,
HTTP_REQUEST_METHOD: "GET",
SERVER_ADDRESS: host,
SERVER_PORT: port,
},
)
def test_instrument_with_custom_trace_config(self):
trace_config = aiohttp.TraceConfig()
AioHttpClientInstrumentor().uninstrument()
AioHttpClientInstrumentor().instrument(trace_configs=[trace_config])
async def make_request(server: aiohttp.test_utils.TestServer):
async with aiohttp.test_utils.TestClient(server) as client:
trace_configs = client.session._trace_configs
self.assertEqual(2, len(trace_configs))
self.assertTrue(trace_config in trace_configs)
async with client as session:
await session.get(TestAioHttpClientInstrumentor.URL)
run_with_test_server(make_request, self.URL, self.default_handler)
self._assert_spans(1)
def test_every_request_by_new_session_creates_one_span(self):
async def make_request(server: aiohttp.test_utils.TestServer):
async with aiohttp.test_utils.TestClient(server) as client:
async with client as session:
await session.get(TestAioHttpClientInstrumentor.URL)
for request_no in range(3):
self.memory_exporter.clear()
with self.subTest(request_no=request_no):
run_with_test_server(make_request, self.URL, self.default_handler)
self._assert_spans(1)
def test_instrument_with_existing_trace_config(self):
trace_config = aiohttp.TraceConfig()
async def create_session(server: aiohttp.test_utils.TestServer):
async with aiohttp.test_utils.TestClient(server, trace_configs=[trace_config]) as client:
# pylint:disable=protected-access
trace_configs = client.session._trace_configs
self.assertEqual(2, len(trace_configs))
self.assertTrue(trace_config in trace_configs)
async with client as session:
await session.get(TestAioHttpClientInstrumentor.URL)
run_with_test_server(create_session, self.URL, self.default_handler)
self._assert_spans(1)
def test_no_op_tracer_provider(self):
AioHttpClientInstrumentor().uninstrument()
AioHttpClientInstrumentor().instrument(tracer_provider=trace_api.NoOpTracerProvider())
run_with_test_server(self.get_default_request(), self.URL, self.default_handler)
spans_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans_list), 0)
def test_uninstrument(self):
AioHttpClientInstrumentor().uninstrument()
run_with_test_server(self.get_default_request(), self.URL, self.default_handler)
self._assert_spans(0)
AioHttpClientInstrumentor().instrument()
run_with_test_server(self.get_default_request(), self.URL, self.default_handler)
self._assert_spans(1)
def test_uninstrument_session(self):
async def uninstrument_request(server: aiohttp.test_utils.TestServer):
client = aiohttp.test_utils.TestClient(server)
AioHttpClientInstrumentor().uninstrument_session(client.session)
async with client as session:
await session.get(self.URL)
run_with_test_server(uninstrument_request, self.URL, self.default_handler)
self._assert_spans(0)
run_with_test_server(self.get_default_request(), self.URL, self.default_handler)
self._assert_spans(1)
def test_suppress_instrumentation(self):
for suppress_ctx in (
suppress_instrumentation,
suppress_http_instrumentation,
):
with self.subTest(suppress_ctx=suppress_ctx.__name__):
with suppress_ctx():
run_with_test_server(
self.get_default_request(),
self.URL,
self.default_handler,
)
self._assert_spans(0)
self._assert_metrics(0)
@staticmethod
def make_suppressed_request(suppress_ctx):
async def suppressed_request(server: aiohttp.test_utils.TestServer):
async with aiohttp.test_utils.TestClient(server) as client:
with suppress_ctx():
await client.get(TestAioHttpClientInstrumentor.URL)
return suppressed_request
def test_suppress_instrumentation_after_creation(self):
for suppress_ctx in (
suppress_instrumentation,
suppress_http_instrumentation,
):
with self.subTest(suppress_ctx=suppress_ctx.__name__):
run_with_test_server(
self.make_suppressed_request(suppress_ctx),
self.URL,
self.default_handler,
)
self._assert_spans(0)
self._assert_metrics(0)
def test_suppress_instrumentation_with_server_exception(self):
# pylint:disable=unused-argument
async def raising_handler(request):
raise aiohttp.web.HTTPFound(location=self.URL)
for suppress_ctx in (
suppress_instrumentation,
suppress_http_instrumentation,
):
with self.subTest(suppress_ctx=suppress_ctx.__name__):
run_with_test_server(
self.make_suppressed_request(suppress_ctx),
self.URL,
raising_handler,
)
self._assert_spans(0)
self._assert_metrics(0)
def test_url_filter(self):
def strip_query_params(url: yarl.URL) -> str:
return str(url.with_query(None))
AioHttpClientInstrumentor().uninstrument()
AioHttpClientInstrumentor().instrument(url_filter=strip_query_params)
url = "/test-path?query=params"
host, port = run_with_test_server(self.get_default_request(url), url, self.default_handler)
span = self._assert_spans(1)
self.assertEqual(
f"http://{host}:{port}/test-path",
span.attributes[HTTP_URL],
)
def test_hooks(self):
def request_hook(span: Span, params: aiohttp.TraceRequestStartParams):
span.update_name(f"{params.method} - {params.url.path}")
def response_hook(
span: Span,
params: aiohttp.TraceRequestEndParams | aiohttp.TraceRequestExceptionParams,
):
span.set_attribute("response_hook_attr", "value")
AioHttpClientInstrumentor().uninstrument()
AioHttpClientInstrumentor().instrument(request_hook=request_hook, response_hook=response_hook)
url = "/test-path"
run_with_test_server(self.get_default_request(url), url, self.default_handler)
span = self._assert_spans(1)
self.assertEqual("GET - /test-path", span.name)
self.assertIn("response_hook_attr", span.attributes)
self.assertEqual(span.attributes["response_hook_attr"], "value")
@mock.patch.dict(os.environ, {"OTEL_PYTHON_AIOHTTP_CLIENT_EXCLUDED_URLS": "/test-path"})
def test_ignores_excluded_urls(self):
# need the env var set at instrument time
AioHttpClientInstrumentor().uninstrument()
AioHttpClientInstrumentor().instrument()
url = "/test-path?query=params"
run_with_test_server(self.get_default_request(url), url, self.default_handler)
self._assert_spans(0)
self._assert_metrics(0)
class TestLoadingAioHttpInstrumentor(unittest.TestCase):
def test_loading_instrumentor(self):
(entry_point,) = entry_points(group="opentelemetry_instrumentor", name="aiohttp-client")
instrumentor = entry_point.load()()
self.assertIsInstance(instrumentor, AioHttpClientInstrumentor)
opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aiohttp-server/ 0000775 0000000 0000000 00000000000 15270700723 0034117 5 ustar 00root root 0000000 0000000 README.rst 0000664 0000000 0000000 00000001656 15270700723 0035537 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aiohttp-server OpenTelemetry aiohttp server Integration
========================================
|pypi|
.. |pypi| image:: https://badge.fury.io/py/opentelemetry-instrumentation-aiohttp-server.svg
:target: https://pypi.org/project/opentelemetry-instrumentation-aiohttp-server/
This library allows tracing HTTP requests made by the
`aiohttp server `_ library.
Installation
------------
::
pip install opentelemetry-instrumentation-aiohttp-server
References
----------
* `OpenTelemetry aiohttp server Instrumentation `_
* `aiohttp Tracing Reference `_
* `OpenTelemetry Project `_
* `OpenTelemetry Python Examples `_
pyproject.toml 0000664 0000000 0000000 00000003333 15270700723 0036756 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aiohttp-server [build-system]
requires = ["hatchling"]
build-backend = "hatchling.build"
[project]
name = "opentelemetry-instrumentation-aiohttp-server"
dynamic = ["version"]
description = "Aiohttp server instrumentation for OpenTelemetry"
readme = "README.rst"
license = "Apache-2.0"
requires-python = ">=3.10"
authors = [
{ name = "OpenTelemetry Authors", email = "cncf-opentelemetry-contributors@lists.cncf.io"}
]
classifiers = [
"Development Status :: 4 - Beta",
"Intended Audience :: Developers",
"License :: OSI Approved :: Apache Software License",
"Programming Language :: Python",
"Programming Language :: Python :: 3",
"Programming Language :: Python :: 3.10",
"Programming Language :: Python :: 3.11",
"Programming Language :: Python :: 3.12",
"Programming Language :: Python :: 3.13",
"Programming Language :: Python :: 3.14",
]
dependencies = [
"opentelemetry-api ~= 1.12",
"opentelemetry-instrumentation == 0.66b2",
"opentelemetry-semantic-conventions == 0.66b2",
"opentelemetry-util-http == 0.66b2",
"wrapt >= 1.0.0, < 3.0.0",
]
[project.optional-dependencies]
instruments = [
"aiohttp ~= 3.0",
]
[project.entry-points.opentelemetry_instrumentor]
aiohttp-server = "opentelemetry.instrumentation.aiohttp_server:AioHttpServerInstrumentor"
[project.urls]
Homepage = "https://github.com/open-telemetry/opentelemetry-python-contrib/tree/main/instrumentation/opentelemetry-instrumentation-aiohttp-server"
Repository = "https://github.com/open-telemetry/opentelemetry-python-contrib"
[tool.hatch.version]
path = "src/opentelemetry/instrumentation/aiohttp_server/version.py"
[tool.hatch.build.targets.sdist]
include = [
"/src",
"/tests",
]
[tool.hatch.build.targets.wheel]
packages = ["src/opentelemetry"]
src/ 0000775 0000000 0000000 00000000000 15270700723 0034627 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aiohttp-server opentelemetry/ 0000775 0000000 0000000 00000000000 15270700723 0037523 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aiohttp-server/src instrumentation/ 0000775 0000000 0000000 00000000000 15270700723 0042766 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aiohttp-server/src/opentelemetry aiohttp_server/ 0000775 0000000 0000000 00000000000 15270700723 0046024 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aiohttp-server/src/opentelemetry/instrumentation __init__.py 0000664 0000000 0000000 00000050045 15270700723 0050141 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aiohttp-server/src/opentelemetry/instrumentation/aiohttp_server # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
"""
The opentelemetry-instrumentation-aiohttp-server package allows tracing HTTP
requests made by the aiohttp server library.
Usage
-----
.. code:: python
from aiohttp import web
from opentelemetry.instrumentation.aiohttp_server import (
AioHttpServerInstrumentor
)
from opentelemetry.sdk.resources import Resource
from opentelemetry.sdk.trace import TracerProvider
from opentelemetry.sdk.trace.sampling import ParentBased, TraceIdRatioBased
# Optional: configure non-default TracerProvider, resource, sampler
resource = Resource(attributes={"service.name": "my-aiohttp-service"})
sampler = ParentBased(root=TraceIdRatioBased(rate=0.25)) # sample 25% of traces
AioHttpServerInstrumentor().instrument(tracer_provider=TracerProvider(resource=resource, sampler=sampler))
async def hello(request):
return web.Response(text="Hello, world")
app = web.Application()
app.add_routes([web.get('/', hello)])
web.run_app(app)
Configuration
-------------
Exclude lists
*************
To exclude certain URLs from tracking, set the environment variable ``OTEL_PYTHON_AIOHTTP_SERVER_EXCLUDED_URLS``
(or ``OTEL_PYTHON_EXCLUDED_URLS`` to cover all instrumentations) to a string of comma delimited regexes that match the
URLs.
For example,
::
export OTEL_PYTHON_AIOHTTP_SERVER_EXCLUDED_URLS="client/.*/info,healthcheck"
will exclude requests such as ``https://site/client/123/info`` and ``https://site/xyz/healthcheck``.
Capture HTTP request and response headers
*****************************************
You can configure the agent to capture specified HTTP headers as span attributes, according to the
`semantic conventions `_.
Request headers
***************
To capture HTTP request headers as span attributes, set the environment variable
``OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_REQUEST`` to a comma delimited list of HTTP header names.
For example,
::
export OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_REQUEST="content-type,custom_request_header"
will extract ``content-type`` and ``custom_request_header`` from the request headers and add them as span attributes.
Request header names in aiohttp are case-insensitive. So, giving the header name as ``CUStom-Header`` in the environment
variable will capture the header named ``custom-header``.
Regular expressions may also be used to match multiple headers that correspond to the given pattern. For example:
::
export OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_REQUEST="Accept.*,X-.*"
Would match all request headers that start with ``Accept`` and ``X-``.
To capture all request headers, set ``OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_REQUEST`` to ``".*"``.
::
export OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_REQUEST=".*"
The name of the added span attribute will follow the format ``http.request.header.`` where ````
is the normalized HTTP header name (lowercase, with ``-`` replaced by ``_``). The value of the attribute will be a
list containing the header values.
For example:
``http.request.header.custom_request_header = [", "]``
Response headers
****************
To capture HTTP response headers as span attributes, set the environment variable
``OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_RESPONSE`` to a comma delimited list of HTTP header names.
For example,
::
export OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_RESPONSE="content-type,custom_response_header"
will extract ``content-type`` and ``custom_response_header`` from the response headers and add them as span attributes.
Response header names in aiohttp are case-insensitive. So, giving the header name as ``CUStom-Header`` in the environment
variable will capture the header named ``custom-header``.
Regular expressions may also be used to match multiple headers that correspond to the given pattern. For example:
::
export OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_RESPONSE="Content.*,X-.*"
Would match all response headers that start with ``Content`` and ``X-``.
To capture all response headers, set ``OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_RESPONSE`` to ``".*"``.
::
export OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_RESPONSE=".*"
The name of the added span attribute will follow the format ``http.response.header.`` where ````
is the normalized HTTP header name (lowercase, with ``-`` replaced by ``_``). The value of the attribute will be a
list containing the header values.
For example:
``http.response.header.custom_response_header = [", "]``
Sanitizing headers
******************
In order to prevent storing sensitive data such as personally identifiable information (PII), session keys, passwords,
etc, set the environment variable ``OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SANITIZE_FIELDS``
to a comma delimited list of HTTP header names to be sanitized. Regexes may be used, and all header names will be
matched in a case-insensitive manner.
For example,
::
export OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SANITIZE_FIELDS=".*session.*,set-cookie"
will replace the value of headers such as ``session-id`` and ``set-cookie`` with ``[REDACTED]`` in the span.
Note:
The environment variable names used to capture HTTP headers are still experimental, and thus are subject to change.
API
---
"""
from __future__ import annotations
from timeit import default_timer
from aiohttp import web
from multidict import CIMultiDictProxy
from opentelemetry import metrics, trace
from opentelemetry.instrumentation._semconv import (
HTTP_DURATION_HISTOGRAM_BUCKETS_NEW,
_filter_semconv_active_request_count_attr,
_filter_semconv_duration_attrs,
_get_schema_url,
_OpenTelemetrySemanticConventionStability,
_OpenTelemetryStabilitySignalType,
_report_new,
_report_old,
_server_active_requests_count_attrs_new,
_server_active_requests_count_attrs_old,
_server_duration_attrs_new,
_server_duration_attrs_old,
_set_http_flavor_version,
_set_http_method,
_set_http_net_host,
_set_http_net_host_port,
_set_http_scheme,
_set_http_target,
_set_http_user_agent,
_set_status,
_StabilityMode,
)
from opentelemetry.instrumentation.aiohttp_server.package import _instruments
from opentelemetry.instrumentation.aiohttp_server.version import __version__
from opentelemetry.instrumentation.instrumentor import BaseInstrumentor
from opentelemetry.instrumentation.utils import (
is_http_instrumentation_enabled,
)
from opentelemetry.propagate import extract
from opentelemetry.propagators.textmap import Getter
from opentelemetry.semconv._incubating.attributes.http_attributes import (
HTTP_HOST,
HTTP_ROUTE,
HTTP_SERVER_NAME,
HTTP_URL,
)
from opentelemetry.semconv.metrics import MetricInstruments
from opentelemetry.semconv.metrics.http_metrics import (
HTTP_SERVER_REQUEST_DURATION,
)
from opentelemetry.util.http import (
OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SANITIZE_FIELDS,
OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_REQUEST,
OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_RESPONSE,
SanitizeValue,
_parse_url_query,
get_custom_headers,
get_excluded_urls,
normalise_request_header_name,
normalise_response_header_name,
redact_query_parameters,
redact_url,
sanitize_method,
)
tracer = None
meter_old = None
meter_new = None
duration_histogram_old = None
duration_histogram_new = None
active_requests_counter = None
_excluded_urls = None
_sem_conv_opt_in_mode = _StabilityMode.DEFAULT
def _parse_active_request_count_attrs(req_attrs, sem_conv_opt_in_mode: _StabilityMode = _StabilityMode.DEFAULT):
return _filter_semconv_active_request_count_attr(
req_attrs,
_server_active_requests_count_attrs_old,
_server_active_requests_count_attrs_new,
sem_conv_opt_in_mode,
)
def _parse_duration_attrs(
req_attrs: dict[str, str | None],
sem_conv_opt_in_mode: _StabilityMode = _StabilityMode.DEFAULT,
):
return _filter_semconv_duration_attrs(
req_attrs,
_server_duration_attrs_old,
_server_duration_attrs_new,
sem_conv_opt_in_mode,
)
def get_default_span_name(request: web.Request) -> str:
"""Returns the span name.
Args:
request: the request object itself.
Returns:
The span name as "{method} {canonical_name}" of a resource if possible or just "{method}".
"""
path = _get_canonical_path(request)
method = sanitize_method(request.method)
if method == "_OTHER":
method = "HTTP"
if path:
return f"{method} {path}"
return f"{method}"
def _get_canonical_path(request: web.Request) -> str:
"""Returns the canonical path from the request handler.
Args:
request: the request object itself.
Returns:
a string containing the canonical path
"""
try:
resource = request.match_info.route.resource
path = resource.canonical
except AttributeError:
path = ""
return path
def collect_request_attributes(
request: web.Request,
sem_conv_opt_in_mode: _StabilityMode = _StabilityMode.DEFAULT,
) -> dict:
"""Collects HTTP request attributes from the aiohttp request context
and returns a dictionary to be used as span creation attributes."""
result: dict[str, str | None] = {}
_set_http_method(
result,
request.method,
sanitize_method(request.method),
sem_conv_opt_in_mode,
)
_set_http_scheme(
result,
request.scheme,
sem_conv_opt_in_mode,
)
server_host = request.url.host
port = request.url.port
if server_host:
_set_http_net_host(result, server_host, sem_conv_opt_in_mode)
if _report_old(sem_conv_opt_in_mode):
result[HTTP_HOST] = server_host
if port:
_set_http_net_host_port(result, port, sem_conv_opt_in_mode)
if request.path_qs:
redacted_target = redact_query_parameters(request.path_qs)
_, redacted_query = _parse_url_query(redacted_target)
_set_http_target(
result,
redacted_target,
request.path,
redacted_query,
sem_conv_opt_in_mode,
)
# old semconv v1.20.0 - always set HTTP_URL when reporting old semconv
if _report_old(sem_conv_opt_in_mode):
result[HTTP_URL] = redact_url(str(request.url))
if user_agent := request.headers.get("user-agent"):
_set_http_user_agent(result, user_agent, sem_conv_opt_in_mode)
flavor = f"{request.version.major}.{request.version.minor}"
_set_http_flavor_version(result, flavor, sem_conv_opt_in_mode)
# http.route for both old and new
result[HTTP_ROUTE] = _get_canonical_path(request)
if _report_old(sem_conv_opt_in_mode):
http_host_value_list = [request.host] if not isinstance(request.host, list) else request.host
if http_host_value_list:
result[HTTP_SERVER_NAME] = ",".join(http_host_value_list)
return result
def collect_request_headers_attributes(
request: web.Request,
) -> dict[str, list[str]]:
sanitize = SanitizeValue(get_custom_headers(OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SANITIZE_FIELDS))
return sanitize.sanitize_header_values(
request.headers,
get_custom_headers(OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_REQUEST),
normalise_request_header_name,
)
def collect_response_headers_attributes(
response: web.Response,
) -> dict[str, list[str]]:
sanitize = SanitizeValue(get_custom_headers(OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SANITIZE_FIELDS))
return sanitize.sanitize_header_values(
response.headers,
get_custom_headers(OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_RESPONSE),
normalise_response_header_name,
)
def set_status_code(
span: trace.Span,
status_code: int,
duration_attrs: dict[str, str | None] | None = None,
sem_conv_opt_in_mode: _StabilityMode = _StabilityMode.DEFAULT,
) -> None:
"""Adds HTTP response attributes to span using the status_code argument."""
if duration_attrs is None:
duration_attrs = {}
status_code_str = str(status_code)
try:
status_code_int = int(status_code)
except ValueError:
status_code_int = -1
_set_status(
span,
duration_attrs,
status_code_int,
status_code_str,
server_span=True,
sem_conv_opt_in_mode=sem_conv_opt_in_mode,
)
class AiohttpGetter(Getter):
"""Extract current trace from headers"""
def get(self, carrier, key: str) -> list | None:
"""Getter implementation to retrieve an HTTP header value from the aiohttp
request context.
Args:
carrier: aiohttp request context object
key: header name in request context
Returns:
A list of all header values matching the key, or None if the key
does not match any header.
"""
headers: CIMultiDictProxy = carrier.headers
if not headers:
return None
return headers.getall(key, None)
def keys(self, carrier: dict) -> list:
return list(carrier.keys())
getter = AiohttpGetter()
def create_aiohttp_middleware(
tracer_provider: trace.TracerProvider | None = None,
):
_tracer = tracer_provider.get_tracer(__name__, __version__) if tracer_provider else tracer
@web.middleware
async def _middleware(request, handler):
"""Middleware for aiohttp implementing tracing logic"""
if not is_http_instrumentation_enabled() or _excluded_urls.url_disabled(request.url.path):
return await handler(request)
span_name = get_default_span_name(request)
request_attrs = collect_request_attributes(request, _sem_conv_opt_in_mode)
active_requests_count_attrs = _parse_active_request_count_attrs(
request_attrs,
_sem_conv_opt_in_mode,
)
with _tracer.start_as_current_span(
span_name,
context=extract(request, getter=getter),
kind=trace.SpanKind.SERVER,
attributes=request_attrs,
set_status_on_exception=False,
record_exception=False,
) as span:
if span.is_recording():
span.set_attributes(collect_request_headers_attributes(request))
start = default_timer()
active_requests_counter.add(1, active_requests_count_attrs)
try:
resp = await handler(request)
set_status_code(
span,
resp.status,
request_attrs,
_sem_conv_opt_in_mode,
)
if span.is_recording():
response_headers_attributes = collect_response_headers_attributes(resp)
span.set_attributes(response_headers_attributes)
except web.HTTPServerError as ex:
set_status_code(
span,
ex.status_code,
request_attrs,
_sem_conv_opt_in_mode,
)
span.record_exception(ex)
raise
except web.HTTPException as ex:
set_status_code(
span,
ex.status_code,
request_attrs,
_sem_conv_opt_in_mode,
)
raise
except Exception as ex:
set_status_code(
span,
type(ex).__qualname__,
request_attrs,
_sem_conv_opt_in_mode,
)
span.record_exception(ex)
raise
finally:
duration_s = default_timer() - start
if duration_histogram_old:
duration_attrs_old = _parse_duration_attrs(request_attrs, _StabilityMode.DEFAULT)
duration_histogram_old.record(max(round(duration_s * 1000), 0), duration_attrs_old)
if duration_histogram_new:
duration_attrs_new = _parse_duration_attrs(request_attrs, _StabilityMode.HTTP)
duration_histogram_new.record(max(duration_s, 0), duration_attrs_new)
active_requests_counter.add(-1, active_requests_count_attrs)
return resp
return _middleware
middleware = create_aiohttp_middleware() # for backwards compatibility
def create_instrumented_application(
tracer_provider: trace.TracerProvider | None = None,
):
_middleware = create_aiohttp_middleware(tracer_provider=tracer_provider)
class _InstrumentedApplication(web.Application):
"""Insert tracing middleware"""
def __init__(self, *args, **kwargs):
middlewares = kwargs.pop("middlewares", [])
middlewares.insert(0, _middleware)
kwargs["middlewares"] = middlewares
super().__init__(*args, **kwargs)
return _InstrumentedApplication
class AioHttpServerInstrumentor(BaseInstrumentor):
# pylint: disable=protected-access
"""An instrumentor for aiohttp.web.Application
See `BaseInstrumentor`
"""
def _instrument(self, **kwargs):
_OpenTelemetrySemanticConventionStability._initialize()
sem_conv_opt_in_mode = _OpenTelemetrySemanticConventionStability._get_opentelemetry_stability_opt_in_mode(
_OpenTelemetryStabilitySignalType.HTTP,
)
tracer_provider = kwargs.get("tracer_provider", None)
# update global values at instrument time so we can test them
global _excluded_urls # pylint: disable=global-statement
_excluded_urls = get_excluded_urls("AIOHTTP_SERVER")
global _sem_conv_opt_in_mode # pylint: disable=global-statement
_sem_conv_opt_in_mode = sem_conv_opt_in_mode
global tracer # pylint: disable=global-statement
tracer = trace.get_tracer(
__name__,
__version__,
schema_url=_get_schema_url(sem_conv_opt_in_mode),
)
global meter_old # pylint: disable=global-statement
global meter_new # pylint: disable=global-statement
global duration_histogram_old # pylint: disable=global-statement
global duration_histogram_new # pylint: disable=global-statement
global active_requests_counter # pylint: disable=global-statement
if _report_old(sem_conv_opt_in_mode):
meter_old = metrics.get_meter(
__name__,
__version__,
schema_url=_get_schema_url(_StabilityMode.DEFAULT),
)
duration_histogram_old = meter_old.create_histogram(
name=MetricInstruments.HTTP_SERVER_DURATION,
unit="ms",
description="Measures the duration of inbound HTTP requests.",
)
if _report_new(sem_conv_opt_in_mode):
meter_new = metrics.get_meter(
__name__,
__version__,
schema_url=_get_schema_url(_StabilityMode.HTTP),
)
duration_histogram_new = meter_new.create_histogram(
name=HTTP_SERVER_REQUEST_DURATION,
unit="s",
description="Duration of HTTP server requests.",
explicit_bucket_boundaries_advisory=HTTP_DURATION_HISTOGRAM_BUCKETS_NEW,
)
meter_for_counter = meter_new or meter_old
active_requests_counter = meter_for_counter.create_up_down_counter(
name=MetricInstruments.HTTP_SERVER_ACTIVE_REQUESTS,
unit="{request}",
description="Number of active HTTP server requests.",
)
self._original_app = web.Application
_InstrumentedApplication = create_instrumented_application(tracer_provider=tracer_provider)
web.Application = _InstrumentedApplication
def _uninstrument(self, **kwargs):
web.Application = self._original_app
def instrumentation_dependencies(self):
return _instruments
package.py 0000664 0000000 0000000 00000000252 15270700723 0047770 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aiohttp-server/src/opentelemetry/instrumentation/aiohttp_server # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
_instruments = ("aiohttp ~= 3.0",)
_supports_metrics = True
_semconv_status = "migration"
version.py 0000664 0000000 0000000 00000000144 15270700723 0050062 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aiohttp-server/src/opentelemetry/instrumentation/aiohttp_server # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
__version__ = "0.66b2"
test-requirements.txt 0000664 0000000 0000000 00000000720 15270700723 0040300 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aiohttp-server aiohttp==3.10.2
aiosignal==1.3.1
asgiref==3.8.1
async-timeout==4.0.3
Deprecated==1.2.14
frozenlist==1.4.1
idna==3.7
iniconfig==2.0.0
multidict==6.0.5
packaging==24.0
pluggy==1.6.0
py-cpuinfo==9.0.0
pytest==7.4.4
pytest-aiohttp==1.0.5
pytest-asyncio==0.23.5
tomli==2.0.1
typing_extensions==4.12.2
wrapt==1.16.0
yarl==1.9.4
zipp==3.19.2
-e opentelemetry-instrumentation
-e util/opentelemetry-util-http
-e instrumentation/opentelemetry-instrumentation-aiohttp-server
tests/ 0000775 0000000 0000000 00000000000 15270700723 0035202 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aiohttp-server __init__.py 0000664 0000000 0000000 00000000000 15270700723 0037301 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aiohttp-server/tests test_aiohttp_server_integration.py 0000664 0000000 0000000 00000107147 15270700723 0044266 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aiohttp-server/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
# pylint: disable=too-many-lines
from enum import Enum
from http import HTTPStatus
import aiohttp
import pytest
import pytest_asyncio
from multidict import CIMultiDict
from opentelemetry.instrumentation._semconv import (
HTTP_DURATION_HISTOGRAM_BUCKETS_NEW,
OTEL_SEMCONV_STABILITY_OPT_IN,
_OpenTelemetrySemanticConventionStability,
_server_active_requests_count_attrs_new,
_server_active_requests_count_attrs_old,
_server_duration_attrs_new,
_server_duration_attrs_old,
_StabilityMode,
)
from opentelemetry.instrumentation.aiohttp_server import (
AioHttpServerInstrumentor,
)
from opentelemetry.instrumentation.utils import suppress_http_instrumentation
from opentelemetry.sdk.metrics.export import (
HistogramDataPoint,
)
from opentelemetry.sdk.trace.sampling import ParentBased, TraceIdRatioBased
from opentelemetry.semconv._incubating.attributes.http_attributes import (
HTTP_FLAVOR,
HTTP_METHOD,
HTTP_ROUTE,
HTTP_SCHEME,
HTTP_STATUS_CODE,
HTTP_TARGET,
HTTP_URL,
HTTP_USER_AGENT,
)
from opentelemetry.semconv._incubating.attributes.net_attributes import (
NET_HOST_NAME,
NET_HOST_PORT,
)
from opentelemetry.semconv.attributes.error_attributes import ERROR_TYPE
from opentelemetry.semconv.attributes.http_attributes import (
HTTP_REQUEST_METHOD,
HTTP_RESPONSE_STATUS_CODE,
)
from opentelemetry.semconv.attributes.network_attributes import (
NETWORK_PROTOCOL_VERSION,
)
from opentelemetry.semconv.attributes.server_attributes import (
SERVER_ADDRESS,
SERVER_PORT,
)
from opentelemetry.semconv.attributes.url_attributes import (
URL_PATH,
URL_QUERY,
URL_SCHEME,
)
from opentelemetry.semconv.attributes.user_agent_attributes import (
USER_AGENT_ORIGINAL,
)
from opentelemetry.test.test_base import TestBase
from opentelemetry.trace import StatusCode
from opentelemetry.util._importlib_metadata import entry_points
from opentelemetry.util.http import (
OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SANITIZE_FIELDS,
OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_REQUEST,
OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_RESPONSE,
)
class HTTPMethod(Enum):
"""HTTP methods and descriptions"""
def __repr__(self):
return f"{self.value}"
CONNECT = "CONNECT"
DELETE = "DELETE"
GET = "GET"
HEAD = "HEAD"
OPTIONS = "OPTIONS"
PATCH = "PATCH"
POST = "POST"
PUT = "PUT"
TRACE = "TRACE"
SCOPE = "opentelemetry.instrumentation.aiohttp_server"
@pytest.fixture(name="test_base", scope="function")
def fixture_test_base():
test_base = TestBase()
test_base.setUp()
_OpenTelemetrySemanticConventionStability._initialized = False
try:
yield test_base
finally:
# Reset semconv stability state otherwise tests can interfere with each other
_OpenTelemetrySemanticConventionStability._initialized = False
test_base.tearDown()
@pytest.fixture(name="tracer", scope="function")
def fixture_tracer(test_base: TestBase):
return test_base.tracer_provider, test_base.memory_exporter
@pytest.fixture(name="meter", scope="function")
def fixture_meter(test_base: TestBase):
return test_base.meter_provider, test_base.memory_metrics_reader
async def default_handler(request, status=200):
return aiohttp.web.Response(status=status)
@pytest.fixture(name="suppress")
def fixture_suppress():
return False
@pytest_asyncio.fixture(name="server_fixture")
async def fixture_server_fixture(tracer, aiohttp_server, suppress):
tracer_provider, _ = tracer
AioHttpServerInstrumentor().instrument(tracer_provider=tracer_provider)
app = aiohttp.web.Application()
app.add_routes(
[
aiohttp.web.get("/test-path", default_handler),
aiohttp.web.get("/test-path/{url_param}", default_handler),
aiohttp.web.get("/object/{object_id}/action/{another_param}", default_handler),
]
)
if suppress:
with suppress_http_instrumentation():
server = await aiohttp_server(app)
else:
server = await aiohttp_server(app)
yield server, app
AioHttpServerInstrumentor().uninstrument()
def test_checking_instrumentor_pkg_installed():
(instrumentor_entrypoint,) = entry_points(group="opentelemetry_instrumentor", name="aiohttp-server")
instrumentor = instrumentor_entrypoint.load()()
assert isinstance(instrumentor, AioHttpServerInstrumentor)
@pytest.mark.asyncio
@pytest.mark.parametrize(
"url, expected_method, expected_status_code",
[
("/test-path", HTTPMethod.GET, HTTPStatus.OK),
("/not-found", HTTPMethod.GET, HTTPStatus.NOT_FOUND),
],
)
async def test_status_code_instrumentation(
test_base: TestBase,
server_fixture,
aiohttp_client,
url,
expected_method,
expected_status_code,
):
server, _ = server_fixture
assert len(test_base.get_finished_spans()) == 0
metrics = test_base.get_sorted_metrics(SCOPE)
assert len(metrics) == 0
client = await aiohttp_client(server)
await client.get(url)
assert len(test_base.get_finished_spans()) == 1
metrics = test_base.get_sorted_metrics(SCOPE)
assert len(metrics) == 2
[span] = test_base.get_finished_spans()
assert expected_method.value == span.attributes[HTTP_METHOD]
assert expected_status_code == span.attributes[HTTP_STATUS_CODE]
assert url == span.attributes[HTTP_TARGET]
@pytest.mark.asyncio
@pytest.mark.parametrize(
"span_name, example_paths",
[
(
"GET /test-path/{url_param}",
(
"/test-path/foo",
"/test-path/bar",
),
),
(
"GET /object/{object_id}/action/{another_param}",
(
"/object/1/action/bar",
"/object/234/action/baz",
),
),
(
"GET",
(
"/i/dont/exist",
"/me-neither",
),
),
],
)
async def test_url_params_instrumentation(
tracer,
server_fixture,
aiohttp_client,
span_name,
example_paths,
):
_, memory_exporter = tracer
server, _ = server_fixture
assert len(memory_exporter.get_finished_spans()) == 0
client = await aiohttp_client(server)
for path in example_paths:
await client.get(path)
assert len(memory_exporter.get_finished_spans()) == 2
for request_path, span in zip(example_paths, memory_exporter.get_finished_spans()):
assert span_name == span.name
assert request_path == span.attributes[HTTP_TARGET]
full_url = f"http://{server.host}:{server.port}{request_path}"
assert full_url == span.attributes[HTTP_URL]
@pytest.mark.asyncio
async def test_span_name_handler_unknown_method(
tracer,
server_fixture,
):
_, memory_exporter = tracer
server, _ = server_fixture
assert len(memory_exporter.get_finished_spans()) == 0
async with aiohttp.ClientSession(base_url=f"http://{server.host}:{server.port}") as session:
# PURGE is accepted by aiohttp but not recognized by sanitize_method.
async with session.request("PURGE", "/test-path") as response:
assert response.status == HTTPStatus.METHOD_NOT_ALLOWED
spans = memory_exporter.get_finished_spans()
assert len(spans) == 1
assert "_OTHER" == spans[0].attributes[HTTP_METHOD]
assert "HTTP" == spans[0].name
@pytest.mark.asyncio
@pytest.mark.parametrize("suppress", [True])
async def test_suppress_instrumentation(test_base: TestBase, server_fixture, aiohttp_client):
server, _ = server_fixture
assert len(test_base.get_finished_spans()) == 0
client = await aiohttp_client(server)
await client.get("/test-path")
assert len(test_base.get_finished_spans()) == 0
@pytest.mark.asyncio
async def test_remove_sensitive_params(test_base: TestBase, aiohttp_server, monkeypatch):
"""Test that sensitive information in URLs is properly redacted."""
# Use old semconv to test HTTP_URL redaction
monkeypatch.setenv(OTEL_SEMCONV_STABILITY_OPT_IN, _StabilityMode.DEFAULT.value)
# Set up instrumentation
AioHttpServerInstrumentor().instrument()
# Create app with test route
app = aiohttp.web.Application()
async def handler(request):
return aiohttp.web.Response(text="hello")
app.router.add_get("/status/200", handler)
# Start the server
server = await aiohttp_server(app)
# Make request with sensitive data in URL
url = f"http://username:password@{server.host}:{server.port}/status/200?Signature=secret"
async with aiohttp.ClientSession() as session:
async with session.get(url) as response:
assert response.status == 200
assert await response.text() == "hello"
# Verify redaction in span attributes
spans = test_base.get_finished_spans()
assert len(spans) == 1
span = spans[0]
assert span.attributes[HTTP_METHOD] == "GET"
assert span.attributes[HTTP_STATUS_CODE] == 200
assert span.attributes[HTTP_URL] == f"http://{server.host}:{server.port}/status/200?Signature=REDACTED"
# Clean up
AioHttpServerInstrumentor().uninstrument()
@pytest.mark.asyncio
async def test_remove_sensitive_params_new(test_base: TestBase, aiohttp_server, monkeypatch):
"""Test URL handling with new semantic conventions (no redaction for URL_PATH/URL_QUERY)."""
# Use new semconv
monkeypatch.setenv(OTEL_SEMCONV_STABILITY_OPT_IN, _StabilityMode.HTTP.value)
# Set up instrumentation
AioHttpServerInstrumentor().instrument()
# Create app with test route
app = aiohttp.web.Application()
async def handler(request):
return aiohttp.web.Response(text="hello")
app.router.add_get("/status/200", handler)
# Start the server
server = await aiohttp_server(app)
# Make request with sensitive data in URL
url = f"http://username:password@{server.host}:{server.port}/status/200?Signature=secret"
async with aiohttp.ClientSession() as session:
async with session.get(url) as response:
assert response.status == 200
assert await response.text() == "hello"
# Verify span attributes with new semconv
spans = test_base.get_finished_spans()
assert len(spans) == 1
span = spans[0]
assert span.attributes[HTTP_REQUEST_METHOD] == "GET"
assert span.attributes[HTTP_RESPONSE_STATUS_CODE] == 200
assert span.attributes[URL_PATH] == "/status/200"
assert span.attributes[URL_QUERY] == "Signature=REDACTED"
assert HTTP_URL not in span.attributes
# Clean up
AioHttpServerInstrumentor().uninstrument()
@pytest.mark.asyncio
@pytest.mark.parametrize(
"env_var",
["OTEL_PYTHON_AIOHTTP_SERVER_EXCLUDED_URLS", "OTEL_PYTHON_EXCLUDED_URLS"],
)
async def test_excluded_urls(test_base: TestBase, aiohttp_server, monkeypatch, env_var):
"""Test that excluded env vars are taken into account."""
monkeypatch.setenv(env_var, "/status/200")
AioHttpServerInstrumentor().instrument()
app = aiohttp.web.Application()
async def handler(request):
return aiohttp.web.Response(text="hello")
app.router.add_get("/status/200", handler)
server = await aiohttp_server(app)
url = f"http://{server.host}:{server.port}/status/200"
async with aiohttp.ClientSession() as session:
async with session.get(url) as response:
assert response.status == 200
assert await response.text() == "hello"
spans = test_base.get_finished_spans()
assert len(spans) == 0
metrics = test_base.get_sorted_metrics(SCOPE)
assert len(metrics) == 0
AioHttpServerInstrumentor().uninstrument()
@pytest.mark.asyncio
@pytest.mark.parametrize(
"tracer",
[TestBase().create_tracer_provider(sampler=ParentBased(TraceIdRatioBased(0.05)))],
)
async def test_non_global_tracer_provider(
tracer,
server_fixture,
aiohttp_client,
):
n_requests = 1000
collection_ratio = 0.05
n_expected_trace_ids = n_requests * collection_ratio
_, memory_exporter = tracer
server, _ = server_fixture
assert len(memory_exporter.get_finished_spans()) == 0
client = await aiohttp_client(server)
for _ in range(n_requests):
await client.get("/test-path")
trace_ids = {span.context.trace_id for span in memory_exporter.get_finished_spans() if span.context is not None}
assert 0.5 * n_expected_trace_ids <= len(trace_ids) <= 1.5 * n_expected_trace_ids
@pytest.mark.asyncio
async def test_custom_request_headers(test_base: TestBase, aiohttp_server, monkeypatch):
# pylint: disable=too-many-locals
monkeypatch.setenv(
OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SANITIZE_FIELDS,
".*my-secret.*",
)
monkeypatch.setenv(
OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_REQUEST,
"Custom-Test-Header-1,Custom-Test-Header-2,Custom-Test-Header-3,Regex-Test-Header-.*,Regex-Invalid-Test-Header-.*,.*my-secret.*",
)
AioHttpServerInstrumentor().instrument()
app = aiohttp.web.Application()
async def handler(request):
return aiohttp.web.Response(text="hello")
app.router.add_get("/status/200", handler)
server = await aiohttp_server(app)
url = f"http://{server.host}:{server.port}/status/200"
async with aiohttp.ClientSession() as session:
headers = {
"custom-test-header-1": "test-header-value-1",
"custom-test-header-2": "test-header-value-2",
"Regex-Test-Header-1": "Regex Test Value 1",
"regex-test-header-2": "RegexTestValue2,RegexTestValue3",
"My-Secret-Header": "My Secret Value",
}
async with session.get(url, headers=headers) as response:
assert response.status == 200
assert await response.text() == "hello"
spans = test_base.get_finished_spans()
assert len(spans) == 1
span = spans[0]
expected = {
"http.request.header.custom_test_header_1": ("test-header-value-1",),
"http.request.header.custom_test_header_2": ("test-header-value-2",),
"http.request.header.regex_test_header_1": ("Regex Test Value 1",),
"http.request.header.regex_test_header_2": ("RegexTestValue2,RegexTestValue3",),
"http.request.header.my_secret_header": ("[REDACTED]",),
}
for attribute, value in expected.items():
assert span.attributes.get(attribute) == value
assert "http.request.header.custom_test_header_3" not in span.attributes
AioHttpServerInstrumentor().uninstrument()
@pytest.mark.asyncio
async def test_custom_response_headers(test_base: TestBase, aiohttp_server, monkeypatch):
monkeypatch.setenv(
OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SANITIZE_FIELDS,
".*my-secret.*",
)
monkeypatch.setenv(
OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_RESPONSE,
"Custom-Test-Header-1,Custom-Test-Header-2,Custom-Test-Header-3,my-custom-regex-header-.*,invalid-regex-header-.*,.*my-secret.*",
)
AioHttpServerInstrumentor().instrument()
app = aiohttp.web.Application()
async def handler(request):
headers = CIMultiDict(
**{
"custom-test-header-1": "test-header-value-1",
"custom-test-header-2": "test-header-value-2",
"my-custom-regex-header-1": "my-custom-regex-value-1,my-custom-regex-value-2",
"My-Custom-Regex-Header-2": "my-custom-regex-value-3,my-custom-regex-value-4",
"My-Secret-Header": "My Secret Value",
}
)
return aiohttp.web.Response(text="hello", headers=headers)
app.router.add_get("/status/200", handler)
server = await aiohttp_server(app)
url = f"http://{server.host}:{server.port}/status/200"
async with aiohttp.ClientSession() as session:
async with session.get(url) as response:
assert response.status == 200
assert await response.text() == "hello"
spans = test_base.get_finished_spans()
assert len(spans) == 1
span = spans[0]
expected = {
"http.response.header.custom_test_header_1": ("test-header-value-1",),
"http.response.header.custom_test_header_2": ("test-header-value-2",),
"http.response.header.my_custom_regex_header_1": ("my-custom-regex-value-1,my-custom-regex-value-2",),
"http.response.header.my_custom_regex_header_2": ("my-custom-regex-value-3,my-custom-regex-value-4",),
"http.response.header.my_secret_header": ("[REDACTED]",),
}
for attribute, value in expected.items():
assert span.attributes.get(attribute) == value
assert "http.response.header.custom_test_header_3" not in span.attributes
AioHttpServerInstrumentor().uninstrument()
# pylint: disable=too-many-locals
@pytest.mark.asyncio
async def test_semantic_conventions_metrics_old_default(test_base: TestBase, aiohttp_server, monkeypatch):
monkeypatch.setenv(OTEL_SEMCONV_STABILITY_OPT_IN, _StabilityMode.DEFAULT.value)
AioHttpServerInstrumentor().instrument()
app = aiohttp.web.Application()
app.router.add_get("/test-path/{param}", default_handler)
server = await aiohttp_server(app)
client_session = aiohttp.ClientSession()
try:
url = f"http://{server.host}:{server.port}/test-path/test-param?query=test"
async with client_session.get( # pylint: disable=not-async-context-manager
url, headers={"User-Agent": "test-agent"}
) as response:
assert response.status == 200
spans = test_base.get_finished_spans()
assert len(spans) == 1
span = spans[0]
# Verify old semconv schema URL
assert span.instrumentation_scope.schema_url == "https://opentelemetry.io/schemas/1.11.0"
# Old semconv span attributes present
assert span.attributes.get(HTTP_METHOD) == "GET"
assert span.attributes.get(HTTP_SCHEME) == "http"
assert span.attributes.get(NET_HOST_NAME) == server.host
assert span.attributes.get(NET_HOST_PORT) == server.port
assert span.attributes.get(HTTP_TARGET) == "/test-path/test-param?query=test"
assert span.attributes.get(HTTP_USER_AGENT) == "test-agent"
assert span.attributes.get(HTTP_FLAVOR) == "1.1"
assert span.attributes.get(HTTP_STATUS_CODE) == 200
assert span.attributes.get(HTTP_ROUTE) == "/test-path/{param}"
# New semconv span attributes NOT present
assert HTTP_REQUEST_METHOD not in span.attributes
assert URL_SCHEME not in span.attributes
assert SERVER_ADDRESS not in span.attributes
assert SERVER_PORT not in span.attributes
assert URL_PATH not in span.attributes
assert URL_QUERY not in span.attributes
assert USER_AGENT_ORIGINAL not in span.attributes
assert NETWORK_PROTOCOL_VERSION not in span.attributes
assert HTTP_RESPONSE_STATUS_CODE not in span.attributes
metrics = test_base.get_sorted_metrics(SCOPE)
expected_metric_names = [
"http.server.active_requests",
"http.server.duration",
]
recommended_metrics_attrs = {
"http.server.active_requests": _server_active_requests_count_attrs_old,
"http.server.duration": _server_duration_attrs_old,
}
for metric in metrics:
assert metric.name in expected_metric_names
if metric.name == "http.server.duration":
assert metric.unit == "ms"
for point in metric.data.data_points:
for attr in point.attributes:
assert attr in recommended_metrics_attrs[metric.name]
finally:
await client_session.close()
AioHttpServerInstrumentor().uninstrument()
# pylint: disable=too-many-locals
@pytest.mark.asyncio
async def test_semantic_conventions_metrics_new(test_base: TestBase, meter, aiohttp_server, monkeypatch):
monkeypatch.setenv(OTEL_SEMCONV_STABILITY_OPT_IN, _StabilityMode.HTTP.value)
AioHttpServerInstrumentor().instrument()
app = aiohttp.web.Application()
app.router.add_get("/test-path/{param}", default_handler)
server = await aiohttp_server(app)
client_session = aiohttp.ClientSession()
try:
url = f"http://{server.host}:{server.port}/test-path/test-param?query=test"
async with client_session.get( # pylint: disable=not-async-context-manager
url, headers={"User-Agent": "test-agent"}
) as response:
assert response.status == 200
spans = test_base.get_finished_spans()
assert len(spans) == 1
span = spans[0]
# Verify new semconv schema URL
assert span.instrumentation_scope.schema_url == "https://opentelemetry.io/schemas/1.21.0"
# New semconv span attributes present
assert span.attributes.get(HTTP_REQUEST_METHOD) == "GET"
assert span.attributes.get(URL_SCHEME) == "http"
assert span.attributes.get(SERVER_ADDRESS) == server.host
assert span.attributes.get(SERVER_PORT) == server.port
assert span.attributes.get(URL_PATH) == "/test-path/test-param"
assert span.attributes.get(URL_QUERY) == "query=test"
assert span.attributes.get(USER_AGENT_ORIGINAL) == "test-agent"
assert span.attributes.get(NETWORK_PROTOCOL_VERSION) == "1.1"
assert span.attributes.get(HTTP_RESPONSE_STATUS_CODE) == 200
assert span.attributes.get(HTTP_ROUTE) == "/test-path/{param}"
# Old semconv span attributes NOT present
assert HTTP_METHOD not in span.attributes
assert HTTP_SCHEME not in span.attributes
assert NET_HOST_NAME not in span.attributes
assert NET_HOST_PORT not in span.attributes
assert HTTP_TARGET not in span.attributes
assert HTTP_USER_AGENT not in span.attributes
assert HTTP_FLAVOR not in span.attributes
assert HTTP_STATUS_CODE not in span.attributes
metrics = test_base.get_sorted_metrics(SCOPE)
expected_metric_names = [
"http.server.active_requests",
"http.server.request.duration",
]
recommended_metrics_attrs = {
"http.server.active_requests": _server_active_requests_count_attrs_new,
"http.server.request.duration": _server_duration_attrs_new,
}
for metric in metrics:
assert metric.name in expected_metric_names
if metric.name == "http.server.request.duration":
assert metric.unit == "s"
for point in metric.data.data_points:
if isinstance(point, HistogramDataPoint) and metric.name == "http.server.request.duration":
assert point.explicit_bounds == HTTP_DURATION_HISTOGRAM_BUCKETS_NEW
for attr in point.attributes:
assert attr in recommended_metrics_attrs[metric.name]
finally:
await client_session.close()
AioHttpServerInstrumentor().uninstrument()
# pylint: disable=too-many-locals
# pylint: disable=too-many-statements
@pytest.mark.asyncio
async def test_semantic_conventions_metrics_both(test_base: TestBase, meter, aiohttp_server, monkeypatch):
monkeypatch.setenv(OTEL_SEMCONV_STABILITY_OPT_IN, _StabilityMode.HTTP_DUP.value)
AioHttpServerInstrumentor().instrument()
app = aiohttp.web.Application()
app.router.add_get("/test-path", default_handler)
server = await aiohttp_server(app)
client_session = aiohttp.ClientSession()
try:
url = f"http://{server.host}:{server.port}/test-path?query=test"
async with client_session.get( # pylint: disable=not-async-context-manager
url, headers={"User-Agent": "test-agent"}
) as response:
assert response.status == 200
spans = test_base.get_finished_spans()
assert len(spans) == 1
span = spans[0]
# Verify new semconv schema URL (both mode uses new schema)
assert span.instrumentation_scope.schema_url == "https://opentelemetry.io/schemas/1.21.0"
# Both old and new semconv span attributes present
assert span.attributes.get(HTTP_METHOD) == "GET"
assert span.attributes.get(HTTP_REQUEST_METHOD) == "GET"
assert span.attributes.get(HTTP_SCHEME) == "http"
assert span.attributes.get(URL_SCHEME) == "http"
assert span.attributes.get(NET_HOST_NAME) == server.host
assert span.attributes.get(SERVER_ADDRESS) == server.host
assert span.attributes.get(NET_HOST_PORT) == server.port
assert span.attributes.get(SERVER_PORT) == server.port
assert span.attributes.get(HTTP_TARGET) == "/test-path?query=test"
assert span.attributes.get(URL_PATH) == "/test-path"
assert span.attributes.get(URL_QUERY) == "query=test"
assert span.attributes.get(HTTP_USER_AGENT) == "test-agent"
assert span.attributes.get(USER_AGENT_ORIGINAL) == "test-agent"
assert span.attributes.get(HTTP_FLAVOR) == "1.1"
assert span.attributes.get(NETWORK_PROTOCOL_VERSION) == "1.1"
assert span.attributes.get(HTTP_STATUS_CODE) == 200
assert span.attributes.get(HTTP_RESPONSE_STATUS_CODE) == 200
assert span.attributes.get(HTTP_ROUTE) == "/test-path"
metrics = test_base.get_sorted_metrics(SCOPE)
assert len(metrics) == 3 # Both duration metrics + active requests
server_active_requests_count_attrs_both = list(_server_active_requests_count_attrs_old)
server_active_requests_count_attrs_both.extend(_server_active_requests_count_attrs_new)
recommended_metrics_attrs = {
"http.server.active_requests": server_active_requests_count_attrs_both,
"http.server.duration": _server_duration_attrs_old,
"http.server.request.duration": _server_duration_attrs_new,
}
for metric in metrics:
if metric.unit == "ms":
assert metric.name == "http.server.duration"
elif metric.unit == "s":
assert metric.name == "http.server.request.duration"
else:
assert metric.name == "http.server.active_requests"
for point in metric.data.data_points:
if isinstance(point, HistogramDataPoint) and metric.name == "http.server.request.duration":
assert point.explicit_bounds == HTTP_DURATION_HISTOGRAM_BUCKETS_NEW
for attr in point.attributes:
assert attr in recommended_metrics_attrs[metric.name]
finally:
await client_session.close()
AioHttpServerInstrumentor().uninstrument()
@pytest.mark.asyncio
@pytest.mark.parametrize(
"exception_class,expected_status",
[
(aiohttp.web.HTTPOk, 200),
(aiohttp.web.HTTPCreated, 201),
],
)
async def test_http_successful_no_error(test_base: TestBase, aiohttp_server, exception_class, expected_status):
AioHttpServerInstrumentor().instrument()
app = aiohttp.web.Application()
async def handler(request):
raise exception_class()
app.router.add_get("/test", handler)
server = await aiohttp_server(app)
url = f"http://{server.host}:{server.port}/test"
async with aiohttp.ClientSession() as session:
async with session.get(url) as response:
assert response.status == expected_status
spans = test_base.get_finished_spans()
assert len(spans) == 1
span = spans[0]
assert span.attributes.get(HTTP_STATUS_CODE) == expected_status
assert span.status.status_code == StatusCode.UNSET
assert len(span.events) == 0
AioHttpServerInstrumentor().uninstrument()
@pytest.mark.asyncio
@pytest.mark.parametrize(
"exception_class,expected_status,kwargs",
[
(aiohttp.web.HTTPMovedPermanently, 301, {"location": "/destination"}),
(aiohttp.web.HTTPFound, 302, {"location": "/destination"}),
],
)
async def test_http_redirection_no_error(
test_base: TestBase,
aiohttp_server,
exception_class,
expected_status,
kwargs,
):
AioHttpServerInstrumentor().instrument()
app = aiohttp.web.Application()
async def handler(request):
raise exception_class(**kwargs)
app.router.add_get("/test", handler)
server = await aiohttp_server(app)
url = f"http://{server.host}:{server.port}/test"
async with aiohttp.ClientSession() as session:
async with session.get(url, allow_redirects=False) as response:
assert response.status == expected_status
spans = test_base.get_finished_spans()
assert len(spans) == 1
span = spans[0]
assert span.attributes.get(HTTP_STATUS_CODE) == expected_status
assert span.status.status_code == StatusCode.UNSET
assert len(span.events) == 0
AioHttpServerInstrumentor().uninstrument()
@pytest.mark.asyncio
@pytest.mark.parametrize(
"exception_class,expected_status,kwargs",
[
(aiohttp.web.HTTPMovedPermanently, 301, {"location": "/destination"}),
(aiohttp.web.HTTPFound, 302, {"location": "/destination"}),
],
)
async def test_http_redirection_no_error_new_semconv(
test_base: TestBase,
aiohttp_server,
monkeypatch,
exception_class,
expected_status,
kwargs,
):
# Use new semconv
monkeypatch.setenv(OTEL_SEMCONV_STABILITY_OPT_IN, _StabilityMode.HTTP.value)
AioHttpServerInstrumentor().instrument()
app = aiohttp.web.Application()
async def handler(request):
raise exception_class(**kwargs)
app.router.add_get("/test", handler)
server = await aiohttp_server(app)
url = f"http://{server.host}:{server.port}/test"
async with aiohttp.ClientSession() as session:
async with session.get(url, allow_redirects=False) as response:
assert response.status == expected_status
spans = test_base.get_finished_spans()
assert len(spans) == 1
span = spans[0]
assert span.attributes.get(HTTP_RESPONSE_STATUS_CODE) == expected_status
assert span.status.status_code == StatusCode.UNSET
assert len(span.events) == 0
AioHttpServerInstrumentor().uninstrument()
@pytest.mark.asyncio
@pytest.mark.parametrize(
"exception_class,expected_status",
[
(aiohttp.web.HTTPBadRequest, 400),
(aiohttp.web.HTTPNotFound, 404),
],
)
async def test_http_client_error_no_error(test_base: TestBase, aiohttp_server, exception_class, expected_status):
AioHttpServerInstrumentor().instrument()
app = aiohttp.web.Application()
async def handler(request):
raise exception_class()
app.router.add_get("/test", handler)
server = await aiohttp_server(app)
url = f"http://{server.host}:{server.port}/test"
async with aiohttp.ClientSession() as session:
async with session.get(url) as response:
assert response.status == expected_status
spans = test_base.get_finished_spans()
assert len(spans) == 1
span = spans[0]
assert span.attributes.get(HTTP_STATUS_CODE) == expected_status
assert span.status.status_code == StatusCode.UNSET
assert len(span.events) == 0
AioHttpServerInstrumentor().uninstrument()
@pytest.mark.asyncio
@pytest.mark.parametrize(
"exception_class,expected_status",
[
(aiohttp.web.HTTPInternalServerError, 500),
(aiohttp.web.HTTPBadGateway, 502),
],
)
async def test_http_server_error_records_error(test_base: TestBase, aiohttp_server, exception_class, expected_status):
AioHttpServerInstrumentor().instrument()
app = aiohttp.web.Application()
async def handler(request):
raise exception_class()
app.router.add_get("/test", handler)
server = await aiohttp_server(app)
url = f"http://{server.host}:{server.port}/test"
async with aiohttp.ClientSession() as session:
async with session.get(url) as response:
assert response.status == expected_status
spans = test_base.get_finished_spans()
assert len(spans) == 1
span = spans[0]
assert span.attributes.get(HTTP_STATUS_CODE) == expected_status
assert span.status.status_code == StatusCode.ERROR
assert len(span.events) == 1
assert span.events[0].name == "exception"
assert span.events[0].attributes["exception.type"] == f"aiohttp.web_exceptions.{exception_class.__name__}"
AioHttpServerInstrumentor().uninstrument()
@pytest.mark.asyncio
@pytest.mark.parametrize(
"exception_class,message",
[
(ValueError, "Something went wrong"),
(RuntimeError, "Unexpected runtime error"),
],
)
async def test_generic_exception_records_error(test_base: TestBase, aiohttp_server, exception_class, message):
AioHttpServerInstrumentor().instrument()
app = aiohttp.web.Application()
async def handler(request):
raise exception_class(message)
app.router.add_get("/test", handler)
server = await aiohttp_server(app)
url = f"http://{server.host}:{server.port}/test"
async with aiohttp.ClientSession() as session:
async with session.get(url) as response:
assert response.status == 500
spans = test_base.get_finished_spans()
assert len(spans) == 1
span = spans[0]
assert span.status.status_code == StatusCode.ERROR
assert len(span.events) == 1
assert span.events[0].name == "exception"
assert span.events[0].attributes["exception.type"] == exception_class.__qualname__
assert span.events[0].attributes["exception.message"] == message
AioHttpServerInstrumentor().uninstrument()
@pytest.mark.asyncio
@pytest.mark.parametrize(
"exception_class,expected_status",
[
(aiohttp.web.HTTPInternalServerError, 500),
(aiohttp.web.HTTPBadGateway, 502),
],
)
async def test_http_server_error_records_error_new_semconv(
test_base: TestBase,
aiohttp_server,
monkeypatch,
exception_class,
expected_status,
):
# Use new semconv
monkeypatch.setenv(OTEL_SEMCONV_STABILITY_OPT_IN, _StabilityMode.HTTP.value)
AioHttpServerInstrumentor().instrument()
app = aiohttp.web.Application()
async def handler(request):
raise exception_class()
app.router.add_get("/test", handler)
server = await aiohttp_server(app)
url = f"http://{server.host}:{server.port}/test"
async with aiohttp.ClientSession() as session:
async with session.get(url) as response:
assert response.status == expected_status
spans = test_base.get_finished_spans()
assert len(spans) == 1
span = spans[0]
assert span.status.status_code == StatusCode.ERROR
assert len(span.events) == 1
assert span.attributes[ERROR_TYPE] == str(expected_status)
assert span.events[0].name == "exception"
assert span.events[0].attributes["exception.type"] == f"aiohttp.web_exceptions.{exception_class.__name__}"
AioHttpServerInstrumentor().uninstrument()
@pytest.mark.asyncio
@pytest.mark.parametrize(
"exception_class,message",
[
(ValueError, "Something went wrong"),
(RuntimeError, "Unexpected runtime error"),
],
)
async def test_generic_exception_records_error_new_semconv(
test_base: TestBase, aiohttp_server, monkeypatch, exception_class, message
):
# Use new semconv
monkeypatch.setenv(OTEL_SEMCONV_STABILITY_OPT_IN, _StabilityMode.HTTP.value)
AioHttpServerInstrumentor().instrument()
app = aiohttp.web.Application()
async def handler(request):
raise exception_class(message)
app.router.add_get("/test", handler)
server = await aiohttp_server(app)
url = f"http://{server.host}:{server.port}/test"
async with aiohttp.ClientSession() as session:
async with session.get(url) as response:
assert response.status == 500
spans = test_base.get_finished_spans()
assert len(spans) == 1
span = spans[0]
print(span.to_json())
assert span.status.status_code == StatusCode.ERROR
assert len(span.events) == 1
assert span.attributes[ERROR_TYPE] == exception_class.__qualname__
assert span.events[0].name == "exception"
assert span.events[0].attributes["exception.type"] == exception_class.__qualname__
AioHttpServerInstrumentor().uninstrument()
opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aiokafka/ 0000775 0000000 0000000 00000000000 15270700723 0032711 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aiokafka/LICENSE 0000664 0000000 0000000 00000026135 15270700723 0033725 0 ustar 00root root 0000000 0000000 Apache License
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README.rst 0000664 0000000 0000000 00000001251 15270700723 0034320 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aiokafka OpenTelemetry aiokafka instrumentation
=======================================
|pypi|
.. |pypi| image:: https://badge.fury.io/py/opentelemetry-instrumentation-aiokafka.svg
:target: https://pypi.org/project/opentelemetry-instrumentation-aiokafka/
Installation
------------
::
pip install opentelemetry-instrumentation-aiokafka
References
----------
* `OpenTelemetry aiokafka Instrumentation `_
* `OpenTelemetry Project `_
* `OpenTelemetry Python Examples `_
pyproject.toml 0000664 0000000 0000000 00000003172 15270700723 0035551 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aiokafka [build-system]
requires = ["hatchling"]
build-backend = "hatchling.build"
[project]
name = "opentelemetry-instrumentation-aiokafka"
dynamic = ["version"]
description = "OpenTelemetry aiokafka instrumentation"
readme = "README.rst"
license = "Apache-2.0"
requires-python = ">=3.10"
authors = [
{ name = "OpenTelemetry Authors", email = "cncf-opentelemetry-contributors@lists.cncf.io" },
]
classifiers = [
"Development Status :: 4 - Beta",
"Intended Audience :: Developers",
"License :: OSI Approved :: Apache Software License",
"Programming Language :: Python",
"Programming Language :: Python :: 3",
"Programming Language :: Python :: 3.10",
"Programming Language :: Python :: 3.11",
"Programming Language :: Python :: 3.12",
"Programming Language :: Python :: 3.13",
"Programming Language :: Python :: 3.14",
]
dependencies = [
"opentelemetry-api ~= 1.27",
"opentelemetry-instrumentation == 0.66b2",
"opentelemetry-semantic-conventions == 0.66b2",
"typing_extensions ~= 4.1",
]
[project.optional-dependencies]
instruments = ["aiokafka >= 0.8, < 1.0"]
[project.entry-points.opentelemetry_instrumentor]
aiokafka = "opentelemetry.instrumentation.aiokafka:AIOKafkaInstrumentor"
[project.urls]
Homepage = "https://github.com/open-telemetry/opentelemetry-python-contrib/tree/main/instrumentation/opentelemetry-instrumentation-aiokafka"
Repository = "https://github.com/open-telemetry/opentelemetry-python-contrib"
[tool.hatch.version]
path = "src/opentelemetry/instrumentation/aiokafka/version.py"
[tool.hatch.build.targets.sdist]
include = ["/src", "/tests"]
[tool.hatch.build.targets.wheel]
packages = ["src/opentelemetry"]
opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aiokafka/src/ 0000775 0000000 0000000 00000000000 15270700723 0033500 5 ustar 00root root 0000000 0000000 opentelemetry/ 0000775 0000000 0000000 00000000000 15270700723 0036315 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aiokafka/src instrumentation/ 0000775 0000000 0000000 00000000000 15270700723 0041560 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aiokafka/src/opentelemetry aiokafka/ 0000775 0000000 0000000 00000000000 15270700723 0043326 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aiokafka/src/opentelemetry/instrumentation __init__.py 0000664 0000000 0000000 00000013602 15270700723 0045441 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aiokafka/src/opentelemetry/instrumentation/aiokafka # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
"""
Instrument aiokafka to report instrumentation-kafka produced and consumed messages
Usage
-----
.. code:: python
import asyncio
from opentelemetry.instrumentation.aiokafka import AIOKafkaInstrumentor
from aiokafka import AIOKafkaProducer, AIOKafkaConsumer
# Instrument kafka
AIOKafkaInstrumentor().instrument()
# report a span of type producer with the default settings
async def produce():
producer = AIOKafkaProducer(bootstrap_servers=['localhost:9092'])
await producer.start()
try:
await producer.send_and_wait('my-topic', b'raw_bytes')
finally:
await producer.stop()
# report a span of type consumer with the default settings
async def consume():
consumer = AIOKafkaConsumer('my-topic', group_id='my-group', bootstrap_servers=['localhost:9092'])
await consumer.start()
try:
async for message in consumer:
# process message
print(message)
finally:
await consumer.stop()
asyncio.run(produce())
asyncio.run(consume())
The ``_instrument()`` method accepts the following keyword args:
- **tracer_provider** (TracerProvider) - an optional tracer provider
- **async_produce_hook** (Callable) - a function with extra user-defined logic to be performed before sending the message
Function signature:
.. code:: python
async def async_produce_hook(span: Span, args, kwargs): ...
- **async_consume_hook** (Callable) - a function with extra user-defined logic to be performed after consuming a message
Function signature:
.. code:: python
async def async_consume_hook(span: Span, record: kafka.record.ABCRecord, args, kwargs): ...
For example:
.. code:: python
import asyncio
from opentelemetry.instrumentation.aiokafka import AIOKafkaInstrumentor
from aiokafka import AIOKafkaProducer, AIOKafkaConsumer
async def async_produce_hook(span, args, kwargs):
if span and span.is_recording():
span.set_attribute("custom_user_attribute_from_async_response_hook", "some-value")
async def async_consume_hook(span, record, args, kwargs):
if span and span.is_recording():
span.set_attribute("custom_user_attribute_from_consume_hook", "some-value")
# instrument kafka with produce and consume hooks
AIOKafkaInstrumentor().instrument(async_produce_hook=async_produce_hook, async_consume_hook=async_consume_hook)
# Using kafka as normal now will automatically generate spans,
# including user custom attributes added from the hooks
async def produce():
producer = AIOKafkaProducer(bootstrap_servers=['localhost:9092'])
await producer.start()
try:
await producer.send_and_wait('my-topic', b'raw_bytes')
finally:
await producer.stop()
asyncio.run(produce())
API
---
"""
from __future__ import annotations
from collections.abc import Collection
from inspect import iscoroutinefunction
from typing import TYPE_CHECKING
import aiokafka
from wrapt import (
wrap_function_wrapper, # type: ignore[reportUnknownVariableType]
)
from opentelemetry import trace
from opentelemetry.instrumentation.aiokafka.package import _instruments
from opentelemetry.instrumentation.aiokafka.utils import (
_wrap_getmany,
_wrap_getone,
_wrap_send,
)
from opentelemetry.instrumentation.aiokafka.version import __version__
from opentelemetry.instrumentation.instrumentor import BaseInstrumentor
from opentelemetry.instrumentation.utils import unwrap
from opentelemetry.semconv.schemas import Schemas
if TYPE_CHECKING:
from typing import TypedDict
from typing_extensions import Unpack
from .utils import ConsumeHookT, ProduceHookT
class InstrumentKwargs(TypedDict, total=False):
tracer_provider: trace.TracerProvider
async_produce_hook: ProduceHookT
async_consume_hook: ConsumeHookT
class UninstrumentKwargs(TypedDict, total=False):
pass
class AIOKafkaInstrumentor(BaseInstrumentor):
"""An instrumentor for kafka module
See `BaseInstrumentor`
"""
def instrumentation_dependencies(self) -> Collection[str]:
return _instruments
def _instrument(self, **kwargs: Unpack[InstrumentKwargs]):
"""Instruments the kafka module
Args:
**kwargs: Optional arguments
``tracer_provider``: a TracerProvider, defaults to global.
``async_produce_hook``: a callable to be executed just before producing a message
``async_consume_hook``: a callable to be executed just after consuming a message
"""
tracer_provider = kwargs.get("tracer_provider")
async_produce_hook = kwargs.get("async_produce_hook")
if not iscoroutinefunction(async_produce_hook):
async_produce_hook = None
async_consume_hook = kwargs.get("async_consume_hook")
if not iscoroutinefunction(async_consume_hook):
async_consume_hook = None
tracer = trace.get_tracer(
__name__,
__version__,
tracer_provider=tracer_provider,
schema_url=Schemas.V1_27_0.value,
)
wrap_function_wrapper(
aiokafka.AIOKafkaProducer,
"send",
_wrap_send(tracer, async_produce_hook),
)
wrap_function_wrapper(
aiokafka.AIOKafkaConsumer,
"getone",
_wrap_getone(tracer, async_consume_hook),
)
wrap_function_wrapper(
aiokafka.AIOKafkaConsumer,
"getmany",
_wrap_getmany(tracer, async_consume_hook),
)
def _uninstrument(self, **kwargs: Unpack[UninstrumentKwargs]):
unwrap(aiokafka.AIOKafkaProducer, "send")
unwrap(aiokafka.AIOKafkaConsumer, "getone")
unwrap(aiokafka.AIOKafkaConsumer, "getmany")
package.py 0000664 0000000 0000000 00000000171 15270700723 0045272 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aiokafka/src/opentelemetry/instrumentation/aiokafka # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
_instruments = ("aiokafka >= 0.8, < 1.0",)
py.typed 0000664 0000000 0000000 00000000000 15270700723 0045013 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aiokafka/src/opentelemetry/instrumentation/aiokafka utils.py 0000664 0000000 0000000 00000044253 15270700723 0045050 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aiokafka/src/opentelemetry/instrumentation/aiokafka # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
from __future__ import annotations
import asyncio
import contextlib
import json
from collections.abc import Awaitable, Callable, MutableSequence, Sequence
from logging import getLogger
from typing import (
TYPE_CHECKING,
Any,
Protocol,
cast,
)
import aiokafka
from opentelemetry import context, propagate, trace
from opentelemetry.context import Context
from opentelemetry.propagators import textmap
from opentelemetry.semconv._incubating.attributes import messaging_attributes
from opentelemetry.semconv.attributes import server_attributes
from opentelemetry.trace import Tracer
from opentelemetry.trace.span import Span
if TYPE_CHECKING:
from aiokafka.structs import RecordMetadata
class AIOKafkaGetOneProto(Protocol):
async def __call__(self, *partitions: aiokafka.TopicPartition) -> aiokafka.ConsumerRecord[object, object]: ...
class AIOKafkaGetManyProto(Protocol):
async def __call__(
self,
*partitions: aiokafka.TopicPartition,
timeout_ms: int = 0,
max_records: int | None = None,
) -> dict[
aiokafka.TopicPartition,
list[aiokafka.ConsumerRecord[object, object]],
]: ...
class AIOKafkaSendProto(Protocol):
async def __call__(
self,
topic: str,
value: object | None = None,
key: object | None = None,
partition: int | None = None,
timestamp_ms: int | None = None,
headers: HeadersT | None = None,
) -> asyncio.Future[RecordMetadata]: ...
ProduceHookT = Callable[[Span, tuple[Any, ...], dict[str, Any]], Awaitable[None]]
ConsumeHookT = Callable[
[
Span,
aiokafka.ConsumerRecord[object, object],
tuple[aiokafka.TopicPartition, ...],
dict[str, Any],
],
Awaitable[None],
]
HeadersT = Sequence[tuple[str, bytes | None]]
_LOG = getLogger(__name__)
def _extract_bootstrap_servers(
client: aiokafka.AIOKafkaClient,
) -> str | list[str]:
return client._bootstrap_servers
def _extract_client_id(client: aiokafka.AIOKafkaClient) -> str:
return client._client_id
def _extract_consumer_group(
consumer: aiokafka.AIOKafkaConsumer,
) -> str | None:
return consumer._group_id # type: ignore[reportUnknownVariableType]
def _extract_argument(
key: str,
position: int,
default_value: Any,
args: tuple[Any, ...],
kwargs: dict[str, Any],
) -> Any:
if len(args) > position:
return args[position]
return kwargs.get(key, default_value)
def _extract_send_topic(args: tuple[Any, ...], kwargs: dict[str, Any]) -> str:
"""extract topic from `send` method arguments in AIOKafkaProducer class"""
return _extract_argument("topic", 0, "unknown", args, kwargs)
def _extract_send_value(args: tuple[Any, ...], kwargs: dict[str, Any]) -> object | None:
"""extract value from `send` method arguments in AIOKafkaProducer class"""
return _extract_argument("value", 1, None, args, kwargs)
def _extract_send_key(args: tuple[Any, ...], kwargs: dict[str, Any]) -> object | None:
"""extract key from `send` method arguments in AIOKafkaProducer class"""
return _extract_argument("key", 2, None, args, kwargs)
def _extract_send_headers(args: tuple[Any, ...], kwargs: dict[str, Any]) -> HeadersT | None:
"""extract headers from `send` method arguments in AIOKafkaProducer class"""
return _extract_argument("headers", 5, None, args, kwargs)
def _move_headers_to_kwargs(args: tuple[Any], kwargs: dict[str, Any]) -> tuple[tuple[Any], dict[str, Any]]:
"""Move headers from args to kwargs"""
if len(args) > 5:
kwargs["headers"] = args[5]
return args[:5], kwargs
def _deserialize_key(key: object | None) -> str | None:
if key is None:
return None
if isinstance(key, bytes):
with contextlib.suppress(UnicodeDecodeError):
return key.decode()
return str(key)
async def _extract_send_partition(
instance: aiokafka.AIOKafkaProducer,
args: tuple[Any, ...],
kwargs: dict[str, Any],
) -> int | None:
"""extract partition `send` method arguments, using the `_partition` method in AIOKafkaProducer class"""
try:
topic = _extract_send_topic(args, kwargs)
key = _extract_send_key(args, kwargs)
value = _extract_send_value(args, kwargs)
partition = _extract_argument("partition", 3, None, args, kwargs)
key_bytes = cast(
"bytes | None",
instance._key_serializer(key) # type: ignore[reportUnknownMemberType]
if instance._key_serializer # type: ignore[reportUnknownMemberType]
else key,
)
value_bytes = cast(
"bytes | None",
instance._value_serializer(value) # type: ignore[reportUnknownMemberType]
if instance._value_serializer # type: ignore[reportUnknownMemberType]
else value,
)
valid_types = (bytes, bytearray, memoryview, type(None))
if type(key_bytes) not in valid_types or type(value_bytes) not in valid_types:
return None
await instance.client._wait_on_metadata(topic) # type: ignore[reportUnknownMemberType]
return instance._partition( # type: ignore[reportUnknownMemberType]
topic, partition, key, value, key_bytes, value_bytes
)
except Exception as exception: # pylint: disable=W0703
_LOG.debug("Unable to extract partition: %s", exception)
return None
class AIOKafkaContextGetter(textmap.Getter["HeadersT"]):
def get(self, carrier: HeadersT, key: str) -> list[str] | None:
for item_key, value in carrier:
if item_key == key:
if value is not None:
return [value.decode()]
return None
def keys(self, carrier: HeadersT) -> list[str]:
return [key for (key, _) in carrier]
class AIOKafkaContextSetter(textmap.Setter["HeadersT"]):
def set(self, carrier: HeadersT, key: str | None, value: str | None) -> None:
if key is None:
return
if not isinstance(carrier, MutableSequence):
_LOG.warning("Unable to set context in headers. Headers is immutable")
return
if value is not None:
carrier.append((key, value.encode()))
else:
carrier.append((key, value))
_aiokafka_getter = AIOKafkaContextGetter()
_aiokafka_setter = AIOKafkaContextSetter()
def _enrich_base_span(
span: Span,
*,
bootstrap_servers: str | list[str],
client_id: str,
topic: str,
partition: int | None,
key: str | None,
) -> None:
span.set_attribute(
messaging_attributes.MESSAGING_SYSTEM,
messaging_attributes.MessagingSystemValues.KAFKA.value,
)
span.set_attribute(server_attributes.SERVER_ADDRESS, json.dumps(bootstrap_servers))
span.set_attribute(messaging_attributes.MESSAGING_CLIENT_ID, client_id)
span.set_attribute(messaging_attributes.MESSAGING_DESTINATION_NAME, topic)
if partition is not None:
span.set_attribute(
messaging_attributes.MESSAGING_DESTINATION_PARTITION_ID,
str(partition),
)
if key is not None:
span.set_attribute(messaging_attributes.MESSAGING_KAFKA_MESSAGE_KEY, key)
def _enrich_send_span(
span: Span,
*,
bootstrap_servers: str | list[str],
client_id: str,
topic: str,
partition: int | None,
key: str | None,
) -> None:
if not span.is_recording():
return
_enrich_base_span(
span,
bootstrap_servers=bootstrap_servers,
client_id=client_id,
topic=topic,
partition=partition,
key=key,
)
span.set_attribute(messaging_attributes.MESSAGING_OPERATION_NAME, "send")
span.set_attribute(
messaging_attributes.MESSAGING_OPERATION_TYPE,
messaging_attributes.MessagingOperationTypeValues.PUBLISH.value,
)
def _enrich_getone_span(
span: Span,
*,
bootstrap_servers: str | list[str],
client_id: str,
consumer_group: str | None,
topic: str,
partition: int | None,
key: str | None,
offset: int,
) -> None:
if not span.is_recording():
return
_enrich_base_span(
span,
bootstrap_servers=bootstrap_servers,
client_id=client_id,
topic=topic,
partition=partition,
key=key,
)
if consumer_group is not None:
span.set_attribute(messaging_attributes.MESSAGING_CONSUMER_GROUP_NAME, consumer_group)
span.set_attribute(messaging_attributes.MESSAGING_OPERATION_NAME, "receive")
span.set_attribute(
messaging_attributes.MESSAGING_OPERATION_TYPE,
messaging_attributes.MessagingOperationTypeValues.RECEIVE.value,
)
span.set_attribute(messaging_attributes.MESSAGING_KAFKA_MESSAGE_OFFSET, offset)
# https://stackoverflow.com/questions/65935155/identify-and-find-specific-message-in-kafka-topic
# A message within Kafka is uniquely defined by its topic name, topic partition and offset.
if partition is not None:
span.set_attribute(
messaging_attributes.MESSAGING_MESSAGE_ID,
f"{topic}.{partition}.{offset}",
)
def _enrich_getmany_poll_span(
span: Span,
*,
bootstrap_servers: str | list[str],
client_id: str,
consumer_group: str | None,
message_count: int,
) -> None:
if not span.is_recording():
return
span.set_attribute(
messaging_attributes.MESSAGING_SYSTEM,
messaging_attributes.MessagingSystemValues.KAFKA.value,
)
span.set_attribute(server_attributes.SERVER_ADDRESS, json.dumps(bootstrap_servers))
span.set_attribute(messaging_attributes.MESSAGING_CLIENT_ID, client_id)
if consumer_group is not None:
span.set_attribute(messaging_attributes.MESSAGING_CONSUMER_GROUP_NAME, consumer_group)
span.set_attribute(messaging_attributes.MESSAGING_BATCH_MESSAGE_COUNT, message_count)
span.set_attribute(messaging_attributes.MESSAGING_OPERATION_NAME, "receive")
span.set_attribute(
messaging_attributes.MESSAGING_OPERATION_TYPE,
messaging_attributes.MessagingOperationTypeValues.RECEIVE.value,
)
def _enrich_getmany_topic_span(
span: Span,
*,
bootstrap_servers: str | list[str],
client_id: str,
consumer_group: str | None,
topic: str,
partition: int,
message_count: int,
) -> None:
if not span.is_recording():
return
_enrich_base_span(
span,
bootstrap_servers=bootstrap_servers,
client_id=client_id,
topic=topic,
partition=partition,
key=None,
)
if consumer_group is not None:
span.set_attribute(messaging_attributes.MESSAGING_CONSUMER_GROUP_NAME, consumer_group)
span.set_attribute(messaging_attributes.MESSAGING_BATCH_MESSAGE_COUNT, message_count)
span.set_attribute(messaging_attributes.MESSAGING_OPERATION_NAME, "receive")
span.set_attribute(
messaging_attributes.MESSAGING_OPERATION_TYPE,
messaging_attributes.MessagingOperationTypeValues.RECEIVE.value,
)
def _get_span_name(operation: str, topic: str):
return f"{topic} {operation}"
def _wrap_send( # type: ignore[reportUnusedFunction]
tracer: Tracer, async_produce_hook: ProduceHookT | None
) -> Callable[..., Awaitable[asyncio.Future[RecordMetadata]]]:
async def _traced_send(
func: AIOKafkaSendProto,
instance: aiokafka.AIOKafkaProducer,
args: tuple[Any, ...],
kwargs: dict[str, Any],
) -> asyncio.Future[RecordMetadata]:
args, kwargs = _move_headers_to_kwargs(args, kwargs)
headers: HeadersT | None = _extract_send_headers(args, kwargs)
if headers is None:
headers = []
kwargs["headers"] = headers
topic = _extract_send_topic(args, kwargs)
bootstrap_servers = _extract_bootstrap_servers(instance.client)
client_id = _extract_client_id(instance.client)
key = _deserialize_key(_extract_send_key(args, kwargs))
partition = await _extract_send_partition(instance, args, kwargs)
span_name = _get_span_name("send", topic)
with tracer.start_as_current_span(span_name, kind=trace.SpanKind.PRODUCER) as span:
_enrich_send_span(
span,
bootstrap_servers=bootstrap_servers,
client_id=client_id,
topic=topic,
partition=partition,
key=key,
)
propagate.inject(
headers,
context=trace.set_span_in_context(span),
setter=_aiokafka_setter,
)
try:
if async_produce_hook is not None:
await async_produce_hook(span, args, kwargs)
except Exception as hook_exception: # pylint: disable=W0703
_LOG.exception(hook_exception)
return await func(*args, **kwargs)
return _traced_send
async def _create_consumer_span(
tracer: Tracer,
async_consume_hook: ConsumeHookT | None,
record: aiokafka.ConsumerRecord[object, object],
extracted_context: Context,
bootstrap_servers: str | list[str],
client_id: str,
consumer_group: str | None,
args: tuple[aiokafka.TopicPartition, ...],
kwargs: dict[str, Any],
) -> trace.Span:
span_name = _get_span_name("receive", record.topic)
with tracer.start_as_current_span(
span_name,
context=extracted_context,
kind=trace.SpanKind.CONSUMER,
) as span:
new_context = trace.set_span_in_context(span, extracted_context)
token = context.attach(new_context)
_enrich_getone_span(
span,
bootstrap_servers=bootstrap_servers,
client_id=client_id,
consumer_group=consumer_group,
topic=record.topic,
partition=record.partition,
key=_deserialize_key(record.key),
offset=record.offset,
)
try:
if async_consume_hook is not None:
await async_consume_hook(span, record, args, kwargs)
except Exception as hook_exception: # pylint: disable=W0703
_LOG.exception(hook_exception)
if token:
context.detach(token)
return span
def _wrap_getone( # type: ignore[reportUnusedFunction]
tracer: Tracer, async_consume_hook: ConsumeHookT | None
) -> Callable[..., Awaitable[aiokafka.ConsumerRecord[object, object]]]:
async def _traced_getone(
func: AIOKafkaGetOneProto,
instance: aiokafka.AIOKafkaConsumer,
args: tuple[aiokafka.TopicPartition, ...],
kwargs: dict[str, Any],
) -> aiokafka.ConsumerRecord[object, object]:
record = await func(*args, **kwargs)
if record:
bootstrap_servers = _extract_bootstrap_servers(instance._client)
client_id = _extract_client_id(instance._client)
consumer_group = _extract_consumer_group(instance)
extracted_context = propagate.extract(record.headers, getter=_aiokafka_getter)
await _create_consumer_span(
tracer,
async_consume_hook,
record,
extracted_context,
bootstrap_servers,
client_id,
consumer_group,
args,
kwargs,
)
return record
return _traced_getone
def _wrap_getmany( # type: ignore[reportUnusedFunction]
tracer: Tracer, async_consume_hook: ConsumeHookT | None
) -> Callable[
...,
Awaitable[
dict[
aiokafka.TopicPartition,
list[aiokafka.ConsumerRecord[object, object]],
]
],
]:
async def _traced_getmany(
func: AIOKafkaGetManyProto,
instance: aiokafka.AIOKafkaConsumer,
args: tuple[aiokafka.TopicPartition, ...],
kwargs: dict[str, Any],
) -> dict[aiokafka.TopicPartition, list[aiokafka.ConsumerRecord[object, object]]]:
records = await func(*args, **kwargs)
if records:
bootstrap_servers = _extract_bootstrap_servers(instance._client)
client_id = _extract_client_id(instance._client)
consumer_group = _extract_consumer_group(instance)
span_name = _get_span_name(
"receive",
", ".join(sorted({topic.topic for topic in records.keys()})),
)
with tracer.start_as_current_span(span_name, kind=trace.SpanKind.CONSUMER) as poll_span:
_enrich_getmany_poll_span(
poll_span,
bootstrap_servers=bootstrap_servers,
client_id=client_id,
consumer_group=consumer_group,
message_count=sum(len(r) for r in records.values()),
)
for topic, topic_records in records.items():
span_name = _get_span_name("receive", topic.topic)
with tracer.start_as_current_span(span_name, kind=trace.SpanKind.CONSUMER) as topic_span:
_enrich_getmany_topic_span(
topic_span,
bootstrap_servers=bootstrap_servers,
client_id=client_id,
consumer_group=consumer_group,
topic=topic.topic,
partition=topic.partition,
message_count=len(topic_records),
)
for record in topic_records:
extracted_context = propagate.extract(record.headers, getter=_aiokafka_getter)
record_span = await _create_consumer_span(
tracer,
async_consume_hook,
record,
extracted_context,
bootstrap_servers,
client_id,
consumer_group,
args,
kwargs,
)
topic_span.add_link(record_span.get_span_context())
return records
return _traced_getmany
version.py 0000664 0000000 0000000 00000000144 15270700723 0045364 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aiokafka/src/opentelemetry/instrumentation/aiokafka # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
__version__ = "0.66b2"
test-requirements.txt 0000664 0000000 0000000 00000000276 15270700723 0037100 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aiokafka aiokafka==0.13.0; python_version >= "3.10"
aiokafka==0.12.0; python_version < "3.10"
pytest==7.4.4
-e opentelemetry-instrumentation
-e instrumentation/opentelemetry-instrumentation-aiokafka
opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aiokafka/tests/ 0000775 0000000 0000000 00000000000 15270700723 0034053 5 ustar 00root root 0000000 0000000 __init__.py 0000664 0000000 0000000 00000000000 15270700723 0036073 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aiokafka/tests test_instrumentation.py 0000664 0000000 0000000 00000046535 15270700723 0040665 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aiokafka/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
from __future__ import annotations
import uuid
from collections.abc import Sequence
from typing import Any, cast
from unittest import IsolatedAsyncioTestCase, TestCase, mock
import aiokafka
from aiokafka import (
AIOKafkaConsumer,
AIOKafkaProducer,
ConsumerRecord,
TopicPartition,
)
from wrapt import BoundFunctionWrapper
from opentelemetry import baggage, context
from opentelemetry.instrumentation.aiokafka import AIOKafkaInstrumentor
from opentelemetry.sdk.trace import ReadableSpan
from opentelemetry.semconv._incubating.attributes import messaging_attributes
from opentelemetry.semconv.attributes import server_attributes
from opentelemetry.test.test_base import TestBase
from opentelemetry.trace import SpanKind, format_trace_id, set_span_in_context
class TestAIOKafkaInstrumentor(TestCase):
def test_instrument_api(self) -> None:
instrumentation = AIOKafkaInstrumentor()
instrumentation.instrument()
self.assertTrue(isinstance(AIOKafkaProducer.send, BoundFunctionWrapper))
self.assertTrue(isinstance(AIOKafkaConsumer.getone, BoundFunctionWrapper))
self.assertTrue(isinstance(AIOKafkaConsumer.getmany, BoundFunctionWrapper))
instrumentation.uninstrument()
self.assertFalse(isinstance(AIOKafkaProducer.send, BoundFunctionWrapper))
self.assertFalse(isinstance(AIOKafkaConsumer.getone, BoundFunctionWrapper))
self.assertFalse(isinstance(AIOKafkaConsumer.getmany, BoundFunctionWrapper))
class TestAIOKafkaInstrumentation(TestBase, IsolatedAsyncioTestCase):
@staticmethod
def consumer_record_factory(number: int, headers: tuple[tuple[str, bytes], ...]) -> ConsumerRecord:
return ConsumerRecord(
f"topic_{number}",
number,
number,
number,
number,
f"key_{number}".encode(),
f"value_{number}".encode(),
None,
number,
number,
headers=headers,
)
@staticmethod
def consumer_batch_factory(
*headers: tuple[tuple[str, bytes], ...],
) -> dict[aiokafka.TopicPartition, list[aiokafka.ConsumerRecord]]:
records = {}
for number, record_headers in enumerate(headers, start=1):
records[aiokafka.TopicPartition(topic=f"topic_{number}", partition=number)] = [
ConsumerRecord(
f"topic_{number}",
number,
number,
number,
number,
f"key_{number}".encode(),
f"value_{number}".encode(),
None,
number,
number,
headers=record_headers,
)
]
return records
@staticmethod
async def consumer_factory(**consumer_kwargs: Any) -> AIOKafkaConsumer:
consumer = AIOKafkaConsumer(**consumer_kwargs)
consumer._client.bootstrap = mock.AsyncMock()
consumer._client._wait_on_metadata = mock.AsyncMock()
await consumer.start()
consumer._fetcher.next_record = mock.AsyncMock()
consumer._fetcher.fetched_records = mock.AsyncMock()
return consumer
@staticmethod
async def producer_factory() -> AIOKafkaProducer:
producer = AIOKafkaProducer()
producer.client._wait_on_metadata = mock.AsyncMock()
producer.client.bootstrap = mock.AsyncMock()
producer._message_accumulator.add_message = mock.AsyncMock()
producer._sender.start = mock.AsyncMock()
producer._partition = mock.Mock(return_value=1)
await producer.start()
return producer
def setUp(self):
super().setUp()
AIOKafkaInstrumentor().instrument(tracer_provider=self.tracer_provider)
def tearDown(self):
super().tearDown()
AIOKafkaInstrumentor().uninstrument()
async def test_getone(self) -> None:
client_id = str(uuid.uuid4())
group_id = str(uuid.uuid4())
consumer = await self.consumer_factory(client_id=client_id, group_id=group_id)
self.addAsyncCleanup(consumer.stop)
next_record_mock = cast(mock.AsyncMock, consumer._fetcher.next_record)
expected_spans = [
{
"name": "topic_1 receive",
"kind": SpanKind.CONSUMER,
"attributes": {
messaging_attributes.MESSAGING_SYSTEM: messaging_attributes.MessagingSystemValues.KAFKA.value,
server_attributes.SERVER_ADDRESS: '"localhost"',
messaging_attributes.MESSAGING_CLIENT_ID: client_id,
messaging_attributes.MESSAGING_DESTINATION_NAME: "topic_1",
messaging_attributes.MESSAGING_DESTINATION_PARTITION_ID: "1",
messaging_attributes.MESSAGING_KAFKA_MESSAGE_KEY: "key_1",
messaging_attributes.MESSAGING_CONSUMER_GROUP_NAME: group_id,
messaging_attributes.MESSAGING_OPERATION_NAME: "receive",
messaging_attributes.MESSAGING_OPERATION_TYPE: messaging_attributes.MessagingOperationTypeValues.RECEIVE.value,
messaging_attributes.MESSAGING_KAFKA_MESSAGE_OFFSET: 1,
messaging_attributes.MESSAGING_MESSAGE_ID: "topic_1.1.1",
},
},
{
"name": "topic_2 receive",
"kind": SpanKind.CONSUMER,
"attributes": {
messaging_attributes.MESSAGING_SYSTEM: messaging_attributes.MessagingSystemValues.KAFKA.value,
server_attributes.SERVER_ADDRESS: '"localhost"',
messaging_attributes.MESSAGING_CLIENT_ID: client_id,
messaging_attributes.MESSAGING_DESTINATION_NAME: "topic_2",
messaging_attributes.MESSAGING_DESTINATION_PARTITION_ID: "2",
messaging_attributes.MESSAGING_KAFKA_MESSAGE_KEY: "key_2",
messaging_attributes.MESSAGING_CONSUMER_GROUP_NAME: group_id,
messaging_attributes.MESSAGING_OPERATION_NAME: "receive",
messaging_attributes.MESSAGING_OPERATION_TYPE: messaging_attributes.MessagingOperationTypeValues.RECEIVE.value,
messaging_attributes.MESSAGING_KAFKA_MESSAGE_OFFSET: 2,
messaging_attributes.MESSAGING_MESSAGE_ID: "topic_2.2.2",
},
},
]
self.memory_exporter.clear()
next_record_mock.side_effect = [
self.consumer_record_factory(
1,
headers=(
(
"traceparent",
b"00-03afa25236b8cd948fa853d67038ac79-405ff022e8247c46-01",
),
),
),
self.consumer_record_factory(2, headers=()),
]
await consumer.getone()
next_record_mock.assert_awaited_with(())
first_span = self.memory_exporter.get_finished_spans()[0]
self.assertEqual(
format_trace_id(first_span.get_span_context().trace_id),
"03afa25236b8cd948fa853d67038ac79",
)
await consumer.getone()
next_record_mock.assert_awaited_with(())
span_list = self.memory_exporter.get_finished_spans()
self._compare_spans(span_list, expected_spans)
async def test_getone_baggage(self) -> None:
received_baggage = None
async def async_consume_hook(span, *_) -> None:
nonlocal received_baggage
received_baggage = baggage.get_all(set_span_in_context(span))
AIOKafkaInstrumentor().uninstrument()
AIOKafkaInstrumentor().instrument(
tracer_provider=self.tracer_provider,
async_consume_hook=async_consume_hook,
)
consumer = await self.consumer_factory()
self.addAsyncCleanup(consumer.stop)
next_record_mock = cast(mock.AsyncMock, consumer._fetcher.next_record)
self.memory_exporter.clear()
next_record_mock.side_effect = [
self.consumer_record_factory(
1,
headers=(
(
"traceparent",
b"00-03afa25236b8cd948fa853d67038ac79-405ff022e8247c46-01",
),
("baggage", b"foo=bar"),
),
),
]
await consumer.getone()
next_record_mock.assert_awaited_with(())
self.assertEqual(received_baggage, {"foo": "bar"})
async def test_getone_consume_hook(self) -> None:
async_consume_hook_mock = mock.AsyncMock()
AIOKafkaInstrumentor().uninstrument()
AIOKafkaInstrumentor().instrument(
tracer_provider=self.tracer_provider,
async_consume_hook=async_consume_hook_mock,
)
consumer = await self.consumer_factory()
self.addAsyncCleanup(consumer.stop)
next_record_mock = cast(mock.AsyncMock, consumer._fetcher.next_record)
next_record_mock.side_effect = [self.consumer_record_factory(1, headers=())]
await consumer.getone()
async_consume_hook_mock.assert_awaited_once()
async def test_getmany(self) -> None:
client_id = str(uuid.uuid4())
group_id = str(uuid.uuid4())
consumer = await self.consumer_factory(client_id=client_id, group_id=group_id)
self.addAsyncCleanup(consumer.stop)
fetched_records_mock = cast(mock.AsyncMock, consumer._fetcher.fetched_records)
expected_spans = [
{
"name": "topic_1 receive",
"kind": SpanKind.CONSUMER,
"attributes": {
messaging_attributes.MESSAGING_SYSTEM: messaging_attributes.MessagingSystemValues.KAFKA.value,
server_attributes.SERVER_ADDRESS: '"localhost"',
messaging_attributes.MESSAGING_CLIENT_ID: client_id,
messaging_attributes.MESSAGING_DESTINATION_NAME: "topic_1",
messaging_attributes.MESSAGING_DESTINATION_PARTITION_ID: "1",
messaging_attributes.MESSAGING_KAFKA_MESSAGE_KEY: "key_1",
messaging_attributes.MESSAGING_CONSUMER_GROUP_NAME: group_id,
messaging_attributes.MESSAGING_OPERATION_NAME: "receive",
messaging_attributes.MESSAGING_OPERATION_TYPE: messaging_attributes.MessagingOperationTypeValues.RECEIVE.value,
messaging_attributes.MESSAGING_KAFKA_MESSAGE_OFFSET: 1,
messaging_attributes.MESSAGING_MESSAGE_ID: "topic_1.1.1",
},
},
{
"name": "topic_1 receive",
"kind": SpanKind.CONSUMER,
"attributes": {
messaging_attributes.MESSAGING_SYSTEM: messaging_attributes.MessagingSystemValues.KAFKA.value,
server_attributes.SERVER_ADDRESS: '"localhost"',
messaging_attributes.MESSAGING_CLIENT_ID: client_id,
messaging_attributes.MESSAGING_DESTINATION_NAME: "topic_1",
messaging_attributes.MESSAGING_DESTINATION_PARTITION_ID: "1",
messaging_attributes.MESSAGING_CONSUMER_GROUP_NAME: group_id,
messaging_attributes.MESSAGING_OPERATION_NAME: "receive",
messaging_attributes.MESSAGING_OPERATION_TYPE: messaging_attributes.MessagingOperationTypeValues.RECEIVE.value,
messaging_attributes.MESSAGING_BATCH_MESSAGE_COUNT: 1,
},
},
{
"name": "topic_2 receive",
"kind": SpanKind.CONSUMER,
"attributes": {
messaging_attributes.MESSAGING_SYSTEM: messaging_attributes.MessagingSystemValues.KAFKA.value,
server_attributes.SERVER_ADDRESS: '"localhost"',
messaging_attributes.MESSAGING_CLIENT_ID: client_id,
messaging_attributes.MESSAGING_DESTINATION_NAME: "topic_2",
messaging_attributes.MESSAGING_DESTINATION_PARTITION_ID: "2",
messaging_attributes.MESSAGING_KAFKA_MESSAGE_KEY: "key_2",
messaging_attributes.MESSAGING_CONSUMER_GROUP_NAME: group_id,
messaging_attributes.MESSAGING_OPERATION_NAME: "receive",
messaging_attributes.MESSAGING_OPERATION_TYPE: messaging_attributes.MessagingOperationTypeValues.RECEIVE.value,
messaging_attributes.MESSAGING_KAFKA_MESSAGE_OFFSET: 2,
messaging_attributes.MESSAGING_MESSAGE_ID: "topic_2.2.2",
},
},
{
"name": "topic_2 receive",
"kind": SpanKind.CONSUMER,
"attributes": {
messaging_attributes.MESSAGING_SYSTEM: messaging_attributes.MessagingSystemValues.KAFKA.value,
server_attributes.SERVER_ADDRESS: '"localhost"',
messaging_attributes.MESSAGING_CLIENT_ID: client_id,
messaging_attributes.MESSAGING_DESTINATION_NAME: "topic_2",
messaging_attributes.MESSAGING_DESTINATION_PARTITION_ID: "2",
messaging_attributes.MESSAGING_CONSUMER_GROUP_NAME: group_id,
messaging_attributes.MESSAGING_OPERATION_NAME: "receive",
messaging_attributes.MESSAGING_OPERATION_TYPE: messaging_attributes.MessagingOperationTypeValues.RECEIVE.value,
messaging_attributes.MESSAGING_BATCH_MESSAGE_COUNT: 1,
},
},
{
"name": "topic_1, topic_2 receive",
"kind": SpanKind.CONSUMER,
"attributes": {
messaging_attributes.MESSAGING_SYSTEM: messaging_attributes.MessagingSystemValues.KAFKA.value,
server_attributes.SERVER_ADDRESS: '"localhost"',
messaging_attributes.MESSAGING_CLIENT_ID: client_id,
messaging_attributes.MESSAGING_CONSUMER_GROUP_NAME: group_id,
messaging_attributes.MESSAGING_OPERATION_NAME: "receive",
messaging_attributes.MESSAGING_OPERATION_TYPE: messaging_attributes.MessagingOperationTypeValues.RECEIVE.value,
messaging_attributes.MESSAGING_BATCH_MESSAGE_COUNT: 2,
},
},
]
self.memory_exporter.clear()
fetched_records_mock.side_effect = [
self.consumer_batch_factory(
(
(
"traceparent",
b"00-03afa25236b8cd948fa853d67038ac79-405ff022e8247c46-01",
),
),
(),
),
]
await consumer.getmany()
fetched_records_mock.assert_awaited_with((), 0.0, max_records=None)
span_list = self.memory_exporter.get_finished_spans()
self._compare_spans(span_list, expected_spans)
async def test_send(self) -> None:
producer = await self.producer_factory()
self.addAsyncCleanup(producer.stop)
add_message_mock = cast(mock.AsyncMock, producer._message_accumulator.add_message)
tracer = self.tracer_provider.get_tracer(__name__)
with tracer.start_as_current_span("test_span") as span:
await producer.send("topic_1", b"value_1")
add_message_mock.assert_awaited_with(
TopicPartition(topic="topic_1", partition=1),
None,
b"value_1",
40.0,
timestamp_ms=None,
headers=[("traceparent", mock.ANY)],
)
add_message_mock.call_args_list[0].kwargs["headers"][0][1].startswith(
f"00-{format_trace_id(span.get_span_context().trace_id)}-".encode()
)
await producer.send("topic_2", b"value_2")
add_message_mock.assert_awaited_with(
TopicPartition(topic="topic_2", partition=1),
None,
b"value_2",
40.0,
timestamp_ms=None,
headers=[("traceparent", mock.ANY)],
)
async def test_send_baggage(self) -> None:
producer = await self.producer_factory()
self.addAsyncCleanup(producer.stop)
add_message_mock = cast(mock.AsyncMock, producer._message_accumulator.add_message)
tracer = self.tracer_provider.get_tracer(__name__)
ctx = baggage.set_baggage("foo", "bar")
context.attach(ctx)
with tracer.start_as_current_span("test_span", context=ctx):
await producer.send("topic_1", b"value_1")
add_message_mock.assert_awaited_with(
TopicPartition(topic="topic_1", partition=1),
None,
b"value_1",
40.0,
timestamp_ms=None,
headers=[("traceparent", mock.ANY), ("baggage", b"foo=bar")],
)
async def test_send_produce_hook(self) -> None:
async_produce_hook_mock = mock.AsyncMock()
AIOKafkaInstrumentor().uninstrument()
AIOKafkaInstrumentor().instrument(
tracer_provider=self.tracer_provider,
async_produce_hook=async_produce_hook_mock,
)
producer = await self.producer_factory()
self.addAsyncCleanup(producer.stop)
await producer.send("topic_1", b"value_1")
async_produce_hook_mock.assert_awaited_once()
def _compare_spans(self, spans: Sequence[ReadableSpan], expected_spans: list[dict]) -> None:
self.assertEqual(len(spans), len(expected_spans))
for span, expected_span in zip(spans, expected_spans):
self.assertEqual(expected_span["name"], span.name, msg=span.name)
self.assertEqual(expected_span["kind"], span.kind, msg=span.name)
self.assertEqual(
expected_span["attributes"],
dict(span.attributes),
msg=span.name,
)
async def test_send_and_wait(self) -> None:
AIOKafkaInstrumentor().uninstrument()
AIOKafkaInstrumentor().instrument(tracer_provider=self.tracer_provider)
producer = await self.producer_factory()
try:
add_message_mock: mock.AsyncMock = producer._message_accumulator.add_message
add_message_mock.side_effect = [
mock.AsyncMock()(),
mock.AsyncMock()(),
]
tracer = self.tracer_provider.get_tracer(__name__)
with tracer.start_as_current_span("test_span") as span:
await producer.send_and_wait("topic_1", b"value_1")
add_message_mock.assert_awaited_with(
TopicPartition(topic="topic_1", partition=1),
None,
b"value_1",
40.0,
timestamp_ms=None,
headers=[("traceparent", mock.ANY)],
)
assert (
add_message_mock.call_args_list[0]
.kwargs["headers"][0][1]
.startswith(f"00-{format_trace_id(span.get_span_context().trace_id)}-".encode())
)
await producer.send_and_wait("topic_2", b"value_2")
add_message_mock.assert_awaited_with(
TopicPartition(topic="topic_2", partition=1),
None,
b"value_2",
40.0,
timestamp_ms=None,
headers=[("traceparent", mock.ANY)],
)
finally:
await producer.stop()
test_utils.py 0000664 0000000 0000000 00000027562 15270700723 0036561 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aiokafka/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
# pylint: disable=unnecessary-dunder-call
from __future__ import annotations
from unittest import IsolatedAsyncioTestCase, mock
import aiokafka
from opentelemetry.instrumentation.aiokafka.utils import (
AIOKafkaContextGetter,
AIOKafkaContextSetter,
_aiokafka_getter,
_aiokafka_setter,
_create_consumer_span,
_extract_send_partition,
_get_span_name,
_wrap_getmany,
_wrap_getone,
_wrap_send,
)
from opentelemetry.trace import SpanKind
class TestUtils(IsolatedAsyncioTestCase):
def setUp(self) -> None:
super().setUp()
self.topic_name = "test_topic"
self.args = [self.topic_name]
self.headers = []
self.kwargs = {"partition": 0, "headers": self.headers}
def test_context_setter(self) -> None:
context_setter = AIOKafkaContextSetter()
carrier_list = [("key1", b"val1")]
context_setter.set(carrier_list, "key2", "val2")
self.assertTrue(("key2", b"val2") in carrier_list)
def test_context_getter(self) -> None:
context_setter = AIOKafkaContextSetter()
context_getter = AIOKafkaContextGetter()
carrier_list = []
context_setter.set(carrier_list, "key1", "val1")
self.assertEqual(context_getter.get(carrier_list, "key1"), ["val1"])
self.assertEqual(["key1"], context_getter.keys(carrier_list))
@mock.patch("opentelemetry.instrumentation.aiokafka.utils._extract_bootstrap_servers")
@mock.patch("opentelemetry.instrumentation.aiokafka.utils._extract_send_partition")
@mock.patch("opentelemetry.instrumentation.aiokafka.utils._enrich_send_span")
@mock.patch("opentelemetry.trace.set_span_in_context")
@mock.patch("opentelemetry.propagate.inject")
async def test_wrap_send_with_topic_as_arg(
self,
inject: mock.MagicMock,
set_span_in_context: mock.MagicMock,
enrich_span: mock.MagicMock,
extract_send_partition: mock.MagicMock,
extract_bootstrap_servers: mock.MagicMock,
) -> None:
await self.wrap_send_helper(
inject,
set_span_in_context,
enrich_span,
extract_send_partition,
extract_bootstrap_servers,
)
@mock.patch("opentelemetry.instrumentation.aiokafka.utils._extract_bootstrap_servers")
@mock.patch("opentelemetry.instrumentation.aiokafka.utils._extract_send_partition")
@mock.patch("opentelemetry.instrumentation.aiokafka.utils._enrich_send_span")
@mock.patch("opentelemetry.trace.set_span_in_context")
@mock.patch("opentelemetry.propagate.inject")
async def test_wrap_send_with_topic_as_kwarg(
self,
inject: mock.MagicMock,
set_span_in_context: mock.MagicMock,
enrich_span: mock.MagicMock,
extract_send_partition: mock.AsyncMock,
extract_bootstrap_servers: mock.MagicMock,
) -> None:
self.args = []
self.kwargs["topic"] = self.topic_name
await self.wrap_send_helper(
inject,
set_span_in_context,
enrich_span,
extract_send_partition,
extract_bootstrap_servers,
)
async def wrap_send_helper(
self,
inject: mock.MagicMock,
set_span_in_context: mock.MagicMock,
enrich_span: mock.MagicMock,
extract_send_partition: mock.AsyncMock,
extract_bootstrap_servers: mock.MagicMock,
) -> None:
tracer = mock.MagicMock()
produce_hook = mock.AsyncMock()
original_send_callback = mock.AsyncMock()
kafka_producer = mock.MagicMock()
expected_span_name = _get_span_name("send", self.topic_name)
wrapped_send = _wrap_send(tracer, produce_hook)
retval = await wrapped_send(original_send_callback, kafka_producer, self.args, self.kwargs)
extract_bootstrap_servers.assert_called_once_with(kafka_producer.client)
extract_send_partition.assert_awaited_once_with(kafka_producer, self.args, self.kwargs)
tracer.start_as_current_span.assert_called_once_with(expected_span_name, kind=SpanKind.PRODUCER)
span = tracer.start_as_current_span().__enter__.return_value
enrich_span.assert_called_once_with(
span,
bootstrap_servers=extract_bootstrap_servers.return_value,
client_id=kafka_producer.client._client_id,
topic=self.topic_name,
partition=extract_send_partition.return_value,
key=None,
)
set_span_in_context.assert_called_once_with(span)
context = set_span_in_context.return_value
inject.assert_called_once_with(self.headers, context=context, setter=_aiokafka_setter)
produce_hook.assert_awaited_once_with(span, self.args, self.kwargs)
original_send_callback.assert_awaited_once_with(*self.args, **self.kwargs)
self.assertEqual(retval, original_send_callback.return_value)
@mock.patch("opentelemetry.propagate.extract")
@mock.patch("opentelemetry.instrumentation.aiokafka.utils._create_consumer_span")
@mock.patch("opentelemetry.instrumentation.aiokafka.utils._extract_bootstrap_servers")
@mock.patch("opentelemetry.instrumentation.aiokafka.utils._extract_client_id")
@mock.patch("opentelemetry.instrumentation.aiokafka.utils._extract_consumer_group")
async def test_wrap_getone(
self,
extract_consumer_group: mock.MagicMock,
extract_client_id: mock.MagicMock,
extract_bootstrap_servers: mock.MagicMock,
_create_consumer_span: mock.MagicMock,
extract: mock.MagicMock,
) -> None:
tracer = mock.MagicMock()
consume_hook = mock.AsyncMock()
original_getone_callback = mock.AsyncMock()
kafka_consumer = mock.MagicMock()
wrapped_getone = _wrap_getone(tracer, consume_hook)
record = await wrapped_getone(original_getone_callback, kafka_consumer, self.args, self.kwargs)
extract_bootstrap_servers.assert_called_once_with(kafka_consumer._client)
bootstrap_servers = extract_bootstrap_servers.return_value
extract_client_id.assert_called_once_with(kafka_consumer._client)
client_id = extract_client_id.return_value
extract_consumer_group.assert_called_once_with(kafka_consumer)
consumer_group = extract_consumer_group.return_value
original_getone_callback.assert_awaited_once_with(*self.args, **self.kwargs)
self.assertEqual(record, original_getone_callback.return_value)
extract.assert_called_once_with(record.headers, getter=_aiokafka_getter)
context = extract.return_value
_create_consumer_span.assert_called_once_with(
tracer,
consume_hook,
record,
context,
bootstrap_servers,
client_id,
consumer_group,
self.args,
self.kwargs,
)
@mock.patch("opentelemetry.propagate.extract")
@mock.patch("opentelemetry.instrumentation.aiokafka.utils._create_consumer_span")
@mock.patch("opentelemetry.instrumentation.aiokafka.utils._enrich_getmany_topic_span")
@mock.patch("opentelemetry.instrumentation.aiokafka.utils._enrich_getmany_poll_span")
@mock.patch("opentelemetry.instrumentation.aiokafka.utils._extract_bootstrap_servers")
@mock.patch("opentelemetry.instrumentation.aiokafka.utils._extract_client_id")
@mock.patch("opentelemetry.instrumentation.aiokafka.utils._extract_consumer_group")
# pylint: disable=too-many-locals
async def test_wrap_getmany(
self,
extract_consumer_group: mock.MagicMock,
extract_client_id: mock.MagicMock,
extract_bootstrap_servers: mock.MagicMock,
_enrich_getmany_poll_span: mock.MagicMock,
_enrich_getmany_topic_span: mock.MagicMock,
_create_consumer_span: mock.AsyncMock,
extract: mock.MagicMock,
) -> None:
tracer = mock.MagicMock()
consume_hook = mock.AsyncMock()
record_mock = mock.MagicMock()
original_getmany_callback = mock.AsyncMock(
return_value={aiokafka.TopicPartition(topic="topic_1", partition=0): [record_mock]}
)
kafka_consumer = mock.MagicMock()
_create_consumer_span.return_value = mock.MagicMock()
wrapped_getmany = _wrap_getmany(tracer, consume_hook)
records = await wrapped_getmany(original_getmany_callback, kafka_consumer, self.args, self.kwargs)
extract_bootstrap_servers.assert_called_once_with(kafka_consumer._client)
bootstrap_servers = extract_bootstrap_servers.return_value
extract_client_id.assert_called_once_with(kafka_consumer._client)
client_id = extract_client_id.return_value
extract_consumer_group.assert_called_once_with(kafka_consumer)
consumer_group = extract_consumer_group.return_value
original_getmany_callback.assert_awaited_once_with(*self.args, **self.kwargs)
self.assertEqual(records, original_getmany_callback.return_value)
extract.assert_called_once_with(record_mock.headers, getter=_aiokafka_getter)
context = extract.return_value
_create_consumer_span.assert_called_once_with(
tracer,
consume_hook,
record_mock,
context,
bootstrap_servers,
client_id,
consumer_group,
self.args,
self.kwargs,
)
@mock.patch("opentelemetry.trace.set_span_in_context")
@mock.patch("opentelemetry.context.attach")
@mock.patch("opentelemetry.instrumentation.aiokafka.utils._enrich_getone_span")
@mock.patch("opentelemetry.context.detach")
async def test_create_consumer_span(
self,
detach: mock.MagicMock,
enrich_span: mock.MagicMock,
attach: mock.MagicMock,
set_span_in_context: mock.MagicMock,
) -> None:
tracer = mock.MagicMock()
consume_hook = mock.AsyncMock()
bootstrap_servers = mock.MagicMock()
extracted_context = mock.MagicMock()
record = mock.MagicMock()
client_id = mock.MagicMock()
consumer_group = mock.MagicMock()
await _create_consumer_span(
tracer,
consume_hook,
record,
extracted_context,
bootstrap_servers,
client_id,
consumer_group,
self.args,
self.kwargs,
)
expected_span_name = _get_span_name("receive", record.topic)
tracer.start_as_current_span.assert_called_once_with(
expected_span_name,
context=extracted_context,
kind=SpanKind.CONSUMER,
)
span = tracer.start_as_current_span.return_value.__enter__()
set_span_in_context.assert_called_once_with(span, extracted_context)
attach.assert_called_once_with(set_span_in_context.return_value)
enrich_span.assert_called_once_with(
span,
bootstrap_servers=bootstrap_servers,
client_id=client_id,
consumer_group=consumer_group,
topic=record.topic,
partition=record.partition,
key=str(record.key),
offset=record.offset,
)
consume_hook.assert_awaited_once_with(span, record, self.args, self.kwargs)
detach.assert_called_once_with(attach.return_value)
async def test_kafka_properties_extractor(self):
aiokafka_instance_mock = mock.Mock()
aiokafka_instance_mock._key_serializer = None
aiokafka_instance_mock._value_serializer = None
aiokafka_instance_mock._partition.return_value = "partition"
aiokafka_instance_mock.client._wait_on_metadata = mock.AsyncMock()
assert await _extract_send_partition(aiokafka_instance_mock, self.args, self.kwargs) == "partition"
aiokafka_instance_mock.client._wait_on_metadata.side_effect = Exception("mocked error")
assert await _extract_send_partition(aiokafka_instance_mock, self.args, self.kwargs) is None
opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aiopg/ 0000775 0000000 0000000 00000000000 15270700723 0032242 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aiopg/LICENSE 0000664 0000000 0000000 00000026135 15270700723 0033256 0 ustar 00root root 0000000 0000000 Apache License
Version 2.0, January 2004
http://www.apache.org/licenses/
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opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aiopg/README.rst 0000664 0000000 0000000 00000001220 15270700723 0033724 0 ustar 00root root 0000000 0000000 OpenTelemetry aiopg instrumentation
===================================
|pypi|
.. |pypi| image:: https://badge.fury.io/py/opentelemetry-instrumentation-aiopg.svg
:target: https://pypi.org/project/opentelemetry-instrumentation-aiopg/
Installation
------------
::
pip install opentelemetry-instrumentation-aiopg
References
----------
* `OpenTelemetry aiopg Instrumentation `_
* `OpenTelemetry Project `_
* `OpenTelemetry Python Examples `_
pyproject.toml 0000664 0000000 0000000 00000003163 15270700723 0035102 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aiopg [build-system]
requires = ["hatchling"]
build-backend = "hatchling.build"
[project]
name = "opentelemetry-instrumentation-aiopg"
dynamic = ["version"]
description = "OpenTelemetry aiopg instrumentation"
readme = "README.rst"
license = "Apache-2.0"
requires-python = ">=3.10"
authors = [
{ name = "OpenTelemetry Authors", email = "cncf-opentelemetry-contributors@lists.cncf.io" },
]
classifiers = [
"Development Status :: 4 - Beta",
"Intended Audience :: Developers",
"License :: OSI Approved :: Apache Software License",
"Programming Language :: Python",
"Programming Language :: Python :: 3",
"Programming Language :: Python :: 3.10",
"Programming Language :: Python :: 3.11",
"Programming Language :: Python :: 3.12",
"Programming Language :: Python :: 3.13",
"Programming Language :: Python :: 3.14",
]
dependencies = [
"opentelemetry-api ~= 1.12",
"opentelemetry-instrumentation == 0.66b2",
"opentelemetry-instrumentation-dbapi == 0.66b2",
"wrapt >= 1.0.0, < 3.0.0",
]
[project.optional-dependencies]
instruments = [
"aiopg >= 0.13.0, < 2.0.0",
]
[project.entry-points.opentelemetry_instrumentor]
aiopg = "opentelemetry.instrumentation.aiopg:AiopgInstrumentor"
[project.urls]
Homepage = "https://github.com/open-telemetry/opentelemetry-python-contrib/tree/main/instrumentation/opentelemetry-instrumentation-aiopg"
Repository = "https://github.com/open-telemetry/opentelemetry-python-contrib"
[tool.hatch.version]
path = "src/opentelemetry/instrumentation/aiopg/version.py"
[tool.hatch.build.targets.sdist]
include = [
"/src",
"/tests",
]
[tool.hatch.build.targets.wheel]
packages = ["src/opentelemetry"]
opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aiopg/src/ 0000775 0000000 0000000 00000000000 15270700723 0033031 5 ustar 00root root 0000000 0000000 opentelemetry/ 0000775 0000000 0000000 00000000000 15270700723 0035646 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aiopg/src instrumentation/ 0000775 0000000 0000000 00000000000 15270700723 0041111 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aiopg/src/opentelemetry aiopg/ 0000775 0000000 0000000 00000000000 15270700723 0042210 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aiopg/src/opentelemetry/instrumentation __init__.py 0000664 0000000 0000000 00000011237 15270700723 0044325 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aiopg/src/opentelemetry/instrumentation/aiopg # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
"""
The integration with PostgreSQL supports the aiopg library,
it can be enabled by using ``AiopgInstrumentor``.
.. aiopg: https://github.com/aio-libs/aiopg
Usage
-----
.. code-block:: python
import asyncio
import aiopg
from opentelemetry.instrumentation.aiopg import AiopgInstrumentor
# Call instrument() to wrap all database connections
AiopgInstrumentor().instrument()
dsn = "user=user password=password host=127.0.0.1"
async def connect():
cnx = await aiopg.connect(dsn)
cursor = await cnx.cursor()
await cursor.execute("CREATE TABLE IF NOT EXISTS test (testField INTEGER)")
await cursor.execute("INSERT INTO test (testField) VALUES (123)")
cursor.close()
cnx.close()
async def create_pool():
pool = await aiopg.create_pool(dsn)
cnx = await pool.acquire()
cursor = await cnx.cursor()
await cursor.execute("CREATE TABLE IF NOT EXISTS test (testField INTEGER)")
await cursor.execute("INSERT INTO test (testField) VALUES (123)")
cursor.close()
cnx.close()
asyncio.run(connect())
asyncio.run(create_pool())
.. code-block:: python
import asyncio
import aiopg
from opentelemetry.instrumentation.aiopg import AiopgInstrumentor
dsn = "user=user password=password host=127.0.0.1"
# Alternatively, use instrument_connection for an individual connection
async def go():
cnx = await aiopg.connect(dsn)
instrumented_cnx = AiopgInstrumentor().instrument_connection(cnx)
cursor = await instrumented_cnx.cursor()
await cursor.execute("CREATE TABLE IF NOT EXISTS test (testField INTEGER)")
await cursor.execute("INSERT INTO test (testField) VALUES (123)")
cursor.close()
instrumented_cnx.close()
asyncio.run(go())
API
---
"""
from collections.abc import Collection
from opentelemetry.instrumentation.aiopg import wrappers
from opentelemetry.instrumentation.aiopg.package import _instruments
from opentelemetry.instrumentation.aiopg.version import __version__
from opentelemetry.instrumentation.instrumentor import BaseInstrumentor
class AiopgInstrumentor(BaseInstrumentor):
_CONNECTION_ATTRIBUTES = {
"database": "info.dbname",
"port": "info.port",
"host": "info.host",
"user": "info.user",
}
_DATABASE_SYSTEM = "postgresql"
def instrumentation_dependencies(self) -> Collection[str]:
return _instruments
def _instrument(self, **kwargs):
"""Integrate with PostgreSQL aiopg library.
aiopg: https://github.com/aio-libs/aiopg
"""
tracer_provider = kwargs.get("tracer_provider")
meter_provider = kwargs.get("meter_provider")
wrappers.wrap_connect(
__name__,
self._DATABASE_SYSTEM,
self._CONNECTION_ATTRIBUTES,
version=__version__,
tracer_provider=tracer_provider,
meter_provider=meter_provider,
)
wrappers.wrap_create_pool(
__name__,
self._DATABASE_SYSTEM,
self._CONNECTION_ATTRIBUTES,
version=__version__,
tracer_provider=tracer_provider,
meter_provider=meter_provider,
)
# pylint:disable=no-self-use
def _uninstrument(self, **kwargs):
""" "Disable aiopg instrumentation"""
wrappers.unwrap_connect()
wrappers.unwrap_create_pool()
# pylint:disable=no-self-use
def instrument_connection(self, connection, tracer_provider=None, meter_provider=None):
"""Enable instrumentation in a aiopg connection.
Args:
connection: The connection to instrument.
tracer_provider: The optional tracer provider to use. If omitted
the current globally configured one is used.
meter_provider: The optional meter provider to use. If omitted the
current globally configured one is used.
Returns:
An instrumented connection.
"""
return wrappers.instrument_connection(
__name__,
connection,
self._DATABASE_SYSTEM,
self._CONNECTION_ATTRIBUTES,
version=__version__,
tracer_provider=tracer_provider,
meter_provider=meter_provider,
)
def uninstrument_connection(self, connection):
"""Disable instrumentation in a aiopg connection.
Args:
connection: The connection to uninstrument.
Returns:
An uninstrumented connection.
"""
return wrappers.uninstrument_connection(connection)
aiopg_integration.py 0000664 0000000 0000000 00000016635 15270700723 0046277 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aiopg/src/opentelemetry/instrumentation/aiopg # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
import inspect
import time
import typing
from collections.abc import Coroutine
import wrapt
from opentelemetry.instrumentation._semconv import _report_new
from opentelemetry.instrumentation.dbapi import (
CursorTracer,
DatabaseApiIntegration,
)
from opentelemetry.semconv.attributes.error_attributes import ERROR_TYPE
from opentelemetry.trace import SpanKind
# pylint: disable=abstract-method,no-member
class AsyncProxyObject(wrapt.ObjectProxy):
def __aiter__(self):
return self.__wrapped__.__aiter__()
async def __anext__(self):
result = await self.__wrapped__.__anext__()
return result
async def __aenter__(self):
return await self.__wrapped__.__aenter__()
async def __aexit__(self, exc_type, exc_val, exc_tb):
return await self.__wrapped__.__aexit__(exc_type, exc_val, exc_tb)
def __await__(self):
return self.__wrapped__.__await__()
class AiopgIntegration(DatabaseApiIntegration):
async def wrapped_connection(
self,
connect_method: typing.Callable[..., typing.Any],
args: tuple[typing.Any, typing.Any],
kwargs: dict[typing.Any, typing.Any],
):
"""Add object proxy to connection object."""
connection = await connect_method(*args, **kwargs)
# pylint: disable=protected-access
self.get_connection_attributes(connection._conn)
return get_traced_connection_proxy(connection, self)
async def wrapped_pool(self, create_pool_method, args, kwargs):
pool = await create_pool_method(*args, **kwargs)
async with pool.acquire() as connection:
# pylint: disable=protected-access
self.get_connection_attributes(connection._conn)
return get_traced_pool_proxy(pool, self)
def get_traced_connection_proxy(connection, db_api_integration, *args, **kwargs):
# pylint: disable=abstract-method,no-member
class TracedConnectionProxy(AsyncProxyObject):
# pylint: disable=unused-argument
def __init__(self, connection, *args, **kwargs):
super().__init__(connection)
def cursor(self, *args, **kwargs):
coro = self._cursor(*args, **kwargs)
return _ContextManager(coro)
async def _cursor(self, *args, **kwargs):
# pylint: disable=protected-access
cursor = await self.__wrapped__._cursor(*args, **kwargs)
return get_traced_cursor_proxy(cursor, db_api_integration)
return TracedConnectionProxy(connection, *args, **kwargs)
def get_traced_pool_proxy(pool, db_api_integration, *args, **kwargs):
# pylint: disable=abstract-method,no-member
class TracedPoolProxy(AsyncProxyObject):
# pylint: disable=unused-argument
def __init__(self, pool, *args, **kwargs):
super().__init__(pool)
def acquire(self):
"""Acquire free connection from the pool."""
coro = self._acquire()
return _PoolAcquireContextManager(coro, self)
async def _acquire(self):
# pylint: disable=protected-access
connection = await self.__wrapped__._acquire()
if not isinstance(connection, AsyncProxyObject):
connection = get_traced_connection_proxy(connection, db_api_integration, *args, **kwargs)
return connection
return TracedPoolProxy(pool, *args, **kwargs)
class AsyncCursorTracer(CursorTracer):
async def traced_execution(
self,
cursor,
query_method: typing.Callable[..., typing.Any],
*args: tuple[typing.Any, typing.Any],
**kwargs: dict[typing.Any, typing.Any],
):
operation_name = self.get_operation_name(cursor, args)
span_name = operation_name
if not span_name:
span_name = (
self._db_api_integration.database
if self._db_api_integration.database
else self._db_api_integration.name
)
with self._db_api_integration._tracer.start_as_current_span(span_name, kind=SpanKind.CLIENT) as span:
if span.is_recording():
self._populate_span(span, cursor, *args)
start_time = time.perf_counter()
error = None
try:
return await query_method(*args, **kwargs)
except Exception as exc:
error = exc
if span.is_recording() and _report_new(self._db_api_integration._sem_conv_opt_in_mode_db):
span.set_attribute(ERROR_TYPE, type(exc).__qualname__)
raise
finally:
self._record_metrics(cursor, operation_name, start_time, error)
def get_traced_cursor_proxy(cursor, db_api_integration, *args, **kwargs):
_traced_cursor = AsyncCursorTracer(db_api_integration)
# pylint: disable=abstract-method,no-member
class AsyncCursorTracerProxy(AsyncProxyObject):
# pylint: disable=unused-argument
def __init__(self, cursor, *args, **kwargs):
super().__init__(cursor)
async def execute(self, *args, **kwargs):
result = await _traced_cursor.traced_execution(self, self.__wrapped__.execute, *args, **kwargs)
return result
async def executemany(self, *args, **kwargs):
result = await _traced_cursor.traced_execution(self, self.__wrapped__.executemany, *args, **kwargs)
return result
async def callproc(self, *args, **kwargs):
result = await _traced_cursor.traced_execution(self, self.__wrapped__.callproc, *args, **kwargs)
return result
return AsyncCursorTracerProxy(cursor, *args, **kwargs)
class _ContextManager(Coroutine):
__slots__ = ("_coro", "_obj")
def __init__(self, coro):
self._coro = coro
self._obj = None
def send(self, value):
return self._coro.send(value)
def throw(self, typ, val=None, tb=None):
if val is None:
return self._coro.throw(typ)
if tb is None:
return self._coro.throw(typ, val)
return self._coro.throw(typ, val, tb)
def close(self):
return self._coro.close()
@property
def gi_frame(self):
return self._coro.gi_frame
@property
def gi_running(self):
return self._coro.gi_running
@property
def gi_code(self):
return self._coro.gi_code
def __next__(self):
return self.send(None)
def __await__(self):
resp = self._coro.__await__()
return resp
async def __aenter__(self):
self._obj = await self._coro
return self._obj
async def __aexit__(self, exc_type, exc, t_b):
try:
if inspect.iscoroutinefunction(self._obj.close):
await self._obj.close()
else:
self._obj.close()
finally:
self._obj = None
class _PoolContextManager(_ContextManager):
__slots__ = ()
async def __aexit__(self, exc_type, exc, tb):
self._obj.close()
await self._obj.wait_closed()
self._obj = None
class _PoolAcquireContextManager(_ContextManager):
# pylint: disable=redefined-slots-in-subclass
__slots__ = ("_coro", "_obj", "_pool")
def __init__(self, coro, pool):
super().__init__(coro)
self._pool = pool
async def __aexit__(self, exc_type, exc, tb):
await self._pool.release(self._obj)
self._pool = None
self._obj = None
package.py 0000664 0000000 0000000 00000000263 15270700723 0044156 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aiopg/src/opentelemetry/instrumentation/aiopg # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
_instruments = ("aiopg >= 0.13.0, < 2.0.0",)
_supports_metrics = True
_semconv_status = "migration"
version.py 0000664 0000000 0000000 00000000144 15270700723 0044246 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aiopg/src/opentelemetry/instrumentation/aiopg # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
__version__ = "0.66b2"
wrappers.py 0000664 0000000 0000000 00000015636 15270700723 0044440 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aiopg/src/opentelemetry/instrumentation/aiopg # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
"""
The trace integration with aiopg based on dbapi integration,
where replaced sync wrap methods to async
Usage
-----
.. code-block:: python
from opentelemetry import trace
from opentelemetry.instrumentation.aiopg import trace_integration
trace_integration(aiopg.connection, "_connect", "postgresql")
API
---
"""
import logging
import typing
import aiopg
import wrapt
from opentelemetry.instrumentation.aiopg.aiopg_integration import (
AiopgIntegration,
AsyncProxyObject,
_ContextManager,
_PoolContextManager,
get_traced_connection_proxy,
)
from opentelemetry.instrumentation.aiopg.version import __version__
from opentelemetry.instrumentation.utils import unwrap
from opentelemetry.metrics import MeterProvider
from opentelemetry.trace import TracerProvider
logger = logging.getLogger(__name__)
def trace_integration(
database_system: str,
connection_attributes: dict = None,
tracer_provider: TracerProvider | None = None,
meter_provider: MeterProvider | None = None,
):
"""Integrate with aiopg library.
based on dbapi integration, where replaced sync wrap methods to async
Args:
database_system: An identifier for the database management system (DBMS)
product being used.
connection_attributes: Attribute names for database, port, host and
user in Connection object.
tracer_provider: The :class:`opentelemetry.trace.TracerProvider` to
use. If omitted the current configured one is used.
meter_provider: The :class:`opentelemetry.metrics.MeterProvider` to
use. If omitted the current configured one is used.
"""
wrap_connect(
__name__,
database_system,
connection_attributes,
__version__,
tracer_provider,
meter_provider,
)
def wrap_connect(
name: str,
database_system: str,
connection_attributes: dict = None,
version: str = "",
tracer_provider: TracerProvider | None = None,
meter_provider: MeterProvider | None = None,
):
"""Integrate with aiopg library.
https://github.com/aio-libs/aiopg
Args:
name: Name of opentelemetry extension for aiopg.
database_system: An identifier for the database management system (DBMS)
product being used.
connection_attributes: Attribute names for database, port, host and
user in Connection object.
version: Version of opentelemetry extension for aiopg.
tracer_provider: The :class:`opentelemetry.trace.TracerProvider` to
use. If omitted the current configured one is used.
meter_provider: The :class:`opentelemetry.metrics.MeterProvider` to
use. If omitted the current configured one is used.
"""
# pylint: disable=unused-argument
def wrap_connect_(
wrapped: typing.Callable[..., typing.Any],
instance: typing.Any,
args: tuple[typing.Any, typing.Any],
kwargs: dict[typing.Any, typing.Any],
):
db_integration = AiopgIntegration(
name,
database_system,
connection_attributes=connection_attributes,
version=version,
tracer_provider=tracer_provider,
meter_provider=meter_provider,
)
return _ContextManager( # pylint: disable=no-value-for-parameter
db_integration.wrapped_connection(wrapped, args, kwargs)
)
try:
wrapt.wrap_function_wrapper(aiopg, "connect", wrap_connect_)
except Exception as ex: # pylint: disable=broad-except
logger.warning("Failed to integrate with aiopg. %s", str(ex))
def unwrap_connect():
"""Disable integration with aiopg library.
https://github.com/aio-libs/aiopg
"""
unwrap(aiopg, "connect")
def instrument_connection(
name: str,
connection,
database_system: str,
connection_attributes: dict = None,
version: str = "",
tracer_provider: TracerProvider | None = None,
meter_provider: MeterProvider | None = None,
):
"""Enable instrumentation in a database connection.
Args:
name: Name of opentelemetry extension for aiopg.
connection: The connection to instrument.
database_system: An identifier for the database management system (DBMS)
product being used.
connection_attributes: Attribute names for database, port, host and
user in a connection object.
version: Version of opentelemetry extension for aiopg.
tracer_provider: The :class:`opentelemetry.trace.TracerProvider` to
use. If omitted the current configured one is used.
meter_provider: The :class:`opentelemetry.metrics.MeterProvider` to
use. If omitted the current configured one is used.
Returns:
An instrumented connection.
"""
if isinstance(connection, AsyncProxyObject):
logger.warning("Connection already instrumented")
return connection
db_integration = AiopgIntegration(
name,
database_system,
connection_attributes=connection_attributes,
version=version,
tracer_provider=tracer_provider,
meter_provider=meter_provider,
)
db_integration.get_connection_attributes(getattr(connection, "_conn", connection))
return get_traced_connection_proxy(connection, db_integration)
def uninstrument_connection(connection):
"""Disable instrumentation in a database connection.
Args:
connection: The connection to uninstrument.
Returns:
An uninstrumented connection.
"""
if isinstance(connection, AsyncProxyObject):
return connection.__wrapped__
logger.warning("Connection is not instrumented")
return connection
def wrap_create_pool(
name: str,
database_system: str,
connection_attributes: dict = None,
version: str = "",
tracer_provider: TracerProvider | None = None,
meter_provider: MeterProvider | None = None,
):
# pylint: disable=unused-argument
def wrap_create_pool_(
wrapped: typing.Callable[..., typing.Any],
instance: typing.Any,
args: tuple[typing.Any, typing.Any],
kwargs: dict[typing.Any, typing.Any],
):
db_integration = AiopgIntegration(
name,
database_system,
connection_attributes=connection_attributes,
version=version,
tracer_provider=tracer_provider,
meter_provider=meter_provider,
)
return _PoolContextManager(db_integration.wrapped_pool(wrapped, args, kwargs))
try:
wrapt.wrap_function_wrapper(aiopg, "create_pool", wrap_create_pool_)
except Exception as ex: # pylint: disable=broad-except
logger.warning("Failed to integrate with DB API. %s", str(ex))
def unwrap_create_pool():
"""Disable integration with aiopg library.
https://github.com/aio-libs/aiopg
"""
unwrap(aiopg, "create_pool")
test-requirements-wrapt1.txt 0000664 0000000 0000000 00000000047 15270700723 0037641 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aiopg -r test-requirements.txt
wrapt==1.17.3
test-requirements-wrapt2.txt 0000664 0000000 0000000 00000000046 15270700723 0037641 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aiopg -r test-requirements.txt
wrapt==2.1.2
test-requirements.txt 0000664 0000000 0000000 00000000533 15270700723 0036425 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aiopg aiopg==1.4.0
asgiref==3.8.1
async-timeout==4.0.3
iniconfig==2.0.0
packaging==24.0
pluggy==1.6.0
psycopg2-binary==2.9.10
py-cpuinfo==9.0.0
pytest==7.4.4
tomli==2.0.1
typing_extensions==4.12.2
zipp==3.19.2
-e opentelemetry-instrumentation
-e instrumentation/opentelemetry-instrumentation-dbapi
-e instrumentation/opentelemetry-instrumentation-aiopg
opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aiopg/tests/ 0000775 0000000 0000000 00000000000 15270700723 0033404 5 ustar 00root root 0000000 0000000 __init__.py 0000664 0000000 0000000 00000000000 15270700723 0035424 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aiopg/tests test_aiopg_integration.py 0000664 0000000 0000000 00000105512 15270700723 0040444 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aiopg/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
import asyncio
import contextlib
import logging
from types import SimpleNamespace
from unittest import mock
from unittest.mock import MagicMock
import aiopg
import psycopg2
import opentelemetry.instrumentation.aiopg
from opentelemetry import trace as trace_api
from opentelemetry.instrumentation._semconv import (
OTEL_SEMCONV_STABILITY_OPT_IN,
_OpenTelemetrySemanticConventionStability,
)
from opentelemetry.instrumentation.aiopg import AiopgInstrumentor, wrappers
from opentelemetry.instrumentation.aiopg.aiopg_integration import (
AiopgIntegration,
_ContextManager,
_PoolAcquireContextManager,
)
from opentelemetry.sdk import resources
from opentelemetry.semconv._incubating.attributes.db_attributes import (
DB_NAME,
DB_STATEMENT,
DB_SYSTEM,
DB_USER,
)
from opentelemetry.semconv._incubating.attributes.net_attributes import (
NET_PEER_NAME,
NET_PEER_PORT,
)
from opentelemetry.semconv._incubating.metrics.db_metrics import (
DB_CLIENT_OPERATION_DURATION,
DB_CLIENT_RESPONSE_RETURNED_ROWS,
)
from opentelemetry.semconv.attributes.db_attributes import (
DB_NAMESPACE,
DB_OPERATION_NAME,
DB_QUERY_TEXT,
DB_SYSTEM_NAME,
)
from opentelemetry.semconv.attributes.error_attributes import ERROR_TYPE
from opentelemetry.semconv.attributes.server_attributes import (
SERVER_ADDRESS,
SERVER_PORT,
)
from opentelemetry.test.test_base import TestBase
def async_call(coro):
return asyncio.run(coro)
@contextlib.contextmanager
def use_semconv_opt_in(sem_conv_mode):
env_patch = mock.patch.dict(
"os.environ",
{OTEL_SEMCONV_STABILITY_OPT_IN: sem_conv_mode},
)
_OpenTelemetrySemanticConventionStability._initialized = False
env_patch.start()
try:
yield
finally:
env_patch.stop()
_OpenTelemetrySemanticConventionStability._initialized = False
class TestAiopgInstrumentor(TestBase):
def setUp(self):
super().setUp()
_OpenTelemetrySemanticConventionStability._initialized = False
self.origin_aiopg_connect = aiopg.connect
self.origin_aiopg_create_pool = aiopg.create_pool
aiopg.connect = mock_connect
aiopg.create_pool = mock_create_pool
def tearDown(self):
_OpenTelemetrySemanticConventionStability._initialized = False
super().tearDown()
aiopg.connect = self.origin_aiopg_connect
aiopg.create_pool = self.origin_aiopg_create_pool
with self.disable_logging():
AiopgInstrumentor().uninstrument()
def test_instrumentor_connect(self):
AiopgInstrumentor().instrument()
cnx = async_call(aiopg.connect(database="test"))
cursor = async_call(cnx.cursor())
query = "SELECT * FROM test"
async_call(cursor.execute(query))
spans_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans_list), 1)
span = spans_list[0]
# Check version and name in span's instrumentation info
self.assertEqualSpanInstrumentationScope(span, opentelemetry.instrumentation.aiopg)
# check that no spans are generated after uninstrument
AiopgInstrumentor().uninstrument()
cnx = async_call(aiopg.connect(database="test"))
cursor = async_call(cnx.cursor())
query = "SELECT * FROM test"
async_call(cursor.execute(query))
spans_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans_list), 1)
def test_instrumentor_connect_new_semconv(self):
with use_semconv_opt_in("database,http"):
AiopgInstrumentor().instrument()
cnx = async_call(
aiopg.connect(
database="testdatabase",
server_host="testhost",
server_port=123,
)
)
cursor = async_call(cnx.cursor())
async_call(cursor.execute("SELECT * FROM test"))
spans_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans_list), 1)
span = spans_list[0]
self.assertEqual(span.attributes[DB_SYSTEM_NAME], "postgresql")
self.assertEqual(span.attributes[DB_NAMESPACE], "testdatabase")
self.assertEqual(span.attributes[DB_QUERY_TEXT], "SELECT * FROM test")
self.assertEqual(span.attributes[SERVER_ADDRESS], "testhost")
self.assertEqual(span.attributes[SERVER_PORT], 123)
self.assertNotIn(DB_SYSTEM, span.attributes)
self.assertNotIn(DB_NAME, span.attributes)
self.assertNotIn(DB_STATEMENT, span.attributes)
self.assertNotIn(NET_PEER_NAME, span.attributes)
self.assertNotIn(NET_PEER_PORT, span.attributes)
def test_instrumentor_connect_ctx_manager(self):
async def _ctx_manager_connect():
AiopgInstrumentor().instrument()
async with aiopg.connect(database="test") as cnx:
async with cnx.cursor() as cursor:
query = "SELECT * FROM test"
await cursor.execute(query)
spans_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans_list), 1)
span = spans_list[0]
# Check version and name in span's instrumentation info
self.assertEqualSpanInstrumentationScope(span, opentelemetry.instrumentation.aiopg)
async_call(_ctx_manager_connect())
def test_instrumentor_create_pool(self):
AiopgInstrumentor().instrument()
pool = async_call(aiopg.create_pool(database="test"))
cnx = async_call(pool.acquire())
cursor = async_call(cnx.cursor())
query = "SELECT * FROM test"
async_call(cursor.execute(query))
spans_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans_list), 1)
span = spans_list[0]
# Check version and name in span's instrumentation info
self.assertEqualSpanInstrumentationScope(span, opentelemetry.instrumentation.aiopg)
# check that no spans are generated after uninstrument
AiopgInstrumentor().uninstrument()
pool = async_call(aiopg.create_pool(database="test"))
cnx = async_call(pool.acquire())
cursor = async_call(cnx.cursor())
query = "SELECT * FROM test"
async_call(cursor.execute(query))
spans_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans_list), 1)
def test_instrumentor_create_pool_ctx_manager(self):
async def _ctx_manager_pool():
AiopgInstrumentor().instrument()
async with aiopg.create_pool(database="test") as pool:
async with pool.acquire() as cnx:
async with cnx.cursor() as cursor:
query = "SELECT * FROM test"
await cursor.execute(query)
spans_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans_list), 1)
span = spans_list[0]
# Check version and name in span's instrumentation info
self.assertEqualSpanInstrumentationScope(span, opentelemetry.instrumentation.aiopg)
async_call(_ctx_manager_pool())
def test_custom_tracer_provider_connect(self):
resource = resources.Resource.create({})
result = self.create_tracer_provider(resource=resource)
tracer_provider, exporter = result
AiopgInstrumentor().instrument(tracer_provider=tracer_provider)
cnx = async_call(aiopg.connect(database="test"))
cursor = async_call(cnx.cursor())
query = "SELECT * FROM test"
async_call(cursor.execute(query))
spans_list = exporter.get_finished_spans()
self.assertEqual(len(spans_list), 1)
span = spans_list[0]
self.assertIs(span.resource, resource)
def test_custom_tracer_provider_create_pool(self):
resource = resources.Resource.create({})
result = self.create_tracer_provider(resource=resource)
tracer_provider, exporter = result
AiopgInstrumentor().instrument(tracer_provider=tracer_provider)
pool = async_call(aiopg.create_pool(database="test"))
cnx = async_call(pool.acquire())
cursor = async_call(cnx.cursor())
query = "SELECT * FROM test"
async_call(cursor.execute(query))
spans_list = exporter.get_finished_spans()
self.assertEqual(len(spans_list), 1)
span = spans_list[0]
self.assertIs(span.resource, resource)
@mock.patch.dict("os.environ", {OTEL_SEMCONV_STABILITY_OPT_IN: "database"})
def test_custom_meter_provider_connect(self):
meter_provider, metrics_reader = self.create_meter_provider()
AiopgInstrumentor().instrument(meter_provider=meter_provider)
cnx = async_call(aiopg.connect(database="test"))
cursor = async_call(cnx.cursor())
async_call(cursor.execute("SELECT * FROM test", rowcount=3))
metric_names = {
metric.name
for resource_metrics in metrics_reader.get_metrics_data().resource_metrics
for scope_metrics in resource_metrics.scope_metrics
for metric in scope_metrics.metrics
}
self.assertIn(DB_CLIENT_OPERATION_DURATION, metric_names)
self.assertIn(DB_CLIENT_RESPONSE_RETURNED_ROWS, metric_names)
def test_instrument_connection(self):
cnx = async_call(
aiopg.connect(
database="testdatabase",
server_host="testhost",
server_port=123,
user="testuser",
)
)
query = "SELECT * FROM test"
cursor = async_call(cnx.cursor())
async_call(cursor.execute(query))
spans_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans_list), 0)
cnx = AiopgInstrumentor().instrument_connection(cnx)
cursor = async_call(cnx.cursor())
async_call(cursor.execute(query))
spans_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans_list), 1)
span = spans_list[0]
self.assertEqual(span.attributes[DB_NAME], "testdatabase")
self.assertEqual(span.attributes[DB_USER], "testuser")
self.assertEqual(span.attributes[NET_PEER_NAME], "testhost")
self.assertEqual(span.attributes[NET_PEER_PORT], 123)
def test_instrument_connection_new_semconv(self):
with use_semconv_opt_in("database,http"):
cnx = async_call(
aiopg.connect(
database="testdatabase",
server_host="testhost",
server_port=123,
)
)
cnx = AiopgInstrumentor().instrument_connection(cnx)
cursor = async_call(cnx.cursor())
async_call(cursor.execute("SELECT * FROM test"))
spans_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans_list), 1)
span = spans_list[0]
self.assertEqual(span.attributes[DB_SYSTEM_NAME], "postgresql")
self.assertEqual(span.attributes[DB_QUERY_TEXT], "SELECT * FROM test")
self.assertNotIn(DB_SYSTEM, span.attributes)
self.assertNotIn(DB_STATEMENT, span.attributes)
def test_instrument_connection_after_instrument(self):
cnx = async_call(aiopg.connect(database="test"))
query = "SELECT * FROM test"
cursor = async_call(cnx.cursor())
async_call(cursor.execute(query))
spans_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans_list), 0)
AiopgInstrumentor().instrument()
cnx = AiopgInstrumentor().instrument_connection(cnx)
cursor = async_call(cnx.cursor())
async_call(cursor.execute(query))
spans_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans_list), 1)
def test_no_op_tracer_provider(self):
cnx = async_call(aiopg.connect(database="test"))
AiopgInstrumentor().instrument_connection(cnx, tracer_provider=trace_api.NoOpTracerProvider())
cursor = async_call(cnx.cursor())
query = "SELECT * FROM test"
async_call(cursor.execute(query))
spans_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans_list), 0)
def test_custom_tracer_provider_instrument_connection(self):
resource = resources.Resource.create({"service.name": "db-test-service"})
result = self.create_tracer_provider(resource=resource)
tracer_provider, exporter = result
cnx = async_call(aiopg.connect(database="test"))
cnx = AiopgInstrumentor().instrument_connection(cnx, tracer_provider=tracer_provider)
cursor = async_call(cnx.cursor())
query = "SELECT * FROM test"
async_call(cursor.execute(query))
spans_list = exporter.get_finished_spans()
self.assertEqual(len(spans_list), 1)
span = spans_list[0]
self.assertEqual(span.resource.attributes["service.name"], "db-test-service")
self.assertIs(span.resource, resource)
def test_uninstrument_connection(self):
AiopgInstrumentor().instrument()
cnx = async_call(aiopg.connect(database="test"))
query = "SELECT * FROM test"
cursor = async_call(cnx.cursor())
async_call(cursor.execute(query))
spans_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans_list), 1)
cnx = AiopgInstrumentor().uninstrument_connection(cnx)
cursor = async_call(cnx.cursor())
async_call(cursor.execute(query))
spans_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans_list), 1)
class TestAiopgIntegration(TestBase):
def setUp(self):
super().setUp()
_OpenTelemetrySemanticConventionStability._initialized = False
self.tracer = self.tracer_provider.get_tracer(__name__)
def tearDown(self):
_OpenTelemetrySemanticConventionStability._initialized = False
super().tearDown()
def test_span_succeeded(self):
connection_props = {
"database": "testdatabase",
"server_host": "testhost",
"server_port": 123,
"user": "testuser",
}
connection_attributes = {
"database": "database",
"port": "server_port",
"host": "server_host",
"user": "user",
}
db_integration = AiopgIntegration(
self.tracer,
"testcomponent",
connection_attributes,
capture_parameters=True,
)
mock_connection = async_call(db_integration.wrapped_connection(mock_connect, {}, connection_props))
cursor = async_call(mock_connection.cursor())
async_call(cursor.execute("Test query", ("param1Value", False)))
spans_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans_list), 1)
span = spans_list[0]
self.assertEqual(span.name, "Test")
self.assertIs(span.kind, trace_api.SpanKind.CLIENT)
self.assertEqual(span.attributes[DB_SYSTEM], "testcomponent")
self.assertEqual(span.attributes[DB_NAME], "testdatabase")
self.assertEqual(span.attributes[DB_STATEMENT], "Test query")
self.assertEqual(
span.attributes["db.statement.parameters"],
"('param1Value', False)",
)
self.assertEqual(span.attributes[DB_USER], "testuser")
self.assertEqual(span.attributes[NET_PEER_NAME], "testhost")
self.assertEqual(span.attributes[NET_PEER_PORT], 123)
self.assertIs(span.status.status_code, trace_api.StatusCode.UNSET)
def test_span_not_recording(self):
connection_props = {
"database": "testdatabase",
"server_host": "testhost",
"server_port": 123,
"user": "testuser",
}
connection_attributes = {
"database": "database",
"port": "server_port",
"host": "server_host",
"user": "user",
}
db_integration = AiopgIntegration(
__name__,
"testcomponent",
connection_attributes,
tracer_provider=trace_api.NoOpTracerProvider(),
)
mock_connection = async_call(db_integration.wrapped_connection(mock_connect, {}, connection_props))
cursor = async_call(mock_connection.cursor())
async_call(cursor.execute("Test query", ("param1Value", False)))
self.assertEqual(len(self.memory_exporter.get_finished_spans()), 0)
def test_span_succeeded_new_semconv(self):
connection_props = {
"database": "testdatabase",
"server_host": "testhost",
"server_port": 123,
"user": "testuser",
}
connection_attributes = {
"database": "database",
"port": "server_port",
"host": "server_host",
"user": "user",
}
with use_semconv_opt_in("database,http"):
db_integration = AiopgIntegration(__name__, "testcomponent", connection_attributes)
mock_connection = async_call(db_integration.wrapped_connection(mock_connect, {}, connection_props))
cursor = async_call(mock_connection.cursor())
async_call(cursor.execute("Test query"))
spans_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans_list), 1)
span = spans_list[0]
self.assertEqual(
span.instrumentation_scope.schema_url,
"https://opentelemetry.io/schemas/1.25.0",
)
self.assertEqual(span.attributes[DB_SYSTEM_NAME], "testcomponent")
self.assertEqual(span.attributes[DB_NAMESPACE], "testdatabase")
self.assertEqual(span.attributes[DB_QUERY_TEXT], "Test query")
self.assertEqual(span.attributes[SERVER_ADDRESS], "testhost")
self.assertEqual(span.attributes[SERVER_PORT], 123)
self.assertNotIn(DB_SYSTEM, span.attributes)
self.assertNotIn(DB_NAME, span.attributes)
self.assertNotIn(DB_STATEMENT, span.attributes)
self.assertNotIn(DB_USER, span.attributes)
self.assertNotIn(NET_PEER_NAME, span.attributes)
self.assertNotIn(NET_PEER_PORT, span.attributes)
def test_span_succeeded_both_semconv(self):
connection_props = {
"database": "testdatabase",
"server_host": "testhost",
"server_port": 123,
"user": "testuser",
}
connection_attributes = {
"database": "database",
"port": "server_port",
"host": "server_host",
"user": "user",
}
with use_semconv_opt_in("database/dup,http/dup"):
db_integration = AiopgIntegration(__name__, "testcomponent", connection_attributes)
mock_connection = async_call(db_integration.wrapped_connection(mock_connect, {}, connection_props))
cursor = async_call(mock_connection.cursor())
async_call(cursor.execute("Test query"))
spans_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans_list), 1)
span = spans_list[0]
self.assertEqual(span.attributes[DB_SYSTEM], "testcomponent")
self.assertEqual(span.attributes[DB_NAME], "testdatabase")
self.assertEqual(span.attributes[DB_STATEMENT], "Test query")
self.assertEqual(span.attributes[DB_USER], "testuser")
self.assertEqual(span.attributes[NET_PEER_NAME], "testhost")
self.assertEqual(span.attributes[NET_PEER_PORT], 123)
self.assertEqual(span.attributes[DB_SYSTEM_NAME], "testcomponent")
self.assertEqual(span.attributes[DB_NAMESPACE], "testdatabase")
self.assertEqual(span.attributes[DB_QUERY_TEXT], "Test query")
self.assertEqual(span.attributes[SERVER_ADDRESS], "testhost")
self.assertEqual(span.attributes[SERVER_PORT], 123)
def test_executemany_new_semconv(self):
with use_semconv_opt_in("database"):
db_integration = AiopgIntegration(__name__, "testcomponent")
mock_connection = async_call(db_integration.wrapped_connection(mock_connect, {}, {}))
cursor = async_call(mock_connection.cursor())
async_call(cursor.executemany("Test query"))
spans_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans_list), 1)
span = spans_list[0]
self.assertEqual(span.attributes[DB_SYSTEM_NAME], "testcomponent")
self.assertEqual(span.attributes[DB_QUERY_TEXT], "Test query")
self.assertNotIn(DB_SYSTEM, span.attributes)
self.assertNotIn(DB_STATEMENT, span.attributes)
def test_span_failed(self):
db_integration = AiopgIntegration(self.tracer, "testcomponent")
mock_connection = async_call(db_integration.wrapped_connection(mock_connect, {}, {}))
cursor = async_call(mock_connection.cursor())
with self.assertRaises(Exception):
async_call(cursor.execute("Test query", throw_exception=True))
spans_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans_list), 1)
span = spans_list[0]
self.assertEqual(span.attributes[DB_STATEMENT], "Test query")
self.assertIs(span.status.status_code, trace_api.StatusCode.ERROR)
self.assertEqual(span.status.description, "ProgrammingError: Test Exception")
def test_span_failed_new_semconv(self):
with use_semconv_opt_in("database"):
db_integration = AiopgIntegration(__name__, "testcomponent")
mock_connection = async_call(db_integration.wrapped_connection(mock_connect, {}, {}))
cursor = async_call(mock_connection.cursor())
with self.assertRaises(psycopg2.ProgrammingError):
async_call(cursor.execute("Test query", throw_exception=True))
spans_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans_list), 1)
span = spans_list[0]
self.assertEqual(span.attributes[DB_QUERY_TEXT], "Test query")
self.assertEqual(span.attributes[ERROR_TYPE], "ProgrammingError")
self.assertIs(span.status.status_code, trace_api.StatusCode.ERROR)
def test_executemany(self):
db_integration = AiopgIntegration(self.tracer, "testcomponent")
mock_connection = async_call(db_integration.wrapped_connection(mock_connect, {}, {}))
cursor = async_call(mock_connection.cursor())
async_call(cursor.executemany("Test query"))
spans_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans_list), 1)
span = spans_list[0]
self.assertEqual(span.attributes[DB_STATEMENT], "Test query")
def test_callproc(self):
db_integration = AiopgIntegration(self.tracer, "testcomponent")
mock_connection = async_call(db_integration.wrapped_connection(mock_connect, {}, {}))
cursor = async_call(mock_connection.cursor())
async_call(cursor.callproc("Test stored procedure"))
spans_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans_list), 1)
span = spans_list[0]
self.assertEqual(
span.attributes[DB_STATEMENT],
"Test stored procedure",
)
def test_wrap_connect(self):
aiopg_mock = AiopgMock()
with mock.patch("aiopg.connect", aiopg_mock.connect):
wrappers.wrap_connect(self.tracer, "-")
connection = async_call(aiopg.connect())
self.assertEqual(aiopg_mock.connect_call_count, 1)
self.assertIsInstance(connection.__wrapped__, mock.Mock)
def test_unwrap_connect(self):
wrappers.wrap_connect(self.tracer, "-")
aiopg_mock = AiopgMock()
with mock.patch("aiopg.connect", aiopg_mock.connect):
connection = async_call(aiopg.connect())
self.assertEqual(aiopg_mock.connect_call_count, 1)
wrappers.unwrap_connect()
connection = async_call(aiopg.connect())
self.assertEqual(aiopg_mock.connect_call_count, 2)
self.assertIsInstance(connection, mock.Mock)
def test_wrap_create_pool(self):
async def check_connection(pool):
async with pool.acquire() as connection:
self.assertEqual(aiopg_mock.create_pool_call_count, 1)
self.assertIsInstance(connection.__wrapped__, AiopgConnectionMock)
aiopg_mock = AiopgMock()
with mock.patch("aiopg.create_pool", aiopg_mock.create_pool):
wrappers.wrap_create_pool(self.tracer, "-")
pool = async_call(aiopg.create_pool())
async_call(check_connection(pool))
def test_unwrap_create_pool(self):
async def check_connection(pool):
async with pool.acquire() as connection:
self.assertEqual(aiopg_mock.create_pool_call_count, 2)
self.assertIsInstance(connection, AiopgConnectionMock)
aiopg_mock = AiopgMock()
with mock.patch("aiopg.create_pool", aiopg_mock.create_pool):
wrappers.wrap_create_pool(self.tracer, "-")
pool = async_call(aiopg.create_pool())
self.assertEqual(aiopg_mock.create_pool_call_count, 1)
wrappers.unwrap_create_pool()
pool = async_call(aiopg.create_pool())
async_call(check_connection(pool))
def test_instrument_connection(self):
connection = mock.Mock()
# Avoid get_attributes failing because can't concatenate mock
connection.database = "-"
connection._conn = connection
connection2 = wrappers.instrument_connection(self.tracer, connection, "-")
self.assertIs(connection2.__wrapped__, connection) # pylint: disable=no-member
def test_uninstrument_connection(self):
connection = mock.Mock()
# Set connection.database to avoid a failure because mock can't
# be concatenated
connection.database = "-"
connection._conn = connection
connection2 = wrappers.instrument_connection(self.tracer, connection, "-")
self.assertIs(connection2.__wrapped__, connection) # pylint: disable=no-member
connection3 = wrappers.uninstrument_connection(connection2)
self.assertIs(connection3, connection)
with self.assertLogs(level=logging.WARNING):
connection4 = wrappers.uninstrument_connection(connection)
self.assertIs(connection4, connection)
class TestAiopgMetrics(TestBase):
def setUp(self):
super().setUp()
_OpenTelemetrySemanticConventionStability._initialized = False
def tearDown(self):
_OpenTelemetrySemanticConventionStability._initialized = False
super().tearDown()
def _get_metric(self, name):
return next(
(metric for metric in self.get_sorted_metrics() if metric.name == name),
None,
)
def test_metrics_not_emitted_in_default_mode(self):
db_integration = AiopgIntegration(__name__, "testcomponent")
mock_connection = async_call(db_integration.wrapped_connection(mock_connect, (), {}))
cursor = async_call(mock_connection.cursor())
async_call(cursor.execute("SELECT 1", rowcount=3))
self.assertIsNone(self._get_metric(DB_CLIENT_OPERATION_DURATION))
self.assertIsNone(self._get_metric(DB_CLIENT_RESPONSE_RETURNED_ROWS))
@mock.patch.dict("os.environ", {OTEL_SEMCONV_STABILITY_OPT_IN: "database"})
def test_operation_duration_recorded(self):
connection_props = {
"database": "testdatabase",
"server_host": "testhost",
"server_port": 123,
"user": "testuser",
}
connection_attributes = {
"database": "database",
"port": "server_port",
"host": "server_host",
"user": "user",
}
db_integration = AiopgIntegration(__name__, "testcomponent", connection_attributes)
mock_connection = async_call(db_integration.wrapped_connection(mock_connect, (), connection_props))
cursor = async_call(mock_connection.cursor())
async_call(cursor.execute("SELECT * FROM users"))
duration_metric = self._get_metric(DB_CLIENT_OPERATION_DURATION)
self.assertIsNotNone(duration_metric)
self.assertEqual(duration_metric.unit, "s")
points = list(duration_metric.data.data_points)
self.assertEqual(len(points), 1)
attributes = dict(points[0].attributes)
self.assertEqual(attributes[DB_SYSTEM_NAME], "testcomponent")
self.assertEqual(attributes[DB_NAMESPACE], "testdatabase")
self.assertEqual(attributes[DB_OPERATION_NAME], "SELECT")
self.assertEqual(attributes[SERVER_ADDRESS], "testhost")
self.assertEqual(attributes[SERVER_PORT], 123)
self.assertNotIn(ERROR_TYPE, attributes)
self.assertEqual(points[0].count, 1)
self.assertGreaterEqual(points[0].sum, 0.0)
@mock.patch.dict("os.environ", {OTEL_SEMCONV_STABILITY_OPT_IN: "database"})
def test_operation_duration_error_type(self):
db_integration = AiopgIntegration(__name__, "testcomponent")
mock_connection = async_call(db_integration.wrapped_connection(mock_connect, (), {}))
cursor = async_call(mock_connection.cursor())
with self.assertRaises(psycopg2.ProgrammingError):
async_call(cursor.execute("SELECT 1", throw_exception=True))
duration_metric = self._get_metric(DB_CLIENT_OPERATION_DURATION)
self.assertIsNotNone(duration_metric)
points = list(duration_metric.data.data_points)
self.assertEqual(len(points), 1)
attributes = dict(points[0].attributes)
self.assertEqual(attributes[ERROR_TYPE], "ProgrammingError")
self.assertEqual(attributes[DB_OPERATION_NAME], "SELECT")
self.assertIsNone(self._get_metric(DB_CLIENT_RESPONSE_RETURNED_ROWS))
@mock.patch.dict("os.environ", {OTEL_SEMCONV_STABILITY_OPT_IN: "database"})
def test_returned_rows_recorded_for_executemany(self):
db_integration = AiopgIntegration(__name__, "testcomponent")
mock_connection = async_call(db_integration.wrapped_connection(mock_connect, (), {}))
cursor = async_call(mock_connection.cursor())
async_call(cursor.executemany("INSERT INTO users VALUES (1)", rowcount=3))
rows_metric = self._get_metric(DB_CLIENT_RESPONSE_RETURNED_ROWS)
self.assertIsNotNone(rows_metric)
self.assertEqual(rows_metric.unit, "{row}")
points = list(rows_metric.data.data_points)
self.assertEqual(len(points), 1)
self.assertEqual(points[0].sum, 3)
self.assertEqual(points[0].count, 1)
@mock.patch.dict("os.environ", {OTEL_SEMCONV_STABILITY_OPT_IN: "database"})
def test_returned_rows_skipped_when_rowcount_unknown(self):
db_integration = AiopgIntegration(__name__, "testcomponent")
mock_connection = async_call(db_integration.wrapped_connection(mock_connect, (), {}))
cursor = async_call(mock_connection.cursor())
async_call(cursor.execute("CREATE TABLE users (id INT)"))
self.assertIsNone(self._get_metric(DB_CLIENT_RESPONSE_RETURNED_ROWS))
self.assertIsNotNone(self._get_metric(DB_CLIENT_OPERATION_DURATION))
# pylint: disable=unused-argument
async def mock_connect(*args, **kwargs):
database = kwargs.get("database")
server_host = kwargs.get("server_host")
server_port = kwargs.get("server_port")
user = kwargs.get("user")
return MockConnection(database, server_port, server_host, user)
# pylint: disable=unused-argument
async def mock_create_pool(*args, **kwargs):
database = kwargs.get("database")
server_host = kwargs.get("server_host")
server_port = kwargs.get("server_port")
user = kwargs.get("user")
return MockPool(database, server_port, server_host, user)
class MockPool:
def __init__(self, database, server_port, server_host, user):
self.database = database
self.server_port = server_port
self.server_host = server_host
self.user = user
# pylint: disable=no-self-use
async def release(self, conn):
return conn
def acquire(self):
"""Acquire free connection from the pool."""
coro = self._acquire()
return _PoolAcquireContextManager(coro, self)
async def _acquire(self):
connect = await mock_connect(self.database, self.server_port, self.server_host, self.user)
return connect
def close(self):
pass
async def wait_closed(self):
pass
class MockPsycopg2Connection:
def __init__(self, database, server_port, server_host, user):
self.database = database
self.server_port = server_port
self.server_host = server_host
self.user = user
self.info = SimpleNamespace(
dbname=database,
port=server_port,
host=server_host,
user=user,
)
class MockConnection:
def __init__(self, database, server_port, server_host, user):
self._conn = MockPsycopg2Connection(database, server_port, server_host, user)
def cursor(self):
coro = self._cursor()
return _ContextManager(coro) # pylint: disable=no-value-for-parameter
# pylint: disable=no-self-use
async def _cursor(self):
return MockCursor()
def close(self):
pass
class MockCursor:
def __init__(self):
self.rowcount = -1
# pylint: disable=unused-argument
async def execute(self, query, params=None, throw_exception=False, rowcount=-1):
self.rowcount = rowcount
if throw_exception:
raise psycopg2.ProgrammingError("Test Exception")
# pylint: disable=unused-argument
async def executemany(self, query, params=None, throw_exception=False, rowcount=-1):
self.rowcount = rowcount
if throw_exception:
raise psycopg2.ProgrammingError("Test Exception")
# pylint: disable=unused-argument
async def callproc(self, query, params=None, throw_exception=False, rowcount=-1):
self.rowcount = rowcount
if throw_exception:
raise psycopg2.ProgrammingError("Test Exception")
def close(self):
pass
class AiopgConnectionMock:
_conn = MagicMock()
async def __aexit__(self, exc_type, exc_val, exc_tb):
pass
async def __aenter__(self):
return MagicMock()
class AiopgPoolMock:
# pylint: disable=no-self-use
async def release(self, conn):
return conn
def acquire(self):
coro = self._acquire()
return _PoolAcquireContextManager(coro, self)
# pylint: disable=no-self-use
async def _acquire(self):
return AiopgConnectionMock()
class AiopgMock:
def __init__(self):
self.connect_call_count = 0
self.create_pool_call_count = 0
async def connect(self, *args, **kwargs):
self.connect_call_count += 1
return MagicMock()
async def create_pool(self, *args, **kwargs):
self.create_pool_call_count += 1
return AiopgPoolMock()
opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-asgi/ 0000775 0000000 0000000 00000000000 15270700723 0032066 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-asgi/LICENSE 0000664 0000000 0000000 00000026135 15270700723 0033102 0 ustar 00root root 0000000 0000000 Apache License
Version 2.0, January 2004
http://www.apache.org/licenses/
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opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-asgi/README.rst 0000664 0000000 0000000 00000001257 15270700723 0033562 0 ustar 00root root 0000000 0000000 OpenTelemetry ASGI Instrumentation
==================================
|pypi|
.. |pypi| image:: https://badge.fury.io/py/opentelemetry-instrumentation-asgi.svg
:target: https://pypi.org/project/opentelemetry-instrumentation-asgi/
This library provides a ASGI middleware that can be used on any ASGI framework
(such as Django, Starlette, FastAPI or Quart) to track requests timing through OpenTelemetry.
Installation
------------
::
pip install opentelemetry-instrumentation-asgi
References
----------
* `OpenTelemetry Project `_
* `OpenTelemetry Python Examples `_
pyproject.toml 0000664 0000000 0000000 00000003023 15270700723 0034721 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-asgi [build-system]
requires = ["hatchling"]
build-backend = "hatchling.build"
[project]
name = "opentelemetry-instrumentation-asgi"
dynamic = ["version"]
description = "ASGI instrumentation for OpenTelemetry"
readme = "README.rst"
license = "Apache-2.0"
requires-python = ">=3.10"
authors = [
{ name = "OpenTelemetry Authors", email = "cncf-opentelemetry-contributors@lists.cncf.io" },
]
classifiers = [
"Development Status :: 4 - Beta",
"Intended Audience :: Developers",
"License :: OSI Approved :: Apache Software License",
"Programming Language :: Python",
"Programming Language :: Python :: 3",
"Programming Language :: Python :: 3.10",
"Programming Language :: Python :: 3.11",
"Programming Language :: Python :: 3.12",
"Programming Language :: Python :: 3.13",
"Programming Language :: Python :: 3.14",
]
dependencies = [
"asgiref ~= 3.0",
"opentelemetry-api ~= 1.12",
"opentelemetry-instrumentation == 0.66b2",
"opentelemetry-semantic-conventions == 0.66b2",
"opentelemetry-util-http == 0.66b2",
]
[project.optional-dependencies]
instruments = [
"asgiref ~= 3.0",
]
[project.urls]
Homepage = "https://github.com/open-telemetry/opentelemetry-python-contrib/tree/main/instrumentation/opentelemetry-instrumentation-asgi"
Repository = "https://github.com/open-telemetry/opentelemetry-python-contrib"
[tool.hatch.version]
path = "src/opentelemetry/instrumentation/asgi/version.py"
[tool.hatch.build.targets.sdist]
include = [
"/src",
"/tests",
]
[tool.hatch.build.targets.wheel]
packages = ["src/opentelemetry"]
opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-asgi/src/ 0000775 0000000 0000000 00000000000 15270700723 0032655 5 ustar 00root root 0000000 0000000 opentelemetry/ 0000775 0000000 0000000 00000000000 15270700723 0035472 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-asgi/src instrumentation/ 0000775 0000000 0000000 00000000000 15270700723 0040735 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-asgi/src/opentelemetry asgi/ 0000775 0000000 0000000 00000000000 15270700723 0041660 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-asgi/src/opentelemetry/instrumentation __init__.py 0000664 0000000 0000000 00000112537 15270700723 0044002 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-asgi/src/opentelemetry/instrumentation/asgi # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
# pylint: disable=too-many-locals,too-many-lines
"""
The opentelemetry-instrumentation-asgi package provides an ASGI middleware that can be used
on any ASGI framework (such as Django-channels / Quart) to track request timing through OpenTelemetry.
Usage (Quart)
-------------
.. code-block:: python
from quart import Quart
from opentelemetry.instrumentation.asgi import OpenTelemetryMiddleware
app = Quart(__name__)
app.asgi_app = OpenTelemetryMiddleware(app.asgi_app)
@app.route("/")
async def hello():
return "Hello!"
if __name__ == "__main__":
app.run(debug=True)
Usage (Django 3.0)
------------------
Modify the application's ``asgi.py`` file as shown below.
.. code-block:: python
import os
from django.core.asgi import get_asgi_application
from opentelemetry.instrumentation.asgi import OpenTelemetryMiddleware
os.environ.setdefault("DJANGO_SETTINGS_MODULE", "asgi_example.settings")
application = get_asgi_application()
application = OpenTelemetryMiddleware(application)
Usage (Raw ASGI)
----------------
.. code-block:: python
from opentelemetry.instrumentation.asgi import OpenTelemetryMiddleware
app = ... # An ASGI application.
app = OpenTelemetryMiddleware(app)
Configuration
-------------
Request/Response hooks
**********************
This instrumentation supports request and response hooks. These are functions that get called
right after a span is created for a request and right before the span is finished for the response.
- The server request hook is passed a server span and ASGI scope object for every incoming request.
- The client request hook is called with the internal span and an ASGI scope when the method ``receive`` is called.
- The client response hook is called with the internal span and an ASGI event when the method ``send`` is called.
For example,
.. code-block:: python
from opentelemetry.trace import Span
from typing import Any
from asgiref.typing import Scope, ASGIReceiveEvent, ASGISendEvent
from opentelemetry.instrumentation.asgi import OpenTelemetryMiddleware
async def application(scope: Scope, receive: ASGIReceiveEvent, send: ASGISendEvent):
await send(
{
"type": "http.response.start",
"status": 200,
"headers": [
[b"content-type", b"text/plain"],
],
}
)
await send(
{
"type": "http.response.body",
"body": b"Hello, world!",
}
)
def server_request_hook(span: Span, scope: Scope):
if span and span.is_recording():
span.set_attribute("custom_user_attribute_from_request_hook", "some-value")
def client_request_hook(span: Span, scope: Scope, message: dict[str, Any]):
if span and span.is_recording():
span.set_attribute("custom_user_attribute_from_client_request_hook", "some-value")
def client_response_hook(span: Span, scope: Scope, message: dict[str, Any]):
if span and span.is_recording():
span.set_attribute("custom_user_attribute_from_response_hook", "some-value")
OpenTelemetryMiddleware(
application,
server_request_hook=server_request_hook,
client_request_hook=client_request_hook,
client_response_hook=client_response_hook,
)
Capture HTTP request and response headers
*****************************************
You can configure the agent to capture specified HTTP headers as span attributes, according to the
`semantic conventions `_.
Request headers
***************
To capture HTTP request headers as span attributes, set the environment variable
``OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_REQUEST`` to a comma delimited list of HTTP header names.
For example,
::
export OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_REQUEST="content-type,custom_request_header"
will extract ``content-type`` and ``custom_request_header`` from the request headers and add them as span attributes.
Request header names in ASGI are case-insensitive. So, giving the header name as ``CUStom-Header`` in the environment
variable will capture the header named ``custom-header``.
Regular expressions may also be used to match multiple headers that correspond to the given pattern. For example:
::
export OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_REQUEST="Accept.*,X-.*"
Would match all request headers that start with ``Accept`` and ``X-``.
To capture all request headers, set ``OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_REQUEST`` to ``".*"``.
::
export OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_REQUEST=".*"
The name of the added span attribute will follow the format ``http.request.header.`` where ````
is the normalized HTTP header name (lowercase, with ``-`` replaced by ``_``). The value of the attribute will be a
list containing the header values.
For example:
``http.request.header.custom_request_header = ["", ""]``
Response headers
****************
To capture HTTP response headers as span attributes, set the environment variable
``OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_RESPONSE`` to a comma delimited list of HTTP header names.
For example,
::
export OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_RESPONSE="content-type,custom_response_header"
will extract ``content-type`` and ``custom_response_header`` from the response headers and add them as span attributes.
Response header names in ASGI are case-insensitive. So, giving the header name as ``CUStom-Header`` in the environment
variable will capture the header named ``custom-header``.
Regular expressions may also be used to match multiple headers that correspond to the given pattern. For example:
::
export OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_RESPONSE="Content.*,X-.*"
Would match all response headers that start with ``Content`` and ``X-``.
To capture all response headers, set ``OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_RESPONSE`` to ``".*"``.
::
export OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_RESPONSE=".*"
The name of the added span attribute will follow the format ``http.response.header.`` where ````
is the normalized HTTP header name (lowercase, with ``-`` replaced by ``_``). The value of the attribute will be a
list containing the header values.
For example:
``http.response.header.custom_response_header = ["", ""]``
Sanitizing headers
******************
In order to prevent storing sensitive data such as personally identifiable information (PII), session keys, passwords,
etc, set the environment variable ``OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SANITIZE_FIELDS``
to a comma delimited list of HTTP header names to be sanitized. Regexes may be used, and all header names will be
matched in a case-insensitive manner.
For example,
::
export OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SANITIZE_FIELDS=".*session.*,set-cookie"
will replace the value of headers such as ``session-id`` and ``set-cookie`` with ``[REDACTED]`` in the span.
Note:
The environment variable names used to capture HTTP headers are still experimental, and thus are subject to change.
API
---
"""
from __future__ import annotations
import typing
import urllib
from collections import defaultdict
from collections.abc import Awaitable, Callable
from functools import wraps
from timeit import default_timer
from typing import Any
from asgiref.compatibility import guarantee_single_callable
from opentelemetry import context, trace
from opentelemetry.instrumentation._semconv import (
HTTP_DURATION_HISTOGRAM_BUCKETS_NEW,
_filter_semconv_active_request_count_attr,
_filter_semconv_duration_attrs,
_get_schema_url,
_OpenTelemetrySemanticConventionStability,
_OpenTelemetryStabilitySignalType,
_report_new,
_report_old,
_server_active_requests_count_attrs_new,
_server_active_requests_count_attrs_old,
_server_duration_attrs_new,
_server_duration_attrs_old,
_set_http_flavor_version,
_set_http_host_server,
_set_http_method,
_set_http_net_host_port,
_set_http_peer_ip_server,
_set_http_peer_port_server,
_set_http_scheme,
_set_http_target,
_set_http_url,
_set_http_user_agent,
_set_status,
_StabilityMode,
)
from opentelemetry.instrumentation.asgi.types import (
ClientRequestHook,
ClientResponseHook,
ServerRequestHook,
)
from opentelemetry.instrumentation.asgi.version import __version__
from opentelemetry.instrumentation.propagators import (
get_global_response_propagator,
)
from opentelemetry.instrumentation.utils import (
_start_internal_or_server_span,
is_http_instrumentation_enabled,
)
from opentelemetry.metrics import get_meter
from opentelemetry.propagators.textmap import Getter, Setter
from opentelemetry.semconv._incubating.attributes.http_attributes import (
HTTP_SERVER_NAME,
HTTP_TARGET,
)
from opentelemetry.semconv._incubating.attributes.user_agent_attributes import (
USER_AGENT_SYNTHETIC_TYPE,
)
from opentelemetry.semconv._incubating.metrics.http_metrics import (
create_http_server_active_requests,
create_http_server_request_body_size,
create_http_server_response_body_size,
)
from opentelemetry.semconv.metrics import MetricInstruments
from opentelemetry.semconv.metrics.http_metrics import (
HTTP_SERVER_REQUEST_DURATION,
)
from opentelemetry.trace import Span, set_span_in_context
from opentelemetry.util.http import (
OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SANITIZE_FIELDS,
OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_REQUEST,
OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_RESPONSE,
ExcludeList,
SanitizeValue,
_parse_url_query,
detect_synthetic_user_agent,
get_custom_headers,
normalise_request_header_name,
normalise_response_header_name,
normalize_user_agent,
parse_excluded_urls,
redact_url,
sanitize_method,
)
class ASGIGetter(Getter[dict]):
def get(self, carrier: dict, key: str) -> list[str] | None:
"""Getter implementation to retrieve a HTTP header value from the ASGI
scope.
Args:
carrier: ASGI scope object
key: header name in scope
Returns:
A list with a single string with the header value if it exists,
else None.
"""
headers = carrier.get("headers")
if not headers:
return None
# ASGI header keys are in lower case
key = key.lower()
decoded = [
_decode_header_item(_value) for (_key, _value) in headers if _decode_header_item(_key).lower() == key
]
if not decoded:
return None
return decoded
def keys(self, carrier: dict) -> list[str]:
headers = carrier.get("headers") or []
return [_decode_header_item(_key) for (_key, _value) in headers]
asgi_getter = ASGIGetter()
class ASGISetter(Setter[dict]):
def set(self, carrier: dict, key: str, value: str) -> None: # pylint: disable=no-self-use
"""Sets response header values on an ASGI scope according to `the spec `_.
Args:
carrier: ASGI scope object
key: response header name to set
value: response header value
Returns:
None
"""
headers = carrier.get("headers")
if not headers:
headers = []
carrier["headers"] = headers
headers.append([key.lower().encode(), value.encode()])
asgi_setter = ASGISetter()
# pylint: disable=too-many-branches
def collect_request_attributes(scope, sem_conv_opt_in_mode=_StabilityMode.DEFAULT):
"""Collects HTTP request attributes from the ASGI scope and returns a
dictionary to be used as span creation attributes."""
server_host, port, http_url = get_host_port_url_tuple(scope)
query_string = scope.get("query_string")
if query_string and http_url:
if isinstance(query_string, bytes):
query_string = query_string.decode("utf8")
http_url += "?" + urllib.parse.unquote(query_string)
result = {}
scheme = scope.get("scheme")
if scheme:
_set_http_scheme(result, scheme, sem_conv_opt_in_mode)
if server_host:
_set_http_host_server(result, server_host, sem_conv_opt_in_mode)
if port:
_set_http_net_host_port(result, port, sem_conv_opt_in_mode)
flavor = scope.get("http_version")
if flavor:
_set_http_flavor_version(result, flavor, sem_conv_opt_in_mode)
path = scope.get("path")
if path:
_set_http_target(result, path, path, query_string, sem_conv_opt_in_mode)
if http_url:
if _report_old(sem_conv_opt_in_mode):
_set_http_url(
result,
redact_url(http_url),
_StabilityMode.DEFAULT,
)
http_method = scope.get("method", "")
if http_method:
_set_http_method(
result,
http_method,
sanitize_method(http_method),
sem_conv_opt_in_mode,
)
http_host_value_list = asgi_getter.get(scope, "host")
if http_host_value_list:
if _report_old(sem_conv_opt_in_mode):
result[HTTP_SERVER_NAME] = ",".join(http_host_value_list)
http_user_agent = asgi_getter.get(scope, "user-agent")
if http_user_agent:
user_agent_raw = http_user_agent[0]
user_agent_value = normalize_user_agent(user_agent_raw)
if user_agent_value:
_set_http_user_agent(result, user_agent_value, sem_conv_opt_in_mode)
# Check for synthetic user agent type
synthetic_type = detect_synthetic_user_agent(user_agent_value)
if synthetic_type:
result[USER_AGENT_SYNTHETIC_TYPE] = synthetic_type
if "client" in scope and scope["client"] is not None:
_set_http_peer_ip_server(result, scope.get("client")[0], sem_conv_opt_in_mode)
_set_http_peer_port_server(result, scope.get("client")[1], sem_conv_opt_in_mode)
# remove None values
result = {k: v for k, v in result.items() if v is not None}
return result
def collect_custom_headers_attributes(
scope_or_response_message: dict[str, Any],
sanitize: SanitizeValue,
header_regexes: list[str],
normalize_names: Callable[[str], str],
) -> dict[str, list[str]]:
"""
Returns custom HTTP request or response headers to be added into SERVER span as span attributes.
Refer to semantic conventions:
- https://github.com/open-telemetry/semantic-conventions/blob/main/docs/http/http-spans.md#http-server-span
"""
headers: defaultdict[str, list[str]] = defaultdict(list)
raw_headers = scope_or_response_message.get("headers")
if raw_headers:
for key, value in raw_headers:
# Decode headers before processing.
headers[_decode_header_item(key)].append(_decode_header_item(value))
return sanitize.sanitize_header_values(
headers,
header_regexes,
normalize_names,
)
def get_host_port_url_tuple(scope):
"""Returns (host, port, full_url) tuple."""
server = scope.get("server") or ["0.0.0.0", 80]
port = server[1]
host_header = asgi_getter.get(scope, "host")
if host_header:
host_value = host_header[0]
# Ensure host_value is a string, not bytes
if isinstance(host_value, bytes):
host_value = _decode_header_item(host_value)
url_host = host_value
else:
url_host = server[0] + (":" + str(port) if str(port) != "80" else "")
server_host = server[0] + (":" + str(port) if str(port) != "80" else "")
# using the scope path is enough, see:
# - https://asgi.readthedocs.io/en/latest/specs/www.html#http-connection-scope (see: root_path and path)
# - https://asgi.readthedocs.io/en/latest/specs/www.html#wsgi-compatibility (see: PATH_INFO)
# PATH_INFO can be derived by stripping root_path from path
# -> that means that the path should contain the root_path already, so prefixing it again is not necessary
# - https://wsgi.readthedocs.io/en/latest/definitions.html#envvar-PATH_INFO
full_path = scope.get("path", "")
http_url = scope.get("scheme", "http") + "://" + url_host + full_path
return server_host, port, http_url
def set_status_code(
span,
status_code,
metric_attributes=None,
sem_conv_opt_in_mode=_StabilityMode.DEFAULT,
):
"""Adds HTTP response attributes to span using the status_code argument."""
status_code_str = str(status_code)
try:
status_code = int(status_code)
except ValueError:
status_code = -1
if metric_attributes is None:
metric_attributes = {}
_set_status(
span,
metric_attributes,
status_code,
status_code_str,
server_span=True,
sem_conv_opt_in_mode=sem_conv_opt_in_mode,
)
def get_default_span_details(scope: dict) -> tuple[str, dict]:
"""
Default span name is the HTTP method and URL path, or just the method.
https://github.com/open-telemetry/opentelemetry-specification/pull/3165
https://opentelemetry.io/docs/reference/specification/trace/semantic_conventions/http/#name
Args:
scope: the ASGI scope dictionary
Returns:
a tuple of the span name, and any attributes to attach to the span.
"""
path = scope.get("path", "").strip()
method = sanitize_method(scope.get("method", "").strip())
if method == "_OTHER":
method = "HTTP"
if method and path: # http
return f"{method} {path}", {}
if path: # websocket
return path, {}
return method, {} # http with no path
def _collect_target_attribute(
scope: dict[str, typing.Any],
) -> str | None:
"""
Returns the target path as defined by the Semantic Conventions.
This value is suitable to use in metrics as it should replace concrete
values with a parameterized name. Example: /api/users/{user_id}
Refer to the specification
https://github.com/open-telemetry/opentelemetry-specification/blob/main/specification/metrics/semantic_conventions/http-metrics.md#parameterized-attributes
Note: this function requires specific code for each framework, as there's no
standard attribute to use.
"""
# FastAPI
root_path = scope.get("root_path", "")
route = scope.get("route")
path_format = getattr(route, "path_format", None)
if path_format:
return f"{root_path}{path_format}"
return None
class OpenTelemetryMiddleware:
"""The ASGI application middleware.
This class is an ASGI middleware that starts and annotates spans for any
requests it is invoked with.
Args:
app: The ASGI application callable to forward requests to.
default_span_details: Callback which should return a string and a tuple, representing the desired default span name and a
dictionary with any additional span attributes to set.
Optional: Defaults to get_default_span_details.
server_request_hook: Optional callback which is called with the server span and ASGI
scope object for every incoming request.
client_request_hook: Optional callback which is called with the internal span, and ASGI
scope and event which are sent as dictionaries for when the method receive is called.
client_response_hook: Optional callback which is called with the internal span, and ASGI
scope and event which are sent as dictionaries for when the method send is called.
tracer_provider: The optional tracer provider to use. If omitted
the current globally configured one is used.
meter_provider: The optional meter provider to use. If omitted
the current globally configured one is used.
exclude_spans: Optionally exclude HTTP `send` and/or `receive` spans from the trace.
"""
# pylint: disable=too-many-branches,too-many-positional-arguments
def __init__(
self,
app,
excluded_urls: ExcludeList | str | None = None,
default_span_details=None,
server_request_hook: ServerRequestHook = None,
client_request_hook: ClientRequestHook = None,
client_response_hook: ClientResponseHook = None,
tracer_provider=None,
meter_provider=None,
tracer=None,
meter=None,
http_capture_headers_server_request: list[str] | None = None,
http_capture_headers_server_response: list[str] | None = None,
http_capture_headers_sanitize_fields: list[str] | None = None,
exclude_spans: list[typing.Literal["receive", "send"]] | None = None,
):
# initialize semantic conventions opt-in if needed
_OpenTelemetrySemanticConventionStability._initialize()
sem_conv_opt_in_mode = _OpenTelemetrySemanticConventionStability._get_opentelemetry_stability_opt_in_mode(
_OpenTelemetryStabilitySignalType.HTTP,
)
self.app = guarantee_single_callable(app)
self.tracer = (
trace.get_tracer(
__name__,
__version__,
tracer_provider,
schema_url=_get_schema_url(sem_conv_opt_in_mode),
)
if tracer is None
else tracer
)
self.meter = (
get_meter(
__name__,
__version__,
meter_provider,
schema_url=_get_schema_url(sem_conv_opt_in_mode),
)
if meter is None
else meter
)
self.duration_histogram_old = None
if _report_old(sem_conv_opt_in_mode):
self.duration_histogram_old = self.meter.create_histogram(
name=MetricInstruments.HTTP_SERVER_DURATION,
unit="ms",
description="Measures the duration of inbound HTTP requests.",
)
self.duration_histogram_new = None
if _report_new(sem_conv_opt_in_mode):
self.duration_histogram_new = self.meter.create_histogram(
name=HTTP_SERVER_REQUEST_DURATION,
description="Duration of HTTP server requests.",
unit="s",
explicit_bucket_boundaries_advisory=HTTP_DURATION_HISTOGRAM_BUCKETS_NEW,
)
self.server_response_size_histogram = None
if _report_old(sem_conv_opt_in_mode):
self.server_response_size_histogram = self.meter.create_histogram(
name=MetricInstruments.HTTP_SERVER_RESPONSE_SIZE,
unit="By",
description="measures the size of HTTP response messages (compressed).",
)
self.server_response_body_size_histogram = None
if _report_new(sem_conv_opt_in_mode):
self.server_response_body_size_histogram = create_http_server_response_body_size(self.meter)
self.server_request_size_histogram = None
if _report_old(sem_conv_opt_in_mode):
self.server_request_size_histogram = self.meter.create_histogram(
name=MetricInstruments.HTTP_SERVER_REQUEST_SIZE,
unit="By",
description="Measures the size of HTTP request messages (compressed).",
)
self.server_request_body_size_histogram = None
if _report_new(sem_conv_opt_in_mode):
self.server_request_body_size_histogram = create_http_server_request_body_size(self.meter)
self.active_requests_counter = create_http_server_active_requests(self.meter)
if isinstance(excluded_urls, str):
excluded_urls = parse_excluded_urls(excluded_urls)
self.excluded_urls = excluded_urls
self.default_span_details = default_span_details or get_default_span_details
def failsafe(func):
if func is None:
return None
@wraps(func)
def wrapper(span: Span, *args, **kwargs):
try:
func(span, *args, **kwargs)
except Exception as exc: # pylint: disable=broad-exception-caught
span.record_exception(exc)
return wrapper
self.server_request_hook = failsafe(server_request_hook)
self.client_request_hook = failsafe(client_request_hook)
self.client_response_hook = failsafe(client_response_hook)
self.content_length_header = None
self._sem_conv_opt_in_mode = sem_conv_opt_in_mode
# Environment variables as constructor parameters
self.http_capture_headers_server_request = (
http_capture_headers_server_request
or (get_custom_headers(OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_REQUEST))
or None
)
self.http_capture_headers_server_response = (
http_capture_headers_server_response
or (get_custom_headers(OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_RESPONSE))
or None
)
self.http_capture_headers_sanitize_fields = SanitizeValue(
http_capture_headers_sanitize_fields
or (get_custom_headers(OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SANITIZE_FIELDS))
or []
)
self.exclude_receive_span = "receive" in exclude_spans if exclude_spans else False
self.exclude_send_span = "send" in exclude_spans if exclude_spans else False
# pylint: disable=too-many-statements
async def __call__(
self,
scope: typing.MutableMapping[str, Any],
receive: Callable[[], Awaitable[typing.MutableMapping[str, Any]]],
send: Callable[[typing.MutableMapping[str, Any]], Awaitable[None]],
) -> None:
"""The ASGI application
Args:
scope: An ASGI environment.
receive: An awaitable callable yielding dictionaries
send: An awaitable callable taking a single dictionary as argument.
"""
start = default_timer()
if not is_http_instrumentation_enabled() or scope["type"] not in (
"http",
"websocket",
):
return await self.app(scope, receive, send)
_, _, url = get_host_port_url_tuple(scope)
if self.excluded_urls and self.excluded_urls.url_disabled(url):
return await self.app(scope, receive, send)
span_name, additional_attributes = self.default_span_details(scope)
attributes = collect_request_attributes(scope, self._sem_conv_opt_in_mode)
attributes.update(additional_attributes)
span, token = _start_internal_or_server_span(
tracer=self.tracer,
span_name=span_name,
start_time=None,
context_carrier=scope,
context_getter=asgi_getter,
attributes=attributes,
)
active_requests_count_attrs = _parse_active_request_count_attrs(
attributes,
self._sem_conv_opt_in_mode,
)
if scope["type"] == "http":
self.active_requests_counter.add(1, active_requests_count_attrs)
try:
with trace.use_span(span, end_on_exit=False) as current_span:
if current_span.is_recording():
for key, value in attributes.items():
current_span.set_attribute(key, value)
if current_span.kind == trace.SpanKind.SERVER:
custom_attributes = (
collect_custom_headers_attributes(
scope,
self.http_capture_headers_sanitize_fields,
self.http_capture_headers_server_request,
normalise_request_header_name,
)
if self.http_capture_headers_server_request
else {}
)
if len(custom_attributes) > 0:
current_span.set_attributes(custom_attributes)
if callable(self.server_request_hook):
self.server_request_hook(current_span, scope)
otel_receive = self._get_otel_receive(span_name, scope, receive)
otel_send = self._get_otel_send(
current_span,
span_name,
scope,
send,
attributes,
)
await self.app(scope, otel_receive, otel_send)
finally:
if scope["type"] == "http":
target = _collect_target_attribute(scope)
if target:
path, query = _parse_url_query(target)
_set_http_target(
attributes,
target,
path,
query,
self._sem_conv_opt_in_mode,
)
duration_s = default_timer() - start
duration_attrs_old = _parse_duration_attrs(attributes, _StabilityMode.DEFAULT)
if target:
duration_attrs_old[HTTP_TARGET] = target
duration_attrs_new = _parse_duration_attrs(attributes, _StabilityMode.HTTP)
span_ctx = set_span_in_context(span)
if self.duration_histogram_old:
self.duration_histogram_old.record(
max(round(duration_s * 1000), 0),
duration_attrs_old,
context=span_ctx,
)
if self.duration_histogram_new:
self.duration_histogram_new.record(
max(duration_s, 0),
duration_attrs_new,
context=span_ctx,
)
self.active_requests_counter.add(-1, active_requests_count_attrs)
if self.content_length_header:
if self.server_response_size_histogram:
self.server_response_size_histogram.record(
self.content_length_header,
duration_attrs_old,
context=span_ctx,
)
if self.server_response_body_size_histogram:
self.server_response_body_size_histogram.record(
self.content_length_header,
duration_attrs_new,
context=span_ctx,
)
request_size = asgi_getter.get(scope, "content-length")
if request_size:
try:
request_size_amount = int(request_size[0])
except ValueError:
pass
else:
if self.server_request_size_histogram:
self.server_request_size_histogram.record(
request_size_amount,
duration_attrs_old,
context=span_ctx,
)
if self.server_request_body_size_histogram:
self.server_request_body_size_histogram.record(
request_size_amount,
duration_attrs_new,
context=span_ctx,
)
if token:
context.detach(token)
if span.is_recording():
span.end()
# pylint: enable=too-many-branches
def _get_otel_receive(self, server_span_name, scope, receive):
if self.exclude_receive_span:
return receive
@wraps(receive)
async def otel_receive():
with self.tracer.start_as_current_span(
" ".join((server_span_name, scope["type"], "receive"))
) as receive_span:
message = await receive()
if callable(self.client_request_hook):
self.client_request_hook(receive_span, scope, message)
if receive_span.is_recording():
if message["type"] == "websocket.receive":
set_status_code(
receive_span,
200,
None,
self._sem_conv_opt_in_mode,
)
receive_span.set_attribute("asgi.event.type", message["type"])
return message
return otel_receive
def _set_send_span(
self,
server_span_name,
scope,
send,
message,
status_code,
expecting_trailers,
):
"""Set send span attributes and status code."""
with self.tracer.start_as_current_span(" ".join((server_span_name, scope["type"], "send"))) as send_span:
if callable(self.client_response_hook):
self.client_response_hook(send_span, scope, message)
if send_span.is_recording():
if message["type"] == "http.response.start":
expecting_trailers = message.get("trailers", False)
send_span.set_attribute("asgi.event.type", message["type"])
if status_code:
set_status_code(
send_span,
status_code,
None,
self._sem_conv_opt_in_mode,
)
return expecting_trailers
def _set_server_span(self, server_span, message, status_code, duration_attrs):
"""Set server span attributes and status code."""
if server_span.is_recording() and server_span.kind == trace.SpanKind.SERVER and "headers" in message:
custom_response_attributes = (
collect_custom_headers_attributes(
message,
self.http_capture_headers_sanitize_fields,
self.http_capture_headers_server_response,
normalise_response_header_name,
)
if self.http_capture_headers_server_response
else {}
)
if len(custom_response_attributes) > 0:
server_span.set_attributes(custom_response_attributes)
if status_code:
set_status_code(
server_span,
status_code,
duration_attrs,
self._sem_conv_opt_in_mode,
)
def _get_otel_send(
self,
server_span,
server_span_name,
scope,
send,
duration_attrs,
):
expecting_trailers = False
@wraps(send)
async def otel_send(message: dict[str, Any]):
nonlocal expecting_trailers
status_code = None
if message["type"] == "http.response.start":
status_code = message["status"]
elif message["type"] == "websocket.send":
status_code = 200
if not self.exclude_send_span:
expecting_trailers = self._set_send_span(
server_span_name,
scope,
send,
message,
status_code,
expecting_trailers,
)
self._set_server_span(server_span, message, status_code, duration_attrs)
propagator = get_global_response_propagator()
if propagator:
propagator.inject(
message,
context=set_span_in_context(server_span, trace.context_api.Context()),
setter=asgi_setter,
)
content_length = asgi_getter.get(message, "content-length")
if content_length:
try:
self.content_length_header = int(content_length[0])
except ValueError:
pass
await send(message)
# pylint: disable=too-many-boolean-expressions
if (
not expecting_trailers
and message["type"] == "http.response.body"
and not message.get("more_body", False)
) or (
expecting_trailers
and message["type"] == "http.response.trailers"
and not message.get("more_trailers", False)
):
server_span.end()
return otel_send
def _parse_duration_attrs(req_attrs, sem_conv_opt_in_mode=_StabilityMode.DEFAULT):
return _filter_semconv_duration_attrs(
req_attrs,
_server_duration_attrs_old,
_server_duration_attrs_new,
sem_conv_opt_in_mode,
)
def _parse_active_request_count_attrs(req_attrs, sem_conv_opt_in_mode=_StabilityMode.DEFAULT):
return _filter_semconv_active_request_count_attr(
req_attrs,
_server_active_requests_count_attrs_old,
_server_active_requests_count_attrs_new,
sem_conv_opt_in_mode,
)
def _decode_header_item(value):
try:
return value.decode("utf-8")
except ValueError:
# ASGI header encoding specs, see:
# - https://asgi.readthedocs.io/en/latest/specs/www.html#wsgi-encoding-differences (see: WSGI encoding differences)
# - https://docs.python.org/3/library/codecs.html#text-encodings (see: Text Encodings)
return value.decode("unicode_escape")
package.py 0000664 0000000 0000000 00000000252 15270700723 0043624 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-asgi/src/opentelemetry/instrumentation/asgi # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
_instruments = ("asgiref ~= 3.0",)
_supports_metrics = True
_semconv_status = "migration"
types.py 0000664 0000000 0000000 00000001360 15270700723 0043376 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-asgi/src/opentelemetry/instrumentation/asgi # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
from collections.abc import Callable
from typing import Any
from opentelemetry.trace import Span
_Scope = dict[str, Any]
_Message = dict[str, Any]
ServerRequestHook = Callable[[Span, _Scope], None] | None
"""
Incoming request callback type.
Args:
- Server span
- ASGI scope as a mapping
"""
ClientRequestHook = Callable[[Span, _Scope, _Message], None] | None
"""
Receive callback type.
Args:
- Internal span
- ASGI scope as a mapping
- ASGI event as a mapping
"""
ClientResponseHook = Callable[[Span, _Scope, _Message], None] | None
"""
Send callback type.
Args:
- Internal span
- ASGI scope as a mapping
- ASGI event as a mapping
"""
version.py 0000664 0000000 0000000 00000000144 15270700723 0043716 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-asgi/src/opentelemetry/instrumentation/asgi # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
__version__ = "0.66b2"
test-requirements.txt 0000664 0000000 0000000 00000000452 15270700723 0036251 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-asgi asgiref==3.8.1
Deprecated==1.2.14
iniconfig==2.0.0
packaging==24.0
pluggy==1.6.0
py-cpuinfo==9.0.0
pytest==7.4.4
tomli==2.0.1
typing_extensions==4.12.2
wrapt==1.16.0
zipp==3.19.2
-e opentelemetry-instrumentation
-e util/opentelemetry-util-http
-e instrumentation/opentelemetry-instrumentation-asgi
opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-asgi/tests/ 0000775 0000000 0000000 00000000000 15270700723 0033230 5 ustar 00root root 0000000 0000000 __init__.py 0000664 0000000 0000000 00000000000 15270700723 0035250 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-asgi/tests test_asgi_custom_headers.py 0000664 0000000 0000000 00000041766 15270700723 0040610 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-asgi/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
import os
import opentelemetry.instrumentation.asgi as otel_asgi
from opentelemetry.test.asgitestutil import AsyncAsgiTestBase
from opentelemetry.test.test_base import TestBase
from opentelemetry.trace import SpanKind
from opentelemetry.util.http import (
OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SANITIZE_FIELDS,
OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_REQUEST,
OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_RESPONSE,
)
from .test_asgi_middleware import simple_asgi
async def http_app_with_custom_headers(scope, receive, send):
message = await receive()
assert scope["type"] == "http"
if message.get("type") == "http.request":
await send(
{
"type": "http.response.start",
"status": 200,
"headers": [
(b"Content-Type", b"text/plain"),
(b"custom-test-header-1", b"test-header-value-1"),
(b"custom-test-header-2", b"test-header-value-2"),
(
b"my-custom-regex-header-1",
b"my-custom-regex-value-1,my-custom-regex-value-2",
),
(
b"My-Custom-Regex-Header-2",
b"my-custom-regex-value-3,my-custom-regex-value-4",
),
(b"my-secret-header", b"my-secret-value"),
(
b"non-utf8-header",
b"Moto Z\xb2",
),
(
b"Moto-Z\xb2-non-utf8-header-key",
b"Moto Z\xb2",
),
],
}
)
await send({"type": "http.response.body", "body": b"*"})
async def http_app_with_repeat_headers(scope, receive, send):
message = await receive()
assert scope["type"] == "http"
if message.get("type") == "http.request":
await send(
{
"type": "http.response.start",
"status": 200,
"headers": [
(b"Content-Type", b"text/plain"),
(b"custom-test-header-1", b"test-header-value-1"),
(b"custom-test-header-1", b"test-header-value-2"),
],
}
)
await send({"type": "http.response.body", "body": b"*"})
async def websocket_app_with_custom_headers(scope, receive, send):
assert scope["type"] == "websocket"
while True:
message = await receive()
if message.get("type") == "websocket.connect":
await send(
{
"type": "websocket.accept",
"headers": [
(b"custom-test-header-1", b"test-header-value-1"),
(b"custom-test-header-2", b"test-header-value-2"),
(
b"my-custom-regex-header-1",
b"my-custom-regex-value-1,my-custom-regex-value-2",
),
(
b"My-Custom-Regex-Header-2",
b"my-custom-regex-value-3,my-custom-regex-value-4",
),
(b"my-secret-header", b"my-secret-value"),
],
}
)
if message.get("type") == "websocket.receive":
if message.get("text") == "ping":
await send({"type": "websocket.send", "text": "pong"})
if message.get("type") == "websocket.disconnect":
break
class TestCustomHeaders(AsyncAsgiTestBase):
constructor_params = {}
__test__ = False
def __init_subclass__(cls) -> None:
if cls is not TestCustomHeaders:
cls.__test__ = True
def setUp(self):
super().setUp()
self.tracer_provider, self.exporter = TestBase.create_tracer_provider()
self.tracer = self.tracer_provider.get_tracer(__name__)
self.app = otel_asgi.OpenTelemetryMiddleware(
simple_asgi,
tracer_provider=self.tracer_provider,
**self.constructor_params,
)
async def test_http_custom_request_headers_in_span_attributes(self):
self.scope["headers"].extend(
[
(b"custom-test-header-1", b"test-header-value-1"),
(b"custom-test-header-2", b"test-header-value-2"),
(b"Regex-Test-Header-1", b"Regex Test Value 1"),
(b"regex-test-header-2", b"RegexTestValue2,RegexTestValue3"),
(b"My-Secret-Header", b"My Secret Value"),
(
b"non-utf8-header",
b"Moto Z\xb2",
),
(
b"Moto-Z\xb2-non-utf8-header-key",
b"Moto Z\xb2",
),
]
)
self.seed_app(self.app)
await self.send_default_request()
await self.get_all_output()
span_list = self.exporter.get_finished_spans()
expected = {
"http.request.header.custom_test_header_1": ("test-header-value-1",),
"http.request.header.custom_test_header_2": ("test-header-value-2",),
"http.request.header.regex_test_header_1": ("Regex Test Value 1",),
"http.request.header.regex_test_header_2": ("RegexTestValue2,RegexTestValue3",),
"http.request.header.non_utf8_header": ("Moto Z²",),
"http.request.header.moto_z²_non_utf8_header_key": ("Moto Z²",),
"http.request.header.my_secret_header": ("[REDACTED]",),
}
for span in span_list:
if span.kind == SpanKind.SERVER:
self.assertSpanHasAttributes(span, expected)
async def test_http_repeat_request_headers_in_span_attributes(self):
self.scope["headers"].extend(
[
(b"custom-test-header-1", b"test-header-value-1"),
(b"custom-test-header-1", b"test-header-value-2"),
]
)
self.seed_app(self.app)
await self.send_default_request()
await self.get_all_output()
span_list = self.exporter.get_finished_spans()
expected = {
"http.request.header.custom_test_header_1": (
"test-header-value-1",
"test-header-value-2",
),
}
span = next(span for span in span_list if span.kind == SpanKind.SERVER)
self.assertSpanHasAttributes(span, expected)
async def test_http_custom_request_headers_not_in_span_attributes(self):
self.scope["headers"].extend(
[
(b"custom-test-header-1", b"test-header-value-1"),
]
)
self.seed_app(self.app)
await self.send_default_request()
await self.get_all_output()
span_list = self.exporter.get_finished_spans()
expected = {
"http.request.header.custom_test_header_1": ("test-header-value-1",),
}
not_expected = {
"http.request.header.custom_test_header_2": ("test-header-value-2",),
}
for span in span_list:
if span.kind == SpanKind.SERVER:
self.assertSpanHasAttributes(span, expected)
for key, _ in not_expected.items():
self.assertNotIn(key, span.attributes)
async def test_http_custom_response_headers_in_span_attributes(self):
self.app = otel_asgi.OpenTelemetryMiddleware(
http_app_with_custom_headers,
tracer_provider=self.tracer_provider,
**self.constructor_params,
)
self.seed_app(self.app)
await self.send_default_request()
await self.get_all_output()
span_list = self.exporter.get_finished_spans()
expected = {
"http.response.header.custom_test_header_1": ("test-header-value-1",),
"http.response.header.custom_test_header_2": ("test-header-value-2",),
"http.response.header.my_custom_regex_header_1": ("my-custom-regex-value-1,my-custom-regex-value-2",),
"http.response.header.my_custom_regex_header_2": ("my-custom-regex-value-3,my-custom-regex-value-4",),
"http.response.header.my_secret_header": ("[REDACTED]",),
"http.response.header.non_utf8_header": ("Moto Z²",),
"http.response.header.moto_z²_non_utf8_header_key": ("Moto Z²",),
}
for span in span_list:
if span.kind == SpanKind.SERVER:
self.assertSpanHasAttributes(span, expected)
async def test_http_repeat_response_headers_in_span_attributes(self):
self.app = otel_asgi.OpenTelemetryMiddleware(
http_app_with_repeat_headers,
tracer_provider=self.tracer_provider,
**self.constructor_params,
)
self.seed_app(self.app)
await self.send_default_request()
await self.get_all_output()
span_list = self.exporter.get_finished_spans()
expected = {
"http.response.header.custom_test_header_1": (
"test-header-value-1",
"test-header-value-2",
),
}
span = next(span for span in span_list if span.kind == SpanKind.SERVER)
self.assertSpanHasAttributes(span, expected)
async def test_http_custom_response_headers_not_in_span_attributes(self):
self.app = otel_asgi.OpenTelemetryMiddleware(
http_app_with_custom_headers,
tracer_provider=self.tracer_provider,
**self.constructor_params,
)
self.seed_app(self.app)
await self.send_default_request()
await self.get_all_output()
span_list = self.exporter.get_finished_spans()
not_expected = {
"http.response.header.custom_test_header_3": ("test-header-value-3",),
}
for span in span_list:
if span.kind == SpanKind.SERVER:
for key, _ in not_expected.items():
self.assertNotIn(key, span.attributes)
async def test_websocket_custom_request_headers_in_span_attributes(self):
self.scope = {
"type": "websocket",
"http_version": "1.1",
"scheme": "ws",
"path": "/",
"query_string": b"",
"headers": [
(b"custom-test-header-1", b"test-header-value-1"),
(b"custom-test-header-2", b"test-header-value-2"),
(b"Regex-Test-Header-1", b"Regex Test Value 1"),
(b"regex-test-header-2", b"RegexTestValue2,RegexTestValue3"),
(b"My-Secret-Header", b"My Secret Value"),
],
"client": ("127.0.0.1", 32767),
"server": ("127.0.0.1", 80),
}
self.seed_app(self.app)
await self.send_input({"type": "websocket.connect"})
await self.send_input({"type": "websocket.receive", "text": "ping"})
await self.send_input({"type": "websocket.disconnect"})
await self.get_all_output()
span_list = self.exporter.get_finished_spans()
expected = {
"http.request.header.custom_test_header_1": ("test-header-value-1",),
"http.request.header.custom_test_header_2": ("test-header-value-2",),
"http.request.header.regex_test_header_1": ("Regex Test Value 1",),
"http.request.header.regex_test_header_2": ("RegexTestValue2,RegexTestValue3",),
"http.request.header.my_secret_header": ("[REDACTED]",),
}
for span in span_list:
if span.kind == SpanKind.SERVER:
self.assertSpanHasAttributes(span, expected)
async def test_websocket_custom_request_headers_not_in_span_attributes(
self,
):
self.scope = {
"type": "websocket",
"http_version": "1.1",
"scheme": "ws",
"path": "/",
"query_string": b"",
"headers": [
(b"Custom-Test-Header-1", b"test-header-value-1"),
(b"Custom-Test-Header-2", b"test-header-value-2"),
],
"client": ("127.0.0.1", 32767),
"server": ("127.0.0.1", 80),
}
self.seed_app(self.app)
await self.send_input({"type": "websocket.connect"})
await self.send_input({"type": "websocket.receive", "text": "ping"})
await self.send_input({"type": "websocket.disconnect"})
await self.get_all_output()
span_list = self.exporter.get_finished_spans()
not_expected = {
"http.request.header.custom_test_header_3": ("test-header-value-3",),
}
for span in span_list:
if span.kind == SpanKind.SERVER:
for key, _ in not_expected.items():
self.assertNotIn(key, span.attributes)
async def test_websocket_custom_response_headers_in_span_attributes(self):
self.scope = {
"type": "websocket",
"http_version": "1.1",
"scheme": "ws",
"path": "/",
"query_string": b"",
"headers": [],
"client": ("127.0.0.1", 32767),
"server": ("127.0.0.1", 80),
}
self.app = otel_asgi.OpenTelemetryMiddleware(
websocket_app_with_custom_headers,
tracer_provider=self.tracer_provider,
**self.constructor_params,
)
self.seed_app(self.app)
await self.send_input({"type": "websocket.connect"})
await self.send_input({"type": "websocket.receive", "text": "ping"})
await self.send_input({"type": "websocket.disconnect"})
await self.get_all_output()
span_list = self.exporter.get_finished_spans()
expected = {
"http.response.header.custom_test_header_1": ("test-header-value-1",),
"http.response.header.custom_test_header_2": ("test-header-value-2",),
"http.response.header.my_custom_regex_header_1": ("my-custom-regex-value-1,my-custom-regex-value-2",),
"http.response.header.my_custom_regex_header_2": ("my-custom-regex-value-3,my-custom-regex-value-4",),
"http.response.header.my_secret_header": ("[REDACTED]",),
}
for span in span_list:
if span.kind == SpanKind.SERVER:
self.assertSpanHasAttributes(span, expected)
async def test_websocket_custom_response_headers_not_in_span_attributes(
self,
):
self.scope = {
"type": "websocket",
"http_version": "1.1",
"scheme": "ws",
"path": "/",
"query_string": b"",
"headers": [],
"client": ("127.0.0.1", 32767),
"server": ("127.0.0.1", 80),
}
self.app = otel_asgi.OpenTelemetryMiddleware(
websocket_app_with_custom_headers,
tracer_provider=self.tracer_provider,
**self.constructor_params,
)
self.seed_app(self.app)
await self.send_input({"type": "websocket.connect"})
await self.send_input({"type": "websocket.receive", "text": "ping"})
await self.send_input({"type": "websocket.disconnect"})
await self.get_all_output()
span_list = self.exporter.get_finished_spans()
not_expected = {
"http.response.header.custom_test_header_3": ("test-header-value-3",),
}
for span in span_list:
if span.kind == SpanKind.SERVER:
for key, _ in not_expected.items():
self.assertNotIn(key, span.attributes)
SANITIZE_FIELDS_TEST_VALUE = ".*my-secret.*"
SERVER_REQUEST_TEST_VALUE = "Custom-Test-Header-1,Custom-Test-Header-2,Custom-Test-Header-3,Regex-Test-Header-.*,Regex-Invalid-Test-Header-.*,.*my-secret.*,non-utf8-header,Moto-Z²-non-utf8-header-key"
SERVER_RESPONSE_TEST_VALUE = "Custom-Test-Header-1,Custom-Test-Header-2,Custom-Test-Header-3,my-custom-regex-header-.*,invalid-regex-header-.*,.*my-secret.*,non-utf8-header,Moto-Z²-non-utf8-header-key"
class TestCustomHeadersEnv(TestCustomHeaders):
def setUp(self):
os.environ.update(
{
OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SANITIZE_FIELDS: SANITIZE_FIELDS_TEST_VALUE,
OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_REQUEST: SERVER_REQUEST_TEST_VALUE,
OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_RESPONSE: SERVER_RESPONSE_TEST_VALUE,
}
)
super().setUp()
def tearDown(self):
os.environ.pop(OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SANITIZE_FIELDS, None)
os.environ.pop(OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_REQUEST, None)
os.environ.pop(OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_RESPONSE, None)
super().tearDown()
class TestCustomHeadersConstructor(TestCustomHeaders):
constructor_params = {
"http_capture_headers_sanitize_fields": SANITIZE_FIELDS_TEST_VALUE.split(","),
"http_capture_headers_server_request": SERVER_REQUEST_TEST_VALUE.split(","),
"http_capture_headers_server_response": SERVER_RESPONSE_TEST_VALUE.split(","),
}
test_asgi_middleware.py 0000664 0000000 0000000 00000241566 15270700723 0037720 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-asgi/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
# pylint: disable=too-many-lines
import sys
import time
import unittest
from timeit import default_timer
from unittest import mock
import opentelemetry.instrumentation.asgi as otel_asgi
from opentelemetry import trace as trace_api
from opentelemetry.instrumentation._semconv import (
HTTP_DURATION_HISTOGRAM_BUCKETS_NEW,
OTEL_SEMCONV_STABILITY_OPT_IN,
_OpenTelemetrySemanticConventionStability,
_server_active_requests_count_attrs_new,
_server_active_requests_count_attrs_old,
_server_duration_attrs_new,
_server_duration_attrs_old,
_StabilityMode,
)
from opentelemetry.instrumentation.propagators import (
TraceResponsePropagator,
get_global_response_propagator,
set_global_response_propagator,
)
from opentelemetry.instrumentation.utils import suppress_http_instrumentation
from opentelemetry.sdk import resources
from opentelemetry.sdk.metrics.export import (
HistogramDataPoint,
NumberDataPoint,
)
from opentelemetry.semconv._incubating.attributes.http_attributes import (
HTTP_FLAVOR,
HTTP_HOST,
HTTP_METHOD,
HTTP_SCHEME,
HTTP_SERVER_NAME,
HTTP_STATUS_CODE,
HTTP_TARGET,
HTTP_URL,
HTTP_USER_AGENT,
)
from opentelemetry.semconv._incubating.attributes.net_attributes import (
NET_HOST_PORT,
NET_PEER_IP,
NET_PEER_PORT,
)
from opentelemetry.semconv._incubating.attributes.user_agent_attributes import (
USER_AGENT_SYNTHETIC_TYPE,
)
from opentelemetry.semconv.attributes.client_attributes import (
CLIENT_ADDRESS,
CLIENT_PORT,
)
from opentelemetry.semconv.attributes.http_attributes import (
HTTP_REQUEST_METHOD,
HTTP_RESPONSE_STATUS_CODE,
)
from opentelemetry.semconv.attributes.network_attributes import (
NETWORK_PROTOCOL_VERSION,
)
from opentelemetry.semconv.attributes.server_attributes import (
SERVER_ADDRESS,
SERVER_PORT,
)
from opentelemetry.semconv.attributes.url_attributes import (
URL_PATH,
URL_QUERY,
URL_SCHEME,
)
from opentelemetry.semconv.attributes.user_agent_attributes import (
USER_AGENT_ORIGINAL,
)
from opentelemetry.test.asgitestutil import (
AsyncAsgiTestBase,
setup_testing_defaults,
)
from opentelemetry.test.test_base import TestBase
from opentelemetry.trace import SpanKind, format_span_id, format_trace_id
_expected_metric_names_old = [
"http.server.active_requests",
"http.server.duration",
"http.server.response.size",
"http.server.request.size",
]
_expected_metric_names_new = [
"http.server.active_requests",
"http.server.request.duration",
"http.server.response.body.size",
"http.server.request.body.size",
]
_expected_metric_names_both = _expected_metric_names_old
_expected_metric_names_both.extend(_expected_metric_names_new)
_recommended_attrs_old = {
"http.server.active_requests": _server_active_requests_count_attrs_old,
"http.server.duration": _server_duration_attrs_old,
"http.server.response.size": _server_duration_attrs_old,
"http.server.request.size": _server_duration_attrs_old,
}
_recommended_attrs_new = {
"http.server.active_requests": _server_active_requests_count_attrs_new,
"http.server.request.duration": _server_duration_attrs_new,
"http.server.response.body.size": _server_duration_attrs_new,
"http.server.request.body.size": _server_duration_attrs_new,
}
_recommended_attrs_both = _recommended_attrs_old.copy()
_recommended_attrs_both.update(_recommended_attrs_new)
_recommended_attrs_both["http.server.active_requests"].extend(_server_active_requests_count_attrs_old)
_SIMULATED_BACKGROUND_TASK_EXECUTION_TIME_S = 0.01
async def http_app(scope, receive, send):
message = await receive()
scope["headers"] = [(b"content-length", b"128")]
assert scope["type"] == "http"
if message.get("type") == "http.request":
await send(
{
"type": "http.response.start",
"status": 200,
"headers": [
[b"Content-Type", b"text/plain"],
[b"content-length", b"1024"],
],
}
)
await send({"type": "http.response.body", "body": b"*"})
async def websocket_app(scope, receive, send):
assert scope["type"] == "websocket"
while True:
message = await receive()
if message.get("type") == "websocket.connect":
await send({"type": "websocket.accept"})
if message.get("type") == "websocket.receive":
if message.get("text") == "ping":
await send({"type": "websocket.send", "text": "pong"})
if message.get("type") == "websocket.disconnect":
break
async def simple_asgi(scope, receive, send):
assert isinstance(scope, dict)
if scope["type"] == "http":
await http_app(scope, receive, send)
elif scope["type"] == "websocket":
await websocket_app(scope, receive, send)
async def long_response_asgi(scope, receive, send):
assert isinstance(scope, dict)
assert scope["type"] == "http"
message = await receive()
scope["headers"] = [(b"content-length", b"128")]
assert scope["type"] == "http"
if message.get("type") == "http.request":
await send(
{
"type": "http.response.start",
"status": 200,
"headers": [
[b"Content-Type", b"text/plain"],
[b"content-length", b"1024"],
],
}
)
await send({"type": "http.response.body", "body": b"*", "more_body": True})
await send({"type": "http.response.body", "body": b"*", "more_body": True})
await send({"type": "http.response.body", "body": b"*", "more_body": True})
await send({"type": "http.response.body", "body": b"*", "more_body": False})
async def background_execution_asgi(scope, receive, send):
assert isinstance(scope, dict)
assert scope["type"] == "http"
message = await receive()
scope["headers"] = [(b"content-length", b"128")]
assert scope["type"] == "http"
if message.get("type") == "http.request":
await send(
{
"type": "http.response.start",
"status": 200,
"headers": [
[b"Content-Type", b"text/plain"],
[b"content-length", b"1024"],
],
}
)
await send(
{
"type": "http.response.body",
"body": b"*",
}
)
# Record when the background task starts; the server span must already be ended by now.
scope["background_task_start_ns"] = time.time_ns()
time.sleep(_SIMULATED_BACKGROUND_TASK_EXECUTION_TIME_S)
async def background_execution_trailers_asgi(scope, receive, send):
assert isinstance(scope, dict)
assert scope["type"] == "http"
message = await receive()
scope["headers"] = [(b"content-length", b"128")]
assert scope["type"] == "http"
if message.get("type") == "http.request":
await send(
{
"type": "http.response.start",
"status": 200,
"headers": [
[b"Content-Type", b"text/plain"],
[b"content-length", b"1024"],
],
"trailers": True,
}
)
await send({"type": "http.response.body", "body": b"*", "more_body": True})
await send({"type": "http.response.body", "body": b"*", "more_body": False})
await send(
{
"type": "http.response.trailers",
"headers": [
[b"trailer", b"test-trailer"],
],
"more_trailers": True,
}
)
await send(
{
"type": "http.response.trailers",
"headers": [
[b"trailer", b"second-test-trailer"],
],
"more_trailers": False,
}
)
# Record when the background task starts; the server span must already be ended by now.
scope["background_task_start_ns"] = time.time_ns()
time.sleep(_SIMULATED_BACKGROUND_TASK_EXECUTION_TIME_S)
async def error_asgi(scope, receive, send):
assert isinstance(scope, dict)
assert scope["type"] == "http"
message = await receive()
scope["headers"] = [(b"content-length", b"128")]
if message.get("type") == "http.request":
try:
raise ValueError
except ValueError:
scope["hack_exc_info"] = sys.exc_info()
await send(
{
"type": "http.response.start",
"status": 200,
"headers": [
[b"Content-Type", b"text/plain"],
[b"content-length", b"1024"],
],
}
)
await send({"type": "http.response.body", "body": b"*"})
class UnhandledException(Exception):
pass
def failing_hook(msg):
def hook(*_):
raise UnhandledException(msg)
return hook
SCOPE = "opentelemetry.instrumentation.asgi"
# pylint: disable=too-many-public-methods
class TestAsgiApplication(AsyncAsgiTestBase):
def setUp(self):
super().setUp()
test_name = ""
if hasattr(self, "_testMethodName"):
test_name = self._testMethodName
sem_conv_mode = "default"
if "new_semconv" in test_name:
sem_conv_mode = "http"
elif "both_semconv" in test_name:
sem_conv_mode = "http/dup"
self.env_patch = mock.patch.dict(
"os.environ",
{
OTEL_SEMCONV_STABILITY_OPT_IN: sem_conv_mode,
},
)
_OpenTelemetrySemanticConventionStability._initialized = False
self.env_patch.start()
def tearDown(self):
self.env_patch.stop()
super().tearDown()
def subTest(self, msg=..., **params):
sub = super().subTest(msg, **params)
self.memory_exporter.clear()
return sub
# Helper to assert exemplars presence across specified histogram metric names.
def _assert_exemplars_present(self, metric_names: set[str], context: str = ""):
metrics = self.get_sorted_metrics(SCOPE)
found = {name: 0 for name in metric_names}
for metric in metrics:
if metric.name not in metric_names:
continue
for point in metric.data.data_points:
found[metric.name] += 1
exemplars = getattr(point, "exemplars", None)
self.assertIsNotNone(
exemplars,
msg=f"Expected exemplars list attribute on histogram data point for {metric.name} ({context})",
)
self.assertGreater(
len(exemplars or []),
0,
msg=f"Expected at least one exemplar on histogram data point for {metric.name} ({context}) but none found.",
)
for ex in exemplars or []:
if hasattr(ex, "span_id"):
self.assertNotEqual(ex.span_id, 0)
if hasattr(ex, "trace_id"):
self.assertNotEqual(ex.trace_id, 0)
for name, count in found.items():
self.assertGreater(
count,
0,
msg=f"Did not encounter any data points for metric {name} while checking exemplars ({context}).",
)
# pylint: disable=too-many-locals
def validate_outputs(
self,
outputs,
error=None,
modifiers=None,
old_sem_conv=True,
new_sem_conv=False,
):
# Ensure modifiers is a list
modifiers = modifiers or []
# Check for expected outputs
self.assertTrue(outputs, "ASGI application produced no response messages")
response_start = outputs[0]
response_final_body = [output for output in outputs if output["type"] == "http.response.body"][-1]
self.assertEqual(response_start["type"], "http.response.start")
self.assertEqual(response_final_body["type"], "http.response.body")
self.assertEqual(response_final_body.get("more_body", False), False)
# Check http response body
self.assertEqual(response_final_body["body"], b"*")
# Check http response start
self.assertEqual(response_start["status"], 200)
self.assertEqual(
response_start["headers"],
[[b"Content-Type", b"text/plain"], [b"content-length", b"1024"]],
)
exc_info = self.scope.get("hack_exc_info")
if error:
self.assertIs(exc_info[0], error)
self.assertIsInstance(exc_info[1], error)
self.assertIsNotNone(exc_info[2])
else:
self.assertIsNone(exc_info)
# Check spans
span_list = self.get_finished_spans()
expected_old = [
{
"name": "GET / http receive",
"kind": trace_api.SpanKind.INTERNAL,
"attributes": {"asgi.event.type": "http.request"},
},
{
"name": "GET / http send",
"kind": trace_api.SpanKind.INTERNAL,
"attributes": {
HTTP_STATUS_CODE: 200,
"asgi.event.type": "http.response.start",
},
},
{
"name": "GET / http send",
"kind": trace_api.SpanKind.INTERNAL,
"attributes": {"asgi.event.type": "http.response.body"},
},
{
"name": "GET /",
"kind": trace_api.SpanKind.SERVER,
"attributes": {
HTTP_METHOD: "GET",
HTTP_SCHEME: "http",
NET_HOST_PORT: 80,
HTTP_HOST: "127.0.0.1",
HTTP_FLAVOR: "1.0",
HTTP_TARGET: "/",
HTTP_URL: "http://127.0.0.1/",
NET_PEER_IP: "127.0.0.1",
NET_PEER_PORT: 32767,
HTTP_STATUS_CODE: 200,
},
},
]
expected_new = [
{
"name": "GET / http receive",
"kind": trace_api.SpanKind.INTERNAL,
"attributes": {"asgi.event.type": "http.request"},
},
{
"name": "GET / http send",
"kind": trace_api.SpanKind.INTERNAL,
"attributes": {
HTTP_RESPONSE_STATUS_CODE: 200,
"asgi.event.type": "http.response.start",
},
},
{
"name": "GET / http send",
"kind": trace_api.SpanKind.INTERNAL,
"attributes": {"asgi.event.type": "http.response.body"},
},
{
"name": "GET /",
"kind": trace_api.SpanKind.SERVER,
"attributes": {
HTTP_REQUEST_METHOD: "GET",
URL_SCHEME: "http",
SERVER_ADDRESS: "127.0.0.1",
SERVER_PORT: 80,
NETWORK_PROTOCOL_VERSION: "1.0",
URL_PATH: "/",
CLIENT_ADDRESS: "127.0.0.1",
CLIENT_PORT: 32767,
HTTP_RESPONSE_STATUS_CODE: 200,
},
},
]
expected_both = [
{
"name": "GET / http receive",
"kind": trace_api.SpanKind.INTERNAL,
"attributes": {"asgi.event.type": "http.request"},
},
{
"name": "GET / http send",
"kind": trace_api.SpanKind.INTERNAL,
"attributes": {
HTTP_STATUS_CODE: 200,
HTTP_RESPONSE_STATUS_CODE: 200,
"asgi.event.type": "http.response.start",
},
},
{
"name": "GET / http send",
"kind": trace_api.SpanKind.INTERNAL,
"attributes": {"asgi.event.type": "http.response.body"},
},
{
"name": "GET /",
"kind": trace_api.SpanKind.SERVER,
"attributes": {
HTTP_REQUEST_METHOD: "GET",
URL_SCHEME: "http",
SERVER_ADDRESS: "127.0.0.1",
SERVER_PORT: 80,
NETWORK_PROTOCOL_VERSION: "1.0",
URL_PATH: "/",
CLIENT_ADDRESS: "127.0.0.1",
CLIENT_PORT: 32767,
HTTP_RESPONSE_STATUS_CODE: 200,
HTTP_METHOD: "GET",
HTTP_SCHEME: "http",
NET_HOST_PORT: 80,
HTTP_HOST: "127.0.0.1",
HTTP_FLAVOR: "1.0",
HTTP_TARGET: "/",
HTTP_URL: "http://127.0.0.1/",
NET_PEER_IP: "127.0.0.1",
NET_PEER_PORT: 32767,
HTTP_STATUS_CODE: 200,
},
},
]
expected = expected_old
if new_sem_conv:
if old_sem_conv:
expected = expected_both
else:
expected = expected_new
# Run our expected modifiers
for modifier in modifiers:
expected = modifier(expected)
# Check that output matches
self.assertEqual(len(span_list), len(expected))
for span, expected in zip(span_list, expected):
self.assertEqual(span.name, expected["name"])
self.assertEqual(span.kind, expected["kind"])
self.assertDictEqual(dict(span.attributes), expected["attributes"])
self.assertEqual(
span.instrumentation_scope.name,
SCOPE,
)
if "events" in expected:
self.assertEqual(len(span.events), len(expected["events"]))
for event, expected in zip(span.events, expected["events"]):
self.assertEqual(event.name, expected["name"])
for name, value in expected["attributes"].items():
self.assertEqual(event.attributes[name], value)
async def test_basic_asgi_call(self):
"""Test that spans are emitted as expected."""
app = otel_asgi.OpenTelemetryMiddleware(simple_asgi)
self.seed_app(app)
await self.send_default_request()
outputs = await self.get_all_output()
self.validate_outputs(outputs)
async def test_basic_asgi_call_new_semconv(self):
"""Test that spans are emitted as expected."""
app = otel_asgi.OpenTelemetryMiddleware(simple_asgi)
self.seed_app(app)
await self.send_default_request()
outputs = await self.get_all_output()
self.validate_outputs(outputs, old_sem_conv=False, new_sem_conv=True)
async def test_basic_asgi_call_both_semconv(self):
"""Test that spans are emitted as expected."""
app = otel_asgi.OpenTelemetryMiddleware(simple_asgi)
self.seed_app(app)
await self.send_default_request()
outputs = await self.get_all_output()
self.validate_outputs(outputs, old_sem_conv=True, new_sem_conv=True)
async def test_asgi_not_recording(self):
mock_tracer = mock.Mock()
mock_span = mock.Mock()
mock_span.is_recording.return_value = False
mock_tracer.start_as_current_span.return_value = mock_span
mock_tracer.start_as_current_span.return_value.__enter__ = mock.Mock(return_value=mock_span)
mock_tracer.start_as_current_span.return_value.__exit__ = mock_span
with mock.patch("opentelemetry.trace.get_tracer") as tracer:
tracer.return_value = mock_tracer
app = otel_asgi.OpenTelemetryMiddleware(simple_asgi)
self.seed_app(app)
await self.send_default_request()
self.assertFalse(mock_span.is_recording())
self.assertTrue(mock_span.is_recording.called)
self.assertFalse(mock_span.set_attribute.called)
self.assertFalse(mock_span.set_status.called)
async def test_asgi_exc_info(self):
"""Test that exception information is emitted as expected."""
app = otel_asgi.OpenTelemetryMiddleware(error_asgi)
self.seed_app(app)
await self.send_default_request()
outputs = await self.get_all_output()
self.validate_outputs(outputs, error=ValueError)
async def test_long_response(self):
"""Test that the server span is ended on the final response body message.
If the server span is ended early then this test will fail due
to discrepancies in the expected list of spans and the emitted list of spans.
"""
app = otel_asgi.OpenTelemetryMiddleware(long_response_asgi)
self.seed_app(app)
await self.send_default_request()
outputs = await self.get_all_output()
def add_more_body_spans(expected: list):
more_body_span = {
"name": "GET / http send",
"kind": trace_api.SpanKind.INTERNAL,
"attributes": {"asgi.event.type": "http.response.body"},
}
extra_spans = [more_body_span] * 3
expected[2:2] = extra_spans
return expected
self.validate_outputs(outputs, modifiers=[add_more_body_spans])
async def test_background_execution(self):
"""Test that the server span is ended BEFORE the background task is finished."""
app = otel_asgi.OpenTelemetryMiddleware(background_execution_asgi)
self.seed_app(app)
await self.send_default_request()
outputs = await self.get_all_output()
self.validate_outputs(outputs)
span_list = self.get_finished_spans()
server_span = span_list[-1]
assert server_span.kind == SpanKind.SERVER
self.assertLessEqual(
server_span.end_time,
self.scope["background_task_start_ns"],
)
async def test_exclude_internal_spans(self):
"""Test that internal spans are excluded from the emitted spans when
the `exclude_receive_span` or `exclude_send_span` attributes are set.
"""
cases = [
(["receive", "send"], ["GET / http receive", "GET / http send"]),
(["send"], ["GET / http send"]),
(["receive"], ["GET / http receive"]),
([], []),
]
for exclude_spans, excluded_spans in cases:
self.memory_exporter.clear()
app = otel_asgi.OpenTelemetryMiddleware(simple_asgi, exclude_spans=exclude_spans)
self.seed_app(app)
await self.send_default_request()
await self.get_all_output()
span_list = self.get_finished_spans()
self.assertTrue(span_list)
for span in span_list:
for excluded_span in excluded_spans:
self.assertNotEqual(span.name, excluded_span)
async def test_trailers(self):
"""Test that trailers are emitted as expected and that the server span is ended
BEFORE the background task is finished."""
app = otel_asgi.OpenTelemetryMiddleware(background_execution_trailers_asgi)
self.seed_app(app)
await self.send_default_request()
outputs = await self.get_all_output()
def add_body_and_trailer_span(expected: list):
body_span = {
"name": "GET / http send",
"kind": trace_api.SpanKind.INTERNAL,
"attributes": {"asgi.event.type": "http.response.body"},
}
trailer_span = {
"name": "GET / http send",
"kind": trace_api.SpanKind.INTERNAL,
"attributes": {"asgi.event.type": "http.response.trailers"},
}
expected[2:2] = [body_span]
expected[4:4] = [trailer_span] * 2
return expected
self.validate_outputs(outputs, modifiers=[add_body_and_trailer_span])
span_list = self.get_finished_spans()
server_span = span_list[-1]
assert server_span.kind == SpanKind.SERVER
self.assertLessEqual(
server_span.end_time,
self.scope["background_task_start_ns"],
)
async def test_override_span_name(self):
"""Test that default span_names can be overwritten by our callback function."""
span_name = "Dymaxion"
def get_predefined_span_details(_):
return span_name, {}
def update_expected_span_name(expected):
for entry in expected:
if entry["kind"] == trace_api.SpanKind.SERVER:
entry["name"] = span_name
else:
entry["name"] = " ".join([span_name] + entry["name"].split(" ")[2:])
return expected
app = otel_asgi.OpenTelemetryMiddleware(simple_asgi, default_span_details=get_predefined_span_details)
self.seed_app(app)
await self.send_default_request()
outputs = await self.get_all_output()
self.validate_outputs(outputs, modifiers=[update_expected_span_name])
async def test_custom_tracer_provider_otel_asgi(self):
resource = resources.Resource.create({"service-test-key": "value"})
result = TestBase.create_tracer_provider(resource=resource)
tracer_provider, exporter = result
app = otel_asgi.OpenTelemetryMiddleware(simple_asgi, tracer_provider=tracer_provider)
self.seed_app(app)
await self.send_default_request()
span_list = exporter.get_finished_spans()
for span in span_list:
self.assertEqual(span.resource.attributes["service-test-key"], "value")
async def test_no_op_tracer_provider_otel_asgi(self):
app = otel_asgi.OpenTelemetryMiddleware(simple_asgi, tracer_provider=trace_api.NoOpTracerProvider())
self.seed_app(app)
await self.send_default_request()
response_start, response_body, *_ = await self.get_all_output()
self.assertEqual(response_body["body"], b"*")
self.assertEqual(response_start["status"], 200)
span_list = self.get_finished_spans()
self.assertEqual(len(span_list), 0)
async def test_behavior_with_scope_server_as_none(self):
"""Test that middleware is ok when server is none in scope."""
def update_expected_server(expected):
expected[3]["attributes"].update(
{
HTTP_HOST: "0.0.0.0",
NET_HOST_PORT: 80,
HTTP_URL: "http://0.0.0.0/",
}
)
return expected
self.scope["server"] = None
app = otel_asgi.OpenTelemetryMiddleware(simple_asgi)
self.seed_app(app)
await self.send_default_request()
outputs = await self.get_all_output()
self.validate_outputs(outputs, modifiers=[update_expected_server])
async def test_behavior_with_scope_server_as_none_new_semconv(self):
"""Test that middleware is ok when server is none in scope."""
def update_expected_server(expected):
expected[3]["attributes"].update(
{
SERVER_ADDRESS: "0.0.0.0",
SERVER_PORT: 80,
}
)
return expected
self.scope["server"] = None
app = otel_asgi.OpenTelemetryMiddleware(simple_asgi)
self.seed_app(app)
await self.send_default_request()
outputs = await self.get_all_output()
self.validate_outputs(
outputs,
modifiers=[update_expected_server],
old_sem_conv=False,
new_sem_conv=True,
)
async def test_behavior_with_scope_server_as_none_both_semconv(self):
"""Test that middleware is ok when server is none in scope."""
def update_expected_server(expected):
expected[3]["attributes"].update(
{
HTTP_HOST: "0.0.0.0",
NET_HOST_PORT: 80,
HTTP_URL: "http://0.0.0.0/",
SERVER_ADDRESS: "0.0.0.0",
SERVER_PORT: 80,
}
)
return expected
self.scope["server"] = None
app = otel_asgi.OpenTelemetryMiddleware(simple_asgi)
self.seed_app(app)
await self.send_default_request()
outputs = await self.get_all_output()
self.validate_outputs(
outputs,
modifiers=[update_expected_server],
old_sem_conv=True,
new_sem_conv=True,
)
async def test_host_header(self):
"""Test that host header is converted to http.server_name."""
hostname = b"server_name_1"
def update_expected_server(expected):
expected[3]["attributes"].update(
{
HTTP_SERVER_NAME: hostname.decode("utf8"),
HTTP_URL: f"http://{hostname.decode('utf8')}/",
}
)
return expected
self.scope["headers"].append([b"host", hostname])
app = otel_asgi.OpenTelemetryMiddleware(simple_asgi)
self.seed_app(app)
await self.send_default_request()
outputs = await self.get_all_output()
self.validate_outputs(outputs, modifiers=[update_expected_server])
async def test_host_header_both_semconv(self):
"""Test that host header is converted to http.server_name."""
hostname = b"server_name_1"
def update_expected_server(expected):
expected[3]["attributes"].update(
{
HTTP_SERVER_NAME: hostname.decode("utf8"),
HTTP_URL: f"http://{hostname.decode('utf8')}/",
}
)
return expected
self.scope["headers"].append([b"host", hostname])
app = otel_asgi.OpenTelemetryMiddleware(simple_asgi)
self.seed_app(app)
await self.send_default_request()
outputs = await self.get_all_output()
self.validate_outputs(
outputs,
modifiers=[update_expected_server],
old_sem_conv=True,
new_sem_conv=True,
)
async def test_user_agent(self):
"""Test that host header is converted to http.server_name."""
user_agent = b"test-agent"
def update_expected_user_agent(expected):
expected[3]["attributes"].update({HTTP_USER_AGENT: user_agent.decode("utf8")})
return expected
self.scope["headers"].append([b"user-agent", user_agent])
app = otel_asgi.OpenTelemetryMiddleware(simple_asgi)
self.seed_app(app)
await self.send_default_request()
outputs = await self.get_all_output()
self.validate_outputs(outputs, modifiers=[update_expected_user_agent])
async def test_user_agent_new_semconv(self):
"""Test that host header is converted to http.server_name."""
user_agent = b"test-agent"
def update_expected_user_agent(expected):
expected[3]["attributes"].update({USER_AGENT_ORIGINAL: user_agent.decode("utf8")})
return expected
self.scope["headers"].append([b"user-agent", user_agent])
app = otel_asgi.OpenTelemetryMiddleware(simple_asgi)
self.seed_app(app)
await self.send_default_request()
outputs = await self.get_all_output()
self.validate_outputs(
outputs,
modifiers=[update_expected_user_agent],
old_sem_conv=False,
new_sem_conv=True,
)
async def test_user_agent_both_semconv(self):
"""Test that host header is converted to http.server_name."""
user_agent = b"test-agent"
def update_expected_user_agent(expected):
expected[3]["attributes"].update(
{
HTTP_USER_AGENT: user_agent.decode("utf8"),
USER_AGENT_ORIGINAL: user_agent.decode("utf8"),
}
)
return expected
self.scope["headers"].append([b"user-agent", user_agent])
app = otel_asgi.OpenTelemetryMiddleware(simple_asgi)
self.seed_app(app)
await self.send_default_request()
await self.communicator.wait()
outputs = await self.get_all_output()
self.validate_outputs(
outputs,
modifiers=[update_expected_user_agent],
old_sem_conv=True,
new_sem_conv=True,
)
async def test_user_agent_synthetic_bot_detection(self):
"""Test that bot user agents are detected as synthetic with type 'bot'"""
test_cases = [
b"Mozilla/5.0 (compatible; Googlebot/2.1; +http://www.google.com/bot.html)",
b"Mozilla/5.0 (compatible; bingbot/2.0; +http://www.bing.com/bingbot.htm)",
b"googlebot/1.0",
b"bingbot/1.0",
]
# Test each user agent case separately to avoid span accumulation
for user_agent in test_cases:
with self.subTest(user_agent=user_agent):
# Clear headers first
self.scope["headers"] = []
def update_expected_synthetic_bot(expected, ua: bytes = user_agent):
expected[3]["attributes"].update(
{
HTTP_USER_AGENT: ua.decode("utf8"),
USER_AGENT_SYNTHETIC_TYPE: "bot",
}
)
return expected
self.scope["headers"].append([b"user-agent", user_agent])
app = otel_asgi.OpenTelemetryMiddleware(simple_asgi)
self.seed_app(app)
await self.send_default_request()
outputs = await self.get_all_output()
self.validate_outputs(outputs, modifiers=[update_expected_synthetic_bot])
async def test_user_agent_synthetic_test_detection(self):
"""Test that test user agents are detected as synthetic with type 'test'"""
test_cases = [
b"alwayson/1.0",
b"AlwaysOn/2.0",
b"test-alwayson-client",
]
# Test each user agent case separately to avoid span accumulation
for user_agent in test_cases:
with self.subTest(user_agent=user_agent):
# Clear headers first
self.scope["headers"] = []
def update_expected_synthetic_test(expected, ua: bytes = user_agent):
expected[3]["attributes"].update(
{
HTTP_USER_AGENT: ua.decode("utf8"),
USER_AGENT_SYNTHETIC_TYPE: "test",
}
)
return expected
self.scope["headers"].append([b"user-agent", user_agent])
app = otel_asgi.OpenTelemetryMiddleware(simple_asgi)
self.seed_app(app)
await self.send_default_request()
outputs = await self.get_all_output()
self.validate_outputs(outputs, modifiers=[update_expected_synthetic_test])
async def test_user_agent_non_synthetic(self):
"""Test that normal user agents are not marked as synthetic"""
test_cases = [
b"Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.124 Safari/537.36",
b"Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/605.1.15 (KHTML, like Gecko) Version/14.1.1 Safari/605.1.15",
b"PostmanRuntime/7.28.4",
b"curl/7.68.0",
]
# Test each user agent case separately to avoid span accumulation
for user_agent in test_cases:
with self.subTest(user_agent=user_agent):
# Clear headers first
self.scope["headers"] = []
def update_expected_non_synthetic(expected, ua: bytes = user_agent):
# Should only have the user agent, not synthetic type
expected[3]["attributes"].update(
{
HTTP_USER_AGENT: ua.decode("utf8"),
}
)
return expected
self.scope["headers"].append([b"user-agent", user_agent])
app = otel_asgi.OpenTelemetryMiddleware(simple_asgi)
self.seed_app(app)
await self.send_default_request()
outputs = await self.get_all_output()
self.validate_outputs(outputs, modifiers=[update_expected_non_synthetic])
async def test_user_agent_synthetic_new_semconv(self):
"""Test synthetic user agent detection with new semantic conventions"""
user_agent = b"Mozilla/5.0 (compatible; Googlebot/2.1)"
def update_expected_synthetic_new_semconv(expected):
expected[3]["attributes"].update(
{
USER_AGENT_ORIGINAL: user_agent.decode("utf8"),
USER_AGENT_SYNTHETIC_TYPE: "bot",
}
)
return expected
self.scope["headers"] = []
self.scope["headers"].append([b"user-agent", user_agent])
app = otel_asgi.OpenTelemetryMiddleware(simple_asgi)
self.seed_app(app)
await self.send_default_request()
outputs = await self.get_all_output()
self.validate_outputs(
outputs,
modifiers=[update_expected_synthetic_new_semconv],
old_sem_conv=False,
new_sem_conv=True,
)
async def test_traceresponse_header(self):
"""Test a traceresponse header is sent when a global propagator is set."""
orig = get_global_response_propagator()
set_global_response_propagator(TraceResponsePropagator())
app = otel_asgi.OpenTelemetryMiddleware(simple_asgi)
self.seed_app(app)
await self.send_default_request()
response_start, response_body, *_ = await self.get_all_output()
span = self.get_finished_spans()[-1]
self.assertEqual(trace_api.SpanKind.SERVER, span.kind)
self.assertEqual(response_body["body"], b"*")
self.assertEqual(response_start["status"], 200)
trace_id = format_trace_id(span.get_span_context().trace_id)
span_id = format_span_id(span.get_span_context().span_id)
trace_flags = span.get_span_context().trace_flags
traceresponse = f"00-{trace_id}-{span_id}-{trace_flags:02x}"
self.assertListEqual(
response_start["headers"],
[
[b"Content-Type", b"text/plain"],
[b"content-length", b"1024"],
[b"traceresponse", f"{traceresponse}".encode()],
[b"access-control-expose-headers", b"traceresponse"],
],
)
set_global_response_propagator(orig)
async def test_websocket(self):
self.scope = {
"method": "GET",
"type": "websocket",
"http_version": "1.1",
"scheme": "ws",
"path": "/",
"query_string": b"",
"headers": [],
"client": ("127.0.0.1", 32767),
"server": ("127.0.0.1", 80),
}
app = otel_asgi.OpenTelemetryMiddleware(simple_asgi)
self.seed_app(app)
await self.send_input({"type": "websocket.connect"})
await self.send_input({"type": "websocket.receive", "text": "ping"})
await self.send_input({"type": "websocket.disconnect"})
await self.get_all_output()
span_list = self.get_finished_spans()
self.assertEqual(len(span_list), 6)
expected = [
{
"name": "GET / websocket receive",
"kind": trace_api.SpanKind.INTERNAL,
"attributes": {"asgi.event.type": "websocket.connect"},
},
{
"name": "GET / websocket send",
"kind": trace_api.SpanKind.INTERNAL,
"attributes": {"asgi.event.type": "websocket.accept"},
},
{
"name": "GET / websocket receive",
"kind": trace_api.SpanKind.INTERNAL,
"attributes": {
"asgi.event.type": "websocket.receive",
HTTP_STATUS_CODE: 200,
},
},
{
"name": "GET / websocket send",
"kind": trace_api.SpanKind.INTERNAL,
"attributes": {
"asgi.event.type": "websocket.send",
HTTP_STATUS_CODE: 200,
},
},
{
"name": "GET / websocket receive",
"kind": trace_api.SpanKind.INTERNAL,
"attributes": {"asgi.event.type": "websocket.disconnect"},
},
{
"name": "GET /",
"kind": trace_api.SpanKind.SERVER,
"attributes": {
HTTP_SCHEME: self.scope["scheme"],
NET_HOST_PORT: self.scope["server"][1],
HTTP_HOST: self.scope["server"][0],
HTTP_FLAVOR: self.scope["http_version"],
HTTP_TARGET: self.scope["path"],
HTTP_URL: f"{self.scope['scheme']}://{self.scope['server'][0]}{self.scope['path']}",
NET_PEER_IP: self.scope["client"][0],
NET_PEER_PORT: self.scope["client"][1],
HTTP_STATUS_CODE: 200,
HTTP_METHOD: self.scope["method"],
},
},
]
for span, expected in zip(span_list, expected):
self.assertEqual(span.name, expected["name"])
self.assertEqual(span.kind, expected["kind"])
self.assertDictEqual(dict(span.attributes), expected["attributes"])
async def test_websocket_new_semconv(self):
self.scope = {
"method": "GET",
"type": "websocket",
"http_version": "1.1",
"scheme": "ws",
"path": "/",
"query_string": b"",
"headers": [],
"client": ("127.0.0.1", 32767),
"server": ("127.0.0.1", 80),
}
app = otel_asgi.OpenTelemetryMiddleware(simple_asgi)
self.seed_app(app)
await self.send_input({"type": "websocket.connect"})
await self.send_input({"type": "websocket.receive", "text": "ping"})
await self.send_input({"type": "websocket.disconnect"})
await self.get_all_output()
span_list = self.get_finished_spans()
self.assertEqual(len(span_list), 6)
expected = [
{
"name": "GET / websocket receive",
"kind": trace_api.SpanKind.INTERNAL,
"attributes": {"asgi.event.type": "websocket.connect"},
},
{
"name": "GET / websocket send",
"kind": trace_api.SpanKind.INTERNAL,
"attributes": {"asgi.event.type": "websocket.accept"},
},
{
"name": "GET / websocket receive",
"kind": trace_api.SpanKind.INTERNAL,
"attributes": {
"asgi.event.type": "websocket.receive",
HTTP_RESPONSE_STATUS_CODE: 200,
},
},
{
"name": "GET / websocket send",
"kind": trace_api.SpanKind.INTERNAL,
"attributes": {
"asgi.event.type": "websocket.send",
HTTP_RESPONSE_STATUS_CODE: 200,
},
},
{
"name": "GET / websocket receive",
"kind": trace_api.SpanKind.INTERNAL,
"attributes": {"asgi.event.type": "websocket.disconnect"},
},
{
"name": "GET /",
"kind": trace_api.SpanKind.SERVER,
"attributes": {
URL_SCHEME: self.scope["scheme"],
SERVER_ADDRESS: self.scope["server"][0],
SERVER_PORT: self.scope["server"][1],
NETWORK_PROTOCOL_VERSION: self.scope["http_version"],
URL_PATH: self.scope["path"],
CLIENT_ADDRESS: self.scope["client"][0],
CLIENT_PORT: self.scope["client"][1],
HTTP_RESPONSE_STATUS_CODE: 200,
HTTP_REQUEST_METHOD: self.scope["method"],
},
},
]
for span, expected in zip(span_list, expected):
self.assertEqual(span.name, expected["name"])
self.assertEqual(span.kind, expected["kind"])
self.assertDictEqual(dict(span.attributes), expected["attributes"])
async def test_websocket_both_semconv(self):
self.scope = {
"method": "GET",
"type": "websocket",
"http_version": "1.1",
"scheme": "ws",
"path": "/",
"query_string": b"",
"headers": [],
"client": ("127.0.0.1", 32767),
"server": ("127.0.0.1", 80),
}
app = otel_asgi.OpenTelemetryMiddleware(simple_asgi)
self.seed_app(app)
await self.send_input({"type": "websocket.connect"})
await self.send_input({"type": "websocket.receive", "text": "ping"})
await self.send_input({"type": "websocket.disconnect"})
await self.get_all_output()
span_list = self.get_finished_spans()
self.assertEqual(len(span_list), 6)
expected = [
{
"name": "GET / websocket receive",
"kind": trace_api.SpanKind.INTERNAL,
"attributes": {"asgi.event.type": "websocket.connect"},
},
{
"name": "GET / websocket send",
"kind": trace_api.SpanKind.INTERNAL,
"attributes": {"asgi.event.type": "websocket.accept"},
},
{
"name": "GET / websocket receive",
"kind": trace_api.SpanKind.INTERNAL,
"attributes": {
"asgi.event.type": "websocket.receive",
HTTP_RESPONSE_STATUS_CODE: 200,
HTTP_STATUS_CODE: 200,
},
},
{
"name": "GET / websocket send",
"kind": trace_api.SpanKind.INTERNAL,
"attributes": {
"asgi.event.type": "websocket.send",
HTTP_RESPONSE_STATUS_CODE: 200,
HTTP_STATUS_CODE: 200,
},
},
{
"name": "GET / websocket receive",
"kind": trace_api.SpanKind.INTERNAL,
"attributes": {"asgi.event.type": "websocket.disconnect"},
},
{
"name": "GET /",
"kind": trace_api.SpanKind.SERVER,
"attributes": {
HTTP_SCHEME: self.scope["scheme"],
NET_HOST_PORT: self.scope["server"][1],
HTTP_HOST: self.scope["server"][0],
HTTP_FLAVOR: self.scope["http_version"],
HTTP_TARGET: self.scope["path"],
HTTP_URL: f"{self.scope['scheme']}://{self.scope['server'][0]}{self.scope['path']}",
NET_PEER_IP: self.scope["client"][0],
NET_PEER_PORT: self.scope["client"][1],
HTTP_STATUS_CODE: 200,
HTTP_METHOD: self.scope["method"],
URL_SCHEME: self.scope["scheme"],
SERVER_ADDRESS: self.scope["server"][0],
SERVER_PORT: self.scope["server"][1],
NETWORK_PROTOCOL_VERSION: self.scope["http_version"],
URL_PATH: self.scope["path"],
CLIENT_ADDRESS: self.scope["client"][0],
CLIENT_PORT: self.scope["client"][1],
HTTP_RESPONSE_STATUS_CODE: 200,
HTTP_REQUEST_METHOD: self.scope["method"],
},
},
]
for span, expected in zip(span_list, expected):
self.assertEqual(span.name, expected["name"])
self.assertEqual(span.kind, expected["kind"])
self.assertDictEqual(dict(span.attributes), expected["attributes"])
async def test_websocket_traceresponse_header(self):
"""Test a traceresponse header is set for websocket messages"""
orig = get_global_response_propagator()
set_global_response_propagator(TraceResponsePropagator())
self.scope = {
"type": "websocket",
"http_version": "1.1",
"scheme": "ws",
"path": "/",
"query_string": b"",
"headers": [],
"client": ("127.0.0.1", 32767),
"server": ("127.0.0.1", 80),
}
app = otel_asgi.OpenTelemetryMiddleware(simple_asgi)
self.seed_app(app)
await self.send_input({"type": "websocket.connect"})
await self.send_input({"type": "websocket.receive", "text": "ping"})
await self.send_input({"type": "websocket.disconnect"})
_, socket_send, *_ = await self.get_all_output()
span = self.get_finished_spans()[-1]
self.assertEqual(trace_api.SpanKind.SERVER, span.kind)
trace_id = format_trace_id(span.get_span_context().trace_id)
span_id = format_span_id(span.get_span_context().span_id)
trace_flags = span.get_span_context().trace_flags
traceresponse = f"00-{trace_id}-{span_id}-{trace_flags:02x}"
self.assertListEqual(
socket_send["headers"],
[
[b"traceresponse", f"{traceresponse}".encode()],
[b"access-control-expose-headers", b"traceresponse"],
],
)
set_global_response_propagator(orig)
async def test_lifespan(self):
self.scope["type"] = "lifespan"
app = otel_asgi.OpenTelemetryMiddleware(simple_asgi)
self.seed_app(app)
await self.send_default_request()
span_list = self.get_finished_spans()
self.assertEqual(len(span_list), 0)
async def test_hooks(self):
def server_request_hook(span, scope):
span.update_name("name from server hook")
def client_request_hook(receive_span, scope, message):
receive_span.update_name("name from client request hook")
def client_response_hook(send_span, scope, message):
send_span.set_attribute("attr-from-hook", "value")
def update_expected_hook_results(expected):
for entry in expected:
if entry["kind"] == trace_api.SpanKind.SERVER:
entry["name"] = "name from server hook"
elif entry["name"] == "GET / http receive":
entry["name"] = "name from client request hook"
elif entry["name"] == "GET / http send":
entry["attributes"].update({"attr-from-hook": "value"})
return expected
app = otel_asgi.OpenTelemetryMiddleware(
simple_asgi,
server_request_hook=server_request_hook,
client_request_hook=client_request_hook,
client_response_hook=client_response_hook,
)
self.seed_app(app)
await self.send_default_request()
outputs = await self.get_all_output()
self.validate_outputs(outputs, modifiers=[update_expected_hook_results])
async def test_hook_exceptions(self):
def exception_event(msg):
return {
"name": "exception",
"attributes": {
"exception.type": f"{__name__}.UnhandledException",
"exception.message": msg,
},
}
def update_expected_hook_results(expected):
for entry in expected:
if entry["kind"] == trace_api.SpanKind.SERVER:
entry["events"] = [exception_event("server request")]
elif entry["name"] == "GET / http receive":
entry["events"] = [exception_event("client request")]
elif entry["name"] == "GET / http send":
entry["events"] = [exception_event("client response")]
return expected
app = otel_asgi.OpenTelemetryMiddleware(
simple_asgi,
server_request_hook=failing_hook("server request"),
client_request_hook=failing_hook("client request"),
client_response_hook=failing_hook("client response"),
)
self.seed_app(app)
await self.send_default_request()
outputs = await self.get_all_output()
self.validate_outputs(outputs, modifiers=[update_expected_hook_results])
async def test_asgi_metrics(self):
app = otel_asgi.OpenTelemetryMiddleware(simple_asgi)
self.seed_app(app)
await self.send_default_request()
await self.get_all_output()
self.seed_app(app)
await self.send_default_request()
await self.get_all_output()
self.seed_app(app)
await self.send_default_request()
await self.get_all_output()
number_data_point_seen = False
histogram_data_point_seen = False
metrics = self.get_sorted_metrics(SCOPE)
self.assertTrue(len(metrics) != 0)
for metric in metrics:
self.assertIn(metric.name, _expected_metric_names_old)
data_points = list(metric.data.data_points)
self.assertEqual(len(data_points), 1)
for point in data_points:
if isinstance(point, HistogramDataPoint):
self.assertEqual(point.count, 3)
histogram_data_point_seen = True
if isinstance(point, NumberDataPoint):
number_data_point_seen = True
for attr in point.attributes:
self.assertIn(attr, _recommended_attrs_old[metric.name])
self.assertTrue(number_data_point_seen and histogram_data_point_seen)
async def test_asgi_metrics_new_semconv(self):
# pylint: disable=too-many-nested-blocks
app = otel_asgi.OpenTelemetryMiddleware(simple_asgi)
self.seed_app(app)
await self.send_default_request()
await self.get_all_output()
self.seed_app(app)
await self.send_default_request()
await self.get_all_output()
self.seed_app(app)
await self.send_default_request()
await self.get_all_output()
number_data_point_seen = False
histogram_data_point_seen = False
metrics = self.get_sorted_metrics(SCOPE)
self.assertTrue(len(metrics) != 0)
for metric in metrics:
self.assertIn(metric.name, _expected_metric_names_new)
data_points = list(metric.data.data_points)
self.assertEqual(len(data_points), 1)
for point in data_points:
if isinstance(point, HistogramDataPoint):
self.assertEqual(point.count, 3)
if metric.name == "http.server.request.duration":
self.assertEqual(
point.explicit_bounds,
HTTP_DURATION_HISTOGRAM_BUCKETS_NEW,
)
histogram_data_point_seen = True
if isinstance(point, NumberDataPoint):
number_data_point_seen = True
for attr in point.attributes:
self.assertIn(attr, _recommended_attrs_new[metric.name])
self.assertTrue(number_data_point_seen and histogram_data_point_seen)
async def test_asgi_metrics_both_semconv(self):
# pylint: disable=too-many-nested-blocks
app = otel_asgi.OpenTelemetryMiddleware(simple_asgi)
self.seed_app(app)
await self.send_default_request()
await self.get_all_output()
self.seed_app(app)
await self.send_default_request()
await self.get_all_output()
self.seed_app(app)
await self.send_default_request()
await self.get_all_output()
number_data_point_seen = False
histogram_data_point_seen = False
metrics = self.get_sorted_metrics(SCOPE)
self.assertTrue(len(metrics) != 0)
for metric in metrics:
self.assertIn(metric.name, _expected_metric_names_both)
data_points = list(metric.data.data_points)
self.assertEqual(len(data_points), 1)
for point in data_points:
if isinstance(point, HistogramDataPoint):
self.assertEqual(point.count, 3)
if metric.name == "http.server.request.duration":
self.assertEqual(
point.explicit_bounds,
HTTP_DURATION_HISTOGRAM_BUCKETS_NEW,
)
histogram_data_point_seen = True
if isinstance(point, NumberDataPoint):
number_data_point_seen = True
for attr in point.attributes:
self.assertIn(attr, _recommended_attrs_both[metric.name])
self.assertTrue(number_data_point_seen and histogram_data_point_seen)
async def test_asgi_metrics_exemplars_expected_old_semconv(self):
"""Failing test placeholder asserting exemplars should be present for duration histogram (old semconv)."""
app = otel_asgi.OpenTelemetryMiddleware(simple_asgi)
for _ in range(5):
self.seed_app(app)
await self.send_default_request()
await self.get_all_output()
self._assert_exemplars_present({"http.server.duration"}, context="old semconv")
async def test_asgi_metrics_exemplars_expected_new_semconv(self):
"""Failing test placeholder asserting exemplars should be present for request duration histogram (new semconv)."""
app = otel_asgi.OpenTelemetryMiddleware(simple_asgi)
for _ in range(5):
self.seed_app(app)
await self.send_default_request()
await self.get_all_output()
self._assert_exemplars_present({"http.server.request.duration"}, context="new semconv")
async def test_asgi_metrics_exemplars_expected_both_semconv(self):
"""Failing test placeholder asserting exemplars should be present for both duration histograms when both semconv modes enabled."""
app = otel_asgi.OpenTelemetryMiddleware(simple_asgi)
for _ in range(5):
self.seed_app(app)
await self.send_default_request()
await self.get_all_output()
self._assert_exemplars_present(
{"http.server.duration", "http.server.request.duration"},
context="both semconv",
)
async def test_basic_metric_success(self):
app = otel_asgi.OpenTelemetryMiddleware(simple_asgi)
self.seed_app(app)
start = default_timer()
await self.send_default_request()
duration = max(round((default_timer() - start) * 1000), 0)
await self.get_all_output()
expected_duration_attributes = {
"http.method": "GET",
"http.host": "127.0.0.1",
"http.scheme": "http",
"http.flavor": "1.0",
"net.host.port": 80,
"http.status_code": 200,
}
expected_requests_count_attributes = {
"http.method": "GET",
"http.host": "127.0.0.1",
"http.scheme": "http",
"http.flavor": "1.0",
}
metrics = self.get_sorted_metrics(SCOPE)
# pylint: disable=too-many-nested-blocks
for metric in metrics:
for point in list(metric.data.data_points):
if isinstance(point, HistogramDataPoint):
self.assertDictEqual(
expected_duration_attributes,
dict(point.attributes),
)
self.assertEqual(point.count, 1)
if metric.name == "http.server.duration":
self.assertAlmostEqual(duration, point.sum, delta=30)
elif metric.name == "http.server.response.size":
self.assertEqual(1024, point.sum)
elif metric.name == "http.server.request.size":
self.assertEqual(128, point.sum)
elif isinstance(point, NumberDataPoint):
self.assertDictEqual(
expected_requests_count_attributes,
dict(point.attributes),
)
self.assertEqual(point.value, 0)
async def test_basic_metric_success_nonrecording_span(self):
mock_tracer = mock.Mock()
mock_span = mock.Mock()
mock_span.is_recording.return_value = False
mock_tracer.start_as_current_span.return_value = mock_span
mock_tracer.start_as_current_span.return_value.__enter__ = mock.Mock(return_value=mock_span)
mock_tracer.start_as_current_span.return_value.__exit__ = mock_span
with mock.patch("opentelemetry.trace.get_tracer") as tracer:
tracer.return_value = mock_tracer
app = otel_asgi.OpenTelemetryMiddleware(simple_asgi)
self.seed_app(app)
start = default_timer()
await self.send_default_request()
duration = max(round((default_timer() - start) * 1000), 0)
await self.get_all_output()
expected_duration_attributes = {
"http.method": "GET",
"http.host": "127.0.0.1",
"http.scheme": "http",
"http.flavor": "1.0",
"net.host.port": 80,
"http.status_code": 200,
}
expected_requests_count_attributes = {
"http.method": "GET",
"http.host": "127.0.0.1",
"http.scheme": "http",
"http.flavor": "1.0",
}
metrics = self.get_sorted_metrics(SCOPE)
# pylint: disable=too-many-nested-blocks
for metric in metrics:
for point in list(metric.data.data_points):
if isinstance(point, HistogramDataPoint):
self.assertDictEqual(
expected_duration_attributes,
dict(point.attributes),
)
self.assertEqual(point.count, 1)
if metric.name == "http.server.duration":
self.assertAlmostEqual(duration, point.sum, delta=15)
elif metric.name == "http.server.response.size":
self.assertEqual(1024, point.sum)
elif metric.name == "http.server.request.size":
self.assertEqual(128, point.sum)
elif isinstance(point, NumberDataPoint):
self.assertDictEqual(
expected_requests_count_attributes,
dict(point.attributes),
)
self.assertEqual(point.value, 0)
async def test_basic_metric_success_new_semconv(self):
app = otel_asgi.OpenTelemetryMiddleware(simple_asgi)
self.seed_app(app)
start = default_timer()
await self.send_default_request()
duration_s = max(default_timer() - start, 0)
await self.get_all_output()
expected_duration_attributes = {
"http.request.method": "GET",
"url.scheme": "http",
"network.protocol.version": "1.0",
"http.response.status_code": 200,
}
expected_requests_count_attributes = {
"http.request.method": "GET",
"url.scheme": "http",
}
metrics = self.get_sorted_metrics(SCOPE)
# pylint: disable=too-many-nested-blocks
for metric in metrics:
for point in list(metric.data.data_points):
if isinstance(point, HistogramDataPoint):
self.assertDictEqual(
expected_duration_attributes,
dict(point.attributes),
)
self.assertEqual(point.count, 1)
if metric.name == "http.server.request.duration":
self.assertAlmostEqual(duration_s, point.sum, places=2)
elif metric.name == "http.server.response.body.size":
self.assertEqual(1024, point.sum)
elif metric.name == "http.server.request.body.size":
self.assertEqual(128, point.sum)
elif isinstance(point, NumberDataPoint):
self.assertDictEqual(
expected_requests_count_attributes,
dict(point.attributes),
)
self.assertEqual(point.value, 0)
async def test_basic_metric_success_both_semconv(self):
app = otel_asgi.OpenTelemetryMiddleware(simple_asgi)
self.seed_app(app)
start = default_timer()
await self.send_default_request()
duration = max(round((default_timer() - start) * 1000), 0)
duration_s = max(default_timer() - start, 0)
await self.get_all_output()
expected_duration_attributes_old = {
"http.method": "GET",
"http.host": "127.0.0.1",
"http.scheme": "http",
"http.flavor": "1.0",
"net.host.port": 80,
"http.status_code": 200,
}
expected_requests_count_attributes = {
"http.method": "GET",
"http.host": "127.0.0.1",
"http.scheme": "http",
"http.flavor": "1.0",
"http.request.method": "GET",
"url.scheme": "http",
}
expected_duration_attributes_new = {
"http.request.method": "GET",
"url.scheme": "http",
"network.protocol.version": "1.0",
"http.response.status_code": 200,
}
metrics = self.get_sorted_metrics(SCOPE)
# pylint: disable=too-many-nested-blocks
for metric in metrics:
for point in list(metric.data.data_points):
if isinstance(point, HistogramDataPoint):
self.assertEqual(point.count, 1)
if metric.name == "http.server.request.duration":
self.assertAlmostEqual(duration_s, point.sum, places=2)
self.assertDictEqual(
expected_duration_attributes_new,
dict(point.attributes),
)
elif metric.name == "http.server.response.body.size":
self.assertEqual(1024, point.sum)
self.assertDictEqual(
expected_duration_attributes_new,
dict(point.attributes),
)
elif metric.name == "http.server.request.body.size":
self.assertEqual(128, point.sum)
self.assertDictEqual(
expected_duration_attributes_new,
dict(point.attributes),
)
elif metric.name == "http.server.duration":
self.assertAlmostEqual(duration, point.sum, delta=30)
self.assertDictEqual(
expected_duration_attributes_old,
dict(point.attributes),
)
elif metric.name == "http.server.response.size":
self.assertEqual(1024, point.sum)
self.assertDictEqual(
expected_duration_attributes_old,
dict(point.attributes),
)
elif metric.name == "http.server.request.size":
self.assertEqual(128, point.sum)
self.assertDictEqual(
expected_duration_attributes_old,
dict(point.attributes),
)
elif isinstance(point, NumberDataPoint):
self.assertDictEqual(
expected_requests_count_attributes,
dict(point.attributes),
)
self.assertEqual(point.value, 0)
async def test_metric_target_attribute(self):
expected_target = "/api/user/{id}"
class TestRoute:
path_format = expected_target
async def target_asgi(scope, receive, send):
assert isinstance(scope, dict)
if scope["type"] == "http":
await http_app(scope, receive, send)
scope["route"] = TestRoute()
else:
raise ValueError("websockets not supported")
app = otel_asgi.OpenTelemetryMiddleware(target_asgi)
self.seed_app(app)
await self.send_default_request()
await self.get_all_output()
metrics = self.get_sorted_metrics(SCOPE)
assertions = 0
for metric in metrics:
if metric.name == "http.server.active_requests":
continue
for point in metric.data.data_points:
if isinstance(point, HistogramDataPoint):
self.assertEqual(
point.attributes["http.target"],
expected_target,
)
assertions += 1
self.assertEqual(assertions, 3)
async def test_no_metric_for_websockets(self):
self.scope = {
"type": "websocket",
"http_version": "1.1",
"scheme": "ws",
"path": "/",
"query_string": b"",
"headers": [],
"client": ("127.0.0.1", 32767),
"server": ("127.0.0.1", 80),
}
app = otel_asgi.OpenTelemetryMiddleware(simple_asgi)
self.seed_app(app)
await self.send_input({"type": "websocket.connect"})
await self.send_input({"type": "websocket.receive", "text": "ping"})
await self.send_input({"type": "websocket.disconnect"})
await self.get_all_output()
self.assertEqual(len(self.get_sorted_metrics(SCOPE)), 0)
async def test_excluded_urls(self):
self.scope["path"] = "/test_excluded_urls"
app = otel_asgi.OpenTelemetryMiddleware(simple_asgi, excluded_urls="test_excluded_urls")
self.seed_app(app)
await self.send_default_request()
await self.get_all_output()
spans = self.get_finished_spans()
self.assertEqual(len(spans), 0)
async def test_no_excluded_urls(self):
self.scope["path"] = "/test_excluded_urls"
app = otel_asgi.OpenTelemetryMiddleware(simple_asgi, excluded_urls="test_excluded_urls")
self.seed_app(app)
self.scope["path"] = "/test_no_excluded_urls"
await self.send_default_request()
await self.get_all_output()
spans = self.get_finished_spans()
self.assertGreater(len(spans), 0)
async def test_suppress_http_instrumentation(self):
app = otel_asgi.OpenTelemetryMiddleware(simple_asgi)
async def suppression_wrapper(scope, receive, send):
with suppress_http_instrumentation():
await app(scope, receive, send)
self.seed_app(suppression_wrapper)
await self.send_default_request()
await self.get_all_output()
spans = self.get_finished_spans()
self.assertEqual(len(spans), 0)
class TestAsgiAttributes(unittest.TestCase):
def setUp(self):
self.scope = {}
setup_testing_defaults(self.scope)
self.span = mock.create_autospec(trace_api.Span, spec_set=True)
def test_request_attributes(self):
self.scope["query_string"] = b"foo=bar"
headers = []
headers.append((b"host", b"test"))
self.scope["headers"] = headers
attrs = otel_asgi.collect_request_attributes(self.scope)
self.assertDictEqual(
attrs,
{
HTTP_METHOD: "GET",
HTTP_HOST: "127.0.0.1",
HTTP_TARGET: "/",
HTTP_URL: "http://test/?foo=bar",
NET_HOST_PORT: 80,
HTTP_SCHEME: "http",
HTTP_SERVER_NAME: "test",
HTTP_FLAVOR: "1.0",
NET_PEER_IP: "127.0.0.1",
NET_PEER_PORT: 32767,
},
)
def test_request_attributes_new_semconv(self):
self.scope["query_string"] = b"foo=bar"
headers = []
headers.append((b"host", b"test"))
self.scope["headers"] = headers
attrs = otel_asgi.collect_request_attributes(
self.scope,
_StabilityMode.HTTP,
)
self.assertDictEqual(
attrs,
{
HTTP_REQUEST_METHOD: "GET",
URL_PATH: "/",
URL_QUERY: "foo=bar",
SERVER_ADDRESS: "127.0.0.1",
SERVER_PORT: 80,
URL_SCHEME: "http",
NETWORK_PROTOCOL_VERSION: "1.0",
CLIENT_ADDRESS: "127.0.0.1",
CLIENT_PORT: 32767,
},
)
def test_request_attributes_both_semconv(self):
self.scope["query_string"] = b"foo=bar"
headers = []
headers.append((b"host", b"test"))
self.scope["headers"] = headers
attrs = otel_asgi.collect_request_attributes(
self.scope,
_StabilityMode.HTTP_DUP,
)
self.assertDictEqual(
attrs,
{
HTTP_METHOD: "GET",
HTTP_HOST: "127.0.0.1",
HTTP_TARGET: "/",
HTTP_URL: "http://test/?foo=bar",
NET_HOST_PORT: 80,
HTTP_SCHEME: "http",
HTTP_SERVER_NAME: "test",
HTTP_FLAVOR: "1.0",
NET_PEER_IP: "127.0.0.1",
NET_PEER_PORT: 32767,
HTTP_REQUEST_METHOD: "GET",
URL_PATH: "/",
URL_QUERY: "foo=bar",
SERVER_ADDRESS: "127.0.0.1",
SERVER_PORT: 80,
URL_SCHEME: "http",
NETWORK_PROTOCOL_VERSION: "1.0",
CLIENT_ADDRESS: "127.0.0.1",
CLIENT_PORT: 32767,
},
)
def test_query_string(self):
self.scope["query_string"] = b"foo=bar"
attrs = otel_asgi.collect_request_attributes(self.scope)
self.assertEqual(attrs[HTTP_URL], "http://127.0.0.1/?foo=bar")
def test_query_string_new_semconv(self):
self.scope["query_string"] = b"foo=bar"
attrs = otel_asgi.collect_request_attributes(
self.scope,
_StabilityMode.HTTP,
)
self.assertEqual(attrs[URL_SCHEME], "http")
self.assertEqual(attrs[CLIENT_ADDRESS], "127.0.0.1")
self.assertEqual(attrs[URL_PATH], "/")
self.assertEqual(attrs[URL_QUERY], "foo=bar")
def test_query_string_both_semconv(self):
self.scope["query_string"] = b"foo=bar"
attrs = otel_asgi.collect_request_attributes(
self.scope,
_StabilityMode.HTTP_DUP,
)
self.assertEqual(attrs[HTTP_URL], "http://127.0.0.1/?foo=bar")
self.assertEqual(attrs[URL_SCHEME], "http")
self.assertEqual(attrs[CLIENT_ADDRESS], "127.0.0.1")
self.assertEqual(attrs[URL_PATH], "/")
self.assertEqual(attrs[URL_QUERY], "foo=bar")
def test_query_string_percent_bytes(self):
self.scope["query_string"] = b"foo%3Dbar"
attrs = otel_asgi.collect_request_attributes(self.scope)
self.assertEqual(attrs[HTTP_URL], "http://127.0.0.1/?foo=bar")
def test_query_string_percent_str(self):
self.scope["query_string"] = "foo%3Dbar"
attrs = otel_asgi.collect_request_attributes(self.scope)
self.assertEqual(attrs[HTTP_URL], "http://127.0.0.1/?foo=bar")
def test_response_attributes(self):
otel_asgi.set_status_code(self.span, 404)
expected = (mock.call(HTTP_STATUS_CODE, 404),)
self.assertEqual(self.span.set_attribute.call_count, 1)
self.assertEqual(self.span.set_attribute.call_count, 1)
self.span.set_attribute.assert_has_calls(expected, any_order=True)
def test_response_attributes_new_semconv(self):
otel_asgi.set_status_code(
self.span,
404,
None,
_StabilityMode.HTTP,
)
expected = (mock.call(HTTP_RESPONSE_STATUS_CODE, 404),)
self.assertEqual(self.span.set_attribute.call_count, 1)
self.assertEqual(self.span.set_attribute.call_count, 1)
self.span.set_attribute.assert_has_calls(expected, any_order=True)
def test_response_attributes_both_semconv(self):
otel_asgi.set_status_code(
self.span,
404,
None,
_StabilityMode.HTTP_DUP,
)
expected = (mock.call(HTTP_STATUS_CODE, 404),)
expected2 = (mock.call(HTTP_RESPONSE_STATUS_CODE, 404),)
self.assertEqual(self.span.set_attribute.call_count, 2)
self.assertEqual(self.span.set_attribute.call_count, 2)
self.span.set_attribute.assert_has_calls(expected, any_order=True)
self.span.set_attribute.assert_has_calls(expected2, any_order=True)
def test_response_attributes_invalid_status_code(self):
otel_asgi.set_status_code(self.span, "Invalid Status Code")
self.assertEqual(self.span.set_status.call_count, 1)
def test_remove_sensitive_params(self):
self.scope["server"] = ("username:password@mock", 80)
self.scope["path"] = "/status/200"
self.scope["query_string"] = b"X-Goog-Signature=1234567890"
attrs = otel_asgi.collect_request_attributes(self.scope)
self.assertEqual(
attrs[HTTP_URL],
"http://REDACTED:REDACTED@mock/status/200?X-Goog-Signature=REDACTED",
)
def test_collect_target_attribute_missing(self):
self.assertIsNone(otel_asgi._collect_target_attribute(self.scope))
def test_collect_target_attribute_fastapi(self):
class TestRoute:
path_format = "/api/users/{user_id}"
self.scope["route"] = TestRoute()
self.assertEqual(
otel_asgi._collect_target_attribute(self.scope),
"/api/users/{user_id}",
)
def test_collect_target_attribute_fastapi_mounted(self):
class TestRoute:
path_format = "/users/{user_id}"
self.scope["route"] = TestRoute()
self.scope["root_path"] = "/api/v2"
self.assertEqual(
otel_asgi._collect_target_attribute(self.scope),
"/api/v2/users/{user_id}",
)
def test_collect_target_attribute_fastapi_starlette_invalid(self):
self.scope["route"] = object()
self.assertIsNone(
otel_asgi._collect_target_attribute(self.scope),
"HTTP_TARGET values is not None",
)
class TestWrappedApplication(AsyncAsgiTestBase):
async def test_mark_span_internal_in_presence_of_span_from_other_framework(
self,
):
tracer_provider, exporter = TestBase.create_tracer_provider()
tracer = tracer_provider.get_tracer(__name__)
app = otel_asgi.OpenTelemetryMiddleware(simple_asgi, tracer_provider=tracer_provider)
# Wrapping the otel intercepted app with server span
async def wrapped_app(scope, receive, send):
with tracer.start_as_current_span("test", kind=SpanKind.SERVER) as _:
await app(scope, receive, send)
self.seed_app(wrapped_app)
await self.send_default_request()
await self.get_all_output()
span_list = exporter.get_finished_spans()
self.assertEqual(SpanKind.INTERNAL, span_list[0].kind)
self.assertEqual(SpanKind.INTERNAL, span_list[1].kind)
self.assertEqual(SpanKind.INTERNAL, span_list[2].kind)
self.assertEqual(trace_api.SpanKind.INTERNAL, span_list[3].kind)
# SERVER "test"
self.assertEqual(SpanKind.SERVER, span_list[4].kind)
# internal span should be child of the test span we have provided
self.assertEqual(span_list[4].context.span_id, span_list[3].parent.span_id)
class TestAsgiApplicationRaisingError(AsyncAsgiTestBase):
def tearDown(self):
pass
async def test_asgi_value_error_exception(self):
"""
Test that exception UnboundLocalError local variable 'start' referenced before assignment is not raised
See https://github.com/open-telemetry/opentelemetry-python-contrib/issues/1883
"""
async def bad_app(_scope, _receive, _send):
raise ValueError("whatever")
app = otel_asgi.OpenTelemetryMiddleware(bad_app)
self.seed_app(app)
await self.send_default_request()
try:
await self.communicator.wait()
except ValueError as exc_info:
self.assertEqual(exc_info.args[0], "whatever")
except Exception as exc_info: # pylint: disable=W0703
self.fail("expecting ValueError('whatever'), received instead: " + str(exc_info))
else:
self.fail("expecting ValueError('whatever')")
if __name__ == "__main__":
unittest.main()
test_getter.py 0000664 0000000 0000000 00000003720 15270700723 0036056 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-asgi/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
from unittest import TestCase
from opentelemetry.instrumentation.asgi import ASGIGetter
class TestASGIGetter(TestCase):
def test_get_none_empty_carrier(self):
getter = ASGIGetter()
carrier = {}
val = getter.get(carrier, "test")
self.assertIsNone(val)
def test_get_none_empty_headers(self):
getter = ASGIGetter()
carrier = {"headers": []}
val = getter.get(carrier, "test")
self.assertIsNone(val)
def test_get_(self):
getter = ASGIGetter()
carrier = {"headers": [(b"test-key", b"val")]}
expected_val = ["val"]
self.assertEqual(
getter.get(carrier, "Test-Key"),
expected_val,
"Should be case insensitive",
)
self.assertEqual(
getter.get(carrier, "test-key"),
expected_val,
"Should be case insensitive",
)
self.assertEqual(
getter.get(carrier, "TEST-KEY"),
expected_val,
"Should be case insensitive",
)
def test_keys_empty_carrier(self):
getter = ASGIGetter()
keys = getter.keys({})
self.assertEqual(keys, [])
def test_keys_empty_headers(self):
getter = ASGIGetter()
keys = getter.keys({"headers": []})
self.assertEqual(keys, [])
def test_keys(self):
getter = ASGIGetter()
carrier = {"headers": [(b"test-key", b"val")]}
expected_val = ["test-key"]
self.assertEqual(
getter.keys(carrier),
expected_val,
"Should be equal",
)
def test_non_utf8_headers(self):
getter = ASGIGetter()
carrier = {"headers": [(b"test-key", b"Moto Z\xb2")]}
expected_val = ["Moto Z²"]
self.assertEqual(
getter.get(carrier, "test-key"),
expected_val,
"Should be equal",
)
opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-asyncclick/ 0000775 0000000 0000000 00000000000 15270700723 0033266 5 ustar 00root root 0000000 0000000 README.rst 0000664 0000000 0000000 00000001226 15270700723 0034677 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-asyncclick OpenTelemetry asyncclick Instrumentation
========================================
|pypi|
.. |pypi| image:: https://badge.fury.io/py/opentelemetry-instrumentation-asyncclick.svg
:target: https://pypi.org/project/opentelemetry-instrumentation-asyncclick/
This library allows tracing requests made by the asyncclick fork of the click library.
Installation
------------
::
pip install opentelemetry-instrumentation-asyncclick
References
----------
* `OpenTelemetry asyncclick/ Tracing `_
* `OpenTelemetry Project `_
pyproject.toml 0000664 0000000 0000000 00000003235 15270700723 0036126 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-asyncclick [build-system]
requires = ["hatchling"]
build-backend = "hatchling.build"
[project]
name = "opentelemetry-instrumentation-asyncclick"
dynamic = ["version"]
description = "Async Click instrumentation for OpenTelemetry"
readme = "README.rst"
license = "Apache-2.0"
requires-python = ">=3.10"
authors = [
{ name = "OpenTelemetry Authors", email = "cncf-opentelemetry-contributors@lists.cncf.io" },
]
classifiers = [
"Development Status :: 4 - Beta",
"Intended Audience :: Developers",
"License :: OSI Approved :: Apache Software License",
"Programming Language :: Python",
"Programming Language :: Python :: 3",
"Programming Language :: Python :: 3.10",
"Programming Language :: Python :: 3.11",
"Programming Language :: Python :: 3.12",
"Programming Language :: Python :: 3.13",
"Programming Language :: Python :: 3.14",
]
dependencies = [
"opentelemetry-api ~= 1.12",
"opentelemetry-instrumentation == 0.66b2",
"opentelemetry-semantic-conventions == 0.66b2",
"wrapt ~= 1.0",
"typing_extensions ~= 4.12",
]
[project.optional-dependencies]
instruments = [
"asyncclick ~= 8.0",
]
[project.entry-points.opentelemetry_instrumentor]
asyncclick = "opentelemetry.instrumentation.asyncclick:AsyncClickInstrumentor"
[project.urls]
Homepage = "https://github.com/open-telemetry/opentelemetry-python-contrib/instrumentation/opentelemetry-instrumentation-asyncclick"
Repository = "https://github.com/open-telemetry/opentelemetry-python-contrib"
[tool.hatch.version]
path = "src/opentelemetry/instrumentation/asyncclick/version.py"
[tool.hatch.build.targets.sdist]
include = [
"/src",
"/tests",
]
[tool.hatch.build.targets.wheel]
packages = ["src/opentelemetry"]
opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-asyncclick/src/ 0000775 0000000 0000000 00000000000 15270700723 0034055 5 ustar 00root root 0000000 0000000 opentelemetry/ 0000775 0000000 0000000 00000000000 15270700723 0036672 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-asyncclick/src instrumentation/ 0000775 0000000 0000000 00000000000 15270700723 0042135 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-asyncclick/src/opentelemetry asyncclick/ 0000775 0000000 0000000 00000000000 15270700723 0044260 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-asyncclick/src/opentelemetry/instrumentation __init__.py 0000664 0000000 0000000 00000007644 15270700723 0046404 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-asyncclick/src/opentelemetry/instrumentation/asyncclick # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
"""
Instrument `asyncclick`_ CLI applications. The instrumentor will avoid instrumenting
well-known servers (e.g. *flask run* and *uvicorn*) to avoid unexpected effects
like every request having the same Trace ID.
.. _asyncclick: https://pypi.org/project/asyncclick/
Usage
-----
.. code-block:: python
import asyncio
import asyncclick
from opentelemetry.instrumentation.asyncclick import AsyncClickInstrumentor
AsyncClickInstrumentor().instrument()
@asyncclick.command()
async def hello():
asyncclick.echo(f"Hello world!")
if __name__ == "__main__":
asyncio.run(hello())
API
---
"""
from __future__ import annotations
import os
import sys
from collections.abc import Awaitable, Callable, Collection
from functools import partial
from logging import getLogger
from typing import (
TYPE_CHECKING,
Any,
TypeVar,
)
import asyncclick
from typing_extensions import ParamSpec, Unpack
from wrapt import (
wrap_function_wrapper, # type: ignore[reportUnknownVariableType]
)
from opentelemetry import trace
from opentelemetry.instrumentation.asyncclick.package import _instruments
from opentelemetry.instrumentation.asyncclick.version import __version__
from opentelemetry.instrumentation.instrumentor import BaseInstrumentor
from opentelemetry.instrumentation.utils import (
unwrap,
)
from opentelemetry.semconv._incubating.attributes.process_attributes import (
PROCESS_COMMAND_ARGS,
PROCESS_EXECUTABLE_NAME,
PROCESS_EXIT_CODE,
PROCESS_PID,
)
from opentelemetry.semconv.attributes.error_attributes import ERROR_TYPE
from opentelemetry.trace.status import StatusCode
if TYPE_CHECKING:
from typing import TypedDict
class InstrumentKwargs(TypedDict, total=False):
tracer_provider: trace.TracerProvider
class UninstrumentKwargs(TypedDict, total=False):
pass
_logger = getLogger(__name__)
T = TypeVar("T")
P = ParamSpec("P")
async def _command_invoke_wrapper(
wrapped: Callable[P, Awaitable[T]],
instance: asyncclick.core.Command,
args: tuple[Any, ...],
kwargs: dict[str, Any],
tracer: trace.Tracer,
) -> T:
# Subclasses of Command include groups and CLI runners, but
# we only want to instrument the actual commands which are
# instances of Command itself.
if instance.__class__ != asyncclick.Command:
return await wrapped(*args, **kwargs)
ctx = args[0]
span_name = ctx.info_name
span_attributes = {
PROCESS_COMMAND_ARGS: sys.argv,
PROCESS_EXECUTABLE_NAME: sys.argv[0],
PROCESS_EXIT_CODE: 0,
PROCESS_PID: os.getpid(),
}
with tracer.start_as_current_span(
name=span_name,
kind=trace.SpanKind.INTERNAL,
attributes=span_attributes,
) as span:
try:
result = await wrapped(*args, **kwargs)
return result
except Exception as exc:
span.set_status(StatusCode.ERROR, str(exc))
if span.is_recording():
span.set_attribute(ERROR_TYPE, type(exc).__qualname__)
span.set_attribute(PROCESS_EXIT_CODE, getattr(exc, "exit_code", 1))
raise
# pylint: disable=no-self-use
class AsyncClickInstrumentor(BaseInstrumentor):
"""An instrumentor for asyncclick"""
def instrumentation_dependencies(self) -> Collection[str]:
return _instruments
def _instrument(self, **kwargs: Unpack[InstrumentKwargs]) -> None:
tracer_provider = kwargs.get("tracer_provider")
tracer = trace.get_tracer(
__name__,
__version__,
tracer_provider,
)
wrap_function_wrapper(
asyncclick.core.Command,
"invoke",
partial(_command_invoke_wrapper, tracer=tracer),
)
def _uninstrument(self, **kwargs: Unpack[UninstrumentKwargs]) -> None:
unwrap(asyncclick.core.Command, "invoke")
package.py 0000664 0000000 0000000 00000000164 15270700723 0046226 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-asyncclick/src/opentelemetry/instrumentation/asyncclick # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
_instruments = ("asyncclick ~= 8.0",)
py.typed 0000664 0000000 0000000 00000000000 15270700723 0045745 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-asyncclick/src/opentelemetry/instrumentation/asyncclick version.py 0000664 0000000 0000000 00000000144 15270700723 0046316 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-asyncclick/src/opentelemetry/instrumentation/asyncclick # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
__version__ = "0.66b2"
test-requirements.txt 0000664 0000000 0000000 00000000437 15270700723 0037454 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-asyncclick
asyncclick~=8.0
Flask~=3.0
pytest==7.4.4
anyio~=4.5
-e opentelemetry-instrumentation
-e instrumentation/opentelemetry-instrumentation-asyncclick
-e instrumentation/opentelemetry-instrumentation-flask
-e instrumentation/opentelemetry-instrumentation-wsgi
-e util/opentelemetry-util-http
opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-asyncclick/tests/ 0000775 0000000 0000000 00000000000 15270700723 0034430 5 ustar 00root root 0000000 0000000 test_asyncclick.py 0000664 0000000 0000000 00000027347 15270700723 0040122 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-asyncclick/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
from __future__ import annotations
import asyncio
import os
from typing import Any
from unittest import IsolatedAsyncioTestCase, mock
import asyncclick
import asyncclick.testing
from asyncclick.testing import CliRunner
from opentelemetry.instrumentation.asyncclick import AsyncClickInstrumentor
from opentelemetry.test.test_base import TestBase
from opentelemetry.trace import SpanKind
from opentelemetry.trace.status import StatusCode
def run_asyncclick_command_test(
command: asyncclick.core.Command, args: tuple[Any, ...] = (), **kwargs: Any
) -> asyncclick.testing.Result:
"""
Run an asyncclick command and return the result.
Args:
command: The AsyncClick command to run
args: Command-line arguments
**kwargs: Additional arguments for CliRunner.invoke
Returns:
The result of invoking the command
"""
async def _run() -> asyncclick.testing.Result:
runner = CliRunner()
return await runner.invoke(command, args, **kwargs)
return asyncio.run(_run())
class ClickTestCase(TestBase, IsolatedAsyncioTestCase):
# pylint: disable=unbalanced-tuple-unpacking
def setUp(self): # pylint: disable=invalid-name
super().setUp()
AsyncClickInstrumentor().instrument()
def tearDown(self): # pylint: disable=invalid-name
super().tearDown()
AsyncClickInstrumentor().uninstrument()
@mock.patch("sys.argv", ["command.py"])
def test_cli_command_wrapping(self):
@asyncclick.command()
async def command() -> None:
pass
result = run_asyncclick_command_test(command)
self.assertEqual(result.exit_code, 0)
(span,) = self.memory_exporter.get_finished_spans()
self.assertEqual(span.status.status_code, StatusCode.UNSET)
self.assertEqual(span.kind, SpanKind.INTERNAL)
self.assertEqual(span.name, "command")
self.assertEqual(
dict(span.attributes),
{
"process.executable.name": "command.py",
"process.command_args": ("command.py",),
"process.exit.code": 0,
"process.pid": os.getpid(),
},
)
@mock.patch("sys.argv", ["command.py"])
def test_cli_command_wrapping_with_name(self):
@asyncclick.command("mycommand")
async def renamedcommand() -> None:
pass
result = run_asyncclick_command_test(renamedcommand)
self.assertEqual(result.exit_code, 0)
(span,) = self.memory_exporter.get_finished_spans()
self.assertEqual(span.status.status_code, StatusCode.UNSET)
self.assertEqual(span.kind, SpanKind.INTERNAL)
self.assertEqual(span.name, "mycommand")
self.assertEqual(
dict(span.attributes),
{
"process.executable.name": "command.py",
"process.command_args": ("command.py",),
"process.exit.code": 0,
"process.pid": os.getpid(),
},
)
@mock.patch("sys.argv", ["command.py", "--opt", "argument"])
def test_cli_command_wrapping_with_options(self):
@asyncclick.command()
@asyncclick.argument("argument")
@asyncclick.option("--opt/--no-opt", default=False)
async def command(argument: str, opt: str) -> None:
pass
argv = ["command.py", "--opt", "argument"]
result = run_asyncclick_command_test(command, argv[1:])
self.assertEqual(result.exit_code, 0)
(span,) = self.memory_exporter.get_finished_spans()
self.assertEqual(span.status.status_code, StatusCode.UNSET)
self.assertEqual(span.kind, SpanKind.INTERNAL)
self.assertEqual(span.name, "command")
self.assertEqual(
dict(span.attributes),
{
"process.executable.name": "command.py",
"process.command_args": tuple(argv),
"process.exit.code": 0,
"process.pid": os.getpid(),
},
)
@mock.patch("sys.argv", ["command-raises.py"])
def test_cli_command_raises_error(self):
@asyncclick.command()
async def command_raises() -> None:
raise ValueError()
result = run_asyncclick_command_test(command_raises)
self.assertEqual(result.exit_code, 1)
(span,) = self.memory_exporter.get_finished_spans()
self.assertEqual(span.status.status_code, StatusCode.ERROR)
self.assertEqual(span.kind, SpanKind.INTERNAL)
self.assertEqual(span.name, "command-raises")
self.assertEqual(
dict(span.attributes),
{
"process.executable.name": "command-raises.py",
"process.command_args": ("command-raises.py",),
"process.exit.code": 1,
"process.pid": os.getpid(),
"error.type": "ValueError",
},
)
def test_uninstrument(self):
AsyncClickInstrumentor().uninstrument()
@asyncclick.command()
async def notracecommand() -> None:
pass
result = run_asyncclick_command_test(notracecommand)
self.assertEqual(result.exit_code, 0)
self.assertFalse(self.memory_exporter.get_finished_spans())
AsyncClickInstrumentor().instrument()
@mock.patch("sys.argv", ["command.py", "sub1", "sub2"])
def test_nested_command_groups(self):
"""Test instrumentation of nested command groups."""
@asyncclick.group()
async def cli() -> None:
pass
@cli.group()
async def sub1() -> None:
pass
@sub1.command()
async def sub2() -> None:
pass
result = run_asyncclick_command_test(cli, ["sub1", "sub2"])
self.assertEqual(result.exit_code, 0)
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1) # Only the leaf command should be instrumented
span = spans[0]
self.assertEqual(span.name, "sub2")
self.assertEqual(
dict(span.attributes),
{
"process.executable.name": "command.py",
"process.command_args": ("command.py", "sub1", "sub2"),
"process.exit.code": 0,
"process.pid": os.getpid(),
},
)
@mock.patch("sys.argv", ["command.py"])
def test_command_with_callback(self):
"""Test instrumentation of commands with callbacks."""
callback_called = False
def callback_func(ctx: asyncclick.Context, param: asyncclick.Parameter, value: bool) -> bool:
nonlocal callback_called
callback_called = True
return value
@asyncclick.command()
@asyncclick.option("--option", callback=callback_func, default="default")
async def command(option: str) -> None:
pass
result = run_asyncclick_command_test(command)
self.assertEqual(result.exit_code, 0)
self.assertTrue(callback_called)
(span,) = self.memory_exporter.get_finished_spans()
self.assertEqual(span.name, "command")
self.assertEqual(span.status.status_code, StatusCode.UNSET)
@mock.patch("sys.argv", ["command.py"])
def test_command_with_result_callback(self):
"""Test instrumentation with result callbacks."""
callback_called = False
@asyncclick.group(chain=True)
async def cli() -> None:
pass
@cli.result_callback()
async def process_result(result: asyncclick.testing.Result) -> None:
nonlocal callback_called
callback_called = True
@cli.command()
async def command() -> None:
pass
result = run_asyncclick_command_test(cli, ["command"])
self.assertEqual(result.exit_code, 0)
self.assertTrue(callback_called)
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
span = spans[0]
self.assertEqual(span.name, "command")
@mock.patch("sys.argv", ["command.py"])
def test_command_chaining(self):
"""Test instrumentation with command chaining."""
@asyncclick.group(chain=True)
async def cli() -> None:
pass
@cli.command()
async def cmd1() -> None:
return "result1"
@cli.command()
async def cmd2() -> None:
return "result2"
result = run_asyncclick_command_test(cli, ["cmd1", "cmd2"])
self.assertEqual(result.exit_code, 0)
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 2)
# Spans should be ordered by execution
self.assertEqual(spans[0].name, "cmd1")
self.assertEqual(spans[1].name, "cmd2")
@mock.patch("sys.argv", ["command.py"])
def test_custom_exit_codes(self) -> None:
"""Test instrumentation with custom exit codes."""
@asyncclick.command()
async def command() -> None:
raise asyncclick.exceptions.Exit(code=42)
result = run_asyncclick_command_test(command)
self.assertEqual(result.exit_code, 42)
(span,) = self.memory_exporter.get_finished_spans()
self.assertEqual(span.name, "command")
self.assertEqual(span.status.status_code, StatusCode.ERROR)
self.assertEqual(span.attributes["process.exit.code"], 42)
self.assertEqual(span.attributes["error.type"], "Exit")
@mock.patch("sys.argv", ["command.py"])
def test_context_object_passing(self):
"""Test that instrumentation preserves context object passing."""
@asyncclick.group()
@asyncclick.option("--debug/--no-debug", default=False)
@asyncclick.pass_context
async def cli(ctx: asyncclick.Context, debug: bool) -> None:
ctx.ensure_object(dict)
ctx.obj["DEBUG"] = debug
@cli.command()
@asyncclick.pass_context
async def command(ctx: asyncclick.Context) -> None:
assert isinstance(ctx.obj, dict)
assert "DEBUG" in ctx.obj
result = run_asyncclick_command_test(cli, ["--debug", "command"])
self.assertEqual(result.exit_code, 0)
(span,) = self.memory_exporter.get_finished_spans()
self.assertEqual(span.name, "command")
def test_multiple_instrumentation(self):
"""Test that instrumenting multiple times only applies once."""
# Already instrumented in setUp, instrument again
AsyncClickInstrumentor().instrument()
@asyncclick.command()
async def command() -> None:
pass
result = run_asyncclick_command_test(command)
self.assertEqual(result.exit_code, 0)
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
def test_concurrency(self):
"""Test instrumentation with concurrent command execution."""
@asyncclick.command()
async def command1() -> None:
pass
@asyncclick.command()
async def command2() -> None:
pass
async def run_both() -> tuple[asyncclick.testing.Result, asyncclick.testing.Result]:
runner = CliRunner()
task1 = asyncio.create_task(runner.invoke(command1))
task2 = asyncio.create_task(runner.invoke(command2))
results = await asyncio.gather(task1, task2)
return results
results = asyncio.run(run_both())
self.assertEqual(results[0].exit_code, 0)
self.assertEqual(results[1].exit_code, 0)
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 2)
span_names = [span.name for span in spans]
self.assertIn("command1", span_names)
self.assertIn("command2", span_names)
opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-asyncio/ 0000775 0000000 0000000 00000000000 15270700723 0032610 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-asyncio/LICENSE 0000664 0000000 0000000 00000026135 15270700723 0033624 0 ustar 00root root 0000000 0000000 Apache License
Version 2.0, January 2004
http://www.apache.org/licenses/
TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION
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"Licensor" shall mean the copyright owner or entity authorized by
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outstanding shares, or (iii) beneficial ownership of such entity.
"You" (or "Your") shall mean an individual or Legal Entity
exercising permissions granted by this License.
"Source" form shall mean the preferred form for making modifications,
including but not limited to software source code, documentation
source, and configuration files.
"Object" form shall mean any form resulting from mechanical
transformation or translation of a Source form, including but
not limited to compiled object code, generated documentation,
and conversions to other media types.
"Work" shall mean the work of authorship, whether in Source or
Object form, made available under the License, as indicated by a
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opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-asyncio/README.rst0000664 0000000 0000000 00000006342 15270700723 0034304 0 ustar 00root root 0000000 0000000 OpenTelemetry asyncio Instrumentation
======================================
|pypi|
.. |pypi| image:: https://badge.fury.io/py/opentelemetry-instrumentation-asyncio.svg
:target: https://pypi.org/project/opentelemetry-instrumentation-asyncio/
AsyncioInstrumentor: Tracing Requests Made by the Asyncio Library
The opentelemetry-instrumentation-asyncio package allows tracing asyncio applications.
It also includes metrics for duration and counts of coroutines and futures. Metrics are generated even if coroutines are not traced.
Set the names of coroutines you want to trace.
-------------------------------------------------
.. code:: bash
export OTEL_PYTHON_ASYNCIO_COROUTINE_NAMES_TO_TRACE=coro_name,coro_name2,coro_name3
If you want to trace specific blocking functions executed with the ``to_thread`` function of asyncio, set the name of the functions in ``OTEL_PYTHON_ASYNCIO_TO_THREAD_FUNCTION_NAMES_TO_TRACE``.
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
.. code:: bash
export OTEL_PYTHON_ASYNCIO_TO_THREAD_FUNCTION_NAMES_TO_TRACE=func_name,func_name2,func_name3
You can enable tracing futures with ``OTEL_PYTHON_ASYNCIO_FUTURE_TRACE_ENABLED``
-----------------------------------------------------------------------------------------------
.. code:: bash
export OTEL_PYTHON_ASYNCIO_FUTURE_TRACE_ENABLED=true
Run instrumented application
-----------------------------
1. coroutine
--------------------
.. code:: python
# export OTEL_PYTHON_ASYNCIO_COROUTINE_NAMES_TO_TRACE=sleep
import asyncio
from opentelemetry.instrumentation.asyncio import AsyncioInstrumentor
AsyncioInstrumentor().instrument()
async def main():
await asyncio.create_task(asyncio.sleep(0.1))
asyncio.run(main())
2. future
--------------------
.. code:: python
# export OTEL_PYTHON_ASYNCIO_FUTURE_TRACE_ENABLED=true
import asyncio
from opentelemetry.instrumentation.asyncio import AsyncioInstrumentor
AsyncioInstrumentor().instrument()
async def main():
future = asyncio.Future()
future.set_result(1)
await asyncio.ensure_future(future)
asyncio.run(main())
3. to_thread
--------------------
.. code:: python
# export OTEL_PYTHON_ASYNCIO_TO_THREAD_FUNCTION_NAMES_TO_TRACE=func
import asyncio
from opentelemetry.instrumentation.asyncio import AsyncioInstrumentor
AsyncioInstrumentor().instrument()
async def main():
await asyncio.to_thread(func)
def func():
pass
asyncio.run(main())
asyncio metric types
----------------------
* `asyncio.process.duration` (seconds) - Duration of asyncio process
* `asyncio.process.created` ({process}) - Number of asyncio process
API
---
Installation
------------
::
pip install opentelemetry-instrumentation-asyncio
References
-----------
* `OpenTelemetry asyncio/ Tracing `_
* `OpenTelemetry Project `_
* `OpenTelemetry Python Examples `_
pyproject.toml 0000664 0000000 0000000 00000003145 15270700723 0035450 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-asyncio [build-system]
requires = ["hatchling"]
build-backend = "hatchling.build"
[project]
name = "opentelemetry-instrumentation-asyncio"
dynamic = ["version"]
description = "OpenTelemetry instrumentation for asyncio"
readme = "README.rst"
license = "Apache-2.0"
requires-python = ">=3.10"
authors = [
{ name = "OpenTelemetry Authors", email = "cncf-opentelemetry-contributors@lists.cncf.io" },
]
classifiers = [
"Development Status :: 4 - Beta",
"Intended Audience :: Developers",
"License :: OSI Approved :: Apache Software License",
"Programming Language :: Python",
"Programming Language :: Python :: 3",
"Programming Language :: Python :: 3.10",
"Programming Language :: Python :: 3.11",
"Programming Language :: Python :: 3.12",
"Programming Language :: Python :: 3.13",
"Programming Language :: Python :: 3.14",
]
dependencies = [
"opentelemetry-api ~= 1.14",
"opentelemetry-instrumentation == 0.66b2",
"opentelemetry-semantic-conventions == 0.66b2",
"wrapt >= 1.0.0, < 3.0.0",
]
[project.optional-dependencies]
instruments = []
[project.entry-points.opentelemetry_instrumentor]
asyncio = "opentelemetry.instrumentation.asyncio:AsyncioInstrumentor"
[project.urls]
Homepage = "https://github.com/open-telemetry/opentelemetry-python-contrib/tree/main/instrumentation/opentelemetry-instrumentation-asyncio"
Repository = "https://github.com/open-telemetry/opentelemetry-python-contrib"
[tool.hatch.version]
path = "src/opentelemetry/instrumentation/asyncio/version.py"
[tool.hatch.build.targets.sdist]
include = [
"/src",
"/tests",
]
[tool.hatch.build.targets.wheel]
packages = ["src/opentelemetry"]
opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-asyncio/src/ 0000775 0000000 0000000 00000000000 15270700723 0033377 5 ustar 00root root 0000000 0000000 opentelemetry/ 0000775 0000000 0000000 00000000000 15270700723 0036214 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-asyncio/src instrumentation/ 0000775 0000000 0000000 00000000000 15270700723 0041457 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-asyncio/src/opentelemetry asyncio/ 0000775 0000000 0000000 00000000000 15270700723 0043124 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-asyncio/src/opentelemetry/instrumentation __init__.py 0000664 0000000 0000000 00000030615 15270700723 0045242 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-asyncio/src/opentelemetry/instrumentation/asyncio # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
"""
.. asyncio: https://github.com/python/asyncio
The opentelemetry-instrumentation-asyncio package allows tracing asyncio applications.
The metric for coroutine, future, is generated even if there is no setting to generate a span.
Run instrumented application
------------------------------
1. coroutine
----------------
.. code:: python
# export OTEL_PYTHON_ASYNCIO_COROUTINE_NAMES_TO_TRACE=sleep
import asyncio
from opentelemetry.instrumentation.asyncio import AsyncioInstrumentor
AsyncioInstrumentor().instrument()
async def main():
await asyncio.create_task(asyncio.sleep(0.1))
asyncio.run(main())
2. future
------------
.. code:: python
# export OTEL_PYTHON_ASYNCIO_FUTURE_TRACE_ENABLED=true
import asyncio
from opentelemetry.instrumentation.asyncio import AsyncioInstrumentor
AsyncioInstrumentor().instrument()
async def main():
future = asyncio.Future()
future.set_result(1)
await asyncio.ensure_future(future)
asyncio.run(main())
3. to_thread
-------------
.. code:: python
# export OTEL_PYTHON_ASYNCIO_TO_THREAD_FUNCTION_NAMES_TO_TRACE=func
import asyncio
from opentelemetry.instrumentation.asyncio import AsyncioInstrumentor
AsyncioInstrumentor().instrument()
async def main():
await asyncio.to_thread(func)
def func():
pass
asyncio.run(main())
asyncio metric types
---------------------
* asyncio.process.duration (seconds) - Duration of asyncio process
* asyncio.process.created ({process}) - Number of asyncio process
API
---
"""
import asyncio
import functools
import sys
from asyncio import futures
from collections.abc import Callable, Collection
from timeit import default_timer
from typing import ParamSpec, TypeVar
from wrapt import wrap_function_wrapper as _wrap
from opentelemetry.instrumentation.asyncio.instrumentation_state import (
_is_instrumented,
)
from opentelemetry.instrumentation.asyncio.package import _instruments
from opentelemetry.instrumentation.asyncio.utils import (
get_coros_to_trace,
get_future_trace_enabled,
get_to_thread_to_trace,
)
from opentelemetry.instrumentation.asyncio.version import __version__
from opentelemetry.instrumentation.instrumentor import BaseInstrumentor
from opentelemetry.instrumentation.utils import unwrap
from opentelemetry.metrics import get_meter
from opentelemetry.trace import get_tracer
from opentelemetry.trace.status import Status, StatusCode
P = ParamSpec("P")
R = TypeVar("R")
ASYNCIO_PREFIX = "asyncio"
class AsyncioInstrumentor(BaseInstrumentor):
"""
An instrumentor for asyncio
See `BaseInstrumentor`
"""
methods_with_coroutine = [
"create_task",
"ensure_future",
"wait_for",
"wait",
"as_completed",
"run_coroutine_threadsafe",
]
def instrumentation_dependencies(self) -> Collection[str]:
return _instruments
def _instrument(self, **kwargs):
self._tracer = get_tracer(__name__, __version__, kwargs.get("tracer_provider"))
self._meter = get_meter(__name__, __version__, kwargs.get("meter_provider"))
self._coros_name_to_trace = get_coros_to_trace()
self._future_active_enabled = get_future_trace_enabled()
self._to_thread_name_to_trace = get_to_thread_to_trace()
self.process_duration_histogram = self._meter.create_histogram(
name="asyncio.process.duration",
description="Duration of asyncio process",
unit="s",
)
self.process_created_counter = self._meter.create_counter(
name="asyncio.process.created",
description="Number of asyncio process",
unit="{process}",
)
for method in self.methods_with_coroutine:
self.instrument_method_with_coroutine(method)
self.instrument_gather()
self.instrument_to_thread()
self.instrument_taskgroup_create_task()
def _uninstrument(self, **kwargs):
for method in self.methods_with_coroutine:
uninstrument_method_with_coroutine(method)
uninstrument_gather()
uninstrument_to_thread()
uninstrument_taskgroup_create_task()
def instrument_method_with_coroutine(self, method_name: str):
"""
Instruments specified asyncio method.
"""
def wrap_coro_or_future(method, instance, args, kwargs):
# If the first argument is a coroutine or future,
# we decorate it with a span and return the task.
if args and len(args) > 0:
first_arg = args[0]
# Check if it's a coroutine or future and wrap it
if asyncio.iscoroutine(first_arg) or futures.isfuture(first_arg):
args = (self.trace_item(first_arg),) + args[1:]
# Check if it's a list and wrap each item
elif isinstance(first_arg, list):
args = ([self.trace_item(item) for item in first_arg],) + args[1:]
return method(*args, **kwargs)
_wrap(asyncio, method_name, wrap_coro_or_future)
def instrument_gather(self):
def wrap_coros_or_futures(method, instance, args, kwargs):
if args and len(args) > 0:
# Check if it's a coroutine or future and wrap it
wrapped_args = tuple(self.trace_item(item) for item in args)
return method(*wrapped_args, **kwargs)
return method(*args, **kwargs)
_wrap(asyncio, "gather", wrap_coros_or_futures)
def instrument_to_thread(self) -> None:
def wrap_to_thread(method, instance, args, kwargs) -> None:
if args:
first_arg = args[0]
# Wrap the first argument
wrapped_first_arg = self.wrap_to_thread_func(first_arg)
wrapped_args = (wrapped_first_arg,) + args[1:]
return method(*wrapped_args, **kwargs)
return method(*args, **kwargs)
_wrap(asyncio, "to_thread", wrap_to_thread)
def instrument_taskgroup_create_task(self) -> None:
# TaskGroup.create_task was added in Python 3.11
if sys.version_info < (3, 11):
return
def wrap_taskgroup_create_task(method, instance, args, kwargs) -> None:
if args:
coro = args[0]
wrapped_coro = self.trace_coroutine(coro)
wrapped_args = (wrapped_coro,) + args[1:]
return method(*wrapped_args, **kwargs)
return method(*args, **kwargs)
_wrap(
asyncio.TaskGroup, # pylint: disable=no-member
"create_task",
wrap_taskgroup_create_task,
)
def trace_to_thread(self, func: Callable[P, R]) -> Callable[P, R]:
return self.wrap_to_thread_func(func)
def wrap_to_thread_func(self, func: Callable[P, R]) -> Callable[P, R]:
"""
Wrap a function so that its execution in the worker thread is
measured and, if enabled, traced.
"""
func_name = _get_func_name(func)
@functools.wraps(func)
def wrapper(*args: P.args, **kwargs: P.kwargs) -> R:
start = default_timer()
span = (
self._tracer.start_span(f"{ASYNCIO_PREFIX} to_thread-{func_name}")
if func_name in self._to_thread_name_to_trace
else None
)
attr = {"type": "to_thread", "name": func_name}
exception = None
try:
result = func(*args, **kwargs)
attr["state"] = "finished"
return result
# Match trace_coroutine and trace_future: a cancellation is
# recorded as state="cancelled" but not as a span error.
except asyncio.CancelledError:
attr["state"] = "cancelled"
raise
except BaseException as exc:
exception = exc
attr["state"] = determine_state(exc)
raise
finally:
self.record_process(start, attr, span, exception)
return wrapper
def trace_item(self, coro_or_future):
"""Trace a coroutine or future item."""
# Task is already traced, return it
if isinstance(coro_or_future, asyncio.Task):
return coro_or_future
if asyncio.iscoroutine(coro_or_future):
return self.trace_coroutine(coro_or_future)
if futures.isfuture(coro_or_future):
return self.trace_future(coro_or_future)
return coro_or_future
async def trace_coroutine(self, coro):
"""
Wrap a coroutine so that we measure its duration, metrics, etc.
If already instrumented, simply 'await coro' to preserve call behavior.
"""
if _is_instrumented(coro):
return await coro
if not hasattr(coro, "__name__"):
return await coro
start = default_timer()
attr = {
"type": "coroutine",
"name": coro.__name__,
}
span = (
self._tracer.start_span(f"{ASYNCIO_PREFIX} coro-" + coro.__name__)
if coro.__name__ in self._coros_name_to_trace
else None
)
exception = None
try:
attr["state"] = "finished"
return await coro
# CancelledError is raised when a coroutine is cancelled
# before it has a chance to run. We don't want to record
# this as an error.
# Still it needs to be raised in order for `asyncio.wait_for`
# to properly work with timeout and raise accordingly `asyncio.TimeoutError`
except asyncio.CancelledError:
attr["state"] = "cancelled"
raise
except Exception as exc:
exception = exc
state = determine_state(exception)
attr["state"] = state
raise
finally:
self.record_process(start, attr, span, exception)
def trace_future(self, future):
"""
Wrap a Future's done callback. If already instrumented, skip re-wrapping.
"""
if _is_instrumented(future):
return future
start = default_timer()
span = self._tracer.start_span(f"{ASYNCIO_PREFIX} future") if self._future_active_enabled else None
def callback(f):
attr = {
"type": "future",
"state": ("cancelled" if f.cancelled() else determine_state(f.exception())),
}
self.record_process(start, attr, span, None if f.cancelled() else f.exception())
future.add_done_callback(callback)
return future
def record_process(self, start: float, attr: dict, span=None, exception=None) -> None:
"""
Record the processing time, update histogram and counter, and handle span.
:param start: Start time of the process.
:param attr: Attributes for the histogram and counter.
:param span: Optional span for tracing.
:param exception: Optional exception occurred during the process.
"""
duration = max(default_timer() - start, 0)
self.process_duration_histogram.record(duration, attr)
self.process_created_counter.add(1, attr)
if span:
if span.is_recording() and exception:
span.set_status(Status(StatusCode.ERROR))
span.record_exception(exception)
span.end()
def _get_func_name(func: object) -> str | None:
func_name = getattr(func, "__name__", None)
if func_name is None and isinstance(func, functools.partial):
func_name = func.func.__name__
return func_name
def determine_state(exception: BaseException) -> str:
if isinstance(exception, asyncio.CancelledError):
return "cancelled"
if isinstance(exception, asyncio.TimeoutError):
return "timeout"
if exception:
return "exception"
return "finished"
def uninstrument_taskgroup_create_task() -> None:
# TaskGroup.create_task was added in Python 3.11
if sys.version_info < (3, 11):
return
unwrap(asyncio.TaskGroup, "create_task") # pylint: disable=no-member
def uninstrument_to_thread() -> None:
unwrap(asyncio, "to_thread")
def uninstrument_gather() -> None:
unwrap(asyncio, "gather")
def uninstrument_method_with_coroutine(method_name: str) -> None:
"""
Uninstrument specified asyncio method.
"""
unwrap(asyncio, method_name)
environment_variables.py 0000664 0000000 0000000 00000001560 15270700723 0050074 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-asyncio/src/opentelemetry/instrumentation/asyncio # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
"""
.. envvar:: OTEL_PYTHON_ASYNCIO_COROUTINE_NAMES_TO_TRACE
Enter the names of the coroutines to be traced through the environment variable below, separated by commas.
.. envvar:: OTEL_PYTHON_ASYNCIO_FUTURE_TRACE_ENABLED
To determine whether the tracing feature for Future of Asyncio in Python is enabled or not.
.. envvar:: OTEL_PYTHON_ASYNCIO_TO_THREAD_FUNCTION_NAMES_TO_TRACE
Enter the names of the functions to be traced through the environment variable below, separated by commas.
"""
OTEL_PYTHON_ASYNCIO_COROUTINE_NAMES_TO_TRACE = "OTEL_PYTHON_ASYNCIO_COROUTINE_NAMES_TO_TRACE"
OTEL_PYTHON_ASYNCIO_FUTURE_TRACE_ENABLED = "OTEL_PYTHON_ASYNCIO_FUTURE_TRACE_ENABLED"
OTEL_PYTHON_ASYNCIO_TO_THREAD_FUNCTION_NAMES_TO_TRACE = "OTEL_PYTHON_ASYNCIO_TO_THREAD_FUNCTION_NAMES_TO_TRACE"
instrumentation_state.py 0000664 0000000 0000000 00000003234 15270700723 0050143 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-asyncio/src/opentelemetry/instrumentation/asyncio # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
"""
Instrumentation State Tracker
This module provides helper functions to safely track whether a coroutine,
Future, or function has already been instrumented by the OpenTelemetry
asyncio instrumentation layer.
Some Python objects (like coroutines or functions) may not support setting
custom attributes or weak references. To avoid memory leaks and runtime
errors, this module uses a WeakKeyDictionary to safely track instrumented
objects.
If an object cannot be weak-referenced, it is silently skipped.
Usage:
if not _is_instrumented(obj):
_mark_instrumented(obj)
# instrument the object...
"""
import weakref
from typing import Any
# A global WeakSet to track instrumented objects.
# Entries are automatically removed when the objects are garbage collected.
_instrumented_tasks = weakref.WeakSet()
def _is_instrumented(obj: Any) -> bool:
"""
Check whether the object has already been instrumented.
If not, mark it as instrumented (only if weakref is supported).
Args:
obj: A coroutine, function, or Future.
Returns:
True if the object was already instrumented.
False if the object is not trackable (no weakref support), or just marked now.
Note:
In Python 3.12+, some internal types like `async_generator_asend`
raise TypeError when weakref is attempted.
"""
try:
if obj in _instrumented_tasks:
return True
_instrumented_tasks.add(obj)
return False
except TypeError:
# Object doesn't support weak references → can't track instrumentation
return False
package.py 0000664 0000000 0000000 00000000144 15270700723 0045070 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-asyncio/src/opentelemetry/instrumentation/asyncio # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
_instruments = tuple()
utils.py 0000664 0000000 0000000 00000002727 15270700723 0044646 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-asyncio/src/opentelemetry/instrumentation/asyncio # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
import os
# pylint: disable=no-name-in-module
from opentelemetry.instrumentation.asyncio.environment_variables import (
OTEL_PYTHON_ASYNCIO_COROUTINE_NAMES_TO_TRACE,
OTEL_PYTHON_ASYNCIO_FUTURE_TRACE_ENABLED,
OTEL_PYTHON_ASYNCIO_TO_THREAD_FUNCTION_NAMES_TO_TRACE,
)
def separate_coro_names_by_comma(coro_names: str) -> set[str]:
"""
Function to separate the coroutines to be traced by comma
"""
if coro_names is None:
return set()
return {coro_name.strip() for coro_name in coro_names.split(",")}
def get_coros_to_trace() -> set:
"""
Function to get the coroutines to be traced from the environment variable
"""
coro_names = os.getenv(OTEL_PYTHON_ASYNCIO_COROUTINE_NAMES_TO_TRACE)
return separate_coro_names_by_comma(coro_names)
def get_future_trace_enabled() -> bool:
"""
Function to get the future active enabled flag from the environment variable
default value is False
"""
return os.getenv(OTEL_PYTHON_ASYNCIO_FUTURE_TRACE_ENABLED, "False").lower() == "true"
def get_to_thread_to_trace() -> set:
"""
Function to get the functions to be traced from the environment variable
"""
func_names = os.getenv(OTEL_PYTHON_ASYNCIO_TO_THREAD_FUNCTION_NAMES_TO_TRACE)
return separate_coro_names_by_comma(func_names)
__all__ = [
"get_coros_to_trace",
"get_future_trace_enabled",
"get_to_thread_to_trace",
]
version.py 0000664 0000000 0000000 00000000144 15270700723 0045162 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-asyncio/src/opentelemetry/instrumentation/asyncio # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
__version__ = "0.66b2"
test-requirements.txt 0000664 0000000 0000000 00000000444 15270700723 0036774 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-asyncio asgiref==3.8.1
Deprecated==1.2.14
iniconfig==2.0.0
packaging==24.0
pluggy==1.6.0
py-cpuinfo==9.0.0
pytest==7.4.4
pytest-asyncio==0.23.5
tomli==2.0.1
typing_extensions==4.12.2
wrapt==1.16.0
zipp==3.19.2
-e opentelemetry-instrumentation
-e instrumentation/opentelemetry-instrumentation-asyncio
opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-asyncio/tests/ 0000775 0000000 0000000 00000000000 15270700723 0033752 5 ustar 00root root 0000000 0000000 __init__.py 0000664 0000000 0000000 00000000114 15270700723 0036000 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-asyncio/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
common_test_func.py 0000664 0000000 0000000 00000001324 15270700723 0037607 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-asyncio/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
import asyncio
async def async_func():
await asyncio.sleep(0.1)
async def factorial(number: int):
factorial_value = 1
for value in range(2, number + 1):
await asyncio.sleep(0)
factorial_value *= value
return factorial_value
async def cancellable_coroutine():
await asyncio.sleep(2)
async def cancellation_coro():
task = asyncio.create_task(cancellable_coroutine())
await asyncio.sleep(0.1)
task.cancel()
await task
async def cancellation_create_task():
await asyncio.create_task(cancellation_coro())
async def ensure_future():
await asyncio.ensure_future(asyncio.sleep(0))
test_asyncio_anext.py 0000664 0000000 0000000 00000003454 15270700723 0040156 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-asyncio/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
import asyncio
from unittest.mock import patch
# pylint: disable=no-name-in-module
from opentelemetry.instrumentation.asyncio import AsyncioInstrumentor
from opentelemetry.instrumentation.asyncio.environment_variables import (
OTEL_PYTHON_ASYNCIO_COROUTINE_NAMES_TO_TRACE,
)
from opentelemetry.test.test_base import TestBase
from opentelemetry.trace import get_tracer
class TestAsyncioAnext(TestBase):
@patch.dict(
"os.environ",
{OTEL_PYTHON_ASYNCIO_COROUTINE_NAMES_TO_TRACE: "async_func"},
)
def setUp(self):
super().setUp()
AsyncioInstrumentor().instrument()
self._tracer = get_tracer(
__name__,
)
def tearDown(self):
super().tearDown()
AsyncioInstrumentor().uninstrument()
# Asyncio anext() does not have __name__ attribute, which is used to determine if the coroutine should be traced.
# This test is to ensure that the instrumentation does not break when the coroutine does not have __name__ attribute.
# Additionally, ensure the coroutine is actually awaited.
def test_asyncio_anext(self):
async def main():
async def async_gen():
# nothing special about this range other than to avoid returning a zero
# from a function named 'main' (which might cause confusion about intent)
for it in range(2, 4):
yield it
async_gen_instance = async_gen()
agen = anext(async_gen_instance)
return await asyncio.create_task(agen)
ret = asyncio.run(main())
self.assertEqual(ret, 2) # first iteration from range()
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 0)
test_asyncio_cancellation.py 0000664 0000000 0000000 00000004751 15270700723 0041474 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-asyncio/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
import asyncio
from unittest.mock import patch
# pylint: disable=no-name-in-module
from opentelemetry.instrumentation.asyncio import AsyncioInstrumentor
from opentelemetry.instrumentation.asyncio.environment_variables import (
OTEL_PYTHON_ASYNCIO_COROUTINE_NAMES_TO_TRACE,
)
from opentelemetry.test.test_base import TestBase
from opentelemetry.trace import SpanKind, get_tracer
from .common_test_func import cancellation_create_task
class TestAsyncioCancel(TestBase):
@patch.dict(
"os.environ",
{OTEL_PYTHON_ASYNCIO_COROUTINE_NAMES_TO_TRACE: "cancellation_coro, cancellable_coroutine"},
)
def setUp(self):
super().setUp()
AsyncioInstrumentor().instrument()
self._tracer = get_tracer(
__name__,
)
def tearDown(self):
super().tearDown()
AsyncioInstrumentor().uninstrument()
def test_cancel(self):
with self._tracer.start_as_current_span("root", kind=SpanKind.SERVER):
try:
asyncio.run(cancellation_create_task())
except asyncio.CancelledError:
pass
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 3)
self.assertEqual(spans[0].context.trace_id, spans[1].context.trace_id)
self.assertEqual(spans[2].context.trace_id, spans[1].context.trace_id)
self.assertEqual(spans[0].name, "asyncio coro-cancellable_coroutine")
self.assertEqual(spans[1].name, "asyncio coro-cancellation_coro")
for metric in self.memory_metrics_reader.get_metrics_data().resource_metrics[0].scope_metrics[0].metrics:
if metric.name == "asyncio.process.duration":
for point in metric.data.data_points:
self.assertEqual(point.attributes["type"], "coroutine")
self.assertIn(
point.attributes["name"],
["cancellation_coro", "cancellable_coroutine"],
)
if metric.name == "asyncio.process.created":
for point in metric.data.data_points:
self.assertEqual(point.attributes["type"], "coroutine")
self.assertIn(
point.attributes["name"],
["cancellation_coro", "cancellable_coroutine"],
)
self.assertIn(point.attributes["state"], ["finished", "cancelled"])
test_asyncio_create_task.py 0000664 0000000 0000000 00000002337 15270700723 0041323 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-asyncio/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
import asyncio
from unittest.mock import patch
# pylint: disable=no-name-in-module
from opentelemetry.instrumentation.asyncio import AsyncioInstrumentor
from opentelemetry.instrumentation.asyncio.environment_variables import (
OTEL_PYTHON_ASYNCIO_COROUTINE_NAMES_TO_TRACE,
)
from opentelemetry.test.test_base import TestBase
from opentelemetry.trace import get_tracer
from .common_test_func import factorial
class TestAsyncioCreateTask(TestBase):
@patch.dict("os.environ", {OTEL_PYTHON_ASYNCIO_COROUTINE_NAMES_TO_TRACE: "sleep"})
def setUp(self):
super().setUp()
AsyncioInstrumentor().instrument()
self._tracer = get_tracer(
__name__,
)
def tearDown(self):
super().tearDown()
AsyncioInstrumentor().uninstrument()
def test_asyncio_create_task(self):
async def async_func():
await asyncio.create_task(asyncio.sleep(0))
await asyncio.create_task(factorial(3))
asyncio.run(async_func())
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
self.assertEqual(spans[0].name, "asyncio coro-sleep")
test_asyncio_duplicate_instrument.py 0000664 0000000 0000000 00000003536 15270700723 0043302 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-asyncio/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
"""
A general test verifying that when the same Future objects (or coroutines) are
repeatedly instrumented (for example, via `trace_future`), callback references
do not leak. In this example, we mimic a typical scenario where a small set of
Futures might be reused throughout an application's lifecycle.
"""
import asyncio
from opentelemetry.instrumentation.asyncio import AsyncioInstrumentor
from opentelemetry.test.test_base import TestBase
class TestAsyncioDuplicateInstrument(TestBase):
"""
Tests whether repeated instrumentation of the same Futures leads to
exponential callback growth (potential memory leak).
"""
def setUp(self):
super().setUp()
self.loop = asyncio.new_event_loop()
asyncio.set_event_loop(self.loop)
self.instrumentor = AsyncioInstrumentor()
self.instrumentor.instrument()
def tearDown(self):
self.instrumentor.uninstrument()
self.loop.close()
asyncio.set_event_loop(None)
super().tearDown()
def test_duplicate_instrumentation_of_futures(self):
"""
If instrumentor.trace_future is called multiple times on the same Future,
we should NOT see an unbounded accumulation of callbacks.
"""
fut1 = asyncio.Future()
fut2 = asyncio.Future()
num_iterations = 10
for _ in range(num_iterations):
self.instrumentor.trace_future(fut1)
self.instrumentor.trace_future(fut2)
self.assertLessEqual(
len(fut1._callbacks),
1,
f"fut1 has {len(fut1._callbacks)} callbacks. Potential leak!",
)
self.assertLessEqual(
len(fut2._callbacks),
1,
f"fut2 has {len(fut2._callbacks)} callbacks. Potential leak!",
)
test_asyncio_ensure_future.py 0000664 0000000 0000000 00000004740 15270700723 0041731 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-asyncio/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
import asyncio
from unittest.mock import patch
import pytest
# pylint: disable=no-name-in-module
from opentelemetry.instrumentation.asyncio import AsyncioInstrumentor
from opentelemetry.instrumentation.asyncio.environment_variables import (
OTEL_PYTHON_ASYNCIO_FUTURE_TRACE_ENABLED,
)
from opentelemetry.test.test_base import TestBase
from opentelemetry.trace import get_tracer
from .common_test_func import async_func
class TestAsyncioEnsureFuture(TestBase):
@patch.dict("os.environ", {OTEL_PYTHON_ASYNCIO_FUTURE_TRACE_ENABLED: "true"})
def setUp(self):
super().setUp()
AsyncioInstrumentor().instrument()
self._tracer = get_tracer(
__name__,
)
def tearDown(self):
super().tearDown()
AsyncioInstrumentor().uninstrument()
@pytest.mark.asyncio
def test_asyncio_loop_ensure_future(self):
"""
async_func is not traced because it is not set in the environment variable
"""
async def test():
task = asyncio.ensure_future(async_func())
await task
asyncio.run(test())
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 0)
@pytest.mark.asyncio
def test_asyncio_ensure_future_with_future(self):
async def test():
with self._tracer.start_as_current_span("root"):
future = asyncio.Future()
future.set_result(1)
task = asyncio.ensure_future(future)
await task
asyncio.run(test())
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 2)
for span in spans:
if span.name == "root":
self.assertEqual(span.parent, None)
if span.name == "asyncio future":
self.assertNotEqual(span.parent.trace_id, 0)
for metric in self.memory_metrics_reader.get_metrics_data().resource_metrics[0].scope_metrics[0].metrics:
if metric.name == "asyncio.process.duration":
for point in metric.data.data_points:
self.assertEqual(point.attributes["type"], "future")
if metric.name == "asyncio.process.created":
for point in metric.data.data_points:
self.assertEqual(point.attributes["type"], "future")
self.assertEqual(point.attributes["state"], "finished")
test_asyncio_future_cancellation.py 0000664 0000000 0000000 00000003614 15270700723 0043063 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-asyncio/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
import asyncio
from unittest.mock import patch
from opentelemetry.instrumentation.asyncio import AsyncioInstrumentor
from opentelemetry.instrumentation.asyncio.environment_variables import (
OTEL_PYTHON_ASYNCIO_FUTURE_TRACE_ENABLED,
)
from opentelemetry.test.test_base import TestBase
from opentelemetry.trace import get_tracer
SCOPE = "opentelemetry.instrumentation.asyncio"
class TestTraceFuture(TestBase):
@patch.dict("os.environ", {OTEL_PYTHON_ASYNCIO_FUTURE_TRACE_ENABLED: "true"})
def setUp(self):
super().setUp()
self._tracer = get_tracer(
__name__,
)
self.instrumentor = AsyncioInstrumentor()
self.instrumentor.instrument()
def tearDown(self):
super().tearDown()
self.instrumentor.uninstrument()
def test_trace_future_cancelled(self):
async def future_cancelled():
with self._tracer.start_as_current_span("root"):
future = asyncio.Future()
future = self.instrumentor.trace_future(future)
future.cancel()
try:
asyncio.run(future_cancelled())
except asyncio.CancelledError as exc:
self.assertEqual(isinstance(exc, asyncio.CancelledError), True)
spans = self.get_finished_spans()
self.assertEqual(len(spans), 2)
self.assertEqual(spans[0].name, "root")
self.assertEqual(spans[1].name, "asyncio future")
metrics = self.get_sorted_metrics(SCOPE)
self.assertEqual(len(metrics), 2)
self.assertEqual(metrics[0].name, "asyncio.process.created")
self.assertEqual(metrics[0].data.data_points[0].attributes["state"], "cancelled")
self.assertEqual(metrics[1].name, "asyncio.process.duration")
self.assertEqual(metrics[1].data.data_points[0].attributes["state"], "cancelled")
test_asyncio_gather.py 0000664 0000000 0000000 00000002543 15270700723 0040307 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-asyncio/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
import asyncio
from unittest.mock import patch
# pylint: disable=no-name-in-module
from opentelemetry.instrumentation.asyncio import AsyncioInstrumentor
from opentelemetry.instrumentation.asyncio.environment_variables import (
OTEL_PYTHON_ASYNCIO_COROUTINE_NAMES_TO_TRACE,
)
from opentelemetry.test.test_base import TestBase
from opentelemetry.trace import get_tracer
from .common_test_func import factorial
class TestAsyncioGather(TestBase):
@patch.dict(
"os.environ",
{OTEL_PYTHON_ASYNCIO_COROUTINE_NAMES_TO_TRACE: "factorial"},
)
def setUp(self):
super().setUp()
AsyncioInstrumentor().instrument()
self._tracer = get_tracer(
__name__,
)
def tearDown(self):
super().tearDown()
AsyncioInstrumentor().uninstrument()
def test_asyncio_gather(self):
async def gather_factorial():
await asyncio.gather(factorial(2), factorial(3), factorial(4))
asyncio.run(gather_factorial())
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 3)
self.assertEqual(spans[0].name, "asyncio coro-factorial")
self.assertEqual(spans[1].name, "asyncio coro-factorial")
self.assertEqual(spans[2].name, "asyncio coro-factorial")
test_asyncio_integration.py 0000664 0000000 0000000 00000002164 15270700723 0041357 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-asyncio/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
import asyncio
from unittest.mock import patch
# pylint: disable=no-name-in-module
from opentelemetry.instrumentation.asyncio import AsyncioInstrumentor
from opentelemetry.instrumentation.asyncio.environment_variables import (
OTEL_PYTHON_ASYNCIO_COROUTINE_NAMES_TO_TRACE,
)
from opentelemetry.test.test_base import TestBase
from opentelemetry.trace import get_tracer
from .common_test_func import ensure_future
class TestAsyncioInstrumentor(TestBase):
def setUp(self):
super().setUp()
self._tracer = get_tracer(
__name__,
)
@patch.dict("os.environ", {OTEL_PYTHON_ASYNCIO_COROUTINE_NAMES_TO_TRACE: "sleep"})
def test_asyncio_integration(self):
AsyncioInstrumentor().instrument()
asyncio.run(ensure_future())
spans = self.memory_exporter.get_finished_spans()
self.memory_exporter.clear()
assert spans
AsyncioInstrumentor().uninstrument()
asyncio.run(ensure_future())
spans = self.memory_exporter.get_finished_spans()
assert not spans
test_asyncio_run_coroutine_threadsafe.py 0000664 0000000 0000000 00000003062 15270700723 0044113 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-asyncio/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
import asyncio
import threading
from concurrent.futures import ThreadPoolExecutor
from unittest.mock import patch
# pylint: disable=no-name-in-module
from opentelemetry.instrumentation.asyncio import AsyncioInstrumentor
from opentelemetry.instrumentation.asyncio.environment_variables import (
OTEL_PYTHON_ASYNCIO_COROUTINE_NAMES_TO_TRACE,
)
from opentelemetry.test.test_base import TestBase
from opentelemetry.trace import get_tracer
class TestRunCoroutineThreadSafe(TestBase):
@patch.dict("os.environ", {OTEL_PYTHON_ASYNCIO_COROUTINE_NAMES_TO_TRACE: "coro"})
def setUp(self):
super().setUp()
AsyncioInstrumentor().instrument()
self.loop = asyncio.new_event_loop()
self.executor = ThreadPoolExecutor(max_workers=1)
self.loop.set_default_executor(self.executor)
self.thread = threading.Thread(target=self.loop.run_forever)
self.thread.start()
self._tracer = get_tracer(
__name__,
)
def tearDown(self):
super().tearDown()
self.loop.call_soon_threadsafe(self.loop.stop)
self.thread.join()
self.loop.close()
AsyncioInstrumentor().uninstrument()
def test_run_coroutine_threadsafe(self):
async def coro():
return 42
future = asyncio.run_coroutine_threadsafe(coro(), self.loop)
result = future.result(timeout=1)
self.assertEqual(result, 42)
spans = self.memory_exporter.get_finished_spans()
assert spans
test_asyncio_taskgroup.py 0000664 0000000 0000000 00000003015 15270700723 0041047 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-asyncio/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
import asyncio
import sys
from unittest import skipIf
from unittest.mock import patch
# pylint: disable=no-name-in-module
from opentelemetry.instrumentation.asyncio import AsyncioInstrumentor
from opentelemetry.instrumentation.asyncio.environment_variables import (
OTEL_PYTHON_ASYNCIO_COROUTINE_NAMES_TO_TRACE,
)
from opentelemetry.test.test_base import TestBase
from opentelemetry.trace import get_tracer
from .common_test_func import async_func
class TestAsyncioTaskgroup(TestBase):
@patch.dict(
"os.environ",
{OTEL_PYTHON_ASYNCIO_COROUTINE_NAMES_TO_TRACE: "async_func"},
)
def setUp(self):
super().setUp()
AsyncioInstrumentor().instrument()
self._tracer = get_tracer(
__name__,
)
def tearDown(self):
super().tearDown()
AsyncioInstrumentor().uninstrument()
@skipIf(
sys.version_info < (3, 11),
"TaskGroup is only available in Python 3.11+",
)
def test_task_group_create_task(self):
async def main():
async with asyncio.TaskGroup() as tg: # pylint: disable=no-member
for _ in range(10):
tg.create_task(async_func())
with self._tracer.start_as_current_span("root"):
asyncio.run(main())
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 11)
self.assertEqual(spans[4].context.trace_id, spans[5].context.trace_id)
test_asyncio_to_thread.py 0000664 0000000 0000000 00000015423 15270700723 0041007 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-asyncio/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
import asyncio
import functools
import time
from unittest.mock import patch
# pylint: disable=no-name-in-module
from opentelemetry.instrumentation.asyncio import AsyncioInstrumentor
from opentelemetry.instrumentation.asyncio.environment_variables import (
OTEL_PYTHON_ASYNCIO_TO_THREAD_FUNCTION_NAMES_TO_TRACE,
)
from opentelemetry.test.test_base import TestBase
from opentelemetry.trace import StatusCode, get_tracer
SCOPE = "opentelemetry.instrumentation.asyncio"
SLEEP_SECONDS = 0.05
class TestAsyncioToThread(TestBase):
@patch.dict(
"os.environ",
{OTEL_PYTHON_ASYNCIO_TO_THREAD_FUNCTION_NAMES_TO_TRACE: "multiply"},
)
def setUp(self):
super().setUp()
AsyncioInstrumentor().instrument()
self._tracer = get_tracer(
__name__,
)
def tearDown(self):
super().tearDown()
AsyncioInstrumentor().uninstrument()
def get_created_and_duration_metrics(self):
metrics = self.get_sorted_metrics(SCOPE)
self.assertEqual(len(metrics), 2)
self.assertEqual(metrics[0].name, "asyncio.process.created")
self.assertEqual(metrics[1].name, "asyncio.process.duration")
return metrics[0], metrics[1]
def test_to_thread(self):
def multiply(x, y):
return x * y
with self._tracer.start_as_current_span("root"):
result = asyncio.run(asyncio.to_thread(multiply, 2, 3))
assert result == 6
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 2)
assert spans[0].name == "asyncio to_thread-multiply"
created, duration = self.get_created_and_duration_metrics()
for metric in (created, duration):
self.assertEqual(len(metric.data.data_points), 1)
point = metric.data.data_points[0]
self.assertEqual(point.attributes["type"], "to_thread")
self.assertEqual(point.attributes["name"], "multiply")
def test_to_thread_duration_covers_execution(self):
def multiply(x, y):
time.sleep(SLEEP_SECONDS)
return x * y
asyncio.run(asyncio.to_thread(multiply, 2, 3))
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
span = spans[0]
# only a lower bound is asserted: it is what fails when the span does
# not cover the call, and an upper bound would be flaky on a busy CI
# host where the worker thread can be descheduled.
self.assertGreaterEqual(
(span.end_time - span.start_time) / 10**9,
SLEEP_SECONDS * 0.9,
)
_, duration = self.get_created_and_duration_metrics()
self.assertEqual(len(duration.data.data_points), 1)
self.assertGreaterEqual(
duration.data.data_points[0].sum,
SLEEP_SECONDS * 0.9,
)
def test_to_thread_exception(self):
def multiply(x, y):
raise ValueError("fail")
with self.assertRaises(ValueError):
asyncio.run(asyncio.to_thread(multiply, 2, 3))
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
span = spans[0]
self.assertEqual(span.name, "asyncio to_thread-multiply")
self.assertEqual(span.status.status_code, StatusCode.ERROR)
self.assertEqual(len(span.events), 1)
self.assertEqual(span.events[0].name, "exception")
created, duration = self.get_created_and_duration_metrics()
for metric in (created, duration):
self.assertEqual(len(metric.data.data_points), 1)
self.assertEqual(metric.data.data_points[0].attributes["state"], "exception")
def test_to_thread_timeout_state(self):
def multiply(x, y):
raise asyncio.TimeoutError("fail")
with self.assertRaises(asyncio.TimeoutError):
asyncio.run(asyncio.to_thread(multiply, 2, 3))
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
span = spans[0]
self.assertEqual(span.status.status_code, StatusCode.ERROR)
self.assertEqual(len(span.events), 1)
self.assertEqual(span.events[0].name, "exception")
created, duration = self.get_created_and_duration_metrics()
for metric in (created, duration):
self.assertEqual(len(metric.data.data_points), 1)
self.assertEqual(metric.data.data_points[0].attributes["state"], "timeout")
def test_to_thread_cancelled_state(self):
def multiply(x, y):
raise asyncio.CancelledError()
with self.assertRaises(asyncio.CancelledError):
asyncio.run(asyncio.to_thread(multiply, 2, 3))
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
span = spans[0]
# cancellation is not an error, consistent with coroutines and futures
self.assertEqual(span.status.status_code, StatusCode.UNSET)
self.assertEqual(len(span.events), 0)
created, duration = self.get_created_and_duration_metrics()
for metric in (created, duration):
self.assertEqual(len(metric.data.data_points), 1)
self.assertEqual(metric.data.data_points[0].attributes["state"], "cancelled")
def test_to_thread_repeated_calls(self):
def multiply(x, y):
return x * y
async def to_thread():
assert await asyncio.to_thread(multiply, 2, 3) == 6
assert await asyncio.to_thread(multiply, 4, 5) == 20
asyncio.run(to_thread())
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 2)
created, duration = self.get_created_and_duration_metrics()
self.assertEqual(len(created.data.data_points), 1)
self.assertEqual(created.data.data_points[0].value, 2)
self.assertEqual(len(duration.data.data_points), 1)
self.assertEqual(duration.data.data_points[0].count, 2)
def test_to_thread_partial_func(self):
def multiply(x, y):
return x * y
double = functools.partial(multiply, 2)
with self._tracer.start_as_current_span("root"):
result = asyncio.run(asyncio.to_thread(double, 3))
assert result == 6
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 2)
assert spans[0].name == "asyncio to_thread-multiply"
created, duration = self.get_created_and_duration_metrics()
for metric in (created, duration):
self.assertEqual(len(metric.data.data_points), 1)
point = metric.data.data_points[0]
self.assertEqual(point.attributes["type"], "to_thread")
self.assertEqual(point.attributes["name"], "multiply")
test_asyncio_utils.py 0000664 0000000 0000000 00000001637 15270700723 0040200 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-asyncio/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
from unittest import TestCase
from unittest.mock import patch
# pylint: disable=no-name-in-module
from opentelemetry.instrumentation.asyncio.environment_variables import (
OTEL_PYTHON_ASYNCIO_COROUTINE_NAMES_TO_TRACE,
OTEL_PYTHON_ASYNCIO_FUTURE_TRACE_ENABLED,
)
from opentelemetry.instrumentation.asyncio.utils import (
get_coros_to_trace,
get_future_trace_enabled,
)
class TestAsyncioToThread(TestCase):
@patch.dict(
"os.environ",
{OTEL_PYTHON_ASYNCIO_COROUTINE_NAMES_TO_TRACE: "test1,test2,test3 ,test4"},
)
def test_separator(self):
self.assertEqual(get_coros_to_trace(), {"test1", "test2", "test3", "test4"})
@patch.dict("os.environ", {OTEL_PYTHON_ASYNCIO_FUTURE_TRACE_ENABLED: "true"})
def test_future_trace_enabled(self):
self.assertEqual(get_future_trace_enabled(), True)
test_asyncio_wait.py 0000664 0000000 0000000 00000006034 15270700723 0040000 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-asyncio/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
import asyncio
import sys
from unittest.mock import patch
# pylint: disable=no-name-in-module
from opentelemetry.instrumentation.asyncio import AsyncioInstrumentor
from opentelemetry.instrumentation.asyncio.environment_variables import (
OTEL_PYTHON_ASYNCIO_COROUTINE_NAMES_TO_TRACE,
)
from opentelemetry.test.test_base import TestBase
from opentelemetry.trace import get_tracer
from .common_test_func import async_func
class TestAsyncioWait(TestBase):
@patch.dict(
"os.environ",
{OTEL_PYTHON_ASYNCIO_COROUTINE_NAMES_TO_TRACE: "async_func"},
)
def setUp(self):
super().setUp()
AsyncioInstrumentor().instrument()
self._tracer = get_tracer(
__name__,
)
def tearDown(self):
super().tearDown()
AsyncioInstrumentor().uninstrument()
def test_asyncio_wait_with_create_task(self):
async def main():
if sys.version_info >= (3, 11):
# In Python 3.11, you can't send coroutines directly to asyncio.wait().
# Instead, you must wrap them in asyncio.create_task().
tasks = [
asyncio.create_task(async_func()),
asyncio.create_task(async_func()),
]
await asyncio.wait(tasks)
else:
await asyncio.wait([async_func(), async_func()])
asyncio.run(main())
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 2)
def test_asyncio_wait_for(self):
async def main():
await asyncio.wait_for(async_func(), 1)
await asyncio.wait_for(async_func(), 1)
asyncio.run(main())
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 2)
def test_asyncio_wait_for_with_timeout(self):
expected_timeout_error = None
async def main():
nonlocal expected_timeout_error
try:
await asyncio.wait_for(async_func(), 0.01)
except asyncio.TimeoutError as timeout_error:
expected_timeout_error = timeout_error
asyncio.run(main())
self.assertNotEqual(expected_timeout_error, None)
def test_asyncio_as_completed(self):
async def main():
if sys.version_info >= (3, 11):
# In Python 3.11, you can't send coroutines directly to asyncio.as_completed().
# Instead, you must wrap them in asyncio.create_task().
tasks = [
asyncio.create_task(async_func()),
asyncio.create_task(async_func()),
]
for task in asyncio.as_completed(tasks):
await task
else:
for task in asyncio.as_completed([async_func(), async_func()]):
await task
asyncio.run(main())
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 2)
opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-asyncpg/ 0000775 0000000 0000000 00000000000 15270700723 0032607 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-asyncpg/LICENSE 0000664 0000000 0000000 00000026135 15270700723 0033623 0 ustar 00root root 0000000 0000000 Apache License
Version 2.0, January 2004
http://www.apache.org/licenses/
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opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-asyncpg/README.rst0000664 0000000 0000000 00000001440 15270700723 0034275 0 ustar 00root root 0000000 0000000 OpenTelemetry asyncpg Instrumentation
=====================================
|pypi|
.. |pypi| image:: https://badge.fury.io/py/opentelemetry-instrumentation-asyncpg.svg
:target: https://pypi.org/project/opentelemetry-instrumentation-asyncpg/
This library allows tracing PostgreSQL queries made by the
`asyncpg `_ library.
Installation
------------
::
pip install opentelemetry-instrumentation-asyncpg
References
----------
* `OpenTelemetry asyncpg Instrumentation `_
* `OpenTelemetry Project `_
* `OpenTelemetry Python Examples `_
pyproject.toml 0000664 0000000 0000000 00000003140 15270700723 0035442 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-asyncpg [build-system]
requires = ["hatchling"]
build-backend = "hatchling.build"
[project]
name = "opentelemetry-instrumentation-asyncpg"
dynamic = ["version"]
description = "OpenTelemetry instrumentation for AsyncPG"
readme = "README.rst"
license = "Apache-2.0"
requires-python = ">=3.10"
authors = [
{ name = "OpenTelemetry Authors", email = "cncf-opentelemetry-contributors@lists.cncf.io" },
]
classifiers = [
"Development Status :: 4 - Beta",
"Intended Audience :: Developers",
"License :: OSI Approved :: Apache Software License",
"Programming Language :: Python",
"Programming Language :: Python :: 3",
"Programming Language :: Python :: 3.10",
"Programming Language :: Python :: 3.11",
"Programming Language :: Python :: 3.12",
"Programming Language :: Python :: 3.13",
"Programming Language :: Python :: 3.14",
]
dependencies = [
"opentelemetry-api ~= 1.12",
"opentelemetry-instrumentation == 0.66b2",
"opentelemetry-semantic-conventions == 0.66b2",
]
[project.optional-dependencies]
instruments = [
"asyncpg >= 0.12.0",
]
[project.entry-points.opentelemetry_instrumentor]
asyncpg = "opentelemetry.instrumentation.asyncpg:AsyncPGInstrumentor"
[project.urls]
Homepage = "https://github.com/open-telemetry/opentelemetry-python-contrib/tree/main/instrumentation/opentelemetry-instrumentation-asyncpg"
Repository = "https://github.com/open-telemetry/opentelemetry-python-contrib"
[tool.hatch.version]
path = "src/opentelemetry/instrumentation/asyncpg/version.py"
[tool.hatch.build.targets.sdist]
include = [
"/src",
"/tests",
]
[tool.hatch.build.targets.wheel]
packages = ["src/opentelemetry"]
opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-asyncpg/src/ 0000775 0000000 0000000 00000000000 15270700723 0033376 5 ustar 00root root 0000000 0000000 opentelemetry/ 0000775 0000000 0000000 00000000000 15270700723 0036213 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-asyncpg/src instrumentation/ 0000775 0000000 0000000 00000000000 15270700723 0041456 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-asyncpg/src/opentelemetry asyncpg/ 0000775 0000000 0000000 00000000000 15270700723 0043122 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-asyncpg/src/opentelemetry/instrumentation __init__.py 0000664 0000000 0000000 00000025767 15270700723 0045254 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-asyncpg/src/opentelemetry/instrumentation/asyncpg # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
"""
This library allows tracing PostgreSQL queries made by the
`asyncpg `_ library.
Usage
-----
Start PostgreSQL:
::
docker run -e POSTGRES_USER=user -e POSTGRES_PASSWORD=password -e POSTGRES_DATABASE=database -p 5432:5432 postgres
Run instrumented code:
.. code-block:: python
import asyncio
import asyncpg
from opentelemetry.instrumentation.asyncpg import AsyncPGInstrumentor
# You can optionally pass a custom TracerProvider to AsyncPGInstrumentor.instrument()
AsyncPGInstrumentor().instrument()
async def main():
conn = await asyncpg.connect(user="user", password="password")
await conn.fetch('''SELECT 42;''')
await conn.close()
asyncio.run(main())
API
---
"""
import re
from collections.abc import Collection
import asyncpg
import asyncpg.prepared_stmt
import wrapt
from opentelemetry import trace
from opentelemetry.instrumentation._semconv import (
_get_schema_url_for_signal_types,
_OpenTelemetrySemanticConventionStability,
_OpenTelemetryStabilitySignalType,
_report_new,
_set_db_name,
_set_db_statement,
_set_db_system,
_set_db_user,
_set_http_net_peer_name_client,
_set_http_peer_port_client,
_set_net_transport,
_StabilityMode,
)
from opentelemetry.instrumentation.asyncpg.package import _instruments
from opentelemetry.instrumentation.asyncpg.version import __version__
from opentelemetry.instrumentation.instrumentor import BaseInstrumentor
from opentelemetry.instrumentation.utils import is_instrumentation_enabled, unwrap
from opentelemetry.semconv._incubating.attributes.db_attributes import (
DbSystemValues,
)
from opentelemetry.semconv._incubating.attributes.net_attributes import (
NetTransportValues,
)
from opentelemetry.semconv.attributes.error_attributes import ERROR_TYPE
from opentelemetry.semconv.attributes.network_attributes import (
NetworkTransportValues,
)
from opentelemetry.trace import SpanKind
from opentelemetry.trace.status import Status, StatusCode
_PREPARED_STMT_METHODS = (
"fetch",
"fetchval",
"fetchrow",
"executemany",
"fetchmany",
)
def _hydrate_span_from_args(
connection,
query,
parameters,
semconv_opt_in_mode=_StabilityMode.DEFAULT,
) -> dict:
"""Get network and database span attributes"""
span_attributes: dict = {}
_set_db_system(
span_attributes,
DbSystemValues.POSTGRESQL.value,
semconv_opt_in_mode,
)
# connection contains _params attribute which is a namedtuple ConnectionParameters.
# https://github.com/MagicStack/asyncpg/blob/master/asyncpg/connection.py#L68
params = getattr(connection, "_params", None)
dbname = getattr(params, "database", None)
if dbname:
_set_db_name(span_attributes, dbname, semconv_opt_in_mode)
user = getattr(params, "user", None)
if user:
_set_db_user(span_attributes, user, semconv_opt_in_mode)
# connection contains _addr attribute which is either a host/port tuple, or unix socket string
# https://magicstack.github.io/asyncpg/current/_modules/asyncpg/connection.html
addr = getattr(connection, "_addr", None)
if isinstance(addr, tuple):
_set_http_net_peer_name_client(span_attributes, addr[0], semconv_opt_in_mode)
_set_http_peer_port_client(span_attributes, addr[1], semconv_opt_in_mode)
_set_net_transport(
span_attributes,
NetTransportValues.IP_TCP.value,
NetworkTransportValues.TCP.value,
semconv_opt_in_mode,
)
elif isinstance(addr, str):
_set_http_net_peer_name_client(span_attributes, addr, semconv_opt_in_mode)
_set_net_transport(
span_attributes,
NetTransportValues.OTHER.value,
NetworkTransportValues.PIPE.value,
semconv_opt_in_mode,
)
if query is not None:
_set_db_statement(span_attributes, query, semconv_opt_in_mode)
if parameters is not None and len(parameters) > 0:
span_attributes["db.statement.parameters"] = str(parameters)
return span_attributes
class AsyncPGInstrumentor(BaseInstrumentor):
_leading_comment_remover = re.compile(r"^/\*.*?\*/")
_tracer = None
def __init__(self, capture_parameters=False):
super().__init__()
self.capture_parameters = capture_parameters
def instrumentation_dependencies(self) -> Collection[str]:
return _instruments
def _instrument(self, **kwargs):
tracer_provider = kwargs.get("tracer_provider")
_OpenTelemetrySemanticConventionStability._initialize()
self._semconv_opt_in_mode = _OpenTelemetrySemanticConventionStability._get_opentelemetry_stability_opt_in_mode(
_OpenTelemetryStabilitySignalType.DATABASE,
)
self._tracer = trace.get_tracer(
__name__,
__version__,
tracer_provider,
schema_url=_get_schema_url_for_signal_types(
[
_OpenTelemetryStabilitySignalType.DATABASE,
]
),
)
for method in [
"Connection.execute",
"Connection.executemany",
"Connection.fetch",
"Connection.fetchval",
"Connection.fetchrow",
]:
wrapt.wrap_function_wrapper("asyncpg.connection", method, self._do_execute)
for method in [
"Cursor.fetch",
"Cursor.forward",
"Cursor.fetchrow",
"CursorIterator.__anext__",
]:
wrapt.wrap_function_wrapper("asyncpg.cursor", method, self._do_cursor_execute)
for method in _PREPARED_STMT_METHODS:
if hasattr(asyncpg.prepared_stmt.PreparedStatement, method):
wrapt.wrap_function_wrapper(
"asyncpg.prepared_stmt",
f"PreparedStatement.{method}",
self._do_prepared_execute,
)
def _uninstrument(self, **__):
for cls, methods in [
(
asyncpg.connection.Connection,
("execute", "executemany", "fetch", "fetchval", "fetchrow"),
),
(asyncpg.cursor.Cursor, ("forward", "fetch", "fetchrow")),
(asyncpg.cursor.CursorIterator, ("__anext__",)),
]:
for method_name in methods:
unwrap(cls, method_name)
for method_name in _PREPARED_STMT_METHODS:
if hasattr(asyncpg.prepared_stmt.PreparedStatement, method_name):
unwrap(asyncpg.prepared_stmt.PreparedStatement, method_name)
async def _do_execute(self, func, instance, args, kwargs):
if not is_instrumentation_enabled():
return await func(*args, **kwargs)
exception = None
params = getattr(instance, "_params", None)
name = args[0] if args[0] else getattr(params, "database", "postgresql")
try:
# Strip leading comments so we get the operation name.
name = self._leading_comment_remover.sub("", name).split()[0]
except IndexError:
name = ""
# Hydrate attributes before span creation to enable filtering
span_attributes = _hydrate_span_from_args(
instance,
args[0],
args[1:] if self.capture_parameters else None,
semconv_opt_in_mode=self._semconv_opt_in_mode,
)
with self._tracer.start_as_current_span(name, kind=SpanKind.CLIENT, attributes=span_attributes) as span:
try:
result = await func(*args, **kwargs)
except Exception as exc: # pylint: disable=W0703
exception = exc
raise
finally:
if span.is_recording() and exception is not None:
span.set_status(Status(StatusCode.ERROR))
if _report_new(self._semconv_opt_in_mode):
span.set_attribute(ERROR_TYPE, type(exception).__qualname__)
return result
async def _do_cursor_execute(self, func, instance, args, kwargs):
"""Wrap cursor based functions. For every call this will generate a new span."""
if not is_instrumentation_enabled():
return await func(*args, **kwargs)
exception = None
params = getattr(instance._connection, "_params", None)
name = instance._query if instance._query else getattr(params, "database", "postgresql")
try:
# Strip leading comments so we get the operation name.
name = self._leading_comment_remover.sub("", name).split()[0]
except IndexError:
name = ""
# Hydrate attributes before span creation to enable filtering
span_attributes = _hydrate_span_from_args(
instance._connection,
instance._query,
instance._args if self.capture_parameters else None,
semconv_opt_in_mode=self._semconv_opt_in_mode,
)
stop = False
with self._tracer.start_as_current_span(
f"CURSOR: {name}",
kind=SpanKind.CLIENT,
attributes=span_attributes,
) as span:
try:
result = await func(*args, **kwargs)
except StopAsyncIteration:
# Do not show this exception to the span
stop = True
except Exception as exc: # pylint: disable=W0703
exception = exc
raise
finally:
if span.is_recording() and exception is not None:
span.set_status(Status(StatusCode.ERROR))
if _report_new(self._semconv_opt_in_mode):
span.set_attribute(ERROR_TYPE, type(exception).__qualname__)
if not stop:
return result
raise StopAsyncIteration
async def _do_prepared_execute(self, func, instance, args, kwargs):
if not is_instrumentation_enabled():
return await func(*args, **kwargs)
exception = None
query = instance._query or ""
try:
name = self._leading_comment_remover.sub("", query).split()[0]
except IndexError:
name = ""
span_attributes = _hydrate_span_from_args(
instance._connection,
query,
args if self.capture_parameters else None,
semconv_opt_in_mode=self._semconv_opt_in_mode,
)
with self._tracer.start_as_current_span(name, kind=SpanKind.CLIENT, attributes=span_attributes) as span:
try:
result = await func(*args, **kwargs)
except Exception as exc: # pylint: disable=W0703
exception = exc
raise
finally:
if span.is_recording() and exception is not None:
span.set_status(Status(StatusCode.ERROR))
if _report_new(self._semconv_opt_in_mode):
span.set_attribute(ERROR_TYPE, type(exception).__qualname__)
return result
package.py 0000664 0000000 0000000 00000000223 15270700723 0045064 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-asyncpg/src/opentelemetry/instrumentation/asyncpg # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
_instruments = ("asyncpg >= 0.12.0",)
_semconv_status = "migration"
version.py 0000664 0000000 0000000 00000000144 15270700723 0045160 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-asyncpg/src/opentelemetry/instrumentation/asyncpg # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
__version__ = "0.66b2"
test-requirements-wrapt1.txt 0000664 0000000 0000000 00000000047 15270700723 0040206 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-asyncpg -r test-requirements.txt
wrapt==1.17.3
test-requirements-wrapt2.txt 0000664 0000000 0000000 00000000046 15270700723 0040206 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-asyncpg -r test-requirements.txt
wrapt==2.1.2
test-requirements.txt 0000664 0000000 0000000 00000000421 15270700723 0036766 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-asyncpg asgiref==3.8.1
async-timeout==4.0.3
asyncpg==0.30.0
iniconfig==2.0.0
packaging==24.0
pluggy==1.6.0
py-cpuinfo==9.0.0
pytest==7.4.4
tomli==2.0.1
typing_extensions==4.12.2
zipp==3.19.2
-e opentelemetry-instrumentation
-e instrumentation/opentelemetry-instrumentation-asyncpg
opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-asyncpg/tests/ 0000775 0000000 0000000 00000000000 15270700723 0033751 5 ustar 00root root 0000000 0000000 __init__.py 0000664 0000000 0000000 00000000000 15270700723 0035771 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-asyncpg/tests test_asyncpg_wrapper.py 0000664 0000000 0000000 00000050562 15270700723 0040517 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-asyncpg/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
import asyncio
import contextlib
from unittest import mock
import asyncpg
import asyncpg.connection
import pytest
from asyncpg import Connection, Record, cursor
from asyncpg.prepared_stmt import PreparedStatement
try:
# wrapt 2.0.0+
from wrapt import BaseObjectProxy # pylint: disable=no-name-in-module
except ImportError:
from wrapt import ObjectProxy as BaseObjectProxy
from opentelemetry import trace as trace_api
from opentelemetry.instrumentation._semconv import (
OTEL_SEMCONV_STABILITY_OPT_IN,
_OpenTelemetrySemanticConventionStability,
)
from opentelemetry.instrumentation.asyncpg import (
_PREPARED_STMT_METHODS,
AsyncPGInstrumentor,
)
from opentelemetry.instrumentation.utils import suppress_instrumentation
from opentelemetry.semconv._incubating.attributes.db_attributes import (
DB_NAME,
DB_STATEMENT,
DB_SYSTEM,
DB_USER,
)
from opentelemetry.semconv._incubating.attributes.net_attributes import (
NET_PEER_NAME,
NET_PEER_PORT,
NET_TRANSPORT,
NetTransportValues,
)
from opentelemetry.semconv.attributes.db_attributes import (
DB_NAMESPACE,
DB_QUERY_TEXT,
DB_SYSTEM_NAME,
)
from opentelemetry.semconv.attributes.error_attributes import ERROR_TYPE
from opentelemetry.semconv.attributes.server_attributes import (
SERVER_ADDRESS,
SERVER_PORT,
)
from opentelemetry.test.test_base import TestBase
@contextlib.contextmanager
def use_semconv_opt_in(sem_conv_mode):
env_patch = mock.patch.dict(
"os.environ",
{OTEL_SEMCONV_STABILITY_OPT_IN: sem_conv_mode},
)
_OpenTelemetrySemanticConventionStability._initialized = False
env_patch.start()
try:
yield
finally:
env_patch.stop()
_OpenTelemetrySemanticConventionStability._initialized = False
class TestAsyncPGInstrumentation(TestBase):
def tearDown(self):
super().tearDown()
AsyncPGInstrumentor().uninstrument()
def test_duplicated_instrumentation_can_be_uninstrumented(self):
AsyncPGInstrumentor().instrument()
AsyncPGInstrumentor().instrument()
AsyncPGInstrumentor().instrument()
AsyncPGInstrumentor().uninstrument()
for method_name in ["execute", "fetch"]:
method = getattr(Connection, method_name, None)
self.assertFalse(hasattr(method, "_opentelemetry_ext_asyncpg_applied"))
def test_duplicated_instrumentation_works(self):
first = AsyncPGInstrumentor()
first.instrument()
second = AsyncPGInstrumentor()
second.instrument()
self.assertIsNotNone(first._tracer)
self.assertIsNotNone(second._tracer)
def test_duplicated_uninstrumentation(self):
AsyncPGInstrumentor().instrument()
AsyncPGInstrumentor().uninstrument()
AsyncPGInstrumentor().uninstrument()
AsyncPGInstrumentor().uninstrument()
for method_name in ["execute", "fetch"]:
method = getattr(Connection, method_name, None)
self.assertFalse(hasattr(method, "_opentelemetry_ext_asyncpg_applied"))
def test_cursor_instrumentation(self):
def assert_wrapped(assert_fnc):
for cls, methods in [
(cursor.Cursor, ("forward", "fetch", "fetchrow")),
(cursor.CursorIterator, ("__anext__",)),
]:
for method_name in methods:
method = getattr(cls, method_name, None)
assert_fnc(
isinstance(method, BaseObjectProxy),
f"{method} isinstance {type(method)}",
)
assert_wrapped(self.assertFalse)
AsyncPGInstrumentor().instrument()
assert_wrapped(self.assertTrue)
AsyncPGInstrumentor().uninstrument()
assert_wrapped(self.assertFalse)
def test_cursor_span_creation(self):
"""Test the cursor wrapper if it creates spans correctly."""
# Mock out all interaction with postgres
async def bind_mock(*args, **kwargs):
return []
async def exec_mock(*args, **kwargs):
return [], None, True
conn = mock.Mock()
conn.is_closed = lambda: False
conn._protocol = mock.Mock()
conn._protocol.bind = bind_mock
conn._protocol.execute = exec_mock
conn._protocol.bind_execute = exec_mock
conn._protocol.close_portal = bind_mock
state = mock.Mock()
state.closed = False
apg = AsyncPGInstrumentor()
apg.instrument(tracer_provider=self.tracer_provider)
# init the cursor and fetch a single record
crs = cursor.Cursor(conn, "SELECT * FROM test", state, [], Record)
asyncio.run(crs._init(1))
with suppress_instrumentation():
self.assertEqual(asyncio.run(crs.fetch(1)), [])
self.assertEqual(self.memory_exporter.get_finished_spans(), ())
asyncio.run(crs.fetch(1))
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
self.assertEqual(spans[0].name, "CURSOR: SELECT")
self.assertTrue(spans[0].status.is_ok)
# Now test that the StopAsyncIteration of the cursor does not get recorded as an ERROR
crs_iter = cursor.CursorIterator(conn, "SELECT * FROM test", state, [], Record, 1, 1)
with suppress_instrumentation(), pytest.raises(StopAsyncIteration):
asyncio.run(anext(crs_iter))
self.assertEqual(len(self.memory_exporter.get_finished_spans()), 1)
with pytest.raises(StopAsyncIteration):
asyncio.run(anext(crs_iter))
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 2)
self.assertEqual([span.status.is_ok for span in spans], [True, True])
def test_no_op_tracer_provider(self):
AsyncPGInstrumentor().uninstrument()
AsyncPGInstrumentor().instrument(tracer_provider=trace_api.NoOpTracerProvider())
# Mock out all interaction with postgres
async def bind_mock(*args, **kwargs):
return []
async def exec_mock(*args, **kwargs):
return [], None, True
conn = mock.Mock()
conn.is_closed = lambda: False
conn._protocol = mock.Mock()
conn._protocol.bind = bind_mock
conn._protocol.execute = exec_mock
conn._protocol.bind_execute = exec_mock
conn._protocol.close_portal = bind_mock
state = mock.Mock()
state.closed = False
# init the cursor and fetch a single record
crs = cursor.Cursor(conn, "SELECT * FROM test", state, [], Record)
asyncio.run(crs._init(1))
asyncio.run(crs.fetch(1))
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 0)
def test_prepared_statement_instrumentation(self):
methods = [m for m in _PREPARED_STMT_METHODS if hasattr(PreparedStatement, m)]
for method_name in methods:
with self.subTest(method=method_name, phase="before"):
self.assertFalse(
isinstance(
getattr(PreparedStatement, method_name),
BaseObjectProxy,
)
)
AsyncPGInstrumentor().instrument()
for method_name in methods:
with self.subTest(method=method_name, phase="instrumented"):
self.assertTrue(
isinstance(
getattr(PreparedStatement, method_name),
BaseObjectProxy,
)
)
AsyncPGInstrumentor().uninstrument()
for method_name in methods:
with self.subTest(method=method_name, phase="uninstrumented"):
self.assertFalse(
isinstance(
getattr(PreparedStatement, method_name),
BaseObjectProxy,
)
)
@staticmethod
def _make_prepared_stmt_conn():
async def bind_execute_mock(*args, **kwargs):
return [], b"SELECT 1", True
async def bind_execute_many_mock(*args, **kwargs):
return None
conn = mock.Mock()
conn._pool_release_ctr = 0
conn.is_closed = lambda: False
conn._protocol = mock.Mock()
conn._protocol.bind_execute = bind_execute_mock
conn._protocol.bind_execute_many = bind_execute_many_mock
state = mock.Mock()
state.closed = False
return conn, state
def test_prepared_statement_span(self):
# Per-method: (query, call_args, expected_span_name)
method_cases = {
"fetch": ("SELECT * FROM users", (), "SELECT"),
"fetchval": ("SELECT id FROM users WHERE id=$1", (1,), "SELECT"),
"fetchrow": ("SELECT * FROM t WHERE v=$1", ("x",), "SELECT"),
"executemany": (
"INSERT INTO t (v) VALUES ($1)",
([("a",), ("b",)],),
"INSERT",
),
"fetchmany": ("SELECT * FROM t", ([],), "SELECT"),
}
for method_name in _PREPARED_STMT_METHODS:
if not hasattr(PreparedStatement, method_name):
continue
query, call_args, expected_name = method_cases[method_name]
with self.subTest(method=method_name):
self.memory_exporter.clear()
conn, state = self._make_prepared_stmt_conn()
apg = AsyncPGInstrumentor()
apg.instrument(tracer_provider=self.tracer_provider)
stmt = PreparedStatement(conn, query, state)
with suppress_instrumentation():
suppressed_result = asyncio.run(getattr(stmt, method_name)(*call_args))
self.assertEqual(self.memory_exporter.get_finished_spans(), ())
result = asyncio.run(getattr(stmt, method_name)(*call_args))
self.assertEqual(result, suppressed_result)
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
self.assertEqual(spans[0].name, expected_name)
self.assertTrue(spans[0].status.is_ok)
self.assertEqual(spans[0].attributes.get("db.statement"), query)
self.assertEqual(spans[0].attributes.get("db.system"), "postgresql")
apg.uninstrument()
def test_prepared_statement_error_span(self):
async def bind_execute_error(*args, **kwargs):
raise RuntimeError("db error")
conn = mock.Mock()
conn._pool_release_ctr = 0
conn.is_closed = lambda: False
conn._protocol = mock.Mock()
conn._protocol.bind_execute = bind_execute_error
state = mock.Mock()
state.closed = False
apg = AsyncPGInstrumentor()
apg.instrument(tracer_provider=self.tracer_provider)
stmt = PreparedStatement(conn, "SELECT 1", state)
with suppress_instrumentation(), self.assertRaisesRegex(RuntimeError, "db error"):
asyncio.run(stmt.fetch())
self.assertEqual(self.memory_exporter.get_finished_spans(), ())
with self.assertRaises(RuntimeError):
asyncio.run(stmt.fetch())
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
self.assertFalse(spans[0].status.is_ok)
class TestAsyncPGSemconvMigration(TestBase):
def setUp(self):
super().setUp()
_OpenTelemetrySemanticConventionStability._initialized = False
def tearDown(self):
super().tearDown()
AsyncPGInstrumentor().uninstrument()
_OpenTelemetrySemanticConventionStability._initialized = False
@staticmethod
def _make_execute_conn(addr=("testhost", 5432)):
async def query_mock(*args, **kwargs):
return b"SELECT 1", [], True
async def execute_mock(*args, **kwargs):
return [], b"SELECT 1", True
conn = mock.Mock()
conn.is_closed = lambda: False
conn._pool_release_ctr = 0
conn._query_loggers = []
conn._execute = execute_mock
conn._protocol = mock.Mock()
conn._protocol.query = query_mock
conn._addr = addr
params = mock.Mock()
params.database = "testdb"
params.user = "testuser"
conn._params = params
return conn
def _run_execute(self, conn, query="SELECT 1"):
apg = AsyncPGInstrumentor()
apg.instrument(tracer_provider=self.tracer_provider)
async def do_execute():
# Use __get__ to bind conn as the instance so wrapt correctly
# receives instance=conn instead of instance=None.
execute = asyncpg.connection.Connection.execute.__get__( # pylint: disable=no-value-for-parameter
conn, asyncpg.connection.Connection
)
await execute(query)
asyncio.run(do_execute())
return self.memory_exporter.get_finished_spans()
def test_schema_url(self):
apg = AsyncPGInstrumentor()
apg.instrument(tracer_provider=self.tracer_provider)
self.assertEqual(
apg._tracer._instrumentation_scope.schema_url,
"https://opentelemetry.io/schemas/1.11.0",
)
def test_schema_url_new_semconv(self):
with use_semconv_opt_in("database"):
apg = AsyncPGInstrumentor()
apg.instrument(tracer_provider=self.tracer_provider)
self.assertEqual(
apg._tracer._instrumentation_scope.schema_url,
"https://opentelemetry.io/schemas/1.25.0",
)
def test_suppress_instrumentation(self) -> None:
conn = self._make_execute_conn()
conn._protocol.query = mock.AsyncMock(return_value="SELECT 1")
with suppress_instrumentation():
spans = self._run_execute(conn)
self.assertEqual(spans, ())
conn._protocol.query.assert_awaited_once_with("SELECT 1", None)
AsyncPGInstrumentor().uninstrument()
self.assertEqual(len(self._run_execute(conn)), 1)
def test_suppress_instrumentation_error(self) -> None:
conn = self._make_execute_conn()
error = RuntimeError("db error")
conn._protocol.query = mock.AsyncMock(side_effect=error)
with suppress_instrumentation(), self.assertRaises(RuntimeError) as raised:
self._run_execute(conn)
self.assertIs(raised.exception, error)
self.assertEqual(self.memory_exporter.get_finished_spans(), ())
def test_span(self):
conn = self._make_execute_conn()
spans = self._run_execute(conn)
self.assertEqual(len(spans), 1)
span = spans[0]
self.assertEqual(span.attributes[DB_SYSTEM], "postgresql")
self.assertEqual(span.attributes[DB_NAME], "testdb")
self.assertEqual(span.attributes[DB_USER], "testuser")
self.assertEqual(span.attributes[NET_PEER_NAME], "testhost")
self.assertEqual(span.attributes[NET_PEER_PORT], 5432)
self.assertEqual(span.attributes[DB_STATEMENT], "SELECT 1")
def test_span_database_only_new_semconv(self):
with use_semconv_opt_in("database"):
conn = self._make_execute_conn()
spans = self._run_execute(conn)
self.assertEqual(len(spans), 1)
span = spans[0]
self.assertEqual(span.attributes[DB_SYSTEM_NAME], "postgresql")
self.assertEqual(span.attributes[DB_NAMESPACE], "testdb")
self.assertEqual(span.attributes[DB_QUERY_TEXT], "SELECT 1")
self.assertEqual(span.attributes[SERVER_ADDRESS], "testhost")
self.assertEqual(span.attributes[SERVER_PORT], 5432)
self.assertNotIn(NET_PEER_NAME, span.attributes)
self.assertNotIn(NET_PEER_PORT, span.attributes)
def test_span_both_semconv(self):
with use_semconv_opt_in("database/dup,http/dup"):
conn = self._make_execute_conn()
spans = self._run_execute(conn)
self.assertEqual(len(spans), 1)
span = spans[0]
self.assertEqual(span.attributes[DB_SYSTEM], "postgresql")
self.assertEqual(span.attributes[DB_NAME], "testdb")
self.assertEqual(span.attributes[DB_STATEMENT], "SELECT 1")
self.assertEqual(span.attributes[DB_USER], "testuser")
self.assertEqual(span.attributes[NET_PEER_NAME], "testhost")
self.assertEqual(span.attributes[NET_PEER_PORT], 5432)
self.assertEqual(span.attributes[DB_SYSTEM_NAME], "postgresql")
self.assertEqual(span.attributes[DB_NAMESPACE], "testdb")
self.assertEqual(span.attributes[DB_QUERY_TEXT], "SELECT 1")
self.assertEqual(span.attributes[SERVER_ADDRESS], "testhost")
self.assertEqual(span.attributes[SERVER_PORT], 5432)
def test_span_new_semconv(self):
with use_semconv_opt_in("database,http"):
conn = self._make_execute_conn()
spans = self._run_execute(conn)
self.assertEqual(len(spans), 1)
span = spans[0]
self.assertEqual(span.attributes[DB_SYSTEM_NAME], "postgresql")
self.assertEqual(span.attributes[DB_NAMESPACE], "testdb")
self.assertEqual(span.attributes[DB_QUERY_TEXT], "SELECT 1")
self.assertEqual(span.attributes[SERVER_ADDRESS], "testhost")
self.assertEqual(span.attributes[SERVER_PORT], 5432)
def test_span_unix_socket_default_semconv(self):
conn = self._make_execute_conn(addr="/var/run/postgresql/.s.PGSQL.5432")
spans = self._run_execute(conn)
self.assertEqual(len(spans), 1)
span = spans[0]
self.assertEqual(
span.attributes[NET_PEER_NAME],
"/var/run/postgresql/.s.PGSQL.5432",
)
self.assertEqual(span.attributes[NET_TRANSPORT], NetTransportValues.OTHER.value)
self.assertNotIn(NET_PEER_PORT, span.attributes)
self.assertNotIn(SERVER_ADDRESS, span.attributes)
def test_span_capture_parameters(self):
apg = AsyncPGInstrumentor(capture_parameters=True)
apg.instrument(tracer_provider=self.tracer_provider)
conn = self._make_execute_conn()
async def do_execute():
execute = asyncpg.connection.Connection.execute.__get__( # pylint: disable=no-value-for-parameter
conn, asyncpg.connection.Connection
)
await execute("SELECT $1", "hello")
asyncio.run(do_execute())
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
self.assertIn("db.statement.parameters", spans[0].attributes)
self.assertIn("hello", spans[0].attributes["db.statement.parameters"])
def _run_execute_error(self, semconv_mode):
async def error_mock(*args, **kwargs):
raise RuntimeError("db error")
conn = mock.Mock()
conn.is_closed = lambda: False
conn._pool_release_ctr = 0
conn._query_loggers = []
conn._execute = error_mock
conn._protocol = mock.Mock()
conn._protocol.query = error_mock
conn._addr = ("testhost", 5432)
params = mock.Mock()
params.database = "testdb"
params.user = "testuser"
conn._params = params
with use_semconv_opt_in(semconv_mode):
apg = AsyncPGInstrumentor()
apg.instrument(tracer_provider=self.tracer_provider)
async def do_execute():
execute = asyncpg.connection.Connection.execute.__get__( # pylint: disable=no-value-for-parameter
conn, asyncpg.connection.Connection
)
await execute("SELECT 1")
with self.assertRaises(RuntimeError):
asyncio.run(do_execute())
return self.memory_exporter.get_finished_spans()
def test_error_type_not_set_on_default_semconv(self):
spans = self._run_execute_error("")
self.assertEqual(len(spans), 1)
span = spans[0]
self.assertFalse(span.status.is_ok)
self.assertNotIn(ERROR_TYPE, span.attributes)
def test_error_type_set_on_new_db_semconv(self):
spans = self._run_execute_error("database")
self.assertEqual(len(spans), 1)
span = spans[0]
self.assertFalse(span.status.is_ok)
self.assertEqual(span.attributes[ERROR_TYPE], "RuntimeError")
def test_error_type_set_on_both_semconv(self):
spans = self._run_execute_error("database/dup,http/dup")
self.assertEqual(len(spans), 1)
span = spans[0]
self.assertFalse(span.status.is_ok)
self.assertEqual(span.attributes[ERROR_TYPE], "RuntimeError")
opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aws-lambda/ 0000775 0000000 0000000 00000000000 15270700723 0033153 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aws-lambda/LICENSE0000664 0000000 0000000 00000026135 15270700723 0034167 0 ustar 00root root 0000000 0000000 Apache License
Version 2.0, January 2004
http://www.apache.org/licenses/
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README.rst 0000664 0000000 0000000 00000002233 15270700723 0034563 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aws-lambda OpenTelemetry AWS Lambda Tracing
================================
|pypi|
.. |pypi| image:: https://badge.fury.io/py/opentelemetry-instrumentation-aws-lambda.svg
:target: https://pypi.org/project/opentelemetry-instrumentation-aws-lambda/
This library provides an Instrumentor used to trace requests made by the Lambda
functions on the AWS Lambda service.
It also provides scripts used by AWS Lambda Layers to automatically initialize
the OpenTelemetry SDK. Learn more on the AWS Distro for OpenTelemetry (ADOT)
`documentation for the Python Lambda Layer `_.
Installation
------------
::
pip install opentelemetry-instrumentation-aws-lambda
References
----------
* `OpenTelemetry AWS Lambda Tracing `_
* `OpenTelemetry Project `_
* `OpenTelemetry Python Examples `_
* `ADOT Python Lambda Layer Documentation `_
pyproject.toml 0000664 0000000 0000000 00000003147 15270700723 0036015 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aws-lambda [build-system]
requires = ["hatchling"]
build-backend = "hatchling.build"
[project]
name = "opentelemetry-instrumentation-aws-lambda"
dynamic = ["version"]
description = "OpenTelemetry AWS Lambda instrumentation"
readme = "README.rst"
license = "Apache-2.0"
requires-python = ">=3.10"
authors = [
{ name = "OpenTelemetry Authors", email = "cncf-opentelemetry-contributors@lists.cncf.io" },
]
classifiers = [
"Development Status :: 4 - Beta",
"Intended Audience :: Developers",
"License :: OSI Approved :: Apache Software License",
"Programming Language :: Python",
"Programming Language :: Python :: 3",
"Programming Language :: Python :: 3.10",
"Programming Language :: Python :: 3.11",
"Programming Language :: Python :: 3.12",
"Programming Language :: Python :: 3.13",
"Programming Language :: Python :: 3.14",
]
dependencies = [
"opentelemetry-instrumentation == 0.66b2",
"opentelemetry-semantic-conventions == 0.66b2",
"opentelemetry-propagator-aws-xray ~= 1.0",
]
[project.optional-dependencies]
instruments = []
[project.entry-points.opentelemetry_instrumentor]
aws-lambda = "opentelemetry.instrumentation.aws_lambda:AwsLambdaInstrumentor"
[project.urls]
Homepage = "https://github.com/open-telemetry/opentelemetry-python-contrib/tree/main/instrumentation/opentelemetry-instrumentation-aws-lambda"
Repository = "https://github.com/open-telemetry/opentelemetry-python-contrib"
[tool.hatch.version]
path = "src/opentelemetry/instrumentation/aws_lambda/version.py"
[tool.hatch.build.targets.sdist]
include = [
"/src",
"/tests",
]
[tool.hatch.build.targets.wheel]
packages = ["src/opentelemetry"]
opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aws-lambda/src/ 0000775 0000000 0000000 00000000000 15270700723 0033742 5 ustar 00root root 0000000 0000000 opentelemetry/ 0000775 0000000 0000000 00000000000 15270700723 0036557 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aws-lambda/src instrumentation/ 0000775 0000000 0000000 00000000000 15270700723 0042022 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aws-lambda/src/opentelemetry aws_lambda/ 0000775 0000000 0000000 00000000000 15270700723 0044114 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aws-lambda/src/opentelemetry/instrumentation __init__.py 0000664 0000000 0000000 00000044571 15270700723 0046240 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aws-lambda/src/opentelemetry/instrumentation/aws_lambda # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
"""
The opentelemetry-instrumentation-aws-lambda package provides an Instrumentor
to traces calls within a Python AWS Lambda function.
Usage
-----
.. code:: python
# Copy this snippet into an AWS Lambda function
import boto3
from opentelemetry.instrumentation.botocore import BotocoreInstrumentor
from opentelemetry.instrumentation.aws_lambda import AwsLambdaInstrumentor
# Enable instrumentation
BotocoreInstrumentor().instrument()
# Lambda function
def lambda_handler(event, context):
s3 = boto3.resource('s3')
for bucket in s3.buckets.all():
print(bucket.name)
return "200 OK"
AwsLambdaInstrumentor().instrument()
API
---
The `instrument` method accepts the following keyword args:
tracer_provider (TracerProvider) - an optional tracer provider
meter_provider (MeterProvider) - an optional meter provider
event_context_extractor (Callable) - a function that returns an OTel Trace
Context given the Lambda Event the AWS Lambda was invoked with
this function signature is: def event_context_extractor(lambda_event: Any) -> Context
for example:
.. code:: python
from opentelemetry.instrumentation.aws_lambda import AwsLambdaInstrumentor
from opentelemetry.propagate import get_global_textmap
def custom_event_context_extractor(lambda_event):
# If the `TraceContextTextMapPropagator` is the global propagator, we
# can use it to parse out the context from the HTTP Headers.
return get_global_textmap().extract(lambda_event["foo"]["headers"])
AwsLambdaInstrumentor().instrument(
event_context_extractor=custom_event_context_extractor
)
---
"""
from __future__ import annotations
import logging
import os
import time
from collections.abc import Callable, Collection
from enum import Enum
from importlib import import_module
from typing import TYPE_CHECKING, Any
from urllib.parse import urlencode
from wrapt import wrap_function_wrapper
from opentelemetry import context as context_api
from opentelemetry.context.context import Context
from opentelemetry.instrumentation.aws_lambda._sqs import (
_is_sqs_event,
_run_sqs_handler,
)
from opentelemetry.instrumentation.aws_lambda.package import _instruments
from opentelemetry.instrumentation.aws_lambda.version import __version__
from opentelemetry.instrumentation.cidict import CIDict
from opentelemetry.instrumentation.instrumentor import BaseInstrumentor
from opentelemetry.instrumentation.utils import unwrap
from opentelemetry.metrics import MeterProvider, get_meter_provider
from opentelemetry.propagate import get_global_textmap
from opentelemetry.semconv._incubating.attributes.cloud_attributes import (
CLOUD_ACCOUNT_ID,
CLOUD_RESOURCE_ID,
)
from opentelemetry.semconv._incubating.attributes.faas_attributes import (
FAAS_INVOCATION_ID,
FAAS_TRIGGER,
FaasTriggerValues,
)
from opentelemetry.semconv._incubating.attributes.http_attributes import (
HTTP_METHOD,
HTTP_ROUTE,
HTTP_SCHEME,
HTTP_STATUS_CODE,
HTTP_TARGET,
HTTP_USER_AGENT,
)
from opentelemetry.semconv._incubating.attributes.net_attributes import (
NET_HOST_NAME,
)
from opentelemetry.trace import (
SpanKind,
TracerProvider,
get_tracer,
get_tracer_provider,
)
from opentelemetry.trace.status import Status, StatusCode
logger = logging.getLogger(__name__)
_HANDLER = "_HANDLER"
_X_AMZN_TRACE_ID = "_X_AMZN_TRACE_ID"
ORIG_HANDLER = "ORIG_HANDLER"
OTEL_INSTRUMENTATION_AWS_LAMBDA_FLUSH_TIMEOUT = "OTEL_INSTRUMENTATION_AWS_LAMBDA_FLUSH_TIMEOUT"
if TYPE_CHECKING:
import typing
from collections.abc import MutableMapping
class LambdaContext(typing.Protocol):
"""Type definition for AWS Lambda context object.
This Protocol defines the interface for the context object passed to Lambda
function handlers, providing information about the invocation, function, and
execution environment.
See Also:
AWS Lambda Context Object documentation:
https://docs.aws.amazon.com/lambda/latest/dg/python-context.html
"""
function_name: str
function_version: str
invoked_function_arn: str
memory_limit_in_mb: int
aws_request_id: str
log_group_name: str
log_stream_name: str
class _LambdaEventType(Enum):
SQS = "sqs"
API_GATEWAY = "api_gateway"
UNKNOWN = "unknown"
def _get_lambda_event_type(lambda_event: Any) -> _LambdaEventType:
if _is_sqs_event(lambda_event):
return _LambdaEventType.SQS
if isinstance(lambda_event, dict) and lambda_event.get("requestContext"):
return _LambdaEventType.API_GATEWAY
return _LambdaEventType.UNKNOWN
def _default_event_context_extractor(lambda_event: Any) -> Context:
"""Default way of extracting the context from the Lambda Event.
Assumes the Lambda Event is a map with the headers under the 'headers' key.
This is the mapping to use when the Lambda is invoked by an API Gateway
REST API where API Gateway is acting as a pure proxy for the request.
Protects headers from being something other than dictionary, as this
is what downstream propagators expect.
See more:
https://docs.aws.amazon.com/apigateway/latest/developerguide/set-up-lambda-proxy-integrations.html#api-gateway-simple-proxy-for-lambda-input-format
Args:
lambda_event: user-defined, so it could be anything, but this
method counts on it being a map with a 'headers' key
Returns:
A Context with configuration found in the event.
"""
return get_global_textmap().extract(
CIDict(_extract_http_headers(lambda_event)),
)
def _extract_http_headers(lambda_event: Any) -> dict[str, Any]:
if not isinstance(lambda_event, dict):
return {}
headers = lambda_event.get("headers")
multi_value_headers = lambda_event.get("multiValueHeaders")
normalized_multi_value_headers = {}
if isinstance(multi_value_headers, dict):
normalized_multi_value_headers = {
key: values[0] for key, values in multi_value_headers.items() if isinstance(values, list) and values
}
if not isinstance(headers, dict):
return normalized_multi_value_headers
return {
**headers,
**normalized_multi_value_headers,
}
def _determine_parent_context(
lambda_event: Any,
event_context_extractor: Callable[[Any], Context],
) -> Context:
"""Determine the parent context for the current Lambda invocation.
See more:
https://github.com/open-telemetry/opentelemetry-specification/blob/main/specification/trace/semantic_conventions/instrumentation/aws-lambda.md#determining-the-parent-of-a-span
Args:
lambda_event: user-defined, so it could be anything, but this
method counts it being a map with a 'headers' key
event_context_extractor: a method which takes the Lambda
Event as input and extracts an OTel Context from it. By default,
the context is extracted from the HTTP headers of an API Gateway
request.
Returns:
A Context with configuration found in the carrier.
"""
if event_context_extractor is None:
return _default_event_context_extractor(lambda_event)
return event_context_extractor(lambda_event)
def _get_api_gateway_v1_proxy_attributes(
lambda_event: Any,
) -> MutableMapping[str, Any]:
"""Sets HTTP attributes for REST APIs and v1 HTTP APIs
More info:
https://docs.aws.amazon.com/apigateway/latest/developerguide/set-up-lambda-proxy-integrations.html#api-gateway-simple-proxy-for-lambda-input-format
"""
attributes = {}
attributes[HTTP_METHOD] = lambda_event.get("httpMethod")
if headers := _extract_http_headers(lambda_event):
headers = CIDict(headers)
if "User-Agent" in headers:
attributes[HTTP_USER_AGENT] = headers["User-Agent"]
if "X-Forwarded-Proto" in headers:
attributes[HTTP_SCHEME] = headers["X-Forwarded-Proto"]
if "Host" in headers:
attributes[NET_HOST_NAME] = headers["Host"]
if "resource" in lambda_event:
attributes[HTTP_ROUTE] = lambda_event["resource"]
if lambda_event.get("queryStringParameters"):
attributes[HTTP_TARGET] = f"{lambda_event['resource']}?{urlencode(lambda_event['queryStringParameters'])}"
else:
attributes[HTTP_TARGET] = lambda_event["resource"]
return attributes
def _get_api_gateway_v2_proxy_attributes(
lambda_event: Any,
) -> MutableMapping[str, Any]:
"""Sets HTTP attributes for v2 HTTP APIs
More info:
https://docs.aws.amazon.com/apigateway/latest/developerguide/http-api-develop-integrations-lambda.html
"""
attributes = {}
if "domainName" in lambda_event["requestContext"]:
attributes[NET_HOST_NAME] = lambda_event["requestContext"]["domainName"]
if lambda_event["requestContext"].get("http"):
http = lambda_event["requestContext"]["http"]
if "method" in http:
attributes[HTTP_METHOD] = http["method"]
if "userAgent" in http:
attributes[HTTP_USER_AGENT] = http["userAgent"]
if "path" in http:
attributes[HTTP_ROUTE] = http["path"]
if lambda_event.get("rawQueryString"):
attributes[HTTP_TARGET] = f"{http['path']}?{lambda_event['rawQueryString']}"
else:
attributes[HTTP_TARGET] = http["path"]
return attributes
def _get_lambda_context_attributes(
lambda_context: LambdaContext,
) -> dict[str, str]:
"""Extracts OpenTelemetry span attributes from AWS Lambda context.
Extract FaaS specific attributes from the AWS Lambda context
according to OpenTelemetry semantic conventions for FaaS & AWS Lambda.
Args:
lambda_context: The AWS Lambda context object.
Returns:
A dictionary mapping of OpenTelemetry attribute names to their values.
"""
function_arn_parts: list[str] = lambda_context.invoked_function_arn.split(":")
# NOTE: `cloud.account.id` can be parsed from the ARN as the fifth item when splitting on `:`
#
# See more:
# https://github.com/open-telemetry/semantic-conventions/blob/main/docs/faas/aws-lambda.md#all-triggers
aws_account_id: str = function_arn_parts[4]
# NOTE: The unmodified function ARN may contain an alias extension e.g.
# `arn:aws:lambda:region:account:function:name:alias`. We can ensure
# the alias extension is not included in the `cloud.resource_id` by keeping
# only the first 7 parts of the original ARN.
#
# See more:
# https://docs.aws.amazon.com/lambda/latest/dg/python-context.html
formatted_function_arn: str = ":".join(function_arn_parts[:7])
# NOTE: The specs mention an exception here, allowing the
# `SpanAttributes.CLOUD_RESOURCE_ID` attribute to be set as a span
# attribute instead of a resource attribute.
#
# See more:
# https://github.com/open-telemetry/semantic-conventions/blob/main/docs/faas/aws-lambda.md#resource-detector
return {
CLOUD_ACCOUNT_ID: aws_account_id,
CLOUD_RESOURCE_ID: formatted_function_arn,
FAAS_INVOCATION_ID: lambda_context.aws_request_id,
}
# pylint: disable=too-many-statements
def _instrument(
wrapped_module_name,
wrapped_function_name,
flush_timeout,
event_context_extractor: Callable[[Any], Context],
tracer_provider: TracerProvider = None,
meter_provider: MeterProvider = None,
):
# pylint: disable=too-many-locals
# pylint: disable=too-many-statements
# pylint: disable=too-many-branches
def _instrumented_lambda_handler_call(call_wrapped, instance, args, kwargs):
lambda_event: Any = args[0]
lambda_context: LambdaContext = args[1]
parent_context = _determine_parent_context(
lambda_event,
event_context_extractor,
)
tracer = get_tracer(
__name__,
__version__,
tracer_provider,
schema_url="https://opentelemetry.io/schemas/1.11.0",
)
token = context_api.attach(parent_context)
event_type = _get_lambda_event_type(lambda_event)
span_attributes: MutableMapping[str, Any] = _get_lambda_context_attributes(lambda_context)
if event_type is _LambdaEventType.SQS:
span_attributes[FAAS_TRIGGER] = FaasTriggerValues.PUBSUB.value
elif event_type is _LambdaEventType.API_GATEWAY:
# If the request came from an API Gateway, extract http attributes from the event
# https://github.com/open-telemetry/opentelemetry-specification/blob/main/specification/trace/semantic_conventions/instrumentation/aws-lambda.md#api-gateway
# https://github.com/open-telemetry/opentelemetry-specification/blob/main/specification/trace/semantic_conventions/http.md#http-server-semantic-conventions
span_attributes[FAAS_TRIGGER] = "http"
if lambda_event.get("version") == "2.0":
span_attributes |= _get_api_gateway_v2_proxy_attributes(lambda_event)
else:
span_attributes |= _get_api_gateway_v1_proxy_attributes(lambda_event)
try:
with tracer.start_as_current_span(
name=lambda_context.function_name,
kind=SpanKind.SERVER,
attributes=span_attributes,
) as span:
exception = None
result = None
try:
if event_type is _LambdaEventType.SQS:
result = _run_sqs_handler(tracer, lambda_event, call_wrapped, args, kwargs)
else:
result = call_wrapped(*args, **kwargs)
# pylint: disable-next=broad-exception-caught
except Exception as exc:
exception = exc
span.set_status(Status(StatusCode.ERROR))
span.record_exception(exception)
if event_type is _LambdaEventType.API_GATEWAY and isinstance(result, dict) and result.get("statusCode"):
span.set_attribute(
HTTP_STATUS_CODE,
result.get("statusCode"),
)
finally:
if token:
context_api.detach(token)
now = time.time()
_tracer_provider = tracer_provider or get_tracer_provider()
if hasattr(_tracer_provider, "force_flush"):
try:
# NOTE: `force_flush` before function quit in case of Lambda freeze.
_tracer_provider.force_flush(flush_timeout)
except Exception: # pylint: disable=broad-except
logger.exception("TracerProvider failed to flush traces")
else:
logger.warning(
"TracerProvider was missing `force_flush` method. This is necessary in case of a Lambda freeze and would exist in the OTel SDK implementation."
)
_meter_provider = meter_provider or get_meter_provider()
if hasattr(_meter_provider, "force_flush"):
rem = flush_timeout - (time.time() - now) * 1000
if rem > 0:
try:
# NOTE: `force_flush` before function quit in case of Lambda freeze.
_meter_provider.force_flush(rem)
except Exception: # pylint: disable=broad-except
logger.exception("MeterProvider failed to flush metrics")
else:
logger.warning(
"MeterProvider was missing `force_flush` method. This is necessary in case of a Lambda freeze and would exist in the OTel SDK implementation."
)
if exception is not None:
raise exception.with_traceback(exception.__traceback__)
return result
wrap_function_wrapper(
wrapped_module_name,
wrapped_function_name,
_instrumented_lambda_handler_call,
)
class AwsLambdaInstrumentor(BaseInstrumentor):
def instrumentation_dependencies(self) -> Collection[str]:
return _instruments
def _instrument(self, **kwargs):
"""Instruments Lambda Handlers on AWS Lambda.
See more:
https://github.com/open-telemetry/semantic-conventions/blob/main/docs/faas/aws-lambda.md
Args:
**kwargs: Optional arguments
``tracer_provider``: a TracerProvider, defaults to global
``meter_provider``: a MeterProvider, defaults to global
``event_context_extractor``: a method which takes the Lambda
Event as input and extracts an OTel Context from it. By default,
the context is extracted from the HTTP headers of an API Gateway
request.
"""
# Don't try if we are not running on AWS Lambda
if "AWS_LAMBDA_FUNCTION_NAME" not in os.environ:
return
lambda_handler = os.environ.get(ORIG_HANDLER, os.environ.get(_HANDLER))
if not lambda_handler:
logger.warning(
(
"Could not find the ORIG_HANDLER or _HANDLER in the environment variables. ",
"This instrumentation requires the OpenTelemetry Lambda extension installed.",
)
)
return
# Convert slash-delimited paths to dot-delimited for valid Python imports
lambda_handler = lambda_handler.replace("/", ".")
(
self._wrapped_module_name,
self._wrapped_function_name,
) = lambda_handler.rsplit(".", 1)
flush_timeout_env = os.environ.get(OTEL_INSTRUMENTATION_AWS_LAMBDA_FLUSH_TIMEOUT, None)
flush_timeout = 30000
try:
if flush_timeout_env is not None:
flush_timeout = int(flush_timeout_env)
except ValueError:
logger.warning(
"Could not convert OTEL_INSTRUMENTATION_AWS_LAMBDA_FLUSH_TIMEOUT value %s to int",
flush_timeout_env,
)
_instrument(
self._wrapped_module_name,
self._wrapped_function_name,
flush_timeout,
event_context_extractor=kwargs.get("event_context_extractor", _default_event_context_extractor),
tracer_provider=kwargs.get("tracer_provider"),
meter_provider=kwargs.get("meter_provider"),
)
def _uninstrument(self, **kwargs):
unwrap(
import_module(self._wrapped_module_name),
self._wrapped_function_name,
)
_sqs.py 0000664 0000000 0000000 00000007234 15270700723 0045441 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aws-lambda/src/opentelemetry/instrumentation/aws_lambda # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
from __future__ import annotations
import logging
from collections.abc import Callable, Mapping
from typing import Any
from opentelemetry.instrumentation.cidict import CIDict
from opentelemetry.propagate import get_global_textmap
from opentelemetry.propagators.textmap import Getter
from opentelemetry.semconv._incubating.attributes.messaging_attributes import (
MESSAGING_BATCH_MESSAGE_COUNT,
MESSAGING_DESTINATION_NAME,
MESSAGING_MESSAGE_ID,
MESSAGING_OPERATION_TYPE,
MESSAGING_SYSTEM,
MessagingOperationTypeValues,
MessagingSystemValues,
)
from opentelemetry.trace import Link, SpanKind, get_current_span
logger = logging.getLogger(__name__)
CarrierT = dict[str, Any]
class _SqsMessageAttributesGetter(Getter[CarrierT]):
"""Extracts W3C trace context from SQS message attribute dicts.
SQS message attributes have the structure:
``{"traceparent": {"dataType": "String", "stringValue": "00-..."}}``.
"""
def get(self, carrier: CarrierT, key: str) -> list[str] | None:
msg_attr = carrier.get(key)
if not isinstance(msg_attr, Mapping):
return None
value = msg_attr.get("stringValue")
return [value] if isinstance(value, str) else None
def keys(self, carrier: CarrierT) -> list[str]:
return list(carrier.keys())
_sqs_getter = _SqsMessageAttributesGetter()
def _is_sqs_event(lambda_event: Any) -> bool:
try:
return bool(
isinstance(lambda_event, dict)
and isinstance(lambda_event.get("Records"), list)
and lambda_event["Records"]
and lambda_event["Records"][0].get("eventSource", "").strip().lower() == "aws:sqs"
)
except Exception as exc: # pylint: disable=broad-except
logger.warning("An unexpected error occurred while checking SQS event: %s", exc)
return False
def _extract_sqs_queue_name(arn: str) -> str:
parts = arn.split(":")
return parts[5] if len(parts) >= 6 else arn
def _get_sqs_span_links(records: list[dict[str, Any]]) -> list[Link]:
links = []
for record in records:
msg_attrs = record.get("messageAttributes") or {}
if not msg_attrs or not isinstance(msg_attrs, dict):
continue
# Wrap in CIDict so propagation header name lookup is case-insensitive
# (e.g. "TRACEPARENT" and "traceparent" are both found).
ctx = get_global_textmap().extract(CIDict(msg_attrs), getter=_sqs_getter)
span_ctx = get_current_span(ctx).get_span_context()
if span_ctx and span_ctx.is_valid:
links.append(
Link(
context=span_ctx,
attributes={MESSAGING_MESSAGE_ID: record.get("messageId", "")},
)
)
return links
def _run_sqs_handler(
tracer: Any,
lambda_event: dict[str, Any],
handler: Callable[..., Any],
args: tuple[Any, ...],
kwargs: dict[str, Any],
) -> Any:
records: list[dict[str, Any]] = lambda_event["Records"]
queue_name = _extract_sqs_queue_name(records[0].get("eventSourceARN", ""))
links = _get_sqs_span_links(records)
attrs: dict[str, Any] = {
MESSAGING_SYSTEM: MessagingSystemValues.AWS_SQS.value,
MESSAGING_DESTINATION_NAME: queue_name,
MESSAGING_OPERATION_TYPE: MessagingOperationTypeValues.PROCESS.value,
}
if len(records) > 1:
attrs[MESSAGING_BATCH_MESSAGE_COUNT] = len(records)
with tracer.start_as_current_span(
f"process {queue_name}".strip(),
kind=SpanKind.CONSUMER,
links=links,
attributes=attrs,
):
return handler(*args, **kwargs)
package.py 0000664 0000000 0000000 00000000145 15270700723 0046061 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aws-lambda/src/opentelemetry/instrumentation/aws_lambda # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
_instruments = tuple()
version.py 0000664 0000000 0000000 00000000144 15270700723 0046152 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aws-lambda/src/opentelemetry/instrumentation/aws_lambda # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
__version__ = "0.66b2"
test-requirements.txt 0000664 0000000 0000000 00000000500 15270700723 0037330 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aws-lambda asgiref==3.8.1
Deprecated==1.2.14
iniconfig==2.0.0
packaging==24.0
pluggy==1.6.0
py-cpuinfo==9.0.0
pytest==7.4.4
tomli==2.0.1
typing_extensions==4.12.2
wrapt==1.16.0
zipp==3.19.2
-e opentelemetry-instrumentation
-e propagator/opentelemetry-propagator-aws-xray
-e instrumentation/opentelemetry-instrumentation-aws-lambda
opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aws-lambda/tests/ 0000775 0000000 0000000 00000000000 15270700723 0034315 5 ustar 00root root 0000000 0000000 __init__.py 0000664 0000000 0000000 00000000000 15270700723 0036335 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aws-lambda/tests mocks/ 0000775 0000000 0000000 00000000000 15270700723 0035352 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aws-lambda/tests __init__.py 0000664 0000000 0000000 00000000000 15270700723 0037451 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aws-lambda/tests/mocks alb_conventional_headers_event.py 0000664 0000000 0000000 00000001663 15270700723 0044143 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aws-lambda/tests/mocks # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
MOCK_LAMBDA_ALB_EVENT = {
"requestContext": {
"elb": {
"targetGroupArn": "arn:aws:elasticloadbalancing:region:123456789012:targetgroup/my-target-group/6d0ecf831eec9f09"
}
},
"httpMethod": "GET",
"path": "/",
"queryStringParameters": {"foo": "bar"},
"headers": {
"accept": "text/html,application/xhtml+xml",
"accept-language": "en-US,en;q=0.8",
"content-type": "text/plain",
"cookie": "cookies",
"host": "lambda-846800462-us-east-2.elb.amazonaws.com",
"user-agent": "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_11_6)",
"x-amzn-trace-id": "Root=1-5bdb40ca-556d8b0c50dc66f0511bf520",
"x-forwarded-for": "72.21.198.66",
"x-forwarded-port": "443",
"x-forwarded-proto": "https",
},
"isBase64Encoded": False,
"body": "request_body",
}
alb_multi_value_headers_event.py 0000664 0000000 0000000 00000002353 15270700723 0043767 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aws-lambda/tests/mocks # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
"""
https://docs.aws.amazon.com/elasticloadbalancing/latest/application/lambda-functions.html#multi-value-headers
When an ALB is configured to send multi-value headers, the headers are sent as a list of values under the key in the multiValueHeaders object.
"""
MOCK_LAMBDA_ALB_MULTI_VALUE_HEADER_EVENT = {
"requestContext": {
"elb": {
"targetGroupArn": "arn:aws:elasticloadbalancing:region:123456789012:targetgroup/my-target-group/6d0ecf831eec9f09"
}
},
"httpMethod": "GET",
"path": "/",
"queryStringParameters": {"foo": "bar"},
"multiValueHeaders": {
"accept": ["text/html,application/xhtml+xml"],
"accept-language": ["en-US,en;q=0.8"],
"content-type": ["text/plain"],
"cookie": ["cookies"],
"host": ["lambda-846800462-us-east-2.elb.amazonaws.com"],
"user-agent": ["Mozilla/5.0 (Macintosh; Intel Mac OS X 10_11_6)"],
"x-amzn-trace-id": ["Root=1-5bdb40ca-556d8b0c50dc66f0511bf520"],
"x-forwarded-for": ["72.21.198.66"],
"x-forwarded-port": ["443"],
"x-forwarded-proto": ["https"],
},
"isBase64Encoded": False,
"body": "request_body",
}
api_gateway_http_api_event.py 0000664 0000000 0000000 00000003714 15270700723 0043314 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aws-lambda/tests/mocks # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
# Generated via `sam local generate-event apigateway http-api-proxy`
MOCK_LAMBDA_API_GATEWAY_HTTP_API_EVENT = {
"version": "2.0",
"routeKey": "$default",
"rawPath": "/path/to/resource",
"rawQueryString": "parameter1=value1¶meter1=value2¶meter2=value",
"cookies": ["cookie1", "cookie2"],
"headers": {"header1": "value1", "Header2": "value1,value2"},
"queryStringParameters": {
"parameter1": "value1,value2",
"parameter2": "value",
},
"requestContext": {
"accountId": "123456789012",
"apiId": "api-id",
"authentication": {
"clientCert": {
"clientCertPem": "CERT_CONTENT",
"subjectDN": "www.example.com",
"issuerDN": "Example issuer",
"serialNumber": "a1:a1:a1:a1:a1:a1:a1:a1:a1:a1:a1:a1:a1:a1:a1:a1",
"validity": {
"notBefore": "May 28 12:30:02 2019 GMT",
"notAfter": "Aug 5 09:36:04 2021 GMT",
},
}
},
"authorizer": {
"jwt": {
"claims": {"claim1": "value1", "claim2": "value2"},
"scopes": ["scope1", "scope2"],
}
},
"domainName": "id.execute-api.us-east-1.amazonaws.com",
"domainPrefix": "id",
"http": {
"method": "POST",
"path": "/path/to/resource",
"protocol": "HTTP/1.1",
"sourceIp": "192.168.0.1/32",
"userAgent": "agent",
},
"requestId": "id",
"routeKey": "$default",
"stage": "$default",
"time": "12/Mar/2020:19:03:58 +0000",
"timeEpoch": 1583348638390,
},
"body": "eyJ0ZXN0IjoiYm9keSJ9",
"pathParameters": {"parameter1": "value1"},
"isBase64Encoded": True,
"stageVariables": {"stageVariable1": "value1", "stageVariable2": "value2"},
}
api_gateway_proxy_event.py 0000664 0000000 0000000 00000006567 15270700723 0042676 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aws-lambda/tests/mocks # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
# Generated via `sam local generate-event apigateway aws-proxy`
MOCK_LAMBDA_API_GATEWAY_PROXY_EVENT = {
"body": "eyJ0ZXN0IjoiYm9keSJ9",
"resource": "/{proxy+}",
"path": "/path/to/resource",
"httpMethod": "POST",
"isBase64Encoded": True,
"queryStringParameters": {"foo": "bar"},
"multiValueQueryStringParameters": {"foo": ["bar"]},
"pathParameters": {"proxy": "/path/to/resource"},
"stageVariables": {"baz": "qux"},
"headers": {
"Accept": "text/html,application/xhtml+xml,application/xml;q=0.9,image/webp,*/*;q=0.8",
"Accept-Encoding": "gzip, deflate, sdch",
"Accept-Language": "en-US,en;q=0.8",
"Cache-Control": "max-age=0",
"CloudFront-Forwarded-Proto": "https",
"CloudFront-Is-Desktop-Viewer": "true",
"CloudFront-Is-Mobile-Viewer": "false",
"CloudFront-Is-SmartTV-Viewer": "false",
"CloudFront-Is-Tablet-Viewer": "false",
"CloudFront-Viewer-Country": "US",
"Host": "1234567890.execute-api.us-east-1.amazonaws.com",
"Upgrade-Insecure-Requests": "1",
"User-Agent": "Custom User Agent String",
"Via": "1.1 08f323deadbeefa7af34d5feb414ce27.cloudfront.net (CloudFront)",
"X-Amz-Cf-Id": "cDehVQoZnx43VYQb9j2-nvCh-9z396Uhbp027Y2JvkCPNLmGJHqlaA==",
"X-Forwarded-For": "127.0.0.1, 127.0.0.2",
"X-Forwarded-Port": "443",
"X-Forwarded-Proto": "https",
},
"multiValueHeaders": {
"Accept": ["text/html,application/xhtml+xml,application/xml;q=0.9,image/webp,*/*;q=0.8"],
"Accept-Encoding": ["gzip, deflate, sdch"],
"Accept-Language": ["en-US,en;q=0.8"],
"Cache-Control": ["max-age=0"],
"CloudFront-Forwarded-Proto": ["https"],
"CloudFront-Is-Desktop-Viewer": ["true"],
"CloudFront-Is-Mobile-Viewer": ["false"],
"CloudFront-Is-SmartTV-Viewer": ["false"],
"CloudFront-Is-Tablet-Viewer": ["false"],
"CloudFront-Viewer-Country": ["US"],
"Host": ["0123456789.execute-api.us-east-1.amazonaws.com"],
"Upgrade-Insecure-Requests": ["1"],
"User-Agent": ["Custom User Agent String"],
"Via": ["1.1 08f323deadbeefa7af34d5feb414ce27.cloudfront.net (CloudFront)"],
"X-Amz-Cf-Id": ["cDehVQoZnx43VYQb9j2-nvCh-9z396Uhbp027Y2JvkCPNLmGJHqlaA=="],
"X-Forwarded-For": ["127.0.0.1, 127.0.0.2"],
"X-Forwarded-Port": ["443"],
"X-Forwarded-Proto": ["https"],
},
"requestContext": {
"accountId": "123456789012",
"resourceId": "123456",
"stage": "prod",
"requestId": "c6af9ac6-7b61-11e6-9a41-93e8deadbeef",
"requestTime": "09/Apr/2015:12:34:56 +0000",
"requestTimeEpoch": 1428582896000,
"identity": {
"cognitoIdentityPoolId": None,
"accountId": None,
"cognitoIdentityId": None,
"caller": None,
"accessKey": None,
"sourceIp": "127.0.0.1",
"cognitoAuthenticationType": None,
"cognitoAuthenticationProvider": None,
"userArn": None,
"userAgent": "Custom User Agent String",
"user": None,
},
"path": "/prod/path/to/resource",
"resourcePath": "/{proxy+}",
"httpMethod": "POST",
"apiId": "1234567890",
"protocol": "HTTP/1.1",
},
}
dynamo_db_event.py 0000664 0000000 0000000 00000003252 15270700723 0041063 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aws-lambda/tests/mocks # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
"""
https://docs.aws.amazon.com/lambda/latest/dg/with-ddb.html
"""
MOCK_LAMBDA_DYNAMO_DB_EVENT = {
"Records": [
{
"eventID": "1",
"eventVersion": "1.0",
"dynamodb": {
"Keys": {"Id": {"N": "101"}},
"NewImage": {
"Message": {"S": "New item!"},
"Id": {"N": "101"},
},
"StreamViewType": "NEW_AND_OLD_IMAGES",
"SequenceNumber": "111",
"SizeBytes": 26,
},
"awsRegion": "us-west-2",
"eventName": "INSERT",
"eventSourceARN": "arn:aws:dynamodb:us-east-2:123456789012:table/my-table/stream/2023-06-10T19:26:16.525",
"eventSource": "aws:dynamodb",
},
{
"eventID": "2",
"eventVersion": "1.0",
"dynamodb": {
"OldImage": {
"Message": {"S": "New item!"},
"Id": {"N": "101"},
},
"SequenceNumber": "222",
"Keys": {"Id": {"N": "101"}},
"SizeBytes": 59,
"NewImage": {
"Message": {"S": "This item has changed"},
"Id": {"N": "101"},
},
"StreamViewType": "NEW_AND_OLD_IMAGES",
},
"awsRegion": "us-west-2",
"eventName": "MODIFY",
"eventSourceARN": "arn:aws:dynamodb:us-east-2:123456789012:table/my-table/stream/2023-06-10T19:26:16.525",
"eventSource": "aws:dynamodb",
},
]
}
lambda_function.py 0000664 0000000 0000000 00000000772 15270700723 0041057 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aws-lambda/tests/mocks # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
import json
from opentelemetry import baggage as baggage_api
def handler(event, context):
baggage_content = dict(baggage_api.get_all().items())
return json.dumps({"baggage_content": baggage_content})
def rest_api_handler(event, context):
return {"statusCode": 200, "body": "200 ok"}
def handler_exc(event, context):
# pylint: disable=broad-exception-raised
raise Exception("500 internal server error")
s3_event.py 0000664 0000000 0000000 00000002651 15270700723 0037456 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aws-lambda/tests/mocks # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
"""
https://docs.aws.amazon.com/lambda/latest/dg/with-s3.html
"""
MOCK_LAMBDA_S3_EVENT = {
"Records": [
{
"eventVersion": "2.1",
"eventSource": "aws:s3",
"awsRegion": "us-east-2",
"eventTime": "2019-09-03T19:37:27.192Z",
"eventName": "ObjectCreated:Put",
"userIdentity": {"principalId": "AWS:AIDAINPONIXQXHT3IKHL2"},
"requestParameters": {"sourceIPAddress": "205.255.255.255"},
"responseElements": {
"x-amz-request-id": "D82B88E5F771F645",
"x-amz-id-2": "vlR7PnpV2Ce81l0PRw6jlUpck7Jo5ZsQjryTjKlc5aLWGVHPZLj5NeC6qMa0emYBDXOo6QBU0Wo=",
},
"s3": {
"s3SchemaVersion": "1.0",
"configurationId": "828aa6fc-f7b5-4305-8584-487c791949c1",
"bucket": {
"name": "DOC-EXAMPLE-BUCKET",
"ownerIdentity": {"principalId": "A3I5XTEXAMAI3E"},
"arn": "arn:aws:s3:::lambda-artifacts-deafc19498e3f2df",
},
"object": {
"key": "b21b84d653bb07b05b1e6b33684dc11b",
"size": 1305107,
"eTag": "b21b84d653bb07b05b1e6b33684dc11b",
"sequencer": "0C0F6F405D6ED209E1",
},
},
}
]
}
sns_event.py 0000664 0000000 0000000 00000002574 15270700723 0037740 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aws-lambda/tests/mocks # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
"""
https://docs.aws.amazon.com/lambda/latest/dg/with-sns.html
"""
MOCK_LAMBDA_SNS_EVENT = {
"Records": [
{
"EventVersion": "1.0",
"EventSubscriptionArn": "arn:aws:sns:us-east-1:123456789012:sns-lambda:21be56ed-a058-49f5-8c98-aedd2564c486",
"EventSource": "aws:sns",
"Sns": {
"SignatureVersion": "1",
"Timestamp": "2019-01-02T12:45:07.000Z",
"Signature": "mock-signature",
"SigningCertURL": "https://sns.us-east-1.amazonaws.com/SimpleNotificationService-ac565b8b1a6c5d002d285f9598aa1d9b.pem",
"MessageId": "95df01b4-ee98-5cb9-9903-4c221d41eb5e",
"Message": "Hello from SNS!",
"MessageAttributes": {
"Test": {"Type": "String", "Value": "TestString"},
"TestBinary": {"Type": "Binary", "Value": "TestBinary"},
},
"Type": "Notification",
"UnsubscribeURL": "https://sns.us-east-1.amazonaws.com/?Action=Unsubscribe&SubscriptionArn=arn:aws:sns:us-east-1:123456789012:test-lambda:21be56ed-a058-49f5-8c98-aedd2564c486",
"TopicArn": "arn:aws:sns:us-east-1:123456789012:sns-lambda",
"Subject": "TestInvoke",
},
}
]
}
sqs_event.py 0000664 0000000 0000000 00000035737 15270700723 0037752 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aws-lambda/tests/mocks # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
"""
https://docs.aws.amazon.com/lambda/latest/dg/with-sqs.html
"""
MOCK_LAMBDA_SQS_EVENT = {
"Records": [
{
"messageId": "059f36b4-87a3-44ab-83d2-661975830a7d",
"receiptHandle": "AQEBwJnKyrHigUMZj6rYigCgxlaS3SLy0a...",
"body": "Test message.",
"attributes": {
"ApproximateReceiveCount": "1",
"SentTimestamp": "1545082649183",
"SenderId": "AIDAIENQZJOLO23YVJ4VO",
"ApproximateFirstReceiveTimestamp": "1545082649185",
},
"messageAttributes": {},
"md5OfBody": "e4e68fb7bd0e697a0ae8f1bb342846b3",
"eventSource": "aws:sqs",
"eventSourceARN": "arn:aws:sqs:us-east-2:123456789012:my-queue",
"awsRegion": "us-east-2",
}
]
}
# SQS event with a W3C traceparent in messageAttributes to test span link extraction.
MOCK_LAMBDA_SQS_EVENT_WITH_TRACE_CONTEXT = {
"Records": [
{
"messageId": "059f36b4-87a3-44ab-83d2-661975830a7d",
"receiptHandle": "AQEBwJnKyrHigUMZj6rYigCgxlaS3SLy0a...",
"body": "Test message.",
"attributes": {
"ApproximateReceiveCount": "1",
"SentTimestamp": "1545082649183",
"SenderId": "AIDAIENQZJOLO23YVJ4VO",
"ApproximateFirstReceiveTimestamp": "1545082649185",
},
"messageAttributes": {
"traceparent": {
"dataType": "String",
"stringValue": "00-5ce0e9a56015fec5aadfa328ae398115-ab54a98ceb1f0ad2-01",
}
},
"md5OfBody": "e4e68fb7bd0e697a0ae8f1bb342846b3",
"eventSource": "aws:sqs",
"eventSourceARN": "arn:aws:sqs:us-east-2:123456789012:my-queue",
"awsRegion": "us-east-2",
}
]
}
# SQS event with an uppercase TRACEPARENT key to test case-insensitive extraction.
MOCK_LAMBDA_SQS_EVENT_UPPERCASE_ATTRS = {
"Records": [
{
"messageId": "059f36b4-87a3-44ab-83d2-661975830a7d",
"receiptHandle": "AQEBwJnKyrHigUMZj6rYigCgxlaS3SLy0a...",
"body": "Test message.",
"attributes": {
"ApproximateReceiveCount": "1",
"SentTimestamp": "1545082649183",
"SenderId": "AIDAIENQZJOLO23YVJ4VO",
"ApproximateFirstReceiveTimestamp": "1545082649185",
},
"messageAttributes": {
"TRACEPARENT": {
"dataType": "String",
"stringValue": "00-5ce0e9a56015fec5aadfa328ae398115-ab54a98ceb1f0ad2-01",
}
},
"md5OfBody": "e4e68fb7bd0e697a0ae8f1bb342846b3",
"eventSource": "aws:sqs",
"eventSourceARN": "arn:aws:sqs:us-east-2:123456789012:my-queue",
"awsRegion": "us-east-2",
}
]
}
# SQS event where messageAttributes is explicitly None.
MOCK_LAMBDA_SQS_EVENT_NULL_MESSAGE_ATTRS = {
"Records": [
{
"messageId": "059f36b4-87a3-44ab-83d2-661975830a7d",
"receiptHandle": "AQEBwJnKyrHigUMZj6rYigCgxlaS3SLy0a...",
"body": "Test message.",
"attributes": {
"ApproximateReceiveCount": "1",
"SentTimestamp": "1545082649183",
"SenderId": "AIDAIENQZJOLO23YVJ4VO",
"ApproximateFirstReceiveTimestamp": "1545082649185",
},
"messageAttributes": None,
"md5OfBody": "e4e68fb7bd0e697a0ae8f1bb342846b3",
"eventSource": "aws:sqs",
"eventSourceARN": "arn:aws:sqs:us-east-2:123456789012:my-queue",
"awsRegion": "us-east-2",
}
]
}
# SQS event where the messageAttributes key is entirely absent from the record.
MOCK_LAMBDA_SQS_EVENT_ABSENT_MESSAGE_ATTRS = {
"Records": [
{
"messageId": "059f36b4-87a3-44ab-83d2-661975830a7d",
"receiptHandle": "AQEBwJnKyrHigUMZj6rYigCgxlaS3SLy0a...",
"body": "Test message.",
"attributes": {
"ApproximateReceiveCount": "1",
"SentTimestamp": "1545082649183",
"SenderId": "AIDAIENQZJOLO23YVJ4VO",
"ApproximateFirstReceiveTimestamp": "1545082649185",
},
"md5OfBody": "e4e68fb7bd0e697a0ae8f1bb342846b3",
"eventSource": "aws:sqs",
"eventSourceARN": "arn:aws:sqs:us-east-2:123456789012:my-queue",
"awsRegion": "us-east-2",
}
]
}
# Three record batch: record 1 has no context, record 2 uses a title case key, record 3 lowercase.
# Exactly two span links should be extracted (records 2 and 3).
MOCK_LAMBDA_SQS_BATCH_EVENT_PARTIAL_CONTEXT = {
"Records": [
{
"messageId": "059f36b4-87a3-44ab-83d2-661975830a7d",
"receiptHandle": "AQEBwJnKyrHigUMZj6rYigCgxlaS3SLy0a...",
"body": "Test message 1 — no trace context.",
"attributes": {
"ApproximateReceiveCount": "1",
"SentTimestamp": "1545082649183",
"SenderId": "AIDAIENQZJOLO23YVJ4VO",
"ApproximateFirstReceiveTimestamp": "1545082649185",
},
"messageAttributes": {},
"md5OfBody": "e4e68fb7bd0e697a0ae8f1bb342846b3",
"eventSource": "aws:sqs",
"eventSourceARN": "arn:aws:sqs:us-east-2:123456789012:my-queue",
"awsRegion": "us-east-2",
},
{
"messageId": "2e1424d4-f796-459a-8184-9c92662be6da",
"receiptHandle": "AQEBwJnKyrHigUMZj6rYigCgxlaS3SLy0b...",
"body": "Test message 2 — title-case Traceparent.",
"attributes": {
"ApproximateReceiveCount": "1",
"SentTimestamp": "1545082650636",
"SenderId": "AIDAIENQZJOLO23YVJ4VO",
"ApproximateFirstReceiveTimestamp": "1545082650649",
},
"messageAttributes": {
"Traceparent": {
"dataType": "String",
"stringValue": "00-aabbccddeeff00112233445566778899-aabbccddeeff0011-01",
}
},
"md5OfBody": "e4e68fb7bd0e697a0ae8f1bb342846b4",
"eventSource": "aws:sqs",
"eventSourceARN": "arn:aws:sqs:us-east-2:123456789012:my-queue",
"awsRegion": "us-east-2",
},
{
"messageId": "7a3b5c9d-1234-5678-abcd-ef0123456789",
"receiptHandle": "AQEBwJnKyrHigUMZj6rYigCgxlaS3SLy0c...",
"body": "Test message 3 — lowercase traceparent.",
"attributes": {
"ApproximateReceiveCount": "1",
"SentTimestamp": "1545082651700",
"SenderId": "AIDAIENQZJOLO23YVJ4VO",
"ApproximateFirstReceiveTimestamp": "1545082651710",
},
"messageAttributes": {
"traceparent": {
"dataType": "String",
"stringValue": "00-cafebabe12345678cafebabe12345678-cafebabe12345678-01",
}
},
"md5OfBody": "e4e68fb7bd0e697a0ae8f1bb342846b5",
"eventSource": "aws:sqs",
"eventSourceARN": "arn:aws:sqs:us-east-2:123456789012:my-queue",
"awsRegion": "us-east-2",
},
]
}
# Malformed: Records list is empty, _is_sqs_event should return False.
MOCK_MALFORMED_SQS_EVENT_EMPTY_RECORDS = {"Records": []}
# Malformed: Records is a string, not a list, _is_sqs_event should return False.
MOCK_MALFORMED_SQS_EVENT_RECORDS_NOT_LIST = {"Records": "not-a-list"}
# Malformed: eventSource is "aws:s3", not "aws:sqs", _is_sqs_event should return False.
MOCK_MALFORMED_SQS_EVENT_WRONG_SOURCE = {
"Records": [
{
"messageId": "059f36b4-87a3-44ab-83d2-661975830a7d",
"receiptHandle": "AQEBwJnKyrHigUMZj6rYigCgxlaS3SLy0a...",
"body": "Test message.",
"attributes": {},
"messageAttributes": {},
"md5OfBody": "e4e68fb7bd0e697a0ae8f1bb342846b3",
"eventSource": "aws:s3",
"eventSourceARN": "arn:aws:s3:::my-bucket",
"awsRegion": "us-east-2",
}
]
}
# Malformed: no Records key at all, _is_sqs_event should return False.
MOCK_MALFORMED_SQS_EVENT_NO_RECORDS_KEY = {"body": "oops, no Records key"}
# SQS event with a traceparent whose stringValue is not a valid W3C traceparent.
# The propagator will parse it as an invalid context, no span link should be extracted.
MOCK_LAMBDA_SQS_EVENT_INVALID_TRACEPARENT = {
"Records": [
{
"messageId": "059f36b4-87a3-44ab-83d2-661975830a7d",
"receiptHandle": "AQEBwJnKyrHigUMZj6rYigCgxlaS3SLy0a...",
"body": "Test message.",
"attributes": {
"ApproximateReceiveCount": "1",
"SentTimestamp": "1545082649183",
"SenderId": "AIDAIENQZJOLO23YVJ4VO",
"ApproximateFirstReceiveTimestamp": "1545082649185",
},
"messageAttributes": {
"traceparent": {
"dataType": "String",
"stringValue": "not-a-valid-traceparent",
}
},
"md5OfBody": "e4e68fb7bd0e697a0ae8f1bb342846b3",
"eventSource": "aws:sqs",
"eventSourceARN": "arn:aws:sqs:us-east-2:123456789012:my-queue",
"awsRegion": "us-east-2",
}
]
}
# SQS event where the messageAttributes value is a bare string rather than a dict.
# _SqsMessageAttributesGetter checks isinstance(msg_attr, Mapping), so no link is extracted.
MOCK_LAMBDA_SQS_EVENT_ATTR_NOT_DICT = {
"Records": [
{
"messageId": "059f36b4-87a3-44ab-83d2-661975830a7d",
"receiptHandle": "AQEBwJnKyrHigUMZj6rYigCgxlaS3SLy0a...",
"body": "Test message.",
"attributes": {
"ApproximateReceiveCount": "1",
"SentTimestamp": "1545082649183",
"SenderId": "AIDAIENQZJOLO23YVJ4VO",
"ApproximateFirstReceiveTimestamp": "1545082649185",
},
"messageAttributes": {
"traceparent": "bare-string-value",
},
"md5OfBody": "e4e68fb7bd0e697a0ae8f1bb342846b3",
"eventSource": "aws:sqs",
"eventSourceARN": "arn:aws:sqs:us-east-2:123456789012:my-queue",
"awsRegion": "us-east-2",
}
]
}
# SQS event where the attribute dict has dataType but no stringValue key.
# The getter returns None for missing stringValue, no link is extracted.
MOCK_LAMBDA_SQS_EVENT_MISSING_STRING_VALUE = {
"Records": [
{
"messageId": "059f36b4-87a3-44ab-83d2-661975830a7d",
"receiptHandle": "AQEBwJnKyrHigUMZj6rYigCgxlaS3SLy0a...",
"body": "Test message.",
"attributes": {
"ApproximateReceiveCount": "1",
"SentTimestamp": "1545082649183",
"SenderId": "AIDAIENQZJOLO23YVJ4VO",
"ApproximateFirstReceiveTimestamp": "1545082649185",
},
"messageAttributes": {
"traceparent": {"dataType": "String"},
},
"md5OfBody": "e4e68fb7bd0e697a0ae8f1bb342846b3",
"eventSource": "aws:sqs",
"eventSourceARN": "arn:aws:sqs:us-east-2:123456789012:my-queue",
"awsRegion": "us-east-2",
}
]
}
# SQS event with no eventSourceARN key, _extract_sqs_queue_name falls back to "".
# The CONSUMER span name becomes "process".
MOCK_LAMBDA_SQS_EVENT_MISSING_ARN = {
"Records": [
{
"messageId": "059f36b4-87a3-44ab-83d2-661975830a7d",
"receiptHandle": "AQEBwJnKyrHigUMZj6rYigCgxlaS3SLy0a...",
"body": "Test message.",
"attributes": {
"ApproximateReceiveCount": "1",
"SentTimestamp": "1545082649183",
"SenderId": "AIDAIENQZJOLO23YVJ4VO",
"ApproximateFirstReceiveTimestamp": "1545082649185",
},
"messageAttributes": {},
"md5OfBody": "e4e68fb7bd0e697a0ae8f1bb342846b3",
"eventSource": "aws:sqs",
"awsRegion": "us-east-2",
}
]
}
# SQS event with a malformed ARN (no colons, fewer than 6 parts).
# _extract_sqs_queue_name returns the full string, CONSUMER span name becomes "process bad-arn".
MOCK_LAMBDA_SQS_EVENT_SHORT_ARN = {
"Records": [
{
"messageId": "059f36b4-87a3-44ab-83d2-661975830a7d",
"receiptHandle": "AQEBwJnKyrHigUMZj6rYigCgxlaS3SLy0a...",
"body": "Test message.",
"attributes": {
"ApproximateReceiveCount": "1",
"SentTimestamp": "1545082649183",
"SenderId": "AIDAIENQZJOLO23YVJ4VO",
"ApproximateFirstReceiveTimestamp": "1545082649185",
},
"messageAttributes": {},
"md5OfBody": "e4e68fb7bd0e697a0ae8f1bb342846b3",
"eventSource": "aws:sqs",
"eventSourceARN": "bad-arn",
"awsRegion": "us-east-2",
}
]
}
# SQS event with two records to test batch attribute handling.
MOCK_LAMBDA_SQS_BATCH_EVENT = {
"Records": [
{
"messageId": "059f36b4-87a3-44ab-83d2-661975830a7d",
"receiptHandle": "AQEBwJnKyrHigUMZj6rYigCgxlaS3SLy0a...",
"body": "Test message 1.",
"attributes": {
"ApproximateReceiveCount": "1",
"SentTimestamp": "1545082649183",
"SenderId": "AIDAIENQZJOLO23YVJ4VO",
"ApproximateFirstReceiveTimestamp": "1545082649185",
},
"messageAttributes": {
"traceparent": {
"dataType": "String",
"stringValue": "00-5ce0e9a56015fec5aadfa328ae398115-ab54a98ceb1f0ad2-01",
}
},
"md5OfBody": "e4e68fb7bd0e697a0ae8f1bb342846b3",
"eventSource": "aws:sqs",
"eventSourceARN": "arn:aws:sqs:us-east-2:123456789012:my-queue",
"awsRegion": "us-east-2",
},
{
"messageId": "2e1424d4-f796-459a-8184-9c92662be6da",
"receiptHandle": "AQEBwJnKyrHigUMZj6rYigCgxlaS3SLy0b...",
"body": "Test message 2.",
"attributes": {
"ApproximateReceiveCount": "1",
"SentTimestamp": "1545082650636",
"SenderId": "AIDAIENQZJOLO23YVJ4VO",
"ApproximateFirstReceiveTimestamp": "1545082650649",
},
"messageAttributes": {
"traceparent": {
"dataType": "String",
"stringValue": "00-8a3c60f7d188f8fa79d48a391a778fa6-53995c3f42cd8ad8-01",
}
},
"md5OfBody": "e4e68fb7bd0e697a0ae8f1bb342846b4",
"eventSource": "aws:sqs",
"eventSourceARN": "arn:aws:sqs:us-east-2:123456789012:my-queue",
"awsRegion": "us-east-2",
},
]
}
test_aws_lambda_instrumentation_manual.py 0000664 0000000 0000000 00000133150 15270700723 0044624 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-aws-lambda/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
# pylint: disable=too-many-lines
import logging
import os
from collections.abc import Callable
from copy import deepcopy
from dataclasses import dataclass
from importlib import import_module, reload
from typing import Any
from unittest import mock
from opentelemetry import propagate
from opentelemetry.baggage.propagation import W3CBaggagePropagator
from opentelemetry.environment_variables import OTEL_PROPAGATORS
from opentelemetry.instrumentation.aws_lambda import (
_HANDLER,
_X_AMZN_TRACE_ID,
OTEL_INSTRUMENTATION_AWS_LAMBDA_FLUSH_TIMEOUT,
AwsLambdaInstrumentor,
_default_event_context_extractor,
)
from opentelemetry.propagate import get_global_textmap
from opentelemetry.propagators.aws.aws_xray_propagator import (
TRACE_ID_FIRST_PART_LENGTH,
TRACE_ID_VERSION,
)
from opentelemetry.semconv._incubating.attributes.cloud_attributes import (
CLOUD_ACCOUNT_ID,
CLOUD_RESOURCE_ID,
)
from opentelemetry.semconv._incubating.attributes.faas_attributes import (
FAAS_INVOCATION_ID,
FAAS_TRIGGER,
FaasTriggerValues,
)
from opentelemetry.semconv._incubating.attributes.http_attributes import (
HTTP_METHOD,
HTTP_ROUTE,
HTTP_SCHEME,
HTTP_STATUS_CODE,
HTTP_TARGET,
HTTP_USER_AGENT,
)
from opentelemetry.semconv._incubating.attributes.messaging_attributes import (
MESSAGING_BATCH_MESSAGE_COUNT,
MESSAGING_DESTINATION_NAME,
MESSAGING_MESSAGE_ID,
MESSAGING_OPERATION_TYPE,
MESSAGING_SYSTEM,
MessagingOperationTypeValues,
MessagingSystemValues,
)
from opentelemetry.semconv._incubating.attributes.net_attributes import (
NET_HOST_NAME,
)
from opentelemetry.test.test_base import TestBase
from opentelemetry.trace import NoOpTracerProvider, SpanKind, StatusCode
from opentelemetry.trace.propagation.tracecontext import (
TraceContextTextMapPropagator,
)
from opentelemetry.util._importlib_metadata import entry_points
from .mocks.alb_conventional_headers_event import MOCK_LAMBDA_ALB_EVENT
from .mocks.alb_multi_value_headers_event import (
MOCK_LAMBDA_ALB_MULTI_VALUE_HEADER_EVENT,
)
from .mocks.api_gateway_http_api_event import (
MOCK_LAMBDA_API_GATEWAY_HTTP_API_EVENT,
)
from .mocks.api_gateway_proxy_event import MOCK_LAMBDA_API_GATEWAY_PROXY_EVENT
from .mocks.dynamo_db_event import MOCK_LAMBDA_DYNAMO_DB_EVENT
from .mocks.s3_event import MOCK_LAMBDA_S3_EVENT
from .mocks.sns_event import MOCK_LAMBDA_SNS_EVENT
from .mocks.sqs_event import (
MOCK_LAMBDA_SQS_BATCH_EVENT,
MOCK_LAMBDA_SQS_BATCH_EVENT_PARTIAL_CONTEXT,
MOCK_LAMBDA_SQS_EVENT,
MOCK_LAMBDA_SQS_EVENT_ABSENT_MESSAGE_ATTRS,
MOCK_LAMBDA_SQS_EVENT_ATTR_NOT_DICT,
MOCK_LAMBDA_SQS_EVENT_INVALID_TRACEPARENT,
MOCK_LAMBDA_SQS_EVENT_MISSING_ARN,
MOCK_LAMBDA_SQS_EVENT_MISSING_STRING_VALUE,
MOCK_LAMBDA_SQS_EVENT_NULL_MESSAGE_ATTRS,
MOCK_LAMBDA_SQS_EVENT_SHORT_ARN,
MOCK_LAMBDA_SQS_EVENT_UPPERCASE_ATTRS,
MOCK_LAMBDA_SQS_EVENT_WITH_TRACE_CONTEXT,
MOCK_MALFORMED_SQS_EVENT_EMPTY_RECORDS,
MOCK_MALFORMED_SQS_EVENT_NO_RECORDS_KEY,
MOCK_MALFORMED_SQS_EVENT_RECORDS_NOT_LIST,
MOCK_MALFORMED_SQS_EVENT_WRONG_SOURCE,
)
class MockLambdaContext:
def __init__(self, function_name, aws_request_id, invoked_function_arn):
self.function_name = function_name
self.invoked_function_arn = invoked_function_arn
self.aws_request_id = aws_request_id
MOCK_LAMBDA_CONTEXT = MockLambdaContext(
function_name="myfunction",
aws_request_id="mock_aws_request_id",
invoked_function_arn="arn:aws:lambda:us-east-1:123456:function:myfunction:myalias",
)
MOCK_LAMBDA_CONTEXT_ATTRIBUTES = {
CLOUD_RESOURCE_ID: ":".join(MOCK_LAMBDA_CONTEXT.invoked_function_arn.split(":")[:7]),
FAAS_INVOCATION_ID: MOCK_LAMBDA_CONTEXT.aws_request_id,
CLOUD_ACCOUNT_ID: MOCK_LAMBDA_CONTEXT.invoked_function_arn.split(":")[4],
}
MOCK_XRAY_TRACE_ID = 0x5FB7331105E8BB83207FA31D4D9CDB4C
MOCK_XRAY_TRACE_ID_STR = f"{MOCK_XRAY_TRACE_ID:x}"
MOCK_XRAY_PARENT_SPAN_ID = 0x3328B8445A6DBAD2
MOCK_XRAY_TRACE_CONTEXT_COMMON = f"Root={TRACE_ID_VERSION}-{MOCK_XRAY_TRACE_ID_STR[:TRACE_ID_FIRST_PART_LENGTH]}-{MOCK_XRAY_TRACE_ID_STR[TRACE_ID_FIRST_PART_LENGTH:]};Parent={MOCK_XRAY_PARENT_SPAN_ID:x}"
MOCK_XRAY_TRACE_CONTEXT_SAMPLED = f"{MOCK_XRAY_TRACE_CONTEXT_COMMON};Sampled=1"
MOCK_XRAY_TRACE_CONTEXT_NOT_SAMPLED = f"{MOCK_XRAY_TRACE_CONTEXT_COMMON};Sampled=0"
# See more:
# https://www.w3.org/TR/trace-context/#examples-of-http-traceparent-headers
MOCK_W3C_TRACE_ID = 0x5CE0E9A56015FEC5AADFA328AE398115
MOCK_W3C_PARENT_SPAN_ID = 0xAB54A98CEB1F0AD2
MOCK_W3C_TRACE_CONTEXT_SAMPLED = f"00-{MOCK_W3C_TRACE_ID:x}-{MOCK_W3C_PARENT_SPAN_ID:x}-01"
MOCK_W3C_TRACE_STATE_KEY = "vendor_specific_key"
MOCK_W3C_TRACE_STATE_VALUE = "test_value"
MOCK_W3C_BAGGAGE_KEY = "baggage_key"
MOCK_W3C_BAGGAGE_VALUE = "baggage_value"
def mock_execute_lambda(event=None, context=None):
"""Mocks the AWS Lambda execution.
NOTE: We don't use `moto`'s `mock_lambda` because we are not instrumenting
calls to AWS Lambda using the AWS SDK. Instead, we are instrumenting AWS
Lambda itself.
See more:
https://docs.aws.amazon.com/lambda/latest/dg/runtimes-modify.html#runtime-wrapper
Args:
event: The Lambda event which may or may not be used by instrumentation.
context: The AWS Lambda context to call the handler with
"""
module_name, handler_name = os.environ[_HANDLER].rsplit(".", 1)
handler_module = import_module(module_name.replace("/", "."))
return getattr(handler_module, handler_name)(event, context or MOCK_LAMBDA_CONTEXT)
class TestAwsLambdaInstrumentorBase(TestBase):
"""AWS Lambda Instrumentation Testsuite"""
def setUp(self):
super().setUp()
self.common_env_patch = mock.patch.dict(
"os.environ",
{
_HANDLER: "tests.mocks.lambda_function.handler",
"AWS_LAMBDA_FUNCTION_NAME": "mylambda",
},
)
self.common_env_patch.start()
# NOTE: Whether AwsLambdaInstrumentor().instrument() is run is decided
# by each test case. It depends on if the test is for auto or manual
# instrumentation.
def tearDown(self):
super().tearDown()
self.common_env_patch.stop()
AwsLambdaInstrumentor().uninstrument()
class TestAwsLambdaInstrumentor(TestAwsLambdaInstrumentorBase):
def test_default_event_context_extractor_does_not_log_for_missing_headers(
self,
):
with mock.patch("opentelemetry.instrumentation.aws_lambda.logger.debug") as debug_mock:
_default_event_context_extractor({})
self.assertEqual(debug_mock.call_count, 0)
def test_active_tracing(self):
test_env_patch = mock.patch.dict(
"os.environ",
{
**os.environ,
# Using Active tracing
OTEL_PROPAGATORS: "xray-lambda",
_X_AMZN_TRACE_ID: MOCK_XRAY_TRACE_CONTEXT_SAMPLED,
},
)
test_env_patch.start()
reload(propagate)
AwsLambdaInstrumentor().instrument()
mock_execute_lambda()
spans = self.memory_exporter.get_finished_spans()
assert spans
self.assertEqual(len(spans), 1)
span = spans[0]
self.assertEqual(span.name, MOCK_LAMBDA_CONTEXT.function_name)
self.assertEqual(span.get_span_context().trace_id, MOCK_XRAY_TRACE_ID)
self.assertEqual(span.kind, SpanKind.SERVER)
self.assertSpanHasAttributes(
span,
MOCK_LAMBDA_CONTEXT_ATTRIBUTES,
)
parent_context = span.parent
self.assertEqual(parent_context.trace_id, span.get_span_context().trace_id)
self.assertEqual(parent_context.span_id, MOCK_XRAY_PARENT_SPAN_ID)
self.assertTrue(parent_context.is_remote)
test_env_patch.stop()
def test_parent_context_from_lambda_event(self):
@dataclass
class TestCase:
name: str
custom_extractor: Callable[[Any], None]
context: dict
expected_traceid: int
expected_parentid: int
xray_traceid: str
expected_state_value: str = None
expected_trace_state_len: int = 0
propagators: str = "tracecontext"
expected_baggage: str = None
disable_aws_context_propagation: bool = False
disable_aws_context_propagation_envvar: str = ""
def custom_event_context_extractor(lambda_event):
return get_global_textmap().extract(lambda_event["foo"]["headers"])
tests = [
TestCase(
name="no_custom_extractor",
custom_extractor=None,
context={
"headers": {
TraceContextTextMapPropagator._TRACEPARENT_HEADER_NAME: MOCK_W3C_TRACE_CONTEXT_SAMPLED,
TraceContextTextMapPropagator._TRACESTATE_HEADER_NAME: f"{MOCK_W3C_TRACE_STATE_KEY}={MOCK_W3C_TRACE_STATE_VALUE},foo=1,bar=2",
}
},
expected_traceid=MOCK_W3C_TRACE_ID,
expected_parentid=MOCK_W3C_PARENT_SPAN_ID,
expected_trace_state_len=3,
expected_state_value=MOCK_W3C_TRACE_STATE_VALUE,
xray_traceid=MOCK_XRAY_TRACE_CONTEXT_NOT_SAMPLED,
),
TestCase(
name="custom_extractor_not_sampled_xray",
custom_extractor=custom_event_context_extractor,
context={
"foo": {
"headers": {
TraceContextTextMapPropagator._TRACEPARENT_HEADER_NAME: MOCK_W3C_TRACE_CONTEXT_SAMPLED,
TraceContextTextMapPropagator._TRACESTATE_HEADER_NAME: f"{MOCK_W3C_TRACE_STATE_KEY}={MOCK_W3C_TRACE_STATE_VALUE},foo=1,bar=2",
}
}
},
expected_traceid=MOCK_W3C_TRACE_ID,
expected_parentid=MOCK_W3C_PARENT_SPAN_ID,
expected_trace_state_len=3,
expected_state_value=MOCK_W3C_TRACE_STATE_VALUE,
xray_traceid=MOCK_XRAY_TRACE_CONTEXT_NOT_SAMPLED,
),
TestCase(
name="custom_extractor_sampled_xray",
custom_extractor=custom_event_context_extractor,
context={
"foo": {
"headers": {
TraceContextTextMapPropagator._TRACEPARENT_HEADER_NAME: MOCK_W3C_TRACE_CONTEXT_SAMPLED,
TraceContextTextMapPropagator._TRACESTATE_HEADER_NAME: f"{MOCK_W3C_TRACE_STATE_KEY}={MOCK_W3C_TRACE_STATE_VALUE},foo=1,bar=2",
}
}
},
expected_traceid=MOCK_XRAY_TRACE_ID,
expected_parentid=MOCK_XRAY_PARENT_SPAN_ID,
xray_traceid=MOCK_XRAY_TRACE_CONTEXT_SAMPLED,
propagators="xray-lambda",
),
TestCase(
name="custom_extractor_sampled_xray",
custom_extractor=custom_event_context_extractor,
context={
"foo": {
"headers": {
TraceContextTextMapPropagator._TRACEPARENT_HEADER_NAME: MOCK_W3C_TRACE_CONTEXT_SAMPLED,
TraceContextTextMapPropagator._TRACESTATE_HEADER_NAME: f"{MOCK_W3C_TRACE_STATE_KEY}={MOCK_W3C_TRACE_STATE_VALUE},foo=1,bar=2",
}
}
},
expected_traceid=MOCK_W3C_TRACE_ID,
expected_parentid=MOCK_W3C_PARENT_SPAN_ID,
expected_trace_state_len=3,
expected_state_value=MOCK_W3C_TRACE_STATE_VALUE,
xray_traceid=MOCK_XRAY_TRACE_CONTEXT_SAMPLED,
),
TestCase(
name="no_custom_extractor_xray",
custom_extractor=None,
context={
"headers": {
TraceContextTextMapPropagator._TRACEPARENT_HEADER_NAME: MOCK_W3C_TRACE_CONTEXT_SAMPLED,
TraceContextTextMapPropagator._TRACESTATE_HEADER_NAME: f"{MOCK_W3C_TRACE_STATE_KEY}={MOCK_W3C_TRACE_STATE_VALUE},foo=1,bar=2",
}
},
expected_traceid=MOCK_W3C_TRACE_ID,
expected_parentid=MOCK_W3C_PARENT_SPAN_ID,
expected_trace_state_len=3,
expected_state_value=MOCK_W3C_TRACE_STATE_VALUE,
xray_traceid=MOCK_XRAY_TRACE_CONTEXT_SAMPLED,
),
TestCase(
name="baggage_propagation",
custom_extractor=None,
context={
"headers": {
TraceContextTextMapPropagator._TRACEPARENT_HEADER_NAME: MOCK_W3C_TRACE_CONTEXT_SAMPLED,
TraceContextTextMapPropagator._TRACESTATE_HEADER_NAME: f"{MOCK_W3C_TRACE_STATE_KEY}={MOCK_W3C_TRACE_STATE_VALUE},foo=1,bar=2",
W3CBaggagePropagator._BAGGAGE_HEADER_NAME: f"{MOCK_W3C_BAGGAGE_KEY}={MOCK_W3C_BAGGAGE_VALUE}",
}
},
expected_traceid=MOCK_W3C_TRACE_ID,
expected_parentid=MOCK_W3C_PARENT_SPAN_ID,
expected_trace_state_len=3,
expected_state_value=MOCK_W3C_TRACE_STATE_VALUE,
xray_traceid=MOCK_XRAY_TRACE_CONTEXT_NOT_SAMPLED,
expected_baggage=MOCK_W3C_BAGGAGE_VALUE,
propagators="tracecontext,baggage",
),
TestCase(
name="case_insensitive_headers_uppercase",
custom_extractor=None,
context={
"headers": {
TraceContextTextMapPropagator._TRACEPARENT_HEADER_NAME.upper(): MOCK_W3C_TRACE_CONTEXT_SAMPLED,
TraceContextTextMapPropagator._TRACESTATE_HEADER_NAME.upper(): f"{MOCK_W3C_TRACE_STATE_KEY}={MOCK_W3C_TRACE_STATE_VALUE},foo=1,bar=2",
}
},
expected_traceid=MOCK_W3C_TRACE_ID,
expected_parentid=MOCK_W3C_PARENT_SPAN_ID,
expected_trace_state_len=3,
expected_state_value=MOCK_W3C_TRACE_STATE_VALUE,
xray_traceid=MOCK_XRAY_TRACE_CONTEXT_NOT_SAMPLED,
),
TestCase(
name="case_insensitive_headers_mixedcase",
custom_extractor=None,
context={
"headers": {
"TraceParent": MOCK_W3C_TRACE_CONTEXT_SAMPLED,
"tRaCeStAtE": f"{MOCK_W3C_TRACE_STATE_KEY}={MOCK_W3C_TRACE_STATE_VALUE},foo=1,bar=2",
}
},
expected_traceid=MOCK_W3C_TRACE_ID,
expected_parentid=MOCK_W3C_PARENT_SPAN_ID,
expected_trace_state_len=3,
expected_state_value=MOCK_W3C_TRACE_STATE_VALUE,
xray_traceid=MOCK_XRAY_TRACE_CONTEXT_NOT_SAMPLED,
),
]
for test in tests:
with self.subTest(test_name=test.name):
test_env_patch = mock.patch.dict(
"os.environ",
{
**os.environ,
# NOT Active Tracing
_X_AMZN_TRACE_ID: test.xray_traceid,
OTEL_PROPAGATORS: test.propagators,
},
)
test_env_patch.start()
reload(propagate)
AwsLambdaInstrumentor().instrument(
event_context_extractor=test.custom_extractor,
)
mock_execute_lambda(test.context)
spans = self.memory_exporter.get_finished_spans()
assert spans
self.assertEqual(len(spans), 1)
span = spans[0]
self.assertEqual(span.get_span_context().trace_id, test.expected_traceid)
parent_context = span.parent
self.assertEqual(parent_context.trace_id, span.get_span_context().trace_id)
self.assertEqual(parent_context.span_id, test.expected_parentid)
self.assertEqual(
len(parent_context.trace_state),
test.expected_trace_state_len,
)
self.assertEqual(
parent_context.trace_state.get(MOCK_W3C_TRACE_STATE_KEY),
test.expected_state_value,
)
self.assertTrue(parent_context.is_remote)
self.memory_exporter.clear()
AwsLambdaInstrumentor().uninstrument()
test_env_patch.stop()
def test_lambda_no_error_with_invalid_flush_timeout(self):
test_env_patch = mock.patch.dict(
"os.environ",
{
**os.environ,
# NOT Active Tracing
_X_AMZN_TRACE_ID: MOCK_XRAY_TRACE_CONTEXT_NOT_SAMPLED,
# NOT using the X-Ray Propagator
OTEL_PROPAGATORS: "tracecontext",
OTEL_INSTRUMENTATION_AWS_LAMBDA_FLUSH_TIMEOUT: "invalid-timeout-string",
},
)
test_env_patch.start()
AwsLambdaInstrumentor().instrument()
mock_execute_lambda()
spans = self.memory_exporter.get_finished_spans()
assert spans
self.assertEqual(len(spans), 1)
test_env_patch.stop()
def test_api_gateway_v1_attributes_case_insensitivity(self):
AwsLambdaInstrumentor().instrument()
mock_execute_lambda(
{
"httpMethod": "GET",
"headers": {
"user-agent": "lowercase-agent",
"host": "lowercase-host",
"x-forwarded-proto": "http",
},
"resource": "/test",
"requestContext": {
"version": "1.0",
},
}
)
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
span = spans[0]
self.assertEqual(span.attributes.get(HTTP_USER_AGENT), "lowercase-agent")
self.assertEqual(span.attributes.get(NET_HOST_NAME), "lowercase-host")
self.assertEqual(span.attributes.get(HTTP_SCHEME), "http")
self.memory_exporter.clear()
mock_execute_lambda(
{
"httpMethod": "GET",
"headers": {
"uSeR-aGeNt": "mixed-agent",
"hOsT": "mixed-host",
"X-fOrWaRdEd-PrOtO": "https",
},
"resource": "/test",
"requestContext": {
"version": "1.0",
},
}
)
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
span = spans[0]
self.assertEqual(span.attributes.get(HTTP_USER_AGENT), "mixed-agent")
self.assertEqual(span.attributes.get(NET_HOST_NAME), "mixed-host")
self.assertEqual(span.attributes.get(HTTP_SCHEME), "https")
def test_lambda_handles_multiple_consumers(self):
test_env_patch = mock.patch.dict(
"os.environ",
{
**os.environ,
# NOT Active Tracing
_X_AMZN_TRACE_ID: MOCK_XRAY_TRACE_CONTEXT_NOT_SAMPLED,
# NOT using the X-Ray Propagator
OTEL_PROPAGATORS: "tracecontext",
},
)
test_env_patch.start()
AwsLambdaInstrumentor().instrument()
mock_execute_lambda({"Records": [{"eventSource": "aws:sqs"}]})
mock_execute_lambda({"Records": [{"eventSource": "aws:s3"}]})
mock_execute_lambda({"Records": [{"EventSource": "aws:sns"}]})
mock_execute_lambda({"Records": [{"eventSource": "aws:dynamodb"}]})
spans = self.memory_exporter.get_finished_spans()
assert spans
# SQS produces 2 spans (SERVER invocation + CONSUMER process), others produce 1 each
assert len(spans) == 5
server_spans = [s for s in spans if s.kind == SpanKind.SERVER]
consumer_spans = [s for s in spans if s.kind == SpanKind.CONSUMER]
assert len(server_spans) == 4
assert len(consumer_spans) == 1
test_env_patch.stop()
def test_lambda_handles_invalid_event_source(self):
test_env_patch = mock.patch.dict(
"os.environ",
{
**os.environ,
# NOT Active Tracing
_X_AMZN_TRACE_ID: MOCK_XRAY_TRACE_CONTEXT_NOT_SAMPLED,
# NOT using the X-Ray Propagator
OTEL_PROPAGATORS: "tracecontext",
},
)
test_env_patch.start()
reload(propagate)
AwsLambdaInstrumentor().instrument()
mock_execute_lambda({"Records": [{"eventSource": "invalid_source"}]})
spans = self.memory_exporter.get_finished_spans()
assert spans
assert len(spans) == 1
# Default to SERVER for unknown sources
assert spans[0].kind == SpanKind.SERVER
for span in spans:
self.assertSpanHasAttributes(
span,
MOCK_LAMBDA_CONTEXT_ATTRIBUTES,
)
test_env_patch.stop()
def test_lambda_handles_list_event(self):
AwsLambdaInstrumentor().instrument()
mock_execute_lambda([{"message": "test"}])
spans = self.memory_exporter.get_finished_spans()
assert spans
def test_lambda_handles_handler_exception(self):
exc_env_patch = mock.patch.dict(
"os.environ",
{_HANDLER: "tests.mocks.lambda_function.handler_exc"},
)
exc_env_patch.start()
AwsLambdaInstrumentor().instrument()
# instrumentor re-raises the exception
with self.assertRaises(Exception):
mock_execute_lambda()
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
span = spans[0]
self.assertEqual(span.status.status_code, StatusCode.ERROR)
self.assertEqual(len(span.events), 1)
event = span.events[0]
self.assertEqual(event.name, "exception")
exc_env_patch.stop()
@mock.patch("opentelemetry.instrumentation.aws_lambda.logger")
def test_lambda_handles_should_do_nothing_when_aws_lambda_environment_variables_not_present(self, logger_mock):
exc_env_patch = mock.patch.dict(
"os.environ",
{_HANDLER: "tests.mocks.lambda_function.handler"},
clear=True,
)
exc_env_patch.start()
AwsLambdaInstrumentor().instrument()
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 0)
exc_env_patch.stop()
logger_mock.warnings.assert_not_called()
def test_lambda_handles_should_warn_when_handler_environment_variable_not_present(
self,
):
exc_env_patch = mock.patch.dict(
"os.environ",
{"AWS_LAMBDA_FUNCTION_NAME": "mylambda"},
clear=True,
)
exc_env_patch.start()
with self.assertLogs(level=logging.WARNING) as warning:
AwsLambdaInstrumentor().instrument()
self.assertEqual(len(warning.records), 1)
self.assertIn(
"This instrumentation requires the OpenTelemetry Lambda extension installed",
warning.records[0].message,
)
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 0)
exc_env_patch.stop()
def test_uninstrument(self):
AwsLambdaInstrumentor().instrument()
mock_execute_lambda(MOCK_LAMBDA_API_GATEWAY_HTTP_API_EVENT)
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
self.memory_exporter.clear()
AwsLambdaInstrumentor().uninstrument()
mock_execute_lambda(MOCK_LAMBDA_API_GATEWAY_HTTP_API_EVENT)
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 0)
def test_no_op_tracer_provider(self):
tracer_provider = NoOpTracerProvider()
AwsLambdaInstrumentor().instrument(tracer_provider=tracer_provider)
mock_execute_lambda(MOCK_LAMBDA_API_GATEWAY_HTTP_API_EVENT)
spans = self.memory_exporter.get_finished_spans()
assert spans is not None
self.assertEqual(len(spans), 0)
def test_load_entry_point(self):
self.assertIs(
next(iter(entry_points(group="opentelemetry_instrumentor", name="aws-lambda"))).load(),
AwsLambdaInstrumentor,
)
# pylint: disable-next=too-many-public-methods
class TestAwsLambdaInstrumentorMocks(TestAwsLambdaInstrumentorBase):
def test_api_gateway_proxy_event_sets_attributes(self):
handler_patch = mock.patch.dict(
"os.environ",
{_HANDLER: "tests.mocks.lambda_function.rest_api_handler"},
)
handler_patch.start()
AwsLambdaInstrumentor().instrument()
mock_execute_lambda(MOCK_LAMBDA_API_GATEWAY_PROXY_EVENT)
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
span, *_ = spans
self.assertEqual(span.kind, SpanKind.SERVER)
self.assertSpanHasAttributes(
span,
MOCK_LAMBDA_CONTEXT_ATTRIBUTES,
)
self.assertSpanHasAttributes(
span,
{
FAAS_TRIGGER: "http",
HTTP_METHOD: "POST",
HTTP_ROUTE: "/{proxy+}",
HTTP_TARGET: "/{proxy+}?foo=bar",
NET_HOST_NAME: "0123456789.execute-api.us-east-1.amazonaws.com",
HTTP_USER_AGENT: "Custom User Agent String",
HTTP_SCHEME: "https",
HTTP_STATUS_CODE: 200,
},
)
def test_api_gateway_http_api_proxy_event_sets_attributes(self):
AwsLambdaInstrumentor().instrument()
mock_execute_lambda(MOCK_LAMBDA_API_GATEWAY_HTTP_API_EVENT)
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
span, *_ = spans
self.assertEqual(span.kind, SpanKind.SERVER)
self.assertSpanHasAttributes(
span,
MOCK_LAMBDA_CONTEXT_ATTRIBUTES,
)
self.assertSpanHasAttributes(
span,
{
FAAS_TRIGGER: "http",
HTTP_METHOD: "POST",
HTTP_ROUTE: "/path/to/resource",
HTTP_TARGET: "/path/to/resource?parameter1=value1¶meter1=value2¶meter2=value",
NET_HOST_NAME: "id.execute-api.us-east-1.amazonaws.com",
HTTP_USER_AGENT: "agent",
},
)
def test_alb_conventional_event_sets_attributes(self):
AwsLambdaInstrumentor().instrument()
mock_execute_lambda(MOCK_LAMBDA_ALB_EVENT)
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
span, *_ = spans
self.assertEqual(span.kind, SpanKind.SERVER)
self.assertSpanHasAttributes(
span,
MOCK_LAMBDA_CONTEXT_ATTRIBUTES,
)
self.assertSpanHasAttributes(
span,
{
FAAS_TRIGGER: "http",
HTTP_METHOD: "GET",
},
)
def test_alb_multi_value_header_event_sets_attributes(self):
AwsLambdaInstrumentor().instrument()
mock_execute_lambda(MOCK_LAMBDA_ALB_MULTI_VALUE_HEADER_EVENT)
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
span, *_ = spans
self.assertEqual(span.kind, SpanKind.SERVER)
self.assertSpanHasAttributes(
span,
MOCK_LAMBDA_CONTEXT_ATTRIBUTES,
)
self.assertSpanHasAttributes(
span,
{
FAAS_TRIGGER: "http",
HTTP_METHOD: "GET",
HTTP_SCHEME: "https",
HTTP_USER_AGENT: "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_11_6)",
NET_HOST_NAME: "lambda-846800462-us-east-2.elb.amazonaws.com",
},
)
def test_alb_mixed_header_event_sets_attributes(self):
AwsLambdaInstrumentor().instrument()
event = deepcopy(MOCK_LAMBDA_ALB_MULTI_VALUE_HEADER_EVENT)
event["headers"] = {"accept": "text/html,application/xhtml+xml"}
mock_execute_lambda(event)
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
span, *_ = spans
self.assertEqual(span.kind, SpanKind.SERVER)
self.assertSpanHasAttributes(
span,
{
HTTP_SCHEME: "https",
HTTP_USER_AGENT: "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_11_6)",
NET_HOST_NAME: "lambda-846800462-us-east-2.elb.amazonaws.com",
},
)
def test_alb_mixed_header_event_prefers_multi_value_headers(self):
AwsLambdaInstrumentor().instrument()
event = deepcopy(MOCK_LAMBDA_ALB_MULTI_VALUE_HEADER_EVENT)
event["headers"] = {
"host": "wrong.example.com",
"user-agent": "wrong-agent",
"x-forwarded-proto": "http",
}
mock_execute_lambda(event)
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
span, *_ = spans
self.assertSpanHasAttributes(
span,
{
HTTP_SCHEME: "https",
HTTP_USER_AGENT: "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_11_6)",
NET_HOST_NAME: "lambda-846800462-us-east-2.elb.amazonaws.com",
},
)
@mock.patch.dict(
"os.environ",
{
_X_AMZN_TRACE_ID: MOCK_XRAY_TRACE_CONTEXT_NOT_SAMPLED,
OTEL_PROPAGATORS: "tracecontext",
},
)
def test_alb_multi_value_header_event_extracts_parent_context(self):
reload(propagate)
AwsLambdaInstrumentor().instrument()
event = deepcopy(MOCK_LAMBDA_ALB_MULTI_VALUE_HEADER_EVENT)
event["multiValueHeaders"][TraceContextTextMapPropagator._TRACEPARENT_HEADER_NAME] = [
MOCK_W3C_TRACE_CONTEXT_SAMPLED
]
mock_execute_lambda(event)
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
span, *_ = spans
self.assertEqual(span.get_span_context().trace_id, MOCK_W3C_TRACE_ID)
parent_context = span.parent
self.assertEqual(parent_context.trace_id, span.get_span_context().trace_id)
self.assertEqual(parent_context.span_id, MOCK_W3C_PARENT_SPAN_ID)
self.assertTrue(parent_context.is_remote)
@mock.patch.dict(
"os.environ",
{
_X_AMZN_TRACE_ID: MOCK_XRAY_TRACE_CONTEXT_NOT_SAMPLED,
OTEL_PROPAGATORS: "tracecontext",
},
)
def test_alb_mixed_header_event_extracts_parent_context(self):
reload(propagate)
AwsLambdaInstrumentor().instrument()
event = deepcopy(MOCK_LAMBDA_ALB_MULTI_VALUE_HEADER_EVENT)
event["headers"] = {"accept": "text/html,application/xhtml+xml"}
event["multiValueHeaders"][TraceContextTextMapPropagator._TRACEPARENT_HEADER_NAME] = [
MOCK_W3C_TRACE_CONTEXT_SAMPLED
]
mock_execute_lambda(event)
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
span, *_ = spans
self.assertEqual(span.get_span_context().trace_id, MOCK_W3C_TRACE_ID)
parent_context = span.parent
self.assertEqual(parent_context.trace_id, span.get_span_context().trace_id)
self.assertEqual(parent_context.span_id, MOCK_W3C_PARENT_SPAN_ID)
self.assertTrue(parent_context.is_remote)
@mock.patch.dict(
"os.environ",
{
_X_AMZN_TRACE_ID: MOCK_XRAY_TRACE_CONTEXT_NOT_SAMPLED,
OTEL_PROPAGATORS: "tracecontext",
},
)
def test_alb_mixed_header_event_prefers_multi_value_traceparent(self):
reload(propagate)
AwsLambdaInstrumentor().instrument()
event = deepcopy(MOCK_LAMBDA_ALB_MULTI_VALUE_HEADER_EVENT)
event["headers"] = {
TraceContextTextMapPropagator._TRACEPARENT_HEADER_NAME: (
"00-11111111111111111111111111111111-2222222222222222-01"
)
}
event["multiValueHeaders"][TraceContextTextMapPropagator._TRACEPARENT_HEADER_NAME] = [
MOCK_W3C_TRACE_CONTEXT_SAMPLED
]
mock_execute_lambda(event)
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
span, *_ = spans
self.assertEqual(span.get_span_context().trace_id, MOCK_W3C_TRACE_ID)
parent_context = span.parent
self.assertEqual(parent_context.trace_id, span.get_span_context().trace_id)
self.assertEqual(parent_context.span_id, MOCK_W3C_PARENT_SPAN_ID)
self.assertTrue(parent_context.is_remote)
def test_dynamo_db_event_sets_attributes(self):
AwsLambdaInstrumentor().instrument()
mock_execute_lambda(MOCK_LAMBDA_DYNAMO_DB_EVENT)
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
span, *_ = spans
self.assertEqual(span.kind, SpanKind.SERVER)
self.assertSpanHasAttributes(
span,
MOCK_LAMBDA_CONTEXT_ATTRIBUTES,
)
def test_s3_event_sets_attributes(self):
AwsLambdaInstrumentor().instrument()
mock_execute_lambda(MOCK_LAMBDA_S3_EVENT)
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
span, *_ = spans
self.assertEqual(span.kind, SpanKind.SERVER)
self.assertSpanHasAttributes(
span,
MOCK_LAMBDA_CONTEXT_ATTRIBUTES,
)
def test_sns_event_sets_attributes(self):
AwsLambdaInstrumentor().instrument()
mock_execute_lambda(MOCK_LAMBDA_SNS_EVENT)
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
span, *_ = spans
self.assertEqual(span.kind, SpanKind.SERVER)
self.assertSpanHasAttributes(
span,
MOCK_LAMBDA_CONTEXT_ATTRIBUTES,
)
def test_sqs_event_sets_attributes(self):
AwsLambdaInstrumentor().instrument()
mock_execute_lambda(MOCK_LAMBDA_SQS_EVENT)
spans = self.memory_exporter.get_finished_spans()
# SQS produces two spans: inner CONSUMER first, outer SERVER second
self.assertEqual(len(spans), 2)
consumer_span, server_span, *_ = spans
self.assertEqual(consumer_span.kind, SpanKind.CONSUMER)
self.assertEqual(server_span.kind, SpanKind.SERVER)
self.assertSpanHasAttributes(
server_span,
{
**MOCK_LAMBDA_CONTEXT_ATTRIBUTES,
FAAS_TRIGGER: FaasTriggerValues.PUBSUB.value,
},
)
self.assertSpanHasAttributes(
consumer_span,
{
MESSAGING_SYSTEM: MessagingSystemValues.AWS_SQS.value,
MESSAGING_DESTINATION_NAME: "my-queue",
MESSAGING_OPERATION_TYPE: MessagingOperationTypeValues.PROCESS.value,
},
)
self.assertEqual(consumer_span.name, "process my-queue")
# Single record event should have no batch count attribute
self.assertNotIn(MESSAGING_BATCH_MESSAGE_COUNT, consumer_span.attributes)
# No span links when messageAttributes is empty
self.assertEqual(len(consumer_span.links), 0)
# CONSUMER span is a child of the SERVER span
self.assertEqual(
consumer_span.parent.span_id,
server_span.get_span_context().span_id,
)
def test_sqs_event_span_links(self):
AwsLambdaInstrumentor().instrument()
mock_execute_lambda(MOCK_LAMBDA_SQS_EVENT_WITH_TRACE_CONTEXT)
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 2)
consumer_span, _server_span, *_ = spans
self.assertEqual(consumer_span.kind, SpanKind.CONSUMER)
# Exactly one link corresponding to the producer's trace context
self.assertEqual(len(consumer_span.links), 1)
link = consumer_span.links[0]
self.assertEqual(
link.context.trace_id,
0x5CE0E9A56015FEC5AADFA328AE398115,
)
self.assertEqual(
link.context.span_id,
0xAB54A98CEB1F0AD2,
)
self.assertEqual(
link.attributes.get(MESSAGING_MESSAGE_ID),
"059f36b4-87a3-44ab-83d2-661975830a7d",
)
def test_sqs_batch_event_attributes(self):
AwsLambdaInstrumentor().instrument()
mock_execute_lambda(MOCK_LAMBDA_SQS_BATCH_EVENT)
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 2)
consumer_span, _server_span, *_ = spans
self.assertEqual(consumer_span.kind, SpanKind.CONSUMER)
self.assertEqual(consumer_span.attributes.get(MESSAGING_BATCH_MESSAGE_COUNT), 2)
self.assertEqual(len(consumer_span.links), 2)
def test_sqs_message_attributes_case_insensitive(self):
AwsLambdaInstrumentor().instrument()
mock_execute_lambda(MOCK_LAMBDA_SQS_EVENT_UPPERCASE_ATTRS)
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 2)
consumer_span, _server_span, *_ = spans
self.assertEqual(consumer_span.kind, SpanKind.CONSUMER)
# Uppercase TRACEPARENT key should still produce a span link
self.assertEqual(len(consumer_span.links), 1)
link = consumer_span.links[0]
self.assertEqual(
link.context.trace_id,
0x5CE0E9A56015FEC5AADFA328AE398115,
)
self.assertEqual(
link.context.span_id,
0xAB54A98CEB1F0AD2,
)
@mock.patch.dict("os.environ", {_HANDLER: "tests.mocks.lambda_function.handler_exc"})
def test_sqs_event_exception(self):
AwsLambdaInstrumentor().instrument()
with self.assertRaises(Exception):
mock_execute_lambda(MOCK_LAMBDA_SQS_EVENT)
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 2)
consumer_span, server_span, *_ = spans
self.assertEqual(consumer_span.status.status_code, StatusCode.ERROR)
self.assertEqual(server_span.status.status_code, StatusCode.ERROR)
# Both spans should have an exception event recorded
self.assertTrue(any(e.name == "exception" for e in consumer_span.events))
self.assertTrue(any(e.name == "exception" for e in server_span.events))
def test_sqs_event_null_message_attrs(self):
AwsLambdaInstrumentor().instrument()
mock_execute_lambda(MOCK_LAMBDA_SQS_EVENT_NULL_MESSAGE_ATTRS)
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 2)
consumer_span, _, *_ = spans
self.assertEqual(consumer_span.kind, SpanKind.CONSUMER)
self.assertEqual(len(consumer_span.links), 0)
def test_sqs_event_absent_message_attrs(self):
AwsLambdaInstrumentor().instrument()
mock_execute_lambda(MOCK_LAMBDA_SQS_EVENT_ABSENT_MESSAGE_ATTRS)
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 2)
consumer_span, _, *_ = spans
self.assertEqual(consumer_span.kind, SpanKind.CONSUMER)
self.assertEqual(len(consumer_span.links), 0)
def test_sqs_batch_event_partial_context(self):
AwsLambdaInstrumentor().instrument()
mock_execute_lambda(MOCK_LAMBDA_SQS_BATCH_EVENT_PARTIAL_CONTEXT)
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 2)
consumer_span, _, *_ = spans
self.assertEqual(consumer_span.kind, SpanKind.CONSUMER)
# Record 1 has no context records 2 and 3 do
self.assertEqual(len(consumer_span.links), 2)
trace_ids = {link.context.trace_id for link in consumer_span.links}
self.assertIn(0xAABBCCDDEEFF00112233445566778899, trace_ids)
self.assertIn(0xCAFEBABE12345678CAFEBABE12345678, trace_ids)
def test_malformed_sqs_event_empty_records(self):
AwsLambdaInstrumentor().instrument()
mock_execute_lambda(MOCK_MALFORMED_SQS_EVENT_EMPTY_RECORDS)
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
self.assertEqual(spans[0].kind, SpanKind.SERVER)
def test_malformed_sqs_event_records_not_list(self):
AwsLambdaInstrumentor().instrument()
mock_execute_lambda(MOCK_MALFORMED_SQS_EVENT_RECORDS_NOT_LIST)
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
self.assertEqual(spans[0].kind, SpanKind.SERVER)
def test_malformed_sqs_event_wrong_source(self):
AwsLambdaInstrumentor().instrument()
mock_execute_lambda(MOCK_MALFORMED_SQS_EVENT_WRONG_SOURCE)
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
self.assertEqual(spans[0].kind, SpanKind.SERVER)
def test_malformed_sqs_event_no_records_key(self):
AwsLambdaInstrumentor().instrument()
mock_execute_lambda(MOCK_MALFORMED_SQS_EVENT_NO_RECORDS_KEY)
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
self.assertEqual(spans[0].kind, SpanKind.SERVER)
def test_sqs_event_invalid_traceparent(self):
AwsLambdaInstrumentor().instrument()
mock_execute_lambda(MOCK_LAMBDA_SQS_EVENT_INVALID_TRACEPARENT)
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 2)
consumer_span, _, *_ = spans
self.assertEqual(consumer_span.kind, SpanKind.CONSUMER)
self.assertEqual(len(consumer_span.links), 0)
def test_sqs_event_attr_not_dict(self):
AwsLambdaInstrumentor().instrument()
mock_execute_lambda(MOCK_LAMBDA_SQS_EVENT_ATTR_NOT_DICT)
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 2)
consumer_span, _, *_ = spans
self.assertEqual(consumer_span.kind, SpanKind.CONSUMER)
self.assertEqual(len(consumer_span.links), 0)
def test_sqs_event_missing_string_value(self):
AwsLambdaInstrumentor().instrument()
mock_execute_lambda(MOCK_LAMBDA_SQS_EVENT_MISSING_STRING_VALUE)
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 2)
consumer_span, _, *_ = spans
self.assertEqual(consumer_span.kind, SpanKind.CONSUMER)
self.assertEqual(len(consumer_span.links), 0)
def test_sqs_event_missing_arn_span_name(self):
AwsLambdaInstrumentor().instrument()
mock_execute_lambda(MOCK_LAMBDA_SQS_EVENT_MISSING_ARN)
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 2)
consumer_span, _, *_ = spans
self.assertEqual(consumer_span.kind, SpanKind.CONSUMER)
self.assertEqual(consumer_span.name, "process")
def test_sqs_event_short_arn_span_name(self):
AwsLambdaInstrumentor().instrument()
mock_execute_lambda(MOCK_LAMBDA_SQS_EVENT_SHORT_ARN)
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 2)
consumer_span, _, *_ = spans
self.assertEqual(consumer_span.kind, SpanKind.CONSUMER)
self.assertEqual(consumer_span.name, "process bad-arn")
def test_slash_delimited_handler_path(self):
"""Test that slash-delimited handler paths work correctly.
AWS Lambda accepts both slash-delimited (python/functions/api.handler)
and dot-delimited (python.functions.api.handler) handler paths.
This test ensures the instrumentation handles both formats.
"""
# Test slash-delimited format
slash_env_patch = mock.patch.dict(
"os.environ",
{_HANDLER: "tests/mocks/lambda_function.handler"},
)
slash_env_patch.start()
AwsLambdaInstrumentor().instrument()
mock_execute_lambda()
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
self.assertSpanHasAttributes(
spans[0],
MOCK_LAMBDA_CONTEXT_ATTRIBUTES,
)
slash_env_patch.stop()
AwsLambdaInstrumentor().uninstrument()
self.memory_exporter.clear()
# Test dot-delimited format (should still work)
dot_env_patch = mock.patch.dict(
"os.environ",
{_HANDLER: "tests.mocks.lambda_function.handler"},
)
dot_env_patch.start()
AwsLambdaInstrumentor().instrument()
mock_execute_lambda()
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
self.assertSpanHasAttributes(
spans[0],
MOCK_LAMBDA_CONTEXT_ATTRIBUTES,
)
dot_env_patch.stop()
def test_lambda_handles_handler_exception_with_api_gateway_proxy_event(
self,
):
exc_env_patch = mock.patch.dict(
"os.environ",
{_HANDLER: "tests.mocks.lambda_function.handler_exc"},
)
exc_env_patch.start()
AwsLambdaInstrumentor().instrument()
# instrumentor re-raises the exception
with self.assertRaises(Exception):
mock_execute_lambda({"requestContext": {"http": {"method": "GET"}}})
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
span, *_ = spans
self.assertEqual(span.status.status_code, StatusCode.ERROR)
self.assertEqual(len(span.events), 1)
event, *_ = span.events
self.assertEqual(event.name, "exception")
exc_env_patch.stop()
opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-boto3sqs/ 0000775 0000000 0000000 00000000000 15270700723 0032720 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-boto3sqs/LICENSE 0000664 0000000 0000000 00000026135 15270700723 0033734 0 ustar 00root root 0000000 0000000 Apache License
Version 2.0, January 2004
http://www.apache.org/licenses/
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README.rst 0000664 0000000 0000000 00000001203 15270700723 0034324 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-boto3sqs OpenTelemetry Boto3 SQS Instrumentation
=======================================
|pypi|
.. |pypi| image:: https://badge.fury.io/py/opentelemetry-instrumentation-boto3sqs.svg
:target: https://pypi.org/project/opentelemetry-instrumentation-boto3sqs/
This library allows tracing requests made by the Boto3 library to the SQS service.
Installation
------------
::
pip install opentelemetry-instrumentation-boto3sqs
References
----------
* `OpenTelemetry boto3sqs/ Tracing `_
* `OpenTelemetry Project `_
pyproject.toml 0000664 0000000 0000000 00000003175 15270700723 0035563 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-boto3sqs [build-system]
requires = ["hatchling"]
build-backend = "hatchling.build"
[project]
name = "opentelemetry-instrumentation-boto3sqs"
dynamic = ["version"]
description = "Boto3 SQS service tracing for OpenTelemetry"
readme = "README.rst"
license = "Apache-2.0"
requires-python = ">=3.10"
authors = [
{ name = "OpenTelemetry Authors", email = "cncf-opentelemetry-contributors@lists.cncf.io" },
]
classifiers = [
"Development Status :: 4 - Beta",
"Intended Audience :: Developers",
"License :: OSI Approved :: Apache Software License",
"Programming Language :: Python",
"Programming Language :: Python :: 3",
"Programming Language :: Python :: 3.10",
"Programming Language :: Python :: 3.11",
"Programming Language :: Python :: 3.12",
"Programming Language :: Python :: 3.13",
"Programming Language :: Python :: 3.14",
]
dependencies = [
"opentelemetry-api ~= 1.12",
"opentelemetry-instrumentation == 0.66b2",
"opentelemetry-semantic-conventions == 0.66b2",
"wrapt >= 1.0.0, < 3.0.0",
]
[project.optional-dependencies]
instruments = [
"boto3 ~= 1.0",
]
[project.entry-points.opentelemetry_instrumentor]
boto3 = "opentelemetry.instrumentation.boto3sqs:Boto3SQSInstrumentor"
[project.urls]
Homepage = "https://github.com/open-telemetry/opentelemetry-python-contrib/tree/main/instrumentation/opentelemetry-instrumentation-boto3sqs"
Repository = "https://github.com/open-telemetry/opentelemetry-python-contrib"
[tool.hatch.version]
path = "src/opentelemetry/instrumentation/boto3sqs/version.py"
[tool.hatch.build.targets.sdist]
include = [
"/src",
"/tests",
]
[tool.hatch.build.targets.wheel]
packages = ["src/opentelemetry"]
opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-boto3sqs/src/ 0000775 0000000 0000000 00000000000 15270700723 0033507 5 ustar 00root root 0000000 0000000 opentelemetry/ 0000775 0000000 0000000 00000000000 15270700723 0036324 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-boto3sqs/src instrumentation/ 0000775 0000000 0000000 00000000000 15270700723 0041567 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-boto3sqs/src/opentelemetry boto3sqs/ 0000775 0000000 0000000 00000000000 15270700723 0043344 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-boto3sqs/src/opentelemetry/instrumentation __init__.py 0000664 0000000 0000000 00000036506 15270700723 0045467 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-boto3sqs/src/opentelemetry/instrumentation/boto3sqs # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
"""
Instrument `boto3sqs`_ to trace SQS applications.
.. _boto3sqs: https://boto3.amazonaws.com/v1/documentation/api/latest/reference/services/sqs.html
Usage
-----
.. code-block:: python
import boto3
from opentelemetry.instrumentation.boto3sqs import Boto3SQSInstrumentor
Boto3SQSInstrumentor().instrument()
---
"""
import logging
from collections.abc import Collection, Generator, Mapping
from typing import Any
import boto3.session
import botocore.client
from wrapt import wrap_function_wrapper
from opentelemetry import context, propagate, trace
from opentelemetry.instrumentation.instrumentor import BaseInstrumentor
from opentelemetry.instrumentation.utils import (
is_instrumentation_enabled,
unwrap,
)
from opentelemetry.propagators.textmap import CarrierT, Getter, Setter
from opentelemetry.semconv._incubating.attributes import messaging_attributes
from opentelemetry.semconv.trace import (
MessagingDestinationKindValues,
MessagingOperationValues,
SpanAttributes,
)
from opentelemetry.trace import Link, Span, SpanKind, Tracer, TracerProvider
from .package import _instruments
from .version import __version__
_logger = logging.getLogger(__name__)
_IS_SQS_INSTRUMENTED_ATTRIBUTE = "_otel_boto3sqs_instrumented"
class Boto3SQSGetter(Getter[CarrierT]):
def get(self, carrier: CarrierT, key: str) -> list[str] | None:
msg_attr = carrier.get(key)
if not isinstance(msg_attr, Mapping):
return None
value = msg_attr.get("StringValue")
if value is None:
return None
return [value]
def keys(self, carrier: CarrierT) -> list[str]:
return list(carrier.keys())
class Boto3SQSSetter(Setter[CarrierT]):
def set(self, carrier: CarrierT, key: str, value: str) -> None:
# This is a limitation defined by AWS for SQS MessageAttributes size
if len(carrier.items()) < 10:
carrier[key] = {
"StringValue": value,
"DataType": "String",
}
else:
_logger.warning(
"Boto3 SQS instrumentation: cannot set context propagation on SQS/SNS message due to maximum amount of "
"MessageAttributes"
)
boto3sqs_getter = Boto3SQSGetter()
boto3sqs_setter = Boto3SQSSetter()
class Boto3SQSInstrumentor(BaseInstrumentor):
received_messages_spans: dict[str, Span] = {}
current_span_related_to_token: Span = None
current_context_token = None
class ContextableList(list):
"""
Since the classic way to process SQS messages is using a `for` loop, without a well defined scope like a
callback - we are doing something similar to the instrumentation of Kafka-python and instrumenting the
`__iter__` functions and the `__getitem__` functions to set the span context of the addressed message. Since
the return value from an `SQS.ReceiveMessage` returns a builtin list, we cannot wrap it and change all of the
calls for `list.__iter__` and `list.__getitem__` - therefore we use ContextableList. It is bound to the
received_messages_spans dict
"""
def __getitem__(self, key: int) -> Any:
retval = super().__getitem__(key)
if not isinstance(retval, dict):
return retval
receipt_handle = retval.get("ReceiptHandle")
if not receipt_handle:
return retval
started_span = Boto3SQSInstrumentor.received_messages_spans.get(receipt_handle)
if started_span is None:
return retval
if Boto3SQSInstrumentor.current_context_token:
context.detach(Boto3SQSInstrumentor.current_context_token)
Boto3SQSInstrumentor.current_context_token = context.attach(trace.set_span_in_context(started_span))
Boto3SQSInstrumentor.current_span_related_to_token = started_span
return retval
def __iter__(self) -> Generator:
index = 0
while index < len(self):
yield self[index]
index = index + 1
def instrumentation_dependencies(self) -> Collection[str]:
return _instruments
@staticmethod
def _enrich_span(
span: Span,
queue_name: str,
queue_url: str,
conversation_id: str | None = None,
operation: MessagingOperationValues | None = None,
message_id: str | None = None,
) -> None:
if not span.is_recording():
return
span.set_attribute(messaging_attributes.MESSAGING_SYSTEM, "aws.sqs")
span.set_attribute(SpanAttributes.MESSAGING_DESTINATION, queue_name)
span.set_attribute(
SpanAttributes.MESSAGING_DESTINATION_KIND,
MessagingDestinationKindValues.QUEUE.value,
)
span.set_attribute(SpanAttributes.MESSAGING_URL, queue_url)
if operation:
span.set_attribute(SpanAttributes.MESSAGING_OPERATION, operation.value)
if conversation_id:
span.set_attribute(SpanAttributes.MESSAGING_CONVERSATION_ID, conversation_id)
if message_id:
span.set_attribute(messaging_attributes.MESSAGING_MESSAGE_ID, message_id)
@staticmethod
def _safe_end_processing_span(receipt_handle: str) -> None:
started_span: Span = Boto3SQSInstrumentor.received_messages_spans.pop(receipt_handle, None)
if started_span:
if Boto3SQSInstrumentor.current_span_related_to_token == started_span:
if Boto3SQSInstrumentor.current_context_token:
context.detach(Boto3SQSInstrumentor.current_context_token)
Boto3SQSInstrumentor.current_context_token = None
started_span.end()
@staticmethod
def _extract_queue_name_from_url(queue_url: str) -> str:
# A Queue name cannot have the `/` char, therefore we can return the part after the last /
return queue_url.rsplit("/", maxsplit=1)[-1]
def _create_processing_span(
self,
queue_name: str,
queue_url: str,
receipt_handle: str,
message: dict[str, Any],
) -> None:
message_attributes = message.get("MessageAttributes", {})
links = []
ctx = propagate.extract(message_attributes, getter=boto3sqs_getter)
parent_span_ctx = trace.get_current_span(ctx).get_span_context()
if parent_span_ctx.is_valid:
links.append(Link(context=parent_span_ctx))
span = self._tracer.start_span(name=f"{queue_name} process", links=links, kind=SpanKind.CONSUMER)
with trace.use_span(span):
message_id = message.get("MessageId")
Boto3SQSInstrumentor.received_messages_spans[receipt_handle] = span
Boto3SQSInstrumentor._enrich_span(
span,
queue_name,
queue_url,
message_id=message_id,
operation=MessagingOperationValues.PROCESS,
)
def _wrap_send_message(self, sqs_class: type) -> None:
def send_wrapper(wrapped, instance, args, kwargs):
if not is_instrumentation_enabled():
return wrapped(*args, **kwargs)
queue_url = kwargs.get("QueueUrl")
# The method expect QueueUrl and Entries params, so if they are None, we call wrapped to receive the
# original exception
queue_name = Boto3SQSInstrumentor._extract_queue_name_from_url(queue_url)
with self._tracer.start_as_current_span(
name=f"{queue_name} send",
kind=SpanKind.PRODUCER,
end_on_exit=True,
) as span:
Boto3SQSInstrumentor._enrich_span(span, queue_name, queue_url)
attributes = kwargs.pop("MessageAttributes", {})
propagate.inject(attributes, setter=boto3sqs_setter)
retval = wrapped(*args, MessageAttributes=attributes, **kwargs)
message_id = retval.get("MessageId")
if message_id:
if span.is_recording():
span.set_attribute(
messaging_attributes.MESSAGING_MESSAGE_ID,
message_id,
)
return retval
wrap_function_wrapper(sqs_class, "send_message", send_wrapper)
def _wrap_send_message_batch(self, sqs_class: type) -> None:
def send_batch_wrapper(wrapped, instance, args, kwargs):
queue_url = kwargs.get("QueueUrl")
entries = kwargs.get("Entries")
# The method expect QueueUrl and Entries params, so if they are None, we call wrapped to receive the
# original exception
if not is_instrumentation_enabled() or not queue_url or not entries:
return wrapped(*args, **kwargs)
queue_name = Boto3SQSInstrumentor._extract_queue_name_from_url(queue_url)
ids_to_spans: dict[str, Span] = {}
for entry in entries:
entry_id = entry["Id"]
span = self._tracer.start_span(name=f"{queue_name} send", kind=SpanKind.PRODUCER)
ids_to_spans[entry_id] = span
Boto3SQSInstrumentor._enrich_span(span, queue_name, queue_url, conversation_id=entry_id)
with trace.use_span(span):
if "MessageAttributes" not in entry:
entry["MessageAttributes"] = {}
propagate.inject(entry["MessageAttributes"], setter=boto3sqs_setter)
retval = wrapped(*args, **kwargs)
for successful_messages in retval.get("Successful", []):
message_identifier = successful_messages["Id"]
message_span = ids_to_spans.get(message_identifier)
if message_span:
if message_span.is_recording():
message_span.set_attribute(
messaging_attributes.MESSAGING_MESSAGE_ID,
successful_messages.get("MessageId"),
)
for span in ids_to_spans.values():
span.end()
return retval
wrap_function_wrapper(sqs_class, "send_message_batch", send_batch_wrapper)
def _wrap_receive_message(self, sqs_class: type) -> None:
def receive_message_wrapper(wrapped, instance, args, kwargs):
queue_url = kwargs.get("QueueUrl")
message_attribute_names = kwargs.pop("MessageAttributeNames", [])
message_attribute_names.extend(propagate.get_global_textmap().fields)
queue_name = Boto3SQSInstrumentor._extract_queue_name_from_url(queue_url)
with self._tracer.start_as_current_span(
name=f"{queue_name} receive",
end_on_exit=True,
kind=SpanKind.CONSUMER,
) as span:
Boto3SQSInstrumentor._enrich_span(
span,
queue_name,
queue_url,
operation=MessagingOperationValues.RECEIVE,
)
retval = wrapped(
*args,
MessageAttributeNames=message_attribute_names,
**kwargs,
)
messages = retval.get("Messages", [])
if not messages:
return retval
for message in messages:
receipt_handle = message.get("ReceiptHandle")
if not receipt_handle:
continue
Boto3SQSInstrumentor._safe_end_processing_span(receipt_handle)
self._create_processing_span(queue_name, queue_url, receipt_handle, message)
retval["Messages"] = Boto3SQSInstrumentor.ContextableList(messages)
return retval
wrap_function_wrapper(sqs_class, "receive_message", receive_message_wrapper)
@staticmethod
def _wrap_delete_message(sqs_class: type) -> None:
def delete_message_wrapper(wrapped, instance, args, kwargs):
receipt_handle = kwargs.get("ReceiptHandle")
if receipt_handle:
Boto3SQSInstrumentor._safe_end_processing_span(receipt_handle)
return wrapped(*args, **kwargs)
wrap_function_wrapper(sqs_class, "delete_message", delete_message_wrapper)
@staticmethod
def _wrap_delete_message_batch(sqs_class: type) -> None:
def delete_message_wrapper_batch(wrapped, instance, args, kwargs):
entries = kwargs.get("Entries")
for entry in entries:
receipt_handle = entry.get("ReceiptHandle")
if receipt_handle:
Boto3SQSInstrumentor._safe_end_processing_span(receipt_handle)
return wrapped(*args, **kwargs)
wrap_function_wrapper(sqs_class, "delete_message_batch", delete_message_wrapper_batch)
def _wrap_client_creation(self) -> None:
"""
Since botocore creates classes on the fly using schemas, the SQS class is not necesraily created upon the call
of `instrument()`. Therefore we need to wrap the creation of the boto3 client, which triggers the creation of
the SQS client.
"""
def client_wrapper(wrapped, instance, args, kwargs):
retval = wrapped(*args, **kwargs)
self._decorate_sqs(type(retval))
return retval
wrap_function_wrapper(boto3.session.Session, "client", client_wrapper)
def _decorate_sqs(self, sqs_class: type) -> None:
"""
Since botocore creates classes on the fly using schemas, we try to find the class that inherits from the base
class and is SQS to wrap.
"""
# We define SQS client as the only client that implements send_message_batch
if not hasattr(sqs_class, "send_message_batch"):
return
if getattr(sqs_class, _IS_SQS_INSTRUMENTED_ATTRIBUTE, False):
return
setattr(sqs_class, _IS_SQS_INSTRUMENTED_ATTRIBUTE, True)
self._wrap_send_message(sqs_class)
self._wrap_send_message_batch(sqs_class)
self._wrap_receive_message(sqs_class)
self._wrap_delete_message(sqs_class)
self._wrap_delete_message_batch(sqs_class)
@staticmethod
def _un_decorate_sqs(sqs_class: type) -> None:
if not getattr(sqs_class, _IS_SQS_INSTRUMENTED_ATTRIBUTE, False):
return
unwrap(sqs_class, "send_message")
unwrap(sqs_class, "send_message_batch")
unwrap(sqs_class, "receive_message")
unwrap(sqs_class, "delete_message")
unwrap(sqs_class, "delete_message_batch")
setattr(sqs_class, _IS_SQS_INSTRUMENTED_ATTRIBUTE, False)
def _instrument(self, **kwargs: dict[str, Any]) -> None:
self._tracer_provider: TracerProvider | None = kwargs.get("tracer_provider")
self._tracer: Tracer = trace.get_tracer(
__name__,
__version__,
self._tracer_provider,
schema_url="https://opentelemetry.io/schemas/1.11.0",
)
self._wrap_client_creation()
for client_cls in botocore.client.BaseClient.__subclasses__():
self._decorate_sqs(client_cls)
def _uninstrument(self, **kwargs: dict[str, Any]) -> None:
unwrap(boto3.session.Session, "client")
for client_cls in botocore.client.BaseClient.__subclasses__():
self._un_decorate_sqs(client_cls)
package.py 0000664 0000000 0000000 00000000246 15270700723 0045313 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-boto3sqs/src/opentelemetry/instrumentation/boto3sqs # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
from collections.abc import Collection
_instruments: Collection[str] = ("boto3 ~= 1.0",)
version.py 0000664 0000000 0000000 00000000144 15270700723 0045402 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-boto3sqs/src/opentelemetry/instrumentation/boto3sqs # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
__version__ = "0.66b2"
test-requirements.txt 0000664 0000000 0000000 00000000606 15270700723 0037104 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-boto3sqs asgiref==3.8.1
boto3==1.34.44
botocore==1.34.44
Deprecated==1.2.14
iniconfig==2.0.0
jmespath==1.0.1
packaging==24.0
pluggy==1.6.0
py-cpuinfo==9.0.0
pytest==7.4.4
python-dateutil==2.8.2
s3transfer==0.10.0
six==1.16.0
tomli==2.0.1
typing_extensions==4.12.2
urllib3==1.26.19
wrapt==1.16.0
zipp==3.19.2
-e opentelemetry-instrumentation
-e instrumentation/opentelemetry-instrumentation-boto3sqs
opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-boto3sqs/tests/ 0000775 0000000 0000000 00000000000 15270700723 0034062 5 ustar 00root root 0000000 0000000 __init__.py 0000664 0000000 0000000 00000000000 15270700723 0036102 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-boto3sqs/tests test_boto3sqs_instrumentation.py 0000664 0000000 0000000 00000035601 15270700723 0042521 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-boto3sqs/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
# pylint: disable=no-name-in-module
from contextlib import contextmanager
from typing import Any
from unittest import TestCase, mock
import boto3
from botocore.awsrequest import AWSResponse
from wrapt import BoundFunctionWrapper
from opentelemetry.instrumentation.boto3sqs import (
Boto3SQSGetter,
Boto3SQSInstrumentor,
Boto3SQSSetter,
)
from opentelemetry.semconv._incubating.attributes import messaging_attributes
from opentelemetry.semconv.trace import (
MessagingDestinationKindValues,
MessagingOperationValues,
SpanAttributes,
)
from opentelemetry.test.test_base import TestBase
from opentelemetry.trace import SpanKind, TraceFlags
from opentelemetry.trace.span import Span, format_span_id, format_trace_id
def _make_sqs_client(*, session=False):
return (boto3.Session() if session else boto3).client(
"sqs",
region_name="us-east-1",
aws_access_key_id="dummy",
aws_secret_access_key="dummy",
)
def _make_sqs_resource(*, session=False):
return (boto3.Session() if session else boto3).resource(
"sqs",
region_name="us-east-1",
aws_access_key_id="dummy",
aws_secret_access_key="dummy",
)
class TestBoto3SQSInstrumentor(TestCase):
def _assert_instrumented(self, client):
self.assertIsInstance(client.send_message, BoundFunctionWrapper)
self.assertIsInstance(client.send_message_batch, BoundFunctionWrapper)
self.assertIsInstance(client.receive_message, BoundFunctionWrapper)
self.assertIsInstance(client.delete_message, BoundFunctionWrapper)
self.assertIsInstance(client.delete_message_batch, BoundFunctionWrapper)
def _assert_uninstrumented(self, client):
self.assertNotIsInstance(client.send_message, BoundFunctionWrapper)
self.assertNotIsInstance(client.send_message_batch, BoundFunctionWrapper)
self.assertNotIsInstance(client.receive_message, BoundFunctionWrapper)
self.assertNotIsInstance(client.delete_message, BoundFunctionWrapper)
self.assertNotIsInstance(client.delete_message_batch, BoundFunctionWrapper)
@staticmethod
@contextmanager
def _active_instrumentor():
Boto3SQSInstrumentor().instrument()
try:
yield
finally:
Boto3SQSInstrumentor().uninstrument()
def test_instrument_api_before_client_init(self) -> None:
for session in (False, True):
with self._active_instrumentor():
client = _make_sqs_client(session=session)
self._assert_instrumented(client)
self._assert_uninstrumented(client)
def test_instrument_api_after_client_init(self) -> None:
for session in (False, True):
client = _make_sqs_client(session=session)
with self._active_instrumentor():
self._assert_instrumented(client)
self._assert_uninstrumented(client)
def test_instrument_multiple_clients(self):
for session in (False, True):
with self._active_instrumentor():
self._assert_instrumented(_make_sqs_client(session=session))
self._assert_instrumented(_make_sqs_client(session=session))
def test_instrument_api_before_resource_init(self) -> None:
for session in (False, True):
with self._active_instrumentor():
sqs = _make_sqs_resource(session=session)
self._assert_instrumented(sqs.meta.client)
self._assert_uninstrumented(sqs.meta.client)
def test_instrument_api_after_resource_init(self) -> None:
for session in (False, True):
sqs = _make_sqs_resource(session=session)
with self._active_instrumentor():
self._assert_instrumented(sqs.meta.client)
self._assert_uninstrumented(sqs.meta.client)
def test_instrument_multiple_resources(self):
for session in (False, True):
with self._active_instrumentor():
self._assert_instrumented(_make_sqs_resource(session=session).meta.client)
self._assert_instrumented(_make_sqs_resource(session=session).meta.client)
class TestBoto3SQSGetter(TestCase):
def setUp(self) -> None:
self.getter = Boto3SQSGetter()
def test_get_none(self) -> None:
carrier = {}
value = self.getter.get(carrier, "test")
self.assertIsNone(value)
def test_get_value(self) -> None:
key = "test"
value = "value"
carrier = {key: {"StringValue": value, "DataType": "String"}}
val = self.getter.get(carrier, key)
self.assertEqual(val, [value])
def test_keys(self):
carrier = {
"test1": {"StringValue": "value1", "DataType": "String"},
"test2": {"StringValue": "value2", "DataType": "String"},
}
keys = self.getter.keys(carrier)
self.assertEqual(keys, list(carrier.keys()))
def test_keys_empty(self):
keys = self.getter.keys({})
self.assertEqual(keys, [])
class TestBoto3SQSSetter(TestCase):
def setUp(self) -> None:
self.setter = Boto3SQSSetter()
def test_simple(self):
original_key = "SomeHeader"
original_value = {"NumberValue": 1, "DataType": "Number"}
carrier = {original_key: original_value.copy()}
key = "test"
value = "value"
self.setter.set(carrier, key, value)
# Ensure the original value is not harmed
for dict_key, dict_val in carrier[original_key].items():
self.assertEqual(original_value[dict_key], dict_val)
# Ensure the new key is added well
self.assertEqual(carrier[key]["StringValue"], value)
class TestBoto3SQSInstrumentation(TestBase):
def setUp(self):
super().setUp()
self._reset_instrumentor()
Boto3SQSInstrumentor().instrument()
self._client = _make_sqs_client()
self._queue_name = "MyQueue"
self._queue_url = f"https://sqs.us-east-1.amazonaws.com/123456789012/{self._queue_name}"
def tearDown(self):
super().tearDown()
Boto3SQSInstrumentor().uninstrument()
self._reset_instrumentor()
@staticmethod
def _reset_instrumentor():
Boto3SQSInstrumentor.received_messages_spans.clear()
Boto3SQSInstrumentor.current_span_related_to_token = None
Boto3SQSInstrumentor.current_context_token = None
@staticmethod
def _make_aws_response_func(response):
def _response_func(*args, **kwargs):
return AWSResponse("http://127.0.0.1", 200, {}, "{}"), response
return _response_func
@contextmanager
def _mocked_endpoint(self, response):
response_func = self._make_aws_response_func(response)
with mock.patch("botocore.endpoint.Endpoint.make_request", new=response_func):
yield
def _assert_injected_span(self, msg_attrs: dict[str, Any], span: Span):
trace_parent = msg_attrs["traceparent"]["StringValue"]
ctx = span.get_span_context()
self.assertEqual(
self._to_trace_parent(ctx.trace_id, ctx.span_id, ctx.trace_flags),
trace_parent.lower(),
)
def _default_span_attrs(self):
return {
messaging_attributes.MESSAGING_SYSTEM: "aws.sqs",
SpanAttributes.MESSAGING_DESTINATION: self._queue_name,
SpanAttributes.MESSAGING_DESTINATION_KIND: MessagingDestinationKindValues.QUEUE.value,
SpanAttributes.MESSAGING_URL: self._queue_url,
}
@staticmethod
def _to_trace_parent(trace_id: int, span_id: int, trace_flags: TraceFlags) -> str:
return f"00-{format_trace_id(trace_id)}-{format_span_id(span_id)}-{trace_flags:02x}".lower()
def _get_only_span(self):
spans = self.get_finished_spans()
self.assertEqual(1, len(spans))
return spans[0]
@staticmethod
def _make_message(message_id: str, body: str, receipt: str):
return {
"MessageId": message_id,
"ReceiptHandle": receipt,
"MD5OfBody": "777",
"Body": body,
"Attributes": {},
"MD5OfMessageAttributes": "111",
"MessageAttributes": {},
}
def _add_trace_parent(self, message: dict[str, Any], trace_id: int, span_id: int):
message["MessageAttributes"]["traceparent"] = {
"StringValue": self._to_trace_parent(trace_id, span_id, TraceFlags.get_default()),
"DataType": "String",
}
def test_send_message(self):
message_id = "123456789"
mock_response = {
"MD5OfMessageBody": "1234",
"MD5OfMessageAttributes": "5678",
"MD5OfMessageSystemAttributes": "9012",
"MessageId": message_id,
"SequenceNumber": "0",
}
message_attrs = {}
with self._mocked_endpoint(mock_response):
self._client.send_message(
QueueUrl=self._queue_url,
MessageBody="hello msg",
MessageAttributes=message_attrs,
)
span = self._get_only_span()
self.assertEqual(f"{self._queue_name} send", span.name)
self.assertEqual(SpanKind.PRODUCER, span.kind)
self.assertEqual(
{
messaging_attributes.MESSAGING_MESSAGE_ID: message_id,
**self._default_span_attrs(),
},
span.attributes,
)
self._assert_injected_span(message_attrs, span)
def test_send_message_batch(self):
expected_message_ids = {"1": "msg-1", "2": "msg-2"}
mock_response = {
"Successful": [
{"Id": "1", "MessageId": "msg-1", "MD5OfMessageBody": "11"},
{"Id": "2", "MessageId": "msg-2", "MD5OfMessageBody": "22"},
],
"Failed": [],
}
entries = [
{"Id": "1", "MessageBody": "hello 1"},
{"Id": "2", "MessageBody": "hello 2"},
]
with self._mocked_endpoint(mock_response):
self._client.send_message_batch(QueueUrl=self._queue_url, Entries=entries)
spans = self.get_finished_spans()
self.assertEqual(2, len(spans))
spans_by_entry_id = {span.attributes[SpanAttributes.MESSAGING_CONVERSATION_ID]: span for span in spans}
for entry in entries:
entry_id = entry["Id"]
span = spans_by_entry_id[entry_id]
self.assertEqual(f"{self._queue_name} send", span.name)
self.assertEqual(SpanKind.PRODUCER, span.kind)
self.assertEqual(
{
SpanAttributes.MESSAGING_CONVERSATION_ID: entry_id,
messaging_attributes.MESSAGING_MESSAGE_ID: expected_message_ids[entry_id],
**self._default_span_attrs(),
},
span.attributes,
)
self._assert_injected_span(entry["MessageAttributes"], span)
def test_send_message_batch_all_failed(self):
mock_response = {
"Failed": [
{
"Id": "1",
"SenderFault": True,
"Code": "InvalidParameterValue",
"Message": "boom",
}
]
}
entries = [{"Id": "1", "MessageBody": "hello 1"}]
with self._mocked_endpoint(mock_response):
self._client.send_message_batch(QueueUrl=self._queue_url, Entries=entries)
span = self._get_only_span()
self.assertEqual(f"{self._queue_name} send", span.name)
self.assertEqual(SpanKind.PRODUCER, span.kind)
self.assertEqual(
{
SpanAttributes.MESSAGING_CONVERSATION_ID: "1",
**self._default_span_attrs(),
},
span.attributes,
)
self.assertNotIn(messaging_attributes.MESSAGING_MESSAGE_ID, span.attributes)
self._assert_injected_span(entries[0]["MessageAttributes"], span)
def test_receive_message(self):
msg_def = {
"1": {"receipt": "01", "trace_id": 10, "span_id": 1},
"2": {"receipt": "02", "trace_id": 20, "span_id": 2},
}
mock_response = {"Messages": []}
for msg_id, attrs in msg_def.items():
message = self._make_message(msg_id, f"hello {msg_id}", attrs["receipt"])
self._add_trace_parent(message, attrs["trace_id"], attrs["span_id"])
mock_response["Messages"].append(message)
message_attr_names = []
with self._mocked_endpoint(mock_response):
response = self._client.receive_message(
QueueUrl=self._queue_url,
MessageAttributeNames=message_attr_names,
)
self.assertIn("traceparent", message_attr_names)
# receive span
span = self._get_only_span()
self.assertEqual(f"{self._queue_name} receive", span.name)
self.assertEqual(SpanKind.CONSUMER, span.kind)
self.assertEqual(
{
SpanAttributes.MESSAGING_OPERATION: MessagingOperationValues.RECEIVE.value,
**self._default_span_attrs(),
},
span.attributes,
)
self.memory_exporter.clear()
# processing spans
self.assertEqual(2, len(response["Messages"]))
for msg in response["Messages"]:
msg_id = msg["MessageId"]
attrs = msg_def[msg_id]
with self._mocked_endpoint(None):
self._client.delete_message(QueueUrl=self._queue_url, ReceiptHandle=attrs["receipt"])
span = self._get_only_span()
self.assertEqual(f"{self._queue_name} process", span.name)
# processing span attributes
self.assertEqual(
{
messaging_attributes.MESSAGING_MESSAGE_ID: msg_id,
SpanAttributes.MESSAGING_OPERATION: MessagingOperationValues.PROCESS.value,
**self._default_span_attrs(),
},
span.attributes,
)
# processing span links
self.assertEqual(1, len(span.links))
link = span.links[0]
self.assertEqual(attrs["trace_id"], link.context.trace_id)
self.assertEqual(attrs["span_id"], link.context.span_id)
self.memory_exporter.clear()
def test_uninstrument(self):
mock_response = {
"MessageId": "123456789",
}
with self._mocked_endpoint(mock_response):
self._client.send_message(
QueueUrl=self._queue_url,
MessageBody="test",
)
spans = self.get_finished_spans()
self.assertEqual(1, len(spans))
self.memory_exporter.clear()
Boto3SQSInstrumentor().uninstrument()
self._client.send_message(
QueueUrl=self._queue_url,
MessageBody="test",
)
spans = self.get_finished_spans()
self.assertEqual(0, len(spans))
opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-botocore/ 0000775 0000000 0000000 00000000000 15270700723 0032757 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-botocore/LICENSE 0000664 0000000 0000000 00000026135 15270700723 0033773 0 ustar 00root root 0000000 0000000 Apache License
Version 2.0, January 2004
http://www.apache.org/licenses/
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README.rst 0000664 0000000 0000000 00000003351 15270700723 0034371 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-botocore OpenTelemetry Botocore Tracing
==============================
|pypi|
.. |pypi| image:: https://badge.fury.io/py/opentelemetry-instrumentation-botocore.svg
:target: https://pypi.org/project/opentelemetry-instrumentation-botocore/
This library allows tracing requests made by the botocore and aiobotocore libraries.
Extensions
----------
The instrumentation supports creating extensions for AWS services for enriching what is collected. We have extensions
for the following AWS services:
- Bedrock Runtime (botocore only)
- DynamoDB
- Lambda
- SNS
- SQS
Bedrock Runtime (botocore only)
*******************************
This extension implements the GenAI semantic conventions for the following API calls:
- Converse
- ConverseStream
- InvokeModel
- InvokeModelWithResponseStream
For the Converse and ConverseStream APIs tracing, events and metrics are implemented.
For the InvokeModel and InvokeModelWithResponseStream APIs tracing, events and metrics implemented only for a subset of
the available models, namely:
- Amazon Titan models
- Amazon Nova models
- Anthropic Claude
Tool calls with InvokeModel and InvokeModelWithResponseStream APIs are supported with:
- Amazon Nova models
- Anthropic Claude 3+
If you don't have an application using Bedrock APIs yet, try our `zero-code examples `_.
Installation
------------
::
pip install opentelemetry-instrumentation-botocore
References
----------
* `OpenTelemetry Botocore Tracing `_
* `OpenTelemetry Project `_
* `OpenTelemetry Python Examples `_
opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-botocore/examples/0000775 0000000 0000000 00000000000 15270700723 0034575 5 ustar 00root root 0000000 0000000 bedrock-runtime/ 0000775 0000000 0000000 00000000000 15270700723 0037610 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-botocore/examples zero-code/ 0000775 0000000 0000000 00000000000 15270700723 0041477 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-botocore/examples/bedrock-runtime .env 0000664 0000000 0000000 00000000714 15270700723 0042272 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-botocore/examples/bedrock-runtime/zero-code # Update this with your real values
AWS_ACCESS_KEY_ID=key
AWS_SECRET_ACCESS_KEY=secret
AWS_DEFAULT_REGION=eu-central-1
# Uncomment and set if your credentials are temporary
# AWS_SESSION_TOKEN=
# Uncomment and change to your OTLP endpoint
# OTEL_EXPORTER_OTLP_ENDPOINT=http://localhost:4317
# OTEL_EXPORTER_OTLP_PROTOCOL=grpc
OTEL_SERVICE_NAME=opentelemetry-python-bedrock
# Uncomment if your OTLP endpoint doesn't support logs
# OTEL_LOGS_EXPORTER=console
README.rst 0000664 0000000 0000000 00000004011 15270700723 0043162 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-botocore/examples/bedrock-runtime/zero-code Bedrock Zero-Code Instrumentation Example
=========================================
This is an example of how to instrument Bedrock calls with zero code changes,
using `opentelemetry-instrument`.
When examples are run, it exports traces and logs to an OTLP
compatible endpoint. Traces include details such as the model used and the
duration of the chat request. Logs capture the chat request and the generated
response, providing a comprehensive view of the performance and behavior of
your OpenAI requests.
Note: `.env <.env>`_ file configures additional environment variables:
- `OTEL_LOGS_EXPORTER=otlp` to specify exporter type.
Available examples
------------------
- `converse.py` uses `bedrock-runtime` `Converse API _`.
- `converse_stream.py` uses `bedrock-runtime` `ConverseStream API _`.
- `invoke_model.py` uses `bedrock-runtime` `InvokeModel API _`.
- `invoke_model_stream.py` uses `bedrock-runtime` `InvokeModelWithResponseStrea API _`.
Setup
-----
Minimally, update the `.env <.env>`_ file with your "AWS_SECRET_ACCESS_KEY",
"AWS_SECRET_ACCESS_KEY", "AWS_DEFAULT_REGION" and if you are using temporary
credentials "AWS_SESSION_TOKEN". An
OTLP compatible endpoint should be listening for traces and logs on
http://localhost:4317. If not, update "OTEL_EXPORTER_OTLP_ENDPOINT" as well.
Next, set up a virtual environment like this:
::
python3 -m venv .venv
source .venv/bin/activate
pip install "python-dotenv[cli]"
pip install -r requirements.txt
Run
---
Run the example like this:
::
dotenv run -- opentelemetry-instrument python converse.py
You should see a poem generated by Bedrock while traces exported to your
configured observability tool.
converse.py 0000664 0000000 0000000 00000001036 15270700723 0043675 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-botocore/examples/bedrock-runtime/zero-code # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
import os
import boto3
def main():
client = boto3.client("bedrock-runtime")
response = client.converse(
modelId=os.getenv("CHAT_MODEL", "amazon.titan-text-lite-v1"),
messages=[
{
"role": "user",
"content": [{"text": "Write a short poem on OpenTelemetry."}],
},
],
)
print(response["output"]["message"]["content"][0]["text"])
if __name__ == "__main__":
main()
converse_stream.py 0000664 0000000 0000000 00000001232 15270700723 0045246 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-botocore/examples/bedrock-runtime/zero-code # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
import os
import boto3
def main():
client = boto3.client("bedrock-runtime")
stream = client.converse_stream(
modelId=os.getenv("CHAT_MODEL", "amazon.titan-text-lite-v1"),
messages=[
{
"role": "user",
"content": [{"text": "Write a short poem on OpenTelemetry."}],
},
],
)
response = ""
for event in stream["stream"]:
if "contentBlockDelta" in event:
response += event["contentBlockDelta"]["delta"]["text"]
print(response)
if __name__ == "__main__":
main()
invoke_model.py 0000664 0000000 0000000 00000001204 15270700723 0044521 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-botocore/examples/bedrock-runtime/zero-code # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
import json
import os
import boto3
def main():
client = boto3.client("bedrock-runtime")
response = client.invoke_model(
modelId=os.getenv("CHAT_MODEL", "amazon.titan-text-lite-v1"),
body=json.dumps(
{
"inputText": "Write a short poem on OpenTelemetry.",
"textGenerationConfig": {},
},
),
)
body = response["body"].read()
response_data = json.loads(body.decode("utf-8"))
print(response_data["results"][0]["outputText"])
if __name__ == "__main__":
main()
invoke_model_stream.py 0000664 0000000 0000000 00000003001 15270700723 0046071 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-botocore/examples/bedrock-runtime/zero-code # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
import json
import os
import boto3
def main():
chat_model = os.getenv("CHAT_MODEL", "amazon.titan-text-lite-v1")
prompt = "Write a short poem on OpenTelemetry."
if "amazon.titan" in chat_model:
body = {
"inputText": prompt,
"textGenerationConfig": {},
}
elif "amazon.nova" in chat_model:
body = {
"messages": [{"role": "user", "content": [{"text": prompt}]}],
"schemaVersion": "messages-v1",
}
elif "anthropic.claude" in chat_model:
body = {
"messages": [{"role": "user", "content": [{"text": prompt, "type": "text"}]}],
"anthropic_version": "bedrock-2023-05-31",
"max_tokens": 200,
}
else:
raise ValueError()
client = boto3.client("bedrock-runtime")
response = client.invoke_model_with_response_stream(
modelId=chat_model,
body=json.dumps(body),
)
answer = ""
for event in response["body"]:
json_bytes = event.get("chunk", {}).get("bytes", b"")
decoded = json_bytes.decode("utf-8")
chunk = json.loads(decoded)
if "outputText" in chunk:
answer += chunk["outputText"]
elif "completion" in chunk:
answer += chunk["completion"]
elif "contentBlockDelta" in chunk:
answer += chunk["contentBlockDelta"]["delta"]["text"]
print(answer)
if __name__ == "__main__":
main()
requirements.txt 0000664 0000000 0000000 00000000245 15270700723 0044764 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-botocore/examples/bedrock-runtime/zero-code boto3~=1.35.99
opentelemetry-sdk~=1.30.0
opentelemetry-exporter-otlp-proto-grpc~=1.30.0
opentelemetry-distro~=0.51b0
opentelemetry-instrumentation-botocore~=0.51b0
pyproject.toml 0000664 0000000 0000000 00000003456 15270700723 0035624 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-botocore [build-system]
requires = ["hatchling"]
build-backend = "hatchling.build"
[project]
name = "opentelemetry-instrumentation-botocore"
dynamic = ["version"]
description = "OpenTelemetry Botocore instrumentation"
readme = "README.rst"
license = "Apache-2.0"
requires-python = ">=3.10"
authors = [
{ name = "OpenTelemetry Authors", email = "cncf-opentelemetry-contributors@lists.cncf.io" },
]
classifiers = [
"Development Status :: 4 - Beta",
"Intended Audience :: Developers",
"License :: OSI Approved :: Apache Software License",
"Programming Language :: Python",
"Programming Language :: Python :: 3",
"Programming Language :: Python :: 3.10",
"Programming Language :: Python :: 3.11",
"Programming Language :: Python :: 3.12",
"Programming Language :: Python :: 3.13",
"Programming Language :: Python :: 3.14",
]
dependencies = [
"opentelemetry-api ~= 1.37",
"opentelemetry-instrumentation == 0.66b2",
"opentelemetry-semantic-conventions == 0.66b2",
"opentelemetry-propagator-aws-xray ~= 1.0",
"wrapt >= 1.0.0, < 3.0.0",
]
[project.optional-dependencies]
instruments = []
instruments-any = [
"botocore ~= 1.0",
"aiobotocore >= 2.0, < 4.0"
]
[project.entry-points.opentelemetry_instrumentor]
botocore = "opentelemetry.instrumentation.botocore:BotocoreInstrumentor"
aiobotocore = "opentelemetry.instrumentation.botocore:AiobotocoreInstrumentor"
[project.urls]
Homepage = "https://github.com/open-telemetry/opentelemetry-python-contrib/tree/main/instrumentation/opentelemetry-instrumentation-botocore"
Repository = "https://github.com/open-telemetry/opentelemetry-python-contrib"
[tool.hatch.version]
path = "src/opentelemetry/instrumentation/botocore/version.py"
[tool.hatch.build.targets.sdist]
include = [
"/src",
"/tests",
]
[tool.hatch.build.targets.wheel]
packages = ["src/opentelemetry"]
opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-botocore/src/ 0000775 0000000 0000000 00000000000 15270700723 0033546 5 ustar 00root root 0000000 0000000 opentelemetry/ 0000775 0000000 0000000 00000000000 15270700723 0036363 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-botocore/src instrumentation/ 0000775 0000000 0000000 00000000000 15270700723 0041626 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-botocore/src/opentelemetry botocore/ 0000775 0000000 0000000 00000000000 15270700723 0043442 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-botocore/src/opentelemetry/instrumentation __init__.py 0000664 0000000 0000000 00000046206 15270700723 0045563 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-botocore/src/opentelemetry/instrumentation/botocore # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
"""
Instrument `botocore`_ and `aiobotocore`_ to trace service requests.
There are two options for instrumenting code. The first option is to use the
``opentelemetry-instrument`` executable which will automatically
instrument your botocore or aiobotocore client. The second is to programmatically enable
instrumentation via the following code:
.. _botocore: https://pypi.org/project/botocore/
.. _aiobotocore: https://pypi.org/project/aiobotocore/
Usage
-----
.. code:: python
from opentelemetry.instrumentation.botocore import BotocoreInstrumentor
import botocore.session
# Instrument botocore
BotocoreInstrumentor().instrument()
# This will create a span with botocore-specific attributes
session = botocore.session.get_session()
session.set_credentials(
access_key="access-key", secret_key="secret-key"
)
ec2 = session.create_client("ec2", region_name="us-west-2")
ec2.describe_instances()
Async Usage
-----------
.. code:: python
from opentelemetry.instrumentation.botocore import AiobotocoreInstrumentor
import aiobotocore.session
import asyncio
async def main():
# Instrument Aiobotocore
AiobotocoreInstrumentor().instrument()
# This will create a span with aiobotocore-specific attributes
session = aiobotocore.session.get_session()
async with session.create_client("ec2") as client:
await client.describe_instances()
asyncio.run(main())
Thread Context Propagation
--------------------------
boto3's S3 ``upload_file`` and ``download_file`` methods use background threads
for multipart transfers. To ensure trace context is propagated to these threads,
also enable the threading instrumentation:
.. code:: python
from opentelemetry.instrumentation.threading import ThreadingInstrumentor
from opentelemetry.instrumentation.botocore import BotocoreInstrumentor
ThreadingInstrumentor().instrument()
BotocoreInstrumentor().instrument()
When using auto-instrumentation (``opentelemetry-instrument``), both instrumentors
are enabled automatically if their packages are installed.
API
---
The `instrument` method (for both ``BotocoreInstrumentor`` and ``AiobotocoreInstrumentor``) accepts the following keyword args:
* tracer_provider (``TracerProvider``) - an optional tracer provider
* request_hook (``Callable[[Span, str, str, dict], None]``) - a function with extra user-defined logic to be performed before performing the request
* response_hook (``Callable[[Span, str, str, dict], None]``) - a function with extra user-defined logic to be performed after performing the request
for example:
.. code:: python
from opentelemetry.instrumentation.botocore import BotocoreInstrumentor
import botocore.session
def request_hook(span, service_name, operation_name, api_params):
# request hook logic
pass
def response_hook(span, service_name, operation_name, result):
# response hook logic
pass
# Instrument botocore with hooks
BotocoreInstrumentor().instrument(request_hook=request_hook, response_hook=response_hook)
# This will create a span with botocore-specific attributes, including custom attributes added from the hooks
session = botocore.session.get_session()
session.set_credentials(
access_key="access-key", secret_key="secret-key"
)
ec2 = session.create_client("ec2", region_name="us-west-2")
ec2.describe_instances()
"""
import logging
from collections.abc import Collection
from typing import Any
from botocore.client import BaseClient
from botocore.endpoint import Endpoint
from botocore.exceptions import ClientError
from wrapt import wrap_function_wrapper
from opentelemetry.instrumentation.botocore.extensions import (
_AIOBOTOCORE_EXTENSIONS,
_BOTOCORE_EXTENSIONS,
)
from opentelemetry.instrumentation.botocore.extensions.registry import (
ExtensionRegistry,
)
from opentelemetry.instrumentation.botocore.extensions.types import (
_AwsSdkCallContext,
_BotocoreInstrumentorContext,
)
from opentelemetry.instrumentation.botocore.package import (
_instruments_aiobotocore,
_instruments_botocore,
)
from opentelemetry.instrumentation.botocore.utils import (
_safe_invoke,
get_server_attributes,
)
from opentelemetry.instrumentation.instrumentor import BaseInstrumentor
from opentelemetry.instrumentation.utils import (
http_status_to_status_code,
is_instrumentation_enabled,
suppress_http_instrumentation,
unwrap,
)
from opentelemetry.metrics import Instrument
from opentelemetry.propagators.aws.aws_xray_propagator import (
TRACE_HEADER_KEY,
AwsXRayPropagator,
)
from opentelemetry.semconv._incubating.attributes.cloud_attributes import (
CLOUD_REGION,
)
from opentelemetry.semconv._incubating.attributes.http_attributes import (
HTTP_STATUS_CODE,
)
from opentelemetry.semconv._incubating.attributes.rpc_attributes import (
RPC_METHOD,
RPC_SERVICE,
RPC_SYSTEM,
)
from opentelemetry.trace.span import Span
from opentelemetry.trace.status import StatusCode
logger = logging.getLogger(__name__)
class BotocoreInstrumentor(BaseInstrumentor):
"""An instrumentor for Botocore.
See `BaseInstrumentor`
"""
def __init__(self):
super().__init__()
if not hasattr(self, "request_hook"):
self.request_hook = None
if not hasattr(self, "response_hook"):
self.response_hook = None
if not hasattr(self, "extension_registry"):
self.extension_registry = None
if not hasattr(self, "propagator"):
self.propagator = AwsXRayPropagator()
def instrumentation_dependencies(self) -> Collection[str]:
return _instruments_botocore
def _instrument(self, **kwargs):
# tracers are lazy initialized per-extension in _get_tracer
self._tracers = {}
# loggers are lazy initialized per-extension in _get_logger
self._loggers = {}
# meters are lazy initialized per-extension in _get_meter
self._meters = {}
# metrics are lazy initialized per-extension in _get_metrics
self._metrics: dict[str, dict[str, Instrument]] = {}
self.request_hook = kwargs.get("request_hook")
self.response_hook = kwargs.get("response_hook")
propagator = kwargs.get("propagator")
if propagator is not None:
self.propagator = propagator
self.extension_registry = ExtensionRegistry(
__name__,
_BOTOCORE_EXTENSIONS,
kwargs.get("tracer_provider"),
kwargs.get("logger_provider"),
kwargs.get("meter_provider"),
)
wrap_function_wrapper(
"botocore.client",
"BaseClient._make_api_call",
self._patched_api_call,
)
wrap_function_wrapper(
"botocore.endpoint",
"Endpoint.prepare_request",
self._patched_endpoint_prepare_request,
)
def _uninstrument(self, **kwargs):
unwrap(BaseClient, "_make_api_call")
unwrap(Endpoint, "prepare_request")
# pylint: disable=unused-argument
def _patched_endpoint_prepare_request(self, wrapped, instance, args, kwargs):
request = args[0]
headers = request.headers
# There may be situations where both Botocore and Aiobotocore are
# instrumented at the same time. To avoid double-injection of headers,
# we add a check to see if the header is already present. If it is,
# we skip injection.
if TRACE_HEADER_KEY in headers:
return wrapped(*args, **kwargs)
# Only the x-ray header is propagated by AWS services. Using any
# other propagator will lose the trace context.
self.propagator.inject(headers)
return wrapped(*args, **kwargs)
# pylint: disable=too-many-branches
def _patched_api_call(self, original_func, instance, args, kwargs):
if not is_instrumentation_enabled():
return original_func(*args, **kwargs)
call_context = _determine_call_context(instance, args)
if call_context is None:
return original_func(*args, **kwargs)
extension = self.extension_registry.get_extension(call_context)
if not extension.should_trace_service_call():
return original_func(*args, **kwargs)
attributes = {
RPC_SYSTEM: "aws-api",
RPC_SERVICE: call_context.service_id,
RPC_METHOD: call_context.operation,
CLOUD_REGION: call_context.region,
**get_server_attributes(call_context.endpoint_url),
}
_safe_invoke(extension.extract_attributes, attributes)
end_span_on_exit = extension.should_end_span_on_exit()
tracer = self.extension_registry.get_tracer(extension)
metrics = self.extension_registry.get_metrics(extension)
instrumentor_ctx = _BotocoreInstrumentorContext(
logger=self.extension_registry.get_logger(extension),
metrics=metrics,
)
with tracer.start_as_current_span(
call_context.span_name,
kind=call_context.span_kind,
attributes=attributes,
# tracing streaming services require to close the span manually
# at a later time after the stream has been consumed
end_on_exit=end_span_on_exit,
set_status_on_exception=False,
) as span:
_safe_invoke(extension.before_service_call, span, instrumentor_ctx)
self._call_request_hook(span, call_context)
try:
with suppress_http_instrumentation():
result = None
try:
result = original_func(*args, **kwargs)
except ClientError as error:
result = getattr(error, "response", None)
_apply_response_attributes(span, result)
http_status = (result or {}).get("ResponseMetadata", {}).get("HTTPStatusCode", 0)
if http_status_to_status_code(http_status) is StatusCode.ERROR:
span.set_status(StatusCode.ERROR, str(error))
_safe_invoke(extension.on_error, span, error, instrumentor_ctx)
else:
_safe_invoke(extension.on_success, span, result, instrumentor_ctx)
raise
except Exception as error:
span.set_status(StatusCode.ERROR, str(error))
raise
_apply_response_attributes(span, result)
_safe_invoke(extension.on_success, span, result, instrumentor_ctx)
finally:
_safe_invoke(extension.after_service_call, instrumentor_ctx)
self._call_response_hook(span, call_context, result)
return result
def _call_request_hook(self, span: Span, call_context: _AwsSdkCallContext):
if not callable(self.request_hook):
return
self.request_hook(
span,
call_context.service,
call_context.operation,
call_context.params,
)
def _call_response_hook(self, span: Span, call_context: _AwsSdkCallContext, result):
if not callable(self.response_hook):
return
self.response_hook(span, call_context.service, call_context.operation, result)
class AiobotocoreInstrumentor(BaseInstrumentor):
"""An instrumentor for Aiobotocore.
See `BaseInstrumentor`
"""
def __init__(self):
super().__init__()
if not hasattr(self, "request_hook"):
self.request_hook = None
if not hasattr(self, "response_hook"):
self.response_hook = None
if not hasattr(self, "extension_registry"):
self.extension_registry = None
if not hasattr(self, "propagator"):
self.propagator = AwsXRayPropagator()
def instrumentation_dependencies(self) -> Collection[str]:
return _instruments_aiobotocore
def _instrument(self, **kwargs):
# Verify that aiobotocore is present
# pylint: disable-next=import-outside-toplevel, unused-import
import aiobotocore.client # noqa: PLC0415, F401
# pylint: disable=attribute-defined-outside-init
self.request_hook = kwargs.get("request_hook")
self.response_hook = kwargs.get("response_hook")
propagator = kwargs.get("propagator")
if propagator is not None:
self.propagator = propagator
self.extension_registry = ExtensionRegistry(
__name__,
_AIOBOTOCORE_EXTENSIONS,
kwargs.get("tracer_provider"),
kwargs.get("logger_provider"),
kwargs.get("meter_provider"),
)
wrap_function_wrapper(
"aiobotocore.client",
"AioBaseClient._make_api_call",
self._patched_api_call,
)
wrap_function_wrapper(
"botocore.endpoint",
"Endpoint.prepare_request",
self._patched_endpoint_prepare_request,
)
def _uninstrument(self, **kwargs):
unwrap("aiobotocore.client.AioBaseClient", "_make_api_call")
unwrap(Endpoint, "prepare_request")
# pylint: disable=unused-argument
def _patched_endpoint_prepare_request(self, wrapped, instance, args, kwargs):
request = args[0]
headers = request.headers
# There may be situations where both Botocore and Aiobotocore are
# instrumented at the same time. To avoid double-injection of headers,
# we add a check to see if the header is already present. If it is,
# we skip injection.
if TRACE_HEADER_KEY in headers:
return wrapped(*args, **kwargs)
# Only the x-ray header is propagated by AWS services. Using any
# other propagator will lose the trace context.
self.propagator.inject(headers)
return wrapped(*args, **kwargs)
# pylint: disable=too-many-branches
async def _patched_api_call(self, original_func, instance, args, kwargs):
if not is_instrumentation_enabled():
return await original_func(*args, **kwargs)
call_context = _determine_call_context(instance, args)
if call_context is None:
return await original_func(*args, **kwargs)
extension = self.extension_registry.get_extension(call_context)
if not extension.should_trace_service_call():
return await original_func(*args, **kwargs)
attributes = {
RPC_SYSTEM: "aws-api",
RPC_SERVICE: call_context.service_id,
RPC_METHOD: call_context.operation,
CLOUD_REGION: call_context.region,
**get_server_attributes(call_context.endpoint_url),
}
_safe_invoke(extension.extract_attributes, attributes)
end_span_on_exit = extension.should_end_span_on_exit()
tracer = self.extension_registry.get_tracer(extension)
metrics = self.extension_registry.get_metrics(extension)
instrumentor_ctx = _BotocoreInstrumentorContext(
logger=self.extension_registry.get_logger(extension),
metrics=metrics,
)
with tracer.start_as_current_span(
call_context.span_name,
kind=call_context.span_kind,
attributes=attributes,
# tracing streaming services require to close the span manually
# at a later time after the stream has been consumed
end_on_exit=end_span_on_exit,
set_status_on_exception=False,
) as span:
_safe_invoke(extension.before_service_call, span, instrumentor_ctx)
self._call_request_hook(span, call_context)
try:
with suppress_http_instrumentation():
result = None
try:
result = await original_func(*args, **kwargs)
except ClientError as error:
result = getattr(error, "response", None)
_apply_response_attributes(span, result)
http_status = (result or {}).get("ResponseMetadata", {}).get("HTTPStatusCode", 0)
if http_status_to_status_code(http_status) is StatusCode.ERROR:
span.set_status(StatusCode.ERROR, str(error))
_safe_invoke(extension.on_error, span, error, instrumentor_ctx)
else:
_safe_invoke(extension.on_success, span, result, instrumentor_ctx)
raise
except Exception as error:
span.set_status(StatusCode.ERROR, str(error))
raise
_apply_response_attributes(span, result)
_safe_invoke(extension.on_success, span, result, instrumentor_ctx)
finally:
_safe_invoke(extension.after_service_call, instrumentor_ctx)
self._call_response_hook(span, call_context, result)
return result
def _call_request_hook(self, span: Span, call_context: _AwsSdkCallContext):
if not callable(self.request_hook):
return
self.request_hook(
span,
call_context.service,
call_context.operation,
call_context.params,
)
def _call_response_hook(self, span: Span, call_context: _AwsSdkCallContext, result):
if not callable(self.response_hook):
return
self.response_hook(span, call_context.service, call_context.operation, result)
def _apply_response_attributes(span: Span, result):
if result is None or not span.is_recording():
return
metadata = result.get("ResponseMetadata")
if metadata is None:
return
request_id = metadata.get("RequestId")
if request_id is None:
headers = metadata.get("HTTPHeaders")
if headers is not None:
request_id = headers.get("x-amzn-RequestId") or headers.get("x-amz-request-id") or headers.get("x-amz-id-2")
if request_id:
# TODO: update when semantic conventions exist
span.set_attribute("aws.request_id", request_id)
retry_attempts = metadata.get("RetryAttempts")
if retry_attempts is not None:
# TODO: update when semantic conventions exists
span.set_attribute("retry_attempts", retry_attempts)
status_code = metadata.get("HTTPStatusCode")
if status_code is not None:
span.set_attribute(HTTP_STATUS_CODE, status_code)
def _determine_call_context(client: BaseClient, args: tuple[str, dict[str, Any]]) -> _AwsSdkCallContext | None:
try:
call_context = _AwsSdkCallContext(client, args)
logger.debug(
"AWS SDK invocation: %s %s",
call_context.service,
call_context.operation,
)
return call_context
except Exception as ex: # pylint:disable=broad-except
# this shouldn't happen actually unless internals of botocore changed and
# extracting essential attributes ('service' and 'operation') failed.
logger.error("Error when initializing call context", exc_info=ex)
return None
environment_variables.py 0000664 0000000 0000000 00000000267 15270700723 0050415 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-botocore/src/opentelemetry/instrumentation/botocore # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
OTEL_INSTRUMENTATION_GENAI_CAPTURE_MESSAGE_CONTENT = "OTEL_INSTRUMENTATION_GENAI_CAPTURE_MESSAGE_CONTENT"
extensions/ 0000775 0000000 0000000 00000000000 15270700723 0045641 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-botocore/src/opentelemetry/instrumentation/botocore __init__.py 0000664 0000000 0000000 00000002330 15270700723 0047750 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-botocore/src/opentelemetry/instrumentation/botocore/extensions # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
import importlib
import logging
_logger = logging.getLogger(__name__)
def _lazy_load(module, cls):
def loader():
imported_mod = importlib.import_module(module, __name__)
return getattr(imported_mod, cls, None)
return loader
_BOTOCORE_EXTENSIONS = {
"bedrock-runtime": _lazy_load(".bedrock", "_BedrockRuntimeExtension"),
"dynamodb": _lazy_load(".dynamodb", "_DynamoDbExtension"),
"lambda": _lazy_load(".lmbd", "_LambdaExtension"),
"secretsmanager": _lazy_load(".secretsmanager", "_SecretsManagerExtension"),
"stepfunctions": _lazy_load(".sfns", "_StepFunctionsExtension"),
"sns": _lazy_load(".sns", "_SnsExtension"),
"sqs": _lazy_load(".sqs", "_SqsExtension"),
}
_AIOBOTOCORE_EXTENSIONS = {
# TODO: Add Bedrock support for aiobotocore
"dynamodb": _lazy_load(".dynamodb", "_DynamoDbExtension"),
"lambda": _lazy_load(".lmbd", "_LambdaExtension"),
"secretsmanager": _lazy_load(".secretsmanager", "_SecretsManagerExtension"),
"stepfunctions": _lazy_load(".sfns", "_StepFunctionsExtension"),
"sns": _lazy_load(".sns", "_SnsExtension"),
"sqs": _lazy_load(".sqs", "_SqsExtension"),
}
_messaging.py 0000664 0000000 0000000 00000002203 15270700723 0050324 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-botocore/src/opentelemetry/instrumentation/botocore/extensions # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
import logging
from collections.abc import MutableMapping
from typing import Any
from opentelemetry.propagate import get_global_textmap, inject
from opentelemetry.propagators.textmap import CarrierT, Setter
_logger = logging.getLogger(__name__)
_MAX_MESSAGE_ATTRIBUTES = 10
class MessageAttributesSetter(Setter[CarrierT]):
def set(self, carrier: CarrierT, key: str, value: str):
carrier[key] = {
"DataType": "String",
"StringValue": value,
}
message_attributes_setter = MessageAttributesSetter()
def inject_propagation_context(
carrier: MutableMapping[str, Any],
) -> MutableMapping[str, Any]:
if carrier is None:
carrier = {}
fields = get_global_textmap().fields
if len(carrier.keys()) + len(fields) <= _MAX_MESSAGE_ATTRIBUTES:
inject(carrier, setter=message_attributes_setter)
else:
_logger.warning(
"botocore instrumentation: cannot set context propagation on "
"SQS/SNS message due to maximum amount of MessageAttributes"
)
return carrier
bedrock.py 0000664 0000000 0000000 00000104203 15270700723 0047624 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-botocore/src/opentelemetry/instrumentation/botocore/extensions # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
# Includes work from:
# Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved.
# SPDX-License-Identifier: Apache-2.0
# pylint: disable=too-many-lines
from __future__ import annotations
import io
import json
import logging
from timeit import default_timer
from typing import Any
from botocore.eventstream import EventStream
from botocore.response import StreamingBody
from opentelemetry.context import get_current
from opentelemetry.instrumentation.botocore.extensions.bedrock_utils import (
ConverseStreamWrapper,
InvokeModelWithResponseStreamWrapper,
_Choice,
estimate_token_count,
genai_capture_message_content,
message_to_event,
)
from opentelemetry.instrumentation.botocore.extensions.types import (
_AttributeMapT,
_AwsSdkExtension,
_BotoClientErrorT,
_BotocoreInstrumentorContext,
)
from opentelemetry.instrumentation.botocore.utils import get_server_attributes
from opentelemetry.metrics import Instrument, Meter
from opentelemetry.semconv._incubating.attributes.error_attributes import (
ERROR_TYPE,
)
from opentelemetry.semconv._incubating.attributes.gen_ai_attributes import (
GEN_AI_OPERATION_NAME,
GEN_AI_REQUEST_MAX_TOKENS,
GEN_AI_REQUEST_MODEL,
GEN_AI_REQUEST_STOP_SEQUENCES,
GEN_AI_REQUEST_TEMPERATURE,
GEN_AI_REQUEST_TOP_P,
GEN_AI_RESPONSE_FINISH_REASONS,
GEN_AI_SYSTEM,
GEN_AI_TOKEN_TYPE,
GEN_AI_USAGE_CACHE_CREATION_INPUT_TOKENS,
GEN_AI_USAGE_CACHE_READ_INPUT_TOKENS,
GEN_AI_USAGE_INPUT_TOKENS,
GEN_AI_USAGE_OUTPUT_TOKENS,
GenAiOperationNameValues,
GenAiSystemValues,
GenAiTokenTypeValues,
)
from opentelemetry.semconv._incubating.metrics.gen_ai_metrics import (
GEN_AI_CLIENT_OPERATION_DURATION,
GEN_AI_CLIENT_TOKEN_USAGE,
)
from opentelemetry.trace.propagation import set_span_in_context
from opentelemetry.trace.span import Span
from opentelemetry.trace.status import Status, StatusCode
_logger = logging.getLogger(__name__)
_GEN_AI_CLIENT_OPERATION_DURATION_BUCKETS = [
0.01,
0.02,
0.04,
0.08,
0.16,
0.32,
0.64,
1.28,
2.56,
5.12,
10.24,
20.48,
40.96,
81.92,
]
_GEN_AI_CLIENT_TOKEN_USAGE_BUCKETS = [
1,
4,
16,
64,
256,
1024,
4096,
16384,
65536,
262144,
1048576,
4194304,
16777216,
67108864,
]
_MODEL_ID_KEY: str = "modelId"
class _BedrockRuntimeExtension(_AwsSdkExtension):
"""
This class is an extension for
Amazon Bedrock Runtime.
"""
_HANDLED_OPERATIONS = {
"Converse",
"ConverseStream",
"InvokeModel",
"InvokeModelWithResponseStream",
}
_DONT_CLOSE_SPAN_ON_END_OPERATIONS = {
"ConverseStream",
"InvokeModelWithResponseStream",
}
def should_end_span_on_exit(self):
return self._call_context.operation not in self._DONT_CLOSE_SPAN_ON_END_OPERATIONS
def setup_metrics(self, meter: Meter, metrics: dict[str, Instrument]):
metrics[GEN_AI_CLIENT_OPERATION_DURATION] = meter.create_histogram(
name=GEN_AI_CLIENT_OPERATION_DURATION,
description="GenAI operation duration",
unit="s",
explicit_bucket_boundaries_advisory=_GEN_AI_CLIENT_OPERATION_DURATION_BUCKETS,
)
metrics[GEN_AI_CLIENT_TOKEN_USAGE] = meter.create_histogram(
name=GEN_AI_CLIENT_TOKEN_USAGE,
description="Measures number of input and output tokens used",
unit="{token}",
explicit_bucket_boundaries_advisory=_GEN_AI_CLIENT_TOKEN_USAGE_BUCKETS,
)
def _extract_metrics_attributes(self) -> _AttributeMapT:
attributes = {
GEN_AI_SYSTEM: GenAiSystemValues.AWS_BEDROCK.value,
**get_server_attributes(self._call_context.endpoint_url),
}
model_id = self._call_context.params.get(_MODEL_ID_KEY)
if not model_id:
return attributes
attributes[GEN_AI_REQUEST_MODEL] = model_id
# titan in invoke model is a text completion one
if "body" in self._call_context.params and "amazon.titan" in model_id:
attributes[GEN_AI_OPERATION_NAME] = GenAiOperationNameValues.TEXT_COMPLETION.value
else:
attributes[GEN_AI_OPERATION_NAME] = GenAiOperationNameValues.CHAT.value
return attributes
def extract_attributes(self, attributes: _AttributeMapT):
if self._call_context.operation not in self._HANDLED_OPERATIONS:
return
attributes[GEN_AI_SYSTEM] = GenAiSystemValues.AWS_BEDROCK.value
model_id = self._call_context.params.get(_MODEL_ID_KEY)
if model_id:
attributes[GEN_AI_REQUEST_MODEL] = model_id
attributes[GEN_AI_OPERATION_NAME] = GenAiOperationNameValues.CHAT.value
# Converse / ConverseStream
if inference_config := self._call_context.params.get("inferenceConfig"):
self._set_if_not_none(
attributes,
GEN_AI_REQUEST_TEMPERATURE,
inference_config.get("temperature"),
)
self._set_if_not_none(
attributes,
GEN_AI_REQUEST_TOP_P,
inference_config.get("topP"),
)
self._set_if_not_none(
attributes,
GEN_AI_REQUEST_MAX_TOKENS,
inference_config.get("maxTokens"),
)
self._set_if_not_none(
attributes,
GEN_AI_REQUEST_STOP_SEQUENCES,
inference_config.get("stopSequences"),
)
# InvokeModel
# Get the request body if it exists
body = self._call_context.params.get("body")
if body:
try:
request_body = json.loads(body)
if "amazon.titan" in model_id:
# titan interface is a text completion one
attributes[GEN_AI_OPERATION_NAME] = GenAiOperationNameValues.TEXT_COMPLETION.value
self._extract_titan_attributes(attributes, request_body)
elif "amazon.nova" in model_id:
self._extract_nova_attributes(attributes, request_body)
elif "anthropic.claude" in model_id:
self._extract_claude_attributes(attributes, request_body)
elif "cohere.command-r" in model_id:
self._extract_command_r_attributes(attributes, request_body)
elif "cohere.command" in model_id:
self._extract_command_attributes(attributes, request_body)
elif "meta.llama" in model_id:
self._extract_llama_attributes(attributes, request_body)
elif "mistral" in model_id:
self._extract_mistral_attributes(attributes, request_body)
except json.JSONDecodeError:
_logger.debug("Error: Unable to parse the body as JSON")
def _extract_titan_attributes(self, attributes, request_body):
config = request_body.get("textGenerationConfig", {})
self._set_if_not_none(attributes, GEN_AI_REQUEST_TEMPERATURE, config.get("temperature"))
self._set_if_not_none(attributes, GEN_AI_REQUEST_TOP_P, config.get("topP"))
self._set_if_not_none(attributes, GEN_AI_REQUEST_MAX_TOKENS, config.get("maxTokenCount"))
self._set_if_not_none(
attributes,
GEN_AI_REQUEST_STOP_SEQUENCES,
config.get("stopSequences"),
)
def _extract_nova_attributes(self, attributes, request_body):
config = request_body.get("inferenceConfig", {})
self._set_if_not_none(attributes, GEN_AI_REQUEST_TEMPERATURE, config.get("temperature"))
self._set_if_not_none(attributes, GEN_AI_REQUEST_TOP_P, config.get("topP"))
self._set_if_not_none(attributes, GEN_AI_REQUEST_MAX_TOKENS, config.get("max_new_tokens"))
self._set_if_not_none(
attributes,
GEN_AI_REQUEST_STOP_SEQUENCES,
config.get("stopSequences"),
)
def _extract_claude_attributes(self, attributes, request_body):
self._set_if_not_none(
attributes,
GEN_AI_REQUEST_MAX_TOKENS,
request_body.get("max_tokens"),
)
self._set_if_not_none(
attributes,
GEN_AI_REQUEST_TEMPERATURE,
request_body.get("temperature"),
)
self._set_if_not_none(attributes, GEN_AI_REQUEST_TOP_P, request_body.get("top_p"))
self._set_if_not_none(
attributes,
GEN_AI_REQUEST_STOP_SEQUENCES,
request_body.get("stop_sequences"),
)
def _extract_command_r_attributes(self, attributes, request_body):
prompt = request_body.get("message")
self._set_if_not_none(attributes, GEN_AI_USAGE_INPUT_TOKENS, estimate_token_count(prompt))
self._set_if_not_none(
attributes,
GEN_AI_REQUEST_MAX_TOKENS,
request_body.get("max_tokens"),
)
self._set_if_not_none(
attributes,
GEN_AI_REQUEST_TEMPERATURE,
request_body.get("temperature"),
)
self._set_if_not_none(attributes, GEN_AI_REQUEST_TOP_P, request_body.get("p"))
self._set_if_not_none(
attributes,
GEN_AI_REQUEST_STOP_SEQUENCES,
request_body.get("stop_sequences"),
)
def _extract_command_attributes(self, attributes, request_body):
prompt = request_body.get("prompt")
self._set_if_not_none(attributes, GEN_AI_USAGE_INPUT_TOKENS, estimate_token_count(prompt))
self._set_if_not_none(
attributes,
GEN_AI_REQUEST_MAX_TOKENS,
request_body.get("max_tokens"),
)
self._set_if_not_none(
attributes,
GEN_AI_REQUEST_TEMPERATURE,
request_body.get("temperature"),
)
self._set_if_not_none(attributes, GEN_AI_REQUEST_TOP_P, request_body.get("p"))
self._set_if_not_none(
attributes,
GEN_AI_REQUEST_STOP_SEQUENCES,
request_body.get("stop_sequences"),
)
def _extract_llama_attributes(self, attributes, request_body):
self._set_if_not_none(
attributes,
GEN_AI_REQUEST_MAX_TOKENS,
request_body.get("max_gen_len"),
)
self._set_if_not_none(
attributes,
GEN_AI_REQUEST_TEMPERATURE,
request_body.get("temperature"),
)
self._set_if_not_none(attributes, GEN_AI_REQUEST_TOP_P, request_body.get("top_p"))
# request for meta llama models does not contain stop_sequences field
def _extract_mistral_attributes(self, attributes, request_body):
prompt = request_body.get("prompt")
if prompt:
self._set_if_not_none(
attributes,
GEN_AI_USAGE_INPUT_TOKENS,
estimate_token_count(prompt),
)
self._set_if_not_none(
attributes,
GEN_AI_REQUEST_MAX_TOKENS,
request_body.get("max_tokens"),
)
self._set_if_not_none(
attributes,
GEN_AI_REQUEST_TEMPERATURE,
request_body.get("temperature"),
)
self._set_if_not_none(attributes, GEN_AI_REQUEST_TOP_P, request_body.get("top_p"))
self._set_if_not_none(attributes, GEN_AI_REQUEST_STOP_SEQUENCES, request_body.get("stop"))
@staticmethod
def _set_if_not_none(attributes, key, value):
if value is not None:
attributes[key] = value
def _get_request_messages(self):
"""Extracts and normalize system and user / assistant messages"""
if system := self._call_context.params.get("system", []):
system_messages = [{"role": "system", "content": system}]
else:
system_messages = []
if not (messages := self._call_context.params.get("messages", [])):
if body := self._call_context.params.get("body"):
decoded_body = json.loads(body)
if system := decoded_body.get("system"):
if isinstance(system, str):
content = [{"text": system}]
else:
content = system
system_messages = [{"role": "system", "content": content}]
messages = decoded_body.get("messages", [])
# if no messages interface, convert to messages format from generic API
if not messages:
model_id = self._call_context.params.get(_MODEL_ID_KEY)
if "amazon.titan" in model_id:
messages = self._get_messages_from_input_text(decoded_body, "inputText")
elif "cohere.command-r" in model_id:
# chat_history can be converted to messages; for now, just use message
messages = self._get_messages_from_input_text(decoded_body, "message")
elif "cohere.command" in model_id or "meta.llama" in model_id or "mistral.mistral" in model_id:
messages = self._get_messages_from_input_text(decoded_body, "prompt")
return system_messages + messages
# pylint: disable=no-self-use
def _get_messages_from_input_text(self, decoded_body: dict[str, Any], input_name: str):
if input_text := decoded_body.get(input_name):
return [{"role": "user", "content": [{"text": input_text}]}]
return []
def before_service_call(self, span: Span, instrumentor_context: _BotocoreInstrumentorContext):
if self._call_context.operation not in self._HANDLED_OPERATIONS:
return
capture_content = genai_capture_message_content()
messages = self._get_request_messages()
for message in messages:
logger = instrumentor_context.logger
for event in message_to_event(message, capture_content):
logger.emit(event)
if span.is_recording():
operation_name = span.attributes.get(GEN_AI_OPERATION_NAME, "")
request_model = span.attributes.get(GEN_AI_REQUEST_MODEL, "")
# avoid setting to an empty string if are not available
if operation_name and request_model:
span.update_name(f"{operation_name} {request_model}")
# this is used to calculate the operation duration metric, duration may be skewed by request_hook
self._operation_start = default_timer()
# pylint: disable=no-self-use,too-many-locals,too-many-branches
def _converse_on_success(
self,
span: Span,
result: dict[str, Any],
instrumentor_context: _BotocoreInstrumentorContext,
capture_content,
):
if span.is_recording():
if usage := result.get("usage"):
if input_tokens := usage.get("inputTokens"):
span.set_attribute(
GEN_AI_USAGE_INPUT_TOKENS,
input_tokens,
)
if output_tokens := usage.get("outputTokens"):
span.set_attribute(
GEN_AI_USAGE_OUTPUT_TOKENS,
output_tokens,
)
if cache_read := usage.get("cacheReadInputTokens"):
span.set_attribute(
GEN_AI_USAGE_CACHE_READ_INPUT_TOKENS,
cache_read,
)
if cache_write := usage.get("cacheWriteInputTokens"):
span.set_attribute(
GEN_AI_USAGE_CACHE_CREATION_INPUT_TOKENS,
cache_write,
)
if stop_reason := result.get("stopReason"):
span.set_attribute(
GEN_AI_RESPONSE_FINISH_REASONS,
[stop_reason],
)
# In case of an early stream closure, the result may not contain outputs
if self._stream_has_output_content(result):
logger = instrumentor_context.logger
choice = _Choice.from_converse(result, capture_content)
# this path is used by streaming apis, in that case we are already out of the span
# context so need to add the span context manually
context = set_span_in_context(span, get_current())
logger.emit(choice.to_choice_event(context=context))
metrics = instrumentor_context.metrics
metrics_attributes = self._extract_metrics_attributes()
if operation_duration_histogram := metrics.get(GEN_AI_CLIENT_OPERATION_DURATION):
duration = max((default_timer() - self._operation_start), 0)
operation_duration_histogram.record(
duration,
attributes=metrics_attributes,
)
if token_usage_histogram := metrics.get(GEN_AI_CLIENT_TOKEN_USAGE):
if usage := result.get("usage"):
if input_tokens := usage.get("inputTokens"):
input_attributes = {
**metrics_attributes,
GEN_AI_TOKEN_TYPE: GenAiTokenTypeValues.INPUT.value,
}
token_usage_histogram.record(input_tokens, input_attributes)
if output_tokens := usage.get("outputTokens"):
output_attributes = {
**metrics_attributes,
GEN_AI_TOKEN_TYPE: GenAiTokenTypeValues.COMPLETION.value,
}
token_usage_histogram.record(output_tokens, output_attributes)
def _invoke_model_on_success(
self,
span: Span,
result: dict[str, Any],
model_id: str,
instrumentor_context: _BotocoreInstrumentorContext,
capture_content,
):
original_body = None
try:
original_body = result["body"]
body_content = original_body.read()
# Replenish stream for downstream application use
new_stream = io.BytesIO(body_content)
result["body"] = StreamingBody(new_stream, len(body_content))
response_body = json.loads(body_content.decode("utf-8"))
if "amazon.titan" in model_id:
self._handle_amazon_titan_response(span, response_body, instrumentor_context, capture_content)
elif "amazon.nova" in model_id:
self._handle_amazon_nova_response(span, response_body, instrumentor_context, capture_content)
elif "anthropic.claude" in model_id:
self._handle_anthropic_claude_response(span, response_body, instrumentor_context, capture_content)
elif "cohere.command-r" in model_id:
self._handle_cohere_command_r_response(span, response_body, instrumentor_context, capture_content)
elif "cohere.command" in model_id:
self._handle_cohere_command_response(span, response_body, instrumentor_context, capture_content)
elif "meta.llama" in model_id:
self._handle_meta_llama_response(span, response_body, instrumentor_context, capture_content)
elif "mistral" in model_id:
self._handle_mistral_ai_response(span, response_body, instrumentor_context, capture_content)
except json.JSONDecodeError:
_logger.debug("Error: Unable to parse the response body as JSON")
except Exception as exc: # pylint: disable=broad-exception-caught
_logger.debug("Error processing response: %s", exc)
finally:
if original_body is not None:
original_body.close()
def _on_stream_error_callback(
self,
span: Span,
exception,
instrumentor_context: _BotocoreInstrumentorContext,
span_ended: bool,
):
span.set_status(Status(StatusCode.ERROR, str(exception)))
if span.is_recording():
span.set_attribute(ERROR_TYPE, type(exception).__qualname__)
if not span_ended:
span.end()
metrics = instrumentor_context.metrics
metrics_attributes = {
**self._extract_metrics_attributes(),
ERROR_TYPE: type(exception).__qualname__,
}
if operation_duration_histogram := metrics.get(GEN_AI_CLIENT_OPERATION_DURATION):
duration = max((default_timer() - self._operation_start), 0)
operation_duration_histogram.record(
duration,
attributes=metrics_attributes,
)
def on_success(
self,
span: Span,
result: dict[str, Any],
instrumentor_context: _BotocoreInstrumentorContext,
):
if self._call_context.operation not in self._HANDLED_OPERATIONS:
return
capture_content = genai_capture_message_content()
if self._call_context.operation == "ConverseStream":
if "stream" in result and isinstance(result["stream"], EventStream):
def stream_done_callback(response, span_ended):
self._converse_on_success(span, response, instrumentor_context, capture_content)
if not span_ended:
span.end()
def stream_error_callback(exception, span_ended):
self._on_stream_error_callback(span, exception, instrumentor_context, span_ended)
result["stream"] = ConverseStreamWrapper(
result["stream"],
stream_done_callback,
stream_error_callback,
)
return
elif self._call_context.operation == "Converse":
self._converse_on_success(span, result, instrumentor_context, capture_content)
model_id = self._call_context.params.get(_MODEL_ID_KEY)
if not model_id:
return
if self._call_context.operation == "InvokeModel":
if "body" in result and isinstance(result["body"], StreamingBody):
self._invoke_model_on_success(
span,
result,
model_id,
instrumentor_context,
capture_content,
)
return
elif self._call_context.operation == "InvokeModelWithResponseStream":
if "body" in result and isinstance(result["body"], EventStream):
def invoke_model_stream_done_callback(response, span_ended):
# the callback gets data formatted as the simpler converse API
self._converse_on_success(span, response, instrumentor_context, capture_content)
if not span_ended:
span.end()
def invoke_model_stream_error_callback(exception, span_ended):
self._on_stream_error_callback(span, exception, instrumentor_context, span_ended)
result["body"] = InvokeModelWithResponseStreamWrapper(
result["body"],
invoke_model_stream_done_callback,
invoke_model_stream_error_callback,
model_id,
)
return
# pylint: disable=no-self-use,too-many-locals
def _handle_amazon_titan_response(
self,
span: Span,
response_body: dict[str, Any],
instrumentor_context: _BotocoreInstrumentorContext,
capture_content: bool,
):
if "inputTextTokenCount" in response_body:
span.set_attribute(GEN_AI_USAGE_INPUT_TOKENS, response_body["inputTextTokenCount"])
if response_body.get("results"):
result = response_body["results"][0]
if "tokenCount" in result:
span.set_attribute(GEN_AI_USAGE_OUTPUT_TOKENS, result["tokenCount"])
if "completionReason" in result:
span.set_attribute(
GEN_AI_RESPONSE_FINISH_REASONS,
[result["completionReason"]],
)
logger = instrumentor_context.logger
choice = _Choice.from_invoke_amazon_titan(response_body, capture_content)
logger.emit(choice.to_choice_event())
metrics = instrumentor_context.metrics
metrics_attributes = self._extract_metrics_attributes()
if operation_duration_histogram := metrics.get(GEN_AI_CLIENT_OPERATION_DURATION):
duration = max((default_timer() - self._operation_start), 0)
operation_duration_histogram.record(
duration,
attributes=metrics_attributes,
)
if token_usage_histogram := metrics.get(GEN_AI_CLIENT_TOKEN_USAGE):
if input_tokens := response_body.get("inputTextTokenCount"):
input_attributes = {
**metrics_attributes,
GEN_AI_TOKEN_TYPE: GenAiTokenTypeValues.INPUT.value,
}
token_usage_histogram.record(input_tokens, input_attributes)
if results := response_body.get("results"):
if output_tokens := results[0].get("tokenCount"):
output_attributes = {
**metrics_attributes,
GEN_AI_TOKEN_TYPE: GenAiTokenTypeValues.COMPLETION.value,
}
token_usage_histogram.record(output_tokens, output_attributes)
# pylint: disable=no-self-use,too-many-locals
def _handle_amazon_nova_response(
self,
span: Span,
response_body: dict[str, Any],
instrumentor_context: _BotocoreInstrumentorContext,
capture_content: bool,
):
if "usage" in response_body:
usage = response_body["usage"]
if "inputTokens" in usage:
span.set_attribute(GEN_AI_USAGE_INPUT_TOKENS, usage["inputTokens"])
if "outputTokens" in usage:
span.set_attribute(GEN_AI_USAGE_OUTPUT_TOKENS, usage["outputTokens"])
if "stopReason" in response_body:
span.set_attribute(GEN_AI_RESPONSE_FINISH_REASONS, [response_body["stopReason"]])
# In case of an early stream closure, the result may not contain outputs
if self._stream_has_output_content(response_body):
logger = instrumentor_context.logger
choice = _Choice.from_converse(response_body, capture_content)
logger.emit(choice.to_choice_event())
metrics = instrumentor_context.metrics
metrics_attributes = self._extract_metrics_attributes()
if operation_duration_histogram := metrics.get(GEN_AI_CLIENT_OPERATION_DURATION):
duration = max((default_timer() - self._operation_start), 0)
operation_duration_histogram.record(
duration,
attributes=metrics_attributes,
)
if token_usage_histogram := metrics.get(GEN_AI_CLIENT_TOKEN_USAGE):
if usage := response_body.get("usage"):
if input_tokens := usage.get("inputTokens"):
input_attributes = {
**metrics_attributes,
GEN_AI_TOKEN_TYPE: GenAiTokenTypeValues.INPUT.value,
}
token_usage_histogram.record(input_tokens, input_attributes)
if output_tokens := usage.get("outputTokens"):
output_attributes = {
**metrics_attributes,
GEN_AI_TOKEN_TYPE: GenAiTokenTypeValues.COMPLETION.value,
}
token_usage_histogram.record(output_tokens, output_attributes)
# pylint: disable=no-self-use
def _handle_anthropic_claude_response(
self,
span: Span,
response_body: dict[str, Any],
instrumentor_context: _BotocoreInstrumentorContext,
capture_content: bool,
):
if usage := response_body.get("usage"):
if "input_tokens" in usage:
span.set_attribute(GEN_AI_USAGE_INPUT_TOKENS, usage["input_tokens"])
if "output_tokens" in usage:
span.set_attribute(GEN_AI_USAGE_OUTPUT_TOKENS, usage["output_tokens"])
if "stop_reason" in response_body:
span.set_attribute(GEN_AI_RESPONSE_FINISH_REASONS, [response_body["stop_reason"]])
logger = instrumentor_context.logger
choice = _Choice.from_invoke_anthropic_claude(response_body, capture_content)
logger.emit(choice.to_choice_event())
metrics = instrumentor_context.metrics
metrics_attributes = self._extract_metrics_attributes()
if operation_duration_histogram := metrics.get(GEN_AI_CLIENT_OPERATION_DURATION):
duration = max((default_timer() - self._operation_start), 0)
operation_duration_histogram.record(
duration,
attributes=metrics_attributes,
)
if token_usage_histogram := metrics.get(GEN_AI_CLIENT_TOKEN_USAGE):
if usage := response_body.get("usage"):
if input_tokens := usage.get("input_tokens"):
input_attributes = {
**metrics_attributes,
GEN_AI_TOKEN_TYPE: GenAiTokenTypeValues.INPUT.value,
}
token_usage_histogram.record(input_tokens, input_attributes)
if output_tokens := usage.get("output_tokens"):
output_attributes = {
**metrics_attributes,
GEN_AI_TOKEN_TYPE: GenAiTokenTypeValues.COMPLETION.value,
}
token_usage_histogram.record(output_tokens, output_attributes)
def _handle_cohere_command_r_response(
self,
span: Span,
response_body: dict[str, Any],
instrumentor_context: _BotocoreInstrumentorContext,
capture_content: bool,
):
if "text" in response_body:
span.set_attribute(
GEN_AI_USAGE_OUTPUT_TOKENS,
estimate_token_count(response_body["text"]),
)
if "finish_reason" in response_body:
span.set_attribute(
GEN_AI_RESPONSE_FINISH_REASONS,
[response_body["finish_reason"]],
)
logger = instrumentor_context.logger
choice = _Choice.from_invoke_cohere_command_r(response_body, capture_content)
logger.emit(choice.to_choice_event())
def _handle_cohere_command_response(
self,
span: Span,
response_body: dict[str, Any],
instrumentor_context: _BotocoreInstrumentorContext,
capture_content: bool,
):
if response_body.get("generations"):
generations = response_body["generations"][0]
if "text" in generations:
span.set_attribute(
GEN_AI_USAGE_OUTPUT_TOKENS,
estimate_token_count(generations["text"]),
)
if "finish_reason" in generations:
span.set_attribute(
GEN_AI_RESPONSE_FINISH_REASONS,
[generations["finish_reason"]],
)
logger = instrumentor_context.logger
choice = _Choice.from_invoke_cohere_command(response_body, capture_content)
logger.emit(choice.to_choice_event())
def _handle_meta_llama_response(
self,
span: Span,
response_body: dict[str, Any],
instrumentor_context: _BotocoreInstrumentorContext,
capture_content: bool,
):
if "prompt_token_count" in response_body:
span.set_attribute(GEN_AI_USAGE_INPUT_TOKENS, response_body["prompt_token_count"])
if "generation_token_count" in response_body:
span.set_attribute(
GEN_AI_USAGE_OUTPUT_TOKENS,
response_body["generation_token_count"],
)
if "stop_reason" in response_body:
span.set_attribute(GEN_AI_RESPONSE_FINISH_REASONS, [response_body["stop_reason"]])
logger = instrumentor_context.logger
choice = _Choice.from_invoke_meta_llama(response_body, capture_content)
logger.emit(choice.to_choice_event())
def _handle_mistral_ai_response(
self,
span: Span,
response_body: dict[str, Any],
instrumentor_context: _BotocoreInstrumentorContext,
capture_content: bool,
):
if "outputs" in response_body:
outputs = response_body["outputs"][0]
if "text" in outputs:
span.set_attribute(
GEN_AI_USAGE_OUTPUT_TOKENS,
estimate_token_count(outputs["text"]),
)
if "stop_reason" in outputs:
span.set_attribute(GEN_AI_RESPONSE_FINISH_REASONS, [outputs["stop_reason"]])
logger = instrumentor_context.logger
choice = _Choice.from_invoke_mistral_mistral(response_body, capture_content)
logger.emit(choice.to_choice_event())
def on_error(
self,
span: Span,
exception: _BotoClientErrorT,
instrumentor_context: _BotocoreInstrumentorContext,
):
if self._call_context.operation not in self._HANDLED_OPERATIONS:
return
span.set_status(Status(StatusCode.ERROR, str(exception)))
if span.is_recording():
span.set_attribute(ERROR_TYPE, type(exception).__qualname__)
if not self.should_end_span_on_exit():
span.end()
metrics = instrumentor_context.metrics
metrics_attributes = {
**self._extract_metrics_attributes(),
ERROR_TYPE: type(exception).__qualname__,
}
if operation_duration_histogram := metrics.get(GEN_AI_CLIENT_OPERATION_DURATION):
duration = max((default_timer() - self._operation_start), 0)
operation_duration_histogram.record(
duration,
attributes=metrics_attributes,
)
def _stream_has_output_content(self, response_body: dict[str, Any]):
return "output" in response_body and "message" in response_body["output"]
bedrock_utils.py 0000664 0000000 0000000 00000055521 15270700723 0051054 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-botocore/src/opentelemetry/instrumentation/botocore/extensions # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
from __future__ import annotations
import json
import math
from collections.abc import Callable, Iterator, Sequence
from os import environ
from typing import Any
from botocore.eventstream import EventStream, EventStreamError
try:
# wrapt 2.0.0+
from wrapt import BaseObjectProxy # pylint: disable=no-name-in-module
except ImportError:
from wrapt import ObjectProxy as BaseObjectProxy
from opentelemetry._logs import LogRecord
from opentelemetry.context import get_current
from opentelemetry.instrumentation.botocore.environment_variables import (
OTEL_INSTRUMENTATION_GENAI_CAPTURE_MESSAGE_CONTENT,
)
from opentelemetry.semconv._incubating.attributes.gen_ai_attributes import (
GEN_AI_SYSTEM,
GenAiSystemValues,
)
_StreamDoneCallableT = Callable[[dict[str, int | str]], None]
_StreamErrorCallableT = Callable[[Exception], None]
# pylint: disable=abstract-method
class ConverseStreamWrapper(BaseObjectProxy):
"""Wrapper for botocore.eventstream.EventStream"""
def __init__(
self,
stream: EventStream,
stream_done_callback: _StreamDoneCallableT,
stream_error_callback: _StreamErrorCallableT,
):
super().__init__(stream)
self._stream_done_callback = stream_done_callback
self._stream_error_callback = stream_error_callback
# accumulating things in the same shape of non-streaming version
# {"usage": {"inputTokens": 0, "outputTokens": 0}, "stopReason": "finish", "output": {"message": {"role": "", "content": [{"text": ""}]}
self._response = {}
self._message = None
self._content_block = {}
self._tool_json_input_buf = ""
self._record_message = False
self._ended = False
def __iter__(self):
try:
for event in self.__wrapped__: # pylint: disable=no-member
self._process_event(event)
yield event
except EventStreamError as exc:
self._handle_stream_error(exc)
raise
def _process_event(self, event):
# pylint: disable=too-many-branches
if "messageStart" in event:
# {'messageStart': {'role': 'assistant'}}
if event["messageStart"].get("role") == "assistant":
self._record_message = True
self._message = {"role": "assistant", "content": []}
return
if "contentBlockStart" in event:
# {'contentBlockStart': {'start': {'toolUse': {'toolUseId': 'id', 'name': 'func_name'}}, 'contentBlockIndex': 1}}
start = event["contentBlockStart"].get("start", {})
if "toolUse" in start:
self._content_block = {"toolUse": start["toolUse"]}
return
if "contentBlockDelta" in event:
# {'contentBlockDelta': {'delta': {'text': "Hello"}, 'contentBlockIndex': 0}}
# {'contentBlockDelta': {'delta': {'toolUse': {'input': '{"location":"Seattle"}'}}, 'contentBlockIndex': 1}}
# {'contentBlockDelta': {'delta': {'toolUse': {'input': 'a", "Yok'}}, 'contentBlockIndex': 1}}
if self._record_message:
delta = event["contentBlockDelta"].get("delta", {})
if "text" in delta:
self._content_block.setdefault("text", "")
self._content_block["text"] += delta["text"]
elif "toolUse" in delta:
if (input_buf := delta["toolUse"].get("input")) is not None:
self._tool_json_input_buf += input_buf
return
if "contentBlockStop" in event:
# {'contentBlockStop': {'contentBlockIndex': 0}}
if self._record_message:
if self._tool_json_input_buf:
try:
self._content_block["toolUse"]["input"] = json.loads(self._tool_json_input_buf)
except json.JSONDecodeError:
self._content_block["toolUse"]["input"] = self._tool_json_input_buf
self._message["content"].append(self._content_block)
self._content_block = {}
self._tool_json_input_buf = ""
return
if "messageStop" in event:
# {'messageStop': {'stopReason': 'end_turn'}}
if stop_reason := event["messageStop"].get("stopReason"):
self._response["stopReason"] = stop_reason
if self._record_message:
self._response["output"] = {"message": self._message}
self._record_message = False
self._message = None
return
if "metadata" in event:
# {'metadata': {'usage': {'inputTokens': 12, 'outputTokens': 15, 'totalTokens': 27}, 'metrics': {'latencyMs': 2980}}}
if usage := event["metadata"].get("usage"):
self._response["usage"] = {}
if input_tokens := usage.get("inputTokens"):
self._response["usage"]["inputTokens"] = input_tokens
if output_tokens := usage.get("outputTokens"):
self._response["usage"]["outputTokens"] = output_tokens
if cache_read := usage.get("cacheReadInputTokens"):
self._response["usage"]["cacheReadInputTokens"] = cache_read
if cache_write := usage.get("cacheWriteInputTokens"):
self._response["usage"]["cacheWriteInputTokens"] = cache_write
self._complete_stream(self._response)
return
def close(self):
self.__wrapped__.close() # pylint: disable=no-member
# Treat the stream as done to ensure the span end.
self._complete_stream(self._response)
def _complete_stream(self, response):
self._stream_done_callback(response, self._ended)
self._ended = True
def _handle_stream_error(self, exc):
self._stream_error_callback(exc, self._ended)
self._ended = True
# pylint: disable=abstract-method
class InvokeModelWithResponseStreamWrapper(BaseObjectProxy):
"""Wrapper for botocore.eventstream.EventStream"""
def __init__(
self,
stream: EventStream,
stream_done_callback: _StreamDoneCallableT,
stream_error_callback: _StreamErrorCallableT,
model_id: str,
):
super().__init__(stream)
self._stream_done_callback = stream_done_callback
self._stream_error_callback = stream_error_callback
self._model_id = model_id
# accumulating things in the same shape of the Converse API
# {"usage": {"inputTokens": 0, "outputTokens": 0}, "stopReason": "finish", "output": {"message": {"role": "", "content": [{"text": ""}]}
self._response = {}
self._message = None
self._content_block = {}
self._tool_json_input_buf = ""
self._record_message = False
self._ended = False
def close(self):
self.__wrapped__.close() # pylint: disable=no-member
# Treat the stream as done to ensure the span end.
self._stream_done_callback(self._response, self._ended)
def _complete_stream(self, response):
self._stream_done_callback(response, self._ended)
self._ended = True
def _handle_stream_error(self, exc):
self._stream_error_callback(exc, self._ended)
self._ended = True
def __iter__(self):
try:
for event in self.__wrapped__: # pylint: disable=no-member
self._process_event(event)
yield event
except EventStreamError as exc:
self._handle_stream_error(exc)
raise
def _process_event(self, event):
if "chunk" not in event:
return
json_bytes = event["chunk"].get("bytes", b"")
decoded = json_bytes.decode("utf-8")
try:
chunk = json.loads(decoded)
except json.JSONDecodeError:
return
if "amazon.titan" in self._model_id:
self._process_amazon_titan_chunk(chunk)
elif "amazon.nova" in self._model_id:
self._process_amazon_nova_chunk(chunk)
elif "anthropic.claude" in self._model_id:
self._process_anthropic_claude_chunk(chunk)
def _process_invocation_metrics(self, invocation_metrics):
self._response["usage"] = {}
if input_tokens := invocation_metrics.get("inputTokenCount"):
self._response["usage"]["inputTokens"] = input_tokens
if output_tokens := invocation_metrics.get("outputTokenCount"):
self._response["usage"]["outputTokens"] = output_tokens
def _process_amazon_titan_chunk(self, chunk):
if (stop_reason := chunk.get("completionReason")) is not None:
self._response["stopReason"] = stop_reason
if invocation_metrics := chunk.get("amazon-bedrock-invocationMetrics"):
# "amazon-bedrock-invocationMetrics":{
# "inputTokenCount":9,"outputTokenCount":128,"invocationLatency":3569,"firstByteLatency":2180
# }
self._process_invocation_metrics(invocation_metrics)
# transform the shape of the message to match other models
self._response["output"] = {"message": {"content": [{"text": chunk["outputText"]}]}}
self._complete_stream(self._response)
def _process_amazon_nova_chunk(self, chunk):
# pylint: disable=too-many-branches
if "messageStart" in chunk:
# {'messageStart': {'role': 'assistant'}}
if chunk["messageStart"].get("role") == "assistant":
self._record_message = True
self._message = {"role": "assistant", "content": []}
return
if "contentBlockStart" in chunk:
# {'contentBlockStart': {'start': {'toolUse': {'toolUseId': 'id', 'name': 'name'}}, 'contentBlockIndex': 31}}
if self._record_message:
self._message["content"].append(self._content_block)
start = chunk["contentBlockStart"].get("start", {})
if "toolUse" in start:
self._content_block = start
else:
self._content_block = {}
return
if "contentBlockDelta" in chunk:
# {'contentBlockDelta': {'delta': {'text': "Hello"}, 'contentBlockIndex': 0}}
# {'contentBlockDelta': {'delta': {'toolUse': {'input': '{"location":"San Francisco"}'}}, 'contentBlockIndex': 31}}
if self._record_message:
delta = chunk["contentBlockDelta"].get("delta", {})
if "text" in delta:
self._content_block.setdefault("text", "")
self._content_block["text"] += delta["text"]
elif "toolUse" in delta:
self._content_block.setdefault("toolUse", {})
self._content_block["toolUse"]["input"] = json.loads(delta["toolUse"]["input"])
return
if "contentBlockStop" in chunk:
# {'contentBlockStop': {'contentBlockIndex': 0}}
if self._record_message:
# create a new content block only for tools
if "toolUse" in self._content_block:
self._message["content"].append(self._content_block)
self._content_block = {}
return
if "messageStop" in chunk:
# {'messageStop': {'stopReason': 'end_turn'}}
if stop_reason := chunk["messageStop"].get("stopReason"):
self._response["stopReason"] = stop_reason
if self._record_message:
self._message["content"].append(self._content_block)
self._content_block = {}
self._response["output"] = {"message": self._message}
self._record_message = False
self._message = None
return
if "metadata" in chunk:
# {'metadata': {'usage': {'inputTokens': 8, 'outputTokens': 117}, 'metrics': {}, 'trace': {}}}
if usage := chunk["metadata"].get("usage"):
self._response["usage"] = {}
if input_tokens := usage.get("inputTokens"):
self._response["usage"]["inputTokens"] = input_tokens
if output_tokens := usage.get("outputTokens"):
self._response["usage"]["outputTokens"] = output_tokens
self._complete_stream(self._response)
return
def _process_anthropic_claude_chunk(self, chunk):
# pylint: disable=too-many-return-statements,too-many-branches
if not (message_type := chunk.get("type")):
return
if message_type == "message_start":
# {'type': 'message_start', 'message': {'id': 'id', 'type': 'message', 'role': 'assistant', 'model': 'claude-2.0', 'content': [], 'stop_reason': None, 'stop_sequence': None, 'usage': {'input_tokens': 18, 'output_tokens': 1}}}
if chunk.get("message", {}).get("role") == "assistant":
self._record_message = True
message = chunk["message"]
self._message = {
"role": message["role"],
"content": message.get("content", []),
}
return
if message_type == "content_block_start":
# {'type': 'content_block_start', 'index': 0, 'content_block': {'type': 'text', 'text': ''}}
# {'type': 'content_block_start', 'index': 1, 'content_block': {'type': 'tool_use', 'id': 'id', 'name': 'func_name', 'input': {}}}
if self._record_message:
block = chunk.get("content_block", {})
if block.get("type") == "text" or block.get("type") == "tool_use":
self._content_block = block
return
if message_type == "content_block_delta":
# {'type': 'content_block_delta', 'index': 0, 'delta': {'type': 'text_delta', 'text': 'Here'}}
# {'type': 'content_block_delta', 'index': 1, 'delta': {'type': 'input_json_delta', 'partial_json': ''}}
if self._record_message:
delta = chunk.get("delta", {})
if delta.get("type") == "text_delta":
self._content_block["text"] += delta.get("text", "")
elif delta.get("type") == "input_json_delta":
self._tool_json_input_buf += delta.get("partial_json", "")
return
if message_type == "content_block_stop":
# {'type': 'content_block_stop', 'index': 0}
if self._tool_json_input_buf:
try:
self._content_block["input"] = json.loads(self._tool_json_input_buf)
except json.JSONDecodeError:
self._content_block["input"] = self._tool_json_input_buf
self._message["content"].append(self._content_block)
self._content_block = {}
self._tool_json_input_buf = ""
return
if message_type == "message_delta":
# {'type': 'message_delta', 'delta': {'stop_reason': 'end_turn', 'stop_sequence': None}, 'usage': {'output_tokens': 123}}
if (stop_reason := chunk.get("delta", {}).get("stop_reason")) is not None:
self._response["stopReason"] = stop_reason
return
if message_type == "message_stop":
# {'type': 'message_stop', 'amazon-bedrock-invocationMetrics': {'inputTokenCount': 18, 'outputTokenCount': 123, 'invocationLatency': 5250, 'firstByteLatency': 290}}
if invocation_metrics := chunk.get("amazon-bedrock-invocationMetrics"):
self._process_invocation_metrics(invocation_metrics)
if self._record_message:
self._response["output"] = {"message": self._message}
self._record_message = False
self._message = None
self._complete_stream(self._response)
return
def estimate_token_count(message: str) -> int:
# https://docs.aws.amazon.com/bedrock/latest/userguide/model-customization-prepare.html
# use 6 chars per token to approximate token count when not provided in response body
return math.ceil(len(message) / 6)
def genai_capture_message_content() -> bool:
capture_content = environ.get(OTEL_INSTRUMENTATION_GENAI_CAPTURE_MESSAGE_CONTENT, "false")
return capture_content.lower() == "true"
def extract_tool_calls(message: dict[str, Any], capture_content: bool) -> Sequence[dict[str, Any]] | None:
content = message.get("content")
if not content:
return None
tool_uses = [item["toolUse"] for item in content if "toolUse" in item]
if not tool_uses:
tool_uses = [item for item in content if isinstance(item, dict) and item.get("type") == "tool_use"]
tool_id_key = "id"
else:
tool_id_key = "toolUseId"
if not tool_uses:
return None
tool_calls = []
for tool_use in tool_uses:
tool_call = {"type": "function"}
if call_id := tool_use.get(tool_id_key):
tool_call["id"] = call_id
if function_name := tool_use.get("name"):
tool_call["function"] = {"name": function_name}
if (function_input := tool_use.get("input")) and capture_content:
tool_call.setdefault("function", {})
tool_call["function"]["arguments"] = function_input
tool_calls.append(tool_call)
return tool_calls
def extract_tool_results(message: dict[str, Any], capture_content: bool) -> Iterator[dict[str, Any]]:
content = message.get("content")
if not content:
return
# langchain sends content as string with InvokeModel and Anthropic Claude
if isinstance(content, str):
return
# Converse format
tool_results = [item["toolResult"] for item in content if "toolResult" in item]
# InvokeModel anthropic.claude format
if not tool_results:
tool_results = [item for item in content if item.get("type") == "tool_result"]
tool_id_key = "tool_use_id"
else:
tool_id_key = "toolUseId"
if not tool_results:
return
# if we have a user message with toolResult keys we need to send
# one tool event for each part of the content
for tool_result in tool_results:
body = {}
if tool_id := tool_result.get(tool_id_key):
body["id"] = tool_id
tool_content = tool_result.get("content")
if capture_content and tool_content:
body["content"] = tool_content
yield body
def message_to_event(message: dict[str, Any], capture_content: bool) -> Iterator[LogRecord]:
attributes = {GEN_AI_SYSTEM: GenAiSystemValues.AWS_BEDROCK.value}
role = message.get("role")
content = message.get("content")
body = {}
if capture_content and content:
body["content"] = content
if role == "assistant":
# the assistant message contains both tool calls and model thinking content
if tool_calls := extract_tool_calls(message, capture_content):
body["tool_calls"] = tool_calls
elif role == "user":
# in case of tool calls we send one tool event for tool call and one for the user event
for tool_body in extract_tool_results(message, capture_content):
yield LogRecord(
event_name="gen_ai.tool.message",
attributes=attributes,
body=tool_body,
context=get_current(),
)
yield LogRecord(
event_name=f"gen_ai.{role}.message",
attributes=attributes,
body=body if body else None,
context=get_current(),
)
class _Choice:
def __init__(self, message: dict[str, Any], finish_reason: str, index: int):
self.message = message
self.finish_reason = finish_reason
self.index = index
@classmethod
def from_converse(cls, response: dict[str, Any], capture_content: bool) -> _Choice:
# be defensive about malformed responses, refer to #3958 for more context
output = response.get("output", {})
orig_message = output.get("message", {})
if role := orig_message.get("role"):
message = {"role": role}
else:
# amazon.titan does not serialize the role
message = {}
if tool_calls := extract_tool_calls(orig_message, capture_content):
message["tool_calls"] = tool_calls
elif capture_content and (content := orig_message.get("content")):
message["content"] = content
return cls(message, response["stopReason"], index=0)
@classmethod
def from_invoke_amazon_titan(cls, response: dict[str, Any], capture_content: bool) -> _Choice:
result = response["results"][0]
if capture_content:
message = {"content": result["outputText"]}
else:
message = {}
return cls(message, result["completionReason"], index=0)
@classmethod
def from_invoke_anthropic_claude(cls, response: dict[str, Any], capture_content: bool) -> _Choice:
message = {"role": response["role"]}
if tool_calls := extract_tool_calls(response, capture_content):
message["tool_calls"] = tool_calls
elif capture_content:
message["content"] = response["content"]
return cls(message, response["stop_reason"], index=0)
@classmethod
def from_invoke_cohere_command_r(cls, response: dict[str, Any], capture_content: bool) -> _Choice:
if capture_content:
message = {"content": response["text"]}
else:
message = {}
return cls(message, response["finish_reason"], index=0)
@classmethod
def from_invoke_cohere_command(cls, response: dict[str, Any], capture_content: bool) -> _Choice:
result = response["generations"][0]
if capture_content:
message = {"content": result["text"]}
else:
message = {}
return cls(message, result["finish_reason"], index=0)
@classmethod
def from_invoke_meta_llama(cls, response: dict[str, Any], capture_content: bool) -> _Choice:
if capture_content:
message = {"content": response["generation"]}
else:
message = {}
return cls(message, response["stop_reason"], index=0)
@classmethod
def from_invoke_mistral_mistral(cls, response: dict[str, Any], capture_content: bool) -> _Choice:
result = response["outputs"][0]
if capture_content:
message = {"content": result["text"]}
else:
message = {}
return cls(message, result["stop_reason"], index=0)
def _to_body_dict(self) -> dict[str, Any]:
return {
"finish_reason": self.finish_reason,
"index": self.index,
"message": self.message,
}
def to_choice_event(self, **event_kwargs) -> LogRecord:
attributes = {GEN_AI_SYSTEM: GenAiSystemValues.AWS_BEDROCK.value}
return LogRecord(
event_name="gen_ai.choice",
attributes=attributes,
body=self._to_body_dict(),
**event_kwargs,
)
dynamodb.py 0000664 0000000 0000000 00000031762 15270700723 0050021 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-botocore/src/opentelemetry/instrumentation/botocore/extensions # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
import abc
import inspect
import json
from collections.abc import Callable
from typing import Any
from urllib.parse import urlparse
from opentelemetry.instrumentation.botocore.extensions.types import (
_AttributeMapT,
_AwsSdkCallContext,
_AwsSdkExtension,
_BotocoreInstrumentorContext,
_BotoResultT,
)
from opentelemetry.semconv._incubating.attributes import (
aws_attributes,
db_attributes,
)
from opentelemetry.semconv._incubating.attributes.net_attributes import (
NET_PEER_NAME,
)
from opentelemetry.trace.span import Span
from opentelemetry.util.types import AttributeValue
# pylint: disable=invalid-name
_AttributePathT = str | tuple[str]
# converter functions
def _conv_val_to_single_attr_tuple(value: str) -> tuple[str]:
return None if value is None else (value,)
def _conv_dict_to_key_tuple(value: dict[str, Any]) -> tuple[str] | None:
return tuple(value.keys()) if isinstance(value, dict) else None
def _conv_list_to_json_list(value: list) -> list[str] | None:
return [json.dumps(item) for item in value] if isinstance(value, list) else None
def _conv_val_to_single_json_tuple(value: str) -> tuple[str] | None:
return (json.dumps(value),) if value is not None else None
def _conv_dict_to_json_str(value: dict) -> str | None:
return json.dumps(value) if isinstance(value, dict) else None
def _conv_val_to_len(value) -> int | None:
return len(value) if value is not None else None
################################################################################
# common request attributes
################################################################################
_REQ_TABLE_NAME = ("TableName", _conv_val_to_single_attr_tuple)
_REQ_REQITEMS_TABLE_NAMES = ("RequestItems", _conv_dict_to_key_tuple)
_REQ_GLOBAL_SEC_INDEXES = ("GlobalSecondaryIndexes", _conv_list_to_json_list)
_REQ_LOCAL_SEC_INDEXES = ("LocalSecondaryIndexes", _conv_list_to_json_list)
_REQ_PROV_READ_CAP = (("ProvisionedThroughput", "ReadCapacityUnits"), None)
_REQ_PROV_WRITE_CAP = (("ProvisionedThroughput", "WriteCapacityUnits"), None)
_REQ_CONSISTENT_READ = ("ConsistentRead", None)
_REQ_PROJECTION = ("ProjectionExpression", None)
_REQ_ATTRS_TO_GET = ("AttributesToGet", None)
_REQ_LIMIT = ("Limit", None)
_REQ_SELECT = ("Select", None)
_REQ_INDEX_NAME = ("IndexName", None)
################################################################################
# common response attributes
################################################################################
_RES_CONSUMED_CAP = ("ConsumedCapacity", _conv_list_to_json_list)
_RES_CONSUMED_CAP_SINGLE = ("ConsumedCapacity", _conv_val_to_single_json_tuple)
_RES_ITEM_COL_METRICS = ("ItemCollectionMetrics", _conv_dict_to_json_str)
################################################################################
# DynamoDB operations with enhanced attributes
################################################################################
_AttrSpecT = tuple[_AttributePathT, Callable | None]
class _DynamoDbOperation(abc.ABC):
start_attributes = None # type: Optional[Dict[str, _AttrSpecT]]
request_attributes = None # type: Optional[Dict[str, _AttrSpecT]]
response_attributes = None # type: Optional[Dict[str, _AttrSpecT]]
@classmethod
@abc.abstractmethod
def operation_name(cls):
pass
@classmethod
def add_start_attributes(cls, call_context: _AwsSdkCallContext, attributes: _AttributeMapT):
pass
@classmethod
def add_response_attributes(cls, call_context: _AwsSdkCallContext, span: Span, result: _BotoResultT):
pass
class _OpBatchGetItem(_DynamoDbOperation):
start_attributes = {
aws_attributes.AWS_DYNAMODB_TABLE_NAMES: _REQ_REQITEMS_TABLE_NAMES,
}
response_attributes = {
aws_attributes.AWS_DYNAMODB_CONSUMED_CAPACITY: _RES_CONSUMED_CAP,
}
@classmethod
def operation_name(cls):
return "BatchGetItem"
class _OpBatchWriteItem(_DynamoDbOperation):
start_attributes = {
aws_attributes.AWS_DYNAMODB_TABLE_NAMES: _REQ_REQITEMS_TABLE_NAMES,
}
response_attributes = {
aws_attributes.AWS_DYNAMODB_CONSUMED_CAPACITY: _RES_CONSUMED_CAP,
aws_attributes.AWS_DYNAMODB_ITEM_COLLECTION_METRICS: _RES_ITEM_COL_METRICS,
}
@classmethod
def operation_name(cls):
return "BatchWriteItem"
class _OpCreateTable(_DynamoDbOperation):
start_attributes = {
aws_attributes.AWS_DYNAMODB_TABLE_NAMES: _REQ_TABLE_NAME,
}
request_attributes = {
aws_attributes.AWS_DYNAMODB_GLOBAL_SECONDARY_INDEXES: _REQ_GLOBAL_SEC_INDEXES,
aws_attributes.AWS_DYNAMODB_LOCAL_SECONDARY_INDEXES: _REQ_LOCAL_SEC_INDEXES,
aws_attributes.AWS_DYNAMODB_PROVISIONED_READ_CAPACITY: _REQ_PROV_READ_CAP,
aws_attributes.AWS_DYNAMODB_PROVISIONED_WRITE_CAPACITY: _REQ_PROV_WRITE_CAP,
}
@classmethod
def operation_name(cls):
return "CreateTable"
class _OpDeleteItem(_DynamoDbOperation):
start_attributes = {
aws_attributes.AWS_DYNAMODB_TABLE_NAMES: _REQ_TABLE_NAME,
}
response_attributes = {
aws_attributes.AWS_DYNAMODB_CONSUMED_CAPACITY: _RES_CONSUMED_CAP_SINGLE,
aws_attributes.AWS_DYNAMODB_ITEM_COLLECTION_METRICS: _RES_ITEM_COL_METRICS,
}
@classmethod
def operation_name(cls):
return "DeleteItem"
class _OpDeleteTable(_DynamoDbOperation):
start_attributes = {
aws_attributes.AWS_DYNAMODB_TABLE_NAMES: _REQ_TABLE_NAME,
}
@classmethod
def operation_name(cls):
return "DeleteTable"
class _OpDescribeTable(_DynamoDbOperation):
start_attributes = {
aws_attributes.AWS_DYNAMODB_TABLE_NAMES: _REQ_TABLE_NAME,
}
@classmethod
def operation_name(cls):
return "DescribeTable"
class _OpGetItem(_DynamoDbOperation):
start_attributes = {
aws_attributes.AWS_DYNAMODB_TABLE_NAMES: _REQ_TABLE_NAME,
}
request_attributes = {
aws_attributes.AWS_DYNAMODB_CONSISTENT_READ: _REQ_CONSISTENT_READ,
aws_attributes.AWS_DYNAMODB_PROJECTION: _REQ_PROJECTION,
}
response_attributes = {
aws_attributes.AWS_DYNAMODB_CONSUMED_CAPACITY: _RES_CONSUMED_CAP_SINGLE,
}
@classmethod
def operation_name(cls):
return "GetItem"
class _OpListTables(_DynamoDbOperation):
request_attributes = {
aws_attributes.AWS_DYNAMODB_EXCLUSIVE_START_TABLE: (
"ExclusiveStartTableName",
None,
),
aws_attributes.AWS_DYNAMODB_LIMIT: _REQ_LIMIT,
}
response_attributes = {
aws_attributes.AWS_DYNAMODB_TABLE_COUNT: (
"TableNames",
_conv_val_to_len,
),
}
@classmethod
def operation_name(cls):
return "ListTables"
class _OpPutItem(_DynamoDbOperation):
start_attributes = {aws_attributes.AWS_DYNAMODB_TABLE_NAMES: _REQ_TABLE_NAME}
response_attributes = {
aws_attributes.AWS_DYNAMODB_CONSUMED_CAPACITY: _RES_CONSUMED_CAP_SINGLE,
aws_attributes.AWS_DYNAMODB_ITEM_COLLECTION_METRICS: _RES_ITEM_COL_METRICS,
}
@classmethod
def operation_name(cls):
return "PutItem"
class _OpQuery(_DynamoDbOperation):
start_attributes = {
aws_attributes.AWS_DYNAMODB_TABLE_NAMES: _REQ_TABLE_NAME,
}
request_attributes = {
aws_attributes.AWS_DYNAMODB_SCAN_FORWARD: ("ScanIndexForward", None),
aws_attributes.AWS_DYNAMODB_ATTRIBUTES_TO_GET: _REQ_ATTRS_TO_GET,
aws_attributes.AWS_DYNAMODB_CONSISTENT_READ: _REQ_CONSISTENT_READ,
aws_attributes.AWS_DYNAMODB_INDEX_NAME: _REQ_INDEX_NAME,
aws_attributes.AWS_DYNAMODB_LIMIT: _REQ_LIMIT,
aws_attributes.AWS_DYNAMODB_PROJECTION: _REQ_PROJECTION,
aws_attributes.AWS_DYNAMODB_SELECT: _REQ_SELECT,
}
response_attributes = {
aws_attributes.AWS_DYNAMODB_CONSUMED_CAPACITY: _RES_CONSUMED_CAP_SINGLE,
}
@classmethod
def operation_name(cls):
return "Query"
class _OpScan(_DynamoDbOperation):
start_attributes = {
aws_attributes.AWS_DYNAMODB_TABLE_NAMES: _REQ_TABLE_NAME,
}
request_attributes = {
aws_attributes.AWS_DYNAMODB_SEGMENT: ("Segment", None),
aws_attributes.AWS_DYNAMODB_TOTAL_SEGMENTS: ("TotalSegments", None),
aws_attributes.AWS_DYNAMODB_ATTRIBUTES_TO_GET: _REQ_ATTRS_TO_GET,
aws_attributes.AWS_DYNAMODB_CONSISTENT_READ: _REQ_CONSISTENT_READ,
aws_attributes.AWS_DYNAMODB_INDEX_NAME: _REQ_INDEX_NAME,
aws_attributes.AWS_DYNAMODB_LIMIT: _REQ_LIMIT,
aws_attributes.AWS_DYNAMODB_PROJECTION: _REQ_PROJECTION,
aws_attributes.AWS_DYNAMODB_SELECT: _REQ_SELECT,
}
response_attributes = {
aws_attributes.AWS_DYNAMODB_COUNT: ("Count", None),
aws_attributes.AWS_DYNAMODB_SCANNED_COUNT: ("ScannedCount", None),
aws_attributes.AWS_DYNAMODB_CONSUMED_CAPACITY: _RES_CONSUMED_CAP_SINGLE,
}
@classmethod
def operation_name(cls):
return "Scan"
class _OpUpdateItem(_DynamoDbOperation):
start_attributes = {
aws_attributes.AWS_DYNAMODB_TABLE_NAMES: _REQ_TABLE_NAME,
}
response_attributes = {
aws_attributes.AWS_DYNAMODB_CONSUMED_CAPACITY: _RES_CONSUMED_CAP_SINGLE,
aws_attributes.AWS_DYNAMODB_ITEM_COLLECTION_METRICS: _RES_ITEM_COL_METRICS,
}
@classmethod
def operation_name(cls):
return "UpdateItem"
class _OpUpdateTable(_DynamoDbOperation):
start_attributes = {
aws_attributes.AWS_DYNAMODB_TABLE_NAMES: _REQ_TABLE_NAME,
}
request_attributes = {
aws_attributes.AWS_DYNAMODB_ATTRIBUTE_DEFINITIONS: (
"AttributeDefinitions",
_conv_list_to_json_list,
),
aws_attributes.AWS_DYNAMODB_GLOBAL_SECONDARY_INDEX_UPDATES: (
"GlobalSecondaryIndexUpdates",
_conv_list_to_json_list,
),
aws_attributes.AWS_DYNAMODB_PROVISIONED_READ_CAPACITY: _REQ_PROV_READ_CAP,
aws_attributes.AWS_DYNAMODB_PROVISIONED_WRITE_CAPACITY: _REQ_PROV_WRITE_CAP,
}
@classmethod
def operation_name(cls):
return "UpdateTable"
################################################################################
# DynamoDB extension
################################################################################
def _is_operation(op: object) -> bool:
try:
return inspect.isclass(op) and issubclass(op, _DynamoDbOperation) and not inspect.isabstract(op)
except TypeError:
return False
_OPERATION_MAPPING = {op.operation_name(): op for op in globals().values() if _is_operation(op)} # type: Dict[str, _DynamoDbOperation]
class _DynamoDbExtension(_AwsSdkExtension):
def __init__(self, call_context: _AwsSdkCallContext):
super().__init__(call_context)
self._op = _OPERATION_MAPPING.get(call_context.operation)
def extract_attributes(self, attributes: _AttributeMapT):
attributes[db_attributes.DB_SYSTEM] = db_attributes.DbSystemValues.DYNAMODB.value
attributes[db_attributes.DB_OPERATION] = self._call_context.operation
attributes[NET_PEER_NAME] = self._get_peer_name()
if self._op is None:
return
def attr_setter(key: str, value: AttributeValue):
attributes[key] = value
self._add_attributes(self._call_context.params, self._op.start_attributes, attr_setter)
def _get_peer_name(self) -> str:
return urlparse(self._call_context.endpoint_url).netloc
def before_service_call(self, span: Span, instrumentor_context: _BotocoreInstrumentorContext):
if not span.is_recording() or self._op is None:
return
self._add_attributes(
self._call_context.params,
self._op.request_attributes,
span.set_attribute,
)
def on_success(
self,
span: Span,
result: _BotoResultT,
instrumentor_context: _BotocoreInstrumentorContext,
):
if not span.is_recording():
return
if self._op is None:
return
self._add_attributes(result, self._op.response_attributes, span.set_attribute)
def _add_attributes(
self,
provider: dict[str, Any],
attributes: dict[str, _AttrSpecT],
setter: Callable[[str, AttributeValue], None],
):
if attributes is None:
return
for attr_key, attr_spec in attributes.items():
attr_path, converter = attr_spec
value = self._get_attr_value(provider, attr_path)
if value is None:
continue
if converter is not None:
value = converter(value)
if value is None:
continue
setter(attr_key, value)
@staticmethod
def _get_attr_value(provider: dict[str, Any], attr_path: _AttributePathT):
if isinstance(attr_path, str):
return provider.get(attr_path)
value = provider
for path_part in attr_path:
value = value.get(path_part)
if value is None:
return None
return None if value is provider else value
lmbd.py 0000664 0000000 0000000 00000007352 15270700723 0047140 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-botocore/src/opentelemetry/instrumentation/botocore/extensions # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
import abc
import inspect
import json
import re
from opentelemetry.instrumentation.botocore.extensions.types import (
_AttributeMapT,
_AwsSdkCallContext,
_AwsSdkExtension,
_BotocoreInstrumentorContext,
)
from opentelemetry.propagate import inject
from opentelemetry.semconv._incubating.attributes.faas_attributes import (
FAAS_INVOKED_NAME,
FAAS_INVOKED_PROVIDER,
FAAS_INVOKED_REGION,
)
from opentelemetry.trace.span import Span
class _LambdaOperation(abc.ABC):
@classmethod
@abc.abstractmethod
def operation_name(cls):
pass
@classmethod
def prepare_attributes(cls, call_context: _AwsSdkCallContext, attributes: _AttributeMapT):
pass
@classmethod
def before_service_call(cls, call_context: _AwsSdkCallContext, span: Span):
pass
class _OpInvoke(_LambdaOperation):
# https://docs.aws.amazon.com/lambda/latest/dg/API_Invoke.html#API_Invoke_RequestParameters
ARN_LAMBDA_PATTERN = re.compile(
"(?:arn:(?:aws[a-zA-Z-]*)?:lambda:)?"
"(?:[a-z]{2}(?:-gov)?-[a-z]+-\\d{1}:)?(?:\\d{12}:)?"
"(?:function:)?([a-zA-Z0-9-_\\.]+)(?::(?:\\$LATEST|[a-zA-Z0-9-_]+))?"
)
@classmethod
def operation_name(cls):
return "Invoke"
@classmethod
def extract_attributes(cls, call_context: _AwsSdkCallContext, attributes: _AttributeMapT):
attributes[FAAS_INVOKED_PROVIDER] = "aws"
attributes[FAAS_INVOKED_NAME] = cls._parse_function_name(call_context)
attributes[FAAS_INVOKED_REGION] = call_context.region
@classmethod
def _parse_function_name(cls, call_context: _AwsSdkCallContext):
function_name_or_arn = call_context.params.get("FunctionName")
matches = cls.ARN_LAMBDA_PATTERN.match(function_name_or_arn)
function_name = matches.group(1)
return function_name_or_arn if function_name is None else function_name
@classmethod
def before_service_call(cls, call_context: _AwsSdkCallContext, span: Span):
cls._inject_current_span(call_context)
@classmethod
def _inject_current_span(cls, call_context: _AwsSdkCallContext):
payload_str = call_context.params.get("Payload")
if payload_str is None:
return
# TODO: reconsider propagation via payload as it manipulates input of the called lambda function
try:
payload = json.loads(payload_str)
headers = payload.get("headers", {})
inject(headers)
payload["headers"] = headers
call_context.params["Payload"] = json.dumps(payload)
except ValueError:
pass
################################################################################
# Lambda extension
################################################################################
def _is_operation(op: object) -> bool:
try:
return inspect.isclass(op) and issubclass(op, _LambdaOperation) and not inspect.isabstract(op)
except TypeError:
return False
_OPERATION_MAPPING: dict[str, _LambdaOperation] = {
op.operation_name(): op for op in globals().values() if _is_operation(op)
}
class _LambdaExtension(_AwsSdkExtension):
def __init__(self, call_context: _AwsSdkCallContext):
super().__init__(call_context)
self._op = _OPERATION_MAPPING.get(call_context.operation)
def extract_attributes(self, attributes: _AttributeMapT):
if self._op is None:
return
self._op.extract_attributes(self._call_context, attributes)
def before_service_call(self, span: Span, instrumentor_context: _BotocoreInstrumentorContext):
if self._op is None:
return
self._op.before_service_call(self._call_context, span)
registry.py 0000664 0000000 0000000 00000015547 15270700723 0050077 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-botocore/src/opentelemetry/instrumentation/botocore/extensions # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
from __future__ import annotations
import logging
from collections.abc import Callable, Mapping
from typing import TYPE_CHECKING
from opentelemetry._logs import get_logger
from opentelemetry.instrumentation.botocore.extensions.types import (
_AwsSdkCallContext,
_AwsSdkExtension,
)
from opentelemetry.instrumentation.botocore.utils import _safe_invoke
from opentelemetry.instrumentation.botocore.version import __version__
from opentelemetry.metrics import get_meter
from opentelemetry.trace import get_tracer
if TYPE_CHECKING:
from opentelemetry._logs import Logger, LoggerProvider
from opentelemetry.metrics import Instrument, Meter, MeterProvider
from opentelemetry.trace import Tracer, TracerProvider
_logger = logging.getLogger(__name__)
class ExtensionRegistry:
"""
Registry for AWS SDK extensions that manages extension lookup and
associated OpenTelemetry instrumentation components (tracers, loggers, meters, metrics).
"""
def __init__(
self,
package_name: str,
extensions: Mapping[str, Callable[[], type[_AwsSdkExtension]]],
tracer_provider: TracerProvider | None = None,
logger_provider: LoggerProvider | None = None,
meter_provider: MeterProvider | None = None,
):
self._package_name = package_name
self._extensions: Mapping[str, Callable[[], type[_AwsSdkExtension]]] = extensions
self._tracer_provider: TracerProvider = tracer_provider
self._logger_provider: LoggerProvider = logger_provider
self._meter_provider: MeterProvider = meter_provider
self._tracers: dict[str, Tracer] = {}
self._loggers: dict[str, Logger] = {}
self._meters: dict[str, Meter] = {}
self._metrics: dict[str, dict[str, Instrument]] = {}
def get_extension(self, call_context: _AwsSdkCallContext) -> _AwsSdkExtension:
"""
Get the appropriate extension for a given call context.
Args:
call_context: The AWS SDK call context
Returns:
The matching extension for the service/operation
"""
try:
loader: Callable[[], type[_AwsSdkExtension]] = self._extensions.get(call_context.service)
if loader is None:
return _AwsSdkExtension(call_context)
extension_cls = loader()
return extension_cls(call_context)
except Exception as exc: # pylint: disable=broad-except
_logger.error("Error when loading extension: %s", exc)
return _AwsSdkExtension(call_context)
def has_extension(self, call_context: _AwsSdkCallContext) -> bool:
"""
Check if a dedicated extension exists for the given call context.
Args:
call_context: The AWS SDK call context
Returns:
True if a service-specific extension exists, False otherwise
"""
return call_context.service in self._extensions
def get_instrumentation_name(self, extension: _AwsSdkExtension) -> str:
"""
Get the instrumentation name for an extension.
Service-specific extensions get a namespaced name (e.g., 'module.s3'),
while the default extension uses just the module name.
Args:
extension: The AWS SDK extension
Returns:
The instrumentation name string
"""
if self.has_extension(extension._call_context):
return f"{self._package_name}.{extension._call_context.service}"
return self._package_name
def get_tracer(self, extension: _AwsSdkExtension) -> Tracer:
"""
Get or create a tracer for the given extension.
Tracers are cached per instrumentation name for reuse.
Args:
extension: The AWS SDK extension
Returns:
A configured Tracer instance
"""
instrumentation_name: str = self.get_instrumentation_name(extension)
if instrumentation_name in self._tracers:
return self._tracers[instrumentation_name]
schema_version: str = extension.tracer_schema_version()
tracer: Tracer = get_tracer(
instrumentation_name,
__version__,
self._tracer_provider,
schema_url=f"https://opentelemetry.io/schemas/{schema_version}",
)
self._tracers[instrumentation_name] = tracer
return tracer
def get_logger(self, extension: _AwsSdkExtension):
"""
Get or create a logger for the given extension.
Loggers are cached per instrumentation name for reuse.
Args:
extension: The AWS SDK extension
Returns:
A configured Logger instance
"""
instrumentation_name: str = self.get_instrumentation_name(extension)
if instrumentation_name in self._loggers:
return self._loggers[instrumentation_name]
schema_version: str = extension.event_logger_schema_version()
logger: Logger = get_logger(
instrumentation_name,
schema_url=f"https://opentelemetry.io/schemas/{schema_version}",
logger_provider=self._logger_provider,
)
self._loggers[instrumentation_name] = logger
return logger
def get_meter(self, extension: _AwsSdkExtension) -> Meter:
"""
Get or create a meter for the given extension.
Meters are cached per instrumentation name for reuse.
Args:
extension: The AWS SDK extension
Returns:
A configured Meter instance
"""
instrumentation_name: str = self.get_instrumentation_name(extension)
if instrumentation_name in self._meters:
return self._meters[instrumentation_name]
schema_version: str = extension.meter_schema_version()
meter = get_meter(
instrumentation_name,
"",
schema_url=f"https://opentelemetry.io/schemas/{schema_version}",
meter_provider=self._meter_provider,
)
self._meters[instrumentation_name] = meter
return meter
def get_metrics(self, extension: _AwsSdkExtension) -> dict[str, Instrument]:
"""
Get or create metrics for the given extension.
Metrics are lazily initialized by calling the extension's setup_metrics method.
Args:
extension: The AWS SDK extension
Returns:
A dictionary mapping metric names to Instrument instances
"""
instrumentation_name: str = self.get_instrumentation_name(extension)
if instrumentation_name in self._metrics:
return self._metrics[instrumentation_name]
meter: Meter = self.get_meter(extension)
metrics: dict[str, Instrument] = {}
_safe_invoke(extension.setup_metrics, meter, metrics)
self._metrics[instrumentation_name] = metrics
return metrics
secretsmanager.py 0000664 0000000 0000000 00000002303 15270700723 0051214 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-botocore/src/opentelemetry/instrumentation/botocore/extensions # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
from opentelemetry.instrumentation.botocore.extensions.types import (
_AttributeMapT,
_AwsSdkExtension,
_BotocoreInstrumentorContext,
_BotoResultT,
)
from opentelemetry.semconv._incubating.attributes.aws_attributes import (
AWS_SECRETSMANAGER_SECRET_ARN,
)
from opentelemetry.trace.span import Span
class _SecretsManagerExtension(_AwsSdkExtension):
def extract_attributes(self, attributes: _AttributeMapT):
"""
SecretId is extracted if a secret ARN, the function extracts the attribute
only if the SecretId parameter is provided as an arn which starts with
`arn:aws:secretsmanager:`
"""
secret_id = self._call_context.params.get("SecretId")
if secret_id and secret_id.startswith("arn:aws:secretsmanager:"):
attributes[AWS_SECRETSMANAGER_SECRET_ARN] = secret_id
def on_success(
self,
span: Span,
result: _BotoResultT,
instrumentor_context: _BotocoreInstrumentorContext,
):
secret_arn = result.get("ARN")
if secret_arn:
span.set_attribute(AWS_SECRETSMANAGER_SECRET_ARN, secret_arn)
sfns.py 0000664 0000000 0000000 00000002751 15270700723 0047171 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-botocore/src/opentelemetry/instrumentation/botocore/extensions # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
from opentelemetry.instrumentation.botocore.extensions.types import (
_AttributeMapT,
_AwsSdkExtension,
_BotocoreInstrumentorContext,
_BotoResultT,
)
from opentelemetry.semconv._incubating.attributes.aws_attributes import (
AWS_STEP_FUNCTIONS_ACTIVITY_ARN,
AWS_STEP_FUNCTIONS_STATE_MACHINE_ARN,
)
from opentelemetry.trace.span import Span
class _StepFunctionsExtension(_AwsSdkExtension):
@staticmethod
def _set_arn_attributes(source, target, setter_func):
"""Helper to set ARN attributes if they exist in source."""
activity_arn = source.get("activityArn")
if activity_arn:
setter_func(target, AWS_STEP_FUNCTIONS_ACTIVITY_ARN, activity_arn)
state_machine_arn = source.get("stateMachineArn")
if state_machine_arn:
setter_func(target, AWS_STEP_FUNCTIONS_STATE_MACHINE_ARN, state_machine_arn)
def extract_attributes(self, attributes: _AttributeMapT):
self._set_arn_attributes(
self._call_context.params,
attributes,
lambda target, key, value: target.__setitem__(key, value),
)
def on_success(
self,
span: Span,
result: _BotoResultT,
instrumentor_context: _BotocoreInstrumentorContext,
):
self._set_arn_attributes(
result,
span,
lambda target, key, value: target.set_attribute(key, value),
)
sns.py 0000664 0000000 0000000 00000012511 15270700723 0047016 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-botocore/src/opentelemetry/instrumentation/botocore/extensions # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
import abc
import inspect
from collections.abc import MutableMapping
from typing import Any
from opentelemetry.instrumentation.botocore.extensions._messaging import (
inject_propagation_context,
)
from opentelemetry.instrumentation.botocore.extensions.types import (
_AttributeMapT,
_AwsSdkCallContext,
_AwsSdkExtension,
_BotocoreInstrumentorContext,
_BotoResultT,
)
from opentelemetry.semconv._incubating.attributes import messaging_attributes
from opentelemetry.semconv._incubating.attributes.aws_attributes import (
AWS_SNS_TOPIC_ARN,
)
from opentelemetry.semconv.trace import (
MessagingDestinationKindValues,
SpanAttributes,
)
from opentelemetry.trace import SpanKind
from opentelemetry.trace.span import Span
################################################################################
# SNS operations
################################################################################
class _SnsOperation(abc.ABC):
@classmethod
@abc.abstractmethod
def operation_name(cls) -> str:
pass
@classmethod
def span_kind(cls) -> SpanKind:
return SpanKind.CLIENT
@classmethod
def extract_attributes(cls, call_context: _AwsSdkCallContext, attributes: _AttributeMapT):
pass
@classmethod
def before_service_call(cls, call_context: _AwsSdkCallContext, span: Span):
pass
class _OpPublish(_SnsOperation):
_arn_arg_names = ("TopicArn", "TargetArn")
_phone_arg_name = "PhoneNumber"
@classmethod
def operation_name(cls) -> str:
return "Publish"
@classmethod
def span_kind(cls) -> SpanKind:
return SpanKind.PRODUCER
@classmethod
def extract_attributes(cls, call_context: _AwsSdkCallContext, attributes: _AttributeMapT):
span_name, destination_name = cls._extract_destination_name(call_context)
call_context.span_name = f"{span_name} send"
attributes[SpanAttributes.MESSAGING_DESTINATION_KIND] = MessagingDestinationKindValues.TOPIC.value
attributes[SpanAttributes.MESSAGING_DESTINATION] = destination_name
attributes[SpanAttributes.MESSAGING_DESTINATION_NAME] = destination_name
@classmethod
def _extract_destination_name(cls, call_context: _AwsSdkCallContext) -> tuple[str, str]:
arn = cls._extract_input_arn(call_context)
if arn:
return arn.rsplit(":", 1)[-1], arn
if cls._phone_arg_name:
phone_number = call_context.params.get(cls._phone_arg_name)
if phone_number:
# phone number redacted because it's a PII
return "phone_number", "phone_number:**"
return "unknown", "unknown"
@classmethod
def _extract_input_arn(cls, call_context: _AwsSdkCallContext) -> str | None:
for input_arn in cls._arn_arg_names:
arn = call_context.params.get(input_arn)
if arn:
return arn
return None
@classmethod
def before_service_call(cls, call_context: _AwsSdkCallContext, span: Span):
cls._inject_span_into_entry(call_context.params)
@classmethod
def _inject_span_into_entry(cls, entry: MutableMapping[str, Any]):
entry["MessageAttributes"] = inject_propagation_context(entry.get("MessageAttributes"))
class _OpPublishBatch(_OpPublish):
_arn_arg_names = ("TopicArn",)
_phone_arg_name = None
@classmethod
def operation_name(cls) -> str:
return "PublishBatch"
@classmethod
def before_service_call(cls, call_context: _AwsSdkCallContext, span: Span):
for entry in call_context.params.get("PublishBatchRequestEntries", ()):
cls._inject_span_into_entry(entry)
################################################################################
# SNS extension
################################################################################
def _is_operation(op: object) -> bool:
try:
return inspect.isclass(op) and issubclass(op, _SnsOperation) and not inspect.isabstract(op)
except TypeError:
return False
_OPERATION_MAPPING: dict[str, _SnsOperation] = {
op.operation_name(): op for op in globals().values() if _is_operation(op)
}
class _SnsExtension(_AwsSdkExtension):
def __init__(self, call_context: _AwsSdkCallContext):
super().__init__(call_context)
self._op = _OPERATION_MAPPING.get(call_context.operation)
if self._op:
call_context.span_kind = self._op.span_kind()
def extract_attributes(self, attributes: _AttributeMapT):
attributes[messaging_attributes.MESSAGING_SYSTEM] = "aws.sns"
topic_arn = self._call_context.params.get("TopicArn")
if topic_arn:
attributes[AWS_SNS_TOPIC_ARN] = topic_arn
if self._op:
self._op.extract_attributes(self._call_context, attributes)
def before_service_call(self, span: Span, instrumentor_context: _BotocoreInstrumentorContext):
if self._op:
self._op.before_service_call(self._call_context, span)
def on_success(
self,
span: Span,
result: _BotoResultT,
instrumentor_context: _BotocoreInstrumentorContext,
):
if not span.is_recording():
return
topic_arn = result.get("TopicArn")
if topic_arn:
span.set_attribute(AWS_SNS_TOPIC_ARN, topic_arn)
sqs.py 0000664 0000000 0000000 00000004600 15270700723 0047021 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-botocore/src/opentelemetry/instrumentation/botocore/extensions # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
import logging
from opentelemetry.instrumentation.botocore.extensions.types import (
_AttributeMapT,
_AwsSdkExtension,
_BotocoreInstrumentorContext,
_BotoResultT,
)
from opentelemetry.semconv._incubating.attributes import messaging_attributes
from opentelemetry.semconv.trace import SpanAttributes
from opentelemetry.trace.span import Span
_SUPPORTED_OPERATIONS = ["SendMessage", "SendMessageBatch", "ReceiveMessage"]
_logger = logging.getLogger(__name__)
class _SqsExtension(_AwsSdkExtension):
def extract_attributes(self, attributes: _AttributeMapT):
queue_url = self._call_context.params.get("QueueUrl")
if queue_url:
# TODO: update when semantic conventions exist
attributes["aws.queue_url"] = queue_url
attributes[messaging_attributes.MESSAGING_SYSTEM] = "aws.sqs"
attributes[SpanAttributes.MESSAGING_URL] = queue_url
try:
attributes[SpanAttributes.MESSAGING_DESTINATION] = queue_url.split("/")[-1]
except IndexError:
_logger.error(
"Could not extract messaging destination from '%s'",
queue_url,
)
def on_success(
self,
span: Span,
result: _BotoResultT,
instrumentor_context: _BotocoreInstrumentorContext,
):
operation = self._call_context.operation
if operation in _SUPPORTED_OPERATIONS:
try:
if operation == "SendMessage":
span.set_attribute(
messaging_attributes.MESSAGING_MESSAGE_ID,
result.get("MessageId"),
)
elif operation == "SendMessageBatch" and result.get("Successful"):
span.set_attribute(
messaging_attributes.MESSAGING_MESSAGE_ID,
result["Successful"][0]["MessageId"],
)
elif operation == "ReceiveMessage" and result.get("Messages"):
span.set_attribute(
messaging_attributes.MESSAGING_MESSAGE_ID,
result["Messages"][0]["MessageId"],
)
except (IndexError, KeyError):
_logger.error("Could not extract the messaging message ID")
types.py 0000664 0000000 0000000 00000013601 15270700723 0047360 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-botocore/src/opentelemetry/instrumentation/botocore/extensions # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
from __future__ import annotations
import logging
from typing import Any
from opentelemetry._logs import Logger
from opentelemetry.metrics import Instrument, Meter
from opentelemetry.trace import SpanKind
from opentelemetry.trace.span import Span
from opentelemetry.util.types import AttributeValue
_logger = logging.getLogger(__name__)
_BotoClientT = "botocore.client.BaseClient"
_BotoResultT = dict[str, Any]
_BotoClientErrorT = "botocore.exceptions.ClientError"
_OperationParamsT = dict[str, Any]
_AttributeMapT = dict[str, AttributeValue]
class _AwsSdkCallContext:
"""An context object providing information about the invoked AWS service
call.
Args:
service: the AWS service (e.g. s3, lambda, ...) which is called
service_id: the name of the service in proper casing
operation: the called operation (e.g. ListBuckets, Invoke, ...) of the
AWS service.
params: a dict of input parameters passed to the service operation.
region: the AWS region in which the service call is made
endpoint_url: the endpoint which the service operation is calling
api_version: the API version of the called AWS service.
span_name: the name used to create the span.
span_kind: the kind used to create the span.
"""
def __init__(self, client: _BotoClientT, args: tuple[str, dict[str, Any]]):
operation = args[0]
try:
params = args[1]
except (IndexError, TypeError):
_logger.warning("Could not get request params.")
params = {}
boto_meta = client.meta
service_model = boto_meta.service_model
self.service = service_model.service_name.lower()
self.operation = operation
self.params = params
# 'operation' and 'service' are essential for instrumentation.
# for all other attributes we extract them defensively. All of them should
# usually exist unless some future botocore version moved things.
self.region: str | None = self._get_attr(boto_meta, "region_name")
self.endpoint_url: str | None = self._get_attr(boto_meta, "endpoint_url")
self.api_version: str | None = self._get_attr(service_model, "api_version")
# name of the service in proper casing
self.service_id = str(self._get_attr(service_model, "service_id", self.service))
self.span_name = f"{self.service_id}.{self.operation}"
self.span_kind = SpanKind.CLIENT
@staticmethod
def _get_attr(obj, name: str, default=None):
try:
return getattr(obj, name)
except AttributeError:
_logger.warning("Could not get attribute '%s'", name)
return default
class _BotocoreInstrumentorContext:
def __init__(
self,
logger: Logger,
metrics: dict[str, Instrument] | None = None,
):
self.logger = logger
self.metrics = metrics or {}
class _AwsSdkExtension:
def __init__(self, call_context: _AwsSdkCallContext):
self._call_context = call_context
@staticmethod
def tracer_schema_version() -> str:
"""Returns the tracer OTel schema version the extension is following"""
return "1.11.0"
@staticmethod
def event_logger_schema_version() -> str:
"""Returns the event logger OTel schema version the extension is following"""
return "1.30.0"
@staticmethod
def meter_schema_version() -> str:
"""Returns the meter OTel schema version the extension is following"""
return "1.30.0"
def should_trace_service_call(self) -> bool: # pylint:disable=no-self-use
"""Returns if the AWS SDK service call should be traced or not
Extensions might override this function to disable tracing for certain
operations.
"""
return True
def should_end_span_on_exit(self) -> bool: # pylint:disable=no-self-use
"""Returns if the span should be closed automatically on exit
Extensions might override this function to disable automatic closing
of the span if they need to close it at a later time themselves.
"""
return True
def setup_metrics(self, meter: Meter, metrics: dict[str, Instrument]):
"""Callback which gets invoked to setup metrics.
Extensions might override this function to add to the metrics dictionary all the metrics
they want to receive later in _BotocoreInstrumentorContext."""
def extract_attributes(self, attributes: _AttributeMapT):
"""Callback which gets invoked before the span is created.
Extensions might override this function to extract additional attributes.
"""
def before_service_call(self, span: Span, instrumentor_context: _BotocoreInstrumentorContext):
"""Callback which gets invoked after the span is created but before the
AWS SDK service is called.
Extensions might override this function e.g. for injecting the span into
a carrier.
"""
def on_success(
self,
span: Span,
result: _BotoResultT,
instrumentor_context: _BotocoreInstrumentorContext,
):
"""Callback that gets invoked when the AWS SDK call returns
successfully.
Extensions might override this function e.g. to extract and set response
attributes on the span.
"""
def on_error(
self,
span: Span,
exception: _BotoClientErrorT,
instrumentor_context: _BotocoreInstrumentorContext,
):
"""Callback that gets invoked when the AWS SDK service call raises a
ClientError.
"""
def after_service_call(self, instrumentor_context: _BotocoreInstrumentorContext):
"""Callback that gets invoked after the AWS SDK service was called.
Extensions might override this function to do some cleanup tasks.
"""
package.py 0000664 0000000 0000000 00000000410 15270700723 0045402 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-botocore/src/opentelemetry/instrumentation/botocore # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
_instruments_botocore = ("botocore~=1.0",)
_instruments_aiobotocore = ("aiobotocore>=2.0,<4.0",)
_instruments = ()
_instruments_any = (*_instruments_botocore, *_instruments_aiobotocore)
utils.py 0000664 0000000 0000000 00000002062 15270700723 0045154 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-botocore/src/opentelemetry/instrumentation/botocore # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
from __future__ import annotations
import logging
from collections.abc import Callable
from urllib.parse import urlparse
from opentelemetry.semconv._incubating.attributes import (
server_attributes as ServerAttributes,
)
from opentelemetry.util.types import AttributeValue
_logger = logging.getLogger(__name__)
def get_server_attributes(endpoint_url: str) -> dict[str, AttributeValue]:
"""Extract server.* attributes from AWS endpoint URL."""
parsed = urlparse(endpoint_url)
attributes = {}
if parsed.hostname:
attributes[ServerAttributes.SERVER_ADDRESS] = parsed.hostname
attributes[ServerAttributes.SERVER_PORT] = parsed.port or 443
return attributes
def _safe_invoke(function: Callable, *args):
function_name = ""
try:
function_name = function.__name__
function(*args)
except Exception as ex: # pylint:disable=broad-except
_logger.error("Error when invoking function '%s'", function_name, exc_info=ex)
version.py 0000664 0000000 0000000 00000000144 15270700723 0045500 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-botocore/src/opentelemetry/instrumentation/botocore # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
__version__ = "0.66b2"
test-requirements-0-wrapt1.txt 0000664 0000000 0000000 00000000051 15270700723 0040506 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-botocore -r test-requirements-0.txt
wrapt==1.17.3
test-requirements-0-wrapt2.txt 0000664 0000000 0000000 00000000050 15270700723 0040506 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-botocore -r test-requirements-0.txt
wrapt==2.1.2
test-requirements-0.txt 0000664 0000000 0000000 00000001313 15270700723 0037274 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-botocore asgiref==3.8.1
aws-xray-sdk==2.12.1
boto3==1.28.80
botocore==1.31.80
certifi==2024.7.4
cffi==1.17.0
charset-normalizer==3.3.2
cryptography==43.0.1
docker==7.0.0
idna==3.7
iniconfig==2.0.0
Jinja2==3.1.6
jmespath==1.0.1
MarkupSafe==2.1.5
moto==5.1.11
packaging==24.0
pluggy==1.6.0
py-cpuinfo==9.0.0
pycparser==2.21
pytest==7.4.4
pytest-vcr==1.0.2
python-dateutil==2.8.2
pytz==2024.1
PyYAML==6.0.1
requests==2.33.1
responses==0.25.0
s3transfer==0.7.0
six==1.16.0
tomli==2.0.1
typing_extensions==4.12.2
urllib3==1.26.19
vcrpy==8.3.0
Werkzeug==3.0.6
xmltodict==0.13.0
zipp==3.19.2
-e opentelemetry-instrumentation
-e propagator/opentelemetry-propagator-aws-xray
-e instrumentation/opentelemetry-instrumentation-botocore
test-requirements-1-wrapt1.txt 0000664 0000000 0000000 00000000051 15270700723 0040507 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-botocore -r test-requirements-1.txt
wrapt==1.17.3
test-requirements-1-wrapt2.txt 0000664 0000000 0000000 00000000050 15270700723 0040507 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-botocore -r test-requirements-1.txt
wrapt==2.1.2
test-requirements-1.txt 0000664 0000000 0000000 00000001312 15270700723 0037274 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-botocore asgiref==3.8.1
aws-xray-sdk==2.12.1
boto3==1.43.0
botocore==1.43.0
certifi==2024.7.4
cffi==1.17.0
charset-normalizer==3.3.2
cryptography==43.0.1
docker==7.0.0
idna==3.7
iniconfig==2.0.0
Jinja2==3.1.6
jmespath==1.0.1
MarkupSafe==2.1.5
moto==5.1.11
packaging==24.0
pluggy==1.6.0
py-cpuinfo==9.0.0
pycparser==2.21
pytest==7.4.4
pytest-vcr==1.0.2
python-dateutil==2.8.2
pytz==2024.1
PyYAML==6.0.1
requests==2.33.1
responses==0.25.0
s3transfer==0.17.0
six==1.16.0
tomli==2.0.1
typing_extensions==4.12.2
urllib3==1.26.19
vcrpy==8.3.0
Werkzeug==3.0.6
xmltodict==0.13.0
zipp==3.19.2
-e opentelemetry-instrumentation
-e propagator/opentelemetry-propagator-aws-xray
-e instrumentation/opentelemetry-instrumentation-botocore
test-requirements-2.txt 0000664 0000000 0000000 00000001375 15270700723 0037306 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-botocore asgiref==3.8.1
aws-xray-sdk==2.12.1
boto3==1.29.4
botocore==1.32.4
aiobotocore==2.8.0
certifi==2024.7.4
cffi==1.17.0
charset-normalizer==3.3.2
cryptography==43.0.1
Deprecated==1.2.14
docker==7.0.0
idna==3.7
iniconfig==2.0.0
Jinja2==3.1.6
jmespath==1.0.1
MarkupSafe==2.1.5
moto==5.1.11
packaging==24.0
pluggy==1.5.0
py-cpuinfo==9.0.0
pycparser==2.21
pytest==7.4.4
pytest-vcr==1.0.2
python-dateutil==2.8.2
pytz==2024.1
PyYAML==6.0.1
requests==2.33.1
responses==0.25.0
s3transfer==0.7.0
six==1.16.0
tomli==2.0.1
typing_extensions==4.12.2
urllib3==1.26.19
vcrpy==8.3.0
Werkzeug==3.0.6
wrapt==1.16.0
xmltodict==0.13.0
zipp==3.19.2
-e opentelemetry-instrumentation
-e propagator/opentelemetry-propagator-aws-xray
-e instrumentation/opentelemetry-instrumentation-botocore
test-requirements-3.txt 0000664 0000000 0000000 00000001376 15270700723 0037310 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-botocore asgiref==3.8.1
aws-xray-sdk==2.12.1
boto3==1.43.0
botocore==1.43.0
aiobotocore==3.7.0
certifi==2024.7.4
cffi==1.17.0
charset-normalizer==3.3.2
cryptography==43.0.1
Deprecated==1.2.14
docker==7.0.0
idna==3.7
iniconfig==2.0.0
Jinja2==3.1.6
jmespath==1.0.1
MarkupSafe==2.1.5
moto==5.1.11
packaging==24.0
pluggy==1.5.0
py-cpuinfo==9.0.0
pycparser==2.21
pytest==7.4.4
pytest-vcr==1.0.2
python-dateutil==2.8.2
pytz==2024.1
PyYAML==6.0.1
requests==2.33.1
responses==0.25.0
s3transfer==0.17.0
six==1.16.0
tomli==2.0.1
typing_extensions==4.15.0
urllib3==1.26.19
vcrpy==8.3.0
Werkzeug==3.0.6
wrapt==1.16.0
xmltodict==0.13.0
zipp==3.19.2
-e opentelemetry-instrumentation
-e propagator/opentelemetry-propagator-aws-xray
-e instrumentation/opentelemetry-instrumentation-botocore
opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-botocore/tests/ 0000775 0000000 0000000 00000000000 15270700723 0034121 5 ustar 00root root 0000000 0000000 README.md 0000664 0000000 0000000 00000001135 15270700723 0035321 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-botocore/tests ## Recording calls
If you need to record calls you may need to export authentication variables and the default region as environment
variables in order to have the code work properly. The recorded tests assume the region us-east-1, so ensure that
AWS_DEFAULT_REGION is set accordingly when recording new calls.
Since tox blocks environment variables by default you need to override its configuration to let them pass:
```
export TOX_OVERRIDE=testenv.pass_env=AWS_ACCESS_KEY_ID,AWS_SECRET_ACCESS_KEY,AWS_SESSION_TOKEN,AWS_DEFAULT_REGION
```
We are not adding it to tox.ini because of security concerns.
__init__.py 0000664 0000000 0000000 00000000000 15270700723 0036141 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-botocore/tests bedrock_utils.py 0000664 0000000 0000000 00000032333 15270700723 0037251 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-botocore/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
from __future__ import annotations
import json
import math
from typing import Any
from botocore.response import StreamingBody
from opentelemetry.instrumentation.botocore.extensions.bedrock import (
_GEN_AI_CLIENT_OPERATION_DURATION_BUCKETS,
_GEN_AI_CLIENT_TOKEN_USAGE_BUCKETS,
)
from opentelemetry.sdk.metrics._internal.point import ResourceMetrics
from opentelemetry.sdk.trace import ReadableSpan
from opentelemetry.semconv._incubating.attributes import (
gen_ai_attributes as GenAIAttributes,
)
from opentelemetry.semconv._incubating.attributes import (
server_attributes as ServerAttributes,
)
from opentelemetry.semconv._incubating.attributes.error_attributes import (
ERROR_TYPE,
)
from opentelemetry.semconv._incubating.metrics.gen_ai_metrics import (
GEN_AI_CLIENT_OPERATION_DURATION,
GEN_AI_CLIENT_TOKEN_USAGE,
)
# pylint: disable=too-many-branches, too-many-locals, too-many-statements
def assert_completion_attributes_from_streaming_body(
span: ReadableSpan,
request_model: str,
response: StreamingBody | None,
operation_name: str = "chat",
request_top_p: int | None = None,
request_temperature: int | None = None,
request_max_tokens: int | None = None,
request_stop_sequences: list[str] | None = None,
):
input_tokens = None
output_tokens = None
finish_reason = None
request_prompt = "Say this is a test"
if response is not None:
original_body = response["body"]
body_content = original_body.read()
response = json.loads(body_content.decode("utf-8"))
assert response
if "amazon.titan" in request_model:
input_tokens = response.get("inputTextTokenCount")
results = response.get("results")
if results:
first_result = results[0]
output_tokens = first_result.get("tokenCount")
finish_reason = (first_result["completionReason"],)
elif "amazon.nova" in request_model:
if usage := response.get("usage"):
input_tokens = usage["inputTokens"]
output_tokens = usage["outputTokens"]
else:
input_tokens, output_tokens = None, None
if "stopReason" in response:
finish_reason = (response["stopReason"],)
else:
finish_reason = None
elif "anthropic.claude" in request_model:
if usage := response.get("usage"):
input_tokens = usage["input_tokens"]
output_tokens = usage["output_tokens"]
else:
input_tokens, output_tokens = None, None
if "stop_reason" in response:
finish_reason = (response["stop_reason"],)
else:
finish_reason = None
elif "cohere.command-r" in request_model:
input_tokens = math.ceil(len(request_prompt) / 6)
text = response.get("text")
if text:
output_tokens = math.ceil(len(text) / 6)
finish_reason = (response["finish_reason"],)
elif "cohere.command" in request_model:
input_tokens = math.ceil(len(request_prompt) / 6)
generations = response.get("generations")
if generations:
first_generation = generations[0]
output_tokens = math.ceil(len(first_generation["text"]) / 6)
finish_reason = (first_generation["finish_reason"],)
elif "meta.llama" in request_model:
if "prompt_token_count" in response:
input_tokens = response.get("prompt_token_count")
if "generation_token_count" in response:
output_tokens = response.get("generation_token_count")
if "stop_reason" in response:
finish_reason = (response["stop_reason"],)
elif "mistral.mistral" in request_model:
input_tokens = math.ceil(len(request_prompt) / 6)
outputs = response.get("outputs")
if outputs:
first_output = outputs[0]
output_tokens = math.ceil(len(first_output["text"]) / 6)
finish_reason = (first_output["stop_reason"],)
return assert_all_attributes(
span,
request_model,
input_tokens,
output_tokens,
finish_reason,
operation_name,
request_top_p,
request_temperature,
request_max_tokens,
tuple(request_stop_sequences) if request_stop_sequences is not None else request_stop_sequences,
)
def assert_converse_completion_attributes(
span: ReadableSpan,
request_model: str,
response: dict[str, Any] | None,
operation_name: str = "chat",
request_top_p: int | None = None,
request_temperature: int | None = None,
request_max_tokens: int | None = None,
request_stop_sequences: list[str] | None = None,
):
if usage := (response and response.get("usage")):
input_tokens = usage["inputTokens"]
output_tokens = usage["outputTokens"]
else:
input_tokens, output_tokens = None, None
if response and "stopReason" in response:
finish_reason = (response["stopReason"],)
else:
finish_reason = None
return assert_all_attributes(
span,
request_model,
input_tokens,
output_tokens,
finish_reason,
operation_name,
request_top_p,
request_temperature,
request_max_tokens,
tuple(request_stop_sequences) if request_stop_sequences is not None else request_stop_sequences,
)
def assert_stream_completion_attributes(
span: ReadableSpan,
request_model: str,
input_tokens: int | None = None,
output_tokens: int | None = None,
finish_reason: tuple[str] | None = None,
operation_name: str = "chat",
request_top_p: int | None = None,
request_temperature: int | None = None,
request_max_tokens: int | None = None,
request_stop_sequences: list[str] | None = None,
):
return assert_all_attributes(
span,
request_model,
input_tokens,
output_tokens,
finish_reason,
operation_name,
request_top_p,
request_temperature,
request_max_tokens,
tuple(request_stop_sequences) if request_stop_sequences is not None else request_stop_sequences,
)
def assert_equal_or_not_present(value, attribute_name, span):
if value is not None:
assert attribute_name in span.attributes
assert value == span.attributes[attribute_name], span.attributes[attribute_name]
else:
assert attribute_name not in span.attributes, attribute_name
def assert_all_attributes(
span: ReadableSpan,
request_model: str,
input_tokens: int | None = None,
output_tokens: int | None = None,
finish_reason: tuple[str] | None = None,
operation_name: str = "chat",
request_top_p: int | None = None,
request_temperature: int | None = None,
request_max_tokens: int | None = None,
request_stop_sequences: tuple[str] | None = None,
server_address: str = "bedrock-runtime.us-east-1.amazonaws.com",
server_port: int = 443,
):
assert span.name == f"{operation_name} {request_model}"
assert operation_name == span.attributes[GenAIAttributes.GEN_AI_OPERATION_NAME]
assert GenAIAttributes.GenAiSystemValues.AWS_BEDROCK.value == span.attributes[GenAIAttributes.GEN_AI_SYSTEM]
assert request_model == span.attributes[GenAIAttributes.GEN_AI_REQUEST_MODEL]
assert server_address == span.attributes[ServerAttributes.SERVER_ADDRESS]
assert server_port == span.attributes[ServerAttributes.SERVER_PORT]
assert_equal_or_not_present(input_tokens, GenAIAttributes.GEN_AI_USAGE_INPUT_TOKENS, span)
assert_equal_or_not_present(output_tokens, GenAIAttributes.GEN_AI_USAGE_OUTPUT_TOKENS, span)
assert_equal_or_not_present(finish_reason, GenAIAttributes.GEN_AI_RESPONSE_FINISH_REASONS, span)
assert_equal_or_not_present(request_top_p, GenAIAttributes.GEN_AI_REQUEST_TOP_P, span)
assert_equal_or_not_present(request_temperature, GenAIAttributes.GEN_AI_REQUEST_TEMPERATURE, span)
assert_equal_or_not_present(request_max_tokens, GenAIAttributes.GEN_AI_REQUEST_MAX_TOKENS, span)
assert_equal_or_not_present(
request_stop_sequences,
GenAIAttributes.GEN_AI_REQUEST_STOP_SEQUENCES,
span,
)
def remove_none_values(body):
result = {}
for key, value in body.items():
if value is None:
continue
if isinstance(value, dict):
result[key] = remove_none_values(value)
else:
result[key] = value
return result
def assert_log_parent(log, span):
if span:
assert log.log_record.trace_id == span.get_span_context().trace_id, (
f"{span.get_span_context().trace_id} does not equal {log.log_record.trace_id}"
)
assert log.log_record.span_id == span.get_span_context().span_id
assert log.log_record.trace_flags == span.get_span_context().trace_flags
def assert_message_in_logs(log, event_name, expected_content, parent_span):
assert log.log_record.event_name == event_name, log.log_record.event_name
assert (
log.log_record.attributes[GenAIAttributes.GEN_AI_SYSTEM] == GenAIAttributes.GenAiSystemValues.AWS_BEDROCK.value
)
if not expected_content:
assert not log.log_record.body
else:
assert log.log_record.body
assert dict(log.log_record.body) == remove_none_values(expected_content), dict(log.log_record.body)
assert_log_parent(log, parent_span)
def assert_all_metric_attributes(
data_point,
operation_name: str,
model: str,
error_type: str | None = None,
server_address: str = "bedrock-runtime.us-east-1.amazonaws.com",
server_port: int = 443,
):
assert GenAIAttributes.GEN_AI_OPERATION_NAME in data_point.attributes
assert data_point.attributes[GenAIAttributes.GEN_AI_OPERATION_NAME] == operation_name
assert GenAIAttributes.GEN_AI_SYSTEM in data_point.attributes
assert data_point.attributes[GenAIAttributes.GEN_AI_SYSTEM] == GenAIAttributes.GenAiSystemValues.AWS_BEDROCK.value
assert GenAIAttributes.GEN_AI_REQUEST_MODEL in data_point.attributes
assert data_point.attributes[GenAIAttributes.GEN_AI_REQUEST_MODEL] == model
assert ServerAttributes.SERVER_ADDRESS in data_point.attributes
assert data_point.attributes[ServerAttributes.SERVER_ADDRESS] == server_address
assert ServerAttributes.SERVER_PORT in data_point.attributes
assert data_point.attributes[ServerAttributes.SERVER_PORT] == server_port
if error_type is not None:
assert ERROR_TYPE in data_point.attributes
assert data_point.attributes[ERROR_TYPE] == error_type
else:
assert ERROR_TYPE not in data_point.attributes
def assert_metrics(
resource_metrics: ResourceMetrics,
operation_name: str,
model: str,
input_tokens: float | None = None,
output_tokens: float | None = None,
error_type: str | None = None,
):
assert len(resource_metrics) == 1
metric_data = resource_metrics[0].scope_metrics[0].metrics
if input_tokens is not None or output_tokens is not None:
expected_metrics_data_len = 2
else:
expected_metrics_data_len = 1
assert len(metric_data) == expected_metrics_data_len
duration_metric = next(
(m for m in metric_data if m.name == GEN_AI_CLIENT_OPERATION_DURATION),
None,
)
assert duration_metric is not None
duration_point = duration_metric.data.data_points[0]
assert duration_point.sum > 0
assert_all_metric_attributes(duration_point, operation_name, model, error_type)
assert duration_point.explicit_bounds == tuple(_GEN_AI_CLIENT_OPERATION_DURATION_BUCKETS)
if input_tokens is not None:
token_usage_metric = next(
(m for m in metric_data if m.name == GEN_AI_CLIENT_TOKEN_USAGE),
None,
)
assert token_usage_metric is not None
input_token_usage = next(
(
d
for d in token_usage_metric.data.data_points
if d.attributes[GenAIAttributes.GEN_AI_TOKEN_TYPE] == GenAIAttributes.GenAiTokenTypeValues.INPUT.value
),
None,
)
assert input_token_usage is not None
assert input_token_usage.sum == input_tokens
assert input_token_usage.explicit_bounds == tuple(_GEN_AI_CLIENT_TOKEN_USAGE_BUCKETS)
assert_all_metric_attributes(input_token_usage, operation_name, model)
if output_tokens is not None:
token_usage_metric = next(
(m for m in metric_data if m.name == GEN_AI_CLIENT_TOKEN_USAGE),
None,
)
assert token_usage_metric is not None
output_token_usage = next(
(
d
for d in token_usage_metric.data.data_points
if d.attributes[GenAIAttributes.GEN_AI_TOKEN_TYPE]
== GenAIAttributes.GenAiTokenTypeValues.COMPLETION.value
),
None,
)
assert output_token_usage is not None
assert output_token_usage.sum == output_tokens
assert output_token_usage.explicit_bounds == tuple(_GEN_AI_CLIENT_TOKEN_USAGE_BUCKETS)
assert_all_metric_attributes(output_token_usage, operation_name, model)
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Connection:
- keep-alive
Content-Type:
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Date:
- Wed, 26 Feb 2025 11:03:49 GMT
Set-Cookie: test_set_cookie
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message: OK
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body: |-
{
"messages": [
{
"role": "user",
"content": [
{
"text": "What is the weather in Seattle and San Francisco today?"
}
]
},
{
"content": [
{
"text": " The User has asked for the current weather in two different cities: Seattle and San Francisco. To provide this information, I will need to use the `get_current_weather` tool twice, once for each city. \n"
},
{
"toolUse": {
"toolUseId": "tooluse_IIpMFTgaRVGyI7x4sJfKzQ",
"name": "get_current_weather",
"input": {
"location": "Seattle"
}
}
},
{
"toolUse": {
"toolUseId": "tooluse_KZPBYYUtS72Um_JDI8hTow",
"name": "get_current_weather",
"input": {
"location": "San Francisco"
}
}
}
],
"role": "assistant"
},
{
"role": "user",
"content": [
{
"toolResult": {
"content": [
{
"json": {
"weather": "50 degrees and raining"
}
}
],
"toolUseId": "tooluse_IIpMFTgaRVGyI7x4sJfKzQ"
}
},
{
"toolResult": {
"content": [
{
"json": {
"weather": "70 degrees and sunny"
}
}
],
"toolUseId": "tooluse_KZPBYYUtS72Um_JDI8hTow"
}
}
]
}
],
"toolConfig": {
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{
"toolSpec": {
"name": "get_current_weather",
"description": "Get the current weather in a given location.",
"inputSchema": {
"json": {
"type": "object",
"properties": {
"location": {
"type": "string",
"description": "The name of the city"
}
},
"required": [
"location"
]
}
}
}
}
]
}
}
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X-Amz-Date:
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X-Amz-Security-Token:
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X-Amzn-Trace-Id:
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authorization:
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"text": "Use the get_cities_list tool to provide exactly 10 popular tourist cities in Japan. Call the tool with a cities array containing: Tokyo, Osaka, Kyoto, Hiroshima, Nara, Yokohama, Sapporo, Fukuoka, Sendai, and Nagoya"
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status:
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message: OK
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{
"messages": [
{
"role": "user",
"content": [
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}
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{
"toolSpec": {
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"type": "object",
"properties": {
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"type": "string",
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}
},
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]
}
}
}
}
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}
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headers:
Connection:
- keep-alive
Content-Type:
- application/vnd.amazon.eventstream
Date:
- Wed, 26 Feb 2025 10:27:39 GMT
Set-Cookie: test_set_cookie
Transfer-Encoding:
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x-amzn-RequestId:
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status:
code: 200
message: OK
- request:
body: |-
{
"messages": [
{
"role": "user",
"content": [
{
"text": "What is the weather in Seattle and San Francisco today?"
}
]
},
{
"content": [
{
"text": " The User has asked for the current weather in two different cities: Seattle and San Francisco. To provide this information, I will use the `get_current_weather` tool for each city. I need to call the tool twice, once for each city.\n"
},
{
"toolUse": {
"toolUseId": "tooluse_JZ11QcxSQ3m3xacMQKVIKw",
"name": "get_current_weather",
"input": {
"location": "Seattle"
}
}
},
{
"toolUse": {
"toolUseId": "tooluse_-hxBEEwGRc-VQqC2i7SFqg",
"name": "get_current_weather",
"input": {
"location": "San Francisco"
}
}
}
],
"role": "assistant"
},
{
"role": "user",
"content": [
{
"toolResult": {
"content": [
{
"json": {
"weather": "50 degrees and raining"
}
}
],
"toolUseId": "tooluse_JZ11QcxSQ3m3xacMQKVIKw"
}
},
{
"toolResult": {
"content": [
{
"json": {
"weather": "70 degrees and sunny"
}
}
],
"toolUseId": "tooluse_-hxBEEwGRc-VQqC2i7SFqg"
}
}
]
}
],
"toolConfig": {
"tools": [
{
"toolSpec": {
"name": "get_current_weather",
"description": "Get the current weather in a given location.",
"inputSchema": {
"json": {
"type": "object",
"properties": {
"location": {
"type": "string",
"description": "The name of the city"
}
},
"required": [
"location"
]
}
}
}
}
]
}
}
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lang/python#3.10.12 md/pyimpl#CPython cfg/retry-mode#legacy Botocore/1.35.56
X-Amz-Date:
- 20250226T102739Z
X-Amz-Security-Token:
- test_aws_security_token
X-Amzn-Trace-Id:
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amz-sdk-invocation-id:
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amz-sdk-request:
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authorization:
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headers:
Connection:
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Content-Type:
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Date:
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Set-Cookie: test_set_cookie
Transfer-Encoding:
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X-Amzn-Bedrock-Content-Type:
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x-amzn-RequestId:
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status:
code: 200
message: OK
version: 1
test_invoke_model_with_response_stream_no_content_different_events[amazon.nova].yaml 0000664 0000000 0000000 00000023445 15270700723 0057272 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-botocore/tests/cassettes interactions:
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body: |-
{
"messages": [
{
"role": "user",
"content": [
{
"text": "Say this is a test"
}
]
},
{
"role": "assistant",
"content": [
{
"text": "This is a test"
}
]
},
{
"role": "user",
"content": [
{
"text": "Say again this is a test"
}
]
}
],
"inferenceConfig": {
"max_new_tokens": 10
},
"schemaVersion": "messages-v1",
"system": [
{
"text": "You are a friendly model"
}
]
}
headers:
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User-Agent:
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lang/python#3.10.12 md/pyimpl#CPython cfg/retry-mode#legacy Botocore/1.35.56
X-Amz-Date:
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X-Amz-Security-Token:
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X-Amzn-Trace-Id:
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amz-sdk-invocation-id:
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amz-sdk-request:
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authorization:
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method: POST
uri: https://bedrock-runtime.us-east-1.amazonaws.com/model/amazon.nova-micro-v1%3A0/invoke-with-response-stream
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Connection:
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Content-Type:
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Date:
- Fri, 28 Mar 2025 09:55:46 GMT
Set-Cookie: test_set_cookie
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message: OK
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body: |-
{
"messages": [
{
"role": "user",
"content": [
{
"text": "What is the weather in Seattle and San Francisco today? Please give one tool call for Seattle and one for San Francisco"
}
]
},
{
"role": "assistant",
"content": [
{
"text": " The User has requested the current weather in two different locations: Seattle and San Francisco. I can use the \"get_current_weather\" tool to obtain this information. I will make two separate tool calls, one for each location.\n"
},
{
"toolUse": {
"toolUseId": "d899da89-5a67-4af2-aa54-54f6d2aadd40",
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}
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{
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"input": {
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}
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{
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"content": [
{
"toolResult": {
"toolUseId": "d899da89-5a67-4af2-aa54-54f6d2aadd40",
"content": [
{
"json": {
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}
}
]
}
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{
"toolResult": {
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}
}
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}
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"properties": {
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}
}
]
}
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X-Amz-Date:
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headers:
Connection:
- keep-alive
Content-Type:
- application/vnd.amazon.eventstream
Date:
- Tue, 25 Mar 2025 16:34:59 GMT
Set-Cookie: test_set_cookie
Transfer-Encoding:
- chunked
X-Amzn-Bedrock-Content-Type:
- application/json
x-amzn-RequestId:
- b9ea026a-ac98-4d87-9352-99984599e41f
status:
code: 200
message: OK
- request:
body: |-
{
"messages": [
{
"role": "user",
"content": [
{
"text": "What is the weather in Seattle and San Francisco today? Please give one tool call for Seattle and one for San Francisco",
"type": "text"
}
]
},
{
"role": "assistant",
"content": [
{
"type": "text",
"text": "Certainly! I'll use the get_current_weather function to check the weather for both Seattle and San Francisco. I'll make two separate tool calls within the same function calls block."
},
{
"type": "tool_use",
"id": "toolu_bdrk_01Rn7Cbar6a4S7we7h6iUwpM",
"name": "get_current_weather",
"input": {
"location": "Seattle"
}
},
{
"type": "tool_use",
"id": "toolu_bdrk_01MwXis2KpuvHLfK1VMtyJ3p",
"name": "get_current_weather",
"input": {
"location": "San Francisco"
}
}
]
},
{
"role": "user",
"content": [
{
"type": "tool_result",
"tool_use_id": "toolu_bdrk_01Rn7Cbar6a4S7we7h6iUwpM",
"content": "50 degrees and raining"
},
{
"type": "tool_result",
"tool_use_id": "toolu_bdrk_01MwXis2KpuvHLfK1VMtyJ3p",
"content": "70 degrees and sunny"
}
]
}
],
"anthropic_version": "bedrock-2023-05-31",
"tools": [
{
"name": "get_current_weather",
"description": "Get the current weather in a given location.",
"input_schema": {
"type": "object",
"properties": {
"location": {
"type": "string",
"description": "The name of the city"
}
},
"required": [
"location"
]
}
}
],
"max_tokens": 1000
}
headers:
Content-Length:
- '1291'
User-Agent:
- Boto3/1.35.56 md/Botocore#1.35.56 ua/2.0 os/linux#6.1.0-1034-oem md/arch#x86_64
lang/python#3.10.12 md/pyimpl#CPython cfg/retry-mode#legacy Botocore/1.35.56
X-Amz-Date:
- 20250325T163502Z
X-Amz-Security-Token:
- test_aws_security_token
X-Amzn-Trace-Id:
- Root=1-e42f5da2-f049566b669ca481c0e86624;Parent=1bdd6579c05809f1;Sampled=1
amz-sdk-invocation-id:
- e8800abb-49e8-4f23-8cf1-b0bc695790ff
amz-sdk-request:
- attempt=1
authorization:
- Bearer test_aws_authorization
method: POST
uri: https://bedrock-runtime.us-east-1.amazonaws.com/model/us.anthropic.claude-3-5-sonnet-20240620-v1%3A0/invoke-with-response-stream
response:
body:
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headers:
Connection:
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Content-Type:
- application/vnd.amazon.eventstream
Date:
- Thu, 06 Feb 2025 05:12:43 GMT
Set-Cookie: test_set_cookie
Transfer-Encoding:
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X-Amzn-Bedrock-Content-Type:
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x-amzn-RequestId:
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status:
code: 200
message: OK
version: 1
test_invoke_model_with_response_stream_with_content_different_events[amazon.nova].yaml 0000664 0000000 0000000 00000023167 15270700723 0057632 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-botocore/tests/cassettes interactions:
- request:
body: |-
{
"messages": [
{
"role": "user",
"content": [
{
"text": "Say this is a test"
}
]
},
{
"role": "assistant",
"content": [
{
"text": "This is a test"
}
]
},
{
"role": "user",
"content": [
{
"text": "Say again this is a test"
}
]
}
],
"inferenceConfig": {
"max_new_tokens": 10
},
"schemaVersion": "messages-v1",
"system": [
{
"text": "You are a friendly model"
}
]
}
headers:
Content-Length:
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User-Agent:
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lang/python#3.10.12 md/pyimpl#CPython cfg/retry-mode#legacy Botocore/1.35.56
X-Amz-Date:
- 20250213T141142Z
X-Amz-Security-Token:
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X-Amzn-Trace-Id:
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amz-sdk-invocation-id:
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amz-sdk-request:
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authorization:
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method: POST
uri: https://bedrock-runtime.us-east-1.amazonaws.com/model/amazon.nova-micro-v1%3A0/invoke-with-response-stream
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Date:
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{
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"content": [
{
"text": "What is the weather in Seattle and San Francisco today? Please give one tool call for Seattle and one for San Francisco"
}
]
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{
"text": " The User has requested the current weather in Seattle and San Francisco. I need to use the \"get_current_weather\" tool for each city separately. I will make two tool calls, one for each city.\n"
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Date:
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x-amzn-RequestId:
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status:
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message: OK
version: 1
test_invoke_model_with_response_stream_with_content_tool_call[anthropic.claude].yaml 0000664 0000000 0000000 00000073444 15270700723 0057247 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-botocore/tests/cassettes interactions:
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body: |-
{
"messages": [
{
"role": "user",
"content": [
{
"text": "What is the weather in Seattle and San Francisco today? Please give one tool call for Seattle and one for San Francisco",
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}
]
}
],
"anthropic_version": "bedrock-2023-05-31",
"tools": [
{
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"description": "Get the current weather in a given location.",
"input_schema": {
"type": "object",
"properties": {
"location": {
"type": "string",
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}
},
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}
],
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X-Amz-Date:
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X-Amz-Security-Token:
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uri: https://bedrock-runtime.us-east-1.amazonaws.com/model/us.anthropic.claude-3-5-sonnet-20240620-v1%3A0/invoke-with-response-stream
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headers:
Connection:
- keep-alive
Content-Type:
- application/vnd.amazon.eventstream
Date:
- Tue, 25 Mar 2025 16:34:35 GMT
Set-Cookie: test_set_cookie
Transfer-Encoding:
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message: OK
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body: |-
{
"messages": [
{
"role": "user",
"content": [
{
"text": "What is the weather in Seattle and San Francisco today? Please give one tool call for Seattle and one for San Francisco",
"type": "text"
}
]
},
{
"role": "assistant",
"content": [
{
"type": "text",
"text": "Certainly! I'll use the get_current_weather function to check the weather for both Seattle and San Francisco. I'll make two separate function calls within the same block for these cities."
},
{
"type": "tool_use",
"id": "toolu_bdrk_01KatiGijVFb9yuMPcnVk38e",
"name": "get_current_weather",
"input": {
"location": "Seattle"
}
},
{
"type": "tool_use",
"id": "toolu_bdrk_01Tzb35EydKHWz4UZP3puTbF",
"name": "get_current_weather",
"input": {
"location": "San Francisco"
}
}
]
},
{
"role": "user",
"content": [
{
"type": "tool_result",
"tool_use_id": "toolu_bdrk_01KatiGijVFb9yuMPcnVk38e",
"content": "50 degrees and raining"
},
{
"type": "tool_result",
"tool_use_id": "toolu_bdrk_01Tzb35EydKHWz4UZP3puTbF",
"content": "70 degrees and sunny"
}
]
}
],
"anthropic_version": "bedrock-2023-05-31",
"tools": [
{
"name": "get_current_weather",
"description": "Get the current weather in a given location.",
"input_schema": {
"type": "object",
"properties": {
"location": {
"type": "string",
"description": "The name of the city"
}
},
"required": [
"location"
]
}
}
],
"max_tokens": 1000
}
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X-Amz-Date:
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X-Amzn-Trace-Id:
- Root=1-feef9d11-6a09175d24533ea9968f07ff;Parent=952177b027cf0daa;Sampled=1
amz-sdk-invocation-id:
- 5ac7874b-78a1-4e44-8fa5-7afeabdc1343
amz-sdk-request:
- attempt=1
authorization:
- Bearer test_aws_authorization
method: POST
uri: https://bedrock-runtime.us-east-1.amazonaws.com/model/us.anthropic.claude-3-5-sonnet-20240620-v1%3A0/invoke-with-response-stream
response:
body:
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RUZHSElKS0xNTk8ifQgFpq0=
headers:
Connection:
- keep-alive
Content-Type:
- application/vnd.amazon.eventstream
Date:
- Tue, 25 Mar 2025 16:34:38 GMT
Set-Cookie: test_set_cookie
Transfer-Encoding:
- chunked
X-Amzn-Bedrock-Content-Type:
- application/json
x-amzn-RequestId:
- 8376cb65-4e45-4f96-a8fc-31cefffb8ca6
status:
code: 200
message: OK
version: 1
conftest.py 0000664 0000000 0000000 00000015365 15270700723 0036253 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-botocore/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
"""Unit tests configuration module."""
import json
import os
import boto3
import pytest
import yaml
from opentelemetry.instrumentation.botocore import BotocoreInstrumentor
from opentelemetry.instrumentation.botocore.environment_variables import (
OTEL_INSTRUMENTATION_GENAI_CAPTURE_MESSAGE_CONTENT,
)
from opentelemetry.sdk._logs import LoggerProvider
from opentelemetry.sdk._logs.export import (
InMemoryLogRecordExporter,
SimpleLogRecordProcessor,
)
from opentelemetry.sdk.metrics import (
MeterProvider,
)
from opentelemetry.sdk.metrics.export import (
InMemoryMetricReader,
)
from opentelemetry.sdk.trace import TracerProvider
from opentelemetry.sdk.trace.export import SimpleSpanProcessor
from opentelemetry.sdk.trace.export.in_memory_span_exporter import (
InMemorySpanExporter,
)
@pytest.fixture(scope="function", name="span_exporter")
def fixture_span_exporter():
exporter = InMemorySpanExporter()
yield exporter
@pytest.fixture(scope="function", name="log_exporter")
def fixture_log_exporter():
exporter = InMemoryLogRecordExporter()
yield exporter
@pytest.fixture(scope="function", name="metric_reader")
def fixture_metric_reader():
reader = InMemoryMetricReader()
yield reader
@pytest.fixture(scope="function", name="tracer_provider")
def fixture_tracer_provider(span_exporter):
provider = TracerProvider()
provider.add_span_processor(SimpleSpanProcessor(span_exporter))
return provider
@pytest.fixture(scope="function", name="logger_provider")
def fixture_logger_provider(log_exporter):
provider = LoggerProvider()
provider.add_log_record_processor(SimpleLogRecordProcessor(log_exporter))
return provider
@pytest.fixture(scope="function", name="meter_provider")
def fixture_meter_provider(metric_reader):
meter_provider = MeterProvider(
metric_readers=[metric_reader],
)
return meter_provider
@pytest.fixture
def bedrock_runtime_client():
return boto3.client("bedrock-runtime")
@pytest.fixture(autouse=True)
def environment():
if not os.getenv("AWS_ACCESS_KEY_ID"):
os.environ["AWS_ACCESS_KEY_ID"] = "test_aws_access_key_id"
if not os.getenv("AWS_SECRET_ACCESS_KEY"):
os.environ["AWS_SECRET_ACCESS_KEY"] = "test_aws_secret_key"
if not os.getenv("AWS_DEFAULT_REGION"):
os.environ["AWS_DEFAULT_REGION"] = "us-east-1"
@pytest.fixture(scope="module")
def vcr_config():
return {
"filter_headers": [
("cookie", "test_cookie"),
("authorization", "Bearer test_aws_authorization"),
("X-Amz-Security-Token", "test_aws_security_token"),
],
"decode_compressed_response": True,
"before_record_response": scrub_response_headers,
}
@pytest.fixture(scope="function")
def instrument_no_content(tracer_provider, logger_provider, meter_provider):
os.environ.update({OTEL_INSTRUMENTATION_GENAI_CAPTURE_MESSAGE_CONTENT: "False"})
instrumentor = BotocoreInstrumentor()
instrumentor.instrument(
tracer_provider=tracer_provider,
logger_provider=logger_provider,
meter_provider=meter_provider,
)
yield instrumentor
os.environ.pop(OTEL_INSTRUMENTATION_GENAI_CAPTURE_MESSAGE_CONTENT, None)
instrumentor.uninstrument()
@pytest.fixture(scope="function")
def instrument_with_content(tracer_provider, logger_provider, meter_provider):
os.environ.update({OTEL_INSTRUMENTATION_GENAI_CAPTURE_MESSAGE_CONTENT: "True"})
instrumentor = BotocoreInstrumentor()
instrumentor.instrument(
tracer_provider=tracer_provider,
logger_provider=logger_provider,
meter_provider=meter_provider,
)
yield instrumentor
os.environ.pop(OTEL_INSTRUMENTATION_GENAI_CAPTURE_MESSAGE_CONTENT, None)
instrumentor.uninstrument()
def scrub_response_headers(response):
"""
This scrubs sensitive response headers. Note they are case-sensitive!
"""
response["headers"]["Set-Cookie"] = "test_set_cookie"
# SDK validates response length which we modify by pretty-printing JSON.
# Content length does not affect our instrumentation so just drop it.
response["headers"].pop("Content-Length", None)
return response
class LiteralBlockScalar(str):
"""Formats the string as a literal block scalar, preserving whitespace and
without interpreting escape characters"""
def literal_block_scalar_presenter(dumper, data):
"""Represents a scalar string as a literal block, via '|' syntax"""
return dumper.represent_scalar("tag:yaml.org,2002:str", data, style="|")
yaml.add_representer(LiteralBlockScalar, literal_block_scalar_presenter)
def process_string_value(string_value):
"""Pretty-prints JSON or returns long strings as a LiteralBlockScalar"""
if isinstance(string_value, bytes):
return string_value
try:
json_data = json.loads(string_value)
return LiteralBlockScalar(json.dumps(json_data, indent=2))
except (ValueError, TypeError):
if len(string_value) > 80:
return LiteralBlockScalar(string_value)
return string_value
def convert_body_to_literal(data):
"""Searches the data for body strings, attempting to pretty-print JSON"""
if isinstance(data, dict):
for key, value in data.items():
# Handle response body case (e.g., response.body.string)
if key == "body" and isinstance(value, dict) and "string" in value:
value["string"] = process_string_value(value["string"])
# Handle request body case (e.g., request.body)
elif key == "body" and isinstance(value, str):
data[key] = process_string_value(value)
else:
convert_body_to_literal(value)
elif isinstance(data, list):
for idx, choice in enumerate(data):
data[idx] = convert_body_to_literal(choice)
# botocore uses bytes types for string values in headers, making recordings
# of them unreadable. It is fine to convert to strings where possible as vcr
# will still match them correctly.
elif isinstance(data, bytes):
try:
return data.decode("utf-8")
except UnicodeDecodeError:
pass
return data
class PrettyPrintJSONBody:
"""This makes request and response body recordings more readable."""
@staticmethod
def serialize(cassette_dict):
cassette_dict = convert_body_to_literal(cassette_dict)
return yaml.dump(cassette_dict, default_flow_style=False, allow_unicode=True)
@staticmethod
def deserialize(cassette_string):
return yaml.load(cassette_string, Loader=yaml.Loader)
@pytest.fixture(scope="module", autouse=True)
def fixture_vcr(vcr):
vcr.register_serializer("yaml", PrettyPrintJSONBody)
return vcr
test_aiobotocore_instrumentation.py 0000664 0000000 0000000 00000042566 15270700723 0043320 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-botocore/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
# pylint:disable=too-many-public-methods
import asyncio
import importlib.util
import json
import unittest
from typing import Any
from unittest.mock import Mock, call, patch
import botocore.stub
from botocore.exceptions import ClientError
from opentelemetry import trace as trace_api
from opentelemetry.instrumentation.auto_instrumentation import (
_load_instrumentors,
)
from opentelemetry.instrumentation.botocore import AiobotocoreInstrumentor
from opentelemetry.instrumentation.utils import suppress_instrumentation
from opentelemetry.semconv._incubating.attributes.cloud_attributes import (
CLOUD_REGION,
)
from opentelemetry.semconv._incubating.attributes.http_attributes import (
HTTP_STATUS_CODE,
)
from opentelemetry.semconv._incubating.attributes.rpc_attributes import (
RPC_METHOD,
RPC_SERVICE,
RPC_SYSTEM,
)
from opentelemetry.semconv.attributes.exception_attributes import (
EXCEPTION_MESSAGE,
EXCEPTION_STACKTRACE,
EXCEPTION_TYPE,
)
from opentelemetry.semconv.attributes.server_attributes import (
SERVER_ADDRESS,
SERVER_PORT,
)
from opentelemetry.test.test_base import TestBase
_REQUEST_ID_REGEX_MATCH = r"[A-Za-z0-9]{52}"
aiobotocore_installed = importlib.util.find_spec("aiobotocore") is not None
@unittest.skipIf(not aiobotocore_installed, "aiobotocore is not installed")
class TestAiobotocoreInstrumentor(TestBase):
"""Aiobotocore integration testsuite"""
def setUp(self):
# pylint: disable-next=import-outside-toplevel
import aiobotocore.session # noqa: PLC0415
super().setUp()
AiobotocoreInstrumentor().instrument()
self.session = aiobotocore.session.get_session()
self.session.set_credentials(
access_key="access-key",
secret_key="secret-key",
)
self.region = "us-west-2"
def tearDown(self):
super().tearDown()
AiobotocoreInstrumentor().uninstrument()
def _default_span_attributes(self, service: str, operation: str):
return {
RPC_SYSTEM: "aws-api",
RPC_SERVICE: service,
RPC_METHOD: operation,
CLOUD_REGION: self.region,
"retry_attempts": 0,
HTTP_STATUS_CODE: 200,
SERVER_ADDRESS: f"{service.lower()}.{self.region}.amazonaws.com",
SERVER_PORT: 443,
}
def assert_only_span(self):
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(1, len(spans))
return spans[0]
def assert_span(
self,
service: str,
operation: str,
request_id=None,
attributes=None,
):
span = self.assert_only_span()
expected = self._default_span_attributes(service, operation)
if attributes:
expected.update(attributes)
span_attributes_request_id = "aws.request_id"
if request_id is _REQUEST_ID_REGEX_MATCH:
actual_request_id = span.attributes[span_attributes_request_id]
self.assertRegex(actual_request_id, _REQUEST_ID_REGEX_MATCH)
expected[span_attributes_request_id] = actual_request_id
elif request_id is not None:
expected[span_attributes_request_id] = request_id
self.assertSpanHasAttributes(span, expected)
self.assertEqual(f"{service}.{operation}", span.name)
return span
def _make_client(self, service: str):
return self.session.create_client(service, region_name=self.region)
@staticmethod
def _make_response_meta(request_id: str) -> dict[str, Any]:
return {
"RequestId": request_id,
"RetryAttempts": 0,
"HTTPStatusCode": 200,
}
def test_traced_client_ec2(self):
"""Test basic EC2 client tracing with stubbed response."""
request_id = "fdcdcab1-ae5c-489e-9c33-4637c5dda355"
async def _test():
async with self._make_client("ec2") as client:
with botocore.stub.Stubber(client) as stubber:
stubber.add_response(
"describe_instances",
{
"Reservations": [],
"ResponseMetadata": self._make_response_meta(request_id),
},
)
await client.describe_instances()
asyncio.run(_test())
self.assert_span("EC2", "DescribeInstances", request_id=request_id)
def test_traced_client_s3(self):
"""Test S3 client tracing with stubbed response."""
request_id = "s3-request-id-12345"
async def _test():
async with self._make_client("s3") as client:
with botocore.stub.Stubber(client) as stubber:
stubber.add_response(
"list_buckets",
{
"Buckets": [],
"Owner": {"ID": "owner-id"},
"ResponseMetadata": self._make_response_meta(request_id),
},
)
await client.list_buckets()
asyncio.run(_test())
self.assert_span("S3", "ListBuckets", request_id=request_id)
def test_no_op_tracer_provider(self):
"""Test that no spans are created when using NoOpTracerProvider."""
AiobotocoreInstrumentor().uninstrument()
AiobotocoreInstrumentor().instrument(tracer_provider=trace_api.NoOpTracerProvider())
async def _test():
async with self._make_client("ec2") as client:
with botocore.stub.Stubber(client) as stubber:
stubber.add_response(
"describe_instances",
{
"Reservations": [],
"ResponseMetadata": self._make_response_meta("test-id"),
},
)
await client.describe_instances()
asyncio.run(_test())
spans_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans_list), 0)
def test_not_recording(self):
"""Test behavior when span is not recording."""
mock_tracer = Mock()
mock_span = Mock()
mock_span.is_recording.return_value = False
mock_tracer.start_span.return_value = mock_span
async def _test():
with patch("opentelemetry.trace.get_tracer") as tracer:
tracer.return_value = mock_tracer
async with self._make_client("ec2") as client:
with botocore.stub.Stubber(client) as stubber:
stubber.add_response(
"describe_instances",
{
"Reservations": [],
"ResponseMetadata": self._make_response_meta("test-id"),
},
)
await client.describe_instances()
self.assertFalse(mock_span.is_recording())
self.assertTrue(mock_span.is_recording.called)
self.assertFalse(mock_span.set_attribute.called)
self.assertFalse(mock_span.set_status.called)
asyncio.run(_test())
def test_client_error(self):
"""Test that ClientError is properly traced with error status."""
async def _test():
async with self._make_client("s3") as client:
with botocore.stub.Stubber(client) as stubber:
stubber.add_client_error(
"get_object",
service_error_code="NoSuchKey",
service_message="The specified key does not exist.",
http_status_code=404,
)
with self.assertRaises(ClientError):
await client.get_object(Bucket="test-bucket", Key="test-key")
asyncio.run(_test())
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(1, len(spans))
span = spans[0]
self.assertIs(span.status.status_code, trace_api.StatusCode.ERROR)
self.assertEqual("S3.GetObject", span.name)
# Verify exception event was recorded
self.assertEqual(1, len(span.events))
event = span.events[0]
self.assertIn(EXCEPTION_STACKTRACE, event.attributes)
self.assertIn(EXCEPTION_TYPE, event.attributes)
self.assertIn(EXCEPTION_MESSAGE, event.attributes)
def test_client_error_with_http_error_status(self):
"""ClientError with HTTP 4xx sets span status to ERROR."""
async def _test():
async with self._make_client("s3") as client:
with botocore.stub.Stubber(client) as stubber:
stubber.add_client_error(
"get_object",
service_error_code="NoSuchBucket",
service_message="The specified bucket does not exist.",
http_status_code=404,
)
with self.assertRaises(ClientError):
await client.get_object(Bucket="non-existent-bucket", Key="key")
asyncio.run(_test())
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(1, len(spans))
span = spans[0]
self.assertIs(span.status.status_code, trace_api.StatusCode.ERROR)
def test_client_error_304_not_modified(self):
"""ClientError with HTTP 304 leaves span status as UNSET."""
async def _test():
async with self._make_client("s3") as client:
with botocore.stub.Stubber(client) as stubber:
stubber.add_client_error(
"get_object",
service_error_code="304",
service_message="Not Modified",
http_status_code=304,
)
with self.assertRaises(ClientError):
await client.get_object(Bucket="test-bucket", Key="key")
asyncio.run(_test())
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(1, len(spans))
span = spans[0]
self.assertIs(span.status.status_code, trace_api.StatusCode.UNSET)
def test_suppress_instrumentation(self):
"""Test that instrumentation can be suppressed."""
async def _test():
async with self._make_client("ec2") as client:
with botocore.stub.Stubber(client) as stubber:
stubber.add_response(
"describe_instances",
{
"Reservations": [],
"ResponseMetadata": self._make_response_meta("test-id"),
},
)
stubber.add_response(
"describe_instances",
{
"Reservations": [],
"ResponseMetadata": self._make_response_meta("test-id-2"),
},
)
with suppress_instrumentation():
await client.describe_instances()
await client.describe_instances()
asyncio.run(_test())
self.assertEqual(0, len(self.get_finished_spans()))
def test_request_hook(self):
"""Test that request hook is called with correct parameters."""
request_hook_service_attribute_name = "request_hook.service_name"
request_hook_operation_attribute_name = "request_hook.operation_name"
request_hook_api_params_attribute_name = "request_hook.api_params"
def request_hook(span, service_name, operation_name, api_params):
hook_attributes = {
request_hook_service_attribute_name: service_name,
request_hook_operation_attribute_name: operation_name,
request_hook_api_params_attribute_name: json.dumps(api_params),
}
span.set_attributes(hook_attributes)
AiobotocoreInstrumentor().uninstrument()
AiobotocoreInstrumentor().instrument(request_hook=request_hook)
request_id = "hook-test-request-id"
async def _test():
async with self._make_client("s3") as client:
with botocore.stub.Stubber(client) as stubber:
stubber.add_response(
"list_objects_v2",
{
"Contents": [],
"ResponseMetadata": self._make_response_meta(request_id),
},
expected_params={"Bucket": "test-bucket"},
)
await client.list_objects_v2(Bucket="test-bucket")
asyncio.run(_test())
self.assert_span(
"S3",
"ListObjectsV2",
request_id=request_id,
attributes={
request_hook_service_attribute_name: "s3",
request_hook_operation_attribute_name: "ListObjectsV2",
request_hook_api_params_attribute_name: json.dumps({"Bucket": "test-bucket"}),
},
)
def test_response_hook(self):
"""Test that response hook is called with correct parameters."""
response_hook_service_attribute_name = "response_hook.service_name"
response_hook_operation_attribute_name = "response_hook.operation_name"
response_hook_bucket_count_attribute_name = "response_hook.bucket_count"
def response_hook(span, service_name, operation_name, result):
hook_attributes = {
response_hook_service_attribute_name: service_name,
response_hook_operation_attribute_name: operation_name,
response_hook_bucket_count_attribute_name: len(result["Buckets"]),
}
span.set_attributes(hook_attributes)
AiobotocoreInstrumentor().uninstrument()
AiobotocoreInstrumentor().instrument(response_hook=response_hook)
request_id = "response-hook-test-id"
async def _test():
async with self._make_client("s3") as client:
with botocore.stub.Stubber(client) as stubber:
stubber.add_response(
"list_buckets",
{
"Buckets": [
{"Name": "bucket1"},
{"Name": "bucket2"},
],
"Owner": {"ID": "owner-id"},
"ResponseMetadata": self._make_response_meta(request_id),
},
)
await client.list_buckets()
asyncio.run(_test())
self.assert_span(
"S3",
"ListBuckets",
request_id=request_id,
attributes={
response_hook_service_attribute_name: "s3",
response_hook_operation_attribute_name: "ListBuckets",
response_hook_bucket_count_attribute_name: 2,
},
)
def test_multiple_operations(self):
"""Test tracing multiple sequential operations."""
async def _test():
async with self._make_client("s3") as client:
with botocore.stub.Stubber(client) as stubber:
stubber.add_response(
"list_buckets",
{
"Buckets": [],
"Owner": {"ID": "owner-id"},
"ResponseMetadata": self._make_response_meta("req-1"),
},
)
stubber.add_response(
"list_buckets",
{
"Buckets": [],
"Owner": {"ID": "owner-id"},
"ResponseMetadata": self._make_response_meta("req-2"),
},
)
await client.list_buckets()
await client.list_buckets()
asyncio.run(_test())
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(2, len(spans))
for span in spans:
self.assertEqual("S3.ListBuckets", span.name)
self.assertEqual("req-1", spans[0].attributes["aws.request_id"])
self.assertEqual("req-2", spans[1].attributes["aws.request_id"])
@patch("opentelemetry.instrumentation.auto_instrumentation._load.get_dist_dependency_conflicts")
@patch("opentelemetry.instrumentation.auto_instrumentation._load._logger")
def test_instruments_with_aiobotocore_installed(self, mock_logger, mock_dep):
mock_distro = Mock()
mock_dep.return_value = None
mock_distro.load_instrumentor.return_value = None
_load_instrumentors(mock_distro)
self.assertEqual(len(mock_distro.load_instrumentor.call_args_list), 2)
eps = [c[0][0].name for c in mock_distro.load_instrumentor.call_args_list]
assert "aiobotocore" in eps
assert "botocore" in eps
mock_logger.debug.assert_has_calls(
[
call("Instrumented %s", "aiobotocore"),
call("Instrumented %s", "botocore"),
],
any_order=True,
)
test_botocore_bedrock.py 0000664 0000000 0000000 00000301002 15270700723 0040754 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-botocore/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
# pylint:disable=too-many-lines
from __future__ import annotations
import io
import json
from unittest import mock
import boto3
import pytest
from botocore.eventstream import EventStream, EventStreamError
from botocore.response import StreamingBody
from opentelemetry.instrumentation.botocore.extensions.bedrock_utils import (
ConverseStreamWrapper,
InvokeModelWithResponseStreamWrapper,
_Choice,
)
from opentelemetry.semconv._incubating.attributes.error_attributes import (
ERROR_TYPE,
)
from opentelemetry.semconv._incubating.attributes.gen_ai_attributes import (
GEN_AI_USAGE_CACHE_CREATION_INPUT_TOKENS,
GEN_AI_USAGE_CACHE_READ_INPUT_TOKENS,
)
from opentelemetry.trace.status import StatusCode
from .bedrock_utils import (
assert_completion_attributes_from_streaming_body,
assert_converse_completion_attributes,
assert_message_in_logs,
assert_metrics,
assert_stream_completion_attributes,
)
BOTO3_VERSION = tuple(int(x) for x in boto3.__version__.split("."))
def filter_message_keys(message, keys):
return {k: v for k, v in message.items() if k in keys}
@pytest.mark.skipif(BOTO3_VERSION < (1, 35, 56), reason="Converse API not available")
@pytest.mark.vcr()
def test_converse_with_content(
span_exporter,
log_exporter,
metric_reader,
bedrock_runtime_client,
instrument_with_content,
):
# pylint:disable=too-many-locals
messages = [{"role": "user", "content": [{"text": "Say this is a test"}]}]
llm_model_value = "amazon.titan-text-lite-v1"
max_tokens, temperature, top_p, stop_sequences = 10, 0.8, 1, ["|"]
response = bedrock_runtime_client.converse(
messages=messages,
modelId=llm_model_value,
inferenceConfig={
"maxTokens": max_tokens,
"temperature": temperature,
"topP": top_p,
"stopSequences": stop_sequences,
},
)
(span,) = span_exporter.get_finished_spans()
assert_converse_completion_attributes(
span,
llm_model_value,
response,
"chat",
top_p,
temperature,
max_tokens,
stop_sequences,
)
logs = log_exporter.get_finished_logs()
assert len(logs) == 2
user_content = filter_message_keys(messages[0], ["content"])
assert_message_in_logs(logs[0], "gen_ai.user.message", user_content, span)
choice_body = {
"index": 0,
"finish_reason": "max_tokens",
"message": {
"content": [{"text": "Hi, how can I help you"}],
"role": "assistant",
},
}
assert_message_in_logs(logs[1], "gen_ai.choice", choice_body, span)
input_tokens = response["usage"]["inputTokens"]
output_tokens = response["usage"]["outputTokens"]
metrics = metric_reader.get_metrics_data().resource_metrics
assert_metrics(metrics, "chat", llm_model_value, input_tokens, output_tokens)
@pytest.mark.skipif(
BOTO3_VERSION < (1, 38, 0),
reason="Prompt cache token usage not in the bedrock-runtime service model",
)
@pytest.mark.vcr()
def test_converse_with_prompt_caching(
span_exporter,
bedrock_runtime_client,
instrument_no_content,
):
# A prefix is only cached once it clears the model minimum (1k tokens for
# Nova Micro), so pad the system prompt past it.
system_content = [
{"text": "You are a helpful assistant for instrumentation tests. " * 300},
{"cachePoint": {"type": "default"}},
]
messages = [{"role": "user", "content": [{"text": "Say this is a test"}]}]
llm_model_value = "us.amazon.nova-micro-v1:0"
# The first call writes the prefix to the cache, the second reads it back.
responses = [
bedrock_runtime_client.converse(
system=system_content,
messages=messages,
modelId=llm_model_value,
inferenceConfig={"maxTokens": 10},
)
for _ in range(2)
]
write_span, read_span = span_exporter.get_finished_spans()
cache_write = responses[0]["usage"]["cacheWriteInputTokens"]
assert cache_write > 0
written = write_span.attributes[GEN_AI_USAGE_CACHE_CREATION_INPUT_TOKENS]
assert written == cache_write
assert isinstance(written, int)
cache_read = responses[1]["usage"]["cacheReadInputTokens"]
assert cache_read > 0
read = read_span.attributes[GEN_AI_USAGE_CACHE_READ_INPUT_TOKENS]
assert read == cache_read
assert isinstance(read, int)
@pytest.mark.skipif(
BOTO3_VERSION < (1, 38, 0),
reason="Prompt cache token usage not in the bedrock-runtime service model",
)
@pytest.mark.vcr()
def test_converse_stream_with_prompt_caching(
span_exporter,
bedrock_runtime_client,
instrument_no_content,
):
# A prefix is only cached once it clears the model minimum (1k tokens for
# Nova Micro), so pad the system prompt past it.
system_content = [
{"text": "You are a helpful assistant for streaming tests. " * 300},
{"cachePoint": {"type": "default"}},
]
messages = [{"role": "user", "content": [{"text": "Say this is a test"}]}]
llm_model_value = "us.amazon.nova-micro-v1:0"
# The first call writes the prefix to the cache, the second reads it back.
usages = []
for _ in range(2):
response = bedrock_runtime_client.converse_stream(
system=system_content,
messages=messages,
modelId=llm_model_value,
inferenceConfig={"maxTokens": 10},
)
# consume the stream in order to have it traced
for event in response["stream"]:
if "metadata" in event:
usages.append(event["metadata"]["usage"])
write_span, read_span = span_exporter.get_finished_spans()
cache_write = usages[0]["cacheWriteInputTokens"]
assert cache_write > 0
written = write_span.attributes[GEN_AI_USAGE_CACHE_CREATION_INPUT_TOKENS]
assert written == cache_write
assert isinstance(written, int)
cache_read = usages[1]["cacheReadInputTokens"]
assert cache_read > 0
read = read_span.attributes[GEN_AI_USAGE_CACHE_READ_INPUT_TOKENS]
assert read == cache_read
assert isinstance(read, int)
@pytest.mark.skipif(BOTO3_VERSION < (1, 35, 56), reason="Converse API not available")
@pytest.mark.vcr()
def test_converse_with_content_different_events(
span_exporter,
log_exporter,
metric_reader,
bedrock_runtime_client,
instrument_with_content,
):
# pylint:disable=too-many-locals
messages = anthropic_claude_converse_messages()
llm_model_value = "anthropic.claude-v2"
system_content = anthropic_claude_converse_system()
response = bedrock_runtime_client.converse(
system=system_content,
messages=messages,
modelId=llm_model_value,
)
(span,) = span_exporter.get_finished_spans()
assert_converse_completion_attributes(
span,
llm_model_value,
response,
"chat",
)
logs = log_exporter.get_finished_logs()
assert len(logs) == 5
assert_message_in_logs(logs[0], "gen_ai.system.message", {"content": system_content}, span)
user_message, assistant_message, last_user_message = messages
user_content = filter_message_keys(user_message, ["content"])
assert_message_in_logs(logs[1], "gen_ai.user.message", user_content, span)
assistant_content = filter_message_keys(assistant_message, ["content"])
assert_message_in_logs(logs[2], "gen_ai.assistant.message", assistant_content, span)
last_user_content = filter_message_keys(last_user_message, ["content"])
assert_message_in_logs(logs[3], "gen_ai.user.message", last_user_content, span)
choice_body = {
"index": 0,
"finish_reason": "end_turn",
"message": {
"content": [{"text": "This is a test"}],
"role": "assistant",
},
}
assert_message_in_logs(logs[4], "gen_ai.choice", choice_body, span)
input_tokens = response["usage"]["inputTokens"]
output_tokens = response["usage"]["outputTokens"]
metrics = metric_reader.get_metrics_data().resource_metrics
assert_metrics(metrics, "chat", llm_model_value, input_tokens, output_tokens)
def converse_tool_call(span_exporter, log_exporter, bedrock_runtime_client, expect_content):
# pylint:disable=too-many-locals
messages = [
{
"role": "user",
"content": [{"text": "What is the weather in Seattle and San Francisco today?"}],
}
]
tool_config = get_tool_config()
llm_model_value = "amazon.nova-micro-v1:0"
response_0 = bedrock_runtime_client.converse(
messages=messages,
modelId=llm_model_value,
toolConfig=tool_config,
)
# first content block is model thinking, so skip it
tool_requests_ids = [
request["toolUse"]["toolUseId"]
for request in response_0["output"]["message"]["content"]
if "toolUse" in request
]
assert len(tool_requests_ids) == 2
tool_call_result = {
"role": "user",
"content": [
{
"toolResult": {
"content": [{"json": {"weather": "50 degrees and raining"}}],
"toolUseId": tool_requests_ids[0],
},
},
{
"toolResult": {
"content": [{"json": {"weather": "70 degrees and sunny"}}],
"toolUseId": tool_requests_ids[1],
},
},
],
}
messages.append(response_0["output"]["message"])
messages.append(tool_call_result)
response_1 = bedrock_runtime_client.converse(
messages=messages,
modelId=llm_model_value,
toolConfig=tool_config,
)
(span_0, span_1) = span_exporter.get_finished_spans()
assert_converse_completion_attributes(
span_0,
llm_model_value,
response_0,
"chat",
)
assert_converse_completion_attributes(
span_1,
llm_model_value,
response_1,
"chat",
)
logs = log_exporter.get_finished_logs()
assert len(logs) == 8
# first span
if expect_content:
user_content = filter_message_keys(messages[0], ["content"])
else:
user_content = {}
assert_message_in_logs(logs[0], "gen_ai.user.message", user_content, span_0)
function_call_0 = {"name": "get_current_weather"}
function_call_1 = {"name": "get_current_weather"}
if expect_content:
function_call_0["arguments"] = {"location": "Seattle"}
function_call_1["arguments"] = {"location": "San Francisco"}
choice_body = {
"index": 0,
"finish_reason": "tool_use",
"message": {
"role": "assistant",
"tool_calls": [
{
"id": tool_requests_ids[0],
"type": "function",
"function": function_call_0,
},
{
"id": tool_requests_ids[1],
"type": "function",
"function": function_call_1,
},
],
},
}
assert_message_in_logs(logs[1], "gen_ai.choice", choice_body, span_0)
# second span
assert_message_in_logs(logs[2], "gen_ai.user.message", user_content, span_1)
assistant_body = response_0["output"]["message"]
assistant_body["tool_calls"] = choice_body["message"]["tool_calls"]
assistant_body.pop("role")
if not expect_content:
assistant_body.pop("content")
assert_message_in_logs(
logs[3],
"gen_ai.assistant.message",
assistant_body,
span_1,
)
tool_message_0 = {
"id": tool_requests_ids[0],
"content": tool_call_result["content"][0]["toolResult"]["content"] if expect_content else None,
}
assert_message_in_logs(logs[4], "gen_ai.tool.message", tool_message_0, span_1)
tool_message_1 = {
"id": tool_requests_ids[1],
"content": tool_call_result["content"][1]["toolResult"]["content"] if expect_content else None,
}
assert_message_in_logs(logs[5], "gen_ai.tool.message", tool_message_1, span_1)
user_message_body = tool_call_result
user_message_body.pop("role")
if not expect_content:
user_message_body.pop("content")
assert_message_in_logs(logs[6], "gen_ai.user.message", user_message_body, span_1)
choice_body = {
"index": 0,
"finish_reason": "end_turn",
"message": {
"role": "assistant",
"content": [
{
"text": " I have received the weather information for both cities. Now I will compile this information and present it to the User.\n\nThe current weather in Seattle is 50 degrees and it's raining. In San Francisco, it's 70 degrees and sunny today."
}
],
},
}
if not expect_content:
choice_body["message"].pop("content")
assert_message_in_logs(logs[7], "gen_ai.choice", choice_body, span_1)
@pytest.mark.skipif(BOTO3_VERSION < (1, 35, 56), reason="Converse API not available")
@pytest.mark.vcr()
def test_converse_tool_call_with_content(
span_exporter,
log_exporter,
bedrock_runtime_client,
instrument_with_content,
):
converse_tool_call(
span_exporter,
log_exporter,
bedrock_runtime_client,
expect_content=True,
)
@pytest.mark.skipif(BOTO3_VERSION < (1, 35, 56), reason="Converse API not available")
@pytest.mark.vcr()
def test_converse_no_content_different_events(
span_exporter,
log_exporter,
bedrock_runtime_client,
instrument_no_content,
):
messages = anthropic_claude_converse_messages()
llm_model_value = "anthropic.claude-v2"
system_content = anthropic_claude_converse_system()
response = bedrock_runtime_client.converse(
system=system_content,
messages=messages,
modelId=llm_model_value,
)
(span,) = span_exporter.get_finished_spans()
assert_converse_completion_attributes(
span,
llm_model_value,
response,
"chat",
)
logs = log_exporter.get_finished_logs()
assert len(logs) == 5
assert_message_in_logs(logs[0], "gen_ai.system.message", None, span)
assert_message_in_logs(logs[1], "gen_ai.user.message", None, span)
assert_message_in_logs(logs[2], "gen_ai.assistant.message", None, span)
assert_message_in_logs(logs[3], "gen_ai.user.message", None, span)
choice_body = {
"index": 0,
"finish_reason": "end_turn",
"message": {"role": "assistant"},
}
assert_message_in_logs(logs[4], "gen_ai.choice", choice_body, span)
@pytest.mark.skipif(BOTO3_VERSION < (1, 35, 56), reason="Converse API not available")
@pytest.mark.vcr()
def test_converse_no_content(
span_exporter,
log_exporter,
bedrock_runtime_client,
instrument_no_content,
):
messages = [{"role": "user", "content": [{"text": "Say this is a test"}]}]
llm_model_value = "amazon.titan-text-lite-v1"
max_tokens, temperature, top_p, stop_sequences = 10, 0.8, 1, ["|"]
response = bedrock_runtime_client.converse(
messages=messages,
modelId=llm_model_value,
inferenceConfig={
"maxTokens": max_tokens,
"temperature": temperature,
"topP": top_p,
"stopSequences": stop_sequences,
},
)
(span,) = span_exporter.get_finished_spans()
assert_converse_completion_attributes(
span,
llm_model_value,
response,
"chat",
top_p,
temperature,
max_tokens,
stop_sequences,
)
logs = log_exporter.get_finished_logs()
assert len(logs) == 2
assert_message_in_logs(logs[0], "gen_ai.user.message", None, span)
choice_body = {
"index": 0,
"finish_reason": "max_tokens",
"message": {"role": "assistant"},
}
assert_message_in_logs(logs[1], "gen_ai.choice", choice_body, span)
@pytest.mark.skipif(BOTO3_VERSION < (1, 35, 56), reason="Converse API not available")
@pytest.mark.vcr()
def test_converse_tool_call_no_content(
span_exporter,
log_exporter,
bedrock_runtime_client,
instrument_no_content,
):
converse_tool_call(
span_exporter,
log_exporter,
bedrock_runtime_client,
expect_content=False,
)
@pytest.mark.skipif(BOTO3_VERSION < (1, 35, 56), reason="Converse API not available")
@pytest.mark.vcr()
def test_converse_with_invalid_model(
span_exporter,
log_exporter,
metric_reader,
bedrock_runtime_client,
instrument_with_content,
):
messages = [{"role": "user", "content": [{"text": "Say this is a test"}]}]
llm_model_value = "does-not-exist"
with pytest.raises(bedrock_runtime_client.exceptions.ValidationException):
bedrock_runtime_client.converse(
messages=messages,
modelId=llm_model_value,
)
(span,) = span_exporter.get_finished_spans()
assert_converse_completion_attributes(
span,
llm_model_value,
None,
"chat",
)
assert span.status.status_code == StatusCode.ERROR
assert span.attributes[ERROR_TYPE] == "ValidationException"
logs = log_exporter.get_finished_logs()
user_content = filter_message_keys(messages[0], ["content"])
assert_message_in_logs(logs[0], "gen_ai.user.message", user_content, span)
metrics = metric_reader.get_metrics_data().resource_metrics
assert_metrics(metrics, "chat", llm_model_value, error_type="ValidationException")
@pytest.mark.skipif(BOTO3_VERSION < (1, 35, 56), reason="ConverseStream API not available")
@pytest.mark.vcr()
def test_converse_stream_with_content(
span_exporter,
log_exporter,
metric_reader,
bedrock_runtime_client,
instrument_with_content,
):
# pylint:disable=too-many-locals
messages = [{"role": "user", "content": [{"text": "Say this is a test"}]}]
llm_model_value = "amazon.titan-text-lite-v1"
max_tokens, temperature, top_p, stop_sequences = 10, 0.8, 1, ["|"]
response = bedrock_runtime_client.converse_stream(
messages=messages,
modelId=llm_model_value,
inferenceConfig={
"maxTokens": max_tokens,
"temperature": temperature,
"topP": top_p,
"stopSequences": stop_sequences,
},
)
# consume the stream in order to have it traced
finish_reason = None
input_tokens, output_tokens = None, None
text = ""
for event in response["stream"]:
if "contentBlockDelta" in event:
text += event["contentBlockDelta"]["delta"]["text"]
if "messageStop" in event:
finish_reason = (event["messageStop"]["stopReason"],)
if "metadata" in event:
usage = event["metadata"]["usage"]
input_tokens = usage["inputTokens"]
output_tokens = usage["outputTokens"]
assert text
assert finish_reason
assert input_tokens
assert output_tokens
(span,) = span_exporter.get_finished_spans()
assert_stream_completion_attributes(
span,
llm_model_value,
input_tokens,
output_tokens,
finish_reason,
"chat",
top_p,
temperature,
max_tokens,
stop_sequences,
)
logs = log_exporter.get_finished_logs()
assert len(logs) == 2
user_content = filter_message_keys(messages[0], ["content"])
assert_message_in_logs(logs[0], "gen_ai.user.message", user_content, span)
choice_body = {
"index": 0,
"finish_reason": "max_tokens",
"message": {
"content": [{"text": "I am here and ready to assist"}],
"role": "assistant",
},
}
assert_message_in_logs(logs[1], "gen_ai.choice", choice_body, span)
metrics = metric_reader.get_metrics_data().resource_metrics
assert_metrics(metrics, "chat", llm_model_value, input_tokens, output_tokens)
@pytest.mark.skipif(BOTO3_VERSION < (1, 35, 56), reason="ConverseStream API not available")
@pytest.mark.vcr()
def test_converse_stream_with_content_different_events(
span_exporter,
log_exporter,
metric_reader,
bedrock_runtime_client,
instrument_with_content,
):
# pylint:disable=too-many-locals
messages = anthropic_claude_converse_messages()
llm_model_value = "anthropic.claude-v2"
system_content = anthropic_claude_converse_system()
response = bedrock_runtime_client.converse_stream(
system=system_content,
messages=messages,
modelId=llm_model_value,
)
# consume the stream in order to have it traced
for _ in response["stream"]:
pass
(span,) = span_exporter.get_finished_spans()
assert_stream_completion_attributes(
span,
llm_model_value,
input_tokens=mock.ANY,
output_tokens=mock.ANY,
finish_reason=("end_turn",),
operation_name="chat",
)
logs = log_exporter.get_finished_logs()
assert len(logs) == 5
assert_message_in_logs(logs[0], "gen_ai.system.message", {"content": system_content}, span)
user_message, assistant_message, last_user_message = messages
user_content = filter_message_keys(user_message, ["content"])
assert_message_in_logs(logs[1], "gen_ai.user.message", user_content, span)
assistant_content = filter_message_keys(assistant_message, ["content"])
assert_message_in_logs(logs[2], "gen_ai.assistant.message", assistant_content, span)
last_user_content = filter_message_keys(last_user_message, ["content"])
assert_message_in_logs(logs[3], "gen_ai.user.message", last_user_content, span)
choice_body = {
"index": 0,
"finish_reason": "end_turn",
"message": {
"role": "assistant",
"content": [{"text": "This is a test"}],
},
}
assert_message_in_logs(logs[4], "gen_ai.choice", choice_body, span)
metrics = metric_reader.get_metrics_data().resource_metrics
assert_metrics(metrics, "chat", llm_model_value, mock.ANY, mock.ANY)
def _rebuild_stream_message(response):
message = {"content": []}
content_block = {}
for stream_msg in response["stream"]:
if "messageStart" in stream_msg:
message.update(stream_msg["messageStart"])
elif "contentBlockStart" in stream_msg:
start = stream_msg["contentBlockStart"]["start"]
if "toolUse" in start:
# toolUse.input is already decoded by the wrapper
content_block = {"toolUse": start["toolUse"]}
elif "contentBlockDelta" in stream_msg:
delta = stream_msg["contentBlockDelta"]["delta"]
if "text" in delta:
content_block.setdefault("text", "")
content_block["text"] += delta["text"]
elif "toolUse" in delta:
# toolUse.input is already decoded by the wrapper
content_block["toolUse"].update(delta["toolUse"])
elif "contentBlockStop" in stream_msg:
message["content"].append(content_block)
elif "messageStop" in stream_msg:
message.update(stream_msg["messageStop"])
return message
def converse_stream_tool_call(span_exporter, log_exporter, bedrock_runtime_client, expect_content):
# pylint:disable=too-many-locals,too-many-statements
messages = [
{
"role": "user",
"content": [{"text": "What is the weather in Seattle and San Francisco today?"}],
}
]
tool_config = get_tool_config()
llm_model_value = "amazon.nova-micro-v1:0"
response_0 = bedrock_runtime_client.converse_stream(
messages=messages,
modelId=llm_model_value,
toolConfig=tool_config,
)
# consume the stream and assemble it as the non-streaming version
response_0_message = _rebuild_stream_message(response_0)
tool_requests_ids = [
request["toolUse"]["toolUseId"] for request in response_0_message["content"] if "toolUse" in request
]
assert len(tool_requests_ids) == 2
tool_call_result = {
"role": "user",
"content": [
{
"toolResult": {
"content": [{"json": {"weather": "50 degrees and raining"}}],
"toolUseId": tool_requests_ids[0],
},
},
{
"toolResult": {
"content": [{"json": {"weather": "70 degrees and sunny"}}],
"toolUseId": tool_requests_ids[1],
},
},
],
}
response_0_message.pop("stopReason")
messages.append(response_0_message)
messages.append(tool_call_result)
response_1 = bedrock_runtime_client.converse_stream(
messages=messages,
modelId=llm_model_value,
toolConfig=tool_config,
)
# consume the stream to have it traced
_ = _rebuild_stream_message(response_1)
(span_0, span_1) = span_exporter.get_finished_spans()
assert_stream_completion_attributes(
span_0,
llm_model_value,
input_tokens=mock.ANY,
output_tokens=mock.ANY,
finish_reason=("tool_use",),
operation_name="chat",
)
assert_stream_completion_attributes(
span_1,
llm_model_value,
input_tokens=mock.ANY,
output_tokens=mock.ANY,
finish_reason=("end_turn",),
operation_name="chat",
)
logs = log_exporter.get_finished_logs()
assert len(logs) == 8
# first span
if expect_content:
user_content = filter_message_keys(messages[0], ["content"])
else:
user_content = {}
assert_message_in_logs(logs[0], "gen_ai.user.message", user_content, span_0)
function_call_0 = {"name": "get_current_weather"}
function_call_1 = {"name": "get_current_weather"}
if expect_content:
function_call_0["arguments"] = {"location": "Seattle"}
function_call_1["arguments"] = {"location": "San Francisco"}
choice_body = {
"index": 0,
"finish_reason": "tool_use",
"message": {
"role": "assistant",
"tool_calls": [
{
"id": tool_requests_ids[0],
"type": "function",
"function": function_call_0,
},
{
"id": tool_requests_ids[1],
"type": "function",
"function": function_call_1,
},
],
},
}
assert_message_in_logs(logs[1], "gen_ai.choice", choice_body, span_0)
# second span
assert_message_in_logs(logs[2], "gen_ai.user.message", user_content, span_1)
assistant_body = response_0_message
assistant_body["tool_calls"] = choice_body["message"]["tool_calls"]
assistant_body.pop("role")
if not expect_content:
assistant_body.pop("content")
assert_message_in_logs(
logs[3],
"gen_ai.assistant.message",
assistant_body,
span_1,
)
tool_message_0 = {
"id": tool_requests_ids[0],
"content": tool_call_result["content"][0]["toolResult"]["content"] if expect_content else None,
}
assert_message_in_logs(logs[4], "gen_ai.tool.message", tool_message_0, span_1)
tool_message_1 = {
"id": tool_requests_ids[1],
"content": tool_call_result["content"][1]["toolResult"]["content"] if expect_content else None,
}
assert_message_in_logs(logs[5], "gen_ai.tool.message", tool_message_1, span_1)
user_message_body = tool_call_result
user_message_body.pop("role")
if not expect_content:
user_message_body.pop("content")
assert_message_in_logs(logs[6], "gen_ai.user.message", user_message_body, span_1)
choice_body = {
"index": 0,
"finish_reason": "end_turn",
"message": {
"role": "assistant",
"content": [
{
"text": " I have received the weather information for both cities. Now I will provide the details to the User.\n\nThe current weather in Seattle is 50 degrees and raining. In San Francisco, the weather is 70 degrees and sunny."
}
],
},
}
if not expect_content:
choice_body["message"].pop("content")
assert_message_in_logs(logs[7], "gen_ai.choice", choice_body, span_1)
@pytest.mark.skipif(BOTO3_VERSION < (1, 35, 56), reason="ConverseStream API not available")
@pytest.mark.vcr()
def test_converse_stream_with_content_tool_call(
span_exporter,
log_exporter,
bedrock_runtime_client,
instrument_with_content,
):
converse_stream_tool_call(
span_exporter,
log_exporter,
bedrock_runtime_client,
expect_content=True,
)
@pytest.mark.skipif(BOTO3_VERSION < (1, 35, 56), reason="ConverseStream API not available")
@pytest.mark.vcr()
def test_converse_stream_tool_call_parsing_errors(
span_exporter,
log_exporter,
bedrock_runtime_client,
instrument_with_content,
):
# pylint:disable=too-many-locals
messages = [
{
"role": "user",
"content": [
{
"text": "Use the get_cities_list tool to provide exactly 10 popular tourist cities in Japan. Call the tool with a cities array containing: Tokyo, Osaka, Kyoto, Hiroshima, Nara, Yokohama, Sapporo, Fukuoka, Sendai, and Nagoya"
}
],
}
]
tool_config = {
"tools": [
{
"toolSpec": {
"name": "get_cities_list",
"description": "Get a list of cities",
"inputSchema": {
"json": {
"type": "object",
"properties": {
"cities": {
"type": "array",
"items": {"type": "string"},
}
},
}
},
}
}
]
}
llm_model_value = "anthropic.claude-3-sonnet-20240229-v1:0"
response_0 = bedrock_runtime_client.converse_stream(
messages=messages, modelId=llm_model_value, toolConfig=tool_config
)
res = ""
tool_use_id = None
for chunk in response_0["stream"]:
if "contentBlockStart" in chunk:
start = chunk["contentBlockStart"]["start"]
tool_use_id = start["toolUse"]["toolUseId"]
elif "contentBlockDelta" in chunk:
delta = chunk["contentBlockDelta"]["delta"]
if "toolUse" in delta:
res += delta["toolUse"].get("input")
tool_use_input = json.loads(res)
expected_tool_use_input = {
"cities": [
"Tokyo",
"Osaka",
"Kyoto",
"Hiroshima",
"Nara",
"Yokohama",
"Sapporo",
"Fukuoka",
"Sendai",
"Nagoya",
]
}
assert tool_use_input == expected_tool_use_input
(span_0,) = span_exporter.get_finished_spans()
assert_stream_completion_attributes(
span_0,
llm_model_value,
input_tokens=mock.ANY,
output_tokens=mock.ANY,
finish_reason=("tool_use",),
operation_name="chat",
)
logs = log_exporter.get_finished_logs()
assert len(logs) == 2
user_content = filter_message_keys(messages[0], ["content"])
assert_message_in_logs(logs[0], "gen_ai.user.message", user_content, span_0)
function_call_0 = {
"name": "get_cities_list",
"arguments": expected_tool_use_input,
}
choice_body = {
"index": 0,
"finish_reason": "tool_use",
"message": {
"role": "assistant",
"tool_calls": [
{
"id": tool_use_id,
"type": "function",
"function": function_call_0,
},
],
},
}
assert_message_in_logs(logs[1], "gen_ai.choice", choice_body, span_0)
@pytest.mark.skipif(BOTO3_VERSION < (1, 35, 56), reason="ConverseStream API not available")
@pytest.mark.vcr()
def test_converse_stream_no_content(
span_exporter,
log_exporter,
bedrock_runtime_client,
instrument_no_content,
):
# pylint:disable=too-many-locals
messages = [{"role": "user", "content": [{"text": "Say this is a test"}]}]
llm_model_value = "amazon.titan-text-lite-v1"
max_tokens, temperature, top_p, stop_sequences = 10, 0.8, 1, ["|"]
response = bedrock_runtime_client.converse_stream(
messages=messages,
modelId=llm_model_value,
inferenceConfig={
"maxTokens": max_tokens,
"temperature": temperature,
"topP": top_p,
"stopSequences": stop_sequences,
},
)
# consume the stream in order to have it traced
finish_reason = None
input_tokens, output_tokens = None, None
text = ""
for event in response["stream"]:
if "contentBlockDelta" in event:
text += event["contentBlockDelta"]["delta"]["text"]
if "messageStop" in event:
finish_reason = event["messageStop"]["stopReason"]
if "metadata" in event:
usage = event["metadata"]["usage"]
input_tokens = usage["inputTokens"]
output_tokens = usage["outputTokens"]
assert text
assert finish_reason
assert input_tokens
assert output_tokens
(span,) = span_exporter.get_finished_spans()
assert_stream_completion_attributes(
span,
llm_model_value,
input_tokens,
output_tokens,
(finish_reason,),
"chat",
top_p,
temperature,
max_tokens,
stop_sequences,
)
logs = log_exporter.get_finished_logs()
assert len(logs) == 2
assert_message_in_logs(logs[0], "gen_ai.user.message", None, span)
choice_body = {
"index": 0,
"finish_reason": finish_reason,
"message": {"role": "assistant"},
}
assert_message_in_logs(logs[1], "gen_ai.choice", choice_body, span)
@pytest.mark.skipif(BOTO3_VERSION < (1, 35, 56), reason="ConverseStream API not available")
@pytest.mark.vcr()
def test_converse_stream_no_content_different_events(
span_exporter,
log_exporter,
bedrock_runtime_client,
instrument_no_content,
):
messages = anthropic_claude_converse_messages()
llm_model_value = "anthropic.claude-v2"
system_content = anthropic_claude_converse_system()
response = bedrock_runtime_client.converse_stream(
system=system_content,
messages=messages,
modelId=llm_model_value,
)
# consume the stream in order to have it traced
for _ in response["stream"]:
pass
(span,) = span_exporter.get_finished_spans()
assert_stream_completion_attributes(
span,
llm_model_value,
input_tokens=mock.ANY,
output_tokens=mock.ANY,
finish_reason=("end_turn",),
operation_name="chat",
)
logs = log_exporter.get_finished_logs()
assert len(logs) == 5
assert_message_in_logs(logs[0], "gen_ai.system.message", None, span)
assert_message_in_logs(logs[1], "gen_ai.user.message", None, span)
assert_message_in_logs(logs[2], "gen_ai.assistant.message", None, span)
assert_message_in_logs(logs[3], "gen_ai.user.message", None, span)
choice_body = {
"index": 0,
"finish_reason": "end_turn",
"message": {"role": "assistant"},
}
assert_message_in_logs(logs[4], "gen_ai.choice", choice_body, span)
@pytest.mark.skipif(BOTO3_VERSION < (1, 35, 56), reason="ConverseStream API not available")
@pytest.mark.vcr()
def test_converse_stream_no_content_tool_call(
span_exporter,
log_exporter,
bedrock_runtime_client,
instrument_no_content,
):
converse_stream_tool_call(
span_exporter,
log_exporter,
bedrock_runtime_client,
expect_content=False,
)
@pytest.mark.skipif(BOTO3_VERSION < (1, 35, 56), reason="ConverseStream API not available")
@pytest.mark.vcr()
def test_converse_stream_handles_event_stream_error(
span_exporter,
log_exporter,
metric_reader,
bedrock_runtime_client,
instrument_with_content,
):
# pylint:disable=too-many-locals
messages = [{"role": "user", "content": [{"text": "Say this is a test"}]}]
llm_model_value = "amazon.titan-text-lite-v1"
max_tokens, temperature, top_p, stop_sequences = 10, 0.8, 1, ["|"]
response = bedrock_runtime_client.converse_stream(
messages=messages,
modelId=llm_model_value,
inferenceConfig={
"maxTokens": max_tokens,
"temperature": temperature,
"topP": top_p,
"stopSequences": stop_sequences,
},
)
with mock.patch.object(
EventStream,
"_parse_event",
side_effect=EventStreamError({"modelStreamErrorException": {}}, "ConverseStream"),
):
with pytest.raises(EventStreamError):
for _event in response["stream"]:
pass
(span,) = span_exporter.get_finished_spans()
input_tokens, output_tokens, finish_reason = None, None, None
assert_stream_completion_attributes(
span,
llm_model_value,
input_tokens,
output_tokens,
finish_reason,
"chat",
top_p,
temperature,
max_tokens,
stop_sequences,
)
assert span.status.status_code == StatusCode.ERROR
assert span.attributes[ERROR_TYPE] == "EventStreamError"
logs = log_exporter.get_finished_logs()
assert len(logs) == 1
user_content = filter_message_keys(messages[0], ["content"])
assert_message_in_logs(logs[0], "gen_ai.user.message", user_content, span)
metrics = metric_reader.get_metrics_data().resource_metrics
assert_metrics(metrics, "chat", llm_model_value, error_type="EventStreamError")
@pytest.mark.skipif(BOTO3_VERSION < (1, 35, 56), reason="ConverseStream API not available")
@pytest.mark.vcr()
def test_converse_stream_with_invalid_model(
span_exporter,
log_exporter,
bedrock_runtime_client,
instrument_with_content,
):
messages = [{"role": "user", "content": [{"text": "Say this is a test"}]}]
llm_model_value = "does-not-exist"
with pytest.raises(bedrock_runtime_client.exceptions.ValidationException):
bedrock_runtime_client.converse_stream(
messages=messages,
modelId=llm_model_value,
)
(span,) = span_exporter.get_finished_spans()
assert_stream_completion_attributes(
span,
llm_model_value,
operation_name="chat",
)
assert span.status.status_code == StatusCode.ERROR
assert span.attributes[ERROR_TYPE] == "ValidationException"
logs = log_exporter.get_finished_logs()
assert len(logs) == 1
user_content = filter_message_keys(messages[0], ["content"])
assert_message_in_logs(logs[0], "gen_ai.user.message", user_content, span)
@pytest.mark.skipif(BOTO3_VERSION < (1, 35, 56), reason="ConverseStream API not available")
@pytest.mark.vcr()
def test_converse_stream_close_before_consumption(
span_exporter,
log_exporter,
bedrock_runtime_client,
instrument_with_content,
):
messages = [{"role": "user", "content": [{"text": "Say this is a test"}]}]
llm_model_value = "amazon.titan-text-lite-v1"
max_tokens, temperature, top_p, stop_sequences = 10, 0.8, 1, ["|"]
response = bedrock_runtime_client.converse_stream(
messages=messages,
modelId=llm_model_value,
inferenceConfig={
"maxTokens": max_tokens,
"temperature": temperature,
"topP": top_p,
"stopSequences": stop_sequences,
},
)
# Close the stream without consuming it
response["stream"].close()
# Verify span is closed regardless of stream consumption
(span,) = span_exporter.get_finished_spans()
assert_stream_completion_attributes(
span,
llm_model_value,
input_tokens=None,
output_tokens=None,
finish_reason=None,
operation_name="chat",
request_top_p=top_p,
request_temperature=temperature,
request_max_tokens=max_tokens,
request_stop_sequences=stop_sequences,
)
assert span.status.status_code == StatusCode.UNSET
logs = log_exporter.get_finished_logs()
assert len(logs) == 1
user_content = filter_message_keys(messages[0], ["content"])
assert_message_in_logs(logs[0], "gen_ai.user.message", user_content, span)
def get_invoke_model_body(
llm_model,
max_tokens=None,
temperature=None,
top_p=None,
stop_sequences=None,
system=None,
messages=None,
tools=None,
):
def set_if_not_none(config, key, value):
if value is not None:
config[key] = value
prompt = "Say this is a test"
if llm_model == "amazon.nova-micro-v1:0":
config = {}
set_if_not_none(config, "max_new_tokens", max_tokens)
set_if_not_none(config, "temperature", temperature)
set_if_not_none(config, "topP", top_p)
set_if_not_none(config, "stopSequences", stop_sequences)
body = {
"messages": messages if messages else [{"role": "user", "content": [{"text": prompt}]}],
"inferenceConfig": config,
"schemaVersion": "messages-v1",
}
if system:
body["system"] = system
if tools:
body["toolConfig"] = tools
elif llm_model == "amazon.titan-text-lite-v1":
config = {}
set_if_not_none(config, "maxTokenCount", max_tokens)
set_if_not_none(config, "temperature", temperature)
set_if_not_none(config, "topP", top_p)
set_if_not_none(config, "stopSequences", stop_sequences)
body = {"inputText": prompt, "textGenerationConfig": config}
elif "anthropic.claude" in llm_model:
body = {
"messages": messages if messages else [{"role": "user", "content": [{"text": prompt, "type": "text"}]}],
"anthropic_version": "bedrock-2023-05-31",
}
if system:
body["system"] = system
# tools are available since 3+
if tools:
body["tools"] = tools
set_if_not_none(body, "max_tokens", max_tokens)
set_if_not_none(body, "temperature", temperature)
set_if_not_none(body, "top_p", top_p)
set_if_not_none(body, "stop_sequences", stop_sequences)
elif "cohere.command-r" in llm_model:
body = {
"message": prompt,
"max_tokens": max_tokens,
"temperature": temperature,
"p": top_p,
"stop_sequences": stop_sequences,
}
elif "cohere.command" in llm_model:
body = {
"prompt": prompt,
"max_tokens": max_tokens,
"temperature": temperature,
"p": top_p,
"stop_sequences": stop_sequences,
}
elif "meta.llama" in llm_model:
body = {
"prompt": prompt,
"max_gen_len": max_tokens,
"temperature": temperature,
"top_p": top_p,
}
elif "mistral.mistral" in llm_model:
body = {
"prompt": prompt,
"max_tokens": max_tokens,
"temperature": temperature,
"top_p": top_p,
"stop": stop_sequences,
}
else:
raise ValueError(f"No config for {llm_model}")
return json.dumps(body)
def get_model_name_from_family(llm_model):
llm_model_name = {
"amazon.titan": "amazon.titan-text-lite-v1",
"amazon.nova": "amazon.nova-micro-v1:0",
"anthropic.claude": "anthropic.claude-v2",
"cohere.command-r": "cohere.command-r-v1:0",
"cohere.command": "cohere.command-light-text-v14",
"meta.llama": "meta.llama3-1-70b-instruct-v1:0",
"mistral.mistral": "mistral.mistral-7b-instruct-v0:2",
}
return llm_model_name[llm_model]
@pytest.mark.parametrize(
"model_family",
[
"amazon.nova",
"amazon.titan",
"anthropic.claude",
"cohere.command-r",
"cohere.command",
"meta.llama",
"mistral.mistral",
],
)
@pytest.mark.vcr()
def test_invoke_model_with_content(
span_exporter,
log_exporter,
bedrock_runtime_client,
instrument_with_content,
model_family,
):
# pylint:disable=too-many-locals
llm_model_value = get_model_name_from_family(model_family)
max_tokens, temperature, top_p, stop_sequences = (
10,
0.8,
0.99 if model_family == "cohere.command-r" else 1,
["|"],
)
body = get_invoke_model_body(llm_model_value, max_tokens, temperature, top_p, stop_sequences)
response = bedrock_runtime_client.invoke_model(
body=body,
modelId=llm_model_value,
)
(span,) = span_exporter.get_finished_spans()
assert_completion_attributes_from_streaming_body(
span,
llm_model_value,
response,
"text_completion" if model_family == "amazon.titan" else "chat",
top_p,
temperature,
max_tokens,
None if model_family == "meta.llama" else stop_sequences,
)
logs = log_exporter.get_finished_logs()
assert len(logs) == 2
if model_family == "anthropic.claude":
user_content = {"content": [{"text": "Say this is a test", "type": "text"}]}
else:
user_content = {"content": [{"text": "Say this is a test"}]}
if model_family == "amazon.titan":
message = {"content": " comment\nHello! I am writing this as a"}
finish_reason = "LENGTH"
elif model_family == "amazon.nova":
message = {
"role": "assistant",
"content": [{"text": "Certainly, here's a test:\n\n---\n\n**"}],
}
finish_reason = "max_tokens"
elif model_family == "anthropic.claude":
message = {
"role": "assistant",
"content": [{"type": "text", "text": 'Okay, I said "This is a test"'}],
}
finish_reason = "max_tokens"
elif model_family == "cohere.command-r":
message = {
"content": "This is a test. How are you doing today",
}
finish_reason = "MAX_TOKENS"
elif model_family == "cohere.command":
message = {
"content": " Let it be a test of knowledge, skills,",
}
finish_reason = "MAX_TOKENS"
elif model_family == "meta.llama":
message = {
"content": " post. This is a test post. This is",
}
finish_reason = "length"
elif model_family == "mistral.mistral":
message = {
"content": "\n\nA man stands before a crowd of people",
}
finish_reason = "length"
else:
pytest.xfail("model family not handled: {model_family}")
assert_message_in_logs(logs[0], "gen_ai.user.message", user_content, span)
choice_body = {
"index": 0,
"finish_reason": finish_reason,
"message": message,
}
assert_message_in_logs(logs[1], "gen_ai.choice", choice_body, span)
@pytest.mark.vcr()
def test_invoke_model_with_content_user_content_as_string(
span_exporter,
log_exporter,
bedrock_runtime_client,
instrument_with_content,
):
llm_model_value = "us.anthropic.claude-3-5-sonnet-20240620-v1:0"
max_tokens = 10
body = json.dumps(
{
"messages": [{"role": "user", "content": "say this is a test"}],
"max_tokens": max_tokens,
"anthropic_version": "bedrock-2023-05-31",
}
)
response = bedrock_runtime_client.invoke_model(
body=body,
modelId=llm_model_value,
)
(span,) = span_exporter.get_finished_spans()
assert_completion_attributes_from_streaming_body(
span,
llm_model_value,
response,
"chat",
request_max_tokens=max_tokens,
)
logs = log_exporter.get_finished_logs()
assert len(logs) == 2
user_content = {"content": "say this is a test"}
assert_message_in_logs(logs[0], "gen_ai.user.message", user_content, span)
message = {
"role": "assistant",
"content": [{"type": "text", "text": "This is a test."}],
}
choice_body = {
"index": 0,
"finish_reason": "end_turn",
"message": message,
}
assert_message_in_logs(logs[1], "gen_ai.choice", choice_body, span)
@pytest.mark.vcr()
def test_invoke_model_with_content_assistant_content_as_string(
span_exporter,
log_exporter,
bedrock_runtime_client,
instrument_with_content,
):
llm_model_value = "us.anthropic.claude-3-5-haiku-20241022-v1:0"
max_tokens = 10
body = json.dumps(
{
"messages": [
{"role": "user", "content": "say this is a test"},
{"role": "assistant", "content": "{"},
],
"max_tokens": max_tokens,
"anthropic_version": "bedrock-2023-05-31",
}
)
response = bedrock_runtime_client.invoke_model(
body=body,
modelId=llm_model_value,
)
(span,) = span_exporter.get_finished_spans()
assert_completion_attributes_from_streaming_body(
span,
llm_model_value,
response,
"chat",
request_max_tokens=max_tokens,
)
logs = log_exporter.get_finished_logs()
assert len(logs) == 3
user_content = {"content": "say this is a test"}
assert_message_in_logs(logs[0], "gen_ai.user.message", user_content, span)
assistant_content = {"content": "{"}
assert_message_in_logs(logs[1], "gen_ai.assistant.message", assistant_content, span)
assistant_response_message = {
"role": "assistant",
"content": [{"type": "text", "text": "this is a test}"}],
}
choice_body = {
"index": 0,
"finish_reason": "end_turn",
"message": assistant_response_message,
}
assert_message_in_logs(logs[2], "gen_ai.choice", choice_body, span)
@pytest.mark.parametrize(
"model_family",
["amazon.nova", "anthropic.claude"],
)
@pytest.mark.vcr()
def test_invoke_model_with_content_different_events(
span_exporter,
log_exporter,
bedrock_runtime_client,
instrument_with_content,
model_family,
):
# pylint:disable=too-many-locals
llm_model_value = get_model_name_from_family(model_family)
max_tokens = 10
if llm_model_value == "amazon.nova-micro-v1:0":
messages = amazon_nova_messages()
system = amazon_nova_system()
finish_reason = "max_tokens"
choice_content = [{"text": "Again, this is a test. If you need"}]
elif llm_model_value == "anthropic.claude-v2":
messages = anthropic_claude_messages()
system = anthropic_claude_system()
finish_reason = "end_turn"
choice_content = [{"type": "text", "text": "This is a test"}]
else:
pytest.xfail("llm_model_value not handled: {llm_model_value}")
body = get_invoke_model_body(
llm_model_value,
system=system,
messages=messages,
max_tokens=max_tokens,
)
response = bedrock_runtime_client.invoke_model(
body=body,
modelId=llm_model_value,
)
(span,) = span_exporter.get_finished_spans()
assert_completion_attributes_from_streaming_body(
span,
llm_model_value,
response,
"chat",
request_max_tokens=max_tokens,
)
logs = log_exporter.get_finished_logs()
assert len(logs) == 5
assert_message_in_logs(
logs[0],
"gen_ai.system.message",
{"content": [{"text": "You are a friendly model"}]},
span,
)
user_message, assistant_message, last_user_message = messages
user_content = filter_message_keys(user_message, ["content"])
assert_message_in_logs(logs[1], "gen_ai.user.message", user_content, span)
assistant_content = filter_message_keys(assistant_message, ["content"])
assert_message_in_logs(logs[2], "gen_ai.assistant.message", assistant_content, span)
last_user_content = filter_message_keys(last_user_message, ["content"])
assert_message_in_logs(logs[3], "gen_ai.user.message", last_user_content, span)
choice_body = {
"index": 0,
"finish_reason": finish_reason,
"message": {"role": "assistant", "content": choice_content},
}
assert_message_in_logs(logs[4], "gen_ai.choice", choice_body, span)
class AnthropicClaudeModel:
@staticmethod
def user_message(prompt: str):
return {
"text": prompt,
"type": "text",
}
@staticmethod
def tool_config():
return get_anthropic_tool_config()
@staticmethod
def assistant_message(response):
return {"role": response["role"], "content": response["content"]}
@staticmethod
def tool_requests_ids(response):
return [content["id"] for content in response["content"] if content["type"] == "tool_use"]
@staticmethod
def tool_requests_ids_from_stream(stream_content):
return [item["id"] for item in stream_content if item["type"] == "tool_use"]
@staticmethod
def tool_calls_results(tool_requests_ids):
assert len(tool_requests_ids) == 2
return {
"role": "user",
"content": [
{
"type": "tool_result",
"tool_use_id": tool_requests_ids[0],
"content": "50 degrees and raining",
},
{
"type": "tool_result",
"tool_use_id": tool_requests_ids[1],
"content": "70 degrees and sunny",
},
],
}
@staticmethod
def tool_messages(tool_requests_ids, tool_call_result, expect_content):
tool_message_0 = {
"id": tool_requests_ids[0],
"content": tool_call_result["content"][0]["content"] if expect_content else None,
}
tool_message_1 = {
"id": tool_requests_ids[1],
"content": tool_call_result["content"][1]["content"] if expect_content else None,
}
return tool_message_0, tool_message_1
@staticmethod
def choice_content(response):
return response["content"]
@staticmethod
def get_stream_body_content(body):
content = []
content_block = {}
input_json_buf = ""
for event in body:
json_bytes = event["chunk"].get("bytes", b"")
decoded = json_bytes.decode("utf-8")
chunk = json.loads(decoded)
if (message_type := chunk.get("type")) is not None:
if message_type == "content_block_start":
content_block = chunk["content_block"]
elif message_type == "content_block_delta":
if chunk["delta"]["type"] == "text_delta":
content_block["text"] += chunk["delta"]["text"]
elif chunk["delta"]["type"] == "input_json_delta":
input_json_buf += chunk["delta"]["partial_json"]
elif message_type == "content_block_stop":
if input_json_buf:
content_block["input"] = json.loads(input_json_buf)
content.append(content_block)
content_block = None
input_json_buf = ""
return content
class AmazonNovaModel:
@staticmethod
def user_message(prompt: str):
return {
"text": prompt,
}
@staticmethod
def assistant_message(response):
return response["output"]["message"]
@staticmethod
def tool_config():
return get_tool_config()
@staticmethod
def tool_requests_ids(response):
return [
content["toolUse"]["toolUseId"]
for content in response["output"]["message"]["content"]
if "toolUse" in content
]
@staticmethod
def tool_requests_ids_from_stream(stream_content):
return [item["toolUse"]["toolUseId"] for item in stream_content if "toolUse" in item]
@staticmethod
def tool_calls_results(tool_requests_ids):
assert len(tool_requests_ids) == 2
return {
"role": "user",
"content": [
{
"toolResult": {
"toolUseId": tool_requests_ids[0],
"content": [{"json": {"weather": "50 degrees and raining"}}],
}
},
{
"toolResult": {
"toolUseId": tool_requests_ids[1],
"content": [{"json": {"weather": "70 degrees and sunny"}}],
}
},
],
}
@staticmethod
def tool_messages(tool_requests_ids, tool_call_result, expect_content):
tool_message_0 = {
"id": tool_requests_ids[0],
"content": tool_call_result["content"][0]["toolResult"]["content"] if expect_content else None,
}
tool_message_1 = {
"id": tool_requests_ids[1],
"content": tool_call_result["content"][1]["toolResult"]["content"] if expect_content else None,
}
return tool_message_0, tool_message_1
@staticmethod
def choice_content(response):
return response["output"]["message"]["content"]
@staticmethod
def get_stream_body_content(body):
content = []
content_block = {}
tool_use = {}
for event in body:
json_bytes = event["chunk"].get("bytes", b"")
decoded = json_bytes.decode("utf-8")
chunk = json.loads(decoded)
if "contentBlockDelta" in chunk:
delta = chunk["contentBlockDelta"]["delta"]
if "text" in delta:
content_block.setdefault("text", "")
content_block["text"] += delta["text"]
elif "toolUse" in delta:
tool_use["toolUse"]["input"] = json.loads(delta["toolUse"]["input"])
elif "contentBlockStart" in chunk:
if content_block:
content.append(content_block)
content_block = {}
start = chunk["contentBlockStart"]["start"]
if "toolUse" in start:
tool_use = start
elif "contentBlockStop" in chunk:
if tool_use:
content.append(tool_use)
tool_use = {}
elif "messageStop" in chunk:
if content_block:
content.append(content_block)
content_block = {}
return content
def invoke_model_tool_call(
span_exporter,
log_exporter,
bedrock_runtime_client,
llm_model_value,
llm_model_config,
expect_content,
):
# pylint:disable=too-many-locals,too-many-statements
user_prompt = "What is the weather in Seattle and San Francisco today? Please expect one tool call for Seattle and one for San Francisco"
user_msg = llm_model_config.user_message(user_prompt)
messages = [{"role": "user", "content": [user_msg]}]
max_tokens = 1000
tool_config = llm_model_config.tool_config()
body = get_invoke_model_body(
llm_model_value,
messages=messages,
tools=tool_config,
max_tokens=max_tokens,
)
response_0 = bedrock_runtime_client.invoke_model(
body=body,
modelId=llm_model_value,
)
response_0_raw_body = response_0["body"].read()
response_0_body = json.loads(response_0_raw_body)
# replenish body for span assertions
new_stream = io.BytesIO(response_0_raw_body)
response_0["body"] = StreamingBody(new_stream, len(response_0_raw_body))
tool_requests_ids = llm_model_config.tool_requests_ids(response_0_body)
assert len(tool_requests_ids) == 2
assistant_message = llm_model_config.assistant_message(response_0_body)
tool_call_result = llm_model_config.tool_calls_results(tool_requests_ids)
messages.append(assistant_message)
messages.append(tool_call_result)
body = get_invoke_model_body(
llm_model_value,
messages=messages,
max_tokens=max_tokens,
tools=tool_config,
)
response_1 = bedrock_runtime_client.invoke_model(
body=body,
modelId=llm_model_value,
)
response_1_raw_body = response_1["body"].read()
response_1_body = json.loads(response_1_raw_body)
# replenish body for span assertions
new_stream = io.BytesIO(response_1_raw_body)
response_1["body"] = StreamingBody(new_stream, len(response_1_raw_body))
(span_0, span_1) = span_exporter.get_finished_spans()
assert_completion_attributes_from_streaming_body(
span_0,
llm_model_value,
response_0,
"chat",
request_max_tokens=max_tokens,
)
assert_completion_attributes_from_streaming_body(
span_1,
llm_model_value,
response_1,
"chat",
request_max_tokens=max_tokens,
)
logs = log_exporter.get_finished_logs()
assert len(logs) == 8
# first span
if expect_content:
user_content = filter_message_keys(messages[0], ["content"])
else:
user_content = {}
assert_message_in_logs(logs[0], "gen_ai.user.message", user_content, span_0)
function_call_0 = {"name": "get_current_weather"}
function_call_1 = {"name": "get_current_weather"}
if expect_content:
function_call_0["arguments"] = {"location": "Seattle"}
function_call_1["arguments"] = {"location": "San Francisco"}
choice_body = {
"index": 0,
"finish_reason": "tool_use",
"message": {
"role": "assistant",
"tool_calls": [
{
"id": tool_requests_ids[0],
"type": "function",
"function": function_call_0,
},
{
"id": tool_requests_ids[1],
"type": "function",
"function": function_call_1,
},
],
},
}
assert_message_in_logs(logs[1], "gen_ai.choice", choice_body, span_0)
# second span
assert_message_in_logs(logs[2], "gen_ai.user.message", user_content, span_1)
assistant_body = assistant_message
assistant_body["tool_calls"] = choice_body["message"]["tool_calls"]
assistant_body.pop("role")
if not expect_content:
assistant_body.pop("content")
assert_message_in_logs(
logs[3],
"gen_ai.assistant.message",
assistant_body,
span_1,
)
tool_message_0, tool_message_1 = llm_model_config.tool_messages(tool_requests_ids, tool_call_result, expect_content)
assert_message_in_logs(logs[4], "gen_ai.tool.message", tool_message_0, span_1)
assert_message_in_logs(logs[5], "gen_ai.tool.message", tool_message_1, span_1)
user_message_body = tool_call_result
user_message_body.pop("role")
if not expect_content:
user_message_body.pop("content")
assert_message_in_logs(logs[6], "gen_ai.user.message", user_message_body, span_1)
choice_content = llm_model_config.choice_content(response_1_body)
choice_body = {
"index": 0,
"finish_reason": "end_turn",
"message": {
"role": "assistant",
"content": choice_content,
},
}
if not expect_content:
choice_body["message"].pop("content")
assert_message_in_logs(logs[7], "gen_ai.choice", choice_body, span_1)
@pytest.mark.parametrize(
"model_family",
["amazon.nova", "anthropic.claude"],
)
@pytest.mark.vcr()
def test_invoke_model_with_content_tool_call(
span_exporter,
log_exporter,
bedrock_runtime_client,
instrument_with_content,
model_family,
):
if model_family == "amazon.nova":
llm_model_value = "amazon.nova-micro-v1:0"
llm_model_config = AmazonNovaModel
elif model_family == "anthropic.claude":
llm_model_value = "us.anthropic.claude-3-5-sonnet-20240620-v1:0"
llm_model_config = AnthropicClaudeModel
else:
pytest.xfail("model family not handled: {model_family}")
invoke_model_tool_call(
span_exporter,
log_exporter,
bedrock_runtime_client,
llm_model_value,
llm_model_config,
expect_content=True,
)
@pytest.mark.parametrize(
"model_family",
[
"amazon.nova",
"amazon.titan",
"anthropic.claude",
"cohere.command-r",
"cohere.command",
"meta.llama",
"mistral.mistral",
],
)
@pytest.mark.vcr()
def test_invoke_model_no_content(
span_exporter,
log_exporter,
bedrock_runtime_client,
instrument_no_content,
model_family,
):
# pylint:disable=too-many-locals
llm_model_value = get_model_name_from_family(model_family)
max_tokens, temperature, top_p, stop_sequences = (
10,
0.8,
0.99 if model_family == "cohere.command-r" else 1,
["|"],
)
body = get_invoke_model_body(llm_model_value, max_tokens, temperature, top_p, stop_sequences)
response = bedrock_runtime_client.invoke_model(
body=body,
modelId=llm_model_value,
)
(span,) = span_exporter.get_finished_spans()
assert_completion_attributes_from_streaming_body(
span,
llm_model_value,
response,
"text_completion" if model_family == "amazon.titan" else "chat",
top_p,
temperature,
max_tokens,
None if model_family == "meta.llama" else stop_sequences,
)
logs = log_exporter.get_finished_logs()
assert len(logs) == 2
assert_message_in_logs(logs[0], "gen_ai.user.message", None, span)
if model_family in ("anthropic.claude", "amazon.nova"):
choice_message = {"role": "assistant"}
finish_reason = "max_tokens"
elif model_family == "amazon.titan":
choice_message = {}
finish_reason = "LENGTH"
elif model_family == "cohere.command-r":
choice_message = {}
finish_reason = "STOP_SEQUENCE"
elif model_family == "cohere.command":
choice_message = {}
finish_reason = "MAX_TOKENS"
elif model_family in ("meta.llama", "mistral.mistral"):
choice_message = {}
finish_reason = "length"
else:
pytest.xfail("model family not handled: {model_family}")
choice_body = {
"index": 0,
"finish_reason": finish_reason,
"message": choice_message,
}
assert_message_in_logs(logs[1], "gen_ai.choice", choice_body, span)
@pytest.mark.parametrize(
"model_family",
["amazon.nova", "anthropic.claude"],
)
@pytest.mark.vcr()
def test_invoke_model_no_content_different_events(
span_exporter,
log_exporter,
bedrock_runtime_client,
instrument_no_content,
model_family,
):
llm_model_value = get_model_name_from_family(model_family)
max_tokens = 10
if llm_model_value == "amazon.nova-micro-v1:0":
messages = amazon_nova_messages()
system = amazon_nova_system()
finish_reason = "max_tokens"
elif llm_model_value == "anthropic.claude-v2":
messages = anthropic_claude_messages()
system = anthropic_claude_system()
finish_reason = "end_turn"
else:
pytest.xfail("llm_model_value not handled: {llm_model_value}")
body = get_invoke_model_body(
llm_model_value,
max_tokens=max_tokens,
system=system,
messages=messages,
)
response = bedrock_runtime_client.invoke_model(
body=body,
modelId=llm_model_value,
)
(span,) = span_exporter.get_finished_spans()
assert_completion_attributes_from_streaming_body(
span,
llm_model_value,
response,
"chat",
request_max_tokens=max_tokens,
)
logs = log_exporter.get_finished_logs()
assert len(logs) == 5
assert_message_in_logs(logs[0], "gen_ai.system.message", None, span)
assert_message_in_logs(logs[1], "gen_ai.user.message", None, span)
assert_message_in_logs(logs[2], "gen_ai.assistant.message", None, span)
assert_message_in_logs(logs[3], "gen_ai.user.message", None, span)
choice_body = {
"index": 0,
"finish_reason": finish_reason,
"message": {"role": "assistant"},
}
assert_message_in_logs(logs[4], "gen_ai.choice", choice_body, span)
@pytest.mark.parametrize(
"model_family",
["amazon.nova", "anthropic.claude"],
)
@pytest.mark.vcr()
def test_invoke_model_no_content_tool_call(
span_exporter,
log_exporter,
bedrock_runtime_client,
instrument_no_content,
model_family,
):
if model_family == "amazon.nova":
llm_model_value = "amazon.nova-micro-v1:0"
llm_model_config = AmazonNovaModel
elif model_family == "anthropic.claude":
llm_model_value = "us.anthropic.claude-3-5-sonnet-20240620-v1:0"
llm_model_config = AnthropicClaudeModel
else:
pytest.xfail("model family not handled: {model_family}")
invoke_model_tool_call(
span_exporter,
log_exporter,
bedrock_runtime_client,
llm_model_value,
llm_model_config,
expect_content=False,
)
@pytest.mark.vcr()
def test_invoke_model_with_invalid_model(
span_exporter,
log_exporter,
bedrock_runtime_client,
instrument_with_content,
):
llm_model_value = "does-not-exist"
with pytest.raises(bedrock_runtime_client.exceptions.ClientError):
bedrock_runtime_client.invoke_model(
body=b"",
modelId=llm_model_value,
)
(span,) = span_exporter.get_finished_spans()
assert_completion_attributes_from_streaming_body(
span,
llm_model_value,
None,
"chat",
)
assert span.status.status_code == StatusCode.ERROR
assert span.attributes[ERROR_TYPE] == "ValidationException"
logs = log_exporter.get_finished_logs()
assert len(logs) == 0
@pytest.mark.parametrize(
"model_family",
["amazon.nova", "amazon.titan", "anthropic.claude"],
)
@pytest.mark.vcr()
def test_invoke_model_with_response_stream_with_content(
span_exporter,
log_exporter,
bedrock_runtime_client,
instrument_with_content,
model_family,
):
# pylint:disable=too-many-locals,too-many-branches,too-many-statements
llm_model_value = get_model_name_from_family(model_family)
max_tokens, temperature, top_p, stop_sequences = 10, 0.8, 1, ["|"]
body = get_invoke_model_body(llm_model_value, max_tokens, temperature, top_p, stop_sequences)
response = bedrock_runtime_client.invoke_model_with_response_stream(
body=body,
modelId=llm_model_value,
)
# consume the stream in order to have it traced
finish_reason = None
input_tokens, output_tokens = None, None
text = ""
for event in response["body"]:
json_bytes = event["chunk"].get("bytes", b"")
decoded = json_bytes.decode("utf-8")
chunk = json.loads(decoded)
# amazon.titan
if (stop_reason := chunk.get("completionReason")) is not None:
finish_reason = stop_reason
if (output_text := chunk.get("outputText")) is not None:
text += output_text
# amazon.titan, anthropic.claude
if invocation_metrics := chunk.get("amazon-bedrock-invocationMetrics"):
input_tokens = invocation_metrics["inputTokenCount"]
output_tokens = invocation_metrics["outputTokenCount"]
# anthropic.claude
if (message_type := chunk.get("type")) is not None:
if message_type == "content_block_start":
text += chunk["content_block"]["text"]
elif message_type == "content_block_delta":
text += chunk["delta"]["text"]
elif message_type == "message_delta":
finish_reason = chunk["delta"]["stop_reason"]
# amazon nova
if "contentBlockDelta" in chunk:
text += chunk["contentBlockDelta"]["delta"]["text"]
if "messageStop" in chunk:
finish_reason = chunk["messageStop"]["stopReason"]
if "metadata" in chunk:
usage = chunk["metadata"]["usage"]
input_tokens = usage["inputTokens"]
output_tokens = usage["outputTokens"]
assert text
assert finish_reason
assert input_tokens
assert output_tokens
(span,) = span_exporter.get_finished_spans()
assert_stream_completion_attributes(
span,
llm_model_value,
input_tokens,
output_tokens,
(finish_reason,),
"text_completion" if model_family == "amazon.titan" else "chat",
top_p,
temperature,
max_tokens,
stop_sequences,
)
logs = log_exporter.get_finished_logs()
assert len(logs) == 2
if model_family == "anthropic.claude":
user_content = {"content": [{"text": "Say this is a test", "type": "text"}]}
else:
user_content = {"content": [{"text": "Say this is a test"}]}
assert_message_in_logs(logs[0], "gen_ai.user.message", user_content, span)
if model_family == "anthropic.claude":
choice_message = {
"content": [{"text": "Okay, I will repeat: This is a test", "type": "text"}],
"role": "assistant",
}
elif model_family == "amazon.nova":
choice_message = {
"content": [{"text": "It sounds like you're initiating a message or"}],
"role": "assistant",
}
elif model_family == "amazon.titan":
choice_message = {"content": [{"text": "\nHello! I am a computer program designed to"}]}
else:
pytest.xfail("model family not handled: {model_family}")
choice_body = {
"index": 0,
"finish_reason": finish_reason,
"message": choice_message,
}
assert_message_in_logs(logs[1], "gen_ai.choice", choice_body, span)
@pytest.mark.parametrize(
"model_family",
["amazon.nova", "anthropic.claude"],
)
@pytest.mark.vcr()
def test_invoke_model_with_response_stream_with_content_different_events(
span_exporter,
log_exporter,
bedrock_runtime_client,
instrument_with_content,
model_family,
):
# pylint:disable=too-many-locals
llm_model_value = get_model_name_from_family(model_family)
if llm_model_value == "amazon.nova-micro-v1:0":
messages = amazon_nova_messages()
system = amazon_nova_system()
finish_reason = "max_tokens"
choice_content = [{"text": "This is a test again. If you need any"}]
elif llm_model_value == "anthropic.claude-v2":
messages = anthropic_claude_messages()
system = anthropic_claude_system()
finish_reason = "end_turn"
choice_content = [{"text": "This is a test", "type": "text"}]
else:
pytest.xfail("llm_model_value not handled: {llm_model_value}")
max_tokens = 10
body = get_invoke_model_body(
llm_model_value,
system=system,
messages=messages,
max_tokens=max_tokens,
)
response = bedrock_runtime_client.invoke_model_with_response_stream(
body=body,
modelId=llm_model_value,
)
# consume the stream in order to have it traced
for _ in response["body"]:
pass
(span,) = span_exporter.get_finished_spans()
assert_stream_completion_attributes(
span,
llm_model_value,
input_tokens=mock.ANY,
output_tokens=mock.ANY,
request_max_tokens=max_tokens,
finish_reason=(finish_reason,),
operation_name="chat",
)
logs = log_exporter.get_finished_logs()
assert len(logs) == 5
assert_message_in_logs(
logs[0],
"gen_ai.system.message",
{"content": [{"text": "You are a friendly model"}]},
span,
)
user_message, assistant_message, last_user_message = messages
user_content = filter_message_keys(user_message, ["content"])
assert_message_in_logs(logs[1], "gen_ai.user.message", user_content, span)
assistant_content = filter_message_keys(assistant_message, ["content"])
assert_message_in_logs(logs[2], "gen_ai.assistant.message", assistant_content, span)
last_user_content = filter_message_keys(last_user_message, ["content"])
assert_message_in_logs(logs[3], "gen_ai.user.message", last_user_content, span)
choice_body = {
"index": 0,
"finish_reason": finish_reason,
"message": {"content": choice_content, "role": "assistant"},
}
assert_message_in_logs(logs[4], "gen_ai.choice", choice_body, span)
def invoke_model_with_response_stream_tool_call(
span_exporter,
log_exporter,
bedrock_runtime_client,
llm_model_value,
llm_model_config,
expect_content,
):
# pylint:disable=too-many-locals,too-many-statements,too-many-branches
user_prompt = "What is the weather in Seattle and San Francisco today? Please give one tool call for Seattle and one for San Francisco"
user_msg_content = llm_model_config.user_message(user_prompt)
messages = [{"role": "user", "content": [user_msg_content]}]
max_tokens = 1000
tool_config = llm_model_config.tool_config()
body = get_invoke_model_body(
llm_model_value,
messages=messages,
tools=tool_config,
max_tokens=max_tokens,
)
response_0 = bedrock_runtime_client.invoke_model_with_response_stream(
body=body,
modelId=llm_model_value,
)
content = llm_model_config.get_stream_body_content(response_0["body"])
assert content
tool_requests_ids = llm_model_config.tool_requests_ids_from_stream(content)
assert len(tool_requests_ids) == 2
tool_call_result = llm_model_config.tool_calls_results(tool_requests_ids)
# remove extra attributes from response
messages.append({"role": "assistant", "content": content})
messages.append(tool_call_result)
body = get_invoke_model_body(
llm_model_value,
messages=messages,
max_tokens=max_tokens,
tools=tool_config,
)
response_1 = bedrock_runtime_client.invoke_model_with_response_stream(
body=body,
modelId=llm_model_value,
)
response_1_content = llm_model_config.get_stream_body_content(response_1["body"])
assert response_1_content
(span_0, span_1) = span_exporter.get_finished_spans()
assert_stream_completion_attributes(
span_0,
llm_model_value,
input_tokens=mock.ANY,
output_tokens=mock.ANY,
request_max_tokens=max_tokens,
finish_reason=("tool_use",),
operation_name="chat",
)
assert_stream_completion_attributes(
span_1,
llm_model_value,
input_tokens=mock.ANY,
output_tokens=mock.ANY,
request_max_tokens=max_tokens,
finish_reason=("end_turn",),
operation_name="chat",
)
logs = log_exporter.get_finished_logs()
assert len(logs) == 8
# first span
if expect_content:
user_content = filter_message_keys(messages[0], ["content"])
else:
user_content = {}
assert_message_in_logs(logs[0], "gen_ai.user.message", user_content, span_0)
function_call_0 = {"name": "get_current_weather"}
function_call_1 = {"name": "get_current_weather"}
if expect_content:
function_call_0["arguments"] = {"location": "Seattle"}
function_call_1["arguments"] = {"location": "San Francisco"}
choice_body = {
"index": 0,
"finish_reason": "tool_use",
"message": {
"role": "assistant",
"tool_calls": [
{
"id": tool_requests_ids[0],
"type": "function",
"function": function_call_0,
},
{
"id": tool_requests_ids[1],
"type": "function",
"function": function_call_1,
},
],
},
}
assert_message_in_logs(logs[1], "gen_ai.choice", choice_body, span_0)
# second span
assert_message_in_logs(logs[2], "gen_ai.user.message", user_content, span_1)
assistant_body = {"role": "assistant", "content": content}
assistant_body["tool_calls"] = choice_body["message"]["tool_calls"]
assistant_body.pop("role")
if not expect_content:
assistant_body.pop("content")
assert_message_in_logs(
logs[3],
"gen_ai.assistant.message",
assistant_body,
span_1,
)
tool_message_0, tool_message_1 = llm_model_config.tool_messages(tool_requests_ids, tool_call_result, expect_content)
assert_message_in_logs(logs[4], "gen_ai.tool.message", tool_message_0, span_1)
assert_message_in_logs(logs[5], "gen_ai.tool.message", tool_message_1, span_1)
user_message_body = tool_call_result
user_message_body.pop("role")
if not expect_content:
user_message_body.pop("content")
assert_message_in_logs(logs[6], "gen_ai.user.message", user_message_body, span_1)
choice_body = {
"index": 0,
"finish_reason": "end_turn",
"message": {
"role": "assistant",
"content": response_1_content,
},
}
if not expect_content:
choice_body["message"].pop("content")
assert_message_in_logs(logs[7], "gen_ai.choice", choice_body, span_1)
@pytest.mark.parametrize(
"model_family",
["amazon.nova", "anthropic.claude"],
)
@pytest.mark.vcr()
def test_invoke_model_with_response_stream_with_content_tool_call(
span_exporter,
log_exporter,
bedrock_runtime_client,
instrument_with_content,
model_family,
):
if model_family == "amazon.nova":
llm_model_value = "amazon.nova-micro-v1:0"
llm_model_config = AmazonNovaModel
elif model_family == "anthropic.claude":
llm_model_value = "us.anthropic.claude-3-5-sonnet-20240620-v1:0"
llm_model_config = AnthropicClaudeModel
else:
pytest.xfail("model family not handled: {model_family}")
invoke_model_with_response_stream_tool_call(
span_exporter,
log_exporter,
bedrock_runtime_client,
llm_model_value,
llm_model_config,
expect_content=True,
)
@pytest.mark.parametrize(
"model_family",
["amazon.nova", "amazon.titan", "anthropic.claude"],
)
@pytest.mark.vcr()
def test_invoke_model_with_response_stream_no_content(
span_exporter,
log_exporter,
bedrock_runtime_client,
instrument_no_content,
model_family,
):
# pylint:disable=too-many-locals,too-many-branches
llm_model_value = get_model_name_from_family(model_family)
max_tokens, temperature, top_p, stop_sequences = 10, 0.8, 1, ["|"]
body = get_invoke_model_body(llm_model_value, max_tokens, temperature, top_p, stop_sequences)
response = bedrock_runtime_client.invoke_model_with_response_stream(
body=body,
modelId=llm_model_value,
)
# consume the stream in order to have it traced
finish_reason = None
input_tokens, output_tokens = None, None
text = ""
for event in response["body"]:
json_bytes = event["chunk"].get("bytes", b"")
decoded = json_bytes.decode("utf-8")
chunk = json.loads(decoded)
# amazon.titan
if (stop_reason := chunk.get("completionReason")) is not None:
finish_reason = stop_reason
if (output_text := chunk.get("outputText")) is not None:
text += output_text
# amazon.titan, anthropic.claude
if invocation_metrics := chunk.get("amazon-bedrock-invocationMetrics"):
input_tokens = invocation_metrics["inputTokenCount"]
output_tokens = invocation_metrics["outputTokenCount"]
# anthropic.claude
if (message_type := chunk.get("type")) is not None:
if message_type == "content_block_start":
text += chunk["content_block"]["text"]
elif message_type == "content_block_delta":
text += chunk["delta"]["text"]
elif message_type == "message_delta":
finish_reason = chunk["delta"]["stop_reason"]
# amazon nova
if "contentBlockDelta" in chunk:
text += chunk["contentBlockDelta"]["delta"]["text"]
if "messageStop" in chunk:
finish_reason = chunk["messageStop"]["stopReason"]
if "metadata" in chunk:
usage = chunk["metadata"]["usage"]
input_tokens = usage["inputTokens"]
output_tokens = usage["outputTokens"]
assert text
assert finish_reason
assert input_tokens
assert output_tokens
(span,) = span_exporter.get_finished_spans()
assert_stream_completion_attributes(
span,
llm_model_value,
input_tokens,
output_tokens,
(finish_reason,),
"text_completion" if model_family == "amazon.titan" else "chat",
top_p,
temperature,
max_tokens,
stop_sequences,
)
logs = log_exporter.get_finished_logs()
assert len(logs) == 2
assert_message_in_logs(logs[0], "gen_ai.user.message", None, span)
message = {} if model_family == "amazon.titan" else {"role": "assistant"}
choice_body = {
"index": 0,
"finish_reason": finish_reason,
"message": message,
}
assert_message_in_logs(logs[1], "gen_ai.choice", choice_body, span)
@pytest.mark.parametrize(
"model_family",
["amazon.nova", "anthropic.claude"],
)
@pytest.mark.vcr()
def test_invoke_model_with_response_stream_no_content_different_events(
span_exporter,
log_exporter,
bedrock_runtime_client,
instrument_no_content,
model_family,
):
llm_model_value = get_model_name_from_family(model_family)
if llm_model_value == "amazon.nova-micro-v1:0":
messages = amazon_nova_messages()
system = amazon_nova_system()
finish_reason = "max_tokens"
elif llm_model_value == "anthropic.claude-v2":
messages = anthropic_claude_messages()
system = anthropic_claude_system()
finish_reason = "end_turn"
else:
pytest.xfail("llm_model_value not handled: {llm_model_value}")
max_tokens = 10
body = get_invoke_model_body(
llm_model_value,
system=system,
messages=messages,
max_tokens=max_tokens,
)
response = bedrock_runtime_client.invoke_model_with_response_stream(
body=body,
modelId=llm_model_value,
)
# consume the stream in order to have it traced
for _ in response["body"]:
pass
(span,) = span_exporter.get_finished_spans()
assert_stream_completion_attributes(
span,
llm_model_value,
input_tokens=mock.ANY,
output_tokens=mock.ANY,
request_max_tokens=max_tokens,
finish_reason=(finish_reason,),
operation_name="chat",
)
logs = log_exporter.get_finished_logs()
assert len(logs) == 5
assert_message_in_logs(logs[0], "gen_ai.system.message", None, span)
assert_message_in_logs(logs[1], "gen_ai.user.message", None, span)
assert_message_in_logs(logs[2], "gen_ai.assistant.message", None, span)
assert_message_in_logs(logs[3], "gen_ai.user.message", None, span)
choice_body = {
"index": 0,
"finish_reason": finish_reason,
"message": {"role": "assistant"},
}
assert_message_in_logs(logs[4], "gen_ai.choice", choice_body, span)
@pytest.mark.parametrize(
"model_family",
["amazon.nova", "anthropic.claude"],
)
@pytest.mark.vcr()
def test_invoke_model_with_response_stream_no_content_tool_call(
span_exporter,
log_exporter,
bedrock_runtime_client,
instrument_no_content,
model_family,
):
if model_family == "amazon.nova":
llm_model_value = "amazon.nova-micro-v1:0"
llm_model_config = AmazonNovaModel
elif model_family == "anthropic.claude":
llm_model_value = "us.anthropic.claude-3-5-sonnet-20240620-v1:0"
llm_model_config = AnthropicClaudeModel
else:
pytest.xfail("model family not handled: {model_family}")
invoke_model_with_response_stream_tool_call(
span_exporter,
log_exporter,
bedrock_runtime_client,
llm_model_value,
llm_model_config,
expect_content=False,
)
@pytest.mark.parametrize(
"model_family",
["amazon.nova", "amazon.titan", "anthropic.claude"],
)
@pytest.mark.vcr()
def test_invoke_model_with_response_stream_close_before_consumption(
span_exporter,
log_exporter,
bedrock_runtime_client,
instrument_with_content,
model_family,
):
llm_model_value = get_model_name_from_family(model_family)
max_tokens, temperature, top_p, stop_sequences = 10, 0.8, 1, ["|"]
body = get_invoke_model_body(llm_model_value, max_tokens, temperature, top_p, stop_sequences)
response = bedrock_runtime_client.invoke_model_with_response_stream(
body=body,
modelId=llm_model_value,
)
# Close the stream without consuming it
response["body"].close()
# Verify span is closed regardless of stream consumption
(span,) = span_exporter.get_finished_spans()
assert_stream_completion_attributes(
span,
llm_model_value,
input_tokens=None,
output_tokens=None,
finish_reason=None,
operation_name="text_completion" if model_family == "amazon.titan" else "chat",
request_top_p=top_p,
request_temperature=temperature,
request_max_tokens=max_tokens,
request_stop_sequences=None if model_family == "meta.llama" else stop_sequences,
)
assert span.status.status_code == StatusCode.UNSET
logs = log_exporter.get_finished_logs()
assert len(logs) == 1
# Set appropriate user_content based on model family
if model_family == "anthropic.claude":
user_content = {"content": [{"text": "Say this is a test", "type": "text"}]}
else:
user_content = {"content": [{"text": "Say this is a test"}]}
assert_message_in_logs(logs[0], "gen_ai.user.message", user_content, span)
@pytest.mark.vcr()
def test_invoke_model_with_response_stream_handles_stream_error(
span_exporter,
log_exporter,
bedrock_runtime_client,
instrument_with_content,
):
# pylint:disable=too-many-locals
llm_model_value = "amazon.titan-text-lite-v1"
max_tokens, temperature, top_p, stop_sequences = 10, 0.8, 1, ["|"]
body = get_invoke_model_body(llm_model_value, max_tokens, temperature, top_p, stop_sequences)
response = bedrock_runtime_client.invoke_model_with_response_stream(
body=body,
modelId=llm_model_value,
)
# consume the stream in order to have it traced
finish_reason = None
input_tokens, output_tokens = None, None
with mock.patch.object(
EventStream,
"_parse_event",
side_effect=EventStreamError({"modelStreamErrorException": {}}, "InvokeModelWithResponseStream"),
):
with pytest.raises(EventStreamError):
for _event in response["body"]:
pass
(span,) = span_exporter.get_finished_spans()
assert_stream_completion_attributes(
span,
llm_model_value,
input_tokens,
output_tokens,
finish_reason,
"text_completion",
top_p,
temperature,
max_tokens,
stop_sequences,
)
logs = log_exporter.get_finished_logs()
assert len(logs) == 1
user_content = {"content": [{"text": "Say this is a test"}]}
assert_message_in_logs(logs[0], "gen_ai.user.message", user_content, span)
@pytest.mark.vcr()
def test_invoke_model_with_response_stream_invalid_model(
span_exporter,
log_exporter,
bedrock_runtime_client,
instrument_with_content,
):
llm_model_value = "does-not-exist"
with pytest.raises(bedrock_runtime_client.exceptions.ClientError):
bedrock_runtime_client.invoke_model_with_response_stream(
body=b"",
modelId=llm_model_value,
)
(span,) = span_exporter.get_finished_spans()
assert_completion_attributes_from_streaming_body(
span,
llm_model_value,
None,
"chat",
)
assert span.status.status_code == StatusCode.ERROR
assert span.attributes[ERROR_TYPE] == "ValidationException"
logs = log_exporter.get_finished_logs()
assert len(logs) == 0
@pytest.mark.parametrize(
"input_value,expected_output",
[
({"location": "Seattle"}, {"location": "Seattle"}),
({}, {}),
(None, None),
],
)
def test_anthropic_claude_chunk_tool_use_input_handling(input_value, expected_output):
"""Test that _process_anthropic_claude_chunk handles various tool_use input formats."""
def stream_done_callback(response, ended):
pass
def stream_error_callback(exc, ended):
pass
wrapper = InvokeModelWithResponseStreamWrapper(
stream=mock.MagicMock(),
stream_done_callback=stream_done_callback,
stream_error_callback=stream_error_callback,
model_id="anthropic.claude-3-5-sonnet-20240620-v1:0",
)
# Simulate message_start
wrapper._process_anthropic_claude_chunk(
{
"type": "message_start",
"message": {
"role": "assistant",
"content": [],
},
}
)
# Simulate content_block_start with specified input
content_block = {
"type": "tool_use",
"id": "test_id",
"name": "test_tool",
}
if input_value is not None:
content_block["input"] = input_value
wrapper._process_anthropic_claude_chunk(
{
"type": "content_block_start",
"index": 0,
"content_block": content_block,
}
)
# Simulate content_block_stop
wrapper._process_anthropic_claude_chunk({"type": "content_block_stop", "index": 0})
# Verify the message content
assert len(wrapper._message["content"]) == 1
tool_block = wrapper._message["content"][0]
assert tool_block["type"] == "tool_use"
assert tool_block["id"] == "test_id"
assert tool_block["name"] == "test_tool"
if expected_output is not None:
assert tool_block["input"] == expected_output
assert isinstance(tool_block["input"], dict)
else:
assert "input" not in tool_block
def test_converse_stream_with_missing_output_in_response():
# Test malformed response missing "output" key
malformed_response = {"stopReason": "end_turn"}
choice = _Choice.from_converse(malformed_response, capture_content=True)
assert choice.finish_reason == "end_turn"
assert choice.message == {}
assert choice.index == 0
def test_converse_stream_accumulates_cache_tokens():
# The ConverseStream metadata event carries prompt cache token usage;
# the wrapper should accumulate it alongside input/output tokens.
wrapper = ConverseStreamWrapper(
stream=mock.MagicMock(),
stream_done_callback=lambda *args, **kwargs: None,
stream_error_callback=lambda *args, **kwargs: None,
)
wrapper._process_event(
{
"metadata": {
"usage": {
"inputTokens": 8,
"outputTokens": 10,
"cacheReadInputTokens": 1500,
"cacheWriteInputTokens": 25,
}
}
}
)
usage = wrapper._response["usage"]
assert usage["inputTokens"] == 8
assert usage["outputTokens"] == 10
assert usage["cacheReadInputTokens"] == 1500
assert usage["cacheWriteInputTokens"] == 25
def amazon_nova_messages():
return [
{"role": "user", "content": [{"text": "Say this is a test"}]},
{"role": "assistant", "content": [{"text": "This is a test"}]},
{
"role": "user",
"content": [{"text": "Say again this is a test"}],
},
]
def amazon_nova_system():
return [
{"text": "You are a friendly model"},
]
def anthropic_claude_converse_messages():
return amazon_nova_messages()
def anthropic_claude_converse_system():
return amazon_nova_system()
def anthropic_claude_messages():
return [
{
"role": "user",
"content": [{"text": "Say this is a test", "type": "text"}],
},
{
"role": "assistant",
"content": [{"text": "This is a test", "type": "text"}],
},
{
"role": "user",
"content": [{"text": "Say again this is a test", "type": "text"}],
},
]
def anthropic_claude_system():
return "You are a friendly model"
def get_tool_config():
return {
"tools": [
{
"toolSpec": {
"name": "get_current_weather",
"description": "Get the current weather in a given location.",
"inputSchema": {
"json": {
"type": "object",
"properties": {
"location": {
"type": "string",
"description": "The name of the city",
}
},
"required": ["location"],
}
},
}
}
]
}
def get_anthropic_tool_config():
return [
{
"name": "get_current_weather",
"description": "Get the current weather in a given location.",
"input_schema": {
"type": "object",
"properties": {
"location": {
"type": "string",
"description": "The name of the city",
}
},
"required": ["location"],
},
}
]
test_botocore_dynamodb.py 0000664 0000000 0000000 00000042654 15270700723 0041157 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-botocore/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
import json
from unittest import mock
import botocore.session
from moto import mock_aws # pylint: disable=import-error
from opentelemetry.instrumentation.botocore import BotocoreInstrumentor
from opentelemetry.instrumentation.botocore.extensions.dynamodb import (
_BotocoreInstrumentorContext,
_DynamoDbExtension,
)
from opentelemetry.semconv._incubating.attributes import (
aws_attributes,
db_attributes,
)
from opentelemetry.semconv._incubating.attributes.net_attributes import (
NET_PEER_NAME,
)
from opentelemetry.test.test_base import TestBase
from opentelemetry.trace.span import Span
# pylint: disable=too-many-public-methods
class TestDynamoDbExtension(TestBase):
def setUp(self):
super().setUp()
BotocoreInstrumentor().instrument()
session = botocore.session.get_session()
session.set_credentials(access_key="access-key", secret_key="secret-key")
self.client = session.create_client("dynamodb", region_name="us-west-2")
self.default_table_name = "test_table"
def tearDown(self):
super().tearDown()
BotocoreInstrumentor().uninstrument()
def _create_table(self, **kwargs):
create_args = {
"TableName": self.default_table_name,
"AttributeDefinitions": [
{"AttributeName": "id", "AttributeType": "S"},
{"AttributeName": "idl", "AttributeType": "S"},
{"AttributeName": "idg", "AttributeType": "S"},
],
"KeySchema": [{"AttributeName": "id", "KeyType": "HASH"}],
"ProvisionedThroughput": {
"ReadCapacityUnits": 5,
"WriteCapacityUnits": 5,
},
"LocalSecondaryIndexes": [
{
"IndexName": "lsi",
"KeySchema": [{"AttributeName": "idl", "KeyType": "HASH"}],
"Projection": {"ProjectionType": "KEYS_ONLY"},
}
],
"GlobalSecondaryIndexes": [
{
"IndexName": "gsi",
"KeySchema": [{"AttributeName": "idg", "KeyType": "HASH"}],
"Projection": {"ProjectionType": "KEYS_ONLY"},
}
],
}
create_args.update(kwargs)
self.client.create_table(**create_args)
def _create_prepared_table(self, **kwargs):
self._create_table(**kwargs)
table = kwargs.get("TableName", self.default_table_name)
self.client.put_item(
TableName=table,
Item={"id": {"S": "1"}, "idl": {"S": "2"}, "idg": {"S": "3"}},
)
self.memory_exporter.clear()
@staticmethod
def _create_extension(operation: str) -> _DynamoDbExtension:
call_context = mock.MagicMock(operation=operation)
return _DynamoDbExtension(call_context)
def assert_span(self, operation: str) -> Span:
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(1, len(spans))
span = spans[0]
self.assertEqual("dynamodb", span.attributes[db_attributes.DB_SYSTEM])
self.assertEqual(operation, span.attributes[db_attributes.DB_OPERATION])
self.assertEqual(
"dynamodb.us-west-2.amazonaws.com",
span.attributes[NET_PEER_NAME],
)
return span
def assert_table_names(self, span: Span, *table_names):
self.assertEqual(
tuple(table_names),
span.attributes[aws_attributes.AWS_DYNAMODB_TABLE_NAMES],
)
def assert_consumed_capacity(self, span: Span, *table_names):
cap = span.attributes[aws_attributes.AWS_DYNAMODB_CONSUMED_CAPACITY]
self.assertEqual(len(cap), len(table_names))
cap_tables = set()
for item in cap:
# should be like {"TableName": name, "CapacityUnits": number, ...}
deserialized = json.loads(item)
cap_tables.add(deserialized["TableName"])
for table_name in table_names:
self.assertIn(table_name, cap_tables)
def assert_item_col_metrics(self, span: Span):
actual = span.attributes[aws_attributes.AWS_DYNAMODB_ITEM_COLLECTION_METRICS]
self.assertIsNotNone(actual)
json.loads(actual)
def assert_provisioned_read_cap(self, span: Span, expected: int):
actual = span.attributes[aws_attributes.AWS_DYNAMODB_PROVISIONED_READ_CAPACITY]
self.assertEqual(expected, actual)
def assert_provisioned_write_cap(self, span: Span, expected: int):
actual = span.attributes[aws_attributes.AWS_DYNAMODB_PROVISIONED_WRITE_CAPACITY]
self.assertEqual(expected, actual)
def assert_consistent_read(self, span: Span, expected: bool):
actual = span.attributes[aws_attributes.AWS_DYNAMODB_CONSISTENT_READ]
self.assertEqual(expected, actual)
def assert_projection(self, span: Span, expected: str):
actual = span.attributes[aws_attributes.AWS_DYNAMODB_PROJECTION]
self.assertEqual(expected, actual)
def assert_attributes_to_get(self, span: Span, *attrs):
self.assertEqual(
tuple(attrs),
span.attributes[aws_attributes.AWS_DYNAMODB_ATTRIBUTES_TO_GET],
)
def assert_index_name(self, span: Span, expected: str):
self.assertEqual(expected, span.attributes[aws_attributes.AWS_DYNAMODB_INDEX_NAME])
def assert_limit(self, span: Span, expected: int):
self.assertEqual(expected, span.attributes[aws_attributes.AWS_DYNAMODB_LIMIT])
def assert_select(self, span: Span, expected: str):
self.assertEqual(expected, span.attributes[aws_attributes.AWS_DYNAMODB_SELECT])
def assert_extension_item_col_metrics(self, operation: str):
span = self.tracer_provider.get_tracer("test").start_span("test")
extension = self._create_extension(operation)
extension.on_success(
span,
{"ItemCollectionMetrics": {"ItemCollectionKey": {"id": "1"}}},
_BotocoreInstrumentorContext(logger=mock.Mock()),
)
self.assert_item_col_metrics(span)
@mock_aws
def test_batch_get_item(self):
table_name1 = "test_table1"
table_name2 = "test_table2"
self._create_prepared_table(TableName=table_name1)
self._create_prepared_table(TableName=table_name2)
self.client.batch_get_item(
RequestItems={
table_name1: {"Keys": [{"id": {"S": "test_key"}}]},
table_name2: {"Keys": [{"id": {"S": "test_key2"}}]},
},
ReturnConsumedCapacity="TOTAL",
)
span = self.assert_span("BatchGetItem")
self.assert_table_names(span, table_name1, table_name2)
self.assert_consumed_capacity(span, table_name1, table_name2)
@mock_aws
def test_batch_write_item(self):
table_name1 = "test_table1"
table_name2 = "test_table2"
self._create_prepared_table(TableName=table_name1)
self._create_prepared_table(TableName=table_name2)
self.client.batch_write_item(
RequestItems={
table_name1: [{"PutRequest": {"Item": {"id": {"S": "123"}}}}],
table_name2: [{"PutRequest": {"Item": {"id": {"S": "456"}}}}],
},
ReturnConsumedCapacity="TOTAL",
ReturnItemCollectionMetrics="SIZE",
)
span = self.assert_span("BatchWriteItem")
self.assert_table_names(span, table_name1, table_name2)
self.assert_consumed_capacity(span, table_name1, table_name2)
self.assert_item_col_metrics(span)
@mock_aws
def test_create_table(self):
local_sec_idx = {
"IndexName": "local_sec_idx",
"KeySchema": [{"AttributeName": "value", "KeyType": "HASH"}],
"Projection": {"ProjectionType": "KEYS_ONLY"},
}
global_sec_idx = {
"IndexName": "global_sec_idx",
"KeySchema": [{"AttributeName": "value", "KeyType": "HASH"}],
"Projection": {"ProjectionType": "KEYS_ONLY"},
}
self.client.create_table(
AttributeDefinitions=[
{"AttributeName": "id", "AttributeType": "S"},
{"AttributeName": "value", "AttributeType": "S"},
],
KeySchema=[{"AttributeName": "id", "KeyType": "HASH"}],
LocalSecondaryIndexes=[local_sec_idx],
GlobalSecondaryIndexes=[global_sec_idx],
ProvisionedThroughput={
"ReadCapacityUnits": 42,
"WriteCapacityUnits": 17,
},
TableName=self.default_table_name,
)
span = self.assert_span("CreateTable")
self.assert_table_names(span, self.default_table_name)
self.assertEqual(
(json.dumps(global_sec_idx),),
span.attributes[aws_attributes.AWS_DYNAMODB_GLOBAL_SECONDARY_INDEXES],
)
self.assertEqual(
(json.dumps(local_sec_idx),),
span.attributes[aws_attributes.AWS_DYNAMODB_LOCAL_SECONDARY_INDEXES],
)
self.assert_provisioned_read_cap(span, 42)
@mock_aws
def test_delete_item(self):
self._create_prepared_table()
self.client.delete_item(
TableName=self.default_table_name,
Key={"id": {"S": "1"}},
ReturnConsumedCapacity="TOTAL",
ReturnItemCollectionMetrics="SIZE",
)
span = self.assert_span("DeleteItem")
self.assert_table_names(span, self.default_table_name)
# moto does not seem to return these:
# self.assert_consumed_capacity(span, self.default_table_name)
# self.assert_item_coll_metrics(span)
def test_delete_item_consumed_capacity(self):
span = self.tracer_provider.get_tracer("test").start_span("test")
extension = self._create_extension("DeleteItem")
extension.on_success(
span,
{"ConsumedCapacity": {"TableName": "table"}},
_BotocoreInstrumentorContext(logger=mock.Mock()),
)
self.assert_consumed_capacity(span, "table")
def test_delete_item_item_collection_metrics(self):
self.assert_extension_item_col_metrics("DeleteItem")
@mock_aws
def test_delete_table(self):
self._create_prepared_table()
self.client.delete_table(TableName=self.default_table_name)
span = self.assert_span("DeleteTable")
self.assert_table_names(span, self.default_table_name)
@mock_aws
def test_describe_table(self):
self._create_prepared_table()
self.client.describe_table(TableName=self.default_table_name)
span = self.assert_span("DescribeTable")
self.assert_table_names(span, self.default_table_name)
@mock_aws
def test_get_item_expression(self):
self._create_prepared_table()
self.client.get_item(
TableName=self.default_table_name,
Key={"id": {"S": "1"}},
ConsistentRead=True,
ProjectionExpression="PE",
ReturnConsumedCapacity="TOTAL",
)
span = self.assert_span("GetItem")
self.assert_table_names(span, self.default_table_name)
self.assert_consistent_read(span, True)
self.assert_consumed_capacity(span, self.default_table_name)
@mock_aws
def test_get_item_non_expression(self):
self._create_prepared_table()
self.client.get_item(
TableName=self.default_table_name,
Key={"id": {"S": "1"}},
ConsistentRead=True,
ProjectionExpression="PE",
ReturnConsumedCapacity="TOTAL",
)
span = self.assert_span("GetItem")
self.assert_table_names(span, self.default_table_name)
self.assert_consistent_read(span, True)
self.assert_projection(span, "PE")
self.assert_consumed_capacity(span, self.default_table_name)
@mock_aws
def test_list_tables(self):
self._create_table(TableName="my_table")
self._create_prepared_table()
self.client.list_tables(ExclusiveStartTableName="my_table", Limit=5)
span = self.assert_span("ListTables")
self.assertEqual(
"my_table",
span.attributes[aws_attributes.AWS_DYNAMODB_EXCLUSIVE_START_TABLE],
)
self.assertEqual(1, span.attributes[aws_attributes.AWS_DYNAMODB_TABLE_COUNT])
self.assertEqual(5, span.attributes[aws_attributes.AWS_DYNAMODB_LIMIT])
@mock_aws
def test_put_item(self):
table = "test_table"
self._create_prepared_table(TableName=table)
self.client.put_item(
TableName=table,
Item={"id": {"S": "1"}, "idl": {"S": "2"}, "idg": {"S": "3"}},
ReturnConsumedCapacity="TOTAL",
ReturnItemCollectionMetrics="SIZE",
)
span = self.assert_span("PutItem")
self.assert_table_names(span, table)
self.assert_consumed_capacity(span, table)
# moto does not seem to return these:
# self.assert_item_coll_metrics(span)
def test_put_item_item_collection_metrics(self):
self.assert_extension_item_col_metrics("PutItem")
@mock_aws
def test_query(self):
self._create_prepared_table()
self.client.query(
TableName=self.default_table_name,
IndexName="lsi",
Select="ALL_ATTRIBUTES",
AttributesToGet=["id"],
Limit=42,
ConsistentRead=True,
KeyConditions={
"id": {
"AttributeValueList": [{"S": "123"}],
"ComparisonOperator": "EQ",
}
},
ScanIndexForward=True,
ProjectionExpression="PE",
ReturnConsumedCapacity="TOTAL",
)
span = self.assert_span("Query")
self.assert_table_names(span, self.default_table_name)
self.assertTrue(span.attributes[aws_attributes.AWS_DYNAMODB_SCAN_FORWARD])
self.assert_attributes_to_get(span, "id")
self.assert_consistent_read(span, True)
self.assert_index_name(span, "lsi")
self.assert_limit(span, 42)
self.assert_projection(span, "PE")
self.assert_select(span, "ALL_ATTRIBUTES")
self.assert_consumed_capacity(span, self.default_table_name)
@mock_aws
def test_scan(self):
self._create_prepared_table()
self.client.scan(
TableName=self.default_table_name,
IndexName="lsi",
AttributesToGet=["id", "idl"],
Limit=42,
Select="ALL_ATTRIBUTES",
TotalSegments=17,
Segment=16,
ProjectionExpression="PE",
ConsistentRead=True,
ReturnConsumedCapacity="TOTAL",
)
span = self.assert_span("Scan")
self.assert_table_names(span, self.default_table_name)
self.assertEqual(16, span.attributes[aws_attributes.AWS_DYNAMODB_SEGMENT])
self.assertEqual(17, span.attributes[aws_attributes.AWS_DYNAMODB_TOTAL_SEGMENTS])
self.assertEqual(0, span.attributes[aws_attributes.AWS_DYNAMODB_COUNT])
self.assertEqual(0, span.attributes[aws_attributes.AWS_DYNAMODB_SCANNED_COUNT])
self.assert_attributes_to_get(span, "id", "idl")
self.assert_consistent_read(span, True)
self.assert_index_name(span, "lsi")
self.assert_limit(span, 42)
self.assert_projection(span, "PE")
self.assert_select(span, "ALL_ATTRIBUTES")
self.assert_consumed_capacity(span, self.default_table_name)
@mock_aws
def test_update_item(self):
self._create_prepared_table()
self.client.update_item(
TableName=self.default_table_name,
Key={"id": {"S": "123"}},
AttributeUpdates={"id": {"Value": {"S": "456"}, "Action": "PUT"}},
ReturnConsumedCapacity="TOTAL",
ReturnItemCollectionMetrics="SIZE",
)
span = self.assert_span("UpdateItem")
self.assert_table_names(span, self.default_table_name)
self.assert_consumed_capacity(span, self.default_table_name)
# moto does not seem to return these:
# self.assert_item_coll_metrics(span)
def test_update_item_item_collection_metrics(self):
self.assert_extension_item_col_metrics("UpdateItem")
@mock_aws
def test_update_table(self):
self._create_prepared_table()
global_sec_idx_updates = {
"Update": {
"IndexName": "gsi",
"ProvisionedThroughput": {
"ReadCapacityUnits": 777,
"WriteCapacityUnits": 666,
},
}
}
attr_definition = {"AttributeName": "id", "AttributeType": "N"}
self.client.update_table(
TableName=self.default_table_name,
AttributeDefinitions=[attr_definition],
ProvisionedThroughput={
"ReadCapacityUnits": 23,
"WriteCapacityUnits": 19,
},
GlobalSecondaryIndexUpdates=[global_sec_idx_updates],
)
span = self.assert_span("UpdateTable")
self.assert_table_names(span, self.default_table_name)
self.assert_provisioned_read_cap(span, 23)
self.assert_provisioned_write_cap(span, 19)
self.assertEqual(
(json.dumps(attr_definition),),
span.attributes[aws_attributes.AWS_DYNAMODB_ATTRIBUTE_DEFINITIONS],
)
self.assertEqual(
(json.dumps(global_sec_idx_updates),),
span.attributes[aws_attributes.AWS_DYNAMODB_GLOBAL_SECONDARY_INDEX_UPDATES],
)
test_botocore_instrumentation.py 0000664 0000000 0000000 00000050747 15270700723 0042627 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-botocore/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
import json
import os
from importlib.metadata import EntryPoint
from unittest.mock import ANY, Mock, call, patch
from urllib.parse import urlparse
import botocore.session
from botocore.exceptions import ClientError, ParamValidationError
from moto import mock_aws # pylint: disable=import-error
from opentelemetry import trace as trace_api
from opentelemetry.instrumentation.auto_instrumentation import (
_load_instrumentors,
)
from opentelemetry.instrumentation.botocore import BotocoreInstrumentor
from opentelemetry.instrumentation.utils import (
suppress_http_instrumentation,
suppress_instrumentation,
)
from opentelemetry.propagate import get_global_textmap, set_global_textmap
from opentelemetry.propagators.aws.aws_xray_propagator import TRACE_HEADER_KEY
from opentelemetry.semconv._incubating.attributes import rpc_attributes
from opentelemetry.semconv._incubating.attributes.cloud_attributes import (
CLOUD_REGION,
)
from opentelemetry.semconv._incubating.attributes.exception_attributes import (
EXCEPTION_MESSAGE,
EXCEPTION_STACKTRACE,
EXCEPTION_TYPE,
)
from opentelemetry.semconv._incubating.attributes.http_attributes import (
HTTP_STATUS_CODE,
)
from opentelemetry.semconv._incubating.attributes.server_attributes import (
SERVER_ADDRESS,
SERVER_PORT,
)
from opentelemetry.test.mock_textmap import MockTextMapPropagator
from opentelemetry.test.test_base import TestBase
from opentelemetry.trace.span import format_span_id, format_trace_id
_REQUEST_ID_REGEX_MATCH = r"[A-Za-z0-9]{52}"
# pylint:disable=too-many-public-methods
class TestBotocoreInstrumentor(TestBase):
"""Botocore integration testsuite"""
def setUp(self):
super().setUp()
BotocoreInstrumentor().instrument()
self.session = botocore.session.get_session()
self.session.set_credentials(access_key="access-key", secret_key="secret-key")
self.region = "us-west-2"
def tearDown(self):
super().tearDown()
BotocoreInstrumentor().uninstrument()
def _make_client(self, service: str):
return self.session.create_client(service, region_name=self.region)
def _default_span_attributes(self, service: str, operation: str):
return {
rpc_attributes.RPC_SYSTEM: "aws-api",
rpc_attributes.RPC_SERVICE: service,
rpc_attributes.RPC_METHOD: operation,
CLOUD_REGION: self.region,
"retry_attempts": 0,
HTTP_STATUS_CODE: 200,
# Some services like IAM or STS have a global endpoint and exclude specified region.
SERVER_ADDRESS: f"{service.lower()}.{'' if self.region == 'aws-global' else self.region + '.'}amazonaws.com",
SERVER_PORT: 443,
}
def assert_only_span(self):
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(1, len(spans))
return spans[0]
def assert_span(
self,
service: str,
operation: str,
request_id=None,
attributes=None,
):
span = self.assert_only_span()
expected = self._default_span_attributes(service, operation)
if attributes:
expected.update(attributes)
span_attributes_request_id = "aws.request_id"
if request_id is _REQUEST_ID_REGEX_MATCH:
actual_request_id = span.attributes[span_attributes_request_id]
self.assertRegex(actual_request_id, _REQUEST_ID_REGEX_MATCH)
expected[span_attributes_request_id] = actual_request_id
elif request_id is not None:
expected[span_attributes_request_id] = request_id
self.assertSpanHasAttributes(span, expected)
self.assertEqual(f"{service}.{operation}", span.name)
return span
@mock_aws
def test_traced_client(self):
ec2 = self._make_client("ec2")
ec2.describe_instances()
request_id = "fdcdcab1-ae5c-489e-9c33-4637c5dda355"
self.assert_span("EC2", "DescribeInstances", request_id=request_id)
@mock_aws
def test_no_op_tracer_provider_ec2(self):
BotocoreInstrumentor().uninstrument()
BotocoreInstrumentor().instrument(tracer_provider=trace_api.NoOpTracerProvider())
ec2 = self._make_client("ec2")
ec2.describe_instances()
spans_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans_list), 0)
@mock_aws
def test_not_recording(self):
mock_tracer = Mock()
mock_span = Mock()
mock_span.is_recording.return_value = False
mock_tracer.start_span.return_value = mock_span
with patch("opentelemetry.trace.get_tracer") as tracer:
tracer.return_value = mock_tracer
ec2 = self._make_client("ec2")
ec2.describe_instances()
self.assertFalse(mock_span.is_recording())
self.assertTrue(mock_span.is_recording.called)
self.assertFalse(mock_span.set_attribute.called)
self.assertFalse(mock_span.set_status.called)
@mock_aws
def test_exception(self):
s3 = self._make_client("s3")
with self.assertRaises(ParamValidationError):
s3.list_objects(bucket="mybucket")
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(1, len(spans))
span = spans[0]
expected = self._default_span_attributes("S3", "ListObjects")
expected.pop(HTTP_STATUS_CODE)
expected.pop("retry_attempts")
self.assertEqual(expected, span.attributes)
self.assertIs(span.status.status_code, trace_api.StatusCode.ERROR)
self.assertEqual(1, len(span.events))
event = span.events[0]
self.assertIn(EXCEPTION_STACKTRACE, event.attributes)
self.assertIn(EXCEPTION_TYPE, event.attributes)
self.assertIn(EXCEPTION_MESSAGE, event.attributes)
@mock_aws
def test_client_error_with_http_error_status(self):
"""ClientError with HTTP 4xx sets span status to ERROR."""
s3 = self._make_client("s3")
with self.assertRaises(ClientError):
s3.get_object(Bucket="non-existent-bucket", Key="non-existent-key")
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(1, len(spans))
span = spans[0]
self.assertIs(span.status.status_code, trace_api.StatusCode.ERROR)
@mock_aws
def test_client_error_304_not_modified(self):
"""S3 IfNoneMatch returning 304 leaves span status as UNSET."""
s3 = self._make_client("s3")
s3.create_bucket(
Bucket="test-bucket",
CreateBucketConfiguration={"LocationConstraint": self.region},
)
etag = s3.put_object(Bucket="test-bucket", Key="key", Body=b"data")["ETag"]
with self.assertRaises(ClientError):
s3.get_object(Bucket="test-bucket", Key="key", IfNoneMatch=etag)
spans = self.memory_exporter.get_finished_spans()
# Filter to the GetObject span
get_spans = [s for s in spans if s.name == "S3.GetObject"]
self.assertEqual(1, len(get_spans))
self.assertIs(get_spans[0].status.status_code, trace_api.StatusCode.UNSET)
@mock_aws
def test_s3_client(self):
s3 = self._make_client("s3")
s3.list_buckets()
self.assert_span("S3", "ListBuckets")
@mock_aws
def test_no_op_tracer_provider_s3(self):
BotocoreInstrumentor().uninstrument()
BotocoreInstrumentor().instrument(tracer_provider=trace_api.NoOpTracerProvider())
s3 = self._make_client("s3")
s3.list_buckets()
spans_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans_list), 0)
@mock_aws
def test_s3_put(self):
s3 = self._make_client("s3")
location = {"LocationConstraint": "us-west-2"}
s3.create_bucket(Bucket="mybucket", CreateBucketConfiguration=location)
self.assert_span("S3", "CreateBucket", request_id=_REQUEST_ID_REGEX_MATCH)
self.memory_exporter.clear()
s3.put_object(Key="foo", Bucket="mybucket", Body=b"bar")
self.assert_span("S3", "PutObject", request_id=_REQUEST_ID_REGEX_MATCH)
self.memory_exporter.clear()
s3.get_object(Bucket="mybucket", Key="foo")
self.assert_span("S3", "GetObject", request_id=_REQUEST_ID_REGEX_MATCH)
@mock_aws
def test_sqs_client(self):
sqs = self._make_client("sqs")
sqs.list_queues()
self.assert_span("SQS", "ListQueues", request_id=_REQUEST_ID_REGEX_MATCH)
@mock_aws
def test_no_op_tracer_provider_sqs(self):
BotocoreInstrumentor().uninstrument()
BotocoreInstrumentor().instrument(tracer_provider=trace_api.NoOpTracerProvider())
sqs = self._make_client("sqs")
sqs.list_queues()
spans_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans_list), 0)
@mock_aws
def test_sqs_send_message(self):
sqs = self._make_client("sqs")
test_queue_name = "test_queue_name"
response = sqs.create_queue(QueueName=test_queue_name)
self.assert_span("SQS", "CreateQueue", request_id=_REQUEST_ID_REGEX_MATCH)
self.memory_exporter.clear()
queue_url = response["QueueUrl"]
sqs.send_message(QueueUrl=queue_url, MessageBody="Test SQS MESSAGE!")
self.assert_span(
"SQS",
"SendMessage",
request_id=_REQUEST_ID_REGEX_MATCH,
attributes={"aws.queue_url": queue_url},
)
@mock_aws
def test_kinesis_client(self):
kinesis = self._make_client("kinesis")
kinesis.list_streams()
self.assert_span("Kinesis", "ListStreams")
@mock_aws
def test_no_op_tracer_provider_kinesis(self):
BotocoreInstrumentor().uninstrument()
BotocoreInstrumentor().instrument(tracer_provider=trace_api.NoOpTracerProvider())
kinesis = self._make_client("kinesis")
kinesis.list_streams()
spans_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans_list), 0)
@mock_aws
def test_unpatch(self):
kinesis = self._make_client("kinesis")
BotocoreInstrumentor().uninstrument()
kinesis.list_streams()
self.assertEqual(0, len(self.memory_exporter.get_finished_spans()))
@mock_aws
def test_no_op_tracer_provider_kms(self):
BotocoreInstrumentor().uninstrument()
BotocoreInstrumentor().instrument(tracer_provider=trace_api.NoOpTracerProvider())
kms = self._make_client("kms")
kms.list_keys(Limit=21)
spans_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans_list), 0)
@mock_aws
def test_uninstrument_does_not_inject_headers(self):
headers = {}
def intercept_headers(**kwargs):
headers.update(kwargs["request"].headers)
ec2 = self._make_client("ec2")
BotocoreInstrumentor().uninstrument()
ec2.meta.events.register_first("before-send.ec2.DescribeInstances", intercept_headers)
with self.tracer_provider.get_tracer("test").start_span("parent"):
ec2.describe_instances()
self.assertNotIn(TRACE_HEADER_KEY, headers)
@mock_aws
def test_double_patch(self):
sqs = self._make_client("sqs")
BotocoreInstrumentor().instrument()
BotocoreInstrumentor().instrument()
sqs.list_queues()
self.assert_span("SQS", "ListQueues", request_id=_REQUEST_ID_REGEX_MATCH)
@mock_aws
def test_kms_client(self):
kms = self._make_client("kms")
kms.list_keys(Limit=21)
span = self.assert_only_span()
expected = self._default_span_attributes("KMS", "ListKeys")
expected["aws.request_id"] = ANY
# check for exact attribute set to make sure not to leak any kms secrets
self.assertEqual(expected, dict(span.attributes))
@mock_aws
def test_sts_client(self):
sts = self._make_client("sts")
sts.get_caller_identity()
span = self.assert_only_span()
expected = self._default_span_attributes("STS", "GetCallerIdentity")
expected["aws.request_id"] = ANY
expected[SERVER_ADDRESS] = urlparse(sts.meta.endpoint_url).hostname
# check for exact attribute set to make sure not to leak any sts secrets
self.assertEqual(expected, dict(span.attributes))
@mock_aws
def test_no_op_tracer_provider_sts(self):
BotocoreInstrumentor().uninstrument()
BotocoreInstrumentor().instrument(tracer_provider=trace_api.NoOpTracerProvider())
sts = self._make_client("sts")
sts.get_caller_identity()
spans_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans_list), 0)
@mock_aws
def test_propagator_injects_into_request(self):
headers = {}
previous_propagator = get_global_textmap()
def check_headers(**kwargs):
nonlocal headers
headers = kwargs["request"].headers
try:
set_global_textmap(MockTextMapPropagator())
ec2 = self._make_client("ec2")
ec2.meta.events.register_first("before-send.ec2.DescribeInstances", check_headers)
ec2.describe_instances()
request_id = "fdcdcab1-ae5c-489e-9c33-4637c5dda355"
span = self.assert_span("EC2", "DescribeInstances", request_id=request_id)
# only x-ray propagation is used in HTTP requests
self.assertIn(TRACE_HEADER_KEY, headers)
xray_context = headers[TRACE_HEADER_KEY]
formated_trace_id = format_trace_id(span.get_span_context().trace_id)
formated_trace_id = formated_trace_id[:8] + "-" + formated_trace_id[8:]
self.assertEqual(
xray_context.lower(),
f"root=1-{formated_trace_id};parent={format_span_id(span.get_span_context().span_id)};sampled=1".lower(),
)
finally:
set_global_textmap(previous_propagator)
@mock_aws
def test_no_op_tracer_provider_xray(self):
BotocoreInstrumentor().uninstrument()
BotocoreInstrumentor().instrument(tracer_provider=trace_api.NoOpTracerProvider())
xray_client = self._make_client("xray")
xray_client.put_trace_segments(TraceSegmentDocuments=["str1"])
spans_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans_list), 0)
@mock_aws
def test_override_xray_propagator_injects_into_request(self):
headers = {}
def check_headers(**kwargs):
nonlocal headers
headers = kwargs["request"].headers
BotocoreInstrumentor().instrument()
ec2 = self._make_client("ec2")
ec2.meta.events.register_first("before-send.ec2.DescribeInstances", check_headers)
ec2.describe_instances()
self.assertNotIn(MockTextMapPropagator.TRACE_ID_KEY, headers)
self.assertNotIn(MockTextMapPropagator.SPAN_ID_KEY, headers)
@mock_aws
def test_suppress_instrumentation_xray_client(self):
xray_client = self._make_client("xray")
with suppress_instrumentation():
xray_client.put_trace_segments(TraceSegmentDocuments=["str1"])
xray_client.put_trace_segments(TraceSegmentDocuments=["str2"])
self.assertEqual(0, len(self.get_finished_spans()))
@mock_aws
def test_suppress_http_instrumentation_xray_client(self):
xray_client = self._make_client("xray")
with suppress_http_instrumentation():
xray_client.put_trace_segments(TraceSegmentDocuments=["str1"])
xray_client.put_trace_segments(TraceSegmentDocuments=["str2"])
self.assertEqual(2, len(self.get_finished_spans()))
@mock_aws
def test_request_hook(self):
request_hook_service_attribute_name = "request_hook.service_name"
request_hook_operation_attribute_name = "request_hook.operation_name"
request_hook_api_params_attribute_name = "request_hook.api_params"
def request_hook(span, service_name, operation_name, api_params):
hook_attributes = {
request_hook_service_attribute_name: service_name,
request_hook_operation_attribute_name: operation_name,
request_hook_api_params_attribute_name: json.dumps(api_params),
}
span.set_attributes(hook_attributes)
BotocoreInstrumentor().uninstrument()
BotocoreInstrumentor().instrument(request_hook=request_hook)
s3 = self._make_client("s3")
params = {
"Bucket": "mybucket",
"CreateBucketConfiguration": {"LocationConstraint": "us-west-2"},
}
s3.create_bucket(**params)
self.assert_span(
"S3",
"CreateBucket",
attributes={
request_hook_service_attribute_name: "s3",
request_hook_operation_attribute_name: "CreateBucket",
request_hook_api_params_attribute_name: json.dumps(params),
},
)
@mock_aws
def test_response_hook(self):
response_hook_service_attribute_name = "request_hook.service_name"
response_hook_operation_attribute_name = "response_hook.operation_name"
response_hook_result_attribute_name = "response_hook.result"
def response_hook(span, service_name, operation_name, result):
hook_attributes = {
response_hook_service_attribute_name: service_name,
response_hook_operation_attribute_name: operation_name,
response_hook_result_attribute_name: len(result["Buckets"]),
}
span.set_attributes(hook_attributes)
BotocoreInstrumentor().uninstrument()
BotocoreInstrumentor().instrument(response_hook=response_hook)
s3 = self._make_client("s3")
s3.list_buckets()
self.assert_span(
"S3",
"ListBuckets",
attributes={
response_hook_service_attribute_name: "s3",
response_hook_operation_attribute_name: "ListBuckets",
response_hook_result_attribute_name: 0,
},
)
@mock_aws
def test_server_attributes(self):
# Test regional endpoint
ec2 = self._make_client("ec2")
ec2.describe_instances()
self.assert_span(
"EC2",
"DescribeInstances",
attributes={
SERVER_ADDRESS: f"ec2.{self.region}.amazonaws.com",
SERVER_PORT: 443,
},
)
self.memory_exporter.clear()
# Test global endpoint
iam_global = self._make_client("iam")
iam_global.list_users()
self.assert_span(
"IAM",
"ListUsers",
attributes={
SERVER_ADDRESS: "iam.amazonaws.com",
SERVER_PORT: 443,
CLOUD_REGION: "aws-global",
},
)
@mock_aws
def test_server_attributes_with_custom_endpoint(self):
with patch.dict(
os.environ,
{"MOTO_S3_CUSTOM_ENDPOINTS": "https://proxy.amazon.org:2025"},
):
s3 = self.session.create_client(
"s3",
region_name=self.region,
endpoint_url="https://proxy.amazon.org:2025",
)
s3.list_buckets()
self.assert_span(
"S3",
"ListBuckets",
attributes={
SERVER_ADDRESS: "proxy.amazon.org",
SERVER_PORT: 2025,
},
)
@patch("opentelemetry.instrumentation.auto_instrumentation._load.get_dist_dependency_conflicts")
@patch("opentelemetry.instrumentation.auto_instrumentation._load._logger")
def test_instruments_with_botocore_installed(self, mock_logger, mock_dep):
def _load_instrumentor(ep: EntryPoint, **kwargs):
# simulate aiobotocore not being present
if ep.name == "aiobotocore":
raise ModuleNotFoundError("aiobotocore")
mock_distro = Mock()
mock_dep.return_value = None
mock_distro.load_instrumentor.side_effect = _load_instrumentor
_load_instrumentors(mock_distro)
eps = [c[0][0].name for c in mock_distro.load_instrumentor.call_args_list]
self.assertIn("botocore", eps)
mock_logger.debug.assert_has_calls(
[
call("Instrumented %s", "botocore"),
call(
"Skipping instrumentation %s: %s",
"aiobotocore",
"aiobotocore",
),
],
any_order=True,
)
test_botocore_lambda.py 0000664 0000000 0000000 00000013561 15270700723 0040575 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-botocore/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
import io
import json
import sys
import zipfile
from unittest import mock
import botocore.session
from moto import mock_aws # pylint: disable=import-error
from pytest import mark
from opentelemetry.instrumentation.botocore import BotocoreInstrumentor
from opentelemetry.instrumentation.botocore.extensions.lmbd import (
_LambdaExtension,
)
from opentelemetry.propagate import get_global_textmap, set_global_textmap
from opentelemetry.semconv._incubating.attributes import rpc_attributes
from opentelemetry.semconv._incubating.attributes.faas_attributes import (
FAAS_INVOKED_NAME,
FAAS_INVOKED_PROVIDER,
FAAS_INVOKED_REGION,
)
from opentelemetry.test.mock_textmap import MockTextMapPropagator
from opentelemetry.test.test_base import TestBase
from opentelemetry.trace.span import Span
def get_as_zip_file(file_name, content):
zip_output = io.BytesIO()
with zipfile.ZipFile(zip_output, "w", zipfile.ZIP_DEFLATED) as zip_file:
zip_file.writestr(file_name, content)
zip_output.seek(0)
return zip_output.read()
def return_headers_lambda_str():
pfunc = """
def lambda_handler(event, context):
print("custom log event")
headers = event.get('headers', event.get('attributes', {}))
return headers
"""
return pfunc
class TestLambdaExtension(TestBase):
def setUp(self):
super().setUp()
BotocoreInstrumentor().instrument()
session = botocore.session.get_session()
session.set_credentials(access_key="access-key", secret_key="secret-key")
self.region = "us-west-2"
self.client = session.create_client("lambda", region_name=self.region)
self.iam_client = session.create_client("iam", region_name=self.region)
def tearDown(self):
super().tearDown()
BotocoreInstrumentor().uninstrument()
def assert_span(self, operation: str) -> Span:
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(1, len(spans))
span = spans[0]
self.assertEqual(operation, span.attributes[rpc_attributes.RPC_METHOD])
self.assertEqual("Lambda", span.attributes[rpc_attributes.RPC_SERVICE])
self.assertEqual("aws-api", span.attributes[rpc_attributes.RPC_SYSTEM])
return span
def assert_invoke_span(self, function_name: str) -> Span:
span = self.assert_span("Invoke")
self.assertEqual("aws", span.attributes[FAAS_INVOKED_PROVIDER])
self.assertEqual(self.region, span.attributes[FAAS_INVOKED_REGION])
self.assertEqual(function_name, span.attributes[FAAS_INVOKED_NAME])
return span
@staticmethod
def _create_extension(operation: str) -> _LambdaExtension:
mock_call_context = mock.MagicMock(operation=operation, params={})
return _LambdaExtension(mock_call_context)
@mock_aws
def test_list_functions(self):
self.client.list_functions()
self.assert_span("ListFunctions")
@mock_aws
def _create_role_and_get_arn(self) -> str:
return self.iam_client.create_role(
RoleName="my-role",
AssumeRolePolicyDocument="some policy",
Path="/my-path/",
)["Role"]["Arn"]
def _create_lambda_function(self, function_name: str, function_code: str):
role_arn = self._create_role_and_get_arn()
self.client.create_function(
FunctionName=function_name,
Runtime="python3.10",
Role=role_arn,
Handler="lambda_function.lambda_handler",
Code={"ZipFile": get_as_zip_file("lambda_function.py", function_code)},
Description="test lambda function",
Timeout=3,
MemorySize=128,
Publish=True,
)
@mark.skip(reason="Docker error, unblocking builds for now.")
@mark.skipif(
sys.platform == "win32",
reason="requires docker and Github CI Windows does not have docker installed by default",
)
@mock_aws
def test_invoke(self):
previous_propagator = get_global_textmap()
try:
set_global_textmap(MockTextMapPropagator())
function_name = "testFunction"
self._create_lambda_function(function_name, return_headers_lambda_str())
# 2 spans for create IAM + create lambda
self.assertEqual(2, len(self.memory_exporter.get_finished_spans()))
self.memory_exporter.clear()
response = self.client.invoke(
Payload=json.dumps({}),
FunctionName=function_name,
InvocationType="RequestResponse",
)
span = self.assert_invoke_span(function_name)
span_context = span.get_span_context()
# # assert injected span
headers = json.loads(response["Payload"].read().decode("utf-8"))
self.assertEqual(
str(span_context.trace_id),
headers[MockTextMapPropagator.TRACE_ID_KEY],
)
self.assertEqual(
str(span_context.span_id),
headers[MockTextMapPropagator.SPAN_ID_KEY],
)
finally:
set_global_textmap(previous_propagator)
def test_invoke_parse_arn(self):
function_name = "my_func"
arns = (
f"arn:aws:lambda:{self.region}:000000000000:function:{function_name}", # full arn
f"000000000000:{function_name}", # partial arn
f"arn:aws:lambda:{self.region}:000000000000:function:{function_name}:alias", # aliased arn
)
for arn in arns:
with self.subTest(arn=arn):
extension = self._create_extension("Invoke")
extension._call_context.params["FunctionName"] = arn
attributes = {}
extension.extract_attributes(attributes)
self.assertEqual(function_name, attributes[FAAS_INVOKED_NAME])
test_botocore_messaging.py 0000664 0000000 0000000 00000002471 15270700723 0041330 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-botocore/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
from opentelemetry.instrumentation.botocore.extensions._messaging import (
inject_propagation_context,
message_attributes_setter,
)
from opentelemetry.test.test_base import TestBase
class TestMessageAttributes(TestBase):
def test_message_attributes_setter(self):
carrier = {}
message_attributes_setter.set(carrier, "key", "value")
self.assertEqual({"key": {"DataType": "String", "StringValue": "value"}}, carrier)
def test_inject_propagation_context(self):
carrier = {
"key1": {"DataType": "String", "StringValue": "value1"},
"key2": {"DataType": "String", "StringValue": "value2"},
}
tracer = self.tracer_provider.get_tracer("test-tracer")
with tracer.start_as_current_span("span"):
inject_propagation_context(carrier)
self.assertGreater(len(carrier), 2)
def test_inject_propagation_context_too_many_attributes(self):
carrier = {f"key{idx}": {"DataType": "String", "StringValue": f"value{idx}"} for idx in range(10)}
tracer = self.tracer_provider.get_tracer("test-tracer")
with tracer.start_as_current_span("span"):
inject_propagation_context(carrier)
self.assertEqual(10, len(carrier))
test_botocore_secretsmanager.py 0000664 0000000 0000000 00000004355 15270700723 0042361 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-botocore/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
import botocore.session
from moto import mock_aws
from opentelemetry.instrumentation.botocore import BotocoreInstrumentor
from opentelemetry.semconv._incubating.attributes.aws_attributes import (
AWS_SECRETSMANAGER_SECRET_ARN,
)
from opentelemetry.test.test_base import TestBase
class TestSecretsManagerExtension(TestBase):
def setUp(self):
super().setUp()
BotocoreInstrumentor().instrument()
session = botocore.session.get_session()
session.set_credentials(access_key="access-key", secret_key="secret-key")
self.region = "us-west-2"
self.client = session.create_client("secretsmanager", region_name=self.region)
def tearDown(self):
super().tearDown()
BotocoreInstrumentor().uninstrument()
def create_secret_and_get_arn(self, name: str = "test-secret") -> str:
"""
Create a secret in mocked Secrets Manager and return its ARN.
"""
# Clear spans before creating secret for helper method
self.memory_exporter.clear()
response = self.client.create_secret(Name=name, SecretString="test-secret-value")
return response["ARN"]
@mock_aws
def test_tag_resource_with_arn(self):
secret_arn = self.create_secret_and_get_arn()
self.client.tag_resource(SecretId=secret_arn, Tags=[{"Key": "Environment", "Value": "Test"}])
spans = self.memory_exporter.get_finished_spans()
assert spans
self.assertEqual(len(spans), 2)
span = spans[1] # tag_resource span
self.assertEqual(
span.attributes[AWS_SECRETSMANAGER_SECRET_ARN],
secret_arn,
)
@mock_aws
def test_create_secret(self):
secret_name = "test-secret"
response = self.client.create_secret(Name=secret_name, SecretString="test-secret-value")
secret_arn = response["ARN"]
spans = self.memory_exporter.get_finished_spans()
assert spans
self.assertEqual(len(spans), 1)
span = spans[0] # create_secret span
# Should capture ARN from response
self.assertEqual(
span.attributes[AWS_SECRETSMANAGER_SECRET_ARN],
secret_arn,
)
test_botocore_sfns.py 0000664 0000000 0000000 00000007217 15270700723 0040327 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-botocore/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
import json
import botocore.session
from moto import mock_aws
from opentelemetry.instrumentation.botocore import BotocoreInstrumentor
from opentelemetry.semconv._incubating.attributes.aws_attributes import (
AWS_STEP_FUNCTIONS_ACTIVITY_ARN,
AWS_STEP_FUNCTIONS_STATE_MACHINE_ARN,
)
from opentelemetry.test.test_base import TestBase
class TestSfnsExtension(TestBase):
def setUp(self):
super().setUp()
BotocoreInstrumentor().instrument()
session = botocore.session.get_session()
session.set_credentials(access_key="access-key", secret_key="secret-key")
self.region = "us-west-2"
self.client = session.create_client("stepfunctions", region_name=self.region)
def tearDown(self):
super().tearDown()
BotocoreInstrumentor().uninstrument()
SIMPLE_STATE_MACHINE_DEF = {
"Comment": "A simple Hello World example",
"StartAt": "HelloState",
"States": {
"HelloState": {
"Type": "Pass",
"Result": "Hello, Moto!",
"End": True,
}
},
}
def create_state_machine_and_get_arn(self, name: str = "TestStateMachine") -> str:
"""
Create a state machine in mocked Step Functions and return its ARN.
"""
definition_json = json.dumps(self.SIMPLE_STATE_MACHINE_DEF)
role_arn = "arn:aws:iam::123456789012:role/DummyRole"
response = self.client.create_state_machine(
name=name,
definition=definition_json,
roleArn=role_arn,
)
return response["stateMachineArn"]
def create_activity_and_get_arn(self, name: str = "TestActivity") -> str:
"""
Create an activity in mocked Step Functions and return its ARN.
"""
response = self.client.create_activity(
name=name,
)
return response["activityArn"]
@mock_aws
def test_sfns_create_state_machine(self):
state_machine_arn = self.create_state_machine_and_get_arn()
spans = self.memory_exporter.get_finished_spans()
assert spans
self.assertEqual(len(spans), 1)
span = spans[0]
self.assertEqual(
span.attributes[AWS_STEP_FUNCTIONS_STATE_MACHINE_ARN],
state_machine_arn,
)
@mock_aws
def test_sfns_describe_state_machine(self):
state_machine_arn = self.create_state_machine_and_get_arn()
self.client.describe_state_machine(stateMachineArn=state_machine_arn)
spans = self.memory_exporter.get_finished_spans()
assert spans
self.assertEqual(len(spans), 2)
span = spans[1]
self.assertEqual(
span.attributes[AWS_STEP_FUNCTIONS_STATE_MACHINE_ARN],
state_machine_arn,
)
@mock_aws
def test_sfns_create_activity(self):
activity_arn = self.create_activity_and_get_arn()
spans = self.memory_exporter.get_finished_spans()
assert spans
self.assertEqual(len(spans), 1)
span = spans[0]
self.assertEqual(
span.attributes[AWS_STEP_FUNCTIONS_ACTIVITY_ARN],
activity_arn,
)
@mock_aws
def test_sfns_describe_activity(self):
activity_arn = self.create_activity_and_get_arn()
self.client.describe_activity(activityArn=activity_arn)
spans = self.memory_exporter.get_finished_spans()
assert spans
self.assertEqual(len(spans), 2)
span = spans[1]
self.assertEqual(
span.attributes[AWS_STEP_FUNCTIONS_ACTIVITY_ARN],
activity_arn,
)
test_botocore_sns.py 0000664 0000000 0000000 00000015317 15270700723 0040161 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-botocore/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
import contextlib
from typing import Any
from unittest import mock
import botocore.session
from botocore.awsrequest import AWSResponse
from moto import mock_aws
from opentelemetry.instrumentation.botocore import BotocoreInstrumentor
from opentelemetry.semconv._incubating.attributes import messaging_attributes
from opentelemetry.semconv._incubating.attributes.aws_attributes import (
AWS_SNS_TOPIC_ARN,
)
from opentelemetry.semconv.trace import (
MessagingDestinationKindValues,
SpanAttributes,
)
from opentelemetry.test.test_base import TestBase
from opentelemetry.trace import SpanKind
from opentelemetry.trace.span import Span
class TestSnsExtension(TestBase):
def setUp(self):
super().setUp()
BotocoreInstrumentor().instrument()
session = botocore.session.get_session()
session.set_credentials(access_key="access-key", secret_key="secret-key")
self.client = session.create_client("sns", region_name="us-west-2")
self.topic_name = "my-topic"
self.topic_arn = f"arn:aws:sns:us-west-2:123456789012:{self.topic_name}"
def tearDown(self):
super().tearDown()
BotocoreInstrumentor().uninstrument()
def _create_topic(self, name: str = None) -> str:
if name is None:
name = self.topic_name
response = self.client.create_topic(Name=name)
self.memory_exporter.clear()
return response["TopicArn"]
@contextlib.contextmanager
def _mocked_aws_endpoint(self, response):
response_func = self._make_aws_response_func(response)
with mock.patch("botocore.endpoint.Endpoint.make_request", new=response_func):
yield
@staticmethod
def _make_aws_response_func(response):
def _response_func(*args, **kwargs):
return AWSResponse("http://127.0.0.1", 200, {}, "{}"), response
return _response_func
def assert_span(self, name: str) -> Span:
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(1, len(spans))
span = spans[0]
self.assertEqual(SpanKind.PRODUCER, span.kind)
self.assertEqual(name, span.name)
self.assertEqual("aws.sns", span.attributes[messaging_attributes.MESSAGING_SYSTEM])
return span
def assert_injected_span(self, message_attrs: dict[str, Any], span: Span):
# traceparent: ---
trace_parent = message_attrs["traceparent"]["StringValue"].split("-")
span_context = span.get_span_context()
self.assertEqual(span_context.trace_id, int(trace_parent[1], 16))
self.assertEqual(span_context.span_id, int(trace_parent[2], 16))
@mock_aws
def test_publish_to_topic_arn(self):
self._test_publish_to_arn("TopicArn")
@mock_aws
def test_publish_to_target_arn(self):
self._test_publish_to_arn("TargetArn")
def _test_publish_to_arn(self, arg_name: str):
target_arn = self._create_topic(self.topic_name)
self.client.publish(
**{
arg_name: target_arn,
"Message": "Hello message",
}
)
span = self.assert_span(f"{self.topic_name} send")
self.assertEqual(
MessagingDestinationKindValues.TOPIC.value,
span.attributes[SpanAttributes.MESSAGING_DESTINATION_KIND],
)
self.assertEqual(
self.topic_arn,
span.attributes[SpanAttributes.MESSAGING_DESTINATION],
)
self.assertEqual(
target_arn,
span.attributes[SpanAttributes.MESSAGING_DESTINATION_NAME],
)
@mock_aws
def test_publish_to_phone_number(self):
phone_number = "+10000000000"
self.client.publish(
PhoneNumber=phone_number,
Message="Hello SNS",
)
span = self.assert_span("phone_number send")
self.assertEqual(
"phone_number:**",
span.attributes[SpanAttributes.MESSAGING_DESTINATION],
)
@mock_aws
def test_publish_injects_span(self):
message_attrs = {}
topic_arn = self._create_topic()
self.client.publish(
TopicArn=topic_arn,
Message="Hello Message",
MessageAttributes=message_attrs,
)
span = self.assert_span(f"{self.topic_name} send")
self.assertEqual(
topic_arn,
span.attributes[AWS_SNS_TOPIC_ARN],
)
self.assert_injected_span(message_attrs, span)
def test_publish_batch_to_topic(self):
topic_arn = f"arn:aws:sns:region:000000000:{self.topic_name}"
message1_attrs = {}
message2_attrs = {}
mock_response = {
"Successful": [
{"Id": "1", "MessageId": "11", "SequenceNumber": "1"},
{"Id": "2", "MessageId": "22", "SequenceNumber": "2"},
],
"Failed": [],
}
# publish_batch not implemented by moto so mock the endpoint instead
with self._mocked_aws_endpoint(mock_response):
self.client.publish_batch(
TopicArn=topic_arn,
PublishBatchRequestEntries=[
{
"Id": "1",
"Message": "Hello message 1",
"MessageAttributes": message1_attrs,
},
{
"Id": "2",
"Message": "Hello message 2",
"MessageAttributes": message2_attrs,
},
],
)
span = self.assert_span(f"{self.topic_name} send")
self.assertEqual(
MessagingDestinationKindValues.TOPIC.value,
span.attributes[SpanAttributes.MESSAGING_DESTINATION_KIND],
)
self.assertEqual(
topic_arn,
span.attributes[AWS_SNS_TOPIC_ARN],
)
self.assertEqual(
topic_arn,
span.attributes[SpanAttributes.MESSAGING_DESTINATION],
)
self.assertEqual(
topic_arn,
span.attributes[SpanAttributes.MESSAGING_DESTINATION_NAME],
)
self.assert_injected_span(message1_attrs, span)
self.assert_injected_span(message2_attrs, span)
@mock_aws
def test_create_topic_span(self):
_ = self.client.create_topic(Name=self.topic_name)
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(1, len(spans))
span = spans[0]
self.assertEqual(SpanKind.CLIENT, span.kind)
self.assertEqual("SNS.CreateTopic", span.name)
self.assertEqual(
self.topic_arn,
span.attributes[AWS_SNS_TOPIC_ARN],
)
test_botocore_sqs.py 0000664 0000000 0000000 00000010644 15270700723 0040162 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-botocore/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
import botocore.session
from moto import mock_aws
from opentelemetry.instrumentation.botocore import BotocoreInstrumentor
from opentelemetry.semconv._incubating.attributes import messaging_attributes
from opentelemetry.semconv.trace import SpanAttributes
from opentelemetry.test.test_base import TestBase
class TestSqsExtension(TestBase):
def setUp(self):
super().setUp()
BotocoreInstrumentor().instrument()
session = botocore.session.get_session()
session.set_credentials(access_key="access-key", secret_key="secret-key")
self.region = "us-west-2"
self.client = session.create_client("sqs", region_name=self.region)
def tearDown(self):
super().tearDown()
BotocoreInstrumentor().uninstrument()
@mock_aws
def test_sqs_messaging_send_message(self):
create_queue_result = self.client.create_queue(QueueName="test_queue_name")
queue_url = create_queue_result["QueueUrl"]
response = self.client.send_message(QueueUrl=queue_url, MessageBody="content")
spans = self.memory_exporter.get_finished_spans()
assert spans
self.assertEqual(len(spans), 2)
span = spans[1]
self.assertEqual(span.attributes[messaging_attributes.MESSAGING_SYSTEM], "aws.sqs")
self.assertEqual(span.attributes[SpanAttributes.MESSAGING_URL], queue_url)
self.assertEqual(
span.attributes[SpanAttributes.MESSAGING_DESTINATION],
"test_queue_name",
)
self.assertEqual(
span.attributes[messaging_attributes.MESSAGING_MESSAGE_ID],
response["MessageId"],
)
@mock_aws
def test_sqs_messaging_send_message_batch(self):
create_queue_result = self.client.create_queue(QueueName="test_queue_name")
queue_url = create_queue_result["QueueUrl"]
response = self.client.send_message_batch(
QueueUrl=queue_url,
Entries=[
{"Id": "1", "MessageBody": "content"},
{"Id": "2", "MessageBody": "content2"},
],
)
spans = self.memory_exporter.get_finished_spans()
assert spans
self.assertEqual(len(spans), 2)
span = spans[1]
self.assertEqual(span.attributes["rpc.method"], "SendMessageBatch")
self.assertEqual(span.attributes[messaging_attributes.MESSAGING_SYSTEM], "aws.sqs")
self.assertEqual(span.attributes[SpanAttributes.MESSAGING_URL], queue_url)
self.assertEqual(
span.attributes[SpanAttributes.MESSAGING_DESTINATION],
"test_queue_name",
)
self.assertEqual(
span.attributes[messaging_attributes.MESSAGING_MESSAGE_ID],
response["Successful"][0]["MessageId"],
)
@mock_aws
def test_sqs_messaging_receive_message(self):
create_queue_result = self.client.create_queue(QueueName="test_queue_name")
queue_url = create_queue_result["QueueUrl"]
self.client.send_message(QueueUrl=queue_url, MessageBody="content")
message_result = self.client.receive_message(QueueUrl=create_queue_result["QueueUrl"])
spans = self.memory_exporter.get_finished_spans()
assert spans
self.assertEqual(len(spans), 3)
span = spans[-1]
self.assertEqual(span.attributes["rpc.method"], "ReceiveMessage")
self.assertEqual(span.attributes[messaging_attributes.MESSAGING_SYSTEM], "aws.sqs")
self.assertEqual(span.attributes[SpanAttributes.MESSAGING_URL], queue_url)
self.assertEqual(
span.attributes[SpanAttributes.MESSAGING_DESTINATION],
"test_queue_name",
)
self.assertEqual(
span.attributes[messaging_attributes.MESSAGING_MESSAGE_ID],
message_result["Messages"][0]["MessageId"],
)
@mock_aws
def test_sqs_messaging_failed_operation(self):
with self.assertRaises(Exception):
self.client.send_message(QueueUrl="non-existing", MessageBody="content")
spans = self.memory_exporter.get_finished_spans()
assert spans
self.assertEqual(len(spans), 1)
span = spans[0]
self.assertEqual(span.attributes["rpc.method"], "SendMessage")
self.assertEqual(span.attributes[messaging_attributes.MESSAGING_SYSTEM], "aws.sqs")
self.assertEqual(span.attributes[SpanAttributes.MESSAGING_URL], "non-existing")
opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-cassandra/ 0000775 0000000 0000000 00000000000 15270700723 0033102 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-cassandra/LICENSE 0000664 0000000 0000000 00000026135 15270700723 0034116 0 ustar 00root root 0000000 0000000 Apache License
Version 2.0, January 2004
http://www.apache.org/licenses/
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README.rst 0000664 0000000 0000000 00000001400 15270700723 0034505 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-cassandra OpenTelemetry Cassandra Instrumentation
=======================================
|pypi|
.. |pypi| image:: https://badge.fury.io/py/opentelemetry-instrumentation-cassandra.svg
:target: https://pypi.org/project/opentelemetry-instrumentation-cassandra/
Instrumentation for Cassandra (cassandra-driver and scylla-driver libraries).
Installation
------------
::
pip install opentelemetry-instrumentation-cassandra
References
----------
* `OpenTelemetry Cassandra Instrumentation `_
* `OpenTelemetry Project `_
* `OpenTelemetry Python Examples `_
pyproject.toml 0000664 0000000 0000000 00000003276 15270700723 0035747 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-cassandra [build-system]
requires = ["hatchling"]
build-backend = "hatchling.build"
[project]
name = "opentelemetry-instrumentation-cassandra"
dynamic = ["version"]
description = "OpenTelemetry Cassandra instrumentation"
readme = "README.rst"
license = "Apache-2.0"
requires-python = ">=3.10"
authors = [
{ name = "OpenTelemetry Authors", email = "cncf-opentelemetry-contributors@lists.cncf.io" },
]
classifiers = [
"Development Status :: 4 - Beta",
"Intended Audience :: Developers",
"License :: OSI Approved :: Apache Software License",
"Programming Language :: Python",
"Programming Language :: Python :: 3",
"Programming Language :: Python :: 3.10",
"Programming Language :: Python :: 3.11",
"Programming Language :: Python :: 3.12",
"Programming Language :: Python :: 3.13",
"Programming Language :: Python :: 3.14",
]
dependencies = [
"opentelemetry-api ~= 1.12",
"opentelemetry-instrumentation == 0.66b2",
"opentelemetry-semantic-conventions == 0.66b2",
"wrapt >= 1.0.0, < 3.0.0",
]
[project.optional-dependencies]
instruments = []
instruments-any = [
"cassandra-driver ~= 3.25",
"scylla-driver ~= 3.25",
]
[project.entry-points.opentelemetry_instrumentor]
cassandra = "opentelemetry.instrumentation.cassandra:CassandraInstrumentor"
[project.urls]
Homepage = "https://github.com/open-telemetry/opentelemetry-python-contrib/tree/main/instrumentation/opentelemetry-instrumentation-cassandra"
Repository = "https://github.com/open-telemetry/opentelemetry-python-contrib"
[tool.hatch.version]
path = "src/opentelemetry/instrumentation/cassandra/version.py"
[tool.hatch.build.targets.sdist]
include = [
"/src",
"/tests",
]
[tool.hatch.build.targets.wheel]
packages = ["src/opentelemetry"]
opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-cassandra/src/ 0000775 0000000 0000000 00000000000 15270700723 0033671 5 ustar 00root root 0000000 0000000 opentelemetry/ 0000775 0000000 0000000 00000000000 15270700723 0036506 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-cassandra/src instrumentation/ 0000775 0000000 0000000 00000000000 15270700723 0041751 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-cassandra/src/opentelemetry cassandra/ 0000775 0000000 0000000 00000000000 15270700723 0043710 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-cassandra/src/opentelemetry/instrumentation __init__.py 0000664 0000000 0000000 00000010025 15270700723 0046017 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-cassandra/src/opentelemetry/instrumentation/cassandra # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
"""
Cassandra instrumentation supporting `cassandra-driver`_ and `scylla-driver`_, it can be enabled by
using ``CassandraInstrumentor``.
.. _cassandra-driver: https://pypi.org/project/cassandra-driver/
.. _scylla-driver: https://pypi.org/project/scylla-driver/
Usage
-----
.. code:: python
import cassandra.cluster
from opentelemetry.instrumentation.cassandra import CassandraInstrumentor
CassandraInstrumentor().instrument()
cluster = cassandra.cluster.Cluster()
session = cluster.connect()
rows = session.execute("SELECT * FROM test")
API
---
"""
from collections.abc import Collection
from importlib.metadata import PackageNotFoundError, distribution
import cassandra.cluster
from wrapt import wrap_function_wrapper
from opentelemetry import trace
from opentelemetry.instrumentation._semconv import (
_get_schema_url_for_signal_types,
_OpenTelemetrySemanticConventionStability,
_OpenTelemetryStabilitySignalType,
_set_db_name,
_set_db_statement,
_set_db_system,
_set_http_net_peer_name_client,
)
from opentelemetry.instrumentation.cassandra.package import (
_instruments_any,
_instruments_cassandra_driver,
_instruments_scylla_driver,
)
from opentelemetry.instrumentation.cassandra.version import __version__
from opentelemetry.instrumentation.instrumentor import BaseInstrumentor
from opentelemetry.instrumentation.utils import unwrap
def _instrument(tracer_provider, include_db_statement=False, sem_conv_opt_in_mode=None):
"""Instruments the cassandra-driver/scylla-driver module
Wraps cassandra.cluster.Session.execute_async().
"""
tracer = trace.get_tracer(
__name__,
__version__,
tracer_provider,
schema_url=_get_schema_url_for_signal_types([_OpenTelemetryStabilitySignalType.DATABASE]),
)
name = "Cassandra"
def _traced_execute_async(func, instance, args, kwargs):
with tracer.start_as_current_span(name, kind=trace.SpanKind.CLIENT) as span:
if span.is_recording():
attrs = {}
_set_db_system(attrs, "cassandra", sem_conv_opt_in_mode)
_set_db_name(attrs, instance.keyspace, sem_conv_opt_in_mode)
_set_http_net_peer_name_client(
attrs,
instance.cluster.contact_points,
sem_conv_opt_in_mode,
)
if include_db_statement:
query = args[0]
_set_db_statement(attrs, str(query), sem_conv_opt_in_mode)
span.set_attributes(attrs)
response = func(*args, **kwargs)
return response
wrap_function_wrapper("cassandra.cluster", "Session.execute_async", _traced_execute_async)
class CassandraInstrumentor(BaseInstrumentor):
def instrumentation_dependencies(self) -> Collection[str]:
# Determine which package of cassandra is installed.
# Right now there are two packages, cassandra-driver and scylla-driver.
# The latter is a fork with additional support for ScyllaDB.
try:
distribution("cassandra-driver")
return (_instruments_cassandra_driver,)
except PackageNotFoundError:
pass
try:
distribution("scylla-driver")
return (_instruments_scylla_driver,)
except PackageNotFoundError:
pass
return _instruments_any
def _instrument(self, **kwargs):
_OpenTelemetrySemanticConventionStability._initialize()
sem_conv_opt_in_mode = _OpenTelemetrySemanticConventionStability._get_opentelemetry_stability_opt_in_mode(
_OpenTelemetryStabilitySignalType.DATABASE,
)
_instrument(
tracer_provider=kwargs.get("tracer_provider"),
include_db_statement=kwargs.get("include_db_statement"),
sem_conv_opt_in_mode=sem_conv_opt_in_mode,
)
def _uninstrument(self, **kwargs):
unwrap(cassandra.cluster.Session, "execute_async")
package.py 0000664 0000000 0000000 00000000476 15270700723 0045664 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-cassandra/src/opentelemetry/instrumentation/cassandra # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
_instruments_cassandra_driver = "cassandra-driver ~= 3.25"
_instruments_scylla_driver = "scylla-driver ~= 3.25"
_instruments = ()
_instruments_any = (_instruments_cassandra_driver, _instruments_scylla_driver)
_semconv_status = "migration"
version.py 0000664 0000000 0000000 00000000144 15270700723 0045746 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-cassandra/src/opentelemetry/instrumentation/cassandra # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
__version__ = "0.66b2"
test-requirements-scylla.txt 0000664 0000000 0000000 00000000754 15270700723 0040557 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-cassandra asgiref==3.8.1
pyasyncore==1.0.4 # for python 3.13 (should removed when cassandra-driver replaces asyncore with recommended asyncio)
click==8.1.7
Deprecated==1.2.14
geomet==0.2.1.post1
iniconfig==2.0.0
packaging==24.0
pluggy==1.6.0
py-cpuinfo==9.0.0
pytest==7.4.4
python-snappy==0.7.3
PyYAML==6.0.1
scylla-driver==3.26.6
six==1.16.0
tomli==2.0.1
typing_extensions==4.12.2
wrapt==1.16.0
zipp==3.19.2
-e opentelemetry-instrumentation
-e instrumentation/opentelemetry-instrumentation-cassandra
test-requirements.txt 0000664 0000000 0000000 00000000732 15270700723 0037266 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-cassandra asgiref==3.8.1
cassandra-driver==3.29.0
pyasyncore==1.0.4 # for python 3.13 (should removed when cassandra-driver replaces asyncore with recommended asyncio)
click==8.1.7
Deprecated==1.2.14
geomet==0.2.1.post1
iniconfig==2.0.0
packaging==24.0
pluggy==1.6.0
py-cpuinfo==9.0.0
pytest==7.4.4
PyYAML==6.0.1
six==1.16.0
tomli==2.0.1
typing_extensions==4.12.2
wrapt==1.16.0
zipp==3.19.2
-e opentelemetry-instrumentation
-e instrumentation/opentelemetry-instrumentation-cassandra
opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-cassandra/tests/ 0000775 0000000 0000000 00000000000 15270700723 0034244 5 ustar 00root root 0000000 0000000 __init__.py 0000664 0000000 0000000 00000000000 15270700723 0036264 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-cassandra/tests test_cassandra_integration.py 0000664 0000000 0000000 00000032664 15270700723 0042153 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-cassandra/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
from importlib.metadata import PackageNotFoundError
from unittest import TestCase, mock
from unittest.mock import call, patch
import cassandra.cluster
from wrapt import BoundFunctionWrapper
import opentelemetry.instrumentation.cassandra
from opentelemetry import trace as trace_api
from opentelemetry.instrumentation._semconv import (
_OpenTelemetrySemanticConventionStability,
)
from opentelemetry.instrumentation.cassandra import CassandraInstrumentor
from opentelemetry.instrumentation.cassandra.package import (
_instruments_cassandra_driver,
_instruments_scylla_driver,
)
from opentelemetry.sdk import resources
from opentelemetry.semconv._incubating.attributes.db_attributes import (
DB_NAME,
DB_STATEMENT,
DB_SYSTEM,
)
from opentelemetry.semconv._incubating.attributes.net_attributes import (
NET_PEER_NAME,
)
from opentelemetry.semconv.attributes.db_attributes import (
DB_NAMESPACE,
DB_QUERY_TEXT,
DB_SYSTEM_NAME,
)
from opentelemetry.semconv.attributes.server_attributes import (
SERVER_ADDRESS,
)
from opentelemetry.test.test_base import TestBase
from opentelemetry.trace import SpanKind
def connect_and_execute_query():
cluster = cassandra.cluster.Cluster()
cluster._is_setup = True
session = cluster.connect()
session.cluster = cluster
session.keyspace = "test"
session._request_init_callbacks = []
query = "SELECT * FROM test"
session.execute(query)
return cluster, session, query
class TestCassandraIntegration(TestBase):
def tearDown(self):
super().tearDown()
with self.disable_logging():
CassandraInstrumentor().uninstrument()
@property
def _mocked_session(self):
return cassandra.cluster.Session(cluster=mock.Mock(), hosts=[])
def test_instrument_uninstrument(self):
instrumentation = CassandraInstrumentor()
instrumentation.instrument()
self.assertTrue(isinstance(cassandra.cluster.Session.execute_async, BoundFunctionWrapper))
instrumentation.uninstrument()
self.assertFalse(isinstance(cassandra.cluster.Session.execute_async, BoundFunctionWrapper))
@mock.patch("cassandra.cluster.Cluster.connect")
@mock.patch("cassandra.cluster.Session.__init__")
@mock.patch("cassandra.cluster.Session._create_response_future")
def test_instrumentor(self, mock_create_response_future, mock_session_init, mock_connect):
mock_create_response_future.return_value = mock.Mock()
mock_session_init.return_value = None
mock_connect.return_value = self._mocked_session
CassandraInstrumentor().instrument()
connect_and_execute_query()
spans_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans_list), 1)
span = spans_list[0]
# Check version and name in span's instrumentation info
self.assertEqualSpanInstrumentationScope(span, opentelemetry.instrumentation.cassandra)
self.assertEqual(span.name, "Cassandra")
self.assertEqual(span.kind, SpanKind.CLIENT)
# check that no spans are generated after uninstrument
CassandraInstrumentor().uninstrument()
connect_and_execute_query()
spans_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans_list), 1)
@mock.patch("cassandra.cluster.Cluster.connect")
@mock.patch("cassandra.cluster.Session.__init__")
@mock.patch("cassandra.cluster.Session._create_response_future")
def test_custom_tracer_provider(self, mock_create_response_future, mock_session_init, mock_connect):
mock_create_response_future.return_value = mock.Mock()
mock_session_init.return_value = None
mock_connect.return_value = self._mocked_session
resource = resources.Resource.create({})
result = self.create_tracer_provider(resource=resource)
tracer_provider, exporter = result
CassandraInstrumentor().instrument(tracer_provider=tracer_provider)
connect_and_execute_query()
span_list = exporter.get_finished_spans()
self.assertEqual(len(span_list), 1)
span = span_list[0]
self.assertIs(span.resource, resource)
@mock.patch("cassandra.cluster.Cluster.connect")
@mock.patch("cassandra.cluster.Session.__init__")
@mock.patch("cassandra.cluster.Session._create_response_future")
def test_instrument_connection_no_op_tracer_provider(
self, mock_create_response_future, mock_session_init, mock_connect
):
mock_create_response_future.return_value = mock.Mock()
mock_session_init.return_value = None
mock_connect.return_value = self._mocked_session
tracer_provider = trace_api.NoOpTracerProvider()
CassandraInstrumentor().instrument(tracer_provider=tracer_provider)
connect_and_execute_query()
spans_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans_list), 0)
class TestCassandraInstrumentationDependencies(TestCase):
"""Tests to verify that the correct package is returned by
instrumentation_dependencies() depending on which driver is installed.
This covers the cases where only cassandra-driver is installed,
only scylla-driver is installed, both are installed, and neither
is installed.
"""
@patch("opentelemetry.instrumentation.cassandra.distribution")
def test_instrumentation_dependencies_cassandra_driver_installed(self, mock_distribution) -> None:
instrumentation = CassandraInstrumentor()
def _distribution(name):
if name == "cassandra-driver":
return
raise PackageNotFoundError
mock_distribution.side_effect = _distribution
package_to_instrument = instrumentation.instrumentation_dependencies()
self.assertEqual(mock_distribution.call_count, 1)
self.assertEqual(
mock_distribution.mock_calls,
[
call("cassandra-driver"),
],
)
self.assertEqual(package_to_instrument, (_instruments_cassandra_driver,))
@patch("opentelemetry.instrumentation.cassandra.distribution")
def test_instrumentation_dependencies_scylla_driver_installed(self, mock_distribution) -> None:
instrumentation = CassandraInstrumentor()
def _distribution(name):
if name == "scylla-driver":
return
raise PackageNotFoundError
mock_distribution.side_effect = _distribution
package_to_instrument = instrumentation.instrumentation_dependencies()
self.assertEqual(mock_distribution.call_count, 2)
self.assertEqual(
mock_distribution.mock_calls,
[
call("cassandra-driver"),
call("scylla-driver"),
],
)
self.assertEqual(package_to_instrument, (_instruments_scylla_driver,))
@patch("opentelemetry.instrumentation.cassandra.distribution")
def test_instrumentation_dependencies_both_installed(self, mock_distribution) -> None:
instrumentation = CassandraInstrumentor()
def _distribution(name):
# The function returns None here for all names
# to simulate both packages being installed
return None
mock_distribution.side_effect = _distribution
package_to_instrument = instrumentation.instrumentation_dependencies()
self.assertEqual(mock_distribution.call_count, 1)
self.assertEqual(mock_distribution.mock_calls, [call("cassandra-driver")])
self.assertEqual(package_to_instrument, (_instruments_cassandra_driver,))
@patch("opentelemetry.instrumentation.cassandra.distribution")
def test_instrumentation_dependencies_none_installed(self, mock_distribution) -> None:
instrumentation = CassandraInstrumentor()
def _distribution(name):
# Function raises PackageNotFoundError
# if name is not in the list. We will
# raise it for both names to simulate
# neither being installed
raise PackageNotFoundError
mock_distribution.side_effect = _distribution
package_to_instrument = instrumentation.instrumentation_dependencies()
self.assertEqual(mock_distribution.call_count, 2)
self.assertEqual(
mock_distribution.mock_calls,
[
call("cassandra-driver"),
call("scylla-driver"),
],
)
self.assertEqual(
package_to_instrument,
(_instruments_cassandra_driver, _instruments_scylla_driver),
)
class TestCassandraSemconvStability(TestBase):
def tearDown(self):
super().tearDown()
with self.disable_logging():
CassandraInstrumentor().uninstrument()
_OpenTelemetrySemanticConventionStability._initialized = False
@property
def _mocked_session(self):
return cassandra.cluster.Session(cluster=mock.Mock(), hosts=[])
@mock.patch("cassandra.cluster.Cluster.connect")
@mock.patch("cassandra.cluster.Session.__init__")
@mock.patch("cassandra.cluster.Session._create_response_future")
def test_default_semconv(self, mock_create_response_future, mock_session_init, mock_connect):
mock_create_response_future.return_value = mock.Mock()
mock_session_init.return_value = None
mock_connect.return_value = self._mocked_session
CassandraInstrumentor().instrument(include_db_statement=True)
connect_and_execute_query()
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
span = spans[0]
self.assertEqual(span.attributes[DB_NAME], "test")
self.assertEqual(span.attributes[DB_SYSTEM], "cassandra")
self.assertEqual(span.attributes[DB_STATEMENT], "SELECT * FROM test")
self.assertIn(NET_PEER_NAME, span.attributes)
self.assertNotIn(DB_NAMESPACE, span.attributes)
self.assertNotIn(DB_SYSTEM_NAME, span.attributes)
self.assertNotIn(DB_QUERY_TEXT, span.attributes)
self.assertNotIn(SERVER_ADDRESS, span.attributes)
self.assertEqual(
span.instrumentation_scope.schema_url,
"https://opentelemetry.io/schemas/1.11.0",
)
@mock.patch("cassandra.cluster.Cluster.connect")
@mock.patch("cassandra.cluster.Session.__init__")
@mock.patch("cassandra.cluster.Session._create_response_future")
def test_new_semconv(self, mock_create_response_future, mock_session_init, mock_connect):
mock_create_response_future.return_value = mock.Mock()
mock_session_init.return_value = None
mock_connect.return_value = self._mocked_session
with mock.patch.dict(
"os.environ",
{"OTEL_SEMCONV_STABILITY_OPT_IN": "database"},
):
_OpenTelemetrySemanticConventionStability._initialized = False
CassandraInstrumentor().instrument(include_db_statement=True)
connect_and_execute_query()
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
span = spans[0]
self.assertEqual(span.attributes[DB_NAMESPACE], "test")
self.assertEqual(span.attributes[DB_SYSTEM_NAME], "cassandra")
self.assertEqual(span.attributes[DB_QUERY_TEXT], "SELECT * FROM test")
self.assertIn(SERVER_ADDRESS, span.attributes)
self.assertNotIn(DB_NAME, span.attributes)
self.assertNotIn(DB_SYSTEM, span.attributes)
self.assertNotIn(DB_STATEMENT, span.attributes)
self.assertNotIn(NET_PEER_NAME, span.attributes)
self.assertEqual(
span.instrumentation_scope.schema_url,
"https://opentelemetry.io/schemas/1.25.0",
)
_OpenTelemetrySemanticConventionStability._initialized = False
@mock.patch("cassandra.cluster.Cluster.connect")
@mock.patch("cassandra.cluster.Session.__init__")
@mock.patch("cassandra.cluster.Session._create_response_future")
def test_dup_semconv(self, mock_create_response_future, mock_session_init, mock_connect):
mock_create_response_future.return_value = mock.Mock()
mock_session_init.return_value = None
mock_connect.return_value = self._mocked_session
with mock.patch.dict(
"os.environ",
{"OTEL_SEMCONV_STABILITY_OPT_IN": "database/dup"},
):
_OpenTelemetrySemanticConventionStability._initialized = False
CassandraInstrumentor().instrument(include_db_statement=True)
connect_and_execute_query()
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
span = spans[0]
self.assertEqual(span.attributes[DB_NAME], "test")
self.assertEqual(span.attributes[DB_SYSTEM], "cassandra")
self.assertEqual(span.attributes[DB_STATEMENT], "SELECT * FROM test")
self.assertIn(NET_PEER_NAME, span.attributes)
self.assertEqual(span.attributes[DB_NAMESPACE], "test")
self.assertEqual(span.attributes[DB_SYSTEM_NAME], "cassandra")
self.assertEqual(span.attributes[DB_QUERY_TEXT], "SELECT * FROM test")
self.assertIn(SERVER_ADDRESS, span.attributes)
self.assertEqual(
span.instrumentation_scope.schema_url,
"https://opentelemetry.io/schemas/1.25.0",
)
_OpenTelemetrySemanticConventionStability._initialized = False
opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-celery/ 0000775 0000000 0000000 00000000000 15270700723 0032426 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-celery/LICENSE 0000664 0000000 0000000 00000026135 15270700723 0033442 0 ustar 00root root 0000000 0000000 Apache License
Version 2.0, January 2004
http://www.apache.org/licenses/
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opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-celery/README.rst 0000664 0000000 0000000 00000001265 15270700723 0034121 0 ustar 00root root 0000000 0000000 OpenTelemetry Celery Instrumentation
====================================
|pypi|
.. |pypi| image:: https://badge.fury.io/py/opentelemetry-instrumentation-celery.svg
:target: https://pypi.org/project/opentelemetry-instrumentation-celery/
Instrumentation for Celery.
Installation
------------
::
pip install opentelemetry-instrumentation-celery
References
----------
* `OpenTelemetry Celery Instrumentation `_
* `OpenTelemetry Project `_
* `OpenTelemetry Python Examples `_
pyproject.toml 0000664 0000000 0000000 00000003130 15270700723 0035260 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-celery [build-system]
requires = ["hatchling"]
build-backend = "hatchling.build"
[project]
name = "opentelemetry-instrumentation-celery"
dynamic = ["version"]
description = "OpenTelemetry Celery Instrumentation"
readme = "README.rst"
license = "Apache-2.0"
requires-python = ">=3.10"
authors = [
{ name = "OpenTelemetry Authors", email = "cncf-opentelemetry-contributors@lists.cncf.io" },
]
classifiers = [
"Development Status :: 4 - Beta",
"Intended Audience :: Developers",
"License :: OSI Approved :: Apache Software License",
"Programming Language :: Python",
"Programming Language :: Python :: 3",
"Programming Language :: Python :: 3.10",
"Programming Language :: Python :: 3.11",
"Programming Language :: Python :: 3.12",
"Programming Language :: Python :: 3.13",
"Programming Language :: Python :: 3.14",
]
dependencies = [
"opentelemetry-api ~= 1.12",
"opentelemetry-instrumentation == 0.66b2",
"opentelemetry-semantic-conventions == 0.66b2",
]
[project.optional-dependencies]
instruments = [
"celery >= 4.0, < 6.0",
]
[project.entry-points.opentelemetry_instrumentor]
celery = "opentelemetry.instrumentation.celery:CeleryInstrumentor"
[project.urls]
Homepage = "https://github.com/open-telemetry/opentelemetry-python-contrib/tree/main/instrumentation/opentelemetry-instrumentation-celery"
Repository = "https://github.com/open-telemetry/opentelemetry-python-contrib"
[tool.hatch.version]
path = "src/opentelemetry/instrumentation/celery/version.py"
[tool.hatch.build.targets.sdist]
include = [
"/src",
"/tests",
]
[tool.hatch.build.targets.wheel]
packages = ["src/opentelemetry"]
opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-celery/src/ 0000775 0000000 0000000 00000000000 15270700723 0033215 5 ustar 00root root 0000000 0000000 opentelemetry/ 0000775 0000000 0000000 00000000000 15270700723 0036032 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-celery/src instrumentation/ 0000775 0000000 0000000 00000000000 15270700723 0041275 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-celery/src/opentelemetry celery/ 0000775 0000000 0000000 00000000000 15270700723 0042560 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-celery/src/opentelemetry/instrumentation __init__.py 0000664 0000000 0000000 00000032031 15270700723 0044670 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-celery/src/opentelemetry/instrumentation/celery # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
"""
Instrument `celery`_ to trace Celery applications.
.. _celery: https://pypi.org/project/celery/
Usage
-----
* Start broker backend
.. code::
docker run -p 5672:5672 rabbitmq
* Run instrumented task
.. code:: python
from opentelemetry.instrumentation.celery import CeleryInstrumentor
from celery import Celery
from celery.signals import worker_process_init
@worker_process_init.connect(weak=False)
def init_celery_tracing(*args, **kwargs):
CeleryInstrumentor().instrument()
app = Celery("tasks", broker="amqp://localhost")
@app.task
def add(x, y):
return x + y
add.delay(42, 50)
Configuration
-------------
The ``CeleryInstrumentor().instrument()`` method accepts the following arguments:
* ``use_span_links`` (bool): When ``True``, Celery task execution spans will be linked to the
task creation spans instead of being created as child spans. This provides a looser
coupling between spans in distributed systems. Defaults to ``False`` to maintain
backward compatibility.
Setting up tracing
------------------
When tracing a celery worker process, tracing and instrumentation both must be initialized after the celery worker
process is initialized. This is required for any tracing components that might use threading to work correctly
such as the BatchSpanProcessor. Celery provides a signal called ``worker_process_init`` that can be used to
accomplish this as shown in the example above.
API
---
"""
from __future__ import annotations
import logging
from collections.abc import Collection, Iterable
from timeit import default_timer
from billiard import VERSION
from billiard.einfo import ExceptionInfo
from celery import signals # pylint: disable=no-name-in-module
from celery.worker.request import Request # pylint: disable=no-name-in-module
from opentelemetry import context as context_api
from opentelemetry import trace
from opentelemetry.instrumentation.celery import utils
from opentelemetry.instrumentation.celery.package import _instruments
from opentelemetry.instrumentation.celery.version import __version__
from opentelemetry.instrumentation.instrumentor import BaseInstrumentor
from opentelemetry.metrics import get_meter
from opentelemetry.propagate import extract, inject
from opentelemetry.propagators.textmap import Getter
from opentelemetry.semconv._incubating.attributes.messaging_attributes import (
MESSAGING_MESSAGE_ID,
)
from opentelemetry.trace.status import Status, StatusCode
if VERSION >= (4, 0, 1):
from billiard.einfo import ExceptionWithTraceback
else:
ExceptionWithTraceback = None
logger = logging.getLogger(__name__)
# Task operations
_TASK_TAG_KEY = "celery.action"
_TASK_APPLY_ASYNC = "apply_async"
_TASK_RUN = "run"
_TASK_RETRY_REASON_KEY = "celery.retry.reason"
_TASK_REVOKED_REASON_KEY = "celery.revoked.reason"
_TASK_REVOKED_TERMINATED_SIGNAL_KEY = "celery.terminated.signal"
_TASK_NAME_KEY = "celery.task_name"
class CeleryGetter(Getter[Request]):
def get(self, carrier: Request, key: str) -> list[str] | None:
value = getattr(carrier, key, None)
if value is None:
return None
# Celery's Context copies all message properties as instance
# attributes, including non-string values like timelimit (tuple
# of ints). The TextMapPropagator contract requires string
# values, so coerce anything that isn't already a string.
if isinstance(value, str):
return [value]
if isinstance(value, Iterable):
return [str(v) if not isinstance(v, str) else v for v in value]
return [str(value)]
def keys(self, carrier: Request) -> list[str]:
return []
celery_getter = CeleryGetter()
class CeleryInstrumentor(BaseInstrumentor):
def __init__(self):
super().__init__()
if not hasattr(self, "metrics"):
self.metrics = None
if not hasattr(self, "task_id_to_start_time"):
self.task_id_to_start_time = {}
def instrumentation_dependencies(self) -> Collection[str]:
return _instruments
def _instrument(self, **kwargs):
# TODO: deprecate this when support for stable semconv is available
tracer_provider = kwargs.get("tracer_provider")
use_span_links = kwargs.get("use_span_links", False)
self._tracer = trace.get_tracer(
__name__,
__version__,
tracer_provider,
schema_url="https://opentelemetry.io/schemas/1.11.0",
)
self._use_span_links = use_span_links
meter_provider = kwargs.get("meter_provider")
meter = get_meter(
__name__,
__version__,
meter_provider,
schema_url="https://opentelemetry.io/schemas/1.11.0",
)
self.task_id_to_start_time = {}
self.create_celery_metrics(meter)
signals.task_prerun.connect(self._trace_prerun, weak=False)
signals.task_postrun.connect(self._trace_postrun, weak=False)
signals.before_task_publish.connect(self._trace_before_publish, weak=False)
signals.after_task_publish.connect(self._trace_after_publish, weak=False)
signals.task_failure.connect(self._trace_failure, weak=False)
signals.task_retry.connect(self._trace_retry, weak=False)
def _uninstrument(self, **kwargs):
signals.task_prerun.disconnect(self._trace_prerun)
signals.task_postrun.disconnect(self._trace_postrun)
signals.before_task_publish.disconnect(self._trace_before_publish)
signals.after_task_publish.disconnect(self._trace_after_publish)
signals.task_failure.disconnect(self._trace_failure)
signals.task_retry.disconnect(self._trace_retry)
self.task_id_to_start_time = {}
def _trace_prerun(self, *args, **kwargs):
task = utils.retrieve_task(kwargs)
task_id = utils.retrieve_task_id(kwargs)
if task is None or task_id is None:
return
self.update_task_duration_time(task_id)
request = task.request
tracectx = extract(request, getter=celery_getter) or None
logger.debug("prerun signal start task_id=%s", task_id)
operation_name = f"{_TASK_RUN}/{task.name}"
if self._use_span_links and tracectx is not None:
parent_span_context = trace.get_current_span(tracectx).get_span_context()
links = [trace.Link(parent_span_context)] if parent_span_context.is_valid else None
span = self._tracer.start_span(operation_name, links=links, kind=trace.SpanKind.CONSUMER)
# Don't attach the context when using links to avoid parent-child relationship
token = None
else:
token = context_api.attach(tracectx) if tracectx is not None else None
span = self._tracer.start_span(operation_name, context=tracectx, kind=trace.SpanKind.CONSUMER)
activation = trace.use_span(span, end_on_exit=True)
activation.__enter__() # pylint: disable=unnecessary-dunder-call
utils.attach_context(task, task_id, span, activation, token)
def _trace_postrun(self, *args, **kwargs):
task = utils.retrieve_task(kwargs)
task_id = utils.retrieve_task_id(kwargs)
if task is None or task_id is None:
return
logger.debug("postrun signal task_id=%s", task_id)
# retrieve and finish the Span
ctx = utils.retrieve_context(task, task_id)
if ctx is None:
logger.warning("no existing span found for task_id=%s", task_id)
return
span, activation, token = ctx
# request context tags
if span.is_recording():
span.set_attribute(_TASK_TAG_KEY, _TASK_RUN)
utils.set_attributes_from_context(span, kwargs)
utils.set_attributes_from_context(span, task.request)
span.set_attribute(_TASK_NAME_KEY, task.name)
activation.__exit__(None, None, None)
utils.detach_context(task, task_id)
self.update_task_duration_time(task_id)
labels = {"task": task.name, "worker": task.request.hostname}
self._record_histograms(task_id, labels)
self.task_id_to_start_time.pop(task_id, None)
# if the process sending the task is not instrumented
# there's no incoming context and no token to detach
if token is not None:
context_api.detach(token)
def _trace_before_publish(self, *args, **kwargs):
task = utils.retrieve_task_from_sender(kwargs)
task_id = utils.retrieve_task_id_from_message(kwargs)
if task_id is None:
return
if task is None:
# task is an anonymous task send using send_task or using canvas workflow
# Signatures() to send to a task not in the current processes dependency
# tree
task_name = kwargs.get("sender", "unknown")
else:
task_name = task.name
operation_name = f"{_TASK_APPLY_ASYNC}/{task_name}"
span = self._tracer.start_span(operation_name, kind=trace.SpanKind.PRODUCER)
# apply some attributes here because most of the data is not available
if span.is_recording():
span.set_attribute(_TASK_TAG_KEY, _TASK_APPLY_ASYNC)
span.set_attribute(MESSAGING_MESSAGE_ID, task_id)
span.set_attribute(_TASK_NAME_KEY, task_name)
utils.set_attributes_from_context(span, kwargs)
activation = trace.use_span(span, end_on_exit=True)
activation.__enter__() # pylint: disable=unnecessary-dunder-call
utils.attach_context(task, task_id, span, activation, None, is_publish=True)
headers = kwargs.get("headers")
if headers:
inject(headers)
@staticmethod
def _trace_after_publish(*args, **kwargs):
task = utils.retrieve_task_from_sender(kwargs)
task_id = utils.retrieve_task_id_from_message(kwargs)
if task is None or task_id is None:
return
# retrieve and finish the Span
ctx = utils.retrieve_context(task, task_id, is_publish=True)
if ctx is None:
logger.warning("no existing span found for task_id=%s", task_id)
return
_, activation, _ = ctx
activation.__exit__(None, None, None) # pylint: disable=unnecessary-dunder-call
utils.detach_context(task, task_id, is_publish=True)
@staticmethod
def _trace_failure(*args, **kwargs):
task = utils.retrieve_task_from_sender(kwargs)
task_id = utils.retrieve_task_id(kwargs)
if task is None or task_id is None:
return
ctx = utils.retrieve_context(task, task_id)
if ctx is None:
return
span, _, _ = ctx
if not span.is_recording():
return
status_kwargs = {"status_code": StatusCode.ERROR}
ex = kwargs.get("einfo")
if hasattr(task, "throws") and ex is not None and isinstance(ex.exception, task.throws):
return
if ex is not None:
# Unwrap the actual exception wrapped by billiard's
# `ExceptionInfo` and `ExceptionWithTraceback`.
if isinstance(ex, ExceptionInfo) and ex.exception is not None:
ex = ex.exception
if ExceptionWithTraceback is not None and isinstance(ex, ExceptionWithTraceback) and ex.exc is not None:
ex = ex.exc
status_kwargs["description"] = str(ex)
span.record_exception(ex)
span.set_status(Status(**status_kwargs))
@staticmethod
def _trace_retry(*args, **kwargs):
task = utils.retrieve_task_from_sender(kwargs)
task_id = utils.retrieve_task_id_from_request(kwargs)
reason = utils.retrieve_reason(kwargs)
if task is None or task_id is None or reason is None:
return
ctx = utils.retrieve_context(task, task_id)
if ctx is None:
return
span, _, _ = ctx
if not span.is_recording():
return
# Add retry reason metadata to span
# Use `str(reason)` instead of `reason.message` in case we get
# something that isn't an `Exception`
span.set_attribute(_TASK_RETRY_REASON_KEY, str(reason))
def update_task_duration_time(self, task_id):
cur_time = default_timer()
task_duration_time_until_now = (
cur_time - self.task_id_to_start_time[task_id] if task_id in self.task_id_to_start_time else cur_time
)
self.task_id_to_start_time[task_id] = task_duration_time_until_now
def _record_histograms(self, task_id, metric_attributes):
if task_id is None:
return
self.metrics["flower.task.runtime.seconds"].record(
self.task_id_to_start_time.get(task_id),
attributes=metric_attributes,
)
def create_celery_metrics(self, meter) -> None:
self.metrics = {
"flower.task.runtime.seconds": meter.create_histogram(
name="flower.task.runtime.seconds",
unit="seconds",
description="The time it took to run the task.",
)
}
package.py 0000664 0000000 0000000 00000000167 15270700723 0044531 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-celery/src/opentelemetry/instrumentation/celery # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
_instruments = ("celery >= 4.0, < 6.0",)
utils.py 0000664 0000000 0000000 00000020330 15270700723 0044270 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-celery/src/opentelemetry/instrumentation/celery # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
from __future__ import annotations
import logging
from collections.abc import Mapping
from typing import TYPE_CHECKING, Any, Protocol, cast
from celery import registry # pylint: disable=no-name-in-module
from celery.app.task import Task
from opentelemetry.semconv._incubating.attributes.messaging_attributes import (
MESSAGING_MESSAGE_ID,
)
from opentelemetry.semconv.trace import SpanAttributes
from opentelemetry.trace import Span
if TYPE_CHECKING:
from contextlib import AbstractContextManager
ContextKey = tuple[str, bool]
ContextTuple = tuple[Span, "AbstractContextManager[Span]", object | None]
ContextDict = dict[ContextKey, ContextTuple]
class ContextCarrier(Protocol):
def get(self, key: str, default: Any = None) -> Any: ...
logger = logging.getLogger(__name__)
# Celery Context key
CTX_KEY = "__otel_task_span"
# Celery Context attributes
CELERY_CONTEXT_ATTRIBUTES = (
"compression",
"correlation_id",
"countdown",
"delivery_info",
"declare",
"eta",
"exchange",
"expires",
"hostname",
"id",
"priority",
"queue",
"reply_to",
"retries",
"routing_key",
"serializer",
"timelimit",
"origin",
"state",
)
# pylint:disable=too-many-branches
def set_attributes_from_context(
span: Span,
context: ContextCarrier,
) -> None:
"""Helper to extract meta values from a Celery Context"""
if not span.is_recording():
return
for key in CELERY_CONTEXT_ATTRIBUTES:
value = context.get(key)
# Skip this key if it is not set
if value is None or value == "":
continue
# Skip `timelimit` if it is not set (it's default/unset value is a
# tuple or a list of `None` values
if key == "timelimit":
if value in [(None, None), [None, None]]:
continue
if None in value:
value = ["" if tl is None else str(tl) for tl in value]
# Skip `retries` if it's value is `0`
if key == "retries" and value == 0:
continue
attribute_name = None
# Celery 4.0 uses `origin` instead of `hostname`; this change preserves
# the same name for the tag despite Celery version
if key == "origin":
key = "hostname"
elif key == "delivery_info":
# Get also destination from this
routing_key = value.get("routing_key")
if routing_key is not None:
span.set_attribute(SpanAttributes.MESSAGING_DESTINATION, routing_key)
value = str(value)
elif key == "id":
attribute_name = MESSAGING_MESSAGE_ID
elif key == "correlation_id":
attribute_name = SpanAttributes.MESSAGING_CONVERSATION_ID
elif key == "routing_key":
attribute_name = SpanAttributes.MESSAGING_DESTINATION
# according to https://docs.celeryproject.org/en/stable/userguide/routing.html#exchange-types
elif key == "declare":
attribute_name = SpanAttributes.MESSAGING_DESTINATION_KIND
for declare in value:
if declare.exchange.type == "direct":
value = "queue"
break
if declare.exchange.type == "topic":
value = "topic"
break
# set attribute name if not set specially for a key
if attribute_name is None:
attribute_name = f"celery.{key}"
span.set_attribute(attribute_name, value)
def attach_context(
task: Task | None,
task_id: str,
span: Span,
activation: AbstractContextManager[Span],
token: object | None,
is_publish: bool = False,
) -> None:
"""Helper to propagate a `Span`, `ContextManager` and context token
for the given `Task` instance. This function uses a `dict` that stores
the Span using the `(task_id, is_publish)` as a key. This is useful
when information must be propagated from one Celery signal to another.
We use (task_id, is_publish) for the key to ensure that publishing a
task from within another task does not cause any conflicts.
This mostly happens when either a task fails and a retry policy is in place,
or when a task is manually retries (e.g. `task.retry()`), we end up trying
to publish a task with the same id as the task currently running.
Previously publishing the new task would overwrite the existing `celery.run` span
in the `dict` causing that span to be forgotten and never finished
NOTE: We cannot test for this well yet, because we do not run a celery worker,
and cannot run `task.apply_async()`
"""
if task is None:
return
ctx_dict = cast(ContextDict | None, getattr(task, CTX_KEY, None))
if ctx_dict is None:
ctx_dict = {}
setattr(task, CTX_KEY, ctx_dict)
ctx_dict[(task_id, is_publish)] = (span, activation, token)
def detach_context(task: Task | None, task_id: str, is_publish: bool = False) -> None:
"""Helper to remove `Span`, `ContextManager` and context token in a
Celery task when it's propagated.
This function handles tasks where no values are attached to the `Task`.
"""
if task is None:
return
span_dict = cast(ContextDict | None, getattr(task, CTX_KEY, None))
if span_dict is None:
return
# See note in `attach_context` for key info
span_dict.pop((task_id, is_publish), None)
def retrieve_context(task: Task | None, task_id: str, is_publish: bool = False) -> ContextTuple | None:
"""Helper to retrieve an active `Span`, `ContextManager` and context token
stored in a `Task` instance
"""
if task is None:
return None
span_dict = cast(ContextDict | None, getattr(task, CTX_KEY, None))
if span_dict is None:
return None
# See note in `attach_context` for key info
return span_dict.get((task_id, is_publish), None)
def retrieve_task(kwargs: Mapping[str, Any]) -> Task | None:
task = kwargs.get("task")
if task is None:
logger.debug("Unable to retrieve task from signal arguments")
return cast(Task | None, task)
def retrieve_task_from_sender(kwargs: Mapping[str, Any]) -> Task | None:
sender = kwargs.get("sender")
if sender is None:
logger.debug("Unable to retrieve the sender from signal arguments")
# before and after publish signals sender is the task name
# for retry and failure signals sender is the task object
if isinstance(sender, str):
sender = registry.tasks.get(sender)
if sender is None:
logger.debug("Unable to retrieve the task from sender=%s", sender)
return cast(Task | None, sender)
def retrieve_task_id(kwargs: Mapping[str, Any]) -> str | None:
task_id = kwargs.get("task_id")
if task_id is None:
logger.debug("Unable to retrieve task_id from signal arguments")
return cast(str | None, task_id)
def retrieve_task_id_from_request(kwargs: Mapping[str, Any]) -> str | None:
# retry signal does not include task_id as argument so use request argument
request = kwargs.get("request")
if request is None:
logger.debug("Unable to retrieve the request from signal arguments")
return None
task_id = cast(str | None, getattr(request, "id", None))
if task_id is None:
logger.debug("Unable to retrieve the task_id from the request")
return task_id
def retrieve_task_id_from_message(kwargs: Mapping[str, Any]) -> str | None:
"""Helper to retrieve the `Task` identifier from the message `body`.
This helper supports Protocol Version 1 and 2. The Protocol is well
detailed in the official documentation:
http://docs.celeryproject.org/en/latest/internals/protocol.html
"""
headers = kwargs.get("headers")
body = kwargs.get("body")
if headers is not None and len(headers) > 0:
# Protocol Version 2 (default from Celery 4.0)
return cast(str | None, headers.get("id"))
# Protocol Version 1
if body is None:
return None
return cast(str | None, body.get("id"))
def retrieve_reason(kwargs: Mapping[str, Any]) -> object | None:
reason = kwargs.get("reason")
if not reason:
logger.debug("Unable to retrieve the retry reason")
return reason
version.py 0000664 0000000 0000000 00000000144 15270700723 0044616 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-celery/src/opentelemetry/instrumentation/celery # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
__version__ = "0.66b2"
test-requirements-0.txt 0000664 0000000 0000000 00000001016 15270700723 0036743 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-celery amqp==5.2.0
asgiref==3.8.1
backports.zoneinfo==0.2.1
billiard==4.2.0
celery==5.3.6
click==8.1.7
click-didyoumean==0.3.0
click-plugins==1.1.1
click-repl==0.3.0
Deprecated==1.2.14
iniconfig==2.0.0
kombu==5.3.5
packaging==24.0
pluggy==1.6.0
prompt-toolkit==3.0.43
py-cpuinfo==9.0.0
pytest==7.4.4
python-dateutil==2.8.2
six==1.16.0
tomli==2.0.1
typing_extensions==4.12.2
tzdata==2024.1
vine==5.1.0
wcwidth==0.2.13
wrapt==1.16.0
zipp==3.19.2
-e opentelemetry-instrumentation
-e instrumentation/opentelemetry-instrumentation-celery
test-requirements-1.txt 0000664 0000000 0000000 00000000764 15270700723 0036755 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-celery amqp==5.2.0
asgiref==3.8.1
billiard==4.2.1
celery==5.3.6
click==8.1.7
click-didyoumean==0.3.0
click-plugins==1.1.1
click-repl==0.3.0
Deprecated==1.2.14
iniconfig==2.0.0
kombu==5.3.5
packaging==24.0
pluggy==1.6.0
prompt-toolkit==3.0.43
py-cpuinfo==9.0.0
pytest==7.4.4
python-dateutil==2.8.2
six==1.16.0
tomli==2.0.1
typing_extensions==4.12.2
tzdata==2024.1
vine==5.1.0
wcwidth==0.2.13
wrapt==1.16.0
zipp==3.19.2
-e opentelemetry-instrumentation
-e instrumentation/opentelemetry-instrumentation-celery
opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-celery/tests/ 0000775 0000000 0000000 00000000000 15270700723 0033570 5 ustar 00root root 0000000 0000000 __init__.py 0000664 0000000 0000000 00000000000 15270700723 0035610 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-celery/tests celery_test_tasks.py 0000664 0000000 0000000 00000001024 15270700723 0037607 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-celery/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
from celery import Celery
from opentelemetry import baggage
class Config:
result_backend = "rpc"
broker_backend = "memory"
app = Celery(broker="memory:///")
app.config_from_object(Config)
class CustomError(Exception):
pass
@app.task
def task_add(num_a, num_b):
return num_a + num_b
@app.task
def task_raises():
raise CustomError("The task failed!")
@app.task
def task_returns_baggage():
return dict(baggage.get_all())
test_duplicate.py 0000664 0000000 0000000 00000001161 15270700723 0037073 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-celery/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
import unittest
from opentelemetry.instrumentation.celery import CeleryInstrumentor
class TestUtils(unittest.TestCase):
def test_duplicate_instrumentaion(self):
first = CeleryInstrumentor()
first.instrument()
second = CeleryInstrumentor()
second.instrument()
CeleryInstrumentor().uninstrument()
self.assertIsNotNone(first.metrics)
self.assertIsNotNone(second.metrics)
self.assertEqual(first.task_id_to_start_time, {})
self.assertEqual(second.task_id_to_start_time, {})
test_getter.py 0000664 0000000 0000000 00000005152 15270700723 0036417 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-celery/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
from unittest import TestCase, mock
from opentelemetry.instrumentation.celery import CeleryGetter
class TestCeleryGetter(TestCase):
def test_get_none(self):
"""Missing attribute on carrier should return None."""
getter = CeleryGetter()
carrier = {}
val = getter.get(carrier, "test")
self.assertIsNone(val)
def test_get_str(self):
"""String attribute should be wrapped in a single-element list."""
mock_obj = mock.Mock()
getter = CeleryGetter()
mock_obj.test = "val"
val = getter.get(mock_obj, "test")
self.assertEqual(val, ["val"])
def test_get_iter(self):
"""Iterable attribute should be returned as a list."""
mock_obj = mock.Mock()
getter = CeleryGetter()
mock_obj.test = ["val"]
val = getter.get(mock_obj, "test")
self.assertEqual(val, ["val"])
def test_get_int(self):
"""Non-string scalar values should be coerced to strings.
Celery's Context stores some attributes as ints (e.g. priority).
The TextMapPropagator contract requires string values; passing
an int to re.split() in TraceState.from_header() causes a
TypeError.
"""
mock_obj = mock.Mock()
getter = CeleryGetter()
mock_obj.test = 42
val = getter.get(mock_obj, "test")
self.assertEqual(val, ["42"])
def test_get_iter_with_non_string_elements(self):
"""Iterable values containing non-strings should be coerced.
Celery's timelimit attribute is a tuple of ints, e.g. (300, 60).
"""
mock_obj = mock.Mock()
getter = CeleryGetter()
mock_obj.test = (300, 60)
val = getter.get(mock_obj, "test")
self.assertEqual(val, ["300", "60"])
def test_get_iter_with_mixed_types(self):
"""Iterables with a mix of strings and non-strings."""
mock_obj = mock.Mock()
getter = CeleryGetter()
mock_obj.test = ["val", 123]
val = getter.get(mock_obj, "test")
self.assertEqual(val, ["val", "123"])
def test_get_non_str_non_iterable(self):
"""Non-string, non-iterable value should be coerced to [str(value)]."""
getter = CeleryGetter()
mock_obj = mock.Mock()
mock_obj.key = 42
val = getter.get(mock_obj, "key")
self.assertEqual(val, ["42"])
def test_keys(self):
"""keys() should return an empty list for any carrier."""
getter = CeleryGetter()
keys = getter.keys({})
self.assertEqual(keys, [])
test_metrics.py 0000664 0000000 0000000 00000005412 15270700723 0036572 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-celery/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
import threading
import time
from platform import python_implementation
from timeit import default_timer
from pytest import mark
from opentelemetry.instrumentation.celery import CeleryInstrumentor
from opentelemetry.test.test_base import TestBase
from .celery_test_tasks import app, task_add
SCOPE = "opentelemetry.instrumentation.celery"
class TestMetrics(TestBase):
def setUp(self):
super().setUp()
self._worker = app.Worker(app=app, pool="solo", concurrency=1, hostname="celery@akochavi")
self._thread = threading.Thread(target=self._worker.start)
self._thread.daemon = True
self._thread.start()
def tearDown(self):
super().tearDown()
self._worker.stop()
self._thread.join()
def get_metrics(self):
result = task_add.delay(1, 2)
timeout = time.time() + 60 * 1 # 1 minutes from now
while not result.ready():
if time.time() > timeout:
break
time.sleep(0.05)
return self.get_sorted_metrics(SCOPE)
def test_basic_metric(self):
CeleryInstrumentor().instrument()
start_time = default_timer()
task_runtime_estimated = (default_timer() - start_time) * 1000
metrics = self.get_metrics()
CeleryInstrumentor().uninstrument()
self.assertEqual(len(metrics), 1)
task_runtime = metrics[0]
print(task_runtime)
self.assertEqual(task_runtime.name, "flower.task.runtime.seconds")
self.assert_metric_expected(
task_runtime,
[
self.create_histogram_data_point(
count=1,
sum_data_point=task_runtime_estimated,
max_data_point=task_runtime_estimated,
min_data_point=task_runtime_estimated,
attributes={
"task": "tests.celery_test_tasks.task_add",
"worker": "celery@akochavi",
},
)
],
est_value_delta=200,
)
@mark.skipif(python_implementation() == "PyPy", reason="Fails randomly in pypy")
def test_metric_uninstrument(self):
CeleryInstrumentor().instrument()
metrics = self.get_metrics()
self.assertEqual(
metrics[0].data.data_points[0].bucket_counts[1],
1,
)
metrics = self.get_metrics()
self.assertEqual(
metrics[0].data.data_points[0].bucket_counts[1],
2,
)
CeleryInstrumentor().uninstrument()
metrics = self.get_metrics()
self.assertEqual(
metrics[0].data.data_points[0].bucket_counts[1],
2,
)
test_tasks.py 0000664 0000000 0000000 00000026174 15270700723 0036261 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-celery/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
import threading
import time
from wrapt import wrap_function_wrapper
from opentelemetry import baggage, context
from opentelemetry.instrumentation.celery import CeleryInstrumentor, utils
from opentelemetry.instrumentation.utils import unwrap
from opentelemetry.semconv.attributes.exception_attributes import (
EXCEPTION_MESSAGE,
EXCEPTION_STACKTRACE,
EXCEPTION_TYPE,
)
from opentelemetry.semconv.trace import SpanAttributes
from opentelemetry.test.test_base import TestBase
from opentelemetry.trace import SpanKind, StatusCode
from .celery_test_tasks import (
CustomError,
app,
task_add,
task_raises,
task_returns_baggage,
)
class TestCeleryInstrumentation(TestBase):
def setUp(self):
super().setUp()
self._worker = app.Worker(app=app, pool="solo", concurrency=1)
self._thread = threading.Thread(target=self._worker.start)
self._thread.daemon = True
self._thread.start()
def tearDown(self):
super().tearDown()
CeleryInstrumentor().uninstrument()
self._worker.stop()
self._thread.join()
CeleryInstrumentor().uninstrument()
def test_task(self):
CeleryInstrumentor().instrument()
result = task_add.delay(1, 2)
timeout = time.time() + 60 * 1 # 1 minutes from now
while not result.ready():
if time.time() > timeout:
break
time.sleep(0.05)
spans = self.sorted_spans(self.memory_exporter.get_finished_spans())
self.assertEqual(len(spans), 2)
consumer, producer = spans
self.assertEqual(consumer.name, "run/tests.celery_test_tasks.task_add")
self.assertEqual(consumer.kind, SpanKind.CONSUMER)
self.assertSpanHasAttributes(
consumer,
{
"celery.action": "run",
"celery.state": "SUCCESS",
SpanAttributes.MESSAGING_DESTINATION: "celery",
"celery.task_name": "tests.celery_test_tasks.task_add",
},
)
self.assertEqual(consumer.status.status_code, StatusCode.UNSET)
self.assertEqual(0, len(consumer.events))
self.assertEqual(producer.name, "apply_async/tests.celery_test_tasks.task_add")
self.assertEqual(producer.kind, SpanKind.PRODUCER)
self.assertSpanHasAttributes(
producer,
{
"celery.action": "apply_async",
"celery.task_name": "tests.celery_test_tasks.task_add",
SpanAttributes.MESSAGING_DESTINATION_KIND: "queue",
SpanAttributes.MESSAGING_DESTINATION: "celery",
},
)
self.assertNotEqual(consumer.parent, producer.context)
self.assertEqual(consumer.parent.span_id, producer.context.span_id)
self.assertEqual(consumer.context.trace_id, producer.context.trace_id)
def test_task_clears_start_time_cache(self):
"""Test that the `task_id_to_start_time` cache is cleared after a task finishes,
to prevent memory leaks."""
instrumentor = CeleryInstrumentor()
instrumentor.instrument()
result = task_add.delay(1, 2)
timeout = time.time() + 60 * 1 # 1 minutes from now
while not result.ready():
if time.time() > timeout:
break
time.sleep(0.05)
self.assertTrue(result.ready())
self.assertEqual(result.result, 3)
self.assertEqual(instrumentor.task_id_to_start_time, {})
def test_task_raises(self):
CeleryInstrumentor().instrument()
result = task_raises.delay()
timeout = time.time() + 60 * 1 # 1 minutes from now
while not result.ready():
if time.time() > timeout:
break
time.sleep(0.05)
spans = self.sorted_spans(self.memory_exporter.get_finished_spans())
self.assertEqual(len(spans), 2)
consumer, producer = spans
self.assertEqual(consumer.name, "run/tests.celery_test_tasks.task_raises")
self.assertEqual(consumer.kind, SpanKind.CONSUMER)
self.assertSpanHasAttributes(
consumer,
{
"celery.action": "run",
"celery.state": "FAILURE",
SpanAttributes.MESSAGING_DESTINATION: "celery",
"celery.task_name": "tests.celery_test_tasks.task_raises",
},
)
self.assertEqual(consumer.status.status_code, StatusCode.ERROR)
self.assertEqual(1, len(consumer.events))
event = consumer.events[0]
self.assertIn(EXCEPTION_STACKTRACE, event.attributes)
self.assertEqual(
f"{CustomError.__module__}.{CustomError.__qualname__}",
event.attributes[EXCEPTION_TYPE],
)
self.assertEqual(
event.attributes[EXCEPTION_MESSAGE],
"The task failed!",
)
self.assertEqual(producer.name, "apply_async/tests.celery_test_tasks.task_raises")
self.assertEqual(producer.kind, SpanKind.PRODUCER)
self.assertSpanHasAttributes(
producer,
{
"celery.action": "apply_async",
"celery.task_name": "tests.celery_test_tasks.task_raises",
SpanAttributes.MESSAGING_DESTINATION_KIND: "queue",
SpanAttributes.MESSAGING_DESTINATION: "celery",
},
)
self.assertNotEqual(consumer.parent, producer.context)
self.assertEqual(consumer.parent.span_id, producer.context.span_id)
self.assertEqual(consumer.context.trace_id, producer.context.trace_id)
def test_uninstrument(self):
CeleryInstrumentor().instrument()
CeleryInstrumentor().uninstrument()
result = task_add.delay(1, 2)
timeout = time.time() + 60 * 1 # 1 minutes from now
while not result.ready():
if time.time() > timeout:
break
time.sleep(0.05)
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 0)
def test_baggage(self):
CeleryInstrumentor().instrument()
ctx = baggage.set_baggage("key", "value")
context.attach(ctx)
task = task_returns_baggage.delay()
timeout = time.time() + 60 * 1 # 1 minutes from now
while not task.ready():
if time.time() > timeout:
break
time.sleep(0.05)
self.assertEqual(task.result, {"key": "value"})
def test_task_not_instrumented_does_not_raise(self):
def _retrieve_context_wrapper_none_token(wrapped, instance, args, kwargs):
ctx = wrapped(*args, **kwargs)
if ctx is None:
return ctx
span, activation, _ = ctx
return span, activation, None
wrap_function_wrapper(
utils,
"retrieve_context",
_retrieve_context_wrapper_none_token,
)
CeleryInstrumentor().instrument()
result = task_add.delay(1, 2)
timeout = time.time() + 60 * 1 # 1 minutes from now
while not result.ready():
if time.time() > timeout:
break
time.sleep(0.05)
spans = self.sorted_spans(self.memory_exporter.get_finished_spans())
self.assertEqual(len(spans), 2)
# TODO: assert we don't have "TypeError: expected an instance of Token, got None" in logs
self.assertTrue(result)
unwrap(utils, "retrieve_context")
def test_task_use_span_links(self):
CeleryInstrumentor().instrument(use_span_links=True)
result = task_add.delay(1, 2)
timeout = time.time() + 60 * 1 # 1 minute from now
while not result.ready():
if time.time() > timeout:
break
time.sleep(0.05)
spans = self.sorted_spans(self.memory_exporter.get_finished_spans())
self.assertEqual(len(spans), 2)
consumer, producer = spans
self.assertEqual(consumer.name, "run/tests.celery_test_tasks.task_add")
self.assertEqual(consumer.kind, SpanKind.CONSUMER)
self.assertSpanHasAttributes(
consumer,
{
"celery.action": "run",
"celery.state": "SUCCESS",
SpanAttributes.MESSAGING_DESTINATION: "celery",
"celery.task_name": "tests.celery_test_tasks.task_add",
},
)
self.assertEqual(consumer.status.status_code, StatusCode.UNSET)
self.assertEqual(0, len(consumer.events))
self.assertEqual(producer.name, "apply_async/tests.celery_test_tasks.task_add")
self.assertEqual(producer.kind, SpanKind.PRODUCER)
self.assertSpanHasAttributes(
producer,
{
"celery.action": "apply_async",
"celery.task_name": "tests.celery_test_tasks.task_add",
SpanAttributes.MESSAGING_DESTINATION_KIND: "queue",
SpanAttributes.MESSAGING_DESTINATION: "celery",
},
)
# Verify that consumer span is not a child of producer span when using links
self.assertIsNone(consumer.parent)
self.assertNotEqual(consumer.context.trace_id, producer.context.trace_id)
# Verify that consumer span has a link to the producer span
self.assertEqual(len(consumer.links), 1)
link = consumer.links[0]
self.assertEqual(link.context.span_id, producer.context.span_id)
self.assertEqual(link.context.trace_id, producer.context.trace_id)
class TestCelerySignatureTask(TestBase):
def setUp(self):
super().setUp()
def start_app(*args, **kwargs):
# Add an additional task that will not be registered with parent thread
@app.task
def hidden_task(num_a):
return num_a * 2
self._worker = app.Worker(app=app, pool="solo", concurrency=1)
return self._worker.start(*args, **kwargs)
self._thread = threading.Thread(target=start_app)
self._worker = app.Worker(app=app, pool="solo", concurrency=1)
self._thread.daemon = True
self._thread.start()
def tearDown(self):
super().tearDown()
self._worker.stop()
self._thread.join()
CeleryInstrumentor().uninstrument()
def test_hidden_task(self):
# no-op since already instrumented
CeleryInstrumentor().instrument()
res = app.signature("tests.test_tasks.hidden_task", (2,)).apply_async()
while not res.ready():
time.sleep(0.05)
spans = self.sorted_spans(self.memory_exporter.get_finished_spans())
self.assertEqual(len(spans), 2)
consumer, producer = spans
self.assertEqual(consumer.name, "run/tests.test_tasks.hidden_task")
self.assertEqual(consumer.kind, SpanKind.CONSUMER)
self.assertEqual(producer.name, "apply_async/tests.test_tasks.hidden_task")
self.assertEqual(producer.kind, SpanKind.PRODUCER)
self.assertNotEqual(consumer.parent, producer.context)
self.assertEqual(consumer.parent.span_id, producer.context.span_id)
self.assertEqual(consumer.context.trace_id, producer.context.trace_id)
test_utils.py 0000664 0000000 0000000 00000023425 15270700723 0036270 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-celery/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
import unittest
from unittest import mock
from celery import Celery
from opentelemetry import trace as trace_api
from opentelemetry.instrumentation.celery import utils
from opentelemetry.sdk import trace
from opentelemetry.semconv._incubating.attributes.messaging_attributes import (
MESSAGING_MESSAGE_ID,
)
from opentelemetry.semconv.trace import SpanAttributes
class TestUtils(unittest.TestCase):
def setUp(self):
self.app = Celery("celery.test_app")
def test_set_attributes_from_context(self):
# it should extract only relevant keys
context = {
"correlation_id": "44b7f305",
"delivery_info": {"eager": True},
"eta": "soon",
"expires": "later",
"hostname": "localhost",
"id": "44b7f305",
"reply_to": "44b7f305",
"retries": 4,
"timelimit": ("now", "later"),
"custom_meta": "custom_value",
"routing_key": "celery",
}
span = trace._Span("name", mock.Mock(spec=trace_api.SpanContext))
utils.set_attributes_from_context(span, context)
self.assertEqual(
span.attributes.get(MESSAGING_MESSAGE_ID),
"44b7f305",
)
self.assertEqual(
span.attributes.get(SpanAttributes.MESSAGING_CONVERSATION_ID),
"44b7f305",
)
self.assertEqual(span.attributes.get(SpanAttributes.MESSAGING_DESTINATION), "celery")
self.assertEqual(span.attributes["celery.delivery_info"], str({"eager": True}))
self.assertEqual(span.attributes.get("celery.eta"), "soon")
self.assertEqual(span.attributes.get("celery.expires"), "later")
self.assertEqual(span.attributes.get("celery.hostname"), "localhost")
self.assertEqual(span.attributes.get("celery.reply_to"), "44b7f305")
self.assertEqual(span.attributes.get("celery.retries"), 4)
self.assertEqual(span.attributes.get("celery.timelimit"), ("now", "later"))
self.assertNotIn("custom_meta", span.attributes)
def test_set_attributes_not_recording(self):
# it should extract only relevant keys
context = {
"correlation_id": "44b7f305",
"delivery_info": {"eager": True},
"eta": "soon",
"expires": "later",
"hostname": "localhost",
"id": "44b7f305",
"reply_to": "44b7f305",
"retries": 4,
"timelimit": ("now", "later"),
"custom_meta": "custom_value",
"routing_key": "celery",
}
mock_span = mock.Mock()
mock_span.is_recording.return_value = False
utils.set_attributes_from_context(mock_span, context)
self.assertFalse(mock_span.is_recording())
self.assertTrue(mock_span.is_recording.called)
self.assertFalse(mock_span.set_attribute.called)
self.assertFalse(mock_span.set_status.called)
def test_set_attributes_partial_timelimit_hard_limit(self):
# it should extract only relevant keys
context = {
"correlation_id": "44b7f305",
"delivery_info": {"eager": True},
"eta": "soon",
"expires": "later",
"hostname": "localhost",
"id": "44b7f305",
"reply_to": "44b7f305",
"retries": 4,
"timelimit": ("now", None),
"custom_meta": "custom_value",
"routing_key": "celery",
}
span = trace._Span("name", mock.Mock(spec=trace_api.SpanContext))
utils.set_attributes_from_context(span, context)
self.assertEqual(span.attributes.get("celery.timelimit"), ("now", ""))
def test_set_attributes_partial_timelimit_soft_limit(self):
# it should extract only relevant keys
context = {
"correlation_id": "44b7f305",
"delivery_info": {"eager": True},
"eta": "soon",
"expires": "later",
"hostname": "localhost",
"id": "44b7f305",
"reply_to": "44b7f305",
"retries": 4,
"timelimit": (None, "later"),
"custom_meta": "custom_value",
"routing_key": "celery",
}
span = trace._Span("name", mock.Mock(spec=trace_api.SpanContext))
utils.set_attributes_from_context(span, context)
self.assertEqual(span.attributes.get("celery.timelimit"), ("", "later"))
def test_set_attributes_from_context_empty_keys(self):
# it should not extract empty keys
context = {
"correlation_id": None,
"exchange": "",
"timelimit": (None, None),
"retries": 0,
}
span = trace._Span("name", mock.Mock(spec=trace_api.SpanContext))
utils.set_attributes_from_context(span, context)
self.assertEqual(len(span.attributes), 0)
# edge case: `timelimit` can also be a list of None values
context = {
"timelimit": [None, None],
}
utils.set_attributes_from_context(span, context)
self.assertEqual(len(span.attributes), 0)
def test_span_propagation(self):
# ensure spans getter and setter works properly
@self.app.task
def fn_task():
return 42
# propagate and retrieve a Span
task_id = "7c6731af-9533-40c3-83a9-25b58f0d837f"
span = trace._Span("name", mock.Mock(spec=trace_api.SpanContext))
utils.attach_context(fn_task, task_id, span, mock.Mock(), "")
ctx = utils.retrieve_context(fn_task, task_id)
self.assertIsNotNone(ctx)
span_after, _, _ = ctx
self.assertIs(span, span_after)
def test_span_delete(self):
# ensure the helper removes properly a propagated Span
@self.app.task
def fn_task():
return 42
# propagate a Span
task_id = "7c6731af-9533-40c3-83a9-25b58f0d837f"
span = trace._Span("name", mock.Mock(spec=trace_api.SpanContext))
utils.attach_context(fn_task, task_id, span, mock.Mock(), "")
# delete the Span
utils.detach_context(fn_task, task_id)
self.assertEqual(utils.retrieve_context(fn_task, task_id), None)
def test_optional_task_span_attach(self):
task_id = "7c6731af-9533-40c3-83a9-25b58f0d837f"
span = trace._Span("name", mock.Mock(spec=trace_api.SpanContext))
# assert this is is a no-aop
self.assertIsNone(utils.attach_context(None, task_id, span, mock.Mock(), ""))
def test_span_delete_empty(self):
# ensure detach_span doesn't raise an exception if span is not present
@self.app.task
def fn_task():
return 42
# delete the Span
task_id = "7c6731af-9533-40c3-83a9-25b58f0d837f"
try:
utils.detach_context(fn_task, task_id)
self.assertEqual(utils.retrieve_context(fn_task, task_id), None)
except Exception as ex: # pylint: disable=broad-except
self.fail(f"Exception was raised: {ex}")
def test_task_id_from_protocol_v1(self):
# ensures a `task_id` is properly returned when Protocol v1 is used.
# `context` is an example of an emitted Signal with Protocol v1
context = {
"body": {
"expires": None,
"utc": True,
"args": ["user"],
"chord": None,
"callbacks": None,
"errbacks": None,
"taskset": None,
"id": "dffcaec1-dd92-4a1a-b3ab-d6512f4beeb7",
"retries": 0,
"task": "tests.contrib.celery.test_integration.fn_task_parameters",
"timelimit": (None, None),
"eta": None,
"kwargs": {"force_logout": True},
},
"sender": "tests.contrib.celery.test_integration.fn_task_parameters",
"exchange": "celery",
"routing_key": "celery",
"retry_policy": None,
"headers": {},
"properties": {},
}
task_id = utils.retrieve_task_id_from_message(context)
self.assertEqual(task_id, "dffcaec1-dd92-4a1a-b3ab-d6512f4beeb7")
def test_task_id_from_protocol_v2(self):
# ensures a `task_id` is properly returned when Protocol v2 is used.
# `context` is an example of an emitted Signal with Protocol v2
context = {
"body": (
["user"],
{"force_logout": True},
{
"chord": None,
"callbacks": None,
"errbacks": None,
"chain": None,
},
),
"sender": "tests.contrib.celery.test_integration.fn_task_parameters",
"exchange": "",
"routing_key": "celery",
"retry_policy": None,
"headers": {
"origin": "gen83744@hostname",
"root_id": "7e917b83-4018-431d-9832-73a28e1fb6c0",
"expires": None,
"shadow": None,
"id": "7e917b83-4018-431d-9832-73a28e1fb6c0",
"kwargsrepr": "{'force_logout': True}",
"lang": "py",
"retries": 0,
"task": "tests.contrib.celery.test_integration.fn_task_parameters",
"group": None,
"timelimit": [None, None],
"parent_id": None,
"argsrepr": "['user']",
"eta": None,
},
"properties": {
"reply_to": "c3054a07-5b28-3855-b18c-1623a24aaeca",
"correlation_id": "7e917b83-4018-431d-9832-73a28e1fb6c0",
},
}
task_id = utils.retrieve_task_id_from_message(context)
self.assertEqual(task_id, "7e917b83-4018-431d-9832-73a28e1fb6c0")
opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-click/ 0000775 0000000 0000000 00000000000 15270700723 0032230 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-click/README.rst 0000664 0000000 0000000 00000001130 15270700723 0033712 0 ustar 00root root 0000000 0000000 OpenTelemetry click Instrumentation
====================================
|pypi|
.. |pypi| image:: https://badge.fury.io/py/opentelemetry-instrumentation-click.svg
:target: https://pypi.org/project/opentelemetry-instrumentation-click/
This library allows tracing requests made by the click library.
Installation
------------
::
pip install opentelemetry-instrumentation-click
References
----------
* `OpenTelemetry click/ Tracing `_
* `OpenTelemetry Project `_
pyproject.toml 0000664 0000000 0000000 00000003153 15270700723 0035067 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-click [build-system]
requires = ["hatchling"]
build-backend = "hatchling.build"
[project]
name = "opentelemetry-instrumentation-click"
dynamic = ["version"]
description = "Click instrumentation for OpenTelemetry"
readme = "README.rst"
license = "Apache-2.0"
requires-python = ">=3.10"
authors = [
{ name = "OpenTelemetry Authors", email = "cncf-opentelemetry-contributors@lists.cncf.io" },
]
classifiers = [
"Development Status :: 4 - Beta",
"Intended Audience :: Developers",
"License :: OSI Approved :: Apache Software License",
"Programming Language :: Python",
"Programming Language :: Python :: 3",
"Programming Language :: Python :: 3.10",
"Programming Language :: Python :: 3.11",
"Programming Language :: Python :: 3.12",
"Programming Language :: Python :: 3.13",
"Programming Language :: Python :: 3.14",
]
dependencies = [
"opentelemetry-api ~= 1.12",
"opentelemetry-instrumentation == 0.66b2",
"opentelemetry-semantic-conventions == 0.66b2",
"wrapt >= 1.0.0, < 3.0.0",
]
[project.optional-dependencies]
instruments = [
"click >= 8.1.3, < 9.0.0",
]
[project.entry-points.opentelemetry_instrumentor]
click = "opentelemetry.instrumentation.click:ClickInstrumentor"
[project.urls]
Homepage = "https://github.com/open-telemetry/opentelemetry-python-contrib/instrumentation/opentelemetry-instrumentation-click"
Repository = "https://github.com/open-telemetry/opentelemetry-python-contrib"
[tool.hatch.version]
path = "src/opentelemetry/instrumentation/click/version.py"
[tool.hatch.build.targets.sdist]
include = [
"/src",
"/tests",
]
[tool.hatch.build.targets.wheel]
packages = ["src/opentelemetry"]
opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-click/src/ 0000775 0000000 0000000 00000000000 15270700723 0033017 5 ustar 00root root 0000000 0000000 opentelemetry/ 0000775 0000000 0000000 00000000000 15270700723 0035634 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-click/src instrumentation/ 0000775 0000000 0000000 00000000000 15270700723 0041077 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-click/src/opentelemetry click/ 0000775 0000000 0000000 00000000000 15270700723 0042164 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-click/src/opentelemetry/instrumentation __init__.py 0000664 0000000 0000000 00000007116 15270700723 0044302 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-click/src/opentelemetry/instrumentation/click # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
"""
Instrument `click`_ CLI applications. The instrumentor will avoid instrumenting
well-known servers (e.g. *flask run* and *uvicorn*) to avoid unexpected effects
like every request having the same Trace ID.
.. _click: https://pypi.org/project/click/
Usage
-----
.. code-block:: python
import click
from opentelemetry.instrumentation.click import ClickInstrumentor
ClickInstrumentor().instrument()
@click.command()
def hello():
click.echo(f"Hello world!")
if __name__ == "__main__":
hello()
API
---
"""
import os
import sys
from collections.abc import Collection
from functools import partial
from logging import getLogger
import click
from wrapt import wrap_function_wrapper
try:
from flask.cli import ScriptInfo as FlaskScriptInfo
except ImportError:
FlaskScriptInfo = None
from opentelemetry import trace
from opentelemetry.instrumentation.click.package import _instruments
from opentelemetry.instrumentation.click.version import __version__
from opentelemetry.instrumentation.instrumentor import BaseInstrumentor
from opentelemetry.instrumentation.utils import (
unwrap,
)
from opentelemetry.semconv._incubating.attributes.process_attributes import (
PROCESS_COMMAND_ARGS,
PROCESS_EXECUTABLE_NAME,
PROCESS_EXIT_CODE,
PROCESS_PID,
)
from opentelemetry.semconv.attributes.error_attributes import ERROR_TYPE
from opentelemetry.trace.status import StatusCode
_logger = getLogger(__name__)
def _skip_servers(ctx: click.Context):
# flask run
if ctx.info_name == "run" and FlaskScriptInfo and isinstance(ctx.obj, FlaskScriptInfo):
return True
# uvicorn
if ctx.info_name == "uvicorn":
return True
return False
def _command_invoke_wrapper(wrapped, instance, args, kwargs, tracer):
# Subclasses of Command include groups and CLI runners, but
# we only want to instrument the actual commands which are
# instances of Command itself.
if instance.__class__ != click.Command:
return wrapped(*args, **kwargs)
ctx = args[0]
# we don't want to create a root span for long running processes like servers
# otherwise all requests would have the same trace id
if _skip_servers(ctx):
return wrapped(*args, **kwargs)
span_name = ctx.info_name
span_attributes = {
PROCESS_COMMAND_ARGS: sys.argv,
PROCESS_EXECUTABLE_NAME: sys.argv[0],
PROCESS_EXIT_CODE: 0,
PROCESS_PID: os.getpid(),
}
with tracer.start_as_current_span(
name=span_name,
kind=trace.SpanKind.INTERNAL,
attributes=span_attributes,
) as span:
try:
return wrapped(*args, **kwargs)
except Exception as exc:
span.set_status(StatusCode.ERROR, str(exc))
if span.is_recording():
span.set_attribute(ERROR_TYPE, exc.__class__.__qualname__)
span.set_attribute(PROCESS_EXIT_CODE, getattr(exc, "exit_code", 1))
raise
class ClickInstrumentor(BaseInstrumentor):
"""An instrumentor for click"""
def instrumentation_dependencies(self) -> Collection[str]:
return _instruments
def _instrument(self, **kwargs):
tracer = trace.get_tracer(
__name__,
__version__,
kwargs.get("tracer_provider"),
)
wrap_function_wrapper(
click.core.Command,
"invoke",
partial(_command_invoke_wrapper, tracer=tracer),
)
def _uninstrument(self, **kwargs):
unwrap(click.core.Command, "invoke")
package.py 0000664 0000000 0000000 00000000172 15270700723 0044131 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-click/src/opentelemetry/instrumentation/click # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
_instruments = ("click >= 8.1.3, < 9.0.0",)
version.py 0000664 0000000 0000000 00000000144 15270700723 0044222 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-click/src/opentelemetry/instrumentation/click # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
__version__ = "0.66b2"
test-requirements.txt 0000664 0000000 0000000 00000001034 15270700723 0036410 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-click asgiref==3.8.1
blinker==1.7.0
click==8.1.7
Deprecated==1.2.14
Flask==3.0.2
iniconfig==2.0.0
itsdangerous==2.1.2
Jinja2==3.1.6
MarkupSafe==2.1.2
packaging==24.0
pluggy==1.6.0
py-cpuinfo==9.0.0
pytest==7.4.4
pytest-asyncio==0.23.5
tomli==2.0.1
typing_extensions==4.12.2
Werkzeug==3.0.6
wrapt==1.16.0
zipp==3.19.2
-e opentelemetry-instrumentation
-e instrumentation/opentelemetry-instrumentation-click
-e instrumentation/opentelemetry-instrumentation-flask
-e instrumentation/opentelemetry-instrumentation-wsgi
-e util/opentelemetry-util-http
opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-click/tests/ 0000775 0000000 0000000 00000000000 15270700723 0033372 5 ustar 00root root 0000000 0000000 test_click.py 0000664 0000000 0000000 00000013755 15270700723 0036024 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-click/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
import os
from unittest import mock
import click
import pytest
from click.testing import CliRunner
try:
from flask import cli as flask_cli
except ImportError:
flask_cli = None
from opentelemetry.instrumentation.click import ClickInstrumentor
from opentelemetry.test.test_base import TestBase
from opentelemetry.trace import SpanKind
from opentelemetry.trace.status import StatusCode
class ClickTestCase(TestBase):
# pylint: disable=unbalanced-tuple-unpacking
def setUp(self):
super().setUp()
ClickInstrumentor().instrument()
def tearDown(self):
super().tearDown()
ClickInstrumentor().uninstrument()
@mock.patch("sys.argv", ["command.py"])
def test_cli_command_wrapping(self):
@click.command()
def command():
pass
runner = CliRunner()
result = runner.invoke(command)
self.assertEqual(result.exit_code, 0)
(span,) = self.memory_exporter.get_finished_spans()
self.assertEqual(span.status.status_code, StatusCode.UNSET)
self.assertEqual(span.kind, SpanKind.INTERNAL)
self.assertEqual(span.name, "command")
self.assertEqual(
dict(span.attributes),
{
"process.executable.name": "command.py",
"process.command_args": ("command.py",),
"process.exit.code": 0,
"process.pid": os.getpid(),
},
)
@mock.patch("sys.argv", ["flask", "command"])
def test_flask_command_wrapping(self):
@click.command()
def command():
pass
runner = CliRunner()
result = runner.invoke(command)
self.assertEqual(result.exit_code, 0)
(span,) = self.memory_exporter.get_finished_spans()
self.assertEqual(span.status.status_code, StatusCode.UNSET)
self.assertEqual(span.kind, SpanKind.INTERNAL)
self.assertEqual(span.name, "command")
self.assertEqual(
dict(span.attributes),
{
"process.executable.name": "flask",
"process.command_args": (
"flask",
"command",
),
"process.exit.code": 0,
"process.pid": os.getpid(),
},
)
@mock.patch("sys.argv", ["command.py"])
def test_cli_command_wrapping_with_name(self):
@click.command("mycommand")
def renamedcommand():
pass
runner = CliRunner()
result = runner.invoke(renamedcommand)
self.assertEqual(result.exit_code, 0)
(span,) = self.memory_exporter.get_finished_spans()
self.assertEqual(span.status.status_code, StatusCode.UNSET)
self.assertEqual(span.kind, SpanKind.INTERNAL)
self.assertEqual(span.name, "mycommand")
self.assertEqual(
dict(span.attributes),
{
"process.executable.name": "command.py",
"process.command_args": ("command.py",),
"process.exit.code": 0,
"process.pid": os.getpid(),
},
)
@mock.patch("sys.argv", ["command.py", "--opt", "argument"])
def test_cli_command_wrapping_with_options(self):
@click.command()
@click.argument("argument")
@click.option("--opt/--no-opt", default=False)
def command(argument, opt):
pass
argv = ["command.py", "--opt", "argument"]
runner = CliRunner()
result = runner.invoke(command, argv[1:])
self.assertEqual(result.exit_code, 0)
(span,) = self.memory_exporter.get_finished_spans()
self.assertEqual(span.status.status_code, StatusCode.UNSET)
self.assertEqual(span.kind, SpanKind.INTERNAL)
self.assertEqual(span.name, "command")
self.assertEqual(
dict(span.attributes),
{
"process.executable.name": "command.py",
"process.command_args": tuple(argv),
"process.exit.code": 0,
"process.pid": os.getpid(),
},
)
@mock.patch("sys.argv", ["command-raises.py"])
def test_cli_command_raises_error(self):
@click.command()
def command_raises():
raise ValueError()
runner = CliRunner()
result = runner.invoke(command_raises)
self.assertEqual(result.exit_code, 1)
(span,) = self.memory_exporter.get_finished_spans()
self.assertEqual(span.status.status_code, StatusCode.ERROR)
self.assertEqual(span.kind, SpanKind.INTERNAL)
self.assertEqual(span.name, "command-raises")
self.assertEqual(
dict(span.attributes),
{
"process.executable.name": "command-raises.py",
"process.command_args": ("command-raises.py",),
"process.exit.code": 1,
"process.pid": os.getpid(),
"error.type": "ValueError",
},
)
def test_uvicorn_cli_command_ignored(self):
@click.command("uvicorn")
def command_uvicorn():
pass
runner = CliRunner()
result = runner.invoke(command_uvicorn)
self.assertEqual(result.exit_code, 0)
self.assertFalse(self.memory_exporter.get_finished_spans())
@pytest.mark.skipif(flask_cli is None, reason="requires flask")
def test_flask_run_command_ignored(self):
runner = CliRunner()
result = runner.invoke(flask_cli.run_command, obj=flask_cli.ScriptInfo())
self.assertEqual(result.exit_code, 2)
self.assertFalse(self.memory_exporter.get_finished_spans())
def test_uninstrument(self):
ClickInstrumentor().uninstrument()
@click.command()
def notracecommand():
pass
runner = CliRunner()
result = runner.invoke(notracecommand)
self.assertEqual(result.exit_code, 0)
self.assertFalse(self.memory_exporter.get_finished_spans())
opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-confluent-kafka/ 0000775 0000000 0000000 00000000000 15270700723 0034213 5 ustar 00root root 0000000 0000000 LICENSE 0000664 0000000 0000000 00000026135 15270700723 0035150 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-confluent-kafka Apache License
Version 2.0, January 2004
http://www.apache.org/licenses/
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README.rst 0000664 0000000 0000000 00000001260 15270700723 0035622 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-confluent-kafka OpenTelemetry confluent-kafka Instrumentation
=============================================
|pypi|
.. |pypi| image:: https://badge.fury.io/py/opentelemetry-instrumentation-confluent-kafka.svg
:target: https://pypi.org/project/opentelemetry-instrumentation-confluent-kafka/
This library allows tracing requests made by the confluent-kafka library.
Installation
------------
::
pip install opentelemetry-instrumentation-confluent-kafka
References
----------
* `OpenTelemetry confluent-kafka/ Tracing `_
* `OpenTelemetry Project `_
pyproject.toml 0000664 0000000 0000000 00000003264 15270700723 0037055 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-confluent-kafka [build-system]
requires = ["hatchling"]
build-backend = "hatchling.build"
[project]
name = "opentelemetry-instrumentation-confluent-kafka"
dynamic = ["version"]
description = "OpenTelemetry Confluent Kafka instrumentation"
readme = "README.rst"
license = "Apache-2.0"
requires-python = ">=3.10"
authors = [
{ name = "OpenTelemetry Authors", email = "cncf-opentelemetry-contributors@lists.cncf.io" },
]
classifiers = [
"Development Status :: 4 - Beta",
"Intended Audience :: Developers",
"License :: OSI Approved :: Apache Software License",
"Programming Language :: Python",
"Programming Language :: Python :: 3",
"Programming Language :: Python :: 3.10",
"Programming Language :: Python :: 3.11",
"Programming Language :: Python :: 3.12",
"Programming Language :: Python :: 3.13",
"Programming Language :: Python :: 3.14",
]
dependencies = [
"opentelemetry-instrumentation == 0.66b2",
"opentelemetry-semantic-conventions == 0.66b2",
"opentelemetry-api ~= 1.12",
"wrapt >= 1.0.0, < 3.0.0",
]
[project.optional-dependencies]
instruments = ["confluent-kafka >= 1.8.2, < 3.0.0"]
[project.entry-points.opentelemetry_instrumentor]
confluent_kafka = "opentelemetry.instrumentation.confluent_kafka:ConfluentKafkaInstrumentor"
[project.urls]
Homepage = "https://github.com/open-telemetry/opentelemetry-python-contrib/tree/main/instrumentation/opentelemetry-instrumentation-confluent-kafka"
Repository = "https://github.com/open-telemetry/opentelemetry-python-contrib"
[tool.hatch.version]
path = "src/opentelemetry/instrumentation/confluent_kafka/version.py"
[tool.hatch.build.targets.sdist]
include = ["/src", "/tests"]
[tool.hatch.build.targets.wheel]
packages = ["src/opentelemetry"]
src/ 0000775 0000000 0000000 00000000000 15270700723 0034723 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-confluent-kafka opentelemetry/ 0000775 0000000 0000000 00000000000 15270700723 0037617 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-confluent-kafka/src instrumentation/ 0000775 0000000 0000000 00000000000 15270700723 0043062 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-confluent-kafka/src/opentelemetry confluent_kafka/ 0000775 0000000 0000000 00000000000 15270700723 0046214 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-confluent-kafka/src/opentelemetry/instrumentation __init__.py 0000664 0000000 0000000 00000036030 15270700723 0050327 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-confluent-kafka/src/opentelemetry/instrumentation/confluent_kafka # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
"""
Instrument confluent-kafka-python to report instrumentation-confluent-kafka produced and consumed messages
Usage
-----
.. code:: python
from opentelemetry.instrumentation.confluent_kafka import ConfluentKafkaInstrumentor
from confluent_kafka import Producer, Consumer
# Instrument kafka
ConfluentKafkaInstrumentor().instrument()
# report a span of type producer with the default settings
conf1 = {'bootstrap.servers': "localhost:9092"}
producer = Producer(conf1)
producer.produce('my-topic',b'raw_bytes')
conf2 = {'bootstrap.servers': "localhost:9092", 'group.id': "foo", 'auto.offset.reset': 'smallest'}
# report a span of type consumer with the default settings
consumer = Consumer(conf2)
def msg_process(msg):
print(msg)
def basic_consume_loop(consumer, topics):
try:
consumer.subscribe(topics)
running = True
while running:
msg = consumer.poll(timeout=1.0)
if msg is None: continue
if msg.error():
if msg.error().code() == KafkaError._PARTITION_EOF:
# End of partition event
sys.stderr.write(f"{msg.topic()} [{msg.partition()}] reached end at offset {msg.offset()}")
elif msg.error():
raise KafkaException(msg.error())
else:
msg_process(msg)
finally:
# Close down consumer to commit final offsets.
consumer.close()
basic_consume_loop(consumer, ["my-topic"])
The ``_instrument()`` method accepts the following keyword args:
- **tracer_provider** (TracerProvider) - an optional tracer provider
- **instrument_producer** (Callable) - a function with extra user-defined logic to be performed before sending the message
Function signature:
.. code:: python
def instrument_producer(producer: Producer, tracer_provider=None): ...
- **instrument_consumer** (Callable) - a function with extra user-defined logic to be performed after consuming a message
Function signature:
.. code:: python
def instrument_consumer(consumer: Consumer, tracer_provider=None): ...
For example:
.. code:: python
from opentelemetry.instrumentation.confluent_kafka import ConfluentKafkaInstrumentor
from opentelemetry.trace import get_tracer_provider
from confluent_kafka import Producer, Consumer
inst = ConfluentKafkaInstrumentor()
tracer_provider = get_tracer_provider()
p = Producer({'bootstrap.servers': 'localhost:9092'})
c = Consumer({
'bootstrap.servers': 'localhost:9092',
'group.id': 'mygroup',
'auto.offset.reset': 'earliest'
})
# instrument confluent kafka with produce and consume hooks
p = inst.instrument_producer(p, tracer_provider)
c = inst.instrument_consumer(c, tracer_provider=tracer_provider)
# Using kafka as normal now will automatically generate spans,
# including user custom attributes added from the hooks
conf = {'bootstrap.servers': "localhost:9092"}
p.produce('my-topic',b'raw_bytes')
msg = c.poll()
"""
from collections.abc import Collection
import confluent_kafka
import wrapt
from confluent_kafka import Consumer, Producer
from opentelemetry import context, propagate, trace
from opentelemetry.instrumentation.instrumentor import BaseInstrumentor
from opentelemetry.instrumentation.utils import unwrap
from opentelemetry.semconv._incubating.attributes.messaging_attributes import (
MessagingOperationTypeValues,
)
from opentelemetry.trace import Tracer
from .package import _instruments
from .utils import (
KafkaPropertiesExtractor,
_create_new_consume_span,
_end_current_consume_span,
_enrich_span,
_get_span_name,
_kafka_setter,
)
from .version import __version__
def _capture_config(args, kwargs):
"""Return the config dict that was passed to a Producer/Consumer
constructor, regardless of whether it was supplied positionally, as
``conf=`` kwarg, or (for Consumer) expanded as **kwargs."""
if args and isinstance(args[0], dict):
return args[0]
conf = kwargs.get("conf")
if isinstance(conf, dict):
return conf
# confluent_kafka.Consumer also supports Consumer(**conf) — in that case
# the kwargs themselves are the config.
if kwargs:
return dict(kwargs)
return None
class AutoInstrumentedProducer(Producer):
def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs)
self.config = _capture_config(args, kwargs)
# This method is deliberately implemented in order to allow wrapt to wrap this function
def produce(self, topic, value=None, *args, **kwargs): # pylint: disable=keyword-arg-before-vararg,useless-super-delegation
super().produce(topic, value, *args, **kwargs)
class AutoInstrumentedConsumer(Consumer):
def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs)
self.config = _capture_config(args, kwargs)
self._current_consume_span = None
# This method is deliberately implemented in order to allow wrapt to wrap this function
def poll(self, timeout=-1): # pylint: disable=useless-super-delegation
return super().poll(timeout)
# This method is deliberately implemented in order to allow wrapt to wrap this function
def consume(self, *args, **kwargs): # pylint: disable=useless-super-delegation
return super().consume(*args, **kwargs)
# This method is deliberately implemented in order to allow wrapt to wrap this function
def close(self): # pylint: disable=useless-super-delegation
return super().close()
class ProxiedProducer(Producer):
def __init__(self, producer: Producer, tracer: Tracer):
self._producer = producer
self._tracer = tracer
# Surface the wrapped producer's config (if any) so that
# KafkaPropertiesExtractor.extract_bootstrap_servers can read it
# through this proxy.
self.config = getattr(producer, "config", None)
def flush(self, timeout=-1):
return self._producer.flush(timeout)
def poll(self, timeout=-1):
return self._producer.poll(timeout)
def purge(self, in_queue=True, in_flight=True, blocking=True):
self._producer.purge(in_queue, in_flight, blocking)
def produce(self, topic, value=None, *args, **kwargs): # pylint: disable=keyword-arg-before-vararg
new_kwargs = kwargs.copy()
new_kwargs["topic"] = topic
new_kwargs["value"] = value
return ConfluentKafkaInstrumentor.wrap_produce(self._producer.produce, self, self._tracer, args, new_kwargs)
def original_producer(self):
return self._producer
class ProxiedConsumer(Consumer):
def __init__(self, consumer: Consumer, tracer: Tracer):
self._consumer = consumer
self._tracer = tracer
self._current_consume_span = None
self._current_context_token = None
# See ProxiedProducer.__init__ for rationale.
self.config = getattr(consumer, "config", None)
def close(self, *args, **kwargs):
return ConfluentKafkaInstrumentor.wrap_close(self._consumer.close, self, args, kwargs)
def committed(self, partitions, timeout=-1):
return self._consumer.committed(partitions, timeout)
def commit(self, *args, **kwargs):
return self._consumer.commit(*args, **kwargs)
def consume(self, *args, **kwargs):
return ConfluentKafkaInstrumentor.wrap_consume(
self._consumer.consume,
self,
self._tracer,
args,
kwargs,
)
def get_watermark_offsets(self, partition, timeout=-1, *args, **kwargs): # pylint: disable=keyword-arg-before-vararg
return self._consumer.get_watermark_offsets(partition, timeout, *args, **kwargs)
def offsets_for_times(self, partitions, timeout=-1):
return self._consumer.offsets_for_times(partitions, timeout)
def poll(self, timeout=-1):
return ConfluentKafkaInstrumentor.wrap_poll(self._consumer.poll, self, self._tracer, [timeout], {})
def subscribe(self, topics, on_assign=lambda *args: None, *args, **kwargs): # pylint: disable=keyword-arg-before-vararg
self._consumer.subscribe(topics, on_assign, *args, **kwargs)
def original_consumer(self):
return self._consumer
class ConfluentKafkaInstrumentor(BaseInstrumentor):
"""An instrumentor for confluent kafka module
See `BaseInstrumentor`
"""
@staticmethod
def instrument_producer(producer: Producer, tracer_provider=None) -> ProxiedProducer:
tracer = trace.get_tracer(
__name__,
__version__,
tracer_provider=tracer_provider,
schema_url="https://opentelemetry.io/schemas/1.11.0",
)
manual_producer = ProxiedProducer(producer, tracer)
return manual_producer
@staticmethod
def instrument_consumer(consumer: Consumer, tracer_provider=None) -> ProxiedConsumer:
tracer = trace.get_tracer(
__name__,
__version__,
tracer_provider=tracer_provider,
schema_url="https://opentelemetry.io/schemas/1.11.0",
)
manual_consumer = ProxiedConsumer(consumer, tracer)
return manual_consumer
@staticmethod
def uninstrument_producer(producer: Producer) -> Producer:
if isinstance(producer, ProxiedProducer):
return producer.original_producer()
return producer
@staticmethod
def uninstrument_consumer(consumer: Consumer) -> Consumer:
if isinstance(consumer, ProxiedConsumer):
return consumer.original_consumer()
return consumer
def instrumentation_dependencies(self) -> Collection[str]:
return _instruments
def _instrument(self, **kwargs):
# TODO: should probably wrap methods directly instead of going through
# these classes. Hopefully it'll make the patching work if called after
# the original classes have already been imported, #4270
self._original_kafka_producer = confluent_kafka.Producer
self._original_kafka_consumer = confluent_kafka.Consumer
confluent_kafka.Producer = AutoInstrumentedProducer
confluent_kafka.Consumer = AutoInstrumentedConsumer
tracer_provider = kwargs.get("tracer_provider")
tracer = trace.get_tracer(
__name__,
__version__,
tracer_provider=tracer_provider,
schema_url="https://opentelemetry.io/schemas/1.11.0",
)
self._tracer = tracer
def _inner_wrap_produce(func, instance, args, kwargs):
return ConfluentKafkaInstrumentor.wrap_produce(func, instance, self._tracer, args, kwargs)
def _inner_wrap_poll(func, instance, args, kwargs):
return ConfluentKafkaInstrumentor.wrap_poll(func, instance, self._tracer, args, kwargs)
def _inner_wrap_consume(func, instance, args, kwargs):
return ConfluentKafkaInstrumentor.wrap_consume(func, instance, self._tracer, args, kwargs)
def _inner_wrap_close(func, instance, args, kwargs):
return ConfluentKafkaInstrumentor.wrap_close(func, instance, args, kwargs)
wrapt.wrap_function_wrapper(
AutoInstrumentedProducer,
"produce",
_inner_wrap_produce,
)
wrapt.wrap_function_wrapper(
AutoInstrumentedConsumer,
"poll",
_inner_wrap_poll,
)
wrapt.wrap_function_wrapper(
AutoInstrumentedConsumer,
"consume",
_inner_wrap_consume,
)
wrapt.wrap_function_wrapper(
AutoInstrumentedConsumer,
"close",
_inner_wrap_close,
)
def _uninstrument(self, **kwargs):
confluent_kafka.Producer = self._original_kafka_producer
confluent_kafka.Consumer = self._original_kafka_consumer
unwrap(AutoInstrumentedProducer, "produce")
unwrap(AutoInstrumentedConsumer, "poll")
@staticmethod
def wrap_produce(func, instance, tracer, args, kwargs):
topic = kwargs.get("topic")
if not topic:
topic = args[0]
span_name = _get_span_name("send", topic)
with tracer.start_as_current_span(name=span_name, kind=trace.SpanKind.PRODUCER) as span:
headers = KafkaPropertiesExtractor.extract_produce_headers(args, kwargs)
if headers is None:
headers = []
kwargs["headers"] = headers
topic = KafkaPropertiesExtractor.extract_produce_topic(args, kwargs)
bootstrap_servers = KafkaPropertiesExtractor.extract_bootstrap_servers(instance)
_enrich_span(
span,
topic,
operation=MessagingOperationTypeValues.PUBLISH,
bootstrap_servers=bootstrap_servers,
) # Publish
propagate.inject(
headers,
setter=_kafka_setter,
)
return func(*args, **kwargs)
@staticmethod
def wrap_poll(func, instance, tracer, args, kwargs):
if instance._current_consume_span:
_end_current_consume_span(instance)
record = func(*args, **kwargs)
if record:
bootstrap_servers = KafkaPropertiesExtractor.extract_bootstrap_servers(instance)
with tracer.start_as_current_span("recv", end_on_exit=True, kind=trace.SpanKind.CONSUMER):
_create_new_consume_span(instance, tracer, [record])
_enrich_span(
instance._current_consume_span,
record.topic(),
record.partition(),
record.offset(),
operation=MessagingOperationTypeValues.PROCESS,
bootstrap_servers=bootstrap_servers,
)
instance._current_context_token = context.attach(trace.set_span_in_context(instance._current_consume_span))
return record
@staticmethod
def wrap_consume(func, instance, tracer, args, kwargs):
if instance._current_consume_span:
_end_current_consume_span(instance)
records = func(*args, **kwargs)
if len(records) > 0:
bootstrap_servers = KafkaPropertiesExtractor.extract_bootstrap_servers(instance)
with tracer.start_as_current_span("recv", end_on_exit=True, kind=trace.SpanKind.CONSUMER):
_create_new_consume_span(instance, tracer, records)
_enrich_span(
instance._current_consume_span,
records[0].topic(),
operation=MessagingOperationTypeValues.PROCESS,
bootstrap_servers=bootstrap_servers,
)
instance._current_context_token = context.attach(trace.set_span_in_context(instance._current_consume_span))
return records
@staticmethod
def wrap_close(func, instance, args, kwargs):
if instance._current_consume_span:
_end_current_consume_span(instance)
func(*args, **kwargs)
package.py 0000664 0000000 0000000 00000000204 15270700723 0050155 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-confluent-kafka/src/opentelemetry/instrumentation/confluent_kafka # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
_instruments = ("confluent-kafka >= 1.8.2, < 3.0.0",)
utils.py 0000664 0000000 0000000 00000013672 15270700723 0047737 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-confluent-kafka/src/opentelemetry/instrumentation/confluent_kafka # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
from logging import getLogger
from opentelemetry import context, propagate
from opentelemetry.propagators import textmap
from opentelemetry.semconv._incubating.attributes.messaging_attributes import (
MESSAGING_MESSAGE_ID,
MESSAGING_OPERATION,
MESSAGING_SYSTEM,
MessagingOperationTypeValues,
)
from opentelemetry.semconv.attributes.server_attributes import (
SERVER_ADDRESS,
SERVER_PORT,
)
from opentelemetry.semconv.trace import (
MessagingDestinationKindValues,
SpanAttributes,
)
from opentelemetry.trace import Link, SpanKind
_LOG = getLogger(__name__)
class KafkaPropertiesExtractor:
@staticmethod
def extract_bootstrap_servers(instance):
config = getattr(instance, "config", None)
if not isinstance(config, dict):
return None
# confluent-kafka uses the dotted key "bootstrap.servers"; also accept
# the python-style "bootstrap_servers" for robustness.
servers = config.get("bootstrap.servers") or config.get("bootstrap_servers")
if isinstance(servers, (list, tuple)):
servers = ",".join(str(s) for s in servers)
return servers
@staticmethod
def _extract_argument(key, position, default_value, args, kwargs):
if len(args) > position:
return args[position]
return kwargs.get(key, default_value)
@staticmethod
def extract_produce_topic(args, kwargs):
"""extract topic from `produce` method arguments in Producer class"""
return kwargs.get("topic") or (args[0] if args else "unknown")
@staticmethod
def extract_produce_headers(args, kwargs):
"""extract headers from `produce` method arguments in Producer class"""
return KafkaPropertiesExtractor._extract_argument("headers", 6, None, args, kwargs)
class KafkaContextGetter(textmap.Getter):
def get(self, carrier: textmap.CarrierT, key: str) -> list[str] | None:
if carrier is None:
return None
carrier_items = carrier
if isinstance(carrier, dict):
carrier_items = carrier.items()
for item_key, value in carrier_items:
if item_key == key:
if value is not None:
return [value.decode()]
return None
def keys(self, carrier: textmap.CarrierT) -> list[str]:
if carrier is None:
return []
carrier_items = carrier
if isinstance(carrier, dict):
carrier_items = carrier.items()
return [key for (key, value) in carrier_items]
class KafkaContextSetter(textmap.Setter):
def set(self, carrier: textmap.CarrierT, key: str, value: str) -> None:
if carrier is None or key is None:
return
if value:
value = value.encode()
if isinstance(carrier, list):
carrier.append((key, value))
if isinstance(carrier, dict):
carrier[key] = value
_kafka_getter = KafkaContextGetter()
def _end_current_consume_span(instance):
if instance._current_context_token:
context.detach(instance._current_context_token)
instance._current_context_token = None
instance._current_consume_span.end()
instance._current_consume_span = None
def _create_new_consume_span(instance, tracer, records):
links = _get_links_from_records(records)
instance._current_consume_span = tracer.start_span(
name=f"{records[0].topic()} process",
links=links,
kind=SpanKind.CONSUMER,
)
def _get_links_from_records(records):
links = []
for record in records:
ctx = propagate.extract(record.headers(), getter=_kafka_getter)
if ctx:
for item in ctx.values():
if hasattr(item, "get_span_context"):
links.append(Link(context=item.get_span_context()))
return links
def _set_bootstrap_servers_attributes(span, bootstrap_servers):
"""Populate server.address and server.port from a bootstrap.servers
string (e.g. ``host1:9092,host2:9092``)."""
if not bootstrap_servers:
return
first_broker = bootstrap_servers.split(",")[0].strip()
if not first_broker:
return
if ":" in first_broker:
host, _, port = first_broker.rpartition(":")
span.set_attribute(SERVER_ADDRESS, host)
try:
span.set_attribute(SERVER_PORT, int(port))
except ValueError:
# Port wasn't numeric; skip rather than emit a bad attribute.
_LOG.debug("non-numeric port in bootstrap.servers: %r", port)
else:
span.set_attribute(SERVER_ADDRESS, first_broker)
def _enrich_span(
span,
topic,
partition: int | None = None,
offset: int | None = None,
operation: MessagingOperationTypeValues | None = None,
bootstrap_servers: str | None = None,
):
if not span.is_recording():
return
span.set_attribute(MESSAGING_SYSTEM, "kafka")
span.set_attribute(SpanAttributes.MESSAGING_DESTINATION, topic)
if partition is not None:
span.set_attribute(SpanAttributes.MESSAGING_KAFKA_PARTITION, partition)
span.set_attribute(
SpanAttributes.MESSAGING_DESTINATION_KIND,
MessagingDestinationKindValues.QUEUE.value,
)
if operation:
span.set_attribute(MESSAGING_OPERATION, operation.value)
else:
span.set_attribute(SpanAttributes.MESSAGING_TEMP_DESTINATION, True)
_set_bootstrap_servers_attributes(span, bootstrap_servers)
# https://stackoverflow.com/questions/65935155/identify-and-find-specific-message-in-kafka-topic
# A message within Kafka is uniquely defined by its topic name, topic partition and offset.
if partition is not None and offset is not None and topic:
span.set_attribute(
MESSAGING_MESSAGE_ID,
f"{topic}.{partition}.{offset}",
)
_kafka_setter = KafkaContextSetter()
def _get_span_name(operation: str, topic: str):
return f"{topic} {operation}"
version.py 0000664 0000000 0000000 00000000144 15270700723 0050252 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-confluent-kafka/src/opentelemetry/instrumentation/confluent_kafka # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
__version__ = "0.66b2"
test-requirements.txt 0000664 0000000 0000000 00000000455 15270700723 0040401 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-confluent-kafka asgiref==3.8.1
confluent-kafka==2.13.2
Deprecated==1.2.14
iniconfig==2.0.0
packaging==24.0
pluggy==1.6.0
py-cpuinfo==9.0.0
pytest==7.4.4
tomli==2.0.1
typing_extensions==4.12.2
wrapt==1.16.0
zipp==3.19.2
-e opentelemetry-instrumentation
-e instrumentation/opentelemetry-instrumentation-confluent-kafka
tests/ 0000775 0000000 0000000 00000000000 15270700723 0035276 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-confluent-kafka __init__.py 0000664 0000000 0000000 00000000000 15270700723 0037375 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-confluent-kafka/tests test_instrumentation.py 0000664 0000000 0000000 00000042531 15270700723 0042157 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-confluent-kafka/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
# pylint: disable=no-name-in-module,import-outside-toplevel
from opentelemetry.instrumentation.confluent_kafka import (
AutoInstrumentedConsumer,
AutoInstrumentedProducer,
ConfluentKafkaInstrumentor,
ProxiedConsumer,
ProxiedProducer,
)
from opentelemetry.instrumentation.confluent_kafka.utils import (
KafkaContextGetter,
KafkaContextSetter,
)
from opentelemetry.semconv._incubating.attributes.messaging_attributes import (
MESSAGING_MESSAGE_ID,
MESSAGING_OPERATION,
MESSAGING_SYSTEM,
)
from opentelemetry.semconv.attributes.server_attributes import (
SERVER_ADDRESS,
SERVER_PORT,
)
from opentelemetry.semconv.trace import (
MessagingDestinationKindValues,
SpanAttributes,
)
from opentelemetry.test.test_base import TestBase
from .utils import MockConsumer, MockedMessage, MockedProducer
class TestConfluentKafka(TestBase):
def test_instrument_api(self) -> None:
from confluent_kafka import Consumer, Producer # noqa: PLC0415
instrumentation = ConfluentKafkaInstrumentor()
producer = Producer({"bootstrap.servers": "localhost:29092"})
producer = instrumentation.instrument_producer(producer)
self.assertEqual(producer.__class__, ProxiedProducer)
producer = instrumentation.uninstrument_producer(producer)
self.assertEqual(producer.__class__, Producer)
consumer = Consumer(
{
"bootstrap.servers": "localhost:29092",
"group.id": "mygroup",
"auto.offset.reset": "earliest",
}
)
consumer = instrumentation.instrument_consumer(consumer)
self.assertEqual(consumer.__class__, ProxiedConsumer)
consumer = instrumentation.uninstrument_consumer(consumer)
self.assertEqual(consumer.__class__, Consumer)
consumer = Consumer(
**{
"bootstrap.servers": "localhost:29092",
"group.id": "mygroup",
"auto.offset.reset": "earliest",
}
)
consumer = instrumentation.instrument_consumer(consumer)
self.assertEqual(consumer.__class__, ProxiedConsumer)
consumer = instrumentation.uninstrument_consumer(consumer)
self.assertEqual(consumer.__class__, Consumer)
def test_instrument_api_with_instrument(self) -> None:
ConfluentKafkaInstrumentor().instrument()
from confluent_kafka import Consumer, Producer # noqa: PLC0415
producer = Producer({"bootstrap.servers": "localhost:29092"})
self.assertEqual(producer.__class__, AutoInstrumentedProducer)
consumer = Consumer(
{
"bootstrap.servers": "localhost:29092",
"group.id": "mygroup",
"auto.offset.reset": "earliest",
}
)
self.assertEqual(consumer.__class__, AutoInstrumentedConsumer)
consumer = Consumer(
**{
"bootstrap.servers": "localhost:29092",
"group.id": "mygroup",
"auto.offset.reset": "earliest",
}
)
self.assertEqual(consumer.__class__, AutoInstrumentedConsumer)
ConfluentKafkaInstrumentor().uninstrument()
def test_consumer_commit_method_exists(self) -> None:
from confluent_kafka import Consumer # noqa: PLC0415
instrumentation = ConfluentKafkaInstrumentor()
consumer = Consumer(
{
"bootstrap.servers": "localhost:29092",
"group.id": "mygroup",
"auto.offset.reset": "earliest",
}
)
consumer = instrumentation.instrument_consumer(consumer)
self.assertEqual(consumer.__class__, ProxiedConsumer)
self.assertTrue(hasattr(consumer, "commit"))
def test_context_setter(self) -> None:
context_setter = KafkaContextSetter()
carrier_dict = {"key1": "val1"}
context_setter.set(carrier_dict, "key2", "val2")
self.assertGreaterEqual(carrier_dict.items(), {"key2": b"val2"}.items())
carrier_list = [("key1", "val1")]
context_setter.set(carrier_list, "key2", "val2")
self.assertTrue(("key2", b"val2") in carrier_list)
def test_context_getter(self) -> None:
context_setter = KafkaContextSetter()
context_getter = KafkaContextGetter()
carrier_dict = {}
context_setter.set(carrier_dict, "key1", "val1")
self.assertEqual(context_getter.get(carrier_dict, "key1"), ["val1"])
self.assertEqual(["key1"], context_getter.keys(carrier_dict))
carrier_list = []
context_setter.set(carrier_list, "key1", "val1")
self.assertEqual(context_getter.get(carrier_list, "key1"), ["val1"])
self.assertEqual(["key1"], context_getter.keys(carrier_list))
def test_poll(self) -> None:
instrumentation = ConfluentKafkaInstrumentor()
mocked_messages = [
MockedMessage("topic-10", 0, 0, []),
MockedMessage("topic-20", 2, 4, []),
MockedMessage("topic-30", 1, 3, []),
]
expected_spans = [
{"name": "recv", "attributes": {}},
{
"name": "topic-10 process",
"attributes": {
MESSAGING_OPERATION: "process",
SpanAttributes.MESSAGING_KAFKA_PARTITION: 0,
MESSAGING_SYSTEM: "kafka",
SpanAttributes.MESSAGING_DESTINATION: "topic-10",
SpanAttributes.MESSAGING_DESTINATION_KIND: MessagingDestinationKindValues.QUEUE.value,
MESSAGING_MESSAGE_ID: "topic-10.0.0",
},
},
{"name": "recv", "attributes": {}},
{
"name": "topic-20 process",
"attributes": {
MESSAGING_OPERATION: "process",
SpanAttributes.MESSAGING_KAFKA_PARTITION: 2,
MESSAGING_SYSTEM: "kafka",
SpanAttributes.MESSAGING_DESTINATION: "topic-20",
SpanAttributes.MESSAGING_DESTINATION_KIND: MessagingDestinationKindValues.QUEUE.value,
MESSAGING_MESSAGE_ID: "topic-20.2.4",
},
},
{"name": "recv", "attributes": {}},
{
"name": "topic-30 process",
"attributes": {
MESSAGING_OPERATION: "process",
SpanAttributes.MESSAGING_KAFKA_PARTITION: 1,
MESSAGING_SYSTEM: "kafka",
SpanAttributes.MESSAGING_DESTINATION: "topic-30",
SpanAttributes.MESSAGING_DESTINATION_KIND: MessagingDestinationKindValues.QUEUE.value,
MESSAGING_MESSAGE_ID: "topic-30.1.3",
},
},
]
consumer = MockConsumer(
mocked_messages,
{
"bootstrap.servers": "localhost:29092",
"group.id": "mygroup",
"auto.offset.reset": "earliest",
},
)
self.memory_exporter.clear()
consumer = instrumentation.instrument_consumer(consumer)
consumer.poll()
consumer.poll()
consumer.poll()
consumer.poll() # empty poll — must not produce a span
span_list = self.memory_exporter.get_finished_spans()
self._compare_spans(span_list, expected_spans)
def test_consume(self) -> None:
instrumentation = ConfluentKafkaInstrumentor()
mocked_messages = [
MockedMessage("topic-1", 0, 0, []),
MockedMessage("topic-1", 2, 1, []),
MockedMessage("topic-1", 3, 2, []),
MockedMessage("topic-2", 0, 0, []),
MockedMessage("topic-3", 0, 3, []),
MockedMessage("topic-2", 0, 1, []),
]
expected_spans = [
{"name": "recv", "attributes": {}},
{
"name": "topic-1 process",
"attributes": {
MESSAGING_OPERATION: "process",
MESSAGING_SYSTEM: "kafka",
SpanAttributes.MESSAGING_DESTINATION: "topic-1",
SpanAttributes.MESSAGING_DESTINATION_KIND: MessagingDestinationKindValues.QUEUE.value,
},
},
{"name": "recv", "attributes": {}},
{
"name": "topic-2 process",
"attributes": {
MESSAGING_OPERATION: "process",
MESSAGING_SYSTEM: "kafka",
SpanAttributes.MESSAGING_DESTINATION: "topic-2",
SpanAttributes.MESSAGING_DESTINATION_KIND: MessagingDestinationKindValues.QUEUE.value,
},
},
{"name": "recv", "attributes": {}},
{
"name": "topic-3 process",
"attributes": {
MESSAGING_OPERATION: "process",
MESSAGING_SYSTEM: "kafka",
SpanAttributes.MESSAGING_DESTINATION: "topic-3",
SpanAttributes.MESSAGING_DESTINATION_KIND: MessagingDestinationKindValues.QUEUE.value,
},
},
]
consumer = MockConsumer(
mocked_messages,
{
"bootstrap.servers": "localhost:29092",
"group.id": "mygroup",
"auto.offset.reset": "earliest",
},
)
self.memory_exporter.clear()
consumer = instrumentation.instrument_consumer(consumer)
consumer.consume(3)
consumer.consume(1)
consumer.consume(2)
consumer.consume(1) # empty consume — must not produce a span
span_list = self.memory_exporter.get_finished_spans()
self._compare_spans(span_list, expected_spans)
def test_poll_empty_does_not_create_span(self) -> None:
instrumentation = ConfluentKafkaInstrumentor()
consumer = MockConsumer(
[],
{
"bootstrap.servers": "localhost:29092",
"group.id": "mygroup",
"auto.offset.reset": "earliest",
},
)
self.memory_exporter.clear()
consumer = instrumentation.instrument_consumer(consumer)
consumer.poll()
consumer.poll()
span_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(span_list), 0)
def test_consume_empty_does_not_create_span(self) -> None:
instrumentation = ConfluentKafkaInstrumentor()
consumer = MockConsumer(
[],
{
"bootstrap.servers": "localhost:29092",
"group.id": "mygroup",
"auto.offset.reset": "earliest",
},
)
self.memory_exporter.clear()
consumer = instrumentation.instrument_consumer(consumer)
consumer.consume(5)
consumer.consume(5)
span_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(span_list), 0)
def test_poll_empty_cleans_up_previous_span_and_token(self) -> None:
instrumentation = ConfluentKafkaInstrumentor()
consumer = MockConsumer(
[MockedMessage("topic-1", 0, 0, [])],
{
"bootstrap.servers": "localhost:29092",
"group.id": "mygroup",
"auto.offset.reset": "earliest",
},
)
consumer = instrumentation.instrument_consumer(consumer)
consumer.poll() # non-empty: sets _current_consume_span and _current_context_token
self.assertIsNotNone(consumer._current_consume_span)
self.assertIsNotNone(consumer._current_context_token)
consumer.poll() # empty: should clean up both
self.assertIsNone(consumer._current_consume_span)
self.assertIsNone(consumer._current_context_token)
def test_consume_empty_cleans_up_previous_span_and_token(self) -> None:
instrumentation = ConfluentKafkaInstrumentor()
consumer = MockConsumer(
[MockedMessage("topic-1", 0, 0, [])],
{
"bootstrap.servers": "localhost:29092",
"group.id": "mygroup",
"auto.offset.reset": "earliest",
},
)
consumer = instrumentation.instrument_consumer(consumer)
consumer.consume(1) # non-empty: sets _current_consume_span and _current_context_token
self.assertIsNotNone(consumer._current_consume_span)
self.assertIsNotNone(consumer._current_context_token)
consumer.consume(1) # empty: should clean up both
self.assertIsNone(consumer._current_consume_span)
self.assertIsNone(consumer._current_context_token)
def test_close(self) -> None:
instrumentation = ConfluentKafkaInstrumentor()
mocked_messages = [
MockedMessage("topic-a", 0, 0, []),
]
expected_spans = [
{"name": "recv", "attributes": {}},
{
"name": "topic-a process",
"attributes": {
MESSAGING_OPERATION: "process",
SpanAttributes.MESSAGING_KAFKA_PARTITION: 0,
MESSAGING_SYSTEM: "kafka",
SpanAttributes.MESSAGING_DESTINATION: "topic-a",
SpanAttributes.MESSAGING_DESTINATION_KIND: MessagingDestinationKindValues.QUEUE.value,
MESSAGING_MESSAGE_ID: "topic-a.0.0",
},
},
]
consumer = MockConsumer(
mocked_messages,
{
"bootstrap.servers": "localhost:29092",
"group.id": "mygroup",
"auto.offset.reset": "earliest",
},
)
self.memory_exporter.clear()
consumer = instrumentation.instrument_consumer(consumer)
consumer.poll()
consumer.close()
span_list = self.memory_exporter.get_finished_spans()
self._compare_spans(span_list, expected_spans)
def _compare_spans(self, spans, expected_spans):
self.assertEqual(len(spans), len(expected_spans))
for span, expected_span in zip(spans, expected_spans):
self.assertEqual(expected_span["name"], span.name)
for attribute_key, expected_attribute_value in expected_span["attributes"].items():
self.assertEqual(expected_attribute_value, span.attributes[attribute_key])
def _assert_topic(self, span, expected_topic: str) -> None:
self.assertEqual(
span.attributes[SpanAttributes.MESSAGING_DESTINATION],
expected_topic,
)
def _assert_span_count(self, span_list, expected_count: int) -> None:
self.assertEqual(len(span_list), expected_count)
def test_producer_poll(self) -> None:
instrumentation = ConfluentKafkaInstrumentor()
message_queue = []
producer = MockedProducer(
message_queue,
{
"bootstrap.servers": "localhost:29092",
},
)
producer = instrumentation.instrument_producer(producer)
producer.produce(topic="topic-1", key="key-1", value="value-1")
msg = producer.poll()
self.assertIsNotNone(msg)
span_list = self.memory_exporter.get_finished_spans()
self._assert_span_count(span_list, 1)
self._assert_topic(span_list[0], "topic-1")
def test_producer_flush(self) -> None:
instrumentation = ConfluentKafkaInstrumentor()
message_queue = []
producer = MockedProducer(
message_queue,
{
"bootstrap.servers": "localhost:29092",
},
)
producer = instrumentation.instrument_producer(producer)
producer.produce(topic="topic-1", key="key-1", value="value-1")
msg = producer.flush()
self.assertIsNotNone(msg)
span_list = self.memory_exporter.get_finished_spans()
self._assert_span_count(span_list, 1)
self._assert_topic(span_list[0], "topic-1")
def test_producer_sets_bootstrap_servers_attributes(self) -> None:
instrumentation = ConfluentKafkaInstrumentor()
producer = MockedProducer(
[],
{
"bootstrap.servers": "broker-a:9092,broker-b:9093",
},
)
producer = instrumentation.instrument_producer(producer)
producer.produce(topic="topic-1", key="k", value="v")
span = self.memory_exporter.get_finished_spans()[0]
self.assertEqual(span.attributes[SERVER_ADDRESS], "broker-a")
self.assertEqual(span.attributes[SERVER_PORT], 9092)
def test_consumer_sets_bootstrap_servers_attributes(self) -> None:
instrumentation = ConfluentKafkaInstrumentor()
consumer = MockConsumer(
[MockedMessage("topic-1", 0, 0, [])],
{
"bootstrap.servers": "broker-1:9092",
"group.id": "g",
"auto.offset.reset": "earliest",
},
)
self.memory_exporter.clear()
consumer = instrumentation.instrument_consumer(consumer)
consumer.poll()
# Second (empty) poll ends the in-flight ` process` span so it
# shows up in the exporter.
consumer.poll()
process_span = next(s for s in self.memory_exporter.get_finished_spans() if s.name == "topic-1 process")
self.assertEqual(process_span.attributes[SERVER_ADDRESS], "broker-1")
self.assertEqual(process_span.attributes[SERVER_PORT], 9092)
utils.py 0000664 0000000 0000000 00000003722 15270700723 0037014 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-confluent-kafka/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
from confluent_kafka import Consumer, Producer
class MockConsumer(Consumer):
def __init__(self, queue, config):
self._queue = queue
self.config = config
super().__init__(config)
def consume(self, num_messages=1, *args, **kwargs): # pylint: disable=keyword-arg-before-vararg
messages = self._queue[:num_messages]
self._queue = self._queue[num_messages:]
return messages
def poll(self, timeout=None):
if len(self._queue) > 0:
return self._queue.pop(0)
return None
class MockedMessage:
def __init__(
self,
topic: str,
partition: int,
offset: int,
headers,
key: str | None = None,
value: str | None = None,
):
self._topic = topic
self._partition = partition
self._offset = offset
self._headers = headers
self._key = key
self._value = value
def topic(self):
return self._topic
def partition(self):
return self._partition
def offset(self):
return self._offset
def headers(self):
return self._headers
def key(self):
return self._key
def value(self):
return self._value
class MockedProducer(Producer):
def __init__(self, queue, config):
self._queue = queue
self.config = config
super().__init__(config)
def produce(self, *args, **kwargs): # pylint: disable=keyword-arg-before-vararg
self._queue.append(
MockedMessage(
topic=kwargs.get("topic"),
partition=0,
offset=0,
headers=[],
key=kwargs.get("key"),
value=kwargs.get("value"),
)
)
def poll(self, *args, **kwargs):
return len(self._queue)
def flush(self, *args, **kwargs):
return len(self._queue)
opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-dbapi/ 0000775 0000000 0000000 00000000000 15270700723 0032222 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-dbapi/LICENSE 0000664 0000000 0000000 00000026135 15270700723 0033236 0 ustar 00root root 0000000 0000000 Apache License
Version 2.0, January 2004
http://www.apache.org/licenses/
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opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-dbapi/README.rst 0000664 0000000 0000000 00000001245 15270700723 0033713 0 ustar 00root root 0000000 0000000 OpenTelemetry Database API instrumentation
==========================================
|pypi|
.. |pypi| image:: https://badge.fury.io/py/opentelemetry-instrumentation-dbapi.svg
:target: https://pypi.org/project/opentelemetry-instrumentation-dbapi/
Installation
------------
::
pip install opentelemetry-instrumentation-dbapi
References
----------
* `OpenTelemetry Database API Instrumentation `_
* `OpenTelemetry Project `_
* `OpenTelemetry Python Examples `_
pyproject.toml 0000664 0000000 0000000 00000002747 15270700723 0035071 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-dbapi [build-system]
requires = ["hatchling"]
build-backend = "hatchling.build"
[project]
name = "opentelemetry-instrumentation-dbapi"
dynamic = ["version"]
description = "OpenTelemetry Database API instrumentation"
readme = "README.rst"
license = "Apache-2.0"
requires-python = ">=3.10"
authors = [
{ name = "OpenTelemetry Authors", email = "cncf-opentelemetry-contributors@lists.cncf.io" },
]
classifiers = [
"Development Status :: 4 - Beta",
"Intended Audience :: Developers",
"License :: OSI Approved :: Apache Software License",
"Programming Language :: Python",
"Programming Language :: Python :: 3",
"Programming Language :: Python :: 3.10",
"Programming Language :: Python :: 3.11",
"Programming Language :: Python :: 3.12",
"Programming Language :: Python :: 3.13",
"Programming Language :: Python :: 3.14",
]
dependencies = [
"opentelemetry-api ~= 1.12",
"opentelemetry-instrumentation == 0.66b2",
"opentelemetry-semantic-conventions == 0.66b2",
"wrapt >= 1.0.0, < 3.0.0",
]
[project.optional-dependencies]
instruments = []
[project.urls]
Homepage = "https://github.com/open-telemetry/opentelemetry-python-contrib/tree/main/instrumentation/opentelemetry-instrumentation-dbapi"
Repository = "https://github.com/open-telemetry/opentelemetry-python-contrib"
[tool.hatch.version]
path = "src/opentelemetry/instrumentation/dbapi/version.py"
[tool.hatch.build.targets.sdist]
include = [
"/src",
"/tests",
]
[tool.hatch.build.targets.wheel]
packages = ["src/opentelemetry"]
opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-dbapi/src/ 0000775 0000000 0000000 00000000000 15270700723 0033011 5 ustar 00root root 0000000 0000000 opentelemetry/ 0000775 0000000 0000000 00000000000 15270700723 0035626 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-dbapi/src instrumentation/ 0000775 0000000 0000000 00000000000 15270700723 0041071 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-dbapi/src/opentelemetry dbapi/ 0000775 0000000 0000000 00000000000 15270700723 0042150 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-dbapi/src/opentelemetry/instrumentation __init__.py 0000664 0000000 0000000 00000115703 15270700723 0044270 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-dbapi/src/opentelemetry/instrumentation/dbapi # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
# pylint: disable=too-many-lines
"""
The trace integration with Database API supports libraries that follow the
Python Database API Specification v2.0.
``_
Usage
-----
The DB-API instrumentor and its utilities provide common, core functionality for
database framework or object relation mapper (ORM) instrumentations. Users will
typically instrument database client code with those framework/ORM-specific
instrumentations, instead of directly using this DB-API integration. Features
such as sqlcommenter can be configured at framework/ORM level as well. See full
list at `instrumentation`_.
.. _instrumentation: https://github.com/open-telemetry/opentelemetry-python-contrib/tree/main/instrumentation
If an instrumentation for your needs does not exist, then DB-API integration can
be used directly as follows.
.. code-block:: python
import mysql.connector
import pyodbc
from opentelemetry.instrumentation.dbapi import (
trace_integration,
wrap_connect,
)
# Example: mysql.connector
trace_integration(mysql.connector, "connect", "mysql")
# Example: pyodbc
trace_integration(pyodbc, "connect", "odbc")
# Or, directly call wrap_connect for more configurability.
wrap_connect(__name__, mysql.connector, "connect", "mysql")
wrap_connect(__name__, pyodbc, "connect", "odbc")
Configuration
-------------
SQLCommenter
************
You can optionally enable sqlcommenter which enriches the query with contextual
information. Queries made after setting up trace integration with sqlcommenter
enabled will have configurable key-value pairs appended to them, e.g.
``"select * from auth_users; /*traceparent=00-01234567-abcd-01*/"``. This
supports context propagation between database client and server when database log
records are enabled. For more information, see:
* `Semantic Conventions - Database Spans `_
* `sqlcommenter `_
.. code:: python
import mysql.connector
from opentelemetry.instrumentation.dbapi import wrap_connect
# Opts into sqlcomment for MySQL trace integration.
wrap_connect(
__name__,
mysql.connector,
"connect",
"mysql",
enable_commenter=True,
)
SQLCommenter with commenter_options
***********************************
The key-value pairs appended to the query can be configured using
``commenter_options``. When sqlcommenter is enabled, all available KVs/tags
are calculated by default. ``commenter_options`` supports *opting out*
of specific KVs.
.. code:: python
import mysql.connector
from opentelemetry.instrumentation.dbapi import wrap_connect
# Opts into sqlcomment for MySQL trace integration.
# Opts out of tags for libpq_version, db_driver.
wrap_connect(
__name__,
mysql.connector,
"connect",
"mysql",
enable_commenter=True,
commenter_options={
"libpq_version": False,
"db_driver": False,
}
)
Available commenter_options
###########################
The following sqlcomment key-values can be opted out of through ``commenter_options``:
+---------------------------+-----------------------------------------------------------+---------------------------------------------------------------------------+
| Commenter Option | Description | Example |
+===========================+===========================================================+===========================================================================+
| ``db_driver`` | Database driver name with version. | ``mysql.connector=2.2.9`` |
+---------------------------+-----------------------------------------------------------+---------------------------------------------------------------------------+
| ``dbapi_threadsafety`` | DB-API threadsafety value: 0-3 or unknown. | ``dbapi_threadsafety=2`` |
+---------------------------+-----------------------------------------------------------+---------------------------------------------------------------------------+
| ``dbapi_level`` | DB-API API level: 1.0, 2.0, or unknown. | ``dbapi_level=2.0`` |
+---------------------------+-----------------------------------------------------------+---------------------------------------------------------------------------+
| ``driver_paramstyle`` | DB-API paramstyle for SQL statement parameter. | ``driver_paramstyle='pyformat'`` |
+---------------------------+-----------------------------------------------------------+---------------------------------------------------------------------------+
| ``libpq_version`` | PostgreSQL libpq version (checked for PostgreSQL only). | ``libpq_version=140001`` |
+---------------------------+-----------------------------------------------------------+---------------------------------------------------------------------------+
| ``mysql_client_version`` | MySQL client version (checked for MySQL only). | ``mysql_client_version='123'`` |
+---------------------------+-----------------------------------------------------------+---------------------------------------------------------------------------+
| ``opentelemetry_values`` | OpenTelemetry context as traceparent at time of query. | ``traceparent='00-03afa25236b8cd948fa853d67038ac79-405ff022e8247c46-01'`` |
+---------------------------+-----------------------------------------------------------+---------------------------------------------------------------------------+
SQLComment in span attribute
****************************
If sqlcommenter is enabled, you can opt into the inclusion of sqlcomment in
the query span ``db.statement`` and/or ``db.query.text`` attribute for your
needs. If ``commenter_options`` have been set, the span attribute comment
will also be configured by this setting.
.. code:: python
import mysql.connector
from opentelemetry.instrumentation.dbapi import wrap_connect
# Opts into sqlcomment for MySQL trace integration.
# Opts into sqlcomment for `db.statement` and/or `db.query.text` span attribute.
wrap_connect(
__name__,
mysql.connector,
"connect",
"mysql",
enable_commenter=True,
enable_attribute_commenter=True,
)
API
---
"""
from __future__ import annotations
import functools
import logging
import re
import sys
import time
from collections.abc import Awaitable, Callable, Sequence
from typing import TYPE_CHECKING, Any, Generic, TypeVar
from wrapt import wrap_function_wrapper
try:
# wrapt 2.0.0+
from wrapt import ( # pylint: disable=no-name-in-module
BaseObjectProxy,
ObjectProxy,
)
except ImportError:
from wrapt import ObjectProxy
from wrapt import ObjectProxy as BaseObjectProxy
from opentelemetry import trace as trace_api
from opentelemetry.instrumentation._semconv import (
_get_schema_url_for_signal_types,
_OpenTelemetrySemanticConventionStability,
_OpenTelemetryStabilitySignalType,
_report_new,
_set_db_name,
_set_db_statement,
_set_db_system,
_set_db_user,
_set_http_net_peer_name_client,
_set_http_peer_port_client,
)
from opentelemetry.instrumentation.dbapi.version import __version__
from opentelemetry.instrumentation.sqlcommenter_utils import _add_sql_comment
from opentelemetry.instrumentation.utils import (
_get_opentelemetry_values,
is_instrumentation_enabled,
unwrap,
)
from opentelemetry.metrics import MeterProvider, get_meter
from opentelemetry.semconv._incubating.metrics.db_metrics import (
create_db_client_operation_duration,
create_db_client_response_returned_rows,
)
from opentelemetry.semconv.attributes.db_attributes import (
DB_NAMESPACE,
DB_OPERATION_NAME,
DB_SYSTEM_NAME,
)
from opentelemetry.semconv.attributes.error_attributes import ERROR_TYPE
from opentelemetry.semconv.attributes.server_attributes import (
SERVER_ADDRESS,
SERVER_PORT,
)
from opentelemetry.trace import SpanKind, TracerProvider, get_tracer
from opentelemetry.util._importlib_metadata import version as util_version
if sys.version_info >= (3, 14):
from string.templatelib import Template as _Template
else:
_Template = ()
if TYPE_CHECKING:
if sys.version_info >= (3, 14):
from string.templatelib import Template
else:
from typing import Never
Template = Never
_DB_DRIVER_ALIASES = {
"MySQLdb": "mysqlclient",
}
_logger = logging.getLogger(__name__)
ConnectionT = TypeVar("ConnectionT")
CursorT = TypeVar("CursorT")
def trace_integration(
connect_module: Callable[..., Any],
connect_method_name: str,
database_system: str,
connection_attributes: dict[str, Any] | None = None,
tracer_provider: TracerProvider | None = None,
capture_parameters: bool = False,
enable_commenter: bool = False,
db_api_integration_factory: type[DatabaseApiIntegration] | None = None,
enable_attribute_commenter: bool = False,
commenter_options: dict[str, Any] | None = None,
meter_provider: MeterProvider | None = None,
):
"""Integrate with DB API library.
https://www.python.org/dev/peps/pep-0249/
Args:
connect_module: Module name where connect method is available.
connect_method_name: The connect method name.
database_system: An identifier for the database management system (DBMS)
product being used.
connection_attributes: Attribute names for database, port, host and
user in Connection object.
tracer_provider: The :class:`opentelemetry.trace.TracerProvider` to
use. If omitted the current configured one is used.
capture_parameters: Configure if db.statement.parameters should be captured.
enable_commenter: Flag to enable/disable sqlcommenter.
db_api_integration_factory: The `DatabaseApiIntegration` to use. If none is passed the
default one is used.
enable_attribute_commenter: Flag to enable/disable sqlcomment inclusion in `db.statement` and/or `db.query.text` span attribute. Only available if enable_commenter=True.
commenter_options: Configurations for tags to be appended at the sql query.
meter_provider: The :class:`opentelemetry.metrics.MeterProvider` to
use. If omitted the current configured one is used.
"""
wrap_connect(
__name__,
connect_module,
connect_method_name,
database_system,
connection_attributes,
version=__version__,
tracer_provider=tracer_provider,
capture_parameters=capture_parameters,
enable_commenter=enable_commenter,
db_api_integration_factory=db_api_integration_factory,
enable_attribute_commenter=enable_attribute_commenter,
commenter_options=commenter_options,
meter_provider=meter_provider,
)
# pylint: disable-next=too-many-positional-arguments
def wrap_connect(
name: str,
connect_module: Callable[..., Any],
connect_method_name: str,
database_system: str,
connection_attributes: dict[str, Any] | None = None,
version: str = "",
tracer_provider: TracerProvider | None = None,
capture_parameters: bool = False,
enable_commenter: bool = False,
db_api_integration_factory: type[DatabaseApiIntegration] | None = None,
commenter_options: dict[str, Any] | None = None,
enable_attribute_commenter: bool = False,
meter_provider: MeterProvider | None = None,
):
"""Integrate with DB API library.
https://www.python.org/dev/peps/pep-0249/
Args:
connect_module: Module name where connect method is available.
connect_method_name: The connect method name.
database_system: An identifier for the database management system (DBMS)
product being used.
connection_attributes: Attribute names for database, port, host and
user in Connection object.
tracer_provider: The :class:`opentelemetry.trace.TracerProvider` to
use. If omitted the current configured one is used.
capture_parameters: Configure if db.statement.parameters should be captured.
enable_commenter: Flag to enable/disable sqlcommenter.
db_api_integration_factory: The `DatabaseApiIntegration` to use. If none is passed the
default one is used.
commenter_options: Configurations for tags to be appended at the sql query.
enable_attribute_commenter: Flag to enable/disable sqlcomment inclusion in `db.statement` and/or `db.query.text` span attribute. Only available if enable_commenter=True.
meter_provider: The :class:`opentelemetry.metrics.MeterProvider` to
use. If omitted the current configured one is used.
"""
db_api_integration_factory = db_api_integration_factory or DatabaseApiIntegration
# pylint: disable=unused-argument
def wrap_connect_(
wrapped: Callable[..., Any],
instance: Any,
args: tuple[Any, Any],
kwargs: dict[Any, Any],
):
db_integration = db_api_integration_factory(
name,
database_system,
connection_attributes=connection_attributes,
version=version,
tracer_provider=tracer_provider,
capture_parameters=capture_parameters,
enable_commenter=enable_commenter,
commenter_options=commenter_options,
connect_module=connect_module,
enable_attribute_commenter=enable_attribute_commenter,
meter_provider=meter_provider,
)
return db_integration.wrapped_connection(wrapped, args, kwargs)
try:
wrap_function_wrapper(connect_module, connect_method_name, wrap_connect_)
except Exception as ex: # pylint: disable=broad-except
_logger.warning("Failed to integrate with DB API. %s", str(ex))
def unwrap_connect(connect_module: Callable[..., Any], connect_method_name: str):
"""Disable integration with DB API library.
https://www.python.org/dev/peps/pep-0249/
Args:
connect_module: Module name where the connect method is available.
connect_method_name: The connect method name.
"""
unwrap(connect_module, connect_method_name)
# pylint: disable-next=too-many-positional-arguments
def instrument_connection(
name: str,
connection: ConnectionT | TracedConnectionProxy[ConnectionT],
database_system: str,
connection_attributes: dict[str, Any] | None = None,
version: str = "",
tracer_provider: TracerProvider | None = None,
capture_parameters: bool = False,
enable_commenter: bool = False,
commenter_options: dict[str, Any] | None = None,
connect_module: Callable[..., Any] | None = None,
enable_attribute_commenter: bool = False,
db_api_integration_factory: type[DatabaseApiIntegration] | None = None,
meter_provider: MeterProvider | None = None,
) -> TracedConnectionProxy[ConnectionT]:
"""Enable instrumentation in a database connection.
Args:
name: The instrumentation module name.
connection: The connection to instrument.
database_system: An identifier for the database management system (DBMS)
product being used.
connection_attributes: Attribute names for database, port, host and
user in a connection object.
tracer_provider: The :class:`opentelemetry.trace.TracerProvider` to
use. If omitted the current configured one is used.
capture_parameters: Configure if db.statement.parameters should be captured.
enable_commenter: Flag to enable/disable sqlcommenter.
commenter_options: Configurations for tags to be appended at the sql query.
connect_module: Module name where connect method is available.
enable_attribute_commenter: Flag to enable/disable sqlcomment inclusion in `db.statement` and/or `db.query.text` span attribute. Only available if enable_commenter=True.
db_api_integration_factory: A class or factory function to use as a
replacement for :class:`DatabaseApiIntegration`. Can be used to
obtain connection attributes from the connect method instead of
from the connection itself (as done by the pymssql intrumentor).
meter_provider: The :class:`opentelemetry.metrics.MeterProvider` to
use. If omitted the current configured one is used.
Returns:
An instrumented connection.
"""
if isinstance(connection, BaseObjectProxy):
_logger.warning("Connection already instrumented")
return connection
db_api_integration_factory = db_api_integration_factory or DatabaseApiIntegration
db_integration = db_api_integration_factory(
name,
database_system,
connection_attributes=connection_attributes,
version=version,
tracer_provider=tracer_provider,
capture_parameters=capture_parameters,
enable_commenter=enable_commenter,
commenter_options=commenter_options,
connect_module=connect_module,
enable_attribute_commenter=enable_attribute_commenter,
meter_provider=meter_provider,
)
db_integration.get_connection_attributes(connection)
return get_traced_connection_proxy(connection, db_integration)
def uninstrument_connection(
connection: ConnectionT | TracedConnectionProxy[ConnectionT],
) -> ConnectionT:
"""Disable instrumentation in a database connection.
Args:
connection: The connection to uninstrument.
Returns:
An uninstrumented connection.
"""
if isinstance(connection, BaseObjectProxy):
return connection.__wrapped__
_logger.warning("Connection is not instrumented")
return connection
class DatabaseApiIntegration:
def __init__(
self,
name: str,
database_system: str,
connection_attributes: dict[str, Any] | None = None,
version: str = "",
tracer_provider: TracerProvider | None = None,
capture_parameters: bool = False,
enable_commenter: bool = False,
commenter_options: dict[str, Any] | None = None,
connect_module: Callable[..., Any] | None = None,
enable_attribute_commenter: bool = False,
meter_provider: MeterProvider | None = None,
):
# Initialize semantic conventions opt-in if needed
_OpenTelemetrySemanticConventionStability._initialize()
self._sem_conv_opt_in_mode_db = (
_OpenTelemetrySemanticConventionStability._get_opentelemetry_stability_opt_in_mode(
_OpenTelemetryStabilitySignalType.DATABASE,
)
)
self._sem_conv_opt_in_mode_http = (
_OpenTelemetrySemanticConventionStability._get_opentelemetry_stability_opt_in_mode(
_OpenTelemetryStabilitySignalType.HTTP,
)
)
if connection_attributes is None:
self.connection_attributes = {
"database": "database",
"port": "port",
"host": "host",
"user": "user",
}
else:
self.connection_attributes = connection_attributes
self._name = name
self._version = version
self._tracer = get_tracer(
self._name,
instrumenting_library_version=self._version,
tracer_provider=tracer_provider,
schema_url=_get_schema_url_for_signal_types(
[
_OpenTelemetryStabilitySignalType.DATABASE,
_OpenTelemetryStabilitySignalType.HTTP,
]
),
)
self._meter = None
self._duration_histogram = None
self._returned_rows_histogram = None
if _report_new(self._sem_conv_opt_in_mode_db):
self._meter = get_meter(
self._name,
self._version,
meter_provider,
schema_url=_get_schema_url_for_signal_types([_OpenTelemetryStabilitySignalType.DATABASE]),
)
self._duration_histogram = create_db_client_operation_duration(self._meter)
self._returned_rows_histogram = create_db_client_response_returned_rows(self._meter)
self.capture_parameters = capture_parameters
self.enable_commenter = enable_commenter
self.commenter_options = commenter_options
self.enable_attribute_commenter = enable_attribute_commenter
self.database_system = database_system
self.connection_props: dict[str, Any] = {}
self.span_attributes: dict[str, Any] = {}
self.name = ""
self.database = ""
self._server_address: str | None = None
self._server_port: int | None = None
self.connect_module = connect_module
self.commenter_data = self.calculate_commenter_data()
def _get_db_version(self, db_driver: str) -> str:
if db_driver in _DB_DRIVER_ALIASES:
return util_version(_DB_DRIVER_ALIASES[db_driver])
db_version = ""
try:
db_version = self.connect_module.__version__
except AttributeError:
db_version = "unknown"
return db_version
def calculate_commenter_data(self) -> dict[str, Any]:
commenter_data: dict[str, Any] = {}
if not self.enable_commenter:
return commenter_data
db_driver = getattr(self.connect_module, "__name__", "unknown")
db_version = self._get_db_version(db_driver)
commenter_data = {
"db_driver": f"{db_driver}:{db_version.split(' ')[0]}",
# PEP 249-compliant drivers should have the following attributes.
# We can assume apilevel "1.0" if not given.
# We use "unknown" for others to prevent uncaught AttributeError.
# https://peps.python.org/pep-0249/#globals
"dbapi_threadsafety": getattr(self.connect_module, "threadsafety", "unknown"),
"dbapi_level": getattr(self.connect_module, "apilevel", "1.0"),
"driver_paramstyle": getattr(self.connect_module, "paramstyle", "unknown"),
}
if self.database_system == "postgresql":
libpq_version = None
# psycopg
try:
libpq_version = self.connect_module.pq.version()
except AttributeError:
pass
# psycopg2
if libpq_version is None:
# this the libpq version the client has been built against
libpq_version = getattr(self.connect_module, "__libpq_version__", None)
# we instrument psycopg modules that are not the root one, in that case you
# won't get the libpq_version
if libpq_version is not None:
commenter_data.update({"libpq_version": libpq_version})
elif self.database_system == "mysql":
mysqlc_version = ""
if db_driver == "MySQLdb":
mysqlc_version = self.connect_module._mysql.get_client_info()
elif db_driver == "pymysql":
mysqlc_version = self.connect_module.get_client_info()
commenter_data.update({"mysql_client_version": mysqlc_version})
return commenter_data
def wrapped_connection(
self,
connect_method: Callable[..., ConnectionT],
args: tuple[Any, ...],
kwargs: dict[Any, Any],
) -> TracedConnectionProxy[ConnectionT]:
"""Add object proxy to connection object."""
connection = connect_method(*args, **kwargs)
self.get_connection_attributes(connection)
return get_traced_connection_proxy(connection, self)
def get_connection_attributes(self, connection: object) -> None:
# Populate span fields using connection
for key, value in self.connection_attributes.items():
# Allow attributes nested in connection object
attribute = functools.reduce(
lambda attribute, attribute_value: getattr(attribute, attribute_value, None),
value.split("."),
connection,
)
if attribute:
self.connection_props[key] = attribute
self.name = self.database_system
self.database = self.connection_props.get("database", "")
if self.database:
# PyMySQL encodes names with utf-8
if hasattr(self.database, "decode"):
self.database = self.database.decode(errors="ignore")
self.name += "." + self.database
user = self.connection_props.get("user")
# PyMySQL encodes this data
if user and isinstance(user, bytes):
user = user.decode()
if user is not None:
_set_db_user(self.span_attributes, str(user), self._sem_conv_opt_in_mode_db)
host = self.connection_props.get("host")
if host is not None:
_set_http_net_peer_name_client(
self.span_attributes,
host,
self._sem_conv_opt_in_mode_http,
)
self._server_address = host
port = self.connection_props.get("port")
if port is not None:
_set_http_peer_port_client(self.span_attributes, port, self._sem_conv_opt_in_mode_http)
self._server_port = port
# pylint: disable=abstract-method,no-member
class TracedConnectionProxy(BaseObjectProxy, Generic[ConnectionT]):
# pylint: disable=unused-argument
def __init__(
self,
connection: ConnectionT,
db_api_integration: DatabaseApiIntegration | None = None,
):
BaseObjectProxy.__init__(self, connection)
self._self_db_api_integration = db_api_integration
def __getattribute__(self, name: str):
if object.__getattribute__(self, name):
return object.__getattribute__(self, name)
return object.__getattribute__(object.__getattribute__(self, "_connection"), name)
def cursor(self, *args: Any, **kwargs: Any):
return get_traced_cursor_proxy(
self.__wrapped__.cursor(*args, **kwargs),
self._self_db_api_integration,
)
def __enter__(self):
self.__wrapped__.__enter__()
return self
def __exit__(self, *args: Any, **kwargs: Any):
self.__wrapped__.__exit__(*args, **kwargs)
def get_traced_connection_proxy(
connection: ConnectionT,
db_api_integration: DatabaseApiIntegration | None,
*args: Any,
**kwargs: Any,
) -> TracedConnectionProxy[ConnectionT]:
return TracedConnectionProxy(connection, db_api_integration)
def _t_string_to_str(template: Template) -> str:
"""Render a PEP 750 Template as a string with expression placeholders."""
parts: list[str] = []
for idx, literal in enumerate(template.strings):
parts.append(literal)
if idx < len(template.interpolations):
parts.append(f"{{{template.interpolations[idx].expression}}}")
return "".join(parts)
class CursorTracer(Generic[CursorT]):
def __init__(self, db_api_integration: DatabaseApiIntegration) -> None:
self._db_api_integration = db_api_integration
self._commenter_enabled = self._db_api_integration.enable_commenter
self._commenter_options = (
self._db_api_integration.commenter_options if self._db_api_integration.commenter_options else {}
)
self._enable_attribute_commenter = self._db_api_integration.enable_attribute_commenter
self._connect_module = self._db_api_integration.connect_module
self._leading_comment_remover = re.compile(r"^/\*.*?\*/")
def _capture_mysql_version(self, cursor) -> None:
"""Lazy capture of mysql-connector client version using cursor, if applicable"""
if (
self._db_api_integration.database_system == "mysql"
and self._db_api_integration.connect_module.__name__ == "mysql.connector"
and not self._db_api_integration.commenter_data["mysql_client_version"]
):
try:
# Autoinstrumentation and some programmatic calls
client_version = cursor._cnx._cmysql.get_client_info()
except AttributeError:
# Other programmatic instrumentation with reassigned wrapped connection
try:
client_version = cursor._connection._cmysql.get_client_info()
except AttributeError as exc:
_logger.debug("Could not set mysql_client_version: %s", exc)
client_version = "unknown"
self._db_api_integration.commenter_data["mysql_client_version"] = client_version
def _get_commenter_data(self) -> dict:
"""Uses DB-API integration to return commenter data for sqlcomment"""
commenter_data = dict(self._db_api_integration.commenter_data)
if self._commenter_options.get("opentelemetry_values", True):
commenter_data.update(**_get_opentelemetry_values())
return {k: v for k, v in commenter_data.items() if self._commenter_options.get(k, True)}
def _update_args_with_added_sql_comment(self, args, cursor) -> tuple:
"""Updates args with cursor info and adds sqlcomment to query statement"""
try:
args_list = list(args)
self._capture_mysql_version(cursor)
commenter_data = self._get_commenter_data()
if not isinstance(args_list[0], str) and not isinstance(args_list[0], _Template):
# Convert sql statement to string, handling psycopg2.sql.Composable object
if hasattr(args_list[0], "as_string"):
args_list[0] = args_list[0].as_string(cursor.connection)
args_list[0] = str(args_list[0])
args_list[0] = _add_sql_comment(args_list[0], **commenter_data)
args = tuple(args_list)
except Exception as exc: # pylint: disable=broad-except
_logger.exception("Exception while generating sql comment: %s", exc)
return args
def _populate_span(
self,
span: trace_api.Span,
cursor: CursorT,
*args: tuple[Any, ...],
):
if not span.is_recording():
return
statement = self.get_statement(cursor, args)
sem_conv_mode = self._db_api_integration._sem_conv_opt_in_mode_db
span_attrs = {}
_set_db_system(
span_attrs,
self._db_api_integration.database_system,
sem_conv_mode,
)
_set_db_name(
span_attrs,
self._db_api_integration.database,
sem_conv_mode,
)
_set_db_statement(span_attrs, statement, sem_conv_mode)
# Set all collected attributes
span.set_attributes(span_attrs)
for (
attribute_key,
attribute_value,
) in self._db_api_integration.span_attributes.items():
span.set_attribute(attribute_key, attribute_value)
if self._db_api_integration.capture_parameters and len(args) > 1:
span.set_attribute("db.statement.parameters", str(args[1]))
def get_operation_name(self, cursor: CursorT, args: Sequence[Any]) -> str: # pylint: disable=no-self-use
if not args:
return ""
query = args[0]
if isinstance(query, _Template):
first_literal = query.strings[0] if query.strings else ""
tokens = self._leading_comment_remover.sub("", first_literal).split()
return tokens[0] if tokens else ""
# `query` can be an empty string. See #2643
if query and isinstance(query, str):
# Strip leading comments so we get the operation name.
return self._leading_comment_remover.sub("", query).split()[0]
return ""
def get_statement(self, cursor: CursorT, args: Sequence[Any]) -> str: # pylint: disable=no-self-use
if not args:
return ""
statement = args[0]
if isinstance(statement, _Template):
return _t_string_to_str(statement)
if isinstance(statement, bytes):
return statement.decode("utf8", "replace")
if isinstance(statement, str):
return statement
return ""
def _get_metric_attributes(
self,
operation_name: str,
error: Exception | None,
) -> dict[str, Any]:
attributes: dict[str, Any] = {
DB_SYSTEM_NAME: self._db_api_integration.database_system,
}
if self._db_api_integration.database:
attributes[DB_NAMESPACE] = self._db_api_integration.database
if operation_name:
attributes[DB_OPERATION_NAME] = operation_name
if self._db_api_integration._server_address is not None:
attributes[SERVER_ADDRESS] = self._db_api_integration._server_address
if self._db_api_integration._server_port is not None:
attributes[SERVER_PORT] = self._db_api_integration._server_port
if error is not None:
attributes[ERROR_TYPE] = type(error).__qualname__
return attributes
def _record_metrics(
self,
cursor: CursorT,
operation_name: str,
start_time: float,
error: Exception | None,
) -> None:
if not _report_new(self._db_api_integration._sem_conv_opt_in_mode_db):
# DB Metrics are not supported without Database semconv opt-in
return
elapsed = time.perf_counter() - start_time
attributes = self._get_metric_attributes(operation_name, error)
self._db_api_integration._duration_histogram.record(elapsed, attributes=attributes)
if error is None:
rowcount = getattr(cursor, "rowcount", None)
if isinstance(rowcount, int) and rowcount >= 0:
self._db_api_integration._returned_rows_histogram.record(rowcount, attributes=attributes)
def traced_execution(
self,
cursor: CursorT,
query_method: Callable[..., Any],
*args: tuple[Any, ...],
**kwargs: dict[Any, Any],
):
if not is_instrumentation_enabled():
return query_method(*args, **kwargs)
operation_name = self.get_operation_name(cursor, args)
name = operation_name
if not name:
name = (
self._db_api_integration.database
if self._db_api_integration.database
else self._db_api_integration.name
)
with self._db_api_integration._tracer.start_as_current_span(name, kind=SpanKind.CLIENT) as span:
if span.is_recording():
if args and self._commenter_enabled:
if self._enable_attribute_commenter:
# sqlcomment is added to executed query and db.statement and/or db.query.text span attribute
args = self._update_args_with_added_sql_comment(args, cursor)
self._populate_span(span, cursor, *args)
else:
# sqlcomment is only added to executed query
# so db.statement and/or db.query.text are set before add_sql_comment
self._populate_span(span, cursor, *args)
args = self._update_args_with_added_sql_comment(args, cursor)
else:
# no sqlcomment anywhere
self._populate_span(span, cursor, *args)
start_time = time.perf_counter()
error: Exception | None = None
try:
return query_method(*args, **kwargs)
except Exception as exc:
error = exc
raise
finally:
self._record_metrics(cursor, operation_name, start_time, error)
async def traced_execution_async(
self,
cursor: CursorT,
query_method: Callable[..., Awaitable[Any]],
*args: tuple[Any, ...],
**kwargs: dict[Any, Any],
):
if not is_instrumentation_enabled():
return await query_method(*args, **kwargs)
operation_name = self.get_operation_name(cursor, args)
name = operation_name
if not name:
name = (
self._db_api_integration.database
if self._db_api_integration.database
else self._db_api_integration.name
)
with self._db_api_integration._tracer.start_as_current_span(name, kind=SpanKind.CLIENT) as span:
if span.is_recording():
if args and self._commenter_enabled:
if self._enable_attribute_commenter:
# sqlcomment is added to executed query and db.statement and/or db.query.text span attribute
args = self._update_args_with_added_sql_comment(args, cursor)
self._populate_span(span, cursor, *args)
else:
# sqlcomment is only added to executed query
# so db.statement and/or db.query.text are set before add_sql_comment
self._populate_span(span, cursor, *args)
args = self._update_args_with_added_sql_comment(args, cursor)
else:
# no sqlcomment anywhere
self._populate_span(span, cursor, *args)
start_time = time.perf_counter()
error: Exception | None = None
try:
return await query_method(*args, **kwargs)
except Exception as exc:
error = exc
raise
finally:
self._record_metrics(cursor, operation_name, start_time, error)
# pylint: disable=abstract-method,no-member
class TracedCursorProxy(ObjectProxy, Generic[CursorT]):
# pylint: disable=unused-argument
def __init__(
self,
cursor: CursorT,
db_api_integration: DatabaseApiIntegration,
):
ObjectProxy.__init__(self, cursor)
self._self_cursor_tracer = CursorTracer[CursorT](db_api_integration)
def execute(self, *args: Any, **kwargs: Any):
return self._self_cursor_tracer.traced_execution(self.__wrapped__, self.__wrapped__.execute, *args, **kwargs)
def executemany(self, *args: Any, **kwargs: Any):
return self._self_cursor_tracer.traced_execution(
self.__wrapped__, self.__wrapped__.executemany, *args, **kwargs
)
def callproc(self, *args: Any, **kwargs: Any):
return self._self_cursor_tracer.traced_execution(self.__wrapped__, self.__wrapped__.callproc, *args, **kwargs)
def __enter__(self):
self.__wrapped__.__enter__()
return self
def __exit__(self, *args, **kwargs):
self.__wrapped__.__exit__(*args, **kwargs)
def get_traced_cursor_proxy(
cursor: CursorT,
db_api_integration: DatabaseApiIntegration,
*args: Any,
**kwargs: Any,
) -> TracedCursorProxy[CursorT]:
return TracedCursorProxy(cursor, db_api_integration)
package.py 0000664 0000000 0000000 00000000204 15270700723 0044111 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-dbapi/src/opentelemetry/instrumentation/dbapi # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
_instruments = tuple()
_semconv_status = "migration"
py.typed 0000664 0000000 0000000 00000000000 15270700723 0043635 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-dbapi/src/opentelemetry/instrumentation/dbapi version.py 0000664 0000000 0000000 00000000174 15270700723 0044211 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-dbapi/src/opentelemetry/instrumentation/dbapi # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
__version__ = "0.66b2"
_instruments = tuple()
test-requirements-wrapt1.txt 0000664 0000000 0000000 00000000047 15270700723 0037621 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-dbapi -r test-requirements.txt
wrapt==1.17.3
test-requirements-wrapt2.txt 0000664 0000000 0000000 00000000046 15270700723 0037621 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-dbapi -r test-requirements.txt
wrapt==2.1.2
test-requirements.txt 0000664 0000000 0000000 00000000352 15270700723 0036404 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-dbapi asgiref==3.8.1
iniconfig==2.0.0
packaging==24.0
pluggy==1.6.0
py-cpuinfo==9.0.0
pytest==7.4.4
tomli==2.0.1
typing_extensions==4.12.2
zipp==3.19.2
-e opentelemetry-instrumentation
-e instrumentation/opentelemetry-instrumentation-dbapi
opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-dbapi/tests/ 0000775 0000000 0000000 00000000000 15270700723 0033364 5 ustar 00root root 0000000 0000000 __init__.py 0000664 0000000 0000000 00000000000 15270700723 0035404 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-dbapi/tests test_dbapi_integration.py 0000664 0000000 0000000 00000225162 15270700723 0040410 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-dbapi/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
# pylint: disable=too-many-lines
import asyncio
import contextlib
import logging
import re
import sys
from unittest import mock
import pytest
from opentelemetry import context
from opentelemetry import trace as trace_api
from opentelemetry.instrumentation import dbapi
from opentelemetry.instrumentation._semconv import (
OTEL_SEMCONV_STABILITY_OPT_IN,
_OpenTelemetrySemanticConventionStability,
)
from opentelemetry.instrumentation.utils import suppress_instrumentation
from opentelemetry.sdk import resources
from opentelemetry.semconv._incubating.attributes import net_attributes
from opentelemetry.semconv._incubating.attributes.db_attributes import (
DB_NAME,
DB_STATEMENT,
DB_SYSTEM,
DB_USER,
)
from opentelemetry.semconv._incubating.attributes.net_attributes import (
NET_PEER_NAME,
NET_PEER_PORT,
)
from opentelemetry.semconv._incubating.metrics.db_metrics import (
DB_CLIENT_OPERATION_DURATION,
DB_CLIENT_RESPONSE_RETURNED_ROWS,
)
from opentelemetry.semconv.attributes.db_attributes import (
DB_NAMESPACE,
DB_OPERATION_NAME,
DB_QUERY_TEXT,
DB_SYSTEM_NAME,
)
from opentelemetry.semconv.attributes.error_attributes import ERROR_TYPE
from opentelemetry.semconv.attributes.server_attributes import (
SERVER_ADDRESS,
SERVER_PORT,
)
from opentelemetry.test.test_base import TestBase
def _get_default_connection_props():
"""Returns standard connection properties for testing."""
return {
"database": "testdatabase",
"server_host": "testhost",
"server_port": 123,
"user": "testuser",
}
def _get_default_connection_attributes():
"""Returns standard connection attributes for testing."""
return {
"database": "database",
"port": "server_port",
"host": "server_host",
"user": "user",
}
@contextlib.contextmanager
def use_semconv_opt_in(sem_conv_mode):
env_patch = mock.patch.dict(
"os.environ",
{OTEL_SEMCONV_STABILITY_OPT_IN: sem_conv_mode},
)
_OpenTelemetrySemanticConventionStability._initialized = False
env_patch.start()
try:
yield
finally:
env_patch.stop()
_OpenTelemetrySemanticConventionStability._initialized = False
# pylint: disable=too-many-public-methods
class TestDBApiIntegration(TestBase):
def setUp(self):
super().setUp()
self.tracer = self.tracer_provider.get_tracer(__name__)
_OpenTelemetrySemanticConventionStability._initialized = False
def test_span_succeeded(self):
connection_props = _get_default_connection_props()
connection_attributes = _get_default_connection_attributes()
db_integration = dbapi.DatabaseApiIntegration(
"instrumenting_module_test_name",
"testcomponent",
connection_attributes,
)
mock_connection = db_integration.wrapped_connection(mock_connect, {}, connection_props)
cursor = mock_connection.cursor()
cursor.execute("Test query", ("param1Value", False))
spans_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans_list), 1)
span = spans_list[0]
self.assertEqual(span.name, "Test")
self.assertIs(span.kind, trace_api.SpanKind.CLIENT)
self.assertEqual(
span.instrumentation_scope.schema_url,
"https://opentelemetry.io/schemas/1.11.0",
)
self.assertEqual(span.attributes[DB_SYSTEM], "testcomponent")
self.assertEqual(span.attributes[DB_NAME], "testdatabase")
self.assertEqual(span.attributes[DB_STATEMENT], "Test query")
self.assertFalse("db.statement.parameters" in span.attributes)
self.assertEqual(span.attributes[DB_USER], "testuser")
self.assertEqual(span.attributes[NET_PEER_NAME], "testhost")
self.assertEqual(span.attributes[NET_PEER_PORT], 123)
self.assertIs(span.status.status_code, trace_api.StatusCode.UNSET)
def test_suppress_instrumentation_async(self):
execute = mock.AsyncMock(return_value="result")
db_integration = dbapi.DatabaseApiIntegration(
"instrumenting_module_test_name",
"testcomponent",
)
with suppress_instrumentation():
result = asyncio.run(
dbapi.CursorTracer(db_integration).traced_execution_async(MockCursor(), execute, "SELECT 1")
)
self.assertEqual(result, "result")
execute.assert_awaited_once_with("SELECT 1")
self.assertEqual(len(self.memory_exporter.get_finished_spans()), 0)
def test_span_succeeded_new_semconv(self):
with use_semconv_opt_in("database,http"):
connection_props = _get_default_connection_props()
connection_attributes = _get_default_connection_attributes()
db_integration = dbapi.DatabaseApiIntegration(
"instrumenting_module_test_name",
"testcomponent",
connection_attributes,
)
mock_connection = db_integration.wrapped_connection(mock_connect, {}, connection_props)
cursor = mock_connection.cursor()
cursor.execute("Test query", ("param1Value", False))
spans_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans_list), 1)
span = spans_list[0]
self.assertEqual(span.name, "Test")
self.assertIs(span.kind, trace_api.SpanKind.CLIENT)
self.assertEqual(
span.instrumentation_scope.schema_url,
"https://opentelemetry.io/schemas/1.25.0",
)
# Stable attributes only
self.assertEqual(span.attributes[DB_SYSTEM_NAME], "testcomponent")
self.assertEqual(span.attributes[DB_NAMESPACE], "testdatabase")
self.assertEqual(span.attributes[DB_QUERY_TEXT], "Test query")
self.assertFalse("db.statement.parameters" in span.attributes)
# db.user removed in stable - no replacement
self.assertFalse(DB_USER in span.attributes)
self.assertEqual(span.attributes[SERVER_ADDRESS], "testhost")
self.assertEqual(span.attributes[SERVER_PORT], 123)
# Old attributes should not be present
self.assertFalse(DB_SYSTEM in span.attributes)
self.assertFalse(DB_NAME in span.attributes)
self.assertFalse(DB_STATEMENT in span.attributes)
self.assertFalse(NET_PEER_NAME in span.attributes)
self.assertFalse(NET_PEER_PORT in span.attributes)
self.assertIs(span.status.status_code, trace_api.StatusCode.UNSET)
def test_span_succeeded_both_semconv(self):
with use_semconv_opt_in("database/dup,http/dup"):
connection_props = _get_default_connection_props()
connection_attributes = _get_default_connection_attributes()
db_integration = dbapi.DatabaseApiIntegration(
"instrumenting_module_test_name",
"testcomponent",
connection_attributes,
)
mock_connection = db_integration.wrapped_connection(mock_connect, {}, connection_props)
cursor = mock_connection.cursor()
cursor.execute("Test query", ("param1Value", False))
spans_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans_list), 1)
span = spans_list[0]
self.assertEqual(span.name, "Test")
self.assertIs(span.kind, trace_api.SpanKind.CLIENT)
self.assertEqual(
span.instrumentation_scope.schema_url,
"https://opentelemetry.io/schemas/1.25.0",
)
# Both old and new attributes should be present
# Old attributes
self.assertEqual(span.attributes[DB_SYSTEM], "testcomponent")
self.assertEqual(span.attributes[DB_NAME], "testdatabase")
self.assertEqual(span.attributes[DB_STATEMENT], "Test query")
self.assertEqual(span.attributes[DB_USER], "testuser")
self.assertEqual(span.attributes[NET_PEER_NAME], "testhost")
self.assertEqual(span.attributes[NET_PEER_PORT], 123)
# New stable attributes
self.assertEqual(span.attributes[DB_SYSTEM_NAME], "testcomponent")
self.assertEqual(span.attributes[DB_NAMESPACE], "testdatabase")
self.assertEqual(span.attributes[DB_QUERY_TEXT], "Test query")
self.assertEqual(span.attributes[SERVER_ADDRESS], "testhost")
self.assertEqual(span.attributes[SERVER_PORT], 123)
self.assertFalse("db.statement.parameters" in span.attributes)
self.assertIs(span.status.status_code, trace_api.StatusCode.UNSET)
def test_span_succeeded_database_only_semconv(self):
with use_semconv_opt_in("database"):
connection_props = _get_default_connection_props()
connection_attributes = _get_default_connection_attributes()
db_integration = dbapi.DatabaseApiIntegration(
"instrumenting_module_test_name",
"testcomponent",
connection_attributes,
)
mock_connection = db_integration.wrapped_connection(mock_connect, {}, connection_props)
cursor = mock_connection.cursor()
cursor.execute("Test query", ("param1Value", False))
spans_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans_list), 1)
span = spans_list[0]
self.assertEqual(
span.instrumentation_scope.schema_url,
"https://opentelemetry.io/schemas/1.25.0",
)
# DB attributes should be stable-only
self.assertEqual(span.attributes[DB_SYSTEM_NAME], "testcomponent")
self.assertEqual(span.attributes[DB_NAMESPACE], "testdatabase")
self.assertEqual(span.attributes[DB_QUERY_TEXT], "Test query")
self.assertFalse(DB_SYSTEM in span.attributes)
self.assertFalse(DB_NAME in span.attributes)
self.assertFalse(DB_STATEMENT in span.attributes)
# Network attributes should remain old semconv
self.assertEqual(span.attributes[NET_PEER_NAME], "testhost")
self.assertEqual(span.attributes[NET_PEER_PORT], 123)
self.assertFalse(SERVER_ADDRESS in span.attributes)
self.assertFalse(SERVER_PORT in span.attributes)
def test_span_succeeded_http_only_semconv(self):
with use_semconv_opt_in("http"):
connection_props = _get_default_connection_props()
connection_attributes = _get_default_connection_attributes()
db_integration = dbapi.DatabaseApiIntegration(
"instrumenting_module_test_name",
"testcomponent",
connection_attributes,
)
mock_connection = db_integration.wrapped_connection(mock_connect, {}, connection_props)
cursor = mock_connection.cursor()
cursor.execute("Test query", ("param1Value", False))
spans_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans_list), 1)
span = spans_list[0]
self.assertEqual(
span.instrumentation_scope.schema_url,
"https://opentelemetry.io/schemas/1.21.0",
)
# DB attributes should remain old semconv
self.assertEqual(span.attributes[DB_SYSTEM], "testcomponent")
self.assertEqual(span.attributes[DB_NAME], "testdatabase")
self.assertEqual(span.attributes[DB_STATEMENT], "Test query")
self.assertFalse(DB_SYSTEM_NAME in span.attributes)
self.assertFalse(DB_NAMESPACE in span.attributes)
self.assertFalse(DB_QUERY_TEXT in span.attributes)
# Network attributes should be stable-only
self.assertEqual(span.attributes[SERVER_ADDRESS], "testhost")
self.assertEqual(span.attributes[SERVER_PORT], 123)
self.assertFalse(NET_PEER_NAME in span.attributes)
self.assertFalse(NET_PEER_PORT in span.attributes)
def test_span_name(self):
db_integration = dbapi.DatabaseApiIntegration("instrumenting_module_test_name", "testcomponent", {})
mock_connection = db_integration.wrapped_connection(mock_connect, {}, {})
cursor = mock_connection.cursor()
cursor.execute("Test query", ("param1Value", False))
cursor.execute(
"""multi
line
query"""
)
cursor.execute("tab\tseparated query")
cursor.execute("/* leading comment */ query")
cursor.execute("/* leading comment */ query /* trailing comment */")
cursor.execute("query /* trailing comment */")
spans_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans_list), 6)
self.assertEqual(spans_list[0].name, "Test")
self.assertEqual(spans_list[1].name, "multi")
self.assertEqual(spans_list[2].name, "tab")
self.assertEqual(spans_list[3].name, "query")
self.assertEqual(spans_list[4].name, "query")
self.assertEqual(spans_list[5].name, "query")
def test_span_succeeded_with_capture_of_statement_parameters(self):
connection_props = _get_default_connection_props()
connection_attributes = _get_default_connection_attributes()
db_integration = dbapi.DatabaseApiIntegration(
"instrumenting_module_test_name",
"testcomponent",
connection_attributes,
capture_parameters=True,
)
mock_connection = db_integration.wrapped_connection(mock_connect, {}, connection_props)
cursor = mock_connection.cursor()
cursor.execute("Test query", ("param1Value", False))
spans_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans_list), 1)
span = spans_list[0]
self.assertEqual(span.name, "Test")
self.assertIs(span.kind, trace_api.SpanKind.CLIENT)
self.assertEqual(span.attributes[DB_SYSTEM], "testcomponent")
self.assertEqual(span.attributes[DB_NAME], "testdatabase")
self.assertEqual(span.attributes[DB_STATEMENT], "Test query")
self.assertEqual(
span.attributes["db.statement.parameters"],
"('param1Value', False)",
)
self.assertEqual(span.attributes[DB_USER], "testuser")
self.assertEqual(span.attributes[net_attributes.NET_PEER_NAME], "testhost")
self.assertEqual(span.attributes[net_attributes.NET_PEER_PORT], 123)
self.assertIs(span.status.status_code, trace_api.StatusCode.UNSET)
def test_span_succeeded_with_capture_of_statement_parameters_new_semconv(
self,
):
with use_semconv_opt_in("database,http"):
connection_props = _get_default_connection_props()
connection_attributes = _get_default_connection_attributes()
db_integration = dbapi.DatabaseApiIntegration(
"instrumenting_module_test_name",
"testcomponent",
connection_attributes,
capture_parameters=True,
)
mock_connection = db_integration.wrapped_connection(mock_connect, {}, connection_props)
cursor = mock_connection.cursor()
cursor.execute("Test query", ("param1Value", False))
spans_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans_list), 1)
span = spans_list[0]
self.assertEqual(span.name, "Test")
self.assertIs(span.kind, trace_api.SpanKind.CLIENT)
# Stable attributes only
self.assertEqual(span.attributes[DB_SYSTEM_NAME], "testcomponent")
self.assertEqual(span.attributes[DB_NAMESPACE], "testdatabase")
self.assertEqual(span.attributes[DB_QUERY_TEXT], "Test query")
self.assertEqual(
span.attributes["db.statement.parameters"],
"('param1Value', False)",
)
# db.user removed in stable - no replacement
self.assertFalse(DB_USER in span.attributes)
self.assertEqual(span.attributes[SERVER_ADDRESS], "testhost")
self.assertEqual(span.attributes[SERVER_PORT], 123)
# Old attributes should not be present
self.assertFalse(DB_SYSTEM in span.attributes)
self.assertFalse(DB_NAME in span.attributes)
self.assertFalse(DB_STATEMENT in span.attributes)
self.assertFalse(NET_PEER_NAME in span.attributes)
self.assertFalse(NET_PEER_PORT in span.attributes)
self.assertIs(span.status.status_code, trace_api.StatusCode.UNSET)
def test_span_succeeded_with_capture_of_statement_parameters_both_semconv(
self,
):
with use_semconv_opt_in("database/dup,http/dup"):
connection_props = _get_default_connection_props()
connection_attributes = _get_default_connection_attributes()
db_integration = dbapi.DatabaseApiIntegration(
"instrumenting_module_test_name",
"testcomponent",
connection_attributes,
capture_parameters=True,
)
mock_connection = db_integration.wrapped_connection(mock_connect, {}, connection_props)
cursor = mock_connection.cursor()
cursor.execute("Test query", ("param1Value", False))
spans_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans_list), 1)
span = spans_list[0]
self.assertEqual(span.name, "Test")
self.assertIs(span.kind, trace_api.SpanKind.CLIENT)
# Both old and new attributes should be present
# Old attributes
self.assertEqual(span.attributes[DB_SYSTEM], "testcomponent")
self.assertEqual(span.attributes[DB_NAME], "testdatabase")
self.assertEqual(span.attributes[DB_STATEMENT], "Test query")
self.assertEqual(
span.attributes["db.statement.parameters"],
"('param1Value', False)",
)
self.assertEqual(span.attributes[DB_USER], "testuser")
self.assertEqual(span.attributes[net_attributes.NET_PEER_NAME], "testhost")
self.assertEqual(span.attributes[net_attributes.NET_PEER_PORT], 123)
# New stable attributes
self.assertEqual(span.attributes[DB_SYSTEM_NAME], "testcomponent")
self.assertEqual(span.attributes[DB_NAMESPACE], "testdatabase")
self.assertEqual(span.attributes[DB_QUERY_TEXT], "Test query")
self.assertEqual(span.attributes[SERVER_ADDRESS], "testhost")
self.assertEqual(span.attributes[SERVER_PORT], 123)
self.assertIs(span.status.status_code, trace_api.StatusCode.UNSET)
def test_span_not_recording(self):
connection_props = _get_default_connection_props()
connection_attributes = _get_default_connection_attributes()
mock_span = mock.Mock()
mock_span.is_recording.return_value = False
db_integration = dbapi.DatabaseApiIntegration(
"instrumenting_module_test_name",
"testcomponent",
connection_attributes,
)
mock_connection = db_integration.wrapped_connection(mock_connect, {}, connection_props)
cursor = mock_connection.cursor()
cursor.execute("Test query", ("param1Value", False))
self.assertFalse(mock_span.is_recording())
self.assertTrue(mock_span.is_recording.called)
self.assertFalse(mock_span.set_attribute.called)
self.assertFalse(mock_span.set_status.called)
def test_span_failed(self):
db_integration = dbapi.DatabaseApiIntegration("instrumenting_module_test_name", "testcomponent")
mock_connection = db_integration.wrapped_connection(mock_connect, {}, {})
cursor = mock_connection.cursor()
with self.assertRaises(Exception):
cursor.execute("Test query", throw_exception=True)
spans_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans_list), 1)
span = spans_list[0]
self.assertEqual(span.attributes[DB_STATEMENT], "Test query")
self.assertIs(span.status.status_code, trace_api.StatusCode.ERROR)
self.assertEqual(span.status.description, "Exception: Test Exception")
def test_custom_tracer_provider_dbapi(self):
resource = resources.Resource.create({"db-resource-key": "value"})
result = self.create_tracer_provider(resource=resource)
tracer_provider, exporter = result
db_integration = dbapi.DatabaseApiIntegration(
"instrumenting_module_test_name",
"testcomponent",
tracer_provider=tracer_provider,
)
mock_connection = db_integration.wrapped_connection(mock_connect, {}, {})
cursor = mock_connection.cursor()
with self.assertRaises(Exception):
cursor.execute("Test query", throw_exception=True)
spans_list = exporter.get_finished_spans()
self.assertEqual(len(spans_list), 1)
span = spans_list[0]
self.assertEqual(span.resource.attributes["db-resource-key"], "value")
self.assertIs(span.status.status_code, trace_api.StatusCode.ERROR)
def test_no_op_tracer_provider(self):
db_integration = dbapi.DatabaseApiIntegration(
"instrumenting_module_test_name",
"testcomponent",
tracer_provider=trace_api.NoOpTracerProvider(),
)
mock_connection = db_integration.wrapped_connection(mock_connect, {}, {})
cursor = mock_connection.cursor()
cursor.executemany("Test query")
spans_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans_list), 0)
def test_suppress_instrumentation(self):
db_integration = dbapi.DatabaseApiIntegration(
"instrumenting_module_test_name",
"testcomponent",
)
mock_connection = db_integration.wrapped_connection(mock_connect, {}, {})
with suppress_instrumentation():
cursor = mock_connection.cursor()
cursor.execute("Test query", ("param1Value", False))
spans_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans_list), 0)
def _get_metric(self, name):
return next(
(metric for metric in self.get_sorted_metrics() if metric.name == name),
None,
)
def test_metrics_not_emitted_in_default_mode(self):
# Without OTEL_SEMCONV_STABILITY_OPT_IN=database, no metrics are exported
db_integration = dbapi.DatabaseApiIntegration("instrumenting_module_test_name", "testcomponent")
mock_connection = db_integration.wrapped_connection(mock_connect, (), {})
cursor = mock_connection.cursor()
cursor.execute("SELECT 1", rowcount=3)
self.assertIsNone(self._get_metric(DB_CLIENT_OPERATION_DURATION))
self.assertIsNone(self._get_metric(DB_CLIENT_RESPONSE_RETURNED_ROWS))
@mock.patch.dict("os.environ", {OTEL_SEMCONV_STABILITY_OPT_IN: "database"})
def test_operation_duration_recorded(self):
connection_props = {
"database": "testdatabase",
"server_host": "testhost",
"server_port": 123,
"user": "testuser",
}
connection_attributes = {
"database": "database",
"port": "server_port",
"host": "server_host",
"user": "user",
}
db_integration = dbapi.DatabaseApiIntegration(
"instrumenting_module_test_name",
"testcomponent",
connection_attributes,
)
mock_connection = db_integration.wrapped_connection(mock_connect, (), connection_props)
cursor = mock_connection.cursor()
cursor.execute("SELECT * FROM users")
duration_metric = self._get_metric(DB_CLIENT_OPERATION_DURATION)
self.assertIsNotNone(duration_metric)
self.assertEqual(duration_metric.unit, "s")
points = list(duration_metric.data.data_points)
self.assertEqual(len(points), 1)
attributes = dict(points[0].attributes)
self.assertEqual(attributes[DB_SYSTEM_NAME], "testcomponent")
self.assertEqual(attributes[DB_NAMESPACE], "testdatabase")
self.assertEqual(attributes[DB_OPERATION_NAME], "SELECT")
self.assertEqual(attributes[SERVER_ADDRESS], "testhost")
self.assertEqual(attributes[SERVER_PORT], 123)
self.assertNotIn(ERROR_TYPE, attributes)
self.assertEqual(points[0].count, 1)
self.assertGreaterEqual(points[0].sum, 0.0)
@mock.patch.dict("os.environ", {OTEL_SEMCONV_STABILITY_OPT_IN: "database"})
def test_operation_duration_error_type(self):
db_integration = dbapi.DatabaseApiIntegration("instrumenting_module_test_name", "testcomponent")
mock_connection = db_integration.wrapped_connection(mock_connect, (), {})
cursor = mock_connection.cursor()
with self.assertRaises(Exception):
cursor.execute("SELECT 1", throw_exception=True)
duration_metric = self._get_metric(DB_CLIENT_OPERATION_DURATION)
self.assertIsNotNone(duration_metric)
points = list(duration_metric.data.data_points)
self.assertEqual(len(points), 1)
attributes = dict(points[0].attributes)
self.assertEqual(attributes[ERROR_TYPE], "Exception")
self.assertEqual(attributes[DB_OPERATION_NAME], "SELECT")
# returned_rows should NOT be recorded on error
rows_metric = self._get_metric(DB_CLIENT_RESPONSE_RETURNED_ROWS)
self.assertIsNone(rows_metric)
@mock.patch.dict("os.environ", {OTEL_SEMCONV_STABILITY_OPT_IN: "database"})
def test_returned_rows_recorded(self):
db_integration = dbapi.DatabaseApiIntegration("instrumenting_module_test_name", "testcomponent")
mock_connection = db_integration.wrapped_connection(mock_connect, (), {})
cursor = mock_connection.cursor()
cursor.execute("SELECT 1", rowcount=3)
rows_metric = self._get_metric(DB_CLIENT_RESPONSE_RETURNED_ROWS)
self.assertIsNotNone(rows_metric)
self.assertEqual(rows_metric.unit, "{row}")
points = list(rows_metric.data.data_points)
self.assertEqual(len(points), 1)
self.assertEqual(points[0].sum, 3)
self.assertEqual(points[0].count, 1)
@mock.patch.dict("os.environ", {OTEL_SEMCONV_STABILITY_OPT_IN: "database"})
def test_returned_rows_skipped_when_rowcount_unknown(self):
db_integration = dbapi.DatabaseApiIntegration("instrumenting_module_test_name", "testcomponent")
mock_connection = db_integration.wrapped_connection(mock_connect, (), {})
cursor = mock_connection.cursor()
# default rowcount is -1 on MockCursor
cursor.execute("CREATE TABLE t (x INT)")
rows_metric = self._get_metric(DB_CLIENT_RESPONSE_RETURNED_ROWS)
self.assertIsNone(rows_metric)
# duration is still recorded
self.assertIsNotNone(self._get_metric(DB_CLIENT_OPERATION_DURATION))
@mock.patch.dict("os.environ", {OTEL_SEMCONV_STABILITY_OPT_IN: "database"})
def test_custom_meter_provider(self):
meter_provider, metrics_reader = self.create_meter_provider()
db_integration = dbapi.DatabaseApiIntegration(
"instrumenting_module_test_name",
"testcomponent",
meter_provider=meter_provider,
)
mock_connection = db_integration.wrapped_connection(mock_connect, (), {})
cursor = mock_connection.cursor()
cursor.execute("SELECT 1", rowcount=1)
metrics_data = metrics_reader.get_metrics_data()
names = {m.name for rm in metrics_data.resource_metrics for sm in rm.scope_metrics for m in sm.metrics}
self.assertIn(DB_CLIENT_OPERATION_DURATION, names)
self.assertIn(DB_CLIENT_RESPONSE_RETURNED_ROWS, names)
@mock.patch.dict("os.environ", {OTEL_SEMCONV_STABILITY_OPT_IN: "database"})
def test_async_operation_duration_recorded(self):
db_integration = dbapi.DatabaseApiIntegration("instrumenting_module_test_name", "testcomponent")
cursor_tracer = dbapi.CursorTracer(db_integration)
mock_cursor = MockCursor()
async def async_execute(_query, rowcount=-1):
mock_cursor.rowcount = rowcount
asyncio.run(cursor_tracer.traced_execution_async(mock_cursor, async_execute, "SELECT 1", rowcount=5))
duration_metric = self._get_metric(DB_CLIENT_OPERATION_DURATION)
self.assertIsNotNone(duration_metric)
points = list(duration_metric.data.data_points)
self.assertEqual(len(points), 1)
self.assertEqual(dict(points[0].attributes)[DB_OPERATION_NAME], "SELECT")
rows_metric = self._get_metric(DB_CLIENT_RESPONSE_RETURNED_ROWS)
self.assertIsNotNone(rows_metric)
rows_points = list(rows_metric.data.data_points)
self.assertEqual(rows_points[0].sum, 5)
def test_commenter_options_propagation(self):
db_integration = dbapi.DatabaseApiIntegration(
"instrumenting_module_test_name",
"testcomponent",
commenter_options={"opentelemetry_values": False},
)
mock_connection = db_integration.wrapped_connection(mock_connect, {}, {})
cursor = mock_connection.cursor()
with self.assertRaises(Exception):
cursor.execute("SELECT 1", throw_exception=True)
spans_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans_list), 1)
span = spans_list[0]
self.assertEqual(span.attributes.get("db.system"), "testcomponent")
self.assertIn("opentelemetry_values", db_integration.commenter_options)
self.assertFalse(db_integration.commenter_options["opentelemetry_values"])
@mock.patch("opentelemetry.instrumentation.dbapi.wrap_connect")
def test_trace_integration_passes_commenter_options(self, mock_wrap_connect):
fake_connect_module = mock.Mock()
fake_options = {"opentelemetry_values": False, "foo": "bar"}
dbapi.trace_integration(
connect_module=fake_connect_module,
connect_method_name="connect",
database_system="testdb",
commenter_options=fake_options,
)
mock_wrap_connect.assert_called_once()
_, _, kwargs = mock_wrap_connect.mock_calls[0]
self.assertIn("commenter_options", kwargs)
self.assertEqual(kwargs["commenter_options"], fake_options)
def test_executemany(self):
db_integration = dbapi.DatabaseApiIntegration("instrumenting_module_test_name", "testcomponent")
mock_connection = db_integration.wrapped_connection(mock_connect, {}, {})
cursor = mock_connection.cursor()
cursor.executemany("Test query")
spans_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans_list), 1)
span = spans_list[0]
self.assertEqual(span.attributes[DB_STATEMENT], "Test query")
# pylint: disable=no-self-use
def test_executemany_iterable_cursor(self):
db_integration = dbapi.DatabaseApiIntegration("instrumenting_module_test_name", "testcomponent")
mock_connection = db_integration.wrapped_connection(mock_connect, {}, {})
cursor = mock_connection.cursor()
cursor.executemany("Test query")
for _row in cursor:
pass
def test_executemany_comment(self):
connect_module = mock.MagicMock()
connect_module.__name__ = "test"
connect_module.__version__ = mock.MagicMock()
connect_module.pq.version.return_value = 123
connect_module.apilevel = 123
connect_module.threadsafety = 123
connect_module.paramstyle = "test"
db_integration = dbapi.DatabaseApiIntegration(
"instrumenting_module_test_name",
"postgresql",
enable_commenter=True,
commenter_options={"db_driver": False, "dbapi_level": False},
connect_module=connect_module,
)
mock_connection = db_integration.wrapped_connection(mock_connect, {}, {})
cursor = mock_connection.cursor()
cursor.executemany("Select 1;")
self.assertRegex(
cursor.query,
r"Select 1 /\*dbapi_threadsafety=123,driver_paramstyle='test',libpq_version=123,traceparent='\d{1,2}-[a-zA-Z0-9_]{32}-[a-zA-Z0-9_]{16}-\d{1,2}'\*/;",
)
spans_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans_list), 1)
span = spans_list[0]
self.assertEqual(
span.attributes[DB_STATEMENT],
"Select 1;",
)
def test_executemany_comment_stmt_enabled(self):
connect_module = mock.MagicMock()
connect_module.__name__ = "test"
connect_module.__version__ = mock.MagicMock()
connect_module.pq.version.return_value = 123
connect_module.apilevel = 123
connect_module.threadsafety = 123
connect_module.paramstyle = "test"
db_integration = dbapi.DatabaseApiIntegration(
"instrumenting_module_test_name",
"postgresql",
enable_commenter=True,
commenter_options={"db_driver": False, "dbapi_level": False},
connect_module=connect_module,
enable_attribute_commenter=True,
)
mock_connection = db_integration.wrapped_connection(mock_connect, {}, {})
cursor = mock_connection.cursor()
cursor.executemany("Select 1;")
self.assertRegex(
cursor.query,
r"Select 1 /\*dbapi_threadsafety=123,driver_paramstyle='test',libpq_version=123,traceparent='\d{1,2}-[a-zA-Z0-9_]{32}-[a-zA-Z0-9_]{16}-\d{1,2}'\*/;",
)
spans_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans_list), 1)
span = spans_list[0]
self.assertRegex(
span.attributes[DB_STATEMENT],
r"Select 1 /\*dbapi_threadsafety=123,driver_paramstyle='test',libpq_version=123,traceparent='\d{1,2}-[a-zA-Z0-9_]{32}-[a-zA-Z0-9_]{16}-\d{1,2}'\*/;",
)
def test_executemany_comment_non_pep_249_compliant(self):
class MockConnectModule:
def __getattr__(self, name):
if name == "__name__":
return "test"
if name == "__version__":
return mock.MagicMock()
if name == "__libpq_version__":
return 123
raise AttributeError("attribute missing")
connect_module = MockConnectModule()
db_integration = dbapi.DatabaseApiIntegration(
"instrumenting_module_test_name",
"postgresql",
enable_commenter=True,
connect_module=connect_module,
commenter_options={"db_driver": False},
)
mock_connection = db_integration.wrapped_connection(mock_connect, {}, {})
cursor = mock_connection.cursor()
cursor.executemany("Select 1;")
self.assertRegex(
cursor.query,
r"Select 1 /\*dbapi_level='1.0',dbapi_threadsafety='unknown',driver_paramstyle='unknown',libpq_version=123,traceparent='\d{1,2}-[a-zA-Z0-9_]{32}-[a-zA-Z0-9_]{16}-\d{1,2}'\*/;",
)
spans_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans_list), 1)
span = spans_list[0]
self.assertEqual(
span.attributes[DB_STATEMENT],
"Select 1;",
)
def test_executemany_comment_non_pep_249_compliant_stmt_enabled(self):
class MockConnectModule:
def __getattr__(self, name):
if name == "__name__":
return "test"
if name == "__version__":
return mock.MagicMock()
if name == "__libpq_version__":
return 123
raise AttributeError("attribute missing")
connect_module = MockConnectModule()
db_integration = dbapi.DatabaseApiIntegration(
"instrumenting_module_test_name",
"postgresql",
enable_commenter=True,
connect_module=connect_module,
commenter_options={"db_driver": False},
enable_attribute_commenter=True,
)
mock_connection = db_integration.wrapped_connection(mock_connect, {}, {})
cursor = mock_connection.cursor()
cursor.executemany("Select 1;")
self.assertRegex(
cursor.query,
r"Select 1 /\*dbapi_level='1.0',dbapi_threadsafety='unknown',driver_paramstyle='unknown',libpq_version=123,traceparent='\d{1,2}-[a-zA-Z0-9_]{32}-[a-zA-Z0-9_]{16}-\d{1,2}'\*/;",
)
spans_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans_list), 1)
span = spans_list[0]
self.assertRegex(
span.attributes[DB_STATEMENT],
r"Select 1 /\*dbapi_level='1.0',dbapi_threadsafety='unknown',driver_paramstyle='unknown',libpq_version=123,traceparent='\d{1,2}-[a-zA-Z0-9_]{32}-[a-zA-Z0-9_]{16}-\d{1,2}'\*/;",
)
def test_executemany_comment_stmt_enabled_matches_db_statement_attribute(
self,
):
connect_module = mock.MagicMock()
connect_module.__version__ = mock.MagicMock()
connect_module.pq.version.return_value = 123
connect_module.apilevel = 123
connect_module.threadsafety = 123
connect_module.paramstyle = "test"
db_integration = dbapi.DatabaseApiIntegration(
"instrumenting_module_test_name",
"postgresql",
enable_commenter=True,
commenter_options={"db_driver": False, "dbapi_level": False},
connect_module=connect_module,
enable_attribute_commenter=True,
)
mock_connection = db_integration.wrapped_connection(mock_connect, {}, {})
cursor = mock_connection.cursor()
cursor.executemany("Select 1;")
self.assertRegex(
cursor.query,
r"Select 1 /\*dbapi_threadsafety=123,driver_paramstyle='test',libpq_version=123,traceparent='\d{1,2}-[a-zA-Z0-9_]{32}-[a-zA-Z0-9_]{16}-\d{1,2}'\*/;",
)
spans_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans_list), 1)
span = spans_list[0]
self.assertRegex(
span.attributes[DB_STATEMENT],
r"Select 1 /\*dbapi_threadsafety=123,driver_paramstyle='test',libpq_version=123,traceparent='\d{1,2}-[a-zA-Z0-9_]{32}-[a-zA-Z0-9_]{16}-\d{1,2}'\*/",
)
cursor_span_id = re.search(r"[a-zA-Z0-9_]{16}", cursor.query).group()
db_statement_span_id = re.search(r"[a-zA-Z0-9_]{16}", span.attributes[DB_STATEMENT]).group()
self.assertEqual(cursor_span_id, db_statement_span_id)
def test_compatible_build_version_psycopg2_libpq(self):
connect_module = mock.MagicMock()
connect_module.__name__ = "test"
connect_module.__version__ = mock.MagicMock()
connect_module.pq.version.side_effect = AttributeError
connect_module.__libpq_version__ = 123
connect_module.apilevel = 123
connect_module.threadsafety = 123
connect_module.paramstyle = "test"
db_integration = dbapi.DatabaseApiIntegration(
"instrumenting_module_test_name",
"postgresql",
enable_commenter=True,
commenter_options={"db_driver": False, "dbapi_level": False},
connect_module=connect_module,
)
mock_connection = db_integration.wrapped_connection(mock_connect, {}, {})
cursor = mock_connection.cursor()
cursor.executemany("Select 1;")
self.assertRegex(
cursor.query,
r"Select 1 /\*dbapi_threadsafety=123,driver_paramstyle='test',libpq_version=123,traceparent='\d{1,2}-[a-zA-Z0-9_]{32}-[a-zA-Z0-9_]{16}-\d{1,2}'\*/;",
)
spans_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans_list), 1)
span = spans_list[0]
self.assertEqual(
span.attributes[DB_STATEMENT],
"Select 1;",
)
def test_compatible_build_version_psycopg_libpq(self):
connect_module = mock.MagicMock()
connect_module.__name__ = "test"
connect_module.__version__ = mock.MagicMock()
connect_module.pq.version.return_value = 123
connect_module.apilevel = 123
connect_module.threadsafety = 123
connect_module.paramstyle = "test"
db_integration = dbapi.DatabaseApiIntegration(
"instrumenting_module_test_name",
"postgresql",
enable_commenter=True,
commenter_options={"db_driver": False, "dbapi_level": False},
connect_module=connect_module,
)
mock_connection = db_integration.wrapped_connection(mock_connect, {}, {})
cursor = mock_connection.cursor()
cursor.executemany("Select 1;")
self.assertRegex(
cursor.query,
r"Select 1 /\*dbapi_threadsafety=123,driver_paramstyle='test',libpq_version=123,traceparent='\d{1,2}-[a-zA-Z0-9_]{32}-[a-zA-Z0-9_]{16}-\d{1,2}'\*/;",
)
spans_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans_list), 1)
span = spans_list[0]
self.assertEqual(
span.attributes[DB_STATEMENT],
"Select 1;",
)
def test_no_libpq_version_when_we_dont_instrument_the_root_module(
self,
):
connect_module = mock.MagicMock()
connect_module.__name__ = "test"
connect_module.__version__ = mock.MagicMock()
connect_module.pq.version.side_effect = AttributeError
connect_module.__libpq_version__ = None
connect_module.apilevel = 123
connect_module.threadsafety = 123
connect_module.paramstyle = "test"
db_integration = dbapi.DatabaseApiIntegration(
"instrumenting_module_test_name",
"postgresql",
enable_commenter=True,
commenter_options={"db_driver": False, "dbapi_level": False},
connect_module=connect_module,
enable_attribute_commenter=True,
)
mock_connection = db_integration.wrapped_connection(mock_connect, {}, {})
cursor = mock_connection.cursor()
cursor.executemany("Select 1;")
self.assertRegex(
cursor.query,
r"Select 1 /\*dbapi_threadsafety=123,driver_paramstyle='test',traceparent='\d{1,2}-[a-zA-Z0-9_]{32}-[a-zA-Z0-9_]{16}-\d{1,2}'\*/;",
)
spans_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans_list), 1)
span = spans_list[0]
self.assertRegex(
span.attributes[DB_STATEMENT],
r"Select 1 /\*dbapi_threadsafety=123,driver_paramstyle='test',traceparent='\d{1,2}-[a-zA-Z0-9_]{32}-[a-zA-Z0-9_]{16}-\d{1,2}'\*/;",
)
def test_executemany_psycopg2_integration_comment(self):
connect_module = mock.MagicMock()
connect_module.__name__ = "psycopg2"
connect_module.__version__ = "1.2.3"
connect_module.pq.version.side_effect = AttributeError
connect_module.__libpq_version__ = 123
connect_module.apilevel = 123
connect_module.threadsafety = 123
connect_module.paramstyle = "test"
db_integration = dbapi.DatabaseApiIntegration(
"instrumenting_module_test_name",
"postgresql",
enable_commenter=True,
commenter_options={"db_driver": True, "dbapi_level": False},
connect_module=connect_module,
)
mock_connection = db_integration.wrapped_connection(mock_connect, {}, {})
cursor = mock_connection.cursor()
cursor.executemany("Select 1;")
self.assertRegex(
cursor.query,
r"Select 1 /\*db_driver='psycopg2%%3A1.2.3',dbapi_threadsafety=123,driver_paramstyle='test',libpq_version=123,traceparent='\d{1,2}-[a-zA-Z0-9_]{32}-[a-zA-Z0-9_]{16}-\d{1,2}'\*/;",
)
spans_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans_list), 1)
span = spans_list[0]
self.assertEqual(
span.attributes[DB_STATEMENT],
"Select 1;",
)
def test_executemany_psycopg2_integration_comment_stmt_enabled(self):
connect_module = mock.MagicMock()
connect_module.__name__ = "psycopg2"
connect_module.__version__ = "1.2.3"
connect_module.pq.version.side_effect = AttributeError
connect_module.__libpq_version__ = 123
connect_module.apilevel = 123
connect_module.threadsafety = 123
connect_module.paramstyle = "test"
db_integration = dbapi.DatabaseApiIntegration(
"instrumenting_module_test_name",
"postgresql",
enable_commenter=True,
commenter_options={"db_driver": True, "dbapi_level": False},
connect_module=connect_module,
enable_attribute_commenter=True,
)
mock_connection = db_integration.wrapped_connection(mock_connect, {}, {})
cursor = mock_connection.cursor()
cursor.executemany("Select 1;")
self.assertRegex(
cursor.query,
r"Select 1 /\*db_driver='psycopg2%%3A1.2.3',dbapi_threadsafety=123,driver_paramstyle='test',libpq_version=123,traceparent='\d{1,2}-[a-zA-Z0-9_]{32}-[a-zA-Z0-9_]{16}-\d{1,2}'\*/;",
)
spans_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans_list), 1)
span = spans_list[0]
self.assertRegex(
span.attributes[DB_STATEMENT],
r"Select 1 /\*db_driver='psycopg2%%3A1.2.3',dbapi_threadsafety=123,driver_paramstyle='test',libpq_version=123,traceparent='\d{1,2}-[a-zA-Z0-9_]{32}-[a-zA-Z0-9_]{16}-\d{1,2}'\*/;",
)
def test_executemany_psycopg_integration_comment(self):
connect_module = mock.MagicMock()
connect_module.__name__ = "psycopg"
connect_module.__version__ = "1.2.3"
connect_module.pq.version.return_value = 123
connect_module.apilevel = 123
connect_module.threadsafety = 123
connect_module.paramstyle = "test"
db_integration = dbapi.DatabaseApiIntegration(
"instrumenting_module_test_name",
"postgresql",
enable_commenter=True,
commenter_options={"db_driver": True, "dbapi_level": False},
connect_module=connect_module,
)
mock_connection = db_integration.wrapped_connection(mock_connect, {}, {})
cursor = mock_connection.cursor()
cursor.executemany("Select 1;")
self.assertRegex(
cursor.query,
r"Select 1 /\*db_driver='psycopg%%3A1.2.3',dbapi_threadsafety=123,driver_paramstyle='test',libpq_version=123,traceparent='\d{1,2}-[a-zA-Z0-9_]{32}-[a-zA-Z0-9_]{16}-\d{1,2}'\*/;",
)
spans_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans_list), 1)
span = spans_list[0]
self.assertEqual(
span.attributes[DB_STATEMENT],
"Select 1;",
)
def test_executemany_psycopg_integration_comment_stmt_enabled(self):
connect_module = mock.MagicMock()
connect_module.__name__ = "psycopg"
connect_module.__version__ = "1.2.3"
connect_module.pq.version.return_value = 123
connect_module.apilevel = 123
connect_module.threadsafety = 123
connect_module.paramstyle = "test"
db_integration = dbapi.DatabaseApiIntegration(
"instrumenting_module_test_name",
"postgresql",
enable_commenter=True,
commenter_options={"db_driver": True, "dbapi_level": False},
connect_module=connect_module,
enable_attribute_commenter=True,
)
mock_connection = db_integration.wrapped_connection(mock_connect, {}, {})
cursor = mock_connection.cursor()
cursor.executemany("Select 1;")
self.assertRegex(
cursor.query,
r"Select 1 /\*db_driver='psycopg%%3A1.2.3',dbapi_threadsafety=123,driver_paramstyle='test',libpq_version=123,traceparent='\d{1,2}-[a-zA-Z0-9_]{32}-[a-zA-Z0-9_]{16}-\d{1,2}'\*/;",
)
spans_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans_list), 1)
span = spans_list[0]
self.assertRegex(
span.attributes[DB_STATEMENT],
r"Select 1 /\*db_driver='psycopg%%3A1.2.3',dbapi_threadsafety=123,driver_paramstyle='test',libpq_version=123,traceparent='\d{1,2}-[a-zA-Z0-9_]{32}-[a-zA-Z0-9_]{16}-\d{1,2}'\*/;",
)
def test_executemany_mysqlconnector_integration_comment(self):
connect_module = mock.MagicMock()
connect_module.__name__ = "mysql.connector"
connect_module.__version__ = "1.2.3"
connect_module.apilevel = 123
connect_module.threadsafety = 123
connect_module.paramstyle = "test"
db_integration = dbapi.DatabaseApiIntegration(
"instrumenting_module_test_name",
"mysql",
enable_commenter=True,
commenter_options={"db_driver": True, "dbapi_level": False},
connect_module=connect_module,
)
mock_connection = db_integration.wrapped_connection(mock_connect, {}, {})
cursor = mock_connection.cursor()
cursor.executemany("Select 1;")
self.assertRegex(
cursor.query,
r"Select 1 /\*db_driver='mysql.connector%%3A1.2.3',dbapi_threadsafety=123,driver_paramstyle='test',mysql_client_version='1.2.3',traceparent='\d{1,2}-[a-zA-Z0-9_]{32}-[a-zA-Z0-9_]{16}-\d{1,2}'\*/;",
)
spans_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans_list), 1)
span = spans_list[0]
self.assertEqual(
span.attributes[DB_STATEMENT],
"Select 1;",
)
def test_executemany_mysqlconnector_integration_comment_stmt_enabled(self):
connect_module = mock.MagicMock()
connect_module.__name__ = "mysql.connector"
connect_module.__version__ = "1.2.3"
connect_module.apilevel = 123
connect_module.threadsafety = 123
connect_module.paramstyle = "test"
db_integration = dbapi.DatabaseApiIntegration(
"instrumenting_module_test_name",
"mysql",
enable_commenter=True,
commenter_options={"db_driver": True, "dbapi_level": False},
connect_module=connect_module,
enable_attribute_commenter=True,
)
mock_connection = db_integration.wrapped_connection(mock_connect, {}, {})
cursor = mock_connection.cursor()
cursor.executemany("Select 1;")
self.assertRegex(
cursor.query,
r"Select 1 /\*db_driver='mysql.connector%%3A1.2.3',dbapi_threadsafety=123,driver_paramstyle='test',mysql_client_version='1.2.3',traceparent='\d{1,2}-[a-zA-Z0-9_]{32}-[a-zA-Z0-9_]{16}-\d{1,2}'\*/;",
)
spans_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans_list), 1)
span = spans_list[0]
self.assertRegex(
span.attributes[DB_STATEMENT],
r"Select 1 /\*db_driver='mysql.connector%%3A1.2.3',dbapi_threadsafety=123,driver_paramstyle='test',mysql_client_version='1.2.3',traceparent='\d{1,2}-[a-zA-Z0-9_]{32}-[a-zA-Z0-9_]{16}-\d{1,2}'\*/;",
)
@mock.patch("opentelemetry.instrumentation.dbapi.util_version")
def test_executemany_mysqlclient_integration_comment(
self,
mock_dbapi_util_version,
):
mock_dbapi_util_version.return_value = "1.2.3"
connect_module = mock.MagicMock()
connect_module.__name__ = "MySQLdb"
connect_module.__version__ = "1.2.3"
connect_module.apilevel = 123
connect_module.threadsafety = 123
connect_module.paramstyle = "test"
connect_module._mysql = mock.MagicMock()
connect_module._mysql.get_client_info = mock.MagicMock(return_value="123")
db_integration = dbapi.DatabaseApiIntegration(
"instrumenting_module_test_name",
"mysql",
enable_commenter=True,
commenter_options={"db_driver": True, "dbapi_level": False},
connect_module=connect_module,
)
mock_connection = db_integration.wrapped_connection(mock_connect, {}, {})
cursor = mock_connection.cursor()
cursor.executemany("Select 1;")
self.assertRegex(
cursor.query,
r"Select 1 /\*db_driver='MySQLdb%%3A1.2.3',dbapi_threadsafety=123,driver_paramstyle='test',mysql_client_version='123',traceparent='\d{1,2}-[a-zA-Z0-9_]{32}-[a-zA-Z0-9_]{16}-\d{1,2}'\*/;",
)
spans_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans_list), 1)
span = spans_list[0]
self.assertEqual(
span.attributes[DB_STATEMENT],
"Select 1;",
)
@mock.patch("opentelemetry.instrumentation.dbapi.util_version")
def test_executemany_mysqlclient_integration_comment_stmt_enabled(
self,
mock_dbapi_util_version,
):
mock_dbapi_util_version.return_value = "1.2.3"
connect_module = mock.MagicMock()
connect_module.__name__ = "MySQLdb"
connect_module.__version__ = "1.2.3"
connect_module.apilevel = 123
connect_module.threadsafety = 123
connect_module.paramstyle = "test"
connect_module._mysql = mock.MagicMock()
connect_module._mysql.get_client_info = mock.MagicMock(return_value="123")
db_integration = dbapi.DatabaseApiIntegration(
"instrumenting_module_test_name",
"mysql",
enable_commenter=True,
commenter_options={"db_driver": True, "dbapi_level": False},
connect_module=connect_module,
enable_attribute_commenter=True,
)
mock_connection = db_integration.wrapped_connection(mock_connect, {}, {})
cursor = mock_connection.cursor()
cursor.executemany("Select 1;")
self.assertRegex(
cursor.query,
r"Select 1 /\*db_driver='MySQLdb%%3A1.2.3',dbapi_threadsafety=123,driver_paramstyle='test',mysql_client_version='123',traceparent='\d{1,2}-[a-zA-Z0-9_]{32}-[a-zA-Z0-9_]{16}-\d{1,2}'\*/;",
)
spans_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans_list), 1)
span = spans_list[0]
self.assertRegex(
span.attributes[DB_STATEMENT],
r"Select 1 /\*db_driver='MySQLdb%%3A1.2.3',dbapi_threadsafety=123,driver_paramstyle='test',mysql_client_version='123',traceparent='\d{1,2}-[a-zA-Z0-9_]{32}-[a-zA-Z0-9_]{16}-\d{1,2}'\*/;",
)
def test_executemany_pymysql_integration_comment(self):
connect_module = mock.MagicMock()
connect_module.__name__ = "pymysql"
connect_module.__version__ = "1.2.3"
connect_module.apilevel = 123
connect_module.threadsafety = 123
connect_module.paramstyle = "test"
connect_module.get_client_info = mock.MagicMock(return_value="123")
db_integration = dbapi.DatabaseApiIntegration(
"instrumenting_module_test_name",
"mysql",
enable_commenter=True,
commenter_options={"db_driver": True, "dbapi_level": False},
connect_module=connect_module,
)
mock_connection = db_integration.wrapped_connection(mock_connect, {}, {})
cursor = mock_connection.cursor()
cursor.executemany("Select 1;")
self.assertRegex(
cursor.query,
r"Select 1 /\*db_driver='pymysql%%3A1.2.3',dbapi_threadsafety=123,driver_paramstyle='test',mysql_client_version='123',traceparent='\d{1,2}-[a-zA-Z0-9_]{32}-[a-zA-Z0-9_]{16}-\d{1,2}'\*/;",
)
spans_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans_list), 1)
span = spans_list[0]
self.assertEqual(
span.attributes[DB_STATEMENT],
"Select 1;",
)
def test_executemany_pymysql_integration_comment_stmt_enabled(self):
connect_module = mock.MagicMock()
connect_module.__name__ = "pymysql"
connect_module.__version__ = "1.2.3"
connect_module.apilevel = 123
connect_module.threadsafety = 123
connect_module.paramstyle = "test"
connect_module.get_client_info = mock.MagicMock(return_value="123")
db_integration = dbapi.DatabaseApiIntegration(
"instrumenting_module_test_name",
"mysql",
enable_commenter=True,
commenter_options={"db_driver": True, "dbapi_level": False},
connect_module=connect_module,
enable_attribute_commenter=True,
)
mock_connection = db_integration.wrapped_connection(mock_connect, {}, {})
cursor = mock_connection.cursor()
cursor.executemany("Select 1;")
self.assertRegex(
cursor.query,
r"Select 1 /\*db_driver='pymysql%%3A1.2.3',dbapi_threadsafety=123,driver_paramstyle='test',mysql_client_version='123',traceparent='\d{1,2}-[a-zA-Z0-9_]{32}-[a-zA-Z0-9_]{16}-\d{1,2}'\*/;",
)
spans_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans_list), 1)
span = spans_list[0]
self.assertRegex(
span.attributes[DB_STATEMENT],
r"Select 1 /\*db_driver='pymysql%%3A1.2.3',dbapi_threadsafety=123,driver_paramstyle='test',mysql_client_version='123',traceparent='\d{1,2}-[a-zA-Z0-9_]{32}-[a-zA-Z0-9_]{16}-\d{1,2}'\*/;",
)
def test_executemany_flask_integration_comment(self):
connect_module = mock.MagicMock()
connect_module.__name__ = "test"
connect_module.pq.version.return_value = 123
connect_module.apilevel = 123
connect_module.threadsafety = 123
connect_module.paramstyle = "test"
db_integration = dbapi.DatabaseApiIntegration(
"instrumenting_module_test_name",
"postgresql",
enable_commenter=True,
commenter_options={"db_driver": False, "dbapi_level": False},
connect_module=connect_module,
)
current_context = context.get_current()
sqlcommenter_context = context.set_value("SQLCOMMENTER_ORM_TAGS_AND_VALUES", {"flask": 1}, current_context)
token = context.attach(sqlcommenter_context)
mock_connection = db_integration.wrapped_connection(mock_connect, {}, {})
cursor = mock_connection.cursor()
cursor.executemany("Select 1;")
self.assertRegex(
cursor.query,
r"Select 1 /\*dbapi_threadsafety=123,driver_paramstyle='test',flask=1,libpq_version=123,traceparent='\d{1,2}-[a-zA-Z0-9_]{32}-[a-zA-Z0-9_]{16}-\d{1,2}'\*/;",
)
spans_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans_list), 1)
span = spans_list[0]
self.assertEqual(
span.attributes[DB_STATEMENT],
"Select 1;",
)
context.detach(token)
def test_executemany_flask_integration_comment_stmt_enabled(self):
connect_module = mock.MagicMock()
connect_module.__name__ = "test"
connect_module.__version__ = mock.MagicMock()
connect_module.pq.version.return_value = 123
connect_module.apilevel = 123
connect_module.threadsafety = 123
connect_module.paramstyle = "test"
db_integration = dbapi.DatabaseApiIntegration(
"instrumenting_module_test_name",
"postgresql",
enable_commenter=True,
commenter_options={"db_driver": False, "dbapi_level": False},
connect_module=connect_module,
enable_attribute_commenter=True,
)
current_context = context.get_current()
sqlcommenter_context = context.set_value("SQLCOMMENTER_ORM_TAGS_AND_VALUES", {"flask": 1}, current_context)
token = context.attach(sqlcommenter_context)
mock_connection = db_integration.wrapped_connection(mock_connect, {}, {})
cursor = mock_connection.cursor()
cursor.executemany("Select 1;")
self.assertRegex(
cursor.query,
r"Select 1 /\*dbapi_threadsafety=123,driver_paramstyle='test',flask=1,libpq_version=123,traceparent='\d{1,2}-[a-zA-Z0-9_]{32}-[a-zA-Z0-9_]{16}-\d{1,2}'\*/;",
)
spans_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans_list), 1)
span = spans_list[0]
self.assertRegex(
span.attributes[DB_STATEMENT],
r"Select 1 /\*dbapi_threadsafety=123,driver_paramstyle='test',flask=1,libpq_version=123,traceparent='\d{1,2}-[a-zA-Z0-9_]{32}-[a-zA-Z0-9_]{16}-\d{1,2}'\*/;",
)
context.detach(token)
def test_callproc(self):
db_integration = dbapi.DatabaseApiIntegration("instrumenting_module_test_name", "testcomponent")
mock_connection = db_integration.wrapped_connection(mock_connect, {}, {})
cursor = mock_connection.cursor()
cursor.callproc("Test stored procedure")
spans_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans_list), 1)
span = spans_list[0]
self.assertEqual(
span.attributes[DB_STATEMENT],
"Test stored procedure",
)
@mock.patch("opentelemetry.instrumentation.dbapi")
def test_wrap_connect(self, mock_dbapi):
dbapi.wrap_connect(self.tracer, mock_dbapi, "connect", "-")
connection = mock_dbapi.connect()
self.assertEqual(mock_dbapi.connect.call_count, 1)
self.assertIsInstance(connection.__wrapped__, mock.Mock) # pylint: disable=no-member
@mock.patch("opentelemetry.instrumentation.dbapi")
def test_unwrap_connect(self, mock_dbapi):
dbapi.wrap_connect(self.tracer, mock_dbapi, "connect", "-")
connection = mock_dbapi.connect()
self.assertEqual(mock_dbapi.connect.call_count, 1)
dbapi.unwrap_connect(mock_dbapi, "connect")
connection = mock_dbapi.connect()
self.assertEqual(mock_dbapi.connect.call_count, 2)
self.assertIsInstance(connection, mock.Mock)
def test_instrument_connection(self):
mocked_conn = MockConnection("dbname", "999", "dbhost", "dbuser")
# Avoid get_attributes failing because can't concatenate mock
connection2 = dbapi.instrument_connection("instrumenting_module_test_name", mocked_conn, "dbname")
self.assertIs(connection2.__wrapped__, mocked_conn) # pylint: disable=no-member
@mock.patch("opentelemetry.instrumentation.dbapi.DatabaseApiIntegration")
def test_instrument_connection_kwargs_defaults(self, mock_dbapiint):
mocked_conn = MockConnection("dbname", "999", "dbhost", "dbuser")
dbapi.instrument_connection("instrumenting_module_test_name", mocked_conn, "foo")
kwargs = mock_dbapiint.call_args[1]
self.assertEqual(kwargs["connection_attributes"], None)
self.assertEqual(kwargs["version"], "")
self.assertEqual(kwargs["tracer_provider"], None)
self.assertEqual(kwargs["capture_parameters"], False)
self.assertEqual(kwargs["enable_commenter"], False)
self.assertEqual(kwargs["commenter_options"], None)
self.assertEqual(kwargs["connect_module"], None)
self.assertEqual(kwargs["enable_attribute_commenter"], False)
@mock.patch("opentelemetry.instrumentation.dbapi.DatabaseApiIntegration")
def test_instrument_connection_kwargs_provided(self, mock_dbapiint):
mocked_conn = MockConnection("dbname", "999", "dbhost", "dbuser")
mock_tracer_provider = mock.MagicMock()
mock_connect_module = mock.MagicMock()
dbapi.instrument_connection(
"instrumenting_module_test_name",
mocked_conn,
"foo",
connection_attributes={"foo": "bar"},
version="test",
tracer_provider=mock_tracer_provider,
capture_parameters=True,
enable_commenter=True,
commenter_options={"foo": "bar"},
connect_module=mock_connect_module,
enable_attribute_commenter=True,
)
kwargs = mock_dbapiint.call_args[1]
self.assertEqual(kwargs["connection_attributes"], {"foo": "bar"})
self.assertEqual(kwargs["version"], "test")
self.assertIs(kwargs["tracer_provider"], mock_tracer_provider)
self.assertEqual(kwargs["capture_parameters"], True)
self.assertEqual(kwargs["enable_commenter"], True)
self.assertEqual(kwargs["commenter_options"], {"foo": "bar"})
self.assertIs(kwargs["connect_module"], mock_connect_module)
self.assertEqual(kwargs["enable_attribute_commenter"], True)
def test_instrument_connection_db_api_integration_factory(self):
mocked_conn = MockConnection("dbname", "999", "dbhost", "dbuser")
class DBApiIntegrationTestClass(dbapi.DatabaseApiIntegration):
pass
conn = dbapi.instrument_connection(
"instrumenting_module_test_name",
mocked_conn,
"dbsystem",
db_api_integration_factory=DBApiIntegrationTestClass,
)
self.assertIsInstance(conn._self_db_api_integration, DBApiIntegrationTestClass)
def test_uninstrument_connection(self):
mocked_conn = MockConnection("dbname", "999", "dbhost", "dbuser")
connection2 = dbapi.instrument_connection("instrumenting_module_test_name", mocked_conn, "-")
self.assertIs(connection2.__wrapped__, mocked_conn) # pylint: disable=no-member
connection3 = dbapi.uninstrument_connection(connection2)
self.assertIs(connection3, mocked_conn)
with self.assertLogs(level=logging.WARNING):
connection4 = dbapi.uninstrument_connection(mocked_conn)
self.assertIs(connection4, mocked_conn)
def test_non_string_sql_conversion(self):
"""Test that non-string SQL statements are converted to strings before adding comments."""
# Create a mock connect_module with required attributes
connect_module = mock.MagicMock()
connect_module.__name__ = "test"
connect_module.__version__ = "1.0"
connect_module.pq.version.return_value = 123
connect_module.apilevel = "2.0"
connect_module.threadsafety = 1
connect_module.paramstyle = "test"
db_integration = dbapi.DatabaseApiIntegration(
"testname",
"postgresql",
enable_commenter=True,
connect_module=connect_module,
)
mock_connection = db_integration.wrapped_connection(mock_connect, {}, {})
cursor = mock_connection.cursor()
input_sql = mock.MagicMock(as_string=lambda conn: "SELECT 2")
expected_sql = "SELECT 2"
cursor.executemany(input_sql)
# Extract the SQL part (before the comment)
actual_sql = cursor.query.split("/*")[0].strip()
self.assertEqual(actual_sql, expected_sql)
spans_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans_list), 1)
def test_capture_mysql_version_primary_success(self):
connect_module = mock.MagicMock()
connect_module.__name__ = "mysql.connector"
connect_module.__version__ = "2.2.9"
db_integration = dbapi.DatabaseApiIntegration(
"instrumenting_module_test_name",
"mysql",
enable_commenter=True,
connect_module=connect_module,
)
mock_cursor = mock.MagicMock()
mock_cursor._cnx._cmysql.get_client_info.return_value = "8.0.32"
mock_connection = db_integration.wrapped_connection(mock_connect, {}, {})
cursor = mock_connection.cursor()
cursor._cnx = mock_cursor._cnx
cursor.execute("SELECT 1;")
mock_cursor._cnx._cmysql.get_client_info.assert_called_once()
self.assertEqual(db_integration.commenter_data["mysql_client_version"], "8.0.32")
def test_capture_mysql_version_fallback_success(self):
connect_module = mock.MagicMock()
connect_module.__name__ = "mysql.connector"
connect_module.__version__ = "2.2.9"
db_integration = dbapi.DatabaseApiIntegration(
"instrumenting_module_test_name",
"mysql",
enable_commenter=True,
connect_module=connect_module,
)
mock_cursor = mock.MagicMock()
mock_cursor._cnx._cmysql.get_client_info.side_effect = AttributeError("Primary method failed")
mock_cursor._connection._cmysql.get_client_info.return_value = "8.0.33"
mock_connection = db_integration.wrapped_connection(mock_connect, {}, {})
cursor = mock_connection.cursor()
cursor._cnx = mock_cursor._cnx
cursor._connection = mock_cursor._connection
cursor.execute("SELECT 1;")
mock_cursor._cnx._cmysql.get_client_info.assert_called_once()
mock_cursor._connection._cmysql.get_client_info.assert_called_once()
self.assertEqual(db_integration.commenter_data["mysql_client_version"], "8.0.33")
@mock.patch("opentelemetry.instrumentation.dbapi._logger")
def test_capture_mysql_version_fallback(self, mock_logger):
connect_module = mock.MagicMock()
connect_module.__name__ = "mysql.connector"
connect_module.__version__ = "2.2.9"
db_integration = dbapi.DatabaseApiIntegration(
"instrumenting_module_test_name",
"mysql",
enable_commenter=True,
connect_module=connect_module,
)
mock_cursor = mock.MagicMock()
mock_cursor._cnx._cmysql.get_client_info.side_effect = AttributeError("Primary method failed")
mock_cursor._connection._cmysql.get_client_info.side_effect = AttributeError("Fallback method failed")
mock_connection = db_integration.wrapped_connection(mock_connect, {}, {})
cursor = mock_connection.cursor()
cursor._cnx = mock_cursor._cnx
cursor._connection = mock_cursor._connection
cursor.execute("SELECT 1;")
mock_cursor._cnx._cmysql.get_client_info.assert_called_once()
mock_cursor._connection._cmysql.get_client_info.assert_called_once()
mock_logger.debug.assert_called_once()
self.assertEqual(db_integration.commenter_data["mysql_client_version"], "unknown")
@pytest.mark.skipif(
sys.version_info < (3, 14),
reason="requires Python 3.14+ for t-strings",
)
def test_t_string_span_attributes(self):
# pylint: disable-next=import-outside-toplevel,no-name-in-module
from string.templatelib import ( # noqa: PLC0415
Interpolation,
Template,
)
connection_props = _get_default_connection_props()
connection_attributes = _get_default_connection_attributes()
db_integration = dbapi.DatabaseApiIntegration(
"instrumenting_module_test_name",
"testcomponent",
connection_attributes,
)
mock_connection = db_integration.wrapped_connection(mock_connect, {}, connection_props)
cursor = mock_connection.cursor()
value = 42
template = Template("SELECT ", Interpolation(value, "value"), " FROM foo")
cursor.execute(template)
spans_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans_list), 1)
span = spans_list[0]
self.assertEqual(span.name, "SELECT")
self.assertEqual(span.attributes[DB_STATEMENT], "SELECT {value} FROM foo")
@pytest.mark.skipif(
sys.version_info < (3, 14),
reason="requires Python 3.14+ for t-strings",
)
def test_t_string_commenter(self):
# pylint: disable-next=import-outside-toplevel,no-name-in-module
from string.templatelib import Interpolation, Template # noqa: PLC0415
connect_module = mock.MagicMock()
connect_module.__name__ = "test"
connect_module.__version__ = mock.MagicMock()
connect_module.pq.version.return_value = 123
connect_module.apilevel = 123
connect_module.threadsafety = 123
connect_module.paramstyle = "test"
db_integration = dbapi.DatabaseApiIntegration(
"instrumenting_module_test_name",
"postgresql",
enable_commenter=True,
commenter_options={"db_driver": False, "dbapi_level": False},
connect_module=connect_module,
)
mock_connection = db_integration.wrapped_connection(mock_connect, {}, {})
cursor = mock_connection.cursor()
value = 42
template = Template("SELECT ", Interpolation(value, "value"), " FROM foo")
cursor.executemany(template)
self.assertIsInstance(cursor.query, Template)
self.assertRegex(
cursor.query.strings[-1],
r" FROM foo /\*dbapi_threadsafety=123,driver_paramstyle='test',"
r"libpq_version=123,traceparent='\d{1,2}-[a-zA-Z0-9_]{32}-[a-zA-Z0-9_]{16}-\d{1,2}'\*/",
)
spans_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans_list), 1)
span = spans_list[0]
self.assertEqual(span.name, "SELECT")
self.assertEqual(span.attributes[DB_STATEMENT], "SELECT {value} FROM foo")
# pylint: disable=unused-argument
def mock_connect(*args, **kwargs):
database = kwargs.get("database")
server_host = kwargs.get("server_host")
server_port = kwargs.get("server_port")
user = kwargs.get("user")
return MockConnection(database, server_port, server_host, user)
class MockConnection:
def __init__(self, database, server_port, server_host, user):
self.database = database
self.server_port = server_port
self.server_host = server_host
self.user = user
# pylint: disable=no-self-use
def cursor(self):
return MockCursor()
class MockCursor:
def __init__(self) -> None:
self.query = ""
self.params = None
self.connection = None
self.rowcount = -1
# Mock mysql.connector modules and method
self._cnx = mock.MagicMock()
self._cnx._cmysql = mock.MagicMock()
self._cnx._cmysql.get_client_info = mock.MagicMock(return_value="1.2.3")
self._items = []
# pylint: disable=unused-argument, no-self-use
def execute(self, query, params=None, throw_exception=False, rowcount=-1):
if throw_exception:
# pylint: disable=broad-exception-raised
raise Exception("Test Exception")
self.rowcount = rowcount
def __iter__(self):
yield from self._items
# pylint: disable=unused-argument, no-self-use
def executemany(self, query, params=None, throw_exception=False, rowcount=-1):
if throw_exception:
# pylint: disable=broad-exception-raised
raise Exception("Test Exception")
self.query = query
self.params = params
self.rowcount = rowcount
# pylint: disable=unused-argument, no-self-use
def callproc(self, query, params=None, throw_exception=False, rowcount=-1):
if throw_exception:
# pylint: disable=broad-exception-raised
raise Exception("Test Exception")
self.rowcount = rowcount
opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-django/ 0000775 0000000 0000000 00000000000 15270700723 0032405 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-django/LICENSE 0000664 0000000 0000000 00000026135 15270700723 0033421 0 ustar 00root root 0000000 0000000 Apache License
Version 2.0, January 2004
http://www.apache.org/licenses/
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opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-django/README.rst 0000664 0000000 0000000 00000001367 15270700723 0034103 0 ustar 00root root 0000000 0000000 OpenTelemetry Django Tracing
============================
|pypi|
.. |pypi| image:: https://badge.fury.io/py/opentelemetry-instrumentation-django.svg
:target: https://pypi.org/project/opentelemetry-instrumentation-django/
This library allows tracing requests for Django applications.
Installation
------------
::
pip install opentelemetry-instrumentation-django
References
----------
* `Django `_
* `OpenTelemetry Instrumentation for Django `_
* `OpenTelemetry Project `_
* `OpenTelemetry Python Examples `_
pyproject.toml 0000664 0000000 0000000 00000003353 15270700723 0035246 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-django [build-system]
requires = ["hatchling"]
build-backend = "hatchling.build"
[project]
name = "opentelemetry-instrumentation-django"
dynamic = ["version"]
description = "OpenTelemetry Instrumentation for Django"
readme = "README.rst"
license = "Apache-2.0"
requires-python = ">=3.10"
authors = [
{ name = "OpenTelemetry Authors", email = "cncf-opentelemetry-contributors@lists.cncf.io" },
]
classifiers = [
"Development Status :: 4 - Beta",
"Intended Audience :: Developers",
"License :: OSI Approved :: Apache Software License",
"Programming Language :: Python",
"Programming Language :: Python :: 3",
"Programming Language :: Python :: 3.10",
"Programming Language :: Python :: 3.11",
"Programming Language :: Python :: 3.12",
"Programming Language :: Python :: 3.13",
"Programming Language :: Python :: 3.14",
]
dependencies = [
"opentelemetry-api ~= 1.12",
"opentelemetry-instrumentation == 0.66b2",
"opentelemetry-instrumentation-wsgi == 0.66b2",
"opentelemetry-semantic-conventions == 0.66b2",
"opentelemetry-util-http == 0.66b2",
]
[project.optional-dependencies]
asgi = [
"opentelemetry-instrumentation-asgi == 0.66b2",
]
instruments = [
"django >= 2.0",
]
[project.entry-points.opentelemetry_instrumentor]
django = "opentelemetry.instrumentation.django:DjangoInstrumentor"
[project.urls]
Homepage = "https://github.com/open-telemetry/opentelemetry-python-contrib/tree/main/instrumentation/opentelemetry-instrumentation-django"
Repository = "https://github.com/open-telemetry/opentelemetry-python-contrib"
[tool.hatch.version]
path = "src/opentelemetry/instrumentation/django/version.py"
[tool.hatch.build.targets.sdist]
include = [
"/src",
"/tests",
]
[tool.hatch.build.targets.wheel]
packages = ["src/opentelemetry"]
opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-django/src/ 0000775 0000000 0000000 00000000000 15270700723 0033174 5 ustar 00root root 0000000 0000000 opentelemetry/ 0000775 0000000 0000000 00000000000 15270700723 0036011 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-django/src instrumentation/ 0000775 0000000 0000000 00000000000 15270700723 0041254 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-django/src/opentelemetry django/ 0000775 0000000 0000000 00000000000 15270700723 0042516 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-django/src/opentelemetry/instrumentation __init__.py 0000664 0000000 0000000 00000053341 15270700723 0044635 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-django/src/opentelemetry/instrumentation/django # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
"""
Instrument `django`_ to trace Django applications.
.. _django: https://pypi.org/project/django/
Usage
-----
.. code:: python
from opentelemetry.instrumentation.django import DjangoInstrumentor
DjangoInstrumentor().instrument()
ASGI support
------------
When running a Django application through ASGI, install the optional ASGI
dependency so this instrumentation can use the ASGI context helpers:
.. code:: console
pip install "opentelemetry-instrumentation-django[asgi]"
Then instrument Django the same way as a WSGI application.
Configuration
-------------
Exclude lists
*************
To exclude certain URLs from tracking, set the environment variable ``OTEL_PYTHON_DJANGO_EXCLUDED_URLS``
(or ``OTEL_PYTHON_EXCLUDED_URLS`` to cover all instrumentations) to a string of comma delimited regexes that match the
URLs.
For example,
::
export OTEL_PYTHON_DJANGO_EXCLUDED_URLS="client/.*/info,healthcheck"
will exclude requests such as ``https://site/client/123/info`` and ``https://site/xyz/healthcheck``.
Request attributes
******************
To extract attributes from Django's request object and use them as span attributes, set the environment variable
``OTEL_PYTHON_DJANGO_TRACED_REQUEST_ATTRS`` to a comma delimited list of request attribute names.
For example,
::
export OTEL_PYTHON_DJANGO_TRACED_REQUEST_ATTRS='path_info,content_type'
will extract the ``path_info`` and ``content_type`` attributes from every traced request and add them as span attributes.
* `Django Request object reference `_
Request and Response hooks
**************************
This instrumentation supports request and response hooks. These are functions that get called
right after a span is created for a request and right before the span is finished for the response.
The hooks can be configured as follows:
.. code:: python
from opentelemetry.instrumentation.django import DjangoInstrumentor
def request_hook(span, request):
pass
def response_hook(span, request, response):
pass
DjangoInstrumentor().instrument(request_hook=request_hook, response_hook=response_hook)
* `Django Request object `_
* `Django Response object `_
Adding attributes from middleware context
#########################################
In many Django applications, certain request attributes become available only *after*
specific middlewares have executed. For example:
- ``django.contrib.auth.middleware.AuthenticationMiddleware`` populates ``request.user``
- ``django.contrib.sites.middleware.CurrentSiteMiddleware`` populates ``request.site``
Because the OpenTelemetry instrumentation creates the span **before** Django middlewares run,
these attributes are **not yet available** in the ``request_hook`` stage.
Therefore, such attributes should be safely attached in the **response_hook**, which executes
after Django finishes processing the request (and after all middlewares have completed).
Example: Attaching the authenticated user and current site to the span:
.. code:: python
def response_hook(span, request, response):
# Attach user information if available
if request.user.is_authenticated:
span.set_attribute("enduser.id", request.user.pk)
span.set_attribute("enduser.username", request.user.get_username())
# Attach current site (if provided by CurrentSiteMiddleware)
if hasattr(request, "site"):
span.set_attribute("site.id", getattr(request.site, "pk", None))
span.set_attribute("site.domain", getattr(request.site, "domain", None))
DjangoInstrumentor().instrument(response_hook=response_hook)
This ensures that middleware-dependent context (like user or site information) is properly
recorded once Django’s middleware stack has finished execution.
Custom Django middleware can also attach arbitrary data to the ``request`` object,
which can later be included as span attributes in the ``response_hook``.
* `Django middleware reference `_
Best practices
##############
- Use **response_hook** (not request_hook) when accessing attributes added by Django middlewares.
- Common middleware-provided attributes include:
- ``request.user`` (AuthenticationMiddleware)
- ``request.site`` (CurrentSiteMiddleware)
- Avoid adding large or sensitive data (e.g., passwords, session tokens, PII) to spans.
- Use **namespaced attribute keys**, e.g., ``enduser.*``, ``site.*``, or ``custom.*``, for clarity.
- Hooks should execute quickly — avoid blocking or long-running operations.
- Hooks can be safely combined with OpenTelemetry **Context propagation** or **Baggage**
for consistent tracing across services.
* `OpenTelemetry semantic conventions `_
Middleware execution order
##########################
In Django’s request lifecycle, the OpenTelemetry `request_hook` is executed before
the first middleware runs. Therefore:
- At `request_hook` time → only the bare `HttpRequest` object is available.
- After middlewares → `request.user`, `request.site` etc. become available.
- At `response_hook` time → all middlewares (including authentication and site middlewares)
have already run, making it the correct place to attach these attributes.
Developers who need to trace attributes from middlewares should always use `response_hook`
to ensure complete and accurate span data.
Capture HTTP request and response headers
*****************************************
You can configure the agent to capture specified HTTP headers as span attributes, according to the
`semantic conventions `_.
Request headers
***************
To capture HTTP request headers as span attributes, set the environment variable
``OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_REQUEST`` to a comma delimited list of HTTP header names.
For example,
::
export OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_REQUEST="content-type,custom_request_header"
will extract ``content-type`` and ``custom_request_header`` from the request headers and add them as span attributes.
Request header names in Django are case-insensitive. So, giving the header name as ``CUStom-Header`` in the environment
variable will capture the header named ``custom-header``.
Regular expressions may also be used to match multiple headers that correspond to the given pattern. For example:
::
export OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_REQUEST="Accept.*,X-.*"
Would match all request headers that start with ``Accept`` and ``X-``.
To capture all request headers, set ``OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_REQUEST`` to ``".*"``.
::
export OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_REQUEST=".*"
The name of the added span attribute will follow the format ``http.request.header.`` where ````
is the normalized HTTP header name (lowercase, with ``-`` replaced by ``_``). The value of the attribute will be a
single item list containing all the header values.
For example:
``http.request.header.custom_request_header = [","]``
Response headers
****************
To capture HTTP response headers as span attributes, set the environment variable
``OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_RESPONSE`` to a comma delimited list of HTTP header names.
For example,
::
export OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_RESPONSE="content-type,custom_response_header"
will extract ``content-type`` and ``custom_response_header`` from the response headers and add them as span attributes.
Response header names in Django are case-insensitive. So, giving the header name as ``CUStom-Header`` in the environment
variable will capture the header named ``custom-header``.
Regular expressions may also be used to match multiple headers that correspond to the given pattern. For example:
::
export OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_RESPONSE="Content.*,X-.*"
Would match all response headers that start with ``Content`` and ``X-``.
To capture all response headers, set ``OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_RESPONSE`` to ``".*"``.
::
export OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_RESPONSE=".*"
The name of the added span attribute will follow the format ``http.response.header.`` where ````
is the normalized HTTP header name (lowercase, with ``-`` replaced by ``_``). The value of the attribute will be a
single item list containing all the header values.
For example:
``http.response.header.custom_response_header = [","]``
Sanitizing headers
******************
In order to prevent storing sensitive data such as personally identifiable information (PII), session keys, passwords,
etc, set the environment variable ``OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SANITIZE_FIELDS``
to a comma delimited list of HTTP header names to be sanitized. Regexes may be used, and all header names will be
matched in a case-insensitive manner.
For example,
::
export OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SANITIZE_FIELDS=".*session.*,set-cookie"
will replace the value of headers such as ``session-id`` and ``set-cookie`` with ``[REDACTED]`` in the span.
Note:
The environment variable names used to capture HTTP headers are still experimental, and thus are subject to change.
SQLCommenter
************
You can optionally enable sqlcommenter which enriches the query with contextual
information. Queries made after setting up trace integration with sqlcommenter
enabled will have configurable key-value pairs appended to them, e.g.
``Users().objects.all()`` will result in
``"select * from auth_users; /*traceparent=00-01234567-abcd-01*/"``. This
supports context propagation between database client and server when database log
records are enabled. For more information, see:
* `Semantic Conventions - Database Spans `_
* `sqlcommenter `_
.. code:: python
from opentelemetry.instrumentation.django import DjangoInstrumentor
DjangoInstrumentor().instrument(is_sql_commentor_enabled=True)
Warning:
Duplicate sqlcomments may be appended to the sqlquery log if DjangoInstrumentor
sqlcommenter is enabled in addition to sqlcommenter for an active instrumentation
of a database driver or object-relational mapper (ORM) in the same database client
stack. For example, if psycopg2 driver is used and Psycopg2Instrumentor has
sqlcommenter enabled, then both DjangoInstrumentor and Psycopg2Instrumentor will
append comments to the query statement.
SQLCommenter with commenter_options
***********************************
The key-value pairs appended to the query can be configured using
variables in Django ``settings.py``. When sqlcommenter is enabled, all
available KVs/tags are calculated by default, i.e. ``True`` for each. The
``settings.py`` values support *opting out* of specific KVs.
Available settings.py commenter options
#######################################
We can configure the tags to be appended to the sqlquery log by adding below variables to
``settings.py``, e.g. ``SQLCOMMENTER_WITH_FRAMEWORK = False``
+-------------------------------------+-----------------------------------------------------------+---------------------------------------------------------------------------+
| ``settings.py`` variable | Description | Example |
+=====================================+===========================================================+===========================================================================+
| ``SQLCOMMENTER_WITH_FRAMEWORK`` | Django framework name with version (URL encoded). | ``framework='django%%%%3A4.2.0'`` |
+-------------------------------------+-----------------------------------------------------------+---------------------------------------------------------------------------+
| ``SQLCOMMENTER_WITH_CONTROLLER`` | Django controller/view name that handles the request. | ``controller='index'`` |
+-------------------------------------+-----------------------------------------------------------+---------------------------------------------------------------------------+
| ``SQLCOMMENTER_WITH_ROUTE`` | URL path pattern that handles the request. | ``route='polls/'`` |
+-------------------------------------+-----------------------------------------------------------+---------------------------------------------------------------------------+
| ``SQLCOMMENTER_WITH_APP_NAME`` | Django app name that handles the request. | ``app_name='polls'`` |
+-------------------------------------+-----------------------------------------------------------+---------------------------------------------------------------------------+
| ``SQLCOMMENTER_WITH_OPENTELEMETRY`` | OpenTelemetry context as traceparent at time of query. | ``traceparent='00-fd720cffceba94bbf75940ff3caaf3cc-4fd1a2bdacf56388-01'`` |
+-------------------------------------+-----------------------------------------------------------+---------------------------------------------------------------------------+
| ``SQLCOMMENTER_WITH_DB_DRIVER`` | Database driver name used by Django. | ``db_driver='django.db.backends.postgresql'`` |
+-------------------------------------+-----------------------------------------------------------+---------------------------------------------------------------------------+
API
---
"""
from collections.abc import Collection
from logging import getLogger
from os import environ
from django.conf import settings
from django.core.exceptions import ImproperlyConfigured
from opentelemetry.instrumentation._semconv import (
HTTP_DURATION_HISTOGRAM_BUCKETS_NEW,
_get_schema_url,
_OpenTelemetrySemanticConventionStability,
_OpenTelemetryStabilitySignalType,
_report_new,
_report_old,
)
from opentelemetry.instrumentation.django.environment_variables import (
OTEL_PYTHON_DJANGO_INSTRUMENT,
)
from opentelemetry.instrumentation.django.middleware.otel_middleware import (
_DjangoMiddleware,
)
from opentelemetry.instrumentation.django.package import _instruments
from opentelemetry.instrumentation.django.version import __version__
from opentelemetry.instrumentation.instrumentor import BaseInstrumentor
from opentelemetry.metrics import get_meter
from opentelemetry.semconv._incubating.metrics.http_metrics import (
create_http_server_active_requests,
)
from opentelemetry.semconv.metrics import MetricInstruments
from opentelemetry.semconv.metrics.http_metrics import (
HTTP_SERVER_REQUEST_DURATION,
)
from opentelemetry.trace import get_tracer
from opentelemetry.util.http import get_excluded_urls, parse_excluded_urls
_excluded_urls_from_env = get_excluded_urls("DJANGO")
_django_middleware_setting = "MIDDLEWARE"
_logger = getLogger(__name__)
def _get_django_otel_middleware_position(middleware_length, default_middleware_position=0):
otel_position = environ.get("OTEL_PYTHON_DJANGO_MIDDLEWARE_POSITION")
try:
middleware_position = int(otel_position)
except (ValueError, TypeError):
_logger.debug(
"Invalid OTEL_PYTHON_DJANGO_MIDDLEWARE_POSITION value: (%s). Using default position: %d.",
otel_position,
default_middleware_position,
)
middleware_position = default_middleware_position
if middleware_position < 0 or middleware_position > middleware_length:
_logger.debug(
"Middleware position %d is out of range (0-%d). Using 0 as the position",
middleware_position,
middleware_length,
)
middleware_position = 0
return middleware_position
class DjangoInstrumentor(BaseInstrumentor):
"""An instrumentor for Django
See `BaseInstrumentor`
"""
_opentelemetry_middleware = ".".join([_DjangoMiddleware.__module__, _DjangoMiddleware.__qualname__])
_sql_commenter_middleware = "opentelemetry.instrumentation.django.middleware.sqlcommenter_middleware.SqlCommenter"
def instrumentation_dependencies(self) -> Collection[str]:
return _instruments
def _instrument(self, **kwargs):
# FIXME this is probably a pattern that will show up in the rest of the
# ext. Find a better way of implementing this.
if environ.get(OTEL_PYTHON_DJANGO_INSTRUMENT) == "False":
return
# initialize semantic conventions opt-in if needed
_OpenTelemetrySemanticConventionStability._initialize()
sem_conv_opt_in_mode = _OpenTelemetrySemanticConventionStability._get_opentelemetry_stability_opt_in_mode(
_OpenTelemetryStabilitySignalType.HTTP,
)
tracer_provider = kwargs.get("tracer_provider")
meter_provider = kwargs.get("meter_provider")
_excluded_urls = kwargs.get("excluded_urls")
tracer = get_tracer(
__name__,
__version__,
tracer_provider=tracer_provider,
schema_url=_get_schema_url(sem_conv_opt_in_mode),
)
meter = get_meter(
__name__,
__version__,
meter_provider=meter_provider,
schema_url=_get_schema_url(sem_conv_opt_in_mode),
)
_DjangoMiddleware._sem_conv_opt_in_mode = sem_conv_opt_in_mode
_DjangoMiddleware._tracer = tracer
_DjangoMiddleware._meter = meter
_DjangoMiddleware._excluded_urls = (
_excluded_urls_from_env if _excluded_urls is None else parse_excluded_urls(_excluded_urls)
)
_DjangoMiddleware._otel_request_hook = kwargs.pop("request_hook", None)
_DjangoMiddleware._otel_response_hook = kwargs.pop("response_hook", None)
_DjangoMiddleware._duration_histogram_old = None
if _report_old(sem_conv_opt_in_mode):
_DjangoMiddleware._duration_histogram_old = meter.create_histogram(
name=MetricInstruments.HTTP_SERVER_DURATION,
unit="ms",
description="Measures the duration of inbound HTTP requests.",
)
_DjangoMiddleware._duration_histogram_new = None
if _report_new(sem_conv_opt_in_mode):
_DjangoMiddleware._duration_histogram_new = meter.create_histogram(
name=HTTP_SERVER_REQUEST_DURATION,
description="Duration of HTTP server requests.",
unit="s",
explicit_bucket_boundaries_advisory=HTTP_DURATION_HISTOGRAM_BUCKETS_NEW,
)
_DjangoMiddleware._active_request_counter = create_http_server_active_requests(meter)
# This can not be solved, but is an inherent problem of this approach:
# the order of middleware entries matters, and here you have no control
# on that:
# https://docs.djangoproject.com/en/3.0/topics/http/middleware/#activating-middleware
# https://docs.djangoproject.com/en/3.0/ref/middleware/#middleware-ordering
settings_middleware = []
try:
settings_middleware = getattr(settings, _django_middleware_setting, [])
except ImproperlyConfigured as exception:
_logger.debug(
"DJANGO_SETTINGS_MODULE environment variable not configured. Defaulting to empty settings: %s",
exception,
)
settings.configure()
settings_middleware = getattr(settings, _django_middleware_setting, [])
except ModuleNotFoundError as exception:
_logger.debug(
"DJANGO_SETTINGS_MODULE points to a non-existent module. Defaulting to empty settings: %s",
exception,
)
settings.configure()
settings_middleware = getattr(settings, _django_middleware_setting, [])
# Django allows to specify middlewares as a tuple, so we convert this tuple to a
# list, otherwise we wouldn't be able to call append/remove
if isinstance(settings_middleware, tuple):
settings_middleware = list(settings_middleware)
is_sql_commentor_enabled = kwargs.pop("is_sql_commentor_enabled", None)
middleware_position = _get_django_otel_middleware_position(
len(settings_middleware), kwargs.pop("middleware_position", 0)
)
if is_sql_commentor_enabled:
settings_middleware.insert(middleware_position, self._sql_commenter_middleware)
settings_middleware.insert(middleware_position, self._opentelemetry_middleware)
setattr(settings, _django_middleware_setting, settings_middleware)
def _uninstrument(self, **kwargs):
settings_middleware = getattr(settings, _django_middleware_setting, None)
# FIXME This is starting to smell like trouble. We have 2 mechanisms
# that may make this condition be True, one implemented in
# BaseInstrumentor and another one implemented in _instrument. Both
# stop _instrument from running and thus, settings_middleware not being
# set.
if settings_middleware is None or (self._opentelemetry_middleware not in settings_middleware):
return
settings_middleware.remove(self._opentelemetry_middleware)
setattr(settings, _django_middleware_setting, settings_middleware)
environment_variables.py 0000664 0000000 0000000 00000000215 15270700723 0047462 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-django/src/opentelemetry/instrumentation/django # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
OTEL_PYTHON_DJANGO_INSTRUMENT = "OTEL_PYTHON_DJANGO_INSTRUMENT"
middleware/ 0000775 0000000 0000000 00000000000 15270700723 0044633 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-django/src/opentelemetry/instrumentation/django __init__.py 0000664 0000000 0000000 00000000000 15270700723 0046732 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-django/src/opentelemetry/instrumentation/django/middleware otel_middleware.py 0000664 0000000 0000000 00000040236 15270700723 0050352 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-django/src/opentelemetry/instrumentation/django/middleware # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
import types
from collections.abc import Callable
from logging import getLogger
from time import time
from timeit import default_timer
from django import VERSION as django_version
from django.http import HttpRequest, HttpResponse
from opentelemetry.context import detach
from opentelemetry.instrumentation._semconv import (
_filter_semconv_active_request_count_attr,
_filter_semconv_duration_attrs,
_report_new,
_report_old,
_server_active_requests_count_attrs_new,
_server_active_requests_count_attrs_old,
_server_duration_attrs_new,
_server_duration_attrs_old,
_StabilityMode,
)
from opentelemetry.instrumentation.propagators import (
get_global_response_propagator,
)
from opentelemetry.instrumentation.utils import (
_start_internal_or_server_span,
extract_attributes_from_object,
)
from opentelemetry.instrumentation.wsgi import (
add_response_attributes,
wsgi_getter,
)
from opentelemetry.instrumentation.wsgi import (
collect_custom_request_headers_attributes as wsgi_collect_custom_request_headers_attributes,
)
from opentelemetry.instrumentation.wsgi import (
collect_custom_response_headers_attributes as wsgi_collect_custom_response_headers_attributes,
)
from opentelemetry.instrumentation.wsgi import (
collect_request_attributes as wsgi_collect_request_attributes,
)
from opentelemetry.semconv._incubating.attributes.http_attributes import (
HTTP_TARGET,
)
from opentelemetry.semconv.attributes.http_attributes import HTTP_ROUTE
from opentelemetry.trace import Span, SpanKind, use_span
from opentelemetry.util.http import (
OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SANITIZE_FIELDS,
OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_REQUEST,
OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_RESPONSE,
SanitizeValue,
get_custom_headers,
get_excluded_urls,
get_traced_request_attrs,
normalise_request_header_name,
normalise_response_header_name,
sanitize_method,
)
try:
from django.core.urlresolvers import ( # pylint: disable=no-name-in-module
Resolver404,
resolve,
)
except ImportError:
from django.urls import Resolver404, resolve
DJANGO_3_0 = django_version >= (3, 0)
if DJANGO_3_0:
from django.core.handlers.asgi import ASGIRequest
else:
ASGIRequest = None
# try/except block exclusive for optional ASGI imports.
try:
from opentelemetry.instrumentation.asgi import (
asgi_getter,
asgi_setter,
set_status_code,
)
from opentelemetry.instrumentation.asgi import (
collect_custom_headers_attributes as asgi_collect_custom_headers_attributes,
)
from opentelemetry.instrumentation.asgi import (
collect_request_attributes as asgi_collect_request_attributes,
)
_is_asgi_supported = True
except ImportError:
asgi_getter = None
asgi_collect_request_attributes = None
set_status_code = None
_is_asgi_supported = False
_logger = getLogger(__name__)
def _is_asgi_request(request: HttpRequest) -> bool:
return ASGIRequest is not None and isinstance(request, ASGIRequest)
class _DjangoMiddleware:
"""Django Middleware for OpenTelemetry"""
_environ_activation_key = "opentelemetry-instrumentor-django.activation_key"
_environ_token = "opentelemetry-instrumentor-django.token"
_environ_span_key = "opentelemetry-instrumentor-django.span_key"
_environ_exception_key = "opentelemetry-instrumentor-django.exception_key"
_environ_active_request_attr_key = "opentelemetry-instrumentor-django.active_request_attr_key"
_environ_duration_attr_key = "opentelemetry-instrumentor-django.duration_attr_key"
_environ_timer_key = "opentelemetry-instrumentor-django.timer_key"
_traced_request_attrs = get_traced_request_attrs("DJANGO")
_excluded_urls = get_excluded_urls("DJANGO")
_tracer = None
_meter = None
_duration_histogram_old = None
_duration_histogram_new = None
_active_request_counter = None
_sem_conv_opt_in_mode = _StabilityMode.DEFAULT
_otel_request_hook: Callable[[Span, HttpRequest], None] = None
_otel_response_hook: Callable[[Span, HttpRequest, HttpResponse], None] = None
def __init__(self, get_response):
self.get_response = get_response
def __call__(self, request):
self.process_request(request)
response = self.get_response(request)
return self.process_response(request, response)
@staticmethod
def _get_span_name(request):
method = sanitize_method(request.method.strip())
if method == "_OTHER":
return "HTTP"
try:
if request.resolver_match:
match = request.resolver_match
else:
match = resolve(request.path)
if hasattr(match, "route") and match.route:
return f"{method} {match.route}"
if hasattr(match, "url_name") and match.url_name:
return f"{method} {match.url_name}"
return request.method
except Resolver404:
return request.method
# pylint: disable=too-many-locals
# pylint: disable=too-many-branches
def process_request(self, request):
# request.META is a dictionary containing all available HTTP headers
# Read more about request.META here:
# https://docs.djangoproject.com/en/3.0/ref/request-response/#django.http.HttpRequest.META
if self._excluded_urls.url_disabled(request.build_absolute_uri("?")):
return
is_asgi_request = _is_asgi_request(request)
if not _is_asgi_supported and is_asgi_request:
return
# pylint:disable=W0212
request._otel_start_time = time()
request_meta = request.META
if is_asgi_request:
carrier = request.scope
carrier_getter = asgi_getter
collect_request_attributes = asgi_collect_request_attributes
else:
carrier = request_meta
carrier_getter = wsgi_getter
collect_request_attributes = wsgi_collect_request_attributes
attributes = collect_request_attributes(
carrier,
self._sem_conv_opt_in_mode,
)
span, token = _start_internal_or_server_span(
tracer=self._tracer,
span_name=self._get_span_name(request),
start_time=request_meta.get("opentelemetry-instrumentor-django.starttime_key"),
context_carrier=carrier,
context_getter=carrier_getter,
attributes=attributes,
)
active_requests_count_attrs = _parse_active_request_count_attrs(
attributes,
self._sem_conv_opt_in_mode,
)
request.META[self._environ_active_request_attr_key] = active_requests_count_attrs
# Pass all of attributes to duration key because we will filter during response
request.META[self._environ_duration_attr_key] = attributes
self._active_request_counter.add(1, active_requests_count_attrs)
if span.is_recording():
attributes = extract_attributes_from_object(request, self._traced_request_attrs, attributes)
if is_asgi_request:
# ASGI requests include extra attributes in request.scope.headers.
attributes = extract_attributes_from_object(
types.SimpleNamespace(
**{
name.decode("latin1"): value.decode("latin1")
for name, value in request.scope.get("headers", [])
}
),
self._traced_request_attrs,
attributes,
)
if span.is_recording() and span.kind == SpanKind.SERVER:
attributes.update(
asgi_collect_custom_headers_attributes(
carrier,
SanitizeValue(
get_custom_headers(OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SANITIZE_FIELDS)
),
get_custom_headers(OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_REQUEST),
normalise_request_header_name,
)
)
else:
if span.is_recording() and span.kind == SpanKind.SERVER:
custom_attributes = wsgi_collect_custom_request_headers_attributes(carrier)
if len(custom_attributes) > 0:
span.set_attributes(custom_attributes)
for key, value in attributes.items():
span.set_attribute(key, value)
activation = use_span(span, end_on_exit=True)
activation.__enter__() # pylint: disable=unnecessary-dunder-call
request_start_time = default_timer()
request.META[self._environ_timer_key] = request_start_time
request.META[self._environ_activation_key] = activation
request.META[self._environ_span_key] = span
if token:
request.META[self._environ_token] = token
if _DjangoMiddleware._otel_request_hook:
try:
_DjangoMiddleware._otel_request_hook( # pylint: disable=not-callable
span, request
)
except Exception: # pylint: disable=broad-exception-caught
# Raising an exception here would leak the request span since process_response
# would not be called. Log the exception instead.
_logger.exception("Exception raised by request_hook")
# pylint: disable=unused-argument
def process_view(self, request, view_func, *args, **kwargs):
# Process view is executed before the view function, here we get the
# route template from request.resolver_match. It is not set yet in process_request
if self._excluded_urls.url_disabled(request.build_absolute_uri("?")):
return
if self._environ_activation_key in request.META.keys() and self._environ_span_key in request.META.keys():
span = request.META[self._environ_span_key]
match = getattr(request, "resolver_match", None)
if match:
route = getattr(match, "route", None)
if route:
if span.is_recording():
# http.route is present for both old and new semconv
span.set_attribute(HTTP_ROUTE, route)
duration_attrs = request.META[self._environ_duration_attr_key]
if _report_old(self._sem_conv_opt_in_mode):
duration_attrs[HTTP_TARGET] = route
if _report_new(self._sem_conv_opt_in_mode):
duration_attrs[HTTP_ROUTE] = route
def process_exception(self, request, exception):
if self._excluded_urls.url_disabled(request.build_absolute_uri("?")):
return
if self._environ_activation_key in request.META.keys():
request.META[self._environ_exception_key] = exception
# pylint: disable=too-many-branches
# pylint: disable=too-many-locals
# pylint: disable=too-many-statements
def process_response(self, request, response):
if self._excluded_urls.url_disabled(request.build_absolute_uri("?")):
return response
is_asgi_request = _is_asgi_request(request)
if not _is_asgi_supported and is_asgi_request:
return response
activation = request.META.pop(self._environ_activation_key, None)
span = request.META.pop(self._environ_span_key, None)
active_requests_count_attrs = request.META.pop(self._environ_active_request_attr_key, None)
duration_attrs = request.META.pop(self._environ_duration_attr_key, None)
request_start_time = request.META.pop(self._environ_timer_key, None)
if activation and span:
if is_asgi_request:
set_status_code(
span,
response.status_code,
metric_attributes=duration_attrs,
sem_conv_opt_in_mode=self._sem_conv_opt_in_mode,
)
if span.is_recording() and span.kind == SpanKind.SERVER:
custom_headers = {}
for key, value in response.items():
asgi_setter.set(custom_headers, key, value)
custom_res_attributes = asgi_collect_custom_headers_attributes(
custom_headers,
SanitizeValue(get_custom_headers(OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SANITIZE_FIELDS)),
get_custom_headers(OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_RESPONSE),
normalise_response_header_name,
)
for key, value in custom_res_attributes.items():
span.set_attribute(key, value)
else:
add_response_attributes(
span,
f"{response.status_code} {response.reason_phrase}",
response.items(),
duration_attrs=duration_attrs,
sem_conv_opt_in_mode=self._sem_conv_opt_in_mode,
)
if span.is_recording() and span.kind == SpanKind.SERVER:
custom_attributes = wsgi_collect_custom_response_headers_attributes(response.items())
if len(custom_attributes) > 0:
span.set_attributes(custom_attributes)
propagator = get_global_response_propagator()
if propagator:
propagator.inject(response)
# record any exceptions raised while processing the request
exception = request.META.pop(self._environ_exception_key, None)
if _DjangoMiddleware._otel_response_hook:
try:
_DjangoMiddleware._otel_response_hook( # pylint: disable=not-callable
span, request, response
)
except Exception: # pylint: disable=broad-exception-caught
_logger.exception("Exception raised by response_hook")
if request_start_time is not None:
duration_s = default_timer() - request_start_time
if self._duration_histogram_old:
duration_attrs_old = _parse_duration_attrs(duration_attrs, _StabilityMode.DEFAULT)
# http.target to be included in old semantic conventions
target = duration_attrs.get(HTTP_TARGET)
if target:
duration_attrs_old[HTTP_TARGET] = target
self._duration_histogram_old.record(
max(round(duration_s * 1000), 0),
duration_attrs_old,
)
if self._duration_histogram_new:
duration_attrs_new = _parse_duration_attrs(duration_attrs, _StabilityMode.HTTP)
self._duration_histogram_new.record(
max(duration_s, 0),
duration_attrs_new,
)
self._active_request_counter.add(-1, active_requests_count_attrs)
if activation and span:
if exception:
activation.__exit__(
type(exception),
exception,
getattr(exception, "__traceback__", None),
)
else:
activation.__exit__(None, None, None)
if request.META.get(self._environ_token, None) is not None:
detach(request.META.get(self._environ_token))
request.META.pop(self._environ_token)
return response
def _parse_duration_attrs(req_attrs, sem_conv_opt_in_mode=_StabilityMode.DEFAULT):
return _filter_semconv_duration_attrs(
req_attrs,
_server_duration_attrs_old,
_server_duration_attrs_new,
sem_conv_opt_in_mode,
)
def _parse_active_request_count_attrs(req_attrs, sem_conv_opt_in_mode=_StabilityMode.DEFAULT):
return _filter_semconv_active_request_count_attr(
req_attrs,
_server_active_requests_count_attrs_old,
_server_active_requests_count_attrs_new,
sem_conv_opt_in_mode,
)
sqlcommenter_middleware.py 0000664 0000000 0000000 00000006702 15270700723 0052120 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-django/src/opentelemetry/instrumentation/django/middleware # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
from contextlib import ExitStack
from logging import getLogger
from typing import Any, TypeVar
# pylint: disable=no-name-in-module
from django import conf, get_version
from django.db import connections
from opentelemetry.instrumentation.sqlcommenter_utils import _add_sql_comment
from opentelemetry.instrumentation.utils import _get_opentelemetry_values
from opentelemetry.trace.propagation.tracecontext import (
TraceContextTextMapPropagator,
)
_propagator = TraceContextTextMapPropagator()
_django_version = get_version()
_logger = getLogger(__name__)
T = TypeVar("T") # pylint: disable-msg=invalid-name
class SqlCommenter:
"""
Middleware to append a comment to each database query with details about
the framework and the execution context.
"""
def __init__(self, get_response) -> None:
self.get_response = get_response
def __call__(self, request) -> Any:
with ExitStack() as stack:
for db_alias in connections:
stack.enter_context(connections[db_alias].execute_wrapper(_QueryWrapper(request)))
return self.get_response(request)
class _QueryWrapper:
def __init__(self, request) -> None:
self.request = request
def __call__(self, execute: type[T], sql, params, many, context) -> T:
# pylint: disable-msg=too-many-locals
with_framework = getattr(conf.settings, "SQLCOMMENTER_WITH_FRAMEWORK", True)
with_controller = getattr(conf.settings, "SQLCOMMENTER_WITH_CONTROLLER", True)
with_route = getattr(conf.settings, "SQLCOMMENTER_WITH_ROUTE", True)
with_app_name = getattr(conf.settings, "SQLCOMMENTER_WITH_APP_NAME", True)
with_opentelemetry = getattr(conf.settings, "SQLCOMMENTER_WITH_OPENTELEMETRY", True)
with_db_driver = getattr(conf.settings, "SQLCOMMENTER_WITH_DB_DRIVER", True)
db_driver = context["connection"].settings_dict.get("ENGINE", "")
resolver_match = self.request.resolver_match
# Convert sql statement to string, handling psycopg2.sql.Composable object
if hasattr(sql, "as_string"):
sql = sql.as_string(context["connection"])
sql = str(sql)
sql = _add_sql_comment(
sql,
# Information about the controller.
controller=(resolver_match.view_name if resolver_match and with_controller else None),
# route is the pattern that matched a request with a controller i.e. the regex
# See https://docs.djangoproject.com/en/stable/ref/urlresolvers/#django.urls.ResolverMatch.route
# getattr() because the attribute doesn't exist in Django < 2.2.
route=(getattr(resolver_match, "route", None) if resolver_match and with_route else None),
# app_name is the application namespace for the URL pattern that matches the URL.
# See https://docs.djangoproject.com/en/stable/ref/urlresolvers/#django.urls.ResolverMatch.app_name
app_name=((resolver_match.app_name or None) if resolver_match and with_app_name else None),
# Framework centric information.
framework=f"django:{_django_version}" if with_framework else None,
# Information about the database and driver.
db_driver=db_driver if with_db_driver else None,
**_get_opentelemetry_values() if with_opentelemetry else {},
)
return execute(sql, params, many, context)
package.py 0000664 0000000 0000000 00000000211 15270700723 0044455 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-django/src/opentelemetry/instrumentation/django # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
_instruments = ("django >= 2.0",)
_supports_metrics = True
version.py 0000664 0000000 0000000 00000000144 15270700723 0044554 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-django/src/opentelemetry/instrumentation/django # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
__version__ = "0.66b2"
test-requirements-0.txt 0000664 0000000 0000000 00000000674 15270700723 0036733 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-django asgiref==3.8.1
Deprecated==1.2.14
Django==2.2.28
iniconfig==2.0.0
packaging==24.0
pluggy==1.6.0
py-cpuinfo==9.0.0
pytest==7.4.4
pytz==2024.1
sqlparse==0.5.0
tomli==2.0.1
typing_extensions==4.12.2
wrapt==1.16.0
zipp==3.19.2
setuptools==79.0.1 ; python_version >= "3.12"
-e opentelemetry-instrumentation
-e instrumentation/opentelemetry-instrumentation-wsgi
-e util/opentelemetry-util-http
-e instrumentation/opentelemetry-instrumentation-django
test-requirements-1.txt 0000664 0000000 0000000 00000000704 15270700723 0036726 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-django asgiref==3.8.1
Deprecated==1.2.14
Django==3.2.25
iniconfig==2.0.0
packaging==24.0
pluggy==1.6.0
py-cpuinfo==9.0.0
pytest==7.4.4
pytz==2024.1
sqlparse==0.5.0
tomli==2.0.1
typing_extensions==4.12.2
wrapt==1.16.0
zipp==3.19.2
-e opentelemetry-instrumentation
-e instrumentation/opentelemetry-instrumentation-wsgi
-e instrumentation/opentelemetry-instrumentation-asgi
-e util/opentelemetry-util-http
-e instrumentation/opentelemetry-instrumentation-django
test-requirements-2.txt 0000664 0000000 0000000 00000000667 15270700723 0036737 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-django asgiref==3.8.1
Deprecated==1.2.14
Django==4.2.17
iniconfig==2.0.0
packaging==24.0
pluggy==1.6.0
py-cpuinfo==9.0.0
pytest==7.4.4
sqlparse==0.5.0
tomli==2.0.1
typing_extensions==4.12.2
wrapt==1.16.0
zipp==3.19.2
-e opentelemetry-instrumentation
-e instrumentation/opentelemetry-instrumentation-wsgi
-e instrumentation/opentelemetry-instrumentation-asgi
-e util/opentelemetry-util-http
-e instrumentation/opentelemetry-instrumentation-django
test-requirements-3.txt 0000664 0000000 0000000 00000000667 15270700723 0036740 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-django asgiref==3.9.1
Deprecated==1.2.14
Django==5.2.11
iniconfig==2.0.0
packaging==24.0
pluggy==1.6.0
py-cpuinfo==9.0.0
pytest==7.4.4
sqlparse==0.5.0
tomli==2.0.1
typing_extensions==4.12.2
wrapt==1.16.0
zipp==3.19.2
-e opentelemetry-instrumentation
-e instrumentation/opentelemetry-instrumentation-wsgi
-e instrumentation/opentelemetry-instrumentation-asgi
-e util/opentelemetry-util-http
-e instrumentation/opentelemetry-instrumentation-django
opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-django/tests/ 0000775 0000000 0000000 00000000000 15270700723 0033547 5 ustar 00root root 0000000 0000000 __init__.py 0000664 0000000 0000000 00000000000 15270700723 0035567 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-django/tests test_middleware.py 0000664 0000000 0000000 00000123301 15270700723 0037216 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-django/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
# pylint: disable=E0611
# pylint: disable=too-many-lines
from sys import modules
from timeit import default_timer
from unittest.mock import Mock, patch
from django import VERSION, conf
from django.http import HttpRequest, HttpResponse
from django.test.client import Client
from django.test.utils import setup_test_environment, teardown_test_environment
from opentelemetry import trace
from opentelemetry.instrumentation._semconv import (
HTTP_DURATION_HISTOGRAM_BUCKETS_NEW,
HTTP_DURATION_HISTOGRAM_BUCKETS_OLD,
OTEL_SEMCONV_STABILITY_OPT_IN,
_OpenTelemetrySemanticConventionStability,
)
from opentelemetry.instrumentation.django import (
DjangoInstrumentor,
_DjangoMiddleware,
)
from opentelemetry.instrumentation.propagators import (
TraceResponsePropagator,
set_global_response_propagator,
)
from opentelemetry.sdk import resources
from opentelemetry.sdk.metrics.export import (
HistogramDataPoint,
NumberDataPoint,
)
from opentelemetry.sdk.trace import Span
from opentelemetry.sdk.trace.id_generator import RandomIdGenerator
from opentelemetry.test.wsgitestutil import WsgiTestBase
from opentelemetry.trace import (
SpanKind,
StatusCode,
format_span_id,
format_trace_id,
)
from opentelemetry.util.http import (
OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SANITIZE_FIELDS,
OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_REQUEST,
OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_RESPONSE,
get_excluded_urls,
get_traced_request_attrs,
)
# pylint: disable=import-error
from .views import (
error,
excluded,
excluded_noarg,
excluded_noarg2,
response_with_custom_header,
route_span_name,
traced,
traced_template,
)
DJANGO_2_0 = VERSION >= (2, 0)
DJANGO_2_2 = VERSION >= (2, 2)
DJANGO_3_0 = VERSION >= (3, 0)
if DJANGO_2_0:
from django.urls import path, re_path
else:
from django.conf.urls import url as re_path
def path(path_argument, *args, **kwargs):
return re_path(rf"^{path_argument}$", *args, **kwargs)
urlpatterns = [
re_path(r"^traced/", traced),
re_path(r"^traced_custom_header/", response_with_custom_header),
re_path(r"^route/(?P[0-9]{4})/template/$", traced_template),
re_path(r"^error/", error),
re_path(r"^excluded_arg/", excluded),
re_path(r"^excluded_noarg/", excluded_noarg),
re_path(r"^excluded_noarg2/", excluded_noarg2),
re_path(r"^span_name/([0-9]{4})/$", route_span_name),
path("", traced, name="empty"),
]
_django_instrumentor = DjangoInstrumentor()
SCOPE = "opentelemetry.instrumentation.django"
# pylint: disable=too-many-public-methods
class TestMiddleware(WsgiTestBase):
@classmethod
def setUpClass(cls):
conf.settings.configure(
ROOT_URLCONF=modules[__name__],
DATABASES={
"default": {},
"other": {},
}, # db.connections gets populated only at first test execution
)
super().setUpClass()
def setUp(self):
super().setUp()
setup_test_environment()
test_name = ""
if hasattr(self, "_testMethodName"):
test_name = self._testMethodName
sem_conv_mode = "default"
if "new_semconv" in test_name:
sem_conv_mode = "http"
elif "both_semconv" in test_name:
sem_conv_mode = "http/dup"
self.env_patch = patch.dict(
"os.environ",
{
"OTEL_PYTHON_DJANGO_EXCLUDED_URLS": "http://testserver/excluded_arg/123,excluded_noarg",
"OTEL_PYTHON_DJANGO_TRACED_REQUEST_ATTRS": "path_info,content_type,non_existing_variable",
OTEL_SEMCONV_STABILITY_OPT_IN: sem_conv_mode,
},
)
_OpenTelemetrySemanticConventionStability._initialized = False
self.env_patch.start()
_django_instrumentor.instrument()
self.exclude_patch = patch(
"opentelemetry.instrumentation.django.middleware.otel_middleware._DjangoMiddleware._excluded_urls",
get_excluded_urls("DJANGO"),
)
self.traced_patch = patch(
"opentelemetry.instrumentation.django.middleware.otel_middleware._DjangoMiddleware._traced_request_attrs",
get_traced_request_attrs("DJANGO"),
)
self.exclude_patch.start()
self.traced_patch.start()
def tearDown(self):
super().tearDown()
self.env_patch.stop()
self.exclude_patch.stop()
self.traced_patch.stop()
teardown_test_environment()
_django_instrumentor.uninstrument()
@classmethod
def tearDownClass(cls):
super().tearDownClass()
conf.settings = conf.LazySettings()
def test_middleware_added_at_position(self):
_django_instrumentor.uninstrument()
if DJANGO_2_0:
middleware = conf.settings.MIDDLEWARE
else:
middleware = conf.settings.MIDDLEWARE_CLASSES
# adding two dummy middlewares
temprory_middelware = "django.utils.deprecation.MiddlewareMixin"
middleware.append(temprory_middelware)
middleware.append(temprory_middelware)
middleware_position = 1
_django_instrumentor.instrument(middleware_position=middleware_position)
self.assertEqual(
middleware[middleware_position],
"opentelemetry.instrumentation.django.middleware.otel_middleware._DjangoMiddleware",
)
def test_middleware_added_at_position_if_wrong_position(self):
_django_instrumentor.uninstrument()
if DJANGO_2_0:
middleware = conf.settings.MIDDLEWARE
else:
middleware = conf.settings.MIDDLEWARE_CLASSES
# adding middleware
temprory_middelware = "django.utils.deprecation.MiddlewareMixin"
middleware.append(temprory_middelware)
middleware_position = 756 # wrong position out of bound of middleware length
_django_instrumentor.instrument(middleware_position=middleware_position)
self.assertEqual(
middleware[0],
"opentelemetry.instrumentation.django.middleware.otel_middleware._DjangoMiddleware",
)
def test_templated_route_get(self):
Client().get("/route/2020/template/")
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
span = spans[0]
self.assertEqual(
span.name,
("GET ^route/(?P[0-9]{4})/template/$" if DJANGO_2_2 else "GET"),
)
self.assertEqual(span.kind, SpanKind.SERVER)
self.assertEqual(span.status.status_code, StatusCode.UNSET)
self.assertEqual(span.attributes["http.method"], "GET")
self.assertEqual(
span.attributes["http.url"],
"http://testserver/route/2020/template/",
)
if DJANGO_2_2:
self.assertEqual(
span.attributes["http.route"],
"^route/(?P[0-9]{4})/template/$",
)
self.assertEqual(span.attributes["http.scheme"], "http")
self.assertEqual(span.attributes["http.status_code"], 200)
def test_traced_get(self):
Client().get("/traced/")
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
span = spans[0]
self.assertEqual(span.name, "GET ^traced/" if DJANGO_2_2 else "GET")
self.assertEqual(span.kind, SpanKind.SERVER)
self.assertEqual(span.status.status_code, StatusCode.UNSET)
self.assertEqual(span.attributes["http.method"], "GET")
self.assertEqual(
span.attributes["http.url"],
"http://testserver/traced/",
)
if DJANGO_2_2:
self.assertEqual(span.attributes["http.route"], "^traced/")
self.assertEqual(span.attributes["http.scheme"], "http")
self.assertEqual(span.attributes["http.status_code"], 200)
def test_traced_get_new_semconv(self):
Client().get("/traced/")
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
span = spans[0]
self.assertEqual(span.name, "GET ^traced/" if DJANGO_2_2 else "GET")
self.assertEqual(span.kind, SpanKind.SERVER)
self.assertEqual(span.status.status_code, StatusCode.UNSET)
self.assertEqual(span.attributes["http.request.method"], "GET")
self.assertEqual(span.attributes["url.scheme"], "http")
self.assertEqual(span.attributes["server.port"], 80)
self.assertEqual(span.attributes["client.address"], "127.0.0.1")
self.assertEqual(span.attributes["network.protocol.version"], "1.1")
if DJANGO_2_2:
self.assertEqual(span.attributes["http.route"], "^traced/")
self.assertEqual(span.attributes["http.response.status_code"], 200)
def test_traced_get_both_semconv(self):
Client().get("/traced/")
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
span = spans[0]
self.assertEqual(span.name, "GET ^traced/" if DJANGO_2_2 else "GET")
self.assertEqual(span.kind, SpanKind.SERVER)
self.assertEqual(span.status.status_code, StatusCode.UNSET)
self.assertEqual(span.attributes["http.method"], "GET")
self.assertEqual(
span.attributes["http.url"],
"http://testserver/traced/",
)
if DJANGO_2_2:
self.assertEqual(span.attributes["http.route"], "^traced/")
self.assertEqual(span.attributes["http.scheme"], "http")
self.assertEqual(span.attributes["http.status_code"], 200)
self.assertEqual(span.attributes["http.request.method"], "GET")
self.assertEqual(span.attributes["url.scheme"], "http")
self.assertEqual(span.attributes["server.port"], 80)
self.assertEqual(span.attributes["client.address"], "127.0.0.1")
self.assertEqual(span.attributes["network.protocol.version"], "1.1")
if DJANGO_2_2:
self.assertEqual(span.attributes["http.route"], "^traced/")
self.assertEqual(span.attributes["http.response.status_code"], 200)
def test_not_recording(self):
mock_tracer = Mock()
mock_span = Mock()
mock_span.is_recording.return_value = False
mock_tracer.start_span.return_value = mock_span
with patch("opentelemetry.trace.get_tracer") as tracer:
tracer.return_value = mock_tracer
Client().get("/traced/")
self.assertFalse(mock_span.is_recording())
self.assertTrue(mock_span.is_recording.called)
self.assertFalse(mock_span.set_attribute.called)
self.assertFalse(mock_span.set_status.called)
def test_empty_path(self):
Client().get("/")
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
span = spans[0]
self.assertEqual(span.name, "GET empty")
def test_traced_post(self):
Client().post("/traced/")
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
span = spans[0]
self.assertEqual(span.name, "POST ^traced/" if DJANGO_2_2 else "POST")
self.assertEqual(span.kind, SpanKind.SERVER)
self.assertEqual(span.status.status_code, StatusCode.UNSET)
self.assertEqual(span.attributes["http.method"], "POST")
self.assertEqual(
span.attributes["http.url"],
"http://testserver/traced/",
)
if DJANGO_2_2:
self.assertEqual(span.attributes["http.route"], "^traced/")
self.assertEqual(span.attributes["http.scheme"], "http")
self.assertEqual(span.attributes["http.status_code"], 200)
def test_traced_post_new_semconv(self):
Client().post("/traced/")
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
span = spans[0]
self.assertEqual(span.name, "POST ^traced/" if DJANGO_2_2 else "POST")
self.assertEqual(span.kind, SpanKind.SERVER)
self.assertEqual(span.status.status_code, StatusCode.UNSET)
self.assertEqual(span.attributes["http.request.method"], "POST")
self.assertEqual(span.attributes["url.scheme"], "http")
self.assertEqual(span.attributes["server.port"], 80)
self.assertEqual(span.attributes["client.address"], "127.0.0.1")
self.assertEqual(span.attributes["network.protocol.version"], "1.1")
if DJANGO_2_2:
self.assertEqual(span.attributes["http.route"], "^traced/")
self.assertEqual(span.attributes["http.response.status_code"], 200)
def test_traced_post_both_semconv(self):
Client().post("/traced/")
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
span = spans[0]
self.assertEqual(span.name, "POST ^traced/" if DJANGO_2_2 else "POST")
self.assertEqual(span.kind, SpanKind.SERVER)
self.assertEqual(span.status.status_code, StatusCode.UNSET)
self.assertEqual(span.attributes["http.method"], "POST")
self.assertEqual(
span.attributes["http.url"],
"http://testserver/traced/",
)
self.assertEqual(span.attributes["http.scheme"], "http")
self.assertEqual(span.attributes["http.status_code"], 200)
self.assertEqual(span.attributes["http.request.method"], "POST")
self.assertEqual(span.attributes["url.scheme"], "http")
self.assertEqual(span.attributes["server.port"], 80)
self.assertEqual(span.attributes["client.address"], "127.0.0.1")
self.assertEqual(span.attributes["network.protocol.version"], "1.1")
if DJANGO_2_2:
self.assertEqual(span.attributes["http.route"], "^traced/")
self.assertEqual(span.attributes["http.response.status_code"], 200)
def test_error(self):
with self.assertRaises(ValueError):
Client().get("/error/")
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
span = spans[0]
self.assertEqual(span.name, "GET ^error/" if DJANGO_2_2 else "GET")
self.assertEqual(span.kind, SpanKind.SERVER)
self.assertEqual(span.status.status_code, StatusCode.ERROR)
self.assertEqual(span.attributes["http.method"], "GET")
self.assertEqual(
span.attributes["http.url"],
"http://testserver/error/",
)
if DJANGO_2_2:
self.assertEqual(span.attributes["http.route"], "^error/")
self.assertEqual(span.attributes["http.scheme"], "http")
self.assertEqual(span.attributes["http.status_code"], 500)
self.assertEqual(len(span.events), 1)
event = span.events[0]
self.assertEqual(event.name, "exception")
self.assertEqual(event.attributes["exception.type"], "ValueError")
self.assertEqual(event.attributes["exception.message"], "error")
def test_error_new_semconv(self):
with self.assertRaises(ValueError):
Client().get("/error/")
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
span = spans[0]
self.assertEqual(span.name, "GET ^error/" if DJANGO_2_2 else "GET")
self.assertEqual(span.kind, SpanKind.SERVER)
self.assertEqual(span.status.status_code, StatusCode.ERROR)
self.assertEqual(span.attributes["http.request.method"], "GET")
if DJANGO_2_2:
self.assertEqual(span.attributes["http.route"], "^error/")
self.assertEqual(span.attributes["url.scheme"], "http")
self.assertEqual(span.attributes["http.response.status_code"], 500)
self.assertEqual(len(span.events), 1)
event = span.events[0]
self.assertEqual(event.name, "exception")
self.assertEqual(event.attributes["exception.type"], "ValueError")
self.assertEqual(event.attributes["exception.message"], "error")
self.assertEqual(span.attributes["error.type"], "500")
def test_error_both_semconv(self):
with self.assertRaises(ValueError):
Client().get("/error/")
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
span = spans[0]
self.assertEqual(span.name, "GET ^error/" if DJANGO_2_2 else "GET")
self.assertEqual(span.kind, SpanKind.SERVER)
self.assertEqual(span.status.status_code, StatusCode.ERROR)
self.assertEqual(span.attributes["http.method"], "GET")
self.assertEqual(
span.attributes["http.url"],
"http://testserver/error/",
)
if DJANGO_2_2:
self.assertEqual(span.attributes["http.route"], "^error/")
self.assertEqual(span.attributes["http.scheme"], "http")
self.assertEqual(span.attributes["http.status_code"], 500)
self.assertEqual(span.attributes["http.request.method"], "GET")
if DJANGO_2_2:
self.assertEqual(span.attributes["http.route"], "^error/")
self.assertEqual(span.attributes["url.scheme"], "http")
self.assertEqual(span.attributes["http.response.status_code"], 500)
self.assertEqual(len(span.events), 1)
event = span.events[0]
self.assertEqual(event.name, "exception")
self.assertEqual(event.attributes["exception.type"], "ValueError")
self.assertEqual(event.attributes["exception.message"], "error")
self.assertEqual(span.attributes["error.type"], "500")
def test_exclude_lists(self):
client = Client()
client.get("/excluded_arg/123")
span_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(span_list), 0)
client.get("/excluded_arg/125")
span_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(span_list), 1)
client.get("/excluded_noarg/")
span_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(span_list), 1)
client.get("/excluded_noarg2/")
span_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(span_list), 1)
def test_exclude_lists_through_instrument(self):
_django_instrumentor.uninstrument()
_django_instrumentor.instrument(excluded_urls="excluded_explicit")
client = Client()
client.get("/excluded_explicit")
span_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(span_list), 0)
client.get("/excluded_arg/123")
span_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(span_list), 1)
def test_span_name(self):
# test no query_string
Client().get("/span_name/1234/")
span_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(span_list), 1)
span = span_list[0]
self.assertEqual(
span.name,
"GET ^span_name/([0-9]{4})/$" if DJANGO_2_2 else "GET",
)
def test_span_name_for_query_string(self):
"""
request not have query string
"""
Client().get("/span_name/1234/?query=test")
span_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(span_list), 1)
span = span_list[0]
self.assertEqual(
span.name,
"GET ^span_name/([0-9]{4})/$" if DJANGO_2_2 else "GET",
)
def test_span_name_404(self):
Client().get("/span_name/1234567890/")
span_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(span_list), 1)
span = span_list[0]
self.assertEqual(span.name, "GET")
def test_nonstandard_http_method_span_name(self):
Client().request(REQUEST_METHOD="NONSTANDARD", PATH_INFO="/span_name/1234/")
span_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(span_list), 1)
span = span_list[0]
self.assertEqual(span.name, "HTTP")
self.assertEqual(span.attributes["http.method"], "_OTHER")
def test_nonstandard_http_method_span_name_new_semconv(self):
Client().request(REQUEST_METHOD="NONSTANDARD", PATH_INFO="/span_name/1234/")
span_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(span_list), 1)
span = span_list[0]
self.assertEqual(span.name, "HTTP")
self.assertEqual(span.attributes["http.request.method"], "_OTHER")
self.assertEqual(span.attributes["http.request.method_original"], "NONSTANDARD")
def test_nonstandard_http_method_span_name_both_semconv(self):
Client().request(REQUEST_METHOD="NONSTANDARD", PATH_INFO="/span_name/1234/")
span_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(span_list), 1)
span = span_list[0]
self.assertEqual(span.name, "HTTP")
self.assertEqual(span.attributes["http.method"], "_OTHER")
self.assertEqual(span.attributes["http.request.method"], "_OTHER")
self.assertEqual(span.attributes["http.request.method_original"], "NONSTANDARD")
def test_traced_request_attrs(self):
Client().get("/span_name/1234/", CONTENT_TYPE="test/ct")
span_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(span_list), 1)
span = span_list[0]
self.assertEqual(span.attributes["path_info"], "/span_name/1234/")
self.assertEqual(span.attributes["content_type"], "test/ct")
self.assertNotIn("non_existing_variable", span.attributes)
def test_hooks(self):
request_hook_args = ()
response_hook_args = ()
def request_hook(span, request):
nonlocal request_hook_args
request_hook_args = (span, request)
def response_hook(span, request, response):
nonlocal response_hook_args
response_hook_args = (span, request, response)
response["hook-header"] = "set by hook"
_DjangoMiddleware._otel_request_hook = request_hook
_DjangoMiddleware._otel_response_hook = response_hook
response = Client().get("/span_name/1234/")
_DjangoMiddleware._otel_request_hook = _DjangoMiddleware._otel_response_hook = None
self.assertEqual(response["hook-header"], "set by hook")
span_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(span_list), 1)
span = span_list[0]
self.assertEqual(span.attributes["path_info"], "/span_name/1234/")
self.assertEqual(len(request_hook_args), 2)
self.assertEqual(request_hook_args[0].name, span.name)
self.assertIsInstance(request_hook_args[0], Span)
self.assertIsInstance(request_hook_args[1], HttpRequest)
self.assertEqual(len(response_hook_args), 3)
self.assertEqual(request_hook_args[0], response_hook_args[0])
self.assertIsInstance(response_hook_args[1], HttpRequest)
self.assertIsInstance(response_hook_args[2], HttpResponse)
self.assertEqual(response_hook_args[2], response)
def test_request_hook_exception(self):
def request_hook(span, request):
# pylint: disable=broad-exception-raised
raise Exception("request hook exception")
_DjangoMiddleware._otel_request_hook = request_hook
Client().get("/span_name/1234/")
_DjangoMiddleware._otel_request_hook = None
# ensure that span ended
finished_spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(finished_spans), 1)
def test_response_hook_exception(self):
def response_hook(span, request, response):
# pylint: disable=broad-exception-raised
raise Exception("response hook exception")
_DjangoMiddleware._otel_response_hook = response_hook
Client().get("/span_name/1234/")
_DjangoMiddleware._otel_response_hook = None
# ensure that span ended
finished_spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(finished_spans), 1)
def test_trace_parent(self):
id_generator = RandomIdGenerator()
trace_id = format_trace_id(id_generator.generate_trace_id())
span_id = format_span_id(id_generator.generate_span_id())
traceparent_value = f"00-{trace_id}-{span_id}-01"
Client().get(
"/span_name/1234/",
HTTP_TRACEPARENT=traceparent_value,
)
span = self.memory_exporter.get_finished_spans()[0]
self.assertEqual(
trace_id,
format_trace_id(span.get_span_context().trace_id),
)
self.assertIsNotNone(span.parent)
self.assertEqual(
trace_id,
format_trace_id(span.parent.trace_id),
)
self.assertEqual(
span_id,
format_span_id(span.parent.span_id),
)
self.memory_exporter.clear()
def test_trace_response_headers(self):
response = Client().get("/span_name/1234/")
self.assertFalse(response.has_header("Server-Timing"))
self.memory_exporter.clear()
set_global_response_propagator(TraceResponsePropagator())
response = Client().get("/span_name/1234/")
self.assertTraceResponseHeaderMatchesSpan(
response,
self.memory_exporter.get_finished_spans()[0],
)
self.memory_exporter.clear()
def test_uninstrument(self):
Client().get("/route/2020/template/")
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
self.memory_exporter.clear()
_django_instrumentor.uninstrument()
Client().get("/route/2020/template/")
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 0)
# pylint: disable=too-many-locals
def test_wsgi_metrics(self):
_expected_metric_names = [
"http.server.active_requests",
"http.server.duration",
]
expected_duration_attributes = {
"http.method": "GET",
"http.scheme": "http",
"http.flavor": "1.1",
"http.server_name": "testserver",
"net.host.port": 80,
"http.status_code": 200,
"http.target": "^span_name/([0-9]{4})/$",
}
expected_requests_count_attributes = {
"http.method": "GET",
"http.scheme": "http",
"http.flavor": "1.1",
"http.server_name": "testserver",
}
start = default_timer()
for _ in range(3):
response = Client().get("/span_name/1234/")
self.assertEqual(response.status_code, 200)
duration = max(round((default_timer() - start) * 1000), 0)
metrics = self.get_sorted_metrics(SCOPE)
number_data_point_seen = False
histrogram_data_point_seen = False
self.assertTrue(len(metrics) != 0)
for metric in metrics:
self.assertIn(metric.name, _expected_metric_names)
data_points = list(metric.data.data_points)
self.assertEqual(len(data_points), 1)
for point in data_points:
if isinstance(point, HistogramDataPoint):
self.assertEqual(point.count, 3)
histrogram_data_point_seen = True
self.assertAlmostEqual(duration, point.sum, delta=100)
self.assertDictEqual(
expected_duration_attributes,
dict(point.attributes),
)
if isinstance(point, NumberDataPoint):
number_data_point_seen = True
self.assertEqual(point.value, 0)
self.assertDictEqual(
expected_requests_count_attributes,
dict(point.attributes),
)
self.assertTrue(histrogram_data_point_seen and number_data_point_seen)
# pylint: disable=too-many-locals
def test_wsgi_metrics_new_semconv(self):
_expected_metric_names = [
"http.server.active_requests",
"http.server.request.duration",
]
expected_duration_attributes = {
"http.request.method": "GET",
"url.scheme": "http",
"network.protocol.version": "1.1",
"http.response.status_code": 200,
"http.route": "^span_name/([0-9]{4})/$",
}
expected_requests_count_attributes = {
"http.request.method": "GET",
"url.scheme": "http",
}
start = default_timer()
for _ in range(3):
response = Client().get("/span_name/1234/")
self.assertEqual(response.status_code, 200)
duration_s = default_timer() - start
metrics = self.get_sorted_metrics(SCOPE)
number_data_point_seen = False
histrogram_data_point_seen = False
self.assertTrue(len(metrics) != 0)
for metric in metrics:
self.assertIn(metric.name, _expected_metric_names)
data_points = list(metric.data.data_points)
self.assertEqual(len(data_points), 1)
for point in data_points:
if isinstance(point, HistogramDataPoint):
self.assertEqual(point.count, 3)
histrogram_data_point_seen = True
self.assertAlmostEqual(duration_s, point.sum, places=1)
self.assertDictEqual(
expected_duration_attributes,
dict(point.attributes),
)
self.assertEqual(
point.explicit_bounds,
HTTP_DURATION_HISTOGRAM_BUCKETS_NEW,
)
if isinstance(point, NumberDataPoint):
number_data_point_seen = True
self.assertEqual(point.value, 0)
self.assertDictEqual(
expected_requests_count_attributes,
dict(point.attributes),
)
self.assertTrue(histrogram_data_point_seen and number_data_point_seen)
# pylint: disable=too-many-locals
# pylint: disable=too-many-nested-blocks
def test_wsgi_metrics_both_semconv(self):
_expected_metric_names = [
"http.server.duration",
"http.server.active_requests",
"http.server.request.duration",
]
expected_duration_attributes_old = {
"http.method": "GET",
"http.scheme": "http",
"http.flavor": "1.1",
"http.server_name": "testserver",
"net.host.port": 80,
"http.status_code": 200,
"http.target": "^span_name/([0-9]{4})/$",
}
expected_duration_attributes_new = {
"http.request.method": "GET",
"url.scheme": "http",
"network.protocol.version": "1.1",
"http.response.status_code": 200,
"http.route": "^span_name/([0-9]{4})/$",
}
expected_requests_count_attributes = {
"http.method": "GET",
"http.scheme": "http",
"http.flavor": "1.1",
"http.server_name": "testserver",
"http.request.method": "GET",
"url.scheme": "http",
}
start = default_timer()
for _ in range(3):
response = Client().get("/span_name/1234/")
self.assertEqual(response.status_code, 200)
duration_s = max(default_timer() - start, 0)
duration = max(round(duration_s * 1000), 0)
metrics = self.get_sorted_metrics(SCOPE)
number_data_point_seen = False
histrogram_data_point_seen = False
self.assertTrue(len(metrics) != 0)
for metric in metrics:
self.assertIn(metric.name, _expected_metric_names)
data_points = list(metric.data.data_points)
self.assertEqual(len(data_points), 1)
for point in data_points:
if isinstance(point, HistogramDataPoint):
self.assertEqual(point.count, 3)
histrogram_data_point_seen = True
if metric.name == "http.server.request.duration":
self.assertAlmostEqual(duration_s, point.sum, places=1)
self.assertDictEqual(
expected_duration_attributes_new,
dict(point.attributes),
)
self.assertEqual(
point.explicit_bounds,
HTTP_DURATION_HISTOGRAM_BUCKETS_NEW,
)
elif metric.name == "http.server.duration":
self.assertAlmostEqual(duration, point.sum, delta=100)
self.assertDictEqual(
expected_duration_attributes_old,
dict(point.attributes),
)
self.assertEqual(
point.explicit_bounds,
HTTP_DURATION_HISTOGRAM_BUCKETS_OLD,
)
if isinstance(point, NumberDataPoint):
number_data_point_seen = True
self.assertEqual(point.value, 0)
self.assertDictEqual(
expected_requests_count_attributes,
dict(point.attributes),
)
self.assertTrue(histrogram_data_point_seen and number_data_point_seen)
def test_wsgi_metrics_unistrument(self):
Client().get("/span_name/1234/")
_django_instrumentor.uninstrument()
Client().get("/span_name/1234/")
metrics = self.get_sorted_metrics(SCOPE)
for metric in metrics:
for point in list(metric.data.data_points):
if isinstance(point, HistogramDataPoint):
self.assertEqual(1, point.count)
if isinstance(point, NumberDataPoint):
self.assertEqual(0, point.value)
class TestMiddlewareWithTracerProvider(WsgiTestBase):
@classmethod
def setUpClass(cls):
conf.settings.configure(ROOT_URLCONF=modules[__name__])
super().setUpClass()
def setUp(self):
super().setUp()
setup_test_environment()
resource = resources.Resource.create({"resource-key": "resource-value"})
result = self.create_tracer_provider(resource=resource)
tracer_provider, exporter = result
self.exporter = exporter
self.tracer_provider = tracer_provider
_django_instrumentor.instrument(tracer_provider=tracer_provider)
def tearDown(self):
super().tearDown()
teardown_test_environment()
_django_instrumentor.uninstrument()
@classmethod
def tearDownClass(cls):
super().tearDownClass()
conf.settings = conf.LazySettings()
def test_tracer_provider_traced(self):
Client().post("/traced/")
spans = self.exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
span = spans[0]
self.assertEqual(span.resource.attributes["resource-key"], "resource-value")
def test_django_with_wsgi_instrumented(self):
tracer = self.tracer_provider.get_tracer(__name__)
with tracer.start_as_current_span("test", kind=SpanKind.SERVER) as parent_span:
Client().get("/span_name/1234/")
span_list = self.exporter.get_finished_spans()
print(span_list)
self.assertEqual(span_list[0].attributes["http.status_code"], 200)
self.assertEqual(trace.SpanKind.INTERNAL, span_list[0].kind)
self.assertEqual(
parent_span.get_span_context().span_id,
span_list[0].parent.span_id,
)
@patch.dict(
"os.environ",
{
OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SANITIZE_FIELDS: ".*my-secret.*",
OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_REQUEST: "Custom-Test-Header-1,Custom-Test-Header-2,Custom-Test-Header-3,Regex-Test-Header-.*,Regex-Invalid-Test-Header-.*,.*my-secret.*",
OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_RESPONSE: "Custom-Test-Header-1,Custom-Test-Header-2,Custom-Test-Header-3,my-custom-regex-header-.*,invalid-regex-header-.*,.*my-secret.*",
},
)
class TestMiddlewareWsgiWithCustomHeaders(WsgiTestBase):
@classmethod
def setUpClass(cls):
conf.settings.configure(ROOT_URLCONF=modules[__name__])
super().setUpClass()
def setUp(self):
super().setUp()
setup_test_environment()
tracer_provider, exporter = self.create_tracer_provider()
self.exporter = exporter
_django_instrumentor.instrument(tracer_provider=tracer_provider)
def tearDown(self):
super().tearDown()
teardown_test_environment()
_django_instrumentor.uninstrument()
@classmethod
def tearDownClass(cls):
super().tearDownClass()
conf.settings = conf.LazySettings()
def test_http_custom_request_headers_in_span_attributes(self):
expected = {
"http.request.header.custom_test_header_1": ("test-header-value-1",),
"http.request.header.custom_test_header_2": ("test-header-value-2",),
"http.request.header.regex_test_header_1": ("Regex Test Value 1",),
"http.request.header.regex_test_header_2": ("RegexTestValue2,RegexTestValue3",),
"http.request.header.my_secret_header": ("[REDACTED]",),
}
Client(
HTTP_CUSTOM_TEST_HEADER_1="test-header-value-1",
HTTP_CUSTOM_TEST_HEADER_2="test-header-value-2",
HTTP_REGEX_TEST_HEADER_1="Regex Test Value 1",
HTTP_REGEX_TEST_HEADER_2="RegexTestValue2,RegexTestValue3",
HTTP_MY_SECRET_HEADER="My Secret Value",
).get("/traced/")
spans = self.exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
span = spans[0]
self.assertEqual(span.kind, SpanKind.SERVER)
self.assertSpanHasAttributes(span, expected)
self.memory_exporter.clear()
def test_http_custom_request_headers_not_in_span_attributes(self):
not_expected = {
"http.request.header.custom_test_header_2": ("test-header-value-2",),
}
Client(HTTP_CUSTOM_TEST_HEADER_1="test-header-value-1").get("/traced/")
spans = self.exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
span = spans[0]
self.assertEqual(span.kind, SpanKind.SERVER)
for key, _ in not_expected.items():
self.assertNotIn(key, span.attributes)
self.memory_exporter.clear()
def test_http_custom_response_headers_in_span_attributes(self):
expected = {
"http.response.header.custom_test_header_1": ("test-header-value-1",),
"http.response.header.custom_test_header_2": ("test-header-value-2",),
"http.response.header.my_custom_regex_header_1": ("my-custom-regex-value-1,my-custom-regex-value-2",),
"http.response.header.my_custom_regex_header_2": ("my-custom-regex-value-3,my-custom-regex-value-4",),
"http.response.header.my_secret_header": ("[REDACTED]",),
}
Client().get("/traced_custom_header/")
spans = self.exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
span = spans[0]
self.assertEqual(span.kind, SpanKind.SERVER)
self.assertSpanHasAttributes(span, expected)
self.memory_exporter.clear()
def test_http_custom_response_headers_not_in_span_attributes(self):
not_expected = {
"http.response.header.custom_test_header_3": ("test-header-value-3",),
}
Client().get("/traced_custom_header/")
spans = self.exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
span = spans[0]
self.assertEqual(span.kind, SpanKind.SERVER)
for key, _ in not_expected.items():
self.assertNotIn(key, span.attributes)
self.memory_exporter.clear()
class TestMiddlewareSpanActivationTiming(WsgiTestBase):
"""Test span activation timing relative to metrics recording."""
@classmethod
def setUpClass(cls):
conf.settings.configure(ROOT_URLCONF=modules[__name__])
super().setUpClass()
def setUp(self):
super().setUp()
setup_test_environment()
_django_instrumentor.instrument()
def tearDown(self):
super().tearDown()
teardown_test_environment()
_django_instrumentor.uninstrument()
@classmethod
def tearDownClass(cls):
super().tearDownClass()
conf.settings = conf.LazySettings()
def test_span_ended_after_metrics_recorded(self):
"""Span activation exits after metrics recording."""
Client().get("/traced/")
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
# Span properly finished
self.assertIsNotNone(spans[0].end_time)
# Metrics recorded
metrics_list = self.memory_metrics_reader.get_metrics_data()
histogram_found = any(
"duration" in metric.name
for rm in metrics_list.resource_metrics
for sm in rm.scope_metrics
for metric in sm.metrics
)
self.assertTrue(histogram_found)
def test_metrics_recorded_with_exception(self):
"""Metrics recorded even when request raises exception."""
with self.assertRaises(ValueError):
Client().get("/error/")
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
self.assertEqual(spans[0].status.status_code, StatusCode.ERROR)
# Metrics still recorded
metrics_list = self.memory_metrics_reader.get_metrics_data()
histogram_found = any(
"duration" in metric.name
for rm in metrics_list.resource_metrics
for sm in rm.scope_metrics
for metric in sm.metrics
)
self.assertTrue(histogram_found)
test_middleware_asgi.py 0000664 0000000 0000000 00000074154 15270700723 0040234 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-django/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
# pylint: disable=E0611
from sys import modules
from unittest.mock import Mock, patch
import pytest
from django import VERSION, conf
from django.http import HttpRequest, HttpResponse
from django.test import SimpleTestCase
from django.test.utils import setup_test_environment, teardown_test_environment
from opentelemetry import trace as trace_api
from opentelemetry.instrumentation._semconv import (
OTEL_SEMCONV_STABILITY_OPT_IN,
_OpenTelemetrySemanticConventionStability,
)
from opentelemetry.instrumentation.django import (
DjangoInstrumentor,
_DjangoMiddleware,
)
from opentelemetry.instrumentation.propagators import (
TraceResponsePropagator,
set_global_response_propagator,
)
from opentelemetry.sdk import resources
from opentelemetry.sdk.trace import Span
from opentelemetry.sdk.trace.id_generator import RandomIdGenerator
from opentelemetry.semconv._incubating.attributes.http_attributes import (
HTTP_METHOD,
HTTP_SCHEME,
HTTP_STATUS_CODE,
HTTP_URL,
)
from opentelemetry.semconv.attributes.client_attributes import CLIENT_ADDRESS
from opentelemetry.semconv.attributes.exception_attributes import (
EXCEPTION_MESSAGE,
EXCEPTION_TYPE,
)
from opentelemetry.semconv.attributes.http_attributes import (
HTTP_REQUEST_METHOD,
HTTP_REQUEST_METHOD_ORIGINAL,
HTTP_RESPONSE_STATUS_CODE,
HTTP_ROUTE,
)
from opentelemetry.semconv.attributes.network_attributes import (
NETWORK_PROTOCOL_VERSION,
)
from opentelemetry.semconv.attributes.server_attributes import SERVER_PORT
from opentelemetry.semconv.attributes.url_attributes import URL_SCHEME
from opentelemetry.test.test_base import TestBase
from opentelemetry.trace import (
SpanKind,
StatusCode,
format_span_id,
format_trace_id,
)
from opentelemetry.util.http import (
OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SANITIZE_FIELDS,
OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_REQUEST,
OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_RESPONSE,
get_excluded_urls,
get_traced_request_attrs,
)
# pylint: disable=import-error
from .views import (
async_error,
async_excluded,
async_excluded_noarg,
async_excluded_noarg2,
async_route_span_name,
async_traced,
async_traced_template,
async_with_custom_header,
)
DJANGO_2_0 = VERSION >= (2, 0)
DJANGO_3_1 = VERSION >= (3, 1)
if DJANGO_2_0:
from django.urls import re_path
else:
from django.conf.urls import url as re_path
urlpatterns = [
re_path(r"^traced/", async_traced),
re_path(r"^traced_custom_header/", async_with_custom_header),
re_path(r"^route/(?P[0-9]{4})/template/$", async_traced_template),
re_path(r"^error/", async_error),
re_path(r"^excluded_arg/", async_excluded),
re_path(r"^excluded_noarg/", async_excluded_noarg),
re_path(r"^excluded_noarg2/", async_excluded_noarg2),
re_path(r"^span_name/([0-9]{4})/$", async_route_span_name),
]
_django_instrumentor = DjangoInstrumentor()
@pytest.mark.skipif(not DJANGO_3_1, reason="AsyncClient implemented since Django 3.1")
# pylint: disable=too-many-public-methods
class TestMiddlewareAsgi(SimpleTestCase, TestBase):
@classmethod
def setUpClass(cls):
conf.settings.configure(ROOT_URLCONF=modules[__name__])
super().setUpClass()
def setUp(self):
super().setUp()
setup_test_environment()
test_name = ""
if hasattr(self, "_testMethodName"):
test_name = self._testMethodName
sem_conv_mode = "default"
if "new_semconv" in test_name:
sem_conv_mode = "http"
elif "both_semconv" in test_name:
sem_conv_mode = "http/dup"
self.env_patch = patch.dict(
"os.environ",
{
"OTEL_PYTHON_DJANGO_EXCLUDED_URLS": "http://testserver/excluded_arg/123,excluded_noarg",
"OTEL_PYTHON_DJANGO_TRACED_REQUEST_ATTRS": "path_info,content_type,non_existing_variable",
OTEL_SEMCONV_STABILITY_OPT_IN: sem_conv_mode,
},
)
_OpenTelemetrySemanticConventionStability._initialized = False
self.env_patch.start()
_django_instrumentor.instrument()
self.exclude_patch = patch(
"opentelemetry.instrumentation.django.middleware.otel_middleware._DjangoMiddleware._excluded_urls",
get_excluded_urls("DJANGO"),
)
self.traced_patch = patch(
"opentelemetry.instrumentation.django.middleware.otel_middleware._DjangoMiddleware._traced_request_attrs",
get_traced_request_attrs("DJANGO"),
)
self.exclude_patch.start()
self.traced_patch.start()
def tearDown(self):
super().tearDown()
self.env_patch.stop()
self.exclude_patch.stop()
self.traced_patch.stop()
teardown_test_environment()
_django_instrumentor.uninstrument()
@classmethod
def tearDownClass(cls):
super().tearDownClass()
conf.settings = conf.LazySettings()
async def test_templated_route_get(self):
await self.async_client.get("/route/2020/template/")
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
span = spans[0]
self.assertEqual(span.name, "GET ^route/(?P[0-9]{4})/template/$")
self.assertEqual(span.kind, SpanKind.SERVER)
self.assertEqual(span.status.status_code, StatusCode.UNSET)
self.assertEqual(span.attributes[HTTP_METHOD], "GET")
self.assertEqual(
span.attributes[HTTP_URL],
"http://testserver/route/2020/template/",
)
self.assertEqual(
span.attributes[HTTP_ROUTE],
"^route/(?P[0-9]{4})/template/$",
)
self.assertEqual(span.attributes[HTTP_SCHEME], "http")
self.assertEqual(span.attributes[HTTP_STATUS_CODE], 200)
async def test_templated_route_get_new_semconv(self):
await self.async_client.get("/route/2020/template/")
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
span = spans[0]
self.assertEqual(span.name, "GET ^route/(?P[0-9]{4})/template/$")
self.assertEqual(span.kind, SpanKind.SERVER)
self.assertEqual(span.status.status_code, StatusCode.UNSET)
self.assertEqual(span.attributes[HTTP_REQUEST_METHOD], "GET")
self.assertEqual(span.attributes[SERVER_PORT], 80)
self.assertEqual(span.attributes[CLIENT_ADDRESS], "127.0.0.1")
self.assertEqual(span.attributes[NETWORK_PROTOCOL_VERSION], "1.1")
self.assertEqual(
span.attributes[HTTP_ROUTE],
"^route/(?P[0-9]{4})/template/$",
)
self.assertEqual(span.attributes[URL_SCHEME], "http")
self.assertEqual(span.attributes[HTTP_RESPONSE_STATUS_CODE], 200)
async def test_templated_route_get_both_semconv(self):
await self.async_client.get("/route/2020/template/")
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
span = spans[0]
self.assertEqual(span.name, "GET ^route/(?P[0-9]{4})/template/$")
self.assertEqual(span.kind, SpanKind.SERVER)
self.assertEqual(span.status.status_code, StatusCode.UNSET)
self.assertEqual(span.attributes[HTTP_METHOD], "GET")
self.assertEqual(
span.attributes[HTTP_URL],
"http://testserver/route/2020/template/",
)
self.assertEqual(span.attributes[HTTP_SCHEME], "http")
self.assertEqual(span.attributes[HTTP_STATUS_CODE], 200)
self.assertEqual(span.attributes[HTTP_REQUEST_METHOD], "GET")
self.assertEqual(span.attributes[SERVER_PORT], 80)
self.assertEqual(span.attributes[CLIENT_ADDRESS], "127.0.0.1")
self.assertEqual(span.attributes[NETWORK_PROTOCOL_VERSION], "1.1")
self.assertEqual(
span.attributes[HTTP_ROUTE],
"^route/(?P[0-9]{4})/template/$",
)
self.assertEqual(span.attributes[URL_SCHEME], "http")
self.assertEqual(span.attributes[HTTP_RESPONSE_STATUS_CODE], 200)
async def test_traced_get(self):
await self.async_client.get("/traced/")
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
span = spans[0]
self.assertEqual(span.name, "GET ^traced/")
self.assertEqual(span.kind, SpanKind.SERVER)
self.assertEqual(span.status.status_code, StatusCode.UNSET)
self.assertEqual(span.attributes[HTTP_METHOD], "GET")
self.assertEqual(
span.attributes[HTTP_URL],
"http://testserver/traced/",
)
self.assertEqual(span.attributes[HTTP_ROUTE], "^traced/")
self.assertEqual(span.attributes[HTTP_SCHEME], "http")
self.assertEqual(span.attributes[HTTP_STATUS_CODE], 200)
async def test_traced_get_new_semconv(self):
await self.async_client.get("/traced/")
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
span = spans[0]
self.assertEqual(span.name, "GET ^traced/")
self.assertEqual(span.kind, SpanKind.SERVER)
self.assertEqual(span.status.status_code, StatusCode.UNSET)
self.assertEqual(span.attributes[HTTP_REQUEST_METHOD], "GET")
self.assertEqual(span.attributes[URL_SCHEME], "http")
self.assertEqual(span.attributes[SERVER_PORT], 80)
self.assertEqual(span.attributes[CLIENT_ADDRESS], "127.0.0.1")
self.assertEqual(span.attributes[NETWORK_PROTOCOL_VERSION], "1.1")
self.assertEqual(span.attributes[HTTP_ROUTE], "^traced/")
self.assertEqual(span.attributes[HTTP_RESPONSE_STATUS_CODE], 200)
async def test_traced_get_both_semconv(self):
await self.async_client.get("/traced/")
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
span = spans[0]
self.assertEqual(span.name, "GET ^traced/")
self.assertEqual(span.kind, SpanKind.SERVER)
self.assertEqual(span.status.status_code, StatusCode.UNSET)
self.assertEqual(span.attributes[HTTP_METHOD], "GET")
self.assertEqual(
span.attributes[HTTP_URL],
"http://testserver/traced/",
)
self.assertEqual(span.attributes[HTTP_SCHEME], "http")
self.assertEqual(span.attributes[HTTP_STATUS_CODE], 200)
self.assertEqual(span.attributes[HTTP_REQUEST_METHOD], "GET")
self.assertEqual(span.attributes[URL_SCHEME], "http")
self.assertEqual(span.attributes[SERVER_PORT], 80)
self.assertEqual(span.attributes[CLIENT_ADDRESS], "127.0.0.1")
self.assertEqual(span.attributes[NETWORK_PROTOCOL_VERSION], "1.1")
self.assertEqual(span.attributes[HTTP_ROUTE], "^traced/")
self.assertEqual(span.attributes[HTTP_RESPONSE_STATUS_CODE], 200)
async def test_not_recording(self):
mock_tracer = Mock()
mock_span = Mock()
mock_span.is_recording.return_value = False
mock_tracer.start_span.return_value = mock_span
with patch("opentelemetry.trace.get_tracer") as tracer:
tracer.return_value = mock_tracer
await self.async_client.get("/traced/")
self.assertFalse(mock_span.is_recording())
self.assertTrue(mock_span.is_recording.called)
self.assertFalse(mock_span.set_attribute.called)
self.assertFalse(mock_span.set_status.called)
async def test_traced_post(self):
await self.async_client.post("/traced/")
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
span = spans[0]
self.assertEqual(span.name, "POST ^traced/")
self.assertEqual(span.kind, SpanKind.SERVER)
self.assertEqual(span.status.status_code, StatusCode.UNSET)
self.assertEqual(span.attributes[HTTP_METHOD], "POST")
self.assertEqual(
span.attributes[HTTP_URL],
"http://testserver/traced/",
)
self.assertEqual(span.attributes[HTTP_ROUTE], "^traced/")
self.assertEqual(span.attributes[HTTP_SCHEME], "http")
self.assertEqual(span.attributes[HTTP_STATUS_CODE], 200)
async def test_traced_post_new_semconv(self):
await self.async_client.post("/traced/")
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
span = spans[0]
self.assertEqual(span.name, "POST ^traced/")
self.assertEqual(span.kind, SpanKind.SERVER)
self.assertEqual(span.status.status_code, StatusCode.UNSET)
self.assertEqual(span.attributes[HTTP_REQUEST_METHOD], "POST")
self.assertEqual(span.attributes[URL_SCHEME], "http")
self.assertEqual(span.attributes[SERVER_PORT], 80)
self.assertEqual(span.attributes[CLIENT_ADDRESS], "127.0.0.1")
self.assertEqual(span.attributes[NETWORK_PROTOCOL_VERSION], "1.1")
self.assertEqual(span.attributes[HTTP_ROUTE], "^traced/")
self.assertEqual(span.attributes[HTTP_RESPONSE_STATUS_CODE], 200)
async def test_traced_post_both_semconv(self):
await self.async_client.post("/traced/")
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
span = spans[0]
self.assertEqual(span.name, "POST ^traced/")
self.assertEqual(span.kind, SpanKind.SERVER)
self.assertEqual(span.status.status_code, StatusCode.UNSET)
self.assertEqual(span.attributes[HTTP_METHOD], "POST")
self.assertEqual(
span.attributes[HTTP_URL],
"http://testserver/traced/",
)
self.assertEqual(span.attributes[HTTP_SCHEME], "http")
self.assertEqual(span.attributes[HTTP_STATUS_CODE], 200)
self.assertEqual(span.attributes[HTTP_REQUEST_METHOD], "POST")
self.assertEqual(span.attributes[URL_SCHEME], "http")
self.assertEqual(span.attributes[SERVER_PORT], 80)
self.assertEqual(span.attributes[CLIENT_ADDRESS], "127.0.0.1")
self.assertEqual(span.attributes[NETWORK_PROTOCOL_VERSION], "1.1")
self.assertEqual(span.attributes[HTTP_ROUTE], "^traced/")
self.assertEqual(span.attributes[HTTP_RESPONSE_STATUS_CODE], 200)
async def test_error(self):
with self.assertRaises(ValueError):
await self.async_client.get("/error/")
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
span = spans[0]
self.assertEqual(span.name, "GET ^error/")
self.assertEqual(span.kind, SpanKind.SERVER)
self.assertEqual(span.status.status_code, StatusCode.ERROR)
self.assertEqual(span.attributes[HTTP_METHOD], "GET")
self.assertEqual(
span.attributes[HTTP_URL],
"http://testserver/error/",
)
self.assertEqual(span.attributes[HTTP_ROUTE], "^error/")
self.assertEqual(span.attributes[HTTP_SCHEME], "http")
self.assertEqual(span.attributes[HTTP_STATUS_CODE], 500)
self.assertEqual(len(span.events), 1)
event = span.events[0]
self.assertEqual(event.name, "exception")
self.assertEqual(event.attributes[EXCEPTION_TYPE], "ValueError")
self.assertEqual(event.attributes[EXCEPTION_MESSAGE], "error")
async def test_error_new_semconv(self):
with self.assertRaises(ValueError):
await self.async_client.get("/error/")
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
span = spans[0]
self.assertEqual(span.name, "GET ^error/")
self.assertEqual(span.kind, SpanKind.SERVER)
self.assertEqual(span.status.status_code, StatusCode.ERROR)
self.assertEqual(span.attributes[HTTP_REQUEST_METHOD], "GET")
self.assertEqual(span.attributes[HTTP_ROUTE], "^error/")
self.assertEqual(span.attributes[URL_SCHEME], "http")
self.assertEqual(span.attributes[HTTP_RESPONSE_STATUS_CODE], 500)
self.assertEqual(len(span.events), 1)
event = span.events[0]
self.assertEqual(event.name, "exception")
self.assertEqual(event.attributes[EXCEPTION_TYPE], "ValueError")
self.assertEqual(event.attributes[EXCEPTION_MESSAGE], "error")
async def test_error_both_semconv(self):
with self.assertRaises(ValueError):
await self.async_client.get("/error/")
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
span = spans[0]
self.assertEqual(span.name, "GET ^error/")
self.assertEqual(span.kind, SpanKind.SERVER)
self.assertEqual(span.status.status_code, StatusCode.ERROR)
self.assertEqual(span.attributes[HTTP_METHOD], "GET")
self.assertEqual(
span.attributes[HTTP_URL],
"http://testserver/error/",
)
self.assertEqual(span.attributes[HTTP_ROUTE], "^error/")
self.assertEqual(span.attributes[HTTP_SCHEME], "http")
self.assertEqual(span.attributes[HTTP_STATUS_CODE], 500)
self.assertEqual(span.attributes[HTTP_REQUEST_METHOD], "GET")
self.assertEqual(span.attributes[HTTP_ROUTE], "^error/")
self.assertEqual(span.attributes[URL_SCHEME], "http")
self.assertEqual(span.attributes[HTTP_RESPONSE_STATUS_CODE], 500)
self.assertEqual(len(span.events), 1)
event = span.events[0]
self.assertEqual(event.name, "exception")
self.assertEqual(event.attributes[EXCEPTION_TYPE], "ValueError")
self.assertEqual(event.attributes[EXCEPTION_MESSAGE], "error")
async def test_exclude_lists(self):
await self.async_client.get("/excluded_arg/123")
span_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(span_list), 0)
await self.async_client.get("/excluded_arg/125")
span_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(span_list), 1)
await self.async_client.get("/excluded_noarg/")
span_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(span_list), 1)
await self.async_client.get("/excluded_noarg2/")
span_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(span_list), 1)
async def test_span_name(self):
# test no query_string
await self.async_client.get("/span_name/1234/")
span_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(span_list), 1)
span = span_list[0]
self.assertEqual(span.name, "GET ^span_name/([0-9]{4})/$")
async def test_span_name_for_query_string(self):
"""
request not have query string
"""
await self.async_client.get("/span_name/1234/?query=test")
span_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(span_list), 1)
span = span_list[0]
self.assertEqual(span.name, "GET ^span_name/([0-9]{4})/$")
async def test_span_name_404(self):
await self.async_client.get("/span_name/1234567890/")
span_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(span_list), 1)
span = span_list[0]
self.assertEqual(span.name, "GET")
async def test_nonstandard_http_method_span_name(self):
await self.async_client.request(method="NONSTANDARD", path="/span_name/1234/")
span_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(span_list), 1)
span = span_list[0]
self.assertEqual(span.name, "HTTP")
async def test_nonstandard_http_method_span_name_new_semconv(self):
await self.async_client.request(method="NONSTANDARD", path="/span_name/1234/")
span_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(span_list), 1)
span = span_list[0]
self.assertEqual(span.name, "HTTP")
self.assertEqual(span.attributes[HTTP_REQUEST_METHOD], "_OTHER")
self.assertEqual(span.attributes[HTTP_REQUEST_METHOD_ORIGINAL], "NONSTANDARD")
async def test_nonstandard_http_method_span_name_both_semconv(self):
await self.async_client.request(method="NONSTANDARD", path="/span_name/1234/")
span_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(span_list), 1)
span = span_list[0]
self.assertEqual(span.name, "HTTP")
self.assertEqual(span.attributes[HTTP_METHOD], "_OTHER")
self.assertEqual(span.attributes[HTTP_REQUEST_METHOD], "_OTHER")
self.assertEqual(span.attributes[HTTP_REQUEST_METHOD_ORIGINAL], "NONSTANDARD")
async def test_traced_request_attrs(self):
await self.async_client.get("/span_name/1234/", CONTENT_TYPE="test/ct")
span_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(span_list), 1)
span = span_list[0]
self.assertEqual(span.attributes["path_info"], "/span_name/1234/")
self.assertEqual(span.attributes["content_type"], "test/ct")
self.assertNotIn("non_existing_variable", span.attributes)
async def test_hooks(self):
request_hook_args = ()
response_hook_args = ()
def request_hook(span, request):
nonlocal request_hook_args
request_hook_args = (span, request)
def response_hook(span, request, response):
nonlocal response_hook_args
response_hook_args = (span, request, response)
response["hook-header"] = "set by hook"
_DjangoMiddleware._otel_request_hook = request_hook
_DjangoMiddleware._otel_response_hook = response_hook
response = await self.async_client.get("/span_name/1234/")
_DjangoMiddleware._otel_request_hook = _DjangoMiddleware._otel_response_hook = None
self.assertEqual(response["hook-header"], "set by hook")
span_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(span_list), 1)
span = span_list[0]
self.assertEqual(span.attributes["path_info"], "/span_name/1234/")
self.assertEqual(len(request_hook_args), 2)
self.assertEqual(request_hook_args[0].name, span.name)
self.assertIsInstance(request_hook_args[0], Span)
self.assertIsInstance(request_hook_args[1], HttpRequest)
self.assertEqual(len(response_hook_args), 3)
self.assertEqual(request_hook_args[0], response_hook_args[0])
self.assertIsInstance(response_hook_args[1], HttpRequest)
self.assertIsInstance(response_hook_args[2], HttpResponse)
self.assertEqual(response_hook_args[2], response)
async def test_trace_parent(self):
id_generator = RandomIdGenerator()
trace_id = format_trace_id(id_generator.generate_trace_id())
span_id = format_span_id(id_generator.generate_span_id())
traceparent_value = f"00-{trace_id}-{span_id}-01"
await self.async_client.get(
"/span_name/1234/",
traceparent=traceparent_value,
)
span = self.memory_exporter.get_finished_spans()[0]
self.assertEqual(
trace_id,
format_trace_id(span.get_span_context().trace_id),
)
self.assertIsNotNone(span.parent)
self.assertEqual(
trace_id,
format_trace_id(span.parent.trace_id),
)
self.assertEqual(
span_id,
format_span_id(span.parent.span_id),
)
self.memory_exporter.clear()
async def test_trace_response_headers(self):
response = await self.async_client.get("/span_name/1234/")
self.assertFalse(response.has_header("Server-Timing"))
self.memory_exporter.clear()
set_global_response_propagator(TraceResponsePropagator())
response = await self.async_client.get("/span_name/1234/")
span = self.memory_exporter.get_finished_spans()[0]
self.assertTrue(response.has_header("traceresponse"))
self.assertEqual(
response["Access-Control-Expose-Headers"],
"traceresponse",
)
trace_id = format_trace_id(span.get_span_context().trace_id)
span_id = format_span_id(span.get_span_context().span_id)
trace_flags = span.get_span_context().trace_flags
self.assertEqual(
response["traceresponse"],
f"00-{trace_id}-{span_id}-{trace_flags:02x}",
)
self.memory_exporter.clear()
class TestMiddlewareAsgiWithTracerProvider(SimpleTestCase, TestBase):
@classmethod
def setUpClass(cls):
conf.settings.configure(ROOT_URLCONF=modules[__name__])
super().setUpClass()
def setUp(self):
super().setUp()
setup_test_environment()
resource = resources.Resource.create({"resource-key": "resource-value"})
result = self.create_tracer_provider(resource=resource)
tracer_provider, exporter = result
self.exporter = exporter
_django_instrumentor.instrument(tracer_provider=tracer_provider)
def tearDown(self):
super().tearDown()
teardown_test_environment()
_django_instrumentor.uninstrument()
@classmethod
def tearDownClass(cls):
super().tearDownClass()
conf.settings = conf.LazySettings()
async def test_tracer_provider_traced(self):
await self.async_client.post("/traced/")
spans = self.exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
span = spans[0]
self.assertEqual(span.resource.attributes["resource-key"], "resource-value")
async def test_no_op_tracer_provider(self):
_django_instrumentor.uninstrument()
_django_instrumentor.instrument(tracer_provider=trace_api.NoOpTracerProvider())
await self.async_client.post("/traced/")
spans = self.exporter.get_finished_spans()
self.assertEqual(len(spans), 0)
@patch.dict(
"os.environ",
{
OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SANITIZE_FIELDS: ".*my-secret.*",
OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_REQUEST: "Custom-Test-Header-1,Custom-Test-Header-2,Custom-Test-Header-3,Regex-Test-Header-.*,Regex-Invalid-Test-Header-.*,.*my-secret.*",
OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_RESPONSE: "Custom-Test-Header-1,Custom-Test-Header-2,Custom-Test-Header-3,my-custom-regex-header-.*,invalid-regex-header-.*,.*my-secret.*",
},
)
class TestMiddlewareAsgiWithCustomHeaders(SimpleTestCase, TestBase):
@classmethod
def setUpClass(cls):
conf.settings.configure(ROOT_URLCONF=modules[__name__])
super().setUpClass()
def setUp(self):
super().setUp()
setup_test_environment()
tracer_provider, exporter = self.create_tracer_provider()
self.exporter = exporter
_django_instrumentor.instrument(tracer_provider=tracer_provider)
def tearDown(self):
super().tearDown()
teardown_test_environment()
_django_instrumentor.uninstrument()
@classmethod
def tearDownClass(cls):
super().tearDownClass()
conf.settings = conf.LazySettings()
async def test_http_custom_request_headers_in_span_attributes(self):
expected = {
"http.request.header.custom_test_header_1": ("test-header-value-1",),
"http.request.header.custom_test_header_2": ("test-header-value-2",),
"http.request.header.regex_test_header_1": ("Regex Test Value 1",),
"http.request.header.regex_test_header_2": ("RegexTestValue2,RegexTestValue3",),
"http.request.header.my_secret_header": ("[REDACTED]",),
}
await self.async_client.get(
"/traced/",
**{
"custom-test-header-1": "test-header-value-1",
"custom-test-header-2": "test-header-value-2",
"Regex-Test-Header-1": "Regex Test Value 1",
"regex-test-header-2": "RegexTestValue2,RegexTestValue3",
"My-Secret-Header": "My Secret Value",
},
)
spans = self.exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
span = spans[0]
self.assertEqual(span.kind, SpanKind.SERVER)
self.assertSpanHasAttributes(span, expected)
self.memory_exporter.clear()
async def test_http_custom_request_headers_not_in_span_attributes(self):
not_expected = {
"http.request.header.custom_test_header_2": ("test-header-value-2",),
}
await self.async_client.get(
"/traced/",
**{
"custom-test-header-1": "test-header-value-1",
},
)
spans = self.exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
span = spans[0]
self.assertEqual(span.kind, SpanKind.SERVER)
for key, _ in not_expected.items():
self.assertNotIn(key, span.attributes)
self.memory_exporter.clear()
async def test_http_custom_response_headers_in_span_attributes(self):
expected = {
"http.response.header.custom_test_header_1": ("test-header-value-1",),
"http.response.header.custom_test_header_2": ("test-header-value-2",),
"http.response.header.my_custom_regex_header_1": ("my-custom-regex-value-1,my-custom-regex-value-2",),
"http.response.header.my_custom_regex_header_2": ("my-custom-regex-value-3,my-custom-regex-value-4",),
"http.response.header.my_secret_header": ("[REDACTED]",),
}
await self.async_client.get("/traced_custom_header/")
spans = self.exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
span = spans[0]
self.assertEqual(span.kind, SpanKind.SERVER)
self.assertSpanHasAttributes(span, expected)
self.memory_exporter.clear()
async def test_http_custom_response_headers_not_in_span_attributes(self):
not_expected = {
"http.response.header.custom_test_header_3": ("test-header-value-3",),
}
await self.async_client.get("/traced_custom_header/")
spans = self.exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
span = spans[0]
self.assertEqual(span.kind, SpanKind.SERVER)
for key, _ in not_expected.items():
self.assertNotIn(key, span.attributes)
self.memory_exporter.clear()
test_sqlcommenter.py 0000664 0000000 0000000 00000015437 15270700723 0037624 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-django/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
# pylint: disable=no-name-in-module
from unittest.mock import MagicMock, patch
import pytest
from django import VERSION, conf
from django.http import HttpResponse
from django.test.utils import setup_test_environment, teardown_test_environment
from opentelemetry.instrumentation.django import DjangoInstrumentor
from opentelemetry.instrumentation.django.middleware.sqlcommenter_middleware import (
SqlCommenter,
_QueryWrapper,
)
from opentelemetry.test.wsgitestutil import WsgiTestBase
DJANGO_2_0 = VERSION >= (2, 0)
_django_instrumentor = DjangoInstrumentor()
class TestMiddleware(WsgiTestBase):
@classmethod
def setUpClass(cls):
conf.settings.configure(
SQLCOMMENTER_WITH_FRAMEWORK=False,
SQLCOMMENTER_WITH_DB_DRIVER=False,
)
super().setUpClass()
def setUp(self):
super().setUp()
setup_test_environment()
_django_instrumentor.instrument(is_sql_commentor_enabled=True)
def tearDown(self):
super().tearDown()
teardown_test_environment()
_django_instrumentor.uninstrument()
@classmethod
def tearDownClass(cls):
super().tearDownClass()
conf.settings = conf.LazySettings()
@patch("opentelemetry.instrumentation.django.middleware.sqlcommenter_middleware.SqlCommenter")
def test_middleware_added(self, sqlcommenter_middleware):
instance = sqlcommenter_middleware.return_value
instance.get_response = HttpResponse()
if DJANGO_2_0:
middleware = conf.settings.MIDDLEWARE
else:
middleware = conf.settings.MIDDLEWARE_CLASSES
self.assertTrue(
"opentelemetry.instrumentation.django.middleware.sqlcommenter_middleware.SqlCommenter" in middleware
)
@patch("opentelemetry.instrumentation.django.middleware.sqlcommenter_middleware.SqlCommenter")
def test_middleware_added_at_position(self, sqlcommenter_middleware):
_django_instrumentor.uninstrument()
if DJANGO_2_0:
middleware = conf.settings.MIDDLEWARE
else:
middleware = conf.settings.MIDDLEWARE_CLASSES
# adding two dummy middlewares
temprory_middelware = "django.utils.deprecation.MiddlewareMixin"
middleware.append(temprory_middelware)
middleware.append(temprory_middelware)
middleware_position = 1
_django_instrumentor.instrument(
is_sql_commentor_enabled=True,
middleware_position=middleware_position,
)
instance = sqlcommenter_middleware.return_value
instance.get_response = HttpResponse()
self.assertEqual(
middleware[middleware_position],
"opentelemetry.instrumentation.django.middleware.otel_middleware._DjangoMiddleware",
)
self.assertEqual(
middleware[middleware_position + 1],
"opentelemetry.instrumentation.django.middleware.sqlcommenter_middleware.SqlCommenter",
)
@patch("opentelemetry.instrumentation.django.middleware.sqlcommenter_middleware._get_opentelemetry_values")
def test_query_wrapper(self, trace_capture):
requests_mock = MagicMock()
requests_mock.resolver_match.view_name = "view"
requests_mock.resolver_match.route = "route"
requests_mock.resolver_match.app_name = "app"
trace_capture.return_value = {
"traceparent": "*traceparent='00-000000000000000000000000deadbeef-000000000000beef-00"
}
qw_instance = _QueryWrapper(requests_mock)
execute_mock_obj = MagicMock()
qw_instance(
execute_mock_obj,
"Select 1;",
MagicMock("test"),
MagicMock("test1"),
MagicMock(),
)
output_sql = execute_mock_obj.call_args[0][0]
self.assertEqual(
output_sql,
"Select 1 /*app_name='app',controller='view',route='route',traceparent='%%2Atraceparent%%3D%%2700-0000000"
"00000000000000000deadbeef-000000000000beef-00'*/;",
)
@patch("opentelemetry.instrumentation.django.middleware.sqlcommenter_middleware._get_opentelemetry_values")
def test_query_wrapper_non_string_queries(self, trace_capture):
"""Test that non-string queries and psycopg2 composable objects are handled correctly."""
requests_mock = MagicMock()
requests_mock.resolver_match.view_name = "view"
requests_mock.resolver_match.route = "route"
requests_mock.resolver_match.app_name = "app"
trace_capture.return_value = {
"traceparent": "*traceparent='00-000000000000000000000000deadbeef-000000000000beef-00"
}
qw_instance = _QueryWrapper(requests_mock)
execute_mock_obj = MagicMock()
input_query = MagicMock(as_string=lambda conn: "SELECT 2")
expected_query_start = "SELECT 2"
qw_instance(
execute_mock_obj,
input_query,
MagicMock("test"),
MagicMock("test1"),
MagicMock(),
)
output_sql = execute_mock_obj.call_args[0][0]
self.assertTrue(
str(output_sql).startswith(str(expected_query_start)),
f"Query should start with {expected_query_start!r}, got {output_sql!r}",
)
@patch("opentelemetry.instrumentation.django.middleware.sqlcommenter_middleware._QueryWrapper")
def test_multiple_connection_support(self, query_wrapper):
if not DJANGO_2_0:
pytest.skip()
requests_mock = MagicMock()
get_response = MagicMock()
sql_instance = SqlCommenter(get_response)
sql_instance(requests_mock)
# check if query_wrapper is added to the context for 2 databases
self.assertEqual(query_wrapper.call_count, 2)
@patch("opentelemetry.instrumentation.django.middleware.sqlcommenter_middleware._get_opentelemetry_values")
def test_empty_sql(self, trace_capture):
requests_mock = MagicMock()
requests_mock.resolver_match.view_name = "view"
requests_mock.resolver_match.route = "route"
requests_mock.resolver_match.app_name = "app"
trace_capture.return_value = {
"traceparent": "*traceparent='00-000000000000000000000000deadbeef-000000000000beef-00"
}
qw_instance = _QueryWrapper(requests_mock)
execute_mock_obj = MagicMock()
qw_instance(
execute_mock_obj,
"",
MagicMock("test"),
MagicMock("test1"),
MagicMock(),
)
output_sql = execute_mock_obj.call_args[0][0]
self.assertEqual(
output_sql,
" /*app_name='app',controller='view',route='route',traceparent='%%2Atraceparent%%3D%%2700-0000000"
"00000000000000000deadbeef-000000000000beef-00'*/",
)
views.py 0000664 0000000 0000000 00000004216 15270700723 0035202 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-django/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
from django.http import HttpResponse
def traced(request): # pylint: disable=unused-argument
return HttpResponse()
def traced_template(request, year): # pylint: disable=unused-argument
return HttpResponse()
def error(request): # pylint: disable=unused-argument
raise ValueError("error")
def excluded(request): # pylint: disable=unused-argument
return HttpResponse()
def excluded_noarg(request): # pylint: disable=unused-argument
return HttpResponse()
def excluded_noarg2(request): # pylint: disable=unused-argument
return HttpResponse()
def route_span_name(request, *args, **kwargs): # pylint: disable=unused-argument
return HttpResponse()
def response_with_custom_header(request):
response = HttpResponse()
response["custom-test-header-1"] = "test-header-value-1"
response["custom-test-header-2"] = "test-header-value-2"
response["my-custom-regex-header-1"] = "my-custom-regex-value-1,my-custom-regex-value-2"
response["my-custom-regex-header-2"] = "my-custom-regex-value-3,my-custom-regex-value-4"
response["my-secret-header"] = "my-secret-value"
return response
async def async_traced(request): # pylint: disable=unused-argument
return HttpResponse()
async def async_traced_template(request, year): # pylint: disable=unused-argument
return HttpResponse()
async def async_error(request): # pylint: disable=unused-argument
raise ValueError("error")
async def async_excluded(request): # pylint: disable=unused-argument
return HttpResponse()
async def async_excluded_noarg(request): # pylint: disable=unused-argument
return HttpResponse()
async def async_excluded_noarg2(request): # pylint: disable=unused-argument
return HttpResponse()
async def async_route_span_name(request, *args, **kwargs): # pylint: disable=unused-argument
return HttpResponse()
async def async_with_custom_header(request):
response = HttpResponse()
response.headers["custom-test-header-1"] = "test-header-value-1"
response.headers["custom-test-header-2"] = "test-header-value-2"
return response
opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-exceptions/ 0000775 0000000 0000000 00000000000 15270700723 0033324 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-exceptions/LICENSE0000664 0000000 0000000 00000026135 15270700723 0034340 0 ustar 00root root 0000000 0000000 Apache License
Version 2.0, January 2004
http://www.apache.org/licenses/
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README.rst 0000664 0000000 0000000 00000001622 15270700723 0034735 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-exceptions OpenTelemetry unhandled exceptions instrumentation
==================================================
|pypi|
.. |pypi| image:: https://badge.fury.io/py/opentelemetry-instrumentation-exceptions.svg
:target: https://pypi.org/project/opentelemetry-instrumentation-exceptions/
Installation
------------
::
pip install opentelemetry-instrumentation-exceptions
Usage
-----
.. code-block:: python
from opentelemetry.instrumentation.exceptions import (
UnhandledExceptionInstrumentor,
)
UnhandledExceptionInstrumentor().instrument()
This instrumentation captures uncaught process exceptions, uncaught thread
exceptions, and unhandled asyncio task exceptions and emits them as OpenTelemetry
logs.
References
----------
* `OpenTelemetry Python Contrib repository `_
* `OpenTelemetry Project `_
pyproject.toml 0000664 0000000 0000000 00000003172 15270700723 0036164 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-exceptions [build-system]
requires = ["hatchling"]
build-backend = "hatchling.build"
[project]
name = "opentelemetry-instrumentation-exceptions"
dynamic = ["version"]
description = "OpenTelemetry unhandled exceptions instrumentation"
readme = "README.rst"
license = "Apache-2.0"
requires-python = ">=3.10"
authors = [
{ name = "OpenTelemetry Authors", email = "cncf-opentelemetry-contributors@lists.cncf.io" },
]
classifiers = [
"Development Status :: 4 - Beta",
"Intended Audience :: Developers",
"License :: OSI Approved :: Apache Software License",
"Programming Language :: Python",
"Programming Language :: Python :: 3",
"Programming Language :: Python :: 3.10",
"Programming Language :: Python :: 3.11",
"Programming Language :: Python :: 3.12",
"Programming Language :: Python :: 3.13",
"Programming Language :: Python :: 3.14",
]
dependencies = [
"opentelemetry-api >= 1.42.0.dev, < 2.0.0",
"opentelemetry-instrumentation == 0.66b2",
"opentelemetry-semantic-conventions == 0.66b2",
]
[project.optional-dependencies]
instruments = []
[project.entry-points.opentelemetry_instrumentor]
exceptions = "opentelemetry.instrumentation.exceptions:UnhandledExceptionInstrumentor"
[project.urls]
Homepage = "https://github.com/open-telemetry/opentelemetry-python-contrib/tree/main/instrumentation/opentelemetry-instrumentation-exceptions"
Repository = "https://github.com/open-telemetry/opentelemetry-python-contrib"
[tool.hatch.version]
path = "src/opentelemetry/instrumentation/exceptions/version.py"
[tool.hatch.build.targets.sdist]
include = [
"/src",
"/tests",
]
[tool.hatch.build.targets.wheel]
packages = ["src/opentelemetry"]
opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-exceptions/src/ 0000775 0000000 0000000 00000000000 15270700723 0034113 5 ustar 00root root 0000000 0000000 opentelemetry/ 0000775 0000000 0000000 00000000000 15270700723 0036730 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-exceptions/src instrumentation/ 0000775 0000000 0000000 00000000000 15270700723 0042173 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-exceptions/src/opentelemetry exceptions/ 0000775 0000000 0000000 00000000000 15270700723 0044354 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-exceptions/src/opentelemetry/instrumentation __init__.py 0000664 0000000 0000000 00000012413 15270700723 0046466 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-exceptions/src/opentelemetry/instrumentation/exceptions # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
"""
Instrument uncaught exceptions to emit OpenTelemetry logs.
Usage
-----
.. code-block:: python
from opentelemetry.instrumentation.exceptions import (
UnhandledExceptionInstrumentor,
)
UnhandledExceptionInstrumentor().instrument()
This instrumentation captures uncaught process exceptions, uncaught thread
exceptions, and unhandled asyncio task exceptions and emits them as
OpenTelemetry logs.
"""
from __future__ import annotations
import asyncio
import sys
import threading
from collections.abc import Collection
from types import TracebackType
from typing import Any
from wrapt import (
wrap_function_wrapper, # type: ignore[reportUnknownVariableType]
)
from opentelemetry._logs import Logger, SeverityNumber, get_logger
from opentelemetry.instrumentation.exceptions.package import _instruments
from opentelemetry.instrumentation.exceptions.version import __version__
from opentelemetry.instrumentation.instrumentor import BaseInstrumentor
from opentelemetry.instrumentation.utils import unwrap
from opentelemetry.semconv.schemas import Schemas
class UnhandledExceptionInstrumentor(BaseInstrumentor):
"""Emit logs for uncaught exceptions and unhandled asyncio exceptions."""
def __init__(self):
super().__init__()
self._logger: Logger | None = None
# pylint: disable-next=no-self-use
def instrumentation_dependencies(self) -> Collection[str]:
return _instruments
def _instrument(self, **kwargs: Any):
self._logger = get_logger(
__name__,
__version__,
kwargs.get("logger_provider"),
schema_url=Schemas.V1_37_0.value,
)
self._install_sys_hook()
self._install_threading_hook()
self._install_asyncio_hook()
def _uninstrument(self, **kwargs: Any):
self._restore_sys_hook()
self._restore_threading_hook()
self._restore_asyncio_hook()
self._logger = None
def _install_sys_hook(self) -> None:
wrap_function_wrapper(
sys,
"excepthook",
self._wrap_sys_excepthook,
)
@staticmethod
def _restore_sys_hook() -> None:
unwrap(sys, "excepthook")
def _install_threading_hook(self) -> None:
wrap_function_wrapper(
threading,
"excepthook",
self._wrap_threading_excepthook,
)
@staticmethod
def _restore_threading_hook() -> None:
unwrap(threading, "excepthook")
def _install_asyncio_hook(self) -> None:
wrap_function_wrapper(
asyncio.BaseEventLoop,
"call_exception_handler",
self._wrap_asyncio_call_exception_handler,
)
@staticmethod
def _restore_asyncio_hook() -> None:
unwrap(asyncio.BaseEventLoop, "call_exception_handler")
def _emit_exception(
self,
exc: BaseException,
*,
severity_text: str,
severity_number: SeverityNumber,
event_name: str,
) -> None:
# BaseException includes process-control signals like KeyboardInterrupt.
if not isinstance(exc, Exception) or self._logger is None:
return
try:
self._logger.emit(
event_name=event_name,
body=str(exc),
severity_text=severity_text,
severity_number=severity_number,
exception=exc,
)
# Logging must never replace the original unhandled exception path.
# pylint: disable-next=broad-exception-caught
except Exception: # pragma: no cover
pass
def _wrap_sys_excepthook(
self,
wrapped,
instance,
args: tuple[type[BaseException], BaseException, TracebackType | None],
kwargs: dict[str, Any],
) -> None:
_, exc, _ = args
self._emit_exception(
exc,
severity_text="FATAL",
severity_number=SeverityNumber.FATAL,
event_name=type(exc).__name__,
)
wrapped(*args, **kwargs)
def _wrap_threading_excepthook(
self,
wrapped,
instance,
args: tuple[threading.ExceptHookArgs],
kwargs: dict[str, Any],
) -> None:
(hook_args,) = args
self._emit_exception(
hook_args.exc_value,
severity_text="ERROR",
severity_number=SeverityNumber.ERROR,
event_name=hook_args.exc_type.__name__,
)
wrapped(*args, **kwargs)
def _wrap_asyncio_call_exception_handler(
self,
wrapped,
instance: asyncio.AbstractEventLoop,
args: tuple[dict[str, Any]],
kwargs: dict[str, Any],
) -> None:
context = args[0] if args else kwargs.get("context")
if context:
exc = context.get("exception")
if isinstance(exc, BaseException):
message = context.get("message")
self._emit_exception(
exc,
severity_text="ERROR",
severity_number=SeverityNumber.ERROR,
event_name=str(message) if message else type(exc).__name__,
)
wrapped(*args, **kwargs)
__all__ = ["UnhandledExceptionInstrumentor"]
package.py 0000664 0000000 0000000 00000000172 15270700723 0046321 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-exceptions/src/opentelemetry/instrumentation/exceptions # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
_instruments = ()
_supports_metrics = False
version.py 0000664 0000000 0000000 00000000144 15270700723 0046412 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-exceptions/src/opentelemetry/instrumentation/exceptions # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
__version__ = "0.66b2"
test-requirements.txt 0000664 0000000 0000000 00000000420 15270700723 0037502 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-exceptions asgiref==3.8.1
Deprecated==1.2.14
iniconfig==2.0.0
packaging==24.0
pluggy==1.6.0
py-cpuinfo==9.0.0
pytest==7.4.4
tomli==2.0.1
typing_extensions==4.12.2
wrapt==1.16.0
zipp==3.19.2
-e opentelemetry-instrumentation
-e instrumentation/opentelemetry-instrumentation-exceptions
opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-exceptions/tests/ 0000775 0000000 0000000 00000000000 15270700723 0034466 5 ustar 00root root 0000000 0000000 test_exceptions.py 0000664 0000000 0000000 00000024723 15270700723 0040211 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-exceptions/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
from __future__ import annotations
import asyncio
import sys
import threading
from collections.abc import Generator
import pytest
import opentelemetry._logs._internal
from opentelemetry._logs import (
SeverityNumber,
get_logger_provider,
set_logger_provider,
)
from opentelemetry.instrumentation.exceptions import (
UnhandledExceptionInstrumentor,
)
from opentelemetry.sdk._logs import LoggerProvider
from opentelemetry.sdk._logs.export import (
InMemoryLogRecordExporter,
SimpleLogRecordProcessor,
)
from opentelemetry.semconv.attributes import exception_attributes
from opentelemetry.util._once import Once
# pylint: disable=redefined-outer-name
@pytest.fixture
def log_exporter() -> Generator[InMemoryLogRecordExporter, None, None]:
snapshot = get_logger_provider()
opentelemetry._logs._internal._LOGGER_PROVIDER_SET_ONCE = Once()
provider = LoggerProvider()
exporter = InMemoryLogRecordExporter()
provider.add_log_record_processor(SimpleLogRecordProcessor(exporter))
set_logger_provider(provider)
try:
yield exporter
finally:
opentelemetry._logs._internal._LOGGER_PROVIDER_SET_ONCE = Once()
set_logger_provider(snapshot)
@pytest.fixture
def instrumentor() -> Generator[UnhandledExceptionInstrumentor, None, None]:
inst = UnhandledExceptionInstrumentor()
try:
yield inst
finally:
inst.uninstrument()
def _raised_value_error() -> ValueError:
try:
raise ValueError("boom")
except ValueError as exc:
return exc
def _finished_log(log_exporter: InMemoryLogRecordExporter):
logs = log_exporter.get_finished_logs()
assert len(logs) == 1
return logs[0].log_record
def test_sys_excepthook_emits_log(
log_exporter: InMemoryLogRecordExporter,
monkeypatch: pytest.MonkeyPatch,
instrumentor: UnhandledExceptionInstrumentor,
) -> None:
called = {"value": False}
def stub_excepthook(exc_type, exc, tb) -> None:
called["value"] = True
monkeypatch.setattr(sys, "excepthook", stub_excepthook)
instrumentor.instrument()
exc = _raised_value_error()
sys.excepthook(type(exc), exc, exc.__traceback__)
log_record = _finished_log(log_exporter)
assert log_record.severity_text == "FATAL"
assert log_record.severity_number == SeverityNumber.FATAL
assert log_record.event_name == "ValueError"
assert log_record.body == "boom"
assert called["value"] is True
attributes = log_record.attributes
assert attributes[exception_attributes.EXCEPTION_TYPE] == "ValueError"
assert isinstance(attributes[exception_attributes.EXCEPTION_TYPE], str)
assert attributes[exception_attributes.EXCEPTION_MESSAGE] == "boom"
assert isinstance(attributes[exception_attributes.EXCEPTION_MESSAGE], str)
assert "ValueError: boom" in attributes[exception_attributes.EXCEPTION_STACKTRACE]
assert isinstance(attributes[exception_attributes.EXCEPTION_STACKTRACE], str)
def test_threading_excepthook_emits_log(
log_exporter: InMemoryLogRecordExporter,
monkeypatch: pytest.MonkeyPatch,
instrumentor: UnhandledExceptionInstrumentor,
) -> None:
called = {"value": False}
def stub_threading_excepthook(args: threading.ExceptHookArgs) -> None:
called["value"] = True
monkeypatch.setattr(threading, "excepthook", stub_threading_excepthook)
instrumentor.instrument()
exc = _raised_value_error()
args = threading.ExceptHookArgs((type(exc), exc, exc.__traceback__, threading.current_thread()))
threading.excepthook(args)
log_record = _finished_log(log_exporter)
assert log_record.severity_text == "ERROR"
assert log_record.severity_number == SeverityNumber.ERROR
assert log_record.event_name == "ValueError"
assert log_record.body == "boom"
assert called["value"] is True
attributes = log_record.attributes
assert attributes[exception_attributes.EXCEPTION_TYPE] == "ValueError"
assert attributes[exception_attributes.EXCEPTION_MESSAGE] == "boom"
assert "ValueError: boom" in attributes[exception_attributes.EXCEPTION_STACKTRACE]
def test_asyncio_unhandled_exception_emits_log(
log_exporter: InMemoryLogRecordExporter,
monkeypatch: pytest.MonkeyPatch,
instrumentor: UnhandledExceptionInstrumentor,
) -> None:
called = {"value": False}
original_handler = asyncio.BaseEventLoop.call_exception_handler
def stub_call_exception_handler(loop, context) -> None:
called["value"] = True
original_handler(loop, context)
monkeypatch.setattr(
asyncio.BaseEventLoop,
"call_exception_handler",
stub_call_exception_handler,
)
instrumentor.instrument()
loop = asyncio.new_event_loop()
loop.set_exception_handler(lambda _loop, _context: None)
try:
exc = _raised_value_error()
loop.call_exception_handler({"exception": exc, "message": "task boom"})
finally:
loop.close()
log_record = _finished_log(log_exporter)
assert log_record.severity_text == "ERROR"
assert log_record.severity_number == SeverityNumber.ERROR
assert log_record.event_name == "task boom"
assert log_record.body == "boom"
assert called["value"] is True
attributes = log_record.attributes
assert attributes[exception_attributes.EXCEPTION_TYPE] == "ValueError"
assert attributes[exception_attributes.EXCEPTION_MESSAGE] == "boom"
assert "ValueError: boom" in attributes[exception_attributes.EXCEPTION_STACKTRACE]
def test_asyncio_unhandled_exception_called_with_kwarg_emits_log(
log_exporter: InMemoryLogRecordExporter,
monkeypatch: pytest.MonkeyPatch,
instrumentor: UnhandledExceptionInstrumentor,
) -> None:
called = {"value": False}
original_handler = asyncio.BaseEventLoop.call_exception_handler
def stub_call_exception_handler(loop, context) -> None:
called["value"] = True
original_handler(loop, context)
monkeypatch.setattr(
asyncio.BaseEventLoop,
"call_exception_handler",
stub_call_exception_handler,
)
instrumentor.instrument()
loop = asyncio.new_event_loop()
loop.set_exception_handler(lambda _loop, _context: None)
try:
exc = _raised_value_error()
loop.call_exception_handler(context={"exception": exc, "message": "task boom"})
finally:
loop.close()
log_record = _finished_log(log_exporter)
assert log_record.severity_text == "ERROR"
assert log_record.severity_number == SeverityNumber.ERROR
assert log_record.event_name == "task boom"
assert log_record.body == "boom"
assert called["value"] is True
attributes = log_record.attributes
assert attributes[exception_attributes.EXCEPTION_TYPE] == "ValueError"
assert attributes[exception_attributes.EXCEPTION_MESSAGE] == "boom"
assert "ValueError: boom" in attributes[exception_attributes.EXCEPTION_STACKTRACE]
def test_asyncio_unhandled_exception_invalid_call(
log_exporter: InMemoryLogRecordExporter,
monkeypatch: pytest.MonkeyPatch,
instrumentor: UnhandledExceptionInstrumentor,
) -> None:
called = {"value": False}
original_handler = asyncio.BaseEventLoop.call_exception_handler
def stub_call_exception_handler(loop, context) -> None:
called["value"] = True
original_handler(loop, context)
monkeypatch.setattr(
asyncio.BaseEventLoop,
"call_exception_handler",
stub_call_exception_handler,
)
instrumentor.instrument()
loop = asyncio.new_event_loop()
loop.set_exception_handler(lambda _loop, _context: None)
try:
_raised_value_error()
with pytest.raises(TypeError):
loop.call_exception_handler()
finally:
loop.close()
logs = log_exporter.get_finished_logs()
assert not logs
@pytest.mark.parametrize(
("message", "expected_event_name"),
((None, "ValueError"), (42, "42")),
)
def test_asyncio_event_name_falls_back_or_coerces(
log_exporter: InMemoryLogRecordExporter,
monkeypatch: pytest.MonkeyPatch,
instrumentor: UnhandledExceptionInstrumentor,
message: object,
expected_event_name: str,
) -> None:
monkeypatch.setattr(
asyncio.BaseEventLoop,
"call_exception_handler",
lambda _loop, _context: None,
)
instrumentor.instrument()
loop = asyncio.new_event_loop()
loop.set_exception_handler(lambda _loop, _context: None)
try:
exc = _raised_value_error()
loop.call_exception_handler({"exception": exc, "message": message})
finally:
loop.close()
assert _finished_log(log_exporter).event_name == expected_event_name
def test_base_exceptions_are_not_emitted(
log_exporter: InMemoryLogRecordExporter,
monkeypatch: pytest.MonkeyPatch,
instrumentor: UnhandledExceptionInstrumentor,
) -> None:
called = {"value": False}
def stub_excepthook(exc_type, exc, tb) -> None:
called["value"] = True
monkeypatch.setattr(sys, "excepthook", stub_excepthook)
instrumentor.instrument()
exc = KeyboardInterrupt()
sys.excepthook(type(exc), exc, exc.__traceback__)
assert not log_exporter.get_finished_logs()
assert called["value"] is True
def test_double_instrument_does_not_emit_duplicate_logs(
log_exporter: InMemoryLogRecordExporter,
monkeypatch: pytest.MonkeyPatch,
instrumentor: UnhandledExceptionInstrumentor,
) -> None:
monkeypatch.setattr(sys, "excepthook", lambda _exc_type, _exc, _tb: None)
instrumentor.instrument()
instrumentor.instrument()
exc = _raised_value_error()
sys.excepthook(type(exc), exc, exc.__traceback__)
assert len(log_exporter.get_finished_logs()) == 1
def test_uninstrument_restores_hooks(
monkeypatch: pytest.MonkeyPatch,
) -> None:
instrumentor = UnhandledExceptionInstrumentor()
def original_sys(exc_type, exc, tb) -> None:
del exc_type, exc, tb
def original_threading(args: threading.ExceptHookArgs) -> None:
del args
def original_asyncio(loop, context) -> None:
del loop, context
monkeypatch.setattr(sys, "excepthook", original_sys)
monkeypatch.setattr(threading, "excepthook", original_threading)
monkeypatch.setattr(
asyncio.BaseEventLoop,
"call_exception_handler",
original_asyncio,
)
instrumentor.instrument(logger_provider=LoggerProvider())
instrumentor.uninstrument()
assert sys.excepthook is original_sys
assert threading.excepthook is original_threading
assert asyncio.BaseEventLoop.call_exception_handler is original_asyncio
opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-falcon/ 0000775 0000000 0000000 00000000000 15270700723 0032405 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-falcon/LICENSE 0000664 0000000 0000000 00000026135 15270700723 0033421 0 ustar 00root root 0000000 0000000 Apache License
Version 2.0, January 2004
http://www.apache.org/licenses/
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opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-falcon/README.rst 0000664 0000000 0000000 00000005334 15270700723 0034101 0 ustar 00root root 0000000 0000000 OpenTelemetry Falcon Tracing
============================
|pypi|
.. |pypi| image:: https://badge.fury.io/py/opentelemetry-instrumentation-falcon.svg
:target: https://pypi.org/project/opentelemetry-instrumentation-falcon/
This library builds on the OpenTelemetry WSGI middleware to track web requests
in Falcon applications.
Installation
------------
::
pip install opentelemetry-instrumentation-falcon
Configuration
-------------
Exclude lists
*************
To exclude certain URLs from being tracked, set the environment variable ``OTEL_PYTHON_FALCON_EXCLUDED_URLS``
(or ``OTEL_PYTHON_EXCLUDED_URLS`` as fallback) with comma delimited regexes representing which URLs to exclude.
For example,
::
export OTEL_PYTHON_FALCON_EXCLUDED_URLS="client/.*/info,healthcheck"
will exclude requests such as ``https://site/client/123/info`` and ``https://site/xyz/healthcheck``.
Request attributes
********************
To extract certain attributes from Falcon's request object and use them as span attributes, set the environment variable ``OTEL_PYTHON_FALCON_TRACED_REQUEST_ATTRS`` to a comma
delimited list of request attribute names.
For example,
::
export OTEL_PYTHON_FALCON_TRACED_REQUEST_ATTRS='query_string,uri_template'
will extract path_info and content_type attributes from every traced request and add them as span attritbues.
Falcon Request object reference: https://falcon.readthedocs.io/en/stable/api/request_and_response.html#id1
Usage
-----
.. code-block:: python
import falcon
from opentelemetry.instrumentation.falcon import FalconInstrumentor
FalconInstrumentor().instrument()
app = falcon.App()
class HelloWorldResource(object):
def on_get(self, req, resp):
resp.text = 'Hello World'
app.add_route('/hello', HelloWorldResource())
Request/Response hooks
**********************
The instrumentation supports specifying request and response hooks. These are functions that get called back by the instrumentation right after a Span is created for a request
and right before the span is finished while processing a response. The hooks can be configured as follows:
.. code-block:: python
from opentelemetry.instrumentation.falcon import FalconInstrumentor
def request_hook(span, req):
pass
def response_hook(span, req, resp):
pass
FalconInstrumentor().instrument(request_hook=request_hook, response_hook=response_hook)
References
----------
* `OpenTelemetry Falcon Instrumentation `_
* `OpenTelemetry Project `_
* `OpenTelemetry Python Examples `_
pyproject.toml 0000664 0000000 0000000 00000003320 15270700723 0035240 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-falcon [build-system]
requires = ["hatchling"]
build-backend = "hatchling.build"
[project]
name = "opentelemetry-instrumentation-falcon"
dynamic = ["version"]
description = "Falcon instrumentation for OpenTelemetry"
readme = "README.rst"
license = "Apache-2.0"
requires-python = ">=3.10"
authors = [
{ name = "OpenTelemetry Authors", email = "cncf-opentelemetry-contributors@lists.cncf.io" },
]
classifiers = [
"Development Status :: 4 - Beta",
"Intended Audience :: Developers",
"License :: OSI Approved :: Apache Software License",
"Programming Language :: Python",
"Programming Language :: Python :: 3",
"Programming Language :: Python :: 3.10",
"Programming Language :: Python :: 3.11",
"Programming Language :: Python :: 3.12",
"Programming Language :: Python :: 3.13",
"Programming Language :: Python :: 3.14",
]
dependencies = [
"opentelemetry-api ~= 1.12",
"opentelemetry-instrumentation == 0.66b2",
"opentelemetry-instrumentation-wsgi == 0.66b2",
"opentelemetry-semantic-conventions == 0.66b2",
"opentelemetry-util-http == 0.66b2",
"packaging >= 20.0",
]
[project.optional-dependencies]
instruments = [
"falcon >= 1.4.1, < 5.0.0",
]
[project.entry-points.opentelemetry_instrumentor]
falcon = "opentelemetry.instrumentation.falcon:FalconInstrumentor"
[project.urls]
Homepage = "https://github.com/open-telemetry/opentelemetry-python-contrib/tree/main/instrumentation/opentelemetry-instrumentation-falcon"
Repository = "https://github.com/open-telemetry/opentelemetry-python-contrib"
[tool.hatch.version]
path = "src/opentelemetry/instrumentation/falcon/version.py"
[tool.hatch.build.targets.sdist]
include = [
"/src",
"/tests",
]
[tool.hatch.build.targets.wheel]
packages = ["src/opentelemetry"]
opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-falcon/src/ 0000775 0000000 0000000 00000000000 15270700723 0033174 5 ustar 00root root 0000000 0000000 opentelemetry/ 0000775 0000000 0000000 00000000000 15270700723 0036011 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-falcon/src instrumentation/ 0000775 0000000 0000000 00000000000 15270700723 0041254 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-falcon/src/opentelemetry falcon/ 0000775 0000000 0000000 00000000000 15270700723 0042516 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-falcon/src/opentelemetry/instrumentation __init__.py 0000664 0000000 0000000 00000051322 15270700723 0044632 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-falcon/src/opentelemetry/instrumentation/falcon # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
"""
This library builds on the OpenTelemetry WSGI middleware to track web requests
in Falcon applications. In addition to opentelemetry-instrumentation-wsgi,
it supports falcon-specific features such as:
* The Falcon resource and method name is used as the Span name.
* The ``falcon.resource`` Span attribute is set so the matched resource.
* Errors from Falcon resources are properly caught and recorded.
Configuration
-------------
Exclude lists
*************
To exclude certain URLs from tracking, set the environment variable ``OTEL_PYTHON_FALCON_EXCLUDED_URLS``
(or ``OTEL_PYTHON_EXCLUDED_URLS`` to cover all instrumentations) to a string of comma delimited regexes that match the
URLs.
For example,
::
export OTEL_PYTHON_FALCON_EXCLUDED_URLS="client/.*/info,healthcheck"
will exclude requests such as ``https://site/client/123/info`` and ``https://site/xyz/healthcheck``.
Request attributes
********************
To extract attributes from Falcon's request object and use them as span attributes, set the environment variable
``OTEL_PYTHON_FALCON_TRACED_REQUEST_ATTRS`` to a comma delimited list of request attribute names.
For example,
::
export OTEL_PYTHON_FALCON_TRACED_REQUEST_ATTRS='query_string,uri_template'
will extract the ``query_string`` and ``uri_template`` attributes from every traced request and add them as span attributes.
Falcon Request object reference: https://falcon.readthedocs.io/en/stable/api/request_and_response.html#id1
Usage
-----
.. code-block:: python
import falcon
from opentelemetry.instrumentation.falcon import FalconInstrumentor
FalconInstrumentor().instrument()
app = falcon.App()
class HelloWorldResource(object):
def on_get(self, req, resp):
resp.text = "Hello World"
app.add_route("/hello", HelloWorldResource())
Request and Response hooks
***************************
This instrumentation supports request and response hooks. These are functions that get called
right after a span is created for a request and right before the span is finished for the response.
The hooks can be configured as follows:
.. code-block:: python
from opentelemetry.instrumentation.falcon import FalconInstrumentor
def request_hook(span, req):
pass
def response_hook(span, req, resp):
pass
FalconInstrumentor().instrument(request_hook=request_hook, response_hook=response_hook)
Capture HTTP request and response headers
*****************************************
You can configure the agent to capture specified HTTP headers as span attributes, according to the
`semantic convention `_.
Request headers
***************
To capture HTTP request headers as span attributes, set the environment variable
``OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_REQUEST`` to a comma delimited list of HTTP header names.
For example,
::
export OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_REQUEST="content-type,custom_request_header"
will extract ``content-type`` and ``custom_request_header`` from the request headers and add them as span attributes.
Request header names in Falcon are case-insensitive and ``-`` characters are replaced by ``_``. So, giving the header
name as ``CUStom_Header`` in the environment variable will capture the header named ``custom-header``.
Regular expressions may also be used to match multiple headers that correspond to the given pattern. For example:
::
export OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_REQUEST="Accept.*,X-.*"
Would match all request headers that start with ``Accept`` and ``X-``.
To capture all request headers, set ``OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_REQUEST`` to ``".*"``.
::
export OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_REQUEST=".*"
The name of the added span attribute will follow the format ``http.request.header.`` where ````
is the normalized HTTP header name (lowercase, with ``-`` replaced by ``_``). The value of the attribute will be a
single item list containing all the header values.
For example:
``http.request.header.custom_request_header = [","]``
Response headers
****************
To capture HTTP response headers as span attributes, set the environment variable
``OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_RESPONSE`` to a comma delimited list of HTTP header names.
For example,
::
export OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_RESPONSE="content-type,custom_response_header"
will extract ``content-type`` and ``custom_response_header`` from the response headers and add them as span attributes.
Response header names in Falcon are case-insensitive. So, giving the header name as ``CUStom-Header`` in the environment
variable will capture the header named ``custom-header``.
Regular expressions may also be used to match multiple headers that correspond to the given pattern. For example:
::
export OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_RESPONSE="Content.*,X-.*"
Would match all response headers that start with ``Content`` and ``X-``.
To capture all response headers, set ``OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_RESPONSE`` to ``".*"``.
::
export OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_RESPONSE=".*"
The name of the added span attribute will follow the format ``http.response.header.`` where ````
is the normalized HTTP header name (lowercase, with ``-`` replaced by ``_``). The value of the attribute will be a
single item list containing all the header values.
For example:
``http.response.header.custom_response_header = [","]``
Sanitizing headers
******************
In order to prevent storing sensitive data such as personally identifiable information (PII), session keys, passwords,
etc, set the environment variable ``OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SANITIZE_FIELDS``
to a comma delimited list of HTTP header names to be sanitized. Regexes may be used, and all header names will be
matched in a case-insensitive manner.
For example,
::
export OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SANITIZE_FIELDS=".*session.*,set-cookie"
will replace the value of headers such as ``session-id`` and ``set-cookie`` with ``[REDACTED]`` in the span.
Note:
The environment variable names used to capture HTTP headers are still experimental, and thus are subject to change.
API
---
"""
from collections.abc import Collection
from logging import getLogger
from sys import exc_info
from time import time_ns
from timeit import default_timer
import falcon
from packaging import version as package_version
import opentelemetry.instrumentation.wsgi as otel_wsgi
from opentelemetry import context, trace
from opentelemetry.instrumentation._semconv import (
HTTP_DURATION_HISTOGRAM_BUCKETS_NEW,
_get_schema_url,
_OpenTelemetrySemanticConventionStability,
_OpenTelemetryStabilitySignalType,
_report_new,
_report_old,
_StabilityMode,
)
from opentelemetry.instrumentation.falcon.package import _instruments
from opentelemetry.instrumentation.falcon.version import __version__
from opentelemetry.instrumentation.instrumentor import BaseInstrumentor
from opentelemetry.instrumentation.propagators import (
FuncSetter,
get_global_response_propagator,
)
from opentelemetry.instrumentation.utils import (
_start_internal_or_server_span,
extract_attributes_from_object,
)
from opentelemetry.metrics import get_meter
from opentelemetry.semconv.attributes.http_attributes import (
HTTP_ROUTE,
)
from opentelemetry.semconv.metrics import MetricInstruments
from opentelemetry.semconv.metrics.http_metrics import (
HTTP_SERVER_REQUEST_DURATION,
)
from opentelemetry.util.http import get_excluded_urls, get_traced_request_attrs
_logger = getLogger(__name__)
_ENVIRON_STARTTIME_KEY = "opentelemetry-falcon.starttime_key"
_ENVIRON_SPAN_KEY = "opentelemetry-falcon.span_key"
_ENVIRON_REQ_ATTRS = "opentelemetry-falcon.req_attrs"
_ENVIRON_ACTIVATION_KEY = "opentelemetry-falcon.activation_key"
_ENVIRON_TOKEN = "opentelemetry-falcon.token"
_ENVIRON_EXC = "opentelemetry-falcon.exc"
_response_propagation_setter = FuncSetter(falcon.Response.append_header)
_parsed_falcon_version = package_version.parse(falcon.__version__)
if _parsed_falcon_version >= package_version.parse("3.0.0"):
# Falcon 3
_instrument_app = "App"
_falcon_version = 3
elif _parsed_falcon_version >= package_version.parse("2.0.0"):
# Falcon 2
_instrument_app = "API"
_falcon_version = 2
else:
# Falcon 1
_instrument_app = "API"
_falcon_version = 1
class _InstrumentedFalconAPI(getattr(falcon, _instrument_app)):
_instrumented_falcon_apps = set()
def __init__(self, *args, **kwargs):
otel_opts = kwargs.pop("_otel_opts", {})
self._sem_conv_opt_in_mode = _OpenTelemetrySemanticConventionStability._get_opentelemetry_stability_opt_in_mode(
_OpenTelemetryStabilitySignalType.HTTP,
)
# inject trace middleware
self._middlewares_list = kwargs.pop("middleware", [])
if self._middlewares_list is None:
self._middlewares_list = []
tracer_provider = otel_opts.pop("tracer_provider", None)
meter_provider = otel_opts.pop("meter_provider", None)
if not isinstance(self._middlewares_list, (list, tuple)):
self._middlewares_list = [self._middlewares_list]
self._otel_tracer = trace.get_tracer(
__name__,
__version__,
tracer_provider,
schema_url=_get_schema_url(self._sem_conv_opt_in_mode),
)
self._otel_meter = get_meter(
__name__,
__version__,
meter_provider,
schema_url=_get_schema_url(self._sem_conv_opt_in_mode),
)
self.duration_histogram_old = None
if _report_old(self._sem_conv_opt_in_mode):
self.duration_histogram_old = self._otel_meter.create_histogram(
name=MetricInstruments.HTTP_SERVER_DURATION,
unit="ms",
description="Measures the duration of inbound HTTP requests.",
)
self.duration_histogram_new = None
if _report_new(self._sem_conv_opt_in_mode):
self.duration_histogram_new = self._otel_meter.create_histogram(
name=HTTP_SERVER_REQUEST_DURATION,
description="Duration of HTTP server requests.",
unit="s",
explicit_bucket_boundaries_advisory=HTTP_DURATION_HISTOGRAM_BUCKETS_NEW,
)
self.active_requests_counter = self._otel_meter.create_up_down_counter(
name=MetricInstruments.HTTP_SERVER_ACTIVE_REQUESTS,
unit="requests",
description="measures the number of concurrent HTTP requests that are currently in-flight",
)
trace_middleware = _TraceMiddleware(
self._otel_tracer,
otel_opts.pop("traced_request_attributes", get_traced_request_attrs("FALCON")),
otel_opts.pop("request_hook", None),
otel_opts.pop("response_hook", None),
self._sem_conv_opt_in_mode,
)
self._middlewares_list.insert(0, trace_middleware)
kwargs["middleware"] = self._middlewares_list
self._otel_excluded_urls = get_excluded_urls("FALCON")
self._is_instrumented_by_opentelemetry = True
_InstrumentedFalconAPI._instrumented_falcon_apps.add(self)
super().__init__(*args, **kwargs)
def __del__(self):
if self in _InstrumentedFalconAPI._instrumented_falcon_apps:
_InstrumentedFalconAPI._instrumented_falcon_apps.remove(self)
def _handle_exception(self, *args):
# Falcon 3 does not execute middleware within the context
# of the exception so we capture the exception here and
# save it into the env dict
if not self._is_instrumented_by_opentelemetry:
return super()._handle_exception(*args)
if _falcon_version == 1:
_, req, _, _ = args # ex, req, resp, params
else:
req, _, _, _ = args # req, resp, ex, params
_, exc, _ = exc_info()
req.env[_ENVIRON_EXC] = exc
return super()._handle_exception(*args)
def __call__(self, env, start_response):
# pylint: disable=unnecessary-dunder-call
# pylint: disable=too-many-locals
# pylint: disable=too-many-branches
if self._otel_excluded_urls.url_disabled(env.get("PATH_INFO", "/")):
return super().__call__(env, start_response)
if not self._is_instrumented_by_opentelemetry:
return super().__call__(env, start_response)
start_time = time_ns()
attributes = otel_wsgi.collect_request_attributes(env, self._sem_conv_opt_in_mode)
span, token = _start_internal_or_server_span(
tracer=self._otel_tracer,
span_name=otel_wsgi.get_default_span_name(env),
start_time=start_time,
context_carrier=env,
context_getter=otel_wsgi.wsgi_getter,
attributes=attributes,
)
active_requests_count_attrs = otel_wsgi._parse_active_request_count_attrs(
attributes, self._sem_conv_opt_in_mode
)
self.active_requests_counter.add(1, active_requests_count_attrs)
if span.is_recording():
if span.is_recording() and span.kind == trace.SpanKind.SERVER:
custom_attributes = otel_wsgi.collect_custom_request_headers_attributes(env)
if len(custom_attributes) > 0:
span.set_attributes(custom_attributes)
activation = trace.use_span(span, end_on_exit=True)
activation.__enter__()
env[_ENVIRON_SPAN_KEY] = span
env[_ENVIRON_ACTIVATION_KEY] = activation
env[_ENVIRON_REQ_ATTRS] = attributes
exception = None
def _start_response(status, response_headers, *args, **kwargs):
response = start_response(status, response_headers, *args, **kwargs)
return response
start = default_timer()
try:
return super().__call__(env, _start_response)
except Exception as exc:
exception = exc
raise
finally:
duration_s = default_timer() - start
if self.duration_histogram_old:
duration_attrs = otel_wsgi._parse_duration_attrs(attributes, _StabilityMode.DEFAULT)
self.duration_histogram_old.record(max(round(duration_s * 1000), 0), duration_attrs)
if self.duration_histogram_new:
duration_attrs = otel_wsgi._parse_duration_attrs(attributes, _StabilityMode.HTTP)
self.duration_histogram_new.record(max(duration_s, 0), duration_attrs)
self.active_requests_counter.add(-1, active_requests_count_attrs)
if exception is None:
activation.__exit__(None, None, None)
else:
activation.__exit__(
type(exception),
exception,
getattr(exception, "__traceback__", None),
)
if token is not None:
context.detach(token)
class _TraceMiddleware:
# pylint:disable=R0201,W0613
def __init__(
self,
tracer=None,
traced_request_attrs=None,
request_hook=None,
response_hook=None,
sem_conv_opt_in_mode: _StabilityMode = _StabilityMode.DEFAULT,
):
self.tracer = tracer
self._traced_request_attrs = traced_request_attrs
self._request_hook = request_hook
self._response_hook = response_hook
self._sem_conv_opt_in_mode = sem_conv_opt_in_mode
def process_request(self, req, resp):
span = req.env.get(_ENVIRON_SPAN_KEY)
if span and self._request_hook:
self._request_hook(span, req)
if not span or not span.is_recording():
return
attributes = extract_attributes_from_object(req, self._traced_request_attrs)
for key, value in attributes.items():
span.set_attribute(key, value)
def process_resource(self, req, resp, resource, params):
span = req.env.get(_ENVIRON_SPAN_KEY)
if not span or not span.is_recording():
return
resource_name = resource.__class__.__name__
span.set_attribute("falcon.resource", resource_name)
def process_response(self, req, resp, resource, req_succeeded=None): # pylint:disable=R0201,R0912
span = req.env.get(_ENVIRON_SPAN_KEY)
req_attrs = req.env.get(_ENVIRON_REQ_ATTRS)
if not span:
return
status = resp.status
if resource is None:
status = falcon.HTTP_404
else:
exc_type, exc = None, None
if _ENVIRON_EXC in req.env:
exc = req.env[_ENVIRON_EXC]
exc_type = type(exc)
if exc_type and not req_succeeded:
if "HTTPNotFound" in exc_type.__name__:
status = falcon.HTTP_404
elif isinstance(exc, (falcon.HTTPError, falcon.HTTPStatus)):
try:
if _falcon_version > 2:
status = falcon.code_to_http_status(exc.status)
else:
status = exc.status
except ValueError:
status = falcon.HTTP_500
else:
status = falcon.HTTP_500
# Falcon 1 does not support response headers. So
# send an empty dict.
response_headers = {}
if _falcon_version > 1:
response_headers = resp.headers
otel_wsgi.add_response_attributes(
span,
status,
response_headers,
req_attrs,
self._sem_conv_opt_in_mode,
)
if _report_new(self._sem_conv_opt_in_mode) and req.uri_template and req_attrs is not None:
req_attrs[HTTP_ROUTE] = req.uri_template
try:
if span.is_recording() and span.kind == trace.SpanKind.SERVER:
# Check if low-cardinality route is available as per semantic-conventions
if req.uri_template:
span.update_name(f"{req.method} {req.uri_template}")
span.set_attribute(HTTP_ROUTE, req.uri_template)
else:
span.update_name(f"{req.method}")
custom_attributes = otel_wsgi.collect_custom_response_headers_attributes(response_headers.items())
if len(custom_attributes) > 0:
span.set_attributes(custom_attributes)
except ValueError:
pass
propagator = get_global_response_propagator()
if propagator:
propagator.inject(resp, setter=_response_propagation_setter)
if self._response_hook:
self._response_hook(span, req, resp)
class FalconInstrumentor(BaseInstrumentor):
# pylint: disable=protected-access
"""An instrumentor for falcon.API
See `BaseInstrumentor`
"""
def instrumentation_dependencies(self) -> Collection[str]:
return _instruments
# pylint:disable=no-self-use
def _remove_instrumented_middleware(self, app):
if hasattr(app, "_is_instrumented_by_opentelemetry") and app._is_instrumented_by_opentelemetry:
if _falcon_version == 3:
app._unprepared_middleware = [
x for x in app._unprepared_middleware if not isinstance(x, _TraceMiddleware)
]
app._middleware = app._prepare_middleware(
app._unprepared_middleware,
independent_middleware=app._independent_middleware,
)
else:
app._middlewares_list = [x for x in app._middlewares_list if not isinstance(x, _TraceMiddleware)]
# pylint: disable=no-member
app._middleware = falcon.api_helpers.prepare_middleware(
app._middlewares_list,
independent_middleware=app._independent_middleware,
)
app._is_instrumented_by_opentelemetry = False
def _instrument(self, **opts):
self._original_falcon_api = getattr(falcon, _instrument_app)
class FalconAPI(_InstrumentedFalconAPI):
def __init__(self, *args, **kwargs):
kwargs["_otel_opts"] = opts
super().__init__(*args, **kwargs)
setattr(falcon, _instrument_app, FalconAPI)
def _uninstrument(self, **kwargs):
for app in _InstrumentedFalconAPI._instrumented_falcon_apps:
self._remove_instrumented_middleware(app)
_InstrumentedFalconAPI._instrumented_falcon_apps.clear()
setattr(falcon, _instrument_app, self._original_falcon_api)
package.py 0000664 0000000 0000000 00000000264 15270700723 0044465 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-falcon/src/opentelemetry/instrumentation/falcon # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
_instruments = ("falcon >= 1.4.1, < 5.0.0",)
_supports_metrics = True
_semconv_status = "migration"
version.py 0000664 0000000 0000000 00000000144 15270700723 0044554 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-falcon/src/opentelemetry/instrumentation/falcon # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
__version__ = "0.66b2"
test-requirements-0.txt 0000664 0000000 0000000 00000000624 15270700723 0036726 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-falcon asgiref==3.8.1
Deprecated==1.2.14
falcon==1.4.1
iniconfig==2.0.0
packaging==24.0
pluggy==1.6.0
py-cpuinfo==9.0.0
pytest==7.4.4
python-mimeparse==1.6.0
six==1.16.0
tomli==2.0.1
typing_extensions==4.12.2
wrapt==1.16.0
zipp==3.19.2
-e opentelemetry-instrumentation
-e instrumentation/opentelemetry-instrumentation-wsgi
-e util/opentelemetry-util-http
-e instrumentation/opentelemetry-instrumentation-falcon
test-requirements-1.txt 0000664 0000000 0000000 00000000560 15270700723 0036726 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-falcon asgiref==3.8.1
Deprecated==1.2.14
falcon==2.0.0
iniconfig==2.0.0
packaging==24.0
pluggy==1.6.0
py-cpuinfo==9.0.0
pytest==7.4.4
tomli==2.0.1
typing_extensions==4.12.2
wrapt==1.16.0
zipp==3.19.2
-e opentelemetry-instrumentation
-e instrumentation/opentelemetry-instrumentation-wsgi
-e util/opentelemetry-util-http
-e instrumentation/opentelemetry-instrumentation-falcon
test-requirements-2.txt 0000664 0000000 0000000 00000000560 15270700723 0036727 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-falcon asgiref==3.8.1
Deprecated==1.2.14
falcon==3.1.1
iniconfig==2.0.0
packaging==24.0
pluggy==1.6.0
py-cpuinfo==9.0.0
pytest==7.4.4
tomli==2.0.1
typing_extensions==4.12.2
wrapt==1.16.0
zipp==3.19.2
-e opentelemetry-instrumentation
-e instrumentation/opentelemetry-instrumentation-wsgi
-e util/opentelemetry-util-http
-e instrumentation/opentelemetry-instrumentation-falcon
test-requirements-3.txt 0000664 0000000 0000000 00000000560 15270700723 0036730 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-falcon asgiref==3.8.1
Deprecated==1.2.14
falcon==3.1.3
iniconfig==2.0.0
packaging==24.0
pluggy==1.6.0
py-cpuinfo==9.0.0
pytest==7.4.4
tomli==2.0.1
typing_extensions==4.12.2
wrapt==1.16.0
zipp==3.19.2
-e opentelemetry-instrumentation
-e instrumentation/opentelemetry-instrumentation-wsgi
-e util/opentelemetry-util-http
-e instrumentation/opentelemetry-instrumentation-falcon
test-requirements-4.txt 0000664 0000000 0000000 00000000560 15270700723 0036731 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-falcon asgiref==3.8.1
Deprecated==1.2.14
falcon==4.0.2
iniconfig==2.0.0
packaging==24.0
pluggy==1.6.0
py-cpuinfo==9.0.0
pytest==7.4.4
tomli==2.0.1
typing_extensions==4.12.2
wrapt==1.16.0
zipp==3.19.2
-e opentelemetry-instrumentation
-e instrumentation/opentelemetry-instrumentation-wsgi
-e util/opentelemetry-util-http
-e instrumentation/opentelemetry-instrumentation-falcon
opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-falcon/tests/ 0000775 0000000 0000000 00000000000 15270700723 0033547 5 ustar 00root root 0000000 0000000 __init__.py 0000664 0000000 0000000 00000000000 15270700723 0035567 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-falcon/tests app.py 0000664 0000000 0000000 00000005233 15270700723 0034625 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-falcon/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
import falcon
from packaging import version as package_version
# pylint:disable=R0201,W0613,E0602
_parsed_falcon_version = package_version.parse(falcon.__version__)
class HelloWorldResource:
def _handle_request(self, _, resp):
# pylint: disable=no-member
resp.status = falcon.HTTP_201
if _parsed_falcon_version < package_version.parse("3.0.0"):
# Falcon 1 and Falcon 2
resp.body = "Hello World"
else:
resp.text = "Hello World"
def on_get(self, req, resp):
self._handle_request(req, resp)
def on_put(self, req, resp):
self._handle_request(req, resp)
def on_patch(self, req, resp):
self._handle_request(req, resp)
def on_post(self, req, resp):
self._handle_request(req, resp)
def on_delete(self, req, resp):
self._handle_request(req, resp)
def on_head(self, req, resp):
self._handle_request(req, resp)
class ErrorResource:
def on_get(self, req, resp):
print(non_existent_var) # noqa
class CustomResponseHeaderResource:
def on_get(self, _, resp):
# pylint: disable=no-member
resp.status = falcon.HTTP_201
resp.set_header("content-type", "text/plain; charset=utf-8")
resp.set_header("content-length", "0")
resp.set_header("my-custom-header", "my-custom-value-1,my-custom-header-2")
resp.set_header("dont-capture-me", "test-value")
resp.set_header(
"my-custom-regex-header-1",
"my-custom-regex-value-1,my-custom-regex-value-2",
)
resp.set_header(
"My-Custom-Regex-Header-2",
"my-custom-regex-value-3,my-custom-regex-value-4",
)
resp.set_header("my-secret-header", "my-secret-value")
class UserResource:
def on_get(self, req, resp, user_id):
# pylint: disable=no-member
resp.status = falcon.HTTP_200
if _parsed_falcon_version < package_version.parse("3.0.0"):
# Falcon 1 and Falcon 2
resp.body = f"Hello user {user_id}"
else:
resp.text = f"Hello user {user_id}"
def make_app():
if _parsed_falcon_version < package_version.parse("3.0.0"):
# Falcon 1 and Falcon 2
app = falcon.API()
else:
# Falcon 3
app = falcon.App()
app.add_route("/hello", HelloWorldResource())
app.add_route("/ping", HelloWorldResource())
app.add_route("/error", ErrorResource())
app.add_route("/test_custom_response_headers", CustomResponseHeaderResource())
app.add_route("/user/{user_id}", UserResource())
return app
test_falcon.py 0000664 0000000 0000000 00000077452 15270700723 0036362 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-falcon/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
#
from timeit import default_timer
from unittest.mock import Mock, patch
import pytest
from falcon import __version__ as _falcon_version
from falcon import testing
from packaging import version as package_version
from opentelemetry import trace
from opentelemetry.instrumentation._semconv import (
HTTP_DURATION_HISTOGRAM_BUCKETS_NEW,
OTEL_SEMCONV_STABILITY_OPT_IN,
_OpenTelemetrySemanticConventionStability,
_server_active_requests_count_attrs_new,
_server_active_requests_count_attrs_old,
_server_duration_attrs_new,
_server_duration_attrs_old,
)
from opentelemetry.instrumentation.falcon import FalconInstrumentor
from opentelemetry.instrumentation.propagators import (
TraceResponsePropagator,
get_global_response_propagator,
set_global_response_propagator,
)
from opentelemetry.sdk.metrics.export import (
HistogramDataPoint,
NumberDataPoint,
)
from opentelemetry.sdk.resources import Resource
from opentelemetry.semconv._incubating.attributes.http_attributes import (
HTTP_FLAVOR,
HTTP_HOST,
HTTP_METHOD,
HTTP_SCHEME,
HTTP_SERVER_NAME,
HTTP_STATUS_CODE,
HTTP_TARGET,
)
from opentelemetry.semconv._incubating.attributes.net_attributes import (
NET_HOST_PORT,
NET_PEER_IP,
NET_PEER_PORT,
)
from opentelemetry.semconv.attributes.client_attributes import (
CLIENT_PORT,
)
from opentelemetry.semconv.attributes.http_attributes import (
HTTP_REQUEST_METHOD,
HTTP_RESPONSE_STATUS_CODE,
HTTP_ROUTE,
)
from opentelemetry.semconv.attributes.network_attributes import (
NETWORK_PROTOCOL_VERSION,
)
from opentelemetry.semconv.attributes.server_attributes import (
SERVER_ADDRESS,
SERVER_PORT,
)
from opentelemetry.semconv.attributes.url_attributes import (
URL_PATH,
URL_SCHEME,
)
from opentelemetry.test.test_base import TestBase
from opentelemetry.test.wsgitestutil import WsgiTestBase
from opentelemetry.trace import StatusCode
from opentelemetry.util.http import (
OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SANITIZE_FIELDS,
OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_REQUEST,
OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_RESPONSE,
)
from .app import make_app
_expected_metric_names = [
"http.server.active_requests",
"http.server.duration",
]
_recommended_attrs = {
"http.server.active_requests": _server_active_requests_count_attrs_new + _server_active_requests_count_attrs_old,
"http.server.duration": _server_duration_attrs_new + _server_duration_attrs_old,
}
_recommended_metrics_attrs_old = {
"http.server.active_requests": _server_active_requests_count_attrs_old,
"http.server.duration": _server_duration_attrs_old,
}
_recommended_metrics_attrs_new = {
"http.server.active_requests": _server_active_requests_count_attrs_new,
"http.server.request.duration": _server_duration_attrs_new,
}
_server_active_requests_count_attrs_both = _server_active_requests_count_attrs_old
_server_active_requests_count_attrs_both.extend(_server_active_requests_count_attrs_new)
_recommended_metrics_attrs_both = {
"http.server.active_requests": _server_active_requests_count_attrs_both,
"http.server.duration": _server_duration_attrs_old,
"http.server.request.duration": _server_duration_attrs_new,
}
_parsed_falcon_version = package_version.parse(_falcon_version)
SCOPE = "opentelemetry.instrumentation.falcon"
class TestFalconBase(TestBase):
def setUp(self):
super().setUp()
test_name = ""
if hasattr(self, "_testMethodName"):
test_name = self._testMethodName
sem_conv_mode = "default"
if "new_semconv" in test_name:
sem_conv_mode = "http"
elif "both_semconv" in test_name:
sem_conv_mode = "http/dup"
self.env_patch = patch.dict(
"os.environ",
{
"OTEL_PYTHON_FALCON_EXCLUDED_URLS": "ping",
"OTEL_PYTHON_FALCON_TRACED_REQUEST_ATTRS": "query_string",
OTEL_SEMCONV_STABILITY_OPT_IN: sem_conv_mode,
},
)
_OpenTelemetrySemanticConventionStability._initialized = False
self.env_patch.start()
FalconInstrumentor().instrument(
request_hook=getattr(self, "request_hook", None),
response_hook=getattr(self, "response_hook", None),
)
self.app = make_app()
@property
def _has_fixed_http_target(self):
# In falcon<3.1.2, HTTP_TARGET is always set to / in TestClient
# In falcon>=3.1.2, HTTP_TARGET is set to unencoded path by default
# https://github.com/falconry/falcon/blob/69cdcd6edd2ee33f4ac9f7793e1cc3c4f99da692/falcon/testing/helpers.py#L1153-1156
return _parsed_falcon_version < package_version.parse("3.1.2")
def client(self):
return testing.TestClient(self.app)
def tearDown(self):
super().tearDown()
with self.disable_logging():
FalconInstrumentor().uninstrument()
self.env_patch.stop()
# pylint: disable=too-many-public-methods
class TestFalconInstrumentation(TestFalconBase, WsgiTestBase):
def test_get(self):
self._test_method("GET")
def test_get_new_semconv(self):
self._test_method("GET", old_semconv=False, new_semconv=True)
def test_get_both_semconv(self):
self._test_method("GET", old_semconv=True, new_semconv=True)
def test_post(self):
self._test_method("POST")
def test_post_new_semconv(self):
self._test_method("POST", old_semconv=False, new_semconv=True)
def test_post_both_semconv(self):
self._test_method("POST", old_semconv=True, new_semconv=True)
def test_patch(self):
self._test_method("PATCH")
def test_patch_new_semconv(self):
self._test_method("PATCH", old_semconv=False, new_semconv=True)
def test_patch_both_semconv(self):
self._test_method("PATCH", old_semconv=True, new_semconv=True)
def test_put(self):
self._test_method("PUT")
def test_put_new_semconv(self):
self._test_method("PUT", old_semconv=False, new_semconv=True)
def test_put_both_semconv(self):
self._test_method("PUT", old_semconv=True, new_semconv=True)
def test_delete(self):
self._test_method("DELETE")
def test_delete_new_semconv(self):
self._test_method("DELETE", old_semconv=False, new_semconv=True)
def test_delete_both_semconv(self):
self._test_method("DELETE", old_semconv=True, new_semconv=True)
def test_head(self):
self._test_method("HEAD")
def test_head_new_semconv(self):
self._test_method("HEAD", old_semconv=False, new_semconv=True)
def test_head_both_semconv(self):
self._test_method("HEAD", old_semconv=True, new_semconv=True)
def _test_method(self, method, old_semconv=True, new_semconv=False):
self.client().simulate_request(method=method, path="/hello")
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
span = spans[0]
self.assertEqual(span.name, f"{method} /hello")
self.assertEqual(span.status.status_code, StatusCode.UNSET)
self.assertEqual(
span.status.description,
None,
)
expected_attributes = {}
expected_attributes_old = {
HTTP_METHOD: method,
HTTP_SERVER_NAME: "falconframework.org",
HTTP_SCHEME: "http",
NET_HOST_PORT: 80,
HTTP_HOST: "falconframework.org",
HTTP_TARGET: "/" if self._has_fixed_http_target else "/hello",
NET_PEER_PORT: 65133,
HTTP_FLAVOR: "1.1",
"falcon.resource": "HelloWorldResource",
HTTP_STATUS_CODE: 201,
HTTP_ROUTE: "/hello",
}
expected_attributes_new = {
HTTP_REQUEST_METHOD: method,
SERVER_ADDRESS: "falconframework.org",
URL_SCHEME: "http",
SERVER_PORT: 80,
URL_PATH: "/hello",
CLIENT_PORT: 65133,
NETWORK_PROTOCOL_VERSION: "1.1",
"falcon.resource": "HelloWorldResource",
HTTP_RESPONSE_STATUS_CODE: 201,
HTTP_ROUTE: "/hello",
}
if old_semconv:
expected_attributes.update(expected_attributes_old)
if new_semconv:
expected_attributes.update(expected_attributes_new)
self.assertSpanHasAttributes(span, expected_attributes)
# In falcon<3, NET_PEER_IP is always set by default to 127.0.0.1
# In falcon>=3, NET_PEER_IP is not set to anything by default
# https://github.com/falconry/falcon/blob/5233d0abed977d9dab78ebadf305f5abe2eef07c/falcon/testing/helpers.py#L1168-L1172
if NET_PEER_IP in span.attributes:
self.assertEqual(span.attributes[NET_PEER_IP], "127.0.0.1")
self.memory_exporter.clear()
def test_404(self):
self.client().simulate_get("/does-not-exist")
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
span = spans[0]
self.assertEqual(span.name, "GET")
self.assertEqual(span.status.status_code, StatusCode.UNSET)
self.assertSpanHasAttributes(
span,
{
HTTP_METHOD: "GET",
HTTP_SERVER_NAME: "falconframework.org",
HTTP_SCHEME: "http",
NET_HOST_PORT: 80,
HTTP_HOST: "falconframework.org",
HTTP_TARGET: "/" if self._has_fixed_http_target else "/does-not-exist",
NET_PEER_PORT: 65133,
HTTP_FLAVOR: "1.1",
HTTP_STATUS_CODE: 404,
},
)
# In falcon<3, NET_PEER_IP is always set by default to 127.0.0.1
# In falcon>=3, NET_PEER_IP is not set to anything by default
# https://github.com/falconry/falcon/blob/5233d0abed977d9dab78ebadf305f5abe2eef07c/falcon/testing/helpers.py#L1168-L1172
if NET_PEER_IP in span.attributes:
self.assertEqual(span.attributes[NET_PEER_IP], "127.0.0.1")
def test_500(self):
try:
self.client().simulate_get("/error")
except NameError:
pass
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
span = spans[0]
self.assertEqual(span.name, "GET /error")
self.assertFalse(span.status.is_ok)
self.assertEqual(span.status.status_code, StatusCode.ERROR)
_parsed_falcon_version = package_version.parse(_falcon_version)
if _parsed_falcon_version < package_version.parse("3.0.0"):
self.assertEqual(
span.status.description,
"NameError: name 'non_existent_var' is not defined",
)
else:
self.assertEqual(span.status.description, None)
self.assertSpanHasAttributes(
span,
{
HTTP_METHOD: "GET",
HTTP_SERVER_NAME: "falconframework.org",
HTTP_SCHEME: "http",
NET_HOST_PORT: 80,
HTTP_HOST: "falconframework.org",
HTTP_TARGET: "/" if self._has_fixed_http_target else "/error",
NET_PEER_PORT: 65133,
HTTP_FLAVOR: "1.1",
HTTP_STATUS_CODE: 500,
HTTP_ROUTE: "/error",
},
)
# In falcon<3, NET_PEER_IP is always set by default to 127.0.0.1
# In falcon>=3, NET_PEER_IP is not set to anything by default
# https://github.com/falconry/falcon/blob/5233d0abed977d9dab78ebadf305f5abe2eef07c/falcon/testing/helpers.py#L1168-L1172
if NET_PEER_IP in span.attributes:
self.assertEqual(span.attributes[NET_PEER_IP], "127.0.0.1")
def test_url_template_new_semconv(self):
self.client().simulate_get("/user/123")
spans = self.memory_exporter.get_finished_spans()
metrics_list = self.memory_metrics_reader.get_metrics_data()
self.assertEqual(len(spans), 1)
self.assertTrue(len(metrics_list.resource_metrics) != 0)
span = spans[0]
self.assertEqual(span.name, "GET /user/{user_id}")
self.assertEqual(span.status.status_code, StatusCode.UNSET)
self.assertEqual(
span.status.description,
None,
)
self.assertSpanHasAttributes(
span,
{
HTTP_REQUEST_METHOD: "GET",
SERVER_ADDRESS: "falconframework.org",
URL_SCHEME: "http",
SERVER_PORT: 80,
URL_PATH: "/user/123",
CLIENT_PORT: 65133,
NETWORK_PROTOCOL_VERSION: "1.1",
"falcon.resource": "UserResource",
HTTP_RESPONSE_STATUS_CODE: 200,
HTTP_ROUTE: "/user/{user_id}",
},
)
for resource_metric in metrics_list.resource_metrics:
for scope_metric in resource_metric.scope_metrics:
for metric in scope_metric.metrics:
if metric.name == "http.server.request.duration":
data_points = list(metric.data.data_points)
for point in data_points:
self.assertIn(
"http.route",
point.attributes,
)
def test_url_template(self):
self.client().simulate_get("/user/123")
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
span = spans[0]
self.assertEqual(span.name, "GET /user/{user_id}")
self.assertEqual(span.status.status_code, StatusCode.UNSET)
self.assertEqual(
span.status.description,
None,
)
self.assertSpanHasAttributes(
span,
{
HTTP_METHOD: "GET",
HTTP_SERVER_NAME: "falconframework.org",
HTTP_SCHEME: "http",
NET_HOST_PORT: 80,
HTTP_HOST: "falconframework.org",
HTTP_TARGET: "/" if self._has_fixed_http_target else "/user/123",
NET_PEER_PORT: 65133,
HTTP_FLAVOR: "1.1",
"falcon.resource": "UserResource",
HTTP_STATUS_CODE: 200,
HTTP_ROUTE: "/user/{user_id}",
},
)
def test_uninstrument(self):
self.client().simulate_get(path="/hello")
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
self.memory_exporter.clear()
FalconInstrumentor().uninstrument()
self.app = make_app()
self.client().simulate_get(path="/hello")
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 0)
def test_no_op_tracer_provider(self):
FalconInstrumentor().uninstrument()
FalconInstrumentor().instrument(tracer_provider=trace.NoOpTracerProvider())
self.memory_exporter.clear()
self.client().simulate_get(path="/hello")
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 0)
def test_exclude_lists(self):
self.client().simulate_get(path="/ping")
span_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(span_list), 0)
self.client().simulate_get(path="/hello")
span_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(span_list), 1)
def test_traced_request_attributes(self):
self.client().simulate_get(path="/hello", query_string="q=abc")
span = self.memory_exporter.get_finished_spans()[0]
self.assertIn("query_string", span.attributes)
self.assertEqual(span.attributes["query_string"], "q=abc")
self.assertNotIn("not_available_attr", span.attributes)
def test_trace_response(self):
orig = get_global_response_propagator()
set_global_response_propagator(TraceResponsePropagator())
response = self.client().simulate_get(path="/hello", query_string="q=abc")
self.assertTraceResponseHeaderMatchesSpan(response.headers, self.memory_exporter.get_finished_spans()[0])
set_global_response_propagator(orig)
def test_traced_not_recording(self):
mock_tracer = Mock()
mock_span = Mock()
mock_span.is_recording.return_value = False
mock_tracer.start_span.return_value = mock_span
with patch("opentelemetry.trace.get_tracer") as tracer:
tracer.return_value = mock_tracer
self.client().simulate_get(path="/hello", query_string="q=abc")
self.assertFalse(mock_span.is_recording())
self.assertTrue(mock_span.is_recording.called)
self.assertFalse(mock_span.set_attribute.called)
self.assertFalse(mock_span.set_status.called)
metrics = self.get_sorted_metrics(SCOPE)
self.assertTrue(len(metrics) != 0)
for metric in metrics:
data_points = list(metric.data.data_points)
self.assertEqual(len(data_points), 1)
for point in list(metric.data.data_points):
if isinstance(point, HistogramDataPoint):
self.assertEqual(point.count, 1)
if isinstance(point, NumberDataPoint):
self.assertEqual(point.value, 0)
for attr in point.attributes:
self.assertIn(
attr,
_recommended_metrics_attrs_old[metric.name],
)
def test_uninstrument_after_instrument(self):
self.client().simulate_get(path="/hello")
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
FalconInstrumentor().uninstrument()
self.memory_exporter.clear()
self.client().simulate_get(path="/hello")
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 0)
def test_falcon_metrics(self):
self.client().simulate_get("/hello/756")
self.client().simulate_get("/hello/756")
self.client().simulate_get("/hello/756")
metrics = self.get_sorted_metrics(SCOPE)
number_data_point_seen = False
histogram_data_point_seen = False
self.assertTrue(len(metrics) != 0)
for metric in metrics:
self.assertIn(metric.name, _expected_metric_names)
data_points = list(metric.data.data_points)
self.assertEqual(len(data_points), 1)
for point in data_points:
if isinstance(point, HistogramDataPoint):
self.assertEqual(point.count, 3)
histogram_data_point_seen = True
if isinstance(point, NumberDataPoint):
number_data_point_seen = True
for attr in point.attributes:
self.assertIn(attr, _recommended_attrs[metric.name])
self.assertTrue(number_data_point_seen and histogram_data_point_seen)
def test_falcon_metric_values_new_semconv(self):
number_data_point_seen = False
histogram_data_point_seen = False
start = default_timer()
self.client().simulate_get("/hello/756")
duration = max(default_timer() - start, 0)
metrics = self.get_sorted_metrics(SCOPE)
for metric in metrics:
data_points = list(metric.data.data_points)
self.assertEqual(len(data_points), 1)
for point in data_points:
if isinstance(point, HistogramDataPoint):
self.assertEqual(point.count, 1)
histogram_data_point_seen = True
self.assertAlmostEqual(duration, point.sum, delta=10)
self.assertEqual(
point.explicit_bounds,
HTTP_DURATION_HISTOGRAM_BUCKETS_NEW,
)
if isinstance(point, NumberDataPoint):
self.assertEqual(point.value, 0)
number_data_point_seen = True
for attr in point.attributes:
self.assertIn(
attr,
_recommended_metrics_attrs_new[metric.name],
)
self.assertTrue(number_data_point_seen and histogram_data_point_seen)
def test_falcon_metric_values_both_semconv(self):
number_data_point_seen = False
histogram_data_point_seen = False
start = default_timer()
self.client().simulate_get("/hello/756")
duration_s = default_timer() - start
metrics = self.get_sorted_metrics(SCOPE)
# pylint: disable=too-many-nested-blocks
for metric in metrics:
if metric.unit == "ms":
self.assertEqual(metric.name, "http.server.duration")
elif metric.unit == "s":
self.assertEqual(metric.name, "http.server.request.duration")
else:
self.assertEqual(metric.name, "http.server.active_requests")
data_points = list(metric.data.data_points)
self.assertEqual(len(data_points), 1)
for point in data_points:
if isinstance(point, HistogramDataPoint):
self.assertEqual(point.count, 1)
if metric.unit == "ms":
self.assertAlmostEqual(
max(round(duration_s * 1000), 0),
point.sum,
delta=10,
)
elif metric.unit == "s":
self.assertAlmostEqual(max(duration_s, 0), point.sum, delta=10)
self.assertEqual(
point.explicit_bounds,
HTTP_DURATION_HISTOGRAM_BUCKETS_NEW,
)
histogram_data_point_seen = True
if isinstance(point, NumberDataPoint):
self.assertEqual(point.value, 0)
number_data_point_seen = True
for attr in point.attributes:
self.assertIn(
attr,
_recommended_metrics_attrs_both[metric.name],
)
self.assertTrue(number_data_point_seen and histogram_data_point_seen)
def test_falcon_metric_values(self):
number_data_point_seen = False
histogram_data_point_seen = False
start = default_timer()
self.client().simulate_get("/hello/756")
duration = max(round((default_timer() - start) * 1000), 0)
metrics = self.get_sorted_metrics(SCOPE)
for metric in metrics:
data_points = list(metric.data.data_points)
self.assertEqual(len(data_points), 1)
for point in list(metric.data.data_points):
if isinstance(point, HistogramDataPoint):
self.assertEqual(point.count, 1)
histogram_data_point_seen = True
self.assertAlmostEqual(duration, point.sum, delta=10)
if isinstance(point, NumberDataPoint):
self.assertEqual(point.value, 0)
number_data_point_seen = True
for attr in point.attributes:
self.assertIn(
attr,
_recommended_metrics_attrs_old[metric.name],
)
self.assertTrue(number_data_point_seen and histogram_data_point_seen)
def test_metric_uninstrument(self):
self.client().simulate_request(method="POST", path="/hello/756")
FalconInstrumentor().uninstrument()
self.client().simulate_request(method="POST", path="/hello/756")
metrics = self.get_sorted_metrics(SCOPE)
for metric in metrics:
for point in list(metric.data.data_points):
if isinstance(point, HistogramDataPoint):
self.assertEqual(point.count, 1)
class TestFalconInstrumentationWithTracerProvider(TestBase):
def setUp(self):
super().setUp()
resource = Resource.create({"resource-key": "resource-value"})
result = self.create_tracer_provider(resource=resource)
tracer_provider, exporter = result
self.exporter = exporter
FalconInstrumentor().instrument(tracer_provider=tracer_provider)
self.app = make_app()
def client(self):
return testing.TestClient(self.app)
def tearDown(self):
super().tearDown()
with self.disable_logging():
FalconInstrumentor().uninstrument()
def test_traced_request(self):
self.client().simulate_request(method="GET", path="/hello")
spans = self.exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
span = spans[0]
self.assertEqual(span.resource.attributes["resource-key"], "resource-value")
self.exporter.clear()
class TestFalconInstrumentationHooks(TestFalconBase):
# pylint: disable=no-self-use
def request_hook(self, span, req):
span.set_attribute("request_hook_attr", "value from hook")
def response_hook(self, span, req, resp):
span.update_name("set from hook")
def test_hooks(self):
self.client().simulate_get(path="/hello", query_string="q=abc")
span = self.memory_exporter.get_finished_spans()[0]
self.assertEqual(span.name, "set from hook")
self.assertIn("request_hook_attr", span.attributes)
self.assertEqual(span.attributes["request_hook_attr"], "value from hook")
class TestFalconInstrumentationWrappedWithOtherFramework(TestFalconBase):
def test_mark_span_internal_in_presence_of_span_from_other_framework(self):
tracer = trace.get_tracer(__name__)
with tracer.start_as_current_span("test", kind=trace.SpanKind.SERVER) as parent_span:
self.client().simulate_request(method="GET", path="/hello")
span = self.memory_exporter.get_finished_spans()[0]
assert span.status.is_ok
self.assertEqual(trace.SpanKind.INTERNAL, span.kind)
self.assertEqual(span.parent.span_id, parent_span.get_span_context().span_id)
@patch.dict(
"os.environ",
{
OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SANITIZE_FIELDS: ".*my-secret.*",
OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_REQUEST: "Custom-Test-Header-1,Custom-Test-Header-2,invalid-header,Regex-Test-Header-.*,Regex-Invalid-Test-Header-.*,.*my-secret.*",
OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_RESPONSE: "content-type,content-length,my-custom-header,invalid-header,my-custom-regex-header-.*,invalid-regex-header-.*,.*my-secret.*",
},
)
class TestCustomRequestResponseHeaders(TestFalconBase):
def test_custom_request_header_added_in_server_span(self):
headers = {
"Custom-Test-Header-1": "Test Value 1",
"Custom-Test-Header-2": "TestValue2,TestValue3",
"Custom-Test-Header-3": "TestValue4",
"Regex-Test-Header-1": "Regex Test Value 1",
"regex-test-header-2": "RegexTestValue2,RegexTestValue3",
"My-Secret-Header": "My Secret Value",
}
self.client().simulate_request(method="GET", path="/hello", headers=headers)
span = self.memory_exporter.get_finished_spans()[0]
assert span.status.is_ok
expected = {
"http.request.header.custom_test_header_1": ("Test Value 1",),
"http.request.header.custom_test_header_2": ("TestValue2,TestValue3",),
"http.request.header.regex_test_header_1": ("Regex Test Value 1",),
"http.request.header.regex_test_header_2": ("RegexTestValue2,RegexTestValue3",),
"http.request.header.my_secret_header": ("[REDACTED]",),
}
not_expected = {
"http.request.header.custom_test_header_3": ("TestValue4",),
}
self.assertEqual(span.kind, trace.SpanKind.SERVER)
self.assertSpanHasAttributes(span, expected)
for key, _ in not_expected.items():
self.assertNotIn(key, span.attributes)
def test_custom_request_header_not_added_in_internal_span(self):
tracer = trace.get_tracer(__name__)
with tracer.start_as_current_span("test", kind=trace.SpanKind.SERVER):
headers = {
"Custom-Test-Header-1": "Test Value 1",
"Custom-Test-Header-2": "TestValue2,TestValue3",
"Regex-Test-Header-1": "Regex Test Value 1",
"regex-test-header-2": "RegexTestValue2,RegexTestValue3",
"My-Secret-Header": "My Secret Value",
}
self.client().simulate_request(method="GET", path="/hello", headers=headers)
span = self.memory_exporter.get_finished_spans()[0]
assert span.status.is_ok
not_expected = {
"http.request.header.custom_test_header_1": ("Test Value 1",),
"http.request.header.custom_test_header_2": ("TestValue2,TestValue3",),
"http.request.header.regex_test_header_1": ("Regex Test Value 1",),
"http.request.header.regex_test_header_2": ("RegexTestValue2,RegexTestValue3",),
"http.request.header.my_secret_header": ("[REDACTED]",),
}
self.assertEqual(span.kind, trace.SpanKind.INTERNAL)
for key, _ in not_expected.items():
self.assertNotIn(key, span.attributes)
@pytest.mark.skipif(
condition=_parsed_falcon_version < package_version.parse("2.0.0"),
reason="falcon<2 does not implement custom response headers",
)
def test_custom_response_header_added_in_server_span(self):
self.client().simulate_request(method="GET", path="/test_custom_response_headers")
span = self.memory_exporter.get_finished_spans()[0]
assert span.status.is_ok
expected = {
"http.response.header.content_type": ("text/plain; charset=utf-8",),
"http.response.header.content_length": ("0",),
"http.response.header.my_custom_header": ("my-custom-value-1,my-custom-header-2",),
"http.response.header.my_custom_regex_header_1": ("my-custom-regex-value-1,my-custom-regex-value-2",),
"http.response.header.my_custom_regex_header_2": ("my-custom-regex-value-3,my-custom-regex-value-4",),
"http.response.header.my_secret_header": ("[REDACTED]",),
}
not_expected = {"http.response.header.dont_capture_me": ("test-value",)}
self.assertEqual(span.kind, trace.SpanKind.SERVER)
self.assertSpanHasAttributes(span, expected)
for key, _ in not_expected.items():
self.assertNotIn(key, span.attributes)
@pytest.mark.skipif(
condition=_parsed_falcon_version < package_version.parse("2.0.0"),
reason="falcon<2 does not implement custom response headers",
)
def test_custom_response_header_not_added_in_internal_span(self):
tracer = trace.get_tracer(__name__)
with tracer.start_as_current_span("test", kind=trace.SpanKind.SERVER):
self.client().simulate_request(method="GET", path="/test_custom_response_headers")
span = self.memory_exporter.get_finished_spans()[0]
assert span.status.is_ok
not_expected = {
"http.response.header.content_type": ("text/plain; charset=utf-8",),
"http.response.header.content_length": ("0",),
"http.response.header.my_custom_header": ("my-custom-value-1,my-custom-header-2",),
"http.response.header.my_custom_regex_header_1": ("my-custom-regex-value-1,my-custom-regex-value-2",),
"http.response.header.my_custom_regex_header_2": ("my-custom-regex-value-3,my-custom-regex-value-4",),
"http.response.header.my_secret_header": ("[REDACTED]",),
}
self.assertEqual(span.kind, trace.SpanKind.INTERNAL)
for key, _ in not_expected.items():
self.assertNotIn(key, span.attributes)
opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-fastapi/ 0000775 0000000 0000000 00000000000 15270700723 0032572 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-fastapi/LICENSE 0000664 0000000 0000000 00000026135 15270700723 0033606 0 ustar 00root root 0000000 0000000 Apache License
Version 2.0, January 2004
http://www.apache.org/licenses/
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opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-fastapi/README.rst0000664 0000000 0000000 00000001416 15270700723 0034263 0 ustar 00root root 0000000 0000000 OpenTelemetry FastAPI Instrumentation
=======================================
|pypi|
.. |pypi| image:: https://badge.fury.io/py/opentelemetry-instrumentation-fastapi.svg
:target: https://pypi.org/project/opentelemetry-instrumentation-fastapi/
This library provides automatic and manual instrumentation of FastAPI web frameworks,
instrumenting http requests served by applications utilizing the framework.
auto-instrumentation using the opentelemetry-instrumentation package is also supported.
Installation
------------
::
pip install opentelemetry-instrumentation-fastapi
References
----------
* `OpenTelemetry Project `_
* `OpenTelemetry Python Examples `_
pyproject.toml 0000664 0000000 0000000 00000003265 15270700723 0035435 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-fastapi [build-system]
requires = ["hatchling"]
build-backend = "hatchling.build"
[project]
name = "opentelemetry-instrumentation-fastapi"
dynamic = ["version"]
description = "OpenTelemetry FastAPI Instrumentation"
readme = "README.rst"
license = "Apache-2.0"
requires-python = ">=3.10"
authors = [
{ name = "OpenTelemetry Authors", email = "cncf-opentelemetry-contributors@lists.cncf.io" },
]
classifiers = [
"Development Status :: 4 - Beta",
"Intended Audience :: Developers",
"License :: OSI Approved :: Apache Software License",
"Programming Language :: Python",
"Programming Language :: Python :: 3",
"Programming Language :: Python :: 3.10",
"Programming Language :: Python :: 3.11",
"Programming Language :: Python :: 3.12",
"Programming Language :: Python :: 3.13",
"Programming Language :: Python :: 3.14",
]
dependencies = [
"opentelemetry-api ~= 1.12",
"opentelemetry-instrumentation == 0.66b2",
"opentelemetry-instrumentation-asgi == 0.66b2",
"opentelemetry-semantic-conventions == 0.66b2",
"opentelemetry-util-http == 0.66b2",
]
[project.optional-dependencies]
instruments = [
"fastapi ~= 0.92",
]
[project.entry-points.opentelemetry_instrumentor]
fastapi = "opentelemetry.instrumentation.fastapi:FastAPIInstrumentor"
[project.urls]
Homepage = "https://github.com/open-telemetry/opentelemetry-python-contrib/tree/main/instrumentation/opentelemetry-instrumentation-fastapi"
Repository = "https://github.com/open-telemetry/opentelemetry-python-contrib"
[tool.hatch.version]
path = "src/opentelemetry/instrumentation/fastapi/version.py"
[tool.hatch.build.targets.sdist]
include = [
"/src",
"/tests",
]
[tool.hatch.build.targets.wheel]
packages = ["src/opentelemetry"]
opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-fastapi/src/ 0000775 0000000 0000000 00000000000 15270700723 0033361 5 ustar 00root root 0000000 0000000 opentelemetry/ 0000775 0000000 0000000 00000000000 15270700723 0036176 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-fastapi/src instrumentation/ 0000775 0000000 0000000 00000000000 15270700723 0041441 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-fastapi/src/opentelemetry fastapi/ 0000775 0000000 0000000 00000000000 15270700723 0043070 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-fastapi/src/opentelemetry/instrumentation __init__.py 0000664 0000000 0000000 00000064703 15270700723 0045213 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-fastapi/src/opentelemetry/instrumentation/fastapi # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
"""
Usage
-----
.. code-block:: python
import fastapi
from opentelemetry.instrumentation.fastapi import FastAPIInstrumentor
app = fastapi.FastAPI()
@app.get("/foobar")
async def foobar():
return {"message": "hello world"}
FastAPIInstrumentor.instrument_app(app)
Auto-instrumentation
********************
FastAPI can also be instrumented without code changes by using the
``opentelemetry-instrument`` command from the
`opentelemetry-instrumentation `_
package. For installation, runtime command, exporter configuration, and
environment variables, see
`Python zero-code instrumentation `_.
Install ``opentelemetry-instrumentation-fastapi`` in the same environment so
the FastAPI integration is available to auto-instrumentation. FastAPI-specific
options, such as excluded URLs and HTTP header capture, are documented below.
Trace propagation
*****************
FastAPI instrumentation uses the underlying ASGI instrumentation, which extracts
incoming context from request headers using the configured global OpenTelemetry
propagator. WebSocket connections are instrumented as ASGI ``websocket`` scopes,
with context extracted from the handshake headers. Propagation data inside
WebSocket message payloads is not parsed automatically. For more information,
see `Python context propagation `_
and `Python distro configuration `_.
Configuration
-------------
Exclude lists
*************
To exclude certain URLs from tracking, set the environment variable ``OTEL_PYTHON_FASTAPI_EXCLUDED_URLS``
(or ``OTEL_PYTHON_EXCLUDED_URLS`` to cover all instrumentations) to a string of comma delimited regexes that match the
URLs.
For example,
::
export OTEL_PYTHON_FASTAPI_EXCLUDED_URLS="client/.*/info,healthcheck"
will exclude requests such as ``https://site/client/123/info`` and ``https://site/xyz/healthcheck``.
You can also pass comma delimited regexes directly to the ``instrument_app`` method:
.. code-block:: python
FastAPIInstrumentor.instrument_app(app, excluded_urls="client/.*/info,healthcheck")
Request/Response hooks
**********************
This instrumentation supports request and response hooks. These are functions that get called
right after a span is created for a request and right before the span is finished for the response.
- The server request hook is passed a server span and ASGI scope object for every incoming request.
- The client request hook is called with the internal span, and ASGI scope and event when the method ``receive`` is called.
- The client response hook is called with the internal span, and ASGI scope and event when the method ``send`` is called.
.. code-block:: python
from opentelemetry.instrumentation.fastapi import FastAPIInstrumentor
from opentelemetry.trace import Span
from starlette.types import Message, Scope
def server_request_hook(span: Span, scope: Scope):
if span and span.is_recording():
span.set_attribute("custom_user_attribute_from_request_hook", "some-value")
def client_request_hook(span: Span, scope: Scope, message: Message):
if span and span.is_recording():
span.set_attribute("custom_user_attribute_from_client_request_hook", "some-value")
def client_response_hook(span: Span, scope: Scope, message: Message):
if span and span.is_recording():
span.set_attribute("custom_user_attribute_from_response_hook", "some-value")
FastAPIInstrumentor().instrument(
server_request_hook=server_request_hook,
client_request_hook=client_request_hook,
client_response_hook=client_response_hook,
)
Capture HTTP request and response headers
*****************************************
You can configure the agent to capture specified HTTP headers as span attributes, according to the
`semantic conventions `_.
Request headers
***************
To capture HTTP request headers as span attributes, set the environment variable
``OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_REQUEST`` to a comma delimited list of HTTP header names,
or pass the ``http_capture_headers_server_request`` keyword argument to the ``instrument_app`` method.
For example using the environment variable,
::
export OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_REQUEST="content-type,custom_request_header"
will extract ``content-type`` and ``custom_request_header`` from the request headers and add them as span attributes.
Request header names in FastAPI are case-insensitive. So, giving the header name as ``CUStom-Header`` in the environment
variable will capture the header named ``custom-header``.
Regular expressions may also be used to match multiple headers that correspond to the given pattern. For example:
::
export OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_REQUEST="Accept.*,X-.*"
Would match all request headers that start with ``Accept`` and ``X-``.
To capture all request headers, set ``OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_REQUEST`` to ``".*"``.
::
export OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_REQUEST=".*"
The name of the added span attribute will follow the format ``http.request.header.`` where ````
is the normalized HTTP header name (lowercase, with ``-`` replaced by ``_``). The value of the attribute will be a
single item list containing all the header values.
For example:
``http.request.header.custom_request_header = ["", ""]``
Response headers
****************
To capture HTTP response headers as span attributes, set the environment variable
``OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_RESPONSE`` to a comma delimited list of HTTP header names,
or pass the ``http_capture_headers_server_response`` keyword argument to the ``instrument_app`` method.
For example using the environment variable,
::
export OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_RESPONSE="content-type,custom_response_header"
will extract ``content-type`` and ``custom_response_header`` from the response headers and add them as span attributes.
Response header names in FastAPI are case-insensitive. So, giving the header name as ``CUStom-Header`` in the environment
variable will capture the header named ``custom-header``.
Regular expressions may also be used to match multiple headers that correspond to the given pattern. For example:
::
export OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_RESPONSE="Content.*,X-.*"
Would match all response headers that start with ``Content`` and ``X-``.
To capture all response headers, set ``OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_RESPONSE`` to ``".*"``.
::
export OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_RESPONSE=".*"
The name of the added span attribute will follow the format ``http.response.header.`` where ````
is the normalized HTTP header name (lowercase, with ``-`` replaced by ``_``). The value of the attribute will be a
list containing the header values.
For example:
``http.response.header.custom_response_header = ["", ""]``
Sanitizing headers
******************
In order to prevent storing sensitive data such as personally identifiable information (PII), session keys, passwords,
etc, set the environment variable ``OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SANITIZE_FIELDS``
to a comma delimited list of HTTP header names to be sanitized, or pass the ``http_capture_headers_sanitize_fields``
keyword argument to the ``instrument_app`` method.
Regexes may be used, and all header names will be matched in a case-insensitive manner.
For example using the environment variable,
::
export OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SANITIZE_FIELDS=".*session.*,set-cookie"
will replace the value of headers such as ``session-id`` and ``set-cookie`` with ``[REDACTED]`` in the span.
Note:
The environment variable names used to capture HTTP headers are still experimental, and thus are subject to change.
API
---
"""
from __future__ import annotations
import functools
import logging
import types
from collections.abc import Collection, Iterator, Sequence
from typing import TYPE_CHECKING, Literal
from weakref import WeakSet as _WeakSet
import fastapi
from starlette.applications import Starlette
from starlette.background import BackgroundTask
from starlette.middleware.errors import ServerErrorMiddleware
from starlette.routing import BaseRoute, Match, Route
from starlette.types import ASGIApp, Receive, Scope, Send
from typing_extensions import Unpack
try:
# FastAPI >= 0.137.2 exposes a public helper that flattens routes added via
# include_router() (nested under _IncludedRouter in 0.137) into matchable
# RouteContext objects. Older versions don't have it; see _flatten_routes.
from fastapi.routing import iter_route_contexts
except ImportError:
iter_route_contexts = None
from opentelemetry.instrumentation._semconv import (
_get_schema_url,
_OpenTelemetrySemanticConventionStability,
_OpenTelemetryStabilitySignalType,
_StabilityMode,
)
from opentelemetry.instrumentation.asgi import OpenTelemetryMiddleware
from opentelemetry.instrumentation.asgi.types import (
ClientRequestHook,
ClientResponseHook,
ServerRequestHook,
)
from opentelemetry.instrumentation.fastapi.package import _instruments
from opentelemetry.instrumentation.fastapi.version import __version__
from opentelemetry.instrumentation.instrumentor import BaseInstrumentor
from opentelemetry.metrics import MeterProvider, get_meter
from opentelemetry.semconv.attributes.http_attributes import HTTP_ROUTE
from opentelemetry.trace import TracerProvider, get_current_span, get_tracer
from opentelemetry.trace.status import Status, StatusCode
from opentelemetry.util.http import (
get_excluded_urls,
parse_excluded_urls,
sanitize_method,
)
if TYPE_CHECKING:
from typing import TypedDict
from fastapi.routing import RouteContext, _EffectiveRouteContext
class _InstrumentKwargs(TypedDict, total=False):
server_request_hook: ServerRequestHook
client_request_hook: ClientRequestHook
client_response_hook: ClientResponseHook
tracer_provider: TracerProvider | None
meter_provider: MeterProvider | None
excluded_urls: str | None
http_capture_headers_server_request: list[str] | None
http_capture_headers_server_response: list[str] | None
http_capture_headers_sanitize_fields: list[str] | None
exclude_spans: list[Literal["receive", "send"]] | None
class _UninstrumentKwargs(TypedDict, total=False):
pass
_excluded_urls_from_env = get_excluded_urls("FASTAPI")
_logger = logging.getLogger(__name__)
class FastAPIInstrumentor(BaseInstrumentor):
"""An instrumentor for FastAPI
See `BaseInstrumentor`
"""
_original_fastapi = None
@staticmethod
def instrument_app( # pylint: disable=too-many-locals
app: fastapi.FastAPI,
server_request_hook: ServerRequestHook = None,
client_request_hook: ClientRequestHook = None,
client_response_hook: ClientResponseHook = None,
tracer_provider: TracerProvider | None = None,
meter_provider: MeterProvider | None = None,
excluded_urls: str | None = None,
http_capture_headers_server_request: list[str] | None = None,
http_capture_headers_server_response: list[str] | None = None,
http_capture_headers_sanitize_fields: list[str] | None = None,
exclude_spans: list[Literal["receive", "send"]] | None = None,
) -> None:
"""Instrument an uninstrumented FastAPI application.
Args:
app: The fastapi ASGI application callable to forward requests to.
server_request_hook: Optional callback which is called with the server span and ASGI
scope object for every incoming request.
client_request_hook: Optional callback which is called with the internal span, and ASGI
scope and event which are sent as dictionaries for when the method receive is called.
client_response_hook: Optional callback which is called with the internal span, and ASGI
scope and event which are sent as dictionaries for when the method send is called.
tracer_provider: The optional tracer provider to use. If omitted
the current globally configured one is used.
meter_provider: The optional meter provider to use. If omitted
the current globally configured one is used.
excluded_urls: Optional comma delimited string of regexes to match URLs that should not be traced.
http_capture_headers_server_request: Optional list of HTTP headers to capture from the request.
http_capture_headers_server_response: Optional list of HTTP headers to capture from the response.
http_capture_headers_sanitize_fields: Optional list of HTTP headers to sanitize.
exclude_spans: Optionally exclude HTTP `send` and/or `receive` spans from the trace.
"""
if not hasattr(app, "_is_instrumented_by_opentelemetry"):
app._is_instrumented_by_opentelemetry = False # pyright: ignore[reportAttributeAccessIssue]
if not getattr(app, "_is_instrumented_by_opentelemetry", False):
# initialize semantic conventions opt-in if needed
_OpenTelemetrySemanticConventionStability._initialize()
sem_conv_opt_in_mode = _OpenTelemetrySemanticConventionStability._get_opentelemetry_stability_opt_in_mode(
_OpenTelemetryStabilitySignalType.HTTP,
)
parsed_excluded_urls = (
_excluded_urls_from_env if excluded_urls is None else parse_excluded_urls(excluded_urls)
)
tracer = get_tracer(
__name__,
__version__,
tracer_provider,
schema_url=_get_schema_url(sem_conv_opt_in_mode),
)
meter = get_meter(
__name__,
__version__,
meter_provider,
schema_url=_get_schema_url(sem_conv_opt_in_mode),
)
original_build_middleware_stack = app.build_middleware_stack
def build_middleware_stack(self: Starlette) -> ASGIApp:
# Define an additional middleware for exception handling
# Normally, `opentelemetry.trace.use_span` covers the recording of
# exceptions into the active span, but `OpenTelemetryMiddleware`
# ends the span too early before the exception can be recorded.
class ExceptionHandlerMiddleware:
def __init__(self, app: ASGIApp) -> None:
self.app = app
async def __call__(self, scope: Scope, receive: Receive, send: Send) -> None:
try:
await self.app(scope, receive, send)
except Exception as exc: # pylint: disable=broad-exception-caught
span = get_current_span()
if span.is_recording():
span.record_exception(exc)
span.set_status(
Status(
status_code=StatusCode.ERROR,
description=f"{type(exc).__name__}: {exc}",
)
)
raise
# For every possible use case of error handling, exception
# handling, trace availability in exception handlers and
# automatic exception recording to work, we need to make a
# series of wrapping and re-wrapping middlewares.
# First, grab the original middleware stack from Starlette. It
# comprises a stack of
# `ServerErrorMiddleware` -> [user defined middlewares] -> `ExceptionMiddleware`
inner_server_error_middleware = original_build_middleware_stack()
if not isinstance(inner_server_error_middleware, ServerErrorMiddleware):
# Oops, something changed about how Starlette creates middleware stacks
_logger.error(
"Skipping FastAPI instrumentation due to unexpected middleware stack: expected %s, got %s",
ServerErrorMiddleware.__name__,
type(inner_server_error_middleware),
)
return inner_server_error_middleware
# We take [user defined middlewares] -> `ExceptionHandlerMiddleware`
# out of the outermost `ServerErrorMiddleware` and instead pass
# it to our own `ExceptionHandlerMiddleware`
exception_middleware = ExceptionHandlerMiddleware(inner_server_error_middleware.app)
# Now, we create a new `ServerErrorMiddleware` that wraps
# `ExceptionHandlerMiddleware` but otherwise uses the same
# original `handler` and debug setting. The end result is a
# middleware stack that's identical to the original stack except
# all user middlewares are covered by our
# `ExceptionHandlerMiddleware`.
error_middleware = ServerErrorMiddleware(
app=exception_middleware,
handler=inner_server_error_middleware.handler,
debug=inner_server_error_middleware.debug,
)
# Finally, we wrap the stack above in our actual OTEL
# middleware. As a result, an active tracing context exists for
# every use case of user-defined error and exception handlers as
# well as automatic recording of exceptions in active spans.
otel_middleware = OpenTelemetryMiddleware(
error_middleware,
excluded_urls=parsed_excluded_urls,
default_span_details=_get_default_span_details,
server_request_hook=server_request_hook,
client_request_hook=client_request_hook,
client_response_hook=client_response_hook,
# Pass in tracer/meter to get __name__and __version__ of fastapi instrumentation
tracer=tracer,
meter=meter,
http_capture_headers_server_request=http_capture_headers_server_request,
http_capture_headers_server_response=http_capture_headers_server_response,
http_capture_headers_sanitize_fields=http_capture_headers_sanitize_fields,
exclude_spans=exclude_spans,
)
# Ultimately, wrap everything in another default
# `ServerErrorMiddleware` (w/o user handlers) so that any
# exceptions raised in `OpenTelemetryMiddleware` are handled.
#
# This should not happen unless there is a bug in
# OpenTelemetryMiddleware, but if there is we don't want that to
# impact the user's application just because we wrapped the
# middlewares in this order.
return ServerErrorMiddleware(
app=otel_middleware,
)
app._original_build_middleware_stack = ( # pyright: ignore[reportAttributeAccessIssue]
original_build_middleware_stack
)
app.build_middleware_stack = types.MethodType(
functools.wraps(app.build_middleware_stack)(build_middleware_stack),
app,
)
if not hasattr(BackgroundTask, "_otel_original_call"):
original_background_task_call = BackgroundTask.__call__
BackgroundTask._otel_original_call = ( # pyright: ignore[reportAttributeAccessIssue]
original_background_task_call
)
async def traced_call(self: BackgroundTask) -> None:
span_name = f"BackgroundTask {getattr(self.func, '__name__', self.func.__class__.__name__)}"
with tracer.start_as_current_span(span_name):
return await original_background_task_call(self)
BackgroundTask.__call__ = traced_call
app._is_instrumented_by_opentelemetry = True # pyright: ignore[reportAttributeAccessIssue]
if app not in _InstrumentedFastAPI._instrumented_fastapi_apps:
_InstrumentedFastAPI._instrumented_fastapi_apps.add(app)
else:
_logger.warning("Attempting to instrument FastAPI app while already instrumented")
@staticmethod
def uninstrument_app(app: fastapi.FastAPI) -> None:
original_build_middleware_stack = getattr(app, "_original_build_middleware_stack", None)
if original_build_middleware_stack:
app.build_middleware_stack = original_build_middleware_stack
del app._original_build_middleware_stack # pyright: ignore[reportAttributeAccessIssue]
app.middleware_stack = app.build_middleware_stack()
if hasattr(BackgroundTask, "_otel_original_call"):
BackgroundTask.__call__ = BackgroundTask._otel_original_call # pyright: ignore[reportAttributeAccessIssue, reportUnknownMemberType]
del BackgroundTask._otel_original_call # pyright: ignore[reportAttributeAccessIssue]
app._is_instrumented_by_opentelemetry = False # pyright: ignore[reportAttributeAccessIssue]
# Remove the app from the set of instrumented apps to avoid calling uninstrument twice
# if the instrumentation is later disabled or such
# Use discard to avoid KeyError if already GC'ed
_InstrumentedFastAPI._instrumented_fastapi_apps.discard(app)
def instrumentation_dependencies(self) -> Collection[str]:
return _instruments
def _instrument(self, **kwargs: Unpack[_InstrumentKwargs]) -> None:
self._original_fastapi = fastapi.FastAPI
_InstrumentedFastAPI._instrument_kwargs = kwargs
fastapi.FastAPI = _InstrumentedFastAPI
def _uninstrument(self, **kwargs: Unpack[_UninstrumentKwargs]) -> None:
# Create a copy of the set to avoid RuntimeError during iteration
instances_to_uninstrument = list(_InstrumentedFastAPI._instrumented_fastapi_apps)
for instance in instances_to_uninstrument:
self.uninstrument_app(instance)
_InstrumentedFastAPI._instrumented_fastapi_apps.clear()
fastapi.FastAPI = self._original_fastapi
class _InstrumentedFastAPI(fastapi.FastAPI):
_instrument_kwargs: _InstrumentKwargs = {}
# Track instrumented app instances using weak references to avoid GC leaks
_instrumented_fastapi_apps: _WeakSet[fastapi.FastAPI] = _WeakSet()
_sem_conv_opt_in_mode = _StabilityMode.DEFAULT
def __init__(self, *args: object, **kwargs: object) -> None:
super().__init__(*args, **kwargs)
FastAPIInstrumentor.instrument_app(self, **_InstrumentedFastAPI._instrument_kwargs)
_InstrumentedFastAPI._instrumented_fastapi_apps.add(self)
def _flatten_routes(
routes: Sequence[BaseRoute],
) -> Iterator[BaseRoute | RouteContext | _EffectiveRouteContext]:
"""
Yield the matchable routes from an app's route list.
FastAPI 0.137 nests routes added via include_router() under _IncludedRouter
tree nodes, which expose no ``path`` attribute. They have to be flattened
into their effective route contexts (each providing matches() and the full
templated path) before they can be matched against a scope.
FastAPI >= 0.137.2 provides the public iter_route_contexts() for this, which
also wraps plain routes uniformly. On older versions fall back to the
private _IncludedRouter.effective_route_contexts(), and on FastAPI < 0.137
(no _IncludedRouter) the routes are already matchable as-is.
"""
if iter_route_contexts is not None:
yield from iter_route_contexts(routes)
return
for starlette_route in routes:
if hasattr(starlette_route, "effective_route_contexts"):
yield from starlette_route.effective_route_contexts() # pyright: ignore[reportAttributeAccessIssue, reportUnknownMemberType]
else:
yield starlette_route
def _get_route_details(scope: Scope) -> str | None:
"""
Function to retrieve Starlette route from scope.
TODO: there is currently no way to retrieve http.route from
a starlette application from scope.
See: https://github.com/encode/starlette/pull/804
Args:
scope: A Starlette scope
Returns:
A string containing the route or None
"""
app: fastapi.FastAPI = scope["app"]
route: str | None = None
for starlette_route in _flatten_routes(app.routes):
match, _ = (
Route.matches(starlette_route, scope)
if isinstance(starlette_route, Route)
else starlette_route.matches(scope)
)
if match == Match.FULL:
try:
route = starlette_route.path # pyright: ignore[reportAttributeAccessIssue, reportUnknownMemberType, reportUnknownVariableType]
except AttributeError:
# Routes added via host routing have no path attribute.
route = scope.get("path")
break
if match == Match.PARTIAL:
route = starlette_route.path # pyright: ignore[reportAttributeAccessIssue, reportUnknownMemberType, reportUnknownVariableType]
return route # pyright: ignore[reportUnknownVariableType]
def _get_default_span_details(scope: Scope) -> tuple[str, dict[str, str]]:
"""
Callback to retrieve span name and attributes from scope.
Args:
scope: A Starlette scope
Returns:
A tuple of span name and attributes
"""
route = _get_route_details(scope)
raw_method: str = scope.get("method", "")
method = sanitize_method(raw_method.strip())
attributes: dict[str, str] = {}
if method == "_OTHER":
method = "HTTP"
if route:
attributes[HTTP_ROUTE] = route
if method and route: # http
span_name = f"{method} {route}"
elif route: # websocket
span_name = route
else: # fallback
span_name = method
return span_name, attributes
package.py 0000664 0000000 0000000 00000000253 15270700723 0045035 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-fastapi/src/opentelemetry/instrumentation/fastapi # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
_instruments = ("fastapi ~= 0.92",)
_supports_metrics = True
_semconv_status = "migration"
py.typed 0000664 0000000 0000000 00000000000 15270700723 0044555 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-fastapi/src/opentelemetry/instrumentation/fastapi version.py 0000664 0000000 0000000 00000000144 15270700723 0045126 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-fastapi/src/opentelemetry/instrumentation/fastapi # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
__version__ = "0.66b2"
test-requirements.in 0000664 0000000 0000000 00000000541 15270700723 0036543 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-fastapi # Used to generate test-requirements.{oldest,latest}.txt with uv pip compile
pytest~=7.4
requests~=2.33.1
urllib3~=2.7.0
httpx~=0.28
fastapi~=0.119.1
wrapt>=1.16.0
-e opentelemetry-instrumentation
-e instrumentation/opentelemetry-instrumentation-asgi
-e util/opentelemetry-util-http
-e instrumentation/opentelemetry-instrumentation-fastapi[instruments]
test-requirements.latest.txt 0000664 0000000 0000000 00000006411 15270700723 0040251 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-fastapi # This file was autogenerated by uv via the following command:
# uv pip compile --python 3.10 --universal --no-emit-package opentelemetry-api --no-emit-package opentelemetry-semantic-conventions -c dev-requirements.txt instrumentation/opentelemetry-instrumentation-fastapi/test-requirements.in -o instrumentation/opentelemetry-instrumentation-fastapi/test-requirements.latest.txt
-e instrumentation/opentelemetry-instrumentation-asgi
# via
# -r instrumentation/opentelemetry-instrumentation-fastapi/test-requirements.in
# opentelemetry-instrumentation-fastapi
-e instrumentation/opentelemetry-instrumentation-fastapi
# via -r instrumentation/opentelemetry-instrumentation-fastapi/test-requirements.in
-e opentelemetry-instrumentation
# via
# -r instrumentation/opentelemetry-instrumentation-fastapi/test-requirements.in
# opentelemetry-instrumentation-asgi
# opentelemetry-instrumentation-fastapi
-e util/opentelemetry-util-http
# via
# -r instrumentation/opentelemetry-instrumentation-fastapi/test-requirements.in
# opentelemetry-instrumentation-asgi
# opentelemetry-instrumentation-fastapi
annotated-doc==0.0.4
# via fastapi
annotated-types==0.7.0
# via pydantic
anyio==4.14.0
# via
# httpx
# starlette
asgiref==3.11.1
# via opentelemetry-instrumentation-asgi
certifi==2026.6.17
# via
# httpcore
# httpx
# requests
charset-normalizer==3.4.7
# via requests
colorama==0.4.6 ; sys_platform == 'win32'
# via pytest
exceptiongroup==1.3.1 ; python_full_version < '3.11'
# via
# anyio
# pytest
fastapi==0.137.2
# via opentelemetry-instrumentation-fastapi
h11==0.16.0
# via httpcore
httpcore==1.0.9
# via httpx
httpx==0.28.1
# via -r instrumentation/opentelemetry-instrumentation-fastapi/test-requirements.in
idna==3.18
# via
# anyio
# httpx
# requests
iniconfig==2.3.0
# via pytest
packaging==26.2
# via
# opentelemetry-instrumentation
# pytest
pluggy==1.6.0
# via pytest
pydantic==2.12.5
# via fastapi
pydantic-core==2.41.5
# via
# -r instrumentation/opentelemetry-instrumentation-fastapi/test-requirements.in
# pydantic
pytest==7.4.4
# via
# -c dev-requirements.txt
# -r instrumentation/opentelemetry-instrumentation-fastapi/test-requirements.in
requests==2.33.1
# via
# -c dev-requirements.txt
# -r instrumentation/opentelemetry-instrumentation-fastapi/test-requirements.in
starlette==1.3.1
# via fastapi
tomli==2.4.1 ; python_full_version < '3.11'
# via pytest
typing-extensions==4.15.0
# via
# anyio
# asgiref
# exceptiongroup
# fastapi
# opentelemetry-api
# opentelemetry-semantic-conventions
# pydantic
# pydantic-core
# starlette
# typing-inspection
typing-inspection==0.4.2
# via
# fastapi
# pydantic
urllib3==2.7.0
# via
# -r instrumentation/opentelemetry-instrumentation-fastapi/test-requirements.in
# requests
wrapt==2.2.1
# via
# -r instrumentation/opentelemetry-instrumentation-fastapi/test-requirements.in
# opentelemetry-instrumentation
# The following packages were excluded from the output:
# opentelemetry-api
# opentelemetry-semantic-conventions
test-requirements.oldest.txt 0000664 0000000 0000000 00000006502 15270700723 0040250 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-fastapi # This file was autogenerated by uv via the following command:
# uv pip compile --python 3.10 --universal --resolution lowest-direct --no-emit-package opentelemetry-api --no-emit-package opentelemetry-semantic-conventions -c dev-requirements.txt instrumentation/opentelemetry-instrumentation-fastapi/test-requirements.in -o instrumentation/opentelemetry-instrumentation-fastapi/test-requirements.oldest.txt
-e instrumentation/opentelemetry-instrumentation-asgi
# via
# -r instrumentation/opentelemetry-instrumentation-fastapi/test-requirements.in
# opentelemetry-instrumentation-fastapi
-e instrumentation/opentelemetry-instrumentation-fastapi
# via -r instrumentation/opentelemetry-instrumentation-fastapi/test-requirements.in
-e opentelemetry-instrumentation
# via
# -r instrumentation/opentelemetry-instrumentation-fastapi/test-requirements.in
# opentelemetry-instrumentation-asgi
# opentelemetry-instrumentation-fastapi
-e util/opentelemetry-util-http
# via
# -r instrumentation/opentelemetry-instrumentation-fastapi/test-requirements.in
# opentelemetry-instrumentation-asgi
# opentelemetry-instrumentation-fastapi
annotated-types==0.7.0
# via pydantic
anyio==4.14.0
# via
# httpx
# starlette
asgiref==3.0.0
# via opentelemetry-instrumentation-asgi
async-timeout==3.0.1
# via asgiref
certifi==2026.6.17
# via
# httpcore
# httpx
# requests
charset-normalizer==3.4.7
# via requests
colorama==0.4.6 ; sys_platform == 'win32'
# via pytest
exceptiongroup==1.3.1 ; python_full_version < '3.11'
# via
# anyio
# pytest
fastapi==0.119.1
# via opentelemetry-instrumentation-fastapi
h11==0.16.0
# via httpcore
httpcore==1.0.9
# via httpx
httpx==0.28.0
# via -r instrumentation/opentelemetry-instrumentation-fastapi/test-requirements.in
idna==3.18
# via
# anyio
# httpx
# requests
iniconfig==2.3.0
# via pytest
packaging==18.0
# via
# opentelemetry-instrumentation
# pytest
pluggy==1.6.0
# via pytest
pydantic==2.12.5
# via fastapi
pydantic-core==2.41.5
# via
# -r instrumentation/opentelemetry-instrumentation-fastapi/test-requirements.in
# pydantic
pyparsing==3.3.2
# via packaging
pytest==7.4.4
# via
# -c dev-requirements.txt
# -r instrumentation/opentelemetry-instrumentation-fastapi/test-requirements.in
requests==2.33.1
# via
# -c dev-requirements.txt
# -r instrumentation/opentelemetry-instrumentation-fastapi/test-requirements.in
six==1.17.0
# via packaging
starlette==0.48.0
# via fastapi
tomli==2.4.1 ; python_full_version < '3.11'
# via pytest
typing-extensions==4.15.0
# via
# anyio
# exceptiongroup
# fastapi
# opentelemetry-api
# opentelemetry-semantic-conventions
# pydantic
# pydantic-core
# starlette
# typing-inspection
typing-inspection==0.4.2
# via pydantic
urllib3==2.7.0
# via
# -r instrumentation/opentelemetry-instrumentation-fastapi/test-requirements.in
# requests
wrapt==1.16.0
# via
# -r instrumentation/opentelemetry-instrumentation-fastapi/test-requirements.in
# opentelemetry-instrumentation
# The following packages were excluded from the output:
# opentelemetry-api
# opentelemetry-semantic-conventions
opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-fastapi/tests/ 0000775 0000000 0000000 00000000000 15270700723 0033734 5 ustar 00root root 0000000 0000000 __init__.py 0000664 0000000 0000000 00000000000 15270700723 0035754 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-fastapi/tests test_fastapi_instrumentation.py 0000664 0000000 0000000 00000273322 15270700723 0042251 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-fastapi/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
# pylint: disable=too-many-lines
import gc as _gc
import logging
import unittest
import weakref as _weakref
from contextlib import ExitStack
from timeit import default_timer
from typing import Any, Final, cast
from unittest.mock import Mock, call, patch
import fastapi
import pytest
from fastapi.background import BackgroundTasks
from fastapi.middleware.asyncexitstack import AsyncExitStackMiddleware
from fastapi.middleware.httpsredirect import HTTPSRedirectMiddleware
from fastapi.responses import JSONResponse, PlainTextResponse
from fastapi.routing import APIRoute
from fastapi.testclient import TestClient
from starlette.background import BackgroundTask
from starlette.routing import BaseRoute, Match
from starlette.types import Receive, Scope, Send
import opentelemetry.instrumentation.fastapi as otel_fastapi
from opentelemetry import trace
from opentelemetry.instrumentation._semconv import (
OTEL_SEMCONV_STABILITY_OPT_IN,
_OpenTelemetrySemanticConventionStability,
_server_active_requests_count_attrs_new,
_server_active_requests_count_attrs_old,
_server_duration_attrs_new,
_server_duration_attrs_old,
)
from opentelemetry.instrumentation.asgi import OpenTelemetryMiddleware
from opentelemetry.instrumentation.auto_instrumentation._load import (
_load_instrumentors,
)
from opentelemetry.instrumentation.dependencies import DependencyConflict
from opentelemetry.sdk.metrics.export import (
HistogramDataPoint,
NumberDataPoint,
)
from opentelemetry.sdk.resources import Resource
from opentelemetry.sdk.trace import ReadableSpan
from opentelemetry.semconv._incubating.attributes.http_attributes import (
HTTP_FLAVOR,
HTTP_HOST,
HTTP_METHOD,
HTTP_SCHEME,
HTTP_SERVER_NAME,
HTTP_STATUS_CODE,
HTTP_TARGET,
HTTP_URL,
)
from opentelemetry.semconv._incubating.attributes.net_attributes import (
NET_HOST_PORT,
)
from opentelemetry.semconv.attributes.exception_attributes import (
EXCEPTION_TYPE,
)
from opentelemetry.semconv.attributes.http_attributes import (
HTTP_REQUEST_METHOD,
HTTP_RESPONSE_STATUS_CODE,
HTTP_ROUTE,
)
from opentelemetry.semconv.attributes.network_attributes import (
NETWORK_PROTOCOL_VERSION,
)
from opentelemetry.semconv.attributes.url_attributes import URL_SCHEME
from opentelemetry.test.globals_test import reset_trace_globals
from opentelemetry.test.test_base import TestBase
from opentelemetry.trace.status import StatusCode
from opentelemetry.util._importlib_metadata import entry_points
from opentelemetry.util.http import (
OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SANITIZE_FIELDS,
OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_REQUEST,
OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_RESPONSE,
get_excluded_urls,
)
_expected_metric_names_old = [
"http.server.active_requests",
"http.server.duration",
"http.server.response.size",
"http.server.request.size",
]
_expected_metric_names_new = [
"http.server.active_requests",
"http.server.request.duration",
"http.server.response.body.size",
"http.server.request.body.size",
]
_expected_metric_names_both = _expected_metric_names_old
_expected_metric_names_both.extend(_expected_metric_names_new)
_recommended_attrs_old = {
"http.server.active_requests": _server_active_requests_count_attrs_old,
"http.server.duration": {
*_server_duration_attrs_old,
HTTP_TARGET,
},
"http.server.response.size": {
*_server_duration_attrs_old,
HTTP_TARGET,
},
"http.server.request.size": {
*_server_duration_attrs_old,
HTTP_TARGET,
},
}
_recommended_attrs_new = {
"http.server.active_requests": _server_active_requests_count_attrs_new,
"http.server.request.duration": _server_duration_attrs_new,
"http.server.response.body.size": _server_duration_attrs_new,
"http.server.request.body.size": _server_duration_attrs_new,
}
_recommended_attrs_both = _recommended_attrs_old.copy()
_recommended_attrs_both.update(_recommended_attrs_new)
_recommended_attrs_both["http.server.active_requests"].extend(_server_active_requests_count_attrs_old)
class CustomMiddleware:
def __init__(self, app: fastapi.FastAPI) -> None:
self.app = app
async def __call__(self, scope: Scope, receive: Receive, send: Send) -> None:
scope["nonstandard_field"] = "here"
await self.app(scope, receive, send)
class CustomRoute(APIRoute):
def matches(self, scope: Scope) -> tuple[Match, Scope]:
assert "nonstandard_field" in scope
return super().matches(scope)
SCOPE = "opentelemetry.instrumentation.fastapi"
class TestBaseFastAPI(TestBase):
def _create_app(self):
app = self._create_fastapi_app()
self._instrumentor.instrument_app(
app=app,
server_request_hook=getattr(self, "server_request_hook", None),
client_request_hook=getattr(self, "client_request_hook", None),
client_response_hook=getattr(self, "client_response_hook", None),
)
return app
def _create_app_explicit_excluded_urls(self):
app = self._create_fastapi_app()
to_exclude = "/user/123,/foobar"
self._instrumentor.instrument_app(
app,
excluded_urls=to_exclude,
server_request_hook=getattr(self, "server_request_hook", None),
client_request_hook=getattr(self, "client_request_hook", None),
client_response_hook=getattr(self, "client_response_hook", None),
)
return app
@classmethod
def setUpClass(cls):
if cls is TestBaseFastAPI:
raise unittest.SkipTest(f"{cls.__name__} is an abstract base class")
super().setUpClass()
def setUp(self):
super().setUp()
test_name = ""
if hasattr(self, "_testMethodName"):
test_name = self._testMethodName
sem_conv_mode = "default"
if "new_semconv" in test_name:
sem_conv_mode = "http"
elif "both_semconv" in test_name:
sem_conv_mode = "http/dup"
self.env_patch = patch.dict(
"os.environ",
{
"OTEL_PYTHON_FASTAPI_EXCLUDED_URLS": "/exclude/123,healthzz",
OTEL_SEMCONV_STABILITY_OPT_IN: sem_conv_mode,
},
)
_OpenTelemetrySemanticConventionStability._initialized = False
self.env_patch.start()
self.exclude_patch = patch(
"opentelemetry.instrumentation.fastapi._excluded_urls_from_env",
get_excluded_urls("FASTAPI"),
)
self.exclude_patch.start()
self._instrumentor = otel_fastapi.FastAPIInstrumentor()
self._app = self._create_app()
self._app.add_middleware(HTTPSRedirectMiddleware)
self._app.add_middleware(CustomMiddleware)
self._client = TestClient(self._app, base_url="https://testserver:443")
# run the lifespan, initialize the middleware stack
# this is more in-line with what happens in a real application when the server starts up
self._exit_stack = ExitStack()
self._exit_stack.enter_context(self._client)
def tearDown(self):
self._exit_stack.close()
super().tearDown()
self.env_patch.stop()
self.exclude_patch.stop()
with self.disable_logging():
self._instrumentor.uninstrument()
self._instrumentor.uninstrument_app(self._app)
@staticmethod
def _create_fastapi_app():
app = fastapi.FastAPI()
sub_app = fastapi.FastAPI()
custom_router = fastapi.APIRouter(route_class=CustomRoute)
@sub_app.get("/home")
async def _home():
return {"message": "sub hi"}
@app.get("/foobar")
async def _foobar():
return {"message": "hello world"}
@app.get("/user/{username}")
async def _user(username: str):
return {"message": username}
@app.get("/exclude/{param}")
async def _exclude(param: str):
return {"message": param}
@app.get("/healthzz")
async def _health():
return {"message": "ok"}
@app.get("/error")
async def _error():
raise UnhandledException("This is an unhandled exception")
@custom_router.get("/success")
async def _():
return None
app.include_router(custom_router, prefix="/custom-router")
app.mount("/sub", app=sub_app)
app.host("testserver2", sub_app)
return app
class UnhandledException(Exception):
pass
class TestBaseManualFastAPI(TestBaseFastAPI):
@classmethod
def setUpClass(cls):
if cls is TestBaseManualFastAPI:
raise unittest.SkipTest(f"{cls.__name__} is an abstract base class")
super().setUpClass()
def test_fastapi_unhandled_exception(self):
"""If the application has an unhandled error the instrumentation should capture that a 500 response is returned."""
try:
resp = self._client.get("/error")
assert resp.status_code == 500, (
resp.content
) # pragma: no cover, for debugging this test if an exception is _not_ raised
except UnhandledException:
pass
else:
self.fail("Expected UnhandledException")
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 3)
span = spans[0]
assert span.name == "GET /error http send"
assert span.attributes[HTTP_STATUS_CODE] == 500
span = spans[2]
assert span.name == "GET /error"
assert span.attributes[HTTP_TARGET] == "/error"
def test_sub_app_fastapi_call(self):
"""
This test is to ensure that a span in case of a sub app targeted contains the correct server url
As this test case covers manual instrumentation, we won't see any additional spans for the sub app.
In this case all generated spans might suffice the requirements for the attributes already
(as the testcase is not setting a root_path for the outer app here)
"""
self._client.get("/sub/home")
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 3)
for span in spans:
# As we are only looking to the "outer" app, we would see only the "GET /sub" spans
self.assertIn("GET /sub", span.name)
# We now want to specifically test all spans including the
# - HTTP_TARGET
# - HTTP_URL
# attributes to be populated with the expected values
spans_with_http_attributes = [
span for span in spans if (HTTP_URL in span.attributes or HTTP_TARGET in span.attributes)
]
# We expect only one span to have the HTTP attributes set (the SERVER span from the app itself)
# the sub app is not instrumented with manual instrumentation tests.
self.assertEqual(1, len(spans_with_http_attributes))
for span in spans_with_http_attributes:
self.assertEqual("/sub/home", span.attributes[HTTP_TARGET])
self.assertEqual(
"https://testserver/sub/home",
span.attributes[HTTP_URL],
)
def test_custom_api_router(self):
"""
This test is to ensure that custom API routers the OpenTelemetryMiddleware does not cause issues with
custom API routers that depend on non-standard fields on the ASGI scope.
"""
resp: Final = self._client.get("/custom-router/success")
spans: Final = self.memory_exporter.get_finished_spans()
spans_with_http_attributes = [
span for span in spans if (HTTP_URL in span.attributes or HTTP_TARGET in span.attributes)
]
self.assertEqual(200, resp.status_code)
for span in spans_with_http_attributes:
self.assertEqual("/custom-router/success", span.attributes[HTTP_TARGET])
self.assertEqual(
"https://testserver/custom-router/success",
span.attributes[HTTP_URL],
)
def test_included_router_route_details(self):
"""
Regression test for
https://github.com/open-telemetry/opentelemetry-python-contrib/issues/4699
FastAPI 0.137 added intermediate ``_IncludedRouter`` objects to
``app.routes`` that do not expose a ``path`` attribute. Resolving the
route details for a request to an ``include_router``-added route must
not raise ``AttributeError`` and must still report the templated route.
"""
app = fastapi.FastAPI()
router = fastapi.APIRouter()
@router.get("/items/{item_id}")
async def _read_item(item_id: str):
return {"item_id": item_id}
app.include_router(router, prefix="/api")
self._instrumentor.instrument_app(app)
try:
client = TestClient(app)
resp = client.get("/api/items/123")
self.assertEqual(200, resp.status_code)
spans = self.memory_exporter.get_finished_spans()
self.assertTrue(spans)
server_span = spans[-1]
self.assertEqual("/api/items/{item_id}", server_span.attributes[HTTP_ROUTE])
self.assertIn("GET /api/items/{item_id}", server_span.name)
finally:
self._instrumentor.uninstrument_app(app)
def test_custom_route_preserves_templated_path(self):
class CustomPathRoute(BaseRoute):
path = "/widgets/{widget_id}"
def matches(self, scope: Scope) -> tuple[Match, Scope]:
return Match.FULL, scope
def url_path_for(self, name: str, /, **path_params: Any) -> Any:
raise NotImplementedError()
async def handle(self, scope: Scope, receive: Receive, send: Send) -> None:
raise NotImplementedError()
app = fastapi.FastAPI()
app.router.routes = [CustomPathRoute()]
scope = cast(
Scope,
{"type": "http", "app": app, "path": "/widgets/42"},
)
with patch.object(otel_fastapi, "iter_route_contexts", None):
self.assertEqual("/widgets/{widget_id}", otel_fastapi._get_route_details(scope))
def test_host_fastapi_call(self):
client = TestClient(self._app, base_url="https://testserver2:443")
client.get("/")
spans = self.memory_exporter.get_finished_spans()
spans_with_http_attributes = [
span for span in spans if (HTTP_URL in span.attributes or HTTP_TARGET in span.attributes)
]
self.assertEqual(1, len(spans_with_http_attributes))
for span in spans_with_http_attributes:
self.assertEqual("/", span.attributes[HTTP_TARGET])
self.assertEqual(
"https://testserver2/",
span.attributes[HTTP_URL],
)
class TestBaseAutoFastAPI(TestBaseFastAPI):
@classmethod
def setUpClass(cls):
if cls is TestBaseAutoFastAPI:
raise unittest.SkipTest(f"{cls.__name__} is an abstract base class")
super().setUpClass()
def test_sub_app_fastapi_call(self):
"""
This test is to ensure that a span in case of a sub app targeted contains the correct server url
As this test case covers auto instrumentation, we will see additional spans for the sub app.
In this case all generated spans might suffice the requirements for the attributes already
(as the testcase is not setting a root_path for the outer app here)
"""
self._client.get("/sub/home")
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 6)
for span in spans:
# As we are only looking to the "outer" app, we would see only the "GET /sub" spans
# -> the outer app is not aware of the sub_apps internal routes
sub_in = "GET /sub" in span.name
# The sub app spans are named GET /home as from the sub app perspective the request targets /home
# -> the sub app is technically not aware of the /sub prefix
home_in = "GET /home" in span.name
# We expect the spans to be either from the outer app or the sub app
self.assertTrue(
sub_in or home_in,
f"Span {span.name} does not have /sub or /home in its name",
)
# We now want to specifically test all spans including the
# - HTTP_TARGET
# - HTTP_URL
# attributes to be populated with the expected values
spans_with_http_attributes = [
span for span in spans if (HTTP_URL in span.attributes or HTTP_TARGET in span.attributes)
]
# We now expect spans with attributes from both the app and its sub app
self.assertEqual(2, len(spans_with_http_attributes))
for span in spans_with_http_attributes:
self.assertEqual("/sub/home", span.attributes[HTTP_TARGET])
self.assertEqual(
"https://testserver/sub/home",
span.attributes[HTTP_URL],
)
# pylint: disable=too-many-public-methods
class TestFastAPIManualInstrumentation(TestBaseManualFastAPI):
def test_instrument_app_with_instrument(self):
if not isinstance(self, TestAutoInstrumentation):
self._instrumentor.instrument()
self._client.get("/foobar")
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 3)
for span in spans:
self.assertIn("GET /foobar", span.name)
self.assertEqual(
span.instrumentation_scope.name,
SCOPE,
)
def test_uninstrument_app(self):
self._client.get("/foobar")
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 3)
self._instrumentor.uninstrument_app(self._app)
self.assertFalse(isinstance(self._app.user_middleware[0].cls, OpenTelemetryMiddleware))
self._client = TestClient(self._app)
resp = self._client.get("/foobar")
self.assertEqual(200, resp.status_code)
span_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(span_list), 3)
def test_uninstrument_app_after_instrument(self):
if not isinstance(self, TestAutoInstrumentation):
self._instrumentor.instrument()
self._instrumentor.uninstrument_app(self._app)
self._client.get("/foobar")
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 0)
def test_basic_fastapi_call(self):
self._client.get("/foobar")
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 3)
for span in spans:
self.assertIn("GET /foobar", span.name)
def test_background_task_span_parents_inner_spans(self):
"""Regression test for #4251: spans created inside a FastAPI
BackgroundTask must be children of a dedicated background-task span
instead of the already-closed request span."""
self.memory_exporter.clear()
app = fastapi.FastAPI()
self._instrumentor.instrument_app(app)
tracer = self.tracer_provider.get_tracer(__name__)
async def background_notify():
with tracer.start_as_current_span("inside-background-task"):
pass
@app.post("/checkout")
async def checkout(background_tasks: BackgroundTasks):
background_tasks.add_task(background_notify)
return {"status": "processing"}
with TestClient(app) as client:
response = client.post("/checkout")
self.assertEqual(200, response.status_code)
spans = self.memory_exporter.get_finished_spans()
request_span = next(span for span in spans if span.name == "POST /checkout")
background_span = next(span for span in spans if span.name == "BackgroundTask background_notify")
inner_span = next(span for span in spans if span.name == "inside-background-task")
self.assertIsNotNone(background_span.parent)
self.assertEqual(
background_span.parent.span_id,
request_span.context.span_id,
)
self.assertIsNotNone(inner_span.parent)
self.assertEqual(
inner_span.parent.span_id,
background_span.context.span_id,
)
otel_fastapi.FastAPIInstrumentor().uninstrument_app(app)
def test_fastapi_route_attribute_added(self):
"""Ensure that fastapi routes are used as the span name."""
self._client.get("/user/123")
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 3)
for span in spans:
self.assertIn("GET /user/{username}", span.name)
self.assertEqual(spans[-1].attributes[HTTP_ROUTE], "/user/{username}")
# ensure that at least one attribute that is populated by
# the asgi instrumentation is successfully feeding though.
self.assertEqual(spans[-1].attributes[HTTP_FLAVOR], "1.1")
def test_fastapi_excluded_urls(self):
"""Ensure that given fastapi routes are excluded."""
self._client.get("/exclude/123")
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 0)
self._client.get("/healthzz")
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 0)
def test_fastapi_excluded_urls_not_env(self):
"""Ensure that given fastapi routes are excluded when passed explicitly (not in the environment)"""
app = self._create_app_explicit_excluded_urls()
client = TestClient(app)
client.get("/user/123")
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 0)
client.get("/foobar")
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 0)
def test_fastapi_metrics(self):
self._client.get("/foobar")
self._client.get("/foobar")
self._client.get("/foobar")
number_data_point_seen = False
histogram_data_point_seen = False
metrics = self.get_sorted_metrics(SCOPE)
self.assertTrue(len(metrics) == 3)
for metric in metrics:
self.assertIn(metric.name, _expected_metric_names_old)
data_points = list(metric.data.data_points)
self.assertEqual(len(data_points), 1)
for point in data_points:
if isinstance(point, HistogramDataPoint):
self.assertEqual(point.count, 3)
histogram_data_point_seen = True
if isinstance(point, NumberDataPoint):
number_data_point_seen = True
for attr in point.attributes:
self.assertIn(attr, _recommended_attrs_old[metric.name])
self.assertTrue(number_data_point_seen and histogram_data_point_seen)
def test_fastapi_metrics_new_semconv(self):
self._client.get("/foobar")
self._client.get("/foobar")
self._client.get("/foobar")
number_data_point_seen = False
histogram_data_point_seen = False
metrics = self.get_sorted_metrics(SCOPE)
self.assertTrue(len(metrics) == 3)
for metric in metrics:
self.assertIn(metric.name, _expected_metric_names_new)
data_points = list(metric.data.data_points)
self.assertEqual(len(data_points), 1)
for point in data_points:
if isinstance(point, HistogramDataPoint):
self.assertEqual(point.count, 3)
histogram_data_point_seen = True
if isinstance(point, NumberDataPoint):
number_data_point_seen = True
for attr in point.attributes:
self.assertIn(attr, _recommended_attrs_new[metric.name])
self.assertTrue(number_data_point_seen and histogram_data_point_seen)
def test_fastapi_metrics_both_semconv(self):
self._client.get("/foobar")
self._client.get("/foobar")
self._client.get("/foobar")
number_data_point_seen = False
histogram_data_point_seen = False
metrics = self.get_sorted_metrics(SCOPE)
self.assertTrue(len(metrics) == 5)
for metric in metrics:
self.assertIn(metric.name, _expected_metric_names_both)
data_points = list(metric.data.data_points)
self.assertEqual(len(data_points), 1)
for point in data_points:
if isinstance(point, HistogramDataPoint):
self.assertEqual(point.count, 3)
histogram_data_point_seen = True
if isinstance(point, NumberDataPoint):
number_data_point_seen = True
for attr in point.attributes:
self.assertIn(attr, _recommended_attrs_both[metric.name])
self.assertTrue(number_data_point_seen and histogram_data_point_seen)
def test_basic_metric_success(self):
start = default_timer()
self._client.get("/foobar")
duration = max(round((default_timer() - start) * 1000), 0)
expected_duration_attributes = {
HTTP_METHOD: "GET",
HTTP_HOST: "testserver:443",
HTTP_SCHEME: "https",
HTTP_FLAVOR: "1.1",
HTTP_SERVER_NAME: "testserver",
NET_HOST_PORT: 443,
HTTP_STATUS_CODE: 200,
HTTP_TARGET: "/foobar",
}
expected_requests_count_attributes = {
HTTP_METHOD: "GET",
HTTP_HOST: "testserver:443",
HTTP_SCHEME: "https",
HTTP_FLAVOR: "1.1",
HTTP_SERVER_NAME: "testserver",
}
metrics = self.get_sorted_metrics(SCOPE)
for metric in metrics:
for point in list(metric.data.data_points):
if isinstance(point, HistogramDataPoint):
self.assertDictEqual(
expected_duration_attributes,
dict(point.attributes),
)
self.assertEqual(point.count, 1)
self.assertAlmostEqual(duration, point.sum, delta=350)
if isinstance(point, NumberDataPoint):
self.assertDictEqual(
expected_requests_count_attributes,
dict(point.attributes),
)
self.assertEqual(point.value, 0)
def test_basic_metric_success_new_semconv(self):
start = default_timer()
self._client.get("/foobar")
duration_s = max(default_timer() - start, 0)
expected_duration_attributes = {
HTTP_REQUEST_METHOD: "GET",
URL_SCHEME: "https",
NETWORK_PROTOCOL_VERSION: "1.1",
HTTP_RESPONSE_STATUS_CODE: 200,
HTTP_ROUTE: "/foobar",
}
expected_requests_count_attributes = {
HTTP_REQUEST_METHOD: "GET",
URL_SCHEME: "https",
}
metrics = self.get_sorted_metrics(SCOPE)
for metric in metrics:
for point in list(metric.data.data_points):
if isinstance(point, HistogramDataPoint):
self.assertDictEqual(
expected_duration_attributes,
dict(point.attributes),
)
self.assertEqual(point.count, 1)
if metric.name == "http.server.request.duration":
self.assertAlmostEqual(duration_s * 0.1, point.sum, places=1)
elif metric.name in (
"http.server.response.body.size",
"http.server.request.body.size",
):
self.assertEqual(25, point.sum)
if isinstance(point, NumberDataPoint):
self.assertDictEqual(
expected_requests_count_attributes,
dict(point.attributes),
)
self.assertEqual(point.value, 0)
def test_basic_metric_success_both_semconv(self):
start = default_timer()
self._client.get("/foobar")
duration = max(round((default_timer() - start) * 1000), 0)
duration_s = max(default_timer() - start, 0)
expected_duration_attributes_old = {
HTTP_METHOD: "GET",
HTTP_HOST: "testserver:443",
HTTP_SCHEME: "https",
HTTP_FLAVOR: "1.1",
HTTP_SERVER_NAME: "testserver",
NET_HOST_PORT: 443,
HTTP_STATUS_CODE: 200,
HTTP_TARGET: "/foobar",
}
expected_duration_attributes_new = {
HTTP_REQUEST_METHOD: "GET",
URL_SCHEME: "https",
NETWORK_PROTOCOL_VERSION: "1.1",
HTTP_RESPONSE_STATUS_CODE: 200,
HTTP_ROUTE: "/foobar",
}
expected_requests_count_attributes = {
HTTP_METHOD: "GET",
HTTP_HOST: "testserver:443",
HTTP_SCHEME: "https",
HTTP_FLAVOR: "1.1",
HTTP_SERVER_NAME: "testserver",
HTTP_REQUEST_METHOD: "GET",
URL_SCHEME: "https",
}
metrics = self.get_sorted_metrics(SCOPE)
for metric in metrics:
for point in list(metric.data.data_points):
if isinstance(point, HistogramDataPoint):
self.assertEqual(point.count, 1)
self.assertAlmostEqual(duration, point.sum, delta=350)
if metric.name == "http.server.request.duration":
self.assertAlmostEqual(duration_s * 0.1, point.sum, places=1)
self.assertDictEqual(
expected_duration_attributes_new,
dict(point.attributes),
)
elif metric.name in (
"http.server.response.body.size",
"http.server.request.body.size",
):
self.assertEqual(25, point.sum)
self.assertDictEqual(
expected_duration_attributes_new,
dict(point.attributes),
)
elif metric.name == "http.server.duration":
self.assertAlmostEqual(duration, point.sum, delta=350)
self.assertDictEqual(
expected_duration_attributes_old,
dict(point.attributes),
)
elif metric.name in (
"http.server.response.size",
"http.server.request.size",
):
self.assertEqual(25, point.sum)
self.assertDictEqual(
expected_duration_attributes_old,
dict(point.attributes),
)
if isinstance(point, NumberDataPoint):
self.assertDictEqual(
expected_requests_count_attributes,
dict(point.attributes),
)
self.assertEqual(point.value, 0)
def test_basic_metric_nonstandard_http_method_success(self):
start = default_timer()
self._client.request("NONSTANDARD", "/foobar")
duration = max(round((default_timer() - start) * 1000), 0)
expected_duration_attributes = {
HTTP_METHOD: "_OTHER",
HTTP_HOST: "testserver:443",
HTTP_SCHEME: "https",
HTTP_FLAVOR: "1.1",
HTTP_SERVER_NAME: "testserver",
NET_HOST_PORT: 443,
HTTP_STATUS_CODE: 405,
HTTP_TARGET: "/foobar",
}
expected_requests_count_attributes = {
HTTP_METHOD: "_OTHER",
HTTP_HOST: "testserver:443",
HTTP_SCHEME: "https",
HTTP_FLAVOR: "1.1",
HTTP_SERVER_NAME: "testserver",
}
metrics = self.get_sorted_metrics(SCOPE)
for metric in metrics:
for point in list(metric.data.data_points):
if isinstance(point, HistogramDataPoint):
self.assertDictEqual(
expected_duration_attributes,
dict(point.attributes),
)
self.assertEqual(point.count, 1)
self.assertAlmostEqual(duration, point.sum, delta=350)
if isinstance(point, NumberDataPoint):
self.assertDictEqual(
expected_requests_count_attributes,
dict(point.attributes),
)
self.assertEqual(point.value, 0)
def test_basic_metric_nonstandard_http_method_success_new_semconv(self):
start = default_timer()
self._client.request("NONSTANDARD", "/foobar")
duration_s = max(default_timer() - start, 0)
expected_duration_attributes = {
HTTP_REQUEST_METHOD: "_OTHER",
URL_SCHEME: "https",
NETWORK_PROTOCOL_VERSION: "1.1",
HTTP_RESPONSE_STATUS_CODE: 405,
HTTP_ROUTE: "/foobar",
}
expected_requests_count_attributes = {
HTTP_REQUEST_METHOD: "_OTHER",
URL_SCHEME: "https",
}
metrics = self.get_sorted_metrics(SCOPE)
for metric in metrics:
for point in list(metric.data.data_points):
if isinstance(point, HistogramDataPoint):
self.assertDictEqual(
expected_duration_attributes,
dict(point.attributes),
)
self.assertEqual(point.count, 1)
if metric.name == "http.server.request.duration":
self.assertAlmostEqual(duration_s * 0.1, point.sum, places=1)
elif metric.name == "http.server.response.body.size":
self.assertEqual(31, point.sum)
elif metric.name == "http.server.request.body.size":
self.assertEqual(25, point.sum)
if isinstance(point, NumberDataPoint):
self.assertDictEqual(
expected_requests_count_attributes,
dict(point.attributes),
)
self.assertEqual(point.value, 0)
def test_basic_metric_nonstandard_http_method_success_both_semconv(self):
start = default_timer()
self._client.request("NONSTANDARD", "/foobar")
duration = max(round((default_timer() - start) * 1000), 0)
duration_s = max(default_timer() - start, 0)
expected_duration_attributes_old = {
HTTP_METHOD: "_OTHER",
HTTP_HOST: "testserver:443",
HTTP_SCHEME: "https",
HTTP_FLAVOR: "1.1",
HTTP_SERVER_NAME: "testserver",
NET_HOST_PORT: 443,
HTTP_STATUS_CODE: 405,
HTTP_TARGET: "/foobar",
}
expected_duration_attributes_new = {
HTTP_REQUEST_METHOD: "_OTHER",
URL_SCHEME: "https",
NETWORK_PROTOCOL_VERSION: "1.1",
HTTP_RESPONSE_STATUS_CODE: 405,
HTTP_ROUTE: "/foobar",
}
expected_requests_count_attributes = {
HTTP_METHOD: "_OTHER",
HTTP_HOST: "testserver:443",
HTTP_SCHEME: "https",
HTTP_FLAVOR: "1.1",
HTTP_SERVER_NAME: "testserver",
HTTP_REQUEST_METHOD: "_OTHER",
URL_SCHEME: "https",
}
metrics = self.get_sorted_metrics(SCOPE)
for metric in metrics:
for point in list(metric.data.data_points):
if isinstance(point, HistogramDataPoint):
self.assertEqual(point.count, 1)
if metric.name == "http.server.request.duration":
self.assertAlmostEqual(duration_s * 0.1, point.sum, places=1)
self.assertDictEqual(
expected_duration_attributes_new,
dict(point.attributes),
)
elif metric.name == "http.server.response.body.size":
self.assertEqual(31, point.sum)
self.assertDictEqual(
expected_duration_attributes_new,
dict(point.attributes),
)
elif metric.name == "http.server.request.body.size":
self.assertEqual(25, point.sum)
self.assertDictEqual(
expected_duration_attributes_new,
dict(point.attributes),
)
elif metric.name == "http.server.duration":
self.assertAlmostEqual(duration, point.sum, delta=350)
self.assertDictEqual(
expected_duration_attributes_old,
dict(point.attributes),
)
elif metric.name == "http.server.response.size":
self.assertEqual(31, point.sum)
self.assertDictEqual(
expected_duration_attributes_old,
dict(point.attributes),
)
elif metric.name == "http.server.request.size":
self.assertEqual(25, point.sum)
self.assertDictEqual(
expected_duration_attributes_old,
dict(point.attributes),
)
if isinstance(point, NumberDataPoint):
self.assertDictEqual(
expected_requests_count_attributes,
dict(point.attributes),
)
self.assertEqual(point.value, 0)
def test_basic_post_request_metric_success(self):
start = default_timer()
response = self._client.post(
"/foobar",
json={"foo": "bar"},
)
duration = max(round((default_timer() - start) * 1000), 0)
response_size = int(response.headers.get("content-length"))
request_size = int(response.request.headers.get("content-length"))
metrics = self.get_sorted_metrics(SCOPE)
for metric in metrics:
for point in list(metric.data.data_points):
if isinstance(point, HistogramDataPoint):
self.assertEqual(point.count, 1)
if metric.name == "http.server.duration":
self.assertAlmostEqual(duration, point.sum, delta=350)
elif metric.name == "http.server.response.size":
self.assertEqual(response_size, point.sum)
elif metric.name == "http.server.request.size":
self.assertEqual(request_size, point.sum)
if isinstance(point, NumberDataPoint):
self.assertEqual(point.value, 0)
def test_basic_post_request_metric_success_new_semconv(self):
start = default_timer()
response = self._client.post(
"/foobar",
json={"foo": "bar"},
)
duration_s = max(default_timer() - start, 0)
response_size = int(response.headers.get("content-length"))
request_size = int(response.request.headers.get("content-length"))
metrics = self.get_sorted_metrics(SCOPE)
for metric in metrics:
for point in list(metric.data.data_points):
if isinstance(point, HistogramDataPoint):
self.assertEqual(point.count, 1)
if metric.name == "http.server.request.duration":
self.assertAlmostEqual(duration_s * 0.1, point.sum, places=1)
elif metric.name == "http.server.response.body.size":
self.assertEqual(response_size, point.sum)
elif metric.name == "http.server.request.body.size":
self.assertEqual(request_size, point.sum)
if isinstance(point, NumberDataPoint):
self.assertEqual(point.value, 0)
def test_basic_post_request_metric_success_both_semconv(self):
start = default_timer()
response = self._client.post(
"/foobar",
json={"foo": "bar"},
)
duration = max(round((default_timer() - start) * 1000), 0)
duration_s = max(default_timer() - start, 0)
response_size = int(response.headers.get("content-length"))
request_size = int(response.request.headers.get("content-length"))
metrics = self.get_sorted_metrics(SCOPE)
for metric in metrics:
for point in list(metric.data.data_points):
if isinstance(point, HistogramDataPoint):
self.assertEqual(point.count, 1)
if metric.name == "http.server.request.duration":
self.assertAlmostEqual(duration_s * 0.1, point.sum, places=1)
elif metric.name == "http.server.response.body.size":
self.assertEqual(response_size, point.sum)
elif metric.name == "http.server.request.body.size":
self.assertEqual(request_size, point.sum)
elif metric.name == "http.server.duration":
self.assertAlmostEqual(duration, point.sum, delta=350)
elif metric.name == "http.server.response.size":
self.assertEqual(response_size, point.sum)
elif metric.name == "http.server.request.size":
self.assertEqual(request_size, point.sum)
if isinstance(point, NumberDataPoint):
self.assertEqual(point.value, 0)
def test_uninstrument_app_restores_background_task_call(self):
"""Regression test for #4251: uninstrumentation must restore the
original BackgroundTask.__call__ after FastAPI patches it."""
self.assertTrue(hasattr(BackgroundTask, "_otel_original_call"))
self._instrumentor.uninstrument_app(self._app)
self.assertFalse(hasattr(BackgroundTask, "_otel_original_call"))
def test_background_task_span_not_duplicated_on_double_instrument_app(
self,
):
"""Regression test for #4251: repeated instrument_app calls must not
wrap BackgroundTask.__call__ multiple times or duplicate spans."""
self.memory_exporter.clear()
app = fastapi.FastAPI()
self._instrumentor.instrument_app(app)
self._instrumentor.instrument_app(app)
tracer = self.tracer_provider.get_tracer(__name__)
async def background_notify():
with tracer.start_as_current_span("inside-background-task"):
pass
@app.post("/checkout")
async def checkout(background_tasks: BackgroundTasks):
background_tasks.add_task(background_notify)
return {"status": "processing"}
with TestClient(app) as client:
response = client.post("/checkout")
self.assertEqual(200, response.status_code)
spans = self.memory_exporter.get_finished_spans()
background_spans = [span for span in spans if span.name == "BackgroundTask background_notify"]
inner_spans = [span for span in spans if span.name == "inside-background-task"]
self.assertEqual(len(background_spans), 1)
self.assertEqual(len(inner_spans), 1)
otel_fastapi.FastAPIInstrumentor().uninstrument_app(app)
def test_metric_uninstrument_app(self):
self._client.get("/foobar")
self._instrumentor.uninstrument_app(self._app)
self._client.get("/foobar")
metrics = self.get_sorted_metrics(SCOPE)
for metric in metrics:
for point in list(metric.data.data_points):
if isinstance(point, HistogramDataPoint):
self.assertEqual(point.count, 1)
if isinstance(point, NumberDataPoint):
self.assertEqual(point.value, 0)
def test_metric_uninstrument(self):
if not isinstance(self, TestAutoInstrumentation):
self._instrumentor.instrument()
self._client.get("/foobar")
self._instrumentor.uninstrument()
self._client.get("/foobar")
metrics = self.get_sorted_metrics(SCOPE)
for metric in metrics:
for point in list(metric.data.data_points):
if isinstance(point, HistogramDataPoint):
self.assertEqual(point.count, 1)
if isinstance(point, NumberDataPoint):
self.assertEqual(point.value, 0)
@staticmethod
def _create_fastapi_app():
app = fastapi.FastAPI()
sub_app = fastapi.FastAPI()
custom_router = fastapi.APIRouter(route_class=CustomRoute)
@sub_app.get("/home")
async def _home():
return {"message": "sub hi"}
@app.get("/foobar")
async def _foobar():
return {"message": "hello world"}
@app.get("/user/{username}")
async def _user(username: str):
return {"message": username}
@app.get("/exclude/{param}")
async def _exclude(param: str):
return {"message": param}
@app.get("/healthzz")
async def _health():
return {"message": "ok"}
@app.get("/error")
async def _error():
raise UnhandledException("This is an unhandled exception")
@custom_router.get("/success")
async def _():
return None
app.include_router(custom_router, prefix="/custom-router")
app.mount("/sub", app=sub_app)
return app
class TestFastAPIManualInstrumentationHooks(TestBaseFastAPI):
def _create_app(self):
def server_request_hook(span: trace.Span, scope: dict[str, Any]):
span.update_name("name from server hook")
def client_request_hook(
receive_span: trace.Span,
scope: dict[str, Any],
message: dict[str, Any],
):
receive_span.update_name("name from client hook")
receive_span.set_attribute("attr-from-request-hook", "set")
def client_response_hook(
send_span: trace.Span,
scope: dict[str, Any],
message: dict[str, Any],
):
send_span.update_name("name from response hook")
send_span.set_attribute("attr-from-response-hook", "value")
self._instrumentor.instrument(
server_request_hook=server_request_hook,
client_request_hook=client_request_hook,
client_response_hook=client_response_hook,
)
app = self._create_fastapi_app()
return app
def test_hooks(self):
self._client.get("/foobar")
spans = cast(
list[ReadableSpan],
self.sorted_spans(self.memory_exporter.get_finished_spans()),
)
self.assertEqual(len(spans), 3)
server_span = spans[2]
self.assertEqual(server_span.name, "name from server hook")
response_spans = spans[:2]
for span in response_spans:
self.assertEqual(span.name, "name from response hook")
self.assertSpanHasAttributes(span, {"attr-from-response-hook": "value"})
class TestAutoInstrumentation(TestBaseAutoFastAPI):
"""Test the auto-instrumented variant
Extending the manual instrumentation as most test cases apply
to both.
"""
def test_entry_point_exists(self):
(ep,) = entry_points(group="opentelemetry_instrumentor")
self.assertEqual(ep.name, "fastapi")
@staticmethod
def _instrumentation_loaded_successfully_call():
return call("Instrumented %s", "fastapi")
@staticmethod
def _instrumentation_failed_to_load_call(dependency_conflict):
return call(dependency_conflict._format_message("fastapi"))
@patch("opentelemetry.instrumentation.auto_instrumentation._load._logger")
def test_instruments_with_fastapi_installed(self, mock_logger):
mock_distro = Mock()
mock_distro.load_instrumentor.return_value = None
_load_instrumentors(mock_distro)
self.assertEqual(len(mock_distro.load_instrumentor.call_args_list), 1)
(ep,) = mock_distro.load_instrumentor.call_args.args
self.assertEqual(ep.name, "fastapi")
mock_logger.debug.assert_has_calls([self._instrumentation_loaded_successfully_call()])
@patch("opentelemetry.instrumentation.auto_instrumentation._load.get_dist_dependency_conflicts")
@patch("opentelemetry.instrumentation.auto_instrumentation._load._logger")
def test_instruments_with_old_fastapi_installed(self, mock_logger, mock_dep): # pylint: disable=no-self-use
dependency_conflict = DependencyConflict("0.58", "0.57")
mock_distro = Mock()
mock_dep.return_value = dependency_conflict
_load_instrumentors(mock_distro)
mock_distro.load_instrumentor.assert_not_called()
mock_logger.error.assert_has_calls([self._instrumentation_failed_to_load_call(dependency_conflict)])
@patch("opentelemetry.instrumentation.auto_instrumentation._load.get_dist_dependency_conflicts")
@patch("opentelemetry.instrumentation.auto_instrumentation._load._logger")
def test_instruments_without_fastapi_installed(self, mock_logger, mock_dep): # pylint: disable=no-self-use
dependency_conflict = DependencyConflict("0.58", None)
mock_distro = Mock()
mock_dep.return_value = dependency_conflict
_load_instrumentors(mock_distro)
mock_distro.load_instrumentor.assert_not_called()
mock_logger.debug.assert_has_calls([self._instrumentation_failed_to_load_call(dependency_conflict)])
def _create_app(self):
# instrumentation is handled by the instrument call
resource = Resource.create({"key1": "value1", "key2": "value2"})
result = self.create_tracer_provider(resource=resource)
tracer_provider, exporter = result
self.memory_exporter = exporter
self._instrumentor.instrument(tracer_provider=tracer_provider)
return self._create_fastapi_app()
def _create_app_explicit_excluded_urls(self):
resource = Resource.create({"key1": "value1", "key2": "value2"})
tracer_provider, exporter = self.create_tracer_provider(resource=resource)
self.memory_exporter = exporter
to_exclude = "/user/123,/foobar"
self._instrumentor.uninstrument() # Disable previous instrumentation (setUp)
self._instrumentor.instrument(
tracer_provider=tracer_provider,
excluded_urls=to_exclude,
)
return self._create_fastapi_app()
def test_request(self):
self._client.get("/foobar")
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 3)
for span in spans:
self.assertEqual(span.resource.attributes["key1"], "value1")
self.assertEqual(span.resource.attributes["key2"], "value2")
def test_mulitple_way_instrumentation(self):
self._instrumentor.instrument_app(self._app)
count = 0
app = self._app.middleware_stack
while app is not None:
if isinstance(app, OpenTelemetryMiddleware):
count += 1
app = getattr(app, "app", None)
self.assertEqual(count, 1)
def test_uninstrument_after_instrument(self):
app = self._create_fastapi_app()
client = TestClient(app)
client.get("/foobar")
self._instrumentor.uninstrument()
client.get("/foobar")
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 3)
def test_no_op_tracer_provider(self):
self._instrumentor.uninstrument()
self._instrumentor.instrument(tracer_provider=trace.NoOpTracerProvider())
app = self._create_fastapi_app()
client = TestClient(app)
client.get("/foobar")
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 0)
def tearDown(self):
self._instrumentor.uninstrument()
super().tearDown()
def test_sub_app_fastapi_call(self):
"""
!!! Attention: we need to override this testcase for the auto-instrumented variant
The reason is, that with auto instrumentation, the sub app is instrumented as well
and therefore we would see the spans for the sub app as well
This test is to ensure that a span in case of a sub app targeted contains the correct server url
"""
self._client.get("/sub/home")
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 6)
for span in spans:
# As we are only looking to the "outer" app, we would see only the "GET /sub" spans
# -> the outer app is not aware of the sub_apps internal routes
sub_in = "GET /sub" in span.name
# The sub app spans are named GET /home as from the sub app perspective the request targets /home
# -> the sub app is technically not aware of the /sub prefix
home_in = "GET /home" in span.name
# We expect the spans to be either from the outer app or the sub app
self.assertTrue(
sub_in or home_in,
f"Span {span.name} does not have /sub or /home in its name",
)
# We now want to specifically test all spans including the
# - HTTP_TARGET
# - HTTP_URL
# attributes to be populated with the expected values
spans_with_http_attributes = [
span for span in spans if (HTTP_URL in span.attributes or HTTP_TARGET in span.attributes)
]
# We now expect spans with attributes from both the app and its sub app
self.assertEqual(2, len(spans_with_http_attributes))
for span in spans_with_http_attributes:
self.assertEqual("/sub/home", span.attributes[HTTP_TARGET])
self.assertEqual(
"https://testserver/sub/home",
span.attributes[HTTP_URL],
)
class TestAutoInstrumentationHooks(TestBaseAutoFastAPI):
"""
Test the auto-instrumented variant for request and response hooks
Extending the manual instrumentation to inherit defined hooks and since most test cases apply
to both.
"""
def _create_app(self):
# instrumentation is handled by the instrument call
self._instrumentor.instrument(
server_request_hook=getattr(self, "server_request_hook", None),
client_request_hook=getattr(self, "client_request_hook", None),
client_response_hook=getattr(self, "client_response_hook", None),
)
return self._create_fastapi_app()
def _create_app_explicit_excluded_urls(self):
resource = Resource.create({"key1": "value1", "key2": "value2"})
tracer_provider, exporter = self.create_tracer_provider(resource=resource)
self.memory_exporter = exporter
to_exclude = "/user/123,/foobar"
self._instrumentor.uninstrument() # Disable previous instrumentation (setUp)
self._instrumentor.instrument(
tracer_provider=tracer_provider,
excluded_urls=to_exclude,
server_request_hook=getattr(self, "server_request_hook", None),
client_request_hook=getattr(self, "client_request_hook", None),
client_response_hook=getattr(self, "client_response_hook", None),
)
return self._create_fastapi_app()
def tearDown(self):
self._instrumentor.uninstrument()
super().tearDown()
def test_sub_app_fastapi_call(self):
"""
!!! Attention: we need to override this testcase for the auto-instrumented variant
The reason is, that with auto instrumentation, the sub app is instrumented as well
and therefore we would see the spans for the sub app as well
This test is to ensure that a span in case of a sub app targeted contains the correct server url
"""
self._client.get("/sub/home")
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 6)
for span in spans:
# As we are only looking to the "outer" app, we would see only the "GET /sub" spans
# -> the outer app is not aware of the sub_apps internal routes
sub_in = "GET /sub" in span.name
# The sub app spans are named GET /home as from the sub app perspective the request targets /home
# -> the sub app is technically not aware of the /sub prefix
home_in = "GET /home" in span.name
# We expect the spans to be either from the outer app or the sub app
self.assertTrue(
sub_in or home_in,
f"Span {span.name} does not have /sub or /home in its name",
)
# We now want to specifically test all spans including the
# - HTTP_TARGET
# - HTTP_URL
# attributes to be populated with the expected values
spans_with_http_attributes = [
span for span in spans if (HTTP_URL in span.attributes or HTTP_TARGET in span.attributes)
]
# We now expect spans with attributes from both the app and its sub app
self.assertEqual(2, len(spans_with_http_attributes))
for span in spans_with_http_attributes:
self.assertEqual("/sub/home", span.attributes[HTTP_TARGET])
self.assertEqual(
"https://testserver/sub/home",
span.attributes[HTTP_URL],
)
class TestAutoInstrumentationLogic(unittest.TestCase):
def test_instrumentation(self):
"""Verify that instrumentation methods are instrumenting and
removing as expected.
"""
instrumentor = otel_fastapi.FastAPIInstrumentor()
original = fastapi.FastAPI
instrumentor.instrument()
try:
instrumented = fastapi.FastAPI
self.assertIsNot(original, instrumented)
finally:
instrumentor.uninstrument()
should_be_original = fastapi.FastAPI
self.assertIs(original, should_be_original)
class TestWrappedApplication(TestBase):
def setUp(self):
super().setUp()
self.app = fastapi.FastAPI()
@self.app.get("/foobar")
async def _():
return {"message": "hello world"}
otel_fastapi.FastAPIInstrumentor().instrument_app(self.app)
self.client = TestClient(self.app)
self.tracer = self.tracer_provider.get_tracer(__name__)
def tearDown(self) -> None:
super().tearDown()
with self.disable_logging():
otel_fastapi.FastAPIInstrumentor().uninstrument_app(self.app)
def test_mark_span_internal_in_presence_of_span_from_other_framework(self):
with self.tracer.start_as_current_span("test", kind=trace.SpanKind.SERVER) as parent_span:
resp = self.client.get("/foobar")
self.assertEqual(200, resp.status_code)
span_list = self.memory_exporter.get_finished_spans()
for span in span_list:
print(str(span.__class__) + ": " + str(span.__dict__))
# there should be 4 spans - single SERVER "test" and three INTERNAL "FastAPI"
self.assertEqual(trace.SpanKind.INTERNAL, span_list[0].kind)
self.assertEqual(trace.SpanKind.INTERNAL, span_list[1].kind)
# main INTERNAL span - child of test
self.assertEqual(trace.SpanKind.INTERNAL, span_list[2].kind)
self.assertEqual(parent_span.context.span_id, span_list[2].parent.span_id)
# SERVER "test"
self.assertEqual(trace.SpanKind.SERVER, span_list[3].kind)
self.assertEqual(parent_span.context.span_id, span_list[3].context.span_id)
class TestFastAPIGarbageCollection(unittest.TestCase):
def test_fastapi_app_is_collected_after_instrument(self):
app = fastapi.FastAPI()
otel_fastapi.FastAPIInstrumentor().instrument_app(app)
app_ref = _weakref.ref(app)
del app
_gc.collect()
self.assertIsNone(app_ref())
@patch.dict(
"os.environ",
{
OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SANITIZE_FIELDS: ".*my-secret.*",
OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_REQUEST: "Custom-Test-Header-1,Custom-Test-Header-2,Custom-Test-Header-3,Regex-Test-Header-.*,Regex-Invalid-Test-Header-.*,.*my-secret.*",
OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_RESPONSE: "Custom-Test-Header-1,Custom-Test-Header-2,Custom-Test-Header-3,my-custom-regex-header-.*,invalid-regex-header-.*,.*my-secret.*",
},
)
class TestHTTPAppWithCustomHeaders(TestBase):
def setUp(self):
super().setUp()
self.app = self._create_app()
otel_fastapi.FastAPIInstrumentor().instrument_app(self.app)
self.client = TestClient(self.app)
def tearDown(self) -> None:
super().tearDown()
with self.disable_logging():
otel_fastapi.FastAPIInstrumentor().uninstrument_app(self.app)
@staticmethod
def _create_app():
app = fastapi.FastAPI()
@app.get("/foobar")
async def _():
headers = {
"custom-test-header-1": "test-header-value-1",
"custom-test-header-2": "test-header-value-2",
"my-custom-regex-header-1": "my-custom-regex-value-1,my-custom-regex-value-2",
"My-Custom-Regex-Header-2": "my-custom-regex-value-3,my-custom-regex-value-4",
"My-Secret-Header": "My Secret Value",
}
content = {"message": "hello world"}
return JSONResponse(content=content, headers=headers)
return app
def test_http_custom_request_headers_in_span_attributes(self):
expected = {
"http.request.header.custom_test_header_1": ("test-header-value-1",),
"http.request.header.custom_test_header_2": ("test-header-value-2",),
"http.request.header.regex_test_header_1": ("Regex Test Value 1",),
"http.request.header.regex_test_header_2": ("RegexTestValue2,RegexTestValue3",),
"http.request.header.my_secret_header": ("[REDACTED]",),
}
resp = self.client.get(
"/foobar",
headers={
"custom-test-header-1": "test-header-value-1",
"custom-test-header-2": "test-header-value-2",
"Regex-Test-Header-1": "Regex Test Value 1",
"regex-test-header-2": "RegexTestValue2,RegexTestValue3",
"My-Secret-Header": "My Secret Value",
},
)
self.assertEqual(200, resp.status_code)
span_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(span_list), 3)
server_span = [span for span in span_list if span.kind == trace.SpanKind.SERVER][0]
self.assertSpanHasAttributes(server_span, expected)
def test_http_custom_request_headers_not_in_span_attributes(self):
not_expected = {
"http.request.header.custom_test_header_3": ("test-header-value-3",),
}
resp = self.client.get(
"/foobar",
headers={
"custom-test-header-1": "test-header-value-1",
"custom-test-header-2": "test-header-value-2",
"Regex-Test-Header-1": "Regex Test Value 1",
"regex-test-header-2": "RegexTestValue2,RegexTestValue3",
"My-Secret-Header": "My Secret Value",
},
)
self.assertEqual(200, resp.status_code)
span_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(span_list), 3)
server_span = [span for span in span_list if span.kind == trace.SpanKind.SERVER][0]
for key, _ in not_expected.items():
self.assertNotIn(key, server_span.attributes)
def test_http_custom_response_headers_in_span_attributes(self):
expected = {
"http.response.header.custom_test_header_1": ("test-header-value-1",),
"http.response.header.custom_test_header_2": ("test-header-value-2",),
"http.response.header.my_custom_regex_header_1": ("my-custom-regex-value-1,my-custom-regex-value-2",),
"http.response.header.my_custom_regex_header_2": ("my-custom-regex-value-3,my-custom-regex-value-4",),
"http.response.header.my_secret_header": ("[REDACTED]",),
}
resp = self.client.get("/foobar")
self.assertEqual(200, resp.status_code)
span_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(span_list), 3)
server_span = [span for span in span_list if span.kind == trace.SpanKind.SERVER][0]
self.assertSpanHasAttributes(server_span, expected)
def test_http_custom_response_headers_not_in_span_attributes(self):
not_expected = {
"http.response.header.custom_test_header_3": ("test-header-value-3",),
}
resp = self.client.get("/foobar")
self.assertEqual(200, resp.status_code)
span_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(span_list), 3)
server_span = [span for span in span_list if span.kind == trace.SpanKind.SERVER][0]
for key, _ in not_expected.items():
self.assertNotIn(key, server_span.attributes)
class TestHTTPAppWithCustomHeadersParameters(TestBase):
"""Minimal tests here since the behavior of this logic is tested above and in the ASGI tests."""
def setUp(self):
super().setUp()
self.instrumentor = otel_fastapi.FastAPIInstrumentor()
self.kwargs = {
"http_capture_headers_server_request": ["a.*", "b.*"],
"http_capture_headers_server_response": ["c.*", "d.*"],
"http_capture_headers_sanitize_fields": [".*secret.*"],
}
self.app = None
def tearDown(self) -> None:
super().tearDown()
with self.disable_logging():
if self.app:
self.instrumentor.uninstrument_app(self.app)
else:
self.instrumentor.uninstrument()
@staticmethod
def _create_app():
app = fastapi.FastAPI()
@app.get("/foobar")
async def _():
headers = {
"carrot": "bar",
"date-secret": "yellow",
"egg": "ham",
}
content = {"message": "hello world"}
return JSONResponse(content=content, headers=headers)
return app
def test_http_custom_request_headers_in_span_attributes_app(self):
self.app = self._create_app()
self.instrumentor.instrument_app(self.app, **self.kwargs)
resp = TestClient(self.app).get(
"/foobar",
headers={
"apple": "red",
"banana-secret": "yellow",
"fig": "green",
},
)
self.assertEqual(200, resp.status_code)
span_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(span_list), 3)
server_span = [span for span in span_list if span.kind == trace.SpanKind.SERVER][0]
expected = {
# apple should be included because it starts with a
"http.request.header.apple": ("red",),
# same with banana because it starts with b,
# redacted because it contains "secret"
"http.request.header.banana_secret": ("[REDACTED]",),
}
self.assertSpanHasAttributes(server_span, expected)
self.assertNotIn("http.request.header.fig", server_span.attributes)
def test_http_custom_request_headers_in_span_attributes_instr(self):
"""As above, but use instrument(), not instrument_app()."""
self.instrumentor.instrument(**self.kwargs)
resp = TestClient(self._create_app()).get(
"/foobar",
headers={
"apple": "red",
"banana-secret": "yellow",
"fig": "green",
},
)
self.assertEqual(200, resp.status_code)
span_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(span_list), 3)
server_span = [span for span in span_list if span.kind == trace.SpanKind.SERVER][0]
expected = {
# apple should be included because it starts with a
"http.request.header.apple": ("red",),
# same with banana because it starts with b,
# redacted because it contains "secret"
"http.request.header.banana_secret": ("[REDACTED]",),
}
self.assertSpanHasAttributes(server_span, expected)
self.assertNotIn("http.request.header.fig", server_span.attributes)
def test_http_custom_response_headers_in_span_attributes_app(self):
self.app = self._create_app()
self.instrumentor.instrument_app(self.app, **self.kwargs)
resp = TestClient(self.app).get("/foobar")
self.assertEqual(200, resp.status_code)
span_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(span_list), 3)
server_span = [span for span in span_list if span.kind == trace.SpanKind.SERVER][0]
expected = {
"http.response.header.carrot": ("bar",),
"http.response.header.date_secret": ("[REDACTED]",),
}
self.assertSpanHasAttributes(server_span, expected)
self.assertNotIn("http.response.header.egg", server_span.attributes)
def test_http_custom_response_headers_in_span_attributes_inst(self):
"""As above, but use instrument(), not instrument_app()."""
self.instrumentor.instrument(**self.kwargs)
resp = TestClient(self._create_app()).get("/foobar")
self.assertEqual(200, resp.status_code)
span_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(span_list), 3)
server_span = [span for span in span_list if span.kind == trace.SpanKind.SERVER][0]
expected = {
"http.response.header.carrot": ("bar",),
"http.response.header.date_secret": ("[REDACTED]",),
}
self.assertSpanHasAttributes(server_span, expected)
self.assertNotIn("http.response.header.egg", server_span.attributes)
@patch.dict(
"os.environ",
{
OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SANITIZE_FIELDS: ".*my-secret.*",
OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_REQUEST: "Custom-Test-Header-1,Custom-Test-Header-2,Custom-Test-Header-3,Regex-Test-Header-.*,Regex-Invalid-Test-Header-.*,.*my-secret.*",
OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_RESPONSE: "Custom-Test-Header-1,Custom-Test-Header-2,Custom-Test-Header-3,my-custom-regex-header-.*,invalid-regex-header-.*,.*my-secret.*",
},
)
class TestWebSocketAppWithCustomHeaders(TestBase):
def setUp(self):
super().setUp()
self.app = self._create_app()
otel_fastapi.FastAPIInstrumentor().instrument_app(self.app)
self.client = TestClient(self.app)
def tearDown(self) -> None:
super().tearDown()
with self.disable_logging():
otel_fastapi.FastAPIInstrumentor().uninstrument_app(self.app)
@staticmethod
def _create_app():
app = fastapi.FastAPI()
@app.websocket("/foobar_web")
async def _(websocket: fastapi.WebSocket):
message = await websocket.receive()
if message.get("type") == "websocket.connect":
await websocket.send(
{
"type": "websocket.accept",
"headers": [
(b"custom-test-header-1", b"test-header-value-1"),
(b"custom-test-header-2", b"test-header-value-2"),
(b"Regex-Test-Header-1", b"Regex Test Value 1"),
(
b"regex-test-header-2",
b"RegexTestValue2,RegexTestValue3",
),
(b"My-Secret-Header", b"My Secret Value"),
],
}
)
await websocket.send_json({"message": "hello world"})
await websocket.close()
if message.get("type") == "websocket.disconnect":
pass
return app
def test_web_socket_custom_request_headers_in_span_attributes(self):
expected = {
"http.request.header.custom_test_header_1": ("test-header-value-1",),
"http.request.header.custom_test_header_2": ("test-header-value-2",),
}
with self.client.websocket_connect(
"/foobar_web",
headers={
"custom-test-header-1": "test-header-value-1",
"custom-test-header-2": "test-header-value-2",
},
) as websocket:
data = websocket.receive_json()
self.assertEqual(data, {"message": "hello world"})
span_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(span_list), 5)
server_span = [span for span in span_list if span.kind == trace.SpanKind.SERVER][0]
self.assertSpanHasAttributes(server_span, expected)
@patch.dict(
"os.environ",
{
OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SANITIZE_FIELDS: ".*my-secret.*",
OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_REQUEST: "Custom-Test-Header-1,Custom-Test-Header-2,Custom-Test-Header-3,Regex-Test-Header-.*,Regex-Invalid-Test-Header-.*,.*my-secret.*",
},
)
def test_web_socket_custom_request_headers_not_in_span_attributes(self):
not_expected = {
"http.request.header.custom_test_header_3": ("test-header-value-3",),
}
with self.client.websocket_connect(
"/foobar_web",
headers={
"custom-test-header-1": "test-header-value-1",
"custom-test-header-2": "test-header-value-2",
},
) as websocket:
data = websocket.receive_json()
self.assertEqual(data, {"message": "hello world"})
span_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(span_list), 5)
server_span = [span for span in span_list if span.kind == trace.SpanKind.SERVER][0]
for key, _ in not_expected.items():
self.assertNotIn(key, server_span.attributes)
def test_web_socket_custom_response_headers_in_span_attributes(self):
expected = {
"http.response.header.custom_test_header_1": ("test-header-value-1",),
"http.response.header.custom_test_header_2": ("test-header-value-2",),
}
with self.client.websocket_connect("/foobar_web") as websocket:
data = websocket.receive_json()
self.assertEqual(data, {"message": "hello world"})
span_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(span_list), 5)
server_span = [span for span in span_list if span.kind == trace.SpanKind.SERVER][0]
self.assertSpanHasAttributes(server_span, expected)
def test_web_socket_custom_response_headers_not_in_span_attributes(self):
not_expected = {
"http.response.header.custom_test_header_3": ("test-header-value-3",),
}
with self.client.websocket_connect("/foobar_web") as websocket:
data = websocket.receive_json()
self.assertEqual(data, {"message": "hello world"})
span_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(span_list), 5)
server_span = [span for span in span_list if span.kind == trace.SpanKind.SERVER][0]
for key, _ in not_expected.items():
self.assertNotIn(key, server_span.attributes)
@patch.dict(
"os.environ",
{
OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_REQUEST: "Custom-Test-Header-1,Custom-Test-Header-2,Custom-Test-Header-3",
},
)
class TestNonRecordingSpanWithCustomHeaders(TestBase):
def setUp(self):
super().setUp()
self.app = fastapi.FastAPI()
@self.app.get("/foobar")
async def _():
return {"message": "hello world"}
reset_trace_globals()
tracer_provider = trace.NoOpTracerProvider()
trace.set_tracer_provider(tracer_provider=tracer_provider)
self._instrumentor = otel_fastapi.FastAPIInstrumentor()
self._instrumentor.instrument_app(self.app)
self.client = TestClient(self.app)
def tearDown(self) -> None:
super().tearDown()
with self.disable_logging():
self._instrumentor.uninstrument_app(self.app)
def test_custom_header_not_present_in_non_recording_span(self):
resp = self.client.get(
"/foobar",
headers={
"custom-test-header-1": "test-header-value-1",
},
)
self.assertEqual(200, resp.status_code)
span_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(span_list), 0)
class TestTraceableExceptionHandling(TestBase):
"""Tests to ensure FastAPI exception handlers are only executed once and with a valid context"""
def setUp(self):
super().setUp()
self.app = fastapi.FastAPI()
otel_fastapi.FastAPIInstrumentor().instrument_app(self.app, exclude_spans=["receive", "send"])
self.client = TestClient(self.app)
self.tracer = self.tracer_provider.get_tracer(__name__)
self.executed = 0
self.request_trace_id = None
self.error_trace_id = None
def tearDown(self) -> None:
super().tearDown()
with self.disable_logging():
otel_fastapi.FastAPIInstrumentor().uninstrument_app(self.app)
def test_error_handler_context(self):
"""OTEL tracing contexts must be available during error handler
execution, and handlers must only be executed once"""
status_code = 501
@self.app.exception_handler(Exception)
async def _(*_):
self.error_trace_id = trace.get_current_span().get_span_context().trace_id
self.executed += 1
return PlainTextResponse("", status_code)
@self.app.get("/foobar")
async def _foobar():
self.request_trace_id = trace.get_current_span().get_span_context().trace_id
raise UnhandledException("Test Exception")
try:
self.client.get(
"/foobar",
)
except UnhandledException:
pass
self.assertIsNotNone(self.request_trace_id)
self.assertEqual(self.request_trace_id, self.error_trace_id)
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
span = spans[0]
self.assertEqual(span.name, "GET /foobar")
self.assertEqual(span.attributes.get(HTTP_STATUS_CODE), status_code)
self.assertEqual(span.status.status_code, StatusCode.ERROR)
self.assertEqual(len(span.events), 1)
event = span.events[0]
self.assertEqual(event.name, "exception")
assert event.attributes is not None
self.assertEqual(
event.attributes.get(EXCEPTION_TYPE),
f"{__name__}.UnhandledException",
)
self.assertEqual(self.executed, 1)
def test_exception_span_recording(self):
"""Exceptions are always recorded in the active span"""
@self.app.get("/foobar")
async def _():
raise UnhandledException("Test Exception")
try:
self.client.get(
"/foobar",
)
except UnhandledException:
pass
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
span = spans[0]
self.assertEqual(span.name, "GET /foobar")
self.assertEqual(span.attributes.get(HTTP_STATUS_CODE), 500)
self.assertEqual(span.status.status_code, StatusCode.ERROR)
self.assertEqual(len(span.events), 1)
event = span.events[0]
self.assertEqual(event.name, "exception")
assert event.attributes is not None
self.assertEqual(
event.attributes.get(EXCEPTION_TYPE),
f"{__name__}.UnhandledException",
)
def test_middleware_exceptions(self):
"""Exceptions from user middlewares are recorded in the active span"""
@self.app.get("/foobar")
async def _foobar():
return PlainTextResponse("Hello World")
@self.app.middleware("http")
async def _(*_):
raise UnhandledException("Test Exception")
try:
self.client.get(
"/foobar",
)
except UnhandledException:
pass
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
span = spans[0]
self.assertEqual(span.name, "GET /foobar")
self.assertEqual(span.attributes.get(HTTP_STATUS_CODE), 500)
self.assertEqual(span.status.status_code, StatusCode.ERROR)
self.assertEqual(len(span.events), 1)
event = span.events[0]
self.assertEqual(event.name, "exception")
assert event.attributes is not None
self.assertEqual(
event.attributes.get(EXCEPTION_TYPE),
f"{__name__}.UnhandledException",
)
class TestFastAPIFallback(TestBaseFastAPI):
@pytest.fixture(autouse=True)
def inject_fixtures(self, caplog):
self.caplog = caplog
@staticmethod
def _create_fastapi_app():
app = TestBaseFastAPI._create_fastapi_app()
def build_middleware_stack():
# Return something that is NOT a ServerErrorMiddleware so the
# instrumentation fallback path triggers, but still wrap the
# router with AsyncExitStackMiddleware so that newer FastAPI
# versions (which assert ``fastapi_middleware_astack`` exists in
# the request scope) can service requests normally.
return AsyncExitStackMiddleware(app.router)
app.build_middleware_stack = build_middleware_stack
return app
def setUp(self):
super().setUp()
self.client = TestClient(self._app)
def test_no_instrumentation(self):
self.client.get(
"/foobar",
)
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 0)
errors = [record for record in self.caplog.get_records("call") if record.levelno >= logging.ERROR]
self.assertEqual(len(errors), 1)
self.assertEqual(
errors[0].getMessage(),
"Skipping FastAPI instrumentation due to unexpected middleware stack: expected ServerErrorMiddleware, got ",
)
class TestFastAPIHostHeaderURL(TestBaseManualFastAPI):
"""Test suite for Host header URL functionality in FastAPI instrumentation."""
def test_host_header_url_construction(self):
"""Test that URLs use Host header value instead of server IP when available."""
# Test with a custom Host header - should use the domain name
resp = self._client.get("/foobar?param=value", headers={"host": "api.mycompany.com"})
self.assertEqual(200, resp.status_code)
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 3)
# Find the server span (the main span, not internal middleware spans)
server_span = None
for span in spans:
if span.kind == trace.SpanKind.SERVER and HTTP_URL in span.attributes:
server_span = span
break
self.assertIsNotNone(server_span, "Server span with HTTP_URL not found")
# Verify the URL uses the Host header domain instead of testserver
expected_url = "https://api.mycompany.com/foobar?param=value"
actual_url = server_span.attributes[HTTP_URL]
self.assertEqual(expected_url, actual_url)
# Also verify that the server name attribute is set correctly
self.assertEqual("api.mycompany.com", server_span.attributes.get("http.server_name"))
def test_host_header_with_port_url_construction(self):
"""Test Host header URL construction when host includes port."""
resp = self._client.get("/user/123", headers={"host": "staging.myapp.com:8443"})
self.assertEqual(200, resp.status_code)
spans = self.memory_exporter.get_finished_spans()
server_span = next(
(span for span in spans if span.kind == trace.SpanKind.SERVER and HTTP_URL in span.attributes),
None,
)
self.assertIsNotNone(server_span)
# Should use the host header value with non-standard port included
expected_url = "https://staging.myapp.com:8443/user/123"
actual_url = server_span.attributes[HTTP_URL]
self.assertEqual(expected_url, actual_url)
def test_no_host_header_fallback_behavior(self):
"""Test fallback to server name when no Host header is present."""
# Make request without custom Host header - should use testserver (default TestClient base)
resp = self._client.get("/foobar")
self.assertEqual(200, resp.status_code)
spans = self.memory_exporter.get_finished_spans()
server_span = next(
(span for span in spans if span.kind == trace.SpanKind.SERVER and HTTP_URL in span.attributes),
None,
)
self.assertIsNotNone(server_span)
# Should fallback to testserver (TestClient default, standard port stripped)
expected_url = "https://testserver/foobar"
actual_url = server_span.attributes[HTTP_URL]
self.assertEqual(expected_url, actual_url)
def test_production_scenario_host_header(self):
"""Test a realistic production scenario with Host header."""
# Simulate a production request with public domain in Host header
resp = self._client.get(
"/foobar?limit=10&offset=20",
headers={
"host": "prod-api.example.com",
"user-agent": "ProductionClient/1.0",
},
)
self.assertEqual(200, resp.status_code) # Valid route should return 200
spans = self.memory_exporter.get_finished_spans()
server_span = next(
(span for span in spans if span.kind == trace.SpanKind.SERVER and HTTP_URL in span.attributes),
None,
)
self.assertIsNotNone(server_span)
# URL should use the production domain from Host header (AS-IS, no default port)
expected_url = "https://prod-api.example.com/foobar?limit=10&offset=20"
actual_url = server_span.attributes[HTTP_URL]
self.assertEqual(expected_url, actual_url)
# Verify other attributes are still correct
self.assertEqual("GET", server_span.attributes[HTTP_METHOD])
self.assertEqual("/foobar", server_span.attributes[HTTP_TARGET])
self.assertEqual(
"prod-api.example.com",
server_span.attributes.get("http.server_name"),
)
def test_host_header_with_special_characters(self):
"""Test Host header handling with special characters and edge cases."""
test_cases = [
(
"api-v2.test-domain.com",
"https://api-v2.test-domain.com/foobar",
),
("localhost", "https://localhost/foobar"),
(
"192.168.1.100",
"https://192.168.1.100/foobar",
), # IP address as host
(
"test.domain.co.uk",
"https://test.domain.co.uk/foobar",
), # Multiple dots
]
for host_value, expected_url in test_cases:
with self.subTest(host=host_value):
# Clear previous spans
self.memory_exporter.clear()
resp = self._client.get("/foobar", headers={"host": host_value})
self.assertEqual(200, resp.status_code)
spans = self.memory_exporter.get_finished_spans()
server_span = next(
(span for span in spans if span.kind == trace.SpanKind.SERVER and HTTP_URL in span.attributes),
None,
)
self.assertIsNotNone(server_span)
actual_url = server_span.attributes[HTTP_URL]
self.assertEqual(expected_url, actual_url)
def test_host_header_maintains_span_attributes(self):
"""Test that using Host header doesn't break other span attributes."""
resp = self._client.get(
"/user/testuser?debug=true",
headers={
"host": "api.testapp.com",
"user-agent": "TestClient/1.0",
},
)
self.assertEqual(200, resp.status_code)
spans = self.memory_exporter.get_finished_spans()
server_span = next(
(span for span in spans if span.kind == trace.SpanKind.SERVER and HTTP_URL in span.attributes),
None,
)
self.assertIsNotNone(server_span)
# Verify URL uses Host header
self.assertEqual(
"https://api.testapp.com/user/testuser?debug=true",
server_span.attributes[HTTP_URL],
)
# Verify all other attributes are still present and correct
self.assertEqual("GET", server_span.attributes[HTTP_METHOD])
self.assertEqual("/user/testuser", server_span.attributes[HTTP_TARGET])
self.assertEqual("https", server_span.attributes[HTTP_SCHEME])
self.assertEqual("api.testapp.com", server_span.attributes.get("http.server_name"))
self.assertEqual(200, server_span.attributes[HTTP_STATUS_CODE])
# Check that route attribute is still set correctly
if HTTP_ROUTE in server_span.attributes:
self.assertEqual("/user/{username}", server_span.attributes[HTTP_ROUTE])
class TestFastAPIHostHeaderURLNewSemconv(TestFastAPIHostHeaderURL):
"""Test Host header URL functionality with new semantic conventions."""
def test_host_header_url_new_semconv(self):
"""Test Host header URL construction with new semantic conventions.
Note: With new semantic conventions, the URL is split into components
(url.scheme, server.address, url.path, etc.) rather than a single http.url.
Host header support may work differently with new semantic conventions.
"""
resp = self._client.get("/foobar?test=new_semconv", headers={"host": "newapi.example.com"})
self.assertEqual(200, resp.status_code)
spans = self.memory_exporter.get_finished_spans()
# With new semantic conventions, look for the main HTTP span with route information
server_span = next(
(span for span in spans if span.kind == trace.SpanKind.SERVER and "http.route" in span.attributes),
None,
)
self.assertIsNotNone(server_span)
# Verify we have the new semantic convention attributes
self.assertIn("url.scheme", server_span.attributes)
self.assertIn("server.address", server_span.attributes)
self.assertIn("url.path", server_span.attributes)
self.assertEqual("https", server_span.attributes.get("url.scheme"))
self.assertEqual("/foobar", server_span.attributes.get("url.path"))
# Current behavior: Host header may not affect server.address in new semantic conventions
# This test documents the current behavior rather than enforcing Host header usage
server_address = server_span.attributes.get("server.address", "")
self.assertIsNotNone(server_address, "testserver") # Should have some value
class TestFastAPIHostHeaderURLBothSemconv(TestFastAPIHostHeaderURL):
"""Test Host header URL functionality with both old and new semantic conventions."""
def test_host_header_url_both_semconv(self):
"""Test Host header URL construction with both semantic conventions enabled."""
resp = self._client.get("/foobar?test=both_semconv", headers={"host": "dual.example.com"})
self.assertEqual(200, resp.status_code)
spans = self.memory_exporter.get_finished_spans()
server_span = next(
(span for span in spans if span.kind == trace.SpanKind.SERVER and HTTP_URL in span.attributes),
None,
)
self.assertIsNotNone(server_span)
# Should use Host header for URL construction regardless of semantic convention mode
expected_url = "https://dual.example.com/foobar?test=both_semconv"
actual_url = server_span.attributes[HTTP_URL]
self.assertEqual(expected_url, actual_url)
def test_fastapi_unhandled_exception(self):
"""Override inherited test - use the both_semconv version instead."""
self.skipTest("Use test_fastapi_unhandled_exception_both_semconv instead")
def test_fastapi_unhandled_exception_both_semconv(self):
"""If the application has an unhandled error the instrumentation should capture that a 500 response is returned."""
try:
resp = self._client.get("/error")
assert resp.status_code == 500, (
resp.content
) # pragma: no cover, for debugging this test if an exception is _not_ raised
except UnhandledException:
pass
else:
self.fail("Expected UnhandledException")
spans = self.memory_exporter.get_finished_spans()
# With both semantic conventions enabled, we expect 3 spans:
# 1. Server span (main HTTP span)
# 2. ASGI receive span
# 3. ASGI send span (for error response)
self.assertEqual(len(spans), 3)
# Find the server span (it should have HTTP attributes)
server_spans = [
span
for span in spans
if span.kind == trace.SpanKind.SERVER
and hasattr(span, "attributes")
and span.attributes
and HTTP_URL in span.attributes
]
self.assertEqual(
len(server_spans),
1,
"Expected exactly one server span with HTTP_URL",
)
server_span = server_spans[0]
# Ensure server_span is not None
assert server_span is not None
self.assertEqual(server_span.name, "GET /error")
test_fastapi_instrumentation_custom_headers.py 0000664 0000000 0000000 00000032272 15270700723 0045333 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-fastapi/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
from collections.abc import Mapping
from unittest.mock import patch
import fastapi
from starlette.responses import JSONResponse
from starlette.testclient import TestClient
import opentelemetry.instrumentation.fastapi as otel_fastapi
from opentelemetry import trace
from opentelemetry.test.globals_test import reset_trace_globals
from opentelemetry.test.test_base import TestBase
from opentelemetry.util.http import (
OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SANITIZE_FIELDS,
OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_REQUEST,
OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_RESPONSE,
)
class MultiMapping(Mapping):
def __init__(self, *items: tuple[str, str]):
self._items = items
def __len__(self):
return len(self._items)
def __getitem__(self, __key):
raise NotImplementedError("use .items() instead")
def __iter__(self):
raise NotImplementedError("use .items() instead")
def items(self):
return self._items
@patch.dict(
"os.environ",
{
OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SANITIZE_FIELDS: ".*my-secret.*",
OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_REQUEST: "Custom-Test-Header-1,Custom-Test-Header-2,Custom-Test-Header-3,Regex-Test-Header-.*,Regex-Invalid-Test-Header-.*,.*my-secret.*",
OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_RESPONSE: "Custom-Test-Header-1,Custom-Test-Header-2,Custom-Test-Header-3,my-custom-regex-header-.*,invalid-regex-header-.*,.*my-secret.*",
},
)
class TestHTTPAppWithCustomHeaders(TestBase):
def setUp(self):
super().setUp()
self.app = self._create_app()
otel_fastapi.FastAPIInstrumentor().instrument_app(self.app)
self.client = TestClient(self.app)
def tearDown(self) -> None:
super().tearDown()
with self.disable_logging():
otel_fastapi.FastAPIInstrumentor().uninstrument_app(self.app)
@staticmethod
def _create_app():
app = fastapi.FastAPI()
@app.get("/foobar")
async def _():
headers = MultiMapping(
("custom-test-header-1", "test-header-value-1"),
("custom-test-header-2", "test-header-value-2"),
("my-custom-regex-header-1", "my-custom-regex-value-1"),
("my-custom-regex-header-1", "my-custom-regex-value-2"),
("My-Custom-Regex-Header-2", "my-custom-regex-value-3"),
("My-Custom-Regex-Header-2", "my-custom-regex-value-4"),
("My-Secret-Header", "My Secret Value"),
)
content = {"message": "hello world"}
return JSONResponse(content=content, headers=headers)
return app
def test_http_custom_request_headers_in_span_attributes(self):
expected = {
"http.request.header.custom_test_header_1": ("test-header-value-1",),
"http.request.header.custom_test_header_2": ("test-header-value-2",),
"http.request.header.regex_test_header_1": ("Regex Test Value 1",),
"http.request.header.regex_test_header_2": ("RegexTestValue2,RegexTestValue3",),
"http.request.header.my_secret_header": ("[REDACTED]",),
}
resp = self.client.get(
"/foobar",
headers={
"custom-test-header-1": "test-header-value-1",
"custom-test-header-2": "test-header-value-2",
"Regex-Test-Header-1": "Regex Test Value 1",
"regex-test-header-2": "RegexTestValue2,RegexTestValue3",
"My-Secret-Header": "My Secret Value",
},
)
self.assertEqual(200, resp.status_code)
span_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(span_list), 3)
server_span = [span for span in span_list if span.kind == trace.SpanKind.SERVER][0]
self.assertSpanHasAttributes(server_span, expected)
def test_http_custom_request_headers_not_in_span_attributes(self):
not_expected = {
"http.request.header.custom_test_header_3": ("test-header-value-3",),
}
resp = self.client.get(
"/foobar",
headers={
"custom-test-header-1": "test-header-value-1",
"custom-test-header-2": "test-header-value-2",
"Regex-Test-Header-1": "Regex Test Value 1",
"regex-test-header-2": "RegexTestValue2,RegexTestValue3",
"My-Secret-Header": "My Secret Value",
},
)
self.assertEqual(200, resp.status_code)
span_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(span_list), 3)
server_span = [span for span in span_list if span.kind == trace.SpanKind.SERVER][0]
for key, _ in not_expected.items():
self.assertNotIn(key, server_span.attributes)
def test_http_custom_response_headers_in_span_attributes(self):
expected = {
"http.response.header.custom_test_header_1": ("test-header-value-1",),
"http.response.header.custom_test_header_2": ("test-header-value-2",),
"http.response.header.my_custom_regex_header_1": (
"my-custom-regex-value-1",
"my-custom-regex-value-2",
),
"http.response.header.my_custom_regex_header_2": (
"my-custom-regex-value-3",
"my-custom-regex-value-4",
),
"http.response.header.my_secret_header": ("[REDACTED]",),
}
resp = self.client.get("/foobar")
self.assertEqual(200, resp.status_code)
span_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(span_list), 3)
server_span = [span for span in span_list if span.kind == trace.SpanKind.SERVER][0]
self.assertSpanHasAttributes(server_span, expected)
def test_http_custom_response_headers_not_in_span_attributes(self):
not_expected = {
"http.response.header.custom_test_header_3": ("test-header-value-3",),
}
resp = self.client.get("/foobar")
self.assertEqual(200, resp.status_code)
span_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(span_list), 3)
server_span = [span for span in span_list if span.kind == trace.SpanKind.SERVER][0]
for key, _ in not_expected.items():
self.assertNotIn(key, server_span.attributes)
@patch.dict(
"os.environ",
{
OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SANITIZE_FIELDS: ".*my-secret.*",
OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_REQUEST: "Custom-Test-Header-1,Custom-Test-Header-2,Custom-Test-Header-3,Regex-Test-Header-.*,Regex-Invalid-Test-Header-.*,.*my-secret.*",
OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_RESPONSE: "Custom-Test-Header-1,Custom-Test-Header-2,Custom-Test-Header-3,my-custom-regex-header-.*,invalid-regex-header-.*,.*my-secret.*",
},
)
class TestWebSocketAppWithCustomHeaders(TestBase):
def setUp(self):
super().setUp()
self.app = self._create_app()
otel_fastapi.FastAPIInstrumentor().instrument_app(self.app)
self.client = TestClient(self.app)
def tearDown(self) -> None:
super().tearDown()
with self.disable_logging():
otel_fastapi.FastAPIInstrumentor().uninstrument_app(self.app)
@staticmethod
def _create_app():
app = fastapi.FastAPI()
@app.websocket("/foobar_web")
async def _(websocket: fastapi.WebSocket):
message = await websocket.receive()
if message.get("type") == "websocket.connect":
await websocket.send(
{
"type": "websocket.accept",
"headers": [
(b"custom-test-header-1", b"test-header-value-1"),
(b"custom-test-header-2", b"test-header-value-2"),
(b"Regex-Test-Header-1", b"Regex Test Value 1"),
(
b"regex-test-header-2",
b"RegexTestValue2,RegexTestValue3",
),
(b"My-Secret-Header", b"My Secret Value"),
],
}
)
await websocket.send_json({"message": "hello world"})
await websocket.close()
if message.get("type") == "websocket.disconnect":
pass
return app
def test_web_socket_custom_request_headers_in_span_attributes(self):
expected = {
"http.request.header.custom_test_header_1": ("test-header-value-1",),
"http.request.header.custom_test_header_2": ("test-header-value-2",),
}
with self.client.websocket_connect(
"/foobar_web",
headers={
"custom-test-header-1": "test-header-value-1",
"custom-test-header-2": "test-header-value-2",
},
) as websocket:
data = websocket.receive_json()
self.assertEqual(data, {"message": "hello world"})
span_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(span_list), 5)
server_span = [span for span in span_list if span.kind == trace.SpanKind.SERVER][0]
self.assertSpanHasAttributes(server_span, expected)
@patch.dict(
"os.environ",
{
OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SANITIZE_FIELDS: ".*my-secret.*",
OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_REQUEST: "Custom-Test-Header-1,Custom-Test-Header-2,Custom-Test-Header-3,Regex-Test-Header-.*,Regex-Invalid-Test-Header-.*,.*my-secret.*",
},
)
def test_web_socket_custom_request_headers_not_in_span_attributes(self):
not_expected = {
"http.request.header.custom_test_header_3": ("test-header-value-3",),
}
with self.client.websocket_connect(
"/foobar_web",
headers={
"custom-test-header-1": "test-header-value-1",
"custom-test-header-2": "test-header-value-2",
},
) as websocket:
data = websocket.receive_json()
self.assertEqual(data, {"message": "hello world"})
span_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(span_list), 5)
server_span = [span for span in span_list if span.kind == trace.SpanKind.SERVER][0]
for key, _ in not_expected.items():
self.assertNotIn(key, server_span.attributes)
def test_web_socket_custom_response_headers_in_span_attributes(self):
expected = {
"http.response.header.custom_test_header_1": ("test-header-value-1",),
"http.response.header.custom_test_header_2": ("test-header-value-2",),
}
with self.client.websocket_connect("/foobar_web") as websocket:
data = websocket.receive_json()
self.assertEqual(data, {"message": "hello world"})
span_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(span_list), 5)
server_span = [span for span in span_list if span.kind == trace.SpanKind.SERVER][0]
self.assertSpanHasAttributes(server_span, expected)
def test_web_socket_custom_response_headers_not_in_span_attributes(self):
not_expected = {
"http.response.header.custom_test_header_3": ("test-header-value-3",),
}
with self.client.websocket_connect("/foobar_web") as websocket:
data = websocket.receive_json()
self.assertEqual(data, {"message": "hello world"})
span_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(span_list), 5)
server_span = [span for span in span_list if span.kind == trace.SpanKind.SERVER][0]
for key, _ in not_expected.items():
self.assertNotIn(key, server_span.attributes)
@patch.dict(
"os.environ",
{
OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_REQUEST: "Custom-Test-Header-1,Custom-Test-Header-2,Custom-Test-Header-3",
},
)
class TestNonRecordingSpanWithCustomHeaders(TestBase):
def setUp(self):
super().setUp()
self.app = fastapi.FastAPI()
@self.app.get("/foobar")
async def _():
return {"message": "hello world"}
reset_trace_globals()
tracer_provider = trace.NoOpTracerProvider()
trace.set_tracer_provider(tracer_provider=tracer_provider)
self._instrumentor = otel_fastapi.FastAPIInstrumentor()
self._instrumentor.instrument_app(self.app)
self.client = TestClient(self.app)
def tearDown(self) -> None:
super().tearDown()
with self.disable_logging():
self._instrumentor.uninstrument_app(self.app)
def test_custom_header_not_present_in_non_recording_span(self):
resp = self.client.get(
"/foobar",
headers={
"custom-test-header-1": "test-header-value-1",
},
)
self.assertEqual(200, resp.status_code)
span_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(span_list), 0)
test_fastapi_instrumentation_wrapped.py 0000664 0000000 0000000 00000003542 15270700723 0043766 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-fastapi/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
import fastapi
from starlette.testclient import TestClient
import opentelemetry.instrumentation.fastapi as otel_fastapi
from opentelemetry import trace
from opentelemetry.test.test_base import TestBase
class TestWrappedApplication(TestBase):
def setUp(self):
super().setUp()
self.app = fastapi.FastAPI()
@self.app.get("/foobar")
async def _():
return {"message": "hello world"}
otel_fastapi.FastAPIInstrumentor().instrument_app(self.app)
self.client = TestClient(self.app)
self.tracer = self.tracer_provider.get_tracer(__name__)
def tearDown(self) -> None:
super().tearDown()
with self.disable_logging():
otel_fastapi.FastAPIInstrumentor().uninstrument_app(self.app)
def test_mark_span_internal_in_presence_of_span_from_other_framework(self):
with self.tracer.start_as_current_span("test", kind=trace.SpanKind.SERVER) as parent_span:
resp = self.client.get("/foobar")
self.assertEqual(200, resp.status_code)
span_list = self.memory_exporter.get_finished_spans()
for span in span_list:
print(str(span.__class__) + ": " + str(span.__dict__))
# there should be 4 spans - single SERVER "test" and three INTERNAL "FastAPI"
self.assertEqual(trace.SpanKind.INTERNAL, span_list[0].kind)
self.assertEqual(trace.SpanKind.INTERNAL, span_list[1].kind)
# main INTERNAL span - child of test
self.assertEqual(trace.SpanKind.INTERNAL, span_list[2].kind)
self.assertEqual(parent_span.context.span_id, span_list[2].parent.span_id)
# SERVER "test"
self.assertEqual(trace.SpanKind.SERVER, span_list[3].kind)
self.assertEqual(parent_span.context.span_id, span_list[3].context.span_id)
opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-flask/ 0000775 0000000 0000000 00000000000 15270700723 0032243 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-flask/LICENSE 0000664 0000000 0000000 00000026135 15270700723 0033257 0 ustar 00root root 0000000 0000000 Apache License
Version 2.0, January 2004
http://www.apache.org/licenses/
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opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-flask/README.rst 0000664 0000000 0000000 00000001346 15270700723 0033736 0 ustar 00root root 0000000 0000000 OpenTelemetry Flask Tracing
===========================
|pypi|
.. |pypi| image:: https://badge.fury.io/py/opentelemetry-instrumentation-flask.svg
:target: https://pypi.org/project/opentelemetry-instrumentation-flask/
This library builds on the OpenTelemetry WSGI middleware to track web requests
in Flask applications.
Installation
------------
::
pip install opentelemetry-instrumentation-flask
References
----------
* `OpenTelemetry Flask Instrumentation `_
* `OpenTelemetry Project `_
* `OpenTelemetry Python Examples `_
pyproject.toml 0000664 0000000 0000000 00000003275 15270700723 0035107 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-flask [build-system]
requires = ["hatchling"]
build-backend = "hatchling.build"
[project]
name = "opentelemetry-instrumentation-flask"
dynamic = ["version"]
description = "Flask instrumentation for OpenTelemetry"
readme = "README.rst"
license = "Apache-2.0"
requires-python = ">=3.10"
authors = [
{ name = "OpenTelemetry Authors", email = "cncf-opentelemetry-contributors@lists.cncf.io" },
]
classifiers = [
"Development Status :: 4 - Beta",
"Intended Audience :: Developers",
"License :: OSI Approved :: Apache Software License",
"Programming Language :: Python",
"Programming Language :: Python :: 3",
"Programming Language :: Python :: 3.10",
"Programming Language :: Python :: 3.11",
"Programming Language :: Python :: 3.12",
"Programming Language :: Python :: 3.13",
"Programming Language :: Python :: 3.14",
]
dependencies = [
"opentelemetry-api ~= 1.12",
"opentelemetry-instrumentation == 0.66b2",
"opentelemetry-instrumentation-wsgi == 0.66b2",
"opentelemetry-semantic-conventions == 0.66b2",
"opentelemetry-util-http == 0.66b2",
"packaging >= 21.0",
]
[project.optional-dependencies]
instruments = [
"flask >= 1.0",
]
[project.entry-points.opentelemetry_instrumentor]
flask = "opentelemetry.instrumentation.flask:FlaskInstrumentor"
[project.urls]
Homepage = "https://github.com/open-telemetry/opentelemetry-python-contrib/tree/main/instrumentation/opentelemetry-instrumentation-flask"
Repository = "https://github.com/open-telemetry/opentelemetry-python-contrib"
[tool.hatch.version]
path = "src/opentelemetry/instrumentation/flask/version.py"
[tool.hatch.build.targets.sdist]
include = [
"/src",
"/tests",
]
[tool.hatch.build.targets.wheel]
packages = ["src/opentelemetry"]
opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-flask/src/ 0000775 0000000 0000000 00000000000 15270700723 0033032 5 ustar 00root root 0000000 0000000 opentelemetry/ 0000775 0000000 0000000 00000000000 15270700723 0035647 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-flask/src instrumentation/ 0000775 0000000 0000000 00000000000 15270700723 0041112 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-flask/src/opentelemetry flask/ 0000775 0000000 0000000 00000000000 15270700723 0042212 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-flask/src/opentelemetry/instrumentation __init__.py 0000664 0000000 0000000 00000102122 15270700723 0044321 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-flask/src/opentelemetry/instrumentation/flask # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
# Note: This package is not named "flask" because of
# https://github.com/PyCQA/pylint/issues/2648
"""
This library builds on the OpenTelemetry WSGI middleware to track web requests
in Flask applications. In addition to opentelemetry-util-http, it
supports Flask-specific features such as:
* The Flask url rule pattern is used as the Span name.
* The ``http.route`` Span attribute is set so that one can see which URL rule
matched a request.
Usage
-----
.. code-block:: python
from flask import Flask
from opentelemetry.instrumentation.flask import FlaskInstrumentor
app = Flask(__name__)
FlaskInstrumentor().instrument_app(app)
@app.route("/")
def hello():
return "Hello!"
if __name__ == "__main__":
app.run(debug=True)
Configuration
-------------
Exclude lists
*************
To exclude certain URLs from tracking, set the environment variable ``OTEL_PYTHON_FLASK_EXCLUDED_URLS``
(or ``OTEL_PYTHON_EXCLUDED_URLS`` to cover all instrumentations) to a string of comma delimited regexes that match the
URLs.
For example,
::
export OTEL_PYTHON_FLASK_EXCLUDED_URLS="client/.*/info,healthcheck"
will exclude requests such as ``https://site/client/123/info`` and ``https://site/xyz/healthcheck``.
You can also pass comma delimited regexes directly to the ``instrument_app`` method:
.. code-block:: python
FlaskInstrumentor().instrument_app(app, excluded_urls="client/.*/info,healthcheck")
Request/Response hooks
**********************
This instrumentation supports request and response hooks. These are functions that get called
right after a span is created for a request and right before the span is finished for the response.
- The client request hook is called with the internal span and an instance of WSGIEnvironment (flask.request.environ)
when the method ``receive`` is called.
- The client response hook is called with the internal span, the status of the response and a list of key-value (tuples)
representing the response headers returned from the response when the method ``send`` is called.
For example,
.. code-block:: python
from opentelemetry.trace import Span
from wsgiref.types import WSGIEnvironment
from typing import List
from opentelemetry.instrumentation.flask import FlaskInstrumentor
def request_hook(span: Span, environ: WSGIEnvironment):
if span and span.is_recording():
span.set_attribute("custom_user_attribute_from_request_hook", "some-value")
def response_hook(span: Span, status: str, response_headers: List):
if span and span.is_recording():
span.set_attribute("custom_user_attribute_from_response_hook", "some-value")
FlaskInstrumentor().instrument(request_hook=request_hook, response_hook=response_hook)
Flask Request object reference: https://flask.palletsprojects.com/en/2.1.x/api/#flask.Request
Capture HTTP request and response headers
*****************************************
You can configure the agent to capture specified HTTP headers as span attributes, according to the
`semantic conventions `_.
Request headers
***************
To capture HTTP request headers as span attributes, set the environment variable
``OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_REQUEST`` to a comma delimited list of HTTP header names.
For example,
::
export OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_REQUEST="content-type,custom_request_header"
will extract ``content-type`` and ``custom_request_header`` from the request headers and add them as span attributes.
Request header names in Flask are case-insensitive and ``-`` characters are replaced by ``_``. So, giving the header
name as ``CUStom_Header`` in the environment variable will capture the header named ``custom-header``.
Regular expressions may also be used to match multiple headers that correspond to the given pattern. For example:
::
export OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_REQUEST="Accept.*,X-.*"
Would match all request headers that start with ``Accept`` and ``X-``.
To capture all request headers, set ``OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_REQUEST`` to ``".*"``.
::
export OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_REQUEST=".*"
The name of the added span attribute will follow the format ``http.request.header.`` where ````
is the normalized HTTP header name (lowercase, with ``-`` replaced by ``_``). The value of the attribute will be a
single item list containing all the header values.
For example:
``http.request.header.custom_request_header = [","]``
Response headers
****************
To capture HTTP response headers as span attributes, set the environment variable
``OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_RESPONSE`` to a comma delimited list of HTTP header names.
For example,
::
export OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_RESPONSE="content-type,custom_response_header"
will extract ``content-type`` and ``custom_response_header`` from the response headers and add them as span attributes.
Response header names in Flask are case-insensitive. So, giving the header name as ``CUStom-Header`` in the environment
variable will capture the header named ``custom-header``.
Regular expressions may also be used to match multiple headers that correspond to the given pattern. For example:
::
export OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_RESPONSE="Content.*,X-.*"
Would match all response headers that start with ``Content`` and ``X-``.
To capture all response headers, set ``OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_RESPONSE`` to ``".*"``.
::
export OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_RESPONSE=".*"
The name of the added span attribute will follow the format ``http.response.header.`` where ````
is the normalized HTTP header name (lowercase, with ``-`` replaced by ``_``). The value of the attribute will be a
single item list containing all the header values.
For example:
``http.response.header.custom_response_header = [","]``
Sanitizing headers
******************
In order to prevent storing sensitive data such as personally identifiable information (PII), session keys, passwords,
etc, set the environment variable ``OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SANITIZE_FIELDS``
to a comma delimited list of HTTP header names to be sanitized. Regexes may be used, and all header names will be
matched in a case-insensitive manner.
For example,
::
export OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SANITIZE_FIELDS=".*session.*,set-cookie"
will replace the value of headers such as ``session-id`` and ``set-cookie`` with ``[REDACTED]`` in the span.
Note:
The environment variable names used to capture HTTP headers are still experimental, and thus are subject to change.
SQLCommenter
************
You can optionally enable sqlcommenter which enriches the query with contextual
information. Queries made after setting up trace integration with sqlcommenter
enabled will have configurable key-value pairs appended to them, e.g.
``"select * from auth_users; /*framework=flask%%3A2.9.3*/"``. This
supports context propagation between database client and server when database log
records are enabled. For more information, see:
* `Semantic Conventions - Database Spans `_
* `sqlcommenter `_
.. code:: python
from opentelemetry.instrumentation.flask import FlaskInstrumentor
FlaskInstrumentor().instrument(enable_commenter=True)
Note:
FlaskInstrumentor sqlcommenter requires that sqlcommenter is also
enabled for an active instrumentation of a database driver or object-relational
mapper (ORM) in the same database client stack. The latter, such as
Psycopg2Instrumentor of SQLAlchemyInstrumentor, will create a base sqlcomment
that is enhanced by FlaskInstrumentor with additional values from context
before appending to the query statement.
SQLCommenter with commenter_options
***********************************
The key-value pairs appended to the query can be configured using
``commenter_options``. When sqlcommenter is enabled, all available KVs/tags
are calculated by default. ``commenter_options`` supports *opting out*
of specific KVs.
.. code:: python
from opentelemetry.instrumentation.flask import FlaskInstrumentor
# Opts into sqlcomment for Flask trace integration.
# Opts out of tags for controller.
FlaskInstrumentor().instrument(
enable_commenter=True,
commenter_options={
"controller": False,
}
)
Available commenter_options
###########################
The following sqlcomment key-values can be opted out of through ``commenter_options``:
+-------------------+----------------------------------------------------+----------------------------------------+
| Commenter Option | Description | Example |
+===================+====================================================+========================================+
| ``framework`` | Flask framework name with version (URL encoded). | ``framework='flask%%%%3A2.9.3'`` |
+-------------------+----------------------------------------------------+----------------------------------------+
| ``route`` | Flask route URI pattern. | ``route='/home'`` |
+-------------------+----------------------------------------------------+----------------------------------------+
| ``controller`` | Flask controller/endpoint name. | ``controller='home_view'`` |
+-------------------+----------------------------------------------------+----------------------------------------+
API
---
"""
import weakref
from collections.abc import Collection
from logging import getLogger
from time import time_ns
from timeit import default_timer
import flask
from packaging import version as package_version
import opentelemetry.instrumentation.wsgi as otel_wsgi
from opentelemetry import context, trace
from opentelemetry.instrumentation._semconv import (
HTTP_DURATION_HISTOGRAM_BUCKETS_NEW,
_get_schema_url,
_OpenTelemetrySemanticConventionStability,
_OpenTelemetryStabilitySignalType,
_report_new,
_report_old,
_StabilityMode,
)
from opentelemetry.instrumentation.flask.package import _instruments
from opentelemetry.instrumentation.flask.version import __version__
from opentelemetry.instrumentation.instrumentor import BaseInstrumentor
from opentelemetry.instrumentation.propagators import (
get_global_response_propagator,
)
from opentelemetry.instrumentation.utils import _start_internal_or_server_span
from opentelemetry.metrics import get_meter
from opentelemetry.semconv._incubating.attributes.http_attributes import (
HTTP_ROUTE,
HTTP_TARGET,
)
from opentelemetry.semconv._incubating.metrics.http_metrics import (
create_http_server_active_requests,
)
from opentelemetry.semconv.metrics import MetricInstruments
from opentelemetry.semconv.metrics.http_metrics import (
HTTP_SERVER_REQUEST_DURATION,
)
from opentelemetry.util._importlib_metadata import version
from opentelemetry.util.http import (
get_excluded_urls,
parse_excluded_urls,
sanitize_method,
)
_logger = getLogger(__name__)
_ENVIRON_STARTTIME_KEY = "opentelemetry-flask.starttime_key"
_ENVIRON_SPAN_KEY = "opentelemetry-flask.span_key"
_ENVIRON_ACTIVATION_KEY = "opentelemetry-flask.activation_key"
_ENVIRON_REQCTX_REF_KEY = "opentelemetry-flask.reqctx_ref_key"
_ENVIRON_TOKEN = "opentelemetry-flask.token"
_excluded_urls_from_env = get_excluded_urls("FLASK")
flask_version = version("flask")
# Global constant for Flask 3.1+ streaming context cleanup
_IS_FLASK_31_PLUS = package_version.parse(flask_version) >= package_version.parse("3.1.0")
if package_version.parse(flask_version) >= package_version.parse("2.2.0"):
def _request_ctx_ref() -> weakref.ReferenceType:
return weakref.ref(flask.globals.request_ctx._get_current_object())
else:
def _request_ctx_ref() -> weakref.ReferenceType:
return weakref.ref(flask._request_ctx_stack.top)
def get_default_span_name():
method = sanitize_method(flask.request.environ.get("REQUEST_METHOD", "").strip())
if method == "_OTHER":
method = "HTTP"
try:
span_name = f"{method} {flask.request.url_rule.rule}"
except AttributeError:
span_name = otel_wsgi.get_default_span_name(flask.request.environ)
return span_name
def _rewrapped_app(
wsgi_app,
active_requests_counter,
duration_histogram_old=None,
response_hook=None,
excluded_urls=None,
sem_conv_opt_in_mode=_StabilityMode.DEFAULT,
duration_histogram_new=None,
):
# pylint: disable=too-many-statements
def _wrapped_app(wrapped_app_environ, start_response):
# We want to measure the time for route matching, etc.
# In theory, we could start the span here and use
# update_name later but that API is "highly discouraged" so
# we better avoid it.
wrapped_app_environ[_ENVIRON_STARTTIME_KEY] = time_ns()
start = default_timer()
attributes = otel_wsgi.collect_request_attributes(wrapped_app_environ, sem_conv_opt_in_mode)
active_requests_count_attrs = otel_wsgi._parse_active_request_count_attrs(
attributes,
sem_conv_opt_in_mode,
)
active_requests_counter.add(1, active_requests_count_attrs)
request_route = None
should_trace = True
def _start_response(status, response_headers, *args, **kwargs):
nonlocal should_trace
should_trace = _should_trace(excluded_urls)
if should_trace:
nonlocal request_route
request_route = flask.request.url_rule
span = flask.request.environ.get(_ENVIRON_SPAN_KEY)
propagator = get_global_response_propagator()
if propagator:
propagator.inject(
response_headers,
setter=otel_wsgi.default_response_propagation_setter,
)
if span:
otel_wsgi.add_response_attributes(
span,
status,
response_headers,
attributes,
sem_conv_opt_in_mode,
)
if span.is_recording() and span.kind == trace.SpanKind.SERVER:
custom_attributes = otel_wsgi.collect_custom_response_headers_attributes(response_headers)
if len(custom_attributes) > 0:
span.set_attributes(custom_attributes)
else:
_logger.warning(
"Flask environ's OpenTelemetry span missing at _start_response(%s)",
status,
)
if response_hook is not None:
response_hook(span, status, response_headers)
return start_response(status, response_headers, *args, **kwargs)
try:
result = wsgi_app(wrapped_app_environ, _start_response)
# Note: Streaming response context cleanup is now handled in the Flask teardown function
# (_wrapped_teardown_request) to ensure proper cleanup following Logfire's recommendations
# for OpenTelemetry generator context management
if should_trace:
duration_s = default_timer() - start
# Get the span from wrapped_app_environ and re-create context manually
# to pass to histogram for exemplars generation
span = wrapped_app_environ.get(_ENVIRON_SPAN_KEY)
metrics_context = trace.set_span_in_context(span)
if duration_histogram_old:
duration_attrs_old = otel_wsgi._parse_duration_attrs(attributes, _StabilityMode.DEFAULT)
if request_route:
# http.target to be included in old semantic conventions
duration_attrs_old[HTTP_TARGET] = str(request_route)
duration_histogram_old.record(
max(round(duration_s * 1000), 0),
duration_attrs_old,
context=metrics_context,
)
if duration_histogram_new:
duration_attrs_new = otel_wsgi._parse_duration_attrs(attributes, _StabilityMode.HTTP)
if request_route:
duration_attrs_new[HTTP_ROUTE] = str(request_route)
duration_histogram_new.record(
max(duration_s, 0),
duration_attrs_new,
context=metrics_context,
)
return result
finally:
active_requests_counter.add(-1, active_requests_count_attrs)
def _should_trace(excluded_urls) -> bool:
return bool(flask.request and (excluded_urls is None or not excluded_urls.url_disabled(flask.request.url)))
return _wrapped_app
def _wrapped_before_request(
request_hook=None,
tracer=None,
excluded_urls=None,
enable_commenter=True,
commenter_options=None,
sem_conv_opt_in_mode=_StabilityMode.DEFAULT,
):
def _before_request():
if excluded_urls and excluded_urls.url_disabled(flask.request.url):
return
flask_request_environ = flask.request.environ
span_name = get_default_span_name()
attributes = otel_wsgi.collect_request_attributes(
flask_request_environ,
sem_conv_opt_in_mode=sem_conv_opt_in_mode,
)
if flask.request.url_rule:
# For 404 that result from no route found, etc, we
# don't have a url_rule.
attributes[HTTP_ROUTE] = flask.request.url_rule.rule
span, token = _start_internal_or_server_span(
tracer=tracer,
span_name=span_name,
start_time=flask_request_environ.get(_ENVIRON_STARTTIME_KEY),
context_carrier=flask_request_environ,
context_getter=otel_wsgi.wsgi_getter,
attributes=attributes,
)
if request_hook:
request_hook(span, flask_request_environ)
if span.is_recording():
for key, value in attributes.items():
span.set_attribute(key, value)
if span.is_recording() and span.kind == trace.SpanKind.SERVER:
custom_attributes = otel_wsgi.collect_custom_request_headers_attributes(flask_request_environ)
if len(custom_attributes) > 0:
span.set_attributes(custom_attributes)
activation = trace.use_span(span, end_on_exit=True)
activation.__enter__() # pylint: disable=unnecessary-dunder-call
flask_request_environ[_ENVIRON_ACTIVATION_KEY] = activation
flask_request_environ[_ENVIRON_REQCTX_REF_KEY] = _request_ctx_ref()
flask_request_environ[_ENVIRON_SPAN_KEY] = span
flask_request_environ[_ENVIRON_TOKEN] = token
if enable_commenter:
current_context = context.get_current()
flask_info = {}
# https://flask.palletsprojects.com/en/1.1.x/api/#flask.has_request_context
if flask and flask.request:
if commenter_options.get("framework", True):
flask_info["framework"] = f"flask:{flask_version}"
if commenter_options.get("controller", True) and flask.request.endpoint:
flask_info["controller"] = flask.request.endpoint
if commenter_options.get("route", True) and flask.request.url_rule and flask.request.url_rule.rule:
flask_info["route"] = flask.request.url_rule.rule
sqlcommenter_context = context.set_value("SQLCOMMENTER_ORM_TAGS_AND_VALUES", flask_info, current_context)
context.attach(sqlcommenter_context)
return _before_request
def _wrapped_teardown_request(
excluded_urls=None,
):
def _teardown_request(exc):
# pylint: disable=unnecessary-dunder-call
if excluded_urls and excluded_urls.url_disabled(flask.request.url):
return
activation = flask.request.environ.get(_ENVIRON_ACTIVATION_KEY)
token = flask.request.environ.get(_ENVIRON_TOKEN)
original_reqctx_ref = flask.request.environ.get(_ENVIRON_REQCTX_REF_KEY)
current_reqctx_ref = _request_ctx_ref()
if not activation or original_reqctx_ref != current_reqctx_ref:
# This request didn't start a span, maybe because it was created in
# a way that doesn't run `before_request`, like when it is created
# with `app.test_request_context`.
#
# Similarly, check that the request_ctx that created the span
# matches the current request_ctx, and only tear down if they match.
# This situation can arise if the original request_ctx handling
# the request calls functions that push new request_ctx's,
# like any decorated with `flask.copy_current_request_context`.
return
try:
# For Flask 3.1+, check if this is a streaming response that might
# have already been cleaned up to prevent double cleanup
is_streaming = False
if _IS_FLASK_31_PLUS:
try:
# Additional safety check: verify we're in a Flask request context
if hasattr(flask, "request") and hasattr(flask.request, "response"):
is_streaming = (
hasattr(flask.request, "response")
and flask.request.response
and hasattr(flask.request.response, "stream")
and flask.request.response.stream
)
except (RuntimeError, AttributeError):
# Not in a proper Flask request context, don't check for streaming
is_streaming = False
if _IS_FLASK_31_PLUS and is_streaming:
# For Flask 3.1+ streaming responses, ensure OpenTelemetry contexts are cleaned up
# This addresses the generator context leak issues documented by Logfire
# (open-telemetry/opentelemetry-python#2606)
try:
context.detach(token)
if hasattr(activation, "__exit__"):
activation.__exit__(None, None, None)
# Mark as cleaned up
flask.request.environ[_ENVIRON_ACTIVATION_KEY] = None
flask.request.environ[_ENVIRON_TOKEN] = None
_logger.debug("Streaming response context cleanup completed in teardown function")
except (
RuntimeError,
ValueError,
TypeError,
AttributeError,
) as cleanup_exc:
_logger.debug(
"Teardown streaming context cleanup failed: %s",
cleanup_exc,
)
return
if exc is None:
activation.__exit__(None, None, None)
else:
activation.__exit__(type(exc), exc, getattr(exc, "__traceback__", None))
if token:
context.detach(token)
flask.request.environ.pop(_ENVIRON_ACTIVATION_KEY, None)
flask.request.environ.pop(_ENVIRON_TOKEN, None)
except (RuntimeError, AttributeError, ValueError) as teardown_exc:
# Log the error but don't raise it to avoid breaking the request handling
_logger.debug(
"Error during request teardown: %s",
teardown_exc,
exc_info=True,
)
return _teardown_request
class _InstrumentedFlask(flask.Flask):
_excluded_urls = None
_tracer_provider = None
_request_hook = None
_response_hook = None
_enable_commenter = True
_commenter_options = None
_meter_provider = None
_sem_conv_opt_in_mode = _StabilityMode.DEFAULT
def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs)
self._original_wsgi_app = self.wsgi_app
self._is_instrumented_by_opentelemetry = True
meter = get_meter(
__name__,
__version__,
_InstrumentedFlask._meter_provider,
schema_url=_get_schema_url(_InstrumentedFlask._sem_conv_opt_in_mode),
)
duration_histogram_old = None
if _report_old(_InstrumentedFlask._sem_conv_opt_in_mode):
duration_histogram_old = meter.create_histogram(
name=MetricInstruments.HTTP_SERVER_DURATION,
unit="ms",
description="Measures the duration of inbound HTTP requests.",
)
duration_histogram_new = None
if _report_new(_InstrumentedFlask._sem_conv_opt_in_mode):
duration_histogram_new = meter.create_histogram(
name=HTTP_SERVER_REQUEST_DURATION,
unit="s",
description="Duration of HTTP server requests.",
explicit_bucket_boundaries_advisory=HTTP_DURATION_HISTOGRAM_BUCKETS_NEW,
)
if _report_new(_InstrumentedFlask._sem_conv_opt_in_mode):
active_requests_counter = create_http_server_active_requests(meter)
else:
active_requests_counter = meter.create_up_down_counter(
name=MetricInstruments.HTTP_SERVER_ACTIVE_REQUESTS,
unit="requests",
description="Measures the number of concurrent HTTP requests that are currently in-flight.",
)
self.wsgi_app = _rewrapped_app(
self.wsgi_app,
active_requests_counter,
duration_histogram_old,
_InstrumentedFlask._response_hook,
excluded_urls=_InstrumentedFlask._excluded_urls,
sem_conv_opt_in_mode=_InstrumentedFlask._sem_conv_opt_in_mode,
duration_histogram_new=duration_histogram_new,
)
tracer = trace.get_tracer(
__name__,
__version__,
_InstrumentedFlask._tracer_provider,
schema_url=_get_schema_url(_InstrumentedFlask._sem_conv_opt_in_mode),
)
_before_request = _wrapped_before_request(
_InstrumentedFlask._request_hook,
tracer,
excluded_urls=_InstrumentedFlask._excluded_urls,
enable_commenter=_InstrumentedFlask._enable_commenter,
commenter_options=_InstrumentedFlask._commenter_options,
sem_conv_opt_in_mode=_InstrumentedFlask._sem_conv_opt_in_mode,
)
self._before_request = _before_request
self.before_request(_before_request)
_teardown_request = _wrapped_teardown_request(
excluded_urls=_InstrumentedFlask._excluded_urls,
)
self.teardown_request(_teardown_request)
class FlaskInstrumentor(BaseInstrumentor):
# pylint: disable=protected-access
"""An instrumentor for flask.Flask
See `BaseInstrumentor`
"""
def instrumentation_dependencies(self) -> Collection[str]:
return _instruments
def _instrument(self, **kwargs):
self._original_flask = flask.Flask
request_hook = kwargs.get("request_hook")
response_hook = kwargs.get("response_hook")
if callable(request_hook):
_InstrumentedFlask._request_hook = request_hook
if callable(response_hook):
_InstrumentedFlask._response_hook = response_hook
tracer_provider = kwargs.get("tracer_provider")
_InstrumentedFlask._tracer_provider = tracer_provider
excluded_urls = kwargs.get("excluded_urls")
_InstrumentedFlask._excluded_urls = (
_excluded_urls_from_env if excluded_urls is None else parse_excluded_urls(excluded_urls)
)
enable_commenter = kwargs.get("enable_commenter", True)
_InstrumentedFlask._enable_commenter = enable_commenter
commenter_options = kwargs.get("commenter_options", {})
_InstrumentedFlask._commenter_options = commenter_options
meter_provider = kwargs.get("meter_provider")
_InstrumentedFlask._meter_provider = meter_provider
sem_conv_opt_in_mode = _OpenTelemetrySemanticConventionStability._get_opentelemetry_stability_opt_in_mode(
_OpenTelemetryStabilitySignalType.HTTP,
)
_InstrumentedFlask._sem_conv_opt_in_mode = sem_conv_opt_in_mode
flask.Flask = _InstrumentedFlask
def _uninstrument(self, **kwargs):
flask.Flask = self._original_flask
# pylint: disable=too-many-locals
@staticmethod
def instrument_app(
app,
request_hook=None,
response_hook=None,
tracer_provider=None,
excluded_urls=None,
enable_commenter=True,
commenter_options=None,
meter_provider=None,
):
if not hasattr(app, "_is_instrumented_by_opentelemetry"):
app._is_instrumented_by_opentelemetry = False
if not app._is_instrumented_by_opentelemetry:
# initialize semantic conventions opt-in if needed
_OpenTelemetrySemanticConventionStability._initialize()
sem_conv_opt_in_mode = _OpenTelemetrySemanticConventionStability._get_opentelemetry_stability_opt_in_mode(
_OpenTelemetryStabilitySignalType.HTTP,
)
excluded_urls = parse_excluded_urls(excluded_urls) if excluded_urls is not None else _excluded_urls_from_env
meter = get_meter(
__name__,
__version__,
meter_provider,
schema_url=_get_schema_url(sem_conv_opt_in_mode),
)
duration_histogram_old = None
if _report_old(sem_conv_opt_in_mode):
duration_histogram_old = meter.create_histogram(
name=MetricInstruments.HTTP_SERVER_DURATION,
unit="ms",
description="Measures the duration of inbound HTTP requests.",
)
duration_histogram_new = None
if _report_new(sem_conv_opt_in_mode):
duration_histogram_new = meter.create_histogram(
name=HTTP_SERVER_REQUEST_DURATION,
unit="s",
description="Duration of HTTP server requests.",
explicit_bucket_boundaries_advisory=HTTP_DURATION_HISTOGRAM_BUCKETS_NEW,
)
if _report_new(sem_conv_opt_in_mode):
active_requests_counter = create_http_server_active_requests(meter)
else:
active_requests_counter = meter.create_up_down_counter(
name=MetricInstruments.HTTP_SERVER_ACTIVE_REQUESTS,
unit="requests",
description="Measures the number of concurrent HTTP requests that are currently in-flight.",
)
app._original_wsgi_app = app.wsgi_app
app.wsgi_app = _rewrapped_app(
app.wsgi_app,
active_requests_counter,
duration_histogram_old,
response_hook=response_hook,
excluded_urls=excluded_urls,
sem_conv_opt_in_mode=sem_conv_opt_in_mode,
duration_histogram_new=duration_histogram_new,
)
tracer = trace.get_tracer(
__name__,
__version__,
tracer_provider,
schema_url=_get_schema_url(sem_conv_opt_in_mode),
)
_before_request = _wrapped_before_request(
request_hook,
tracer,
excluded_urls=excluded_urls,
enable_commenter=enable_commenter,
commenter_options=(commenter_options if commenter_options else {}),
sem_conv_opt_in_mode=sem_conv_opt_in_mode,
)
app._before_request = _before_request
app.before_request(_before_request)
_teardown_request = _wrapped_teardown_request(
excluded_urls=excluded_urls,
)
app._teardown_request = _teardown_request
app.teardown_request(_teardown_request)
app._is_instrumented_by_opentelemetry = True
else:
_logger.warning("Attempting to instrument Flask app while already instrumented")
@staticmethod
def uninstrument_app(app):
if hasattr(app, "_original_wsgi_app"):
app.wsgi_app = app._original_wsgi_app
# FIXME add support for other Flask blueprints that are not None
app.before_request_funcs[None].remove(app._before_request)
app.teardown_request_funcs[None].remove(app._teardown_request)
del app._original_wsgi_app
app._is_instrumented_by_opentelemetry = False
else:
_logger.warning("Attempting to uninstrument Flask app while already uninstrumented")
package.py 0000664 0000000 0000000 00000000250 15270700723 0044154 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-flask/src/opentelemetry/instrumentation/flask # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
_instruments = ("flask >= 1.0",)
_supports_metrics = True
_semconv_status = "migration"
version.py 0000664 0000000 0000000 00000000144 15270700723 0044250 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-flask/src/opentelemetry/instrumentation/flask # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
__version__ = "0.66b2"
test-requirements-0.txt 0000664 0000000 0000000 00000000677 15270700723 0036574 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-flask asgiref==3.8.1
click==8.1.7
Deprecated==1.2.14
Flask==2.1.3
iniconfig==2.0.0
itsdangerous==2.1.2
Jinja2==3.1.6
MarkupSafe==2.1.2
packaging==24.0
pluggy==1.6.0
py-cpuinfo==9.0.0
pytest==7.4.4
tomli==2.0.1
typing_extensions==4.12.2
Werkzeug==2.3.8
wrapt==1.16.0
zipp==3.19.2
-e opentelemetry-instrumentation
-e instrumentation/opentelemetry-instrumentation-wsgi
-e util/opentelemetry-util-http
-e instrumentation/opentelemetry-instrumentation-flask
test-requirements-1.txt 0000664 0000000 0000000 00000000677 15270700723 0036575 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-flask asgiref==3.8.1
click==8.1.7
Deprecated==1.2.14
Flask==2.2.0
iniconfig==2.0.0
itsdangerous==2.1.2
Jinja2==3.1.6
MarkupSafe==2.1.2
packaging==24.0
pluggy==1.6.0
py-cpuinfo==9.0.0
pytest==7.4.4
tomli==2.0.1
typing_extensions==4.12.2
Werkzeug==2.3.8
wrapt==1.16.0
zipp==3.19.2
-e opentelemetry-instrumentation
-e instrumentation/opentelemetry-instrumentation-wsgi
-e util/opentelemetry-util-http
-e instrumentation/opentelemetry-instrumentation-flask
test-requirements-2.txt 0000664 0000000 0000000 00000000716 15270700723 0036570 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-flask asgiref==3.8.1
blinker==1.7.0
click==8.1.7
Deprecated==1.2.14
Flask==3.0.2
iniconfig==2.0.0
itsdangerous==2.1.2
Jinja2==3.1.6
MarkupSafe==2.1.2
packaging==24.0
pluggy==1.6.0
py-cpuinfo==9.0.0
pytest==7.4.4
tomli==2.0.1
typing_extensions==4.12.2
Werkzeug==3.0.6
wrapt==1.16.0
zipp==3.19.2
-e opentelemetry-instrumentation
-e instrumentation/opentelemetry-instrumentation-wsgi
-e util/opentelemetry-util-http
-e instrumentation/opentelemetry-instrumentation-flask
test-requirements-3.txt 0000664 0000000 0000000 00000000716 15270700723 0036571 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-flask asgiref==3.8.1
blinker>=1.9.0
click==8.1.7
Deprecated==1.2.14
Flask>=3.1.0
iniconfig==2.0.0
itsdangerous>=2.2.0
Jinja2==3.1.6
MarkupSafe==2.1.2
packaging==24.0
pluggy==1.6.0
py-cpuinfo==9.0.0
pytest==7.4.4
tomli==2.0.1
typing_extensions==4.12.2
Werkzeug>=3.1.0
wrapt==1.16.0
zipp==3.19.2
-e opentelemetry-instrumentation
-e instrumentation/opentelemetry-instrumentation-wsgi
-e util/opentelemetry-util-http
-e instrumentation/opentelemetry-instrumentation-flask
opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-flask/tests/ 0000775 0000000 0000000 00000000000 15270700723 0033405 5 ustar 00root root 0000000 0000000 __init__.py 0000664 0000000 0000000 00000000000 15270700723 0035425 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-flask/tests base_test.py 0000664 0000000 0000000 00000006764 15270700723 0035666 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-flask/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
from concurrent.futures import ( # pylint: disable=E0611
ThreadPoolExecutor,
as_completed,
)
from random import randint
import flask
from werkzeug.test import Client
from werkzeug.wrappers import Response
from opentelemetry import context, trace
class InstrumentationTest:
@staticmethod
def _hello_endpoint(helloid):
if helloid == 500:
raise ValueError(":-(")
return "Hello: " + str(helloid)
@staticmethod
def _sqlcommenter_endpoint():
current_context = context.get_current()
sqlcommenter_flask_values = current_context.get("SQLCOMMENTER_ORM_TAGS_AND_VALUES", {})
return sqlcommenter_flask_values
@staticmethod
def _copy_context_endpoint():
@flask.copy_current_request_context
def _extract_header():
return flask.request.headers["x-req"]
# Despite `_extract_header` copying the request context,
# calling it shouldn't detach the parent Flask span's contextvar
request_header = _extract_header()
return {
"span_name": trace.get_current_span().name,
"request_header": request_header,
}
@staticmethod
def _multithreaded_endpoint(count):
def do_random_stuff():
@flask.copy_current_request_context
def inner():
return randint(0, 100)
return inner
executor = ThreadPoolExecutor(count)
futures = []
for _ in range(count):
futures.append(executor.submit(do_random_stuff()))
numbers = []
for future in as_completed(futures):
numbers.append(future.result())
return " ".join([str(i) for i in numbers])
@staticmethod
def _custom_response_headers():
resp = flask.Response("test response")
resp.headers["content-type"] = "text/plain; charset=utf-8"
resp.headers["content-length"] = "13"
resp.headers["my-custom-header"] = "my-custom-value-1,my-custom-header-2"
resp.headers["my-custom-regex-header-1"] = "my-custom-regex-value-1,my-custom-regex-value-2"
resp.headers["My-Custom-Regex-Header-2"] = "my-custom-regex-value-3,my-custom-regex-value-4"
resp.headers["my-secret-header"] = "my-secret-value"
return resp
@staticmethod
def _repeat_custom_response_headers():
headers = {
"content-type": "text/plain; charset=utf-8",
"my-custom-header": ["my-custom-value-1", "my-custom-header-2"],
}
return flask.Response("test response", headers=headers)
def _common_initialization(self):
def excluded_endpoint():
return "excluded"
def excluded2_endpoint():
return "excluded2"
# pylint: disable=no-member
self.app.route("/hello/")(self._hello_endpoint)
self.app.route("/sqlcommenter")(self._sqlcommenter_endpoint)
self.app.route("/multithreaded")(self._multithreaded_endpoint)
self.app.route("/copy_context")(self._copy_context_endpoint)
self.app.route("/excluded/")(self._hello_endpoint)
self.app.route("/excluded")(excluded_endpoint)
self.app.route("/excluded2")(excluded2_endpoint)
self.app.route("/test_custom_response_headers")(self._custom_response_headers)
self.app.route("/test_repeat_custom_response_headers")(self._repeat_custom_response_headers)
self.client = Client(self.app, Response)
test_automatic.py 0000664 0000000 0000000 00000005513 15270700723 0036731 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-flask/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
import flask
from werkzeug.test import Client
from werkzeug.wrappers import Response
from opentelemetry import trace as trace_api
from opentelemetry.instrumentation.flask import FlaskInstrumentor
from opentelemetry.test.wsgitestutil import WsgiTestBase
# pylint: disable=import-error
from .base_test import InstrumentationTest
class TestAutomatic(InstrumentationTest, WsgiTestBase):
def setUp(self):
super().setUp()
FlaskInstrumentor().instrument()
self.app = flask.Flask(__name__)
self._common_initialization()
def tearDown(self):
super().tearDown()
with self.disable_logging():
FlaskInstrumentor().uninstrument()
def test_uninstrument(self):
# pylint: disable=access-member-before-definition
resp = self.client.get("/hello/123")
self.assertEqual(200, resp.status_code)
self.assertEqual([b"Hello: 123"], list(resp.response))
span_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(span_list), 1)
FlaskInstrumentor().uninstrument()
self.app = flask.Flask(__name__)
self.app.route("/hello/")(self._hello_endpoint)
self.client = Client(self.app, Response)
resp = self.client.get("/hello/123")
self.assertEqual(200, resp.status_code)
self.assertEqual([b"Hello: 123"], list(resp.response))
span_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(span_list), 1)
def test_exluded_urls_explicit(self):
FlaskInstrumentor().uninstrument()
FlaskInstrumentor().instrument(excluded_urls="/hello/456")
self.app = flask.Flask(__name__)
self.app.route("/hello/")(self._hello_endpoint)
client = Client(self.app, Response)
resp = client.get("/hello/123")
self.assertEqual(200, resp.status_code)
self.assertEqual([b"Hello: 123"], list(resp.response))
span_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(span_list), 1)
resp = client.get("/hello/456")
self.assertEqual(200, resp.status_code)
self.assertEqual([b"Hello: 456"], list(resp.response))
span_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(span_list), 1)
def test_no_op_tracer_provider(self):
FlaskInstrumentor().uninstrument()
FlaskInstrumentor().instrument(tracer_provider=trace_api.NoOpTracerProvider())
self.app = flask.Flask(__name__)
self.app.route("/hello/")(self._hello_endpoint)
self.client = Client(self.app, Response)
self.client.get("/hello/123")
span_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(span_list), 0)
test_copy_context.py 0000664 0000000 0000000 00000002470 15270700723 0037460 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-flask/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
import flask
from werkzeug.test import Client
from werkzeug.wrappers import Response
from opentelemetry.instrumentation.flask import FlaskInstrumentor
from opentelemetry.test.wsgitestutil import WsgiTestBase
from .base_test import InstrumentationTest
class TestCopyContext(InstrumentationTest, WsgiTestBase):
def setUp(self):
super().setUp()
FlaskInstrumentor().instrument()
self.app = flask.Flask(__name__)
self._common_initialization()
def tearDown(self):
super().tearDown()
with self.disable_logging():
FlaskInstrumentor().uninstrument()
def test_copycontext(self):
"""Test that instrumentation tear down does not blow up
when the request calls functions where the context has been
copied via `flask.copy_current_request_context`
"""
self.app = flask.Flask(__name__)
self.app.route("/copy_context")(self._copy_context_endpoint)
client = Client(self.app, Response)
resp = client.get("/copy_context", headers={"x-req": "a-header"})
self.assertEqual(200, resp.status_code)
self.assertEqual("GET /copy_context", resp.json["span_name"])
self.assertEqual("a-header", resp.json["request_header"])
test_flask_compatibility.py 0000664 0000000 0000000 00000034414 15270700723 0040776 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-flask/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
"""
Tests for Flask compatibility across versions, focusing on
context cleanup and streaming response handling.
"""
import io
import threading
import time
from importlib.metadata import version
from unittest import mock, skipIf
import flask
from opentelemetry import trace
from opentelemetry.instrumentation.flask import (
_ENVIRON_ACTIVATION_KEY,
_ENVIRON_TOKEN,
FlaskInstrumentor,
_request_ctx_ref,
)
from opentelemetry.test.wsgitestutil import WsgiTestBase
class TestFlaskCompatibility(WsgiTestBase):
def setUp(self):
super().setUp()
self.flask_version = version("flask")
def test_streaming_response_context_cleanup(self):
"""Test that streaming responses properly clean up context"""
app = flask.Flask(__name__)
FlaskInstrumentor().instrument_app(app)
@app.route("/stream")
def streaming_endpoint():
def generate():
yield "Hello "
yield "World!"
return flask.Response(flask.stream_with_context(generate()))
@app.route("/normal")
def normal_endpoint():
return "Normal Response"
client = app.test_client()
# Test streaming response
with self.subTest("streaming_response"):
response = client.get("/stream")
self.assertEqual(response.status_code, 200)
self.assertEqual(b"Hello World!", response.data)
# Verify that context is properly cleaned up
current_span = trace.get_current_span()
span_context = current_span.get_span_context()
# Either we have a valid trace (non-zero) or we have a NoOp span
self.assertTrue(span_context.trace_id >= 0)
# Test normal response for comparison
with self.subTest("normal_response"):
response = client.get("/normal")
self.assertEqual(response.status_code, 200)
self.assertEqual(b"Normal Response", response.data)
def test_generator_response_context_cleanup(self):
"""Test that generator responses properly clean up context"""
app = flask.Flask(__name__)
FlaskInstrumentor().instrument_app(app)
@app.route("/generator")
def generator_endpoint():
def generate():
for chunk_idx in range(5):
yield f"Chunk {chunk_idx}\n"
return flask.Response(flask.stream_with_context(generate()))
client = app.test_client()
response = client.get("/generator")
self.assertEqual(response.status_code, 200)
expected = b"".join(f"Chunk {chunk_idx}\n".encode() for chunk_idx in range(5))
self.assertEqual(response.data, expected)
def test_file_response_context_cleanup(self):
"""Test context cleanup with file responses"""
app = flask.Flask(__name__)
FlaskInstrumentor().instrument_app(app)
@app.route("/file")
def file_endpoint():
# Simulate file response using io.BytesIO
file_data = io.BytesIO(b"File content here")
return flask.send_file(file_data, as_attachment=True, download_name="test.txt")
client = app.test_client()
response = client.get("/file")
self.assertEqual(response.status_code, 200)
self.assertEqual(response.data, b"File content here")
def test_multiple_requests_context_isolation(self):
"""Test context isolation between multiple requests"""
app = flask.Flask(__name__)
FlaskInstrumentor().instrument_app(app)
results = []
@app.route("/test/")
def test_endpoint(request_id):
results.append(f"Request {request_id}")
return f"Response {request_id}"
client = app.test_client()
# Make multiple requests and verify they don't interfere
for request_idx in range(10):
response = client.get(f"/test/{request_idx}")
self.assertEqual(response.status_code, 200)
self.assertEqual(response.data, f"Response {request_idx}".encode())
# Verify all requests were processed
self.assertEqual(len(results), 10)
for request_idx in range(10):
self.assertIn(f"Request {request_idx}", results)
def test_request_context_reference_handling(self):
"""Test request context reference handling works correctly"""
app = flask.Flask(__name__)
FlaskInstrumentor().instrument_app(app)
@app.route("/context_test")
def context_test_endpoint():
# Store request context reference at different points
context_refs = []
context_refs.append(_request_ctx_ref())
# Do some work
result = "Context test"
context_refs.append(_request_ctx_ref())
return result
client = app.test_client()
response = client.get("/context_test")
self.assertEqual(response.status_code, 200)
self.assertEqual(response.data, b"Context test")
def test_concurrent_requests_isolation(self):
"""Test that concurrent requests have proper context isolation"""
app = flask.Flask(__name__)
FlaskInstrumentor().instrument_app(app)
results = []
errors = []
@app.route("/slow_stream/")
def slow_stream_endpoint(request_id):
def generate():
for chunk_idx in range(3):
time.sleep(0.01) # Small delay to simulate work
yield f"Request {request_id} - Chunk {chunk_idx}\n"
return flask.Response(flask.stream_with_context(generate()))
def make_request(request_id):
try:
client = app.test_client()
response = client.get(f"/slow_stream/{request_id}")
results.append((request_id, response.status_code, response.data))
except (RuntimeError, ValueError) as exc:
errors.append((request_id, exc))
# Create multiple concurrent requests
threads = []
for thread_idx in range(5):
thread = threading.Thread(target=make_request, args=(thread_idx,))
threads.append(thread)
thread.start()
# Wait for all threads to complete
for thread in threads:
thread.join()
# Verify all requests completed successfully
self.assertEqual(len(errors), 0, f"Errors occurred: {errors}")
self.assertEqual(len(results), 5)
for request_id, status_code, data in results:
self.assertEqual(status_code, 200)
expected = b"".join(f"Request {request_id} - Chunk {chunk_idx}\n".encode() for chunk_idx in range(3))
self.assertEqual(data, expected)
def test_flask_version_compatibility(self):
"""Test that the instrumentation works with the current Flask version"""
app = flask.Flask(__name__)
FlaskInstrumentor().instrument_app(app)
@app.route("/version_test")
def version_test_endpoint():
return f"Flask {self.flask_version} compatible"
client = app.test_client()
response = client.get("/version_test")
self.assertEqual(response.status_code, 200)
expected_text = f"Flask {self.flask_version} compatible"
self.assertEqual(response.data, expected_text.encode())
def test_context_leak_prevention(self):
"""Test that context doesn't leak after multiple requests"""
app = flask.Flask(__name__)
FlaskInstrumentor().instrument_app(app)
@app.route("/leak_test")
def leak_test_endpoint():
def generate():
yield "Part 1\n"
yield "Part 2\n"
yield "Part 3\n"
return flask.Response(flask.stream_with_context(generate()))
client = app.test_client()
# Make multiple streaming requests
for _ in range(10):
response = client.get("/leak_test")
self.assertEqual(response.status_code, 200)
expected = b"Part 1\nPart 2\nPart 3\n"
self.assertEqual(response.data, expected)
# After all requests, there should be no lingering context
# This is a basic check - more sophisticated leak detection would require
# instrumentation-specific testing utilities
# If we got here without errors, context cleanup worked
def test_streaming_with_error_in_cleanup(self):
"""Test graceful handling when cleanup operations fail"""
app = flask.Flask(__name__)
FlaskInstrumentor().instrument_app(app)
# Mock the cleanup functions to raise exceptions
with (
mock.patch("opentelemetry.instrumentation.flask.context.detach") as mock_detach,
mock.patch("opentelemetry.trace.use_span") as mock_use_span,
):
# Make detach raise an exception
mock_detach.side_effect = RuntimeError("Detach error")
# Make the span activation __exit__ raise an exception
mock_span_instance = mock.Mock()
mock_span_instance.is_recording.return_value = True
mock_span_instance.__exit__ = mock.Mock(side_effect=RuntimeError("Exit error"))
mock_use_span.return_value.__enter__ = mock.Mock(return_value=mock_span_instance)
@app.route("/stream_cleanup_error")
def stream_cleanup_error_endpoint():
def generate():
yield "Data"
return flask.Response(flask.stream_with_context(generate()))
client = app.test_client()
# The request should still complete successfully despite cleanup errors
response = client.get("/stream_cleanup_error")
self.assertEqual(response.status_code, 200)
self.assertEqual(response.data, b"Data")
@skipIf(
lambda: (
not __import__(
"opentelemetry.instrumentation.flask",
fromlist=["_IS_FLASK_31_PLUS"],
)._IS_FLASK_31_PLUS
),
"Flask 3.1+ streaming context cleanup requires Flask 3.1+",
)
def test_flask_31_streaming_context_cleanup(self):
"""Test that Flask 3.1+ streaming responses have proper context cleanup to prevent token reuse"""
app = flask.Flask(__name__)
FlaskInstrumentor().instrument_app(app)
@app.route("/stream_flask31")
def flask31_streaming_endpoint():
def generate():
for chunk_idx in range(10):
yield f"Chunk {chunk_idx}\n"
return flask.Response(flask.stream_with_context(generate()))
@app.route("/stream_normal")
def stream_normal_endpoint():
def generate():
for chunk_idx in range(5):
yield f"Normal {chunk_idx}\n"
return flask.Response(flask.stream_with_context(generate()))
client = app.test_client()
# Make multiple consecutive streaming requests to test for token reuse issues
for request_idx in range(20):
response = client.get("/stream_flask31")
self.assertEqual(response.status_code, 200)
expected_data = "".join(f"Chunk {j}\n" for j in range(10)).encode()
self.assertEqual(response.data, expected_data)
# Test normal streaming requests as well
for request_idx in range(5):
response = client.get("/stream_normal")
self.assertEqual(response.status_code, 200)
expected_data = "".join(f"Normal {j}\n" for j in range(5)).encode()
self.assertEqual(response.data, expected_data)
# Mix of streaming requests
for request_idx in range(10):
endpoint = "/stream_flask31" if request_idx % 2 == 0 else "/stream_normal"
response = client.get(endpoint)
self.assertEqual(response.status_code, 200)
# For Flask 3.1+, streaming context cleanup is now handled in Flask's teardown function
# This ensures OpenTelemetry contexts are properly cleaned up for streaming responses
# following Logfire's recommendations (see open-telemetry/opentelemetry-python#2606)
# If we reach this point, the Flask 3.1+ streaming context cleanup is working
def test_duplicate_teardown_request_does_not_cause_errors(self):
"""Test that _teardown_request can be called multiple times without errors.
Flask may call teardown_request multiple times in some scenarios.
After the first call, _ENVIRON_ACTIVATION_KEY and _ENVIRON_TOKEN
should be cleaned up so subsequent calls are no-ops.
"""
app = flask.Flask(__name__)
# Register the check handler BEFORE instrumenting so it runs AFTER
# the instrumentation's teardown (Flask uses LIFO order).
cleaned_up = {}
call_count = {"teardown_calls": 0}
@app.teardown_request
def check_cleanup(exc):
cleaned_up["activation_present"] = _ENVIRON_ACTIVATION_KEY in flask.request.environ
cleaned_up["token_present"] = _ENVIRON_TOKEN in flask.request.environ
FlaskInstrumentor().instrument_app(app)
# Wrap the instrumentation's teardown to count calls and invoke it
# a second time to simulate duplicate teardown.
instrumentation_teardown = app.teardown_request_funcs[None][-1]
def counting_teardown(exc):
call_count["teardown_calls"] += 1
instrumentation_teardown(exc)
# Call it again to simulate duplicate teardown - should not raise
instrumentation_teardown(exc)
app.teardown_request_funcs[None][-1] = counting_teardown
@app.route("/test")
def test_endpoint():
return "OK"
client = app.test_client()
response = client.get("/test")
self.assertEqual(response.status_code, 200)
# Verify the teardown was actually called
self.assertGreater(call_count["teardown_calls"], 0)
# Verify env keys are cleaned up after teardown
self.assertFalse(
cleaned_up.get("activation_present", True),
"_ENVIRON_ACTIVATION_KEY should be cleaned up after teardown",
)
self.assertFalse(
cleaned_up.get("token_present", True),
"_ENVIRON_TOKEN should be cleaned up after teardown",
)
test_multithreading.py 0000664 0000000 0000000 00000002527 15270700723 0037765 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-flask/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
import flask
from werkzeug.test import Client
from werkzeug.wrappers import Response
from opentelemetry.instrumentation.flask import FlaskInstrumentor
from opentelemetry.test.wsgitestutil import WsgiTestBase
# pylint: disable=import-error
from .base_test import InstrumentationTest
class TestMultiThreading(InstrumentationTest, WsgiTestBase):
def setUp(self):
super().setUp()
FlaskInstrumentor().instrument()
self.app = flask.Flask(__name__)
self._common_initialization()
def tearDown(self):
super().tearDown()
with self.disable_logging():
FlaskInstrumentor().uninstrument()
def test_multithreaded(self):
"""Test that instrumentation tear down does not blow up
when the request thread spawn children threads and the request
context is copied to the children threads
"""
self.app = flask.Flask(__name__)
self.app.route("/multithreaded/")(self._multithreaded_endpoint)
client = Client(self.app, Response)
count = 5
resp = client.get(f"/multithreaded/{count}")
self.assertEqual(200, resp.status_code)
# Should return the specified number of random integers
self.assertEqual(count, len(resp.text.split(" ")))
test_programmatic.py 0000664 0000000 0000000 00000131614 15270700723 0037432 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-flask/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
# pylint: disable=too-many-lines
from timeit import default_timer
from unittest.mock import Mock, patch
from flask import Flask, request
from opentelemetry import trace
from opentelemetry.instrumentation._semconv import (
HTTP_DURATION_HISTOGRAM_BUCKETS_NEW,
OTEL_SEMCONV_STABILITY_OPT_IN,
_OpenTelemetrySemanticConventionStability,
_server_active_requests_count_attrs_new,
_server_active_requests_count_attrs_old,
_server_duration_attrs_new,
_server_duration_attrs_old,
)
from opentelemetry.instrumentation.flask import FlaskInstrumentor
from opentelemetry.instrumentation.propagators import (
TraceResponsePropagator,
get_global_response_propagator,
set_global_response_propagator,
)
from opentelemetry.instrumentation.wsgi import OpenTelemetryMiddleware
from opentelemetry.sdk.metrics.export import (
HistogramDataPoint,
NumberDataPoint,
)
from opentelemetry.sdk.resources import Resource
from opentelemetry.semconv._incubating.attributes.http_attributes import (
HTTP_FLAVOR,
HTTP_HOST,
HTTP_METHOD,
HTTP_REQUEST_METHOD,
HTTP_RESPONSE_STATUS_CODE,
HTTP_ROUTE,
HTTP_SCHEME,
HTTP_SERVER_NAME,
HTTP_STATUS_CODE,
HTTP_TARGET,
)
from opentelemetry.semconv._incubating.attributes.net_attributes import (
NET_HOST_NAME,
NET_HOST_PORT,
)
from opentelemetry.semconv._incubating.attributes.network_attributes import (
NETWORK_PROTOCOL_VERSION,
)
from opentelemetry.semconv._incubating.attributes.server_attributes import (
SERVER_ADDRESS,
SERVER_PORT,
)
from opentelemetry.semconv._incubating.attributes.url_attributes import (
URL_PATH,
URL_SCHEME,
)
from opentelemetry.semconv.attributes.error_attributes import ERROR_TYPE
from opentelemetry.test.wsgitestutil import WsgiTestBase
from opentelemetry.util.http import (
OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SANITIZE_FIELDS,
OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_REQUEST,
OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_RESPONSE,
OTEL_PYTHON_INSTRUMENTATION_HTTP_CAPTURE_ALL_METHODS,
get_excluded_urls,
)
# pylint: disable=import-error
from .base_test import InstrumentationTest
def expected_attributes(override_attributes):
default_attributes = {
HTTP_METHOD: "GET",
HTTP_SERVER_NAME: "localhost",
HTTP_SCHEME: "http",
NET_HOST_PORT: 80,
NET_HOST_NAME: "localhost",
HTTP_HOST: "localhost",
HTTP_TARGET: "/",
HTTP_FLAVOR: "1.1",
HTTP_STATUS_CODE: 200,
}
for key, val in override_attributes.items():
default_attributes[key] = val
return default_attributes
def expected_attributes_new(override_attributes):
default_attributes = {
HTTP_REQUEST_METHOD: "GET",
SERVER_PORT: 80,
SERVER_ADDRESS: "localhost",
URL_PATH: "/hello/123",
NETWORK_PROTOCOL_VERSION: "1.1",
HTTP_RESPONSE_STATUS_CODE: 200,
}
for key, val in override_attributes.items():
default_attributes[key] = val
return default_attributes
_server_duration_attrs_old_copy = _server_duration_attrs_old.copy()
_server_duration_attrs_old_copy.append("http.target")
_server_duration_attrs_new_copy = _server_duration_attrs_new.copy()
_server_duration_attrs_new_copy.append("http.route")
_expected_metric_names_old = [
"http.server.active_requests",
"http.server.duration",
]
_expected_metric_names_new = [
"http.server.active_requests",
"http.server.request.duration",
]
_recommended_metrics_attrs_old = {
"http.server.active_requests": _server_active_requests_count_attrs_old,
"http.server.duration": _server_duration_attrs_old_copy,
}
_recommended_metrics_attrs_new = {
"http.server.active_requests": _server_active_requests_count_attrs_new,
"http.server.request.duration": _server_duration_attrs_new_copy,
}
_server_active_requests_count_attrs_both = _server_active_requests_count_attrs_old
_server_active_requests_count_attrs_both.extend(_server_active_requests_count_attrs_new)
_recommended_metrics_attrs_both = {
"http.server.active_requests": _server_active_requests_count_attrs_both,
"http.server.duration": _server_duration_attrs_old_copy,
"http.server.request.duration": _server_duration_attrs_new_copy,
}
SCOPE = "opentelemetry.instrumentation.flask"
# pylint: disable=too-many-public-methods
class TestProgrammatic(InstrumentationTest, WsgiTestBase):
def setUp(self):
super().setUp()
test_name = ""
if hasattr(self, "_testMethodName"):
test_name = self._testMethodName
sem_conv_mode = "default"
if "new_semconv" in test_name:
sem_conv_mode = "http"
elif "both_semconv" in test_name:
sem_conv_mode = "http/dup"
self.env_patch = patch.dict(
"os.environ",
{
"OTEL_PYTHON_FLASK_EXCLUDED_URLS": "http://localhost/env_excluded_arg/123,env_excluded_noarg,env_excluded_arg/789",
OTEL_SEMCONV_STABILITY_OPT_IN: sem_conv_mode,
},
)
_OpenTelemetrySemanticConventionStability._initialized = False
self.env_patch.start()
self.exclude_patch = patch(
"opentelemetry.instrumentation.flask._excluded_urls_from_env",
get_excluded_urls("FLASK"),
)
self.exclude_patch.start()
self.app = Flask(__name__)
FlaskInstrumentor().instrument_app(self.app)
self._common_initialization()
def tearDown(self):
super().tearDown()
self.env_patch.stop()
self.exclude_patch.stop()
with self.disable_logging():
FlaskInstrumentor().uninstrument_app(self.app)
def test_instrument_app_and_instrument(self):
FlaskInstrumentor().instrument()
resp = self.client.get("/hello/123")
self.assertEqual(200, resp.status_code)
self.assertEqual([b"Hello: 123"], list(resp.response))
span_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(span_list), 1)
FlaskInstrumentor().uninstrument()
def test_uninstrument_app(self):
resp = self.client.get("/hello/123")
self.assertEqual(200, resp.status_code)
self.assertEqual([b"Hello: 123"], list(resp.response))
span_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(span_list), 1)
FlaskInstrumentor().uninstrument_app(self.app)
resp = self.client.get("/hello/123")
self.assertEqual(200, resp.status_code)
self.assertEqual([b"Hello: 123"], list(resp.response))
span_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(span_list), 1)
def test_uninstrument_app_after_instrument(self):
FlaskInstrumentor().instrument()
FlaskInstrumentor().uninstrument_app(self.app)
resp = self.client.get("/hello/123")
self.assertEqual(200, resp.status_code)
self.assertEqual([b"Hello: 123"], list(resp.response))
span_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(span_list), 0)
FlaskInstrumentor().uninstrument()
# pylint: disable=no-member
def test_only_strings_in_environ(self):
"""
Some WSGI servers (such as Gunicorn) expect keys in the environ object
to be strings
OpenTelemetry should adhere to this convention.
"""
nonstring_keys = set()
def assert_environ():
for key in request.environ:
if not isinstance(key, str):
nonstring_keys.add(key)
return "hi"
self.app.route("/assert_environ")(assert_environ)
self.client.get("/assert_environ")
self.assertEqual(nonstring_keys, set())
def test_simple(self):
expected_attrs = expected_attributes(
{
HTTP_TARGET: "/hello/123",
HTTP_ROUTE: "/hello/",
}
)
self.client.get("/hello/123")
span_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(span_list), 1)
self.assertEqual(span_list[0].name, "GET /hello/")
self.assertEqual(span_list[0].kind, trace.SpanKind.SERVER)
self.assertEqual(span_list[0].attributes, expected_attrs)
def test_simple_new_semconv(self):
expected_attrs = expected_attributes_new(
{
HTTP_ROUTE: "/hello/",
URL_SCHEME: "http",
}
)
self.client.get("/hello/123")
span_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(span_list), 1)
self.assertEqual(span_list[0].name, "GET /hello/")
self.assertEqual(span_list[0].kind, trace.SpanKind.SERVER)
self.assertEqual(span_list[0].attributes, expected_attrs)
def test_simple_both_semconv(self):
expected_attrs = expected_attributes(
{
HTTP_TARGET: "/hello/123",
HTTP_ROUTE: "/hello/",
}
)
expected_attrs.update(
expected_attributes_new(
{
HTTP_ROUTE: "/hello/",
URL_SCHEME: "http",
}
)
)
self.client.get("/hello/123")
span_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(span_list), 1)
self.assertEqual(span_list[0].name, "GET /hello/")
self.assertEqual(span_list[0].kind, trace.SpanKind.SERVER)
self.assertEqual(span_list[0].attributes, expected_attrs)
def test_trace_response(self):
orig = get_global_response_propagator()
set_global_response_propagator(TraceResponsePropagator())
response = self.client.get("/hello/123")
span_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(span_list), 1)
self.assertTraceResponseHeaderMatchesSpan(
response.headers,
span_list[0],
)
set_global_response_propagator(orig)
def test_not_recording(self):
mock_tracer = Mock()
mock_span = Mock()
mock_span.is_recording.return_value = False
mock_tracer.start_span.return_value = mock_span
with patch("opentelemetry.trace.get_tracer") as tracer:
tracer.return_value = mock_tracer
self.client.get("/hello/123")
self.assertFalse(mock_span.is_recording())
self.assertTrue(mock_span.is_recording.called)
self.assertFalse(mock_span.set_attribute.called)
self.assertFalse(mock_span.set_status.called)
def test_404(self):
expected_attrs = expected_attributes(
{
HTTP_METHOD: "POST",
HTTP_TARGET: "/bye",
HTTP_STATUS_CODE: 404,
}
)
resp = self.client.post("/bye")
self.assertEqual(404, resp.status_code)
resp.close()
span_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(span_list), 1)
self.assertEqual(span_list[0].name, "POST /bye")
self.assertEqual(span_list[0].kind, trace.SpanKind.SERVER)
self.assertEqual(span_list[0].attributes, expected_attrs)
def test_404_new_semconv(self):
expected_attrs = expected_attributes_new(
{
HTTP_REQUEST_METHOD: "POST",
HTTP_RESPONSE_STATUS_CODE: 404,
URL_PATH: "/bye",
URL_SCHEME: "http",
}
)
resp = self.client.post("/bye")
self.assertEqual(404, resp.status_code)
resp.close()
span_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(span_list), 1)
self.assertEqual(span_list[0].name, "POST /bye")
self.assertEqual(span_list[0].kind, trace.SpanKind.SERVER)
self.assertEqual(span_list[0].attributes, expected_attrs)
def test_404_both_semconv(self):
expected_attrs = expected_attributes(
{
HTTP_METHOD: "POST",
HTTP_TARGET: "/bye",
HTTP_STATUS_CODE: 404,
}
)
expected_attrs.update(
expected_attributes_new(
{
HTTP_REQUEST_METHOD: "POST",
HTTP_RESPONSE_STATUS_CODE: 404,
URL_PATH: "/bye",
URL_SCHEME: "http",
}
)
)
resp = self.client.post("/bye")
self.assertEqual(404, resp.status_code)
resp.close()
span_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(span_list), 1)
self.assertEqual(span_list[0].name, "POST /bye")
self.assertEqual(span_list[0].kind, trace.SpanKind.SERVER)
self.assertEqual(span_list[0].attributes, expected_attrs)
def test_internal_error(self):
expected_attrs = expected_attributes(
{
HTTP_TARGET: "/hello/500",
HTTP_ROUTE: "/hello/",
HTTP_STATUS_CODE: 500,
}
)
resp = self.client.get("/hello/500")
self.assertEqual(500, resp.status_code)
resp.close()
span_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(span_list), 1)
self.assertEqual(span_list[0].name, "GET /hello/")
self.assertEqual(span_list[0].kind, trace.SpanKind.SERVER)
self.assertEqual(span_list[0].attributes, expected_attrs)
def test_internal_error_new_semconv(self):
expected_attrs = expected_attributes_new(
{
URL_PATH: "/hello/500",
HTTP_ROUTE: "/hello/",
HTTP_RESPONSE_STATUS_CODE: 500,
ERROR_TYPE: "500",
URL_SCHEME: "http",
}
)
resp = self.client.get("/hello/500")
self.assertEqual(500, resp.status_code)
resp.close()
span_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(span_list), 1)
self.assertEqual(span_list[0].name, "GET /hello/")
self.assertEqual(span_list[0].kind, trace.SpanKind.SERVER)
self.assertEqual(span_list[0].attributes, expected_attrs)
def test_internal_error_both_semconv(self):
expected_attrs = expected_attributes(
{
HTTP_TARGET: "/hello/500",
HTTP_ROUTE: "/hello/",
HTTP_STATUS_CODE: 500,
}
)
expected_attrs.update(
expected_attributes_new(
{
URL_PATH: "/hello/500",
HTTP_RESPONSE_STATUS_CODE: 500,
ERROR_TYPE: "500",
URL_SCHEME: "http",
}
)
)
resp = self.client.get("/hello/500")
self.assertEqual(500, resp.status_code)
resp.close()
span_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(span_list), 1)
self.assertEqual(span_list[0].name, "GET /hello/")
self.assertEqual(span_list[0].kind, trace.SpanKind.SERVER)
self.assertEqual(span_list[0].attributes, expected_attrs)
def test_exclude_lists_from_env(self):
self.client.get("/env_excluded_arg/123")
span_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(span_list), 0)
self.client.get("/env_excluded_arg/125")
span_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(span_list), 1)
self.client.get("/env_excluded_noarg")
span_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(span_list), 1)
self.client.get("/env_excluded_noarg2")
span_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(span_list), 1)
def test_exclude_lists_from_explicit(self):
excluded_urls = "http://localhost/explicit_excluded_arg/123,explicit_excluded_noarg"
app = Flask(__name__)
FlaskInstrumentor().instrument_app(app, excluded_urls=excluded_urls)
client = app.test_client()
client.get("/explicit_excluded_arg/123")
span_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(span_list), 0)
client.get("/explicit_excluded_arg/125")
span_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(span_list), 1)
client.get("/explicit_excluded_noarg")
span_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(span_list), 1)
client.get("/explicit_excluded_noarg2")
span_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(span_list), 1)
def test_flask_metrics(self):
start = default_timer()
self.client.get("/hello/123")
self.client.get("/hello/321")
self.client.get("/hello/756")
duration = max(round((default_timer() - start) * 1000), 0)
metrics = self.get_sorted_metrics(SCOPE)
number_data_point_seen = False
histogram_data_point_seen = False
self.assertTrue(len(metrics) != 0)
for metric in metrics:
self.assertIn(metric.name, _expected_metric_names_old)
data_points = list(metric.data.data_points)
self.assertEqual(len(data_points), 1)
for point in data_points:
if isinstance(point, HistogramDataPoint):
self.assertEqual(point.count, 3)
self.assertAlmostEqual(duration, point.sum, delta=10)
histogram_data_point_seen = True
if isinstance(point, NumberDataPoint):
number_data_point_seen = True
for attr in point.attributes:
self.assertIn(
attr,
_recommended_metrics_attrs_old[metric.name],
)
self.assertTrue(number_data_point_seen and histogram_data_point_seen)
def test_flask_metrics_new_semconv(self):
start = default_timer()
self.client.get("/hello/123")
self.client.get("/hello/321")
self.client.get("/hello/756")
duration_s = max(default_timer() - start, 0)
metrics = self.get_sorted_metrics(SCOPE)
number_data_point_seen = False
histogram_data_point_seen = False
self.assertTrue(len(metrics) != 0)
for metric in metrics:
self.assertIn(metric.name, _expected_metric_names_new)
data_points = list(metric.data.data_points)
self.assertEqual(len(data_points), 1)
for point in data_points:
if isinstance(point, HistogramDataPoint):
self.assertEqual(point.count, 3)
self.assertAlmostEqual(duration_s, point.sum, places=1)
self.assertEqual(
point.explicit_bounds,
HTTP_DURATION_HISTOGRAM_BUCKETS_NEW,
)
histogram_data_point_seen = True
if isinstance(point, NumberDataPoint):
number_data_point_seen = True
for attr in point.attributes:
self.assertIn(
attr,
_recommended_metrics_attrs_new[metric.name],
)
self.assertTrue(number_data_point_seen and histogram_data_point_seen)
def test_flask_metric_values(self):
start = default_timer()
self.client.post("/hello/756")
self.client.post("/hello/756")
self.client.post("/hello/756")
duration = max(round((default_timer() - start) * 1000), 0)
metrics = self.get_sorted_metrics(SCOPE)
for metric in metrics:
for point in list(metric.data.data_points):
if isinstance(point, HistogramDataPoint):
self.assertEqual(point.count, 3)
self.assertAlmostEqual(duration, point.sum, delta=10)
if isinstance(point, NumberDataPoint):
self.assertEqual(point.value, 0)
def _assert_basic_metric(
self,
expected_duration_attributes,
expected_requests_count_attributes,
expected_histogram_explicit_bounds=None,
):
# pylint: disable=too-many-nested-blocks
metrics = self.get_sorted_metrics(SCOPE)
for metric in metrics:
for point in list(metric.data.data_points):
if isinstance(point, HistogramDataPoint):
self.assertDictEqual(
expected_duration_attributes,
dict(point.attributes),
)
if expected_histogram_explicit_bounds is not None:
self.assertEqual(
expected_histogram_explicit_bounds,
point.explicit_bounds,
)
self.assertEqual(point.count, 1)
elif isinstance(point, NumberDataPoint):
self.assertDictEqual(
expected_requests_count_attributes,
dict(point.attributes),
)
self.assertEqual(point.value, 0)
def test_basic_metric_success(self):
self.client.get("/hello/756")
expected_duration_attributes = {
"http.method": "GET",
"http.target": "/hello/",
"http.host": "localhost",
"http.scheme": "http",
"http.flavor": "1.1",
"http.server_name": "localhost",
"net.host.port": 80,
"http.status_code": 200,
"net.host.name": "localhost",
}
expected_requests_count_attributes = {
"http.method": "GET",
"http.host": "localhost",
"http.scheme": "http",
"http.flavor": "1.1",
"http.server_name": "localhost",
}
self._assert_basic_metric(
expected_duration_attributes,
expected_requests_count_attributes,
)
def test_basic_metric_success_new_semconv(self):
self.client.get("/hello/756")
expected_duration_attributes = {
"http.request.method": "GET",
"url.scheme": "http",
"http.route": "/hello/",
"network.protocol.version": "1.1",
"http.response.status_code": 200,
}
expected_requests_count_attributes = {
"http.request.method": "GET",
"url.scheme": "http",
}
self._assert_basic_metric(
expected_duration_attributes,
expected_requests_count_attributes,
expected_histogram_explicit_bounds=HTTP_DURATION_HISTOGRAM_BUCKETS_NEW,
)
def test_basic_metric_nonstandard_http_method_success(self):
self.client.open("/hello/756", method="NONSTANDARD")
expected_duration_attributes = {
"http.method": "_OTHER",
"http.host": "localhost",
"http.scheme": "http",
"http.flavor": "1.1",
"http.server_name": "localhost",
"net.host.port": 80,
"http.status_code": 405,
"net.host.name": "localhost",
}
expected_requests_count_attributes = {
"http.method": "_OTHER",
"http.host": "localhost",
"http.scheme": "http",
"http.flavor": "1.1",
"http.server_name": "localhost",
}
self._assert_basic_metric(
expected_duration_attributes,
expected_requests_count_attributes,
)
def test_basic_metric_nonstandard_http_method_success_new_semconv(self):
self.client.open("/hello/756", method="NONSTANDARD")
expected_duration_attributes = {
"http.request.method": "_OTHER",
"url.scheme": "http",
"network.protocol.version": "1.1",
"http.response.status_code": 405,
}
expected_requests_count_attributes = {
"http.request.method": "_OTHER",
"url.scheme": "http",
}
self._assert_basic_metric(
expected_duration_attributes,
expected_requests_count_attributes,
expected_histogram_explicit_bounds=HTTP_DURATION_HISTOGRAM_BUCKETS_NEW,
)
@patch.dict(
"os.environ",
{
OTEL_PYTHON_INSTRUMENTATION_HTTP_CAPTURE_ALL_METHODS: "1",
},
)
def test_basic_metric_nonstandard_http_method_allowed_success_new_semconv(
self,
):
self.client.open("/hello/756", method="NONSTANDARD")
expected_duration_attributes = {
"http.request.method": "NONSTANDARD",
"url.scheme": "http",
"network.protocol.version": "1.1",
"http.response.status_code": 405,
}
expected_requests_count_attributes = {
"http.request.method": "NONSTANDARD",
"url.scheme": "http",
}
self._assert_basic_metric(
expected_duration_attributes,
expected_requests_count_attributes,
expected_histogram_explicit_bounds=HTTP_DURATION_HISTOGRAM_BUCKETS_NEW,
)
def test_metric_uninstrument(self):
self.client.delete("/hello/756")
FlaskInstrumentor().uninstrument_app(self.app)
self.client.delete("/hello/756")
metrics_list = self.memory_metrics_reader.get_metrics_data()
for resource_metric in metrics_list.resource_metrics:
for scope_metric in resource_metric.scope_metrics:
for metric in scope_metric.metrics:
for point in list(metric.data.data_points):
if isinstance(point, HistogramDataPoint):
self.assertEqual(point.count, 1)
def test_flask_metrics_excluded_urls(self):
start = default_timer()
self.client.get("/env_excluded_arg/123")
self.client.get("/env_excluded_noarg")
self.client.get("/env_excluded_arg/789")
duration = max(round((default_timer() - start) * 1000), 0)
metrics_list = self.memory_metrics_reader.get_metrics_data()
number_data_point_seen = False
histogram_data_point_seen = False
self.assertTrue(len(metrics_list.resource_metrics) != 0)
for resource_metric in metrics_list.resource_metrics:
self.assertTrue(len(resource_metric.scope_metrics) != 0)
for scope_metric in resource_metric.scope_metrics:
self.assertTrue(len(scope_metric.metrics) != 0)
for metric in scope_metric.metrics:
self.assertIn(metric.name, _expected_metric_names_old)
data_points = list(metric.data.data_points)
self.assertEqual(len(data_points), 1)
for point in data_points:
if isinstance(point, HistogramDataPoint):
self.assertEqual(point.count, 0)
self.assertAlmostEqual(duration, point.sum, delta=10)
histogram_data_point_seen = True
if isinstance(point, NumberDataPoint):
number_data_point_seen = True
for attr in point.attributes:
self.assertIn(
attr,
_recommended_metrics_attrs_old[metric.name],
)
self.assertTrue(number_data_point_seen)
self.assertFalse(histogram_data_point_seen)
def test_flask_metrics_excluded_urls_new_semconv(self):
start = default_timer()
self.client.get("/env_excluded_arg/123")
self.client.get("/env_excluded_noarg")
self.client.get("/env_excluded_arg/789")
duration_s = max(default_timer() - start, 0)
metrics_list = self.memory_metrics_reader.get_metrics_data()
number_data_point_seen = False
histogram_data_point_seen = False
self.assertTrue(len(metrics_list.resource_metrics) != 0)
for resource_metric in metrics_list.resource_metrics:
self.assertTrue(len(resource_metric.scope_metrics) != 0)
for scope_metric in resource_metric.scope_metrics:
self.assertTrue(len(scope_metric.metrics) != 0)
for metric in scope_metric.metrics:
self.assertIn(metric.name, _expected_metric_names_new)
data_points = list(metric.data.data_points)
self.assertEqual(len(data_points), 1)
for point in data_points:
if isinstance(point, HistogramDataPoint):
self.assertEqual(point.count, 0)
self.assertAlmostEqual(duration_s, point.sum, places=1)
self.assertEqual(
point.explicit_bounds,
HTTP_DURATION_HISTOGRAM_BUCKETS_NEW,
)
histogram_data_point_seen = True
if isinstance(point, NumberDataPoint):
number_data_point_seen = True
for attr in point.attributes:
self.assertIn(
attr,
_recommended_metrics_attrs_new[metric.name],
)
self.assertTrue(number_data_point_seen)
self.assertFalse(histogram_data_point_seen)
def test_duration_histogram_old_record_with_context(self):
with patch("opentelemetry.trace.set_span_in_context") as mock_set_span:
self.client.get("/hello/123")
# Verify that trace.set_span_in_context was called for metrics exemplar context
# with same trace, span ID as trace
mock_set_span.assert_called()
call_args = mock_set_span.call_args
self.assertEqual(len(call_args[0]), 1)
span_arg = call_args[0][0]
self.assertIsNotNone(span_arg)
finished_spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(finished_spans), 1)
finished_span = finished_spans[0]
self.assertEqual(span_arg.context.trace_id, finished_span.context.trace_id)
self.assertEqual(span_arg.context.span_id, finished_span.context.span_id)
def test_duration_histogram_new_record_with_context_new_semconv(self):
with patch("opentelemetry.trace.set_span_in_context") as mock_set_span:
self.client.get("/hello/123")
# Verify that trace.set_span_in_context was called for metrics exemplar context
# with same trace, span ID as trace
mock_set_span.assert_called()
call_args = mock_set_span.call_args
self.assertEqual(len(call_args[0]), 1)
span_arg = call_args[0][0]
self.assertIsNotNone(span_arg)
finished_spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(finished_spans), 1)
finished_span = finished_spans[0]
self.assertEqual(span_arg.context.trace_id, finished_span.context.trace_id)
self.assertEqual(span_arg.context.span_id, finished_span.context.span_id)
def test_active_requests_counter_decremented_on_error(self):
"""Regression test for https://github.com/open-telemetry/opentelemetry-python-contrib/issues/4431.
http.server.active_requests must be decremented even when the view
raises an exception, so it does not permanently leak.
"""
self.client.get("/hello/123")
resp = self.client.get("/hello/500")
self.assertEqual(500, resp.status_code)
metrics_list = self.memory_metrics_reader.get_metrics_data()
active_requests_value = None
for resource_metric in metrics_list.resource_metrics:
for scope_metric in resource_metric.scope_metrics:
for metric in scope_metric.metrics:
if metric.name != "http.server.active_requests":
continue
points = [p.value for p in metric.data.data_points if isinstance(p, NumberDataPoint)]
if points:
active_requests_value = points[-1]
self.assertIsNotNone(
active_requests_value,
"http.server.active_requests metric not found",
)
self.assertEqual(
0,
active_requests_value,
f"active_requests counter leaked: expected 0 but got {active_requests_value}",
)
class TestProgrammaticHooks(InstrumentationTest, WsgiTestBase):
def setUp(self):
super().setUp()
hook_headers = (
"hook_attr",
"hello otel",
)
def request_hook_test(span, environ):
span.update_name("name from hook")
def response_hook_test(span, environ, response_headers):
span.set_attribute("hook_attr", "hello world")
response_headers.append(hook_headers)
self.app = Flask(__name__)
FlaskInstrumentor().instrument_app(
self.app,
request_hook=request_hook_test,
response_hook=response_hook_test,
)
self._common_initialization()
def tearDown(self):
super().tearDown()
with self.disable_logging():
FlaskInstrumentor().uninstrument_app(self.app)
def test_hooks(self):
expected_attrs = expected_attributes(
{
"http.target": "/hello/123",
"http.route": "/hello/",
"hook_attr": "hello world",
}
)
resp = self.client.get("/hello/123")
span_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(span_list), 1)
self.assertEqual(span_list[0].name, "name from hook")
self.assertEqual(span_list[0].attributes, expected_attrs)
self.assertEqual(resp.headers["hook_attr"], "hello otel")
class TestProgrammaticHooksWithoutApp(InstrumentationTest, WsgiTestBase):
def setUp(self):
super().setUp()
hook_headers = (
"hook_attr",
"hello otel without app",
)
def request_hook_test(span, environ):
span.update_name("without app")
def response_hook_test(span, environ, response_headers):
span.set_attribute("hook_attr", "hello world without app")
response_headers.append(hook_headers)
FlaskInstrumentor().instrument(request_hook=request_hook_test, response_hook=response_hook_test)
# pylint: disable=import-outside-toplevel,reimported,redefined-outer-name
from flask import Flask # noqa: PLC0415
self.app = Flask(__name__)
self._common_initialization()
def tearDown(self):
super().tearDown()
with self.disable_logging():
FlaskInstrumentor().uninstrument()
def test_no_app_hooks(self):
expected_attrs = expected_attributes(
{
"http.target": "/hello/123",
"http.route": "/hello/",
"hook_attr": "hello world without app",
}
)
resp = self.client.get("/hello/123")
span_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(span_list), 1)
self.assertEqual(span_list[0].name, "without app")
self.assertEqual(span_list[0].attributes, expected_attrs)
self.assertEqual(resp.headers["hook_attr"], "hello otel without app")
class TestProgrammaticCustomTracerProvider(InstrumentationTest, WsgiTestBase):
def setUp(self):
super().setUp()
resource = Resource.create({"service.name": "flask-api"})
result = self.create_tracer_provider(resource=resource)
tracer_provider, exporter = result
self.memory_exporter = exporter
self.app = Flask(__name__)
FlaskInstrumentor().instrument_app(self.app, tracer_provider=tracer_provider)
self._common_initialization()
def tearDown(self):
super().tearDown()
with self.disable_logging():
FlaskInstrumentor().uninstrument_app(self.app)
def test_custom_span_name(self):
self.client.get("/hello/123")
span_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(span_list), 1)
self.assertEqual(span_list[0].resource.attributes["service.name"], "flask-api")
class TestProgrammaticCustomTracerProviderWithoutApp(InstrumentationTest, WsgiTestBase):
def setUp(self):
super().setUp()
resource = Resource.create({"service.name": "flask-api-no-app"})
result = self.create_tracer_provider(resource=resource)
tracer_provider, exporter = result
self.memory_exporter = exporter
FlaskInstrumentor().instrument(tracer_provider=tracer_provider)
# pylint: disable=import-outside-toplevel,reimported,redefined-outer-name
from flask import Flask # noqa: PLC0415
self.app = Flask(__name__)
self._common_initialization()
def tearDown(self):
super().tearDown()
with self.disable_logging():
FlaskInstrumentor().uninstrument()
def test_custom_span_name(self):
self.client.get("/hello/123")
span_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(span_list), 1)
self.assertEqual(
span_list[0].resource.attributes["service.name"],
"flask-api-no-app",
)
class TestProgrammaticWrappedWithOtherFramework(InstrumentationTest, WsgiTestBase):
def setUp(self):
super().setUp()
self.app = Flask(__name__)
self.app.wsgi_app = OpenTelemetryMiddleware(self.app.wsgi_app)
FlaskInstrumentor().instrument_app(self.app)
self._common_initialization()
def tearDown(self) -> None:
super().tearDown()
with self.disable_logging():
FlaskInstrumentor().uninstrument_app(self.app)
def test_mark_span_internal_in_presence_of_span_from_other_framework(self):
resp = self.client.get("/hello/123")
self.assertEqual(200, resp.status_code)
resp.get_data()
span_list = self.memory_exporter.get_finished_spans()
self.assertEqual(trace.SpanKind.INTERNAL, span_list[0].kind)
self.assertEqual(trace.SpanKind.SERVER, span_list[1].kind)
self.assertEqual(span_list[0].parent.span_id, span_list[1].context.span_id)
@patch.dict(
"os.environ",
{
OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SANITIZE_FIELDS: ".*my-secret.*",
OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_REQUEST: "Custom-Test-Header-1,Custom-Test-Header-2,Custom-Test-Header-3,Regex-Test-Header-.*,Regex-Invalid-Test-Header-.*,.*my-secret.*",
OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_SERVER_RESPONSE: "content-type,content-length,my-custom-header,invalid-header,my-custom-regex-header-.*,invalid-regex-header-.*,.*my-secret.*",
},
)
class TestCustomRequestResponseHeaders(InstrumentationTest, WsgiTestBase):
def setUp(self):
super().setUp()
self.app = Flask(__name__)
FlaskInstrumentor().instrument_app(self.app)
self._common_initialization()
def tearDown(self):
super().tearDown()
with self.disable_logging():
FlaskInstrumentor().uninstrument_app(self.app)
def test_custom_request_header_added_in_server_span(self):
headers = {
"Custom-Test-Header-1": "Test Value 1",
"Custom-Test-Header-2": "TestValue2,TestValue3",
"Regex-Test-Header-1": "Regex Test Value 1",
"regex-test-header-2": "RegexTestValue2,RegexTestValue3",
"My-Secret-Header": "My Secret Value",
}
resp = self.client.get("/hello/123", headers=headers)
self.assertEqual(200, resp.status_code)
span = self.memory_exporter.get_finished_spans()[0]
expected = {
"http.request.header.custom_test_header_1": ("Test Value 1",),
"http.request.header.custom_test_header_2": ("TestValue2,TestValue3",),
"http.request.header.regex_test_header_1": ("Regex Test Value 1",),
"http.request.header.regex_test_header_2": ("RegexTestValue2,RegexTestValue3",),
"http.request.header.my_secret_header": ("[REDACTED]",),
}
self.assertEqual(span.kind, trace.SpanKind.SERVER)
self.assertSpanHasAttributes(span, expected)
def test_repeat_custom_request_header_added_in_server_span(self):
headers = [
("Custom-Test-Header-1", "Test Value 1"),
("Custom-Test-Header-1", "Test Value 2"),
]
resp = self.client.get("/hello/123", headers=headers)
self.assertEqual(200, resp.status_code)
span = self.memory_exporter.get_finished_spans()[0]
expected = {
"http.request.header.custom_test_header_1": ("Test Value 1, Test Value 2",),
}
self.assertEqual(span.kind, trace.SpanKind.SERVER)
self.assertSpanHasAttributes(span, expected)
def test_custom_request_header_not_added_in_internal_span(self):
tracer = trace.get_tracer(__name__)
with tracer.start_as_current_span("test", kind=trace.SpanKind.SERVER):
headers = {
"Custom-Test-Header-1": "Test Value 1",
"Custom-Test-Header-2": "TestValue2,TestValue3",
"Regex-Test-Header-1": "Regex Test Value 1",
"regex-test-header-2": "RegexTestValue2,RegexTestValue3",
"My-Secret-Header": "My Secret Value",
}
resp = self.client.get("/hello/123", headers=headers)
self.assertEqual(200, resp.status_code)
span = self.memory_exporter.get_finished_spans()[0]
not_expected = {
"http.request.header.custom_test_header_1": ("Test Value 1",),
"http.request.header.custom_test_header_2": ("TestValue2,TestValue3",),
"http.request.header.regex_test_header_1": ("Regex Test Value 1",),
"http.request.header.regex_test_header_2": ("RegexTestValue2,RegexTestValue3",),
"http.request.header.my_secret_header": ("[REDACTED]",),
}
self.assertEqual(span.kind, trace.SpanKind.INTERNAL)
for key, _ in not_expected.items():
self.assertNotIn(key, span.attributes)
def test_custom_response_header_added_in_server_span(self):
resp = self.client.get("/test_custom_response_headers")
self.assertEqual(resp.status_code, 200)
span = self.memory_exporter.get_finished_spans()[0]
expected = {
"http.response.header.content_type": ("text/plain; charset=utf-8",),
"http.response.header.content_length": ("13",),
"http.response.header.my_custom_header": ("my-custom-value-1,my-custom-header-2",),
"http.response.header.my_custom_regex_header_1": ("my-custom-regex-value-1,my-custom-regex-value-2",),
"http.response.header.my_custom_regex_header_2": ("my-custom-regex-value-3,my-custom-regex-value-4",),
"http.response.header.my_secret_header": ("[REDACTED]",),
}
self.assertEqual(span.kind, trace.SpanKind.SERVER)
self.assertSpanHasAttributes(span, expected)
def test_repeat_custom_response_header_added_in_server_span(self):
resp = self.client.get("/test_repeat_custom_response_headers")
self.assertEqual(resp.status_code, 200)
span = self.memory_exporter.get_finished_spans()[0]
expected = {
"http.response.header.content_type": ("text/plain; charset=utf-8",),
"http.response.header.my_custom_header": ("my-custom-value-1,my-custom-header-2",),
}
self.assertEqual(span.kind, trace.SpanKind.SERVER)
self.assertSpanHasAttributes(span, expected)
def test_custom_response_header_not_added_in_internal_span(self):
tracer = trace.get_tracer(__name__)
with tracer.start_as_current_span("test", kind=trace.SpanKind.SERVER):
resp = self.client.get("/test_custom_response_headers")
self.assertEqual(resp.status_code, 200)
span = self.memory_exporter.get_finished_spans()[0]
not_expected = {
"http.response.header.content_type": ("text/plain; charset=utf-8",),
"http.response.header.content_length": ("13",),
"http.response.header.my_custom_header": ("my-custom-value-1,my-custom-header-2",),
"http.response.header.my_custom_regex_header_1": ("my-custom-regex-value-1,my-custom-regex-value-2",),
"http.response.header.my_custom_regex_header_2": ("my-custom-regex-value-3,my-custom-regex-value-4",),
"http.response.header.my_secret_header": ("[REDACTED]",),
}
self.assertEqual(span.kind, trace.SpanKind.INTERNAL)
for key, _ in not_expected.items():
self.assertNotIn(key, span.attributes)
test_sqlcommenter.py 0000664 0000000 0000000 00000004343 15270700723 0037454 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-flask/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
import flask
from werkzeug.test import Client
from werkzeug.wrappers import Response
from opentelemetry.instrumentation.flask import FlaskInstrumentor
from opentelemetry.test.wsgitestutil import WsgiTestBase
# pylint: disable=import-error
from .base_test import InstrumentationTest
class TestSQLCommenter(InstrumentationTest, WsgiTestBase):
def setUp(self):
super().setUp()
FlaskInstrumentor().instrument()
self.app = flask.Flask(__name__)
self._common_initialization()
def tearDown(self):
super().tearDown()
with self.disable_logging():
FlaskInstrumentor().uninstrument()
def test_sqlcommenter_enabled_default(self):
self.app = flask.Flask(__name__)
self.app.route("/sqlcommenter")(self._sqlcommenter_endpoint)
client = Client(self.app, Response)
resp = client.get("/sqlcommenter")
self.assertEqual(200, resp.status_code)
self.assertRegex(
list(resp.response)[0].strip(),
b'{"controller":"_sqlcommenter_endpoint","framework":"flask:(.*)","route":"/sqlcommenter"}',
)
def test_sqlcommenter_enabled_with_configurations(self):
FlaskInstrumentor().uninstrument()
FlaskInstrumentor().instrument(enable_commenter=True, commenter_options={"route": False})
self.app = flask.Flask(__name__)
self.app.route("/sqlcommenter")(self._sqlcommenter_endpoint)
client = Client(self.app, Response)
resp = client.get("/sqlcommenter")
self.assertEqual(200, resp.status_code)
self.assertRegex(
list(resp.response)[0].strip(),
b'{"controller":"_sqlcommenter_endpoint","framework":"flask:(.*)"}',
)
def test_sqlcommenter_disabled(self):
FlaskInstrumentor().uninstrument()
FlaskInstrumentor().instrument(enable_commenter=False)
self.app = flask.Flask(__name__)
self.app.route("/sqlcommenter")(self._sqlcommenter_endpoint)
client = Client(self.app, Response)
resp = client.get("/sqlcommenter")
self.assertEqual(200, resp.status_code)
self.assertEqual(list(resp.response)[0].strip(), b"{}")
opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-grpc/ 0000775 0000000 0000000 00000000000 15270700723 0032076 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-grpc/LICENSE 0000664 0000000 0000000 00000026135 15270700723 0033112 0 ustar 00root root 0000000 0000000 Apache License
Version 2.0, January 2004
http://www.apache.org/licenses/
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opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-grpc/README.rst 0000664 0000000 0000000 00000001154 15270700723 0033566 0 ustar 00root root 0000000 0000000 OpenTelemetry gRPC Integration
==============================
|pypi|
.. |pypi| image:: https://badge.fury.io/py/opentelemetry-instrumentation-grpc.svg
:target: https://pypi.org/project/opentelemetry-instrumentation-grpc/
Client and server interceptors for `gRPC Python`_.
.. _gRPC Python: https://grpc.github.io/grpc/python/grpc.html
Installation
------------
::
pip install opentelemetry-instrumentation-grpc
References
----------
* `OpenTelemetry Project `_
* `OpenTelemetry Python Examples `_ pyproject.toml 0000664 0000000 0000000 00000003534 15270700723 0034740 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-grpc [build-system]
requires = ["hatchling"]
build-backend = "hatchling.build"
[project]
name = "opentelemetry-instrumentation-grpc"
dynamic = ["version"]
description = "OpenTelemetry gRPC instrumentation"
readme = "README.rst"
license = "Apache-2.0"
requires-python = ">=3.10"
authors = [
{ name = "OpenTelemetry Authors", email = "cncf-opentelemetry-contributors@lists.cncf.io" },
]
classifiers = [
"Development Status :: 4 - Beta",
"Intended Audience :: Developers",
"License :: OSI Approved :: Apache Software License",
"Programming Language :: Python",
"Programming Language :: Python :: 3",
"Programming Language :: Python :: 3.10",
"Programming Language :: Python :: 3.11",
"Programming Language :: Python :: 3.12",
"Programming Language :: Python :: 3.13",
"Programming Language :: Python :: 3.14",
]
dependencies = [
"opentelemetry-api ~= 1.12",
"opentelemetry-instrumentation == 0.66b2",
"opentelemetry-semantic-conventions == 0.66b2",
"wrapt >= 1.0.0, < 3.0.0",
]
[project.optional-dependencies]
instruments = [
"grpcio >= 1.42.0",
]
[project.entry-points.opentelemetry_instrumentor]
grpc_client = "opentelemetry.instrumentation.grpc:GrpcInstrumentorClient"
grpc_server = "opentelemetry.instrumentation.grpc:GrpcInstrumentorServer"
grpc_aio_client = "opentelemetry.instrumentation.grpc:GrpcAioInstrumentorClient"
grpc_aio_server = "opentelemetry.instrumentation.grpc:GrpcAioInstrumentorServer"
[project.urls]
Homepage = "https://github.com/open-telemetry/opentelemetry-python-contrib/tree/main/instrumentation/opentelemetry-instrumentation-grpc"
Repository = "https://github.com/open-telemetry/opentelemetry-python-contrib"
[tool.hatch.version]
path = "src/opentelemetry/instrumentation/grpc/version.py"
[tool.hatch.build.targets.sdist]
include = [
"/src",
"/tests",
]
[tool.hatch.build.targets.wheel]
packages = ["src/opentelemetry"]
opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-grpc/src/ 0000775 0000000 0000000 00000000000 15270700723 0032665 5 ustar 00root root 0000000 0000000 opentelemetry/ 0000775 0000000 0000000 00000000000 15270700723 0035502 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-grpc/src instrumentation/ 0000775 0000000 0000000 00000000000 15270700723 0040745 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-grpc/src/opentelemetry grpc/ 0000775 0000000 0000000 00000000000 15270700723 0041700 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-grpc/src/opentelemetry/instrumentation __init__.py 0000664 0000000 0000000 00000050605 15270700723 0044017 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-grpc/src/opentelemetry/instrumentation/grpc # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
# pylint:disable=no-name-in-module
# pylint:disable=relative-beyond-top-level
# pylint:disable=import-error
# pylint:disable=no-self-use
"""
Usage Client
------------
.. code-block:: python
import logging
import grpc
from opentelemetry import trace
from opentelemetry.instrumentation.grpc import GrpcInstrumentorClient
from opentelemetry.sdk.trace import TracerProvider
from opentelemetry.sdk.trace.export import (
ConsoleSpanExporter,
SimpleSpanProcessor,
)
try:
from .gen import helloworld_pb2, helloworld_pb2_grpc
except ImportError:
from gen import helloworld_pb2, helloworld_pb2_grpc
trace.set_tracer_provider(TracerProvider())
trace.get_tracer_provider().add_span_processor(SimpleSpanProcessor(ConsoleSpanExporter()))
grpc_client_instrumentor = GrpcInstrumentorClient()
grpc_client_instrumentor.instrument()
def run():
with grpc.insecure_channel("localhost:50051") as channel:
stub = helloworld_pb2_grpc.GreeterStub(channel)
response = stub.SayHello(helloworld_pb2.HelloRequest(name="YOU"))
print("Greeter client received: " + response.message)
if __name__ == "__main__":
logging.basicConfig()
run()
Usage Server
------------
.. code-block:: python
import logging
from concurrent import futures
import grpc
from opentelemetry import trace
from opentelemetry.instrumentation.grpc import GrpcInstrumentorServer
from opentelemetry.sdk.trace import TracerProvider
from opentelemetry.sdk.trace.export import (
ConsoleSpanExporter,
SimpleSpanProcessor,
)
try:
from .gen import helloworld_pb2, helloworld_pb2_grpc
except ImportError:
from gen import helloworld_pb2, helloworld_pb2_grpc
trace.set_tracer_provider(TracerProvider())
trace.get_tracer_provider().add_span_processor(SimpleSpanProcessor(ConsoleSpanExporter()))
grpc_server_instrumentor = GrpcInstrumentorServer()
grpc_server_instrumentor.instrument()
class Greeter(helloworld_pb2_grpc.GreeterServicer):
def SayHello(self, request, context):
return helloworld_pb2.HelloReply(message="Hello, %s!" % request.name)
def serve():
server = grpc.server(futures.ThreadPoolExecutor())
helloworld_pb2_grpc.add_GreeterServicer_to_server(Greeter(), server)
server.add_insecure_port("[::]:50051")
server.start()
server.wait_for_termination()
if __name__ == "__main__":
logging.basicConfig()
serve()
You can also add the interceptor manually, rather than using
:py:class:`~opentelemetry.instrumentation.grpc.GrpcInstrumentorServer`:
.. code-block:: python
from opentelemetry.instrumentation.grpc import server_interceptor
server = grpc.server(futures.ThreadPoolExecutor(), interceptors=[server_interceptor()])
Usage Aio Client
----------------
.. code-block:: python
import logging
import asyncio
import grpc
from opentelemetry import trace
from opentelemetry.instrumentation.grpc import GrpcAioInstrumentorClient
from opentelemetry.sdk.trace import TracerProvider
from opentelemetry.sdk.trace.export import (
ConsoleSpanExporter,
SimpleSpanProcessor,
)
try:
from .gen import helloworld_pb2, helloworld_pb2_grpc
except ImportError:
from gen import helloworld_pb2, helloworld_pb2_grpc
trace.set_tracer_provider(TracerProvider())
trace.get_tracer_provider().add_span_processor(SimpleSpanProcessor(ConsoleSpanExporter()))
grpc_client_instrumentor = GrpcAioInstrumentorClient()
grpc_client_instrumentor.instrument()
async def run():
async with grpc.aio.insecure_channel("localhost:50051") as channel:
stub = helloworld_pb2_grpc.GreeterStub(channel)
response = await stub.SayHello(helloworld_pb2.HelloRequest(name="YOU"))
print("Greeter client received: " + response.message)
if __name__ == "__main__":
logging.basicConfig()
asyncio.run(run())
You can also add the interceptor manually, rather than using
:py:class:`~opentelemetry.instrumentation.grpc.GrpcAioInstrumentorClient`:
.. code-block:: python
from opentelemetry.instrumentation.grpc import aio_client_interceptors
async with grpc.aio.insecure_channel("localhost:50051", interceptors=aio_client_interceptors()) as channel:
Usage Aio Server
----------------
.. code-block:: python
import logging
import asyncio
import grpc
from opentelemetry import trace
from opentelemetry.instrumentation.grpc import GrpcAioInstrumentorServer
from opentelemetry.sdk.trace import TracerProvider
from opentelemetry.sdk.trace.export import (
ConsoleSpanExporter,
SimpleSpanProcessor,
)
try:
from .gen import helloworld_pb2, helloworld_pb2_grpc
except ImportError:
from gen import helloworld_pb2, helloworld_pb2_grpc
trace.set_tracer_provider(TracerProvider())
trace.get_tracer_provider().add_span_processor(SimpleSpanProcessor(ConsoleSpanExporter()))
grpc_server_instrumentor = GrpcAioInstrumentorServer()
grpc_server_instrumentor.instrument()
class Greeter(helloworld_pb2_grpc.GreeterServicer):
async def SayHello(self, request, context):
return helloworld_pb2.HelloReply(message="Hello, %s!" % request.name)
async def serve():
server = grpc.aio.server()
helloworld_pb2_grpc.add_GreeterServicer_to_server(Greeter(), server)
server.add_insecure_port("[::]:50051")
await server.start()
await server.wait_for_termination()
if __name__ == "__main__":
logging.basicConfig()
asyncio.run(serve())
You can also add the interceptor manually, rather than using
:py:class:`~opentelemetry.instrumentation.grpc.GrpcAioInstrumentorServer`:
.. code-block:: python
from opentelemetry.instrumentation.grpc import aio_server_interceptor
server = grpc.aio.server(interceptors=[aio_server_interceptor()])
Filters
-------
If you prefer to filter specific requests to be instrumented, you can specify
the condition by assigning filters to instrumentors.
You can write a global server instrumentor as follows:
.. code-block::
from opentelemetry.instrumentation.grpc import filters, GrpcInstrumentorServer
grpc_server_instrumentor = GrpcInstrumentorServer(
filter_ = filters.any_of(
filters.method_name("SimpleMethod"),
filters.method_name("ComplexMethod"),
)
)
grpc_server_instrumentor.instrument()
You can also use the filters directly on the provided interceptors:
.. code-block::
import grpc
from concurrent import futures
from opentelemetry.instrumentation.grpc import filters
from opentelemetry.instrumentation.grpc import server_interceptor
my_interceptor = server_interceptor(
filter_ = filters.negate(filters.method_name("TestMethod"))
)
server = grpc.server(futures.ThreadPoolExecutor(),
interceptors = [my_interceptor])
``filter_`` option also applies to both global and manual client intrumentors.
Environment variable
--------------------
If you'd like to exclude specific services for the instrumentations, you can use
``OTEL_PYTHON_GRPC_EXCLUDED_SERVICES`` environment variables.
For example, if you assign ``"GRPCTestServer,GRPCHealthServer"`` to the variable,
then the global interceptor automatically adds the filters to exclude requests to
services ``GRPCTestServer`` and ``GRPCHealthServer``.
"""
import os
from collections.abc import Callable, Collection
import grpc # pylint:disable=import-self
from wrapt import wrap_function_wrapper as _wrap
from opentelemetry import trace
from opentelemetry.instrumentation.grpc.filters import (
any_of,
negate,
service_name,
)
from opentelemetry.instrumentation.grpc.grpcext import intercept_channel
from opentelemetry.instrumentation.grpc.package import _instruments
from opentelemetry.instrumentation.grpc.version import __version__
from opentelemetry.instrumentation.instrumentor import BaseInstrumentor
from opentelemetry.instrumentation.utils import unwrap
# pylint:disable=import-outside-toplevel
# pylint:disable=import-self
# pylint:disable=unused-argument
class GrpcInstrumentorServer(BaseInstrumentor):
"""
Globally instrument the grpc server.
Usage::
grpc_server_instrumentor = GrpcInstrumentorServer()
grpc_server_instrumentor.instrument()
If you want to add a filter that only intercept requests
to match the condition, pass ``filter_`` to GrpcInstrumentorServer.
grpc_server_instrumentor = GrpcInstrumentorServer(
filter_=filters.method_prefix("SimpleMethod"))
grpc_server_instrumentor.instrument()
"""
# pylint:disable=redefined-outer-name
def __init__(self, filter_=None):
excluded_service_filter = _excluded_service_filter()
if excluded_service_filter is not None:
if filter_ is None:
filter_ = excluded_service_filter
else:
filter_ = any_of(filter_, excluded_service_filter)
self._filter = filter_
def instrumentation_dependencies(self) -> Collection[str]:
return _instruments
def _instrument(self, **kwargs):
self._original_func = grpc.server
tracer_provider = kwargs.get("tracer_provider")
def server(*args, **kwargs):
if kwargs.get("interceptors"):
kwargs["interceptors"] = list(kwargs["interceptors"])
# add our interceptor as the first
kwargs["interceptors"].insert(
0,
server_interceptor(tracer_provider=tracer_provider, filter_=self._filter),
)
else:
kwargs["interceptors"] = [server_interceptor(tracer_provider=tracer_provider, filter_=self._filter)]
return self._original_func(*args, **kwargs)
grpc.server = server
def _uninstrument(self, **kwargs):
grpc.server = self._original_func
class GrpcAioInstrumentorServer(BaseInstrumentor):
"""
Globally instrument the grpc.aio server.
Usage::
grpc_aio_server_instrumentor = GrpcAioInstrumentorServer()
grpc_aio_server_instrumentor.instrument()
"""
# pylint:disable=redefined-outer-name
def __init__(self, filter_=None):
excluded_service_filter = _excluded_service_filter()
if excluded_service_filter is not None:
if filter_ is None:
filter_ = excluded_service_filter
else:
filter_ = any_of(filter_, excluded_service_filter)
self._filter = filter_
def instrumentation_dependencies(self) -> Collection[str]:
return _instruments
def _instrument(self, **kwargs):
self._original_func = grpc.aio.server
tracer_provider = kwargs.get("tracer_provider")
def server(*args, **kwargs):
if kwargs.get("interceptors"):
kwargs["interceptors"] = list(kwargs["interceptors"])
# add our interceptor as the first
kwargs["interceptors"].insert(
0,
aio_server_interceptor(tracer_provider=tracer_provider, filter_=self._filter),
)
else:
kwargs["interceptors"] = [aio_server_interceptor(tracer_provider=tracer_provider, filter_=self._filter)]
return self._original_func(*args, **kwargs)
grpc.aio.server = server
def _uninstrument(self, **kwargs):
grpc.aio.server = self._original_func
class GrpcInstrumentorClient(BaseInstrumentor):
"""
Globally instrument the grpc client
Usage::
grpc_client_instrumentor = GrpcInstrumentorClient()
grpc_client_instrumentor.instrument()
If you want to add a filter that only intercept requests
to match the condition, pass ``filter_`` option to GrpcInstrumentorClient.
grpc_client_instrumentor = GrpcInstrumentorClient(
filter_=filters.negate(filters.health_check())
)
grpc_client_instrumentor.instrument()
"""
def __init__(self, filter_=None):
excluded_service_filter = _excluded_service_filter()
if excluded_service_filter is not None:
if filter_ is None:
filter_ = excluded_service_filter
else:
filter_ = any_of(filter_, excluded_service_filter)
self._filter = filter_
self._request_hook = None
self._response_hook = None
# Figures out which channel type we need to wrap
def _which_channel(self, kwargs):
# handle legacy argument
if "channel_type" in kwargs:
if kwargs.get("channel_type") == "secure":
return ("secure_channel",)
return ("insecure_channel",)
# handle modern arguments
types = []
for ctype in ("secure_channel", "insecure_channel"):
if kwargs.get(ctype, True):
types.append(ctype)
return tuple(types)
def instrumentation_dependencies(self) -> Collection[str]:
return _instruments
def _instrument(self, **kwargs):
self._request_hook = kwargs.get("request_hook")
self._response_hook = kwargs.get("response_hook")
for ctype in self._which_channel(kwargs):
_wrap(
"grpc",
ctype,
self.wrapper_fn,
)
def _uninstrument(self, **kwargs):
for ctype in self._which_channel(kwargs):
unwrap(grpc, ctype)
def wrapper_fn(self, original_func, instance, args, kwargs):
channel = original_func(*args, **kwargs)
tracer_provider = kwargs.get("tracer_provider")
request_hook = self._request_hook
response_hook = self._response_hook
return intercept_channel(
channel,
client_interceptor(
tracer_provider=tracer_provider,
filter_=self._filter,
request_hook=request_hook,
response_hook=response_hook,
),
)
class GrpcAioInstrumentorClient(BaseInstrumentor):
"""
Globally instrument the grpc.aio client.
Usage::
grpc_aio_client_instrumentor = GrpcAioInstrumentorClient()
grpc_aio_client_instrumentor.instrument()
"""
# pylint:disable=redefined-outer-name
def __init__(self, filter_=None):
excluded_service_filter = _excluded_service_filter()
if excluded_service_filter is not None:
if filter_ is None:
filter_ = excluded_service_filter
else:
filter_ = any_of(filter_, excluded_service_filter)
self._filter = filter_
self._request_hook = None
self._response_hook = None
def instrumentation_dependencies(self) -> Collection[str]:
return _instruments
def _add_interceptors(self, tracer_provider, kwargs):
if kwargs.get("interceptors"):
kwargs["interceptors"] = list(kwargs["interceptors"])
kwargs["interceptors"] = (
aio_client_interceptors(
tracer_provider=tracer_provider,
filter_=self._filter,
request_hook=self._request_hook,
response_hook=self._response_hook,
)
+ kwargs["interceptors"]
)
else:
kwargs["interceptors"] = aio_client_interceptors(
tracer_provider=tracer_provider,
filter_=self._filter,
request_hook=self._request_hook,
response_hook=self._response_hook,
)
return kwargs
def _instrument(self, **kwargs):
self._original_insecure = grpc.aio.insecure_channel
self._original_secure = grpc.aio.secure_channel
self._request_hook = kwargs.get("request_hook")
self._response_hook = kwargs.get("response_hook")
tracer_provider = kwargs.get("tracer_provider")
def insecure(*args, **kwargs):
kwargs = self._add_interceptors(tracer_provider, kwargs)
return self._original_insecure(*args, **kwargs)
def secure(*args, **kwargs):
kwargs = self._add_interceptors(tracer_provider, kwargs)
return self._original_secure(*args, **kwargs)
grpc.aio.insecure_channel = insecure
grpc.aio.secure_channel = secure
def _uninstrument(self, **kwargs):
grpc.aio.insecure_channel = self._original_insecure
grpc.aio.secure_channel = self._original_secure
def client_interceptor(tracer_provider=None, filter_=None, request_hook=None, response_hook=None):
"""Create a gRPC client channel interceptor.
Args:
tracer: The tracer to use to create client-side spans.
filter_: filter function that returns True if gRPC requests
matches the condition. Default is None and intercept
all requests.
Returns:
An invocation-side interceptor object.
"""
from . import _client # noqa: PLC0415
tracer = trace.get_tracer(
__name__,
__version__,
tracer_provider,
schema_url="https://opentelemetry.io/schemas/1.11.0",
)
return _client.OpenTelemetryClientInterceptor(
tracer,
filter_=filter_,
request_hook=request_hook,
response_hook=response_hook,
)
def server_interceptor(tracer_provider=None, filter_=None):
"""Create a gRPC server interceptor.
Args:
tracer: The tracer to use to create server-side spans.
filter_: filter function that returns True if gRPC requests
matches the condition. Default is None and intercept
all requests.
Returns:
A service-side interceptor object.
"""
from . import _server # noqa: PLC0415
tracer = trace.get_tracer(
__name__,
__version__,
tracer_provider,
schema_url="https://opentelemetry.io/schemas/1.11.0",
)
return _server.OpenTelemetryServerInterceptor(tracer, filter_=filter_)
def aio_client_interceptors(tracer_provider=None, filter_=None, request_hook=None, response_hook=None):
"""Create a gRPC client channel interceptor.
Args:
tracer: The tracer to use to create client-side spans.
Returns:
An invocation-side interceptor object.
"""
from . import _aio_client # noqa: PLC0415
tracer = trace.get_tracer(
__name__,
__version__,
tracer_provider,
schema_url="https://opentelemetry.io/schemas/1.11.0",
)
return [
_aio_client.UnaryUnaryAioClientInterceptor(
tracer,
filter_=filter_,
request_hook=request_hook,
response_hook=response_hook,
),
_aio_client.UnaryStreamAioClientInterceptor(
tracer,
filter_=filter_,
request_hook=request_hook,
response_hook=response_hook,
),
_aio_client.StreamUnaryAioClientInterceptor(
tracer,
filter_=filter_,
request_hook=request_hook,
response_hook=response_hook,
),
_aio_client.StreamStreamAioClientInterceptor(
tracer,
filter_=filter_,
request_hook=request_hook,
response_hook=response_hook,
),
]
def aio_server_interceptor(tracer_provider=None, filter_=None):
"""Create a gRPC aio server interceptor.
Args:
tracer: The tracer to use to create server-side spans.
Returns:
A service-side interceptor object.
"""
from . import _aio_server # noqa: PLC0415
tracer = trace.get_tracer(
__name__,
__version__,
tracer_provider,
schema_url="https://opentelemetry.io/schemas/1.11.0",
)
return _aio_server.OpenTelemetryAioServerInterceptor(tracer, filter_=filter_)
def _excluded_service_filter() -> Callable[[object], bool] | None:
services = _parse_services(os.environ.get("OTEL_PYTHON_GRPC_EXCLUDED_SERVICES", ""))
if len(services) == 0:
return None
filters = (service_name(srv) for srv in services)
return negate(any_of(*filters))
def _parse_services(excluded_services: str) -> list[str]:
if excluded_services != "":
excluded_service_list = [s.strip() for s in excluded_services.split(",")]
else:
excluded_service_list = []
return excluded_service_list
_aio_client.py 0000664 0000000 0000000 00000016507 15270700723 0044530 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-grpc/src/opentelemetry/instrumentation/grpc # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
import functools
import logging
import grpc
from grpc.aio import ClientCallDetails, Metadata
from opentelemetry.instrumentation.grpc._client import (
OpenTelemetryClientInterceptor,
_carrier_setter,
)
from opentelemetry.instrumentation.utils import is_instrumentation_enabled
from opentelemetry.propagate import inject
from opentelemetry.semconv._incubating.attributes.rpc_attributes import (
RPC_GRPC_STATUS_CODE,
)
from opentelemetry.trace.status import Status, StatusCode
logger = logging.getLogger(__name__)
def _unary_done_callback(span, code, details, response_hook):
def callback(call):
try:
span.set_attribute(
RPC_GRPC_STATUS_CODE,
code.value[0],
)
if code != grpc.StatusCode.OK:
span.set_status(
Status(
status_code=StatusCode.ERROR,
description=details,
)
)
response_hook(span, details)
finally:
span.end()
return callback
class _BaseAioClientInterceptor(OpenTelemetryClientInterceptor):
@staticmethod
def propagate_trace_in_details(client_call_details: ClientCallDetails):
metadata = client_call_details.metadata
if not metadata:
mutable_metadata = Metadata()
else:
mutable_metadata = Metadata(*tuple(metadata))
inject(mutable_metadata, setter=_carrier_setter)
return ClientCallDetails(
client_call_details.method,
client_call_details.timeout,
mutable_metadata,
client_call_details.credentials,
client_call_details.wait_for_ready,
)
@staticmethod
def add_error_details_to_span(span, exc):
if isinstance(exc, grpc.RpcError):
span.set_attribute(
RPC_GRPC_STATUS_CODE,
exc.code().value[0],
)
span.set_status(
Status(
status_code=StatusCode.ERROR,
description=f"{type(exc).__name__}: {exc}",
)
)
span.record_exception(exc)
def _start_interceptor_span(self, method):
# method _should_ be a string here but due to a bug in grpc, it is
# populated with a bytes object. Handle both cases such that we
# are forward-compatible with a fixed version of grpc
# More info: https://github.com/grpc/grpc/issues/31092
if isinstance(method, bytes):
method = method.decode()
return self._start_span(
method,
end_on_exit=False,
record_exception=False,
set_status_on_exception=False,
)
async def _wrap_unary_response(self, continuation, span):
try:
call = await continuation()
# code and details are both coroutines that need to be await-ed,
# the callbacks added with add_done_callback do not allow async
# code so we need to get the code and details here then pass them
# to the callback.
code = await call.code()
details = await call.details()
callback = _unary_done_callback(span, code, details, self._call_response_hook)
try:
call.add_done_callback(callback)
except NotImplementedError:
# Some grpc.aio interceptors (e.g. interceptors that await the
# call object) wrap the call in a type that does not implement
# add_done_callback. In that case call the callback immediately
# since code and details are already known.
callback(call)
return call
except grpc.aio.AioRpcError as exc:
self.add_error_details_to_span(span, exc)
raise exc
async def _wrap_stream_response(self, span, call):
try:
async for response in call:
if self._response_hook:
self._call_response_hook(span, response)
yield response
except Exception as exc:
self.add_error_details_to_span(span, exc)
raise exc
finally:
span.end()
def tracing_skipped(self, client_call_details):
return not is_instrumentation_enabled() or not self.rpc_matches_filters(client_call_details)
def rpc_matches_filters(self, client_call_details):
return self._filter is None or self._filter(client_call_details)
class UnaryUnaryAioClientInterceptor(
grpc.aio.UnaryUnaryClientInterceptor,
_BaseAioClientInterceptor,
):
async def intercept_unary_unary(self, continuation, client_call_details, request):
if self.tracing_skipped(client_call_details):
return await continuation(client_call_details, request)
with self._start_interceptor_span(
client_call_details.method,
) as span:
new_details = self.propagate_trace_in_details(client_call_details)
if self._request_hook:
self._call_request_hook(span, request)
continuation_with_args = functools.partial(continuation, new_details, request)
return await self._wrap_unary_response(continuation_with_args, span)
class UnaryStreamAioClientInterceptor(
grpc.aio.UnaryStreamClientInterceptor,
_BaseAioClientInterceptor,
):
async def intercept_unary_stream(self, continuation, client_call_details, request):
if self.tracing_skipped(client_call_details):
return await continuation(client_call_details, request)
with self._start_interceptor_span(
client_call_details.method,
) as span:
new_details = self.propagate_trace_in_details(client_call_details)
resp = await continuation(new_details, request)
if self._request_hook:
self._call_request_hook(span, request)
return self._wrap_stream_response(span, resp)
class StreamUnaryAioClientInterceptor(
grpc.aio.StreamUnaryClientInterceptor,
_BaseAioClientInterceptor,
):
async def intercept_stream_unary(self, continuation, client_call_details, request_iterator):
if self.tracing_skipped(client_call_details):
return await continuation(client_call_details, request_iterator)
with self._start_interceptor_span(
client_call_details.method,
) as span:
new_details = self.propagate_trace_in_details(client_call_details)
continuation_with_args = functools.partial(continuation, new_details, request_iterator)
return await self._wrap_unary_response(continuation_with_args, span)
class StreamStreamAioClientInterceptor(
grpc.aio.StreamStreamClientInterceptor,
_BaseAioClientInterceptor,
):
async def intercept_stream_stream(self, continuation, client_call_details, request_iterator):
if self.tracing_skipped(client_call_details):
return await continuation(client_call_details, request_iterator)
with self._start_interceptor_span(
client_call_details.method,
) as span:
new_details = self.propagate_trace_in_details(client_call_details)
resp = await continuation(new_details, request_iterator)
return self._wrap_stream_response(span, resp)
_aio_server.py 0000664 0000000 0000000 00000012477 15270700723 0044562 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-grpc/src/opentelemetry/instrumentation/grpc # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
import grpc
import grpc.aio
try:
# wrapt 2.0.0+
from wrapt import BaseObjectProxy # pylint: disable=no-name-in-module
except ImportError:
from wrapt import ObjectProxy as BaseObjectProxy
from opentelemetry.instrumentation.utils import is_instrumentation_enabled
from opentelemetry.semconv._incubating.attributes.rpc_attributes import (
RPC_GRPC_STATUS_CODE,
)
from ._server import OpenTelemetryServerInterceptor, _wrap_rpc_behavior
from ._utilities import _server_status
# pylint:disable=abstract-method,no-member
class _OpenTelemetryAioServicerContext(BaseObjectProxy):
def __init__(self, servicer_context, active_span):
super().__init__(servicer_context)
self._self_active_span = active_span
self._self_code = grpc.StatusCode.OK
self._self_details = None
async def abort(self, code, details="", trailing_metadata=tuple()):
self._self_code = code
self._self_details = details
self._self_active_span.set_attribute(RPC_GRPC_STATUS_CODE, code.value[0])
status = _server_status(code, details)
self._self_active_span.set_status(status)
return await self.__wrapped__.abort(code, details, trailing_metadata)
def set_code(self, code):
self._self_code = code
details = self._self_details or code.value[1]
self._self_active_span.set_attribute(RPC_GRPC_STATUS_CODE, code.value[0])
if code != grpc.StatusCode.OK:
status = _server_status(code, details)
self._self_active_span.set_status(status)
return self.__wrapped__.set_code(code)
def set_details(self, details):
self._self_details = details
if self._self_code != grpc.StatusCode.OK:
status = _server_status(self._self_code, details)
self._self_active_span.set_status(status)
return self.__wrapped__.set_details(details)
class OpenTelemetryAioServerInterceptor(grpc.aio.ServerInterceptor, OpenTelemetryServerInterceptor):
"""
An AsyncIO gRPC server interceptor, to add OpenTelemetry.
Usage::
tracer = some OpenTelemetry tracer
interceptors = [
AsyncOpenTelemetryServerInterceptor(tracer),
]
server = aio.server(
futures.ThreadPoolExecutor(max_workers=concurrency),
interceptors = (interceptors,))
"""
async def intercept_service(self, continuation, handler_call_details):
if not is_instrumentation_enabled():
return await continuation(handler_call_details)
if self._filter is not None and not self._filter(handler_call_details):
return await continuation(handler_call_details)
def telemetry_wrapper(behavior, request_streaming, response_streaming):
# handle streaming responses specially
if response_streaming:
return self._intercept_aio_server_stream(
behavior,
handler_call_details,
)
return self._intercept_aio_server_unary(
behavior,
handler_call_details,
)
next_handler = await continuation(handler_call_details)
return _wrap_rpc_behavior(next_handler, telemetry_wrapper)
def _intercept_aio_server_unary(self, behavior, handler_call_details):
async def _unary_interceptor(request_or_iterator, context):
with self._set_remote_context(context):
with self._start_span(
handler_call_details,
context,
set_status_on_exception=False,
) as span:
# wrap the context
context = _OpenTelemetryAioServicerContext(context, span)
# And now we run the actual RPC.
try:
return await behavior(request_or_iterator, context)
except Exception as error:
# Bare exceptions are likely to be gRPC aborts, which
# we handle in our context wrapper.
# Here, we're interested in uncaught exceptions.
# pylint:disable=unidiomatic-typecheck
if type(error) != Exception: # noqa: E721
span.record_exception(error)
raise error
return _unary_interceptor
def _intercept_aio_server_stream(self, behavior, handler_call_details):
async def _stream_interceptor(request_or_iterator, context):
with self._set_remote_context(context):
with self._start_span(
handler_call_details,
context,
set_status_on_exception=False,
) as span:
context = _OpenTelemetryAioServicerContext(context, span)
try:
async for response in behavior(request_or_iterator, context):
yield response
except Exception as error:
# pylint:disable=unidiomatic-typecheck
if type(error) != Exception: # noqa: E721
span.record_exception(error)
raise error
return _stream_interceptor
_client.py 0000664 0000000 0000000 00000017523 15270700723 0043677 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-grpc/src/opentelemetry/instrumentation/grpc # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
# pylint:disable=relative-beyond-top-level
# pylint:disable=arguments-differ
# pylint:disable=no-member
# pylint:disable=signature-differs
"""Implementation of the invocation-side open-telemetry interceptor."""
import logging
from collections import OrderedDict
from collections.abc import Callable, MutableMapping
import grpc
from opentelemetry import trace
from opentelemetry.instrumentation.grpc import grpcext
from opentelemetry.instrumentation.grpc._utilities import RpcInfo
from opentelemetry.instrumentation.utils import is_instrumentation_enabled
from opentelemetry.propagate import inject
from opentelemetry.propagators.textmap import Setter
from opentelemetry.semconv._incubating.attributes.rpc_attributes import (
RPC_GRPC_STATUS_CODE,
RPC_METHOD,
RPC_SERVICE,
RPC_SYSTEM,
)
from opentelemetry.trace.status import Status, StatusCode
logger = logging.getLogger(__name__)
class _CarrierSetter(Setter):
"""We use a custom setter in order to be able to lower case
keys as is required by grpc.
"""
def set(self, carrier: MutableMapping[str, str], key: str, value: str):
carrier[key.lower()] = value
_carrier_setter = _CarrierSetter()
def _make_future_done_callback(span, rpc_info):
def callback(response_future):
with trace.use_span(span, end_on_exit=True):
code = response_future.code()
if code != grpc.StatusCode.OK:
rpc_info.error = code
span.set_attribute(RPC_GRPC_STATUS_CODE, code.value[0])
span.set_status(
Status(
status_code=StatusCode.ERROR,
)
)
return
response = response_future.result()
rpc_info.response = response
return callback
def _safe_invoke(function: Callable, *args):
function_name = ""
try:
function_name = function.__name__
function(*args)
except Exception as ex: # pylint:disable=broad-except
logger.error("Error when invoking function '%s'", function_name, exc_info=ex)
class OpenTelemetryClientInterceptor(grpcext.UnaryClientInterceptor, grpcext.StreamClientInterceptor):
def __init__(self, tracer, filter_=None, request_hook=None, response_hook=None):
self._tracer = tracer
self._filter = filter_
self._request_hook = request_hook
self._response_hook = response_hook
def _start_span(self, method, **kwargs):
service, meth = method.lstrip("/").split("/", 1)
attributes = {
RPC_SYSTEM: "grpc",
RPC_GRPC_STATUS_CODE: grpc.StatusCode.OK.value[0],
RPC_METHOD: meth,
RPC_SERVICE: service,
}
return self._tracer.start_as_current_span(
name=method,
kind=trace.SpanKind.CLIENT,
attributes=attributes,
**kwargs,
)
# pylint:disable=no-self-use
def _trace_result(self, span, rpc_info, result):
# If the RPC is called asynchronously, add a callback to end the span
# when the future is done, else end the span immediately
if isinstance(result, grpc.Future):
result.add_done_callback(_make_future_done_callback(span, rpc_info))
return result
response = result
# Handle the case when the RPC is initiated via the with_call
# method and the result is a tuple with the first element as the
# response.
# http://www.grpc.io/grpc/python/grpc.html#grpc.UnaryUnaryMultiCallable.with_call
if isinstance(result, tuple):
response = result[0]
rpc_info.response = response
if self._response_hook:
self._call_response_hook(span, response)
span.end()
return result
def _intercept(self, request, metadata, client_info, invoker):
if not is_instrumentation_enabled():
return invoker(request, metadata)
if not metadata:
mutable_metadata = OrderedDict()
else:
mutable_metadata = OrderedDict(metadata)
with self._start_span(
client_info.full_method,
end_on_exit=False,
record_exception=False,
set_status_on_exception=False,
) as span:
result = None
try:
inject(mutable_metadata, setter=_carrier_setter)
metadata = tuple(mutable_metadata.items())
rpc_info = RpcInfo(
full_method=client_info.full_method,
metadata=metadata,
timeout=client_info.timeout,
request=request,
)
if self._request_hook:
self._call_request_hook(span, request)
result = invoker(request, metadata)
except Exception as exc:
if isinstance(exc, grpc.RpcError):
span.set_attribute(
RPC_GRPC_STATUS_CODE,
exc.code().value[0],
)
span.set_status(
Status(
status_code=StatusCode.ERROR,
description=f"{type(exc).__name__}: {exc}",
)
)
span.record_exception(exc)
raise exc
finally:
if result is None:
span.end()
return self._trace_result(span, rpc_info, result)
def _call_request_hook(self, span, request):
if not callable(self._request_hook):
return
_safe_invoke(self._request_hook, span, request)
def _call_response_hook(self, span, response):
if not callable(self._response_hook):
return
_safe_invoke(self._response_hook, span, response)
def intercept_unary(self, request, metadata, client_info, invoker):
if self._filter is not None and not self._filter(client_info):
return invoker(request, metadata)
return self._intercept(request, metadata, client_info, invoker)
# For RPCs that stream responses, the result can be a generator. To record
# the span across the generated responses and detect any errors, we wrap
# the result in a new generator that yields the response values.
def _intercept_server_stream(self, request_or_iterator, metadata, client_info, invoker):
if not metadata:
mutable_metadata = OrderedDict()
else:
mutable_metadata = OrderedDict(metadata)
with self._start_span(client_info.full_method) as span:
inject(mutable_metadata, setter=_carrier_setter)
metadata = tuple(mutable_metadata.items())
rpc_info = RpcInfo(
full_method=client_info.full_method,
metadata=metadata,
timeout=client_info.timeout,
)
if client_info.is_client_stream:
rpc_info.request = request_or_iterator
try:
yield from invoker(request_or_iterator, metadata)
except grpc.RpcError as err:
span.set_status(Status(StatusCode.ERROR))
span.set_attribute(RPC_GRPC_STATUS_CODE, err.code().value[0])
raise err
def intercept_stream(self, request_or_iterator, metadata, client_info, invoker):
if not is_instrumentation_enabled():
return invoker(request_or_iterator, metadata)
if self._filter is not None and not self._filter(client_info):
return invoker(request_or_iterator, metadata)
if client_info.is_server_stream and not client_info.is_client_stream:
return self._intercept_server_stream(request_or_iterator, metadata, client_info, invoker)
return self._intercept(request_or_iterator, metadata, client_info, invoker)
_server.py 0000664 0000000 0000000 00000026232 15270700723 0043724 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-grpc/src/opentelemetry/instrumentation/grpc # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
# pylint:disable=relative-beyond-top-level
# pylint:disable=arguments-differ
# pylint:disable=no-member
# pylint:disable=signature-differs
"""
Implementation of the service-side open-telemetry interceptor.
"""
import logging
from contextlib import contextmanager
from urllib.parse import unquote
import grpc
from opentelemetry import trace
from opentelemetry.context import attach, detach
from opentelemetry.instrumentation.utils import is_instrumentation_enabled
from opentelemetry.propagate import extract
from opentelemetry.semconv._incubating.attributes.net_attributes import (
NET_PEER_IP,
NET_PEER_NAME,
NET_PEER_PORT,
)
from opentelemetry.semconv._incubating.attributes.rpc_attributes import (
RPC_GRPC_STATUS_CODE,
RPC_METHOD,
RPC_SERVICE,
RPC_SYSTEM,
)
from ._utilities import _server_status
logger = logging.getLogger(__name__)
# wrap an RPC call
# see https://github.com/grpc/grpc/issues/18191
def _wrap_rpc_behavior(handler, continuation):
if handler is None:
return None
if handler.request_streaming and handler.response_streaming:
behavior_fn = handler.stream_stream
handler_factory = grpc.stream_stream_rpc_method_handler
elif handler.request_streaming and not handler.response_streaming:
behavior_fn = handler.stream_unary
handler_factory = grpc.stream_unary_rpc_method_handler
elif not handler.request_streaming and handler.response_streaming:
behavior_fn = handler.unary_stream
handler_factory = grpc.unary_stream_rpc_method_handler
else:
behavior_fn = handler.unary_unary
handler_factory = grpc.unary_unary_rpc_method_handler
return handler_factory(
continuation(behavior_fn, handler.request_streaming, handler.response_streaming),
request_deserializer=handler.request_deserializer,
response_serializer=handler.response_serializer,
)
# pylint:disable=abstract-method
class _OpenTelemetryServicerContext(grpc.ServicerContext):
def __init__(self, servicer_context, active_span):
self._servicer_context = servicer_context
self._active_span = active_span
self._code = grpc.StatusCode.OK
self._details = None
super().__init__()
def __getattr__(self, attr):
return getattr(self._servicer_context, attr)
def is_active(self, *args, **kwargs):
return self._servicer_context.is_active(*args, **kwargs)
def time_remaining(self, *args, **kwargs):
return self._servicer_context.time_remaining(*args, **kwargs)
def cancel(self, *args, **kwargs):
return self._servicer_context.cancel(*args, **kwargs)
def add_callback(self, *args, **kwargs):
return self._servicer_context.add_callback(*args, **kwargs)
def disable_next_message_compression(self):
return self._service_context.disable_next_message_compression()
def invocation_metadata(self, *args, **kwargs):
return self._servicer_context.invocation_metadata(*args, **kwargs)
def peer(self):
return self._servicer_context.peer()
def peer_identities(self):
return self._servicer_context.peer_identities()
def peer_identity_key(self):
return self._servicer_context.peer_identity_key()
def auth_context(self):
return self._servicer_context.auth_context()
def set_compression(self, compression):
return self._servicer_context.set_compression(compression)
def send_initial_metadata(self, *args, **kwargs):
return self._servicer_context.send_initial_metadata(*args, **kwargs)
def set_trailing_metadata(self, *args, **kwargs):
return self._servicer_context.set_trailing_metadata(*args, **kwargs)
def trailing_metadata(self):
return self._servicer_context.trailing_metadata()
def abort(self, code, details):
self._code = code
self._details = details
self._active_span.set_attribute(RPC_GRPC_STATUS_CODE, code.value[0])
status = _server_status(code, details)
self._active_span.set_status(status)
return self._servicer_context.abort(code, details)
def abort_with_status(self, status):
return self._servicer_context.abort_with_status(status)
def code(self):
if not hasattr(self._servicer_context, "code"):
raise RuntimeError("code() is not supported with the installed version of grpcio")
return self._servicer_context.code()
def details(self):
if not hasattr(self._servicer_context, "details"):
raise RuntimeError("details() is not supported with the installed version of grpcio")
return self._servicer_context.details()
def set_code(self, code):
self._code = code
# use details if we already have it, otherwise the status description
details = self._details or code.value[1]
self._active_span.set_attribute(RPC_GRPC_STATUS_CODE, code.value[0])
if code != grpc.StatusCode.OK:
status = _server_status(code, details)
self._active_span.set_status(status)
return self._servicer_context.set_code(code)
def set_details(self, details):
self._details = details
if self._code != grpc.StatusCode.OK:
status = _server_status(self._code, details)
self._active_span.set_status(status)
return self._servicer_context.set_details(details)
# pylint:disable=abstract-method
# pylint:disable=no-self-use
# pylint:disable=unused-argument
class OpenTelemetryServerInterceptor(grpc.ServerInterceptor):
"""
A gRPC server interceptor, to add OpenTelemetry.
Usage::
tracer = some OpenTelemetry tracer
filter = filters.negate(filters.method_name("service.Foo"))
interceptors = [
OpenTelemetryServerInterceptor(tracer, filter),
]
server = grpc.server(
futures.ThreadPoolExecutor(max_workers=concurrency),
interceptors = interceptors)
"""
def __init__(self, tracer, filter_=None):
self._tracer = tracer
self._filter = filter_
@contextmanager
def _set_remote_context(self, servicer_context):
metadata = servicer_context.invocation_metadata()
if metadata:
md_dict = {md.key: md.value for md in metadata}
ctx = extract(md_dict)
token = attach(ctx)
try:
yield
finally:
if token:
detach(token)
else:
yield
def _start_span(self, handler_call_details, context, set_status_on_exception=False):
# standard attributes
attributes = {
RPC_SYSTEM: "grpc",
RPC_GRPC_STATUS_CODE: grpc.StatusCode.OK.value[0],
}
# if we have details about the call, split into service and method
if handler_call_details.method:
service, method = handler_call_details.method.lstrip("/").split("/", 1)
attributes.update(
{
RPC_METHOD: method,
RPC_SERVICE: service,
}
)
# add some attributes from the metadata
metadata = dict(context.invocation_metadata())
if "user-agent" in metadata:
attributes["rpc.user_agent"] = metadata["user-agent"]
# Split up the peer to keep with how other telemetry sources
# do it. This looks like:
# * ipv6:[::1]:57284
# * ipv4:127.0.0.1:57284
# * ipv4:10.2.1.1:57284,127.0.0.1:57284
#
if not context.peer().startswith("unix:"):
try:
ip, port = context.peer().split(",")[0].split(":", 1)[1].rsplit(":", 1)
ip = unquote(ip)
attributes.update(
{
NET_PEER_IP: ip,
NET_PEER_PORT: port,
}
)
# other telemetry sources add this, so we will too
if ip in ("[::1]", "127.0.0.1"):
attributes[NET_PEER_NAME] = "localhost"
except IndexError:
logger.warning("Failed to parse peer address '%s'", context.peer())
return self._tracer.start_as_current_span(
name=handler_call_details.method,
kind=trace.SpanKind.SERVER,
attributes=attributes,
set_status_on_exception=set_status_on_exception,
)
def intercept_service(self, continuation, handler_call_details):
if not is_instrumentation_enabled():
return continuation(handler_call_details)
if self._filter is not None and not self._filter(handler_call_details):
return continuation(handler_call_details)
def telemetry_wrapper(behavior, request_streaming, response_streaming):
def telemetry_interceptor(request_or_iterator, context):
# handle streaming responses specially
if response_streaming:
return self._intercept_server_stream(
behavior,
handler_call_details,
request_or_iterator,
context,
)
with self._set_remote_context(context):
with self._start_span(
handler_call_details,
context,
set_status_on_exception=False,
) as span:
# wrap the context
context = _OpenTelemetryServicerContext(context, span)
# And now we run the actual RPC.
try:
return behavior(request_or_iterator, context)
except Exception as error:
# Bare exceptions are likely to be gRPC aborts, which
# we handle in our context wrapper.
# Here, we're interested in uncaught exceptions.
# pylint:disable=unidiomatic-typecheck
if type(error) != Exception: # noqa: E721
span.record_exception(error)
raise error
return telemetry_interceptor
return _wrap_rpc_behavior(continuation(handler_call_details), telemetry_wrapper)
# Handle streaming responses separately - we have to do this
# to return a *new* generator or various upstream things
# get confused, or we'll lose the consistent trace
def _intercept_server_stream(self, behavior, handler_call_details, request_or_iterator, context):
with self._set_remote_context(context):
with self._start_span(handler_call_details, context, set_status_on_exception=False) as span:
context = _OpenTelemetryServicerContext(context, span)
try:
yield from behavior(request_or_iterator, context)
except Exception as error:
# pylint:disable=unidiomatic-typecheck
if type(error) != Exception: # noqa: E721
span.record_exception(error)
raise error
_utilities.py 0000664 0000000 0000000 00000002124 15270700723 0044423 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-grpc/src/opentelemetry/instrumentation/grpc # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
"""Internal utilities."""
import grpc
from opentelemetry.trace.status import Status, StatusCode
class RpcInfo:
def __init__(
self,
full_method=None,
metadata=None,
timeout=None,
request=None,
response=None,
error=None,
):
self.full_method = full_method
self.metadata = metadata
self.timeout = timeout
self.request = request
self.response = response
self.error = error
def _server_status(code, details):
error_status = Status(status_code=StatusCode.ERROR, description=f"{code}:{details}")
status_codes = {
grpc.StatusCode.UNKNOWN: error_status,
grpc.StatusCode.DEADLINE_EXCEEDED: error_status,
grpc.StatusCode.UNIMPLEMENTED: error_status,
grpc.StatusCode.INTERNAL: error_status,
grpc.StatusCode.UNAVAILABLE: error_status,
grpc.StatusCode.DATA_LOSS: error_status,
}
return status_codes.get(code, Status(status_code=StatusCode.UNSET, description=""))
filters/ 0000775 0000000 0000000 00000000000 15270700723 0043350 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-grpc/src/opentelemetry/instrumentation/grpc __init__.py 0000664 0000000 0000000 00000013316 15270700723 0045465 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-grpc/src/opentelemetry/instrumentation/grpc/filters # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
import os
from collections.abc import Callable
from typing import TypeVar
import grpc
CallDetailsT = TypeVar(
"CallDetailsT",
grpc.HandlerCallDetails,
grpc.ClientCallDetails,
grpc.aio.ClientCallDetails,
)
# pylint: disable=invalid-name
Condition = Callable[[CallDetailsT], bool]
def _full_method(metadata):
name = ""
if isinstance(metadata, grpc.HandlerCallDetails):
name = metadata.method
elif isinstance(metadata, grpc.aio.ClientCallDetails):
name = metadata.method
# name _should_ be a string here but due to a bug in grpc, it is
# populated with a bytes object. Handle both cases such that we
# are forward-compatible with a fixed version of grpc
# More info: https://github.com/grpc/grpc/issues/31092
if isinstance(name, bytes):
name = name.decode()
# NOTE: replace here if there's better way to match cases to handle
# grpcext._interceptor._UnaryClientInfo/_StreamClientInfo
elif hasattr(metadata, "full_method"):
name = metadata.full_method
# NOTE: this is to handle the grpc.aio Server case. The type interface
# indicates that metadata should be a grpc.HandlerCallDetails and be
# matched prior to this but it is in fact an internal C-extension level
# object.
elif hasattr(metadata, "method"):
name = metadata.method
return name
def _split_full_method(metadata):
name = _full_method(metadata)
service, method = os.path.split(name)
if service != "":
service = os.path.normpath(service)
service = service.lstrip("/")
return (service, method)
def all_of(*args: Condition[CallDetailsT]) -> Condition[CallDetailsT]:
"""Returns a filter function that returns True if all filter functions
assigned matches conditions.
Args:
args (function): a list of filter function
Returns:
A filter function that returns True if all filter functions
assigned matches conditions.
"""
def filter_fn(metadata):
return all(func(metadata) for func in args)
return filter_fn
def any_of(*args: Condition[CallDetailsT]) -> Condition[CallDetailsT]:
"""Returns a filter function that returns True if any of filter functions
assigned matches conditions.
Args:
args (function): a list of filter function
Returns:
A filter function that returns True if any of filter functions
assigned matches conditions.
"""
def filter_fn(metadata):
return any(func(metadata) for func in args)
return filter_fn
def negate(func: Condition[CallDetailsT]) -> Condition[CallDetailsT]:
"""Returns a filter function that negate the result of func
Args:
func (function): filter function to negate the result
Returns:
A filter function that negate the result of func
"""
def filter_fn(metadata):
return not func(metadata)
return filter_fn
def method_name(name: str) -> Condition[CallDetailsT]:
"""Returns a filter function that return True if
request's gRPC method name matches name.
Args:
name (str): method name to match
Returns:
A filter function that returns True if request's gRPC method
name matches name
"""
def filter_fn(metadata):
_, method = _split_full_method(metadata)
return method == name
return filter_fn
def method_prefix(prefix: str) -> Condition[CallDetailsT]:
"""Returns a filter function that return True if
request's gRPC method name starts with prefix.
Args:
prefix (str): method prefix to match
Returns:
A filter function that returns True if request's gRPC method
name starts with prefix
"""
def filter_fn(metadata):
_, method = _split_full_method(metadata)
return method.startswith(prefix)
return filter_fn
def full_method_name(name: str) -> Condition[CallDetailsT]:
"""Returns a filter function that return True if
request's gRPC full method name matches name.
Args:
name (str): full method name to match
Returns:
A filter function that returns True if request's gRPC full
method name matches name
"""
def filter_fn(metadata):
fm = _full_method(metadata)
return fm == name
return filter_fn
def service_name(name: str) -> Condition[CallDetailsT]:
"""Returns a filter function that return True if
request's gRPC service name matches name.
Args:
name (str): service name to match
Returns:
A filter function that returns True if request's gRPC service
name matches name
"""
def filter_fn(metadata):
service, _ = _split_full_method(metadata)
return service == name
return filter_fn
def service_prefix(prefix: str) -> Condition[CallDetailsT]:
"""Returns a filter function that return True if
request's gRPC service name starts with prefix.
Args:
prefix (str): service prefix to match
Returns:
A filter function that returns True if request's gRPC service
name starts with prefix
"""
def filter_fn(metadata):
service, _ = _split_full_method(metadata)
return service.startswith(prefix)
return filter_fn
def health_check() -> Condition[CallDetailsT]:
"""Returns a Filter that returns true if the request's
service name is health check defined by gRPC Health Checking Protocol.
https://github.com/grpc/grpc/blob/master/doc/health-checking.md
"""
return service_prefix("grpc.health.v1.Health")
__all__ = [
"full_method_name",
"health_check",
"method_name",
"method_prefix",
"service_name",
"service_prefix",
]
grpcext/ 0000775 0000000 0000000 00000000000 15270700723 0043354 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-grpc/src/opentelemetry/instrumentation/grpc __init__.py 0000664 0000000 0000000 00000007117 15270700723 0045473 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-grpc/src/opentelemetry/instrumentation/grpc/grpcext # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
# pylint:disable=import-outside-toplevel
# pylint:disable=import-self
# pylint:disable=no-name-in-module
import abc
class UnaryClientInfo(abc.ABC):
"""Consists of various information about a unary RPC on the
invocation-side.
Attributes:
full_method: A string of the full RPC method, i.e.,
/package.service/method.
timeout: The length of time in seconds to wait for the computation to
terminate or be cancelled, or None if this method should block until
the computation is terminated or is cancelled no matter how long that
takes.
"""
class StreamClientInfo(abc.ABC):
"""Consists of various information about a stream RPC on the
invocation-side.
Attributes:
full_method: A string of the full RPC method, i.e.,
/package.service/method.
is_client_stream: Indicates whether the RPC is client-streaming.
is_server_stream: Indicates whether the RPC is server-streaming.
timeout: The length of time in seconds to wait for the computation to
terminate or be cancelled, or None if this method should block until
the computation is terminated or is cancelled no matter how long that
takes.
"""
class UnaryClientInterceptor(abc.ABC):
"""Affords intercepting unary-unary RPCs on the invocation-side."""
@abc.abstractmethod
def intercept_unary(self, request, metadata, client_info, invoker):
"""Intercepts unary-unary RPCs on the invocation-side.
Args:
request: The request value for the RPC.
metadata: Optional :term:`metadata` to be transmitted to the
service-side of the RPC.
client_info: A UnaryClientInfo containing various information about
the RPC.
invoker: The handler to complete the RPC on the client. It is the
interceptor's responsibility to call it.
Returns:
The result from calling invoker(request, metadata).
"""
raise NotImplementedError()
class StreamClientInterceptor(abc.ABC):
"""Affords intercepting stream RPCs on the invocation-side."""
@abc.abstractmethod
def intercept_stream(self, request_or_iterator, metadata, client_info, invoker):
"""Intercepts stream RPCs on the invocation-side.
Args:
request_or_iterator: The request value for the RPC if
`client_info.is_client_stream` is `false`; otherwise, an iterator of
request values.
metadata: Optional :term:`metadata` to be transmitted to the service-side
of the RPC.
client_info: A StreamClientInfo containing various information about
the RPC.
invoker: The handler to complete the RPC on the client. It is the
interceptor's responsibility to call it.
Returns:
The result from calling invoker(metadata).
"""
raise NotImplementedError()
def intercept_channel(channel, *interceptors):
"""Creates an intercepted channel.
Args:
channel: A Channel.
interceptors: Zero or more UnaryClientInterceptors or
StreamClientInterceptors
Returns:
A Channel.
Raises:
TypeError: If an interceptor derives from neither UnaryClientInterceptor
nor StreamClientInterceptor.
"""
from . import _interceptor # noqa: PLC0415
return _interceptor.intercept_channel(channel, *interceptors)
__all__ = (
"StreamClientInfo",
"StreamClientInterceptor",
"UnaryClientInterceptor",
"intercept_channel",
)
_interceptor.py 0000664 0000000 0000000 00000025040 15270700723 0046424 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-grpc/src/opentelemetry/instrumentation/grpc/grpcext # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
# pylint:disable=relative-beyond-top-level
# pylint:disable=no-member
"""Implementation of gRPC Python interceptors."""
import collections
import grpc
from opentelemetry.instrumentation.grpc import grpcext
class _UnaryClientInfo(collections.namedtuple("_UnaryClientInfo", ("full_method", "timeout"))):
pass
class _StreamClientInfo(
collections.namedtuple(
"_StreamClientInfo",
("full_method", "is_client_stream", "is_server_stream", "timeout"),
)
):
pass
class _InterceptorUnaryUnaryMultiCallable(grpc.UnaryUnaryMultiCallable):
def __init__(self, method, base_callable, interceptor):
self._method = method
self._base_callable = base_callable
self._interceptor = interceptor
def __call__(
self,
request,
timeout=None,
metadata=None,
credentials=None,
wait_for_ready=None,
compression=None,
):
def invoker(request, metadata):
return self._base_callable(
request,
timeout,
metadata,
credentials,
wait_for_ready,
compression,
)
client_info = _UnaryClientInfo(self._method, timeout)
return self._interceptor.intercept_unary(request, metadata, client_info, invoker)
def with_call(
self,
request,
timeout=None,
metadata=None,
credentials=None,
wait_for_ready=None,
compression=None,
):
def invoker(request, metadata):
return self._base_callable.with_call(
request,
timeout,
metadata,
credentials,
wait_for_ready,
compression,
)
client_info = _UnaryClientInfo(self._method, timeout)
return self._interceptor.intercept_unary(request, metadata, client_info, invoker)
def future(
self,
request,
timeout=None,
metadata=None,
credentials=None,
wait_for_ready=None,
compression=None,
):
def invoker(request, metadata):
return self._base_callable.future(
request,
timeout,
metadata,
credentials,
wait_for_ready,
compression,
)
client_info = _UnaryClientInfo(self._method, timeout)
return self._interceptor.intercept_unary(request, metadata, client_info, invoker)
class _InterceptorUnaryStreamMultiCallable(grpc.UnaryStreamMultiCallable):
def __init__(self, method, base_callable, interceptor):
self._method = method
self._base_callable = base_callable
self._interceptor = interceptor
def __call__(
self,
request,
timeout=None,
metadata=None,
credentials=None,
wait_for_ready=None,
compression=None,
):
def invoker(request, metadata):
return self._base_callable(
request,
timeout,
metadata,
credentials,
wait_for_ready,
compression,
)
client_info = _StreamClientInfo(self._method, False, True, timeout)
return self._interceptor.intercept_stream(request, metadata, client_info, invoker)
class _InterceptorStreamUnaryMultiCallable(grpc.StreamUnaryMultiCallable):
def __init__(self, method, base_callable, interceptor):
self._method = method
self._base_callable = base_callable
self._interceptor = interceptor
def __call__(
self,
request_iterator,
timeout=None,
metadata=None,
credentials=None,
wait_for_ready=None,
compression=None,
):
def invoker(request_iterator, metadata):
return self._base_callable(
request_iterator,
timeout,
metadata,
credentials,
wait_for_ready,
compression,
)
client_info = _StreamClientInfo(self._method, True, False, timeout)
return self._interceptor.intercept_stream(request_iterator, metadata, client_info, invoker)
def with_call(
self,
request_iterator,
timeout=None,
metadata=None,
credentials=None,
wait_for_ready=None,
compression=None,
):
def invoker(request_iterator, metadata):
return self._base_callable.with_call(
request_iterator,
timeout,
metadata,
credentials,
wait_for_ready,
compression,
)
client_info = _StreamClientInfo(self._method, True, False, timeout)
return self._interceptor.intercept_stream(request_iterator, metadata, client_info, invoker)
def future(
self,
request_iterator,
timeout=None,
metadata=None,
credentials=None,
wait_for_ready=None,
compression=None,
):
def invoker(request_iterator, metadata):
return self._base_callable.future(
request_iterator,
timeout,
metadata,
credentials,
wait_for_ready,
compression,
)
client_info = _StreamClientInfo(self._method, True, False, timeout)
return self._interceptor.intercept_stream(request_iterator, metadata, client_info, invoker)
class _InterceptorStreamStreamMultiCallable(grpc.StreamStreamMultiCallable):
def __init__(self, method, base_callable, interceptor):
self._method = method
self._base_callable = base_callable
self._interceptor = interceptor
def __call__(
self,
request_iterator,
timeout=None,
metadata=None,
credentials=None,
wait_for_ready=None,
compression=None,
):
def invoker(request_iterator, metadata):
return self._base_callable(
request_iterator,
timeout,
metadata,
credentials,
wait_for_ready,
compression,
)
client_info = _StreamClientInfo(self._method, True, True, timeout)
return self._interceptor.intercept_stream(request_iterator, metadata, client_info, invoker)
class _InterceptorChannel(grpc.Channel):
def __init__(self, channel, interceptor):
self._channel = channel
self._interceptor = interceptor
def subscribe(self, *args, **kwargs):
self._channel.subscribe(*args, **kwargs)
def unsubscribe(self, *args, **kwargs):
self._channel.unsubscribe(*args, **kwargs)
def unary_unary(
self,
method,
request_serializer=None,
response_deserializer=None,
_registered_method=False,
):
if _registered_method:
base_callable = self._channel.unary_unary(
method,
request_serializer,
response_deserializer,
_registered_method,
)
else:
base_callable = self._channel.unary_unary(method, request_serializer, response_deserializer)
if isinstance(self._interceptor, grpcext.UnaryClientInterceptor):
return _InterceptorUnaryUnaryMultiCallable(method, base_callable, self._interceptor)
return base_callable
def unary_stream(
self,
method,
request_serializer=None,
response_deserializer=None,
_registered_method=False,
):
if _registered_method:
base_callable = self._channel.unary_stream(
method,
request_serializer,
response_deserializer,
_registered_method,
)
else:
base_callable = self._channel.unary_stream(method, request_serializer, response_deserializer)
if isinstance(self._interceptor, grpcext.StreamClientInterceptor):
return _InterceptorUnaryStreamMultiCallable(method, base_callable, self._interceptor)
return base_callable
def stream_unary(
self,
method,
request_serializer=None,
response_deserializer=None,
_registered_method=False,
):
if _registered_method:
base_callable = self._channel.stream_unary(
method,
request_serializer,
response_deserializer,
_registered_method,
)
else:
base_callable = self._channel.stream_unary(method, request_serializer, response_deserializer)
if isinstance(self._interceptor, grpcext.StreamClientInterceptor):
return _InterceptorStreamUnaryMultiCallable(method, base_callable, self._interceptor)
return base_callable
def stream_stream(
self,
method,
request_serializer=None,
response_deserializer=None,
_registered_method=False,
):
if _registered_method:
base_callable = self._channel.stream_stream(
method,
request_serializer,
response_deserializer,
_registered_method,
)
else:
base_callable = self._channel.stream_stream(method, request_serializer, response_deserializer)
if isinstance(self._interceptor, grpcext.StreamClientInterceptor):
return _InterceptorStreamStreamMultiCallable(method, base_callable, self._interceptor)
return base_callable
def close(self):
if not hasattr(self._channel, "close"):
raise RuntimeError("close() is not supported with the installed version of grpcio")
self._channel.close()
def __enter__(self):
"""Enters the runtime context related to the channel object."""
return self
def __exit__(self, exc_type, exc_val, exc_tb):
"""Exits the runtime context related to the channel object."""
self.close()
def intercept_channel(channel, *interceptors):
result = channel
for interceptor in interceptors:
if not isinstance(interceptor, grpcext.UnaryClientInterceptor) and not isinstance(
interceptor, grpcext.StreamClientInterceptor
):
raise TypeError(
"interceptor must be either a grpcext.UnaryClientInterceptor or a grpcext.StreamClientInterceptor"
)
result = _InterceptorChannel(result, interceptor)
return result
package.py 0000664 0000000 0000000 00000000163 15270700723 0043645 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-grpc/src/opentelemetry/instrumentation/grpc # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
_instruments = ("grpcio >= 1.42.0",)
version.py 0000664 0000000 0000000 00000000144 15270700723 0043736 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-grpc/src/opentelemetry/instrumentation/grpc # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
__version__ = "0.66b2"
test-requirements-0-wrapt1.txt 0000664 0000000 0000000 00000000051 15270700723 0037625 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-grpc -r test-requirements-0.txt
wrapt==1.17.3
test-requirements-0-wrapt2.txt 0000664 0000000 0000000 00000000050 15270700723 0037625 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-grpc -r test-requirements-0.txt
wrapt==2.1.2
test-requirements-0.txt 0000664 0000000 0000000 00000000411 15270700723 0036411 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-grpc asgiref==3.8.1
grpcio==1.62.0
iniconfig==2.0.0
packaging==24.0
pluggy==1.6.0
protobuf==3.20.3
py-cpuinfo==9.0.0
pytest==7.4.4
tomli==2.0.1
typing_extensions==4.12.2
zipp==3.19.2
-e opentelemetry-instrumentation
-e instrumentation/opentelemetry-instrumentation-grpc
test-requirements-1-wrapt1.txt 0000664 0000000 0000000 00000000051 15270700723 0037626 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-grpc -r test-requirements-1.txt
wrapt==1.17.3
test-requirements-1-wrapt2.txt 0000664 0000000 0000000 00000000050 15270700723 0037626 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-grpc -r test-requirements-1.txt
wrapt==2.1.2
test-requirements-1.txt 0000664 0000000 0000000 00000000411 15270700723 0036412 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-grpc asgiref==3.8.1
grpcio==1.75.1
iniconfig==2.0.0
packaging==24.0
pluggy==1.6.0
protobuf==3.20.3
py-cpuinfo==9.0.0
pytest==7.4.4
tomli==2.0.1
typing_extensions==4.12.2
zipp==3.19.2
-e opentelemetry-instrumentation
-e instrumentation/opentelemetry-instrumentation-grpc
opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-grpc/tests/ 0000775 0000000 0000000 00000000000 15270700723 0033240 5 ustar 00root root 0000000 0000000 __init__.py 0000664 0000000 0000000 00000000114 15270700723 0035266 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-grpc/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
_aio_client.py 0000664 0000000 0000000 00000002320 15270700723 0035775 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-grpc/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
from .protobuf.test_server_pb2 import Request
CLIENT_ID = 1
async def simple_method(stub, error=False):
request = Request(client_id=CLIENT_ID, request_data="error" if error else "data")
return await stub.SimpleMethod(request, metadata=(("key", "value"),))
async def client_streaming_method(stub, error=False):
# create a generator
def request_messages():
for _ in range(5):
request = Request(client_id=CLIENT_ID, request_data="error" if error else "data")
yield request
return await stub.ClientStreamingMethod(request_messages())
def server_streaming_method(stub, error=False):
request = Request(client_id=CLIENT_ID, request_data="error" if error else "data")
return stub.ServerStreamingMethod(request, metadata=(("key", "value"),))
def bidirectional_streaming_method(stub, error=False):
# create a generator
def request_messages():
for _ in range(5):
request = Request(client_id=CLIENT_ID, request_data="error" if error else "data")
yield request
return stub.BidirectionalStreamingMethod(request_messages(), metadata=(("key", "value"),))
_client.py 0000664 0000000 0000000 00000002721 15270700723 0035152 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-grpc/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
from .protobuf.test_server_pb2 import Request
CLIENT_ID = 1
def simple_method(stub, error=False):
request = Request(client_id=CLIENT_ID, request_data="error" if error else "data")
stub.SimpleMethod(request, metadata=(("key", "value"),))
def simple_method_future(stub, error=False):
request = Request(client_id=CLIENT_ID, request_data="error" if error else "data")
return stub.SimpleMethod.future(request, metadata=(("key", "value"),))
def client_streaming_method(stub, error=False):
# create a generator
def request_messages():
for _ in range(5):
request = Request(client_id=CLIENT_ID, request_data="error" if error else "data")
yield request
stub.ClientStreamingMethod(request_messages(), metadata=(("key", "value"),))
def server_streaming_method(stub, error=False):
request = Request(client_id=CLIENT_ID, request_data="error" if error else "data")
response_iterator = stub.ServerStreamingMethod(request, metadata=(("key", "value"),))
list(response_iterator)
def bidirectional_streaming_method(stub, error=False):
def request_messages():
for _ in range(5):
request = Request(client_id=CLIENT_ID, request_data="error" if error else "data")
yield request
response_iterator = stub.BidirectionalStreamingMethod(request_messages(), metadata=(("key", "value"),))
list(response_iterator)
_server.py 0000664 0000000 0000000 00000004351 15270700723 0035203 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-grpc/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
from concurrent import futures
import grpc
from .protobuf import test_server_pb2, test_server_pb2_grpc
SERVER_ID = 1
class TestServer(test_server_pb2_grpc.GRPCTestServerServicer):
# pylint: disable=invalid-name
# pylint: disable=no-self-use
def SimpleMethod(self, request, context):
if request.request_data == "error":
context.set_code(grpc.StatusCode.INVALID_ARGUMENT)
return test_server_pb2.Response()
response = test_server_pb2.Response(server_id=SERVER_ID, response_data="data")
return response
def ClientStreamingMethod(self, request_iterator, context):
data = list(request_iterator)
if data[0].request_data == "error":
context.set_code(grpc.StatusCode.INVALID_ARGUMENT)
return test_server_pb2.Response()
response = test_server_pb2.Response(server_id=SERVER_ID, response_data="data")
return response
def ServerStreamingMethod(self, request, context):
if request.request_data == "error":
context.abort(
code=grpc.StatusCode.INVALID_ARGUMENT,
details="server stream error",
)
return test_server_pb2.Response()
# create a generator
def response_messages():
for _ in range(5):
response = test_server_pb2.Response(server_id=SERVER_ID, response_data="data")
yield response
return response_messages()
def BidirectionalStreamingMethod(self, request_iterator, context):
data = list(request_iterator)
if data[0].request_data == "error":
context.abort(
code=grpc.StatusCode.INVALID_ARGUMENT,
details="bidirectional error",
)
return
for _ in range(5):
yield test_server_pb2.Response(server_id=SERVER_ID, response_data="data")
def create_test_server(port):
# pylint: disable=consider-using-with
server = grpc.server(futures.ThreadPoolExecutor(max_workers=1))
test_server_pb2_grpc.add_GRPCTestServerServicer_to_server(TestServer(), server)
server.add_insecure_port(f"localhost:{port}")
return server
protobuf/ 0000775 0000000 0000000 00000000000 15270700723 0035021 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-grpc/tests test_server.proto 0000664 0000000 0000000 00000002042 15270700723 0040451 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-grpc/tests/protobuf // Copyright 2019 gRPC authors.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
syntax = "proto3";
message Request {
int64 client_id = 1;
string request_data = 2;
}
message Response {
int64 server_id = 1;
string response_data = 2;
}
service GRPCTestServer {
rpc SimpleMethod (Request) returns (Response);
rpc ClientStreamingMethod (stream Request) returns (Response);
rpc ServerStreamingMethod (Request) returns (stream Response);
rpc BidirectionalStreamingMethod (stream Request) returns (stream Response);
}
test_server_pb2.py 0000664 0000000 0000000 00000014344 15270700723 0040511 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-grpc/tests/protobuf # Generated by the protocol buffer compiler. DO NOT EDIT!
# source: test_server.proto
from google.protobuf import descriptor as _descriptor
from google.protobuf import message as _message
from google.protobuf import reflection as _reflection
from google.protobuf import symbol_database as _symbol_database
# @@protoc_insertion_point(imports)
_sym_db = _symbol_database.Default()
DESCRIPTOR = _descriptor.FileDescriptor(
name="test_server.proto",
package="",
syntax="proto3",
serialized_options=None,
serialized_pb=b'\n\x11test_server.proto"2\n\x07Request\x12\x11\n\tclient_id\x18\x01 \x01(\x03\x12\x14\n\x0crequest_data\x18\x02 \x01(\t"4\n\x08Response\x12\x11\n\tserver_id\x18\x01 \x01(\x03\x12\x15\n\rresponse_data\x18\x02 \x01(\t2\xce\x01\n\x0eGRPCTestServer\x12#\n\x0cSimpleMethod\x12\x08.Request\x1a\t.Response\x12.\n\x15\x43lientStreamingMethod\x12\x08.Request\x1a\t.Response(\x01\x12.\n\x15ServerStreamingMethod\x12\x08.Request\x1a\t.Response0\x01\x12\x37\n\x1c\x42idirectionalStreamingMethod\x12\x08.Request\x1a\t.Response(\x01\x30\x01\x62\x06proto3',
)
_REQUEST = _descriptor.Descriptor(
name="Request",
full_name="Request",
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name="client_id",
full_name="Request.client_id",
index=0,
number=1,
type=3,
cpp_type=2,
label=1,
has_default_value=False,
default_value=0,
message_type=None,
enum_type=None,
containing_type=None,
is_extension=False,
extension_scope=None,
serialized_options=None,
file=DESCRIPTOR,
),
_descriptor.FieldDescriptor(
name="request_data",
full_name="Request.request_data",
index=1,
number=2,
type=9,
cpp_type=9,
label=1,
has_default_value=False,
default_value=b"".decode("utf-8"),
message_type=None,
enum_type=None,
containing_type=None,
is_extension=False,
extension_scope=None,
serialized_options=None,
file=DESCRIPTOR,
),
],
extensions=[],
nested_types=[],
enum_types=[],
serialized_options=None,
is_extendable=False,
syntax="proto3",
extension_ranges=[],
oneofs=[],
serialized_start=21,
serialized_end=71,
)
_RESPONSE = _descriptor.Descriptor(
name="Response",
full_name="Response",
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name="server_id",
full_name="Response.server_id",
index=0,
number=1,
type=3,
cpp_type=2,
label=1,
has_default_value=False,
default_value=0,
message_type=None,
enum_type=None,
containing_type=None,
is_extension=False,
extension_scope=None,
serialized_options=None,
file=DESCRIPTOR,
),
_descriptor.FieldDescriptor(
name="response_data",
full_name="Response.response_data",
index=1,
number=2,
type=9,
cpp_type=9,
label=1,
has_default_value=False,
default_value=b"".decode("utf-8"),
message_type=None,
enum_type=None,
containing_type=None,
is_extension=False,
extension_scope=None,
serialized_options=None,
file=DESCRIPTOR,
),
],
extensions=[],
nested_types=[],
enum_types=[],
serialized_options=None,
is_extendable=False,
syntax="proto3",
extension_ranges=[],
oneofs=[],
serialized_start=73,
serialized_end=125,
)
DESCRIPTOR.message_types_by_name["Request"] = _REQUEST
DESCRIPTOR.message_types_by_name["Response"] = _RESPONSE
_sym_db.RegisterFileDescriptor(DESCRIPTOR)
Request = _reflection.GeneratedProtocolMessageType(
"Request",
(_message.Message,),
{
"DESCRIPTOR": _REQUEST,
"__module__": "test_server_pb2",
# @@protoc_insertion_point(class_scope:Request)
},
)
_sym_db.RegisterMessage(Request)
Response = _reflection.GeneratedProtocolMessageType(
"Response",
(_message.Message,),
{
"DESCRIPTOR": _RESPONSE,
"__module__": "test_server_pb2",
# @@protoc_insertion_point(class_scope:Response)
},
)
_sym_db.RegisterMessage(Response)
_GRPCTESTSERVER = _descriptor.ServiceDescriptor(
name="GRPCTestServer",
full_name="GRPCTestServer",
file=DESCRIPTOR,
index=0,
serialized_options=None,
serialized_start=128,
serialized_end=334,
methods=[
_descriptor.MethodDescriptor(
name="SimpleMethod",
full_name="GRPCTestServer.SimpleMethod",
index=0,
containing_service=None,
input_type=_REQUEST,
output_type=_RESPONSE,
serialized_options=None,
),
_descriptor.MethodDescriptor(
name="ClientStreamingMethod",
full_name="GRPCTestServer.ClientStreamingMethod",
index=1,
containing_service=None,
input_type=_REQUEST,
output_type=_RESPONSE,
serialized_options=None,
),
_descriptor.MethodDescriptor(
name="ServerStreamingMethod",
full_name="GRPCTestServer.ServerStreamingMethod",
index=2,
containing_service=None,
input_type=_REQUEST,
output_type=_RESPONSE,
serialized_options=None,
),
_descriptor.MethodDescriptor(
name="BidirectionalStreamingMethod",
full_name="GRPCTestServer.BidirectionalStreamingMethod",
index=3,
containing_service=None,
input_type=_REQUEST,
output_type=_RESPONSE,
serialized_options=None,
),
],
)
_sym_db.RegisterServiceDescriptor(_GRPCTESTSERVER)
DESCRIPTOR.services_by_name["GRPCTestServer"] = _GRPCTESTSERVER
# @@protoc_insertion_point(module_scope)
test_server_pb2_grpc.py 0000664 0000000 0000000 00000016221 15270700723 0041520 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-grpc/tests/protobuf # Generated by the gRPC Python protocol compiler plugin. DO NOT EDIT!
import grpc
from tests.protobuf import test_server_pb2 as test__server__pb2
class GRPCTestServerStub:
"""Missing associated documentation comment in .proto file"""
def __init__(self, channel):
"""Constructor.
Args:
channel: A grpc.Channel.
"""
# pylint: disable=invalid-name
self.SimpleMethod = channel.unary_unary(
"/GRPCTestServer/SimpleMethod",
request_serializer=test__server__pb2.Request.SerializeToString,
response_deserializer=test__server__pb2.Response.FromString,
)
self.ClientStreamingMethod = channel.stream_unary(
"/GRPCTestServer/ClientStreamingMethod",
request_serializer=test__server__pb2.Request.SerializeToString,
response_deserializer=test__server__pb2.Response.FromString,
)
self.ServerStreamingMethod = channel.unary_stream(
"/GRPCTestServer/ServerStreamingMethod",
request_serializer=test__server__pb2.Request.SerializeToString,
response_deserializer=test__server__pb2.Response.FromString,
)
self.BidirectionalStreamingMethod = channel.stream_stream(
"/GRPCTestServer/BidirectionalStreamingMethod",
request_serializer=test__server__pb2.Request.SerializeToString,
response_deserializer=test__server__pb2.Response.FromString,
)
class GRPCTestServerServicer:
"""Missing associated documentation comment in .proto file"""
# pylint: disable=invalid-name
# pylint: disable=no-self-use
def SimpleMethod(self, request, context):
"""Missing associated documentation comment in .proto file"""
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details("Method not implemented!")
raise NotImplementedError("Method not implemented!")
def ClientStreamingMethod(self, request_iterator, context):
"""Missing associated documentation comment in .proto file"""
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details("Method not implemented!")
raise NotImplementedError("Method not implemented!")
def ServerStreamingMethod(self, request, context):
"""Missing associated documentation comment in .proto file"""
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details("Method not implemented!")
raise NotImplementedError("Method not implemented!")
def BidirectionalStreamingMethod(self, request_iterator, context):
"""Missing associated documentation comment in .proto file"""
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details("Method not implemented!")
raise NotImplementedError("Method not implemented!")
def add_GRPCTestServerServicer_to_server(
servicer, server
): # pylint: disable=invalid-name
rpc_method_handlers = {
"SimpleMethod": grpc.unary_unary_rpc_method_handler(
servicer.SimpleMethod,
request_deserializer=test__server__pb2.Request.FromString,
response_serializer=test__server__pb2.Response.SerializeToString,
),
"ClientStreamingMethod": grpc.stream_unary_rpc_method_handler(
servicer.ClientStreamingMethod,
request_deserializer=test__server__pb2.Request.FromString,
response_serializer=test__server__pb2.Response.SerializeToString,
),
"ServerStreamingMethod": grpc.unary_stream_rpc_method_handler(
servicer.ServerStreamingMethod,
request_deserializer=test__server__pb2.Request.FromString,
response_serializer=test__server__pb2.Response.SerializeToString,
),
"BidirectionalStreamingMethod": grpc.stream_stream_rpc_method_handler(
servicer.BidirectionalStreamingMethod,
request_deserializer=test__server__pb2.Request.FromString,
response_serializer=test__server__pb2.Response.SerializeToString,
),
}
generic_handler = grpc.method_handlers_generic_handler(
"GRPCTestServer", rpc_method_handlers
)
server.add_generic_rpc_handlers((generic_handler,))
# This class is part of an EXPERIMENTAL API.
class GRPCTestServer:
"""Missing associated documentation comment in .proto file"""
# pylint: disable=invalid-name
@staticmethod
def SimpleMethod(
request,
target,
options=(),
channel_credentials=None,
call_credentials=None,
compression=None,
wait_for_ready=None,
timeout=None,
metadata=None,
):
return grpc.experimental.unary_unary(
request,
target,
"/GRPCTestServer/SimpleMethod",
test__server__pb2.Request.SerializeToString,
test__server__pb2.Response.FromString,
options,
channel_credentials,
call_credentials,
compression,
wait_for_ready,
timeout,
metadata,
)
@staticmethod
def ClientStreamingMethod(
request_iterator,
target,
options=(),
channel_credentials=None,
call_credentials=None,
compression=None,
wait_for_ready=None,
timeout=None,
metadata=None,
):
return grpc.experimental.stream_unary(
request_iterator,
target,
"/GRPCTestServer/ClientStreamingMethod",
test__server__pb2.Request.SerializeToString,
test__server__pb2.Response.FromString,
options,
channel_credentials,
call_credentials,
compression,
wait_for_ready,
timeout,
metadata,
)
@staticmethod
def ServerStreamingMethod(
request,
target,
options=(),
channel_credentials=None,
call_credentials=None,
compression=None,
wait_for_ready=None,
timeout=None,
metadata=None,
):
return grpc.experimental.unary_stream(
request,
target,
"/GRPCTestServer/ServerStreamingMethod",
test__server__pb2.Request.SerializeToString,
test__server__pb2.Response.FromString,
options,
channel_credentials,
call_credentials,
compression,
wait_for_ready,
timeout,
metadata,
)
@staticmethod
def BidirectionalStreamingMethod(
request_iterator,
target,
options=(),
channel_credentials=None,
call_credentials=None,
compression=None,
wait_for_ready=None,
timeout=None,
metadata=None,
):
return grpc.experimental.stream_stream(
request_iterator,
target,
"/GRPCTestServer/BidirectionalStreamingMethod",
test__server__pb2.Request.SerializeToString,
test__server__pb2.Response.FromString,
options,
channel_credentials,
call_credentials,
compression,
wait_for_ready,
timeout,
metadata,
)
test_aio_client_interceptor.py 0000664 0000000 0000000 00000027556 15270700723 0041335 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-grpc/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
from unittest import IsolatedAsyncioTestCase
from unittest.mock import patch
import grpc
import opentelemetry.instrumentation.grpc
from opentelemetry import trace
from opentelemetry.instrumentation.grpc import (
GrpcAioInstrumentorClient,
aio_client_interceptors,
)
from opentelemetry.instrumentation.grpc._aio_client import (
UnaryUnaryAioClientInterceptor,
)
from opentelemetry.instrumentation.utils import suppress_instrumentation
from opentelemetry.propagate import get_global_textmap, set_global_textmap
from opentelemetry.semconv._incubating.attributes.rpc_attributes import (
RPC_GRPC_STATUS_CODE,
RPC_METHOD,
RPC_SERVICE,
RPC_SYSTEM,
)
from opentelemetry.test.mock_textmap import MockTextMapPropagator
from opentelemetry.test.test_base import TestBase
from ._aio_client import (
bidirectional_streaming_method,
client_streaming_method,
server_streaming_method,
simple_method,
)
from ._server import create_test_server
from .protobuf import test_server_pb2_grpc # pylint: disable=no-name-in-module
class RecordingInterceptor(grpc.aio.UnaryUnaryClientInterceptor):
recorded_details = None
async def intercept_unary_unary(self, continuation, client_call_details, request):
self.recorded_details = client_call_details
return await continuation(client_call_details, request)
class TestAioClientInterceptor(TestBase, IsolatedAsyncioTestCase):
def setUp(self):
super().setUp()
self.server = create_test_server(25565)
self.server.start()
interceptors = aio_client_interceptors()
self._channel = grpc.aio.insecure_channel("localhost:25565", interceptors=interceptors)
self._stub = test_server_pb2_grpc.GRPCTestServerStub(self._channel)
def tearDown(self):
super().tearDown()
self.server.stop(1000)
async def asyncTearDown(self):
await self._channel.close()
async def test_instrument(self):
instrumentor = GrpcAioInstrumentorClient()
try:
instrumentor.instrument()
channel = grpc.aio.insecure_channel("localhost:25565")
stub = test_server_pb2_grpc.GRPCTestServerStub(channel)
response = await simple_method(stub)
assert response.response_data == "data"
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
finally:
instrumentor.uninstrument()
async def test_uninstrument(self):
instrumentor = GrpcAioInstrumentorClient()
instrumentor.instrument()
instrumentor.uninstrument()
channel = grpc.aio.insecure_channel("localhost:25565")
stub = test_server_pb2_grpc.GRPCTestServerStub(channel)
response = await simple_method(stub)
assert response.response_data == "data"
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 0)
async def test_unary_unary(self):
response = await simple_method(self._stub)
assert response.response_data == "data"
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
span = spans[0]
self.assertEqual(span.name, "/GRPCTestServer/SimpleMethod")
self.assertIs(span.kind, trace.SpanKind.CLIENT)
# Check version and name in span's instrumentation info
self.assertEqualSpanInstrumentationScope(span, opentelemetry.instrumentation.grpc)
self.assertSpanHasAttributes(
span,
{
RPC_METHOD: "SimpleMethod",
RPC_SERVICE: "GRPCTestServer",
RPC_SYSTEM: "grpc",
RPC_GRPC_STATUS_CODE: grpc.StatusCode.OK.value[0],
},
)
async def test_unary_stream(self):
async for response in server_streaming_method(self._stub):
self.assertEqual(response.response_data, "data")
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
span = spans[0]
self.assertEqual(span.name, "/GRPCTestServer/ServerStreamingMethod")
self.assertIs(span.kind, trace.SpanKind.CLIENT)
# Check version and name in span's instrumentation info
self.assertEqualSpanInstrumentationScope(span, opentelemetry.instrumentation.grpc)
self.assertSpanHasAttributes(
span,
{
RPC_METHOD: "ServerStreamingMethod",
RPC_SERVICE: "GRPCTestServer",
RPC_SYSTEM: "grpc",
RPC_GRPC_STATUS_CODE: grpc.StatusCode.OK.value[0],
},
)
async def test_stream_unary(self):
response = await client_streaming_method(self._stub)
assert response.response_data == "data"
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
span = spans[0]
self.assertEqual(span.name, "/GRPCTestServer/ClientStreamingMethod")
self.assertIs(span.kind, trace.SpanKind.CLIENT)
# Check version and name in span's instrumentation info
self.assertEqualSpanInstrumentationScope(span, opentelemetry.instrumentation.grpc)
self.assertSpanHasAttributes(
span,
{
RPC_METHOD: "ClientStreamingMethod",
RPC_SERVICE: "GRPCTestServer",
RPC_SYSTEM: "grpc",
RPC_GRPC_STATUS_CODE: grpc.StatusCode.OK.value[0],
},
)
async def test_stream_stream(self):
async for response in bidirectional_streaming_method(self._stub):
self.assertEqual(response.response_data, "data")
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
span = spans[0]
self.assertEqual(span.name, "/GRPCTestServer/BidirectionalStreamingMethod")
self.assertIs(span.kind, trace.SpanKind.CLIENT)
# Check version and name in span's instrumentation info
self.assertEqualSpanInstrumentationScope(span, opentelemetry.instrumentation.grpc)
self.assertSpanHasAttributes(
span,
{
RPC_METHOD: "BidirectionalStreamingMethod",
RPC_SERVICE: "GRPCTestServer",
RPC_SYSTEM: "grpc",
RPC_GRPC_STATUS_CODE: grpc.StatusCode.OK.value[0],
},
)
async def test_error_simple(self):
with self.assertRaises(grpc.RpcError):
await simple_method(self._stub, error=True)
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
span = spans[0]
self.assertIs(
span.status.status_code,
trace.StatusCode.ERROR,
)
self.assertEqual(
span.attributes[RPC_GRPC_STATUS_CODE],
grpc.StatusCode.INVALID_ARGUMENT.value[0],
)
async def test_error_unary_stream(self):
with self.assertRaises(grpc.RpcError):
async for _ in server_streaming_method(self._stub, error=True):
pass
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
span = spans[0]
self.assertIs(
span.status.status_code,
trace.StatusCode.ERROR,
)
self.assertEqual(
span.attributes[RPC_GRPC_STATUS_CODE],
grpc.StatusCode.INVALID_ARGUMENT.value[0],
)
async def test_error_stream_unary(self):
with self.assertRaises(grpc.RpcError):
await client_streaming_method(self._stub, error=True)
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
span = spans[0]
self.assertIs(
span.status.status_code,
trace.StatusCode.ERROR,
)
self.assertEqual(
span.attributes[RPC_GRPC_STATUS_CODE],
grpc.StatusCode.INVALID_ARGUMENT.value[0],
)
async def test_error_stream_stream(self):
with self.assertRaises(grpc.RpcError):
async for _ in bidirectional_streaming_method(self._stub, error=True):
pass
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
span = spans[0]
self.assertIs(
span.status.status_code,
trace.StatusCode.ERROR,
)
self.assertEqual(
span.attributes[RPC_GRPC_STATUS_CODE],
grpc.StatusCode.INVALID_ARGUMENT.value[0],
)
# pylint:disable=no-self-use
async def test_client_interceptor_trace_context_propagation(self):
"""ensure that client interceptor correctly inject trace context into all outgoing requests."""
previous_propagator = get_global_textmap()
try:
set_global_textmap(MockTextMapPropagator())
interceptor = UnaryUnaryAioClientInterceptor(trace.NoOpTracer())
recording_interceptor = RecordingInterceptor()
interceptors = [interceptor, recording_interceptor]
channel = grpc.aio.insecure_channel("localhost:25565", interceptors=interceptors)
stub = test_server_pb2_grpc.GRPCTestServerStub(channel)
await simple_method(stub)
metadata = recording_interceptor.recorded_details.metadata
assert len(metadata) == 3
assert metadata.get_all("key") == ["value"]
assert metadata.get_all("mock-traceid") == ["0"]
assert metadata.get_all("mock-spanid") == ["0"]
finally:
set_global_textmap(previous_propagator)
async def test_unary_unary_with_suppress_key(self):
with suppress_instrumentation():
response = await simple_method(self._stub)
assert response.response_data == "data"
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 0)
async def test_unary_stream_with_suppress_key(self):
with suppress_instrumentation():
async for response in server_streaming_method(self._stub):
self.assertEqual(response.response_data, "data")
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 0)
async def test_stream_unary_with_suppress_key(self):
with suppress_instrumentation():
response = await client_streaming_method(self._stub)
assert response.response_data == "data"
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 0)
async def test_stream_stream_with_suppress_key(self):
with suppress_instrumentation():
async for response in bidirectional_streaming_method(self._stub):
self.assertEqual(response.response_data, "data")
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 0)
async def test_unary_unary_add_done_callback_not_implemented(self):
"""Span should still be finished when add_done_callback raises NotImplementedError."""
def _raise_not_implemented(self_call, callback):
raise NotImplementedError
with patch.object(
grpc.aio.UnaryUnaryCall,
"add_done_callback",
_raise_not_implemented,
):
response = await simple_method(self._stub)
assert response.response_data == "data"
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
span = spans[0]
self.assertEqual(span.name, "/GRPCTestServer/SimpleMethod")
self.assertIs(span.kind, trace.SpanKind.CLIENT)
self.assertSpanHasAttributes(
span,
{
RPC_METHOD: "SimpleMethod",
RPC_SERVICE: "GRPCTestServer",
RPC_SYSTEM: "grpc",
RPC_GRPC_STATUS_CODE: grpc.StatusCode.OK.value[0],
},
)
test_aio_client_interceptor_filter.py 0000664 0000000 0000000 00000010357 15270700723 0042671 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-grpc/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
import os
from unittest import IsolatedAsyncioTestCase, mock
import grpc
from opentelemetry.instrumentation.grpc import (
GrpcAioInstrumentorClient,
aio_client_interceptors,
filters,
)
from opentelemetry.test.test_base import TestBase
from ._aio_client import (
bidirectional_streaming_method,
client_streaming_method,
server_streaming_method,
simple_method,
)
from ._server import create_test_server
from .protobuf import test_server_pb2_grpc # pylint: disable=no-name-in-module
class TestAioClientInterceptorFiltered(TestBase, IsolatedAsyncioTestCase):
def setUp(self):
super().setUp()
self.server = create_test_server(25565)
self.server.start()
interceptors = aio_client_interceptors(filter_=filters.method_name("NotSimpleMethod"))
self._channel = grpc.aio.insecure_channel("localhost:25565", interceptors=interceptors)
self._stub = test_server_pb2_grpc.GRPCTestServerStub(self._channel)
def tearDown(self):
super().tearDown()
self.server.stop(1000)
async def asyncTearDown(self):
await self._channel.close()
async def test_instrument_filtered(self):
instrumentor = GrpcAioInstrumentorClient(filter_=filters.method_name("NotSimpleMethod"))
try:
instrumentor.instrument()
channel = grpc.aio.insecure_channel("localhost:25565")
stub = test_server_pb2_grpc.GRPCTestServerStub(channel)
response = await simple_method(stub)
assert response.response_data == "data"
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 0)
finally:
instrumentor.uninstrument()
async def test_instrument_filtered_env(self):
with mock.patch.dict(
os.environ,
{"OTEL_PYTHON_GRPC_EXCLUDED_SERVICES": "GRPCMockServer,GRPCTestServer"},
):
instrumentor = GrpcAioInstrumentorClient()
try:
instrumentor.instrument()
channel = grpc.aio.insecure_channel("localhost:25565")
stub = test_server_pb2_grpc.GRPCTestServerStub(channel)
response = await simple_method(stub)
assert response.response_data == "data"
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 0)
finally:
instrumentor.uninstrument()
async def test_instrument_filtered_env_and_option(self):
with mock.patch.dict(
os.environ,
{"OTEL_PYTHON_GRPC_EXCLUDED_SERVICES": "GRPCMockServer"},
):
instrumentor = GrpcAioInstrumentorClient(filter_=filters.service_prefix("GRPCTestServer"))
try:
instrumentor.instrument()
channel = grpc.aio.insecure_channel("localhost:25565")
stub = test_server_pb2_grpc.GRPCTestServerStub(channel)
response = await simple_method(stub)
assert response.response_data == "data"
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
finally:
instrumentor.uninstrument()
async def test_unary_unary_filtered(self):
response = await simple_method(self._stub)
assert response.response_data == "data"
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 0)
async def test_unary_stream_filtered(self):
async for response in server_streaming_method(self._stub):
self.assertEqual(response.response_data, "data")
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 0)
async def test_stream_unary_filtered(self):
response = await client_streaming_method(self._stub)
assert response.response_data == "data"
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 0)
async def test_stream_stream_filtered(self):
async for response in bidirectional_streaming_method(self._stub):
self.assertEqual(response.response_data, "data")
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 0)
test_aio_client_interceptor_hooks.py 0000664 0000000 0000000 00000005536 15270700723 0042532 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-grpc/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
from unittest import IsolatedAsyncioTestCase
import grpc
from opentelemetry.instrumentation.grpc import GrpcAioInstrumentorClient
from opentelemetry.test.test_base import TestBase
from ._aio_client import simple_method
from ._server import create_test_server
from .protobuf import test_server_pb2_grpc # pylint: disable=no-name-in-module
def request_hook(span, request):
span.set_attribute("request_data", request.request_data)
def response_hook(span, response):
span.set_attribute("response_data", response)
def request_hook_with_exception(_span, _request):
raise Exception() # pylint: disable=broad-exception-raised
def response_hook_with_exception(_span, _response):
raise Exception() # pylint: disable=broad-exception-raised
class TestAioClientInterceptorWithHooks(TestBase, IsolatedAsyncioTestCase):
def setUp(self):
super().setUp()
self.server = create_test_server(25565)
self.server.start()
def tearDown(self):
super().tearDown()
self.server.stop(None)
async def test_request_and_response_hooks(self):
instrumentor = GrpcAioInstrumentorClient()
try:
instrumentor.instrument(
request_hook=request_hook,
response_hook=response_hook,
)
channel = grpc.aio.insecure_channel(
"localhost:25565",
)
stub = test_server_pb2_grpc.GRPCTestServerStub(channel)
response = await simple_method(stub)
assert response.response_data == "data"
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
span = spans[0]
self.assertIn("request_data", span.attributes)
self.assertEqual(span.attributes["request_data"], "data")
self.assertIn("response_data", span.attributes)
self.assertEqual(span.attributes["response_data"], "")
finally:
instrumentor.uninstrument()
async def test_hooks_with_exception(self):
instrumentor = GrpcAioInstrumentorClient()
try:
instrumentor.instrument(
request_hook=request_hook_with_exception,
response_hook=response_hook_with_exception,
)
channel = grpc.aio.insecure_channel(
"localhost:25565",
)
stub = test_server_pb2_grpc.GRPCTestServerStub(channel)
response = await simple_method(stub)
assert response.response_data == "data"
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
span = spans[0]
self.assertEqual(span.name, "/GRPCTestServer/SimpleMethod")
finally:
instrumentor.uninstrument()
test_aio_server_interceptor.py 0000664 0000000 0000000 00000060317 15270700723 0041355 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-grpc/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
import asyncio
from unittest import IsolatedAsyncioTestCase
import grpc
import grpc.aio
import opentelemetry.instrumentation.grpc
from opentelemetry import trace
from opentelemetry.instrumentation.grpc import (
GrpcAioInstrumentorServer,
aio_server_interceptor,
)
from opentelemetry.instrumentation.utils import suppress_instrumentation
from opentelemetry.sdk import trace as trace_sdk
from opentelemetry.semconv._incubating.attributes.net_attributes import (
NET_PEER_IP,
NET_PEER_NAME,
)
from opentelemetry.semconv._incubating.attributes.rpc_attributes import (
RPC_GRPC_STATUS_CODE,
RPC_METHOD,
RPC_SERVICE,
RPC_SYSTEM,
)
from opentelemetry.test.test_base import TestBase
from opentelemetry.trace import StatusCode
from .protobuf.test_server_pb2 import Request, Response
from .protobuf.test_server_pb2_grpc import (
GRPCTestServerServicer,
add_GRPCTestServerServicer_to_server,
)
# pylint:disable=unused-argument
# pylint:disable=no-self-use
class Servicer(GRPCTestServerServicer):
"""Our test servicer"""
# pylint:disable=C0103
async def SimpleMethod(self, request, context):
return Response(
server_id=request.client_id,
response_data=request.request_data,
)
# pylint:disable=C0103
async def ServerStreamingMethod(self, request, context):
for data in ("one", "two", "three"):
yield Response(
server_id=request.client_id,
response_data=data,
)
class SuppressAioRpcInterceptor(grpc.aio.ServerInterceptor):
"""An interceptor which runs the rest of the server interceptor chain
with instrumentation suppressed."""
async def intercept_service(self, continuation, handler_call_details):
with suppress_instrumentation():
return await continuation(handler_call_details)
async def run_with_test_server(runnable, servicer=Servicer(), interceptors=None):
server = grpc.aio.server(interceptors=interceptors)
add_GRPCTestServerServicer_to_server(servicer, server)
port = server.add_insecure_port("[::]:0")
channel = grpc.aio.insecure_channel(f"localhost:{port:d}")
await server.start()
try:
resp = await runnable(channel)
finally:
await server.stop(1000)
return resp
class TestOpenTelemetryAioServerInterceptor(TestBase, IsolatedAsyncioTestCase):
async def test_instrumentor(self):
"""Check that automatic instrumentation configures the interceptor"""
rpc_call = "/GRPCTestServer/SimpleMethod"
grpc_aio_server_instrumentor = GrpcAioInstrumentorServer()
try:
grpc_aio_server_instrumentor.instrument()
async def request(channel):
request = Request(client_id=1, request_data="test")
msg = request.SerializeToString()
return await channel.unary_unary(rpc_call)(msg)
await run_with_test_server(request)
spans_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans_list), 1)
span = spans_list[0]
self.assertEqual(span.name, rpc_call)
self.assertIs(span.kind, trace.SpanKind.SERVER)
# Check version and name in span's instrumentation info
self.assertEqualSpanInstrumentationScope(span, opentelemetry.instrumentation.grpc)
# Check attributes
self.assertSpanHasAttributes(
span,
{
NET_PEER_IP: "[::1]",
NET_PEER_NAME: "localhost",
RPC_METHOD: "SimpleMethod",
RPC_SERVICE: "GRPCTestServer",
RPC_SYSTEM: "grpc",
RPC_GRPC_STATUS_CODE: grpc.StatusCode.OK.value[0],
},
)
finally:
grpc_aio_server_instrumentor.uninstrument()
async def test_uninstrument(self):
"""Check that uninstrument removes the interceptor"""
rpc_call = "/GRPCTestServer/SimpleMethod"
grpc_aio_server_instrumentor = GrpcAioInstrumentorServer()
grpc_aio_server_instrumentor.instrument()
grpc_aio_server_instrumentor.uninstrument()
async def request(channel):
request = Request(client_id=1, request_data="test")
msg = request.SerializeToString()
return await channel.unary_unary(rpc_call)(msg)
await run_with_test_server(request)
spans_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans_list), 0)
async def test_create_span(self):
"""Check that the interceptor wraps calls with spans server-side."""
rpc_call = "/GRPCTestServer/SimpleMethod"
async def request(channel):
request = Request(client_id=1, request_data="test")
msg = request.SerializeToString()
return await channel.unary_unary(rpc_call)(msg)
await run_with_test_server(request, interceptors=[aio_server_interceptor()])
spans_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans_list), 1)
span = spans_list[0]
self.assertEqual(span.name, rpc_call)
self.assertIs(span.kind, trace.SpanKind.SERVER)
# Check version and name in span's instrumentation info
self.assertEqualSpanInstrumentationScope(span, opentelemetry.instrumentation.grpc)
# Check attributes
self.assertSpanHasAttributes(
span,
{
NET_PEER_IP: "[::1]",
NET_PEER_NAME: "localhost",
RPC_METHOD: "SimpleMethod",
RPC_SERVICE: "GRPCTestServer",
RPC_SYSTEM: "grpc",
RPC_GRPC_STATUS_CODE: grpc.StatusCode.OK.value[0],
},
)
async def test_create_two_spans(self):
"""Verify that the interceptor captures sub spans within the given
trace"""
rpc_call = "/GRPCTestServer/SimpleMethod"
class TwoSpanServicer(GRPCTestServerServicer):
# pylint:disable=C0103
async def SimpleMethod(self, request, context):
# create another span
tracer = trace.get_tracer(__name__)
with tracer.start_as_current_span("child") as child:
child.add_event("child event")
return Response(
server_id=request.client_id,
response_data=request.request_data,
)
async def request(channel):
request = Request(client_id=1, request_data="test")
msg = request.SerializeToString()
return await channel.unary_unary(rpc_call)(msg)
await run_with_test_server(
request,
servicer=TwoSpanServicer(),
interceptors=[aio_server_interceptor()],
)
spans_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans_list), 2)
child_span = spans_list[0]
parent_span = spans_list[1]
self.assertEqual(parent_span.name, rpc_call)
self.assertIs(parent_span.kind, trace.SpanKind.SERVER)
# Check version and name in span's instrumentation info
self.assertEqualSpanInstrumentationScope(parent_span, opentelemetry.instrumentation.grpc)
# Check attributes
self.assertSpanHasAttributes(
parent_span,
{
NET_PEER_IP: "[::1]",
NET_PEER_NAME: "localhost",
RPC_METHOD: "SimpleMethod",
RPC_SERVICE: "GRPCTestServer",
RPC_SYSTEM: "grpc",
RPC_GRPC_STATUS_CODE: grpc.StatusCode.OK.value[0],
},
)
# Check the child span
self.assertEqual(child_span.name, "child")
self.assertEqual(parent_span.context.trace_id, child_span.context.trace_id)
async def test_create_span_streaming(self):
"""Check that the interceptor wraps calls with spans server-side, on a
streaming call."""
rpc_call = "/GRPCTestServer/ServerStreamingMethod"
async def request(channel):
request = Request(client_id=1, request_data="test")
msg = request.SerializeToString()
async for response in channel.unary_stream(rpc_call)(msg):
print(response)
await run_with_test_server(request, interceptors=[aio_server_interceptor()])
spans_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans_list), 1)
span = spans_list[0]
self.assertEqual(span.name, rpc_call)
self.assertIs(span.kind, trace.SpanKind.SERVER)
# Check version and name in span's instrumentation info
self.assertEqualSpanInstrumentationScope(span, opentelemetry.instrumentation.grpc)
# Check attributes
self.assertSpanHasAttributes(
span,
{
NET_PEER_IP: "[::1]",
NET_PEER_NAME: "localhost",
RPC_METHOD: "ServerStreamingMethod",
RPC_SERVICE: "GRPCTestServer",
RPC_SYSTEM: "grpc",
RPC_GRPC_STATUS_CODE: grpc.StatusCode.OK.value[0],
},
)
async def test_create_two_spans_streaming(self):
"""Verify that the interceptor captures sub spans within the given
trace"""
rpc_call = "/GRPCTestServer/ServerStreamingMethod"
class TwoSpanServicer(GRPCTestServerServicer):
# pylint:disable=C0103
async def ServerStreamingMethod(self, request, context):
# create another span
tracer = trace.get_tracer(__name__)
with tracer.start_as_current_span("child") as child:
child.add_event("child event")
for data in ("one", "two", "three"):
yield Response(
server_id=request.client_id,
response_data=data,
)
async def request(channel):
request = Request(client_id=1, request_data="test")
msg = request.SerializeToString()
async for response in channel.unary_stream(rpc_call)(msg):
print(response)
await run_with_test_server(
request,
servicer=TwoSpanServicer(),
interceptors=[aio_server_interceptor()],
)
spans_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans_list), 2)
child_span = spans_list[0]
parent_span = spans_list[1]
self.assertEqual(parent_span.name, rpc_call)
self.assertIs(parent_span.kind, trace.SpanKind.SERVER)
# Check version and name in span's instrumentation info
self.assertEqualSpanInstrumentationScope(parent_span, opentelemetry.instrumentation.grpc)
# Check attributes
self.assertSpanHasAttributes(
parent_span,
{
NET_PEER_IP: "[::1]",
NET_PEER_NAME: "localhost",
RPC_METHOD: "ServerStreamingMethod",
RPC_SERVICE: "GRPCTestServer",
RPC_SYSTEM: "grpc",
RPC_GRPC_STATUS_CODE: grpc.StatusCode.OK.value[0],
},
)
# Check the child span
self.assertEqual(child_span.name, "child")
self.assertEqual(parent_span.context.trace_id, child_span.context.trace_id)
async def test_suppress_instrumentation(self):
"""Check that no span is created for a call when instrumentation
is suppressed."""
rpc_call = "/GRPCTestServer/SimpleMethod"
async def request(channel):
request = Request(client_id=1, request_data="test")
msg = request.SerializeToString()
return await channel.unary_unary(rpc_call)(msg)
await run_with_test_server(
request,
interceptors=[
SuppressAioRpcInterceptor(),
aio_server_interceptor(),
],
)
spans_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans_list), 0)
async def test_suppress_instrumentation_streaming(self):
"""Check that no span is created for a streaming call when
instrumentation is suppressed."""
rpc_call = "/GRPCTestServer/ServerStreamingMethod"
async def request(channel):
request = Request(client_id=1, request_data="test")
msg = request.SerializeToString()
async for response in channel.unary_stream(rpc_call)(msg):
print(response)
await run_with_test_server(
request,
interceptors=[
SuppressAioRpcInterceptor(),
aio_server_interceptor(),
],
)
spans_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans_list), 0)
async def test_span_lifetime(self):
"""Verify that the interceptor captures sub spans within the given
trace"""
rpc_call = "/GRPCTestServer/SimpleMethod"
class SpanLifetimeServicer(GRPCTestServerServicer):
# pylint:disable=C0103
async def SimpleMethod(self, request, context):
self.span = trace.get_current_span()
return Response(
server_id=request.client_id,
response_data=request.request_data,
)
async def request(channel):
request = Request(client_id=1, request_data="test")
msg = request.SerializeToString()
return await channel.unary_unary(rpc_call)(msg)
lifetime_servicer = SpanLifetimeServicer()
active_span_before_call = trace.get_current_span()
await run_with_test_server(
request,
servicer=lifetime_servicer,
interceptors=[aio_server_interceptor()],
)
active_span_in_handler = lifetime_servicer.span
active_span_after_call = trace.get_current_span()
self.assertEqual(active_span_before_call, trace.INVALID_SPAN)
self.assertEqual(active_span_after_call, trace.INVALID_SPAN)
self.assertIsInstance(active_span_in_handler, trace_sdk.Span)
self.assertIsNone(active_span_in_handler.parent)
async def test_sequential_server_spans(self):
"""Check that sequential RPCs get separate server spans."""
rpc_call = "/GRPCTestServer/SimpleMethod"
async def request(channel):
request = Request(client_id=1, request_data="test")
msg = request.SerializeToString()
return await channel.unary_unary(rpc_call)(msg)
async def sequential_requests(channel):
await request(channel)
await request(channel)
await run_with_test_server(sequential_requests, interceptors=[aio_server_interceptor()])
spans_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans_list), 2)
span1 = spans_list[0]
span2 = spans_list[1]
# Spans should belong to separate traces
self.assertNotEqual(span1.context.span_id, span2.context.span_id)
self.assertNotEqual(span1.context.trace_id, span2.context.trace_id)
for span in (span1, span2):
# each should be a root span
self.assertIsNone(span2.parent)
# check attributes
self.assertSpanHasAttributes(
span,
{
NET_PEER_IP: "[::1]",
NET_PEER_NAME: "localhost",
RPC_METHOD: "SimpleMethod",
RPC_SERVICE: "GRPCTestServer",
RPC_SYSTEM: "grpc",
RPC_GRPC_STATUS_CODE: grpc.StatusCode.OK.value[0],
},
)
async def test_concurrent_server_spans(self):
"""Check that concurrent RPC calls don't interfere with each other.
This is the same check as test_sequential_server_spans except that the
RPCs are concurrent. Two handlers are invoked at the same time on two
separate threads. Each one should see a different active span and
context.
"""
rpc_call = "/GRPCTestServer/SimpleMethod"
latch = get_latch(2)
class LatchedServicer(GRPCTestServerServicer):
# pylint:disable=C0103
async def SimpleMethod(self, request, context):
await latch()
return Response(
server_id=request.client_id,
response_data=request.request_data,
)
async def request(channel):
request = Request(client_id=1, request_data="test")
msg = request.SerializeToString()
return await channel.unary_unary(rpc_call)(msg)
async def concurrent_requests(channel):
await asyncio.gather(request(channel), request(channel))
await run_with_test_server(
concurrent_requests,
servicer=LatchedServicer(),
interceptors=[aio_server_interceptor()],
)
spans_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans_list), 2)
span1 = spans_list[0]
span2 = spans_list[1]
# Spans should belong to separate traces
self.assertNotEqual(span1.context.span_id, span2.context.span_id)
self.assertNotEqual(span1.context.trace_id, span2.context.trace_id)
for span in (span1, span2):
# each should be a root span
self.assertIsNone(span2.parent)
# check attributes
self.assertSpanHasAttributes(
span,
{
NET_PEER_IP: "[::1]",
NET_PEER_NAME: "localhost",
RPC_METHOD: "SimpleMethod",
RPC_SERVICE: "GRPCTestServer",
RPC_SYSTEM: "grpc",
RPC_GRPC_STATUS_CODE: grpc.StatusCode.OK.value[0],
},
)
async def test_abort(self):
"""Check that we can catch an abort properly"""
rpc_call = "/GRPCTestServer/SimpleMethod"
failure_message = "failure message"
class AbortServicer(GRPCTestServerServicer):
# pylint:disable=C0103
async def SimpleMethod(self, request, context):
await context.abort(grpc.StatusCode.INTERNAL, failure_message)
testcase = self
async def request(channel):
request = Request(client_id=1, request_data=failure_message)
msg = request.SerializeToString()
with testcase.assertRaises(grpc.RpcError) as cm:
await channel.unary_unary(rpc_call)(msg)
self.assertEqual(cm.exception.code(), grpc.StatusCode.INTERNAL)
self.assertEqual(cm.exception.details(), failure_message)
await run_with_test_server(
request,
servicer=AbortServicer(),
interceptors=[aio_server_interceptor()],
)
spans_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans_list), 1)
span = spans_list[0]
self.assertEqual(span.name, rpc_call)
self.assertIs(span.kind, trace.SpanKind.SERVER)
# Check version and name in span's instrumentation info
self.assertEqualSpanInstrumentationScope(span, opentelemetry.instrumentation.grpc)
# make sure this span errored, with the right status and detail
self.assertEqual(span.status.status_code, StatusCode.ERROR)
self.assertEqual(
span.status.description,
f"{grpc.StatusCode.INTERNAL}:{failure_message}",
)
# Check attributes
self.assertSpanHasAttributes(
span,
{
NET_PEER_IP: "[::1]",
NET_PEER_NAME: "localhost",
RPC_METHOD: "SimpleMethod",
RPC_SERVICE: "GRPCTestServer",
RPC_SYSTEM: "grpc",
RPC_GRPC_STATUS_CODE: grpc.StatusCode.INTERNAL.value[0],
},
)
async def test_abort_with_trailing_metadata(self):
"""Check that we can catch an abort properly when trailing_metadata provided"""
rpc_call = "/GRPCTestServer/SimpleMethod"
failure_message = "failure message"
class AbortServicer(GRPCTestServerServicer):
# pylint:disable=C0103
async def SimpleMethod(self, request, context):
metadata = (("meta", "data"),)
await context.abort(
grpc.StatusCode.FAILED_PRECONDITION,
failure_message,
trailing_metadata=metadata,
)
testcase = self
async def request(channel):
request = Request(client_id=1, request_data=failure_message)
msg = request.SerializeToString()
with testcase.assertRaises(grpc.RpcError) as cm:
await channel.unary_unary(rpc_call)(msg)
self.assertEqual(cm.exception.code(), grpc.StatusCode.FAILED_PRECONDITION)
self.assertEqual(cm.exception.details(), failure_message)
await run_with_test_server(
request,
servicer=AbortServicer(),
interceptors=[aio_server_interceptor()],
)
spans_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans_list), 1)
span = spans_list[0]
self.assertEqual(span.name, rpc_call)
self.assertIs(span.kind, trace.SpanKind.SERVER)
# Check version and name in span's instrumentation info
self.assertEqualSpanInstrumentationScope(span, opentelemetry.instrumentation.grpc)
# make sure this span errored, with the right status and detail
self.assertEqual(span.status.status_code, StatusCode.UNSET)
self.assertEqual(span.status.description, None)
# Check attributes
self.assertSpanHasAttributes(
span,
{
NET_PEER_IP: "[::1]",
NET_PEER_NAME: "localhost",
RPC_METHOD: "SimpleMethod",
RPC_SERVICE: "GRPCTestServer",
RPC_SYSTEM: "grpc",
RPC_GRPC_STATUS_CODE: grpc.StatusCode.FAILED_PRECONDITION.value[0],
},
)
async def test_non_list_interceptors(self):
"""Check that we handle non-list interceptors correctly."""
grpc_server_instrumentor = GrpcAioInstrumentorServer()
grpc_server_instrumentor.instrument()
try:
rpc_call = "/GRPCTestServer/SimpleMethod"
async def request(channel):
request = Request(client_id=1, request_data="test")
msg = request.SerializeToString()
return await channel.unary_unary(rpc_call)(msg)
class MockInterceptor(grpc.aio.ServerInterceptor):
async def intercept_service(self, continuation, handler_call_details):
return await continuation(handler_call_details)
await run_with_test_server(request, interceptors=(MockInterceptor(),))
finally:
grpc_server_instrumentor.uninstrument()
spans_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans_list), 1)
span = spans_list[0]
self.assertEqual(span.name, rpc_call)
self.assertIs(span.kind, trace.SpanKind.SERVER)
# Check version and name in span's instrumentation info
self.assertEqualSpanInstrumentationScope(span, opentelemetry.instrumentation.grpc)
# Check attributes
self.assertSpanHasAttributes(
span,
{
NET_PEER_IP: "[::1]",
NET_PEER_NAME: "localhost",
RPC_METHOD: "SimpleMethod",
RPC_SERVICE: "GRPCTestServer",
RPC_SYSTEM: "grpc",
RPC_GRPC_STATUS_CODE: grpc.StatusCode.OK.value[0],
},
)
def get_latch(num):
"""Get a countdown latch function for use in n threads."""
cv = asyncio.Condition()
count = 0
async def countdown_latch():
"""Block until n-1 other threads have called."""
nonlocal count
async with cv:
count += 1
cv.notify()
async with cv:
while count < num:
await cv.wait()
return countdown_latch
test_aio_server_interceptor_filter.py 0000664 0000000 0000000 00000006671 15270700723 0042725 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-grpc/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
from unittest import IsolatedAsyncioTestCase
import grpc
import grpc.aio
from opentelemetry import trace
from opentelemetry.instrumentation.grpc import (
GrpcAioInstrumentorServer,
aio_server_interceptor,
filters,
)
from opentelemetry.test.test_base import TestBase
from .protobuf.test_server_pb2 import Request
from .protobuf.test_server_pb2_grpc import add_GRPCTestServerServicer_to_server
from .test_aio_server_interceptor import Servicer
# pylint:disable=unused-argument
# pylint:disable=no-self-use
async def run_with_test_server(runnable, filter_=None, servicer=Servicer(), add_interceptor=True):
if add_interceptor:
interceptors = [aio_server_interceptor(filter_=filter_)]
server = grpc.aio.server(interceptors=interceptors)
else:
server = grpc.aio.server()
add_GRPCTestServerServicer_to_server(servicer, server)
port = server.add_insecure_port("[::]:0")
channel = grpc.aio.insecure_channel(f"localhost:{port:d}")
await server.start()
resp = await runnable(channel)
await server.stop(1000)
return resp
class TestOpenTelemetryAioServerInterceptor(TestBase, IsolatedAsyncioTestCase):
async def test_instrumentor(self):
"""Check that automatic instrumentation configures the interceptor"""
rpc_call = "/GRPCTestServer/SimpleMethod"
grpc_aio_server_instrumentor = GrpcAioInstrumentorServer(filter_=filters.method_name("NotSimpleMethod"))
try:
grpc_aio_server_instrumentor.instrument()
async def request(channel):
request = Request(client_id=1, request_data="test")
msg = request.SerializeToString()
return await channel.unary_unary(rpc_call)(msg)
await run_with_test_server(request, add_interceptor=False)
spans_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans_list), 0)
finally:
grpc_aio_server_instrumentor.uninstrument()
async def test_create_span(self):
"""
Check that the interceptor wraps calls with spans server-side when filter
passed and RPC matches the filter.
"""
rpc_call = "/GRPCTestServer/SimpleMethod"
async def request(channel):
request = Request(client_id=1, request_data="test")
msg = request.SerializeToString()
return await channel.unary_unary(rpc_call)(msg)
await run_with_test_server(
request,
filter_=filters.method_name("SimpleMethod"),
)
spans_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans_list), 1)
span = spans_list[0]
self.assertEqual(span.name, rpc_call)
self.assertIs(span.kind, trace.SpanKind.SERVER)
async def test_create_span_filtered(self):
"""Check that the interceptor wraps calls with spans server-side."""
rpc_call = "/GRPCTestServer/SimpleMethod"
async def request(channel):
request = Request(client_id=1, request_data="test")
msg = request.SerializeToString()
return await channel.unary_unary(rpc_call)(msg)
await run_with_test_server(
request,
filter_=filters.method_name("NotSimpleMethod"),
)
spans_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans_list), 0)
test_client_interceptor.py 0000664 0000000 0000000 00000032323 15270700723 0040471 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-grpc/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
# pylint:disable=cyclic-import
from unittest import mock
import grpc
import opentelemetry.instrumentation.grpc
from opentelemetry import trace
from opentelemetry.instrumentation.grpc import GrpcInstrumentorClient
from opentelemetry.instrumentation.grpc._client import (
OpenTelemetryClientInterceptor,
)
from opentelemetry.instrumentation.grpc.grpcext._interceptor import (
_UnaryClientInfo,
)
from opentelemetry.instrumentation.utils import suppress_instrumentation
from opentelemetry.propagate import get_global_textmap, set_global_textmap
from opentelemetry.sdk.trace import Span as SdkSpan
from opentelemetry.semconv._incubating.attributes.rpc_attributes import (
RPC_GRPC_STATUS_CODE,
RPC_METHOD,
RPC_SERVICE,
RPC_SYSTEM,
)
from opentelemetry.test.mock_textmap import MockTextMapPropagator
from opentelemetry.test.test_base import TestBase
from ._client import (
bidirectional_streaming_method,
client_streaming_method,
server_streaming_method,
simple_method,
simple_method_future,
)
from ._server import create_test_server
from .protobuf import test_server_pb2_grpc
from .protobuf.test_server_pb2 import Request
# User defined interceptor. Is used in the tests along with the opentelemetry client interceptor.
class Interceptor(
grpc.UnaryUnaryClientInterceptor,
grpc.UnaryStreamClientInterceptor,
grpc.StreamUnaryClientInterceptor,
grpc.StreamStreamClientInterceptor,
):
def __init__(self):
pass
def intercept_unary_unary(self, continuation, client_call_details, request):
return self._intercept_call(continuation, client_call_details, request)
def intercept_unary_stream(self, continuation, client_call_details, request):
return self._intercept_call(continuation, client_call_details, request)
def intercept_stream_unary(self, continuation, client_call_details, request_iterator):
return self._intercept_call(continuation, client_call_details, request_iterator)
def intercept_stream_stream(self, continuation, client_call_details, request_iterator):
return self._intercept_call(continuation, client_call_details, request_iterator)
@staticmethod
def _intercept_call(continuation, client_call_details, request_or_iterator):
return continuation(client_call_details, request_or_iterator)
class TestClientProto(TestBase):
def setUp(self):
super().setUp()
GrpcInstrumentorClient().instrument()
self.server = create_test_server(25565)
self.server.start()
# use a user defined interceptor along with the opentelemetry client interceptor
interceptors = [Interceptor()]
self.channel = grpc.insecure_channel("localhost:25565")
self.channel = grpc.intercept_channel(self.channel, *interceptors)
self._stub = test_server_pb2_grpc.GRPCTestServerStub(self.channel)
def tearDown(self):
super().tearDown()
GrpcInstrumentorClient().uninstrument()
self.server.stop(None)
self.channel.close()
def test_unary_unary_future(self):
simple_method_future(self._stub).result()
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
span = spans[0]
self.assertEqual(span.name, "/GRPCTestServer/SimpleMethod")
self.assertIs(span.kind, trace.SpanKind.CLIENT)
# Check version and name in span's instrumentation info
self.assertEqualSpanInstrumentationScope(span, opentelemetry.instrumentation.grpc)
def test_unary_unary(self):
simple_method(self._stub)
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
span = spans[0]
self.assertEqual(span.name, "/GRPCTestServer/SimpleMethod")
self.assertIs(span.kind, trace.SpanKind.CLIENT)
# Check version and name in span's instrumentation info
self.assertEqualSpanInstrumentationScope(span, opentelemetry.instrumentation.grpc)
self.assertSpanHasAttributes(
span,
{
RPC_METHOD: "SimpleMethod",
RPC_SERVICE: "GRPCTestServer",
RPC_SYSTEM: "grpc",
RPC_GRPC_STATUS_CODE: grpc.StatusCode.OK.value[0],
},
)
def test_unary_stream(self):
server_streaming_method(self._stub)
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
span = spans[0]
self.assertEqual(span.name, "/GRPCTestServer/ServerStreamingMethod")
self.assertIs(span.kind, trace.SpanKind.CLIENT)
# Check version and name in span's instrumentation info
self.assertEqualSpanInstrumentationScope(span, opentelemetry.instrumentation.grpc)
self.assertSpanHasAttributes(
span,
{
RPC_METHOD: "ServerStreamingMethod",
RPC_SERVICE: "GRPCTestServer",
RPC_SYSTEM: "grpc",
RPC_GRPC_STATUS_CODE: grpc.StatusCode.OK.value[0],
},
)
def test_stream_unary(self):
client_streaming_method(self._stub)
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
span = spans[0]
self.assertEqual(span.name, "/GRPCTestServer/ClientStreamingMethod")
self.assertIs(span.kind, trace.SpanKind.CLIENT)
# Check version and name in span's instrumentation info
self.assertEqualSpanInstrumentationScope(span, opentelemetry.instrumentation.grpc)
self.assertSpanHasAttributes(
span,
{
RPC_METHOD: "ClientStreamingMethod",
RPC_SERVICE: "GRPCTestServer",
RPC_SYSTEM: "grpc",
RPC_GRPC_STATUS_CODE: grpc.StatusCode.OK.value[0],
},
)
def test_stream_stream(self):
bidirectional_streaming_method(self._stub)
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
span = spans[0]
self.assertEqual(span.name, "/GRPCTestServer/BidirectionalStreamingMethod")
self.assertIs(span.kind, trace.SpanKind.CLIENT)
# Check version and name in span's instrumentation info
self.assertEqualSpanInstrumentationScope(span, opentelemetry.instrumentation.grpc)
self.assertSpanHasAttributes(
span,
{
RPC_METHOD: "BidirectionalStreamingMethod",
RPC_SERVICE: "GRPCTestServer",
RPC_SYSTEM: "grpc",
RPC_GRPC_STATUS_CODE: grpc.StatusCode.OK.value[0],
},
)
def test_stream_stream_preserves_call_interface(self):
"""Regression test for issue #1180.
Bidirectional streaming RPCs must return an object that implements
grpc.Call (add_done_callback, cancel, is_active, etc.) rather than
a bare generator. Before the fix, bidi streams were routed through
the generator-based _intercept_server_stream, which stripped the
grpc.Call interface and caused downstream code to crash with:
AttributeError: 'generator' object has no attribute 'add_done_callback'
"""
def request_messages():
for _ in range(5):
yield Request(client_id=1, request_data="data")
response_iterator = self._stub.BidirectionalStreamingMethod(request_messages(), metadata=(("key", "value"),))
for attr in ("add_done_callback", "cancel", "is_active"):
self.assertTrue(
hasattr(response_iterator, attr),
f"bidi stream response missing grpc.Call method '{attr}'",
)
list(response_iterator)
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
span = spans[0]
self.assertEqual(span.name, "/GRPCTestServer/BidirectionalStreamingMethod")
self.assertIs(span.kind, trace.SpanKind.CLIENT)
self.assertSpanHasAttributes(
span,
{
RPC_METHOD: "BidirectionalStreamingMethod",
RPC_SERVICE: "GRPCTestServer",
RPC_SYSTEM: "grpc",
RPC_GRPC_STATUS_CODE: grpc.StatusCode.OK.value[0],
},
)
def test_error_simple(self):
with self.assertRaises(grpc.RpcError):
simple_method(self._stub, error=True)
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
span = spans[0]
self.assertIs(
span.status.status_code,
trace.StatusCode.ERROR,
)
self.assertEqual(
span.attributes[RPC_GRPC_STATUS_CODE],
grpc.StatusCode.INVALID_ARGUMENT.value[0],
)
def test_error_stream_unary(self):
with self.assertRaises(grpc.RpcError):
client_streaming_method(self._stub, error=True)
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
span = spans[0]
self.assertIs(
span.status.status_code,
trace.StatusCode.ERROR,
)
self.assertEqual(
span.attributes[RPC_GRPC_STATUS_CODE],
grpc.StatusCode.INVALID_ARGUMENT.value[0],
)
def test_error_unary_stream(self):
with self.assertRaises(grpc.RpcError):
server_streaming_method(self._stub, error=True)
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
span = spans[0]
self.assertIs(
span.status.status_code,
trace.StatusCode.ERROR,
)
self.assertEqual(
span.attributes[RPC_GRPC_STATUS_CODE],
grpc.StatusCode.INVALID_ARGUMENT.value[0],
)
def test_error_stream_stream(self):
with self.assertRaises(grpc.RpcError):
bidirectional_streaming_method(self._stub, error=True)
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
span = spans[0]
self.assertIs(
span.status.status_code,
trace.StatusCode.ERROR,
)
self.assertEqual(
span.attributes[RPC_GRPC_STATUS_CODE],
grpc.StatusCode.INVALID_ARGUMENT.value[0],
)
def test_client_interceptor_falsy_response(
self,
):
"""ensure that client interceptor closes the span only once even if the response is falsy."""
with mock.patch.object(SdkSpan, "end") as span_end_mock:
tracer_provider, _exporter = self.create_tracer_provider()
tracer = tracer_provider.get_tracer(__name__)
interceptor = OpenTelemetryClientInterceptor(tracer)
def invoker(_request, _metadata):
return {}
request = Request(client_id=1, request_data="data")
interceptor.intercept_unary(
request,
{},
_UnaryClientInfo(
full_method="/GRPCTestServer/SimpleMethod",
timeout=None,
),
invoker=invoker,
)
self.assertEqual(span_end_mock.call_count, 1)
def test_client_interceptor_trace_context_propagation(
self,
): # pylint: disable=no-self-use
"""ensure that client interceptor correctly inject trace context into all outgoing requests."""
previous_propagator = get_global_textmap()
try:
set_global_textmap(MockTextMapPropagator())
interceptor = OpenTelemetryClientInterceptor(trace.NoOpTracer())
carrier = tuple()
def invoker(request, metadata):
nonlocal carrier
carrier = metadata
return {}
request = Request(client_id=1, request_data="data")
interceptor.intercept_unary(
request,
{},
_UnaryClientInfo(full_method="/GRPCTestServer/SimpleMethod", timeout=None),
invoker=invoker,
)
assert len(carrier) == 2
assert carrier[0][0] == "mock-traceid"
assert carrier[0][1] == "0"
assert carrier[1][0] == "mock-spanid"
assert carrier[1][1] == "0"
finally:
set_global_textmap(previous_propagator)
def test_unary_unary_with_suppress_key(self):
with suppress_instrumentation():
simple_method(self._stub)
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 0)
def test_unary_stream_with_suppress_key(self):
with suppress_instrumentation():
server_streaming_method(self._stub)
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 0)
def test_stream_unary_with_suppress_key(self):
with suppress_instrumentation():
client_streaming_method(self._stub)
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 0)
def test_stream_stream_with_suppress_key(self):
with suppress_instrumentation():
bidirectional_streaming_method(self._stub)
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 0)
test_client_interceptor_filter.py 0000664 0000000 0000000 00000051756 15270700723 0042051 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-grpc/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
# pylint:disable=cyclic-import
import os
from unittest import mock
import grpc
import opentelemetry.instrumentation.grpc
from opentelemetry import trace
from opentelemetry.instrumentation.grpc import GrpcInstrumentorClient, filters
from opentelemetry.instrumentation.grpc._client import (
OpenTelemetryClientInterceptor,
)
from opentelemetry.instrumentation.grpc.grpcext._interceptor import (
_UnaryClientInfo,
)
from opentelemetry.instrumentation.utils import suppress_instrumentation
from opentelemetry.propagate import get_global_textmap, set_global_textmap
from opentelemetry.semconv._incubating.attributes.rpc_attributes import (
RPC_GRPC_STATUS_CODE,
RPC_METHOD,
RPC_SERVICE,
RPC_SYSTEM,
)
from opentelemetry.test.mock_textmap import MockTextMapPropagator
from opentelemetry.test.test_base import TestBase
from ._client import (
bidirectional_streaming_method,
client_streaming_method,
server_streaming_method,
simple_method,
simple_method_future,
)
from ._server import create_test_server
from .protobuf import test_server_pb2_grpc
from .protobuf.test_server_pb2 import Request
# User defined interceptor. Is used in the tests along with the opentelemetry client interceptor.
class Interceptor(
grpc.UnaryUnaryClientInterceptor,
grpc.UnaryStreamClientInterceptor,
grpc.StreamUnaryClientInterceptor,
grpc.StreamStreamClientInterceptor,
):
def __init__(self):
pass
def intercept_unary_unary(self, continuation, client_call_details, request):
return self._intercept_call(continuation, client_call_details, request)
def intercept_unary_stream(self, continuation, client_call_details, request):
return self._intercept_call(continuation, client_call_details, request)
def intercept_stream_unary(self, continuation, client_call_details, request_iterator):
return self._intercept_call(continuation, client_call_details, request_iterator)
def intercept_stream_stream(self, continuation, client_call_details, request_iterator):
return self._intercept_call(continuation, client_call_details, request_iterator)
@staticmethod
def _intercept_call(continuation, client_call_details, request_or_iterator):
return continuation(client_call_details, request_or_iterator)
class TestClientProtoFilterMethodName(TestBase):
def setUp(self):
super().setUp()
GrpcInstrumentorClient(filter_=filters.method_name("SimpleMethod")).instrument()
self.server = create_test_server(25565)
self.server.start()
# use a user defined interceptor along with the opentelemetry client interceptor
interceptors = [Interceptor()]
self.channel = grpc.insecure_channel("localhost:25565")
self.channel = grpc.intercept_channel(self.channel, *interceptors)
self._stub = test_server_pb2_grpc.GRPCTestServerStub(self.channel)
def tearDown(self):
super().tearDown()
GrpcInstrumentorClient().uninstrument()
self.server.stop(None)
self.channel.close()
def test_unary_unary_future(self):
simple_method_future(self._stub).result()
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
span = spans[0]
self.assertEqual(span.name, "/GRPCTestServer/SimpleMethod")
self.assertIs(span.kind, trace.SpanKind.CLIENT)
# Check version and name in span's instrumentation info
self.assertEqualSpanInstrumentationScope(span, opentelemetry.instrumentation.grpc)
def test_unary_unary(self):
simple_method(self._stub)
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
span = spans[0]
self.assertEqual(span.name, "/GRPCTestServer/SimpleMethod")
self.assertIs(span.kind, trace.SpanKind.CLIENT)
# Check version and name in span's instrumentation info
self.assertEqualSpanInstrumentationScope(span, opentelemetry.instrumentation.grpc)
self.assertSpanHasAttributes(
span,
{
RPC_METHOD: "SimpleMethod",
RPC_SERVICE: "GRPCTestServer",
RPC_SYSTEM: "grpc",
RPC_GRPC_STATUS_CODE: grpc.StatusCode.OK.value[0],
},
)
def test_unary_stream(self):
server_streaming_method(self._stub)
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 0)
def test_stream_unary(self):
client_streaming_method(self._stub)
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 0)
def test_stream_stream(self):
bidirectional_streaming_method(self._stub)
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 0)
def test_error_simple(self):
with self.assertRaises(grpc.RpcError):
simple_method(self._stub, error=True)
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
span = spans[0]
self.assertIs(
span.status.status_code,
trace.StatusCode.ERROR,
)
def test_error_stream_unary(self):
with self.assertRaises(grpc.RpcError):
client_streaming_method(self._stub, error=True)
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 0)
def test_error_unary_stream(self):
with self.assertRaises(grpc.RpcError):
server_streaming_method(self._stub, error=True)
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 0)
def test_error_stream_stream(self):
with self.assertRaises(grpc.RpcError):
bidirectional_streaming_method(self._stub, error=True)
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 0)
def test_client_interceptor_trace_context_propagation(
self,
): # pylint: disable=no-self-use
"""ensure that client interceptor correctly inject trace context into all outgoing requests."""
previous_propagator = get_global_textmap()
try:
set_global_textmap(MockTextMapPropagator())
interceptor = OpenTelemetryClientInterceptor(trace.NoOpTracer())
carrier = tuple()
def invoker(request, metadata):
nonlocal carrier
carrier = metadata
return {}
request = Request(client_id=1, request_data="data")
interceptor.intercept_unary(
request,
{},
_UnaryClientInfo(full_method="/GRPCTestServer/SimpleMethod", timeout=None),
invoker=invoker,
)
assert len(carrier) == 2
assert carrier[0][0] == "mock-traceid"
assert carrier[0][1] == "0"
assert carrier[1][0] == "mock-spanid"
assert carrier[1][1] == "0"
finally:
set_global_textmap(previous_propagator)
class TestClientProtoFilterMethodPrefix(TestBase):
def setUp(self):
super().setUp()
GrpcInstrumentorClient(filter_=filters.method_prefix("Simple")).instrument()
self.server = create_test_server(25565)
self.server.start()
# use a user defined interceptor along with the opentelemetry client interceptor
interceptors = [Interceptor()]
self.channel = grpc.insecure_channel("localhost:25565")
self.channel = grpc.intercept_channel(self.channel, *interceptors)
self._stub = test_server_pb2_grpc.GRPCTestServerStub(self.channel)
def tearDown(self):
super().tearDown()
GrpcInstrumentorClient().uninstrument()
self.server.stop(None)
self.channel.close()
def test_unary_unary_future(self):
simple_method_future(self._stub).result()
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
span = spans[0]
self.assertEqual(span.name, "/GRPCTestServer/SimpleMethod")
self.assertIs(span.kind, trace.SpanKind.CLIENT)
# Check version and name in span's instrumentation info
self.assertEqualSpanInstrumentationScope(span, opentelemetry.instrumentation.grpc)
def test_unary_unary(self):
simple_method(self._stub)
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
span = spans[0]
self.assertEqual(span.name, "/GRPCTestServer/SimpleMethod")
self.assertIs(span.kind, trace.SpanKind.CLIENT)
# Check version and name in span's instrumentation info
self.assertEqualSpanInstrumentationScope(span, opentelemetry.instrumentation.grpc)
self.assertSpanHasAttributes(
span,
{
RPC_METHOD: "SimpleMethod",
RPC_SERVICE: "GRPCTestServer",
RPC_SYSTEM: "grpc",
RPC_GRPC_STATUS_CODE: grpc.StatusCode.OK.value[0],
},
)
def test_unary_stream(self):
server_streaming_method(self._stub)
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 0)
def test_stream_unary(self):
client_streaming_method(self._stub)
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 0)
def test_stream_stream(self):
bidirectional_streaming_method(self._stub)
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 0)
def test_error_simple(self):
with self.assertRaises(grpc.RpcError):
simple_method(self._stub, error=True)
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
span = spans[0]
self.assertIs(
span.status.status_code,
trace.StatusCode.ERROR,
)
def test_error_stream_unary(self):
with self.assertRaises(grpc.RpcError):
client_streaming_method(self._stub, error=True)
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 0)
def test_error_unary_stream(self):
with self.assertRaises(grpc.RpcError):
server_streaming_method(self._stub, error=True)
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 0)
def test_error_stream_stream(self):
with self.assertRaises(grpc.RpcError):
bidirectional_streaming_method(self._stub, error=True)
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 0)
def test_client_interceptor_trace_context_propagation(
self,
): # pylint: disable=no-self-use
"""ensure that client interceptor correctly inject trace context into all outgoing requests."""
previous_propagator = get_global_textmap()
try:
set_global_textmap(MockTextMapPropagator())
interceptor = OpenTelemetryClientInterceptor(trace.NoOpTracer())
carrier = tuple()
def invoker(request, metadata):
nonlocal carrier
carrier = metadata
return {}
request = Request(client_id=1, request_data="data")
interceptor.intercept_unary(
request,
{},
_UnaryClientInfo(full_method="/GRPCTestServer/SimpleMethod", timeout=None),
invoker=invoker,
)
assert len(carrier) == 2
assert carrier[0][0] == "mock-traceid"
assert carrier[0][1] == "0"
assert carrier[1][0] == "mock-spanid"
assert carrier[1][1] == "0"
finally:
set_global_textmap(previous_propagator)
class TestClientProtoFilterByEnv(TestBase):
def setUp(self):
with mock.patch.dict(
os.environ,
{"OTEL_PYTHON_GRPC_EXCLUDED_SERVICES": "GRPCMockServer,GRPCTestServer"},
):
super().setUp()
GrpcInstrumentorClient().instrument()
self.server = create_test_server(25565)
self.server.start()
# use a user defined interceptor along with the opentelemetry client interceptor
interceptors = [Interceptor()]
self.channel = grpc.insecure_channel("localhost:25565")
self.channel = grpc.intercept_channel(self.channel, *interceptors)
self._stub = test_server_pb2_grpc.GRPCTestServerStub(self.channel)
def tearDown(self):
super().tearDown()
GrpcInstrumentorClient().uninstrument()
self.server.stop(None)
self.channel.close()
def test_unary_unary_future(self):
simple_method_future(self._stub).result()
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 0)
def test_unary_unary(self):
simple_method(self._stub)
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 0)
class TestClientProtoFilterByEnvAndOption(TestBase):
def setUp(self):
with mock.patch.dict(
os.environ,
{"OTEL_PYTHON_GRPC_EXCLUDED_SERVICES": "GRPCMockServer"},
):
super().setUp()
GrpcInstrumentorClient(filter_=filters.service_prefix("GRPCTestServer")).instrument()
self.server = create_test_server(25565)
self.server.start()
# use a user defined interceptor along with the opentelemetry client interceptor
interceptors = [Interceptor()]
self.channel = grpc.insecure_channel("localhost:25565")
self.channel = grpc.intercept_channel(self.channel, *interceptors)
self._stub = test_server_pb2_grpc.GRPCTestServerStub(self.channel)
def tearDown(self):
super().tearDown()
GrpcInstrumentorClient().uninstrument()
self.server.stop(None)
self.channel.close()
def test_unary_unary_future(self):
simple_method_future(self._stub).result()
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
span = spans[0]
self.assertEqual(span.name, "/GRPCTestServer/SimpleMethod")
self.assertIs(span.kind, trace.SpanKind.CLIENT)
# Check version and name in span's instrumentation info
self.assertEqualSpanInstrumentationScope(span, opentelemetry.instrumentation.grpc)
def test_unary_unary(self):
simple_method(self._stub)
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
span = spans[0]
self.assertEqual(span.name, "/GRPCTestServer/SimpleMethod")
self.assertIs(span.kind, trace.SpanKind.CLIENT)
# Check version and name in span's instrumentation info
self.assertEqualSpanInstrumentationScope(span, opentelemetry.instrumentation.grpc)
self.assertSpanHasAttributes(
span,
{
RPC_METHOD: "SimpleMethod",
RPC_SERVICE: "GRPCTestServer",
RPC_SYSTEM: "grpc",
RPC_GRPC_STATUS_CODE: grpc.StatusCode.OK.value[0],
},
)
def test_unary_stream(self):
server_streaming_method(self._stub)
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
span = spans[0]
self.assertEqual(span.name, "/GRPCTestServer/ServerStreamingMethod")
self.assertIs(span.kind, trace.SpanKind.CLIENT)
# Check version and name in span's instrumentation info
self.assertEqualSpanInstrumentationScope(span, opentelemetry.instrumentation.grpc)
self.assertSpanHasAttributes(
span,
{
RPC_METHOD: "ServerStreamingMethod",
RPC_SERVICE: "GRPCTestServer",
RPC_SYSTEM: "grpc",
RPC_GRPC_STATUS_CODE: grpc.StatusCode.OK.value[0],
},
)
def test_stream_unary(self):
client_streaming_method(self._stub)
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
span = spans[0]
self.assertEqual(span.name, "/GRPCTestServer/ClientStreamingMethod")
self.assertIs(span.kind, trace.SpanKind.CLIENT)
# Check version and name in span's instrumentation info
self.assertEqualSpanInstrumentationScope(span, opentelemetry.instrumentation.grpc)
self.assertSpanHasAttributes(
span,
{
RPC_METHOD: "ClientStreamingMethod",
RPC_SERVICE: "GRPCTestServer",
RPC_SYSTEM: "grpc",
RPC_GRPC_STATUS_CODE: grpc.StatusCode.OK.value[0],
},
)
def test_stream_stream(self):
bidirectional_streaming_method(self._stub)
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
span = spans[0]
self.assertEqual(span.name, "/GRPCTestServer/BidirectionalStreamingMethod")
self.assertIs(span.kind, trace.SpanKind.CLIENT)
# Check version and name in span's instrumentation info
self.assertEqualSpanInstrumentationScope(span, opentelemetry.instrumentation.grpc)
self.assertSpanHasAttributes(
span,
{
RPC_METHOD: "BidirectionalStreamingMethod",
RPC_SERVICE: "GRPCTestServer",
RPC_SYSTEM: "grpc",
RPC_GRPC_STATUS_CODE: grpc.StatusCode.OK.value[0],
},
)
def test_error_simple(self):
with self.assertRaises(grpc.RpcError):
simple_method(self._stub, error=True)
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
span = spans[0]
self.assertIs(
span.status.status_code,
trace.StatusCode.ERROR,
)
def test_error_stream_unary(self):
with self.assertRaises(grpc.RpcError):
client_streaming_method(self._stub, error=True)
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
span = spans[0]
self.assertIs(
span.status.status_code,
trace.StatusCode.ERROR,
)
def test_error_unary_stream(self):
with self.assertRaises(grpc.RpcError):
server_streaming_method(self._stub, error=True)
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
span = spans[0]
self.assertIs(
span.status.status_code,
trace.StatusCode.ERROR,
)
def test_error_stream_stream(self):
with self.assertRaises(grpc.RpcError):
bidirectional_streaming_method(self._stub, error=True)
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
span = spans[0]
self.assertIs(
span.status.status_code,
trace.StatusCode.ERROR,
)
def test_client_interceptor_trace_context_propagation(
self,
): # pylint: disable=no-self-use
"""ensure that client interceptor correctly inject trace context into all outgoing requests."""
previous_propagator = get_global_textmap()
try:
set_global_textmap(MockTextMapPropagator())
interceptor = OpenTelemetryClientInterceptor(trace.NoOpTracer())
carrier = tuple()
def invoker(request, metadata):
nonlocal carrier
carrier = metadata
return {}
request = Request(client_id=1, request_data="data")
interceptor.intercept_unary(
request,
{},
_UnaryClientInfo(full_method="/GRPCTestServer/SimpleMethod", timeout=None),
invoker=invoker,
)
assert len(carrier) == 2
assert carrier[0][0] == "mock-traceid"
assert carrier[0][1] == "0"
assert carrier[1][0] == "mock-spanid"
assert carrier[1][1] == "0"
finally:
set_global_textmap(previous_propagator)
def test_unary_unary_with_suppress_key(self):
with suppress_instrumentation():
simple_method(self._stub)
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 0)
def test_unary_stream_with_suppress_key(self):
with suppress_instrumentation():
server_streaming_method(self._stub)
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 0)
def test_stream_unary_with_suppress_key(self):
with suppress_instrumentation():
client_streaming_method(self._stub)
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 0)
def test_stream_stream_with_suppress_key(self):
with suppress_instrumentation():
bidirectional_streaming_method(self._stub)
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 0)
test_client_interceptor_hooks.py 0000664 0000000 0000000 00000010223 15270700723 0041667 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-grpc/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
import grpc
from opentelemetry import trace
from opentelemetry.instrumentation.grpc import GrpcInstrumentorClient
from opentelemetry.test.test_base import TestBase
from ._client import simple_method
from ._server import create_test_server
from .protobuf import test_server_pb2_grpc
# User defined interceptor. Is used in the tests along with the opentelemetry client interceptor.
class Interceptor(
grpc.UnaryUnaryClientInterceptor,
grpc.UnaryStreamClientInterceptor,
grpc.StreamUnaryClientInterceptor,
grpc.StreamStreamClientInterceptor,
):
def __init__(self):
pass
def intercept_unary_unary(self, continuation, client_call_details, request):
return self._intercept_call(continuation, client_call_details, request)
def intercept_unary_stream(self, continuation, client_call_details, request):
return self._intercept_call(continuation, client_call_details, request)
def intercept_stream_unary(self, continuation, client_call_details, request_iterator):
return self._intercept_call(continuation, client_call_details, request_iterator)
def intercept_stream_stream(self, continuation, client_call_details, request_iterator):
return self._intercept_call(continuation, client_call_details, request_iterator)
@staticmethod
def _intercept_call(continuation, client_call_details, request_or_iterator):
return continuation(client_call_details, request_or_iterator)
def request_hook(span, request):
span.set_attribute("request_data", request.request_data)
def response_hook(span, response):
span.set_attribute("response_data", response.response_data)
def request_hook_with_exception(_span, _request):
raise Exception() # pylint: disable=broad-exception-raised
def response_hook_with_exception(_span, _response):
raise Exception() # pylint: disable=broad-exception-raised
class TestHooks(TestBase):
def setUp(self):
super().setUp()
self.server = create_test_server(25565)
self.server.start()
# use a user defined interceptor along with the opentelemetry client interceptor
self.interceptors = [Interceptor()]
def tearDown(self):
super().tearDown()
self.server.stop(None)
def test_response_and_request_hooks(self):
instrumentor = GrpcInstrumentorClient()
try:
instrumentor.instrument(
request_hook=request_hook,
response_hook=response_hook,
)
channel = grpc.insecure_channel("localhost:25565")
channel = grpc.intercept_channel(channel, *self.interceptors)
stub = test_server_pb2_grpc.GRPCTestServerStub(channel)
simple_method(stub)
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
span = spans[0]
self.assertEqual(span.name, "/GRPCTestServer/SimpleMethod")
self.assertIs(span.kind, trace.SpanKind.CLIENT)
self.assertIn("request_data", span.attributes)
self.assertEqual(span.attributes["request_data"], "data")
self.assertIn("response_data", span.attributes)
self.assertEqual(span.attributes["response_data"], "data")
finally:
instrumentor.uninstrument()
def test_hooks_with_exception(self):
instrumentor = GrpcInstrumentorClient()
try:
instrumentor.instrument(
request_hook=request_hook_with_exception,
response_hook=response_hook_with_exception,
)
channel = grpc.insecure_channel("localhost:25565")
channel = grpc.intercept_channel(channel, *self.interceptors)
stub = test_server_pb2_grpc.GRPCTestServerStub(channel)
simple_method(stub)
spans = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans), 1)
span = spans[0]
self.assertEqual(span.name, "/GRPCTestServer/SimpleMethod")
self.assertIs(span.kind, trace.SpanKind.CLIENT)
finally:
instrumentor.uninstrument()
test_filters.py 0000664 0000000 0000000 00000022414 15270700723 0036245 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-grpc/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
import collections
import grpc
import pytest
from opentelemetry.instrumentation.grpc import filters
class _HandlerCallDetails(
collections.namedtuple(
"_HanlderCallDetails",
(
"method",
"invocation_metadata",
),
),
grpc.HandlerCallDetails,
):
pass
class _UnaryClientInfo(collections.namedtuple("_UnaryClientInfo", ("full_method", "timeout"))):
pass
class _StreamClientInfo(
collections.namedtuple(
"_StreamClientInfo",
("full_method", "is_client_stream", "is_server_stream", "timeout"),
)
):
pass
@pytest.mark.parametrize(
"test_case",
[
(
True,
"SimpleMethod",
_HandlerCallDetails(
method="SimpleMethod",
invocation_metadata=[("tracer", "foo"), ("caller", "bar")],
),
),
(
True,
"SimpleMethod",
grpc.aio.ClientCallDetails(
method="SimpleMethod",
timeout=3000,
metadata=None,
credentials=None,
wait_for_ready=None,
),
),
(
True,
"SimpleMethod",
grpc.aio.ClientCallDetails(
method=b"SimpleMethod",
timeout=3000,
metadata=None,
credentials=None,
wait_for_ready=None,
),
),
(
False,
"SimpleMethod",
grpc.aio.ClientCallDetails(
method="NotSimpleMethod",
timeout=3000,
metadata=None,
credentials=None,
wait_for_ready=None,
),
),
(
False,
"SimpleMethod",
_HandlerCallDetails(
method="NotSimpleMethod",
invocation_metadata=[("tracer", "foo"), ("caller", "bar")],
),
),
(
True,
"SimpleMethod",
_UnaryClientInfo(
full_method="/GRPCTestServer/SimpleMethod",
timeout=3000,
),
),
(
False,
"SimpleMethod",
_UnaryClientInfo(
full_method="/GRPCTestServer/NotSimpleMethod",
timeout=3000,
),
),
(
True,
"SimpleMethod",
_StreamClientInfo(
full_method="/GRPCTestServer/SimpleMethod",
is_client_stream=True,
is_server_stream=False,
timeout=3000,
),
),
(
False,
"SimpleMethod",
_StreamClientInfo(
full_method="/GRPCTestServer/NotSimpleMethod",
is_client_stream=True,
is_server_stream=False,
timeout=3000,
),
),
],
)
def test_method_name(test_case):
fn = filters.method_name(test_case[1])
assert test_case[0] == fn(test_case[2])
@pytest.mark.parametrize(
"test_case",
[
(
True,
"Simple",
_HandlerCallDetails(
method="SimpleMethod",
invocation_metadata=[("tracer", "foo"), ("caller", "bar")],
),
),
(
False,
"Simple",
_HandlerCallDetails(
method="NotSimpleMethod",
invocation_metadata=[("tracer", "foo"), ("caller", "bar")],
),
),
(
True,
"Simple",
_UnaryClientInfo(
full_method="/GRPCTestServer/SimpleMethod",
timeout=3000,
),
),
(
False,
"Simple",
_UnaryClientInfo(
full_method="/GRPCTestServer/NotSimpleMethod",
timeout=3000,
),
),
(
True,
"Simple",
_StreamClientInfo(
full_method="/GRPCTestServer/SimpleMethod",
is_client_stream=True,
is_server_stream=False,
timeout=3000,
),
),
(
False,
"Simple",
_StreamClientInfo(
full_method="/GRPCTestServer/NotSimpleMethod",
is_client_stream=True,
is_server_stream=False,
timeout=3000,
),
),
],
)
def test_method_prefix(test_case):
fn = filters.method_prefix(test_case[1])
assert test_case[0] == fn(test_case[2])
@pytest.mark.parametrize(
"test_case",
[
(
True,
"GRPCTestServer",
_UnaryClientInfo(
full_method="/GRPCTestServer/SimpleMethod",
timeout=3000,
),
),
(
False,
"GRPCTestServer",
_UnaryClientInfo(
full_method="/GRPCRealServer/SimpleMethod",
timeout=3000,
),
),
(
True,
"GRPCTestServer",
_StreamClientInfo(
full_method="/GRPCTestServer/SimpleMethod",
is_client_stream=True,
is_server_stream=False,
timeout=3000,
),
),
(
False,
"GRPCTestServer",
_StreamClientInfo(
full_method="/GRPCRealServer/SimpleMethod",
is_client_stream=True,
is_server_stream=False,
timeout=3000,
),
),
],
)
def test_service_name(test_case):
fn = filters.service_name(test_case[1])
assert test_case[0] == fn(test_case[2])
@pytest.mark.parametrize(
"test_case",
[
(
True,
"GRPCTest",
_UnaryClientInfo(
full_method="/GRPCTestServer/SimpleMethod",
timeout=3000,
),
),
(
False,
"GRPCTest",
_UnaryClientInfo(
full_method="/GRPCRealServer/SimpleMethod",
timeout=3000,
),
),
(
True,
"GRPCTest",
_StreamClientInfo(
full_method="/GRPCTestServer/SimpleMethod",
is_client_stream=True,
is_server_stream=False,
timeout=3000,
),
),
(
False,
"GRPCTest",
_StreamClientInfo(
full_method="/GRPCRealServer/SimpleMethod",
is_client_stream=True,
is_server_stream=False,
timeout=3000,
),
),
],
)
def test_service_prefix(test_case):
fn = filters.service_prefix(test_case[1])
assert test_case[0] == fn(test_case[2])
@pytest.mark.parametrize(
"test_case",
[
(
True,
_UnaryClientInfo(
full_method="/grpc.health.v1.Health/Check",
timeout=3000,
),
),
(
False,
_UnaryClientInfo(
full_method="/GRPCRealServer/SimpleMethod",
timeout=3000,
),
),
(
True,
_StreamClientInfo(
full_method="/grpc.health.v1.Health/Check",
is_client_stream=True,
is_server_stream=False,
timeout=3000,
),
),
(
False,
_StreamClientInfo(
full_method="/GRPCRealServer/SimpleMethod",
is_client_stream=True,
is_server_stream=False,
timeout=3000,
),
),
],
)
def test_health_check(test_case):
fn = filters.health_check()
assert test_case[0] == fn(test_case[1])
@pytest.mark.parametrize(
"test_case",
[
(
True,
filters.all_of(
filters.method_name("SimpleMethod"),
filters.service_name("GRPCTestServer"),
),
_UnaryClientInfo(
full_method="/GRPCTestServer/SimpleMethod",
timeout=3000,
),
),
(
True,
filters.any_of(
filters.method_name("NotSimpleMethod"),
filters.service_name("GRPCTestServer"),
),
_UnaryClientInfo(
full_method="/GRPCTestServer/SimpleMethod",
timeout=3000,
),
),
(
True,
filters.any_of(
filters.service_name("GRPCMockServer"),
filters.service_name("GRPCTestServer"),
),
_UnaryClientInfo(
full_method="/GRPCTestServer/SimpleMethod",
timeout=3000,
),
),
(
False,
filters.negate(filters.method_name("SimpleMethod")),
_UnaryClientInfo(
full_method="/GRPCTestServer/SimpleMethod",
timeout=3000,
),
),
],
)
def test_all_any_negate(test_case):
fn = test_case[1]
assert test_case[0] == fn(test_case[2])
test_server_interceptor.py 0000664 0000000 0000000 00000062573 15270700723 0040533 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-grpc/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
# pylint:disable=unused-argument
# pylint:disable=no-self-use
import contextlib
import tempfile
import threading
from concurrent import futures
from unittest import mock
import grpc
import opentelemetry.instrumentation.grpc
from opentelemetry import trace
from opentelemetry.instrumentation.grpc import (
GrpcInstrumentorServer,
server_interceptor,
)
from opentelemetry.instrumentation.utils import suppress_instrumentation
from opentelemetry.sdk import trace as trace_sdk
from opentelemetry.semconv._incubating.attributes.net_attributes import (
NET_PEER_IP,
NET_PEER_NAME,
)
from opentelemetry.semconv._incubating.attributes.rpc_attributes import (
RPC_GRPC_STATUS_CODE,
RPC_METHOD,
RPC_SERVICE,
RPC_SYSTEM,
)
from opentelemetry.test.test_base import TestBase
from opentelemetry.trace import StatusCode
from .protobuf.test_server_pb2 import Request, Response
from .protobuf.test_server_pb2_grpc import (
GRPCTestServerServicer,
add_GRPCTestServerServicer_to_server,
)
class UnaryUnaryMethodHandler(grpc.RpcMethodHandler):
def __init__(self, handler):
self.request_streaming = False
self.response_streaming = False
self.request_deserializer = None
self.response_serializer = None
self.unary_unary = handler
self.unary_stream = None
self.stream_unary = None
self.stream_stream = None
class UnaryUnaryRpcHandler(grpc.GenericRpcHandler):
def __init__(self, handler):
self._unary_unary_handler = handler
def service(self, handler_call_details):
return UnaryUnaryMethodHandler(self._unary_unary_handler)
class SuppressRpcInterceptor(grpc.ServerInterceptor):
"""An interceptor which runs the rest of the server interceptor chain
with instrumentation suppressed."""
def intercept_service(self, continuation, handler_call_details):
with suppress_instrumentation():
return continuation(handler_call_details)
class Servicer(GRPCTestServerServicer):
"""Our test servicer"""
# pylint:disable=C0103
def SimpleMethod(self, request, context):
return Response(
server_id=request.client_id,
response_data=request.request_data,
)
# pylint:disable=C0103
def ServerStreamingMethod(self, request, context):
for data in ("one", "two", "three"):
yield Response(
server_id=request.client_id,
response_data=data,
)
class TestOpenTelemetryServerInterceptor(TestBase):
net_peer_span_attributes = {
NET_PEER_IP: "[::1]",
NET_PEER_NAME: "localhost",
}
@contextlib.contextmanager
def server(self, max_workers=1, interceptors=None):
with futures.ThreadPoolExecutor(max_workers=max_workers) as executor:
server = grpc.server(
executor,
options=(("grpc.so_reuseport", 0),),
interceptors=interceptors or [],
)
port = server.add_insecure_port("[::]:0")
channel = grpc.insecure_channel(f"localhost:{port:d}")
yield server, channel
def test_instrumentor(self):
def handler(request, context):
return b""
grpc_server_instrumentor = GrpcInstrumentorServer()
grpc_server_instrumentor.instrument()
try:
with self.server(max_workers=1) as (server, channel):
server.add_generic_rpc_handlers((UnaryUnaryRpcHandler(handler),))
rpc_call = "TestServicer/handler"
try:
server.start()
channel.unary_unary(rpc_call)(b"test")
finally:
server.stop(None)
finally:
grpc_server_instrumentor.uninstrument()
spans_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans_list), 1)
span = spans_list[0]
self.assertEqual(span.name, rpc_call)
self.assertIs(span.kind, trace.SpanKind.SERVER)
# Check version and name in span's instrumentation info
self.assertEqualSpanInstrumentationScope(span, opentelemetry.instrumentation.grpc)
# Check attributes
self.assertSpanHasAttributes(
span,
{
**self.net_peer_span_attributes,
RPC_METHOD: "handler",
RPC_SERVICE: "TestServicer",
RPC_SYSTEM: "grpc",
RPC_GRPC_STATUS_CODE: grpc.StatusCode.OK.value[0],
},
)
def test_uninstrument(self):
def handler(request, context):
return b""
grpc_server_instrumentor = GrpcInstrumentorServer()
grpc_server_instrumentor.instrument()
grpc_server_instrumentor.uninstrument()
with self.server(max_workers=1) as (server, channel):
server.add_generic_rpc_handlers((UnaryUnaryRpcHandler(handler),))
rpc_call = "TestServicer/test"
try:
server.start()
channel.unary_unary(rpc_call)(b"test")
finally:
server.stop(None)
spans_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans_list), 0)
def test_create_span(self):
"""Check that the interceptor wraps calls with spans server-side."""
# Intercept gRPC calls...
interceptor = server_interceptor()
with self.server(
max_workers=1,
interceptors=[interceptor],
) as (server, channel):
add_GRPCTestServerServicer_to_server(Servicer(), server)
rpc_call = "/GRPCTestServer/SimpleMethod"
request = Request(client_id=1, request_data="test")
msg = request.SerializeToString()
try:
server.start()
channel.unary_unary(rpc_call)(msg)
finally:
server.stop(None)
spans_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans_list), 1)
span = spans_list[0]
self.assertEqual(span.name, rpc_call)
self.assertIs(span.kind, trace.SpanKind.SERVER)
# Check version and name in span's instrumentation info
self.assertEqualSpanInstrumentationScope(span, opentelemetry.instrumentation.grpc)
# Check attributes
self.assertSpanHasAttributes(
span,
{
**self.net_peer_span_attributes,
RPC_METHOD: "SimpleMethod",
RPC_SERVICE: "GRPCTestServer",
RPC_SYSTEM: "grpc",
RPC_GRPC_STATUS_CODE: grpc.StatusCode.OK.value[0],
},
)
def test_create_two_spans(self):
"""Verify that the interceptor captures sub spans within the given
trace"""
class TwoSpanServicer(GRPCTestServerServicer):
# pylint:disable=C0103
def SimpleMethod(self, request, context):
# create another span
tracer = trace.get_tracer(__name__)
with tracer.start_as_current_span("child") as child:
child.add_event("child event")
return Response(
server_id=request.client_id,
response_data=request.request_data,
)
# Intercept gRPC calls...
interceptor = server_interceptor()
# setup the server
with self.server(
max_workers=1,
interceptors=[interceptor],
) as (server, channel):
add_GRPCTestServerServicer_to_server(TwoSpanServicer(), server)
# setup the RPC
rpc_call = "/GRPCTestServer/SimpleMethod"
request = Request(client_id=1, request_data="test")
msg = request.SerializeToString()
try:
server.start()
channel.unary_unary(rpc_call)(msg)
finally:
server.stop(None)
spans_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans_list), 2)
child_span = spans_list[0]
parent_span = spans_list[1]
self.assertEqual(parent_span.name, rpc_call)
self.assertIs(parent_span.kind, trace.SpanKind.SERVER)
# Check version and name in span's instrumentation info
self.assertEqualSpanInstrumentationScope(parent_span, opentelemetry.instrumentation.grpc)
# Check attributes
self.assertSpanHasAttributes(
parent_span,
{
**self.net_peer_span_attributes,
RPC_METHOD: "SimpleMethod",
RPC_SERVICE: "GRPCTestServer",
RPC_SYSTEM: "grpc",
RPC_GRPC_STATUS_CODE: grpc.StatusCode.OK.value[0],
},
)
# Check the child span
self.assertEqual(child_span.name, "child")
self.assertEqual(parent_span.context.trace_id, child_span.context.trace_id)
def test_create_span_streaming(self):
"""Check that the interceptor wraps calls with spans server-side, on a
streaming call."""
# Intercept gRPC calls...
interceptor = server_interceptor()
with self.server(
max_workers=1,
interceptors=[interceptor],
) as (server, channel):
add_GRPCTestServerServicer_to_server(Servicer(), server)
# setup the RPC
rpc_call = "/GRPCTestServer/ServerStreamingMethod"
request = Request(client_id=1, request_data="test")
msg = request.SerializeToString()
try:
server.start()
list(channel.unary_stream(rpc_call)(msg))
finally:
server.stop(None)
spans_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans_list), 1)
span = spans_list[0]
self.assertEqual(span.name, rpc_call)
self.assertIs(span.kind, trace.SpanKind.SERVER)
# Check version and name in span's instrumentation info
self.assertEqualSpanInstrumentationScope(span, opentelemetry.instrumentation.grpc)
# Check attributes
self.assertSpanHasAttributes(
span,
{
**self.net_peer_span_attributes,
RPC_METHOD: "ServerStreamingMethod",
RPC_SERVICE: "GRPCTestServer",
RPC_SYSTEM: "grpc",
RPC_GRPC_STATUS_CODE: grpc.StatusCode.OK.value[0],
},
)
def test_create_two_spans_streaming(self):
"""Verify that the interceptor captures sub spans in a
streaming call, within the given trace"""
class TwoSpanServicer(GRPCTestServerServicer):
# pylint:disable=C0103
def ServerStreamingMethod(self, request, context):
# create another span
tracer = trace.get_tracer(__name__)
with tracer.start_as_current_span("child") as child:
child.add_event("child event")
for data in ("one", "two", "three"):
yield Response(
server_id=request.client_id,
response_data=data,
)
# Intercept gRPC calls...
interceptor = server_interceptor()
with self.server(
max_workers=1,
interceptors=[interceptor],
) as (server, channel):
add_GRPCTestServerServicer_to_server(TwoSpanServicer(), server)
# setup the RPC
rpc_call = "/GRPCTestServer/ServerStreamingMethod"
request = Request(client_id=1, request_data="test")
msg = request.SerializeToString()
try:
server.start()
list(channel.unary_stream(rpc_call)(msg))
finally:
server.stop(None)
spans_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans_list), 2)
child_span = spans_list[0]
parent_span = spans_list[1]
self.assertEqual(parent_span.name, rpc_call)
self.assertIs(parent_span.kind, trace.SpanKind.SERVER)
# Check version and name in span's instrumentation info
self.assertEqualSpanInstrumentationScope(parent_span, opentelemetry.instrumentation.grpc)
# Check attributes
self.assertSpanHasAttributes(
parent_span,
{
**self.net_peer_span_attributes,
RPC_METHOD: "ServerStreamingMethod",
RPC_SERVICE: "GRPCTestServer",
RPC_SYSTEM: "grpc",
RPC_GRPC_STATUS_CODE: grpc.StatusCode.OK.value[0],
},
)
# Check the child span
self.assertEqual(child_span.name, "child")
self.assertEqual(parent_span.context.trace_id, child_span.context.trace_id)
def test_suppress_instrumentation(self):
"""Check that no span is created for a call when instrumentation
is suppressed."""
interceptor = server_interceptor()
with self.server(
max_workers=1,
interceptors=[SuppressRpcInterceptor(), interceptor],
) as (server, channel):
add_GRPCTestServerServicer_to_server(Servicer(), server)
rpc_call = "/GRPCTestServer/SimpleMethod"
request = Request(client_id=1, request_data="test")
msg = request.SerializeToString()
try:
server.start()
channel.unary_unary(rpc_call)(msg)
finally:
server.stop(None)
spans_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans_list), 0)
def test_suppress_instrumentation_streaming(self):
"""Check that no span is created for a streaming call when
instrumentation is suppressed."""
interceptor = server_interceptor()
with self.server(
max_workers=1,
interceptors=[SuppressRpcInterceptor(), interceptor],
) as (server, channel):
add_GRPCTestServerServicer_to_server(Servicer(), server)
rpc_call = "/GRPCTestServer/ServerStreamingMethod"
request = Request(client_id=1, request_data="test")
msg = request.SerializeToString()
try:
server.start()
list(channel.unary_stream(rpc_call)(msg))
finally:
server.stop(None)
spans_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans_list), 0)
def test_span_lifetime(self):
"""Check that the span is active for the duration of the call."""
interceptor = server_interceptor()
# To capture the current span at the time the handler is called
active_span_in_handler = None
def handler(request, context):
nonlocal active_span_in_handler
active_span_in_handler = trace.get_current_span()
return b""
with self.server(
max_workers=1,
interceptors=[interceptor],
) as (server, channel):
server.add_generic_rpc_handlers((UnaryUnaryRpcHandler(handler),))
active_span_before_call = trace.get_current_span()
try:
server.start()
channel.unary_unary("TestServicer/handler")(b"")
finally:
server.stop(None)
active_span_after_call = trace.get_current_span()
self.assertEqual(active_span_before_call, trace.INVALID_SPAN)
self.assertEqual(active_span_after_call, trace.INVALID_SPAN)
self.assertIsInstance(active_span_in_handler, trace_sdk.Span)
self.assertIsNone(active_span_in_handler.parent)
def test_sequential_server_spans(self):
"""Check that sequential RPCs get separate server spans."""
interceptor = server_interceptor()
# Capture the currently active span in each thread
active_spans_in_handler = []
def handler(request, context):
active_spans_in_handler.append(trace.get_current_span())
return b""
with self.server(
max_workers=1,
interceptors=[interceptor],
) as (server, channel):
server.add_generic_rpc_handlers((UnaryUnaryRpcHandler(handler),))
try:
server.start()
channel.unary_unary("TestServicer/handler")(b"")
channel.unary_unary("TestServicer/handler")(b"")
finally:
server.stop(None)
self.assertEqual(len(active_spans_in_handler), 2)
# pylint:disable=unbalanced-tuple-unpacking
span1, span2 = active_spans_in_handler
# Spans should belong to separate traces
self.assertNotEqual(span1.context.span_id, span2.context.span_id)
self.assertNotEqual(span1.context.trace_id, span2.context.trace_id)
for span in (span1, span2):
# each should be a root span
self.assertIsNone(span2.parent)
# check attributes
self.assertSpanHasAttributes(
span,
{
**self.net_peer_span_attributes,
RPC_METHOD: "handler",
RPC_SERVICE: "TestServicer",
RPC_SYSTEM: "grpc",
RPC_GRPC_STATUS_CODE: grpc.StatusCode.OK.value[0],
},
)
def test_concurrent_server_spans(self):
"""Check that concurrent RPC calls don't interfere with each other.
This is the same check as test_sequential_server_spans except that the
RPCs are concurrent. Two handlers are invoked at the same time on two
separate threads. Each one should see a different active span and
context.
"""
interceptor = server_interceptor()
# Capture the currently active span in each thread
active_spans_in_handler = []
latch = get_latch(2)
def handler(request, context):
latch()
active_spans_in_handler.append(trace.get_current_span())
return b""
with self.server(
max_workers=2,
interceptors=[interceptor],
) as (server, channel):
server.add_generic_rpc_handlers((UnaryUnaryRpcHandler(handler),))
try:
server.start()
# Interleave calls so spans are active on each thread at the same
# time
with futures.ThreadPoolExecutor(max_workers=2) as tpe:
f1 = tpe.submit(channel.unary_unary("TestServicer/handler"), b"")
f2 = tpe.submit(channel.unary_unary("TestServicer/handler"), b"")
futures.wait((f1, f2))
finally:
server.stop(None)
self.assertEqual(len(active_spans_in_handler), 2)
# pylint:disable=unbalanced-tuple-unpacking
span1, span2 = active_spans_in_handler
# Spans should belong to separate traces
self.assertNotEqual(span1.context.span_id, span2.context.span_id)
self.assertNotEqual(span1.context.trace_id, span2.context.trace_id)
for span in (span1, span2):
# each should be a root span
self.assertIsNone(span2.parent)
# check attributes
self.assertSpanHasAttributes(
span,
{
**self.net_peer_span_attributes,
RPC_METHOD: "handler",
RPC_SERVICE: "TestServicer",
RPC_SYSTEM: "grpc",
RPC_GRPC_STATUS_CODE: grpc.StatusCode.OK.value[0],
},
)
def test_abort(self):
"""Check that we can catch an abort properly"""
# Intercept gRPC calls...
interceptor = server_interceptor()
# our detailed failure message
failure_message = "This is a test failure"
# aborting RPC handlers
def error_status_handler(request, context):
context.abort(grpc.StatusCode.INTERNAL, failure_message)
def unset_status_handler(request, context):
context.abort(grpc.StatusCode.FAILED_PRECONDITION, failure_message)
rpc_call_error = "TestServicer/error_status_handler"
rpc_call_unset = "TestServicer/unset_status_handler"
rpc_calls = {
rpc_call_error: error_status_handler,
rpc_call_unset: unset_status_handler,
}
for rpc_call, handler in rpc_calls.items():
with self.server(
max_workers=1,
interceptors=[interceptor],
) as (server, channel):
server.add_generic_rpc_handlers((UnaryUnaryRpcHandler(handler),))
server.start()
with self.assertRaises(Exception):
channel.unary_unary(rpc_call)(b"")
# unfortunately, these are just bare exceptions in grpc...
server.stop(None)
spans_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans_list), 2)
# check error span
span = spans_list[0]
self.assertEqual(span.name, rpc_call_error)
self.assertIs(span.kind, trace.SpanKind.SERVER)
# Check version and name in span's instrumentation info
self.assertEqualSpanInstrumentationScope(span, opentelemetry.instrumentation.grpc)
# make sure this span errored, with the right status and detail
self.assertEqual(span.status.status_code, StatusCode.ERROR)
self.assertEqual(
span.status.description,
f"{grpc.StatusCode.INTERNAL}:{failure_message}",
)
# Check attributes
self.assertSpanHasAttributes(
span,
{
**self.net_peer_span_attributes,
RPC_METHOD: "error_status_handler",
RPC_SERVICE: "TestServicer",
RPC_SYSTEM: "grpc",
RPC_GRPC_STATUS_CODE: grpc.StatusCode.INTERNAL.value[0],
},
)
# check unset status span
span = spans_list[1]
self.assertEqual(span.name, rpc_call_unset)
self.assertIs(span.kind, trace.SpanKind.SERVER)
# Check version and name in span's instrumentation info
self.assertEqualSpanInstrumentationScope(span, opentelemetry.instrumentation.grpc)
self.assertEqual(span.status.description, None)
self.assertEqual(span.status.status_code, StatusCode.UNSET)
# Check attributes
self.assertSpanHasAttributes(
span,
{
**self.net_peer_span_attributes,
RPC_METHOD: "unset_status_handler",
RPC_SERVICE: "TestServicer",
RPC_SYSTEM: "grpc",
RPC_GRPC_STATUS_CODE: grpc.StatusCode.FAILED_PRECONDITION.value[0],
},
)
def test_non_list_interceptors(self):
"""Check that we handle non-list interceptors correctly."""
grpc_server_instrumentor = GrpcInstrumentorServer()
grpc_server_instrumentor.instrument()
try:
with self.server(
max_workers=1,
interceptors=(mock.MagicMock(),),
) as (server, channel):
add_GRPCTestServerServicer_to_server(Servicer(), server)
rpc_call = "/GRPCTestServer/SimpleMethod"
request = Request(client_id=1, request_data="test")
msg = request.SerializeToString()
try:
server.start()
channel.unary_unary(rpc_call)(msg)
finally:
server.stop(None)
finally:
grpc_server_instrumentor.uninstrument()
spans_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans_list), 1)
span = spans_list[0]
self.assertEqual(span.name, rpc_call)
self.assertIs(span.kind, trace.SpanKind.SERVER)
# Check version and name in span's instrumentation info
self.assertEqualSpanInstrumentationScope(span, opentelemetry.instrumentation.grpc)
# Check attributes
self.assertSpanHasAttributes(
span,
{
**self.net_peer_span_attributes,
RPC_METHOD: "SimpleMethod",
RPC_SERVICE: "GRPCTestServer",
RPC_SYSTEM: "grpc",
RPC_GRPC_STATUS_CODE: grpc.StatusCode.OK.value[0],
},
)
class TestOpenTelemetryServerInterceptorUnix(
TestOpenTelemetryServerInterceptor,
):
net_peer_span_attributes = {}
@contextlib.contextmanager
def server(self, max_workers=1, interceptors=None):
with (
futures.ThreadPoolExecutor(max_workers=max_workers) as executor,
tempfile.TemporaryDirectory() as tmp,
):
server = grpc.server(
executor,
options=(("grpc.so_reuseport", 0),),
interceptors=interceptors or [],
)
sock = f"unix://{tmp}/grpc.sock"
server.add_insecure_port(sock)
channel = grpc.insecure_channel(sock)
yield server, channel
def get_latch(num):
"""Get a countdown latch function for use in n threads."""
cv = threading.Condition()
count = 0
def countdown_latch():
"""Block until n-1 other threads have called."""
nonlocal count
cv.acquire()
count += 1
cv.notify()
cv.release()
cv.acquire()
while count < num:
cv.wait()
cv.release()
return countdown_latch
test_server_interceptor_filter.py 0000664 0000000 0000000 00000014725 15270700723 0042074 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-grpc/tests # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
# pylint:disable=unused-argument
# pylint:disable=no-self-use
from concurrent import futures
import grpc
import opentelemetry.instrumentation.grpc
from opentelemetry import trace
from opentelemetry.instrumentation.grpc import (
GrpcInstrumentorServer,
filters,
server_interceptor,
)
from opentelemetry.semconv._incubating.attributes.net_attributes import (
NET_PEER_IP,
NET_PEER_NAME,
)
from opentelemetry.semconv._incubating.attributes.rpc_attributes import (
RPC_GRPC_STATUS_CODE,
RPC_METHOD,
RPC_SERVICE,
RPC_SYSTEM,
)
from opentelemetry.test.test_base import TestBase
from .protobuf.test_server_pb2 import Request, Response
from .protobuf.test_server_pb2_grpc import (
GRPCTestServerServicer,
add_GRPCTestServerServicer_to_server,
)
class UnaryUnaryMethodHandler(grpc.RpcMethodHandler):
def __init__(self, handler):
self.request_streaming = False
self.response_streaming = False
self.request_deserializer = None
self.response_serializer = None
self.unary_unary = handler
self.unary_stream = None
self.stream_unary = None
self.stream_stream = None
class UnaryUnaryRpcHandler(grpc.GenericRpcHandler):
def __init__(self, handler):
self._unary_unary_handler = handler
def service(self, handler_call_details):
return UnaryUnaryMethodHandler(self._unary_unary_handler)
class Servicer(GRPCTestServerServicer):
"""Our test servicer"""
# pylint:disable=C0103
def SimpleMethod(self, request, context):
return Response(
server_id=request.client_id,
response_data=request.request_data,
)
# pylint:disable=C0103
def ServerStreamingMethod(self, request, context):
for data in ("one", "two", "three"):
yield Response(
server_id=request.client_id,
response_data=data,
)
class TestOpenTelemetryServerInterceptorFilterMethodName(TestBase):
def test_instrumentor(self):
def handler(request, context):
return b""
grpc_server_instrumentor = GrpcInstrumentorServer(filter_=filters.method_name("handler"))
grpc_server_instrumentor.instrument()
with futures.ThreadPoolExecutor(max_workers=1) as executor:
server = grpc.server(
executor,
options=(("grpc.so_reuseport", 0),),
)
server.add_generic_rpc_handlers((UnaryUnaryRpcHandler(handler),))
port = server.add_insecure_port("[::]:0")
channel = grpc.insecure_channel(f"localhost:{port:d}")
rpc_call = "TestServicer/handler"
try:
server.start()
channel.unary_unary(rpc_call)(b"test")
finally:
server.stop(None)
spans_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans_list), 1)
span = spans_list[0]
self.assertEqual(span.name, rpc_call)
self.assertIs(span.kind, trace.SpanKind.SERVER)
# Check version and name in span's instrumentation info
self.assertEqualSpanInstrumentationScope(span, opentelemetry.instrumentation.grpc)
# Check attributes
self.assertSpanHasAttributes(
span,
{
NET_PEER_IP: "[::1]",
NET_PEER_NAME: "localhost",
RPC_METHOD: "handler",
RPC_SERVICE: "TestServicer",
RPC_SYSTEM: "grpc",
RPC_GRPC_STATUS_CODE: grpc.StatusCode.OK.value[0],
},
)
grpc_server_instrumentor.uninstrument()
def test_uninstrument(self):
def handler(request, context):
return b""
grpc_server_instrumentor = GrpcInstrumentorServer(filter_=filters.method_name("SimpleMethod"))
grpc_server_instrumentor.instrument()
grpc_server_instrumentor.uninstrument()
with futures.ThreadPoolExecutor(max_workers=1) as executor:
server = grpc.server(
executor,
options=(("grpc.so_reuseport", 0),),
)
server.add_generic_rpc_handlers((UnaryUnaryRpcHandler(handler),))
port = server.add_insecure_port("[::]:0")
channel = grpc.insecure_channel(f"localhost:{port:d}")
rpc_call = "TestServicer/test"
try:
server.start()
channel.unary_unary(rpc_call)(b"test")
finally:
server.stop(None)
spans_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans_list), 0)
def test_create_span(self):
"""Check that the interceptor wraps calls with spans server-side."""
# Intercept gRPC calls...
interceptor = server_interceptor(filter_=filters.method_name("SimpleMethod"))
with futures.ThreadPoolExecutor(max_workers=1) as executor:
server = grpc.server(
executor,
options=(("grpc.so_reuseport", 0),),
interceptors=[interceptor],
)
add_GRPCTestServerServicer_to_server(Servicer(), server)
port = server.add_insecure_port("[::]:0")
channel = grpc.insecure_channel(f"localhost:{port:d}")
rpc_call = "/GRPCTestServer/SimpleMethod"
request = Request(client_id=1, request_data="test")
msg = request.SerializeToString()
try:
server.start()
channel.unary_unary(rpc_call)(msg)
finally:
server.stop(None)
spans_list = self.memory_exporter.get_finished_spans()
self.assertEqual(len(spans_list), 1)
span = spans_list[0]
self.assertEqual(span.name, rpc_call)
self.assertIs(span.kind, trace.SpanKind.SERVER)
# Check version and name in span's instrumentation info
self.assertEqualSpanInstrumentationScope(span, opentelemetry.instrumentation.grpc)
# Check attributes
self.assertSpanHasAttributes(
span,
{
NET_PEER_IP: "[::1]",
NET_PEER_NAME: "localhost",
RPC_METHOD: "SimpleMethod",
RPC_SERVICE: "GRPCTestServer",
RPC_SYSTEM: "grpc",
RPC_GRPC_STATUS_CODE: grpc.StatusCode.OK.value[0],
},
)
opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-httpx/ 0000775 0000000 0000000 00000000000 15270700723 0032312 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-httpx/LICENSE 0000664 0000000 0000000 00000026135 15270700723 0033326 0 ustar 00root root 0000000 0000000 Apache License
Version 2.0, January 2004
http://www.apache.org/licenses/
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opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-httpx/README.rst 0000664 0000000 0000000 00000016563 15270700723 0034014 0 ustar 00root root 0000000 0000000 OpenTelemetry HTTPX Instrumentation
===================================
|pypi|
.. |pypi| image:: https://badge.fury.io/py/opentelemetry-instrumentation-httpx.svg
:target: https://pypi.org/project/opentelemetry-instrumentation-httpx/
This library allows tracing HTTP requests made by the
`httpx `_ and
`httpx2 `_ libraries.
If both libraries are installed, use ``HTTPXClientInstrumentor`` for
``httpx`` clients and ``HTTPX2ClientInstrumentor`` for ``httpx2`` clients.
The instrumentors can be enabled independently.
Installation
------------
::
pip install opentelemetry-instrumentation-httpx
Usage
-----
Instrumenting all clients
*************************
When using the instrumentor, all clients will automatically trace requests.
.. code-block:: python
import httpx
import asyncio
from opentelemetry.instrumentation.httpx import HTTPXClientInstrumentor
url = "https://example.com"
HTTPXClientInstrumentor().instrument()
with httpx.Client() as client:
response = client.get(url)
async def get(url):
async with httpx.AsyncClient() as client:
response = await client.get(url)
asyncio.run(get(url))
The same package also supports `httpx2 `_ using
the ``HTTPX2ClientInstrumentor``:
.. code-block:: python
import httpx2
import asyncio
from opentelemetry.instrumentation.httpx import HTTPX2ClientInstrumentor
url = "https://example.com"
HTTPX2ClientInstrumentor().instrument()
with httpx2.Client() as client:
response = client.get(url)
async def get(url):
async with httpx2.AsyncClient() as client:
response = await client.get(url)
asyncio.run(get(url))
Instrumenting single clients
****************************
If you only want to instrument requests for specific client instances, you can
use the `HTTPXClientInstrumentor.instrument_client` method.
.. code-block:: python
import httpx
import asyncio
from opentelemetry.instrumentation.httpx import HTTPXClientInstrumentor
url = "https://example.com"
with httpx.Client() as client:
HTTPXClientInstrumentor.instrument_client(client)
response = client.get(url)
async def get(url):
async with httpx.AsyncClient() as client:
HTTPXClientInstrumentor.instrument_client(client)
response = await client.get(url)
asyncio.run(get(url))
For ``httpx2`` clients, use ``HTTPX2ClientInstrumentor.instrument_client``:
.. code-block:: python
import httpx2
from opentelemetry.instrumentation.httpx import HTTPX2ClientInstrumentor
with httpx2.Client() as client:
HTTPX2ClientInstrumentor.instrument_client(client)
response = client.get("https://example.com")
Uninstrument
************
If you need to uninstrument clients, there are two options available.
.. code-block:: python
import httpx
from opentelemetry.instrumentation.httpx import HTTPXClientInstrumentor
HTTPXClientInstrumentor().instrument()
client = httpx.Client()
# Uninstrument a specific client
HTTPXClientInstrumentor.uninstrument_client(client)
# Uninstrument all clients
HTTPXClientInstrumentor().uninstrument()
Using transports directly
*************************
If you don't want to use the instrumentor class, you can use the transport classes directly.
.. code-block:: python
import httpx
import asyncio
from opentelemetry.instrumentation.httpx import (
AsyncOpenTelemetryTransport,
SyncOpenTelemetryTransport,
)
url = "https://example.com"
transport = httpx.HTTPTransport()
telemetry_transport = SyncOpenTelemetryTransport(transport)
with httpx.Client(transport=telemetry_transport) as client:
response = client.get(url)
transport = httpx.AsyncHTTPTransport()
telemetry_transport = AsyncOpenTelemetryTransport(transport)
async def get(url):
async with httpx.AsyncClient(transport=telemetry_transport) as client:
response = await client.get(url)
asyncio.run(get(url))
For ``httpx2`` transports, use ``SyncOpenTelemetryTransportHttpx2`` and
``AsyncOpenTelemetryTransportHttpx2``:
.. code-block:: python
import httpx2
from opentelemetry.instrumentation.httpx import SyncOpenTelemetryTransportHttpx2
transport = httpx2.HTTPTransport()
telemetry_transport = SyncOpenTelemetryTransportHttpx2(transport)
with httpx2.Client(transport=telemetry_transport) as client:
response = client.get("https://example.com")
Request and response hooks
***************************
The instrumentation supports specifying request and response hooks. These are functions that get called back by the instrumentation right after a span is created for a request
and right before the span is finished while processing a response.
.. note::
The request hook receives the raw arguments provided to the transport layer. The response hook receives the raw return values from the transport layer.
The hooks can be configured as follows:
.. code-block:: python
from opentelemetry.instrumentation.httpx import HTTPXClientInstrumentor
def request_hook(span, request):
# method, url, headers, stream, extensions = request
pass
def response_hook(span, request, response):
# method, url, headers, stream, extensions = request
# status_code, headers, stream, extensions = response
pass
async def async_request_hook(span, request):
# method, url, headers, stream, extensions = request
pass
async def async_response_hook(span, request, response):
# method, url, headers, stream, extensions = request
# status_code, headers, stream, extensions = response
pass
HTTPXClientInstrumentor().instrument(
request_hook=request_hook,
response_hook=response_hook,
async_request_hook=async_request_hook,
async_response_hook=async_response_hook
)
Or if you are using the transport classes directly:
.. code-block:: python
import httpx
from opentelemetry.instrumentation.httpx import SyncOpenTelemetryTransport, AsyncOpenTelemetryTransport
def request_hook(span, request):
# method, url, headers, stream, extensions = request
pass
def response_hook(span, request, response):
# method, url, headers, stream, extensions = request
# status_code, headers, stream, extensions = response
pass
async def async_request_hook(span, request):
# method, url, headers, stream, extensions = request
pass
async def async_response_hook(span, request, response):
# method, url, headers, stream, extensions = request
# status_code, headers, stream, extensions = response
pass
transport = httpx.HTTPTransport()
telemetry_transport = SyncOpenTelemetryTransport(
transport,
request_hook=request_hook,
response_hook=response_hook
)
async_transport = httpx.AsyncHTTPTransport()
async_telemetry_transport = AsyncOpenTelemetryTransport(
async_transport,
request_hook=async_request_hook,
response_hook=async_response_hook
)
References
----------
* `OpenTelemetry HTTPX Instrumentation `_
* `OpenTelemetry Project `_
pyproject.toml 0000664 0000000 0000000 00000003410 15270700723 0035145 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-httpx [build-system]
requires = ["hatchling"]
build-backend = "hatchling.build"
[project]
name = "opentelemetry-instrumentation-httpx"
dynamic = ["version"]
description = "OpenTelemetry HTTPX Instrumentation"
readme = "README.rst"
license = "Apache-2.0"
requires-python = ">=3.10"
authors = [
{ name = "OpenTelemetry Authors", email = "cncf-opentelemetry-contributors@lists.cncf.io" },
]
classifiers = [
"Development Status :: 4 - Beta",
"Intended Audience :: Developers",
"License :: OSI Approved :: Apache Software License",
"Programming Language :: Python",
"Programming Language :: Python :: 3",
"Programming Language :: Python :: 3.10",
"Programming Language :: Python :: 3.11",
"Programming Language :: Python :: 3.12",
"Programming Language :: Python :: 3.13",
"Programming Language :: Python :: 3.14",
]
dependencies = [
"opentelemetry-api ~= 1.12",
"opentelemetry-instrumentation == 0.66b2",
"opentelemetry-semantic-conventions == 0.66b2",
"opentelemetry-util-http == 0.66b2",
"wrapt >= 1.0.0, < 3.0.0",
]
[project.optional-dependencies]
instruments = []
instruments-any = [
"httpx >= 0.18.0",
"httpx2 >= 2.0.0",
]
[project.entry-points.opentelemetry_instrumentor]
httpx = "opentelemetry.instrumentation.httpx:HTTPXClientInstrumentor"
httpx2 = "opentelemetry.instrumentation.httpx:HTTPX2ClientInstrumentor"
[project.urls]
Homepage = "https://github.com/open-telemetry/opentelemetry-python-contrib/tree/main/instrumentation/opentelemetry-instrumentation-httpx"
Repository = "https://github.com/open-telemetry/opentelemetry-python-contrib"
[tool.hatch.version]
path = "src/opentelemetry/instrumentation/httpx/version.py"
[tool.hatch.build.targets.sdist]
include = [
"/src",
"/tests",
]
[tool.hatch.build.targets.wheel]
packages = ["src/opentelemetry"]
opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-httpx/src/ 0000775 0000000 0000000 00000000000 15270700723 0033101 5 ustar 00root root 0000000 0000000 opentelemetry/ 0000775 0000000 0000000 00000000000 15270700723 0035716 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-httpx/src instrumentation/ 0000775 0000000 0000000 00000000000 15270700723 0041161 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-httpx/src/opentelemetry httpx/ 0000775 0000000 0000000 00000000000 15270700723 0042330 5 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-httpx/src/opentelemetry/instrumentation __init__.py 0000664 0000000 0000000 00000204154 15270700723 0044447 0 ustar 00root root 0000000 0000000 opentelemetry-python-contrib-0.66b2/instrumentation/opentelemetry-instrumentation-httpx/src/opentelemetry/instrumentation/httpx # Copyright The OpenTelemetry Authors
# SPDX-License-Identifier: Apache-2.0
# pylint: disable=too-many-lines
"""
Usage
-----
Instrumenting all clients
*************************
When using the instrumentor, all clients will automatically trace requests.
.. code-block:: python
import httpx
import asyncio
from opentelemetry.instrumentation.httpx import HTTPXClientInstrumentor
url = "https://example.com"
HTTPXClientInstrumentor().instrument()
with httpx.Client() as client:
response = client.get(url)
async def get(url):
async with httpx.AsyncClient() as client:
response = await client.get(url)
asyncio.run(get(url))
When instrumenting ``httpx2`` clients, use ``HTTPX2ClientInstrumentor``:
.. code-block:: python
import httpx2
import asyncio
from opentelemetry.instrumentation.httpx import HTTPX2ClientInstrumentor
url = "https://example.com"
HTTPX2ClientInstrumentor().instrument()
with httpx2.Client() as client:
response = client.get(url)
async def get(url):
async with httpx2.AsyncClient() as client:
response = await client.get(url)
asyncio.run(get(url))
Instrumenting single clients
****************************
If you only want to instrument requests for specific client instances, you can
use the `instrument_client` method.
.. code-block:: python
import httpx
import asyncio
from opentelemetry.instrumentation.httpx import HTTPXClientInstrumentor
url = "https://example.com"
with httpx.Client() as client:
HTTPXClientInstrumentor.instrument_client(client)
response = client.get(url)
async def get(url):
async with httpx.AsyncClient() as client:
HTTPXClientInstrumentor.instrument_client(client)
response = await client.get(url)
asyncio.run(get(url))
For ``httpx2`` clients, use ``HTTPX2ClientInstrumentor.instrument_client``:
.. code-block:: python
import httpx2
from opentelemetry.instrumentation.httpx import HTTPX2ClientInstrumentor
with httpx2.Client() as client:
HTTPX2ClientInstrumentor.instrument_client(client)
response = client.get("https://example.com")
Uninstrument
************
If you need to uninstrument clients, there are two options available.
.. code-block:: python
import httpx
from opentelemetry.instrumentation.httpx import HTTPXClientInstrumentor
HTTPXClientInstrumentor().instrument()
client = httpx.Client()
# Uninstrument a specific client
HTTPXClientInstrumentor.uninstrument_client(client)
# Uninstrument all clients
HTTPXClientInstrumentor().uninstrument()
Using transports directly
*************************
If you don't want to use the instrumentor class, you can use the transport classes directly.
.. code-block:: python
import httpx
import asyncio
from opentelemetry.instrumentation.httpx import (
AsyncOpenTelemetryTransport,
SyncOpenTelemetryTransport,
)
url = "https://example.com"
transport = httpx.HTTPTransport()
telemetry_transport = SyncOpenTelemetryTransport(transport)
with httpx.Client(transport=telemetry_transport) as client:
response = client.get(url)
transport = httpx.AsyncHTTPTransport()
telemetry_transport = AsyncOpenTelemetryTransport(transport)
async def get(url):
async with httpx.AsyncClient(transport=telemetry_transport) as client:
response = await client.get(url)
asyncio.run(get(url))
For ``httpx2`` transports, use ``SyncOpenTelemetryTransportHttpx2`` and
``AsyncOpenTelemetryTransportHttpx2``:
.. code-block:: python
import httpx2
from opentelemetry.instrumentation.httpx import (
SyncOpenTelemetryTransportHttpx2,
)
transport = httpx2.HTTPTransport()
telemetry_transport = SyncOpenTelemetryTransportHttpx2(transport)
with httpx2.Client(transport=telemetry_transport) as client:
response = client.get("https://example.com")
Request and response hooks
***************************
The instrumentation supports specifying request and response hooks. These are functions that get called back by the instrumentation right after a span is created for a request
and right before the span is finished while processing a response.
.. note::
The request hook receives the raw arguments provided to the transport layer. The response hook receives the raw return values from the transport layer.
The hooks can be configured as follows:
.. code-block:: python
from opentelemetry.instrumentation.httpx import HTTPXClientInstrumentor
def request_hook(span, request):
# method, url, headers, stream, extensions = request
pass
def response_hook(span, request, response):
# method, url, headers, stream, extensions = request
# status_code, headers, stream, extensions = response
pass
async def async_request_hook(span, request):
# method, url, headers, stream, extensions = request
pass
async def async_response_hook(span, request, response):
# method, url, headers, stream, extensions = request
# status_code, headers, stream, extensions = response
pass
HTTPXClientInstrumentor().instrument(
request_hook=request_hook,
response_hook=response_hook,
async_request_hook=async_request_hook,
async_response_hook=async_response_hook,
)
Or if you are using the transport classes directly:
.. code-block:: python
import httpx
from opentelemetry.instrumentation.httpx import (
SyncOpenTelemetryTransport,
AsyncOpenTelemetryTransport,
)
def request_hook(span, request):
# method, url, headers, stream, extensions = request
pass
def response_hook(span, request, response):
# method, url, headers, stream, extensions = request
# status_code, headers, stream, extensions = response
pass
async def async_request_hook(span, request):
# method, url, headers, stream, extensions = request
pass
async def async_response_hook(span, request, response):
# method, url, headers, stream, extensions = request
# status_code, headers, stream, extensions = response
pass
transport = httpx.HTTPTransport()
telemetry_transport = SyncOpenTelemetryTransport(transport, request_hook=request_hook, response_hook=response_hook)
async_transport = httpx.AsyncHTTPTransport()
async_telemetry_transport = AsyncOpenTelemetryTransport(
async_transport,
request_hook=async_request_hook,
response_hook=async_response_hook,
)
Configuration
-------------
Exclude lists
*************
To exclude certain URLs from tracking, set the environment variable ``OTEL_PYTHON_HTTPX_EXCLUDED_URLS``
(or ``OTEL_PYTHON_EXCLUDED_URLS`` to cover all instrumentations) to a string of comma delimited regexes that match the
URLs.
For example,
::
export OTEL_PYTHON_HTTPX_EXCLUDED_URLS="client/.*/info,healthcheck"
will exclude requests such as ``https://site/client/123/info`` and ``https://site/xyz/healthcheck``.
Capture HTTP request and response headers
*****************************************
You can configure the agent to capture specified HTTP headers as span attributes, according to the
`semantic conventions `_.
Request headers
***************
To capture HTTP request headers as span attributes, set the environment variable
``OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_CLIENT_REQUEST`` to a comma delimited list of HTTP header names.
For example using the environment variable,
::
export OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_CLIENT_REQUEST="content-type,custom_request_header"
will extract ``content-type`` and ``custom_request_header`` from the request headers and add them as span attributes.
Request header names in HttpX are case-insensitive. So, giving the header name as ``CUStom-Header`` in the environment
variable will capture the header named ``custom-header``.
Regular expressions may also be used to match multiple headers that correspond to the given pattern. For example:
::
export OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_CLIENT_REQUEST="Accept.*,X-.*"
Would match all request headers that start with ``Accept`` and ``X-``.
To capture all request headers, set ``OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_CLIENT_REQUEST`` to ``".*"``.
::
export OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_CLIENT_REQUEST=".*"
The name of the added span attribute will follow the format ``http.request.header.`` where ````
is the normalized HTTP header name (lowercase, with ``-`` replaced by ``_``). The value of the attribute will be a
single item list containing all the header values.
For example:
``http.request.header.custom_request_header = ["", ""]``
Response headers
****************
To capture HTTP response headers as span attributes, set the environment variable
``OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_CLIENT_RESPONSE`` to a comma delimited list of HTTP header names.
For example using the environment variable,
::
export OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_CLIENT_RESPONSE="content-type,custom_response_header"
will extract ``content-type`` and ``custom_response_header`` from the response headers and add them as span attributes.
Response header names in HttpX are case-insensitive. So, giving the header name as ``CUStom-Header`` in the environment
variable will capture the header named ``custom-header``.
Regular expressions may also be used to match multiple headers that correspond to the given pattern. For example:
::
export OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_CLIENT_RESPONSE="Content.*,X-.*"
Would match all response headers that start with ``Content`` and ``X-``.
To capture all response headers, set ``OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_CLIENT_RESPONSE`` to ``".*"``.
::
export OTEL_INSTRUMENTATION_HTTP_CAPTURE_HEADERS_CLIENT_RESPONSE=".*"
The name of the added span attribute will follow the format ``http.response.header.`` where ``