pax_global_header00006660000000000000000000000064136213427620014520gustar00rootroot0000000000000052 comment=de586251cb579bcb80eef435825cb3cedc202f52 toil-releases-3.24.0/000077500000000000000000000000001362134276200143565ustar00rootroot00000000000000toil-releases-3.24.0/.gitignore000066400000000000000000000004331362134276200163460ustar00rootroot00000000000000*.pyc /src/*.egg-info /build /dist /docs/_build __pycache__ .eggs/ .cache/ .pytest_cache/ .idea/ /test-report.xml /test-report-*.xml venv/ v3nv/ tmp/ /src/toil/test/cwl/spec /cwltool_deps/ /docs/generated_rst/ /docker/Dockerfile /docker/toil-*.tar.gz /src/toil/version.py .coverage* toil-releases-3.24.0/.gitlab-ci.yml000066400000000000000000000163711362134276200170220ustar00rootroot00000000000000image: quay.io/vgteam/vg_ci_prebake:latest # Note that we must run in a priviliged container for our internal Docker daemon to come up. before_script: - startdocker || true - docker info - cat /etc/hosts - export PYTHONIOENCODING=utf-8 - mkdir -p ~/.kube && cp "$GITLAB_SECRET_FILE_KUBE_CONFIG" ~/.kube/config - mkdir -p ~/.aws && cp "$GITLAB_SECRET_FILE_AWS_CREDENTIALS" ~/.aws/credentials after_script: # We need to clean up any files that Toil may have made via Docker that # aren't deletable by the Gitlab user. If we don't do this, Gitlab will try # and clean them up before running the next job on the runner, fail, and fail # that next job. - pwd - sudo rm -rf tmp - stopdocker || true stages: - main_tests - test - integration # Python2.7 py2_batch_systems: stage: test script: - pwd - apt update && DEBIAN_FRONTEND=noninteractive apt install -y tzdata && apt install -y jq - virtualenv -p python2.7 venv && . venv/bin/activate && make prepare && make develop extras=[all] && pip install htcondor awscli==1.16.272 - python -m pytest -s -r s src/toil/test/batchSystems/batchSystemTest.py - python -m pytest -s -r s src/toil/test/mesos/MesosDataStructuresTest.py py2_cwl: stage: test script: - pwd - virtualenv -p python2.7 venv && . venv/bin/activate && make prepare && make develop extras=[all] && pip install htcondor - python -m pytest -s -r s src/toil/test/cwl/cwlTest.py py2_wdl: stage: test script: - pwd - virtualenv -p python2.7 venv && . venv/bin/activate && make prepare && make develop extras=[all] && pip install htcondor - python -m pytest -s -r s src/toil/test/wdl/toilwdlTest.py py2_jobstore_and_provisioning: stage: test script: - pwd - virtualenv -p python2.7 venv && . venv/bin/activate && make prepare && make develop extras=[all] && pip install htcondor - python -m pytest -s -r s src/toil/test/sort/sortTest.py - python -m pytest -s -r s src/toil/test/provisioners/aws/awsProvisionerTest.py - python -m pytest -s -r s src/toil/test/provisioners/clusterScalerTest.py - python -m pytest -s -r s src/toil/test/provisioners/gceProvisionerTest.py py2_main: stage: main_tests script: - pwd - virtualenv -p python2.7 venv && . venv/bin/activate && make prepare && make develop extras=[all] && pip install htcondor - python -m pytest -s -r s src/toil/test/src - python -m pytest -s -r s src/toil/test/utils py2_appliance_build: stage: main_tests script: - pwd - apt update && DEBIAN_FRONTEND=noninteractive apt install -y tzdata && apt install -y jq - virtualenv -p python2.7 venv && . venv/bin/activate && make prepare && make develop extras=[all] && pip install htcondor awscli==1.16.272 # This reads GITLAB_SECRET_FILE_QUAY_CREDENTIALS - python setup_gitlab_docker.py - make push_docker py2_integration_jobstore: stage: integration script: - pwd - apt update && DEBIAN_FRONTEND=noninteractive apt install -y tzdata && apt install -y jq - virtualenv -p python2.7 venv && . venv/bin/activate && make prepare && make develop extras=[all] && pip install htcondor awscli==1.16.272 - export TOIL_TEST_INTEGRATIVE=True; export TOIL_AWS_KEYNAME=id_rsa; export TOIL_AWS_ZONE=us-west-2a # This reads GITLAB_SECRET_FILE_SSH_KEYS - python setup_gitlab_ssh.py - python -m pytest -s -r s src/toil/test/jobStores/jobStoreTest.py py2_integration_sort: stage: integration script: - pwd - apt update && DEBIAN_FRONTEND=noninteractive apt install -y tzdata && apt install -y jq - virtualenv -p python2.7 venv && . venv/bin/activate && make prepare && make develop extras=[all] && pip install htcondor awscli==1.16.272 - export TOIL_TEST_INTEGRATIVE=True; export TOIL_AWS_KEYNAME=id_rsa; export TOIL_AWS_ZONE=us-west-2a # This reads GITLAB_SECRET_FILE_SSH_KEYS - python setup_gitlab_ssh.py - python -m pytest -s -r s src/toil/test/sort/sortTest.py - python -m pytest -s -r s src/toil/test/provisioners/clusterScalerTest.py #py2_integration_provisioner: # stage: integration # script: # - pwd # - apt update && DEBIAN_FRONTEND=noninteractive apt install -y tzdata && apt install -y jq # - virtualenv -p python2.7 venv && . venv/bin/activate && make prepare && make develop extras=[all] && pip install htcondor awscli==1.16.272 # - export TOIL_TEST_INTEGRATIVE=True; export TOIL_AWS_KEYNAME=id_rsa; export TOIL_AWS_ZONE=us-west-2a # # This reads GITLAB_SECRET_FILE_SSH_KEYS # - python setup_gitlab_ssh.py # - python -m pytest -s -r s src/toil/test/provisioners/aws/awsProvisionerTest.py # Python3.6 py3_batch_systems: stage: test script: - pwd - apt update && DEBIAN_FRONTEND=noninteractive apt install -y tzdata && apt install -y jq - virtualenv -p python3.6 venv && . venv/bin/activate && make prepare && make develop extras=[all] && pip install htcondor awscli==1.16.272 - python -m pytest -s -r s src/toil/test/batchSystems/batchSystemTest.py - python -m pytest -s -r s src/toil/test/mesos/MesosDataStructuresTest.py py3_cwl: stage: test script: - pwd - virtualenv -p python3.6 venv && . venv/bin/activate && make prepare && make develop extras=[all] && pip install htcondor - python -m pytest -s -r s src/toil/test/cwl/cwlTest.py py3_wdl: stage: test script: - pwd - virtualenv -p python3.6 venv && . venv/bin/activate && make prepare && make develop extras=[all] && pip install htcondor - python -m pytest -s -r s src/toil/test/wdl/toilwdlTest.py py3_jobstore_and_provisioning: stage: test script: - pwd - virtualenv -p python3.6 venv && . venv/bin/activate && make prepare && make develop extras=[all] && pip install htcondor - python -m pytest -s -r s src/toil/test/jobStores/jobStoreTest.py - python -m pytest -s -r s src/toil/test/sort/sortTest.py - python -m pytest -s -r s src/toil/test/provisioners/aws/awsProvisionerTest.py - python -m pytest -s -r s src/toil/test/provisioners/clusterScalerTest.py - python -m pytest -s -r s src/toil/test/provisioners/gceProvisionerTest.py py3_main: stage: main_tests script: - pwd - virtualenv -p python3.6 venv && . venv/bin/activate && make prepare && make develop extras=[all] && pip install htcondor - python -m pytest -s -r s src/toil/test/src - python -m pytest -s -r s src/toil/test/utils py3_appliance_build: stage: main_tests script: - pwd - apt update && DEBIAN_FRONTEND=noninteractive apt install -y tzdata && apt install -y jq - virtualenv -p python3.6 venv && . venv/bin/activate && make prepare && make develop extras=[all] && pip install htcondor awscli==1.16.272 # This reads GITLAB_SECRET_FILE_QUAY_CREDENTIALS - python3.6 setup_gitlab_docker.py - make push_docker #py3_integration: # stage: integration # script: # - pwd # - apt update && DEBIAN_FRONTEND=noninteractive apt install -y tzdata && apt install -y jq # - virtualenv -p python3.6 venv && . venv/bin/activate && make prepare && make develop extras=[all] && pip install htcondor awscli==1.16.272 # - export TOIL_TEST_INTEGRATIVE=True # - export TOIL_AWS_KEYNAME=id_rsa # - export TOIL_AWS_ZONE=us-west-2a # # This reads GITLAB_SECRET_FILE_SSH_KEYS # - python setup_gitlab_ssh.py # - python -m pytest -s -r s src/toil/test/jobStores/jobStoreTest.py toil-releases-3.24.0/.travis.yml000066400000000000000000000006251362134276200164720ustar00rootroot00000000000000language: python python: - "3.5" - "3.6" - "2.7" install: - make prepare - make develop extras=[aws,google] # adding extras to avoid import errors script: - TOIL_TEST_QUICK=True make test_offline env: # Necessary to get boto to work in Travis's Ubuntu Precise # environment (see #2498). Consider removing this if/when we # transition to the Xenial environment. - BOTO_CONFIG=/dev/null toil-releases-3.24.0/CODE_OF_CONDUCT.md000066400000000000000000000062331362134276200171610ustar00rootroot00000000000000# Contributor Covenant Code of Conduct ## Our Pledge In the interest of fostering an open and welcoming environment, we as contributors and maintainers pledge to making participation in our project and our community a harassment-free experience for everyone, regardless of age, body size, disability, ethnicity, gender identity and expression, level of experience, nationality, personal appearance, race, religion, or sexual identity and orientation. ## Our Standards Examples of behavior that contributes to creating a positive environment include: * Using welcoming and inclusive language * Being respectful of differing viewpoints and experiences * Gracefully accepting constructive criticism * Focusing on what is best for the community * Showing empathy towards other community members Examples of unacceptable behavior by participants include: * The use of sexualized language or imagery and unwelcome sexual attention or advances * Trolling, insulting/derogatory comments, and personal or political attacks * Public or private harassment * Publishing others' private information, such as a physical or electronic address, without explicit permission * Other conduct which could reasonably be considered inappropriate in a professional setting ## Our Responsibilities Project maintainers are responsible for clarifying the standards of acceptable behavior and are expected to take appropriate and fair corrective action in response to any instances of unacceptable behavior. 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The project team will review and investigate all complaints, and will respond in a way that it deems appropriate to the circumstances. The project team is obligated to maintain confidentiality with regard to the reporter of an incident. Further details of specific enforcement policies may be posted separately. Project maintainers who do not follow or enforce the Code of Conduct in good faith may face temporary or permanent repercussions as determined by other members of the project's leadership. ## Attribution This Code of Conduct is adapted from the [Contributor Covenant][homepage], version 1.4, available at [http://contributor-covenant.org/version/1/4][version] [homepage]: http://contributor-covenant.org [version]: http://contributor-covenant.org/version/1/4/ toil-releases-3.24.0/CONTRIBUTING.md000066400000000000000000000003611362134276200166070ustar00rootroot00000000000000Contribution Guidelines ======================= Before proposing a pull request, please read our [Contributor's Guide][1]. [1]: https://toil.readthedocs.io/en/master/contributing/contributing.html#contributing "Toil Contributor's Guide" toil-releases-3.24.0/LICENSE000066400000000000000000000263741362134276200153770ustar00rootroot00000000000000 Apache License Version 2.0, January 2004 http://www.apache.org/licenses/ TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION 1. Definitions. "License" shall mean the terms and conditions for use, reproduction, and distribution as defined by Sections 1 through 9 of this document. "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 other entities that control, are controlled by, or are under common control with that entity. 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"Contribution" shall mean any work of authorship, including the original version of the Work and any modifications or additions to that Work or Derivative Works thereof, that is intentionally submitted to Licensor for inclusion in the Work by the copyright owner or by an individual or Legal Entity authorized to submit on behalf of the copyright owner. For the purposes of this definition, "submitted" means any form of electronic, verbal, or written communication sent to the Licensor or its representatives, including but not limited to communication on electronic mailing lists, source code control systems, and issue tracking systems that are managed by, or on behalf of, the Licensor for the purpose of discussing and improving the Work, but excluding communication that is conspicuously marked or otherwise designated in writing by the copyright owner as "Not a Contribution." "Contributor" shall mean Licensor and any individual or Legal Entity on behalf of whom a Contribution has been received by Licensor and subsequently incorporated within the Work. 2. Grant of Copyright License. Subject to the terms and conditions of this License, each Contributor hereby grants to You a perpetual, worldwide, non-exclusive, no-charge, royalty-free, irrevocable copyright license to reproduce, prepare Derivative Works of, publicly display, publicly perform, sublicense, and distribute the Work and such Derivative Works in Source or Object form. 3. Grant of Patent License. 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We also recommend that a file or class name and description of purpose be included on the same "printed page" as the copyright notice for easier identification within third-party archives. Copyright 2011 UCSC Computational Genomics Lab Original Contributors: Benedict Paten, Hannes Schmidt, John Vivian, Christopher Ketchum, Joel Armstrong and co-authors (benedictpaten@gmail.com) 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. toil-releases-3.24.0/Makefile000066400000000000000000000226721362134276200160270ustar00rootroot00000000000000# Copyright (C) 2015-2018 UCSC Computational Genomics Lab # # 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. include common.mk define help Supported targets: prepare, develop, docs, sdist, clean, test, docker and push_docker. Please note that all build targets require a virtualenv to be active. The 'prepare' target installs Toil's build requirements into the current virtualenv. The 'develop' target creates an editable install of Toil and its runtime requirements in the current virtualenv. The install is called 'editable' because changes to the source code immediately affect the virtualenv. Set the 'extras' variable to ensure that the 'develop' target installs support for extras; some tests require extras to be installed. Consult setup.py for the list of supported extras. To install Toil in develop mode with all extras, run make develop extras=[all] The 'sdist' target creates a source distribution of Toil. It is used for some unit tests and for installing the currently checked out version of Toil into the appliance image. The 'clean' target cleans up the side effects of 'develop', 'sdist', 'docs', and 'docker' on this machine. It does not undo externally visible effects like removing packages already uploaded to PyPI. The 'docs' target uses Sphinx to create HTML documentation in the docs/_build directory Targets are provided to run Toil's tests. Note that these targets do *not* automatically install Toil's dependencies; it is recommended to 'make develop' before running any of them. The 'test' target runs Toil's unit tests serially with pytest. It will run some docker tests and setup. Note: this target does not capture output from the terminal. For any of the test targets, set the 'tests' variable to run a particular test, e.g. make test tests=src/toil/test/sort/sortTest.py::SortTest::testSort The 'integration_test' target runs toil's integration tests. These are more thorough but also more costly than the regular unit tests. For the AWS integration tests to run, the environment variable 'TOIL_AWS_KEYNAME' must be set. This user will be charged for expenses accrued during the test. The 'docker' target builds the Docker images that make up the Toil appliance. You may set the TOIL_DOCKER_REGISTRY variable to override the default registry that the 'push_docker' target pushes the appliance images to, for example: TOIL_DOCKER_REGISTRY=quay.io/USER make docker If Docker is not installed, Docker-related targets tasks and tests will be skipped. The same can be achieved by setting TOIL_DOCKER_REGISTRY to an empty string. The 'push_docker' target pushes the Toil appliance images to a remote Docker registry. It requires the TOIL_DOCKER_REGISTRY variable to be set to a value other than the default to avoid accidentally pushing to the official Docker registry for Toil. The TOIL_DOCKER_NAME environment variable can be set to customize the appliance image name that is created by the 'docker' target and pushed by the 'push_docker' target. The Toil team\'s continuous integration system overrides this variable to avoid conflicts between concurrently executing builds for the same revision, e.g. toil-pr and toil-it. endef export help help: @printf "$$help" # This Makefile uses bash features like printf and <() SHELL=bash python=python pip=pip tests=src tests_local=src/toil/test # do slightly less than travis timeout of 10 min. pytest_args_local=-vv --timeout=530 extras= sdist_name:=toil-$(shell $(python) version_template.py distVersion).tar.gz green=\033[0;32m normal=\033[0m red=\033[0;31m cyan=\033[0;36m develop: check_venv $(pip) install -e .$(extras) clean_develop: check_venv - $(pip) uninstall -y toil - rm -rf src/*.egg-info - rm src/toil/version.py sdist: dist/$(sdist_name) dist/$(sdist_name): check_venv @test -f dist/$(sdist_name) && mv dist/$(sdist_name) dist/$(sdist_name).old || true $(python) setup.py sdist @test -f dist/$(sdist_name).old \ && ( cmp -s <(tar -xOzf dist/$(sdist_name)) <(tar -xOzf dist/$(sdist_name).old) \ && mv dist/$(sdist_name).old dist/$(sdist_name) \ && printf "$(cyan)No significant changes to sdist, reinstating backup.$(normal)\n" \ || rm dist/$(sdist_name).old ) \ || true clean_sdist: - rm -rf dist - rm src/toil/version.py # We always claim to be Travis, so that local test runs will not skip Travis tests. # Gitlab doesn't run tests via the Makefile. # The auto-deployment test needs the docker appliance test: check_venv check_build_reqs docker TRAVIS=true \ $(python) -m pytest --cov=toil $(pytest_args_local) $(tests) # This target will skip building docker and all docker based tests # these are our travis tests; rename? test_offline: check_venv check_build_reqs @printf "$(cyan)All docker related tests will be skipped.$(normal)\n" TOIL_SKIP_DOCKER=True \ TRAVIS=true \ $(python) -m pytest $(pytest_args_local) $(tests_local) ifdef TOIL_DOCKER_REGISTRY docker_image:=$(TOIL_DOCKER_REGISTRY)/$(TOIL_DOCKER_NAME) grafana_image:=$(TOIL_DOCKER_REGISTRY)/toil-grafana prometheus_image:=$(TOIL_DOCKER_REGISTRY)/toil-prometheus mtail_image:=$(TOIL_DOCKER_REGISTRY)/toil-mtail define tag_docker @printf "$(cyan)Removing old tag $2. This may fail but that's expected.$(normal)\n" -docker rmi $2 docker tag $1 $2 @printf "$(green)Tagged appliance image $1 as $2.$(normal)\n" endef docker: docker/Dockerfile # Pre-pull everything for i in $$(seq 1 11); do if [[ $$i == "11" ]] ; then exit 1 ; fi ; docker pull ubuntu:16.04 && break || sleep 60; done for i in $$(seq 1 11); do if [[ $$i == "11" ]] ; then exit 1 ; fi ; docker pull prom/prometheus:v2.0.0 && break || sleep 60; done for i in $$(seq 1 11); do if [[ $$i == "11" ]] ; then exit 1 ; fi ; docker pull grafana/grafana && break || sleep 60; done for i in $$(seq 1 11); do if [[ $$i == "11" ]] ; then exit 1 ; fi ; docker pull sscaling/mtail && break || sleep 60; done @set -ex \ ; cd docker \ ; docker build --tag=$(docker_image):$(TOIL_DOCKER_TAG) -f Dockerfile . @set -ex \ ; cd dashboard/prometheus \ ; docker build --tag=$(prometheus_image):$(TOIL_DOCKER_TAG) -f Dockerfile . @set -ex \ ; cd dashboard/grafana \ ; docker build --tag=$(grafana_image):$(TOIL_DOCKER_TAG) -f Dockerfile . @set -ex \ ; cd dashboard/mtail \ ; docker build --tag=$(mtail_image):$(TOIL_DOCKER_TAG) -f Dockerfile . docker/$(sdist_name): dist/$(sdist_name) cp $< $@ docker/Dockerfile: docker/Dockerfile.py docker/$(sdist_name) _TOIL_SDIST_NAME=$(sdist_name) $(python) docker/Dockerfile.py > $@ clean_docker: -rm docker/Dockerfile docker/$(sdist_name) -docker rmi $(docker_image):$(TOIL_DOCKER_TAG) push_docker: docker # Weird if logic is so we fail if all the pushes fail for i in $$(seq 1 6); do if [[ $$i == "6" ]] ; then exit 1 ; fi ; docker push $(docker_image):$(TOIL_DOCKER_TAG) && break || sleep 60; done for i in $$(seq 1 6); do if [[ $$i == "6" ]] ; then exit 1 ; fi ; docker push $(grafana_image):$(TOIL_DOCKER_TAG) && break || sleep 60; done for i in $$(seq 1 6); do if [[ $$i == "6" ]] ; then exit 1 ; fi ; docker push $(prometheus_image):$(TOIL_DOCKER_TAG) && break || sleep 60; done for i in $$(seq 1 6); do if [[ $$i == "6" ]] ; then exit 1 ; fi ; docker push $(mtail_image):$(TOIL_DOCKER_TAG) && break || sleep 60; done else docker docker_push clean_docker: @printf "$(cyan)Skipping '$@' target as TOIL_DOCKER_REGISTRY is empty or Docker is not installed.$(normal)\n" endif docs: check_venv check_build_reqs # Strange, but seemingly benign Sphinx warning floods stderr if not filtered: cd docs && make html clean_docs: check_venv - cd docs && make clean clean: clean_develop clean_sdist clean_docs check_build_reqs: @$(python) -c 'import mock; import pytest' \ || ( printf "$(red)Build requirements are missing. Run 'make prepare' to install them.$(normal)\n" ; false ) prepare: check_venv $(pip) install mock==1.0.1 pytest==4.3.1 pytest-cov==2.6.1 stubserver==1.0.1 pytest-timeout==1.3.3 cwltest check_venv: @$(python) -c 'import sys, os; sys.exit( int( 0 if "VIRTUAL_ENV" in os.environ else 1 ) )' \ || ( printf "$(red)A virtualenv must be active.$(normal)\n" ; false ) check_clean_working_copy: @printf "$(green)Checking if your working copy is clean ...$(normal)\n" @git diff --exit-code > /dev/null \ || ( printf "$(red)Your working copy looks dirty.$(normal)\n" ; false ) @git diff --cached --exit-code > /dev/null \ || ( printf "$(red)Your index looks dirty.$(normal)\n" ; false ) @test -z "$$(git ls-files --other --exclude-standard --directory)" \ || ( printf "$(red)You have untracked files:$(normal)\n" \ ; git ls-files --other --exclude-standard --directory \ ; false ) check_cpickle: # fail if cPickle.dump(s) called without HIGHEST_PROTOCOL # https://github.com/BD2KGenomics/toil/issues/1503 ! find src -iname '*.py' | xargs grep 'cPickle.dump' | grep --invert-match HIGHEST_PROTOCOL .PHONY: help \ prepare \ check_cpickle \ develop clean_develop \ sdist clean_sdist \ test test_offline \ docs clean_docs \ clean \ check_venv \ check_clean_working_copy \ check_build_reqs \ docker clean_docker push_docker toil-releases-3.24.0/README.rst000066400000000000000000000025021362134276200160440ustar00rootroot00000000000000ATTENTION: Toil will be dropping python 2.7 support on January 1, 2020 when python 2.7 itself is scheduled to die. This is when the last release of python 2.7 compatible toil will be. Toil is a scalable, efficient, cross-platform (Linux & macOS) pipeline management system, written entirely in Python, and designed around the principles of functional programming. * Check the `website`_ for a description of Toil and its features. * Full documentation for the latest stable release can be found at `Read the Docs`_. * Please subscribe to low-volume `announce`_ mailing list so we keep you informed * Google Groups discussion `forum`_ * See our occasional `blog`_ for tutorials. .. _website: http://toil.ucsc-cgl.org/ .. _Read the Docs: https://toil.readthedocs.io/en/latest .. _announce: https://groups.google.com/forum/#!forum/toil-announce .. _forum: https://groups.google.com/forum/#!forum/toil-community .. _blog: https://toilpipelines.wordpress.com/ .. image:: https://badges.gitter.im/bd2k-genomics-toil/Lobby.svg :alt: Join the chat at https://gitter.im/bd2k-genomics-toil/Lobby :target: https://gitter.im/bd2k-genomics-toil/Lobby?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge Note: Toil moved from https://github.com/BD2KGenomics/toil to https://github.com/DataBiosphere/toil on July 5th, 2018. toil-releases-3.24.0/ROADMAP.md000066400000000000000000000023301362134276200157610ustar00rootroot00000000000000# Near Term (In Progress, Estimated Completion Date?) * Libcloud provisioning - [ ] Google - [ ] AWS - [ ] Fix flaky tests - [ ] Run massive workflows - [ ] Better feedback (error messages, logging). # Medium Term (~ 6-month goals, by ~June 2018?) * Batch systems - [ ] Google Pipelines - [ ] AWS Batch - [ ] Containerize leader (work with Consonance) - [ ] Change the thread pool model to improve single machine usage. * Improve the development process. - [ ] Add a linter - [ ] Add a code coverage tool. - [ ] Organize tests. - [ ] Better access to tests for external developers. - [ ] TES support - [ ] WES Support (if Consonance does not work well) # Longer Term - [ ] Better track versions of specifications (e.g. CWL, WDL) and dependencies. - [ ] Add other provisioners: OpenStack - [ ] Singularity support. - [ ] Uniform configuration (i.e. not just environment variables). - [ ] Add management and monitoring UIs. - [ ] Python 3 support. - [ ] Add URL wrapping for streaming instead of copying. # Completed - [x] Basic WDL support. - [x] Travis CI for commits. - [x] Run Toil within Popper (https://cross.ucsc.edu/tag/popper/). - [x] Grafana for workflow monitoring - [x] Finish Google jobStore (GCP) toil-releases-3.24.0/attic/000077500000000000000000000000001362134276200154625ustar00rootroot00000000000000toil-releases-3.24.0/attic/README.md000066400000000000000000000651641362134276200167550ustar00rootroot00000000000000#Toil Python based pipeline management software for clusters that makes running recursive and dynamically scheduled computations straightforward. So far works with gridEngine, lsf, parasol and on multi-core machines. ##Authors [Benedict Paten](https://github.com/benedictpaten/), [Dent Earl](https://github.com/dentearl/), [Daniel Zerbino](https://github.com/dzserbino/), [Glenn Hickey](https://github.com/glennhickey/), other UCSC people. ##Requirements * Python 2.5 or later, but less than 3.0 ##Installation 1. Install sonLib. See https://github.com/benedictpaten/sonLib 2. Place the directory containing the toil in the same directory as sonLib. The directory containing both sonLib and toil should be on your python path. i.e. PYTHONPATH=${PYTHONPATH}:FOO where FOO/toil is the path containing the base directory of toil. 3. Build the code: Type 'make all' in the base directory, this just puts some stuff that is currently all python based in the bin dir. In the future there might be some actual compilation. 4. Test the code: python allTests.py or 'make test'. ##Running and examining a toil script The following walks through running a toil script and using the command-line tools **toilStatus**, **toilRun** and **toilStats**, which are used to analyse the status, restart and print performance statistics, respectively, about a run. Once toil is installed, running a toil script is performed by executing the script from the command-line, e.g. (using the file sorting toy example in **tests/sort/scriptTreeTest_Sort.py**): []$ scriptTreeTest_Sort.py --fileToSort foo --toil bar/toil --batchSystem parasol --logLevel INFO --stats Which in this case uses the parasol batch system, and INFO level logging and where foo is the file to sort and bar/toil is the location of a directory (which should not already exist) from which the batch will be managed. Details of the toil options are described below; the stats option is used to gather statistics about the jobs in a run. The script will return a zero exit value if the toil system is successfully able to run to completion, else it will create an exception. If the script fails because a job failed then the log file information of the job will be reported to std error. The toil directory (here 'bar/toil') is not automatically deleted regardless of success or failure, and contains a record of the jobs run, which can be enquired about using the **toilStatus** command. e.g. []$toilStatus bar/toil --verbose ``` There are 0 active jobs, 0 parent jobs with children, 0 totally failed jobs and 0 empty jobs (i.e. finished but not cleaned up) curre ntly in toil: toil There are no failed jobs to report ``` If a job failed, this provides a convenient way to reprint the error. The following are the important options to **toilStatus**: --toil=TOIL Directory containing the jobtree. The toil location can also be specified as the argument to the script. default=./toil --verbose Print loads of information, particularly all the log files of jobs that failed. default=False --failIfNotComplete Return exit value of 1 if toil jobs not all completed. default=False If a job in the script failed or the system goes down, you may wish to retry the job after fixing the error. This can be achieved by restarting the script with the **toilRun** command which will restart an existing toil. []$ toilRun --toil bar/toil --logLevel INFO It will always attempt to restart the jobs from the previous point of failure. If the script was run with the **--stats** option then **toilStats** can be run on the pipeline do generate information about the performance of the run, in terms of how many jobs were run, how long they executed for and how much CPU time/wait time was involved, e.g.: []$toilStats bar/toil ``` Batch System: singleMachine Default CPU: 1 Default Memory: 2097152K Job Time: 0.50 Max CPUs: 9.22337e+18 Max Threads: 4 Total Clock: 0.09 Total Runtime: 7.60 Slave Count | Time* | Clock | Wait | Memory n | min med* ave max total | min med ave max total | min med ave max total | min med ave max total 365 | 0.01 0.02 0.02 0.06 6.82 | 0.01 0.01 0.01 0.04 4.71 | 0.00 0.00 0.01 0.03 2.11 | 9781248K 13869056K 13799121K 14639104K 5036679168K Job Slave Jobs | min med ave max | 2 2 2 2 Count | Time* | Clock | Wait | Memory n | min med* ave max total | min med ave max total | min med ave max total | min med ave max total 367 | 0.00 0.00 0.00 0.03 0.68 | 0.00 0.00 0.00 0.01 0.42 | 0.00 0.00 0.00 0.03 0.26 | 9461760K 13869056K 13787694K 14639104K 5060083712K Cleanup Count | Time* | Clock | Wait | Memory n | min med* ave max total | min med ave max total | min med ave max total | min med ave max total 1 | 0.00 0.00 0.00 0.00 0.00 | 0.00 0.00 0.00 0.00 0.00 | 0.00 0.00 0.00 0.00 0.00 | 14639104K 14639104K 14639104K 14639104K 14639104K Up Count | Time* | Clock | Wait | Memory n | min med* ave max total | min med ave max total | min med ave max total | min med ave max total 124 | 0.00 0.00 0.00 0.01 0.15 | 0.00 0.00 0.00 0.01 0.12 | 0.00 0.00 0.00 0.01 0.03 | 13713408K 14090240K 14044985K 14581760K 1741578240K Setup Count | Time* | Clock | Wait | Memory n | min med* ave max total | min med ave max total | min med ave max total | min med ave max total 1 | 0.00 0.00 0.00 0.00 0.00 | 0.00 0.00 0.00 0.00 0.00 | 0.00 0.00 0.00 0.00 0.00 | 9551872K 9551872K 9551872K 9551872K 9551872K Down Count | Time* | Clock | Wait | Memory n | min med* ave max total | min med ave max total | min med ave max total | min med ave max total 241 | 0.00 0.00 0.00 0.03 0.53 | 0.00 0.00 0.00 0.00 0.30 | 0.00 0.00 0.00 0.03 0.23 | 9461760K 13828096K 13669354K 14155776K 3294314496K ``` The breakdown is given per "slave", which is unit of serial execution, and per "job", which corresponds to a scriptTree job (see below). Despite its simplicity, we've found this can be **very** useful for tracking down performance issues, particularly when trying out a pipeline on a new system. The important arguments to **toilStats** are: --outputFile=OUTPUTFILE File in which to write results --raw output the raw xml data. --pretty, --human if not raw, prettify the numbers to be human readable. --categories=CATEGORIES comma separated list from [time, clock, wait, memory] --sortCategory=SORTCATEGORY how to sort Job list. may be from [alpha, time, clock, wait, memory, count]. default=%(default)s --sortField=SORTFIELD how to sort Job list. may be from [min, med, ave, max, total]. default=%(default)s --sortReverse, --reverseSort reverse sort order. --cache stores a cache to speed up data display. ##toil options A toil script will have the following command-line options. Options that control logging. --logOff Turn off logging. (default is CRITICAL) --logInfo Turn on logging at INFO level. (default is CRITICAL) --logDebug Turn on logging at DEBUG level. (default is CRITICAL) --logLevel=LOGLEVEL Log at level (may be either OFF/INFO/DEBUG/CRITICAL). (default is CRITICAL) --logFile=LOGFILE File to log in --rotatingLogging Turn on rotating logging, which prevents log files getting too big. Options to specify the location of the toil and turn on stats collation about the performance of jobs. --toil=TOIL Directory in which to place job management files and the global accessed temporary file directories(this needs to be globally accessible by all machines running jobs). If you pass an existing directory it will check if it's a valid existing jobtree, then try and restart the jobs in it. The default=./toil --stats Records statistics about the job-tree to be used by toilStats. default=False Options for specifying the batch system, and arguments to the batch system/big batch system (see below). --batchSystem=BATCHSYSTEM The type of batch system to run the job(s) with, currently can be 'singleMachine'/'parasol'/'acidTest'/'gridEngine'/'lsf'. default=singleMachine --maxThreads=MAXTHREADS The maximum number of threads (technically processes at this point) to use when running in single machine mode. Increasing this will allow more jobs to run concurrently when running on a single machine. default=4 --parasolCommand=PARASOLCOMMAND The command to run the parasol program default=parasol Options to specify default cpu/memory requirements (if not specified by the jobs themselves), and to limit the total amount of memory/cpu requested from the batch system. --defaultMemory=DEFAULTMEMORY The default amount of memory to request for a job (in bytes), by default is 2^31 = 2 gigabytes, default=2147483648 --defaultCores=DEFAULTCORES The default the number of cpus to dedicate a job. default=1 --maxCpus=MAXCPUS The maximum number of cpus to request from the batch system at any one time. default=9223372036854775807 --maxMemory=MAXMEMORY The maximum amount of memory to request from the batch system at any one time. default=9223372036854775807 Options for rescuing/killing/restarting jobs, includes options for jobs that either run too long/fail or get lost (some batch systems have issues!). --retryCount=RETRYCOUNT Number of times to retry a failing job before giving up and labeling job failed. default=0 --maxJobDuration=MAXJOBDURATION Maximum runtime of a job (in seconds) before we kill it (this is a lower bound, and the actual time before killing the job may be longer). default=9223372036854775807 --rescueJobsFrequency=RESCUEJOBSFREQUENCY Period of time to wait (in seconds) between checking for missing/overlong jobs, that is jobs which get lost by the batch system. Expert parameter. (default is set by the batch system) toil big batch system options; toil can employ a secondary batch system for running large memory/cpu jobs using the following arguments. --bigBatchSystem=BIGBATCHSYSTEM The batch system to run for jobs with larger memory/cpus requests, currently can be 'singleMachine'/'parasol'/'acidTest'/'gridEngine'. default=none --bigMemoryThreshold=BIGMEMORYTHRESHOLD The memory threshold above which to submit to the big queue. default=9223372036854775807 --bigCpuThreshold=BIGCPUTHRESHOLD The cpu threshold above which to submit to the big queue. default=9223372036854775807 --bigMaxCpus=BIGMAXCPUS The maximum number of big batch system cpus to allow at one time on the big queue. default=9223372036854775807 --bigMaxMemory=BIGMAXMEMORY The maximum amount of memory to request from the big batch system at any one time. default=9223372036854775807 Miscellaneous options. --jobTime=JOBTIME The approximate time (in seconds) that you'd like a list of child jobs to be run serially before being parallelized. This parameter allows one to avoid over parallelizing tiny jobs, and therefore paying significant scheduling overhead, by running tiny jobs in series on a single node/core of the cluster. default=30 --maxLogFileSize=MAXLOGFILESIZE The maximum size of a job log file to keep (in bytes), log files larger than this will be truncated to the last X bytes. Default is 50 kilobytes, default=50120 --command=COMMAND The command to run (which will generate subsequent jobs). This is deprecated ##Overview of toil The following sections are for people creating toil scripts and as general information. The presentation **[docs/toilSlides.pdf](https://github.com/benedictpaten/toil/blob/master/doc/toilSlides.pdf)** is also a quite useful, albeit slightly out of date, guide to using toil. - Most batch systems (such as LSF, Parasol, etc.) do not allow jobs to spawn other jobs in a simple way. The basic pattern provided by toil is as follows: 1. You have a job running on your cluster which requires further parallelisation. 2. You create a list of jobs to perform this parallelisation. These are the 'child' jobs of your process, we call them collectively the 'children'. 3. You create a 'follow-on' job, to be performed after all the children have successfully completed. This job is responsible for cleaning up the input files created for the children and doing any further processing. Children should not cleanup files created by parents, in case of a batch system failure which requires the child to be re-run (see 'Atomicity' below). 4. You end your current job successfully. 5. The batch system runs the children. These jobs may in turn have children and follow-on jobs. 6. Upon completion of all the children (and children's children and follow-ons, collectively descendants) the follow-on job is run. The follow-on job may create more children. ##scriptTree ScriptTree provides a Python interface to toil, and is now the only way to interface with toil (previously you could manipulate XML files, but I've removed that functionality as I improved the underlying system). Aside from being the interface to toil, scriptTree was designed to remediate some of the pain of writing wrapper scripts for cluster jobs, via the extension of a simple python wrapper class (called a 'Job' to avoid confusion with the more general use of the word 'job') which does much of the work for you. Using scriptTree, you can describe your script as a series of these classes which link together, with all the arguments and options specified in one place. The script then, using the magic of python pickles, generates all the wrappers dynamically and clean them up when done. This inherited template pattern has the following advantages: 1. You write (potentially) just one script, not a series of wrappers. It is much easier to understand, maintain, document and explain. 2. You write less boiler plate. 3. You can organise all the input arguments and options in one place. The best way to learn how to use script tree is to look at an example. The following is taken from (an old version of) toil.test.sort.scriptTreeTest_Sort.py which provides a complete script for performing a parallel merge sort. Below is the first 'Job' of this script inherited from the base class 'toil.scriptTree.Job'. Its job is to setup the merge sort. ```python class Setup(Job): """Sets up the sort. """ def __init__(self, inputFile, N): Job.__init__(self, time=1, memory=1000000, cpu=1) self.inputFile = inputFile self.N = N def run(self): tempOutputFile = getTempFile(rootDir=self.getGlobalTempDir()) self.addChildJob(Down(self.inputFile, 0, os.path.getsize(self.inputFile), self.N, tempOutputFile)) self.setFollowOnJob(Cleanup(tempOutputFile, self.inputFile)) ``` The constructor (**__init__()**) assigns some variables to the class. When invoking the constructor of the base class (which should be the first thing the job does), you can optionally pass time (in seconds), memory (in bytes) and cpu parameters. The time parameter is your estimate of how long the job will run - UPDATE: IT IS CURRENTLY UNUSED BY THE SCHEDULAR. The memory and cpu parameters allow you to guarantee resources for a job. The run method is where the variables assigned by the constructor are used and where in general actual work is done. Aside from doing the specific work of the job (in this case creating a temporary file to hold some intermediate output), the run method is also where children and a follow-on job are created, using **addChildJob()** and **setFollowOnJob()**. A job may have arbitrary numbers of children, but one or zero follow-on jobs. Jobs are also provided with two temporary file directories called **localTempDir** and **globalTempDir**, which can be accessed with the methods **getLocalTempDir()** and **getGlobalTempDir()**, respectively. The **localTempDir** is the path to a temporary directory that is local to the machine on which the job is being executed and that will exist only for the length of the run method. It is useful for storing interim results that are computed during runtime. All files in this directory are guaranteed to be removed once the run method has finished - even if your job crashes. A job can either be created as a follow-on, or it can be the very first job, or it can be created as a child of another job. Let a job not created as a follow-on be called a 'founder'. Each founder job may have a follow-on job. If it has a follow-on job, this follow-on job may in turn have a follow-on, etc. Thus each founder job defines a chain of follow-ons. Let a founder job and its maximal sequence of follow-ons be called a 'chain'. Let the last follow-on job in a chain be called the chain's 'closer'. For each chain of jobs a temporary directory, **globalTempDir**, is created immediately prior to calling the founder job's run method, this directory and its contents then persist until the completion of closer job's run method. Thus the **globalTempDir** is a scratch directory in which temporary results can be stored on disk between job jobs in a chain. Furthermore, files created in this directory can be passed to the children of job jobs in the chain, allowing results to be transmitted from a job job to its children. ##Making Functions into Jobs To avoid the need to create a Job class for every job, I've added the ability to wrap functions, hence the code for the setup function described above becomes: ``` def setup(job, inputFile, N): """Sets up the sort. """ tempOutputFile = getTempFile(rootDir=job.getGlobalTempDir()) job.addChildJobFn(down, (inputFile, 0, os.path.getsize(inputFile), N, tempOutputFile)) job.setFollowOnFn(cleanup, (tempOutputFile, inputFile)) ``` The code to turn this into a job uses the static method **[Job.makeJobFnJob](https://github.com/benedictpaten/toil/blob/development/scriptTree/job.py#L142)**: ``` Job.makeJobFnJob(setup, (fileToSort, N)) ``` Notice that the child and follow-on jobs have also been refactored as functions, hence the methods **[addChildJobFn](https://github.com/benedictpaten/toil/blob/development/scriptTree/job.py#L82)** and **[setFollowOnFn](https://github.com/benedictpaten/toil/blob/development/scriptTree/job.py#L67)**, which take functions as opposed to Job objects. Note, there are two types of functions you can wrap - **job functions**, whose first argument must be the wrapping job object (the setup function above is an excample of a job function), and plain functions that do not have a reference to the wrapping job. ##Creating a scriptTree script: ScriptTree jobs are serialized (written and retrieved from disk) so that they can be executed in parallel on a cluster of different machines. Thankfully, this is mostly transparent to the user, except for the fact that jobs must be 'pickled' (see python docs), which creates a few constraints upon what can and can not be passed to and stored by a job. Currently the preferred way to run a pipeline is to create an executable python script. For example, see **tests/sorts/scriptTreeTest_Sort.py**. The first line to notice is: ```python from toil.scriptTree.job import Job, Stack ``` This imports the Job and Stack objects (the stack object is used to run the jobs). Most of the code defines a series of jobs (see above). The **main()** method is where the script is setup and run. The line: ```python parser = OptionParser() ``` Creates an options parser using the python module optparse. The line: ```python Stack.addToilOptions(parser) ``` Adds the toil options to the parser. Most importantly it adds the command line options "--toil [path to toil]", which is the location in which the toil will be created, and which must be supplied to the script. The subsequent lines parse the input arguments, notably the line: ```python options, args = parser.parse_args() ``` reads in the input parameters. The line: ```python i = Stack(Setup(options.fileToSort, int(options.N))).startToil(options) ``` Is where the first job is created (the Setup job shown above), where a stack object is created, which is passed the first job as its sole construction argument, and finally where the toil is executed from, using the stack's **startToil(options)** function. The 'options' argument will contain a dictionary of command line arguments which are used by toil. The return value of this function is equal to the number of failed jobs. In this case we choose to throw an exception if there are any remaining. One final important detail, the lines: ```python if __name__ == '__main__': from toil.test.sort.scriptTreeTest_Sort import * ``` reload the objects in the module, such that their module names will be absolute (this is necessary for the serialization that is used). Jobs in other classes that are imported do not need to be reloaded in this way. ##Atomicity toil and scriptTree are designed to be robust, so that individuals jobs (jobs) can fail, and be subsequently restarted. It is assumed jobs can fail at any point. Thus until toil knows your children have been completed okay you can not assume that your Job has been completed. To ensure that your pipeline can be restarted after a failure ensure that every job (job): 1. **Never cleans up / alters its own input files.** Instead, parents and follow on jobs may clean up the files of children or prior jobs. 2. Can be re-run from just its input files any number of times. A job should only depend on its input, and it should be possible to run the job as many times as desired, essentially until news of its completion is successfully transmitted to the jobtree master process. These two properties are the key to job atomicity. Additionally, you'll find it much easier if a job: 3. Only creates temp files in the two provided temporary file directories. This ensures we don't soil the cluster's disks. 4. Logs sensibly, so that error messages can be transmitted back to the master and the pipeline can be successfully debugged. ##Environment toil replicates the environment in which toil or scriptTree is invoked and provides this environment to all the jobs/jobs. This ensures uniformity of the environment variables for every job. ##FAQ's: * _How robust is toil to failures of nodes and/or the master?_ Toil checkpoints its state on disk, so that it or the job manager can be wiped out and restarted. There is some gnarly test code to show how this works, it will keep crashing everything, at random points, but eventually everything will complete okay. As a user you needn't worry about any of this, but your child jobs must be atomic (as with all batch systems), and must follow the convention regarding input files. * _How scaleable?_ We have tested having 1000 concurrent jobs running on our cluster. This will depend on the underlying batch system being used. * _Can you support the XYZ batch system?_ See the abstract base class '[AbstractBatchSystem](https://github.com/benedictpaten/toil/blob/master/batchSystems/abstractBatchSystem.py)' in the code to see what functions need to be implemented. It's reasonably straight forward. * _Is there an API for the toil top level commands?_ Not really - at this point please use scriptTree and the few command line utilities present in the bin directory. * _Why am I getting the error "ImportError: No module named etree.ElementTree"?_ The version of python in your path is less than 2.5. When toil spawns a new job it will use the python found in your PATH. Make sure that the first python in your PATH points to a python version greater than or equal to 2.5 but less than 3.0 toil-releases-3.24.0/attic/absolute_imports.py000066400000000000000000000111061362134276200214260ustar00rootroot00000000000000from __future__ import absolute_import import os import sys import ast import tempfile import shutil def enable_absolute_imports(script, script_name): """ Empty modules >>> enable_absolute_imports('') 'from __future__ import absolute_import\\n' Ignore empty lines >>> enable_absolute_imports('\\n') 'from __future__ import absolute_import\\n' Append after initial comments, like shebangs >>> enable_absolute_imports('#foo\\n') '#foo\\nfrom __future__ import absolute_import\\n' Insert before regular comments >>> enable_absolute_imports('#foo\\nimport bar\\n') '#foo\\nfrom __future__ import absolute_import\\nimport bar\\n' Insert before non-import statements >>> enable_absolute_imports('if False:\\n pass\\n') 'from __future__ import absolute_import\\nif False:\\n pass\\n' Idempotence >>> enable_absolute_imports('from __future__ import absolute_import\\n') is None True Other __future__ imports >>> enable_absolute_imports('from __future__ import print_function\\n') 'from __future__ import absolute_import\\nfrom __future__ import print_function\\n' Insert before from ... immport statements >>> enable_absolute_imports('from blah import fasel\\n') 'from __future__ import absolute_import\\nfrom blah import fasel\\n' Insert before multiple future imports >>> enable_absolute_imports('from __future__ import print_function\\nfrom __future__ import nested_scopes\\n') 'from __future__ import absolute_import\\nfrom __future__ import print_function\\nfrom __future__ import nested_scopes\\n' Insert before wrapped multi-name future import >>> enable_absolute_imports('from __future__ import (print_function,\\n nested_scopes)\\n') 'from __future__ import absolute_import\\nfrom __future__ import (print_function,\\n nested_scopes)\\n' Usually docstrings show up as attributes of other nodes but unassociated docstring become Expr nodes in the AST. >>> enable_absolute_imports("#foo\\n\\n'''bar'''\\n\\npass") "#foo\\n\\nfrom __future__ import absolute_import\\n'''bar'''\\n\\npass\\n" Unassociated multiline docstring >>> enable_absolute_imports("#foo\\n\\n'''bar\\n'''\\n\\npass") "#foo\\n\\nfrom __future__ import absolute_import\\n'''bar\\n'''\\n\\npass\\n" """ tree = ast.parse(script, filename=script_name) lines = script.split('\n') while lines and lines[-1] == "": lines.pop() node = None for child in ast.iter_child_nodes(tree): if isinstance(child, ast.Import): node = child break elif isinstance(child, ast.ImportFrom): assert child.level == 0 # don't know what this means if child.module == '__future__': if any(alias.name == 'absolute_import' for alias in child.names): return None else: if node is None: node = child else: node = child break if node is None: if len(tree.body) == 0: node = ast.stmt() node.lineno = len(lines) + 1 else: node = tree.body[0] # This crazy heuristic tries to handle top-level docstrings with newlines in them # for which lineno is the line where the docstring ends if isinstance(node, ast.Expr) and isinstance(node.value, ast.Str): node.lineno -= node.value.s.count('\n') line = 'from __future__ import absolute_import' lines.insert(node.lineno - 1, line) lines.append("") return '\n'.join(lines) def main(root_path): for dir_path, dir_names, file_names in os.walk(root_path): for file_name in file_names: if file_name.endswith('.py') and file_name != 'setup.py': file_path = os.path.join(dir_path, file_name) with open(file_path) as file: script = file.read() new_script = enable_absolute_imports(script, file_name) if new_script is not None: temp_handle, temp_file_path = tempfile.mkstemp(prefix=file_name, dir=dir_path) try: with os.fdopen(temp_handle, 'w') as temp_file: temp_file.write(new_script) except: os.unlink(temp_file_path) raise else: 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Returns the FileID of the sorted file """ # Write the input file to the file store job.fileStore.logToMaster("Starting the merge sort") return job.addChildJobFn(down, input_file_id, n, down_checkpoints=down_checkpoints, memory='600M').rv() def down(job, input_file_id, n, down_checkpoints): """Input is a file and a range into that file to sort and an output location in which to write the sorted file. If the range is larger than a threshold N the range is divided recursively and a follow on job is then created which merges back the results. Otherwise, the file is sorted and placed in the output. """ # Read the file input_file = job.fileStore.readGlobalFile(input_file_id, cache=False) length = os.path.getsize(input_file) if length > n: # We will subdivide the file job.fileStore.logToMaster("Splitting file: %s of size: %s" % (input_file_id, length), level=logging.CRITICAL) # Split the file into two copies mid_point = get_midpoint(input_file, 0, length) t1 = job.fileStore.getLocalTempFile() with open(t1, 'w') as fH: copy_subrange_of_file(input_file, 0, mid_point + 1, fH) t2 = job.fileStore.getLocalTempFile() with open(t2, 'w') as fH: copy_subrange_of_file(input_file, mid_point + 1, length, fH) # Call the down function recursively return job.addFollowOnJobFn(up, job.addChildJobFn(down, job.fileStore.writeGlobalFile(t1), n, down_checkpoints=down_checkpoints, memory='600M').rv(), job.addChildJobFn(down, job.fileStore.writeGlobalFile(t2), n, down_checkpoints=down_checkpoints, memory='600M').rv()).rv() else: # We can sort this bit of the file job.fileStore.logToMaster("Sorting file: %s of size: %s" % (input_file_id, length), level=logging.CRITICAL) # Sort the copy and write back to the fileStore output_file = job.fileStore.getLocalTempFile() sort(input_file, output_file) return job.fileStore.writeGlobalFile(output_file) def up(job, input_file_id_1, input_file_id_2): """Merges the two files and places them in the output. """ with job.fileStore.writeGlobalFileStream() as (fileHandle, output_id): with job.fileStore.readGlobalFileStream(input_file_id_1) as inputFileHandle1: with job.fileStore.readGlobalFileStream(input_file_id_2) as inputFileHandle2: job.fileStore.logToMaster("Merging %s and %s to %s" % (input_file_id_1, input_file_id_2, output_id)) merge(inputFileHandle1, inputFileHandle2, fileHandle) # Cleanup up the input files - these deletes will occur after the completion is successful. job.fileStore.deleteGlobalFile(input_file_id_1) job.fileStore.deleteGlobalFile(input_file_id_2) return output_id # convenience functions def sort(in_file, out_file): """Sorts the given file. """ filehandle = open(in_file, 'r') lines = filehandle.readlines() filehandle.close() lines.sort() filehandle = open(out_file, 'w') for line in lines: filehandle.write(line) filehandle.close() def merge(filehandle_1, filehandle_2, output_filehandle): """Merges together two files maintaining sorted order. """ line2 = filehandle_2.readline() for line1 in filehandle_1.readlines(): while line2 != '' and line2 <= line1: output_filehandle.write(line2) line2 = filehandle_2.readline() output_filehandle.write(line1) while line2 != '': output_filehandle.write(line2) line2 = filehandle_2.readline() def copy_subrange_of_file(input_file, file_start, file_end, output_filehandle): """Copies the range (in bytes) between fileStart and fileEnd to the given output file handle. """ with open(input_file, 'r') as fileHandle: fileHandle.seek(file_start) data = fileHandle.read(file_end - file_start) assert len(data) == file_end - file_start output_filehandle.write(data) def get_midpoint(file, file_start, file_end): """Finds the point in the file to split. Returns an int i such that fileStart <= i < fileEnd """ filehandle = open(file, 'r') mid_point = (file_start + file_end) / 2 assert mid_point >= file_start filehandle.seek(mid_point) line = filehandle.readline() assert len(line) >= 1 if len(line) + mid_point < file_end: return mid_point + len(line) - 1 filehandle.seek(file_start) line = filehandle.readline() assert len(line) >= 1 assert len(line) + file_start <= file_end return len(line) + file_start - 1 def make_file_to_sort(file_name, lines, line_length): with open(file_name, 'w') as fileHandle: for _ in xrange(lines): line = "".join(random.choice('actgACTGNXYZ') for _ in xrange(line_length - 1)) + '\n' fileHandle.write(line) def main(): parser = ArgumentParser() Job.Runner.addToilOptions(parser) parser.add_argument('--num-lines', default=1000, help='Number of lines in file to sort.', type=int) parser.add_argument('--line-length', default=50, help='Length of lines in file to sort.', type=int) parser.add_argument("--N", help="The threshold below which a serial sort function is used to sort file. " "All lines must of length less than or equal to N or program will fail", default=10000) options = parser.parse_args() if int(options.N) <= 0: raise RuntimeError("Invalid value of N: %s" % options.N) file_name = 'file_to_sort.txt' make_file_to_sort(file_name=file_name, lines=options.num_lines, line_length=options.line_length) with Toil(options) as toil: sort_file_url = 'file://' + os.path.abspath('file_to_sort.txt') if not toil.options.restart: sort_file_id = toil.importFile(sort_file_url) sorted_file_id = toil.start(Job.wrapJobFn(setup, sort_file_id, int(options.N), False, memory='600M')) else: sorted_file_id = toil.restart() toil.exportFile(sorted_file_id, sort_file_url) if __name__ == '__main__': main() toil-releases-3.24.0/common.mk000066400000000000000000000056051362134276200162050ustar00rootroot00000000000000# Toil Environment Variables # # Configure how toil runs in different environments. For more detailed descriptions, see: # https://toil.readthedocs.io/en/latest/appendices/environment_vars.html SHELL=bash python=python ############ ### MAIN ### ############ # this specifies the toil docker "appliance" # which is the docker image used for all toil autoscaling runs # https://toil.readthedocs.io/en/latest/running/cloud/amazon.html#toil-provisioner # TODO: Add and link a better readthedocs for the toil appliance export TOIL_DOCKER_REGISTRY?=quay.io/ucsc_cgl export TOIL_DOCKER_NAME?=toil export TOIL_DOCKER_TAG?=$(shell $(python) version_template.py dockerTag) export TOIL_APPLIANCE_SELF?=$(TOIL_DOCKER_REGISTRY)/$(TOIL_DOCKER_NAME):$(TOIL_DOCKER_TAG) # TOIL_CHECK_ENV='' # Determines whether toil refers to the same virtualenv paths it spawned from (across machines) ########### ### AWS ### ########### export TOIL_AWS_ZONE?=us-west-2a export TOIL_AWS_NODE_DEBUG?=False # Don't shut down EC2 instances that fail so that they can be debugged # TOIL_AWS_AMI='' # ID of the (normally CoreOS) AMI to use in node provisioning. Defaults to latest. ####################### ### KUBERNETES ONLY ### ####################### # TOIL_AWS_SECRET_NAME='' # Name of the AWS secret, if any, to mount in containers. ############## ### GOOGLE ### ############## # GOOGLE_APPLICATION_CREDENTIALS='' https://cloud.google.com/docs/authentication/getting-started#setting_the_environment_variable ########### ### HPC ### ########### # https://toil.readthedocs.io/en/latest/developingWorkflows/toilAPIBatchsystem.html#batch-system-enivronmental-variables # TOIL_SLURM_ARGS='' # TOIL_GRIDENGINE_ARGS='' # TOIL_GRIDENGINE_PE='' # TOIL_TORQUE_ARGS='' # TOIL_TORQUE_REQS='' # TOIL_LSF_ARGS='' # TOIL_HTCONDOR_PARAMS='' ############ ### MISC ### ############ # TOIL_CUSTOM_DOCKER_INIT_COMMAND='' # Any custom bash command run prior to initiating the toil run. #################### ### TESTING ONLY ### #################### export TOIL_TEST_INTEGRATIVE?=False # If ``True``, this allows the integration tests to run. export TOIL_TEST_QUICK?=False # If ``True``, long running tests are skipped. export TOIL_SKIP_DOCKER?=False # Skip docker dependent tests export TRAVIS?=True # Run tests for travis (shorter unit tests) export TOIL_AWS_KEYNAME?=id_rsa # SSH key to use for tests in AWS. export TOIL_GOOGLE_KEYNAME?=id_rsa # SSH key to use for tests in google. # TOIL_GOOGLE_PROJECTID='' # Project ID required to to run the google cloud tests. TODO: Add this. # Required for running Mesos master and slave daemons as part of the tests # http://mesos.apache.org/documentation/latest/configuration/libprocess/ export LIBPROCESS_IP?=127.0.0.1 # TOIL_TEST_TEMP='' # Where Toil tests will write their temporary files. Defaults to the system's temp directory. # TOIL_BOTO_DIR='' # Only used for google scale testing; should likely be removed? toil-releases-3.24.0/contrib/000077500000000000000000000000001362134276200160165ustar00rootroot00000000000000toil-releases-3.24.0/contrib/admin/000077500000000000000000000000001362134276200171065ustar00rootroot00000000000000toil-releases-3.24.0/contrib/admin/test-pr000077500000000000000000000013631362134276200204350ustar00rootroot00000000000000#!/usr/bin/env bash # test-pr: submit a PR from an external contributor for Gitlab testing set -e # Check arguments if [[ "${#}" -ne 3 ]] ; then printf >&2 "test-pr: submit a PR from an external contributor for Gitlab testing\n\n" printf >&2 "\tusage: test-pr GH_USER SOURCE_BRANCH DEST_BRANCH\n\n" printf >&2 "\texample: test-pr arostamianfar defaultcaching issues/2586-allow-enabling-caching\n\n" exit 1 fi # Parse arguments GH_USER="${1}" shift SOURCE_BRANCH="${1}" shift DEST_BRANCH="${1}" shift echo "Fetch ${SOURCE_BRANCH} from ${GH_USER}" git fetch "git@github.com:${GH_USER}/toil.git" "${SOURCE_BRANCH}" echo "Push to Toil ${DEST_BRANCH}" git push git@github.com:DataBiosphere/toil.git "FETCH_HEAD:refs/heads/${DEST_BRANCH}" toil-releases-3.24.0/dashboard/000077500000000000000000000000001362134276200163055ustar00rootroot00000000000000toil-releases-3.24.0/dashboard/grafana/000077500000000000000000000000001362134276200177045ustar00rootroot00000000000000toil-releases-3.24.0/dashboard/grafana/Dockerfile000066400000000000000000000002241362134276200216740ustar00rootroot00000000000000FROM grafana/grafana EXPOSE 3000 ENV GF_AUTH_ANONYMOUS_ENABLED "true" COPY ./toil_dashboard.json /usr/share/grafana/public/dashboards/home.json toil-releases-3.24.0/dashboard/grafana/toil_dashboard.json000066400000000000000000000344731362134276200235700ustar00rootroot00000000000000{ "__inputs": [ { "name": "DS_PROMETHEUS", "label": "prometheus", "description": "", "type": "datasource", "pluginId": "prometheus", "pluginName": "Prometheus" } ], "__requires": [ { "type": "grafana", "id": "grafana", "name": "Grafana", "version": "4.1.0" }, { "type": "panel", "id": "graph", "name": "Graph", "version": "" }, { "type": "datasource", "id": "prometheus", "name": "Prometheus", "version": "1.0.0" } ], "annotations": { "list": [] }, "editable": false, "gnetId": null, "graphTooltip": 0, "hideControls": false, "id": null, "links": [], "refresh": "30s", "rows": [ { "collapse": false, "height": 279, "panels": [ { "aliasColors": {}, "bars": false, "dashLength": 10, "dashes": false, "datasource": "DS_PROMETHEUS", "fill": 1, "id": 1, "legend": { "alignAsTable": false, "avg": false, "current": false, "hideEmpty": true, "hideZero": false, "max": false, "min": false, "show": true, "total": false, "values": false }, "lines": true, "linewidth": 1, "links": [], "nullPointMode": "null", "percentage": false, "pointradius": 5, "points": false, "renderer": "flot", "seriesOverrides": [], "spaceLength": 10, "span": 6, "stack": false, "steppedLine": false, "targets": [ { "expr": "avg(irate(node_cpu{mode=\"user\",job=\"aws-node-exporter\"}[5m])) without (cpu)", "intervalFactor": 2, "legendFormat": "{{instance}}", "metric": "node", "refId": "A", "step": 10 } ], "thresholds": [], "timeFrom": null, "timeShift": null, "title": "CPU usage", "tooltip": { "shared": true, "sort": 0, "value_type": "individual" }, "type": "graph", "xaxis": { "buckets": null, "mode": "time", "name": null, "show": true, "values": [] }, "yaxes": [ { "format": "short", "label": null, "logBase": 1, "max": "1", "min": "0", "show": true }, { "format": "short", "label": null, "logBase": 1, "max": null, "min": null, "show": true } ] }, { "aliasColors": {}, "bars": false, "dashLength": 10, "dashes": false, "datasource": "DS_PROMETHEUS", "fill": 1, "id": 2, "legend": { "avg": false, "current": false, "max": false, "min": false, "show": true, "total": false, "values": false }, "lines": true, "linewidth": 1, "links": [], "nullPointMode": "null", "percentage": false, "pointradius": 5, "points": false, "renderer": "flot", "seriesOverrides": [], "spaceLength": 10, "span": 6, "stack": false, "steppedLine": false, "targets": [ { "expr": "node_memory_MemTotal{job=\"aws-node-exporter\"} - node_memory_MemFree{job=\"aws-node-exporter\"} - node_memory_Buffers{job=\"aws-node-exporter\"} - node_memory_Cached{job=\"aws-node-exporter\"}", "intervalFactor": 2, "legendFormat": "{{instance}}", "refId": "A", "step": 10 } ], "thresholds": [], "timeFrom": null, "timeShift": null, "title": "Memory usage", "tooltip": { "shared": true, "sort": 0, "value_type": "individual" }, "type": "graph", "xaxis": { "buckets": null, "mode": "time", "name": null, "show": true, "values": [] }, "yaxes": [ { "format": "bytes", "label": null, "logBase": 1, "max": null, "min": null, "show": true }, { "format": "short", "label": null, "logBase": 1, "max": null, "min": null, "show": true } ] } ], "repeat": null, "repeatIteration": null, "repeatRowId": null, "showTitle": false, "title": "Dashboard Row", "titleSize": "h6" }, { "collapse": false, "height": 202, "panels": [ { "aliasColors": {}, "bars": false, "dashLength": 10, "dashes": false, "datasource": "DS_PROMETHEUS", "fill": 1, "id": 3, "legend": { "avg": false, "current": false, "max": false, "min": false, "show": true, "total": false, "values": false }, "lines": true, "linewidth": 1, "links": [], "nullPointMode": "null", "percentage": false, "pointradius": 5, "points": false, "renderer": "flot", "seriesOverrides": [], "spaceLength": 10, "span": 6, "stack": false, "steppedLine": false, "targets": [ { "expr": "autoscaler_cur_size", "format": "time_series", "intervalFactor": 2, "legendFormat": "{{node_type}} (current)", "refId": "A", "step": 10 }, { "expr": "autoscaler_desired_size", "format": "time_series", "intervalFactor": 2, "legendFormat": "{{node_type}} (desired)", "refId": "B", "step": 10 } ], "thresholds": [], "timeFrom": null, "timeShift": null, "title": "Cluster size", "tooltip": { "shared": true, "sort": 0, "value_type": "individual" }, "type": "graph", "xaxis": { "buckets": null, "mode": "time", "name": null, "show": true, "values": [] }, "yaxes": [ { "format": "short", "label": null, "logBase": 1, "max": null, "min": null, "show": true }, { "format": "short", "label": null, "logBase": 1, "max": null, "min": null, "show": true } ] }, { "aliasColors": {}, "bars": false, "dashLength": 10, "dashes": false, "datasource": "DS_PROMETHEUS", "fill": 1, "id": 4, "legend": { "avg": false, "current": false, "max": false, "min": false, "show": false, "total": false, "values": false }, "lines": true, "linewidth": 1, "links": [], "nullPointMode": "null", "percentage": false, "pointradius": 5, "points": false, "renderer": "flot", "seriesOverrides": [], "spaceLength": 10, "span": 6, "stack": false, "steppedLine": false, "targets": [ { "expr": "autoscaler_queue_size", "intervalFactor": 2, "legendFormat": "Queue size", "refId": "A", "step": 10 } ], "thresholds": [], "timeFrom": null, "timeShift": null, "title": "Queue size", "tooltip": { "shared": true, "sort": 0, "value_type": "individual" }, "type": "graph", "xaxis": { "buckets": null, "mode": "time", "name": null, "show": true, "values": [] }, "yaxes": [ { "format": "short", "label": null, "logBase": 1, "max": null, "min": null, "show": true }, { "format": "short", "label": null, "logBase": 1, "max": null, "min": null, "show": true } ] } ], "repeat": null, "repeatIteration": null, "repeatRowId": null, "showTitle": false, "title": "Dashboard Row", "titleSize": "h6" }, { "collapse": false, "height": 208, "panels": [ { "aliasColors": {}, "bars": true, "dashLength": 10, "dashes": false, "datasource": "DS_PROMETHEUS", "fill": 1, "id": 5, "legend": { "alignAsTable": false, "avg": false, "current": false, "hideEmpty": true, "hideZero": true, "max": false, "min": false, "rightSide": false, "show": false, "total": false, "values": false }, "lines": false, "linewidth": 1, "links": [], "nullPointMode": "null as zero", "percentage": false, "pointradius": 5, "points": false, "renderer": "flot", "seriesOverrides": [], "spaceLength": 10, "span": 6, "stack": true, "steppedLine": false, "targets": [ { "expr": "sum((((issued_jobs - completed_jobs) or issued_jobs)) or (issued_jobs - completed_jobs) or issued_jobs) by (job_type)", "format": "time_series", "intervalFactor": 2, "legendFormat": "{{job_type}}", "refId": "A", "step": 10 }, { "expr": "", "format": "time_series", "intervalFactor": 2, "refId": "B" } ], "thresholds": [], "timeFrom": null, "timeShift": null, "title": "Running or queued jobs (log scale)", "tooltip": { "shared": true, "sort": 2, "value_type": "individual" }, "type": "graph", "xaxis": { "buckets": null, "mode": "time", "name": null, "show": true, "values": [] }, "yaxes": [ { "format": "short", "label": null, "logBase": 10, "max": null, "min": null, "show": true }, { "format": "short", "label": null, "logBase": 1, "max": null, "min": null, "show": true } ] }, { "aliasColors": {}, "bars": false, "dashLength": 10, "dashes": false, "datasource": "DS_PROMETHEUS", "fill": 1, "id": 6, "legend": { "avg": false, "current": false, "max": false, "min": false, "show": true, "total": false, "values": false }, "lines": true, "linewidth": 1, "links": [], "nullPointMode": "null", "percentage": false, "pointradius": 5, "points": false, "renderer": "flot", "seriesOverrides": [], "spaceLength": 10, "span": 6, "stack": false, "steppedLine": false, "targets": [ { "expr": "failed_jobs", "intervalFactor": 2, "legendFormat": "{{job_type}}", "refId": "A", "step": 10 } ], "thresholds": [], "timeFrom": null, "timeShift": null, "title": "Failed jobs", "tooltip": { "shared": true, "sort": 0, "value_type": "individual" }, "type": "graph", "xaxis": { "buckets": null, "mode": "time", "name": null, "show": true, "values": [] }, "yaxes": [ { "format": "short", "label": null, "logBase": 1, "max": null, "min": null, "show": true }, { "format": "short", "label": null, "logBase": 1, "max": null, "min": null, "show": true } ] } ], "repeat": null, "repeatIteration": null, "repeatRowId": null, "showTitle": false, "title": "Dashboard Row", "titleSize": "h6" } ], "schemaVersion": 14, "style": "dark", "tags": [], "templating": { "list": [] }, "time": { "from": "now-1h", "to": "now" }, "timepicker": { "refresh_intervals": [ "5s", "10s", "30s", "1m", "5m", "15m", "30m", "1h", "2h", "1d" ], "time_options": [ "5m", "15m", "1h", "6h", "12h", "24h", "2d", "7d", "30d" ] }, "timezone": "browser", "title": "toil stats", "version": 9 } toil-releases-3.24.0/dashboard/mtail/000077500000000000000000000000001362134276200174135ustar00rootroot00000000000000toil-releases-3.24.0/dashboard/mtail/Dockerfile000066400000000000000000000001771362134276200214120ustar00rootroot00000000000000FROM sscaling/mtail EXPOSE 3903 COPY ./toil.mtail /home/toil.mtail ENTRYPOINT ["mtail", "-progs", "/home/", "-logfds", "0"] toil-releases-3.24.0/dashboard/mtail/toil.mtail000066400000000000000000000016611362134276200214160ustar00rootroot00000000000000gauge autoscaler_cur_size by node_type gauge autoscaler_desired_size by node_type gauge autoscaler_queue_size counter total_issued_jobs counter issued_jobs by job_type counter total_completed_jobs counter completed_jobs by job_type counter total_failed_jobs counter failed_jobs by job_type counter missing_jobs /desired_size '(?P\S+)' (?P\d+)/ { autoscaler_desired_size[$node_type] = $desired_size } /current_size '(?P\S+)' (?P\d+)/ { autoscaler_cur_size[$node_type] = $cur_size } /queue_size (?P\d+)/ { autoscaler_queue_size = $queue_size } /issued_job '(?P\S+)'/ { issued_jobs[$job_type]++ total_issued_jobs++ } /missing_job/ { missing_jobs++ } /failed_job '(?P\S+)'/ { total_failed_jobs++ failed_jobs[$job_type]++ } /completed_job '(?P\S+)'/ { completed_jobs[$job_type]++ total_completed_jobs++ } toil-releases-3.24.0/dashboard/prometheus/000077500000000000000000000000001362134276200205005ustar00rootroot00000000000000toil-releases-3.24.0/dashboard/prometheus/Dockerfile000066400000000000000000000002341362134276200224710ustar00rootroot00000000000000FROM prom/prometheus:v2.0.0 COPY ./prometheus.yml /etc/prometheus/prometheus.yml COPY ./run.sh /opt/run.sh EXPOSE 9090 9090 ENTRYPOINT [ "/opt/run.sh" ] toil-releases-3.24.0/dashboard/prometheus/prometheus.yml000066400000000000000000000032041362134276200234150ustar00rootroot00000000000000# my global config global: scrape_interval: 15s # Set the scrape interval to every 15 seconds. Default is every 1 minute. evaluation_interval: 15s # Evaluate rules every 15 seconds. The default is every 1 minute. # scrape_timeout is set to the global default (10s). # Attach these labels to any time series or alerts when communicating with # external systems (federation, remote storage, Alertmanager). external_labels: monitor: 'codelab-monitor' # Load rules once and periodically evaluate them according to the global 'evaluation_interval'. rule_files: # - "first.rules" # - "second.rules" # A scrape configuration containing exactly one endpoint to scrape: # Here it's Prometheus itself. scrape_configs: # The job name is added as a label `job=` to any timeseries scraped from this config. - job_name: 'prometheus' # metrics_path defaults to '/metrics' # scheme defaults to 'http'. static_configs: - targets: ['localhost:9090'] - job_name: 'toil' static_configs: - targets: ['localhost:3903'] - job_name: 'node' static_configs: - targets: ['localhost:9100'] - job_name: 'aws-node-exporter' ec2_sd_configs: - refresh_interval: 15s region: ZONE_NAME port: 9100 relabel_configs: - source_labels: ['__meta_ec2_tag_Name'] action: keep regex: CLUSTER_NAME - source_labels: ['__meta_ec2_instance_state'] action: drop regex: '.*(stopped|terminated).*' toil-releases-3.24.0/dashboard/prometheus/run.sh000077500000000000000000000007021362134276200216420ustar00rootroot00000000000000#!/bin/sh #Set cluster name sed -i "s/^\([[:blank:]]*\) regex: CLUSTER_NAME/\1 regex: \'${1}\'/g" /etc/prometheus/prometheus.yml sed -i "s/^\([[:blank:]]*\) region: ZONE_NAME/\1 region: \'${2}\'/g" /etc/prometheus/prometheus.yml exec /bin/prometheus --config.file=/etc/prometheus/prometheus.yml --storage.tsdb.path=/prometheus --web.console.libraries=/usr/share/prometheus/console_libraries --web.console.templates=/usr/share/prometheus/consoles toil-releases-3.24.0/docker/000077500000000000000000000000001362134276200156255ustar00rootroot00000000000000toil-releases-3.24.0/docker/Dockerfile.py000066400000000000000000000150271362134276200202530ustar00rootroot00000000000000# Copyright (C) 2015-2016 Regents of the University of California # # 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. from __future__ import print_function import os import sys import textwrap applianceSelf = os.environ['TOIL_APPLIANCE_SELF'] sdistName = os.environ['_TOIL_SDIST_NAME'] # Make sure to install packages into the pip for the version of Python we are # building for. pip = 'python{}.{} -m pip'.format(sys.version_info[0], sys.version_info[1]) dependencies = ' '.join(['libffi-dev', # For client side encryption for extras with PyNACL 'python3.6', 'python3.6-dev', 'python-dev', # For installing Python packages with native code 'python-pip', # Bootstrap pip, but needs upgrading, see below 'python3-pip', 'libcurl4-openssl-dev', 'libssl-dev', 'wget', 'curl', 'openssh-server', 'mesos=1.0.1-2.0.94.ubuntu1604', "nodejs", # CWL support for javascript expressions 'rsync', 'screen', 'build-essential', # We need a build environment to build Singularity 3. 'uuid-dev', 'libgpgme11-dev', 'libseccomp-dev', 'pkg-config', 'squashfs-tools', 'cryptsetup', 'git']) def heredoc(s): s = textwrap.dedent(s).format(**globals()) return s[1:] if s.startswith('\n') else s motd = heredoc(''' This is the Toil appliance. You can run your Toil script directly on the appliance. Run toil .py --help to see all options for running your workflow. For more information see http://toil.readthedocs.io/en/latest/ Copyright (C) 2015-2020 Regents of the University of California Version: {applianceSelf} ''') # Prepare motd to be echoed in the Dockerfile using a RUN statement that uses bash's print motd = ''.join(l + '\\n\\\n' for l in motd.splitlines()) print(heredoc(''' FROM ubuntu:16.04 RUN apt-get -y update --fix-missing && apt-get -y upgrade && apt-get -y install apt-transport-https ca-certificates software-properties-common && apt-get clean && rm -rf /var/lib/apt/lists/* RUN echo "deb http://repos.mesosphere.io/ubuntu/ xenial main" \ > /etc/apt/sources.list.d/mesosphere.list \ && apt-key adv --keyserver keyserver.ubuntu.com --recv E56151BF \ && echo "deb http://deb.nodesource.com/node_6.x xenial main" \ > /etc/apt/sources.list.d/nodesource.list \ && apt-key adv --keyserver keyserver.ubuntu.com --recv 68576280 RUN add-apt-repository -y ppa:deadsnakes/ppa RUN apt-get -y update --fix-missing && \ DEBIAN_FRONTEND=noninteractive apt-get -y upgrade && \ DEBIAN_FRONTEND=noninteractive apt-get -y install {dependencies} && \ apt-get clean && \ rm -rf /var/lib/apt/lists/* RUN wget -q https://dl.google.com/go/go1.13.3.linux-amd64.tar.gz && \ tar xf go1.13.3.linux-amd64.tar.gz && \ rm go1.13.3.linux-amd64.tar.gz && \ mv go/bin/* /usr/bin/ && \ mv go /usr/local/ RUN mkdir -p $(go env GOPATH)/src/github.com/sylabs && \ cd $(go env GOPATH)/src/github.com/sylabs && \ git clone https://github.com/sylabs/singularity.git && \ cd singularity && \ git checkout v3.4.2 && \ ./mconfig && \ cd ./builddir && \ make -j4 && \ make install RUN mkdir /root/.ssh && \ chmod 700 /root/.ssh ADD waitForKey.sh /usr/bin/waitForKey.sh ADD customDockerInit.sh /usr/bin/customDockerInit.sh RUN chmod 777 /usr/bin/waitForKey.sh && chmod 777 /usr/bin/customDockerInit.sh # The stock pip is too old and can't install from sdist with extras RUN {pip} install --upgrade pip==9.0.1 # Default setuptools is too old RUN {pip} install --upgrade setuptools==36.5.0 # Include virtualenv, as it is still the recommended way to deploy pipelines RUN {pip} install --upgrade virtualenv==15.0.3 # Install s3am (--never-download prevents silent upgrades to pip, wheel and setuptools) RUN virtualenv --python python3.6 --never-download /home/s3am \ && /home/s3am/bin/pip install s3am==2.0 \ && ln -s /home/s3am/bin/s3am /usr/local/bin/ # Install statically linked version of docker client RUN curl https://download.docker.com/linux/static/stable/x86_64/docker-18.06.1-ce.tgz \ | tar -xvzf - --transform='s,[^/]*/,,g' -C /usr/local/bin/ \ && chmod u+x /usr/local/bin/docker # Fix for Mesos interface dependency missing on ubuntu RUN {pip} install protobuf==3.0.0 # Fix for https://issues.apache.org/jira/browse/MESOS-3793 ENV MESOS_LAUNCHER=posix # Fix for `screen` (https://github.com/BD2KGenomics/toil/pull/1386#issuecomment-267424561) ENV TERM linux # Run bash instead of sh inside of screen ENV SHELL /bin/bash RUN echo "defshell -bash" > ~/.screenrc # An appliance may need to start more appliances, e.g. when the leader appliance launches the # worker appliance on a worker node. To support this, we embed a self-reference into the image: ENV TOIL_APPLIANCE_SELF {applianceSelf} RUN mkdir /var/lib/toil ENV TOIL_WORKDIR /var/lib/toil # This component changes most frequently and keeping it last maximizes Docker cache hits. COPY {sdistName} . RUN {pip} install {sdistName}[all] RUN rm {sdistName} # We intentionally inherit the default ENTRYPOINT and CMD from the base image, to the effect # that the running appliance just gives you a shell. To start the Mesos master or slave # daemons, the user # should override the entrypoint via --entrypoint. RUN echo '[ ! -z "$TERM" -a -r /etc/motd ] && cat /etc/motd' >> /etc/bash.bashrc \ && printf '{motd}' > /etc/motd ''')) toil-releases-3.24.0/docker/customDockerInit.sh000066400000000000000000000011231362134276200214440ustar00rootroot00000000000000#!/usr/bin/env bash # Runs custom initialization before running the main docker service. # The first argument is a single string containing the custom init command. # The second argument is the docker service binary (e.g. mesos-slave). # The rest of the arguments are passed into the service. # All arguments are required! # # Example usage: # $ customDockerInit.sh 'echo "hello world"' mesos-slave --log_dir=/var/lib/mesos ... CUSTOM_INIT_COMMAND="${1}" SERVICE_COMMAND="${2}" SERVICE_COMMAND_ARGS="${@:3}" bash -c "${CUSTOM_INIT_COMMAND}" eval "${SERVICE_COMMAND}" "${SERVICE_COMMAND_ARGS}" toil-releases-3.24.0/docker/waitForKey.sh000066400000000000000000000001201362134276200202360ustar00rootroot00000000000000#!/usr/bin/env bash while [ ! -f "$1" ]; do sleep 2; done; mesos-slave "${@:2}" toil-releases-3.24.0/docs/000077500000000000000000000000001362134276200153065ustar00rootroot00000000000000toil-releases-3.24.0/docs/Makefile000066400000000000000000000163511362134276200167540ustar00rootroot00000000000000# Makefile for Sphinx documentation # # You can set these variables from the command line. SPHINXOPTS = SPHINXBUILD = sphinx-build PAPER = BUILDDIR = _build # User-friendly check for sphinx-build ifeq ($(shell which $(SPHINXBUILD) >/dev/null 2>&1; echo $$?), 1) $(error The '$(SPHINXBUILD)' command was not found. Make sure you have Sphinx installed, then set the SPHINXBUILD environment variable to point to the full path of the '$(SPHINXBUILD)' executable. Alternatively you can add the directory with the executable to your PATH. If you don't have Sphinx installed, grab it from http://sphinx-doc.org/) endif # Internal variables. PAPEROPT_a4 = -D latex_paper_size=a4 PAPEROPT_letter = -D latex_paper_size=letter ALLSPHINXOPTS = -d $(BUILDDIR)/doctrees $(PAPEROPT_$(PAPER)) $(SPHINXOPTS) . # the i18n builder cannot share the environment and doctrees with the others I18NSPHINXOPTS = $(PAPEROPT_$(PAPER)) $(SPHINXOPTS) . .PHONY: help clean html dirhtml singlehtml pickle json htmlhelp qthelp devhelp epub latex latexpdf text man changes linkcheck doctest coverage gettext help: @echo "Please use \`make ' where is one of" @echo " html to make standalone HTML files" @echo " dirhtml to make HTML files named index.html in directories" @echo " singlehtml to make a single large HTML file" @echo " pickle to make pickle files" @echo " json to make JSON files" @echo " htmlhelp to make HTML files and a HTML help project" @echo " qthelp to make HTML files and a qthelp project" @echo " applehelp to make an Apple Help Book" @echo " devhelp to make HTML files and a Devhelp project" @echo " epub to make an epub" @echo " latex to make LaTeX files, you can set PAPER=a4 or PAPER=letter" @echo " latexpdf to make LaTeX files and run them through pdflatex" @echo " latexpdfja to make LaTeX files and run them through platex/dvipdfmx" @echo " text to make text files" @echo " man to make manual pages" @echo " texinfo to make Texinfo files" @echo " info to make Texinfo files and run them through makeinfo" @echo " gettext to make PO message catalogs" @echo " changes to make an overview of all changed/added/deprecated items" @echo " xml to make Docutils-native XML files" @echo " pseudoxml to make pseudoxml-XML files for display purposes" @echo " linkcheck to check all external links for integrity" @echo " doctest to run all doctests embedded in the documentation (if enabled)" @echo " coverage to run coverage check of the documentation (if enabled)" clean: rm -rf $(BUILDDIR)/* html: $(SPHINXBUILD) -b html $(ALLSPHINXOPTS) $(BUILDDIR)/html @echo @echo "Build finished. The HTML pages are in $(BUILDDIR)/html." dirhtml: $(SPHINXBUILD) -b dirhtml $(ALLSPHINXOPTS) $(BUILDDIR)/dirhtml @echo @echo "Build finished. The HTML pages are in $(BUILDDIR)/dirhtml." singlehtml: $(SPHINXBUILD) -b singlehtml $(ALLSPHINXOPTS) $(BUILDDIR)/singlehtml @echo @echo "Build finished. The HTML page is in $(BUILDDIR)/singlehtml." pickle: $(SPHINXBUILD) -b pickle $(ALLSPHINXOPTS) $(BUILDDIR)/pickle @echo @echo "Build finished; now you can process the pickle files." json: $(SPHINXBUILD) -b json $(ALLSPHINXOPTS) $(BUILDDIR)/json @echo @echo "Build finished; now you can process the JSON files." htmlhelp: $(SPHINXBUILD) -b htmlhelp $(ALLSPHINXOPTS) $(BUILDDIR)/htmlhelp @echo @echo "Build finished; now you can run HTML Help Workshop with the" \ ".hhp project file in $(BUILDDIR)/htmlhelp." qthelp: $(SPHINXBUILD) -b qthelp $(ALLSPHINXOPTS) $(BUILDDIR)/qthelp @echo @echo "Build finished; now you can run "qcollectiongenerator" with the" \ ".qhcp project file in $(BUILDDIR)/qthelp, like this:" @echo "# qcollectiongenerator $(BUILDDIR)/qthelp/Toil.qhcp" @echo "To view the help file:" @echo "# assistant -collectionFile $(BUILDDIR)/qthelp/Toil.qhc" applehelp: $(SPHINXBUILD) -b applehelp $(ALLSPHINXOPTS) $(BUILDDIR)/applehelp @echo @echo "Build finished. The help book is in $(BUILDDIR)/applehelp." @echo "N.B. You won't be able to view it unless you put it in" \ "~/Library/Documentation/Help or install it in your application" \ "bundle." devhelp: $(SPHINXBUILD) -b devhelp $(ALLSPHINXOPTS) $(BUILDDIR)/devhelp @echo @echo "Build finished." @echo "To view the help file:" @echo "# mkdir -p $$HOME/.local/share/devhelp/Toil" @echo "# ln -s $(BUILDDIR)/devhelp $$HOME/.local/share/devhelp/Toil" @echo "# devhelp" epub: $(SPHINXBUILD) -b epub $(ALLSPHINXOPTS) $(BUILDDIR)/epub @echo @echo "Build finished. The epub file is in $(BUILDDIR)/epub." latex: $(SPHINXBUILD) -b latex $(ALLSPHINXOPTS) $(BUILDDIR)/latex @echo @echo "Build finished; the LaTeX files are in $(BUILDDIR)/latex." @echo "Run \`make' in that directory to run these through (pdf)latex" \ "(use \`make latexpdf' here to do that automatically)." latexpdf: $(SPHINXBUILD) -b latex $(ALLSPHINXOPTS) $(BUILDDIR)/latex @echo "Running LaTeX files through pdflatex..." $(MAKE) -C $(BUILDDIR)/latex all-pdf @echo "pdflatex finished; the PDF files are in $(BUILDDIR)/latex." latexpdfja: $(SPHINXBUILD) -b latex $(ALLSPHINXOPTS) $(BUILDDIR)/latex @echo "Running LaTeX files through platex and dvipdfmx..." $(MAKE) -C $(BUILDDIR)/latex all-pdf-ja @echo "pdflatex finished; the PDF files are in $(BUILDDIR)/latex." text: $(SPHINXBUILD) -b text $(ALLSPHINXOPTS) $(BUILDDIR)/text @echo @echo "Build finished. The text files are in $(BUILDDIR)/text." man: $(SPHINXBUILD) -b man $(ALLSPHINXOPTS) $(BUILDDIR)/man @echo @echo "Build finished. The manual pages are in $(BUILDDIR)/man." texinfo: $(SPHINXBUILD) -b texinfo $(ALLSPHINXOPTS) $(BUILDDIR)/texinfo @echo @echo "Build finished. The Texinfo files are in $(BUILDDIR)/texinfo." @echo "Run \`make' in that directory to run these through makeinfo" \ "(use \`make info' here to do that automatically)." info: $(SPHINXBUILD) -b texinfo $(ALLSPHINXOPTS) $(BUILDDIR)/texinfo @echo "Running Texinfo files through makeinfo..." make -C $(BUILDDIR)/texinfo info @echo "makeinfo finished; the Info files are in $(BUILDDIR)/texinfo." gettext: $(SPHINXBUILD) -b gettext $(I18NSPHINXOPTS) $(BUILDDIR)/locale @echo @echo "Build finished. The message catalogs are in $(BUILDDIR)/locale." changes: $(SPHINXBUILD) -b changes $(ALLSPHINXOPTS) $(BUILDDIR)/changes @echo @echo "The overview file is in $(BUILDDIR)/changes." linkcheck: $(SPHINXBUILD) -b linkcheck $(ALLSPHINXOPTS) $(BUILDDIR)/linkcheck @echo @echo "Link check complete; look for any errors in the above output " \ "or in $(BUILDDIR)/linkcheck/output.txt." doctest: $(SPHINXBUILD) -b doctest $(ALLSPHINXOPTS) $(BUILDDIR)/doctest @echo "Testing of doctests in the sources finished, look at the " \ "results in $(BUILDDIR)/doctest/output.txt." coverage: $(SPHINXBUILD) -b coverage $(ALLSPHINXOPTS) $(BUILDDIR)/coverage @echo "Testing of coverage in the sources finished, look at the " \ "results in $(BUILDDIR)/coverage/python.txt." xml: $(SPHINXBUILD) -b xml $(ALLSPHINXOPTS) $(BUILDDIR)/xml @echo @echo "Build finished. The XML files are in $(BUILDDIR)/xml." pseudoxml: $(SPHINXBUILD) -b pseudoxml $(ALLSPHINXOPTS) $(BUILDDIR)/pseudoxml @echo @echo "Build finished. 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Ê46d¥½ç!üúŸSj–›î&“rWÞ/éïîe/Ù{òp­5×f\±¡gÐкÂý°Ô²,Í cgÑšw5, 2ý‹ö,k…Þ7XhY.f(C1Wù/ã ù.‹.…ü”ò(×ö&¾¥Óæé>Cœ¢­9³Ùn…u‰U¥GÀqÚµ‰Tr¤ª÷Øà­û=™rÆ…ŸCBë öÃRȳ4-ŸCNæ¸hY—ì_±c\-ÖEüEÊ,oä¿Œ/äº,ºòQ?*gý§æÍó| ••[{Ç)Ò^Ã÷mA›RY,!ÈÌqˆà8À|0p‘˜ã³jÈÚŒ2ÁÒŒÇᶡ¸qlu6áîóõ¼pÊx8#Cõ%¸qn¬phÚü‡¸’6ÿ#j ›Q}8a·øÄ™ú’Ü8·WÿÄ¿ÿÙtoil-releases-3.24.0/docs/_static/shortcut.png000066400000000000000000000004261362134276200213170ustar00rootroot00000000000000‰PNG  IHDR(-S3PLTEH}H}H}H}H}H}H}H}H}H}H}H}H}H}H}H}—Y¨tRNS`¿ÿ Ïï@Pߟ¯0pjÉ=IDATx$Ž…1i ¼ï¿ìWŃs¾¸¡ŠœU3Cã·û}YßOª¶kõ`¯·InFƒ'šÁ]¢ƒó7ç!’{,àÜ‚ä6úÃÉK¾íØ_ÓtÑþJ™§ÛEïIcœ¥5ªE ®×çg—ô{W¶=£_îÏžÃð>à¨ÀqRÓIEND®B`‚toil-releases-3.24.0/docs/appendices/000077500000000000000000000000001362134276200174215ustar00rootroot00000000000000toil-releases-3.24.0/docs/appendices/architecture.rst000066400000000000000000000270671362134276200226510ustar00rootroot00000000000000Toil Architecture ***************** The following diagram layouts out the software architecture of Toil. .. figure:: toil_architecture.jpg :align: center :alt: Toil's architecture is composed of the leader, the job store, the worker processes, the batch system, the node provisioner, and the stats and logging monitor. :figclass: align-center Figure 1: The basic components of Toil's architecture. These components are described below: * the leader: The leader is responsible for deciding which jobs should be run. To do this it traverses the job graph. Currently this is a single threaded process, but we make aggressive steps to prevent it becoming a bottleneck (see `Read-only Leader`_ described below). * the job-store: Handles all files shared between the components. Files in the job-store are the means by which the state of the workflow is maintained. Each job is backed by a file in the job store, and atomic updates to this state are used to ensure the workflow can always be resumed upon failure. The job-store can also store all user files, allowing them to be shared between jobs. The job-store is defined by the :class:`~toil.jobStores.abstractJobStore.AbstractJobStore` class. Multiple implementations of this class allow Toil to support different back-end file stores, e.g.: S3, network file systems, Google file store, etc. * workers: The workers are temporary processes responsible for running jobs, one at a time per worker. Each worker process is invoked with a job argument that it is responsible for running. The worker monitors this job and reports back success or failure to the leader by editing the job's state in the file-store. If the job defines successor jobs the worker may choose to immediately run them (see `Job Chaining`_ below). * the batch-system: Responsible for scheduling the jobs given to it by the leader, creating a worker command for each job. The batch-system is defined by the :class:`~toil.batchSystems.abstractBatchSystem.AbstractBatchSystem` class. Toil uses multiple existing batch systems to schedule jobs, including Apache Mesos, GridEngine and a multi-process single node implementation that allows workflows to be run without any of these frameworks. Toil can therefore fairly easily be made to run a workflow using an existing cluster. * the node provisioner: Creates worker nodes in which the batch system schedules workers. It is defined by the :class:`~toil.provisioners.abstractProvisioner.AbstractProvisioner` class. * the statistics and logging monitor: Monitors logging and statistics produced by the workers and reports them. Uses the job-store to gather this information. Optimizations ------------- Toil implements lots of optimizations designed for scalability. Here we detail some of the key optimizations. Read-only leader ~~~~~~~~~~~~~~~~ The leader process is currently implemented as a single thread. Most of the leader's tasks revolve around processing the state of jobs, each stored as a file within the job-store. To minimise the load on this thread, each worker does as much work as possible to manage the state of the job it is running. As a result, with a couple of minor exceptions, the leader process never needs to write or update the state of a job within the job-store. For example, when a job is complete and has no further successors the responsible worker deletes the job from the job-store, marking it complete. The leader then only has to check for the existence of the file when it receives a signal from the batch-system to know that the job is complete. This off-loading of state management is orthogonal to future parallelization of the leader. Job chaining ~~~~~~~~~~~~ The scheduling of successor jobs is partially managed by the worker, reducing the number of individual jobs the leader needs to process. Currently this is very simple: if the there is a single next successor job to run and its resources fit within the resources of the current job and closely match the resources of the current job then the job is run immediately on the worker without returning to the leader. Further extensions of this strategy are possible, but for many workflows which define a series of serial successors (e.g. map sequencing reads, post-process mapped reads, etc.) this pattern is very effective at reducing leader workload. Preemptable node support ~~~~~~~~~~~~~~~~~~~~~~~~ Critical to running at large-scale is dealing with intermittent node failures. Toil is therefore designed to always be resumable providing the job-store does not become corrupt. This robustness allows Toil to run on preemptible nodes, which are only available when others are not willing to pay more to use them. Designing workflows that divide into many short individual jobs that can use preemptable nodes allows for workflows to be efficiently scheduled and executed. Caching ~~~~~~~ Running bioinformatic pipelines often require the passing of large datasets between jobs. Toil caches the results from jobs such that child jobs running on the same node can directly use the same file objects, thereby eliminating the need for an intermediary transfer to the job store. Caching also reduces the burden on the local disks, because multiple jobs can share a single file. The resulting drop in I/O allows pipelines to run faster, and, by the sharing of files, allows users to run more jobs in parallel by reducing overall disk requirements. To demonstrate the efficiency of caching, we ran an experimental internal pipeline on 3 samples from the TCGA Lung Squamous Carcinoma (LUSC) dataset. The pipeline takes the tumor and normal exome fastqs, and the tumor rna fastq and input, and predicts MHC presented neoepitopes in the patient that are potential targets for T-cell based immunotherapies. The pipeline was run individually on the samples on c3.8xlarge machines on AWS (60GB RAM,600GB SSD storage, 32 cores). The pipeline aligns the data to hg19-based references, predicts MHC haplotypes using PHLAT, calls mutations using 2 callers (MuTect and RADIA) and annotates them using SnpEff, then predicts MHC:peptide binding using the IEDB suite of tools before running an in-house rank boosting algorithm on the final calls. To optimize time taken, The pipeline is written such that mutations are called on a per-chromosome basis from the whole-exome bams and are merged into a complete vcf. Running mutect in parallel on whole exome bams requires each mutect job to download the complete Tumor and Normal Bams to their working directories -- An operation that quickly fills the disk and limits the parallelizability of jobs. The script was run in Toil, with and without caching, and Figure 2 shows that the workflow finishes faster in the cached case while using less disk on average than the uncached run. We believe that benefits of caching arising from file transfers will be much higher on magnetic disk-based storage systems as compared to the SSD systems we tested this on. .. figure:: caching_benefits.png :width: 700px :align: center :height: 1000px :alt: Graph outlining the efficiency gain from caching. :figclass: align-center Figure 2: Efficiency gain from caching. The lower half of each plot describes the disk used by the pipeline recorded every 10 minutes over the duration of the pipeline, and the upper half shows the corresponding stage of the pipeline that is being processed. Since jobs requesting the same file shared the same inode, the effective load on the disk is considerably lower than in the uncached case where every job downloads a personal copy of every file it needs. We see that in all cases, the uncached run uses almost 300-400GB more that the cached run in the resource heavy mutation calling step. We also see a benefit in terms of wall time for each stage since we eliminate the time taken for file transfers. Toil support for Common Workflow Language ----------------------------------------- The CWL document and input document are loaded using the 'cwltool.load_tool' module. This performs normalization and URI expansion (for example, relative file references are turned into absolute file URIs), validates the document against the CWL schema, initializes Python objects corresponding to major document elements (command line tools, workflows, workflow steps), and performs static type checking that sources and sinks have compatible types. Input files referenced by the CWL document and input document are imported into the Toil file store. CWL documents may use any URI scheme supported by Toil file store, including local files and object storage. The 'location' field of File references are updated to reflect the import token returned by the Toil file store. For directory inputs, the directory listing is stored in Directory object. Each individual files is imported into Toil file store. An initial workflow Job is created from the toplevel CWL document. Then, control passes to the Toil engine which schedules the initial workflow job to run. When the toplevel workflow job runs, it traverses the CWL workflow and creates a toil job for each step. The dependency graph is expressed by making downstream jobs children of upstream jobs, and initializing the child jobs with an input object containing the promises of output from upstream jobs. Because Toil jobs have a single output, but CWL permits steps to have multiple output parameters that may feed into multiple other steps, the input to a CWLJob is expressed with an "indirect dictionary". This is a dictionary of input parameters, where each entry value is a tuple of a promise and a promise key. When the job runs, the indirect dictionary is turned into a concrete input object by resolving each promise into its actual value (which is always a dict), and then looking up the promise key to get the actual value for the the input parameter. If a workflow step specifies a scatter, then a scatter job is created and connected into the workflow graph as described above. When the scatter step runs, it creates child jobs for each parameterizations of the scatter. A gather job is added as a follow-on to gather the outputs into arrays. When running a command line tool, it first creates output and temporary directories under the Toil local temp dir. It runs the command line tool using the single_job_executor from CWLTool, providing a Toil-specific constructor for filesystem access, and overriding the default PathMapper to use ToilPathMapper. The ToilPathMapper keeps track of a file's symbolic identifier (the Toil FileID), its local path on the host (the value returned by readGlobalFile) and the the location of the file inside the Docker container. After executing single_job_executor from CWLTool, it gets back the output object and status. If the underlying job failed, raise an exception. Files from the output object are added to the file store using writeGlobalFile and the 'location' field of File references are updated to reflect the token returned by the Toil file store. When the workflow completes, it returns an indirect dictionary linking to the outputs of the job steps that contribute to the final output. This is the value returned by toil.start() or toil.restart(). This is resolved to get the final output object. The files in this object are exported from the file store to 'outdir' on the host file system, and the 'location' field of File references are updated to reflect the final exported location of the output files. toil-releases-3.24.0/docs/appendices/aws_min_permissions.rst000066400000000000000000000013421362134276200242430ustar00rootroot00000000000000.. _minAwsPermissions: Minimum AWS IAM permissions --------------------------- Toil requires at least the following permissions in an IAM role to operate on a cluster. These are added by default when launching a cluster. However, ensure that they are present if creating a custom IAM role when :ref:`launching a cluster ` with the ``--awsEc2ProfileArn`` parameter. :: { "Version": "2012-10-17", "Statement": [ { "Effect": "Allow", "Action": [ "ec2:*", "s3:*", "sdb:*", "iam:PassRole" ], "Resource": "*" } ] } toil-releases-3.24.0/docs/appendices/caching_benefits.png000066400000000000000000002236401362134276200234110ustar00rootroot00000000000000‰PNG  IHDR@$I¸…'gIDATxìׄ@€á°—@àTE(5·pÇÕ¢àûMfö/n à © ©H@*R €T¤ ©H@*R R €T¤çy¾rŽãˆeYªª†!nÒoMÓÌó9Ó4]VeãøðãåtZžNü5Ú¶­®ë®ëö}_ëºR€ï‹¼ÈiÛ6Mû¾/ËòÍž@¬ÅQßF½„A’H,*¡ JH $ =P‰T"!ˆP@@  (bï(ö>_‹p~`ÿµMàž]Q_a"‘¸\.È[íL&c4‘ëtº@ 0ÝÙ`0`Úï÷•ºÝ®ÕjŻݾZ­>„ÚƒÖà×ëõ›úC©T« O6›m6›½F£ÑÈçóI’$Ëòt:UˆˆˆUˆˆn·Ûߧd2)B<ýÄ&ûñx¸Ýn„¡P¨Ùl†Ãa\§Óé×·yÔüt8õz½P(üy:ê;Žð„¡h9’$ùýþv»m6›±Yÿjz½´Z­oF“ÉI$A©T*x î“ü‹Åãñ Ò8Nô“ÿÇ DDĪ@DD½^O”„ŸŸü‘äóyµTÄb±\.‡ž0ŸÏ1 ƒêâáp˜J¥‹…šx½^“ÉF±r»Ý*oN§êÄf³Áµ,Ëz½þ~¿k†Ê›ý~/Š"NßÎΊB• B!\K…ååe ÍÄÖ××I¥R)bN þµá`áw™‡9‚ ½§¿¿¿Ñh W*•ïJ¥CH§Ó===÷÷÷ìÝ;Šõzý» Ò5<<<44D€ß€moo›=RÀ÷ÐLEë:lll°:5C¨ì@!„J!„pE¥Âáá! 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…"JB D*’R€JŠ+€d¡¤T»‡aì¿X@¸|îÌÔ{Ü3ݸ¿Z­Þïw¥þx<F8f;Ëåò­*œÏg“É´ÛíþS8Ô‚3 …B•Jåv»)u&”úý¾úE“É„Ðl6§Ó)«F£| sP¥R‰ý²k.½^/å~&Á¬Vëjµúý ‚ ˆ*‚ ˆ*0€De½^“c±M|"‘‡Á`Ðápx½ÞZ­Öjµ4Íb±àžëõJ«£Ñ¨\.ët:Ôâ­*är¹__¡ƒÿGèøÀx< dzôçó©¬Äh4b,óùªC@¨X“Éd‡uAØ uÎP}„Ã(‚ ¢ ‚ ÂÇ©‚Çãáwòf³¡^¯×É€?äóy¥“Öjµ—Ë… ív[àåýwUøñ Zö¿Uát:e³Ùý~O†ív«¶ò¬D¯×«oÜý~*•"‹Eü5“Çãö, ãø¼W•("ˆ ¥€(%€„‚£B@DH(ª €¢H 0¼ù±ÍRÓñ\oàÅú#û¬sî>« ö·¿µö% øføöíÛîî® h’ºº:€Ga¢1`Ë¿R*hØ0ç{©ðGE*œ*Ƹ½½uiÑÿs©@½”o­­­e|rrÂë(c0@h0ƒßŽ$I’” I’$)H‚÷•ýÆeÛ~ttÔ`||¼³³óÏ™œœôØõõõg©055uû‘×××Ͻ ßVüóóóì…˜J&^dPPçCÃȼ¥¥Åfüôô´ùbAìììø YqÔ5mmm½/%R­T)¸þ‹÷R¡­­íïÌÍÍ©ÀÐhllŒ¢#HÌÝŸKåO_ZZ’ÆÀÀ€ÿ]$ØÞÞæ¥üH’$I©$I’ü†R¡X!bK~vvÖ]5úýýý}äþþþz,ôÍfq<22¢j_Ò{©  ß ¼ UOeüððÀë°ûÎIèîî~yyq·¾¾~eeE&ÁÁÁƒf(•Hx~~®” ÞNxÔÒ«°¶¶Æˆ9!“ cx___H2&âűñ$Å%EGßÛÛkjj ÿák$I’R!I’$¥W!ºb9«ø^ù* _ Z¢U Ekòáá¡7jü-™ôôôÄG,¬‹É ëWÑN ÞÝÝ577onnùàññq´8KIæš¡ÅÏÏÏK\F¥TX^^ªQ*(=*sFK´A%g-àñuYŸ¥‚n “7år}}àQˆU.I íÎ?’$IR*$I’$_Q*8ûÿû÷ï~¤ÌI>–¼ªü‡‡‡+Ûš'&&N>áu!NOO½B‹B©²wi}_21fX[[â[vs ĵPkS–=@!ÈÄ£æìí핉#›8ÜÚ yå׬Ôãtssc^)ö÷÷5Jsvuu9ËÈ7é333Œ F‡[Ž[5ÜÞÞÞåVé*h¹Ölí)újaaÁW…:¨x2I’$¥B’$Iò•¤BÔÉ´··+Ù×y<66öøø(XK[3lÇT€ ¹ìèèÐrà¯SYK&Ž R_ÔÐÐà]%XVêÖÓz ø ôÃêêj8 Ž.5¿¸ž‡h;–›!©‚{P)žžžÄ5I×"Ê/+rÌ©åàêêªÄÍ@˜Jœ„`ƒTJ…ËËK‡½ÊÓcTG‘F¯(ÒI’$)’$I’/LÙ¶ÿÿóø™Sý'¢Å-BÄ "\ˆØŒlçó:â2Œ3š*±šwø©AíÐ` of a workflow that is packaged as a setuptools distribution. Toil can be easily deployed to a remote host. First, assuming you've followed our :ref:`prepareAWS` section to install Toil and use it to create a remote leader node on (in this example) AWS, you can now log into this into using :ref:`sshCluster` and once on the remote host, create and activate a virtualenv (noting to make sure to use the ``--system-site-packages`` option!):: $ virtualenv --system-site-packages venv $ . venv/bin/activate Note the ``--system-site-packages`` option, which ensures that globally-installed packages are accessible inside the virtualenv. Do not (re)install Toil after this! The ``--system-site-packages`` option has already transferred Toil and the dependencies from your local installation of Toil for you. From here, you can install a project and its dependencies:: $ tree . ├── util │   ├── __init__.py │   └── sort │   ├── __init__.py │   └── quick.py └── workflow ├── __init__.py └── main.py 3 directories, 5 files $ pip install matplotlib $ cp -R workflow util venv/lib/python2.7/site-packages Ideally, your project would have a ``setup.py`` file (see `setuptools`_) which streamlines the installation process:: $ tree . ├── util │   ├── __init__.py │   └── sort │   ├── __init__.py │   └── quick.py ├── workflow │ ├── __init__.py │ └── main.py └── setup.py 3 directories, 6 files $ pip install . Or, if your project has been published to PyPI:: $ pip install my-project In each case, we have created a virtualenv with the ``--system-site-packages`` flag in the ``venv`` subdirectory then installed the ``matplotlib`` distribution from PyPI along with the two packages that our project consists of. (Again, both Python and Toil are assumed to be present on the leader and all worker nodes.) We can now run our workflow:: $ python main.py --batchSystem=mesos … .. important:: If workflow's external dependencies contain native code (i.e. are not pure Python) then they must be manually installed on each worker. .. warning:: Neither ``python setup.py develop`` nor ``pip install -e .`` can be used in this process as, instead of copying the source files, they create ``.egg-link`` files that Toil can't auto-deploy. Similarly, ``python setup.py install`` doesn't work either as it installs the project as a Python ``.egg`` which is also not currently supported by Toil (though it `could be`_ in the future). Also note that using the ``--single-version-externally-managed`` flag with ``setup.py`` will prevent the installation of your package as an ``.egg``. It will also disable the automatic installation of your project's dependencies. .. _setuptools: http://setuptools.readthedocs.io/en/latest/index.html .. _could be: https://github.com/BD2KGenomics/toil/issues/1367 Auto Deployment with Sibling Modules ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ This scenario applies if the user script imports modules that are its siblings:: $ cd my_project $ ls userScript.py utilities.py $ ./userScript.py --batchSystem=mesos … Here ``userScript.py`` imports additional functionality from ``utilities.py``. Toil detects that ``userScript.py`` has sibling modules and copies them to the workers, alongside the user script. Note that sibling modules will be auto-deployed regardless of whether they are actually imported by the user script–all .py files residing in the same directory as the user script will automatically be auto-deployed. Sibling modules are a suitable method of organizing the source code of reasonably complicated workflows. Auto-Deploying a Package Hierarchy ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Recall that in Python, a `package`_ is a directory containing one or more ``.py`` files—one of which must be called ``__init__.py``—and optionally other packages. For more involved workflows that contain a significant amount of code, this is the recommended way of organizing the source code. Because we use a package hierarchy, we can't really refer to the user script as such, we call it the user *module* instead. It is merely one of the modules in the package hierarchy. We need to inform Toil that we want to use a package hierarchy by invoking Python's ``-m`` option. That enables Toil to identify the entire set of modules belonging to the workflow and copy all of them to each worker. Note that while using the ``-m`` option is optional in the scenarios above, it is mandatory in this one. The following shell session illustrates this:: $ cd my_project $ tree . ├── utils │   ├── __init__.py │   └── sort │   ├── __init__.py │   └── quick.py └── workflow ├── __init__.py └── main.py 3 directories, 5 files $ python -m workflow.main --batchSystem=mesos … .. _package: https://docs.python.org/2/tutorial/modules.html#packages Here the user module ``main.py`` does not reside in the current directory, but is part of a package called ``util``, in a subdirectory of the current directory. Additional functionality is in a separate module called ``util.sort.quick`` which corresponds to ``util/sort/quick.py``. Because we invoke the user module via ``python -m workflow.main``, Toil can determine the root directory of the hierarchy–``my_project`` in this case–and copy all Python modules underneath it to each worker. The ``-m`` option is documented `here`_ .. _here: https://docs.python.org/2/using/cmdline.html#cmdoption-m When ``-m`` is passed, Python adds the current working directory to ``sys.path``, the list of root directories to be considered when resolving a module name like ``workflow.main``. Without that added convenience we'd have to run the workflow as ``PYTHONPATH="$PWD" python -m workflow.main``. This also means that Toil can detect the root directory of the user module's package hierarchy even if it isn't the current working directory. In other words we could do this:: $ cd my_project $ export PYTHONPATH="$PWD" $ cd /some/other/dir $ python -m workflow.main --batchSystem=mesos … Also note that the root directory itself must not be package, i.e. must not contain an ``__init__.py``. Relying on Shared Filesystems ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Bare-metal clusters typically mount a shared file system like NFS on each node. If every node has that file system mounted at the same path, you can place your project on that shared filesystem and run your user script from there. Additionally, you can clone the Toil source tree into a directory on that shared file system and you won't even need to install Toil on every worker. Be sure to add both your project directory and the Toil clone to ``PYTHONPATH``. Toil replicates ``PYTHONPATH`` from the leader to every worker. .. admonition:: Using a shared filesystem Toil currently only supports a ``tempdir`` set to a local, non-shared directory. .. _deploying_toil: Toil Appliance -------------- The term Toil Appliance refers to the Mesos Docker image that Toil uses to simulate the machines in the virtual mesos cluster. It's easily deployed, only needs Docker, and allows for workflows to be run in single-machine mode and for clusters of VMs to be provisioned. To specify a different image, see the Toil :ref:`envars` section. For more information on the Toil Appliance, see the :ref:`runningAWS` section. toil-releases-3.24.0/docs/appendices/environment_vars.rst000066400000000000000000000271021362134276200235540ustar00rootroot00000000000000.. _envars: Environment Variables ===================== There are several environment variables that affect the way Toil runs. +----------------------------------+----------------------------------------------------+ | TOIL_CHECK_ENV | A flag that determines whether Toil will try to | | | refer back to a Python virtual environment in | | | which it is installed when composing commands that | | | may be run on other hosts. If set to ``True``, if | | | Toil is installed in the current virtual | | | environment, it will use absolute paths to its own | | | executables (and the virtual environment must thus | | | be available on at the same path on all nodes). | | | Otherwise, Toil internal commands such as | | | ``_toil_worker`` will be resolved according to the | | | ``PATH`` on the node where they are executed. This | | | setting can be useful in a shared HPC environment, | | | where users may have their own Toil installations | | | in virtual environments. | +----------------------------------+----------------------------------------------------+ | TOIL_WORKDIR | An absolute path to a directory where Toil will | | | write its temporary files. This directory must | | | exist on each worker node and may be set to a | | | different value on each worker. The ``--workDir`` | | | command line option overrides this. On Mesos nodes,| | | ``TOIL_WORKDIR`` generally defaults to the Mesos | | | sandbox, except on CGCloud-provisioned nodes where | | | it defaults to ``/var/lib/mesos``. In all other | | | cases, the system's `standard temporary directory`_| | | is used. | +----------------------------------+----------------------------------------------------+ | TOIL_KUBERNETES_OWNER | A name prefix for easy identification of | | | Kubernetes jobs. If not set, Toil will use the | | | current user name. | +----------------------------------+----------------------------------------------------+ | TOIL_APPLIANCE_SELF | The fully qualified reference for the Toil | | | Appliance you wish to use, in the form | | | ``REPO/IMAGE:TAG``. | | | ``quay.io/ucsc_cgl/toil:3.6.0`` and | | | ``cket/toil:3.5.0`` are both examples of valid | | | options. Note that since Docker defaults to | | | Dockerhub repos, only quay.io repos need to | | | specify their registry. | +----------------------------------+----------------------------------------------------+ | TOIL_DOCKER_REGISTRY | The URL of the registry of the Toil Appliance | | | image you wish to use. Docker will use Dockerhub | | | by default, but the quay.io registry is also | | | very popular and easily specifiable by setting | | | this option to ``quay.io``. | +----------------------------------+----------------------------------------------------+ | TOIL_DOCKER_NAME | The name of the Toil Appliance image you | | | wish to use. Generally this is simply ``toil`` but | | | this option is provided to override this, | | | since the image can be built with arbitrary names. | +----------------------------------+----------------------------------------------------+ | TOIL_AWS_SECRET_NAME | For the Kubernetes batch system, the name of a | | | Kubernetes secret which contains a ``credentials`` | | | file granting access to AWS resources. Will be | | | mounted as ``~/.aws`` inside Kubernetes-managed | | | Toil containers. Enables the AWSJobStore to be | | | used with the Kubernetes batch system, if the | | | credentials allow access to S3 and SimpleDB. | +----------------------------------+----------------------------------------------------+ | TOIL_AWS_ZONE | The EC2 zone to provision nodes in if using | | | Toil's provisioner. | +----------------------------------+----------------------------------------------------+ | TOIL_AWS_AMI | ID of the AMI to use in node provisioning. If in | | | doubt, don't set this variable. | +----------------------------------+----------------------------------------------------+ | TOIL_AWS_NODE_DEBUG | Determines whether to preserve nodes that have | | | failed health checks. If set to ``True``, nodes | | | that fail EC2 health checks won't immediately be | | | terminated so they can be examined and the cause | | | of failure determined. If any EC2 nodes are left | | | behind in this manner, the security group will | | | also be left behind by necessity as it cannot be | | | deleted until all associated nodes have been | | | terminated. | +----------------------------------+----------------------------------------------------+ | TOIL_SLURM_ARGS | Arguments for sbatch for the slurm batch system. | | | Do not pass CPU or memory specifications here. | | | Instead, define resource requirements for the job. | | | There is no default value for this variable. | +----------------------------------+----------------------------------------------------+ | TOIL_GRIDENGINE_ARGS | Arguments for qsub for the gridengine batch | | | system. Do not pass CPU or memory specifications | | | here. Instead, define resource requirements for | | | the job. There is no default value for this | | | variable. | +----------------------------------+----------------------------------------------------+ | TOIL_GRIDENGINE_PE | Parallel environment arguments for qsub and for | | | the gridengine batch system. There is no default | | | value for this variable. | +----------------------------------+----------------------------------------------------+ | TOIL_TORQUE_ARGS | Arguments for qsub for the Torque batch system. | | | Do not pass CPU or memory specifications here. | | | Instead, define extra parameters for the job such | | | as queue. Example: -q medium | | | Use TOIL_TORQUE_REQS to pass extra values for the | | | -l resource requirements parameter. | | | There is no default value for this variable. | +----------------------------------+----------------------------------------------------+ | TOIL_TORQUE_REQS | Arguments for the resource requirements for Torque | | | batch system. Do not pass CPU or memory | | | specifications here. Instead, define extra resource| | | requirements as a string that goes after the -l | | | argument to qsub. Example: | | | walltime=2:00:00,file=50gb | | | There is no default value for this variable. | +----------------------------------+----------------------------------------------------+ | TOIL_LSF_ARGS | Additional arguments for the LSF's bsub command. | | | Instead, define extra parameters for the job such | | | as queue. Example: -q medium. | | | There is no default value for this variable. | +----------------------------------+----------------------------------------------------+ | TOIL_HTCONDOR_PARAMS | Additional parameters to include in the HTCondor | | | submit file passed to condor_submit. Do not pass | | | CPU or memory specifications here. Instead define | | | extra parameters which may be required by HTCondor.| | | This variable is parsed as a semicolon-separated | | | string of ``parameter = value`` pairs. Example: | | | ``requirements = TARGET.has_sse4_2 == true; | | | accounting_group = test``. | | | There is no default value for this variable. | +----------------------------------+----------------------------------------------------+ | TOIL_CUSTOM_DOCKER_INIT_COMMAND | Any custom bash command to run in the Toil docker | | | container prior to running the Toil services. | | | Can be used for any custom initialization in the | | | worker and/or primary nodes such as private docker | | | docker authentication. Example for AWS ECR: | | | ``pip install awscli && eval $(aws ecr get-login | | | --no-include-email --region us-east-1)``. | +----------------------------------+----------------------------------------------------+ .. _standard temporary directory: https://docs.python.org/2/library/tempfile.html#tempfile.gettempdir toil-releases-3.24.0/docs/appendices/toil_architecture.jpg000066400000000000000000000345461362134276200236500ustar00rootroot00000000000000‰PNG  IHDR§bRÊŸ9-IDATxÚìÜ1 Å@EQÝÿžMÊttoÌ9`÷«/x!ÅÔaÄéEw›åˆÓqªü=ö ˆ“ã…ýâäxÙ/ NŽö ˆ“ã…ý‚89^Ø/ NŽö âäxa¿€89^Ø/ˆߎ×ó;³wD ÄéÜ8ÍŒÙ9ââ'Ÿ‡þMœ@œÄ qÄIœ''qBœq'Ä ÄIœ'@œÄ qq'q'@œâä% ã% §¸8yIÂxIÄ).N>ÿáóˆ“8!N€8‰ââ$Nˆ Nâ„88‰“8‰ Nâ„88‰“8!N Nâ„88!Nˆˆ“8!N€8‰ââ$Nâ$N€8‰ÓÍÞÙ´TÕEø8uÔ¨Aƒ ‚F4“GbˆDÑÀÈ¡H)Afƒ¢ "0²Åj A‰b V¢ejP©PV–ZÙ;Ö‚årßûvÞ#VT÷y`“÷ž}Ï>ëÖs÷Þëœ9 'ä„œ9 §UN555z¼µµ5drôèQ=¶gÏžðíÛ·èX¿+.._¿~ káéÓ§z®sçÎ…ßÉÇÖ-[tìúúúà8×®]ÓãçÏŸÿicnܸ1”••ÉwŠœrrœ––&:ãóçÏˉ;???¼yó&¬äĉzìСCa­LLLè¹NŸ>~. 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commented out # serve to show the default. from __future__ import absolute_import import sys import os import inspect import re from datetime import datetime import toil.version import time # This makes the modules located in docs/vendor/sphinxcontrib available to import sphinxPath = os.path.abspath(os.path.join(os.path.pardir, os.path.dirname('docs/vendor/sphinxcontrib/'))) sys.path.append(sphinxPath) import fulltoc def fetch_parent_dir(filepath, n=1): '''Returns a parent directory, n places above the input filepath. Equivalent to something like: '/home/user/dir'.split('/')[-2] if n=2. ''' filepath = os.path.realpath(filepath) for i in range(n): filepath = os.path.dirname(filepath) return os.path.basename(filepath) if not hasattr(sys, 'real_prefix'): raise RuntimeError('A virtualenv must be active and Sphinx must be installed in it') path_to_dir = os.path.dirname(os.path.abspath(__file__)) # Example of toil.version.__file__ on sphinx: # /home/docs/checkouts/readthedocs.org/user_builds/toil/envs/3.13.0/local/lib/python2.7/site-packages/toil-3.13.0a1-py2.7.egg/toil/version.pyc envPath = os.path.abspath(toil.version.__file__) # Example of __file__ on sphinx: # /home/docs/checkouts/readthedocs.org/user_builds/toil/checkouts/3.13.0/docs/conf.py wdPath_version = fetch_parent_dir(__file__, 2) # Expected output: 3.13.0 assert wdPath_version in envPath, \ "Another Toil installation seems to have precedence over this working directory." toilVersion = toil.version.baseVersion # -- General configuration ------------------------------------------------ # If your documentation needs a minimal Sphinx version, state it here. #needs_sphinx = '1.0' # Add any Sphinx extension module names here, as strings. They can be extensions # coming with Sphinx (named 'sphinx.ext.*') or your custom ones. extensions = [ 'sphinx.ext.autodoc', 'sphinx.ext.doctest', 'sphinx.ext.todo', 'sphinx.ext.coverage', 'sphinx.ext.viewcode', 'sphinx.ext.intersphinx', 'fulltoc', ] intersphinx_mapping = {'python': ('https://docs.python.org/2', None),} # Link definitions available everywhere so we don't need to keep repeating ourselves. rst_epilog = """ .. _Common Workflow Language: http://www.commonwl.org/ .. _CGCloud: https://github.com/BD2KGenomics/cgcloud """ def skip(app, what, name, obj, skip, options): return name != '__init__' and (skip or inspect.isclass(obj) or name.startswith('_') and not inspect.ismodule(obj)) def setup(app): app.connect('autodoc-skip-member', skip) # Add any paths that contain templates here, relative to this directory. templates_path = ['_templates'] # The suffix(es) of source filenames. Specify multiple suffix as list of string: # Example: source_suffix = ['.rst', '.md'] source_suffix = '.rst' # The encoding of source files. #source_encoding = 'utf-8-sig' # The master toctree document. master_doc = 'index' # General information about the project. project = u'Toil' build_date = datetime.utcfromtimestamp(int(os.environ.get('SOURCE_DATE_EPOCH', time.time()))) copyright = u'2015 – %i UCSC Computational Genomics Lab' % build_date.year author = u'UCSC Computational Genomics Lab' # The version info for the project you're documenting, acts as replacement for # |version| and |release|, also used in various other places throughout the # built documents. # # The short X.Y version. version = re.split('[A-Za-z]', toilVersion)[0] # The full version, including alpha/beta/rc tags. release = toilVersion # The language for content autogenerated by Sphinx. Refer to documentation # for a list of supported languages. # # This is also used if you do content translation via gettext catalogs. # Usually you set "language" from the command line for these cases. language = None # There are two options for replacing |today|: either, you set today to some # non-false value, then it is used: #today = '' # Else, today_fmt is used as the format for a strftime call. #today_fmt = '%B %d, %Y' # List of patterns, relative to source directory, that match files and # directories to ignore when looking for source files. exclude_patterns = ['_build'] # The reST default role (used for this markup: `text`) to use for all # documents. #default_role = None # If true, '()' will be appended to :func: etc. cross-reference text. #add_function_parentheses = True # If true, the current module name will be prepended to all description # unit titles (such as .. function::). #add_module_names = True # If true, sectionauthor and moduleauthor directives will be shown in the # output. They are ignored by default. #show_authors = False # The name of the Pygments (syntax highlighting) style to use. pygments_style = 'sphinx' # A list of ignored prefixes for module index sorting. #modindex_common_prefix = [] # If true, keep warnings as "system message" paragraphs in the built documents. #keep_warnings = False # If true, 2do and 2doList produce output, else they produce nothing. todo_include_todos = True # Include doc string for __init__ method in the documentation autoclass_content = 'class' autodoc_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 = 'alabaster' html_theme_options = { "github_banner": True, "github_user": "BD2KGenomics", "github_repo": "toil", "caption_font_size": "24px" } # Theme options are theme-specific and customize the look and feel of a theme # further. For a list of options available for each theme, see the # documentation. #html_theme_options = {} # Add any paths that contain custom themes here, relative to this directory. #html_theme_path = [] # The name for this set of Sphinx documents. If None, it defaults to # " v documentation". #html_title = None # A shorter title for the navigation bar. Default is the same as html_title. #html_short_title = None # The name of an image file (relative to this directory) to place at the top # of the sidebar. html_logo = "_static/logo.png" # The name of an image file (within the static path) to use as favicon of the # docs. This file should be a Windows icon file (.ico) being 16x16 or 32x32 # pixels large. html_favicon = "_static/favicon.ico" # 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 = ['_static'] # Add any extra paths that contain custom files (such as robots.txt or # .htaccess) here, relative to this directory. These files are copied # directly to the root of the documentation. #html_extra_path = [] # If not '', a 'Last updated on:' timestamp is inserted at every page bottom, # using the given strftime format. #html_last_updated_fmt = '%b %d, %Y' # If true, SmartyPants will be used to convert quotes and dashes to # typographically correct entities. #html_use_smartypants = True # Custom sidebar templates, maps document names to template names. #html_sidebars = {} # Additional templates that should be rendered to pages, maps page names to # template names. #html_additional_pages = {} # If false, no module index is generated. #html_domain_indices = True # If false, no index is generated. #html_use_index = True # If true, the index is split into individual pages for each letter. #html_split_index = False # If true, links to the reST sources are added to the pages. html_show_sourcelink = False # If true, "Created using Sphinx" is shown in the HTML footer. Default is True. #html_show_sphinx = True # If true, "(C) Copyright ..." is shown in the HTML footer. Default is True. #html_show_copyright = True # If true, an OpenSearch description file will be output, and all pages will # contain a tag referring to it. The value of this option must be the # base URL from which the finished HTML is served. #html_use_opensearch = '' # This is the file name suffix for HTML files (e.g. ".xhtml"). #html_file_suffix = None # Language to be used for generating the HTML full-text search index. # Sphinx supports the following languages: # 'da', 'de', 'en', 'es', 'fi', 'fr', 'hu', 'it', 'ja' # 'nl', 'no', 'pt', 'ro', 'ru', 'sv', 'tr' #html_search_language = 'en' # A dictionary with options for the search language support, empty by default. # Now only 'ja' uses this config value #html_search_options = {'type': 'default'} # The name of a javascript file (relative to the configuration directory) that # implements a search results scorer. If empty, the default will be used. #html_search_scorer = 'scorer.js' # Output file base name for HTML help builder. htmlhelp_basename = 'Toildoc' # -- Options for LaTeX output --------------------------------------------- latex_elements = { # The paper size ('letterpaper' or 'a4paper'). #'papersize': 'letterpaper', # The font size ('10pt', '11pt' or '12pt'). #'pointsize': '10pt', # Additional stuff for the LaTeX preamble. #'preamble': '', # Latex figure (float) alignment #'figure_align': 'htbp', } # Grouping the document tree into LaTeX files. List of tuples # (source start file, target name, title, # author, documentclass [howto, manual, or own class]). latex_documents = [ (master_doc, 'Toil.tex', u'Toil Documentation', u'UCSC Computational Genomics Lab', 'manual'), ] # The name of an image file (relative to this directory) to place at the top of # the title page. #latex_logo = None # For "manual" documents, if this is true, then toplevel headings are parts, # not chapters. #latex_use_parts = False # If true, show page references after internal links. #latex_show_pagerefs = False # If true, show URL addresses after external links. #latex_show_urls = False # Documents to append as an appendix to all manuals. #latex_appendices = [] # If false, no module index is generated. #latex_domain_indices = True # -- Options for manual page output --------------------------------------- # One entry per manual page. List of tuples # (source start file, name, description, authors, manual section). man_pages = [ (master_doc, 'toil', u'Toil Documentation', [author], 1) ] # If true, show URL addresses after external links. #man_show_urls = False # -- Options for Texinfo output ------------------------------------------- # Grouping the document tree into Texinfo files. List of tuples # (source start file, target name, title, author, # dir menu entry, description, category) texinfo_documents = [ (master_doc, 'Toil', u'Toil Documentation', author, 'Toil', 'One line description of project.', 'Miscellaneous'), ] # Documents to append as an appendix to all manuals. #texinfo_appendices = [] # If false, no module index is generated. #texinfo_domain_indices = True # How to display URL addresses: 'footnote', 'no', or 'inline'. #texinfo_show_urls = 'footnote' # If true, do not generate a @detailmenu in the "Top" node's menu. #texinfo_no_detailmenu = False toil-releases-3.24.0/docs/contributing/000077500000000000000000000000001362134276200200155ustar00rootroot00000000000000toil-releases-3.24.0/docs/contributing/contributing.rst000066400000000000000000000411101362134276200232530ustar00rootroot00000000000000.. highlight:: console .. _runningTests: Running Tests ------------- Test make targets, invoked as ``$ make ``, subject to which environment variables are set (see :ref:`test_env_vars`). +-------------------------+---------------------------------------------------+ | TARGET | DESCRIPTION | +-------------------------+---------------------------------------------------+ | test | Invokes all tests. | +-------------------------+---------------------------------------------------+ | integration_test | Invokes only the integration tests. | +-------------------------+---------------------------------------------------+ | test_offline | Skips building the Docker appliance and only | | | invokes tests that have no docker dependencies. | +-------------------------+---------------------------------------------------+ | integration_test_local | Makes integration tests easier to debug locally | | | by running the integration tests serially and | | | doesn't redirect output. This makes it appears on | | | the terminal as expected. | +-------------------------+---------------------------------------------------+ Before running tests for the first time, initialize your virtual environment following the steps in :ref:`buildFromSource`. Run all tests (including slow tests):: $ make test Run only quick tests (as of Jul 25, 2018, this was ~ 20 minutes):: $ export TOIL_TEST_QUICK=True; make test Run an individual test with:: $ make test tests=src/toil/test/sort/sortTest.py::SortTest::testSort The default value for ``tests`` is ``"src"`` which includes all tests in the ``src/`` subdirectory of the project root. Tests that require a particular feature will be skipped implicitly. If you want to explicitly skip tests that depend on a currently installed *feature*, use :: $ make test tests="-m 'not aws' src" This will run only the tests that don't depend on the ``aws`` extra, even if that extra is currently installed. Note the distinction between the terms *feature* and *extra*. Every extra is a feature but there are features that are not extras, such as the ``gridengine`` and ``parasol`` features. To skip tests involving both the ``parasol`` feature and the ``aws`` extra, use the following:: $ make test tests="-m 'not aws and not parasol' src" Running Tests with pytest ~~~~~~~~~~~~~~~~~~~~~~~~~ Often it is simpler to use pytest directly, instead of calling the ``make`` wrapper. This usually works as expected, but some tests need some manual preparation. To run a specific test with pytest, use the following:: python -m pytest src/toil/test/sort/sortTest.py::SortTest::testSort For more information, see the `pytest documentation`_. .. _pytest documentation: https://docs.pytest.org/en/latest/ .. _test_env_vars: Running Integration Tests ~~~~~~~~~~~~~~~~~~~~~~~~~ These tests are generally only run using in our CI workflow due to their resource requirements and cost. However, they can be made available for local testing: - Running tests that make use of Docker (e.g. autoscaling tests and Docker tests) require an appliance image to be hosted. First, make sure you have gone through the set up found in :ref:`quaySetup`. Then to build and host the appliance image run the ``make`` target ``push_docker``. :: $ make push_docker - Running integration tests require activation via an environment variable as well as exporting information relevant to the desired tests. Enable the integration tests:: $ export TOIL_TEST_INTEGRATIVE=True - Finally, set the environment variables for keyname and desired zone:: $ export TOIL_X_KEYNAME=[Your Keyname] $ export TOIL_X_ZONE=[Desired Zone] Where ``X`` is one of our currently supported cloud providers (``GCE``, ``AWS``). - See the above sections for guidance on running tests. Test Environment Variables ~~~~~~~~~~~~~~~~~~~~~~~~~~ +------------------------+----------------------------------------------------+ | TOIL_TEST_TEMP | An absolute path to a directory where Toil tests | | | will write their temporary files. Defaults to the | | | system's `standard temporary directory`_. | +------------------------+----------------------------------------------------+ | TOIL_TEST_INTEGRATIVE | If ``True``, this allows the integration tests to | | | run. Only valid when running the tests from the | | | source directory via ``make test`` or | | | ``make test_parallel``. | +------------------------+----------------------------------------------------+ | TOIL_AWS_KEYNAME | An AWS keyname (see :ref:`prepareAWS`), which | | | is required to run the AWS tests. | +------------------------+----------------------------------------------------+ | TOIL_GOOGLE_PROJECTID | A Google Cloud account projectID | | | (see :ref:`runningGCE`), which is required to | | | to run the Google Cloud tests. | +------------------------+----------------------------------------------------+ | TOIL_TEST_QUICK | If ``True``, long running tests are skipped. | +------------------------+----------------------------------------------------+ .. _standard temporary directory: https://docs.python.org/2/library/tempfile.html#tempfile.gettempdir .. admonition:: Partial install and failing tests Some tests may fail with an ImportError if the required extras are not installed. Install Toil with all of the extras do prevent such errors. .. _quaySetup: Using Docker with Quay ~~~~~~~~~~~~~~~~~~~~~~ `Docker`_ is needed for some of the tests. Follow the appropriate installation instructions for your system on their website to get started. When running ``make test`` you might still get the following error:: $ make test Please set TOIL_DOCKER_REGISTRY, e.g. to quay.io/USER. To solve, make an account with `Quay`_ and specify it like so:: $ TOIL_DOCKER_REGISTRY=quay.io/USER make test where ``USER`` is your Quay username. For convenience you may want to add this variable to your bashrc by running :: $ echo 'export TOIL_DOCKER_REGISTRY=quay.io/USER' >> $HOME/.bashrc Running Mesos Tests ~~~~~~~~~~~~~~~~~~~ If you're running Toil's Mesos tests, be sure to create the virtualenv with ``--system-site-packages`` to include the Mesos Python bindings. Verify this by activating the virtualenv and running ``pip list | grep mesos``. On macOS, this may come up empty. To fix it, run the following: .. code-block:: bash for i in /usr/local/lib/python2.7/site-packages/*mesos*; do ln -snf $i venv/lib/python2.7/site-packages/; done .. _Docker: https://www.docker.com/products/docker .. _Quay: https://quay.io/ .. _log into Quay: https://docs.quay.io/solution/getting-started.html .. _appliance_dev: Developing with Docker ---------------------- To develop on features reliant on the Toil Appliance (the docker image toil uses for AWS autoscaling), you should consider setting up a personal registry on `Quay`_ or `Docker Hub`_. Because the Toil Appliance images are tagged with the Git commit they are based on and because only commits on our master branch trigger an appliance build on Quay, as soon as a developer makes a commit or dirties the working copy they will no longer be able to rely on Toil to automatically detect the proper Toil Appliance image. Instead, developers wishing to test any appliance changes in autoscaling should build and push their own appliance image to a personal Docker registry. This is described in the next section. Making Your Own Toil Docker Image ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ **Note!** Toil checks if the docker image specified by TOIL_APPLIANCE_SELF exists prior to launching by using the docker v2 schema. This should be valid for any major docker repository, but there is an option to override this if desired using the option: `-\\-forceDockerAppliance`. Here is a general workflow (similar instructions apply when using Docker Hub): #. Make some changes to the provisioner of your local version of Toil #. Go to the location where you installed the Toil source code and run :: $ make docker to automatically build a docker image that can now be uploaded to your personal `Quay`_ account. If you have not installed Toil source code yet see :ref:`buildFromSource`. #. If it's not already you will need Docker installed and need to `log into Quay`_. Also you will want to make sure that your Quay account is public. #. Set the environment variable ``TOIL_DOCKER_REGISTRY`` to your Quay account. If you find yourself doing this often you may want to add :: export TOIL_DOCKER_REGISTRY=quay.io/ to your ``.bashrc`` or equivalent. #. Now you can run :: $ make push_docker which will upload the docker image to your Quay account. Take note of the image's tag for the next step. #. Finally you will need to tell Toil from where to pull the Appliance image you've created (it uses the Toil release you have installed by default). To do this set the environment variable ``TOIL_APPLIANCE_SELF`` to the url of your image. For more info see :ref:`envars`. #. Now you can launch your cluster! For more information see :ref:`Autoscaling`. Running a Cluster Locally ~~~~~~~~~~~~~~~~~~~~~~~~~ The Toil Appliance container can also be useful as a test environment since it can simulate a Toil cluster locally. An important caveat for this is autoscaling, since autoscaling will only work on an EC2 instance and cannot (at this time) be run on a local machine. To spin up a local cluster, start by using the following Docker run command to launch a Toil leader container:: docker run --entrypoint=mesos-master --net=host -d --name=leader --volume=/home/jobStoreParentDir:/jobStoreParentDir quay.io/ucsc_cgl/toil:3.6.0 --registry=in_memory --ip=127.0.0.1 --port=5050 --allocation_interval=500ms A couple notes on this command: the ``-d`` flag tells Docker to run in daemon mode so the container will run in the background. To verify that the container is running you can run ``docker ps`` to see all containers. If you want to run your own container rather than the official UCSC container you can simply replace the ``quay.io/ucsc_cgl/toil:3.6.0`` parameter with your own container name. Also note that we are not mounting the job store directory itself, but rather the location where the job store will be written. Due to complications with running Docker on MacOS, I recommend only mounting directories within your home directory. The next command will launch the Toil worker container with similar parameters:: docker run --entrypoint=mesos-slave --net=host -d --name=worker --volume=/home/jobStoreParentDir:/jobStoreParentDir quay.io/ucsc_cgl/toil:3.6.0 --work_dir=/var/lib/mesos --master=127.0.0.1:5050 --ip=127.0.0.1 —-attributes=preemptable:False --resources=cpus:2 Note here that we are specifying 2 CPUs and a non-preemptable worker. We can easily change either or both of these in a logical way. To change the number of cores we can change the 2 to whatever number you like, and to change the worker to be preemptable we change ``preemptable:False`` to ``preemptable:True``. Also note that the same volume is mounted into the worker. This is needed since both the leader and worker write and read from the job store. Now that your cluster is running, you can run :: docker exec -it leader bash to get a shell in your leader 'node'. You can also replace the ``leader`` parameter with ``worker`` to get shell access in your worker. .. admonition:: Docker-in-Docker issues If you want to run Docker inside this Docker cluster (Dockerized tools, perhaps), you should also mount in the Docker socket via ``-v /var/run/docker.sock:/var/run/docker.sock``. This will give the Docker client inside the Toil Appliance access to the Docker engine on the host. Client/engine version mismatches have been known to cause issues, so we recommend using Docker version 1.12.3 on the host to be compatible with the Docker client installed in the Appliance. Finally, be careful where you write files inside the Toil Appliance - 'child' Docker containers launched in the Appliance will actually be siblings to the Appliance since the Docker engine is located on the host. This means that the 'child' container can only mount in files from the Appliance if the files are located in a directory that was originally mounted into the Appliance from the host - that way the files are accessible to the sibling container. Note: if Docker can't find the file/directory on the host it will silently fail and mount in an empty directory. .. _Quay: https://quay.io/ .. _Docker Hub: https://hub.docker.com/ Maintainer's Guidelines ----------------------- In general, as developers and maintainers of the code, we adhere to the following guidelines: * We strive to never break the build on master. All development should be done on branches, in either the main Toil repository or in developers' forks. * Pull requests should be used for any and all changes (except truly trivial ones). * Pull requests should be in response to issues. If you find yourself making a pull request without an issue, you should create the issue first. Naming Conventions ~~~~~~~~~~~~~~~~~~ * **Commit messages** *should* be `great`_. Most importantly, they *must*: - Have a short subject line. If in need of more space, drop down **two** lines and write a body to explain what is changing and why it has to change. - Write the subject line as a command: `Destroy all humans`, not `All humans destroyed`. - Reference the issue being fixed in a Github-parseable format, such as `(resolves #1234)` at the end of the subject line, or `This will fix #1234.` somewhere in the body. If no single commit on its own fixes the issue, the cross-reference must appear in the pull request title or body instead. * **Branches** in the main Toil repository *must* start with ``issues/``, followed by the issue number (or numbers, separated by a dash), followed by a short, lowercase, hyphenated description of the change. (There can be many open pull requests with their associated branches at any given point in time and this convention ensures that we can easily identify branches.) Say there is an issue numbered #123 titled `Foo does not work`. The branch name would be ``issues/123-fix-foo`` and the title of the commit would be `Fix foo in case of bar (resolves #123).` .. _great: https://chris.beams.io/posts/git-commit/#seven-rules Pull Requests ~~~~~~~~~~~~~ * All pull requests must be reviewed by a person other than the request's author. * Modified pull requests must be re-reviewed before merging. **Note that Github does not enforce this!** * Pull requests will not be merged unless Travis and Gitlab CI tests pass. Gitlab tests are only run on code in the main Toil repository on some branch, so it is the responsibility of the approving reviewer to make sure that pull requests from outside repositories are copied to branches in the main repository. This can be accomplished with (from a Toil clone): .. code-block:: bash ./contrib/admin/test-pr theirusername their-branch issues/123-fix-description-here This must be repeated every time the PR submitter updates their PR, after checking to see that the update is not malicious. If there is no issue corresponding to the PR, after which the branch can be named, the reviewer of the PR should first create the issue. Developers who have push access to the main Toil repository are encouraged to make their pull requests from within the repository, to avoid this step. * Prefer using "Squash and marge" when merging pull requests to master especially when the PR contains a "single unit" of work (i.e. if one were to rewrite the PR from scratch with all the fixes included, they would have one commit for the entire PR). This makes the commit history on master more readable and easier to debug in case of a breakage. When squashing a PR from multiple authors, please add `Co-authored-by`_ to give credit to all contributing authors. See `Issue #2816`_ for more details. .. _Co-authored-by: https://github.blog/2018-01-29-commit-together-with-co-authors/ .. _Issue #2816: https://github.com/DataBiosphere/toil/issues/2816 toil-releases-3.24.0/docs/developingWorkflows/000077500000000000000000000000001362134276200213605ustar00rootroot00000000000000toil-releases-3.24.0/docs/developingWorkflows/developing.rst000066400000000000000000000677341362134276200242670ustar00rootroot00000000000000.. _tutorial-ref: Developing a Workflow ===================== This tutorial walks through the features of Toil necessary for developing a workflow using the Toil Python API. .. note:: "script" and "workflow" will be used interchangeably Scripting Quick Start --------------------- To begin, consider this short toil script which illustrates defining a workflow: .. literalinclude:: ../../src/toil/test/docs/scripts/tutorial_quickstart.py The workflow consists of a single job. The resource requirements for that job are (optionally) specified by keyword arguments (memory, cores, disk). The script is run using :func:`toil.job.Job.Runner.getDefaultOptions`. Below we explain the components of this code in detail. Job Basics ---------- The atomic unit of work in a Toil workflow is a :class:`~toil.job.Job`. User scripts inherit from this base class to define units of work. For example, here is a more long-winded class-based version of the job in the quick start example:: from toil.job import Job class HelloWorld(Job): def __init__(self, message): Job.__init__(self, memory="2G", cores=2, disk="3G") self.message = message def run(self, fileStore): return "Hello, world!, here's a message: %s" % self.message In the example a class, HelloWorld, is defined. The constructor requests 2 gigabytes of memory, 2 cores and 3 gigabytes of local disk to complete the work. The :func:`toil.job.Job.run` method is the function the user overrides to get work done. Here it just logs a message using :func:`toil.job.Job.log`, which will be registered in the log output of the leader process of the workflow. Invoking a Workflow ------------------- We can add to the previous example to turn it into a complete workflow by adding the necessary function calls to create an instance of HelloWorld and to run this as a workflow containing a single job. This uses the :class:`toil.job.Job.Runner` class, which is used to start and resume Toil workflows. For example: .. literalinclude:: ../../src/toil/test/docs/scripts/tutorial_invokeworkflow.py .. note:: Do not include a `.` in the name of your python script (besides `.py` at the end). This is to allow toil to import the types and functions defined in your file while starting a new process. Alternatively, the more powerful :class:`toil.common.Toil` class can be used to run and resume workflows. It is used as a context manager and allows for preliminary setup, such as staging of files into the job store on the leader node. An instance of the class is initialized by specifying an options object. The actual workflow is then invoked by calling the :func:`toil.common.Toil.start` method, passing the root job of the workflow, or, if a workflow is being restarted, :func:`toil.common.Toil.restart` should be used. Note that the context manager should have explicit if else branches addressing restart and non restart cases. The boolean value for these if else blocks is toil.options.restart. For example: .. literalinclude:: ../../src/toil/test/docs/scripts/tutorial_invokeworkflow2.py The call to :func:`toil.job.Job.Runner.getDefaultOptions` creates a set of default options for the workflow. The only argument is a description of how to store the workflow's state in what we call a *job-store*. Here the job-store is contained in a directory within the current working directory called "toilWorkflowRun". Alternatively this string can encode other ways to store the necessary state, e.g. an S3 bucket object store location. By default the job-store is deleted if the workflow completes successfully. The workflow is executed in the final line, which creates an instance of HelloWorld and runs it as a workflow. Note all Toil workflows start from a single starting job, referred to as the *root* job. The return value of the root job is returned as the result of the completed workflow (see promises below to see how this is a useful feature!). Specifying Commandline Arguments -------------------------------- To allow command line control of the options we can use the :func:`toil.job.Job.Runner.getDefaultArgumentParser` method to create a :class:`argparse.ArgumentParser` object which can be used to parse command line options for a Toil script. For example: .. literalinclude:: ../../src/toil/test/docs/scripts/tutorial_arguments.py Creates a fully fledged script with all the options Toil exposed as command line arguments. Running this script with "--help" will print the full list of options. Alternatively an existing :class:`argparse.ArgumentParser` or :class:`optparse.OptionParser` object can have Toil script command line options added to it with the :func:`toil.job.Job.Runner.addToilOptions` method. Resuming a Workflow ------------------- In the event that a workflow fails, either because of programmatic error within the jobs being run, or because of node failure, the workflow can be resumed. Workflows can only not be reliably resumed if the job-store itself becomes corrupt. Critical to resumption is that jobs can be rerun, even if they have apparently completed successfully. Put succinctly, a user defined job should not corrupt its input arguments. That way, regardless of node, network or leader failure the job can be restarted and the workflow resumed. To resume a workflow specify the "restart" option in the options object passed to :func:`toil.common.Toil.start`. If node failures are expected it can also be useful to use the integer "retryCount" option, which will attempt to rerun a job retryCount number of times before marking it fully failed. In the common scenario that a small subset of jobs fail (including retry attempts) within a workflow Toil will continue to run other jobs until it can do no more, at which point :func:`toil.common.Toil.start` will raise a :exc:`toil.leader.FailedJobsException` exception. Typically at this point the user can decide to fix the script and resume the workflow or delete the job-store manually and rerun the complete workflow. Functions and Job Functions --------------------------- Defining jobs by creating class definitions generally involves the boilerplate of creating a constructor. To avoid this the classes :class:`toil.job.FunctionWrappingJob` and :class:`toil.job.JobFunctionWrappingTarget` allow functions to be directly converted to jobs. For example, the quick start example (repeated here): .. literalinclude:: ../../src/toil/test/docs/scripts/tutorial_quickstart.py Is equivalent to the previous example, but using a function to define the job. The function call:: Job.wrapFn(helloWorld, "Woot") Creates the instance of the :class:`toil.job.FunctionWrappingTarget` that wraps the function. The keyword arguments *memory*, *cores* and *disk* allow resource requirements to be specified as before. Even if they are not included as keyword arguments within a function header they can be passed as arguments when wrapping a function as a job and will be used to specify resource requirements. We can also use the function wrapping syntax to a *job function*, a function whose first argument is a reference to the wrapping job. Just like a *self* argument in a class, this allows access to the methods of the wrapping job, see :class:`toil.job.JobFunctionWrappingTarget`. For example: .. literalinclude:: ../../src/toil/test/docs/scripts/tutorial_jobfunctions.py Here ``helloWorld()`` is a job function. It uses the :func:`toil.job.Job.log` to log a message that will be printed to the output console. Here the only subtle difference to note is the line:: hello_job = Job.wrapJobFn(helloWorld, "Woot") Which uses the function :func:`toil.job.Job.wrapJobFn` to wrap the job function instead of :func:`toil.job.Job.wrapFn` which wraps a vanilla function. Workflows with Multiple Jobs ---------------------------- A *parent* job can have *child* jobs and *follow-on* jobs. These relationships are specified by methods of the job class, e.g. :func:`toil.job.Job.addChild` and :func:`toil.job.Job.addFollowOn`. Considering a set of jobs the nodes in a job graph and the child and follow-on relationships the directed edges of the graph, we say that a job B that is on a directed path of child/follow-on edges from a job ``A`` in the job graph is a *successor* of ``A``, similarly ``A`` is a *predecessor* of ``B``. A parent job's child jobs are run directly after the parent job has completed, and in parallel. The follow-on jobs of a job are run after its child jobs and their successors have completed. They are also run in parallel. Follow-ons allow the easy specification of cleanup tasks that happen after a set of parallel child tasks. The following shows a simple example that uses the earlier ``helloWorld()`` job function: .. literalinclude:: ../../src/toil/test/docs/scripts/tutorial_multiplejobs.py In the example four jobs are created, first ``j1`` is run, then ``j2`` and ``j3`` are run in parallel as children of ``j1``, finally ``j4`` is run as a follow-on of ``j1``. There are multiple short hand functions to achieve the same workflow, for example: .. literalinclude:: ../../src/toil/test/docs/scripts/tutorial_multiplejobs2.py Equivalently defines the workflow, where the functions :func:`toil.job.Job.addChildJobFn` and :func:`toil.job.Job.addFollowOnJobFn` are used to create job functions as children or follow-ons of an earlier job. Jobs graphs are not limited to trees, and can express arbitrary directed acyclic graphs. For a precise definition of legal graphs see :func:`toil.job.Job.checkJobGraphForDeadlocks`. The previous example could be specified as a DAG as follows: .. literalinclude:: ../../src/toil/test/docs/scripts/tutorial_multiplejobs3.py Note the use of an extra child edge to make ``j4`` a child of both ``j2`` and ``j3``. Dynamic Job Creation -------------------- The previous examples show a workflow being defined outside of a job. However, Toil also allows jobs to be created dynamically within jobs. For example: .. literalinclude:: ../../src/toil/test/docs/scripts/tutorial_dynamic.py The job function ``binaryStringFn`` logs all possible binary strings of length ``n`` (here ``n=5``), creating a total of ``2^(n+2) - 1`` jobs dynamically and recursively. Static and dynamic creation of jobs can be mixed in a Toil workflow, with jobs defined within a job or job function being created at run time. .. _promises: Promises -------- The previous example of dynamic job creation shows variables from a parent job being passed to a child job. Such forward variable passing is naturally specified by recursive invocation of successor jobs within parent jobs. This can also be achieved statically by passing around references to the return variables of jobs. In Toil this is achieved with promises, as illustrated in the following example: .. literalinclude:: ../../src/toil/test/docs/scripts/tutorial_promises.py Running this workflow results in three log messages from the jobs: ``i is 1`` from ``j1``, ``i is 2`` from ``j2`` and ``i is 3`` from ``j3``. The return value from the first job is *promised* to the second job by the call to :func:`toil.job.Job.rv` in the following line:: j2 = j1.addChildFn(fn, j1.rv()) The value of ``j1.rv()`` is a *promise*, rather than the actual return value of the function, because ``j1`` for the given input has at that point not been evaluated. A promise (:class:`toil.job.Promise`) is essentially a pointer to for the return value that is replaced by the actual return value once it has been evaluated. Therefore, when ``j2`` is run the promise becomes 2. Promises also support indexing of return values:: def parent(job): indexable = Job.wrapJobFn(fn) job.addChild(indexable) job.addFollowOnFn(raiseWrap, indexable.rv(2)) def raiseWrap(arg): raise RuntimeError(arg) # raises "2" def fn(job): return (0, 1, 2, 3) Promises can be quite useful. For example, we can combine dynamic job creation with promises to achieve a job creation process that mimics the functional patterns possible in many programming languages: .. literalinclude:: ../../src/toil/test/docs/scripts/tutorial_promises2.py The return value ``l`` of the workflow is a list of all binary strings of length 10, computed recursively. Although a toy example, it demonstrates how closely Toil workflows can mimic typical programming patterns. Promised Requirements --------------------- Promised requirements are a special case of :ref:`promises` that allow a job's return value to be used as another job's resource requirements. This is useful when, for example, a job's storage requirement is determined by a file staged to the job store by an earlier job: .. literalinclude:: ../../src/toil/test/docs/scripts/tutorial_requirements.py Note that this also makes use of the ``size`` attribute of the :ref:`FileID` object. This promised requirements mechanism can also be used in combination with an aggregator for multiple jobs' output values:: def parentJob(job): aggregator = [] for fileNum in range(0,10): downloadJob = Job.wrapJobFn(stageFn, "File://"+os.path.realpath(__file__), cores=0.1, memory='32M', disk='1M') job.addChild(downloadJob) aggregator.append(downloadJob) analysis = Job.wrapJobFn(analysisJob, fileStoreID=downloadJob.rv(0), disk=PromisedRequirement(lambda xs: sum(xs), [j.rv(1) for j in aggregator])) job.addFollowOn(analysis) .. admonition:: Limitations Just like regular promises, the return value must be determined prior to scheduling any job that depends on the return value. In our example above, notice how the dependent jobs were follow ons to the parent while promising jobs are children of the parent. This ordering ensures that all promises are properly fulfilled. .. _FileID: FileID ------ The :class:`toil.fileStore.FileID` class is a small wrapper around Python's builtin string class. It is used to represent a file's ID in the file store, and has a ``size`` attribute that is the file's size in bytes. This object is returned by ``importFile`` and ``writeGlobalFile``. .. _managingFiles: Managing files within a workflow -------------------------------- It is frequently the case that a workflow will want to create files, both persistent and temporary, during its run. The :class:`toil.fileStores.abstractFileStore.AbstractFileStore` class is used by jobs to manage these files in a manner that guarantees cleanup and resumption on failure. The :func:`toil.job.Job.run` method has a file store instance as an argument. The following example shows how this can be used to create temporary files that persist for the length of the job, be placed in a specified local disk of the node and that will be cleaned up, regardless of failure, when the job finishes: .. literalinclude:: ../../src/toil/test/docs/scripts/tutorial_managing.py Job functions can also access the file store for the job. The equivalent of the ``LocalFileStoreJob`` class is :: def localFileStoreJobFn(job): scratchDir = job.tempDir scratchFile = job.fileStore.getLocalTempFile() Note that the ``fileStore`` attribute is accessed as an attribute of the ``job`` argument. In addition to temporary files that exist for the duration of a job, the file store allows the creation of files in a *global* store, which persists during the workflow and are globally accessible (hence the name) between jobs. For example: .. literalinclude:: ../../src/toil/test/docs/scripts/tutorial_managing2.py The example demonstrates the global read, write and delete functionality of the file-store, using both local copies of the files and streams to read and write the files. It covers all the methods provided by the file store interface. What is obvious is that the file-store provides no functionality to update an existing "global" file, meaning that files are, barring deletion, immutable. Also worth noting is that there is no file system hierarchy for files in the global file store. These limitations allow us to fairly easily support different object stores and to use caching to limit the amount of network file transfer between jobs. Staging of Files into the Job Store ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ External files can be imported into or exported out of the job store prior to running a workflow when the :class:`toil.common.Toil` context manager is used on the leader. The context manager provides methods :func:`toil.common.Toil.importFile`, and :func:`toil.common.Toil.exportFile` for this purpose. The destination and source locations of such files are described with URLs passed to the two methods. A list of the currently supported URLs can be found at :func:`toil.jobStores.abstractJobStore.AbstractJobStore.importFile`. To import an external file into the job store as a shared file, pass the optional ``sharedFileName`` parameter to that method. If a workflow fails for any reason an imported file acts as any other file in the job store. If the workflow was configured such that it not be cleaned up on a failed run, the file will persist in the job store and needs not be staged again when the workflow is resumed. Example: .. literalinclude:: ../../src/toil/test/docs/scripts/tutorial_staging.py Using Docker Containers in Toil ------------------------------- Docker containers are commonly used with Toil. The combination of Toil and Docker allows for pipelines to be fully portable between any platform that has both Toil and Docker installed. Docker eliminates the need for the user to do any other tool installation or environment setup. In order to use Docker containers with Toil, Docker must be installed on all workers of the cluster. Instructions for installing Docker can be found on the `Docker`_ website. .. _Docker: https://docs.docker.com/engine/getstarted/step_one/ When using Toil-based autoscaling, Docker will be automatically set up on the cluster's worker nodes, so no additional installation steps are necessary. Further information on using Toil-based autoscaling can be found in the :ref:`Autoscaling` documentation. In order to use docker containers in a Toil workflow, the container can be built locally or downloaded in real time from an online docker repository like Quay_. If the container is not in a repository, the container's layers must be accessible on each node of the cluster. .. _Quay: quay.io When invoking docker containers from within a Toil workflow, it is strongly recommended that you use :func:`dockerCall`, a toil job function provided in ``toil.lib.docker``. ``dockerCall`` leverages docker's own python API, and provides container cleanup on job failure. When docker containers are run without this feature, failed jobs can result in resource leaks. Docker's API can be found at `docker-py`_. .. _docker-py: https://docker-py.readthedocs.io/en/stable/ In order to use ``dockerCall``, your installation of Docker must be set up to run without ``sudo``. Instructions for setting this up can be found here_. .. _here: https://docs.docker.com/engine/installation/linux/ubuntulinux/#/create-a-docker-group An example of a basic ``dockerCall`` is below:: dockerCall(job=job, tool='quay.io/ucsc_cgl/bwa', workDir=job.tempDir, parameters=['index', '/data/reference.fa']) Note the assumption that `reference.fa` file is located in `/data`. This is Toil's standard convention as a mount location to reduce boilerplate when calling `dockerCall`. Users can choose their own mount locations by supplying a `volumes` kwarg to `dockerCall`, such as: `volumes={working_dir: {'bind': '/data', 'mode': 'rw'}}`, where `working_dir` is an absolute path on the user's filesystem. ``dockerCall`` can also be added to workflows like any other job function: .. literalinclude:: ../../src/toil/test/docs/scripts/tutorial_docker.py `cgl-docker-lib`_ contains ``dockerCall``-compatible Dockerized tools that are commonly used in bioinformatics analysis. .. _cgl-docker-lib: https://github.com/BD2KGenomics/cgl-docker-lib/blob/master/README.md The documentation provides guidelines for developing your own Docker containers that can be used with Toil and ``dockerCall``. In order for a container to be compatible with ``dockerCall``, it must have an ``ENTRYPOINT`` set to a wrapper script, as described in cgl-docker-lib containerization standards. This can be set by passing in the optional keyword argument, 'entrypoint'. Example: entrypoint=["/bin/bash","-c"] dockerCall supports currently the 75 keyword arguments found in the python `Docker API`_, under the 'run' command. .. _Docker API: https://docker-py.readthedocs.io/en/stable/containers.html .. _service-dev-ref: Services -------- It is sometimes desirable to run *services*, such as a database or server, concurrently with a workflow. The :class:`toil.job.Job.Service` class provides a simple mechanism for spawning such a service within a Toil workflow, allowing precise specification of the start and end time of the service, and providing start and end methods to use for initialization and cleanup. The following simple, conceptual example illustrates how services work: .. literalinclude:: ../../src/toil/test/docs/scripts/tutorial_services.py In this example the DemoService starts a database in the start method, returning an object from the start method indicating how a client job would access the database. The service's stop method cleans up the database, while the service's check method is polled periodically to check the service is alive. A DemoService instance is added as a service of the root job ``j``, with resource requirements specified. The return value from :func:`toil.job.Job.addService` is a promise to the return value of the service's start method. When the promised is fulfilled it will represent how to connect to the database. The promise is passed to a child job of ``j``, which uses it to make a database connection. The services of a job are started before any of its successors have been run and stopped after all the successors of the job have completed successfully. Multiple services can be created per job, all run in parallel. Additionally, services can define sub-services using :func:`toil.job.Job.Service.addChild`. This allows complex networks of services to be created, e.g. Apache Spark clusters, within a workflow. .. _checkpoints: Checkpoints ----------- Services complicate resuming a workflow after failure, because they can create complex dependencies between jobs. For example, consider a service that provides a database that multiple jobs update. If the database service fails and loses state, it is not clear that just restarting the service will allow the workflow to be resumed, because jobs that created that state may have already finished. To get around this problem Toil supports *checkpoint* jobs, specified as the boolean keyword argument ``checkpoint`` to a job or wrapped function, e.g.:: j = Job(checkpoint=True) A checkpoint job is rerun if one or more of its successors fails its retry attempts, until it itself has exhausted its retry attempts. Upon restarting a checkpoint job all its existing successors are first deleted, and then the job is rerun to define new successors. By checkpointing a job that defines a service, upon failure of the service the database and the jobs that access the service can be redefined and rerun. To make the implementation of checkpoint jobs simple, a job can only be a checkpoint if when first defined it has no successors, i.e. it can only define successors within its run method. Encapsulation ------------- Let ``A`` be a root job potentially with children and follow-ons. Without an encapsulated job the simplest way to specify a job ``B`` which runs after ``A`` and all its successors is to create a parent of ``A``, call it ``Ap``, and then make ``B`` a follow-on of ``Ap``. e.g.: .. literalinclude:: ../../src/toil/test/docs/scripts/tutorial_encapsulation.py An *encapsulated job* ``E(A)`` of ``A`` saves making ``Ap``, instead we can write: .. literalinclude:: ../../src/toil/test/docs/scripts/tutorial_encapsulation2.py Note the call to :func:`toil.job.Job.encapsulate` creates the :class:`toil.job.Job.EncapsulatedJob`. .. _depending_on_toil: Depending on Toil ----------------- If you are packing your workflow(s) as a pip-installable distribution on PyPI, you might be tempted to declare Toil as a dependency in your ``setup.py``, via the ``install_requires`` keyword argument to ``setup()``. Unfortunately, this does not work, for two reasons: For one, Toil uses Setuptools' *extra* mechanism to manage its own optional dependencies. If you explicitly declared a dependency on Toil, you would have to hard-code a particular combination of extras (or no extras at all), robbing the user of the choice what Toil extras to install. Secondly, and more importantly, declaring a dependency on Toil would only lead to Toil being installed on the leader node of a cluster, but not the worker nodes. Auto-deployment does not work here because Toil cannot auto-deploy itself, the classic "Which came first, chicken or egg?" problem. In other words, you shouldn't explicitly depend on Toil. Document the dependency instead (as in "This workflow needs Toil version X.Y.Z to be installed") and optionally add a version check to your ``setup.py``. Refer to the ``check_version()`` function in the ``toil-lib`` project's `setup.py`_ for an example. Alternatively, you can also just depend on ``toil-lib`` and you'll get that check for free. .. _setup.py: https://github.com/BD2KGenomics/toil-lib/blob/master/setup.py If your workflow depends on a dependency of Toil, consider not making that dependency explicit either. If you do, you risk a version conflict between your project and Toil. The ``pip`` utility may silently ignore that conflict, breaking either Toil or your workflow. It is safest to simply assume that Toil installs that dependency for you. The only downside is that you are locked into the exact version of that dependency that Toil declares. But such is life with Python, which, unlike Java, has no means of dependencies belonging to different software components within the same process, and whose favored software distribution utility is `incapable`_ of properly resolving overlapping dependencies and detecting conflicts. .. _incapable: https://github.com/pypa/pip/issues/988 Best Practices for Dockerizing Toil Workflows --------------------------------------------- `Computational Genomics Lab`_'s `Dockstore`_ based production system provides workflow authors a way to run Dockerized versions of their pipeline in an automated, scalable fashion. To be compatible with this system of a workflow should meet the following requirements. In addition to the Docker container, a common workflow language `descriptor file`_ is needed. For inputs: * Only command line arguments should be used for configuring the workflow. If the workflow relies on a configuration file, like `Toil-RNAseq`_ or `ProTECT`_, a wrapper script inside the Docker container can be used to parse the CLI and generate the necessary configuration file. * All inputs to the pipeline should be explicitly enumerated rather than implicit. For example, don't rely on one FASTQ read's path to discover the location of its pair. This is necessary since all inputs are mapped to their own isolated directories when the Docker is called via Dockstore. * All inputs must be documented in the CWL descriptor file. Examples of this file can be seen in both `Toil-RNAseq`_ and `ProTECT`_. For outputs: * All outputs should be written to a local path rather than S3. * Take care to package outputs in a local and user-friendly way. For example, don't tar up all output if there are specific files that will care to see individually. * All output file names should be deterministic and predictable. For example, don't prepend the name of an output file with PASS/FAIL depending on the outcome of the pipeline. * All outputs must be documented in the CWL descriptor file. Examples of this file can be seen in both `Toil-RNAseq`_ and `ProTECT`_. .. _descriptor file: https://dockstore.org/docs/getting-started-with-cwl .. _Computational Genomics Lab: https://cgl.genomics.ucsc.edu/ .. _Dockstore: https://dockstore.org/docs .. _Toil-RNAseq: https://github.com/BD2KGenomics/toil-rnaseq .. _ProTECT: https://github.com/BD2KGenomics/protect toil-releases-3.24.0/docs/developingWorkflows/toilAPI.rst000066400000000000000000000002111362134276200234050ustar00rootroot00000000000000.. _api: Toil Class API ************** The Toil class configures and starts a Toil run. .. autoclass:: toil.common::Toil :members: toil-releases-3.24.0/docs/developingWorkflows/toilAPIBatchsystem.rst000066400000000000000000000031031362134276200256170ustar00rootroot00000000000000.. highlight:: bash .. _batchSystemInterface: Batch System API ================ The batch system interface is used by Toil to abstract over different ways of running batches of jobs, for example Slurm, GridEngine, Mesos, Parasol and a single node. The :class:`toil.batchSystems.abstractBatchSystem.AbstractBatchSystem` API is implemented to run jobs using a given job management system, e.g. Mesos. Batch System Enivronmental Variables ------------------------------------ Environmental variables allow passing of scheduler specific parameters. For SLURM:: export TOIL_SLURM_ARGS="-t 1:00:00 -q fatq" For TORQUE there are two environment variables - one for everything but the resource requirements, and another - for resources requirements (without the `-l` prefix):: export TOIL_TORQUE_ARGS="-q fatq" export TOIL_TORQUE_REQS="walltime=1:00:00" For GridEngine (SGE, UGE), there is an additional environmental variable to define the `parallel environment `_ for running multicore jobs:: export TOIL_GRIDENGINE_PE='smp' export TOIL_GRIDENGINE_ARGS='-q batch.q' For HTCondor, additional parameters can be included in the submit file passed to condor_submit:: export TOIL_HTCONDOR_PARAMS='requirements = TARGET.has_sse4_2 == true; accounting_group = test' The environment variable is parsed as a semicolon-separated string of ``parameter = value`` pairs. Batch System API ---------------- .. autoclass:: toil.batchSystems.abstractBatchSystem::AbstractBatchSystem :members: toil-releases-3.24.0/docs/developingWorkflows/toilAPIExceptions.rst000066400000000000000000000012201362134276200254500ustar00rootroot00000000000000.. _api-exceptions: Exceptions API ************** Toil specific exceptions. .. autoexception:: toil.job::JobException :members: .. autoexception:: toil.job::JobGraphDeadlockException :members: .. autoexception:: toil.jobStores.abstractJobStore::ConcurrentFileModificationException :members: .. autoexception:: toil.jobStores.abstractJobStore::JobStoreExistsException :members: .. autoexception:: toil.jobStores.abstractJobStore::NoSuchFileException :members: .. autoexception:: toil.jobStores.abstractJobStore::NoSuchJobException :members: .. autoexception:: toil.jobStores.abstractJobStore::NoSuchJobStoreException :members: toil-releases-3.24.0/docs/developingWorkflows/toilAPIFilestore.rst000066400000000000000000000004101362134276200252630ustar00rootroot00000000000000.. _api-filestore: job.fileStore API ***************** The AbstractFileStore is an abstraction of a Toil run's shared storage. .. autoclass:: toil.fileStores.abstractFileStore::AbstractFileStore :members: .. autoclass:: toil.fileStores::FileID :members: toil-releases-3.24.0/docs/developingWorkflows/toilAPIJobFunctions.rst000066400000000000000000000014731362134276200257440ustar00rootroot00000000000000.. _api-jobfunctions: Toil Job API ************ Functions to wrap jobs and return values (promises). FunctionWrappingJob ------------------- The subclass of Job for wrapping user functions. .. autoclass:: toil.job::FunctionWrappingJob :members: JobFunctionWrappingJob ---------------------- The subclass of FunctionWrappingJob for wrapping user job functions. .. autoclass:: toil.job::JobFunctionWrappingJob :members: EncapsulatedJob --------------- The subclass of Job for *encapsulating* a job, allowing a subgraph of jobs to be treated as a single job. .. autoclass:: toil.job::EncapsulatedJob :members: Promise ------- The class used to reference return values of jobs/services not yet run/started. .. autoclass:: toil.job::Promise :members: .. autoclass:: toil.job::PromisedRequirement :members: toil-releases-3.24.0/docs/developingWorkflows/toilAPIJobstore.rst000066400000000000000000000006771362134276200251350ustar00rootroot00000000000000.. _jobStoreInterface: Job Store API ============= The job store interface is an abstraction layer that that hides the specific details of file storage, for example standard file systems, S3, etc. The :class:`~toil.jobStores.abstractJobStore.AbstractJobStore` API is implemented to support a give file store, e.g. S3. Implement this API to support a new file store. .. autoclass:: toil.jobStores.abstractJobStore::AbstractJobStore :members: toil-releases-3.24.0/docs/developingWorkflows/toilAPIMethods.rst000066400000000000000000000002431362134276200247360ustar00rootroot00000000000000.. _api-methods: Job Methods API *************** Jobs are the units of work in Toil which are composed into workflows. .. autoclass:: toil.job.Job :members: toil-releases-3.24.0/docs/developingWorkflows/toilAPIRunner.rst000066400000000000000000000002541362134276200246060ustar00rootroot00000000000000.. _api-runner: Job.Runner API ************** The Runner contains the methods needed to configure and start a Toil run. .. autoclass:: toil.job::Job.Runner :members: toil-releases-3.24.0/docs/developingWorkflows/toilAPIService.rst000066400000000000000000000002731362134276200247360ustar00rootroot00000000000000.. _api-service: Job.Service API *************** The Service class allows databases and servers to be spawned within a Toil workflow. .. autoclass:: toil.job::Job.Service :members: toil-releases-3.24.0/docs/gettingStarted/000077500000000000000000000000001362134276200202765ustar00rootroot00000000000000toil-releases-3.24.0/docs/gettingStarted/googleScreenShot.png000066400000000000000000001425031362134276200242630ustar00rootroot00000000000000‰PNG  IHDRÏÞ$†§ ¯iCCPICC ProfileH‰•–TSiÇ¿÷Ò" %ôŽtH¯”^m„H(1‚€]Á± "6t¨ ŽJ‘± ‚X±È  ®ƒPQÙ,ag÷ìîÙÿ;7ïwnî»ïÿ¾÷¾s.ä‘(¦"L{»1#£¢™¸çr€ d€ ‡›*r ôˆæÎÕø}¤Ñ]“é^ÿþÿ•/.• ˆp,/•›‚ðy$.sEâ4PH­µi¢i.D˜.F "|jšf¹yšcgùÞLMh°;ÂÃàÉŽ8ÒG$ÏLç& }Èt„Í„<a„¸|ál„SRVOó„õcÿ©OÂ_zÆJ{r8 Rž}–á=©¢dNæÿ¹ÿ[)É’¹{h"Aæ‹}‚‘3Y³Š¤Õ~RÆ. ˜co¦~†ùŸ°9榺GÏ1ãá7Ç’¤0×9æˆç¯¤±CçX¼:XÚ_˜¼Ô_Ú?Ž-å¸TÏ9Žx±ç8‹1Çé‚ð¥sœšâ7_ã.Í‹%ÁRÏñb/é3¦¤Î{ãræï•Æõ™÷)õËóð”æ…aÒzQš›´§(9pÞ²·4Ÿš"½6 ùÀæ8‘ã8ß'Pº>Àxä`‚@`æÀ ®Òâ2¦¿ià¾Z”)$ðÓ˜®È®‰c²…\Sc¦…™9 €é=8ûŠ?<˜Ù[?Ÿã·`ÝŠ$çsñûhG¶Sö|Noò^4ïáJÄé³9ôô, % ´€>0AÜÙà‚8ö D•€ ø ˆÁZ°l9 ì@8 N€ pœ à"¸ ®ƒÛ  ô‚Ç  ×`ŒƒI‚p¢AJ:¤A r‚è04½½½]„®@×£[ÑwÑèQôw £‚1ÂØcؘHLf-&S€)ÃÔaÚ0½˜!Ì8‹e`õ°¶Xl6»»{[‹mÆvc±c8N g„sÄà8¸4\îîî ®7„û„'áÕñx/|4^ˆßŠ/ÀWá/ã{ð/ñ“*A‡`O ð™„Ý„“„&ÂÂa’(GÔ#:C‰‰Ä-ÄBb ±ø„øD"i’ìHA$i3©t†tƒ4@úL–'’ÝÉËÉò.r9¹™üüB¡èR\(Ñ”4Ê.J%ååå“ MÆT†-ÓÙ$S,S/Ó#óV– «#ë*»R6K¶@öœìÙ7TU—êNåP7R‹©¨}Ô19šœ¹\€\ŠÜN¹*¹›rÃò8y]yOyž|¶ü ùkòƒ4M‹æNãÒ¶ÑNÒÚhCt,]Φ'Òóè§éôQy+…p… …b…K ý C—Áf$3v3Î2î3¾,P]ຠnÁŽ5 zL(.TtQŒSÌU¬UìUü¢ÄTòTJRÚ«Ô ôT­l¨¤¼Vùˆr›ò›…ô… ¹ sž]øHV1T VY§rB¥CeLUMÕ[U¤zHõšê5†š‹Z¢Ú~µËj#ê4u'uú~õ+ꯘ LWf2³ÙÊÕPÑðÑh×èÔ˜ÔÔÓ ÓܪY«ùT‹¨ÅÒŠ×Ú¯Õ¢5ª­®½D{½vµö#‚K‡¯sP§]gBWO7Bw»nƒî°ž¢[/K¯Zï‰>EßY~©þ=¬Ë Éà°A—!lhmÈ7,6¼cÙ ŒucŒíŒ…Æ¥Æ}&dW“t“j“S†©¿éVÓÓ·‹´E/Ú»¨}Ñw3k³d³“fÍåÍ}Í·š7™¿·0´àZ[ܳ¤XzYn²l´|gedguÄê5Íz‰õvëëo6¶6b››[mÛÛÛ>ÈÚɺa‡±s³ÛdwÑî³½}šýYû?L’ª†ë-Ž[|rñ £¦#Çñ¸c¿Ó)Æé˜S¿³†3ǹÔù¹‹– Ï¥Ì奫k¢ë)×·nfnb·:· w{÷ îÍ(o\NOyÏ0Ï"Ïg^š^ ^Õ^£ÞÖÞë¼›}0>~>{}úتl.»’=êkë»Á·ÕìâWä÷ÜßÐ_ìß´^â»dß’'Ku– —6€vÀ¾€§zk ½6^ÜB YR2êº;ôq˜~˜$¬%\6|yxeøD„GD~Dä¢È ‘·£”£QѸèðè²è±ežË,Zn½-*2ÿ;dáçv—:¶ü‹þ»‹Ó°ú= iTXtXML:com.adobe.xmp 526 463 1 íu—ê@IDATxì¸U÷ÆÝ R"*" ‚J|b+6"¨ØÝØØñ7ñ³1ÐT±¥¤K:ï~÷qî¹'ï½çÜsÏ}×óœ33{v¾3³ß½Ö^³§Ò¸qã L"„€B@¤Œ@¥Oy¦ —" ! „€0«,„€B@ôy¦‡—b ! „€æ©{@! „@ºHóL1ÅB@ €È³Âß@! 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" " "PþxÝRà ã ˜l뀧r¾8ω¼³¯¿«þòåËqÕUW¡N:¦;]ºt1ÿ+¯¼Ò¬¼'$$Ë-Mš41yíÛ·Ï×õÐÐPp¥ž+ù´0Ø©ÿþŽUöV­Z™~8[XŽ¢…–Z ÂÂÂÀv¯@ë‚mU¸í¶Û †9sæ‹EûNÑQ©R%ójÓ¦ 6lØ`¬÷ðáÃí:4_ŒÃÞ½{u„çi`¢(HII1/¶M±pìØ1“§D@D@D@D@Ê'Re 'ÛíÚµst‰±÷ß¿ã3'Ç\1çÛNqqqæ«îtëáĸJ•*8xð .ºè"»X¡ïÎnF ö ¿ó…\½¯W¯žöùÞ½{›C{ÕßµZØ'Š‡™3gÚ—™÷ØØX$%%™Ý•š6mêÈ»ä’KÇ<øì³ÏŒè`y;…‡‡‹]žhuhÛ¶- dgë]D@D@D@D ð¹(°-6+ûsY°Ø}r}‰‰A=pà 7¸f×™èèhŒ1Âäýë_ÿÂÉ“'Ï)w!'(@è”››ë° pg$®þ”Ø/ŠÆg4oÞ<_Q{»U [p{SZI*W®lÊÞxã  ûÐsÏ=gÚãuŒ ËËSLž</¿ür¾úõAD@D@D@D üðzLAùAṧ:ty÷íÛg ÑÕˆacâ×èRà ;ã'ÀUzw‰“ôâlAÊ =Ý/^lÚa?FŽYh]t5âJþüùóM€ô™3g°hÑ"ãZÄ<º±NŠZ8ñgP±è.ňÆãõ×_¯§86l˜y§X¢‹-ÌS(Ÿ|n)°-åÁB`ßRîæCWòÒoŸ“ûGyÄd3&€·<ð€9ß°aÃsv[²ëéܹ3^}õU#.¸Ò^ÔDáÁÕ~NÌçÍ›g¬tobà±í>ä©.Æð:Æ°žF1L¬ƒPã$Ÿî<Ôµk×sªbO=õ” ªfüÝ­XMaAap×]w³ÛÒ9•è„ˆ€ˆ€ˆ€ˆ@™%ðÿ™w¥íÔ§"IEND®B`‚toil-releases-3.24.0/docs/gettingStarted/install.rst000066400000000000000000000206441362134276200225040ustar00rootroot00000000000000 .. highlight:: console .. _installation-ref: Installation ============ This document describes how to prepare for and install Toil. Note that Toil requires that the user run all commands inside of a Python `virtualenv`_. Instructions for installing and creating a Python virtual environment are provided below. .. _virtualenv: https://virtualenv.pypa.io/en/stable/ .. _venvPrep: Preparing Your Python Runtime Environment ----------------------------------------- Toil currently supports Python 2.7, 3.5, and 3.6, and requires a virtualenv to be active to install. If not already present, please install the latest Python ``virtualenv`` using pip_:: $ sudo pip install virtualenv And create a virtual environment called ``venv`` in your home directory:: $ virtualenv ~/venv .. _pip: https://pip.readthedocs.io/en/latest/installing/ If the user does not have root privileges, there are a few more steps, but one can download a specific virtualenv package directly, untar the file, create, and source the virtualenv (version 15.1.0 as an example) using :: $ curl -O https://pypi.python.org/packages/d4/0c/9840c08189e030873387a73b90ada981885010dd9aea134d6de30cd24cb8/virtualenv-15.1.0.tar.gz $ tar xvfz virtualenv-15.1.0.tar.gz $ cd virtualenv-15.1.0 $ python virtualenv.py ~/venv Now that you've created your virtualenv, activate your virtual environment:: $ source ~/venv/bin/activate Basic Installation ------------------ If you need only the basic version of Toil, it can be easily installed using pip:: $ pip install toil Now you're ready to run :ref:`your first Toil workflow `! (If you need any of the extra features don't do this yet and instead skip to the next section.) .. _extras: Installing Toil with Extra Features ----------------------------------- .. _python-dev: .. topic:: Python headers and static libraries Needed for the ``mesos``, ``aws``, ``google``, and ``encryption`` extras. On Ubuntu:: $ sudo apt-get install build-essential python-dev On macOS:: $ xcode-select --install .. _libffi-dev: .. topic:: Encryption specific headers and library Needed for the ``encryption`` extra. On Ubuntu:: $ sudo apt-get install libssl-dev libffi-dev On macOS:: $ brew install libssl libffi Or see `Cryptography`_ for other systems. Some optional features, called *extras*, are not included in the basic installation of Toil. To install Toil with all its bells and whistles, first install any necessary headers and libraries (`python-dev`_, `libffi-dev`_). Then run :: $ pip install toil[aws,mesos,google,encryption,cwl] or :: $ pip install toil[all] Here's what each extra provides: +----------------+------------------------------------------------------------+ | Extra | Description | +================+============================================================+ | ``all`` | Installs all extras (though htcondor is linux-only and | | | will be skipped if not on a linux computer). | +----------------+------------------------------------------------------------+ | ``aws`` | Provides support for managing a cluster on Amazon Web | | | Service (`AWS`_) using Toil's built in :ref:`clusterRef`. | | | Clusters can scale up and down automatically. | | | It also supports storing workflow state. | +----------------+------------------------------------------------------------+ | ``google`` | Experimental. Stores workflow state in `Google Cloud | | | Storage`_. | +----------------+------------------------------------------------------------+ | ``mesos`` | Provides support for running Toil on an `Apache Mesos`_ | | | cluster. Note that running Toil on other batch systems | | | does not require an extra. The ``mesos`` extra requires | | | the following native dependencies: | | | | | | * `Apache Mesos`_ (Tested with Mesos v1.0.0) | | | * :ref:`Python headers and static libraries ` | | | | | | .. important:: | | | If launching toil remotely on a mesos instance, | | | to install Toil with the ``mesos`` extra in a | | | virtualenv, be sure to create that virtualenv with the | | | ``--system-site-packages`` flag (only use remotely!):: | | | | | | $ virtualenv ~/venv --system-site-packages | | | | | | Otherwise, you'll see something like this: | | | | | | .. code-block:: python | | | | | | ImportError: No module named mesos.native | | | | +----------------+------------------------------------------------------------+ | ``htcondor`` | Support for the htcondor batch system. This currently is | | | a linux only extra. | +----------------+------------------------------------------------------------+ | ``encryption`` | Provides client-side encryption for files stored in the | | | AWS job store. This extra requires the | | | following native dependencies: | | | | | | * :ref:`Python headers and static libraries ` | | | * :ref:`libffi headers and library ` | +----------------+------------------------------------------------------------+ | ``cwl`` | Provides support for running workflows written using the | | | `Common Workflow Language`_. | +----------------+------------------------------------------------------------+ | ``wdl`` | Provides support for running workflows written using the | | | `Workflow Description Language`_. This extra has no native | | | dependencies. | +----------------+------------------------------------------------------------+ .. _AWS: https://aws.amazon.com/ .. _Apache Mesos: https://mesos.apache.org/gettingstarted/ .. _Google Cloud Storage: https://cloud.google.com/storage/ .. _Workflow Description Language: https://software.broadinstitute.org/wdl/ .. _Cryptography: https://cryptography.io/en/latest/installation/ .. _Homebrew: http://brew.sh/ .. _buildFromSource: Building from Source -------------------- If developing with Toil, you will need to build from source. This allows changes you make to Toil to be reflected immediately in your runtime environment. First, clone the source:: $ git clone https://github.com/DataBiosphere/toil.git $ cd toil Then, create and activate a virtualenv:: $ virtualenv venv $ . venv/bin/activate From there, you can list all available Make targets by running ``make``. First and foremost, we want to install Toil's build requirements (these are additional packages that Toil needs to be tested and built but not to be run):: $ make prepare Now, we can install Toil in development mode (such that changes to the source code will immediately affect the virtualenv):: $ make develop Or, to install with support for all optional :ref:`extras`:: $ make develop extras=[aws,mesos,google,encryption,cwl] Or:: $ make develop extras=[all] To build the docs, run ``make develop`` with all extras followed by :: $ make docs To run a quick batch of tests (this should take less than 30 minutes) run :: $ export TOIL_TEST_QUICK=True; make test For more information on testing see :ref:`runningTests`. toil-releases-3.24.0/docs/gettingStarted/quickStart.rst000066400000000000000000000632651362134276200231760ustar00rootroot00000000000000.. _running: Quickstart Examples =================== .. _quickstart: Running a basic workflow ------------------------ A Toil workflow can be run with just three steps: 1. Install Toil (see :ref:`installation-ref`) 2. Copy and paste the following code block into a new file called ``helloWorld.py``: .. literalinclude:: ../../src/toil/test/docs/scripts/tutorial_helloworld.py 3. Specify the name of the :ref:`job store ` and run the workflow:: (venv) $ python helloWorld.py file:my-job-store .. note:: Don't actually type ``(venv) $`` in at the beginning of each command. This is intended only to remind the user that they should have their :ref:`virtual environment ` running. Congratulations! You've run your first Toil workflow using the default :ref:`Batch System `, ``singleMachine``, using the ``file`` job store. Toil uses batch systems to manage the jobs it creates. The ``singleMachine`` batch system is primarily used to prepare and debug workflows on a local machine. Once validated, try running them on a full-fledged batch system (see :ref:`batchsysteminterface`). Toil supports many different batch systems such as `Apache Mesos`_ and Grid Engine; its versatility makes it easy to run your workflow in all kinds of places. Toil is totally customizable! Run ``python helloWorld.py --help`` to see a complete list of available options. For something beyond a "Hello, world!" example, refer to :ref:`runningDetail`. .. _Apache Mesos: https://mesos.apache.org/getting-started/ .. _cwlquickstart: Running a basic CWL workflow ---------------------------- The `Common Workflow Language`_ (CWL) is an emerging standard for writing workflows that are portable across multiple workflow engines and platforms. Running CWL workflows using Toil is easy. #. First ensure that Toil is installed with the ``cwl`` extra (see :ref:`extras`):: (venv) $ pip install 'toil[cwl]' This installs the ``toil-cwl-runner`` and ``cwltoil`` executables. #. Copy and paste the following code block into ``example.cwl``: .. code-block:: yaml cwlVersion: v1.0 class: CommandLineTool baseCommand: echo stdout: output.txt inputs: message: type: string inputBinding: position: 1 outputs: output: type: stdout and this code into ``example-job.yaml``: .. code-block:: yaml message: Hello world! #. To run the workflow simply enter :: (venv) $ toil-cwl-runner example.cwl example-job.yaml Your output will be in ``output.txt``:: (venv) $ cat output.txt Hello world! To learn more about CWL, see the `CWL User Guide`_ (from where this example was shamelessly borrowed). To run this workflow on an AWS cluster have a look at :ref:`awscwl`. For information on using CWL with Toil see the section :ref:`cwl` .. _CWL User Guide: https://www.commonwl.org/user_guide/ Running a basic WDL workflow ---------------------------- The `Workflow Description Language`_ (WDL) is another emerging language for writing workflows that are portable across multiple workflow engines and platforms. Running WDL workflows using Toil is still in alpha, and currently experimental. Toil currently supports basic workflow syntax (see :ref:`wdl` for more details and examples). Here we go over running a basic WDL helloworld workflow. #. First ensure that Toil is installed with the ``wdl`` extra (see :ref:`extras`):: (venv) $ pip install 'toil[wdl]' This installs the ``toil-wdl-runner`` executable. #. Copy and paste the following code block into ``wdl-helloworld.wdl``:: workflow write_simple_file { call write_file } task write_file { String message command { echo ${message} > wdl-helloworld-output.txt } output { File test = "wdl-helloworld-output.txt" } } and this code into ``wdl-helloworld.json``:: { "write_simple_file.write_file.message": "Hello world!" } #. To run the workflow simply enter :: (venv) $ toil-wdl-runner wdl-helloworld.wdl wdl-helloworld.json Your output will be in ``wdl-helloworld-output.txt``:: (venv) $ cat wdl-helloworld-output.txt Hello world! To learn more about WDL, see the main `WDL website`_ . .. _WDL website: https://software.broadinstitute.org/wdl/ .. _Workflow Description Language: https://software.broadinstitute.org/wdl/ .. _runningDetail: A (more) real-world example --------------------------- For a more detailed example and explanation, we've developed a sample pipeline that merge-sorts a temporary file. This is not supposed to be an efficient sorting program, rather a more fully worked example of what Toil is capable of. .. _sortExample: Running the example ~~~~~~~~~~~~~~~~~~~ #. Download :download:`the example code <../../src/toil/test/sort/sort.py>` #. Run it with the default settings:: (venv) $ python sort.py file:jobStore The workflow created a file called ``sortedFile.txt`` in your current directory. Have a look at it and notice that it contains a whole lot of sorted lines! This workflow does a smart merge sort on a file it generates, ``fileToSort.txt``. The sort is *smart* because each step of the process---splitting the file into separate chunks, sorting these chunks, and merging them back together---is compartmentalized into a **job**. Each job can specify its own resource requirements and will only be run after the jobs it depends upon have run. Jobs without dependencies will be run in parallel. .. note:: Delete ``fileToSort.txt`` before moving on to #3. This example introduces options that specify dimensions for ``fileToSort.txt``, if it does not already exist. If it exists, this workflow will use the existing file and the results will be the same as #2. 3. Run with custom options:: (venv) $ python sort.py file:jobStore --numLines=5000 --lineLength=10 --overwriteOutput=True --workDir=/tmp/ Here we see that we can add our own options to a Toil script. As noted above, the first two options, ``--numLines`` and ``--lineLength``, determine the number of lines and how many characters are in each line. ``--overwriteOutput`` causes the current contents of ``sortedFile.txt`` to be overwritten, if it already exists. The last option, ``--workDir``, is an option built into Toil to specify where temporary files unique to a job are kept. Describing the source code ~~~~~~~~~~~~~~~~~~~~~~~~~~ To understand the details of what's going on inside. Let's start with the ``main()`` function. It looks like a lot of code, but don't worry---we'll break it down piece by piece. .. literalinclude:: ../../src/toil/test/sort/sort.py :pyobject: main First we make a parser to process command line arguments using the `argparse`_ module. It's important that we add the call to :func:`Job.Runner.addToilOptions` to initialize our parser with all of Toil's default options. Then we add the command line arguments unique to this workflow, and parse the input. The help message listed with the arguments should give you a pretty good idea of what they can do. Next we do a little bit of verification of the input arguments. The option ``--fileToSort`` allows you to specify a file that needs to be sorted. If this option isn't given, it's here that we make our own file with the call to :func:`makeFileToSort`. Finally we come to the context manager that initializes the workflow. We create a path to the input file prepended with ``'file://'`` as per the documentation for :func:`toil.common.Toil` when staging a file that is stored locally. Notice that we have to check whether or not the workflow is restarting so that we don't import the file more than once. Finally we can kick off the workflow by calling :func:`toil.common.Toil.start` on the job ``setup``. When the workflow ends we capture its output (the sorted file's fileID) and use that in :func:`toil.common.Toil.exportFile` to move the sorted file from the job store back into "userland". Next let's look at the job that begins the actual workflow, ``setup``. .. literalinclude:: ../../src/toil/test/sort/sort.py :pyobject: setup ``setup`` really only does two things. First it writes to the logs using :func:`Job.log` and then calls :func:`addChildJobFn`. Child jobs run directly after the current job. This function turns the 'job function' ``down`` into an actual job and passes in the inputs including an optional resource requirement, ``memory``. The job doesn't actually get run until the call to :func:`Job.rv`. Once the job ``down`` finishes, its output is returned here. Now we can look at what ``down`` does. .. literalinclude:: ../../src/toil/test/sort/sort.py :pyobject: down Down is the recursive part of the workflow. First we read the file into the local filestore by calling :func:`job.fileStore.readGlobalFile`. This puts a copy of the file in the temp directory for this particular job. This storage will disappear once this job ends. For a detailed explanation of the filestore, job store, and their interfaces have a look at :ref:`managingFiles`. Next ``down`` checks the base case of the recursion: is the length of the input file less than ``N`` (remember ``N`` was an option we added to the workflow in ``main``)? In the base case, we just sort the file, and return the file ID of this new sorted file. If the base case fails, then the file is split into two new tempFiles using :func:`job.fileStore.getLocalTempFile` and the helper function ``copySubRangeOfFile``. Finally we add a follow on Job ``up`` with :func:`job.addFollowOnJobFn`. We've already seen child jobs. A follow-on Job is a job that runs after the current job and *all* of its children (and their children and follow-ons) have completed. Using a follow-on makes sense because ``up`` is responsible for merging the files together and we don't want to merge the files together until we *know* they are sorted. Again, the return value of the follow-on job is requested using :func:`Job.rv`. Looking at ``up`` .. literalinclude:: ../../src/toil/test/sort/sort.py :pyobject: up we see that the two input files are merged together and the output is written to a new file using :func:`job.fileStore.writeGlobalFileStream`. After a little cleanup, the output file is returned. Once the final ``up`` finishes and all of the ``rv()`` promises are fulfilled, ``main`` receives the sorted file's ID which it uses in ``exportFile`` to send it to the user. There are other things in this example that we didn't go over such as :ref:`checkpoints` and the details of much of the :ref:`api`. .. _argparse: https://docs.python.org/2.7/library/argparse.html At the end of the script the lines .. code-block:: python if __name__ == '__main__' main() are included to ensure that the main function is only run once in the '__main__' process invoked by you, the user. In Toil terms, by invoking the script you created the *leader process* in which the ``main()`` function is run. A *worker process* is a separate process whose sole purpose is to host the execution of one or more jobs defined in that script. In any Toil workflow there is always one leader process, and potentially many worker processes. When using the single-machine batch system (the default), the worker processes will be running on the same machine as the leader process. With full-fledged batch systems like Mesos the worker processes will typically be started on separate machines. The boilerplate ensures that the pipeline is only started once---on the leader---but not when its job functions are imported and executed on the individual workers. Typing ``python sort.py --help`` will show the complete list of arguments for the workflow which includes both Toil's and ones defined inside ``sort.py``. A complete explanation of Toil's arguments can be found in :ref:`commandRef`. Logging ~~~~~~~ By default, Toil logs a lot of information related to the current environment in addition to messages from the batch system and jobs. This can be configured with the ``--logLevel`` flag. For example, to only log ``CRITICAL`` level messages to the screen:: (venv) $ python sort.py file:jobStore --logLevel=critical --overwriteOutput=True This hides most of the information we get from the Toil run. For more detail, we can run the pipeline with ``--logLevel=debug`` to see a comprehensive output. For more information, see :ref:`workflowOptions`. Error Handling and Resuming Pipelines ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ With Toil, you can recover gracefully from a bug in your pipeline without losing any progress from successfully completed jobs. To demonstrate this, let's add a bug to our example code to see how Toil handles a failure and how we can resume a pipeline after that happens. Add a bad assertion at line 52 of the example (the first line of ``down()``): .. code-block:: python def down(job, inputFileStoreID, N, downCheckpoints, memory=sortMemory): ... assert 1 == 2, "Test error!" When we run the pipeline, Toil will show a detailed failure log with a traceback:: (venv) $ python sort.py file:jobStore ... ---TOIL WORKER OUTPUT LOG--- ... m/j/jobonrSMP Traceback (most recent call last): m/j/jobonrSMP File "toil/src/toil/worker.py", line 340, in main m/j/jobonrSMP job._runner(jobGraph=jobGraph, jobStore=jobStore, fileStore=fileStore) m/j/jobonrSMP File "toil/src/toil/job.py", line 1270, in _runner m/j/jobonrSMP returnValues = self._run(jobGraph, fileStore) m/j/jobonrSMP File "toil/src/toil/job.py", line 1217, in _run m/j/jobonrSMP return self.run(fileStore) m/j/jobonrSMP File "toil/src/toil/job.py", line 1383, in run m/j/jobonrSMP rValue = userFunction(*((self,) + tuple(self._args)), **self._kwargs) m/j/jobonrSMP File "toil/example.py", line 30, in down m/j/jobonrSMP assert 1 == 2, "Test error!" m/j/jobonrSMP AssertionError: Test error! If we try and run the pipeline again, Toil will give us an error message saying that a job store of the same name already exists. By default, in the event of a failure, the job store is preserved so that the workflow can be restarted, starting from the previously failed jobs. We can restart the pipeline by running :: (venv) $ python sort.py file:jobStore --restart --overwriteOutput=True We can also change the number of times Toil will attempt to retry a failed job:: (venv) $ python sort.py file:jobStore --retryCount 2 --restart --overwriteOutput=True You'll now see Toil attempt to rerun the failed job until it runs out of tries. ``--retryCount`` is useful for non-systemic errors, like downloading a file that may experience a sporadic interruption, or some other non-deterministic failure. To successfully restart our pipeline, we can edit our script to comment out line 30, or remove it, and then run :: (venv) $ python sort.py file:jobStore --restart --overwriteOutput=True The pipeline will run successfully, and the job store will be removed on the pipeline's completion. Collecting Statistics ~~~~~~~~~~~~~~~~~~~~~ Please see the :ref:`cli_status` section for more on gathering runtime and resource info on jobs. Launching a Toil Workflow in AWS -------------------------------- After having installed the ``aws`` extra for Toil during the :ref:`installation-ref` and set up AWS (see :ref:`prepareAWS`), the user can run the basic ``helloWorld.py`` script (:ref:`quickstart`) on a VM in AWS just by modifying the run command. Note that when running in AWS, users can either run the workflow on a single instance or run it on a cluster (which is running across multiple containers on multiple AWS instances). For more information on running Toil workflows on a cluster, see :ref:`runningAWS`. Also! Remember to use the :ref:`destroyCluster` command when finished to destroy the cluster! Otherwise things may not be cleaned up properly. #. Launch a cluster in AWS using the :ref:`launchCluster` command:: (venv) $ toil launch-cluster --keyPairName --leaderNodeType t2.medium --zone us-west-2a The arguments ``keyPairName``, ``leaderNodeType``, and ``zone`` are required to launch a cluster. #. Copy ``helloWorld.py`` to the ``/tmp`` directory on the leader node using the :ref:`rsyncCluster` command:: (venv) $ toil rsync-cluster --zone us-west-2a helloWorld.py :/tmp Note that the command requires defining the file to copy as well as the target location on the cluster leader node. #. Login to the cluster leader node using the :ref:`sshCluster` command:: (venv) $ toil ssh-cluster --zone us-west-2a Note that this command will log you in as the ``root`` user. #. Run the Toil script in the cluster:: $ python /tmp/helloWorld.py aws:us-west-2:my-S3-bucket In this particular case, we create an S3 bucket called ``my-S3-bucket`` in the ``us-west-2`` availability zone to store intermediate job results. Along with some other ``INFO`` log messages, you should get the following output in your terminal window: ``Hello, world!, here's a message: You did it!``. #. Exit from the SSH connection. :: $ exit #. Use the :ref:`destroyCluster` command to destroy the cluster:: (venv) $ toil destroy-cluster --zone us-west-2a Note that this command will destroy the cluster leader node and any resources created to run the job, including the S3 bucket. .. _awscwl: Running a CWL Workflow on AWS ----------------------------- After having installed the ``aws`` and ``cwl`` extras for Toil during the :ref:`installation-ref` and set up AWS (see :ref:`prepareAWS`), the user can run a CWL workflow with Toil on AWS. Also! Remember to use the :ref:`destroyCluster` command when finished to destroy the cluster! Otherwise things may not be cleaned up properly. #. First launch a node in AWS using the :ref:`launchCluster` command:: (venv) $ toil launch-cluster --keyPairName --leaderNodeType t2.medium --zone us-west-2a #. Copy ``example.cwl`` and ``example-job.yaml`` from the :ref:`CWL example ` to the node using the :ref:`rsyncCluster` command:: (venv) $ toil rsync-cluster --zone us-west-2a example.cwl :/tmp (venv) $ toil rsync-cluster --zone us-west-2a example-job.yaml :/tmp #. SSH into the cluster's leader node using the :ref:`sshCluster` utility:: (venv) $ toil ssh-cluster --zone us-west-2a #. Once on the leader node, it's a good idea to update and install the following:: sudo apt-get update sudo apt-get -y upgrade sudo apt-get -y dist-upgrade sudo apt-get -y install git sudo pip install mesos.cli #. Now create a new ``virtualenv`` with the ``--system-site-packages`` option and activate:: virtualenv --system-site-packages venv source venv/bin/activate #. Now run the CWL workflow:: (venv) $ toil-cwl-runner --provisioner aws --jobStore aws:us-west-2a:any-name /tmp/example.cwl /tmp/example-job.yaml .. tip:: When running a CWL workflow on AWS, input files can be provided either on the local file system or in S3 buckets using ``s3://`` URI references. Final output files will be copied to the local file system of the leader node. #. Finally, log out of the leader node and from your local computer, destroy the cluster:: (venv) $ toil destroy-cluster --zone us-west-2a .. _awscactus: Running a Workflow with Autoscaling - Cactus --------------------------------------------------- `Cactus `__ is a reference-free, whole-genome multiple alignment program that can be run on any of the cloud platforms Toil supports. .. note:: **Cloud Independence**: This example provides a "cloud agnostic" view of running Cactus with Toil. Most options will not change between cloud providers. However, each provisioner has unique inputs for ``--leaderNodeType``, ``--nodeType`` and ``--zone``. We recommend the following: +----------------------+----------------+------------+---------------+ | Option | Used in | AWS | Google | +----------------------+----------------+------------+---------------+ | ``--leaderNodeType`` | launch-cluster | t2.medium | n1-standard-1 | +----------------------+----------------+------------+---------------+ | ``--zone`` | launch-cluster | us-west-2a | | +----------------------+----------------+------------+ us-west1-a + | ``--zone`` | cactus | us-west-2 | | +----------------------+----------------+------------+---------------+ | ``--nodeType`` | cactus | c3.4xlarge | n1-standard-8 | +----------------------+----------------+------------+---------------+ When executing ``toil launch-cluster`` with ``gce`` specified for ``--provisioner``, the option ``--boto`` must be specified and given a path to your .boto file. See :ref:`runningGCE` for more information about the ``--boto`` option. Also! Remember to use the :ref:`destroyCluster` command when finished to destroy the cluster! Otherwise things may not be cleaned up properly. #. Download :download:`pestis.tar.gz <../../src/toil/test/cactus/pestis.tar.gz>` #. Launch a leader node using the :ref:`launchCluster` command:: (venv) $ toil launch-cluster --provisioner --keyPairName --leaderNodeType --zone .. note:: **A Helpful Tip** When using AWS, setting the environment variable eliminates having to specify the ``--zone`` option for each command. This will be supported for GCE in the future. :: (venv) $ export TOIL_AWS_ZONE=us-west-2c #. Create appropriate directory for uploading files:: (venv) $ toil ssh-cluster --provisioner $ mkdir /root/cact_ex $ exit #. Copy the required files, i.e., seqFile.txt (a text file containing the locations of the input sequences as well as their phylogenetic tree, see `here `__), organisms' genome sequence files in FASTA format, and configuration files (e.g. blockTrim1.xml, if desired), up to the leader node:: (venv) $ toil rsync-cluster --provisioner pestis-short-aws-seqFile.txt :/root/cact_ex (venv) $ toil rsync-cluster --provisioner GCF_000169655.1_ASM16965v1_genomic.fna :/root/cact_ex (venv) $ toil rsync-cluster --provisioner GCF_000006645.1_ASM664v1_genomic.fna :/root/cact_ex (venv) $ toil rsync-cluster --provisioner GCF_000182485.1_ASM18248v1_genomic.fna :/root/cact_ex (venv) $ toil rsync-cluster --provisioner GCF_000013805.1_ASM1380v1_genomic.fna :/root/cact_ex (venv) $ toil rsync-cluster --provisioner setup_leaderNode.sh :/root/cact_ex (venv) $ toil rsync-cluster --provisioner blockTrim1.xml :/root/cact_ex (venv) $ toil rsync-cluster --provisioner blockTrim3.xml :/root/cact_ex #. Log in to the leader node:: (venv) $ toil ssh-cluster --provisioner #. Set up the environment of the leader node to run Cactus:: $ bash /root/cact_ex/setup_leaderNode.sh $ source cact_venv/bin/activate (cact_venv) $ cd cactus (cact_venv) $ pip install --upgrade . #. Run `Cactus `__ as an autoscaling workflow:: (cact_venv) $ TOIL_APPLIANCE_SELF=quay.io/ucsc_cgl/toil:3.14.0 cactus --provisioner --nodeType --maxNodes 2 --minNodes 0 --retry 10 --batchSystem mesos --disableCaching --logDebug --logFile /logFile_pestis3 --configFile /root/cact_ex/blockTrim3.xml ::cactus-pestis /root/cact_ex/pestis-short-aws-seqFile.txt /root/cact_ex/pestis_output3.hal .. note:: **Pieces of the Puzzle**: ``TOIL_APPLIANCE_SELF=quay.io/ucsc_cgl/toil:3.14.0`` --- specifies the version of Toil being used, 3.14.0; if the latest one is desired, please eliminate. ``--nodeType`` --- determines the instance type used for worker nodes. The instance type specified here must be on the same cloud provider as the one specified with ``--leaderNodeType`` ``--maxNodes 2`` --- creates up to two instances of the type specified with ``--nodeType`` and launches Mesos worker containers inside them. ``--logDebug`` --- equivalent to ``--logLevel DEBUG``. ``--logFile /logFile_pestis3`` --- writes logs in a file named `logFile_pestis3` under ``/`` folder. ``--configFile`` --- this is not required depending on whether a specific configuration file is intended to run the alignment. ``::cactus-pestis`` --- creates a bucket, named ``cactus-pestis``, with the specified cloud provider to store intermediate job files and metadata. **NOTE**: If you want to use a GCE-based jobstore, specify ``google`` here, not ``gce``. The result file, named ``pestis_output3.hal``, is stored under ``/root/cact_ex`` folder of the leader node. Use ``cactus --help`` to see all the Cactus and Toil flags available. #. Log out of the leader node:: (cact_venv) $ exit #. Download the resulted output to local machine:: (venv) $ toil rsync-cluster --provisioner :/root/cact_ex/pestis_output3.hal #. Destroy the cluster:: (venv) $ toil destroy-cluster --provisioner toil-releases-3.24.0/docs/index.rst000066400000000000000000000045521362134276200171550ustar00rootroot00000000000000Toil Documentation ================== Toil is an open-source pure-Python workflow engine that lets people write better pipelines. Check out our `website`_ for a comprehensive list of Toil's features and read our `paper`_ to learn what Toil can do in the real world. Please subscribe to our low-volume `announce`_ mailing list and feel free to also join us on `GitHub`_ and `Gitter`_. If using Toil for your research, please cite Vivian, J., Rao, A. A., Nothaft, F. A., Ketchum, C., Armstrong, J., Novak, A., … Paten, B. (2017). Toil enables reproducible, open source, big biomedical data analyses. Nature Biotechnology, 35(4), 314–316. http://doi.org/10.1038/nbt.3772 .. _website: http://toil.ucsc-cgl.org/ .. _announce: https://groups.google.com/forum/#!forum/toil-announce .. _GridEngine: http://gridscheduler.sourceforge.net/ .. _Parasol: http://genecats.soe.ucsc.edu/eng/parasol.html .. _Apache Mesos: http://mesos.apache.org/ .. _spot market: https://aws.amazon.com/ec2/spot/ .. _Amazon Web Services: https://aws.amazon.com/ .. _Google Compute Engine: https://cloud.google.com/compute/ .. _OpenStack: https://www.openstack.org/ .. _GitHub: https://github.com/BD2KGenomics/toil .. _Gitter: https://gitter.im/bd2k-genomics-toil/Lobby .. _paper: http://biorxiv.org/content/early/2016/07/07/062497 .. todolist:: .. toctree:: :caption: Getting Started :maxdepth: 2 gettingStarted/install gettingStarted/quickStart .. toctree:: :caption: Running Toil :maxdepth: 2 running/introduction running/cliOptions running/debugging running/cloud/cloud running/hpcEnvironments running/cwl running/wdl .. toctree:: :caption: Developing Toil Workflows :maxdepth: 2 developingWorkflows/developing developingWorkflows/toilAPI developingWorkflows/toilAPIJobstore developingWorkflows/toilAPIJobFunctions developingWorkflows/toilAPIMethods developingWorkflows/toilAPIRunner developingWorkflows/toilAPIFilestore developingWorkflows/toilAPIBatchsystem developingWorkflows/toilAPIService developingWorkflows/toilAPIExceptions .. toctree:: :caption: Contributing to Toil :maxdepth: 2 contributing/contributing .. toctree:: :caption: Appendices :maxdepth: 2 appendices/architecture appendices/aws_min_permissions appendices/deploy appendices/environment_vars * :ref:`genindex` * :ref:`search` toil-releases-3.24.0/docs/running/000077500000000000000000000000001362134276200167665ustar00rootroot00000000000000toil-releases-3.24.0/docs/running/cliOptions.rst000066400000000000000000000506111362134276200216460ustar00rootroot00000000000000.. _commandRef: .. _workflowOptions: Commandline Options =================== A quick way to see all of Toil's commandline options is by executing the following on a toil script:: $ toil example.py --help For a basic toil workflow, Toil has one mandatory argument, the job store. All other arguments are optional. The Job Store ------------- Running toil scripts requires a filepath or url to a centralizing location for all of the files of the workflow. This is Toil's one required positional argument: the job store. To use the :ref:`quickstart ` example, if you're on a node that has a large **/scratch** volume, you can specify that the jobstore be created there by executing: ``python HelloWorld.py /scratch/my-job-store``, or more explicitly, ``python HelloWorld.py file:/scratch/my-job-store``. Syntax for specifying different job stores: Local: ``file:job-store-name`` AWS: ``aws:region-here:job-store-name`` Google: ``google:projectID-here:job-store-name`` Different types of job store options can be found below. .. _optionsRef: Commandline Options ------------------- **Core Toil Options** --workDir WORKDIR Absolute path to directory where temporary files generated during the Toil run should be placed. Temp files and folders, as well as standard output and error from batch system jobs (unless --noStdOutErr), will be placed in a directory toil- within workDir. The workflowID is generated by Toil and will be reported in the workflow logs. Default is determined by the variables (TMPDIR, TEMP, TMP) via mkdtemp. This directory needs to exist on all machines running jobs; if capturing standard output and error from batch system jobs is desired, it will generally need to be on a shared file system. --noStdOutErr Do not capture standard output and error from batch system jobs. --stats Records statistics about the toil workflow to be used by 'toil stats'. --clean=STATE Determines the deletion of the jobStore upon completion of the program. Choices: 'always', 'onError','never', or 'onSuccess'. The -\\-stats option requires information from the jobStore upon completion so the jobStore will never be deleted with that flag. If you wish to be able to restart the run, choose 'never' or 'onSuccess'. Default is 'never' if stats is enabled, and 'onSuccess' otherwise --cleanWorkDir STATE Determines deletion of temporary worker directory upon completion of a job. Choices: 'always', 'never', 'onSuccess'. Default = always. WARNING: This option should be changed for debugging only. Running a full pipeline with this option could fill your disk with intermediate data. --clusterStats FILEPATH If enabled, writes out JSON resource usage statistics to a file. The default location for this file is the current working directory, but an absolute path can also be passed to specify where this file should be written. This option only applies when using scalable batch systems. --restart If -\\-restart is specified then will attempt to restart existing workflow at the location pointed to by the -\\-jobStore option. Will raise an exception if the workflow does not exist. **Logging Options** Toil hides stdout and stderr by default except in case of job failure. Log levels in toil are based on priority from the logging module: --logOff Only CRITICAL log levels are shown. Equivalent to ``--logLevel=OFF`` or ``--logLevel=CRITICAL``. --logCritical Only CRITICAL log levels are shown. Equivalent to ``--logLevel=OFF`` or ``--logLevel=CRITICAL``. --logError Only ERROR, and CRITICAL log levels are shown. Equivalent to ``--logLevel=ERROR``. --logWarning Only WARN, ERROR, and CRITICAL log levels are shown. Equivalent to ``--logLevel=WARNING``. --logInfo All log statements are shown, except DEBUG. Equivalent to ``--logLevel=INFO``. --logDebug All log statements are shown. Equivalent to ``--logLevel=DEBUG``. --logLevel=LOGLEVEL May be set to: ``OFF`` (or ``CRITICAL``), ``ERROR``, ``WARN`` (or ``WARNING``), ``INFO``, or ``DEBUG``. --logFile FILEPATH Specifies a file path to write the logging output to. --rotatingLogging Turn on rotating logging, which prevents log files from getting too big (set using ``--maxLogFileSize BYTESIZE``). --maxLogFileSize BYTESIZE Sets the maximum log file size in bytes (``--rotatingLogging`` must be active). **Batch System Options** --batchSystem BATCHSYSTEM The type of batch system to run the job(s) with, currently can be one of LSF, Mesos, Slurm, Torque, HTCondor, singleMachine, parasol, gridEngine'. (default: singleMachine) --parasolCommand PARASOLCOMMAND The name or path of the parasol program. Will be looked up on PATH unless it starts with a slash. (default: parasol) --parasolMaxBatches PARASOLMAXBATCHES Maximum number of job batches the Parasol batch is allowed to create. One batch is created for jobs with a unique set of resource requirements. (default: 1000) --scale SCALE A scaling factor to change the value of all submitted tasks' submitted cores. Used in singleMachine batch system. (default: 1) --linkImports When using Toil's importFile function for staging, input files are copied to the job store. Specifying this option saves space by sym-linking imported files. As long as caching is enabled Toil will protect the file automatically by changing the permissions to read-only. --mesosMaster MESOSMASTERADDRESS The host and port of the Mesos master separated by a colon. (default: 169.233.147.202:5050) **Autoscaling Options** --provisioner CLOUDPROVIDER The provisioner for cluster auto-scaling. The currently supported choices are 'aws' or 'gce'. The default is None. --nodeTypes NODETYPES List of node types separated by commas. The syntax for each node type depends on the provisioner used. For the cgcloud and AWS provisioners this is the name of an EC2 instance type, optionally followed by a colon and the price in dollars to bid for a spot instance of that type, for example 'c3.8xlarge:0.42'. If no spot bid is specified, nodes of this type will be non-preemptable. It is acceptable to specify an instance as both preemptable and non-preemptable, including it twice in the list. In that case, preemptable nodes of that type will be preferred when creating new nodes once the maximum number of preemptable-nodes have been reached. --nodeOptions NODEOPTIONS Options for provisioning the nodes. The syntax depends on the provisioner used. Neither the CGCloud nor the AWS provisioner support any node options. --minNodes MINNODES Minimum number of nodes of each type in the cluster, if using auto-scaling. This should be provided as a comma-separated list of the same length as the list of node types. default=0 --maxNodes MAXNODES Maximum number of nodes of each type in the cluster, if using autoscaling, provided as a comma-separated list. The first value is used as a default if the list length is less than the number of nodeTypes. default=10 --preemptableCompensation PREEMPTABLECOMPENSATION The preference of the autoscaler to replace preemptable nodes with non-preemptable nodes, when preemptable nodes cannot be started for some reason. Defaults to 0.0. This value must be between 0.0 and 1.0, inclusive. A value of 0.0 disables such compensation, a value of 0.5 compensates two missing preemptable nodes with a non-preemptable one. A value of 1.0 replaces every missing pre-emptable node with a non-preemptable one. --nodeStorage NODESTORAGE Specify the size of the root volume of worker nodes when they are launched in gigabytes. You may want to set this if your jobs require a lot of disk space. The default value is 50. --metrics Enable the prometheus/grafana dashboard for monitoring CPU/RAM usage, queue size, and issued jobs. --defaultMemory INT The default amount of memory to request for a job. Only applicable to jobs that do not specify an explicit value for this requirement. Standard suffixes like K, Ki, M, Mi, G or Gi are supported. Default is 2.0G --defaultCores FLOAT The default number of CPU cores to dedicate a job. Only applicable to jobs that do not specify an explicit value for this requirement. Fractions of a core (for example 0.1) are supported on some batch systems, namely Mesos and singleMachine. Default is 1.0 --defaultDisk INT The default amount of disk space to dedicate a job. Only applicable to jobs that do not specify an explicit value for this requirement. Standard suffixes like K, Ki, M, Mi, G or Gi are supported. Default is 2.0G --maxCores INT The maximum number of CPU cores to request from the batch system at any one time. Standard suffixes like K, Ki, M, Mi, G or Gi are supported. --maxMemory INT The maximum amount of memory to request from the batch system at any one time. Standard suffixes like K, Ki, M, Mi, G or Gi are supported. --maxDisk INT The maximum amount of disk space to request from the batch system at any one time. Standard suffixes like K, Ki, M, Mi, G or Gi are supported. --retryCount RETRYCOUNT Number of times to retry a failing job before giving up and labeling job failed. default=1 --maxJobDuration MAXJOBDURATION Maximum runtime of a job (in seconds) before we kill it (this is a lower bound, and the actual time before killing the job may be longer). --rescueJobsFrequency RESCUEJOBSFREQUENCY Period of time to wait (in seconds) between checking for missing/overlong jobs, that is jobs which get lost by the batch system. --maxServiceJobs MAXSERVICEJOBS The maximum number of service jobs that can be run concurrently, excluding service jobs running on preemptable nodes. default=9223372036854775807 --maxPreemptableServiceJobs MAXPREEMPTABLESERVICEJOBS The maximum number of service jobs that can run concurrently on preemptable nodes. default=9223372036854775807 --deadlockWait DEADLOCKWAIT The minimum number of seconds to observe the cluster stuck running only the same service jobs before throwing a deadlock exception. default=60 --statePollingWait STATEPOLLINGWAIT Time, in seconds, to wait before doing a scheduler query for job state. Return cached results if within the waiting period. **Miscellaneous Options** --disableCaching Disables caching in the file store. This flag must be set to use a batch system that does not support caching such as Grid Engine, Parasol, LSF, or Slurm. --disableChaining Disables chaining of jobs (chaining uses one job's resource allocation for its successor job if possible). --maxLogFileSize MAXLOGFILESIZE The maximum size of a job log file to keep (in bytes), log files larger than this will be truncated to the last X bytes. Setting this option to zero will prevent any truncation. Setting this option to a negative value will truncate from the beginning. Default=62.5 K --writeLogs FILEPATH Write worker logs received by the leader into their own files at the specified path. Any non-empty standard output and error from failed batch system jobs will also be written into files at this path. The current working directory will be used if a path is not specified explicitly. Note: By default only the logs of failed jobs are returned to leader. Set log level to 'debug' to get logs back from successful jobs, and adjust 'maxLogFileSize' to control the truncation limit for worker logs. --writeLogsGzip FILEPATH Identical to -\\-writeLogs except the logs files are gzipped on the leader. --realTimeLogging Enable real-time logging from workers to masters. --sseKey SSEKEY Path to file containing 32 character key to be used for server-side encryption on awsJobStore or googleJobStore. SSE will not be used if this flag is not passed. --setEnv NAME NAME=VALUE or NAME, -e NAME=VALUE or NAME are also valid. Set an environment variable early on in the worker. If VALUE is omitted, it will be looked up in the current environment. Independently of this option, the worker will try to emulate the leader's environment before running a job. Using this option, a variable can be injected into the worker process itself before it is started. --servicePollingInterval SERVICEPOLLINGINTERVAL Interval of time service jobs wait between polling for the existence of the keep-alive flag (default=60) --debugWorker Experimental no forking mode for local debugging. Specifically, workers are not forked and stderr/stdout are not redirected to the log. (default=False) Restart Option -------------- In the event of failure, Toil can resume the pipeline by adding the argument ``--restart`` and rerunning the python script. Toil pipelines can even be edited and resumed which is useful for development or troubleshooting. Running Workflows with Services ------------------------------- Toil supports jobs, or clusters of jobs, that run as *services* to other *accessor* jobs. Example services include server databases or Apache Spark Clusters. As service jobs exist to provide services to accessor jobs their runtime is dependent on the concurrent running of their accessor jobs. The dependencies between services and their accessor jobs can create potential deadlock scenarios, where the running of the workflow hangs because only service jobs are being run and their accessor jobs can not be scheduled because of too limited resources to run both simultaneously. To cope with this situation Toil attempts to schedule services and accessors intelligently, however to avoid a deadlock with workflows running service jobs it is advisable to use the following parameters: * ``--maxServiceJobs``: The maximum number of service jobs that can be run concurrently, excluding service jobs running on preemptable nodes. * ``--maxPreemptableServiceJobs``: The maximum number of service jobs that can run concurrently on preemptable nodes. Specifying these parameters so that at a maximum cluster size there will be sufficient resources to run accessors in addition to services will ensure that such a deadlock can not occur. If too low a limit is specified then a deadlock can occur in which toil can not schedule sufficient service jobs concurrently to complete the workflow. Toil will detect this situation if it occurs and throw a :class:`toil.DeadlockException` exception. Increasing the cluster size and these limits will resolve the issue. Setting Options directly with the Toil Script --------------------------------------------- It's good to remember that commandline options can be overridden in the Toil script itself. For example, :func:`toil.job.Job.Runner.getDefaultOptions` can be used to run toil with all default options, and in this example, it will override commandline args to run the default options and always run with the "./toilWorkflow" directory specified as the jobstore: .. code-block:: python options = Job.Runner.getDefaultOptions("./toilWorkflow") # Get the options object with Toil(options) as toil: toil.start(Job()) # Run the script However, each option can be explicitly set within the script by supplying arguments (in this example, we are setting ``logLevel = "DEBUG"`` (all log statements are shown) and ``clean="ALWAYS"`` (always delete the jobstore) like so: .. code-block:: python options = Job.Runner.getDefaultOptions("./toilWorkflow") # Get the options object options.logLevel = "DEBUG" # Set the log level to the debug level. options.clean = "ALWAYS" # Always delete the jobStore after a run with Toil(options) as toil: toil.start(Job()) # Run the script However, the usual incantation is to accept commandline args from the user with the following: .. code-block:: python parser = Job.Runner.getDefaultArgumentParser() # Get the parser options = parser.parse_args() # Parse user args to create the options object with Toil(options) as toil: toil.start(Job()) # Run the script Which can also, of course, then accept script supplied arguments as before (which will overwrite any user supplied args): .. code-block:: python parser = Job.Runner.getDefaultArgumentParser() # Get the parser options = parser.parse_args() # Parse user args to create the options object options.logLevel = "DEBUG" # Set the log level to the debug level. options.clean = "ALWAYS" # Always delete the jobStore after a run with Toil(options) as toil: toil.start(Job()) # Run the script toil-releases-3.24.0/docs/running/cloud/000077500000000000000000000000001362134276200200745ustar00rootroot00000000000000toil-releases-3.24.0/docs/running/cloud/amazon.rst000066400000000000000000000405001362134276200221120ustar00rootroot00000000000000 .. _runningAWS: Running in AWS ============== Toil jobs can be run on a variety of cloud platforms. Of these, Amazon Web Services (AWS) is currently the best-supported solution. Toil provides the :ref:`clusterRef` to conveniently create AWS clusters, connect to the leader of the cluster, and then launch a workflow. The leader handles distributing the jobs over the worker nodes and autoscaling to optimize costs. The :ref:`Autoscaling` section details how to create a cluster and run a workflow that will dynamically scale depending on the workflow's needs. The :ref:`StaticProvisioning` section explains how a static cluster (one that won't automatically change in size) can be created and provisioned (grown, shrunk, destroyed, etc.). .. _EC2 instance type: https://aws.amazon.com/ec2/instance-types/ .. _prepareAWS: Preparing your AWS environment ------------------------------ To use Amazon Web Services (AWS) to run Toil or to just use S3 to host the files during the computation of a workflow, first set up and configure an account with AWS: #. If necessary, create and activate an `AWS account`_ #. Only needed once, but AWS requires that users "subscribe" to use the `Container Linux by CoreOS AMI`_. You will encounter errors if this is not done. #. Next, generate a key pair for AWS with the command (do NOT generate your key pair with the Amazon browser): :: $ ssh-keygen -t rsa #. This should prompt you to save your key. Please save it in :: ~/.ssh/id_rsa #. Now move this to where your OS can see it as an authorized key:: $ cat ~/.ssh/id_rsa.pub >> ~/.ssh/authorized_keys $ eval `ssh-agent -s` $ ssh-add #. You'll also need to chmod your private key (good practice but also enforced by AWS):: $ chmod 400 id_rsa #. Now you'll need to add the key to AWS via the browser. For example, on us-west1, this address would accessible at:: https://us-west-1.console.aws.amazon.com/ec2/v2/home?region=us-west-1#KeyPairs:sort=keyName #. Now click on the "Import Key Pair" button to add your key: .. image:: amazonaddkeypair.png :target: https://us-west-1.console.aws.amazon.com/ec2/v2/home?region=us-west-1#KeyPairs:sort=keyName :alt: Adding an Amazon Key Pair #. Next, you need to create an AWS access key. First go to the IAM dashboard, again; for "us-west1", the example link would be here:: https://console.aws.amazon.com/iam/home?region=us-west-1#/home #. The directions (transcribed from: https://docs.aws.amazon.com/general/latest/gr/managing-aws-access-keys.html ) are now: 1. On the IAM Dashboard page, choose your account name in the navigation bar, and then choose My Security Credentials. 2. Expand the Access keys (access key ID and secret access key) section. 3. Choose Create New Access Key. Then choose Download Key File to save the access key ID and secret access key to a file on your computer. After you close the dialog box, you can't retrieve this secret access key again. #. Now you should have a newly generated "AWS Access Key ID" and "AWS Secret Access Key". We can now install the AWS CLI and make sure that it has the proper credentials: :: $ pip install awscli --upgrade --user #. Now configure your AWS credentials with: :: $ aws configure #. Add your "AWS Access Key ID" and "AWS Secret Access Key" from earlier and your region and output format: :: " AWS Access Key ID [****************Q65Q]: " " AWS Secret Access Key [****************G0ys]: " " Default region name [us-west-1]: " " Default output format [json]: " #. Toil also relies on boto, and you'll need to create a boto file containing your credentials as well. To do this, run: :: $ nano ~/.boto #. Paste in the following (with your actual "AWS Access Key ID" and "AWS Secret Access Key"): :: [Credentials] aws_access_key_id = ****************Q65Q aws_secret_access_key = ****************G0ys #. If not done already, install toil (example uses version 3.12.0, but we recommend the latest release): :: $ virtualenv venv $ source venv/bin/activate $ pip install toil[all]==3.12.0 #. Now that toil is installed and you are running a virtualenv, an example of launching a toil leader node would be the following (again, note that we set TOIL_APPLIANCE_SELF to toil version 3.12.0 in this example, but please set the version to the installed version that you are using if you're using a different version): :: $ TOIL_APPLIANCE_SELF=quay.io/ucsc_cgl/toil:3.12.0 toil launch-cluster clustername --leaderNodeType t2.medium --zone us-west-1a --keyPairName id_rsa To further break down each of these commands: **TOIL_APPLIANCE_SELF=quay.io/ucsc_cgl/toil:latest** --- This is optional. It specifies a mesos docker image that we maintain with the latest version of toil installed on it. If you want to use a different version of toil, please specify the image tag you need from https://quay.io/repository/ucsc_cgl/toil?tag=latest&tab=tags. **toil launch-cluster** --- Base command in toil to launch a cluster. **clustername** --- Just choose a name for your cluster. **--leaderNodeType t2.medium** --- Specify the leader node type. Make a t2.medium (2CPU; 4Gb RAM; $0.0464/Hour). List of available AWS instances: https://aws.amazon.com/ec2/pricing/on-demand/ **--zone us-west-1a** --- Specify the AWS zone you want to launch the instance in. Must have the same prefix as the zone in your awscli credentials (which, in the example of this tutorial is: "us-west-1"). **--keyPairName id_rsa** --- The name of your key pair, which should be "id_rsa" if you've followed this tutorial. .. _Container Linux by CoreOS AMI: https://aws.amazon.com/marketplace/pp/B01H62FDJM/ .. _AWS account: https://aws.amazon.com/premiumsupport/knowledge-center/create-and-activate-aws-account/ .. _key pair: http://docs.aws.amazon.com/AWSEC2/latest/UserGuide/ec2-key-pairs.html .. _Amazon's instructions : http://docs.aws.amazon.com/AWSEC2/latest/UserGuide/ec2-key-pairs.html#how-to-generate-your-own-key-and-import-it-to-aws .. _install: http://docs.aws.amazon.com/cli/latest/userguide/installing.html .. _configure: http://docs.aws.amazon.com/cli/latest/userguide/cli-chap-getting-started.html .. _blog instructions: https://toilpipelines.wordpress.com/2018/01/18/running-toil-autoscaling-with-aws/ .. _awsJobStore: AWS Job Store ------------- Using the AWS job store is straightforward after you've finished :ref:`prepareAWS`; all you need to do is specify the prefix for the job store name. To run the sort example :ref:`sort example ` with the AWS job store you would type :: $ python sort.py aws:us-west-2:my-aws-sort-jobstore .. _installProvisioner: Toil Provisioner ---------------- The Toil provisioner is included in Toil alongside the ``[aws]`` extra and allows us to spin up a cluster. Getting started with the provisioner is simple: #. Make sure you have Toil installed with the AWS extras. For detailed instructions see :ref:`extras`. #. You will need an AWS account and you will need to save your AWS credentials on your local machine. For help setting up an AWS account see `here `__. For setting up your AWS credentials follow instructions `here `__. The Toil provisioner is built around the Toil Appliance, a Docker image that bundles Toil and all its requirements (e.g. Mesos). This makes deployment simple across platforms, and you can even simulate a cluster locally (see :ref:`appliance_dev` for details). .. admonition:: Choosing Toil Appliance Image When using the Toil provisioner, the appliance image will be automatically chosen based on the pip-installed version of Toil on your system. That choice can be overridden by setting the environment variables ``TOIL_DOCKER_REGISTRY`` and ``TOIL_DOCKER_NAME`` or ``TOIL_APPLIANCE_SELF``. See :ref:`envars` for more information on these variables. If you are developing with autoscaling and want to test and build your own appliance have a look at :ref:`appliance_dev`. For information on using the Toil Provisioner have a look at :ref:`Autoscaling`. .. _launchAwsClusterDetails: Details about Launching a Cluster in AWS ---------------------------------------- Using the provisioner to launch a Toil leader instance is simple using the ``launch-cluster`` command. For example, to launch a cluster named "my-cluster" with a t2.medium leader in the us-west-2a zone, run :: (venv) $ toil launch-cluster my-cluster --leaderNodeType t2.medium --zone us-west-2a --keyPairName The cluster name is used to uniquely identify your cluster and will be used to populate the instance's ``Name`` tag. Also, the Toil provisioner will automatically tag your cluster with an ``Owner`` tag that corresponds to your keypair name to facilitate cost tracking. In addition, the ``ToilNodeType`` tag can be used to filter "leader" vs. "worker" nodes in your cluster. The leaderNodeType is an `EC2 instance type`_. This only affects the leader node. .. _EC2 instance type: https://aws.amazon.com/ec2/instance-types/ The ``--zone`` parameter specifies which EC2 availability zone to launch the cluster in. Alternatively, you can specify this option via the ``TOIL_AWS_ZONE`` environment variable. Note: the zone is different from an EC2 region. A region corresponds to a geographical area like ``us-west-2 (Oregon)``, and availability zones are partitions of this area like ``us-west-2a``. By default, Toil creates an IAM role for each cluster with sufficient permissions to perform cluster operations (e.g. full S3, EC2, and SDB access). If the default permissions are not sufficient for your use case (e.g. if you need access to ECR), you may create a custom IAM role with all necessary permissions and set the ``--awsEc2ProfileArn`` parameter when launching the cluster. Note that your custom role must at least have :ref:`these permissions ` in order for the Toil cluster to function properly. For more information on options try: :: (venv) $ toil launch-cluster --help .. _StaticProvisioning: Static Provisioning ^^^^^^^^^^^^^^^^^^^ Toil can be used to manage a cluster in the cloud by using the :ref:`clusterRef`. The cluster utilities also make it easy to run a toil workflow directly on this cluster. We call this static provisioning because the size of the cluster does not change. This is in contrast with :ref:`Autoscaling`. To launch worker nodes alongside the leader we use the ``-w`` option:: (venv) $ toil launch-cluster my-cluster --leaderNodeType t2.small -z us-west-2a --keyPairName your-AWS-key-pair-name --nodeTypes m3.large,t2.micro -w 1,4 This will spin up a leader node of type t2.small with five additional workers --- one m3.large instance and four t2.micro. Currently static provisioning is only possible during the cluster's creation. The ability to add new nodes and remove existing nodes via the native provisioner is in development. Of course the cluster can always be deleted with the :ref:`destroyCluster` utility. Uploading Workflows ^^^^^^^^^^^^^^^^^^^ Now that our cluster is launched, we use the :ref:`rsyncCluster` utility to copy the workflow to the leader. For a simple workflow in a single file this might look like :: (venv) $ toil rsync-cluster -z us-west-2a my-cluster toil-workflow.py :/ .. note:: If your toil workflow has dependencies have a look at the :ref:`autoDeploying` section for a detailed explanation on how to include them. .. _Autoscaling: Running a Workflow with Autoscaling ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ Autoscaling is a feature of running Toil in a cloud whereby additional cloud instances are launched to run the workflow. Autoscaling leverages Mesos containers to provide an execution environment for these workflows. .. note:: Make sure you've done the AWS setup in :ref:`prepareAWS`. #. Download :download:`sort.py <../../../src/toil/test/sort/sort.py>` #. Launch the leader node in AWS using the :ref:`launchCluster` command: :: (venv) $ toil launch-cluster --keyPairName --leaderNodeType t2.medium --zone us-west-2a #. Copy the ``sort.py`` script up to the leader node: :: (venv) $ toil rsync-cluster sort.py :/root #. Login to the leader node: :: (venv) $ toil ssh-cluster #. Run the script as an autoscaling workflow: :: $ python /root/sort.py aws:us-west-2: --provisioner aws --nodeTypes c3.large --maxNodes 2 --batchSystem mesos .. note:: In this example, the autoscaling Toil code creates up to two instances of type `c3.large` and launches Mesos slave containers inside them. The containers are then available to run jobs defined by the `sort.py` script. Toil also creates a bucket in S3 called `aws:us-west-2:autoscaling-sort-jobstore` to store intermediate job results. The Toil autoscaler can also provision multiple different node types, which is useful for workflows that have jobs with varying resource requirements. For example, one could execute the script with ``--nodeTypes c3.large,r3.xlarge --maxNodes 5,1``, which would allow the provisioner to create up to five c3.large nodes and one r3.xlarge node for memory-intensive jobs. In this situation, the autoscaler would avoid creating the more expensive r3.xlarge node until needed, running most jobs on the c3.large nodes. #. View the generated file to sort:: $ head fileToSort.txt #. View the sorted file:: $ head sortedFile.txt For more information on other autoscaling (and other) options have a look at :ref:`workflowOptions` and/or run :: $ python my-toil-script.py --help .. important:: Some important caveats about starting a toil run through an ssh session are explained in the :ref:`sshCluster` section. Preemptability ^^^^^^^^^^^^^^ Toil can run on a heterogeneous cluster of both preemptable and non-preemptable nodes. Being preemptable node simply means that the node may be shut down at any time, while jobs are running. These jobs can then be restarted later somewhere else. A node type can be specified as preemptable by adding a `spot bid`_ to its entry in the list of node types provided with the ``--nodeTypes`` flag. If spot instance prices rise above your bid, the preemptable node whill be shut down. While individual jobs can each explicitly specify whether or not they should be run on preemptable nodes via the boolean ``preemptable`` resource requirement, the ``--defaultPreemptable`` flag will allow jobs without a ``preemptable`` requirement to run on preemptable machines. .. admonition:: Specify Preemptability Carefully Ensure that your choices for ``--nodeTypes`` and ``--maxNodes <>`` make sense for your workflow and won't cause it to hang. You should make sure the provisioner is able to create nodes large enough to run the largest job in the workflow, and that non-preemptable node types are allowed if there are non-preemptable jobs in the workflow. Finally, the ``--preemptableCompensation`` flag can be used to handle cases where preemptable nodes may not be available but are required for your workflow. With this flag enabled, the autoscaler will attempt to compensate for a shortage of preemptable nodes of a certain type by creating non-preemptable nodes of that type, if non-preemptable nodes of that type were specified in ``--nodeTypes``. .. _spot bid: https://aws.amazon.com/ec2/spot/pricing/ Dashboard --------- Toil provides a dashboard for viewing the RAM and CPU usage of each node, the number of issued jobs of each type, the number of failed jobs, and the size of the jobs queue. To launch this dashboard for a toil workflow, include the ``--metrics`` flag in the toil script command. The dashboard can then be viewed in your browser at localhost:3000 while connected to the leader node through ``toil ssh-cluster``. On AWS, the dashboard keeps track of every node in the cluster to monitor CPU and RAM usage, but it can also be used while running a workflow on a single machine. The dashboard uses Grafana as the front end for displaying real-time plots, and Prometheus for tracking metrics exported by toil. 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c;z¼vMÖý+‰š»p½*[»Œeš«?éÈöu;*V±qcµró>½/ï>㦣¶P‹§Äèä½ë¬|÷@“ÆÆéÐå,ãç†ò<íß¼J£cc7jœÖl;¤‚š>?pµÿãÎ!ä\8‰p5Bà$BÀÕ9€“9W#äN"ä\8‰p5Bà$BÀÕ9€“9W#äN"ä\8‰p5Bà$BÀÕ9€“9W#äN"ä\8‰p5Bà$BÀÕ9€“9W#äN"ä\8‰pµÿ›ÜŽœßDIEND®B`‚toil-releases-3.24.0/docs/running/cloud/cloud.rst000066400000000000000000000043071362134276200217400ustar00rootroot00000000000000 .. _cloudOverview: Running in the Cloud ==================== Toil supports Amazon Web Services (AWS) and Google Compute Engine (GCE) in the cloud and has autoscaling capabilities that can adapt to the size of your workflow, whether your workflow requires 10 instances or 20,000. Toil does this by creating a virtual cluster with `Apache Mesos`_. `Apache Mesos`_ requires a leader node to coordinate the workflow, and worker nodes to execute the various tasks within the workflow. As the workflow runs, Toil will "autoscale", creating and terminating workers as needed to meet the demands of the workflow. Once a user is familiar with the basics of running toil locally (specifying a :ref:`jobStore `, and how to write a toil script), they can move on to the guides below to learn how to translate these workflows into cloud ready workflows. .. _cloudProvisioning: Managing a Cluster of Virtual Machines (Provisioning) ----------------------------------------------------- Toil can launch and manage a cluster of virtual machines to run using the *provisioner* to run a workflow distributed over several nodes. The provisioner also has the ability to automatically scale up or down the size of the cluster to handle dynamic changes in computational demand (autoscaling). Currently we have working provisioners with AWS and GCE (Azure support has been deprecated). Toil uses `Apache Mesos`_ as the :ref:`batchSystemOverview`. See here for instructions for :ref:`runningAWS`. See here for instructions for :ref:`runningGCE`. .. _Apache Mesos: https://mesos.apache.org/gettingstarted/ .. _cloudJobStore: Storage (Toil jobStore) ----------------------- Toil can make use of cloud storage such as AWS or Google buckets to take care of storage needs. This is useful when running Toil in single machine mode on any cloud platform since it allows you to make use of their integrated storage systems. .. FIXME add link to batch system overview for single machine mode For an overview of the job store see :ref:`jobStoreOverview`. For instructions configuring a particular job store see: - :ref:`awsJobStore` - :ref:`googleJobStore` Cloud Platforms =============== .. toctree:: amazon gce clusterUtils toil-releases-3.24.0/docs/running/cloud/clusterUtils.rst000066400000000000000000000360741362134276200233420ustar00rootroot00000000000000.. _clusterRef: Cluster Utilities ----------------- There are several utilities used for starting and managing a Toil cluster using the AWS provisioner. They are installed via the ``[aws]`` or ``[google]`` extra. For installation details see :ref:`installProvisioner`. The cluster utilities are used for :ref:`runningAWS` and are comprised of ``toil launch-cluster``, ``toil rsync-cluster``, ``toil ssh-cluster``, and ``toil destroy-cluster`` entry points. Cluster commands specific to ``toil`` are: ``status`` --- Reports runtime and resource usage for all jobs in a specified jobstore (workflow must have originally been run using the -\\-stats option). ``stats`` --- Inspects a job store to see which jobs have failed, run successfully, etc. ``destroy-cluster`` --- For autoscaling. Terminates the specified cluster and associated resources. ``launch-cluster`` --- For autoscaling. This is used to launch a toil leader instance with the specified provisioner. ``rsync-cluster`` --- For autoscaling. Used to transfer files to a cluster launched with ``toil launch-cluster``. ``ssh-cluster`` --- SSHs into the toil appliance container running on the leader of the cluster. ``clean`` --- Delete the job store used by a previous Toil workflow invocation. ``kill`` --- Kills any running jobs in a rogue toil. For information on a specific utility run:: toil launch-cluster --help for a full list of its options and functionality. The cluster utilities can be used for :ref:`runningGCE` and :ref:`runningAWS`. .. tip:: By default, all of the cluster utilities expect to be running on AWS. To run with Google you will need to specify the ``--provisioner gce`` option for each utility. .. note:: Boto must be `configured`_ with AWS credentials before using cluster utilities. :ref:`runningGCE` contains instructions for .. _configured: http://boto3.readthedocs.io/en/latest/guide/quickstart.html#configuration .. _cli_status: Stats Command -------------- To use the stats command, a workflow must first be run using the ``--stats`` option. Using this command makes certain that toil does not delete the job store, no matter what other options are specified (i.e. normally the option ``--clean=always`` would delete the job, but ``--stats`` will override this). An example of this would be running the following:: python discoverfiles.py file:my-jobstore --stats Where ``discoverfiles.py`` is the following: .. literalinclude:: ../../../src/toil/test/docs/scripts/tutorial_discoverfiles.py Notice the ``displayName`` key, which can rename a job, giving it an alias when it is finally displayed in stats. Running this workflow file should record three job names: ``sysFiles`` (job1), ``userFiles`` (job2), and ``discoverFiles`` (job3). To see the runtime and resources used for each job when it was run, type :: toil stats file:my-jobstore This should output the following: .. code-block:: python Batch System: singleMachine Default Cores: 1 Default Memory: 2097152K Max Cores: 9.22337e+18 Total Clock: 0.56 Total Runtime: 1.01 Worker Count | Time* | Clock | Wait | Memory n | min med* ave max total | min med ave max total | min med ave max total | min med ave max total 1 | 0.14 0.14 0.14 0.14 0.14 | 0.13 0.13 0.13 0.13 0.13 | 0.01 0.01 0.01 0.01 0.01 | 76K 76K 76K 76K 76K Job Worker Jobs | min med ave max | 3 3 3 3 Count | Time* | Clock | Wait | Memory n | min med* ave max total | min med ave max total | min med ave max total | min med ave max total 3 | 0.01 0.06 0.05 0.07 0.14 | 0.00 0.06 0.04 0.07 0.12 | 0.00 0.01 0.00 0.01 0.01 | 76K 76K 76K 76K 229K sysFiles Count | Time* | Clock | Wait | Memory n | min med* ave max total | min med ave max total | min med ave max total | min med ave max total 1 | 0.01 0.01 0.01 0.01 0.01 | 0.00 0.00 0.00 0.00 0.00 | 0.01 0.01 0.01 0.01 0.01 | 76K 76K 76K 76K 76K userFiles Count | Time* | Clock | Wait | Memory n | min med* ave max total | min med ave max total | min med ave max total | min med ave max total 1 | 0.06 0.06 0.06 0.06 0.06 | 0.06 0.06 0.06 0.06 0.06 | 0.01 0.01 0.01 0.01 0.01 | 76K 76K 76K 76K 76K discoverFiles Count | Time* | Clock | Wait | Memory n | min med* ave max total | min med ave max total | min med ave max total | min med ave max total 1 | 0.07 0.07 0.07 0.07 0.07 | 0.07 0.07 0.07 0.07 0.07 | 0.00 0.00 0.00 0.00 0.00 | 76K 76K 76K 76K 76K Once we're done, we can clean up the job store by running :: toil clean file:my-jobstore Status Command -------------- Continuing the example from the stats section above, if we ran our workflow with the command :: python discoverfiles.py file:my-jobstore --stats We could interrogate our jobstore with the status command, for example:: toil status file:my-jobstore If the run was successful, this would not return much valuable information, something like :: 2018-01-11 19:31:29,739 - toil.lib.bioio - INFO - Root logger is at level 'INFO', 'toil' logger at level 'INFO'. 2018-01-11 19:31:29,740 - toil.utils.toilStatus - INFO - Parsed arguments 2018-01-11 19:31:29,740 - toil.utils.toilStatus - INFO - Checking if we have files for Toil The root job of the job store is absent, the workflow completed successfully. Otherwise, the ``status`` command should return the following: There are ``x`` unfinished jobs, ``y`` parent jobs with children, ``z`` jobs with services, ``a`` services, and ``b`` totally failed jobs currently in ``c``. Clean Command ------------- If a Toil pipeline didn't finish successfully, or was run using ``--clean=always`` or ``--stats``, the job store will exist until it is deleted. ``toil clean `` ensures that all artifacts associated with a job store are removed. This is particularly useful for deleting AWS job stores, which reserves an SDB domain as well as an S3 bucket. The deletion of the job store can be modified by the ``--clean`` argument, and may be set to ``always``, ``onError``, ``never``, or ``onSuccess`` (default). Temporary directories where jobs are running can also be saved from deletion using the ``--cleanWorkDir``, which has the same options as ``--clean``. This option should only be run when debugging, as intermediate jobs will fill up disk space. .. _launchCluster: Launch-Cluster Command ---------------------- Running ``toil launch-cluster`` starts up a leader for a cluster. Workers can be added to the initial cluster by specifying the ``-w`` option. An example would be :: $ toil launch-cluster my-cluster --leaderNodeType t2.small -z us-west-2a --keyPairName your-AWS-key-pair-name --nodeTypes m3.large,t2.micro -w 1,4 Options are listed below. These can also be displayed by running :: $ toil launch-cluster --help launch-cluster's main positional argument is the clusterName. This is simply the name of your cluster. If it does not exist yet, Toil will create it for you. **Launch-Cluster Options** --help -h also accepted. Displays this help menu. --tempDirRoot TEMPDIRROOT Path to the temporary directory where all temp files are created, by default uses the current working directory as the base. --version Display version. --provisioner CLOUDPROVIDER -p CLOUDPROVIDER also accepted. The provisioner for cluster auto-scaling. Both AWS and GCE are currently supported. --zone ZONE -z ZONE also accepted. The availability zone of the leader. This parameter can also be set via the TOIL_AWS_ZONE or TOIL_GCE_ZONE environment variables, or by the ec2_region_name parameter in your .boto file if using AWS, or derived from the instance metadata if using this utility on an existing EC2 instance. --leaderNodeType LEADERNODETYPE Non-preemptable node type to use for the cluster leader. --keyPairName KEYPAIRNAME The name of the AWS or ssh key pair to include on the instance. --boto BOTOPATH The path to the boto credentials directory. This is transferred to all nodes in order to access the AWS jobStore from non-AWS instances. --tag KEYVALUE KEYVALUE is specified as KEY=VALUE. -t KEY=VALUE also accepted. Tags are added to the AWS cluster for this node and all of its children. Tags are of the form: -t key1=value1 --tag key2=value2. Multiple tags are allowed and each tag needs its own flag. By default the cluster is tagged with: { "Name": clusterName, "Owner": IAM username }. --vpcSubnet VPCSUBNET VPC subnet ID to launch cluster in. Uses default subnet if not specified. This subnet needs to have auto assign IPs turned on. --nodeTypes NODETYPES Comma-separated list of node types to create while launching the leader. The syntax for each node type depends on the provisioner used. For the AWS provisioner this is the name of an EC2 instance type followed by a colon and the price in dollars to bid for a spot instance, for example 'c3.8xlarge:0.42'. Must also provide the --workers argument to specify how many workers of each node type to create. --workers WORKERS -w WORKERS also accepted. Comma-separated list of the number of workers of each node type to launch alongside the leader when the cluster is created. This can be useful if running toil without auto-scaling but with need of more hardware support. --leaderStorage LEADERSTORAGE Specify the size (in gigabytes) of the root volume for the leader instance. This is an EBS volume. --nodeStorage NODESTORAGE Specify the size (in gigabytes) of the root volume for any worker instances created when using the -w flag. This is an EBS volume. **Logging Options** --logOff Same as -\\-logCritical. --logCritical Turn on logging at level CRITICAL and above. (default is INFO) --logError Turn on logging at level ERROR and above. (default is INFO) --logWarning Turn on logging at level WARNING and above. (default is INFO) --logInfo Turn on logging at level INFO and above. (default is INFO) --logDebug Turn on logging at level DEBUG and above. (default is INFO) --logLevel LOGLEVEL Log at given level (may be either OFF (or CRITICAL), ERROR, WARN (or WARNING), INFO or DEBUG). (default is INFO) --logFile LOGFILE File to log in. --rotatingLogging Turn on rotating logging, which prevents log files getting too big. .. _sshCluster: Ssh-Cluster Command ------------------- Toil provides the ability to ssh into the leader of the cluster. This can be done as follows:: $ toil ssh-cluster CLUSTER-NAME-HERE This will open a shell on the Toil leader and is used to start an :ref:`Autoscaling` run. Issues with docker prevent using ``screen`` and ``tmux`` when sshing the cluster (The shell doesn't know that it is a TTY which prevents it from allocating a new screen session). This can be worked around via :: $ script $ screen Simply running ``screen`` within ``script`` will get things working properly again. Finally, you can execute remote commands with the following syntax:: $ toil ssh-cluster CLUSTER-NAME-HERE remoteCommand It is not advised that you run your Toil workflow using remote execution like this unless a tool like `nohup `_ is used to ensure the process does not die if the SSH connection is interrupted. For an example usage, see :ref:`Autoscaling`. .. _rsyncCluster: Rsync-Cluster Command --------------------- The most frequent use case for the ``rsync-cluster`` utility is deploying your Toil script to the Toil leader. Note that the syntax is the same as traditional `rsync `_ with the exception of the hostname before the colon. This is not needed in ``toil rsync-cluster`` since the hostname is automatically determined by Toil. Here is an example of its usage:: $ toil rsync-cluster CLUSTER-NAME-HERE \ ~/localFile :/remoteDestination .. _destroyCluster: Destroy-Cluster Command ----------------------- The ``destroy-cluster`` command is the advised way to get rid of any Toil cluster launched using the :ref:`launchCluster` command. It ensures that all attached nodes, volumes, security groups, etc. are deleted. If a node or cluster is shut down using Amazon's online portal residual resources may still be in use in the background. To delete a cluster run :: $ toil destroy-cluster CLUSTER-NAME-HERE Kill Command ------------ To kill all currently running jobs for a given jobstore, use the command :: toil kill file:my-jobstore toil-releases-3.24.0/docs/running/cloud/gce.rst000066400000000000000000000073461362134276200213760ustar00rootroot00000000000000.. _runningGCE: Running in Google Compute Engine (GCE) ====================================== Toil supports a provisioner with Google, and a :ref:`googleJobStore`. To get started, follow instructions for :ref:`prepareGoogle`. .. _prepareGoogle: Preparing your Google environment --------------------------------- Toil supports using the `Google Cloud Platform`_. Setting this up is easy! #. Make sure that the ``google`` extra (:ref:`extras`) is installed #. Follow `Google's Instructions`_ to download credentials and set the ``GOOGLE_APPLICATION_CREDENTIALS`` environment variable #. Create a new ssh key with the proper format. To create a new ssh key run the command :: $ ssh-keygen -t rsa -f ~/.ssh/id_rsa -C [USERNAME] where ``[USERNAME]`` is something like ``jane@example.com``. Make sure to leave your password blank. .. warning:: This command could overwrite an old ssh key you may be using. If you have an existing ssh key you would like to use, it will need to be called id_rsa and it needs to have no password set. Make sure only you can read the SSH keys: :: $ chmod 400 ~/.ssh/id_rsa ~/.ssh/id_rsa.pub #. Add your newly formatted public key to Google. To do this, log into your Google Cloud account and go to `metadata`_ section under the Compute tab. .. image:: googleScreenShot.png Near the top of the screen click on 'SSH Keys', then edit, add item, and paste the key. Then save: .. image:: googleScreenShot2.png For more details look at Google's instructions for `adding SSH keys`_. .. _Google Cloud Platform: https://cloud.google.com/storage/ .. _adding SSH keys: https://cloud.google.com/compute/docs/instances/adding-removing-ssh-keys .. _metadata: https://console.cloud.google.com/compute/metadata .. _Google's Instructions: https://cloud.google.com/docs/authentication/getting-started .. _googleJobStore: Google Job Store ---------------- To use the Google Job Store you will need to set the ``GOOGLE_APPLICATION_CREDENTIALS`` environment variable by following `Google's instructions`_. Then to run the sort example with the Google job store you would type :: $ python sort.py google:my-project-id:my-google-sort-jobstore Running a Workflow with Autoscaling ----------------------------------- .. warning:: Google Autoscaling is in beta! The steps to run a GCE workflow are similar to those of AWS (:ref:`Autoscaling`), except you will need to explicitly specify the ``--provisioner gce`` option which otherwise defaults to ``aws``. #. Download :download:`sort.py <../../../src/toil/test/sort/sort.py>` #. Launch the leader node in GCE using the :ref:`launchCluster` command:: (venv) $ toil launch-cluster --provisioner gce --leaderNodeType n1-standard-1 --keyPairName --zone us-west1-a Where ```` is the first part of ``[USERNAME]`` used when setting up your ssh key. For example if ``[USERNAME]`` was jane@example.com, ```` should be ``jane``. The ``--keyPairName`` option is for an SSH key that was added to the Google account. If your ssh key ``[USERNAME]`` was ``jane@example.com``, then your key pair name will be just ``jane``. #. Upload the sort example and ssh into the leader:: (venv) $ toil rsync-cluster --provisioner gce sort.py :/root (venv) $ toil ssh-cluster --provisioner gce #. Run the workflow:: $ python /root/sort.py google:: --provisioner gce --batchSystem mesos --nodeTypes n1-standard-2 --maxNodes 2 #. Clean up:: $ exit # this exits the ssh from the leader node (venv) $ toil destroy-cluster --provisioner gce .. _Google's Instructions: https://cloud.google.com/docs/authentication/getting-started toil-releases-3.24.0/docs/running/cloud/googleScreenShot.png000066400000000000000000001423341362134276200240630ustar00rootroot00000000000000‰PNG  IHDRÏÞ$†§ ¯iCCPICC ProfileH‰•–TSiÇ¿÷Ò" %ôŽtH¯”^m„H(1‚€]Á± "6t¨ ŽJ‘± ‚X±È  ®ƒPQÙ,ag÷ìîÙÿ;7ïwnî»ïÿ¾÷¾s.ä‘(¦"L{»1#£¢™¸çr€ d€ ‡›*r ôˆæÎÕø}¤Ñ]“é^ÿþÿ•/.• ˆp,/•›‚ðy$.sEâ4PH­µi¢i.D˜.F "|jšf¹yšcgùÞLMh°;ÂÃàÉŽ8ÒG$ÏLç& }Èt„Í„<a„¸|ál„SRVOó„õcÿ©OÂ_zÆJ{r8 Rž}–á=©¢dNæÿ¹ÿ[)É’¹{h"Aæ‹}‚‘3Y³Š¤Õ~RÆ. ˜co¦~†ùŸ°9榺GÏ1ãá7Ç’¤0×9æˆç¯¤±CçX¼:XÚ_˜¼Ô_Ú?Ž-å¸TÏ9Žx±ç8‹1Çé‚ð¥sœšâ7_ã.Í‹%ÁRÏñb/é3¦¤Î{ãræï•Æõ™÷)õËóð”æ…aÒzQš›´§(9pÞ²·4Ÿš"½6 ùÀæ8‘ã8ß'Pº>Àxä`‚@`æÀ ®Òâ2¦¿ià¾Z”)$ðÓ˜®È®‰c²…\Sc¦…™9 €é=8ûŠ?<˜Ù[?Ÿã·`ÝŠ$çsñûhG¶Sö|Noò^4ïáJÄé³9ôô, % ´€>0AÜÙà‚8ö D•€ ø ˆÁZ°l9 ì@8 N€ pœ à"¸ ®ƒÛ  ô‚Ç  ×`ŒƒI‚p¢AJ:¤A r‚è04½½½]„®@×£[ÑwÑèQôw £‚1ÂØcؘHLf-&S€)ÃÔaÚ0½˜!Ì8‹e`õ°¶Xl6»»{[‹mÆvc±c8N g„sÄà8¸4\îîî ®7„û„'áÕñx/|4^ˆßŠ/ÀWá/ã{ð/ñ“*A‡`O ð™„Ý„“„&ÂÂa’(GÔ#:C‰‰Ä-ÄBb ±ø„øD"i’ìHA$i3©t†tƒ4@úL–'’ÝÉËÉò.r9¹™üüB¡èR\(Ñ”4Ê.J%ååå“ MÆT†-ÓÙ$S,S/Ó#óV– «#ë*»R6K¶@öœìÙ7TU—êNåP7R‹©¨}Ô19šœ¹\€\ŠÜN¹*¹›rÃò8y]yOyž|¶ü ùkòƒ4M‹æNãÒ¶ÑNÒÚhCt,]Φ'Òóè§éôQy+…p… …b…K ý C—Áf$3v3Î2î3¾,P]ຠnÁŽ5 zL(.TtQŒSÌU¬UìUü¢ÄTòTJRÚ«Ô ôT­l¨¤¼Vùˆr›ò›…ô… ¹ sž]øHV1T VY§rB¥CeLUMÕ[U¤zHõšê5†š‹Z¢Ú~µËj#ê4u'uú~õ+ꯘ LWf2³ÙÊÕPÑðÑh×èÔ˜ÔÔÓ ÓܪY«ùT‹¨ÅÒŠ×Ú¯Õ¢5ª­®½D{½vµö#‚K‡¯sP§]gBWO7Bw»nƒî°ž¢[/K¯Zï‰>EßY~©þ=¬Ë Éà°A—!lhmÈ7,6¼cÙ ŒucŒíŒ…Æ¥Æ}&dW“t“j“S†©¿éVÓÓ·‹´E/Ú»¨}Ñw3k³d³“fÍåÍ}Í·š7™¿·0´àZ[ܳ¤XzYn²l´|gedguÄê5Íz‰õvëëo6¶6b››[mÛÛÛ>ÈÚɺa‡±s³ÛdwÑî³½}šýYû?L’ª†ë-Ž[|rñ £¦#Çñ¸c¿Ó)Æé˜S¿³†3ǹÔù¹‹– Ï¥Ì奫k¢ë)×·nfnb·:· w{÷ îÍ(o\NOyÏ0Ï"Ïg^š^ ^Õ^£ÞÖÞë¼›}0>~>{}úتl.»’=êkë»Á·ÕìâWä÷ÜßÐ_ìß´^â»dß’'Ku– —6€vÀ¾€§zk ½6^ÜB YR2êº;ôq˜~˜$¬%\6|yxeøD„GD~Dä¢È ‘·£”£QѸèðè²è±ežË,Zn½-*2ÿ;dáçv—:¶ü‹þ»‹Ó°ú= iTXtXML:com.adobe.xmp 463 526 *RY@IDATxì¸U÷ÆÝ R"*" ‚J|b+6"¨ØÝØØñ7ñ³1ÐT±¥¤K:ï~÷qî¹'ï½çÜsÏ}×óœ33{v¾3³ß½Ö^³§Ò¸qã L"„€B@¤Œ@¥Oy¦ —" ! „€0«,„€B@ôy¦‡—b ! „€æ©{@! „@ºHóL1ÅB@ €È³Âß@! 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" " "PþxÝRà ã ˜l뀧r¾8ω¼³¯¿«þòåËqÕUW¡N:¦;]ºt1ÿ+¯¼Ò¬¼'$$Ë-Mš41yíÛ·Ï×õÐÐPp¥ž+ù´0Ø©ÿþŽUöV­Z™~8[XŽ¢…–Z ÂÂÂÀv¯@ë‚mU¸í¶Û †9sæ‹EûNÑQ©R%ójÓ¦ 6lØ`¬÷ðáÃí:4_ŒÃÞ½{u„çi`¢(HII1/¶M±pìØ1“§D@D@D@D@Ê'Re 'ÛíÚµst‰±÷ß¿ã3'Ç\1çÛNqqqæ«îtëáĸJ•*8xð .ºè"»X¡ïÎnF ö ¿ó…\½¯W¯žöùÞ½{›C{ÕßµZØ'Š‡™3gÚ—™÷ØØX$%%™Ý•š6mêÈ»ä’KÇ<øì³ÏŒè`y;…‡‡‹]žhuhÛ¶- dgë]D@D@D@D ð¹(°-6+ûsY°Ø}r}‰‰A=pà 7¸f×™èèhŒ1Âäýë_ÿÂÉ“'Ï)w!'(@è”››ë° pg$®þ”Ø/ŠÆg4oÞ<_Q{»U [p{SZI*W®lÊÞxã  ûÐsÏ=gÚãuŒ ËËSLž</¿ür¾úõAD@D@D@D üðzLAùAṧ:ty÷íÛg ÑÕˆacâ×èRà ;ã'ÀUzw‰“ôâlAÊ =Ý/^lÚa?FŽYh]t5âJþüùóM€ô™3g°hÑ"ãZÄ<º±NŠZ8ñgP±è.ňÆãõ×_¯§86l˜y§X¢‹-ÌS(Ÿ|n)°-åÁB`ßRîæCWòÒoŸ“ûGyÄd3&€·<ð€9ß°aÃsv[²ëéܹ3^}õU#.¸Ò^ÔDáÁÕ~NÌçÍ›g¬tobà±í>ä©.Æð:Æ°žF1L¬ƒPã$Ÿî<Ôµk×sªbO=õ” ªfüÝ­XMaAap×]w³ÛÒ9•è„ˆ€ˆ€ˆ€ˆ@™%ðÿ™w¥íÔ§"IEND®B`‚toil-releases-3.24.0/docs/running/cwl.rst000066400000000000000000000322241362134276200203100ustar00rootroot00000000000000.. _cwl: CWL in Toil =========== The Common Workflow Language (CWL) is an emerging standard for writing workflows that are portable across multiple workflow engines and platforms. Toil has full support for the CWL v1.0.1 specification. Running CWL Locally ------------------- The `toil-cwl-runner` command provides cwl-parsing functionality using cwltool, and leverages the job-scheduling and batch system support of Toil. To run in local batch mode, provide the CWL file and the input object file:: $ toil-cwl-runner example.cwl example-job.yml For a simple example of CWL with Toil see :ref:`cwlquickstart`. Note for macOS + Docker + Toil ++++++++++++++++++++++++++++++ When invoking CWL documents that make use of Docker containers if you see errors that look like :: docker: Error response from daemon: Mounts denied: The paths /var/...tmp are not shared from OS X and are not known to Docker. you may need to add :: export TMPDIR=/tmp/docker_tmp either in your startup file (``.bashrc``) or add it manually in your shell before invoking toil. Detailed Usage Instructions --------------------------- Help information can be found by using this toil command: :: $ toil-cwl-runner -h A more detailed example shows how we can specify both Toil and cwltool arguments for our workflow: :: $ toil-cwl-runner \ --singularity \ --jobStore my_jobStore \ --batchSystem lsf \ --workDir `pwd` \ --outdir `pwd` \ --logFile cwltoil.log \ --writeLogs `pwd` \ --logLevel DEBUG \ --retryCount 2 \ --disableCaching \ --maxLogFileSize 20000000000 \ --stats \ standard_bam_processing.cwl \ inputs.yaml In this example, we set the following options, which are all passed to Toil: ``--singularity``: Specifies that all jobs with Docker fornat containers specified should be run using the Singularity container engine instead of the Docker container engine. ``--jobStore``: Path to a folder that already exists, which will contain the Toil jobstore and all related job-tracking information. ``--batchSystem``: Use the specified HPC or Cloud-based cluster platform. ``--workDir``: The directory where all temporary files will be created for the workflow. A subdirectory of this will be set as the ``$TMPDIR`` environment variable and this subdirectory can be referenced using the CWL parameter reference ``$(runtime.tmpdir)`` in CWL tools and workflows. ``--outdir``: Directory where final ``File`` and ``Directory`` outputs will be written. References to these and other output types will be in the JSON object printed to the stdout stream after workflow execution. ``--logFile``: Path to the main logfile with logs from all jobs. ``--writeLogs``: Directory where all job logs will be stored. ``--retryCount``: How many times to retry each Toil job. ``--disableCaching``: Currently required for batch systems (LSF, slurm, gridengine, htcondor, torque) ``--maxLogFileSize``: Logs that get larger than this value will be truncated. ``--stats``: Save resources usages in json files that can be collected with the ``toil stats`` command after the workflow is done. Running CWL in the Cloud ------------------------ To run in cloud and HPC configurations, you may need to provide additional command line parameters to select and configure the batch system to use. To run a CWL workflow in AWS with toil see :ref:`awscwl`. .. _File literals: http://www.commonwl.org/v1.0/CommandLineTool.html#File .. _Directory: http://www.commonwl.org/v1.0/CommandLineTool.html#Directory .. _secondaryFiles: http://www.commonwl.org/v1.0/CommandLineTool.html#CommandInputParameter .. _InitialWorkDirRequirement: http://www.commonwl.org/v1.0/CommandLineTool.html#InitialWorkDirRequirement Running CWL within Toil Scripts ------------------------------------ A CWL workflow can be run indirectly in a native Toil script. However, this is not the :ref:`standard ` way to run CWL workflows with Toil and doing so comes at the cost of job efficiency. For some use cases, such as running one process on multiple files, it may be useful. For example, if you want to run a CWL workflow with 3 YML files specifying different samples inputs, it could look something like: .. literalinclude:: ../../src/toil/test/docs/scripts/tutorial_cwlexample.py Toil & CWL Tips --------------- **See logs for just one job by using the full log file** This requires knowing the job's toil-generated ID, which can be found in the log files. :: cat cwltoil.log | grep jobVM1fIs **Grep for full tool commands from toil logs** This gives you a more concise view of the commands being run (note that this information is only available from Toil when running with `--logDebug`). :: pcregrep -M "\[job .*\.cwl.*$\n(.* .*$\n)*" cwltoil.log # ^allows for multiline matching **Find Bams that have been generated for specific step while pipeline is running:** :: find . | grep -P '^./out_tmpdir.*_MD\.bam$' **See what jobs have been run** :: cat log/cwltoil.log | grep -oP "\[job .*.cwl\]" | sort | uniq or: :: cat log/cwltoil.log | grep -i "issued job" **Get status of a workflow** :: $ toil status /home/johnsoni/TEST_RUNS_3/TEST_run/tmp/jobstore-09ae0acc-c800-11e8-9d09-70106fb1697e 2018-10-04 15:01:44,184 MainThread INFO toil.lib.bioio: Root logger is at level 'INFO', 'toil' logger at level 'INFO'. 2018-10-04 15:01:44,185 MainThread INFO toil.utils.toilStatus: Parsed arguments 2018-10-04 15:01:47,081 MainThread INFO toil.utils.toilStatus: Traversing the job graph gathering jobs. This may take a couple of minutes. Of the 286 jobs considered, there are 179 jobs with children, 107 jobs ready to run, 0 zombie jobs, 0 jobs with services, 0 services, and 0 jobs with log files currently in file:/home/user/jobstore-09ae0acc-c800-11e8-9d09-70106fb1697e. **Toil Stats** You can get run statistics broken down by CWL file. This only works once the workflow is finished: :: $ toil stats /path/to/jobstore The output will contain CPU, memory, and walltime information for all CWL job types: :: 2018-10-15 12:06:19,003 MainThread INFO toil.lib.bioio: Root logger is at level 'INFO', 'toil' logger at level 'INFO'. 2018-10-15 12:06:19,004 MainThread INFO toil.utils.toilStats: Parsed arguments 2018-10-15 12:06:19,004 MainThread INFO toil.utils.toilStats: Checking if we have files for toil 2018-10-15 12:06:19,004 MainThread INFO toil.utils.toilStats: Checked arguments Batch System: lsf Default Cores: 1 Default Memory: 10485760K Max Cores: 9.22337e+18 Total Clock: 106608.01 Total Runtime: 86634.11 Worker Count | Time* | Clock | Wait | Memory n | min med* ave max total | min med ave max total | min med ave max total | min med ave max total 1659 | 0.00 0.80 264.87 12595.59 439424.40 | 0.00 0.46 449.05 42240.74 744968.80 | -35336.69 0.16 -184.17 4230.65 -305544.39 | 48K 223K 1020K 40235K 1692300K Job Worker Jobs | min med ave max | 1077 1077 1077 1077 Count | Time* | Clock | Wait | Memory n | min med* ave max total | min med ave max total | min med ave max total | min med ave max total 1077 | 0.04 1.18 407.06 12593.43 438404.73 | 0.01 0.28 691.17 42240.35 744394.14 | -35336.83 0.27 -284.11 4230.49 -305989.41 | 135K 268K 1633K 40235K 1759734K ResolveIndirect Count | Time* | Clock | Wait | Memory n | min med* ave max total | min med ave max total | min med ave max total | min med ave max total 205 | 0.04 0.07 0.16 2.29 31.95 | 0.01 0.02 0.02 0.14 3.60 | 0.02 0.05 0.14 2.28 28.35 | 190K 266K 256K 314K 52487K CWLGather Count | Time* | Clock | Wait | Memory n | min med* ave max total | min med ave max total | min med ave max total | min med ave max total 40 | 0.05 0.17 0.29 1.90 11.62 | 0.01 0.02 0.02 0.05 0.80 | 0.03 0.14 0.27 1.88 10.82 | 188K 265K 250K 316K 10039K CWLWorkflow Count | Time* | Clock | Wait | Memory n | min med* ave max total | min med ave max total | min med ave max total | min med ave max total 205 | 0.09 0.40 0.98 13.70 200.82 | 0.04 0.15 0.16 1.08 31.78 | 0.04 0.26 0.82 12.62 169.04 | 190K 270K 257K 316K 52826K file:///home/johnsoni/pipeline_0.0.39/ACCESS-Pipeline/cwl_tools/expression_tools/group_waltz_files.cwl Count | Time* | Clock | Wait | Memory n | min med* ave max total | min med ave max total | min med ave max total | min med ave max total 99 | 0.29 0.49 0.59 2.50 58.11 | 0.14 0.26 0.29 1.04 28.95 | 0.14 0.22 0.29 1.48 29.16 | 135K 135K 135K 136K 13459K file:///home/johnsoni/pipeline_0.0.39/ACCESS-Pipeline/cwl_tools/expression_tools/make_sample_output_dirs.cwl Count | Time* | Clock | Wait | Memory n | min med* ave max total | min med ave max total | min med ave max total | min med ave max total 11 | 0.34 0.52 0.74 2.63 8.18 | 0.20 0.30 0.41 1.17 4.54 | 0.14 0.20 0.33 1.45 3.65 | 136K 136K 136K 136K 1496K file:///home/johnsoni/pipeline_0.0.39/ACCESS-Pipeline/cwl_tools/expression_tools/consolidate_files.cwl Count | Time* | Clock | Wait | Memory n | min med* ave max total | min med ave max total | min med ave max total | min med ave max total 8 | 0.31 0.59 0.71 1.80 5.69 | 0.18 0.35 0.37 0.63 2.94 | 0.13 0.27 0.34 1.17 2.75 | 136K 136K 136K 136K 1091K file:///home/johnsoni/pipeline_0.0.39/ACCESS-Pipeline/cwl_tools/bwa-mem/bwa-mem.cwl Count | Time* | Clock | Wait | Memory n | min med* ave max total | min med ave max total | min med ave max total | min med ave max total 22 | 895.76 3098.13 3587.34 12593.43 78921.51 | 2127.02 7910.31 8123.06 16959.13 178707.34 | -11049.84 -3827.96 -4535.72 19.49 -99785.83 | 5659K 5950K 5854K 6128K 128807K **Understanding toil log files** There is a `worker_log.txt` file for each job, this file is written to while the job is running, and deleted after the job finishes. The contents are printed to the main log file and transferred to a log file in the `--logDir` folder once the job is completed successfully. The new log file will be named something like: :: file:.cwl_.log file:---home-johnsoni-pipeline_1.1.14-ACCESS--Pipeline-cwl_tools-marianas-ProcessLoopUMIFastq.cwl_I-O-jobfGsQQw000.log This is the toil job command with spaces replaced by dashes. toil-releases-3.24.0/docs/running/debugging.rst000066400000000000000000000037151362134276200214610ustar00rootroot00000000000000.. _debugging: Toil Debugging ============== Toil has a number of tools to assist in debugging. Here we provide help in working through potential problems that a user might encounter in attempting to run a workflow. Introspecting the Jobstore -------------------------- Note: Currently these features are only implemented for use locally (single machine) with the fileJobStore. To view what files currently reside in the jobstore, run the following command:: $ toil debug-file file:path-to-jobstore-directory --listFilesInJobStore When run from the commandline, this should generate a file containing the contents of the job store (in addition to displaying a series of log messages to the terminal). This file is named "jobstore_files.txt" by default and will be generated in the current working directory. If one wishes to copy any of these files to a local directory, one can run for example:: $ toil debug-file file:path-to-jobstore --fetch overview.txt *.bam *.fastq --localFilePath=/home/user/localpath To fetch ``overview.txt``, and all ``.bam`` and ``.fastq`` files. This can be used to recover previously used input and output files for debugging or reuse in other workflows, or use in general debugging to ensure that certain outputs were imported into the jobStore. Stats and Status ---------------- See :ref:`cli_status` for more about gathering statistics about job success, runtime, and resource usage from workflows. Using a Python debugger ----------------------- If you execute a workflow using the :code:`--debugWorker` flag, Toil will not fork in order to run jobs, which means you can either use `pdb `_, or an `IDE that supports debugging Python `_ as you would normally. Note that the :code:`--debugWorker` flag will only work with the :code:`singleMachine` batch system (the default), and not any of the custom job schedulers.toil-releases-3.24.0/docs/running/hpcEnvironments.rst000066400000000000000000000045631362134276200227120ustar00rootroot00000000000000.. _hpcEnvironmentsOverview: HPC Environments ================ Toil is a flexible framework that can be leveraged in a variety of environments, including high-performance computing (HPC) environments. Toil provides support for a number of batch systems, including `Grid Engine`_, `Slurm`_, `Torque`_ and `LSF`_, which are popular schedulers used in these environments. Toil also supports `HTCondor`_, which is a popular scheduler for high-throughput computing (HTC). To use one of these batch systems specify the "-\\-batchSystem" argument to the toil script. Due to the cost and complexity of maintaining support for these schedulers we currently consider them to be "community supported", that is the core development team does not regularly test or develop support for these systems. However, there are members of the Toil community currently deploying Toil in HPC environments and we welcome external contributions. Developing the support of a new or existing batch system involves extending the abstract batch system class :class:`toil.batchSystems.abstractBatchSystem.AbstractBatchSystem`. Standard Output/Error from Batch System Jobs -------------------------------------------- Standard output and error from batch system jobs (except for the Parasol and Mesos batch systems) are redirected to files in the ``toil-`` directory created within the temporary directory specified by the ``--workDir`` option; see :ref:`optionsRef`. Each file is named as follows: ``toil_job__batch___.log``, where ```` is ``std_output`` for standard output, and ``std_error`` for standard error. HTCondor will also write job event log files with `` = job_events``. If capturing standard output and error is desired, ``--workDir`` will generally need to be on a shared file system; otherwise if these are written to local temporary directories on each node (e.g. ``/tmp``) Toil will not be able to retrieve them. Alternatively, the ``--noStdOutErr`` option forces Toil to discard all standard output and error from batch system jobs. .. _Grid Engine: http://www.univa.com/oracle .. _Slurm: https://www.schedmd.com/ .. _Torque: http://www.adaptivecomputing.com/products/open-source/torque/ .. _LSF: https://en.wikipedia.org/wiki/Platform_LSF .. _HTCondor: https://research.cs.wisc.edu/htcondor/ toil-releases-3.24.0/docs/running/introduction.rst000066400000000000000000000071241362134276200222450ustar00rootroot00000000000000.. _runningOverview: Introduction ============ Toil runs in various environments, including :ref:`locally ` and :ref:`in the cloud ` (Amazon Web Services and Google Compute Engine). Toil also supports two DSLs: :ref:`CWL ` and (Amazon Web Services and Google Compute Engine). Toil also supports two DSLs: :ref:`CWL ` and :ref:`WDL ` (experimental). Toil is built in a modular way so that it can be used on lots of different systems, and with different configurations. The three configurable pieces are the - :ref:`jobStoreInterface`: A filepath or url that can host and centralize all files for a workflow (e.g. a local folder, or an AWS s3 bucket url). - :ref:`batchSystemInterface`: Specifies either a local single-machine or a currently supported HPC environment (lsf, parasol, mesos, slurm, torque, htcondor, or gridengine). Mesos is a special case, and is launched for cloud environments. - :ref:`provisionerOverview`: For running in the cloud only. This specifies which cloud provider provides instances to do the "work" of your workflow. .. _jobStoreOverview: Job Store --------- The job store is a storage abstraction which contains all of the information used in a Toil run. This centralizes all of the files used by jobs in the workflow and also the details of the progress of the run. If a workflow crashes or fails, the job store contains all of the information necessary to resume with minimal repetition of work. Several different job stores are supported, including the file job store and cloud job stores. .. _fileJobStore: File Job Store ~~~~~~~~~~~~~~ The file job store is for use locally, and keeps the workflow information in a directory on the machine where the workflow is launched. This is the simplest and most convenient job store for testing or for small runs. For an example that uses the file job store, see :ref:`quickstart`. Cloud Job Stores ~~~~~~~~~~~~~~~~ Toil currently supports the following cloud storage systems as job stores: - :ref:`awsJobStore`: An AWS S3 bucket formatted as "aws::" where only numbers, letters, and dashes are allowed in the bucket name. Example: `aws:us-west-2:my-aws-jobstore-name`. - :ref:`googleJobStore`: A Google Cloud Storage bucket formatted as "gce::" where only numbers, letters, and dashes are allowed in the bucket name. Example: `gce:us-west2-a:my-google-jobstore-name`. These use cloud buckets to house all of the files. This is useful if there are several different worker machines all running jobs that need to access the job store. .. _batchSystemOverview: Batch System ------------ A Toil batch system is either a local single-machine (one computer) or a currently supported HPC cluster of computers (lsf, parasol, mesos, slurm, torque, htcondor, or gridengine). Mesos is a special case, and is launched for cloud environments. These environments manage individual worker nodes under a leader node to process the work required in a workflow. The leader and its workers all coordinate their tasks and files through a centralized job store location. See :ref:`batchSystemInterface` for a more detailed description of different batch systems. .. _provisionerOverview: Provisioner ----------- The Toil provisioner provides a tool set for running a Toil workflow on a particular cloud platform. The :ref:`clusterRef` are command line tools used to provision nodes in your desired cloud platform. They allows you to launch nodes, ssh to the leader, and rsync files back and forth. For detailed instructions for using the provisioner see :ref:`runningAWS` or :ref:`runningGCE`. toil-releases-3.24.0/docs/running/wdl.rst000066400000000000000000000143751362134276200203200ustar00rootroot00000000000000.. _wdl: WDL in Toil *********** Support is still in the alpha phase and should be able to handle basic wdl files. See the specification below for more details. How to Run a WDL file in Toil ----------------------------- Recommended best practice when running wdl files is to first use the Broad's wdltool for syntax validation and generating the needed json input file. Full documentation can be found on the repository_, and a precompiled jar binary can be downloaded here: wdltool_ (this requires java7_). That means two steps. First, make sure your wdl file is valid and devoid of syntax errors by running ``java -jar wdltool.jar validate example_wdlfile.wdl`` Second, generate a complementary json file if your wdl file needs one. This json will contain keys for every necessary input that your wdl file needs to run: ``java -jar wdltool.jar inputs example_wdlfile.wdl`` When this json template is generated, open the file, and fill in values as necessary by hand. WDL files all require json files to accompany them. If no variable inputs are needed, a json file containing only '{}' may be required. Once a wdl file is validated and has an appropriate json file, workflows can be run in toil using: ``toil-wdl-runner example_wdlfile.wdl example_jsonfile.json`` See options below for more parameters. ENCODE Example from ENCODE-DCC ------------------------------ To follow this example, you will need docker installed. The original workflow can be found here: https://github.com/ENCODE-DCC/pipeline-container We've included the wdl file and data files in the toil repository needed to run this example. First, download the example code_ and unzip. The file needed is "testENCODE/encode_mapping_workflow.wdl". Next, use wdltool_ (this requires java7_) to validate this file: ``java -jar wdltool.jar validate encode_mapping_workflow.wdl`` Next, use wdltool to generate a json file for this wdl file: ``java -jar wdltool.jar inputs encode_mapping_workflow.wdl`` This json file once opened should look like this:: { "encode_mapping_workflow.fastqs": "Array[File]", "encode_mapping_workflow.trimming_parameter": "String", "encode_mapping_workflow.reference": "File" } The trimming_parameter should be set to 'native'. Download the example code_ and unzip. Inside are two data files required for the run ``ENCODE_data/reference/GRCh38_chr21_bwa.tar.gz`` ``ENCODE_data/ENCFF000VOL_chr21.fq.gz`` Editing the json to include these as inputs, the json should now look something like this:: { "encode_mapping_workflow.fastqs": ["/path/to/unzipped/ENCODE_data/ENCFF000VOL_chr21.fq.gz"], "encode_mapping_workflow.trimming_parameter": "native", "encode_mapping_workflow.reference": "/path/to/unzipped/ENCODE_data/reference/GRCh38_chr21_bwa.tar.gz" } The wdl and json files can now be run using the command ``toil-wdl-runner encode_mapping_workflow.wdl encode_mapping_workflow.json`` This should deposit the output files in the user's current working directory (to change this, specify a new directory with the '-o' option). GATK Examples from the Broad ---------------------------- Simple examples of WDL can be found on the Broad's website as tutorials: https://software.broadinstitute.org/wdl/documentation/topic?name=wdl-tutorials. One can follow along with these tutorials, write their own wdl files following the directions and run them using either cromwell or toil. For example, in tutorial 1, if you've followed along and named your wdl file 'helloHaplotypeCall.wdl', then once you've validated your wdl file using wdltool_ (this requires java7_) using ``java -jar wdltool.jar validate helloHaplotypeCaller.wdl`` and generated a json file (and subsequently typed in appropriate filepaths* and variables) using ``java -jar wdltool.jar inputs helloHaplotypeCaller.wdl`` * Absolute filepath inputs are recommended for local testing. then the wdl script can be run using ``toil-wdl-runner helloHaplotypeCaller.wdl helloHaplotypeCaller_inputs.json`` toilwdl.py Options ------------------ **'-o'** or **'-\\-output_directory'**: Specifies the output folder, and defaults to the current working directory if not specified by the user. **'-\\-gen_parse_files'**: Creates "AST.out", which holds a printed AST of the wdl file and "mappings.out", which holds the printed task, workflow, csv, and tsv dictionaries generated by the parser. **'-\\-dont_delete_compiled'**: Saves the compiled toil python workflow file for debugging. Any number of arbitrary options may also be specified. These options will not be parsed immediately, but passed down as toil options once the wdl/json files are processed. For valid toil options, see the documentation: http://toil.readthedocs.io/en/latest/running/cliOptions.html Running WDL within Toil Scripts ------------------------------------ .. note:: A cromwell.jar file is needed in order to run a WDL workflow. A WDL workflow can be run indirectly in a native Toil script. However, this is not the :ref:`standard ` way to run WDL workflows with Toil and doing so comes at the cost of job efficiency. For some use cases, such as running one process on multiple files, it may be useful. For example, if you want to run a WDL workflow with 3 JSON files specifying different samples inputs, it could look something like: .. literalinclude:: ../../src/toil/test/docs/scripts/tutorial_wdlexample.py WDL Specifications ------------------ WDL language specifications can be found here: https://github.com/broadinstitute/wdl/blob/develop/SPEC.md Implementing support for more features is currently underway, but a basic roadmap so far is: CURRENTLY IMPLEMENTED: * Scatter * Many Built-In Functions * Docker Calls * Handles Priority, and Output File Wrangling * Currently Handles Primitives and Arrays TO BE IMPLEMENTED: * Integrate Cloud Autoscaling Capacity More Robustly * WDL Files That "Import" Other WDL Files (Including URI Handling for 'http://' and 'https://') .. _repository: https://github.com/broadinstitute/wdltool .. _wdltool: https://github.com/broadinstitute/wdltool/releases .. _java7: http://www.oracle.com/technetwork/java/javase/downloads/java-archive-downloads-javase7-521261.html .. _here: https://github.com/BD2KGenomics/toil/tree/master/src/toil/test/wdl/ENCODE_data.zip .. _code: http://toil-datasets.s3.amazonaws.com/ENCODE_data.zip toil-releases-3.24.0/docs/vendor/000077500000000000000000000000001362134276200166035ustar00rootroot00000000000000toil-releases-3.24.0/docs/vendor/sphinxcontrib/000077500000000000000000000000001362134276200214755ustar00rootroot00000000000000toil-releases-3.24.0/docs/vendor/sphinxcontrib/__init__.py000066400000000000000000000005531362134276200236110ustar00rootroot00000000000000# -*- coding: utf-8 -*- """ sphinxcontrib ~~~~~~~~~~~~~ This package is a namespace package that contains all extensions distributed in the ``sphinx-contrib`` distribution. :copyright: Copyright 2007-2009 by the Sphinx team, see AUTHORS. :license: BSD, see LICENSE for details. """ __import__('pkg_resources').declare_namespace(__name__) toil-releases-3.24.0/docs/vendor/sphinxcontrib/fulltoc.py000066400000000000000000000063311362134276200235220ustar00rootroot00000000000000# -*- encoding: utf-8 -*- # # Copyright © 2012 New Dream Network, LLC (DreamHost) # # Author: Doug Hellmann # # 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. from sphinx import addnodes def html_page_context(app, pagename, templatename, context, doctree): """Event handler for the html-page-context signal. Modifies the context directly. - Replaces the 'toc' value created by the HTML builder with one that shows all document titles and the local table of contents. - Sets display_toc to True so the table of contents is always displayed, even on empty pages. - Replaces the 'toctree' function with one that uses the entire document structure, ignores the maxdepth argument, and uses only prune and collapse. """ rendered_toc = get_rendered_toctree(app.builder, pagename) context['toc'] = rendered_toc context['display_toc'] = True # force toctree to display if "toctree" not in context: # json builder doesn't use toctree func, so nothing to replace return def make_toctree(collapse=True): return get_rendered_toctree(app.builder, pagename, prune=False, collapse=collapse, ) context['toctree'] = make_toctree def get_rendered_toctree(builder, docname, prune=False, collapse=True): """Build the toctree relative to the named document, with the given parameters, and then return the rendered HTML fragment. """ fulltoc = build_full_toctree(builder, docname, prune=prune, collapse=collapse, ) rendered_toc = builder.render_partial(fulltoc)['fragment'] return rendered_toc def build_full_toctree(builder, docname, prune, collapse): """Return a single toctree starting from docname containing all sub-document doctrees. """ env = builder.env doctree = env.get_doctree(env.config.master_doc) toctrees = [] for toctreenode in doctree.traverse(addnodes.toctree): toctree = env.resolve_toctree(docname, builder, toctreenode, collapse=collapse, prune=prune, ) toctrees.append(toctree) if not toctrees: return None result = toctrees[0] for toctree in toctrees[1:]: if toctree: result.extend(toctree.children) env.resolve_references(result, docname, builder) return result def setup(app): app.connect('html-page-context', html_page_context) toil-releases-3.24.0/examples000077700000000000000000000000001362134276200232502src/toil/test/docs/scripts/ustar00rootroot00000000000000toil-releases-3.24.0/setup.cfg000066400000000000000000000002661362134276200162030ustar00rootroot00000000000000[tool:pytest] # Look for any python file, the default of test_*.py wouldn't work for us python_files=*.py # Also run doctestsi addopts = --doctest-modules --tb=native --assert=plain toil-releases-3.24.0/setup.py000066400000000000000000000175741362134276200161060ustar00rootroot00000000000000# Copyright (C) 2015-2016 Regents of the University of California # # 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. from setuptools import find_packages, setup import sys import os import copy # setting the 'CPPFLAGS' flag specifies the necessary cython dependency for "http-parser", for more info: # toil issue: https://github.com/DataBiosphere/toil/issues/2924 # very similar to this issue: https://github.com/mcfletch/pyopengl/issues/11 # the "right way" is waiting for a fix from "http-parser", but this fixes things in the meantime since that might take a while cppflags = os.environ.get('CPPFLAGS') if cppflags: # note, duplicate options don't affect things here so we don't check - Mark D os.environ['CPPFLAGS'] = ' '.join([cppflags, '-DPYPY_VERSION']) else: os.environ['CPPFLAGS'] = '-DPYPY_VERSION' def runSetup(): """ Calls setup(). This function exists so the setup() invocation preceded more internal functionality. The `version` module is imported dynamically by importVersion() below. """ boto = 'boto==2.48.0' boto3 = 'boto3>=1.7.50, <2.0' futures = 'futures==3.1.1' pycryptodome = 'pycryptodome==3.5.1' pymesos = 'pymesos==0.3.7' psutil = 'psutil >= 3.0.1, <6' pynacl = 'pynacl==1.1.2' gcs = 'google-cloud-storage==1.6.0' gcs_oauth2_boto_plugin = 'gcs_oauth2_boto_plugin==1.14' apacheLibcloud = 'apache-libcloud==2.2.1' cwltool = 'cwltool==1.0.20190906054215' schemaSalad = 'schema-salad<5,>=4.5.20190815125611' galaxyLib = 'galaxy-lib==18.9.2' htcondor = 'htcondor>=8.6.0' kubernetes = 'kubernetes>=10, <11' pytx = 'pytz>=2012' dill = 'dill==0.2.7.1' six = 'six>=1.10.0' future = 'future' requests = 'requests>=2, <3' docker = 'docker==2.5.1' subprocess32 = 'subprocess32<=3.5.2' dateutil = 'python-dateutil' addict = 'addict<=2.2.0' sphinx = 'sphinx==1.7.5' pathlib2 = 'pathlib2==2.3.2' core_reqs = [ dill, six, future, requests, docker, dateutil, psutil, subprocess32, addict, sphinx, pathlib2] aws_reqs = [ boto, boto3, futures, pycryptodome] cwl_reqs = [ cwltool, schemaSalad, galaxyLib] encryption_reqs = [ pynacl] google_reqs = [ gcs_oauth2_boto_plugin, # is this being used?? apacheLibcloud, gcs] htcondor_reqs = [ htcondor] kubernetes_reqs = [ kubernetes] mesos_reqs = [ pymesos, psutil] wdl_reqs = [] # htcondor is not supported by apple # this is tricky to conditionally support in 'all' due # to how wheels work, so it is not included in all and # must be explicitly installed as an extra all_reqs = \ aws_reqs + \ cwl_reqs + \ encryption_reqs + \ google_reqs + \ kubernetes_reqs + \ mesos_reqs # remove the subprocess32 backport if not python2 if not sys.version_info[0] == 2: core_reqs.remove(subprocess32) setup( name='toil', version=version.distVersion, description='Pipeline management software for clusters.', author='Benedict Paten', author_email='benedict@soe.usc.edu', url="https://github.com/BD2KGenomics/toil", classifiers=[ 'Development Status :: 5 - Production/Stable', 'Environment :: Console', 'Intended Audience :: Developers', 'Intended Audience :: Science/Research', 'Intended Audience :: Healthcare Industry', 'License :: OSI Approved :: Apache Software License', 'Natural Language :: English', 'Operating System :: MacOS :: MacOS X', 'Operating System :: POSIX', 'Operating System :: POSIX :: Linux', 'Programming Language :: Python :: 2.7', 'Programming Language :: Python :: 3.5', 'Programming Language :: Python :: 3.6', 'Topic :: Scientific/Engineering', 'Topic :: Scientific/Engineering :: Bio-Informatics', 'Topic :: Scientific/Engineering :: Astronomy', 'Topic :: Scientific/Engineering :: Atmospheric Science', 'Topic :: Scientific/Engineering :: Information Analysis', 'Topic :: Scientific/Engineering :: Medical Science Apps.', 'Topic :: System :: Distributed Computing', 'Topic :: Utilities'], license="Apache License v2.0", install_requires=core_reqs, extras_require={ 'aws': aws_reqs, 'cwl': cwl_reqs, 'encryption': encryption_reqs, 'google': google_reqs, 'htcondor:sys_platform!="darwin"': htcondor_reqs, 'kubernetes': kubernetes_reqs, 'mesos': mesos_reqs, 'wdl': wdl_reqs, 'all': all_reqs}, package_dir={'': 'src'}, packages=find_packages(where='src', # Note that we intentionally include the top-level `test` package for # functionality like the @experimental and @integrative decoratorss: exclude=['*.test.*']), package_data = { '': ['*.yml', 'cloud-config'], }, # Unfortunately, the names of the entry points are hard-coded elsewhere in the code base so # you can't just change them here. Luckily, most of them are pretty unique strings, and thus # easy to search for. entry_points={ 'console_scripts': [ 'toil = toil.utils.toilMain:main', '_toil_worker = toil.worker:main', 'cwltoil = toil.cwl.cwltoil:main [cwl]', 'toil-cwl-runner = toil.cwl.cwltoil:main [cwl]', 'toil-wdl-runner = toil.wdl.toilwdl:main', '_toil_mesos_executor = toil.batchSystems.mesos.executor:main [mesos]', '_toil_kubernetes_executor = toil.batchSystems.kubernetes:executor [kubernetes]']}) def importVersion(): """ Load and return the module object for src/toil/version.py, generating it from the template if required. """ import imp try: # Attempt to load the template first. It only exists in a working copy cloned via git. import version_template except ImportError: # If loading the template fails we must be in a unpacked source distribution and # src/toil/version.py will already exist. pass else: # Use the template to generate src/toil/version.py import os import errno from tempfile import NamedTemporaryFile new = version_template.expand_() try: with open('src/toil/version.py') as f: old = f.read() except IOError as e: if e.errno == errno.ENOENT: old = None else: raise if old != new: with NamedTemporaryFile(mode='w',dir='src/toil', prefix='version.py.', delete=False) as f: f.write(new) os.rename(f.name, 'src/toil/version.py') # Unfortunately, we can't use a straight import here because that would also load the stuff # defined in src/toil/__init__.py which imports modules from external dependencies that may # yet to be installed when setup.py is invoked. return imp.load_source('toil.version', 'src/toil/version.py') version = importVersion() runSetup() toil-releases-3.24.0/setup_gitlab_docker.py000066400000000000000000000015101362134276200207360ustar00rootroot00000000000000import json import os import subprocess import sys env_var = 'GITLAB_SECRET_FILE_QUAY_CREDENTIALS' if env_var not in os.environ: print('Error: could not find environment variable ' + env_var) sys.exit(1) print('Starting quay.io login process...') with open(os.environ[env_var], 'r') as f: keys = json.load(f) process = subprocess.Popen('docker login quay.io -u "{user}" --password-stdin'.format(user=keys['user']), stdout=subprocess.PIPE, stderr=subprocess.PIPE, stdin=subprocess.PIPE, shell=True) print('Logging into quay.io...') stdout, stderr = process.communicate(input=keys['password'].encode('utf-8')) if 'Login Succeeded' in str(stdout): print('Login Succeeded.') else: print('Error while attempting to log into quay.io:\n' + str(stderr)) sys.exit(1) toil-releases-3.24.0/setup_gitlab_ssh.py000066400000000000000000000016331362134276200202720ustar00rootroot00000000000000import json import os good_spot = os.path.expanduser('~/.ssh') if not os.path.exists(good_spot): os.mkdir(good_spot) def format_private_key(private_key): private_key_header = '-----BEGIN RSA PRIVATE KEY-----' private_key_footer = '-----END RSA PRIVATE KEY-----' assert private_key.startswith(private_key_header) private_key_body = private_key[len(private_key_header):] assert private_key_body.endswith(private_key_footer) private_key_body = private_key_body[:-len(private_key_footer)] return private_key_header + private_key_body.replace(' ', '\n') + private_key_footer with open(os.environ['GITLAB_SECRET_FILE_SSH_KEYS'], 'r') as keys_json_file: keys = json.loads(keys_json_file.read()) with open(os.path.join(good_spot, 'id_rsa.pub'), 'w') as f: f.write(keys['public']) with open(os.path.join(good_spot, 'id_rsa'), 'w') as f: f.write(format_private_key(keys['private'])) toil-releases-3.24.0/src/000077500000000000000000000000001362134276200151455ustar00rootroot00000000000000toil-releases-3.24.0/src/toil/000077500000000000000000000000001362134276200161145ustar00rootroot00000000000000toil-releases-3.24.0/src/toil/__init__.py000066400000000000000000000701321362134276200202300ustar00rootroot00000000000000 # Copyright (C) 2015-2018 Regents of the University of California # # 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. from __future__ import absolute_import import errno import logging import os import requests import sys import time from datetime import datetime from pytz import timezone from docker.errors import ImageNotFound from toil.lib.memoize import memoize from toil.lib.misc import mkdir_p from toil.lib.retry import retry from toil.version import currentCommit # subprocess32 is a backport of python3's subprocess module for use on Python2, # and includes many reliability bug fixes relevant on POSIX platforms. if os.name == 'posix' and sys.version_info[0] < 3: import subprocess32 as subprocess else: import subprocess try: import cPickle as pickle except ImportError: import pickle try: from urllib import urlretrieve except ImportError: from urllib.request import urlretrieve log = logging.getLogger(__name__) def which(cmd, mode=os.F_OK | os.X_OK, path=None): """ Copy-pasted in from python3.6's shutil.which(). Given a command, mode, and a PATH string, return the path which conforms to the given mode on the PATH, or None if there is no such file. `mode` defaults to os.F_OK | os.X_OK. `path` defaults to the result of os.environ.get("PATH"), or can be overridden with a custom search path. """ # Check that a given file can be accessed with the correct mode. # Additionally check that `file` is not a directory, as on Windows # directories pass the os.access check. def _access_check(fn, mode): return (os.path.exists(fn) and os.access(fn, mode) and not os.path.isdir(fn)) # If we're given a path with a directory part, look it up directly rather # than referring to PATH directories. This includes checking relative to the # current directory, e.g. ./script if os.path.dirname(cmd): if _access_check(cmd, mode): return cmd return None if path is None: path = os.environ.get("PATH", os.defpath) if not path: return None path = path.split(os.pathsep) if sys.platform == "win32": # The current directory takes precedence on Windows. if not os.curdir in path: path.insert(0, os.curdir) # PATHEXT is necessary to check on Windows. pathext = os.environ.get("PATHEXT", "").split(os.pathsep) # See if the given file matches any of the expected path extensions. # This will allow us to short circuit when given "python.exe". # If it does match, only test that one, otherwise we have to try # others. if any(cmd.lower().endswith(ext.lower()) for ext in pathext): files = [cmd] else: files = [cmd + ext for ext in pathext] else: # On other platforms you don't have things like PATHEXT to tell you # what file suffixes are executable, so just pass on cmd as-is. files = [cmd] seen = set() for dir in path: normdir = os.path.normcase(dir) if not normdir in seen: seen.add(normdir) for thefile in files: name = os.path.join(dir, thefile) if _access_check(name, mode): return name return None def toilPackageDirPath(): """ Returns the absolute path of the directory that corresponds to the top-level toil package. The return value is guaranteed to end in '/toil'. """ result = os.path.dirname(os.path.realpath(__file__)) assert result.endswith('/toil') return result def inVirtualEnv(): """ Returns whether we are inside a virtualenv or Conda virtual environment. """ return hasattr(sys, 'real_prefix') or 'CONDA_DEFAULT_ENV' in os.environ def resolveEntryPoint(entryPoint): """ Returns the path to the given entry point (see setup.py) that *should* work on a worker. The return value may be an absolute or a relative path. """ if os.environ.get("TOIL_CHECK_ENV", None) == 'True' and inVirtualEnv(): path = os.path.join(os.path.dirname(sys.executable), entryPoint) # Inside a virtualenv we try to use absolute paths to the entrypoints. if os.path.isfile(path): # If the entrypoint is present, Toil must have been installed into the virtualenv (as # opposed to being included via --system-site-packages). For clusters this means that # if Toil is installed in a virtualenv on the leader, it must be installed in # a virtualenv located at the same path on each worker as well. assert os.access(path, os.X_OK) return path # Otherwise, we aren't in a virtualenv, or we're in a virtualenv but Toil # came in via --system-site-packages, or we think the virtualenv might not # exist on the workers. return entryPoint @memoize def physicalMemory(): """ >>> n = physicalMemory() >>> n > 0 True >>> n == physicalMemory() True """ try: return os.sysconf('SC_PAGE_SIZE') * os.sysconf('SC_PHYS_PAGES') except ValueError: return int(subprocess.check_output(['sysctl', '-n', 'hw.memsize']).decode('utf-8').strip()) def physicalDisk(config, toilWorkflowDir=None): if toilWorkflowDir is None: from toil.common import Toil toilWorkflowDir = Toil.getWorkflowDir(config.workflowID, config.workDir) diskStats = os.statvfs(toilWorkflowDir) return diskStats.f_frsize * diskStats.f_bavail def applianceSelf(forceDockerAppliance=False): """ Returns the fully qualified name of the Docker image to start Toil appliance containers from. The result is determined by the current version of Toil and three environment variables: ``TOIL_DOCKER_REGISTRY``, ``TOIL_DOCKER_NAME`` and ``TOIL_APPLIANCE_SELF``. ``TOIL_DOCKER_REGISTRY`` specifies an account on a publicly hosted docker registry like Quay or Docker Hub. The default is UCSC's CGL account on Quay.io where the Toil team publishes the official appliance images. ``TOIL_DOCKER_NAME`` specifies the base name of the image. The default of `toil` will be adequate in most cases. ``TOIL_APPLIANCE_SELF`` fully qualifies the appliance image, complete with registry, image name and version tag, overriding both ``TOIL_DOCKER_NAME`` and `TOIL_DOCKER_REGISTRY`` as well as the version tag of the image. Setting TOIL_APPLIANCE_SELF will not be necessary in most cases. :rtype: str """ import toil.version registry = lookupEnvVar(name='docker registry', envName='TOIL_DOCKER_REGISTRY', defaultValue=toil.version.dockerRegistry) name = lookupEnvVar(name='docker name', envName='TOIL_DOCKER_NAME', defaultValue=toil.version.dockerName) appliance = lookupEnvVar(name='docker appliance', envName='TOIL_APPLIANCE_SELF', defaultValue=registry + '/' + name + ':' + toil.version.dockerTag) checkDockerSchema(appliance) if forceDockerAppliance: return appliance else: return checkDockerImageExists(appliance=appliance) def customDockerInitCmd(): """ Returns the custom command (if any) provided through the ``TOIL_CUSTOM_DOCKER_INIT_COMMAND`` environment variable to run prior to running the workers and/or the primary node's services. This can be useful for doing any custom initialization on instances (e.g. authenticating to private docker registries). An empty string is returned if the environment variable is not set. :rtype: str """ command = lookupEnvVar(name='user-defined custom docker init command', envName='TOIL_CUSTOM_DOCKER_INIT_COMMAND', defaultValue='') return command.replace("'", "'\\''") # Ensure any single quotes are escaped. def lookupEnvVar(name, envName, defaultValue): """ Use this for looking up environment variables that control Toil and are important enough to log the result of that lookup. :param str name: the human readable name of the variable :param str envName: the name of the environment variable to lookup :param str defaultValue: the fall-back value :return: the value of the environment variable or the default value the variable is not set :rtype: str """ try: value = os.environ[envName] except KeyError: log.info('Using default %s of %s as %s is not set.', name, defaultValue, envName) return defaultValue else: log.info('Overriding %s of %s with %s from %s.', name, defaultValue, value, envName) return value def checkDockerImageExists(appliance): """ Attempts to check a url registryName for the existence of a docker image with a given tag. :param str appliance: The url of a docker image's registry (with a tag) of the form: 'quay.io/:' or ':'. Examples: 'quay.io/ucsc_cgl/toil:latest', 'ubuntu:latest', or 'broadinstitute/genomes-in-the-cloud:2.0.0'. :return: Raises an exception if the docker image cannot be found or is invalid. Otherwise, it will return the appliance string. :rtype: str """ if currentCommit in appliance: return appliance registryName, imageName, tag = parseDockerAppliance(appliance) if registryName == 'docker.io': return requestCheckDockerIo(origAppliance=appliance, imageName=imageName, tag=tag) else: return requestCheckRegularDocker(origAppliance=appliance, registryName=registryName, imageName=imageName, tag=tag) def parseDockerAppliance(appliance): """ Takes string describing a docker image and returns the parsed registry, image reference, and tag for that image. Example: "quay.io/ucsc_cgl/toil:latest" Should return: "quay.io", "ucsc_cgl/toil", "latest" If a registry is not defined, the default is: "docker.io" If a tag is not defined, the default is: "latest" :param appliance: The full url of the docker image originally specified by the user (or the default). e.g. "quay.io/ucsc_cgl/toil:latest" :return: registryName, imageName, tag """ appliance = appliance.lower() # get the tag if ':' in appliance: tag = appliance.split(':')[-1] appliance = appliance[:-(len(':' + tag))] # remove only the tag else: # default to 'latest' if no tag is specified tag = 'latest' # get the registry and image registryName = 'docker.io' # default if not specified imageName = appliance # will be true if not specified if '/' in appliance and '.' in appliance.split('/')[0]: registryName = appliance.split('/')[0] imageName = appliance[len(registryName):] registryName = registryName.strip('/') imageName = imageName.strip('/') return registryName, imageName, tag def checkDockerSchema(appliance): if not appliance: raise ImageNotFound("No docker image specified.") elif '://' in appliance: raise ImageNotFound("Docker images cannot contain a schema (such as '://'): %s" "" % appliance) elif len(appliance) > 256: raise ImageNotFound("Docker image must be less than 256 chars: %s" "" % appliance) class ApplianceImageNotFound(ImageNotFound): """ Compose an ApplianceImageNotFound error complaining that the given name and tag for TOIL_APPLIANCE_SELF specify an image manifest which could not be retrieved from the given URL, because it produced the given HTTP error code. :param str origAppliance: The full url of the docker image originally specified by the user (or the default). e.g. "quay.io/ucsc_cgl/toil:latest" :param str url: The URL at which the image's manifest is supposed to appear :param int statusCode: the failing HTTP status code returned by the URL """ def __init__(self, origAppliance, url, statusCode): msg = ("The docker image that TOIL_APPLIANCE_SELF specifies (%s) produced " "a nonfunctional manifest URL (%s). The HTTP status returned was %s. " "The specifier is most likely unsupported or malformed. " "Please supply a docker image with the format: " "'.io/:' or ':' " "(for official docker.io images). Examples: " "'quay.io/ucsc_cgl/toil:latest', 'ubuntu:latest', or " "'broadinstitute/genomes-in-the-cloud:2.0.0'." "" % (origAppliance, url, str(statusCode))) super(ApplianceImageNotFound, self).__init__(msg) def requestCheckRegularDocker(origAppliance, registryName, imageName, tag): """ Checks to see if an image exists using the requests library. URL is based on the docker v2 schema described here: https://docs.docker.com/registry/spec/manifest-v2-2/ This has the following format: https://{websitehostname}.io/v2/{repo}/manifests/{tag} Does not work with the official (docker.io) site, because they require an OAuth token, so a separate check is done for docker.io images. :param str origAppliance: The full url of the docker image originally specified by the user (or the default). e.g. "quay.io/ucsc_cgl/toil:latest" :param str registryName: The url of a docker image's registry. e.g. "quay.io" :param str imageName: The image, including path and excluding the tag. e.g. "ucsc_cgl/toil" :param str tag: The tag used at that docker image's registry. e.g. "latest" :return: Return True if match found. Raise otherwise. """ ioURL = 'https://{webhost}/v2/{pathName}/manifests/{tag}' \ ''.format(webhost=registryName, pathName=imageName, tag=tag) response = requests.head(ioURL) if not response.ok: raise ApplianceImageNotFound(origAppliance, ioURL, response.status_code) else: return origAppliance def requestCheckDockerIo(origAppliance, imageName, tag): """ Checks docker.io to see if an image exists using the requests library. URL is based on the docker v2 schema. Requires that an access token be fetched first. :param str origAppliance: The full url of the docker image originally specified by the user (or the default). e.g. "ubuntu:latest" :param str imageName: The image, including path and excluding the tag. e.g. "ubuntu" :param str tag: The tag used at that docker image's registry. e.g. "latest" :return: Return True if match found. Raise otherwise. """ # only official images like 'busybox' or 'ubuntu' if '/' not in imageName: imageName = 'library/' + imageName token_url = 'https://auth.docker.io/token?service=registry.docker.io&scope=repository:{repo}:pull'.format(repo=imageName) requests_url = 'https://registry-1.docker.io/v2/{repo}/manifests/{tag}'.format(repo=imageName, tag=tag) token = requests.get(token_url) jsonToken = token.json() bearer = jsonToken["token"] response = requests.head(requests_url, headers={'Authorization': 'Bearer {}'.format(bearer)}) if not response.ok: raise ApplianceImageNotFound(origAppliance, requests_url, response.status_code) else: return origAppliance def logProcessContext(config): # toil.version.version (string) cannot be imported at top level because it conflicts with # toil.version (module) and Sphinx doesn't like that. from toil.version import version log.info("Running Toil version %s.", version) log.debug("Configuration: %s", config.__dict__) try: from boto import provider from botocore.session import Session from botocore.credentials import create_credential_resolver, RefreshableCredentials, JSONFileCache cache_path = '~/.cache/aws/cached_temporary_credentials' datetime_format = "%Y-%m-%dT%H:%M:%SZ" # incidentally the same as the format used by AWS log = logging.getLogger(__name__) # But in addition to our manual cache, we also are going to turn on boto3's # new built-in caching layer. def datetime_to_str(dt): """ Convert a naive (implicitly UTC) datetime object into a string, explicitly UTC. >>> datetime_to_str(datetime(1970, 1, 1, 0, 0, 0)) '1970-01-01T00:00:00Z' """ return dt.strftime(datetime_format) def str_to_datetime(s): """ Convert a string, explicitly UTC into a naive (implicitly UTC) datetime object. >>> str_to_datetime( '1970-01-01T00:00:00Z' ) datetime.datetime(1970, 1, 1, 0, 0) Just to show that the constructor args for seconds and microseconds are optional: >>> datetime(1970, 1, 1, 0, 0, 0) datetime.datetime(1970, 1, 1, 0, 0) """ return datetime.strptime(s, datetime_format) class BotoCredentialAdapter(provider.Provider): """ Adapter to allow Boto 2 to use AWS credentials obtained via Boto 3's credential finding logic. This allows for automatic role assumption respecting the Boto 3 config files, even when parts of the app still use Boto 2. This class also handles cacheing credentials in multi-process environments to avoid loads of processes swamping the EC2 metadata service. """ """ Create a new BotoCredentialAdapter. """ # TODO: We take kwargs because new boto2 versions have an 'anon' # argument and we want to be future proof def __init__(self, name, access_key=None, secret_key=None, security_token=None, profile_name=None, **kwargs): """ Create a new BotoCredentialAdapter. """ # TODO: We take kwargs because new boto2 versions have an 'anon' # argument and we want to be future proof if (name == 'aws' or name is None) and access_key is None and not kwargs.get('anon', False): # We are on AWS and we don't have credentials passed along and we aren't anonymous. # We will backend into a boto3 resolver for getting credentials. # Make sure to enable boto3's own caching, so we can share that # cash with pure boto3 code elsewhere in Toil. self._boto3_resolver = create_credential_resolver(Session(profile=profile_name), cache=JSONFileCache()) else: # We will use the normal flow self._boto3_resolver = None # Pass along all the arguments super(BotoCredentialAdapter, self).__init__(name, access_key=access_key, secret_key=secret_key, security_token=security_token, profile_name=profile_name, **kwargs) def get_credentials(self, access_key=None, secret_key=None, security_token=None, profile_name=None): """ Make sure our credential fields are populated. Called by the base class constructor. """ if self._boto3_resolver is not None: # Go get the credentials from the cache, or from boto3 if not cached. # We need to be eager here; having the default None # _credential_expiry_time makes the accessors never try to refresh. self._obtain_credentials_from_cache_or_boto3() else: # We're not on AWS, or they passed a key, or we're anonymous. # Use the normal route; our credentials shouldn't expire. super(BotoCredentialAdapter, self).get_credentials(access_key=access_key, secret_key=secret_key, security_token=security_token, profile_name=profile_name) def _populate_keys_from_metadata_server(self): """ This override is misnamed; it's actually the only hook we have to catch _credential_expiry_time being too soon and refresh the credentials. We actually just go back and poke the cache to see if it feels like getting us new credentials. Boto 2 hardcodes a refresh within 5 minutes of expiry: https://github.com/boto/boto/blob/591911db1029f2fbb8ba1842bfcc514159b37b32/boto/provider.py#L247 Boto 3 wants to refresh 15 or 10 minutes before expiry: https://github.com/boto/botocore/blob/8d3ea0e61473fba43774eb3c74e1b22995ee7370/botocore/credentials.py#L279 So if we ever want to refresh, Boto 3 wants to refresh too. """ # This should only happen if we have expiring credentials, which we should only get from boto3 assert(self._boto3_resolver is not None) self._obtain_credentials_from_cache_or_boto3() def _obtain_credentials_from_boto3(self): """ We know the current cached credentials are not good, and that we need to get them from Boto 3. Fill in our credential fields (_access_key, _secret_key, _security_token, _credential_expiry_time) from Boto 3. """ # We get a Credentials object # # or a RefreshableCredentials, or None on failure. creds = None for attempt in retry(timeout=10, predicate=lambda _: True): with attempt: creds = self._boto3_resolver.load_credentials() if creds is None: try: resolvers = str(self._boto3_resolver.providers) except: resolvers = "(Resolvers unavailable)" raise RuntimeError("Could not obtain AWS credentials from Boto3. Resolvers tried: " + resolvers) # Make sure the credentials actually has some credentials if it is lazy creds.get_frozen_credentials() # Get when the credentials will expire, if ever if isinstance(creds, RefreshableCredentials): # Credentials may expire. # Get a naive UTC datetime like boto 2 uses from the boto 3 time. self._credential_expiry_time = creds._expiry_time.astimezone(timezone('UTC')).replace(tzinfo=None) else: # Credentials never expire self._credential_expiry_time = None # Then, atomically get all the credentials bits. They may be newer than we think they are, but never older. frozen = creds.get_frozen_credentials() # Copy them into us self._access_key = frozen.access_key self._secret_key = frozen.secret_key self._security_token = frozen.token def _obtain_credentials_from_cache_or_boto3(self): """ Get the cached credentials, or retrieve them from Boto 3 and cache them (or wait for another cooperating process to do so) if they are missing or not fresh enough. """ cache_path = '~/.cache/aws/cached_temporary_credentials' path = os.path.expanduser(cache_path) tmp_path = path + '.tmp' while True: log.debug('Attempting to read cached credentials from %s.', path) try: with open(path, 'r') as f: content = f.read() if content: record = content.split('\n') assert len(record) == 4 self._access_key = record[0] self._secret_key = record[1] self._security_token = record[2] self._credential_expiry_time = str_to_datetime(record[3]) else: log.debug('%s is empty. Credentials are not temporary.', path) self._obtain_credentials_from_boto3() return except IOError as e: if e.errno == errno.ENOENT: log.debug('Cached credentials are missing.') dir_path = os.path.dirname(path) if not os.path.exists(dir_path): log.debug('Creating parent directory %s', dir_path) # A race would be ok at this point mkdir_p(dir_path) else: raise else: if self._credentials_need_refresh(): log.debug('Cached credentials are expired.') else: log.debug('Cached credentials exist and are still fresh.') return # We get here if credentials are missing or expired log.debug('Racing to create %s.', tmp_path) # Only one process, the winner, will succeed try: fd = os.open(tmp_path, os.O_CREAT | os.O_EXCL | os.O_WRONLY, 0o600) except OSError as e: if e.errno == errno.EEXIST: log.debug('Lost the race to create %s. Waiting on winner to remove it.', tmp_path) while os.path.exists(tmp_path): time.sleep(0.1) log.debug('Winner removed %s. Trying from the top.', tmp_path) else: raise else: try: log.debug('Won the race to create %s. Requesting credentials from backend.', tmp_path) self._obtain_credentials_from_boto3() except: os.close(fd) fd = None log.debug('Failed to obtain credentials, removing %s.', tmp_path) # This unblocks the loosers. os.unlink(tmp_path) # Bail out. It's too likely to happen repeatedly raise else: if self._credential_expiry_time is None: os.close(fd) fd = None log.debug('Credentials are not temporary. Leaving %s empty and renaming it to %s.', tmp_path, path) # No need to actually cache permanent credentials, # because we hnow we aren't getting them from the # metadata server or by assuming a role. Those both # give temporary credentials. else: log.debug('Writing credentials to %s.', tmp_path) with os.fdopen(fd, 'w') as fh: fd = None fh.write('\n'.join([ self._access_key, self._secret_key, self._security_token, datetime_to_str(self._credential_expiry_time)])) log.debug('Wrote credentials to %s. Renaming to %s.', tmp_path, path) os.rename(tmp_path, path) return finally: if fd is not None: os.close(fd) provider.Provider = BotoCredentialAdapter except ImportError: pass toil-releases-3.24.0/src/toil/batchSystems/000077500000000000000000000000001362134276200205655ustar00rootroot00000000000000toil-releases-3.24.0/src/toil/batchSystems/__init__.py000066400000000000000000000040671362134276200227050ustar00rootroot00000000000000# Copyright (C) 2015-2016 Regents of the University of California # # 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. from __future__ import absolute_import from past.builtins import cmp from builtins import str from builtins import object import sys if sys.version_info >= (3, 0): # https://docs.python.org/3.0/whatsnew/3.0.html#ordering-comparisons def cmp(a, b): return (a > b) - (a < b) class MemoryString(object): def __init__(self, string): if string[-1] == 'K' or string[-1] == 'M' or string[-1] == 'G' or string[-1] == 'T': #10K self.unit = string[-1] self.val = float(string[:-1]) elif len(string) >= 3 and (string[-2] == 'k' or string[-2] == 'M' or string[-2] == 'G' or string[-2] == 'T'): self.unit = string[-2] self.val = float(string[:-2]) else: self.unit = 'B' self.val = float(string) self.bytes = self.byteVal() def __str__(self): if self.unit != 'B': return str(self.val) + self.unit else: return str(self.val) def byteVal(self): if self.unit == 'B': return self.val elif self.unit == 'K': return self.val * 1024 elif self.unit == 'M': return self.val * 1048576 elif self.unit == 'G': return self.val * 1073741824 elif self.unit == 'T': return self.val * 1099511627776 def __cmp__(self, other): return cmp(self.bytes, other.bytes) def __gt__(self, other): return self.bytes > other.bytes toil-releases-3.24.0/src/toil/batchSystems/abstractBatchSystem.py000066400000000000000000000501451362134276200251160ustar00rootroot00000000000000# Copyright (C) 2015-2018 Regents of the University of California # # 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. from __future__ import absolute_import from future import standard_library standard_library.install_aliases() from future.utils import with_metaclass from builtins import object import os import shutil import logging from abc import ABCMeta, abstractmethod from collections import namedtuple from contextlib import contextmanager from toil.lib.objects import abstractclassmethod from toil.batchSystems import registry from toil.common import Toil, cacheDirName from toil.fileStores.abstractFileStore import AbstractFileStore from toil.deferred import DeferredFunctionManager try: from toil.cwl.cwltoil import CWL_INTERNAL_JOBS except ImportError: # CWL extra not installed CWL_INTERNAL_JOBS = () logger = logging.getLogger(__name__) # A class containing the information required for worker cleanup on shutdown of the batch system. WorkerCleanupInfo = namedtuple('WorkerCleanupInfo', ( # A path to the value of config.workDir (where the cache would go) 'workDir', # The value of config.workflowID (used to identify files specific to this workflow) 'workflowID', # The value of the cleanWorkDir flag 'cleanWorkDir')) class AbstractBatchSystem(with_metaclass(ABCMeta, object)): """ An abstract (as far as Python currently allows) base class to represent the interface the batch system must provide to Toil. """ # noinspection PyMethodParameters @abstractclassmethod def supportsAutoDeployment(cls): """ Whether this batch system supports auto-deployment of the user script itself. If it does, the :meth:`.setUserScript` can be invoked to set the resource object representing the user script. Note to implementors: If your implementation returns True here, it should also override :rtype: bool """ raise NotImplementedError() # noinspection PyMethodParameters @abstractclassmethod def supportsWorkerCleanup(cls): """ Indicates whether this batch system invokes :meth:`workerCleanup` after the last job for a particular workflow invocation finishes. Note that the term *worker* refers to an entire node, not just a worker process. A worker process may run more than one job sequentially, and more than one concurrent worker process may exist on a worker node, for the same workflow. The batch system is said to *shut down* after the last worker process terminates. :rtype: bool """ raise NotImplementedError() def setUserScript(self, userScript): """ Set the user script for this workflow. This method must be called before the first job is issued to this batch system, and only if :meth:`.supportsAutoDeployment` returns True, otherwise it will raise an exception. :param toil.resource.Resource userScript: the resource object representing the user script or module and the modules it depends on. """ raise NotImplementedError() @abstractmethod def issueBatchJob(self, jobNode): """ Issues a job with the specified command to the batch system and returns a unique jobID. :param jobNode a toil.job.JobNode :return: a unique jobID that can be used to reference the newly issued job :rtype: int """ raise NotImplementedError() @abstractmethod def killBatchJobs(self, jobIDs): """ Kills the given job IDs. After returning, the killed jobs will not appear in the results of getRunningBatchJobIDs. :param jobIDs: list of IDs of jobs to kill :type jobIDs: list[int] """ raise NotImplementedError() # FIXME: Return value should be a set (then also fix the tests) @abstractmethod def getIssuedBatchJobIDs(self): """ Gets all currently issued jobs :return: A list of jobs (as jobIDs) currently issued (may be running, or may be waiting to be run). Despite the result being a list, the ordering should not be depended upon. :rtype: list[str] """ raise NotImplementedError() @abstractmethod def getRunningBatchJobIDs(self): """ Gets a map of jobs as jobIDs that are currently running (not just waiting) and how long they have been running, in seconds. :return: dictionary with currently running jobID keys and how many seconds they have been running as the value :rtype: dict[int,float] """ raise NotImplementedError() @abstractmethod def getUpdatedBatchJob(self, maxWait): """ Returns information about job that has updated its status (i.e. ceased running, either successfully or with an error). Each such job will be returned exactly once. :param float maxWait: the number of seconds to block, waiting for a result :rtype: tuple(str, int, float) or None :return: If a result is available, returns a tuple (jobID, exitValue, wallTime). Otherwise it returns None. wallTime is the number of seconds (a strictly positive float) in wall-clock time the job ran for, or None if this batch system does not support tracking wall time. Returns None for jobs that were killed. """ raise NotImplementedError() @abstractmethod def shutdown(self): """ Called at the completion of a toil invocation. Should cleanly terminate all worker threads. """ raise NotImplementedError() def setEnv(self, name, value=None): """ Set an environment variable for the worker process before it is launched. The worker process will typically inherit the environment of the machine it is running on but this method makes it possible to override specific variables in that inherited environment before the worker is launched. Note that this mechanism is different to the one used by the worker internally to set up the environment of a job. A call to this method affects all jobs issued after this method returns. Note to implementors: This means that you would typically need to copy the variables before enqueuing a job. If no value is provided it will be looked up from the current environment. """ raise NotImplementedError() @classmethod def setOptions(cls, setOption): """ Process command line or configuration options relevant to this batch system. The :param setOption: A function with signature setOption(varName, parsingFn=None, checkFn=None, default=None) used to update run configuration """ pass class BatchSystemSupport(AbstractBatchSystem): """ Partial implementation of AbstractBatchSystem, support methods. """ def __init__(self, config, maxCores, maxMemory, maxDisk): """ Initializes initial state of the object :param toil.common.Config config: object is setup by the toilSetup script and has configuration parameters for the jobtree. You can add code to that script to get parameters for your batch system. :param float maxCores: the maximum number of cores the batch system can request for any one job :param int maxMemory: the maximum amount of memory the batch system can request for any one job, in bytes :param int maxDisk: the maximum amount of disk space the batch system can request for any one job, in bytes """ super(BatchSystemSupport, self).__init__() self.config = config self.maxCores = maxCores self.maxMemory = maxMemory self.maxDisk = maxDisk self.environment = {} """ :type: dict[str,str] """ self.workerCleanupInfo = WorkerCleanupInfo(workDir=self.config.workDir, workflowID=self.config.workflowID, cleanWorkDir=self.config.cleanWorkDir) def checkResourceRequest(self, memory, cores, disk): """ Check resource request is not greater than that available or allowed. :param int memory: amount of memory being requested, in bytes :param float cores: number of cores being requested :param int disk: amount of disk space being requested, in bytes :raise InsufficientSystemResources: raised when a resource is requested in an amount greater than allowed """ assert memory is not None assert disk is not None assert cores is not None if cores > self.maxCores: raise InsufficientSystemResources('cores', cores, self.maxCores) if memory > self.maxMemory: raise InsufficientSystemResources('memory', memory, self.maxMemory) if disk > self.maxDisk: raise InsufficientSystemResources('disk', disk, self.maxDisk) def setEnv(self, name, value=None): """ Set an environment variable for the worker process before it is launched. The worker process will typically inherit the environment of the machine it is running on but this method makes it possible to override specific variables in that inherited environment before the worker is launched. Note that this mechanism is different to the one used by the worker internally to set up the environment of a job. A call to this method affects all jobs issued after this method returns. Note to implementors: This means that you would typically need to copy the variables before enqueuing a job. If no value is provided it will be looked up from the current environment. :param str name: the environment variable to be set on the worker. :param str value: if given, the environment variable given by name will be set to this value. if None, the variable's current value will be used as the value on the worker :raise RuntimeError: if value is None and the name cannot be found in the environment """ if value is None: try: value = os.environ[name] except KeyError: raise RuntimeError("%s does not exist in current environment", name) self.environment[name] = value def formatStdOutErrPath(self, jobID, batchSystem, batchJobIDfmt, fileDesc): """ Format path for batch system standard output/error and other files. Files will be written to the Toil workflow directory with names containing both the Toil and batch system job IDs, for ease of debugging job failures. :param: string jobID : Toil job ID :param: string batchSystem : Name of the batch system :param: string batchJobIDfmt : A string which the particular batch system will format into the batch job ID once it is submitted :param: string fileDesc : File description, should be 'std_output' for standard output, 'std_error' for standard error, and as appropriate for other files :rtype: string : Formatted filename; however if self.config.noStdOutErr is true, returns '/dev/null' or equivalent. """ if self.config.noStdOutErr: return os.devnull workflowDir = Toil.getWorkflowDir(self.config.workflowID, self.config.workDir) fileName = 'toil_job_{jobID}_batch_{batchSystem}_{batchJobIDfmt}_{fileDesc}.log'.format( jobID=jobID, batchSystem=batchSystem, batchJobIDfmt=batchJobIDfmt, fileDesc=fileDesc) return os.path.join(workflowDir, fileName) @staticmethod def workerCleanup(info): """ Cleans up the worker node on batch system shutdown. Also see :meth:`supportsWorkerCleanup`. :param WorkerCleanupInfo info: A named tuple consisting of all the relevant information for cleaning up the worker. """ assert isinstance(info, WorkerCleanupInfo) workflowDir = Toil.getWorkflowDir(info.workflowID, info.workDir) DeferredFunctionManager.cleanupWorker(workflowDir) workflowDirContents = os.listdir(workflowDir) AbstractFileStore.shutdownFileStore(workflowDir, info.workflowID) if (info.cleanWorkDir == 'always' or info.cleanWorkDir in ('onSuccess', 'onError') and workflowDirContents in ([], [cacheDirName(info.workflowID)])): shutil.rmtree(workflowDir, ignore_errors=True) class BatchSystemLocalSupport(BatchSystemSupport): """ Adds a local queue for helper jobs, useful for CWL & others """ def __init__(self, config, maxCores, maxMemory, maxDisk): super(BatchSystemLocalSupport, self).__init__(config, maxCores, maxMemory, maxDisk) self.localBatch = registry.batchSystemFactoryFor( registry.defaultBatchSystem())()( config, config.maxLocalJobs, maxMemory, maxDisk) def handleLocalJob(self, jobNode): # type: (JobNode) -> Optional[int] """ To be called by issueBatchJobs. Returns the jobID if the jobNode has been submitted to the local queue, otherwise returns None """ if (not self.config.runCwlInternalJobsOnWorkers and jobNode.jobName.startswith(CWL_INTERNAL_JOBS)): return self.localBatch.issueBatchJob(jobNode) else: return None def killLocalJobs(self, jobIDs): """ To be called by killBatchJobs. Will kill all local jobs that match the provided jobIDs. """ self.localBatch.killBatchJobs(jobIDs) def getIssuedLocalJobIDs(self): """To be called by getIssuedBatchJobIDs""" return self.localBatch.getIssuedBatchJobIDs() def getRunningLocalJobIDs(self): """To be called by getRunningBatchJobIDs().""" return self.localBatch.getRunningBatchJobIDs() def getUpdatedLocalJob(self, maxWait): # type: (int) -> Optional[Tuple[int, int, int]] """To be called by getUpdatedBatchJob()""" return self.localBatch.getUpdatedBatchJob(maxWait) def getNextJobID(self): # type: () -> int """ Must be used to get job IDs so that the local and batch jobs do not conflict. """ with self.localBatch.jobIndexLock: jobID = self.localBatch.jobIndex self.localBatch.jobIndex += 1 return jobID def shutdownLocal(self): # type: () -> None """To be called from shutdown()""" self.localBatch.shutdown() class NodeInfo(object): """ The coresUsed attribute is a floating point value between 0 (all cores idle) and 1 (all cores busy), reflecting the CPU load of the node. The memoryUsed attribute is a floating point value between 0 (no memory used) and 1 (all memory used), reflecting the memory pressure on the node. The coresTotal and memoryTotal attributes are the node's resources, not just the used resources The requestedCores and requestedMemory attributes are all the resources that Toil Jobs have reserved on the node, regardless of whether the resources are actually being used by the Jobs. The workers attribute is an integer reflecting the number of workers currently active workers on the node. """ def __init__(self, coresUsed, memoryUsed, coresTotal, memoryTotal, requestedCores, requestedMemory, workers): self.coresUsed = coresUsed self.memoryUsed = memoryUsed self.coresTotal = coresTotal self.memoryTotal = memoryTotal self.requestedCores = requestedCores self.requestedMemory = requestedMemory self.workers = workers class AbstractScalableBatchSystem(AbstractBatchSystem): """ A batch system that supports a variable number of worker nodes. Used by :class:`toil. provisioners.clusterScaler.ClusterScaler` to scale the number of worker nodes in the cluster up or down depending on overall load. """ @abstractmethod def getNodes(self, preemptable=None): """ Returns a dictionary mapping node identifiers of preemptable or non-preemptable nodes to NodeInfo objects, one for each node. :param bool preemptable: If True (False) only (non-)preemptable nodes will be returned. If None, all nodes will be returned. :rtype: dict[str,NodeInfo] """ raise NotImplementedError() @abstractmethod def nodeInUse(self, nodeIP): """ Can be used to determine if a worker node is running any tasks. If the node is doesn't exist, this function should simply return False. :param str nodeIP: The worker nodes private IP address :return: True if the worker node has been issued any tasks, else False :rtype: bool """ raise NotImplementedError() @abstractmethod @contextmanager def nodeFiltering(self, filter): """ Used to prevent races in autoscaling where 1) nodes have reported to the autoscaler as having no jobs 2) scaler decides to terminate these nodes. In parallel the batch system assigns jobs to the same nodes 3) scaler terminates nodes, resulting in job failures for all jobs on that node. Call this method prior to node termination to ensure that nodes being considered for termination are not assigned new jobs. Call the method again passing None as the filter to disable the filtering after node termination is done. :param method: This will be used as a filter on nodes considered when assigning new jobs. After this context manager exits the filter should be removed :rtype: None """ raise NotImplementedError() @abstractmethod def ignoreNode(self, nodeAddress): """ Stop sending jobs to this node. Used in autoscaling when the autoscaler is ready to terminate a node, but jobs are still running. This allows the node to be terminated after the current jobs have finished. :param str: IP address of node to ignore. :rtype: None """ raise NotImplementedError() @abstractmethod def unignoreNode(self, nodeAddress): """ Stop ignoring this address, presumably after a node with this address has been terminated. This allows for the possibility of a new node having the same address as a terminated one. """ raise NotImplementedError() class InsufficientSystemResources(Exception): """ To be raised when a job requests more of a particular resource than is either currently allowed or avaliable """ def __init__(self, resource, requested, available): """ Creates an instance of this exception that indicates which resource is insufficient for current demands, as well as the amount requested and amount actually available. :param str resource: string representing the resource type :param int|float requested: the amount of the particular resource requested that resulted in this exception :param int|float available: amount of the particular resource actually available """ self.requested = requested self.available = available self.resource = resource def __str__(self): return 'Requesting more {} than either physically available, or enforced by --max{}. ' \ 'Requested: {}, Available: {}'.format(self.resource, self.resource.capitalize(), self.requested, self.available) toil-releases-3.24.0/src/toil/batchSystems/abstractGridEngineBatchSystem.py000066400000000000000000000373031362134276200270530ustar00rootroot00000000000000# Copyright (C) 2015-2016 Regents of the University of California # # 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. from __future__ import absolute_import from builtins import str from datetime import datetime import logging import time from threading import Thread, Lock from abc import ABCMeta, abstractmethod # Python 3 compatibility imports from six.moves.queue import Empty, Queue from future.utils import with_metaclass from toil import subprocess from toil.lib.objects import abstractclassmethod from toil.batchSystems.abstractBatchSystem import BatchSystemLocalSupport logger = logging.getLogger(__name__) def with_retries(operation, *args, **kwargs): retries = 3 latest_err = None while retries: retries -= 1 try: return operation(*args, **kwargs) except subprocess.CalledProcessError as err: latest_err = err logger.error( "Operation %s failed with code %d: %s", operation, err.returncode, err.output) raise latest_err class AbstractGridEngineBatchSystem(BatchSystemLocalSupport): """ A partial implementation of BatchSystemSupport for batch systems run on a standard HPC cluster. By default worker cleanup and auto-deployment are not implemented. """ class Worker(with_metaclass(ABCMeta, Thread)): def __init__(self, newJobsQueue, updatedJobsQueue, killQueue, killedJobsQueue, boss): """ Abstract worker interface class. All instances are created with five initial arguments (below). Note the Queue instances passed are empty. :param newJobsQueue: a Queue of new (unsubmitted) jobs :param updatedJobsQueue: a Queue of jobs that have been updated :param killQueue: a Queue of active jobs that need to be killed :param killedJobsQueue: Queue of killed jobs for this worker :param boss: the AbstractGridEngineBatchSystem instance that controls this AbstractGridEngineWorker """ Thread.__init__(self) self.boss = boss self.boss.config.statePollingWait = \ self.boss.config.statePollingWait or self.boss.getWaitDuration() self.newJobsQueue = newJobsQueue self.updatedJobsQueue = updatedJobsQueue self.killQueue = killQueue self.killedJobsQueue = killedJobsQueue self.waitingJobs = list() self.runningJobs = set() self.runningJobsLock = Lock() self.batchJobIDs = dict() self._checkOnJobsCache = None self._checkOnJobsTimestamp = None def getBatchSystemID(self, jobID): """ Get batch system-specific job ID Note: for the moment this is the only consistent way to cleanly get the batch system job ID :param: string jobID: toil job ID """ if jobID not in self.batchJobIDs: raise RuntimeError("Unknown jobID, could not be converted") (job, task) = self.batchJobIDs[jobID] if task is None: return str(job) else: return str(job) + "." + str(task) def forgetJob(self, jobID): """ Remove jobID passed :param: string jobID: toil job ID """ with self.runningJobsLock: self.runningJobs.remove(jobID) del self.batchJobIDs[jobID] def createJobs(self, newJob): """ Create a new job with the Toil job ID. Implementation-specific; called by AbstractGridEngineWorker.run() :param string newJob: Toil job ID """ activity = False # Load new job id if present: if newJob is not None: self.waitingJobs.append(newJob) # Launch jobs as necessary: while len(self.waitingJobs) > 0 and \ len(self.runningJobs) < int(self.boss.config.maxLocalJobs): activity = True jobID, cpu, memory, command, jobName = self.waitingJobs.pop(0) # prepare job submission command subLine = self.prepareSubmission(cpu, memory, jobID, command, jobName) logger.debug("Running %r", subLine) batchJobID = with_retries(self.submitJob, subLine) logger.debug("Submitted job %s", str(batchJobID)) # Store dict for mapping Toil job ID to batch job ID # TODO: Note that this currently stores a tuple of (batch system # ID, Task), but the second value is None by default and doesn't # seem to be used self.batchJobIDs[jobID] = (batchJobID, None) # Add to queue of running jobs with self.runningJobsLock: self.runningJobs.add(jobID) return activity def killJobs(self): """ Kill any running jobs within worker """ killList = list() while True: try: jobId = self.killQueue.get(block=False) except Empty: break else: killList.append(jobId) if not killList: return False # Do the dirty job for jobID in list(killList): if jobID in self.runningJobs: logger.debug('Killing job: %s', jobID) # this call should be implementation-specific, all other # code is redundant w/ other implementations self.killJob(jobID) else: if jobID in self.waitingJobs: self.waitingJobs.remove(jobID) self.killedJobsQueue.put(jobID) killList.remove(jobID) # Wait to confirm the kill while killList: for jobID in list(killList): batchJobID = self.getBatchSystemID(jobID) if with_retries(self.getJobExitCode, batchJobID) is not None: logger.debug('Adding jobID %s to killedJobsQueue', jobID) self.killedJobsQueue.put(jobID) killList.remove(jobID) self.forgetJob(jobID) if len(killList) > 0: logger.warn("Some jobs weren't killed, trying again in %is.", self.boss.sleepSeconds()) return True def checkOnJobs(self): """Check and update status of all running jobs. Respects statePollingWait and will return cached results if not within time period to talk with the scheduler. """ if (self._checkOnJobsTimestamp and (datetime.now() - self._checkOnJobsTimestamp).total_seconds() < self.boss.config.statePollingWait): return self._checkOnJobsCache activity = False for jobID in list(self.runningJobs): batchJobID = self.getBatchSystemID(jobID) status = with_retries(self.getJobExitCode, batchJobID) if status is not None: activity = True self.updatedJobsQueue.put((jobID, status)) self.forgetJob(jobID) self._checkOnJobsCache = activity self._checkOnJobsTimestamp = datetime.now() return activity def run(self): """ Run any new jobs """ while True: activity = False newJob = None if not self.newJobsQueue.empty(): activity = True newJob = self.newJobsQueue.get() if newJob is None: logger.debug('Received queue sentinel.') break activity |= self.killJobs() activity |= self.createJobs(newJob) activity |= self.checkOnJobs() if not activity: logger.debug('No activity, sleeping for %is', self.boss.sleepSeconds()) @abstractmethod def prepareSubmission(self, cpu, memory, jobID, command, jobName): """ Preparation in putting together a command-line string for submitting to batch system (via submitJob().) :param: string cpu :param: string memory :param: string jobID : Toil job ID :param: string subLine: the command line string to be called :param: string jobName: the name of the Toil job, to provide metadata to batch systems if desired :rtype: string """ raise NotImplementedError() @abstractmethod def submitJob(self, subLine): """ Wrapper routine for submitting the actual command-line call, then processing the output to get the batch system job ID :param: string subLine: the literal command line string to be called :rtype: string: batch system job ID, which will be stored internally """ raise NotImplementedError() @abstractmethod def getRunningJobIDs(self): """ Get a list of running job IDs. Implementation-specific; called by boss AbstractGridEngineBatchSystem implementation via AbstractGridEngineBatchSystem.getRunningBatchJobIDs() :rtype: list """ raise NotImplementedError() @abstractmethod def killJob(self, jobID): """ Kill specific job with the Toil job ID. Implementation-specific; called by AbstractGridEngineWorker.killJobs() :param string jobID: Toil job ID """ raise NotImplementedError() @abstractmethod def getJobExitCode(self, batchJobID): """ Returns job exit code. Implementation-specific; called by AbstractGridEngineWorker.checkOnJobs() :param string batchjobID: batch system job ID """ raise NotImplementedError() def __init__(self, config, maxCores, maxMemory, maxDisk): super(AbstractGridEngineBatchSystem, self).__init__( config, maxCores, maxMemory, maxDisk) self.config = config self.currentJobs = set() # NOTE: this may be batch system dependent, maybe move into the worker? # Doing so would effectively make each subclass of AbstractGridEngineBatchSystem # much smaller self.maxCPU, self.maxMEM = self.obtainSystemConstants() self.newJobsQueue = Queue() self.updatedJobsQueue = Queue() self.killQueue = Queue() self.killedJobsQueue = Queue() # get the associated worker class here self.worker = self.Worker(self.newJobsQueue, self.updatedJobsQueue, self.killQueue, self.killedJobsQueue, self) self.worker.start() self._getRunningBatchJobIDsTimestamp = None self._getRunningBatchJobIDsCache = {} @classmethod def supportsWorkerCleanup(cls): return False @classmethod def supportsAutoDeployment(cls): return False def issueBatchJob(self, jobNode): # Avoid submitting internal jobs to the batch queue, handle locally localID = self.handleLocalJob(jobNode) if localID: return localID else: self.checkResourceRequest(jobNode.memory, jobNode.cores, jobNode.disk) jobID = self.getNextJobID() self.currentJobs.add(jobID) self.newJobsQueue.put((jobID, jobNode.cores, jobNode.memory, jobNode.command, jobNode.jobName)) logger.debug("Issued the job command: %s with job id: %s and job name %s", jobNode.command, str(jobID), jobNode.jobName) return jobID def killBatchJobs(self, jobIDs): """ Kills the given jobs, represented as Job ids, then checks they are dead by checking they are not in the list of issued jobs. """ self.killLocalJobs(jobIDs) jobIDs = set(jobIDs) logger.debug('Jobs to be killed: %r', jobIDs) for jobID in jobIDs: self.killQueue.put(jobID) while jobIDs: killedJobId = self.killedJobsQueue.get() if killedJobId is None: break jobIDs.remove(killedJobId) if killedJobId in self.currentJobs: self.currentJobs.remove(killedJobId) if jobIDs: logger.debug('Some kills (%s) still pending, sleeping %is', len(jobIDs), self.sleepSeconds()) def getIssuedBatchJobIDs(self): """ Gets the list of issued jobs """ return list(self.getIssuedLocalJobIDs()) + list(self.currentJobs) def getRunningBatchJobIDs(self): """ Retrieve running job IDs from local and batch scheduler. Respects statePollingWait and will return cached results if not within time period to talk with the scheduler. """ if (self._getRunningBatchJobIDsTimestamp and ( datetime.now() - self._getRunningBatchJobIDsTimestamp).total_seconds() < self.config.statePollingWait): batchIds = self._getRunningBatchJobIDsCache else: batchIds = with_retries(self.worker.getRunningJobIDs) self._getRunningBatchJobIDsCache = batchIds self._getRunningBatchJobIDsTimestamp = datetime.now() batchIds.update(self.getRunningLocalJobIDs()) return batchIds def getUpdatedBatchJob(self, maxWait): local_tuple = self.getUpdatedLocalJob(0) if local_tuple: return local_tuple else: try: item = self.updatedJobsQueue.get(timeout=maxWait) except Empty: return None logger.debug('UpdatedJobsQueue Item: %s', item) jobID, retcode = item self.currentJobs.remove(jobID) return jobID, retcode, None def shutdown(self): """ Signals worker to shutdown (via sentinel) then cleanly joins the thread """ self.shutdownLocal() newJobsQueue = self.newJobsQueue self.newJobsQueue = None newJobsQueue.put(None) self.worker.join() def setEnv(self, name, value=None): if value and ',' in value: raise ValueError(type(self).__name__ + " does not support commata in environment variable values") return super(AbstractGridEngineBatchSystem, self).setEnv(name, value) @classmethod def getWaitDuration(self): return 1 def sleepSeconds(self, sleeptime=1): """ Helper function to drop on all state-querying functions to avoid over-querying. """ time.sleep(sleeptime) return sleeptime @abstractclassmethod def obtainSystemConstants(cls): """ Returns the max. memory and max. CPU for the system """ raise NotImplementedError() toil-releases-3.24.0/src/toil/batchSystems/gridengine.py000066400000000000000000000157471362134276200232700ustar00rootroot00000000000000# Copyright (C) 2015-2016 Regents of the University of California # # 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. from __future__ import absolute_import from __future__ import division from builtins import map from builtins import str from builtins import range from past.utils import old_div import logging import os from pipes import quote from toil import subprocess import time import math # Python 3 compatibility imports from six.moves.queue import Empty, Queue from six import iteritems from toil.batchSystems import MemoryString from toil.batchSystems.abstractGridEngineBatchSystem import AbstractGridEngineBatchSystem logger = logging.getLogger(__name__) class GridEngineBatchSystem(AbstractGridEngineBatchSystem): class Worker(AbstractGridEngineBatchSystem.Worker): """ Grid Engine-specific AbstractGridEngineWorker methods """ def getRunningJobIDs(self): times = {} with self.runningJobsLock: currentjobs = dict((str(self.batchJobIDs[x][0]), x) for x in self.runningJobs) process = subprocess.Popen(["qstat"], stdout=subprocess.PIPE) stdout, stderr = process.communicate() for currline in stdout.decode('utf-8').split('\n'): items = currline.strip().split() if items: if items[0] in currentjobs and items[4] == 'r': jobstart = " ".join(items[5:7]) jobstart = time.mktime(time.strptime(jobstart, "%m/%d/%Y %H:%M:%S")) times[currentjobs[items[0]]] = time.time() - jobstart return times def killJob(self, jobID): subprocess.check_call(['qdel', self.getBatchSystemID(jobID)]) def prepareSubmission(self, cpu, memory, jobID, command, jobName): return self.prepareQsub(cpu, memory, jobID) + [command] def submitJob(self, subLine): process = subprocess.Popen(subLine, stdout=subprocess.PIPE) result = int(process.stdout.readline().decode('utf-8').strip()) return result def getJobExitCode(self, sgeJobID): # the task is set as part of the job ID if using getBatchSystemID() job, task = (sgeJobID, None) if '.' in sgeJobID: job, task = sgeJobID.split('.', 1) args = ["qacct", "-j", str(job)] if task is not None: args.extend(["-t", str(task)]) logger.debug("Running %r", args) process = subprocess.Popen(args, stdout=subprocess.PIPE, stderr=subprocess.STDOUT) for line in process.stdout: if line.startswith("failed") and int(line.split()[1]) == 1: return 1 elif line.startswith("exit_status"): logger.debug('Exit Status: %r', line.split()[1]) return int(line.split()[1]) return None """ Implementation-specific helper methods """ def prepareQsub(self, cpu, mem, jobID): qsubline = ['qsub', '-V', '-b', 'y', '-terse', '-j', 'y', '-cwd', '-N', 'toil_job_' + str(jobID)] if self.boss.environment: qsubline.append('-v') qsubline.append(','.join(k + '=' + quote(os.environ[k] if v is None else v) for k, v in self.boss.environment.items())) reqline = list() sgeArgs = os.getenv('TOIL_GRIDENGINE_ARGS') if mem is not None: memStr = str(old_div(mem, 1024)) + 'K' if not self.boss.config.manualMemArgs: # for UGE instead of SGE; see #2309 reqline += ['vf=' + memStr, 'h_vmem=' + memStr] elif self.boss.config.manualMemArgs and not sgeArgs: raise ValueError("--manualMemArgs set to True, but TOIL_GRIDGENGINE_ARGS is not set." "Please set TOIL_GRIDGENGINE_ARGS to specify memory allocation for " "your system. Default adds the arguments: vf= h_vmem= " "to qsub.") if len(reqline) > 0: qsubline.extend(['-hard', '-l', ','.join(reqline)]) if sgeArgs: sgeArgs = sgeArgs.split() for arg in sgeArgs: if arg.startswith(("vf=", "hvmem=", "-pe")): raise ValueError("Unexpected CPU, memory or pe specifications in TOIL_GRIDGENGINE_ARGs: %s" % arg) qsubline.extend(sgeArgs) if cpu is not None and math.ceil(cpu) > 1: peConfig = os.getenv('TOIL_GRIDENGINE_PE') or 'shm' qsubline.extend(['-pe', peConfig, str(int(math.ceil(cpu)))]) stdoutfile = self.boss.formatStdOutErrPath(jobID, 'gridengine', '$JOB_ID', 'std_output') stderrfile = self.boss.formatStdOutErrPath(jobID, 'gridengine', '$JOB_ID', 'std_error') qsubline.extend(['-o', stdoutfile, '-e', stderrfile]) return qsubline """ The interface for SGE aka Sun GridEngine. """ @classmethod def getWaitDuration(cls): return 1 @classmethod def obtainSystemConstants(cls): def byteStrip(s): return s.encode('utf-8').strip() lines = [_f for _f in map(byteStrip, subprocess.check_output(["qhost"]).decode('utf-8').split('\n')) if _f] line = lines[0] items = line.strip().split() num_columns = len(items) cpu_index = None mem_index = None for i in range(num_columns): if items[i] == 'NCPU': cpu_index = i elif items[i] == 'MEMTOT': mem_index = i if cpu_index is None or mem_index is None: RuntimeError('qhost command does not return NCPU or MEMTOT columns') maxCPU = 0 maxMEM = MemoryString("0") for line in lines[2:]: items = line.strip().split() if len(items) < num_columns: RuntimeError('qhost output has a varying number of columns') if items[cpu_index] != '-' and items[cpu_index] > maxCPU: maxCPU = items[cpu_index] if items[mem_index] != '-' and MemoryString(items[mem_index]) > maxMEM: maxMEM = MemoryString(items[mem_index]) if maxCPU is 0 or maxMEM is 0: RuntimeError('qhost returned null NCPU or MEMTOT info') return maxCPU, maxMEM toil-releases-3.24.0/src/toil/batchSystems/htcondor.py000066400000000000000000000335761362134276200227750ustar00rootroot00000000000000# Copyright (C) 2018, HTCondor Team, Computer Sciences Department, # University of Wisconsin-Madison, WI. # # 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. from __future__ import absolute_import from builtins import str import sys import os import logging import time import math from toil.batchSystems.abstractGridEngineBatchSystem import AbstractGridEngineBatchSystem import htcondor import classad logger = logging.getLogger(__name__) class HTCondorBatchSystem(AbstractGridEngineBatchSystem): # When using HTCondor, the Schedd handles scheduling class Worker(AbstractGridEngineBatchSystem.Worker): # Override the createJobs method so that we can use htcondor.Submit objects # and so that we can get disk allocation requests and ceil the CPU request. def createJobs(self, newJob): activity = False if newJob is not None: self.waitingJobs.append(newJob) # Queue jobs as necessary: while len(self.waitingJobs) > 0 and len(self.runningJobs) < int(self.boss.config.maxLocalJobs): activity = True jobID, cpu, memory, disk, jobName, command = self.waitingJobs.pop(0) # Prepare the htcondor.Submit object submitObj = self.prepareSubmission(cpu, memory, disk, jobID, jobName, command) logger.debug("Submitting %r", submitObj) # Submit job and get batch system ID (i.e. the ClusterId) batchJobID = self.submitJob(submitObj) logger.debug("Submitted job %s", str(batchJobID)) # Store dict for mapping Toil job ID to batch job ID # TODO: Note that this currently stores a tuple of (batch system # ID, Task), but the second value is None by default and doesn't # seem to be used self.batchJobIDs[jobID] = (batchJobID, None) # Add to queue of queued ("running") jobs self.runningJobs.add(jobID) return activity def prepareSubmission(self, cpu, memory, disk, jobID, jobName, command): # Convert resource requests cpu = int(math.ceil(cpu)) # integer CPUs memory = float(memory)/1024 # memory in KB disk = float(disk)/1024 # disk in KB # NOTE: formatStdOutErrPath() puts files in the Toil workflow directory, which defaults # to being in the system temporary directory ($TMPDIR, /tmp) which is unlikely to be on # a shared filesystem. So to make this work we need to set should_transfer_files = Yes # in the submit file, so that HTCondor will write the standard output/error files on the # compute node, then transfer back once the job has completed. stdoutfile = self.boss.formatStdOutErrPath(jobID, 'htcondor', '$(cluster)', 'std_output') stderrfile = self.boss.formatStdOutErrPath(jobID, 'htcondor', '$(cluster)', 'std_error') condorlogfile = self.boss.formatStdOutErrPath(jobID, 'htcondor', '$(cluster)', 'job_events') # Execute the entire command as /bin/sh -c "command" # TODO: Transfer the jobStore directory if using a local file store with a relative path. submit_parameters = { 'executable': '/bin/sh', 'transfer_executable': 'False', 'arguments': '''"-c '{0}'"'''.format(command).encode('utf-8'), # Workaround for HTCondor Python bindings Unicode conversion bug 'environment': self.getEnvString(), 'getenv': 'True', 'should_transfer_files': 'Yes', # See note above for stdoutfile, stderrfile 'output': stdoutfile, 'error': stderrfile, 'log': condorlogfile, 'request_cpus': '{0}'.format(cpu), 'request_memory': '{0:.3f}KB'.format(memory), 'request_disk': '{0:.3f}KB'.format(disk), 'leave_in_queue': '(JobStatus == 4)', '+IsToilJob': 'True', '+ToilJobID': '{0}'.format(jobID), '+ToilJobName': '"{0}"'.format(jobName), '+ToilJobKilled': 'False', } # Extra parameters for HTCondor extra_parameters = os.getenv('TOIL_HTCONDOR_PARAMS') if extra_parameters is not None: logger.debug("Extra HTCondor parameters added to submit file from TOIL_HTCONDOR_PARAMS env. variable: {}".format(extra_parameters)) for parameter, value in [parameter_value.split('=', 1) for parameter_value in extra_parameters.split(';')]: parameter = parameter.strip() value = value.strip() if parameter in submit_parameters: raise ValueError("Some extra parameters are incompatible: {}".format(extra_parameters)) submit_parameters[parameter] = value # Return the Submit object return htcondor.Submit(submit_parameters) def submitJob(self, submitObj): # Queue the job using a Schedd transaction schedd = self.connectSchedd() with schedd.transaction() as txn: batchJobID = submitObj.queue(txn) # Return the ClusterId return batchJobID def getRunningJobIDs(self): # Get all Toil jobs that are running requirements = '(JobStatus == 2) && (IsToilJob)' projection = ['ClusterId', 'ToilJobID', 'EnteredCurrentStatus'] schedd = self.connectSchedd() ads = schedd.xquery(requirements = requirements, projection = projection) # Only consider the Toil jobs that are part of this workflow batchJobIDs = [batchJobID for (batchJobID, task) in self.batchJobIDs.values()] job_runtimes = {} for ad in ads: batchJobID = int(ad['ClusterId']) jobID = int(ad['ToilJobID']) if not (batchJobID in batchJobIDs): continue # HTCondor stores the start of the runtime as a Unix timestamp runtime = time.time() - ad['EnteredCurrentStatus'] job_runtimes[jobID] = runtime return job_runtimes def killJob(self, jobID): batchJobID = self.batchJobIDs[jobID][0] logger.debug("Killing HTCondor job {0}".format(batchJobID)) # Set the job to be killed when its exit status is checked schedd = self.connectSchedd() job_spec = '(ClusterId == {0})'.format(batchJobID) schedd.edit(job_spec, 'ToilJobKilled', 'True') def getJobExitCode(self, batchJobID): logger.debug("Getting exit code for HTCondor job {0}".format(batchJobID)) status = { 1: 'Idle', 2: 'Running', 3: 'Removed', 4: 'Completed', 5: 'Held', 6: 'Transferring Output', 7: 'Suspended' } requirements = '(ClusterId == {0})'.format(batchJobID) projection = ['JobStatus', 'ToilJobKilled', 'ExitCode', 'HoldReason', 'HoldReasonSubCode'] schedd = self.connectSchedd() ads = schedd.xquery(requirements = requirements, projection = projection) # Make sure a ClassAd was returned try: try: ad = next(ads) except TypeError: ad = ads.next() except StopIteration: logger.error( "No HTCondor ads returned using constraint: {0}".format(requirements)) raise # Make sure only one ClassAd was returned try: try: next(ads) except TypeError: ads.next() except StopIteration: pass else: logger.warning( "Multiple HTCondor ads returned using constraint: {0}".format(requirements)) if ad['ToilJobKilled']: logger.debug("HTCondor job {0} was killed by Toil".format(batchJobID)) # Remove the job from the Schedd and return 1 job_spec = 'ClusterId == {0}'.format(batchJobID) schedd.act(htcondor.JobAction.Remove, job_spec) return 1 elif status[ad['JobStatus']] == 'Completed': logger.debug("HTCondor job {0} completed with exit code {1}".format( batchJobID, ad['ExitCode'])) # Remove the job from the Schedd and return its exit code job_spec = 'ClusterId == {0}'.format(batchJobID) schedd.act(htcondor.JobAction.Remove, job_spec) return int(ad['ExitCode']) elif status[ad['JobStatus']] == 'Held': logger.error("HTCondor job {0} was held: '{1} (sub code {2})'".format( batchJobID, ad['HoldReason'], ad['HoldReasonSubCode'])) # Remove the job from the Schedd and return 1 job_spec = 'ClusterId == {0}'.format(batchJobID) schedd.act(htcondor.JobAction.Remove, job_spec) return 1 else: # Job still running or idle or doing something else logger.debug("HTCondor job {0} has not completed (Status: {1})".format( batchJobID, status[ad['JobStatus']])) return None """ Implementation-specific helper methods """ def connectSchedd(self): '''Connect to HTCondor Schedd and return a Schedd object''' condor_host = os.getenv('TOIL_HTCONDOR_COLLECTOR') schedd_name = os.getenv('TOIL_HTCONDOR_SCHEDD') # If TOIL_HTCONDOR_ variables are set, use them to find the Schedd if condor_host and schedd_name: logger.debug( "Connecting to HTCondor Schedd {0} using Collector at {1}".format( schedd_name, condor_host)) try: schedd_ad = htcondor.Collector(condor_host).locate( htcondor.DaemonTypes.Schedd, schedd_name) except IOError: logger.error( "Could not connect to HTCondor Collector at {0}".format(condor_host)) raise except ValueError: logger.error( "Could not find HTCondor Schedd with name {0}".format(schedd_name)) raise else: schedd = htcondor.Schedd(schedd_ad) # Otherwise assume the Schedd is on the local machine else: logger.debug("Connecting to HTCondor Schedd on local machine") schedd = htcondor.Schedd() # Ping the Schedd to make sure it's there and responding try: schedd.xquery(limit = 0) except RuntimeError: logger.error("Could not connect to HTCondor Schedd") raise return schedd def getEnvString(self): '''Build an environment string that a HTCondor Submit object can use. For examples of valid strings, see: http://research.cs.wisc.edu/htcondor/manual/current/condor_submit.html#man-condor-submit-environment ''' env_items = [] if self.boss.environment: for key, value in self.boss.environment.items(): # Each variable should be in the form of ='' env_string = key + "=" # The entire value should be encapsulated in single quotes # Quote marks (single or double) that are part of the value should be duplicated env_string += "'" + value.replace("'", "''").replace('"', '""') + "'" env_items.append(env_string) # The entire string should be encapsulated in double quotes # Each variable should be separated by a single space return '"' + ' '.join(env_items) + '"' # Override the issueBatchJob method so HTCondor can be given the disk request def issueBatchJob(self, jobNode): # Avoid submitting internal jobs to the batch queue, handle locally localID = self.handleLocalJob(jobNode) if localID: return localID else: self.checkResourceRequest(jobNode.memory, jobNode.cores, jobNode.disk) jobID = self.getNextJobID() self.currentJobs.add(jobID) # Add the jobNode.disk and jobNode.jobName to the job tuple self.newJobsQueue.put((jobID, jobNode.cores, jobNode.memory, jobNode.disk, jobNode.jobName, jobNode.command)) logger.debug("Issued the job command: %s with job id: %s ", jobNode.command, str(jobID)) return jobID @classmethod def obtainSystemConstants(cls): # Since it's not always clear what the max cpus and max memory available # in an HTCondor slot might be, use some reasonable constants for now. # TODO: Use a htcondor.Collector().query() to determine reasonable values. max_cpu = 4 max_mem = 4e9 return max_cpu, max_mem toil-releases-3.24.0/src/toil/batchSystems/kubernetes.py000066400000000000000000001237101362134276200233120ustar00rootroot00000000000000# Copyright (C) 2019 Regents of the University of California # # 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. """ Batch system for running Toil workflows on Kubernetes. Ony useful with network-based job stores, like AWSJobStore. Within non-priveleged Kubernetes containers, additional Docker containers cannot yet be launched. That functionality will need to wait for user-mode Docker """ from __future__ import absolute_import from future import standard_library standard_library.install_aliases() from builtins import str import base64 import datetime import getpass import kubernetes import logging import os import pickle import pytz import string import subprocess import sys import uuid import time from kubernetes.client.rest import ApiException from six.moves.queue import Empty, Queue from toil import applianceSelf, customDockerInitCmd from toil.batchSystems.abstractBatchSystem import (AbstractBatchSystem, BatchSystemLocalSupport) from toil.lib.humanize import human2bytes from toil.resource import Resource logger = logging.getLogger(__name__) def slow_down(seconds): """ Toil jobs that have completed are not allowed to have taken 0 seconds, but Kubernetes timestamps things to the second. It is possible in Kubernetes for a pod to have identical start and end timestamps. This function takes a possibly 0 job length in seconds an enforces a minimum length to satisfy Toil. :param float seconds: Kubernetes timestamp difference :return: seconds, or a small positive number if seconds is 0 :rtype: float """ return max(seconds, sys.float_info.epsilon) def utc_now(): """ Return a datetime in the UTC timezone corresponding to right now. """ return datetime.datetime.utcnow().replace(tzinfo=pytz.UTC) class KubernetesBatchSystem(BatchSystemLocalSupport): @classmethod def supportsAutoDeployment(cls): return True @classmethod def supportsWorkerCleanup(cls): return False def __init__(self, config, maxCores, maxMemory, maxDisk): super(KubernetesBatchSystem, self).__init__(config, maxCores, maxMemory, maxDisk) # Turn down log level for Kubernetes modules and dependencies. # Otherwise if we are at debug log level, we dump every # request/response to Kubernetes, including tokens which we shouldn't # reveal on CI. logging.getLogger('kubernetes').setLevel(logging.ERROR) logging.getLogger('requests_oauthlib').setLevel(logging.ERROR) # This will hold the last time our Kubernetes credentials were refreshed self.credential_time = None # And this will hold our cache of API objects self._apis = {} # Get our namespace (and our Kubernetes credentials to make sure they exist) self.namespace = self._api('namespace') # Make a Kubernetes-acceptable version of our username: not too long, # and all lowercase letters, numbers, or - or . acceptableChars = set(string.ascii_lowercase + string.digits + '-.') # Use TOIL_KUBERNETES_OWNER if present in env var if os.environ.get("TOIL_KUBERNETES_OWNER", None) is not None: username = os.environ.get("TOIL_KUBERNETES_OWNER") else: username = ''.join([c for c in getpass.getuser().lower() if c in acceptableChars])[:100] # Create a prefix for jobs, starting with our username self.jobPrefix = '{}-toil-{}-'.format(username, uuid.uuid4()) # Instead of letting Kubernetes assign unique job names, we assign our # own based on a numerical job ID. This functionality is managed by the # BatchSystemLocalSupport. # Here is where we will store the user script resource object if we get one. self.userScript = None # Ge the image to deploy from Toil's configuration self.dockerImage = applianceSelf() # Get the name of the AWS secret, if any, to mount in containers. # TODO: have some way to specify this (env var?)! self.awsSecretName = os.environ.get("TOIL_AWS_SECRET_NAME", None) # Set this to True to enable the experimental wait-for-job-update code self.enableWatching = True self.jobIds = set() def _api(self, kind, max_age_seconds = 5 * 60): """ The Kubernetes module isn't clever enough to renew its credentials when they are about to expire. See https://github.com/kubernetes-client/python/issues/741. We work around this by making sure that every time we are about to talk to Kubernetes, we have fresh credentials. And we do that by reloading the config and replacing our Kubernetes API objects before we do any Kubernetes things. TODO: We can still get in trouble if a single watch or listing loop goes on longer than our credentials last, though. This method is the Right Way to get any Kubernetes API. You call it with the API you want ('batch', 'core', or 'customObjects') and it returns an API object with guaranteed fresh credentials. It also recognizes 'namespace' and returns our namespace as a string. max_age_seconds needs to be << your cluster's credential expiry time. """ now = datetime.datetime.now() if self.credential_time is None or (now - self.credential_time).total_seconds() > max_age_seconds: # Credentials need a refresh try: # Load ~/.kube/config or KUBECONFIG kubernetes.config.load_kube_config() # Worked. We're using kube config config_source = 'kube' except TypeError: # Didn't work. Try pod-based credentials in case we are in a pod. try: kubernetes.config.load_incluster_config() # Worked. We're using in_cluster config config_source = 'in_cluster' except kubernetes.config.ConfigException: raise RuntimeError('Could not load Kubernetes configuration from ~/.kube/config, $KUBECONFIG, or current pod.') # Now fill in the API objects with these credentials self._apis['batch'] = kubernetes.client.BatchV1Api() self._apis['core'] = kubernetes.client.CoreV1Api() self._apis['customObjects'] = kubernetes.client.CustomObjectsApi() # And save the time self.credential_time = now if kind == 'namespace': # We just need the namespace string if config_source == 'in_cluster': # Our namespace comes from a particular file. with open("/var/run/secrets/kubernetes.io/serviceaccount/namespace", 'r') as fh: return fh.read().strip() else: # Find all contexts and the active context. # The active context gets us our namespace. contexts, activeContext = kubernetes.config.list_kube_config_contexts() if not contexts: raise RuntimeError("No Kubernetes contexts available in ~/.kube/config or $KUBECONFIG") # Identify the namespace to work in return activeContext.get('context', {}).get('namespace', 'default') else: # We need an API object try: return self._apis[kind] except KeyError: raise RuntimeError("Unknown Kubernetes API type: {}".format(kind)) def setUserScript(self, userScript): logger.info('Setting user script for deployment: {}'.format(userScript)) self.userScript = userScript # setEnv is provided by BatchSystemSupport, updates self.environment def issueBatchJob(self, jobNode): # TODO: get a sensible self.maxCores, etc. so we can checkResourceRequest. # How do we know if the cluster will autoscale? # Try the job as local localID = self.handleLocalJob(jobNode) if localID: # It is a local job return localID else: # We actually want to send to the cluster # Check resource requirements (managed by BatchSystemSupport) self.checkResourceRequest(jobNode.memory, jobNode.cores, jobNode.disk) # Make a batch system scope job ID jobID = self.getNextJobID() # Make a unique name jobName = self.jobPrefix + str(jobID) # Make a job dict to send to the executor. # First just wrap the command and the environment to run it in job = {'command': jobNode.command, 'environment': self.environment.copy()} # TODO: query customDockerInitCmd to respect TOIL_CUSTOM_DOCKER_INIT_COMMAND if self.userScript is not None: # If there's a user script resource be sure to send it along job['userScript'] = self.userScript # Encode it in a form we can send in a command-line argument. # Pickle in the highest protocol to prevent mixed Python2/3 workflows from trying to work # TODO: Make the appliance use/support Python 3 # Make sure it is text so we can ship it to Kubernetes via JSON. encodedJob = base64.b64encode(pickle.dumps(job, pickle.HIGHEST_PROTOCOL)).decode('utf-8') # The Kubernetes API makes sense only in terms of the YAML format. Objects # represent sections of the YAML files. Except from our point of view, all # the internal nodes in the YAML structure are named and typed. # For docs, start at the root of the job hierarchy: # https://github.com/kubernetes-client/python/blob/master/kubernetes/docs/V1Job.md # Make a definition for the container's resource requirements. # Add on a bit for Kubernetes overhead (Toil worker's memory, hot deployed # user scripts). # Kubernetes needs some lower limit of memory to run the pod at all without # OOMing. We also want to provision some extra space so that when # we test _isPodStuckOOM we never get True unless the job has # exceeded jobNode.memory. requirements_dict = {'cpu': jobNode.cores, 'memory': jobNode.memory + 1024 * 1024 * 512, 'ephemeral-storage': jobNode.disk + 1024 * 1024 * 512} # Use the requirements as the limits, for predictable behavior, and because # the UCSC Kubernetes admins want it that way. limits_dict = requirements_dict resources = kubernetes.client.V1ResourceRequirements(limits=limits_dict, requests=requirements_dict) # Collect volumes and mounts volumes = [] mounts = [] # Mount volume to provision disk ephemeral_volume_name = 'tmp' ephemeral_volume_source = kubernetes.client.V1EmptyDirVolumeSource() ephemeral_volume = kubernetes.client.V1Volume(name=ephemeral_volume_name, empty_dir=ephemeral_volume_source) volumes.append(ephemeral_volume) ephemeral_volume_mount = kubernetes.client.V1VolumeMount(mount_path='/tmp', name=ephemeral_volume_name) mounts.append(ephemeral_volume_mount) if self.awsSecretName is not None: # Also mount an AWS secret, if provided. # TODO: make this generic somehow secret_volume_name = 's3-credentials' secret_volume_source = kubernetes.client.V1SecretVolumeSource(secret_name=self.awsSecretName) secret_volume = kubernetes.client.V1Volume(name=secret_volume_name, secret=secret_volume_source) volumes.append(secret_volume) secret_volume_mount = kubernetes.client.V1VolumeMount(mount_path='/root/.aws', name=secret_volume_name) mounts.append(secret_volume_mount) # Make a container definition container = kubernetes.client.V1Container(command=['_toil_kubernetes_executor', encodedJob], image=self.dockerImage, name="runner-container", resources=resources, volume_mounts=mounts) # Wrap the container in a spec pod_spec = kubernetes.client.V1PodSpec(containers=[container], volumes=volumes, restart_policy="Never") # Wrap the spec in a template template = kubernetes.client.V1PodTemplateSpec(spec=pod_spec) # Make another spec for the job, asking to run the template with no backoff job_spec = kubernetes.client.V1JobSpec(template=template, backoff_limit=0) # Make metadata to tag the job with info. # We use generate_name to ensure a unique name metadata = kubernetes.client.V1ObjectMeta(name=jobName) # And make the actual job job = kubernetes.client.V1Job(spec=job_spec, metadata=metadata, api_version="batch/v1", kind="Job") # Make the job launched = self._api('batch').create_namespaced_job(self.namespace, job) logger.debug('Launched job: %s', jobName) return jobID def _isJobOurs(self, jobObject): """ Determine if a Kubernetes job belongs to us. :param kubernetes.client.V1Job jobObject: a Kubernetes job being considered. :return: True if the job is our responsibility, and false otherwise. :rtype: bool """ return jobObject.metadata.name.startswith(self.jobPrefix) def _ourJobObjects(self, onlySucceeded=False, limit=None): """ Yield all Kubernetes V1Job objects that we are responsible for that the cluster knows about. Doesn't support a free-form selector, because there's only about 3 things jobs can be selected on: https://stackoverflow.com/a/55808444 :param bool onlySucceeded: restrict results to succeeded jobs. :param int limit: max results to yield. """ # We need to page through the list from the cluster with a continuation # token. These expire after about 5 minutes. If we use an expired one, # we get a 410 error and a new token, and we can use the new token to # get the rest of the list, but the list will be updated. # # TODO: How to get the new token isn't clear. See # https://github.com/kubernetes-client/python/issues/953. For now we # will just throw an error if we don't get to the end of the list in # time. token = None # Do our own limiting since we need to apply a filter that the server # can't. seen = 0 # TODO: We ought to label our jobs by owning Toil workflow so we can # look them up instead of filtering down later. while True: # We can't just pass e.g. a None continue token when there isn't # one, because the Kubernetes module reads its kwargs dict and # cares about presence/absence. So we build a dict to send. kwargs = {} if onlySucceeded: # Check only successful jobs. # Note that for selectors it is "successful" while for the # actual object field it is "succeeded". kwargs['field_selector'] = 'status.successful==1' if token is not None: kwargs['_continue'] = token results = self._api('batch').list_namespaced_job(self.namespace, **kwargs) for job in results.items: if self._isJobOurs(job): # This job belongs to us yield job # Don't go over the limit seen += 1 if limit is not None and seen >= limit: return # Remember the continuation token, if any token = getattr(results.metadata, 'continue', None) if token is None: # There isn't one. We got everything. break def _getPodForJob(self, jobObject): """ Get the pod that belongs to the given job, or None if the job's pod is missing. The pod knows about things like the job's exit code. :param kubernetes.client.V1Job jobObject: a Kubernetes job to look up pods for. :return: The pod for the job, or None if no pod is found. :rtype: kubernetes.client.V1Pod """ token = None # Work out what the return code was (which we need to get from the # pods) We get the associated pods by querying on the label selector # `job-name=JOBNAME` query = 'job-name={}'.format(jobObject.metadata.name) while True: # We can't just pass e.g. a None continue token when there isn't # one, because the Kubernetes module reads its kwargs dict and # cares about presence/absence. So we build a dict to send. kwargs = {'label_selector': query} if token is not None: kwargs['_continue'] = token results = self._api('core').list_namespaced_pod(self.namespace, **kwargs) for pod in results.items: # Return the first pod we find return pod # Remember the continuation token, if any token = getattr(results.metadata, 'continue', None) if token is None: # There isn't one. We got everything. break # If we get here, no pages had any pods. return None def _getLogForPod(self, podObject): """ Get the log for a pod. :param kubernetes.client.V1Pod podObject: a Kubernetes pod with one container to get the log from. :return: The log for the only container in the pod. :rtype: str """ return self._api('core').read_namespaced_pod_log(podObject.metadata.name, namespace=self.namespace) def _isPodStuckOOM(self, podObject, minFreeBytes=1024 * 1024 * 2): """ Poll the current memory usage for the pod from the cluster. Return True if the pod looks to be in a soft/stuck out of memory (OOM) state, where it is using too much memory to actually make progress, but not enough to actually trigger the OOM killer to kill it. For some large memory limits, on some Kubernetes clusters, pods can get stuck in this state when their memory limits are high (approx. 200 Gi). We operationalize "OOM" as having fewer than minFreeBytes bytes free. We assume the pod has only one container, as Toil's pods do. :param kubernetes.client.V1Pod podObject: a Kubernetes pod with one container to check up on. :param int minFreeBytes: Minimum free bytes to not be OOM. :return: True if the pod is OOM, false otherwise. :rtype: bool """ # Compose a query to get just the pod we care about query = 'metadata.name=' + podObject.metadata.name # Look for it # TODO: When the Kubernetes Python API actually wraps the metrics API, switch to that response = self._api('customObjects').list_namespaced_custom_object('metrics.k8s.io', 'v1beta1', self.namespace, 'pods', field_selector=query) # Pull out the items items = response.get('items', []) if len(items) == 0: # If there's no statistics we can't say we're stuck OOM return False # Assume the first result is the right one, because of the selector # Assume it has exactly one pod, because we made it containers = items[0].get('containers', [{}]) if len(containers) == 0: # If there are no containers (because none have started yet?), we can't say we're stuck OOM return False # Otherwise, assume it just has one container. # Grab the memory usage string, like 123Ki, and convert to bytes. # If anything is missing, assume 0 bytes used. bytesUsed = human2bytes(containers[0].get('usage', {}).get('memory', '0')) # Also get the limit out of the pod object's spec bytesAllowed = human2bytes(podObject.spec.containers[0].resources.limits['memory']) if bytesAllowed - bytesUsed < minFreeBytes: # This is too much! logger.warning('Pod %s has used %d of %d bytes of memory; reporting as stuck due to OOM.', podObject.metadata.name, bytesUsed, bytesAllowed) return True def _getIDForOurJob(self, jobObject): """ Get the JobID number that belongs to the given job that we own. :param kubernetes.client.V1Job jobObject: a Kubernetes job object that is a job we issued. :return: The JobID for the job. :rtype: int """ return int(jobObject.metadata.name[len(self.jobPrefix):]) def getUpdatedBatchJob(self, maxWait): entry = datetime.datetime.now() result = self._getUpdatedBatchJobImmediately() if result is not None or maxWait == 0: # We got something on the first try, or we only get one try return result # Otherwise we need to maybe wait. if self.enableWatching: # Try watching for something to happen and use that. w = kubernetes.watch.Watch() if self.enableWatching: for j in self._ourJobObjects(): for event in w.stream(self._api('core').list_namespaced_pod, self.namespace, timeout_seconds=maxWait): pod = event['object'] if pod.metadata.name.startswith(self.jobPrefix): if pod.status.phase == 'Failed' or pod.status.phase == 'Succeeded': containerStatuses = pod.status.container_statuses logger.debug("FINISHED") if containerStatuses is None or len(containerStatuses) == 0: logger.debug("No job container statuses for job %s" % (pod.metadata.owner_references[0].name)) return (int(pod.metadata.owner_references[0].name[len(self.jobPrefix):]), -1, 0) # Get termination onformation from the pod termination = pod.status.container_statuses[0].state.terminated logger.info("REASON: %s Exit Code: %s", termination.reason, termination.exit_code) if termination.exit_code != 0: # The pod failed. Dump information about it. logger.debug('Failed pod information: %s', str(pod)) logger.warning('Log from failed pod: %s', self._getLogForPod(pod)) jobID = int(pod.metadata.owner_references[0].name[len(self.jobPrefix):]) terminated = pod.status.container_statuses[0].state.terminated runtime = slow_down((terminated.finished_at - terminated.started_at).total_seconds()) result = (jobID, terminated.exit_code, runtime) self._api('batch').delete_namespaced_job(pod.metadata.owner_references[0].name, self.namespace, propagation_policy='Foreground') self._waitForJobDeath(pod.metadata.owner_references[0].name) return result else: continue else: # Try polling instead while result is None and (datetime.datetime.now() - entry).total_seconds() < maxWait: # We still have nothing and we haven't hit the timeout. # Poll result = self._getUpdatedBatchJobImmediately() if result is None: # Still nothing. Wait a second, or some fraction of our max wait time. time.sleep(min(maxWait/2, 1.0)) # When we get here, either we found something or we ran out of time return result def _getUpdatedBatchJobImmediately(self): """ Return None if no updated (completed or failed) batch job is currently available, and jobID, exitCode, runtime if such a job can be found. """ # See if a local batch job has updated and is available immediately local_tuple = self.getUpdatedLocalJob(0) if local_tuple: # If so, use it return local_tuple # Otherwise we didn't get a local job. # Go looking for other jobs # Everybody else does this with a queue and some other thread that # is responsible for populating it. # But we can just ask kubernetes now. # Find a job that is done, failed, or stuck jobObject = None # Put 'done', 'failed', or 'stuck' here chosenFor = '' for j in self._ourJobObjects(onlySucceeded=True, limit=1): # Look for succeeded jobs because that's the only filter Kubernetes has jobObject = j chosenFor = 'done' if jobObject is None: for j in self._ourJobObjects(): # If there aren't any succeeded jobs, scan all jobs # See how many times each failed failCount = getattr(j.status, 'failed', 0) if failCount is None: # Make sure it is an int failCount = 0 if failCount > 0: # Take the first failed one you find jobObject = j chosenFor = 'failed' break if jobObject is None: # If no jobs are failed, look for jobs with pods that are stuck for various reasons. for j in self._ourJobObjects(): pod = self._getPodForJob(j) if pod is None: # Skip jobs with no pod continue # Containers can get stuck in Waiting with reason ImagePullBackOff # Get the statuses of the pod's containers containerStatuses = pod.status.container_statuses if containerStatuses is None or len(containerStatuses) == 0: # Pod exists but has no container statuses # This happens when the pod is just "Scheduled" # ("PodScheduled" status event) and isn't actually starting # to run yet. # Can't be stuck in ImagePullBackOff continue waitingInfo = getattr(getattr(pod.status.container_statuses[0], 'state', None), 'waiting', None) if waitingInfo is not None and waitingInfo.reason == 'ImagePullBackOff': # Assume it will never finish, even if the registry comes back or whatever. # We can get into this state when we send in a non-existent image. # See https://github.com/kubernetes/kubernetes/issues/58384 jobObject = j chosenFor = 'stuck' logger.warning('Failing stuck job; did you try to run a non-existent Docker image?' ' Check TOIL_APPLIANCE_SELF.') break # Pods can also get stuck nearly but not quite out of memory, # if their memory limits are high and they try to exhaust them. if self._isPodStuckOOM(pod): # We found a job that probably should be OOM! Report it as stuck. # Polling function takes care of the logging. jobObject = j chosenFor = 'stuck' break if jobObject is None: # Say we couldn't find anything return None # Otherwise we got something. # Work out what the job's ID was (whatever came after our name prefix) jobID = int(jobObject.metadata.name[len(self.jobPrefix):]) # Work out when the job was submitted. If the pod fails before actually # running, this is the basis for our runtime. jobSubmitTime = getattr(jobObject.status, 'start_time', None) if jobSubmitTime is None: # If somehow this is unset, say it was just now. jobSubmitTime = utc_now() # Grab the pod pod = self._getPodForJob(jobObject) if pod is not None: if chosenFor == 'done' or chosenFor == 'failed': # The job actually finished or failed # Get the statuses of the pod's containers containerStatuses = pod.status.container_statuses # Get when the pod started (reached the Kubelet) as a datetime startTime = getattr(pod.status, 'start_time', None) if startTime is None: # If the pod never made it to the kubelet to get a # start_time, say it was when the job was submitted. startTime = jobSubmitTime if containerStatuses is None or len(containerStatuses) == 0: # No statuses available. # This happens when a pod is "Scheduled". But how could a # 'done' or 'failed' pod be merely "Scheduled"? # Complain so we can find out. logger.warning('Exit code and runtime unavailable; pod has no container statuses') logger.warning('Pod: %s', str(pod)) exitCode = -1 # Say it stopped now and started when it was scheduled/submitted. # We still need a strictly positive runtime. runtime = slow_down((utc_now() - startTime).totalSeconds()) else: # Get the termination info from the pod's main (only) container terminatedInfo = getattr(getattr(containerStatuses[0], 'state', None), 'terminated', None) if terminatedInfo is None: logger.warning('Exit code and runtime unavailable; pod stopped without container terminating') logger.warning('Pod: %s', str(pod)) exitCode = -1 # Say it stopped now and started when it was scheduled/submitted. # We still need a strictly positive runtime. runtime = slow_down((utc_now() - startTime).totalSeconds()) else: # Extract the exit code exitCode = terminatedInfo.exit_code # Compute how long the job actually ran for (subtract # datetimes). We need to look at the pod's start time # because the job's start time is just when the job is # created. And we need to look at the pod's end time # because the job only gets a completion time if # successful. runtime = slow_down((terminatedInfo.finished_at - pod.status.start_time).total_seconds()) if chosenFor == 'failed': # Warn the user with the failed pod's log # TODO: cut this down somehow? logger.warning('Log from failed pod: %s', self._getLogForPod(pod)) else: # The job has gotten stuck assert chosenFor == 'stuck' # Synthesize an exit code exitCode = -1 # Say it ran from when the job was submitted to when the pod got stuck runtime = slow_down((utc_now() - jobSubmitTime).totalSeconds()) else: # The pod went away from under the job. logging.warning('Exit code and runtime unavailable; pod vanished') exitCode = -1 # Say it ran from when the job was submitted to when the pod vanished runtime = slow_down((utc_now() - jobSubmitTime).totalSeconds()) try: # Delete the job and all dependents (pods) self._api('batch').delete_namespaced_job(jobObject.metadata.name, self.namespace, propagation_policy='Foreground') # That just kicks off the deletion process. Foreground doesn't # actually block. See # https://kubernetes.io/docs/concepts/workloads/controllers/garbage-collection/#foreground-cascading-deletion # We have to either wait until the deletion is done and we can't # see the job anymore, or ban the job from being "updated" again if # we see it. If we don't block on deletion, we can't use limit=1 # on our query for succeeded jobs. So we poll for the job's # non-existence. self._waitForJobDeath(jobObject.metadata.name) except kubernetes.client.rest.ApiException: # TODO: check to see if this is a 404 on the thing we tried to delete # If so, it is gone already and we don't need to delete it again. pass # Return the one finished job we found return jobID, exitCode, runtime def _waitForJobDeath(self, jobName): """ Block until the job with the given name no longer exists. """ # We do some exponential backoff on the polling # TODO: use a wait instead of polling? backoffTime = 0.1 maxBackoffTime = 6.4 while True: try: # Look for the job self._api('batch').read_namespaced_job(jobName, self.namespace) # If we didn't 404, wait a bit with exponential backoff time.sleep(backoffTime) if backoffTime < maxBackoffTime: backoffTime *= 2 except kubernetes.client.rest.ApiException: # We finally got a failure! break def shutdown(self): # Shutdown local processes first self.shutdownLocal() # Clears jobs belonging to this run for job in self._ourJobObjects(): jobName = job.metadata.name try: # Look at the pods and log why they failed, if they failed, for debugging. pod = self._getPodForJob(job) if pod.status.phase == 'Failed': logger.debug('Failed pod encountered at shutdown: %s', str(pod)) except: # Don't get mad if that doesn't work. pass # Kill jobs whether they succeeded or failed try: # Delete with background poilicy so we can quickly issue lots of commands response = self._api('batch').delete_namespaced_job(jobName, self.namespace, propagation_policy='Background') logger.debug('Killed job for shutdown: %s', jobName) except ApiException as e: logger.error("Exception when calling BatchV1Api->delte_namespaced_job: %s" % e) def _getIssuedNonLocalBatchJobIDs(self): """ Get the issued batch job IDs that are not for local jobs. """ jobIDs = [] got_list = self._ourJobObjects() for job in got_list: # Get the ID for each job jobIDs.append(self._getIDForOurJob(job)) return jobIDs def getIssuedBatchJobIDs(self): # Make sure to send the local jobs also return self._getIssuedNonLocalBatchJobIDs() + list(self.getIssuedLocalJobIDs()) def getRunningBatchJobIDs(self): # We need a dict from jobID (integer) to seconds it has been running secondsPerJob = dict() for job in self._ourJobObjects(): # Grab the pod for each job pod = self._getPodForJob(job) if pod is None: # Jobs whose pods are gone are not running continue if pod.status.phase == 'Running': # The job's pod is running # The only time we have handy is when the pod got assigned to a # kubelet, which is technically before it started running. runtime = (utc_now() - pod.status.start_time).total_seconds() # Save it under the stringified job ID secondsPerJob[self._getIDForOurJob(job)] = runtime # Mix in the local jobs secondsPerJob.update(self.getRunningLocalJobIDs()) return secondsPerJob def killBatchJobs(self, jobIDs): # Kill all the ones that are local self.killLocalJobs(jobIDs) # Clears workflow's jobs listed in jobIDs. # First get the jobs we even issued non-locally issuedOnKubernetes = set(self._getIssuedNonLocalBatchJobIDs()) for jobID in jobIDs: # For each job we are supposed to kill if jobID not in issuedOnKubernetes: # It never went to Kubernetes (or wasn't there when we just # looked), so we can't kill it on Kubernetes. continue # Work out what the job would be named jobName = self.jobPrefix + str(jobID) # Delete the requested job in the foreground. # This doesn't block, but it does delete expeditiously. response = self._api('batch').delete_namespaced_job(jobName, self.namespace, propagation_policy='Foreground') logger.debug('Killed job by request: %s', jobName) for jobID in jobIDs: # Now we need to wait for all the jobs we killed to be gone. # Work out what the job would be named jobName = self.jobPrefix + str(jobID) # Block until it doesn't exist self._waitForJobDeath(jobName) def executor(): """ Main function of the _toil_kubernetes_executor entrypoint. Runs inside the Toil container. Responsible for setting up the user script and running the command for the job (which may in turn invoke the Toil worker entrypoint). """ logging.basicConfig(level=logging.DEBUG) logger.debug("Starting executor") if len(sys.argv) != 2: logger.error('Executor requires exactly one base64-encoded argument') sys.exit(1) # Take in a base64-encoded pickled dict as our first argument and decode it try: # Make sure to encode the text arguments to bytes before base 64 decoding job = pickle.loads(base64.b64decode(sys.argv[1].encode('utf-8'))) except: exc_info = sys.exc_info() logger.error('Exception while unpickling task: ', exc_info=exc_info) sys.exit(1) # Set JTRES_ROOT and other global state needed for resource # downloading/deployment to work. logger.debug('Preparing system for resource download') Resource.prepareSystem() if 'userScript' in job: job['userScript'].register() logger.debug("Invoking command: '%s'", job['command']) # Construct the job's environment jobEnv = dict(os.environ, **job['environment']) logger.debug('Using environment variables: %s', jobEnv.keys()) # Start the child process child = subprocess.Popen(job['command'], preexec_fn=lambda: os.setpgrp(), shell=True, env=jobEnv) # Reporduce child's exit code sys.exit(child.wait()) toil-releases-3.24.0/src/toil/batchSystems/lsf.py000066400000000000000000000243311362134276200217260ustar00rootroot00000000000000# Copyright (C) 2013 by Thomas Keane (tk2@sanger.ac.uk) # # Permission is hereby granted, free of charge, to any person obtaining a copy # of this software and associated documentation files (the "Software"), to deal # in the Software without restriction, including without limitation the rights # to use, copy, modify, merge, publish, distribute, sublicense, and/or sell # copies of the Software, and to permit persons to whom the Software is # furnished to do so, subject to the following conditions: # # The above copyright notice and this permission notice shall be included in # all copies or substantial portions of the Software. # # THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR # IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, # FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE # AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER # LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, # OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN # THE SOFTWARE. from __future__ import absolute_import from __future__ import division from builtins import str from builtins import range from past.utils import old_div import logging import math from toil import subprocess import os from dateutil.parser import parse from dateutil.tz import tzlocal from datetime import datetime from toil.batchSystems import MemoryString from toil.batchSystems.abstractGridEngineBatchSystem import \ AbstractGridEngineBatchSystem from toil.batchSystems.lsfHelper import (parse_memory_resource, parse_memory_limit, per_core_reservation) logger = logging.getLogger(__name__) class LSFBatchSystem(AbstractGridEngineBatchSystem): class Worker(AbstractGridEngineBatchSystem.Worker): """LSF specific AbstractGridEngineWorker methods.""" def getRunningJobIDs(self): times = {} with self.runningJobsLock: currentjobs = dict((str(self.batchJobIDs[x][0]), x) for x in self.runningJobs) process = subprocess.Popen( ["bjobs", "-o", "jobid stat start_time delimiter='|'"], stdout=subprocess.PIPE) stdout, _ = process.communicate() for curline in stdout.decode('utf-8').split('\n'): items = curline.strip().split('|') if items[0] in currentjobs and items[1] == 'RUN': jobstart = parse(items[2], default=datetime.now(tzlocal())) times[currentjobs[items[0]]] = datetime.now(tzlocal()) \ - jobstart return times def killJob(self, jobID): subprocess.check_call(['bkill', self.getBatchSystemID(jobID)]) def prepareSubmission(self, cpu, memory, jobID, command, jobName): return self.prepareBsub(cpu, memory, jobID) + [command] def submitJob(self, subLine): combinedEnv = self.boss.environment combinedEnv.update(os.environ) process = subprocess.Popen(subLine, stdout=subprocess.PIPE, env=combinedEnv) line = process.stdout.readline().decode('utf-8') logger.debug("BSUB: " + line) result = int(line.strip().split()[1].strip('<>')) logger.debug("Got the job id: {}".format(result)) return result def getJobExitCode(self, lsfJobID): # the task is set as part of the job ID if using getBatchSystemID() job, task = (lsfJobID, None) if '.' in lsfJobID: job, task = lsfJobID.split('.', 1) # first try bjobs to find out job state args = ["bjobs", "-l", str(job)] logger.debug("Checking job exit code for job via bjobs: " "{}".format(job)) process = subprocess.Popen(args, stdout=subprocess.PIPE, stderr=subprocess.STDOUT) output = process.stdout.read().decode('utf-8').replace("\n ", "") process_output = output.split('\n') started = 0 for line in process_output: if "Done successfully" in line or "Status " in line: logger.debug("bjobs detected job completed for job: " "{}".format(job)) return 0 elif "New job is waiting for scheduling" in line: logger.debug("bjobs detected job pending scheduling for " "job: {}".format(job)) return None elif "PENDING REASONS" in line or "Status " in line: logger.debug("bjobs detected job pending for job: " "{}".format(job)) return None elif "Exited with exit code" in line: exit = int(line[line.find("Exited with exit code ")+22:] .split('.')[0]) logger.error("bjobs detected job exit code " "{} for job {}".format(exit, job)) return exit elif "Completed " in line: logger.error("bjobs detected job failed for job: " "{}".format(job)) return 1 elif line.find("Started on ") > -1 or "Status " in line: started = 1 if started == 1: logger.debug("bjobs detected job started but not completed: " "{}".format(job)) return None # if not found in bjobs, then try bacct (slower than bjobs) logger.debug("bjobs failed to detect job - trying bacct: " "{}".format(job)) args = ["bacct", "-l", str(job)] process = subprocess.Popen(args, stdout=subprocess.PIPE, stderr=subprocess.STDOUT) output = process.stdout.read().decode('utf-8') process_output = output.split('\n') for line in process_output: if line.find("Completed ") > -1 or line.find("") > -1: logger.debug("Detected job completed for job: " "{}".format(job)) return 0 elif line.find("Completed ") > -1 or line.find("") > -1: logger.error("Detected job failed for job: " "{}".format(job)) return 1 logger.debug("Can't determine exit code for job or job still " "running: {}".format(job)) return None """ Implementation-specific helper methods """ def prepareBsub(self, cpu, mem, jobID): """ Make a bsub commandline to execute. params: cpu: number of cores needed mem: number of bytes of memory needed jobID: ID number of the job """ if mem: if per_core_reservation(): mem = float(mem)/1024**3/math.ceil(cpu) mem_resource = parse_memory_resource(mem) mem_limit = parse_memory_limit(mem) else: mem = old_div(float(mem), 1024**3) mem_resource = parse_memory_resource(mem) mem_limit = parse_memory_limit(mem) bsubMem = ['-R', 'select[mem > {m}] ' 'rusage[mem={m}]'.format(m=mem_resource), '-M', str(mem_limit)] else: bsubMem = [] bsubCpu = [] if cpu is None else ['-n', str(math.ceil(cpu))] bsubline = ["bsub", "-cwd", ".", "-J", "toil_job_{}".format(jobID)] bsubline.extend(bsubMem) bsubline.extend(bsubCpu) stdoutfile = self.boss.formatStdOutErrPath(jobID, 'lsf', '%J', 'std_output') stderrfile = self.boss.formatStdOutErrPath(jobID, 'lsf', '%J', 'std_error') bsubline.extend(['-o', stdoutfile, '-e', stderrfile]) lsfArgs = os.getenv('TOIL_LSF_ARGS') if lsfArgs: bsubline.extend(lsfArgs.split()) return bsubline def getWaitDuration(self): """We give LSF a second to catch its breath (in seconds)""" return 8 @classmethod def obtainSystemConstants(cls): p = subprocess.Popen(["lshosts"], stdout=subprocess.PIPE, stderr=subprocess.STDOUT) line = p.stdout.readline().decode('utf-8') items = line.strip().split() num_columns = len(items) cpu_index = None mem_index = None for i in range(num_columns): if items[i] == 'ncpus': cpu_index = i elif items[i] == 'maxmem': mem_index = i if cpu_index is None or mem_index is None: RuntimeError("lshosts command does not return ncpus or maxmem " "columns") # p.stdout.readline().decode('utf-8') maxCPU = 0 maxMEM = MemoryString("0") for line in p.stdout: split_items = line.strip().split() items = [item.decode('utf-8') for item in split_items if isinstance(item, bytes)] if len(items) < num_columns: RuntimeError("lshosts output has a varying number of " "columns") if items[cpu_index] != '-' and int(items[cpu_index]) > int(maxCPU): maxCPU = items[cpu_index] if (items[mem_index] != '-' and MemoryString(items[mem_index]) > maxMEM): maxMEM = MemoryString(items[mem_index]) if maxCPU is 0 or maxMEM is 0: RuntimeError("lshosts returns null ncpus or maxmem info") logger.debug("Got the maxMEM: {}".format(maxMEM)) logger.debug("Got the maxCPU: {}".format(maxCPU)) return maxCPU, maxMEM toil-releases-3.24.0/src/toil/batchSystems/lsfHelper.py000077500000000000000000000137131362134276200230730ustar00rootroot00000000000000#!/usr/bin/env python # Adapted from https://github.com/roryk/ipython-cluster-helper # ipython-cluster-helper is licensed under the MIT license # # Copyright 2013-2017 "Rory Kirchne" and contributors # # Permission is hereby granted, free of charge, to any person obtaining a copy # of this software and associated documentation files (the "Software"), to deal # in the Software without restriction, including without limitation the rights # to use, copy, modify, merge, publish, distribute, sublicense, and/or sell # copies of the Software, and to permit persons to whom the Software is # furnished to do so, subject to the following conditions: # # The above copyright notice and this permission notice shall be included in all # copies or substantial portions of the Software. # # THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR # IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, # FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE # AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER # LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, # OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE # SOFTWARE. from __future__ import print_function from __future__ import division from past.utils import old_div import math import os from toil import subprocess import fnmatch LSB_PARAMS_FILENAME = "lsb.params" LSF_CONF_FILENAME = "lsf.conf" LSF_CONF_ENV = ["LSF_CONFDIR", "LSF_ENVDIR"] DEFAULT_LSF_UNITS = "KB" DEFAULT_RESOURCE_UNITS = "MB" def find(basedir, string): """ walk basedir and return all files matching string """ matches = [] for root, dirnames, filenames in os.walk(basedir): for filename in fnmatch.filter(filenames, string): matches.append(os.path.join(root, filename)) return matches def find_first_match(basedir, string): """ return the first file that matches string starting from basedir """ matches = find(basedir, string) return matches[0] if matches else matches def get_conf_file(filename, env): conf_path = os.environ.get(env) if not conf_path: return None conf_file = find_first_match(conf_path, filename) return conf_file def apply_conf_file(fn, conf_filename): for env in LSF_CONF_ENV: conf_file = get_conf_file(conf_filename, env) if conf_file: with open(conf_file) as conf_handle: value = fn(conf_handle) if value: return value return None def per_core_reserve_from_stream(stream): for k, v in tokenize_conf_stream(stream): if k in {"RESOURCE_RESERVE_PER_SLOT", "RESOURCE_RESERVE_PER_TASK"}: return v.upper() return None def get_lsf_units_from_stream(stream): for k, v in tokenize_conf_stream(stream): if k == "LSF_UNIT_FOR_LIMITS": return v return None def tokenize_conf_stream(conf_handle): """ convert the key=val pairs in a LSF config stream to tuples of tokens """ for line in conf_handle: if line.startswith("#"): continue tokens = line.split("=") if len(tokens) != 2: continue yield (tokens[0].strip(), tokens[1].strip()) def apply_bparams(fn): """ apply fn to each line of bparams, returning the result """ cmd = ["bparams", "-a"] try: output = subprocess.check_output(cmd).decode('utf-8') except: return None return fn(output.split("\n")) def apply_lsadmin(fn): """ apply fn to each line of lsadmin, returning the result """ cmd = ["lsadmin", "showconf", "lim"] try: output = subprocess.check_output(cmd).decode('utf-8') except: return None return fn(output.split("\n")) def get_lsf_units(resource=False): """ check if we can find LSF_UNITS_FOR_LIMITS in lsadmin and lsf.conf files, preferring the value in bparams, then lsadmin, then the lsf.conf file """ lsf_units = apply_bparams(get_lsf_units_from_stream) if lsf_units: return lsf_units lsf_units = apply_lsadmin(get_lsf_units_from_stream) if lsf_units: return lsf_units lsf_units = apply_conf_file(get_lsf_units_from_stream, LSF_CONF_FILENAME) if lsf_units: return lsf_units # -R usage units are in MB, not KB by default if resource: return DEFAULT_RESOURCE_UNITS else: return DEFAULT_LSF_UNITS def parse_memory_resource(mem): """ Parse memory parameter for -R """ return parse_memory(mem, True) def parse_memory_limit(mem): """ Parse memory parameter for -M """ return parse_memory(mem, False) def parse_memory(mem, resource): """ Parse memory parameter """ lsf_unit = get_lsf_units(resource=resource) return convert_mb(float(mem) * 1024, lsf_unit) def per_core_reservation(): """ returns True if the cluster is configured for reservations to be per core, False if it is per job """ per_core = apply_bparams(per_core_reserve_from_stream) if per_core: if per_core.upper() == "Y": return True else: return False per_core = apply_lsadmin(per_core_reserve_from_stream) if per_core: if per_core.upper() == "Y": return True else: return False per_core = apply_conf_file(per_core_reserve_from_stream, LSB_PARAMS_FILENAME) if per_core and per_core.upper() == "Y": return True else: return False return False def convert_mb(kb, unit): UNITS = {"B": -2, "KB": -1, "MB": 0, "GB": 1, "TB": 2} assert unit in UNITS, ("%s not a valid unit, valid units are %s." % (unit, list(UNITS.keys()))) return int(old_div(float(kb), float(math.pow(1024, UNITS[unit])))) if __name__ == "__main__": print(get_lsf_units()) print(per_core_reservation()) toil-releases-3.24.0/src/toil/batchSystems/mesos/000077500000000000000000000000001362134276200217135ustar00rootroot00000000000000toil-releases-3.24.0/src/toil/batchSystems/mesos/__init__.py000066400000000000000000000066551362134276200240400ustar00rootroot00000000000000# Copyright (C) 2015-2016 Regents of the University of California # # 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. from __future__ import absolute_import from future import standard_library standard_library.install_aliases() from builtins import object from queue import Queue from collections import namedtuple from bisect import bisect from threading import Lock from toil.provisioners.abstractProvisioner import Shape TaskData = namedtuple('TaskData', ( # Time when the task was started 'startTime', # Mesos' ID of the agent where task is being run 'agentID', # IP of agent where task is being run 'agentIP', # Mesos' ID of the executor running the task 'executorID', # Memory requirement of the task 'memory', # CPU requirement of the task 'cores')) class JobQueue(object): def __init__(self): # mapping of jobTypes to queues of jobs of that type self.queues = {} # list of jobTypes in decreasing resource expense self.sortedTypes = [] self.jobLock = Lock() def insertJob(self, job, jobType): with self.jobLock: if jobType not in self.queues: index = bisect(self.sortedTypes, jobType) self.sortedTypes.insert(index, jobType) self.queues[jobType] = Queue() self.queues[jobType].put(job) def jobIDs(self): with self.jobLock: return [job.jobID for queue in list(self.queues.values()) for job in list(queue.queue)] def nextJobOfType(self, jobType): with self.jobLock: job = self.queues[jobType].get(block=False) if self.queues[jobType].empty(): del self.queues[jobType] self.sortedTypes.remove(jobType) return job def typeEmpty(self, jobType): # without a lock we could get a false negative from this method # if it were called while nextJobOfType was executing with self.jobLock: return self.queues.get(jobType, Queue()).empty() class MesosShape(Shape): def __gt__(self, other): """ Inverted. Returns True if self is less than other, else returns False. This is because jobTypes are sorted in decreasing order, and this was done to give expensive jobs priority. """ return not self.greater_than(other) ToilJob = namedtuple('ToilJob', ( # A job ID specific to this batch system implementation 'jobID', # What string to display in the mesos UI 'name', # A ResourceRequirement tuple describing the resources needed by this job 'resources', # The command to be run on the worker node 'command', # The resource object representing the user script 'userScript', # A dictionary with additional environment variables to be set on the worker process 'environment', # A named tuple containing all the required info for cleaning up the worker node 'workerCleanupInfo')) toil-releases-3.24.0/src/toil/batchSystems/mesos/batchSystem.py000066400000000000000000001107321362134276200245570ustar00rootroot00000000000000# Copyright (C) 2015-2016 Regents of the University of California # # 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. from __future__ import absolute_import from builtins import filter from builtins import str from builtins import object import ast import logging import os import pwd import socket import time import sys import getpass import json import traceback import addict try: from urllib2 import urlopen from urllib import quote_plus except ImportError: from urllib.request import urlopen from urllib.parse import quote_plus from contextlib import contextmanager from six.moves.queue import Empty, Queue from six import iteritems, itervalues from pymesos import MesosSchedulerDriver, Scheduler, encode_data, decode_data from toil.lib.compatibility import USING_PYTHON2 from toil import pickle from toil.lib.memoize import strict_bool from toil import resolveEntryPoint from toil.batchSystems.abstractBatchSystem import (AbstractScalableBatchSystem, BatchSystemLocalSupport, NodeInfo) from toil.batchSystems.mesos import ToilJob, MesosShape, TaskData, JobQueue log = logging.getLogger(__name__) class MesosBatchSystem(BatchSystemLocalSupport, AbstractScalableBatchSystem, Scheduler): """ A Toil batch system implementation that uses Apache Mesos to distribute toil jobs as Mesos tasks over a cluster of agent nodes. A Mesos framework consists of a scheduler and an executor. This class acts as the scheduler and is typically run on the master node that also runs the Mesos master process with which the scheduler communicates via a driver component. The executor is implemented in a separate class. It is run on each agent node and communicates with the Mesos agent process via another driver object. The scheduler may also be run on a separate node from the master, which we then call somewhat ambiguously the driver node. """ @classmethod def supportsAutoDeployment(cls): return True @classmethod def supportsWorkerCleanup(cls): return True class ExecutorInfo(object): def __init__(self, nodeAddress, agentId, nodeInfo, lastSeen): super(MesosBatchSystem.ExecutorInfo, self).__init__() self.nodeAddress = nodeAddress self.agentId = agentId self.nodeInfo = nodeInfo self.lastSeen = lastSeen def __init__(self, config, maxCores, maxMemory, maxDisk): super(MesosBatchSystem, self).__init__(config, maxCores, maxMemory, maxDisk) # The auto-deployed resource representing the user script. Will be passed along in every # Mesos task. Also see setUserScript(). self.userScript = None """ :type: toil.resource.Resource """ # Dictionary of queues, which toil assigns jobs to. Each queue represents a job type, # defined by resource usage self.jobQueues = JobQueue() # Address of the Mesos master in the form host:port where host can be an IP or a hostname self.mesosMasterAddress = config.mesosMasterAddress # Written to when Mesos kills tasks, as directed by Toil. # Jobs must not enter this set until they are removed from runningJobMap. self.killedJobIds = set() # The IDs of job to be killed self.killJobIds = set() # Contains jobs on which killBatchJobs were called, regardless of whether or not they # actually were killed or ended by themselves self.intendedKill = set() # Map of host address to job ids # this is somewhat redundant since Mesos returns the number of workers per # node. However, that information isn't guaranteed to reach the leader, # so we also track the state here. When the information is returned from # mesos, prefer that information over this attempt at state tracking. self.hostToJobIDs = {} # see self.setNodeFilter self.nodeFilter = [] # Dict of launched jobIDs to TaskData objects self.runningJobMap = {} # Mesos has no easy way of getting a task's resources so we track them here self.taskResources = {} # Queue of jobs whose status has been updated, according to Mesos self.updatedJobsQueue = Queue() # The Mesos driver used by this scheduler self.driver = None # The string framework ID that we are assigned when registering with the Mesos master self.frameworkId = None # A dictionary mapping a node's IP to an ExecutorInfo object describing important # properties of our executor running on that node. Only an approximation of the truth. self.executors = {} # A dictionary mapping back from agent ID to the last observed IP address of its node. self.agentsByID = {} # A set of Mesos agent IDs, one for each agent running on a # non-preemptable node. Only an approximation of the truth. Recently # launched nodes may be absent from this set for a while and a node's # absence from this set does not imply its preemptability. But it is # generally safer to assume a node is preemptable since # non-preemptability is a stronger requirement. If we tracked the set # of preemptable nodes instead, we'd have to use absence as an # indicator of non-preemptability and could therefore be misled into # believing that a recently launched preemptable node was # non-preemptable. self.nonPreemptableNodes = set() self.executor = self._buildExecutor() # These control how frequently to log a message that would indicate if no jobs are # currently able to run on the offers given. This can happen if the cluster is busy # or if the nodes in the cluster simply don't have enough resources to run the jobs self.lastTimeOfferLogged = 0 self.logPeriod = 30 # seconds self.ignoredNodes = set() self._startDriver() def setUserScript(self, userScript): self.userScript = userScript def ignoreNode(self, nodeAddress): self.ignoredNodes.add(nodeAddress) def unignoreNode(self, nodeAddress): self.ignoredNodes.remove(nodeAddress) def issueBatchJob(self, jobNode): """ Issues the following command returning a unique jobID. Command is the string to run, memory is an int giving the number of bytes the job needs to run in and cores is the number of cpus needed for the job and error-file is the path of the file to place any std-err/std-out in. """ localID = self.handleLocalJob(jobNode) if localID: return localID self.checkResourceRequest(jobNode.memory, jobNode.cores, jobNode.disk) jobID = self.getNextJobID() job = ToilJob(jobID=jobID, name=str(jobNode), resources=MesosShape(wallTime=0, **jobNode._requirements), command=jobNode.command, userScript=self.userScript, environment=self.environment.copy(), workerCleanupInfo=self.workerCleanupInfo) jobType = job.resources log.debug("Queueing the job command: %s with job id: %s ...", jobNode.command, str(jobID)) # TODO: round all elements of resources self.taskResources[jobID] = job.resources self.jobQueues.insertJob(job, jobType) log.debug("... queued") return jobID def killBatchJobs(self, jobIDs): # Some jobs may be local. Kill them first. self.killLocalJobs(jobIDs) # The driver thread does the actual work of killing the remote jobs. # We have to give it instructions, and block until the jobs are killed. assert self.driver is not None # This is the set of jobs that this invocation has asked to be killed, # but which haven't been killed yet. localSet = set() for jobID in jobIDs: # Queue the job up to be killed self.killJobIds.add(jobID) localSet.add(jobID) # Record that we meant to kill it, in case it finishes up by itself. self.intendedKill.add(jobID) if jobID in self.getIssuedBatchJobIDs(): # Since the job has been issued, we have to kill it taskId = addict.Dict() taskId.value = str(jobID) log.debug("Kill issued job %s" % str(jobID)) self.driver.killTask(taskId) else: # This job was never issued. Maybe it is a local job. # We don't have to kill it. log.debug("Skip non-issued job %s" % str(jobID)) self.killJobIds.remove(jobID) localSet.remove(jobID) # Now localSet just has the non-local/issued jobs that we asked to kill while localSet: # Wait until they are all dead intersection = localSet.intersection(self.killedJobIds) if intersection: localSet -= intersection # When jobs are killed that we asked for, clear them out of # killedJobIds where the other thread put them self.killedJobIds -= intersection else: time.sleep(1) # Now all the jobs we asked to kill are dead. We know they are no # longer running, because that update happens before their IDs go into # killedJobIds. So we can safely return. def getIssuedBatchJobIDs(self): jobIds = set(self.jobQueues.jobIDs()) jobIds.update(list(self.runningJobMap.keys())) return list(jobIds) + list(self.getIssuedLocalJobIDs()) def getRunningBatchJobIDs(self): currentTime = dict() for jobID, data in list(self.runningJobMap.items()): currentTime[jobID] = time.time() - data.startTime currentTime.update(self.getRunningLocalJobIDs()) return currentTime def getUpdatedBatchJob(self, maxWait): local_tuple = self.getUpdatedLocalJob(0) if local_tuple: return local_tuple while True: try: item = self.updatedJobsQueue.get(timeout=maxWait) except Empty: return None jobId, exitValue, wallTime = item try: self.intendedKill.remove(jobId) except KeyError: log.debug('Job %s ended with status %i, took %s seconds.', jobId, exitValue, '???' if wallTime is None else str(wallTime)) return item else: log.debug('Job %s ended naturally before it could be killed.', jobId) def nodeInUse(self, nodeIP): return nodeIP in self.hostToJobIDs @contextmanager def nodeFiltering(self, filter): self.nodeFilter = [filter] yield self.nodeFilter = [] def getWaitDuration(self): """ Gets the period of time to wait (floating point, in seconds) between checking for missing/overlong jobs. """ return 1 def _buildExecutor(self): """ Creates and returns an ExecutorInfo-shaped object representing our executor implementation. """ # The executor program is installed as a setuptools entry point by setup.py info = addict.Dict() info.name = "toil" info.command.value = resolveEntryPoint('_toil_mesos_executor') info.executor_id.value = "toil-%i" % os.getpid() info.source = pwd.getpwuid(os.getuid()).pw_name return info def _startDriver(self): """ The Mesos driver thread which handles the scheduler's communication with the Mesos master """ framework = addict.Dict() framework.user = getpass.getuser() # We must determine the user name ourselves with pymesos framework.name = "toil" framework.principal = framework.name # Make the driver which implements most of the scheduler logic and calls back to us for the user-defined parts. # Make sure it will call us with nice namespace-y addicts self.driver = MesosSchedulerDriver(self, framework, self._resolveAddress(self.mesosMasterAddress), use_addict=True, implicit_acknowledgements=True) self.driver.start() @staticmethod def _resolveAddress(address): """ Resolves the host in the given string. The input is of the form host[:port]. This method is idempotent, i.e. the host may already be a dotted IP address. >>> # noinspection PyProtectedMember >>> f=MesosBatchSystem._resolveAddress >>> f('localhost') '127.0.0.1' >>> f('127.0.0.1') '127.0.0.1' >>> f('localhost:123') '127.0.0.1:123' >>> f('127.0.0.1:123') '127.0.0.1:123' """ address = address.split(':') assert len(address) in (1, 2) address[0] = socket.gethostbyname(address[0]) return ':'.join(address) def shutdown(self): self.shutdownLocal() log.debug("Stopping Mesos driver") self.driver.stop() log.debug("Joining Mesos driver") driver_result = self.driver.join() log.debug("Joined Mesos driver") if driver_result is not None and driver_result != 'DRIVER_STOPPED': # TODO: The docs say join should return a code, but it keeps returning # None when apparently successful. So tolerate that here too. raise RuntimeError("Mesos driver failed with %s" % driver_result) def registered(self, driver, frameworkId, masterInfo): """ Invoked when the scheduler successfully registers with a Mesos master """ log.debug("Registered with framework ID %s", frameworkId.value) # Save the framework ID self.frameworkId = frameworkId.value def _declineAllOffers(self, driver, offers): for offer in offers: log.debug("Declining offer %s.", offer.id.value) driver.declineOffer(offer.id) def _parseOffer(self, offer): cores = 0 memory = 0 disk = 0 preemptable = None for attribute in offer.attributes: if attribute.name == 'preemptable': assert preemptable is None, "Attribute 'preemptable' occurs more than once." preemptable = strict_bool(attribute.text.value) if preemptable is None: log.debug('Agent not marked as either preemptable or not. Assuming non-preemptable.') preemptable = False for resource in offer.resources: if resource.name == "cpus": cores += resource.scalar.value elif resource.name == "mem": memory += resource.scalar.value elif resource.name == "disk": disk += resource.scalar.value return cores, memory, disk, preemptable def _prepareToRun(self, jobType, offer): # Get the first element to ensure FIFO job = self.jobQueues.nextJobOfType(jobType) task = self._newMesosTask(job, offer) return task def _updateStateToRunning(self, offer, runnableTasks): for task in runnableTasks: resourceKey = int(task.task_id.value) resources = self.taskResources[resourceKey] agentIP = socket.gethostbyname(offer.hostname) try: self.hostToJobIDs[agentIP].append(resourceKey) except KeyError: self.hostToJobIDs[agentIP] = [resourceKey] self.runningJobMap[int(task.task_id.value)] = TaskData(startTime=time.time(), agentID=offer.agent_id.value, agentIP=agentIP, executorID=task.executor.executor_id.value, cores=resources.cores, memory=resources.memory) del self.taskResources[resourceKey] log.debug('Launched Mesos task %s.', task.task_id.value) def resourceOffers(self, driver, offers): """ Invoked when resources have been offered to this framework. """ self._trackOfferedNodes(offers) jobTypes = self.jobQueues.sortedTypes if not jobTypes: log.debug('There are no queued tasks. Declining Mesos offers.') # Without jobs, we can get stuck with no jobs and no new offers until we decline it. self._declineAllOffers(driver, offers) return unableToRun = True # Right now, gives priority to largest jobs for offer in offers: if offer.hostname in self.ignoredNodes: log.debug("Declining offer %s because node %s is designated for termination" % (offer.id.value, offer.hostname)) driver.declineOffer(offer.id) continue runnableTasks = [] # TODO: In an offer, can there ever be more than one resource with the same name? offerCores, offerMemory, offerDisk, offerPreemptable = self._parseOffer(offer) log.debug('Got offer %s for a %spreemptable agent with %.2f MiB memory, %.2f core(s) ' 'and %.2f MiB of disk.', offer.id.value, '' if offerPreemptable else 'non-', offerMemory, offerCores, offerDisk) remainingCores = offerCores remainingMemory = offerMemory remainingDisk = offerDisk for jobType in jobTypes: runnableTasksOfType = [] # Because we are not removing from the list until outside of the while loop, we # must decrement the number of jobs left to run ourselves to avoid an infinite # loop. nextToLaunchIndex = 0 # Toil specifies disk and memory in bytes but Mesos uses MiB while ( not self.jobQueues.typeEmpty(jobType) # On a non-preemptable node we can run any job, on a preemptable node we # can only run preemptable jobs: and (not offerPreemptable or jobType.preemptable) and remainingCores >= jobType.cores and remainingDisk >= toMiB(jobType.disk) and remainingMemory >= toMiB(jobType.memory)): task = self._prepareToRun(jobType, offer) # TODO: this used to be a conditional but Hannes wanted it changed to an assert # TODO: ... so we can understand why it exists. assert int(task.task_id.value) not in self.runningJobMap runnableTasksOfType.append(task) log.debug("Preparing to launch Mesos task %s with %.2f cores, %.2f MiB memory, and %.2f MiB disk using offer %s ...", task.task_id.value, jobType.cores, toMiB(jobType.memory), toMiB(jobType.disk), offer.id.value) remainingCores -= jobType.cores remainingMemory -= toMiB(jobType.memory) remainingDisk -= toMiB(jobType.disk) nextToLaunchIndex += 1 if not self.jobQueues.typeEmpty(jobType): # report that remaining jobs cannot be run with the current resourcesq: log.debug('Offer %(offer)s not suitable to run the tasks with requirements ' '%(requirements)r. Mesos offered %(memory)s memory, %(cores)s cores ' 'and %(disk)s of disk on a %(non)spreemptable agent.', dict(offer=offer.id.value, requirements=jobType.__dict__, non='' if offerPreemptable else 'non-', memory=fromMiB(offerMemory), cores=offerCores, disk=fromMiB(offerDisk))) runnableTasks.extend(runnableTasksOfType) # Launch all runnable tasks together so we only call launchTasks once per offer if runnableTasks: unableToRun = False driver.launchTasks(offer.id, runnableTasks) self._updateStateToRunning(offer, runnableTasks) else: log.debug('Although there are queued jobs, none of them could be run with offer %s ' 'extended to the framework.', offer.id) driver.declineOffer(offer.id) if unableToRun and time.time() > (self.lastTimeOfferLogged + self.logPeriod): self.lastTimeOfferLogged = time.time() log.debug('Although there are queued jobs, none of them were able to run in ' 'any of the offers extended to the framework. There are currently ' '%i jobs running. Enable debug level logging to see more details about ' 'job types and offers received.', len(self.runningJobMap)) def _trackOfferedNodes(self, offers): for offer in offers: # All AgentID messages are required to have a value according to the Mesos Protobuf file. assert 'value' in offer.agent_id try: nodeAddress = socket.gethostbyname(offer.hostname) except: log.debug("Failed to resolve hostname %s" % offer.hostname) raise self._registerNode(nodeAddress, offer.agent_id.value) preemptable = False for attribute in offer.attributes: if attribute.name == 'preemptable': preemptable = strict_bool(attribute.text.value) if preemptable: try: self.nonPreemptableNodes.remove(offer.agent_id.value) except KeyError: pass else: self.nonPreemptableNodes.add(offer.agent_id.value) def _filterOfferedNodes(self, offers): if not self.nodeFilter: return offers executorInfoOrNone = [self.executors.get(socket.gethostbyname(offer.hostname)) for offer in offers] executorInfos = [_f for _f in executorInfoOrNone if _f] executorsToConsider = list(filter(self.nodeFilter[0], executorInfos)) ipsToConsider = {ex.nodeAddress for ex in executorsToConsider} return [offer for offer in offers if socket.gethostbyname(offer.hostname) in ipsToConsider] def _newMesosTask(self, job, offer): """ Build the Mesos task object for a given the Toil job and Mesos offer """ task = addict.Dict() task.task_id.value = str(job.jobID) task.agent_id.value = offer.agent_id.value task.name = job.name task.data = encode_data(pickle.dumps(job)) task.executor = addict.Dict(self.executor) task.resources = [] task.resources.append(addict.Dict()) cpus = task.resources[-1] cpus.name = 'cpus' cpus.type = 'SCALAR' cpus.scalar.value = job.resources.cores task.resources.append(addict.Dict()) disk = task.resources[-1] disk.name = 'disk' disk.type = 'SCALAR' if toMiB(job.resources.disk) > 1: disk.scalar.value = toMiB(job.resources.disk) else: log.warning("Job %s uses less disk than Mesos requires. Rounding %s up to 1 MiB.", job.jobID, job.resources.disk) disk.scalar.value = 1 task.resources.append(addict.Dict()) mem = task.resources[-1] mem.name = 'mem' mem.type = 'SCALAR' if toMiB(job.resources.memory) > 1: mem.scalar.value = toMiB(job.resources.memory) else: log.warning("Job %s uses less memory than Mesos requires. Rounding %s up to 1 MiB.", job.jobID, job.resources.memory) mem.scalar.value = 1 return task def statusUpdate(self, driver, update): """ Invoked when the status of a task has changed (e.g., a agent is lost and so the task is lost, a task finishes and an executor sends a status update saying so, etc). Note that returning from this callback _acknowledges_ receipt of this status update! If for whatever reason the scheduler aborts during this callback (or the process exits) another status update will be delivered (note, however, that this is currently not true if the agent sending the status update is lost/fails during that time). """ jobID = int(update.task_id.value) log.debug("Job %i is in state '%s' due to reason '%s'.", jobID, update.state, update.reason) def jobEnded(_exitStatus, wallTime=None): """ Notify external observers of the job ending. """ self.updatedJobsQueue.put((jobID, _exitStatus, wallTime)) agentIP = None try: agentIP = self.runningJobMap[jobID].agentIP except KeyError: log.warning("Job %i returned exit code %i but isn't tracked as running.", jobID, _exitStatus) else: # Mark the job as no longer running. We MUST do this BEFORE # saying we killed the job, or it will be possible for another # thread to kill a job and then see it as running. del self.runningJobMap[jobID] try: self.hostToJobIDs[agentIP].remove(jobID) except KeyError: log.warning("Job %i returned exit code %i from unknown host.", jobID, _exitStatus) try: self.killJobIds.remove(jobID) except KeyError: pass else: # We were asked to kill this job, so say that we have done so. # We do this LAST, after all status updates for the job have # been handled, to ensure a consistent view of the scheduler # state from other threads. self.killedJobIds.add(jobID) if update.state == 'TASK_FINISHED': # We get the running time of the job via the timestamp, which is in job-local time in seconds labels = update.labels.labels wallTime = None for label in labels: if label['key'] == 'wallTime': wallTime = float(label['value']) break assert(wallTime is not None) jobEnded(0, wallTime=wallTime) elif update.state == 'TASK_FAILED': try: exitStatus = int(update.message) except ValueError: exitStatus = 255 log.warning("Job %i failed with message '%s' due to reason '%s' on executor '%s' on agent '%s'.", jobID, update.message, update.reason, update.executor_id, update.agent_id) else: log.warning("Job %i failed with exit status %i and message '%s' due to reason '%s' on executor '%s' on agent '%s'.", jobID, exitStatus, update.message, update.reason, update.executor_id, update.agent_id) jobEnded(exitStatus) elif update.state in ('TASK_LOST', 'TASK_KILLED', 'TASK_ERROR'): log.warning("Job %i is in unexpected state %s with message '%s' due to reason '%s'.", jobID, update.state, update.message, update.reason) jobEnded(255) if 'limitation' in update: log.warning("Job limit info: %s" % update.limitation) def frameworkMessage(self, driver, executorId, agentId, message): """ Invoked when an executor sends a message. """ # Take it out of base 64 encoding from Protobuf if USING_PYTHON2: message = decode_data(message) else: message = decode_data(message).decode() log.debug('Got framework message from executor %s running on agent %s: %s', executorId.value, agentId.value, message) message = ast.literal_eval(message) assert isinstance(message, dict) # Handle the mandatory fields of a message nodeAddress = message.pop('address') executor = self._registerNode(nodeAddress, agentId.value) # Handle optional message fields for k, v in iteritems(message): if k == 'nodeInfo': assert isinstance(v, dict) resources = [taskData for taskData in itervalues(self.runningJobMap) if taskData.executorID == executorId.value] requestedCores = sum(taskData.cores for taskData in resources) requestedMemory = sum(taskData.memory for taskData in resources) executor.nodeInfo = NodeInfo(requestedCores=requestedCores, requestedMemory=requestedMemory, **v) self.executors[nodeAddress] = executor else: raise RuntimeError("Unknown message field '%s'." % k) def _registerNode(self, nodeAddress, agentId, nodePort=5051): """ Called when we get communication from an agent. Remembers the information about the agent by address, and the agent address by agent ID. """ executor = self.executors.get(nodeAddress) if executor is None or executor.agentId != agentId: executor = self.ExecutorInfo(nodeAddress=nodeAddress, agentId=agentId, nodeInfo=None, lastSeen=time.time()) self.executors[nodeAddress] = executor else: executor.lastSeen = time.time() # Record the IP under the agent id self.agentsByID[agentId] = nodeAddress return executor def getNodes(self, preemptable=None, timeout=600): timeout = timeout or sys.maxsize return {nodeAddress: executor.nodeInfo for nodeAddress, executor in iteritems(self.executors) if time.time() - executor.lastSeen < timeout and (preemptable is None or preemptable == (executor.agentId not in self.nonPreemptableNodes))} def reregistered(self, driver, masterInfo): """ Invoked when the scheduler re-registers with a newly elected Mesos master. """ log.debug('Registered with new master') def _handleFailedExecutor(self, agentID, executorID=None): """ Should be called when we find out an executor has failed. Gets the log from some container (since we are never handed a container ID) that ran on the given executor on the given agent, if the agent is still up, and dumps it to our log. All IDs are strings. If executorID is None, dumps all executors from the agent. Useful for debugging failing executor code. """ log.warning("Handling failure of executor '%s' on agent '%s'.", executorID, agentID) try: # Look up the IP. We should always know it unless we get answers # back without having accepted offers. agentAddress = self.agentsByID[agentID] # For now we assume the agent is always on the same port. We could # maybe sniff this from the URL that comes in the offer but it's # not guaranteed to be there. agentPort = 5051 # We need the container ID to read the log, but we are never given # it, and I can't find a good way to list it, because the API only # seems to report running containers. So we dump all the avaiilable # files with /files/debug and look for one that looks right. filesQueryURL = errorLogURL = "http://%s:%d/files/debug" % \ (agentAddress, agentPort) # Download all the root mount points, which are in an object from # mounted name to real name filesDict = json.loads(urlopen(filesQueryURL).read()) log.debug('Available files: %s', repr(filesDict.keys())) # Generate filenames for each container pointing to where stderr should be stderrFilenames = [] # And look for the actual agent logs. agentLogFilenames = [] for filename in filesDict.iterkeys(): if (self.frameworkId in filename and agentID in filename and (executorID is None or executorID in filename)): stderrFilenames.append("%s/stderr" % filename) elif filename.endswith("log"): agentLogFilenames.append(filename) if '/slave/log' not in agentLogFilenames: # Look here even if not reported. agentLogFilenames.append('/slave/log') if len(stderrFilenames) == 0: log.warning("Could not find any containers in '%s'." % filesDict) for stderrFilename in stderrFilenames: try: # According to # http://mesos.apache.org/documentation/latest/sandbox/ we can use # the web API to fetch the error log. errorLogURL = "http://%s:%d/files/download?path=%s" % \ (agentAddress, agentPort, quote_plus(stderrFilename)) log.warning("Attempting to retrieve executor error log: %s", errorLogURL) for line in urlopen(errorLogURL): # Warn all the lines of the executor's error log log.warning("Executor: %s", line.rstrip()) except Exception as e: log.warning("Could not retrieve exceutor log due to: '%s'.", e) log.warning(traceback.format_exc()) for agentLogFilename in agentLogFilenames: try: agentLogURL = "http://%s:%d/files/download?path=%s" % \ (agentAddress, agentPort, quote_plus(agentLogFilename)) log.warning("Attempting to retrieve agent log: %s", agentLogURL) for line in urlopen(agentLogURL): # Warn all the lines of the agent's log log.warning("Agent: %s", line.rstrip()) except Exception as e: log.warning("Could not retrieve agent log due to: '%s'.", e) log.warning(traceback.format_exc()) except Exception as e: log.warning("Could not retrieve logs due to: '%s'.", e) log.warning(traceback.format_exc()) def executorLost(self, driver, executorId, agentId, status): """ Invoked when an executor has exited/terminated abnormally. """ failedId = executorId.get('value', None) log.warning("Executor '%s' reported lost with status '%s'.", failedId, status) self._handleFailedExecutor(agentId.value, failedId) @classmethod def setOptions(cls, setOption): setOption("mesosMasterAddress", None, None, 'localhost:5050') def toMiB(n): return n / 1024 / 1024 def fromMiB(n): return n * 1024 * 1024 toil-releases-3.24.0/src/toil/batchSystems/mesos/conftest.py000066400000000000000000000014661362134276200241210ustar00rootroot00000000000000# Copyright (C) 2015-2016 Regents of the University of California # # 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. # https://pytest.org/latest/example/pythoncollection.html collect_ignore = [] try: import pymesos except ImportError: collect_ignore.append("batchSystem.py") collect_ignore.append("executor.py") toil-releases-3.24.0/src/toil/batchSystems/mesos/executor.py000066400000000000000000000306271362134276200241330ustar00rootroot00000000000000# Copyright (C) 2015-2016 Regents of the University of California # # 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. from __future__ import absolute_import from future import standard_library standard_library.install_aliases() from builtins import str import os import os.path import random import socket import signal import sys import threading import logging import psutil import traceback import time import json import resource try: from urllib2 import urlopen except ImportError: from urllib.request import urlopen import addict from pymesos import MesosExecutorDriver, Executor, decode_data, encode_data from toil import subprocess, pickle from toil.lib.expando import Expando from toil.lib.threading import cpu_count from toil.batchSystems.abstractBatchSystem import BatchSystemSupport from toil.resource import Resource log = logging.getLogger(__name__) class MesosExecutor(Executor): """ Part of Toil's Mesos framework, runs on a Mesos agent. A Toil job is passed to it via the task.data field, and launched via call(toil.command). """ def __init__(self): super(MesosExecutor, self).__init__() self.popenLock = threading.Lock() self.runningTasks = {} self.workerCleanupInfo = None log.debug('Preparing system for resource download') Resource.prepareSystem() self.address = None self.id = None # Setting this value at this point will ensure that the toil workflow directory will go to # the mesos sandbox if the user hasn't specified --workDir on the command line. if not os.getenv('TOIL_WORKDIR'): os.environ['TOIL_WORKDIR'] = os.getcwd() def registered(self, driver, executorInfo, frameworkInfo, agentInfo): """ Invoked once the executor driver has been able to successfully connect with Mesos. """ # Get the ID we have been assigned, if we have it self.id = executorInfo.executor_id.get('value', None) log.debug("Registered executor %s with framework", self.id) self.address = socket.gethostbyname(agentInfo.hostname) nodeInfoThread = threading.Thread(target=self._sendFrameworkMessage, args=[driver]) nodeInfoThread.daemon = True nodeInfoThread.start() def reregistered(self, driver, agentInfo): """ Invoked when the executor re-registers with a restarted agent. """ log.debug("Re-registered") def disconnected(self, driver): """ Invoked when the executor becomes "disconnected" from the agent (e.g., the agent is being restarted due to an upgrade). """ log.critical("Disconnected from agent") def killTask(self, driver, taskId): """ Kill parent task process and all its spawned children """ try: pid = self.runningTasks[taskId.value] pgid = os.getpgid(pid) except KeyError: pass else: os.killpg(pgid, signal.SIGKILL) def shutdown(self, driver): log.critical('Shutting down executor ...') for taskId in list(self.runningTasks.keys()): self.killTask(driver, taskId) Resource.cleanSystem() BatchSystemSupport.workerCleanup(self.workerCleanupInfo) log.critical('... executor shut down.') def error(self, driver, message): """ Invoked when a fatal error has occurred with the executor and/or executor driver. """ log.critical("FATAL ERROR: " + message) def _sendFrameworkMessage(self, driver): message = None while True: # The psutil documentation recommends that we ignore the value returned by the first # invocation of cpu_percent(). However, we do want to send a sign of life early after # starting (e.g. to unblock the provisioner waiting for an instance to come up) so # we call it once and discard the value. if message is None: message = Expando(address=self.address) psutil.cpu_percent() else: message.nodeInfo = dict(coresUsed=float(psutil.cpu_percent()) * .01, memoryUsed=float(psutil.virtual_memory().percent) * .01, coresTotal=cpu_count(), memoryTotal=psutil.virtual_memory().total, workers=len(self.runningTasks)) log.debug("Send framework message: %s", message) driver.sendFrameworkMessage(encode_data(repr(message))) # Prevent workers launched together from repeatedly hitting the leader at the same time time.sleep(random.randint(45, 75)) def launchTask(self, driver, task): """ Invoked by SchedulerDriver when a Mesos task should be launched by this executor """ log.debug("Asked to launch task %s", repr(task)) def runTask(): log.debug("Running task %s", task.task_id.value) startTime = time.time() sendUpdate(task, 'TASK_RUNNING', wallTime=0) # try to unpickle the task try: taskData = pickle.loads(decode_data(task.data)) except: exc_info = sys.exc_info() log.error('Exception while unpickling task: ', exc_info=exc_info) exc_type, exc_value, exc_trace = exc_info sendUpdate(task, 'TASK_FAILED', wallTime=0, msg=''.join(traceback.format_exception_only(exc_type, exc_value))) return # This is where task.data is first invoked. Using this position to setup cleanupInfo if self.workerCleanupInfo is not None: assert self.workerCleanupInfo == taskData.workerCleanupInfo else: self.workerCleanupInfo = taskData.workerCleanupInfo # try to invoke a run on the unpickled task try: process = runJob(taskData) self.runningTasks[task.task_id.value] = process.pid try: exitStatus = process.wait() wallTime = time.time() - startTime if 0 == exitStatus: sendUpdate(task, 'TASK_FINISHED', wallTime) elif -9 == exitStatus: sendUpdate(task, 'TASK_KILLED', wallTime) else: sendUpdate(task, 'TASK_FAILED', wallTime, msg=str(exitStatus)) finally: del self.runningTasks[task.task_id.value] except: wallTime = time.time() - startTime exc_info = sys.exc_info() log.error('Exception while running task:', exc_info=exc_info) exc_type, exc_value, exc_trace = exc_info sendUpdate(task, 'TASK_FAILED', wallTime=wallTime, msg=''.join(traceback.format_exception_only(exc_type, exc_value))) wallTime = time.time() - startTime sendUpdate(task, 'TASK_FINISHED', wallTime) def runJob(job): """ :type job: toil.batchSystems.mesos.ToilJob :rtype: subprocess.Popen """ if job.userScript: job.userScript.register() log.debug("Invoking command: '%s'", job.command) # Construct the job's environment jobEnv = dict(os.environ, **job.environment) log.debug('Using environment variables: %s', jobEnv.keys()) with self.popenLock: return subprocess.Popen(job.command, preexec_fn=lambda: os.setpgrp(), shell=True, env=jobEnv) def sendUpdate(task, taskState, wallTime, msg=''): update = addict.Dict() update.task_id.value = task.task_id.value if self.id is not None: # Sign our messages as from us, since the driver doesn't do it. update.executor_id.value = self.id update.state = taskState update.message = msg # Add wallTime as a label. labels = addict.Dict() labels.labels = [{'key': 'wallTime', 'value': str(wallTime)}] update.labels = labels driver.sendStatusUpdate(update) thread = threading.Thread(target=runTask) thread.start() def frameworkMessage(self, driver, message): """ Invoked when a framework message has arrived for this executor. """ log.debug("Received message from framework: {}".format(message)) def main(): logging.basicConfig(level=logging.DEBUG) log.debug("Starting executor") if not os.environ.get("MESOS_AGENT_ENDPOINT"): # Some Mesos setups in our tests somehow lack this variable. Provide a # fake one to maybe convince the executor driver to work. os.environ["MESOS_AGENT_ENDPOINT"] = os.environ.get("MESOS_SLAVE_ENDPOINT", "127.0.0.1:5051") log.warning("Had to fake MESOS_AGENT_ENDPOINT as %s" % os.environ["MESOS_AGENT_ENDPOINT"]) # must be set manually to enable toggling of the mesos log level for debugging jenkins # may be useful: https://github.com/DataBiosphere/toil/pull/2338#discussion_r223854931 if False: try: urlopen("http://%s/logging/toggle?level=1&duration=15mins" % os.environ["MESOS_AGENT_ENDPOINT"]).read() log.debug("Toggled agent log level") except Exception as e: log.debug("Failed to toggle agent log level") # Parse the agent state agent_state = json.loads(urlopen("http://%s/state" % os.environ["MESOS_AGENT_ENDPOINT"]).read()) if 'completed_frameworks' in agent_state: # Drop the completed frameworks which grow over time del agent_state['completed_frameworks'] log.debug("Agent state: %s", str(agent_state)) log.debug("Virtual memory info in executor: %s" % repr(psutil.virtual_memory())) if os.path.exists('/sys/fs/cgroup/memory'): # Mesos can limit memory with a cgroup, so we should report on that. for (dirpath, dirnames, filenames) in os.walk('/sys/fs/cgroup/memory', followlinks=True): for filename in filenames: if 'limit_in_bytes' not in filename: continue log.debug('cgroup memory info from %s:' % os.path.join(dirpath, filename)) try: for line in open(os.path.join(dirpath, filename)): log.debug(line.rstrip()) except Exception as e: log.debug("Failed to read file") # Mesos can also impose rlimit limits, including on things that really # ought to not be limited, like virtual address space size. log.debug('DATA rlimit: %s', str(resource.getrlimit(resource.RLIMIT_DATA))) log.debug('STACK rlimit: %s', str(resource.getrlimit(resource.RLIMIT_STACK))) log.debug('RSS rlimit: %s', str(resource.getrlimit(resource.RLIMIT_RSS))) log.debug('AS rlimit: %s', str(resource.getrlimit(resource.RLIMIT_AS))) executor = MesosExecutor() log.debug('Made executor') driver = MesosExecutorDriver(executor, use_addict=True) old_on_event = driver.on_event def patched_on_event(event): """ Intercept and log all pymesos events. """ log.debug("Event: %s", repr(event)) old_on_event(event) driver.on_event = patched_on_event log.debug('Made driver') driver.start() log.debug('Started driver') driver_result = driver.join() log.debug('Joined driver') # Tolerate a None in addition to the code the docs suggest we should receive from join() exit_value = 0 if (driver_result is None or driver_result == 'DRIVER_STOPPED') else 1 assert len(executor.runningTasks) == 0 sys.exit(exit_value) toil-releases-3.24.0/src/toil/batchSystems/mesos/test/000077500000000000000000000000001362134276200226725ustar00rootroot00000000000000toil-releases-3.24.0/src/toil/batchSystems/mesos/test/__init__.py000066400000000000000000000117651362134276200250150ustar00rootroot00000000000000from __future__ import absolute_import from future import standard_library standard_library.install_aliases() from builtins import next from builtins import object from abc import ABCMeta, abstractmethod import logging import shutil import threading from toil import subprocess from past.builtins import basestring from six.moves.urllib.request import urlopen from contextlib import closing import time from toil.lib.retry import retry from toil import which # replace with shutil.which() directly; python3 only from toil.lib.threading import ExceptionalThread, cpu_count from future.utils import with_metaclass log = logging.getLogger(__name__) class MesosTestSupport(object): """ A mixin for test cases that need a running Mesos master and agent on the local host """ def _startMesos(self, numCores=None): if numCores is None: numCores = cpu_count() shutil.rmtree('/tmp/mesos', ignore_errors=True) self.master = self.MesosMasterThread(numCores) self.master.start() self.agent = self.MesosAgentThread(numCores) self.agent.start() # Wait for the master to come up. # Bad Things will happen if the master is not yet ready when Toil tries to use it. for attempt in retry(predicate=lambda e: True): with attempt: log.info('Checking if Mesos is ready...') with closing(urlopen('http://127.0.0.1:5050/version')) as content: content.read() log.info('Mesos is ready! Running test.') def _stopProcess(self, process, timeout=10): """ Gracefully stop a process on a timeout, given the Popen object for the process. """ process.terminate() waited = 0 while waited < timeout and process.poll() is None: time.sleep(1) waited += 1 if process.poll() is None: # It didn't shut down gracefully log.warning('Forcibly killing child which ignored SIGTERM') process.kill() def _stopMesos(self): self._stopProcess(self.agent.popen) self.agent.join() self._stopProcess(self.master.popen) self.master.join() class MesosThread(with_metaclass(ABCMeta, ExceptionalThread)): lock = threading.Lock() def __init__(self, numCores): threading.Thread.__init__(self) self.numCores = numCores with self.lock: self.popen = subprocess.Popen(self.mesosCommand()) @abstractmethod def mesosCommand(self): raise NotImplementedError def tryRun(self): self.popen.wait() log.info('Exiting %s', self.__class__.__name__) def findMesosBinary(self, names): if isinstance(names, basestring): # Handle a single string names = [names] for name in names: try: return which(name) except StopIteration: try: # Special case for users of PyCharm on OS X. This is where Homebrew installs # it. It's hard to set PATH for PyCharm (or any GUI app) on OS X so let's # make it easy for those poor souls. return which(name, path='/usr/local/sbin') except StopIteration: pass # If we get here, nothing we can use is present. We need to complain. if len(names) == 1: sought = "binary '%s'" % names[0] else: sought = 'any binary in %s' % str(names) raise RuntimeError("Cannot find %s. Make sure Mesos is installed " "and it's 'bin' directory is present on the PATH." % sought) class MesosMasterThread(MesosThread): def mesosCommand(self): return [self.findMesosBinary('mesos-master'), '--registry=in_memory', '--ip=127.0.0.1', '--port=5050', '--allocation_interval=500ms'] class MesosAgentThread(MesosThread): def mesosCommand(self): # NB: The --resources parameter forces this test to use a predictable number of # cores, independent of how many cores the system running the test actually has. # We also make sure to point it explicitly at the right temp work directory, and # to disable systemd support because we have to be root to make systemd make us # things and we probably aren't when testing. return [self.findMesosBinary(['mesos-agent', 'mesos-slave']), '--ip=127.0.0.1', '--master=127.0.0.1:5050', '--attributes=preemptable:False', '--resources=cpus(*):%i' % self.numCores, '--work_dir=/tmp/mesos', '--no-systemd_enable_support'] toil-releases-3.24.0/src/toil/batchSystems/options.py000066400000000000000000000165441362134276200226440ustar00rootroot00000000000000from __future__ import absolute_import # Copyright (C) 2015-2016 Regents of the University of California # # 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 # from toil.lib.threading import cpu_count from .registry import batchSystemFactoryFor, defaultBatchSystem, uniqueNames import socket from contextlib import closing def getPublicIP(): """Get the IP that this machine uses to contact the internet. If behind a NAT, this will still be this computer's IP, and not the router's.""" try: # Try to get the internet-facing IP by attempting a connection # to a non-existent server and reading what IP was used. with closing(socket.socket(socket.AF_INET, socket.SOCK_DGRAM)) as sock: # 203.0.113.0/24 is reserved as TEST-NET-3 by RFC 5737, so # there is guaranteed to be no one listening on the other # end (and we won't accidentally DOS anyone). sock.connect(('203.0.113.1', 1)) ip = sock.getsockname()[0] return ip except: # Something went terribly wrong. Just give loopback rather # than killing everything, because this is often called just # to provide a default argument return '127.0.0.1' def _parasolOptions(addOptionFn, config=None): addOptionFn("--parasolCommand", dest="parasolCommand", default=None, help="The name or path of the parasol program. Will be looked up on PATH " "unless it starts with a slash. default=%s" % 'parasol') addOptionFn("--parasolMaxBatches", dest="parasolMaxBatches", default=None, help="Maximum number of job batches the Parasol batch is allowed to create. One " "batch is created for jobs with a a unique set of resource requirements. " "default=%i" % 1000) def _singleMachineOptions(addOptionFn, config): addOptionFn("--scale", dest="scale", default=None, help=("A scaling factor to change the value of all submitted " "tasks's submitted cores. Used in singleMachine batch " "system. default=%s" % 1)) if config.cwl: addOptionFn( "--noLinkImports", dest="linkImports", default=True, action='store_false', help="When using a filesystem based job " "store, CWL input files are by default symlinked in. " "Specifying this option instead copies the files into the job " "store, which may protect them from being modified externally. " "When not specified and as long as caching is enabled, Toil will " "protect the file automatically by changing the permissions to " "read-only.") else: addOptionFn( "--linkImports", dest="linkImports", default=False, action='store_true', help="When using Toil's importFile function " "for staging, input files are copied to the job store. Specifying " "this option saves space by sym-linking imported files. As long " "as caching is enabled Toil will protect the file " "automatically by changing the permissions to read-only.") def _mesosOptions(addOptionFn, config=None): addOptionFn("--mesosMaster", dest="mesosMasterAddress", default=getPublicIP() + ':5050', help=("The host and port of the Mesos master separated by colon. (default: %(default)s)")) # Built in batch systems that have options _options = [ _parasolOptions, _singleMachineOptions, _mesosOptions ] def addOptionsDefinition(optionsDefinition): _options.append(optionsDefinition) def setOptions(config, setOption): batchSystem = config.batchSystem factory = batchSystemFactoryFor(batchSystem) batchSystem = factory() batchSystem.setOptions(setOption) def addOptions(addOptionFn, config): addOptionFn("--batchSystem", dest="batchSystem", default=defaultBatchSystem(), help=("The type of batch system to run the job(s) with, currently can be one " "of %s'. default=%s" % (', '.join(uniqueNames()), defaultBatchSystem()))) addOptionFn("--disableHotDeployment", dest="disableAutoDeployment", action='store_true', default=None, help=("Hot-deployment was renamed to auto-deployment. Option now redirects to " "--disableAutoDeployment. Left in for backwards compatibility.")) addOptionFn("--disableAutoDeployment", dest="disableAutoDeployment", action='store_true', default=None, help=("Should auto-deployment of the user script be deactivated? If True, the user " "script/package should be present at the same location on all workers. " "default=false")) localCores = cpu_count() addOptionFn("--maxLocalJobs", default=localCores, help="For batch systems that support a local queue for " "housekeeping jobs (Mesos, GridEngine, htcondor, lsf, slurm, " "torque), the maximum number of these housekeeping jobs to " "run on the local system. " "The default (equal to the number of cores) is a maximum of " "{} concurrent local housekeeping jobs.".format(localCores)) addOptionFn("--manualMemArgs", default=False, action='store_true', dest="manualMemArgs", help="Do not add the default arguments: 'hv=MEMORY' & 'h_vmem=MEMORY' to " "the qsub call, and instead rely on TOIL_GRIDGENGINE_ARGS to supply " "alternative arguments. Requires that TOIL_GRIDGENGINE_ARGS be set.") addOptionFn("--runCwlInternalJobsOnWorkers", dest="runCwlInternalJobsOnWorkers", action='store_true', default=None, help=("Whether to run CWL internal jobs (e.g. CWLScatter) on the worker nodes " "instead of the primary node. If false (default), then all such jobs are run on " "the primary node. Setting this to true can speed up the pipeline for very large " "workflows with many sub-workflows and/or scatters, provided that the worker " "pool is large enough.")) for o in _options: o(addOptionFn, config) def setDefaultOptions(config): """ Set default options for builtin batch systems. This is required if a Config object is not constructed from an Options object. """ config.batchSystem = "singleMachine" config.disableAutoDeployment = False config.environment = {} config.statePollingWait = None # if not set, will default to seconds in getWaitDuration() config.maxLocalJobs = cpu_count() config.manualMemArgs = False # single machine config.scale = 1 config.linkImports = False # mesos config.mesosMasterAddress = '%s:5050' % getPublicIP() # parasol config.parasolCommand = 'parasol' config.parasolMaxBatches = 10000 toil-releases-3.24.0/src/toil/batchSystems/parasol.py000066400000000000000000000404021362134276200226000ustar00rootroot00000000000000# Copyright (C) 2015-2016 Regents of the University of California # # 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. from __future__ import absolute_import from __future__ import division from builtins import next from builtins import str from past.utils import old_div from future.utils import listitems import logging import os import re import sys from toil import subprocess import tempfile import time from threading import Thread # Python 3 compatibility imports from six.moves.queue import Empty, Queue from six import itervalues from toil.lib.iterables import concat from toil import which from toil.batchSystems.abstractBatchSystem import BatchSystemSupport from toil.lib.bioio import getTempFile from toil.common import Toil logger = logging.getLogger(__name__) class ParasolBatchSystem(BatchSystemSupport): """ The interface for Parasol. """ @classmethod def supportsWorkerCleanup(cls): return False @classmethod def supportsAutoDeployment(cls): return False def __init__(self, config, maxCores, maxMemory, maxDisk): super(ParasolBatchSystem, self).__init__(config, maxCores, maxMemory, maxDisk) if maxMemory != sys.maxsize: logger.warn('The Parasol batch system does not support maxMemory.') # Keep the name of the results file for the pstat2 command.. command = config.parasolCommand if os.path.sep not in command: try: command = which(command) except StopIteration: raise RuntimeError("Can't find %s on PATH." % command) logger.debug('Using Parasol at %s', command) self.parasolCommand = command jobStoreType, path = Toil.parseLocator(config.jobStore) if jobStoreType != 'file': raise RuntimeError("The parasol batch system doesn't currently work with any " "jobStore type except file jobStores.") self.parasolResultsDir = tempfile.mkdtemp(dir=os.path.abspath(path)) logger.debug("Using parasol results dir: %s", self.parasolResultsDir) # In Parasol, each results file corresponds to a separate batch, and all jobs in a batch # have the same cpu and memory requirements. The keys to this dictionary are the (cpu, # memory) tuples for each batch. A new batch is created whenever a job has a new unique # combination of cpu and memory requirements. self.resultsFiles = dict() self.maxBatches = config.parasolMaxBatches # Allows the worker process to send back the IDs of jobs that have finished, so the batch # system can decrease its used cpus counter self.cpuUsageQueue = Queue() # Also stores finished job IDs, but is read by getUpdatedJobIDs(). self.updatedJobsQueue = Queue() # Use this to stop the worker when shutting down self.running = True self.worker = Thread(target=self.updatedJobWorker, args=()) self.worker.start() self.usedCpus = 0 self.jobIDsToCpu = {} # Set of jobs that have been issued but aren't known to have finished or been killed yet. # Jobs that end by themselves are removed in getUpdatedJob, and jobs that are killed are # removed in killBatchJobs. self.runningJobs = set() def _runParasol(self, command, autoRetry=True): """ Issues a parasol command using popen to capture the output. If the command fails then it will try pinging parasol until it gets a response. When it gets a response it will recursively call the issue parasol command, repeating this pattern for a maximum of N times. The final exit value will reflect this. """ command = list(concat(self.parasolCommand, command)) while True: logger.debug('Running %r', command) process = subprocess.Popen(command, stdout=subprocess.PIPE, stderr=subprocess.PIPE, bufsize=-1) stdout, stderr = process.communicate() status = process.wait() for line in stderr.decode('utf-8').split('\n'): if line: logger.warn(line) if status == 0: return 0, stdout.decode('utf-8').split('\n') message = 'Command %r failed with exit status %i' % (command, status) if autoRetry: logger.warn(message) else: logger.error(message) return status, None logger.warn('Waiting for a 10s, before trying again') time.sleep(10) parasolOutputPattern = re.compile("your job ([0-9]+).*") def issueBatchJob(self, jobNode): """ Issues parasol with job commands. """ self.checkResourceRequest(jobNode.memory, jobNode.cores, jobNode.disk) MiB = 1 << 20 truncatedMemory = (old_div(jobNode.memory, MiB)) * MiB # Look for a batch for jobs with these resource requirements, with # the memory rounded down to the nearest megabyte. Rounding down # meams the new job can't ever decrease the memory requirements # of jobs already in the batch. if len(self.resultsFiles) >= self.maxBatches: raise RuntimeError( 'Number of batches reached limit of %i' % self.maxBatches) try: results = self.resultsFiles[(truncatedMemory, jobNode.cores)] except KeyError: results = getTempFile(rootDir=self.parasolResultsDir) self.resultsFiles[(truncatedMemory, jobNode.cores)] = results # Prefix the command with environment overrides, optionally looking them up from the # current environment if the value is None command = ' '.join(concat('env', self.__environment(), jobNode.command)) parasolCommand = ['-verbose', '-ram=%i' % jobNode.memory, '-cpu=%i' % jobNode.cores, '-results=' + results, 'add', 'job', command] # Deal with the cpus self.usedCpus += jobNode.cores while True: # Process finished results with no wait try: jobID = self.cpuUsageQueue.get_nowait() except Empty: break if jobID in list(self.jobIDsToCpu.keys()): self.usedCpus -= self.jobIDsToCpu.pop(jobID) assert self.usedCpus >= 0 while self.usedCpus > self.maxCores: # If we are still waiting jobID = self.cpuUsageQueue.get() if jobID in list(self.jobIDsToCpu.keys()): self.usedCpus -= self.jobIDsToCpu.pop(jobID) assert self.usedCpus >= 0 # Now keep going while True: line = self._runParasol(parasolCommand)[1][0] match = self.parasolOutputPattern.match(line) if match is None: # This is because parasol add job will return success, even if the job was not # properly issued! logger.debug('We failed to properly add the job, we will try again after a 5s.') time.sleep(5) else: jobID = int(match.group(1)) self.jobIDsToCpu[jobID] = jobNode.cores self.runningJobs.add(jobID) logger.debug("Got the parasol job id: %s from line: %s" % (jobID, line)) return jobID def setEnv(self, name, value=None): if value and ' ' in value: raise ValueError('Parasol does not support spaces in environment variable values.') return super(ParasolBatchSystem, self).setEnv(name, value) def __environment(self): return (k + '=' + (os.environ[k] if v is None else v) for k, v in listitems(self.environment)) def killBatchJobs(self, jobIDs): """Kills the given jobs, represented as Job ids, then checks they are dead by checking they are not in the list of issued jobs. """ while True: for jobID in jobIDs: if jobID in self.runningJobs: self.runningJobs.remove(jobID) exitValue = self._runParasol(['remove', 'job', str(jobID)], autoRetry=False)[0] logger.debug("Tried to remove jobID: %i, with exit value: %i" % (jobID, exitValue)) runningJobs = self.getIssuedBatchJobIDs() if set(jobIDs).difference(set(runningJobs)) == set(jobIDs): break logger.warn( 'Tried to kill some jobs, but something happened and they are still ' 'going, will try againin 5s.') time.sleep(5) # Update the CPU usage, because killed jobs aren't written to the results file. for jobID in jobIDs: if jobID in list(self.jobIDsToCpu.keys()): self.usedCpus -= self.jobIDsToCpu.pop(jobID) runningPattern = re.compile(r'r\s+([0-9]+)\s+[\S]+\s+[\S]+\s+([0-9]+)\s+[\S]+') def getJobIDsForResultsFile(self, resultsFile): """ Get all queued and running jobs for a results file. """ jobIDs = [] for line in self._runParasol(['-extended', 'list', 'jobs'])[1]: fields = line.strip().split() if len(fields) == 0 or fields[-1] != resultsFile: continue jobID = fields[0] jobIDs.append(int(jobID)) return set(jobIDs) def getIssuedBatchJobIDs(self): """ Gets the list of jobs issued to parasol in all results files, but not including jobs created by other users. """ issuedJobs = set() for resultsFile in itervalues(self.resultsFiles): issuedJobs.update(self.getJobIDsForResultsFile(resultsFile)) return list(issuedJobs) def getRunningBatchJobIDs(self): """ Returns map of running jobIDs and the time they have been running. """ # Example lines.. # r 5410186 benedictpaten worker 1247029663 localhost # r 5410324 benedictpaten worker 1247030076 localhost runningJobs = {} issuedJobs = self.getIssuedBatchJobIDs() for line in self._runParasol(['pstat2'])[1]: if line != '': match = self.runningPattern.match(line) if match is not None: jobID = int(match.group(1)) startTime = int(match.group(2)) if jobID in issuedJobs: # It's one of our jobs runningJobs[jobID] = time.time() - startTime return runningJobs def getUpdatedBatchJob(self, maxWait): while True: try: jobID, status, wallTime = self.updatedJobsQueue.get(timeout=maxWait) except Empty: return None try: self.runningJobs.remove(jobID) except KeyError: # We tried to kill this job, but it ended by itself instead, so skip it. pass else: return jobID, status, wallTime def updatedJobWorker(self): """ We use the parasol results to update the status of jobs, adding them to the list of updated jobs. Results have the following structure.. (thanks Mark D!) int status; /* Job status - wait() return format. 0 is good. */ char *host; /* Machine job ran on. */ char *jobId; /* Job queuing system job ID */ char *exe; /* Job executable file (no path) */ int usrTicks; /* 'User' CPU time in ticks. */ int sysTicks; /* 'System' CPU time in ticks. */ unsigned submitTime; /* Job submission time in seconds since 1/1/1970 */ unsigned startTime; /* Job start time in seconds since 1/1/1970 */ unsigned endTime; /* Job end time in seconds since 1/1/1970 */ char *user; /* User who ran job */ char *errFile; /* Location of stderr file on host */ Plus you finally have the command name. """ resultsFiles = set() resultsFileHandles = [] try: while self.running: # Look for any new results files that have been created, and open them newResultsFiles = set(os.listdir(self.parasolResultsDir)).difference(resultsFiles) for newFile in newResultsFiles: newFilePath = os.path.join(self.parasolResultsDir, newFile) resultsFileHandles.append(open(newFilePath, 'r')) resultsFiles.add(newFile) for fileHandle in resultsFileHandles: while self.running: line = fileHandle.readline() if not line: break assert line[-1] == '\n' (status, host, jobId, exe, usrTicks, sysTicks, submitTime, startTime, endTime, user, errFile, command) = line[:-1].split(None, 11) status = int(status) jobId = int(jobId) if os.WIFEXITED(status): status = os.WEXITSTATUS(status) else: status = -status self.cpuUsageQueue.put(jobId) startTime = int(startTime) endTime = int(endTime) if endTime == startTime: # Both, start and end time is an integer so to get sub-second # accuracy we use the ticks reported by Parasol as an approximation. # This isn't documented but what Parasol calls "ticks" is actually a # hundredth of a second. Parasol does the unit conversion early on # after a job finished. Search paraNode.c for ticksToHundreths. We # also cheat a little by always reporting at least one hundredth of a # second. usrTicks = int(usrTicks) sysTicks = int(sysTicks) wallTime = float( max( 1, usrTicks + sysTicks) ) * 0.01 else: wallTime = float(endTime - startTime) self.updatedJobsQueue.put((jobId, status, wallTime)) time.sleep(1) except: logger.warn("Error occurred while parsing parasol results files.") raise finally: for fileHandle in resultsFileHandles: fileHandle.close() def shutdown(self): self.killBatchJobs(self.getIssuedBatchJobIDs()) # cleanup jobs for results in itervalues(self.resultsFiles): exitValue = self._runParasol(['-results=' + results, 'clear', 'sick'], autoRetry=False)[0] if exitValue is not None: logger.warn("Could not clear sick status of the parasol batch %s" % results) exitValue = self._runParasol(['-results=' + results, 'flushResults'], autoRetry=False)[0] if exitValue is not None: logger.warn("Could not flush the parasol batch %s" % results) self.running = False logger.debug('Joining worker thread...') self.worker.join() logger.debug('... joined worker thread.') for results in list(self.resultsFiles.values()): os.remove(results) os.rmdir(self.parasolResultsDir) @classmethod def setOptions(cls, setOption): from toil.common import iC setOption("parasolCommand", None, None, 'parasol') setOption("parasolMaxBatches", int, iC(1), 10000) toil-releases-3.24.0/src/toil/batchSystems/parasolTestSupport.py000066400000000000000000000105531362134276200250410ustar00rootroot00000000000000# Copyright (C) 2015-2018 Regents of the University of California # # 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. from __future__ import absolute_import from builtins import object import logging import tempfile import threading import time from toil import subprocess import signal import os import errno from toil.lib.objects import InnerClass from toil.lib.threading import cpu_count from toil import physicalMemory log = logging.getLogger(__name__) def rm_f(path): """Remove the file at the given path with os.remove(), ignoring errors caused by the file's absence.""" try: os.remove(path) except OSError as e: if e.errno == errno.ENOENT: pass else: raise class ParasolTestSupport(object): """ For test cases that need a running Parasol leader and worker on the local host """ def _startParasol(self, numCores=None, memory=None): if numCores is None: numCores = cpu_count() if memory is None: memory = physicalMemory() self.numCores = numCores self.memory = memory self.leader = self.ParasolLeaderThread() self.leader.start() self.worker = self.ParasolWorkerThread() self.worker.start() while self.leader.popen is None or self.worker.popen is None: log.info('Waiting for leader and worker processes') time.sleep(.1) def _stopParasol(self): self.worker.popen.kill() self.worker.join() self.leader.popen.kill() self.leader.join() for path in ('para.results', 'parasol.jid'): rm_f(path) class ParasolThread(threading.Thread): # Lock is used because subprocess is NOT thread safe: http://tinyurl.com/pkp5pgq lock = threading.Lock() def __init__(self): threading.Thread.__init__(self) self.popen = None def parasolCommand(self): raise NotImplementedError def run(self): command = self.parasolCommand() with self.lock: self.popen = subprocess.Popen(command) status = self.popen.wait() if status != 0 and status != -signal.SIGKILL: log.error("Command '%s' failed with %i.", command, status) raise subprocess.CalledProcessError(status, command) log.info('Exiting %s', self.__class__.__name__) @InnerClass class ParasolLeaderThread(ParasolThread): def __init__(self): super(ParasolTestSupport.ParasolLeaderThread, self).__init__() self.machineList = None def run(self): with tempfile.NamedTemporaryFile(prefix='machineList.txt', mode='w') as f: self.machineList = f.name # name - Network name # cpus - Number of CPUs we can use # ramSize - Megabytes of memory # tempDir - Location of (local) temp dir # localDir - Location of local data dir # localSize - Megabytes of local disk # switchName - Name of switch this is on f.write('localhost {numCores} {ramSize} {tempDir} {tempDir} 1024 foo'.format( numCores=self.outer.numCores, tempDir=tempfile.gettempdir(), ramSize=self.outer.memory / 1024 / 1024)) f.flush() super(ParasolTestSupport.ParasolLeaderThread, self).run() def parasolCommand(self): return ['paraHub', '-spokes=1', '-debug', self.machineList] @InnerClass class ParasolWorkerThread(ParasolThread): def parasolCommand(self): return ['paraNode', '-cpu=%i' % self.outer.numCores, '-randomDelay=0', '-debug', 'start'] toil-releases-3.24.0/src/toil/batchSystems/registry.py000066400000000000000000000064331362134276200230150ustar00rootroot00000000000000# Copyright (C) 2015-2016 Regents of the University of California # # 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 # def _gridengineBatchSystemFactory(): from toil.batchSystems.gridengine import GridEngineBatchSystem return GridEngineBatchSystem def _parasolBatchSystemFactory(): from toil.batchSystems.parasol import ParasolBatchSystem return ParasolBatchSystem def _lsfBatchSystemFactory(): from toil.batchSystems.lsf import LSFBatchSystem return LSFBatchSystem def _singleMachineBatchSystemFactory(): from toil.batchSystems.singleMachine import SingleMachineBatchSystem return SingleMachineBatchSystem def _mesosBatchSystemFactory(): from toil.batchSystems.mesos.batchSystem import MesosBatchSystem return MesosBatchSystem def _slurmBatchSystemFactory(): from toil.batchSystems.slurm import SlurmBatchSystem return SlurmBatchSystem def _torqueBatchSystemFactory(): from toil.batchSystems.torque import TorqueBatchSystem return TorqueBatchSystem def _htcondorBatchSystemFactory(): from toil.batchSystems.htcondor import HTCondorBatchSystem return HTCondorBatchSystem def _kubernetesBatchSystemFactory(): from toil.batchSystems.kubernetes import KubernetesBatchSystem return KubernetesBatchSystem _DEFAULT_REGISTRY = { 'parasol' : _parasolBatchSystemFactory, 'singleMachine' : _singleMachineBatchSystemFactory, 'single_machine' : _singleMachineBatchSystemFactory, 'gridEngine' : _gridengineBatchSystemFactory, 'gridengine' : _gridengineBatchSystemFactory, 'lsf' : _lsfBatchSystemFactory, 'LSF' : _lsfBatchSystemFactory, 'mesos' : _mesosBatchSystemFactory, 'Mesos' : _mesosBatchSystemFactory, 'slurm' : _slurmBatchSystemFactory, 'Slurm' : _slurmBatchSystemFactory, 'torque' : _torqueBatchSystemFactory, 'Torque' : _torqueBatchSystemFactory, 'htcondor' : _htcondorBatchSystemFactory, 'HTCondor' : _htcondorBatchSystemFactory, 'kubernetes' : _kubernetesBatchSystemFactory, 'Kubernetes' : _kubernetesBatchSystemFactory, 'k8s' : _kubernetesBatchSystemFactory } _UNIQUE_NAME = { 'parasol', 'singleMachine', 'gridEngine', 'LSF', 'Mesos', 'Slurm', 'Torque', 'HTCondor', 'Kubernetes' } _batchSystemRegistry = _DEFAULT_REGISTRY.copy() _batchSystemNames = set(_UNIQUE_NAME) def addBatchSystemFactory(key, batchSystemFactory): _batchSystemNames.add(key) _batchSystemRegistry[key] = batchSystemFactory def batchSystemFactoryFor(batchSystem): return _batchSystemRegistry[batchSystem ] def defaultBatchSystem(): return 'singleMachine' def uniqueNames(): return list(_batchSystemNames) def batchSystems(): list(set(_batchSystemRegistry.values())) toil-releases-3.24.0/src/toil/batchSystems/singleMachine.py000066400000000000000000000405111362134276200237060ustar00rootroot00000000000000# Copyright (C) 2015-2016 Regents of the University of California # # 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. from __future__ import absolute_import from __future__ import division from future import standard_library standard_library.install_aliases() from builtins import str from builtins import range from builtins import object from past.utils import old_div from contextlib import contextmanager import logging import os import time import math from threading import Thread from threading import Lock, Condition from six.moves.queue import Empty, Queue import toil from toil import subprocess from toil.batchSystems.abstractBatchSystem import BatchSystemSupport from toil.lib.threading import cpu_count from toil import worker as toil_worker from toil.common import Toil log = logging.getLogger(__name__) class SingleMachineBatchSystem(BatchSystemSupport): """ The interface for running jobs on a single machine, runs all the jobs you give it as they come in, but in parallel. """ @classmethod def supportsAutoDeployment(cls): return False @classmethod def supportsWorkerCleanup(cls): return True numCores = cpu_count() minCores = 0.1 """ The minimal fractional CPU. Tasks with a smaller core requirement will be rounded up to this value. One important invariant of this class is that each worker thread represents a CPU requirement of minCores, meaning that we can never run more than numCores / minCores jobs concurrently. """ physicalMemory = toil.physicalMemory() def __init__(self, config, maxCores, maxMemory, maxDisk): if maxCores > self.numCores: log.warning('Limiting maxCores to CPU count of system (%i).', self.numCores) maxCores = self.numCores if maxMemory > self.physicalMemory: log.warning('Limiting maxMemory to physically available memory (%i).', self.physicalMemory) maxMemory = self.physicalMemory self.physicalDisk = toil.physicalDisk(config) if maxDisk > self.physicalDisk: log.warning('Limiting maxDisk to physically available disk (%i).', self.physicalDisk) maxDisk = self.physicalDisk super(SingleMachineBatchSystem, self).__init__(config, maxCores, maxMemory, maxDisk) assert self.maxCores >= self.minCores assert self.maxMemory >= 1 # The scale allows the user to apply a factor to each task's cores requirement, thereby # squeezing more tasks onto each core (scale < 1) or stretching tasks over more cores # (scale > 1). self.scale = config.scale if config.badWorker > 0 and config.debugWorker: # We can't throw SIGUSR1 at the worker because it is also going to # be the leader and/or test harness. raise RuntimeError("Cannot use badWorker and debugWorker together; " "worker would have to kill the leader") self.debugWorker = config.debugWorker # Number of worker threads that will be started self.numWorkers = int(old_div(self.maxCores, self.minCores)) # A counter to generate job IDs and a lock to guard it self.jobIndex = 0 self.jobIndexLock = Lock() # A dictionary mapping IDs of submitted jobs to the command line self.jobs = {} """ :type: dict[str,toil.job.JobNode] """ # A queue of jobs waiting to be executed. Consumed by the workers. self.inputQueue = Queue() # A queue of finished jobs. Produced by the workers. self.outputQueue = Queue() # A dictionary mapping IDs of currently running jobs to their Info objects self.runningJobs = {} """ :type: dict[str,Info] """ # The list of worker threads self.workerThreads = [] """ :type list[Thread] """ # Variables involved with non-blocking resource acquisition self.acquisitionTimeout = 5 self.acquisitionRetryDelay = 10 self.aquisitionCondition = Condition() # A pool representing available CPU in units of minCores self.coreFractions = ResourcePool(self.numWorkers, 'cores', self.acquisitionTimeout) # A lock to work around the lack of thread-safety in Python's subprocess module self.popenLock = Lock() # A pool representing available memory in bytes self.memory = ResourcePool(self.maxMemory, 'memory', self.acquisitionTimeout) # A pool representing the available space in bytes self.disk = ResourcePool(self.maxDisk, 'disk', self.acquisitionTimeout) if not self.debugWorker: log.debug('Setting up the thread pool with %i workers, ' 'given a minimum CPU fraction of %f ' 'and a maximum CPU value of %i.', self.numWorkers, self.minCores, maxCores) for i in range(self.numWorkers): worker = Thread(target=self.worker, args=(self.inputQueue,)) self.workerThreads.append(worker) worker.start() else: log.debug('Started in worker debug mode.') def _runWorker(self, jobCommand, jobID, environment): """ Run the jobCommand using the worker and wait for it to finish. The worker is forked unless it is a '_toil_worker' job and debugWorker is True. """ startTime = time.time() # Time job is started if self.debugWorker and "_toil_worker" in jobCommand: # Run the worker without forking jobName, jobStoreLocator, jobStoreID = jobCommand.split()[1:] # Parse command jobStore = Toil.resumeJobStore(jobStoreLocator) # TODO: The following does not yet properly populate self.runningJobs so it is not possible to kill # running jobs in forkless mode - see the "None" value in place of popen info = Info(time.time(), None, killIntended=False) try: self.runningJobs[jobID] = info try: toil_worker.workerScript(jobStore, jobStore.config, jobName, jobStoreID, redirectOutputToLogFile=not self.debugWorker) # Call the worker finally: self.runningJobs.pop(jobID) finally: if not info.killIntended: self.outputQueue.put((jobID, 0, time.time() - startTime)) else: with self.popenLock: popen = subprocess.Popen(jobCommand, shell=True, env=dict(os.environ, **environment)) info = Info(time.time(), popen, killIntended=False) try: self.runningJobs[jobID] = info try: statusCode = popen.wait() if statusCode != 0 and not info.killIntended: log.error("Got exit code %i (indicating failure) " "from job %s.", statusCode, self.jobs[jobID]) finally: self.runningJobs.pop(jobID) finally: if not info.killIntended: self.outputQueue.put((jobID, statusCode, time.time() - startTime)) # Note: The input queue is passed as an argument because the corresponding attribute is reset # to None in shutdown() def worker(self, inputQueue): while True: if self.debugWorker and inputQueue.empty(): return args = inputQueue.get() if args is None: break jobCommand, jobID, jobCores, jobMemory, jobDisk, environment = args while True: try: coreFractions = int(old_div(jobCores, self.minCores)) log.debug('Acquiring %i bytes of memory from a pool of %s.', jobMemory, self.memory) with self.memory.acquisitionOf(jobMemory): log.debug('Acquiring %i fractional cores from a pool of %s to satisfy a ' 'request of %f cores', coreFractions, self.coreFractions, jobCores) with self.coreFractions.acquisitionOf(coreFractions): with self.disk.acquisitionOf(jobDisk): self._runWorker(jobCommand, jobID, environment) except ResourcePool.AcquisitionTimeoutException as e: log.debug('Could not acquire enough (%s) to run job (%s). Requested: (%s), ' 'Avaliable: %s. Sleeping for 10s.', e.resource, jobID, e.requested, e.available) with self.aquisitionCondition: # Make threads sleep for the given delay, or until another job finishes. # Whichever is sooner. self.aquisitionCondition.wait(timeout=self.acquisitionRetryDelay) continue else: log.debug('Finished job. self.coreFractions ~ %s and self.memory ~ %s', self.coreFractions.value, self.memory.value) with self.aquisitionCondition: # Wake up sleeping threads self.aquisitionCondition.notifyAll() break def issueBatchJob(self, jobNode): """Adds the command and resources to a queue to be run.""" # Round cores to minCores and apply scale cores = math.ceil(jobNode.cores * self.scale / self.minCores) * self.minCores assert cores <= self.maxCores, ('The job {} is requesting {} cores, more than the maximum of ' '{} cores this batch system was configured with. Scale is ' 'set to {}.'.format(jobNode.jobName, cores, self.maxCores, self.scale)) assert cores >= self.minCores assert jobNode.memory <= self.maxMemory, ('The job {} is requesting {} bytes of memory, more than ' 'the maximum of {} this batch system was configured ' 'with.'.format(jobNode.jobName, jobNode.memory, self.maxMemory)) self.checkResourceRequest(jobNode.memory, cores, jobNode.disk) log.debug("Issuing the command: %s with memory: %i, cores: %i, disk: %i" % ( jobNode.command, jobNode.memory, cores, jobNode.disk)) with self.jobIndexLock: jobID = self.jobIndex self.jobIndex += 1 self.jobs[jobID] = jobNode.command self.inputQueue.put((jobNode.command, jobID, cores, jobNode.memory, jobNode.disk, self.environment.copy())) if self.debugWorker: # then run immediately, blocking for return self.worker(self.inputQueue) return jobID def killBatchJobs(self, jobIDs): """Kills jobs by ID.""" log.debug('Killing jobs: {}'.format(jobIDs)) for jobID in jobIDs: if jobID in self.runningJobs: info = self.runningJobs[jobID] info.killIntended = True if info.popen != None: os.kill(info.popen.pid, 9) else: # No popen if running in forkless mode currently assert self.debugWorker log.critical("Can't kill job: %s in debug mode" % jobID) while jobID in self.runningJobs: pass def getIssuedBatchJobIDs(self): """Just returns all the jobs that have been run, but not yet returned as updated.""" return list(self.jobs.keys()) def getRunningBatchJobIDs(self): now = time.time() return {jobID: now - info.time for jobID, info in list(self.runningJobs.items())} def shutdown(self): """ Cleanly terminate worker threads. Add sentinels to inputQueue equal to maxThreads. Join all worker threads. """ # Remove reference to inputQueue (raises exception if inputQueue is used after method call) inputQueue = self.inputQueue self.inputQueue = None for i in range(self.numWorkers): inputQueue.put(None) for thread in self.workerThreads: thread.join() BatchSystemSupport.workerCleanup(self.workerCleanupInfo) def getUpdatedBatchJob(self, maxWait): """Returns a tuple of a no-longer-running, the return value of its process, and its runtime, or None.""" try: item = self.outputQueue.get(timeout=maxWait) except Empty: return None jobID, exitValue, wallTime = item jobCommand = self.jobs.pop(jobID) log.debug("Ran jobID: %s with exit value: %i", jobID, exitValue) return jobID, exitValue, wallTime @classmethod def setOptions(cls, setOption): setOption("scale", default=1) class Info(object): # Can't use namedtuple here since killIntended needs to be mutable def __init__(self, startTime, popen, killIntended): self.time = startTime self.popen = popen self.killIntended = killIntended class ResourcePool(object): def __init__(self, initial_value, resourceType, timeout): super(ResourcePool, self).__init__() self.condition = Condition() self.value = initial_value self.resourceType = resourceType self.timeout = timeout def acquire(self, amount): with self.condition: startTime = time.time() while amount > self.value: if time.time() - startTime >= self.timeout: # This means the thread timed out waiting for the resource. We exit the nested # context managers in worker to prevent blocking of a resource due to # unavailability of a nested resource request. raise self.AcquisitionTimeoutException(resource=self.resourceType, requested=amount, available=self.value) # Allow 5 seconds to get the resource, else quit through the above if condition. # This wait + timeout is the last thing in the loop such that a request that takes # longer than 5s due to multiple wakes under the 5 second threshold are still # honored. self.condition.wait(timeout=self.timeout) self.value -= amount self.__validate() def release(self, amount): with self.condition: self.value += amount self.__validate() self.condition.notifyAll() def __validate(self): assert 0 <= self.value def __str__(self): return str(self.value) def __repr__(self): return "ResourcePool(%i)" % self.value @contextmanager def acquisitionOf(self, amount): self.acquire(amount) try: yield finally: self.release(amount) class AcquisitionTimeoutException(Exception): """To be raised when a resource request times out.""" def __init__(self, resource, requested, available): """ Creates an instance of this exception that indicates which resource is insufficient for current demands, as well as the amount requested and amount actually available. :param str resource: string representing the resource type :param int|float requested: the amount of the particular resource requested that resulted in this exception :param int|float available: amount of the particular resource actually available """ self.requested = requested self.available = available self.resource = resource toil-releases-3.24.0/src/toil/batchSystems/slurm.py000066400000000000000000000247601362134276200223120ustar00rootroot00000000000000# Copyright (c) 2016 Duke Center for Genomic and Computational Biology # # 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. from __future__ import absolute_import from __future__ import division from builtins import str from past.utils import old_div import logging import os from pipes import quote from toil import subprocess import time import math # Python 3 compatibility imports from six.moves.queue import Empty, Queue from six import iteritems from toil.batchSystems import MemoryString from toil.batchSystems.abstractGridEngineBatchSystem import AbstractGridEngineBatchSystem logger = logging.getLogger(__name__) class SlurmBatchSystem(AbstractGridEngineBatchSystem): class Worker(AbstractGridEngineBatchSystem.Worker): def getRunningJobIDs(self): # Should return a dictionary of Job IDs and number of seconds times = {} with self.runningJobsLock: currentjobs = dict((str(self.batchJobIDs[x][0]), x) for x in self.runningJobs) # currentjobs is a dictionary that maps a slurm job id (string) to our own internal job id # squeue arguments: # -h for no header # --format to get jobid i, state %t and time days-hours:minutes:seconds lines = subprocess.check_output(['squeue', '-h', '--format', '%i %t %M']).decode('utf-8').split('\n') for line in lines: values = line.split() if len(values) < 3: continue slurm_jobid, state, elapsed_time = values if slurm_jobid in currentjobs and state == 'R': seconds_running = self.parse_elapsed(elapsed_time) times[currentjobs[slurm_jobid]] = seconds_running return times def killJob(self, jobID): subprocess.check_call(['scancel', self.getBatchSystemID(jobID)]) def prepareSubmission(self, cpu, memory, jobID, command, jobName): return self.prepareSbatch(cpu, memory, jobID, jobName) + ['--wrap={}'.format(command)] def submitJob(self, subLine): try: output = subprocess.check_output(subLine, stderr=subprocess.STDOUT).decode('utf-8') # sbatch prints a line like 'Submitted batch job 2954103' result = int(output.strip().split()[-1]) logger.debug("sbatch submitted job %d", result) return result except OSError as e: logger.error("sbatch command failed") raise e def getJobExitCode(self, slurmJobID): logger.debug("Getting exit code for slurm job %d", int(slurmJobID)) state, rc = self._getJobDetailsFromSacct(slurmJobID) if rc == -999: state, rc = self._getJobDetailsFromScontrol(slurmJobID) logger.debug("s job state is %s", state) # If Job is in a running state, return None to indicate we don't have an update if state in ('PENDING', 'RUNNING', 'CONFIGURING', 'COMPLETING', 'RESIZING', 'SUSPENDED'): return None return rc def _getJobDetailsFromSacct(self, slurmJobID): # SLURM job exit codes are obtained by running sacct. args = ['sacct', '-n', # no header '-j', str(slurmJobID), # job '--format', 'State,ExitCode', # specify output columns '-P', # separate columns with pipes '-S', '1970-01-01'] # override start time limit process = subprocess.Popen(args, stdout=subprocess.PIPE, stderr=subprocess.STDOUT) rc = process.returncode if rc != 0: # no accounting system or some other error return (None, -999) for line in process.stdout: values = line.decode('utf-8').strip().split('|') if len(values) < 2: continue state, exitcode = values logger.debug("sacct job state is %s", state) # If Job is in a running state, return None to indicate we don't have an update status, signal = [int(n) for n in exitcode.split(':')] if signal > 0: # A non-zero signal may indicate e.g. an out-of-memory killed job status = 128 + signal logger.debug("sacct exit code is %s, returning status %d", exitcode, status) return (state, status) logger.debug("Did not find exit code for job in sacct output") return None def _getJobDetailsFromScontrol(self, slurmJobID): args = ['scontrol', 'show', 'job', str(slurmJobID)] process = subprocess.Popen(args, stdout=subprocess.PIPE, stderr=subprocess.STDOUT) job = dict() for line in process.stdout: values = line.decode('utf-8').strip().split() # If job information is not available an error is issued: # slurm_load_jobs error: Invalid job id specified # There is no job information, so exit. if len(values)>0 and values[0] == 'slurm_load_jobs': return (None, None) # Output is in the form of many key=value pairs, multiple pairs on each line # and multiple lines in the output. Each pair is pulled out of each line and # added to a dictionary for v in values: bits = v.split('=') job[bits[0]] = bits[1] state = job['JobState'] try: exitcode = job['ExitCode'] if exitcode is not None: status, signal = [int(n) for n in exitcode.split(':')] if signal > 0: # A non-zero signal may indicate e.g. an out-of-memory killed job status = 128 + signal logger.debug("scontrol exit code is %s, returning status %d", exitcode, status) rc = status else: rc = None except KeyError: rc = None return (state, rc) """ Implementation-specific helper methods """ def prepareSbatch(self, cpu, mem, jobID, jobName): # Returns the sbatch command line before the script to run sbatch_line = ['sbatch', '-J', 'toil_job_{}_{}'.format(jobID, jobName)] if self.boss.environment: argList = [] for k, v in self.boss.environment.items(): quoted_value = quote(os.environ[k] if v is None else v) argList.append('{}={}'.format(k, quoted_value)) sbatch_line.append('--export=' + ','.join(argList)) if mem is not None: # memory passed in is in bytes, but slurm expects megabytes sbatch_line.append('--mem={}'.format(old_div(int(mem), 2 ** 20))) if cpu is not None: sbatch_line.append('--cpus-per-task={}'.format(int(math.ceil(cpu)))) stdoutfile = self.boss.formatStdOutErrPath(jobID, 'slurm', '%j', 'std_output') stderrfile = self.boss.formatStdOutErrPath(jobID, 'slurm', '%j', 'std_error') sbatch_line.extend(['-o', stdoutfile, '-e', stderrfile]) # "Native extensions" for SLURM (see DRMAA or SAGA) nativeConfig = os.getenv('TOIL_SLURM_ARGS') if nativeConfig is not None: logger.debug("Native SLURM options appended to sbatch from TOIL_SLURM_ARGS env. variable: {}".format(nativeConfig)) if ("--mem" in nativeConfig) or ("--cpus-per-task" in nativeConfig): raise ValueError("Some resource arguments are incompatible: {}".format(nativeConfig)) sbatch_line.extend(nativeConfig.split()) return sbatch_line def parse_elapsed(self, elapsed): # slurm returns elapsed time in days-hours:minutes:seconds format # Sometimes it will only return minutes:seconds, so days may be omitted # For ease of calculating, we'll make sure all the delimeters are ':' # Then reverse the list so that we're always counting up from seconds -> minutes -> hours -> days total_seconds = 0 try: elapsed = elapsed.replace('-', ':').split(':') elapsed.reverse() seconds_per_unit = [1, 60, 3600, 86400] for index, multiplier in enumerate(seconds_per_unit): if index < len(elapsed): total_seconds += multiplier * int(elapsed[index]) except ValueError: pass # slurm may return INVALID instead of a time return total_seconds """ The interface for SLURM """ @classmethod def getWaitDuration(cls): return 1 @classmethod def obtainSystemConstants(cls): # sinfo -Ne --format '%m,%c' # sinfo arguments: # -N for node-oriented # -h for no header # -e for exact values (e.g. don't return 32+) # --format to get memory, cpu max_cpu = 0 max_mem = MemoryString('0') lines = subprocess.check_output(['sinfo', '-Nhe', '--format', '%m %c']).decode('utf-8').split('\n') for line in lines: values = line.split() if len(values) < 2: continue mem, cpu = values max_cpu = max(max_cpu, int(cpu)) max_mem = max(max_mem, MemoryString(mem + 'M')) if max_cpu == 0 or max_mem.byteVal() == 0: RuntimeError('sinfo did not return memory or cpu info') return max_cpu, max_mem toil-releases-3.24.0/src/toil/batchSystems/torque.py000066400000000000000000000244771362134276200224740ustar00rootroot00000000000000# Copyright (C) 2015 UCSC Computational Genomics Lab # # 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. from __future__ import absolute_import from __future__ import division from builtins import str from past.utils import old_div import logging import os from pipes import quote from toil import subprocess import time import math import sys import shlex import xml.etree.ElementTree as ET import tempfile from toil.batchSystems import MemoryString from toil.batchSystems.abstractGridEngineBatchSystem import AbstractGridEngineBatchSystem logging.basicConfig(level=logging.DEBUG) logger = logging.getLogger(__name__) class TorqueBatchSystem(AbstractGridEngineBatchSystem): # class-specific Worker class Worker(AbstractGridEngineBatchSystem.Worker): def __init__(self, newJobsQueue, updatedJobsQueue, killQueue, killedJobsQueue, boss): super(self.__class__, self).__init__(newJobsQueue, updatedJobsQueue, killQueue, killedJobsQueue, boss) self._version = self._pbsVersion() def _pbsVersion(self): """ Determines PBS/Torque version via pbsnodes """ try: out = subprocess.check_output(["pbsnodes", "--version"]).decode('utf-8') if "PBSPro" in out: logger.debug("PBS Pro proprietary Torque version detected") self._version = "pro" else: logger.debug("Torque OSS version detected") self._version = "oss" except subprocess.CalledProcessError as e: if e.returncode != 0: logger.error("Could not determine PBS/Torque version") return self._version """ Torque-specific AbstractGridEngineWorker methods """ def getRunningJobIDs(self): times = {} with self.runningJobsLock: currentjobs = dict((str(self.batchJobIDs[x][0].strip()), x) for x in self.runningJobs) logger.debug("getRunningJobIDs current jobs are: " + str(currentjobs)) # Skip running qstat if we don't have any current jobs if not currentjobs: return times # Only query for job IDs to avoid clogging the batch system on heavily loaded clusters # PBS plain qstat will return every running job on the system. jobids = sorted(list(currentjobs.keys())) if self._version == "pro": process = subprocess.Popen(['qstat', '-x'] + jobids, stdout=subprocess.PIPE) elif self._version == "oss": process = subprocess.Popen(['qstat'] + jobids, stdout=subprocess.PIPE) stdout, stderr = process.communicate() # qstat supports XML output which is more comprehensive, but PBSPro does not support it # so instead we stick with plain commandline qstat tabular outputs for currline in stdout.decode('utf-8').split('\n'): items = currline.strip().split() if items: jobid = items[0].strip() if jobid in currentjobs: logger.debug("getRunningJobIDs job status for is: " + items[4]) if jobid in currentjobs and items[4] == 'R': walltime = items[3] logger.debug("getRunningJobIDs qstat reported walltime is: " + walltime) # normal qstat has a quirk with job time where it reports '0' # when initially running; this catches this case if walltime == '0': walltime = time.mktime(time.strptime(walltime, "%S")) else: walltime = time.mktime(time.strptime(walltime, "%H:%M:%S")) times[currentjobs[jobid]] = walltime logger.debug("Job times from qstat are: " + str(times)) return times def getUpdatedBatchJob(self, maxWait): try: logger.debug("getUpdatedBatchJob: Job updates") pbsJobID, retcode = self.updatedJobsQueue.get(timeout=maxWait) self.updatedJobsQueue.task_done() jobID, retcode = (self.jobIDs[pbsJobID], retcode) self.currentjobs -= {self.jobIDs[pbsJobID]} except Empty: logger.debug("getUpdatedBatchJob: Job queue is empty") pass else: return jobID, retcode, None def killJob(self, jobID): subprocess.check_call(['qdel', self.getBatchSystemID(jobID)]) def prepareSubmission(self, cpu, memory, jobID, command, jobName): return self.prepareQsub(cpu, memory, jobID) + [self.generateTorqueWrapper(command, jobID)] def submitJob(self, subLine): process = subprocess.Popen(subLine, stdout=subprocess.PIPE) so, se = process.communicate() return so def getJobExitCode(self, torqueJobID): if self._version == "pro": args = ["qstat", "-x", "-f", str(torqueJobID).split('.')[0]] elif self._version == "oss": args = ["qstat", "-f", str(torqueJobID).split('.')[0]] process = subprocess.Popen(args, stdout=subprocess.PIPE, stderr=subprocess.STDOUT) for line in process.stdout: line = line.strip() #logger.debug("getJobExitCode exit status: " + line) # Case differences due to PBSPro vs OSS Torque qstat outputs if line.startswith("failed") or line.startswith("FAILED") and int(line.split()[1]) == 1: return 1 if line.startswith("exit_status") or line.startswith("Exit_status"): status = line.split(' = ')[1] logger.debug('Exit Status: ' + status) return int(status) if 'unknown job id' in line.lower(): # some clusters configure Torque to forget everything about just # finished jobs instantly, apparently for performance reasons logger.debug('Batch system no longer remembers about job {}'.format(torqueJobID)) # return assumed success; status files should reveal failure return 0 return None """ Implementation-specific helper methods """ def prepareQsub(self, cpu, mem, jobID): # TODO: passing $PWD on command line not working for -d, resorting to # $PBS_O_WORKDIR but maybe should fix this here instead of in script? qsubline = ['qsub', '-S', '/bin/sh', '-V', '-N', 'toil_job_{}'.format(jobID)] if self.boss.environment: qsubline.append('-v') qsubline.append(','.join(k + '=' + quote(os.environ[k] if v is None else v) for k, v in self.boss.environment.items())) reqline = list() if mem is not None: memStr = str(old_div(mem, 1024)) + 'K' reqline.append('mem=' + memStr) if cpu is not None and math.ceil(cpu) > 1: reqline.append('nodes=1:ppn=' + str(int(math.ceil(cpu)))) # Other resource requirements can be passed through the environment (see man qsub) reqlineEnv = os.getenv('TOIL_TORQUE_REQS') if reqlineEnv is not None: logger.debug("Additional Torque resource requirements appended to qsub from "\ "TOIL_TORQUE_REQS env. variable: {}".format(reqlineEnv)) if ("mem=" in reqlineEnv) or ("nodes=" in reqlineEnv) or ("ppn=" in reqlineEnv): raise ValueError("Incompatible resource arguments ('mem=', 'nodes=', 'ppn='): {}".format(reqlineEnv)) reqline.append(reqlineEnv) if reqline: qsubline += ['-l',','.join(reqline)] # All other qsub parameters can be passed through the environment (see man qsub). # No attempt is made to parse them out here and check that they do not conflict # with those that we already constructed above arglineEnv = os.getenv('TOIL_TORQUE_ARGS') if arglineEnv is not None: logger.debug("Native Torque options appended to qsub from TOIL_TORQUE_ARGS env. variable: {}".\ format(arglineEnv)) if ("mem=" in arglineEnv) or ("nodes=" in arglineEnv) or ("ppn=" in arglineEnv): raise ValueError("Incompatible resource arguments ('mem=', 'nodes=', 'ppn='): {}".format(arglineEnv)) qsubline += shlex.split(arglineEnv) return qsubline def generateTorqueWrapper(self, command, jobID): """ A very simple script generator that just wraps the command given; for now this goes to default tempdir """ stdoutfile = self.boss.formatStdOutErrPath(jobID, 'torque', '$PBS_JOBID', 'std_output') stderrfile = self.boss.formatStdOutErrPath(jobID, 'torque', '$PBS_JOBID', 'std_error') _, tmpFile = tempfile.mkstemp(suffix='.sh', prefix='torque_wrapper') fh = open(tmpFile , 'w') fh.write("#!/bin/sh\n") fh.write("#PBS -o {}\n".format(stdoutfile)) fh.write("#PBS -e {}\n".format(stderrfile)) fh.write("cd $PBS_O_WORKDIR\n\n") fh.write(command + "\n") fh.close return tmpFile @classmethod def obtainSystemConstants(cls): # See: https://github.com/BD2KGenomics/toil/pull/1617#issuecomment-293525747 logger.debug("PBS/Torque does not need obtainSystemConstants to assess global cluster resources.") #return maxCPU, maxMEM return None, None toil-releases-3.24.0/src/toil/common.py000066400000000000000000001773501362134276200177730ustar00rootroot00000000000000# Copyright (C) 2015-2018 Regents of the University of California # # 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. from __future__ import absolute_import from future import standard_library standard_library.install_aliases() from builtins import str from builtins import range from builtins import object import logging import os import re import sys import tempfile import time import uuid import requests from argparse import ArgumentParser from six import iteritems from toil.lib.humanize import bytes2human from toil.lib.retry import retry from toil import subprocess from toil import pickle from toil import logProcessContext from toil.lib.bioio import addLoggingOptions, getLogLevelString, setLoggingFromOptions from toil.realtimeLogger import RealtimeLogger from toil.batchSystems.options import addOptions as addBatchOptions from toil.batchSystems.options import setDefaultOptions as setDefaultBatchOptions from toil.batchSystems.options import setOptions as setBatchOptions from toil.provisioners import clusterFactory from toil.provisioners.aws import checkValidNodeTypes, zoneToRegion from toil import lookupEnvVar from toil.version import dockerRegistry, dockerTag # aim to pack autoscaling jobs within a 30 minute block before provisioning a new node defaultTargetTime = 1800 logger = logging.getLogger(__name__) class Config(object): """ Class to represent configuration operations for a toil workflow run. """ def __init__(self): # Core options self.workflowID = None """This attribute uniquely identifies the job store and therefore the workflow. It is necessary in order to distinguish between two consecutive workflows for which self.jobStore is the same, e.g. when a job store name is reused after a previous run has finished sucessfully and its job store has been clean up.""" self.workflowAttemptNumber = None self.jobStore = None self.logLevel = getLogLevelString() self.workDir = None self.noStdOutErr = False self.stats = False # Because the stats option needs the jobStore to persist past the end of the run, # the clean default value depends the specified stats option and is determined in setOptions self.clean = None self.cleanWorkDir = None self.clusterStats = None # Restarting the workflow options self.restart = False # Batch system options setDefaultBatchOptions(self) # Autoscaling options self.provisioner = None self.nodeTypes = [] checkValidNodeTypes(self.provisioner, self.nodeTypes) self.nodeOptions = None self.minNodes = None self.maxNodes = [10] self.targetTime = defaultTargetTime self.betaInertia = 0.1 self.scaleInterval = 60 self.preemptableCompensation = 0.0 self.nodeStorage = 50 self.metrics = False # Parameters to limit service jobs, so preventing deadlock scheduling scenarios self.maxPreemptableServiceJobs = sys.maxsize self.maxServiceJobs = sys.maxsize self.deadlockWait = 60 # Number of seconds to wait before declaring a deadlock self.statePollingWait = 1 # Number of seconds to wait before querying job state # Resource requirements self.defaultMemory = 2147483648 self.defaultCores = 1 self.defaultDisk = 2147483648 self.readGlobalFileMutableByDefault = False self.defaultPreemptable = False self.maxCores = sys.maxsize self.maxMemory = sys.maxsize self.maxDisk = sys.maxsize # Retrying/rescuing jobs self.retryCount = 1 self.maxJobDuration = sys.maxsize self.rescueJobsFrequency = 3600 # Misc self.disableCaching = True self.disableChaining = False self.disableJobStoreChecksumVerification = False self.maxLogFileSize = 64000 self.writeLogs = None self.writeLogsGzip = None self.writeLogsFromAllJobs = False self.sseKey = None self.servicePollingInterval = 60 self.useAsync = True self.forceDockerAppliance = False self.runCwlInternalJobsOnWorkers = False # Debug options self.debugWorker = False self.disableWorkerOutputCapture = False self.badWorker = 0.0 self.badWorkerFailInterval = 0.01 # CWL self.cwl = False def setOptions(self, options): """ Creates a config object from the options object. """ from toil.lib.humanize import human2bytes # This import is used to convert # from human readable quantites to integers def setOption(varName, parsingFn=None, checkFn=None, default=None): # If options object has the option "varName" specified # then set the "varName" attrib to this value in the config object x = getattr(options, varName, None) if x is None: x = default if x is not None: if parsingFn is not None: x = parsingFn(x) if checkFn is not None: try: checkFn(x) except AssertionError: raise RuntimeError("The %s option has an invalid value: %s" % (varName, x)) setattr(self, varName, x) # Function to parse integer from string expressed in different formats h2b = lambda x: human2bytes(str(x)) def parseJobStore(s): name, rest = Toil.parseLocator(s) if name == 'file': # We need to resolve relative paths early, on the leader, because the worker process # may have a different working directory than the leader, e.g. under Mesos. return Toil.buildLocator(name, os.path.abspath(rest)) else: return s def parseStrList(s): s = s.split(",") s = [str(x) for x in s] return s def parseIntList(s): s = s.split(",") s = [int(x) for x in s] return s # Core options setOption("jobStore", parsingFn=parseJobStore) # TODO: LOG LEVEL STRING setOption("workDir") if self.workDir is not None: self.workDir = os.path.abspath(self.workDir) if not os.path.exists(self.workDir): raise RuntimeError("The path provided to --workDir (%s) does not exist." % self.workDir) setOption("noStdOutErr") setOption("stats") setOption("cleanWorkDir") setOption("clean") if self.stats: if self.clean != "never" and self.clean is not None: raise RuntimeError("Contradicting options passed: Clean flag is set to %s " "despite the stats flag requiring " "the jobStore to be intact at the end of the run. " "Set clean to \'never\'" % self.clean) self.clean = "never" elif self.clean is None: self.clean = "onSuccess" setOption('clusterStats') setOption("restart") # Batch system options setOption("batchSystem") setBatchOptions(self, setOption) setOption("disableAutoDeployment") setOption("scale", float, fC(0.0)) setOption("mesosMasterAddress") setOption("parasolCommand") setOption("parasolMaxBatches", int, iC(1)) setOption("linkImports") setOption("environment", parseSetEnv) # Autoscaling options setOption("provisioner") setOption("nodeTypes", parseStrList) setOption("nodeOptions") setOption("minNodes", parseIntList) setOption("maxNodes", parseIntList) setOption("targetTime", int) if self.targetTime <= 0: raise RuntimeError('targetTime (%s) must be a positive integer!' '' % self.targetTime) setOption("betaInertia", float) if not 0.0 <= self.betaInertia <= 0.9: raise RuntimeError('betaInertia (%f) must be between 0.0 and 0.9!' '' % self.betaInertia) setOption("scaleInterval", float) setOption("metrics") setOption("preemptableCompensation", float) if not 0.0 <= self.preemptableCompensation <= 1.0: raise RuntimeError('preemptableCompensation (%f) must be between 0.0 and 1.0!' '' % self.preemptableCompensation) setOption("nodeStorage", int) # Parameters to limit service jobs / detect deadlocks setOption("maxServiceJobs", int) setOption("maxPreemptableServiceJobs", int) setOption("deadlockWait", int) setOption("statePollingWait", int) # Resource requirements setOption("defaultMemory", h2b, iC(1)) setOption("defaultCores", float, fC(1.0)) setOption("defaultDisk", h2b, iC(1)) setOption("readGlobalFileMutableByDefault") setOption("maxCores", int, iC(1)) setOption("maxMemory", h2b, iC(1)) setOption("maxDisk", h2b, iC(1)) setOption("defaultPreemptable") # Retrying/rescuing jobs setOption("retryCount", int, iC(1)) setOption("maxJobDuration", int, iC(1)) setOption("rescueJobsFrequency", int, iC(1)) # Misc setOption("maxLocalJobs", int) setOption("disableCaching") setOption("disableChaining") setOption("disableJobStoreChecksumVerification") setOption("maxLogFileSize", h2b, iC(1)) setOption("writeLogs") setOption("writeLogsGzip") setOption("writeLogsFromAllJobs") setOption("runCwlInternalJobsOnWorkers") assert not (self.writeLogs and self.writeLogsGzip), \ "Cannot use both --writeLogs and --writeLogsGzip at the same time." assert not self.writeLogsFromAllJobs or self.writeLogs or self.writeLogsGzip, \ "To enable --writeLogsFromAllJobs, either --writeLogs or --writeLogsGzip must be set." def checkSse(sseKey): with open(sseKey) as f: assert (len(f.readline().rstrip()) == 32) setOption("sseKey", checkFn=checkSse) setOption("servicePollingInterval", float, fC(0.0)) setOption("forceDockerAppliance") # Debug options setOption("debugWorker") setOption("disableWorkerOutputCapture") setOption("badWorker", float, fC(0.0, 1.0)) setOption("badWorkerFailInterval", float, fC(0.0)) def __eq__(self, other): return self.__dict__ == other.__dict__ def __hash__(self): return self.__dict__.__hash__() jobStoreLocatorHelp = ("A job store holds persistent information about the jobs and files in a " "workflow. If the workflow is run with a distributed batch system, the job " "store must be accessible by all worker nodes. Depending on the desired " "job store implementation, the location should be formatted according to " "one of the following schemes:\n\n" "file: where points to a directory on the file systen\n\n" "aws:: where is the name of an AWS region like " "us-west-2 and will be prepended to the names of any top-level " "AWS resources in use by job store, e.g. S3 buckets.\n\n " "google:: TODO: explain\n\n" "For backwards compatibility, you may also specify ./foo (equivalent to " "file:./foo or just file:foo) or /bar (equivalent to file:/bar).") def _addOptions(addGroupFn, config): # # Core options # addOptionFn = addGroupFn("toil core options", "Options to specify the location of the Toil workflow and turn on " "stats collation about the performance of jobs.") addOptionFn('jobStore', type=str, help="The location of the job store for the workflow. " + jobStoreLocatorHelp) addOptionFn("--workDir", dest="workDir", default=None, help="Absolute path to directory where temporary files generated during the Toil " "run should be placed. Temp files and folders, as well as standard output " "and error from batch system jobs (unless --noStdOutErr), will be placed in a " "directory toil- within workDir. The workflowID is generated by " "Toil and will be reported in the workflow logs. Default is determined by the " "variables (TMPDIR, TEMP, TMP) via mkdtemp. This directory needs to exist on " "all machines running jobs; if capturing standard output and error from batch " "system jobs is desired, it will generally need to be on a shared file system.") addOptionFn("--noStdOutErr", dest="noStdOutErr", action="store_true", default=None, help="Do not capture standard output and error from batch system jobs.") addOptionFn("--stats", dest="stats", action="store_true", default=None, help="Records statistics about the toil workflow to be used by 'toil stats'.") addOptionFn("--clean", dest="clean", choices=['always', 'onError', 'never', 'onSuccess'], default=None, help=("Determines the deletion of the jobStore upon completion of the program. " "Choices: 'always', 'onError','never', 'onSuccess'. The --stats option requires " "information from the jobStore upon completion so the jobStore will never be deleted with" "that flag. If you wish to be able to restart the run, choose \'never\' or \'onSuccess\'. " "Default is \'never\' if stats is enabled, and \'onSuccess\' otherwise")) addOptionFn("--cleanWorkDir", dest="cleanWorkDir", choices=['always', 'never', 'onSuccess', 'onError'], default='always', help=( "Determines deletion of temporary worker directory upon completion of a job. Choices: 'always', " "'never', 'onSuccess'. Default = always. WARNING: This option should be changed for debugging " "only. Running a full pipeline with this option could fill your disk with intermediate data.")) addOptionFn("--clusterStats", dest="clusterStats", nargs='?', action='store', default=None, const=os.getcwd(), help="If enabled, writes out JSON resource usage statistics to a file. " "The default location for this file is the current working directory, " "but an absolute path can also be passed to specify where this file " "should be written. This options only applies when using scalable batch " "systems.") # # Restarting the workflow options # addOptionFn = addGroupFn("toil options for restarting an existing workflow", "Allows the restart of an existing workflow") addOptionFn("--restart", dest="restart", default=None, action="store_true", help="If --restart is specified then will attempt to restart existing workflow " "at the location pointed to by the --jobStore option. Will raise an exception " "if the workflow does not exist") # # Batch system options # addOptionFn = addGroupFn("toil options for specifying the batch system", "Allows the specification of the batch system, and arguments to the " "batch system/big batch system (see below).") addBatchOptions(addOptionFn, config) # # Auto scaling options # addOptionFn = addGroupFn("toil options for autoscaling the cluster of worker nodes", "Allows the specification of the minimum and maximum number of nodes " "in an autoscaled cluster, as well as parameters to control the " "level of provisioning.") addOptionFn("--provisioner", dest="provisioner", choices=['aws', 'gce'], help="The provisioner for cluster auto-scaling. The currently supported choices are" "'gce', or 'aws'. The default is %s." % config.provisioner) addOptionFn('--nodeTypes', default=None, help="List of node types separated by commas. The syntax for each node type " "depends on the provisioner used. For the cgcloud and AWS provisioners " "this is the name of an EC2 instance type, optionally followed by a " "colon and the price in dollars " "to bid for a spot instance of that type, for example 'c3.8xlarge:0.42'." "If no spot bid is specified, nodes of this type will be non-preemptable." "It is acceptable to specify an instance as both preemptable and " "non-preemptable, including it twice in the list. In that case," "preemptable nodes of that type will be preferred when creating " "new nodes once the maximum number of preemptable-nodes has been" "reached.") addOptionFn('--nodeOptions', default=None, help = "Options for provisioning the nodes. The syntax " "depends on the provisioner used. Neither the CGCloud nor the AWS " "provisioner support any node options.") addOptionFn('--minNodes', default=None, help="Mininum number of nodes of each type in the cluster, if using " "auto-scaling. This should be provided as a comma-separated " "list of the same length as the list of node types. default=0") addOptionFn('--maxNodes', default=None, help="Maximum number of nodes of each type in the cluster, if using " "autoscaling, provided as a comma-separated list. The first value is used " "as a default if the list length is less than the number of nodeTypes. " "default=%s" % config.maxNodes[0]) addOptionFn("--targetTime", dest="targetTime", default=None, help=("Sets how rapidly you aim to complete jobs in seconds. Shorter times mean " "more aggressive parallelization. The autoscaler attempts to scale up/down " "so that it expects all queued jobs will complete within targetTime " "seconds. default=%s" % config.targetTime)) addOptionFn("--betaInertia", dest="betaInertia", default=None, help=("A smoothing parameter to prevent unnecessary oscillations in the " "number of provisioned nodes. This controls an exponentially weighted " "moving average of the estimated number of nodes. A value of 0.0 " "disables any smoothing, and a value of 0.9 will smooth so much that " "few changes will ever be made. Must be between 0.0 and 0.9. " "default=%s" % config.betaInertia)) addOptionFn("--scaleInterval", dest="scaleInterval", default=None, help=("The interval (seconds) between assessing if the scale of" " the cluster needs to change. default=%s" % config.scaleInterval)) addOptionFn("--preemptableCompensation", dest="preemptableCompensation", default=None, help=("The preference of the autoscaler to replace preemptable nodes with " "non-preemptable nodes, when preemptable nodes cannot be started for some " "reason. Defaults to %s. This value must be between 0.0 and 1.0, inclusive. " "A value of 0.0 disables such compensation, a value of 0.5 compensates two " "missing preemptable nodes with a non-preemptable one. A value of 1.0 " "replaces every missing pre-emptable node with a non-preemptable one." % config.preemptableCompensation)) addOptionFn("--nodeStorage", dest="nodeStorage", default=50, help=("Specify the size of the root volume of worker nodes when they are launched " "in gigabytes. You may want to set this if your jobs require a lot of disk " "space. The default value is 50.")) addOptionFn("--metrics", dest="metrics", default=False, action="store_true", help=( "Enable the prometheus/grafana dashboard for monitoring CPU/RAM usage, queue size, " "and issued jobs.")) # # Parameters to limit service jobs / detect service deadlocks # if not config.cwl: addOptionFn = addGroupFn( "toil options for limiting the number of service jobs and detecting service deadlocks", "Allows the specification of the maximum number of service jobs " "in a cluster. By keeping this limited " " we can avoid all the nodes being occupied with services, so causing a deadlock") addOptionFn("--maxServiceJobs", dest="maxServiceJobs", default=None, help=( "The maximum number of service jobs that can be run concurrently, excluding service jobs running on preemptable nodes. default=%s" % config.maxServiceJobs)) addOptionFn("--maxPreemptableServiceJobs", dest="maxPreemptableServiceJobs", default=None, help=( "The maximum number of service jobs that can run concurrently on preemptable nodes. default=%s" % config.maxPreemptableServiceJobs)) addOptionFn("--deadlockWait", dest="deadlockWait", default=None, help=( "The minimum number of seconds to observe the cluster stuck running only the same service jobs before throwing a deadlock exception. default=%s" % config.deadlockWait)) addOptionFn("--statePollingWait", dest="statePollingWait", default=1, help=("Time, in seconds, to wait before doing a scheduler query for job state. " "Return cached results if within the waiting period.")) # # Resource requirements # addOptionFn = addGroupFn("toil options for cores/memory requirements", "The options to specify default cores/memory requirements (if not " "specified by the jobs themselves), and to limit the total amount of " "memory/cores requested from the batch system.") addOptionFn('--defaultMemory', dest='defaultMemory', default=None, metavar='INT', help='The default amount of memory to request for a job. Only applicable to jobs ' 'that do not specify an explicit value for this requirement. Standard ' 'suffixes like K, Ki, M, Mi, G or Gi are supported. Default is %s' % bytes2human(config.defaultMemory, symbols='iec')) addOptionFn('--defaultCores', dest='defaultCores', default=None, metavar='FLOAT', help='The default number of CPU cores to dedicate a job. Only applicable to jobs ' 'that do not specify an explicit value for this requirement. Fractions of a ' 'core (for example 0.1) are supported on some batch systems, namely Mesos ' 'and singleMachine. Default is %.1f ' % config.defaultCores) addOptionFn('--defaultDisk', dest='defaultDisk', default=None, metavar='INT', help='The default amount of disk space to dedicate a job. Only applicable to jobs ' 'that do not specify an explicit value for this requirement. Standard ' 'suffixes like K, Ki, M, Mi, G or Gi are supported. Default is %s' % bytes2human(config.defaultDisk, symbols='iec')) assert not config.defaultPreemptable, 'User would be unable to reset config.defaultPreemptable' addOptionFn('--defaultPreemptable', dest='defaultPreemptable', action='store_true') addOptionFn('--maxCores', dest='maxCores', default=None, metavar='INT', help='The maximum number of CPU cores to request from the batch system at any one ' 'time. Standard suffixes like K, Ki, M, Mi, G or Gi are supported. Default ' 'is %s' % bytes2human(config.maxCores, symbols='iec')) addOptionFn('--maxMemory', dest='maxMemory', default=None, metavar='INT', help="The maximum amount of memory to request from the batch system at any one " "time. Standard suffixes like K, Ki, M, Mi, G or Gi are supported. Default " "is %s" % bytes2human(config.maxMemory, symbols='iec')) addOptionFn('--maxDisk', dest='maxDisk', default=None, metavar='INT', help='The maximum amount of disk space to request from the batch system at any ' 'one time. Standard suffixes like K, Ki, M, Mi, G or Gi are supported. ' 'Default is %s' % bytes2human(config.maxDisk, symbols='iec')) # # Retrying/rescuing jobs # addOptionFn = addGroupFn("toil options for rescuing/killing/restarting jobs", \ "The options for jobs that either run too long/fail or get lost \ (some batch systems have issues!)") addOptionFn("--retryCount", dest="retryCount", default=None, help=("Number of times to retry a failing job before giving up and " "labeling job failed. default=%s" % config.retryCount)) addOptionFn("--maxJobDuration", dest="maxJobDuration", default=None, help=("Maximum runtime of a job (in seconds) before we kill it " "(this is a lower bound, and the actual time before killing " "the job may be longer). default=%s" % config.maxJobDuration)) addOptionFn("--rescueJobsFrequency", dest="rescueJobsFrequency", default=None, help=("Period of time to wait (in seconds) between checking for " "missing/overlong jobs, that is jobs which get lost by the batch " "system. Expert parameter. default=%s" % config.rescueJobsFrequency)) # # Misc options # addOptionFn = addGroupFn("Toil Miscellaneous Options", "Miscellaneous Options") addOptionFn('--disableCaching', dest='disableCaching', type='bool', nargs='?', const=True, default=True, help='Disables caching in the file store. This flag must be set to use ' 'a batch system that does not support caching such as Grid Engine, Parasol, ' 'LSF, or Slurm') addOptionFn('--disableChaining', dest='disableChaining', action='store_true', default=False, help="Disables chaining of jobs (chaining uses one job's resource allocation " "for its successor job if possible).") addOptionFn("--disableJobStoreChecksumVerification", dest="disableJobStoreChecksumVerification", default=False, action="store_true", help=("Disables checksum verification for files transferred to/from the job store. " "Checksum verification is a safety check to ensure the data is not corrupted " "during transfer. Currently only supported for non-streaming AWS files.")) addOptionFn("--maxLogFileSize", dest="maxLogFileSize", default=None, help=("The maximum size of a job log file to keep (in bytes), log files " "larger than this will be truncated to the last X bytes. Setting " "this option to zero will prevent any truncation. Setting this " "option to a negative value will truncate from the beginning." "Default=%s" % bytes2human(config.maxLogFileSize))) addOptionFn("--writeLogs", dest="writeLogs", nargs='?', action='store', default=None, const=os.getcwd(), help="Write worker logs received by the leader into their own files at the " "specified path. Any non-empty standard output and error from failed batch " "system jobs will also be written into files at this path. " "The current working directory will be used if a path is " "not specified explicitly. Note: By default only the logs of failed jobs are " "returned to leader. Set log level to 'debug' or enable " "'--writeLogsFromAllJobs' to get logs back from successful jobs, and adjust " "'maxLogFileSize' to control the truncation limit for worker logs.") addOptionFn("--writeLogsGzip", dest="writeLogsGzip", nargs='?', action='store', default=None, const=os.getcwd(), help="Identical to --writeLogs except the logs files are gzipped on the leader.") addOptionFn("--writeLogsFromAllJobs", dest="writeLogsFromAllJobs", action='store_true', default=False, help="Whether to write logs from all jobs (including the successful ones) without " "necessarily setting the log level to 'debug'. Ensure that either --writeLogs " "or --writeLogsGzip is set if enabling this option.") addOptionFn("--realTimeLogging", dest="realTimeLogging", action="store_true", default=False, help="Enable real-time logging from workers to masters") addOptionFn("--sseKey", dest="sseKey", default=None, help="Path to file containing 32 character key to be used for server-side encryption on " "awsJobStore or googleJobStore. SSE will not be used if this flag is not passed.") addOptionFn("--setEnv", '-e', metavar='NAME=VALUE or NAME', dest="environment", default=[], action="append", help="Set an environment variable early on in the worker. If VALUE is omitted, " "it will be looked up in the current environment. Independently of this " "option, the worker will try to emulate the leader's environment before " "running a job, except for some variables known to vary across systems. " "Using this option, a variable can be injected into the worker process " "itself before it is started.") addOptionFn("--servicePollingInterval", dest="servicePollingInterval", default=None, help="Interval of time service jobs wait between polling for the existence" " of the keep-alive flag (defailt=%s)" % config.servicePollingInterval) addOptionFn('--forceDockerAppliance', dest='forceDockerAppliance', action='store_true', default=False, help='Disables sanity checking the existence of the docker image specified by ' 'TOIL_APPLIANCE_SELF, which Toil uses to provision mesos for autoscaling.') # # Debug options # addOptionFn = addGroupFn("toil debug options", "Debug options") addOptionFn("--debugWorker", default=False, action="store_true", help="Experimental no forking mode for local debugging." " Specifically, workers are not forked and" " stderr/stdout are not redirected to the log.") addOptionFn("--disableWorkerOutputCapture", default=False, action="store_true", help="Let worker output go to worker's standard" " out/error instead of per-job logs.") addOptionFn("--badWorker", dest="badWorker", default=None, help=( "For testing purposes randomly kill 'badWorker' proportion of jobs using SIGKILL, default=%s" % config.badWorker)) addOptionFn("--badWorkerFailInterval", dest="badWorkerFailInterval", default=None, help=("When killing the job pick uniformly within the interval from 0.0 to " "'badWorkerFailInterval' seconds after the worker starts, default=%s" % config.badWorkerFailInterval)) def addOptions(parser, config=Config()): """ Adds toil options to a parser object, either optparse or argparse. """ # Wrapper function that allows toil to be used with both the optparse and # argparse option parsing modules addLoggingOptions(parser) # This adds the logging stuff. if isinstance(parser, ArgumentParser): def addGroup(headingString, bodyString): return parser.add_argument_group(headingString, bodyString).add_argument parser.register("type", "bool", lambda v: v.lower() == "true") # Custom type for arg=True/False. _addOptions(addGroup, config) else: raise RuntimeError("Unanticipated class passed to addOptions(), %s. Expecting " "argparse.ArgumentParser" % parser.__class__) def getNodeID(): """ Return unique ID of the current node (host). Tries several methods until success. The returned ID should be identical across calls from different processes on the same node at least until the next OS reboot. The last resort method is uuid.getnode() that in some rare OS configurations may return a random ID each time it is called. However, this method should never be reached on a Linux system, because reading from /proc/sys/kernel/random/boot_id will be tried prior to that. If uuid.getnode() is reached, it will be called twice, and exception raised if the values are not identical. """ for idSourceFile in ["/var/lib/dbus/machine-id", "/proc/sys/kernel/random/boot_id"]: if os.path.exists(idSourceFile): try: with open(idSourceFile, "r") as inp: nodeID = inp.readline().strip() except EnvironmentError: logger.warning(("Exception when trying to read ID file {}. Will try next method to get node ID.").format(idSourceFile), exc_info=True) else: if len(nodeID.split()) == 1: logger.debug("Obtained node ID {} from file {}".format(nodeID, idSourceFile)) break else: logger.warning(("Node ID {} from file {} contains spaces. Will try next method to get node ID.").format(nodeID, idSourceFile)) else: nodeIDs = [] for i_call in range(2): nodeID = str(uuid.getnode()).strip() if len(nodeID.split()) == 1: nodeIDs.append(nodeID) else: logger.warning("Node ID {} from uuid.getnode() contains spaces".format(nodeID)) nodeID = "" if len(nodeIDs) == 2: if nodeIDs[0] == nodeIDs[1]: nodeID = nodeIDs[0] else: logger.warning( "Different node IDs {} received from repeated calls to uuid.getnode(). You should use " \ "another method to generate node ID.".format(nodeIDs)) logger.debug("Obtained node ID {} from uuid.getnode()".format(nodeID)) if not nodeID: logger.warning( "Failed to generate stable node ID, returning empty string. If you see this message with a " \ "work dir on a shared file system when using workers running on multiple nodes, you might experience " \ "cryptic job failures") return nodeID class Toil(object): """ A context manager that represents a Toil workflow, specifically the batch system, job store, and its configuration. """ def __init__(self, options): """ Initialize a Toil object from the given options. Note that this is very light-weight and that the bulk of the work is done when the context is entered. :param argparse.Namespace options: command line options specified by the user """ super(Toil, self).__init__() self.options = options self.config = None """ :type: toil.common.Config """ self._jobStore = None """ :type: toil.jobStores.abstractJobStore.AbstractJobStore """ self._batchSystem = None """ :type: toil.batchSystems.abstractBatchSystem.AbstractBatchSystem """ self._provisioner = None """ :type: toil.provisioners.abstractProvisioner.AbstractProvisioner """ self._jobCache = dict() self._inContextManager = False def __enter__(self): """ Derive configuration from the command line options, load the job store and, on restart, consolidate the derived configuration with the one from the previous invocation of the workflow. """ setLoggingFromOptions(self.options) config = Config() config.setOptions(self.options) jobStore = self.getJobStore(config.jobStore) if not config.restart: config.workflowAttemptNumber = 0 jobStore.initialize(config) else: jobStore.resume() # Merge configuration from job store with command line options config = jobStore.config config.setOptions(self.options) config.workflowAttemptNumber += 1 jobStore.writeConfig() self.config = config self._jobStore = jobStore self._inContextManager = True return self # noinspection PyUnusedLocal def __exit__(self, exc_type, exc_val, exc_tb): """ Clean up after a workflow invocation. Depending on the configuration, delete the job store. """ try: if (exc_type is not None and self.config.clean == "onError" or exc_type is None and self.config.clean == "onSuccess" or self.config.clean == "always"): try: self._jobStore.destroy() logger.info("Successfully deleted the job store: %s" % str(self._jobStore)) except: logger.info("Failed to delete the job store: %s" % str(self._jobStore)) raise except Exception as e: if exc_type is None: raise else: logger.exception('The following error was raised during clean up:') self._inContextManager = False return False # let exceptions through def start(self, rootJob): """ Invoke a Toil workflow with the given job as the root for an initial run. This method must be called in the body of a ``with Toil(...) as toil:`` statement. This method should not be called more than once for a workflow that has not finished. :param toil.job.Job rootJob: The root job of the workflow :return: The root job's return value """ self._assertContextManagerUsed() self.writePIDFile() if self.config.restart: raise ToilRestartException('A Toil workflow can only be started once. Use ' 'Toil.restart() to resume it.') self._batchSystem = self.createBatchSystem(self.config) self._setupAutoDeployment(rootJob.getUserScript()) try: self._setBatchSystemEnvVars() self._serialiseEnv() self._cacheAllJobs() # Pickle the promised return value of the root job, then write the pickled promise to # a shared file, where we can find and unpickle it at the end of the workflow. # Unpickling the promise will automatically substitute the promise for the actual # return value. with self._jobStore.writeSharedFileStream('rootJobReturnValue') as fH: rootJob.prepareForPromiseRegistration(self._jobStore) promise = rootJob.rv() pickle.dump(promise, fH, protocol=pickle.HIGHEST_PROTOCOL) # Setup the first wrapper and cache it rootJobGraph = rootJob._serialiseFirstJob(self._jobStore) self._cacheJob(rootJobGraph) self._setProvisioner() return self._runMainLoop(rootJobGraph) finally: self._shutdownBatchSystem() def restart(self): """ Restarts a workflow that has been interrupted. :return: The root job's return value """ self._assertContextManagerUsed() self.writePIDFile() if not self.config.restart: raise ToilRestartException('A Toil workflow must be initiated with Toil.start(), ' 'not restart().') from toil.job import JobException try: self._jobStore.loadRootJob() except JobException: logger.warning( 'Requested restart but the workflow has already been completed; allowing exports to rerun.') return self._jobStore.getRootJobReturnValue() self._batchSystem = self.createBatchSystem(self.config) self._setupAutoDeployment() try: self._setBatchSystemEnvVars() self._serialiseEnv() self._cacheAllJobs() self._setProvisioner() rootJobGraph = self._jobStore.clean(jobCache=self._jobCache) return self._runMainLoop(rootJobGraph) finally: self._shutdownBatchSystem() def _setProvisioner(self): if self.config.provisioner is None: self._provisioner = None else: self._provisioner = clusterFactory(provisioner=self.config.provisioner, clusterName=None, zone=None, # read from instance meta-data nodeStorage=self.config.nodeStorage, sseKey=self.config.sseKey) self._provisioner.setAutoscaledNodeTypes(self.config.nodeTypes) @classmethod def getJobStore(cls, locator): """ Create an instance of the concrete job store implementation that matches the given locator. :param str locator: The location of the job store to be represent by the instance :return: an instance of a concrete subclass of AbstractJobStore :rtype: toil.jobStores.abstractJobStore.AbstractJobStore """ name, rest = cls.parseLocator(locator) if name == 'file': from toil.jobStores.fileJobStore import FileJobStore return FileJobStore(rest) elif name == 'aws': from toil.jobStores.aws.jobStore import AWSJobStore return AWSJobStore(rest) elif name == 'google': from toil.jobStores.googleJobStore import GoogleJobStore return GoogleJobStore(rest) else: raise RuntimeError("Unknown job store implementation '%s'" % name) @staticmethod def parseLocator(locator): if locator[0] in '/.' or ':' not in locator: return 'file', locator else: try: name, rest = locator.split(':', 1) except ValueError: raise RuntimeError('Invalid job store locator syntax.') else: return name, rest @staticmethod def buildLocator(name, rest): assert ':' not in name return name + ':' + rest @classmethod def resumeJobStore(cls, locator): jobStore = cls.getJobStore(locator) jobStore.resume() return jobStore @staticmethod def createBatchSystem(config): """ Creates an instance of the batch system specified in the given config. :param toil.common.Config config: the current configuration :rtype: batchSystems.abstractBatchSystem.AbstractBatchSystem :return: an instance of a concrete subclass of AbstractBatchSystem """ kwargs = dict(config=config, maxCores=config.maxCores, maxMemory=config.maxMemory, maxDisk=config.maxDisk) from toil.batchSystems.registry import batchSystemFactoryFor try: factory = batchSystemFactoryFor(config.batchSystem) batchSystemClass = factory() except: raise RuntimeError('Unrecognised batch system: %s' % config.batchSystem) if not config.disableCaching and not batchSystemClass.supportsWorkerCleanup(): raise RuntimeError('%s currently does not support shared caching. Set the ' '--disableCaching flag if you want to ' 'use this batch system.' % config.batchSystem) logger.debug('Using the %s' % re.sub("([a-z])([A-Z])", "\g<1> \g<2>", batchSystemClass.__name__).lower()) return batchSystemClass(**kwargs) def _setupAutoDeployment(self, userScript=None): """ Determine the user script, save it to the job store and inject a reference to the saved copy into the batch system such that it can auto-deploy the resource on the worker nodes. :param toil.resource.ModuleDescriptor userScript: the module descriptor referencing the user script. If None, it will be looked up in the job store. """ if userScript is not None: # This branch is hit when a workflow is being started if userScript.belongsToToil: logger.debug('User script %s belongs to Toil. No need to auto-deploy it.', userScript) userScript = None else: if (self._batchSystem.supportsAutoDeployment() and not self.config.disableAutoDeployment): # Note that by saving the ModuleDescriptor, and not the Resource we allow for # redeploying a potentially modified user script on workflow restarts. with self._jobStore.writeSharedFileStream('userScript') as f: pickle.dump(userScript, f, protocol=pickle.HIGHEST_PROTOCOL) else: from toil.batchSystems.singleMachine import SingleMachineBatchSystem if not isinstance(self._batchSystem, SingleMachineBatchSystem): logger.warn('Batch system does not support auto-deployment. The user ' 'script %s will have to be present at the same location on ' 'every worker.', userScript) userScript = None else: # This branch is hit on restarts from toil.jobStores.abstractJobStore import NoSuchFileException try: with self._jobStore.readSharedFileStream('userScript') as f: userScript = safeUnpickleFromStream(f) except NoSuchFileException: logger.debug('User script neither set explicitly nor present in the job store.') userScript = None if userScript is None: logger.debug('No user script to auto-deploy.') else: logger.debug('Saving user script %s as a resource', userScript) userScriptResource = userScript.saveAsResourceTo(self._jobStore) logger.debug('Injecting user script %s into batch system.', userScriptResource) self._batchSystem.setUserScript(userScriptResource) def importFile(self, srcUrl, sharedFileName=None): """ Imports the file at the given URL into job store. See :func:`toil.jobStores.abstractJobStore.AbstractJobStore.importFile` for a full description """ self._assertContextManagerUsed() return self._jobStore.importFile(srcUrl, sharedFileName=sharedFileName) def exportFile(self, jobStoreFileID, dstUrl): """ Exports file to destination pointed at by the destination URL. See :func:`toil.jobStores.abstractJobStore.AbstractJobStore.exportFile` for a full description """ self._assertContextManagerUsed() self._jobStore.exportFile(jobStoreFileID, dstUrl) def _setBatchSystemEnvVars(self): """ Sets the environment variables required by the job store and those passed on command line. """ for envDict in (self._jobStore.getEnv(), self.config.environment): for k, v in iteritems(envDict): self._batchSystem.setEnv(k, v) def _serialiseEnv(self): """ Puts the environment in a globally accessible pickle file. """ # Dump out the environment of this process in the environment pickle file. with self._jobStore.writeSharedFileStream("environment.pickle") as fileHandle: pickle.dump(dict(os.environ), fileHandle, pickle.HIGHEST_PROTOCOL) logger.debug("Written the environment for the jobs to the environment file") def _cacheAllJobs(self): """ Downloads all jobs in the current job store into self.jobCache. """ logger.debug('Caching all jobs in job store') self._jobCache = {jobGraph.jobStoreID: jobGraph for jobGraph in self._jobStore.jobs()} logger.debug('{} jobs downloaded.'.format(len(self._jobCache))) def _cacheJob(self, job): """ Adds given job to current job cache. :param toil.jobGraph.JobGraph job: job to be added to current job cache """ self._jobCache[job.jobStoreID] = job @staticmethod def getWorkflowDir(workflowID, configWorkDir=None): """ Returns a path to the directory where worker directories and the cache will be located for this workflow. :param str workflowID: Unique identifier for the workflow :param str configWorkDir: Value passed to the program using the --workDir flag :return: Path to the workflow directory :rtype: str """ workDir = configWorkDir or os.getenv('TOIL_WORKDIR') or tempfile.gettempdir() if not os.path.exists(workDir): raise RuntimeError("The directory specified by --workDir or TOIL_WORKDIR (%s) does not " "exist." % workDir) # Create the workflow dir, make it unique to each host in case workDir is on a shared FS. # This prevents workers on different nodes from erasing each other's directories. workflowDir = os.path.join(workDir, 'toil-%s-%s' % (workflowID, getNodeID())) try: # Directory creation is atomic os.mkdir(workflowDir) except OSError as err: if err.errno != 17: # The directory exists if a previous worker set it up. raise else: logger.debug('Created the workflow directory at %s' % workflowDir) return workflowDir def _runMainLoop(self, rootJob): """ Runs the main loop with the given job. :param toil.job.Job rootJob: The root job for the workflow. :rtype: Any """ logProcessContext(self.config) with RealtimeLogger(self._batchSystem, level=self.options.logLevel if self.options.realTimeLogging else None): # FIXME: common should not import from leader from toil.leader import Leader return Leader(config=self.config, batchSystem=self._batchSystem, provisioner=self._provisioner, jobStore=self._jobStore, rootJob=rootJob, jobCache=self._jobCache).run() def _shutdownBatchSystem(self): """ Shuts down current batch system if it has been created. """ assert self._batchSystem is not None startTime = time.time() logger.debug('Shutting down batch system ...') self._batchSystem.shutdown() logger.debug('... finished shutting down the batch system in %s seconds.' % (time.time() - startTime)) def _assertContextManagerUsed(self): if not self._inContextManager: raise ToilContextManagerException() def writePIDFile(self): """ Write a the pid of this process to a file in the jobstore. Overwriting the current contents of pid.log is a feature, not a bug of this method. Other methods will rely on always having the most current pid available. So far there is no reason to store any old pids. """ with self._jobStore.writeSharedFileStream('pid.log') as f: f.write(str(os.getpid()).encode('utf-8')) class ToilRestartException(Exception): def __init__(self, message): super(ToilRestartException, self).__init__(message) class ToilContextManagerException(Exception): def __init__(self): super(ToilContextManagerException, self).__init__( 'This method cannot be called outside the "with Toil(...)" context manager.') class ToilMetrics: def __init__(self, provisioner=None): clusterName = 'none' region = 'us-west-2' if provisioner is not None: clusterName = provisioner.clusterName if provisioner._zone is not None: if provisioner.cloud == 'aws': # Remove AZ name region = zoneToRegion(provisioner._zone) else: region = provisioner._zone registry = lookupEnvVar(name='docker registry', envName='TOIL_DOCKER_REGISTRY', defaultValue=dockerRegistry) self.mtailImage = "%s/toil-mtail:%s" % (registry, dockerTag) self.grafanaImage = "%s/toil-grafana:%s" % (registry, dockerTag) self.prometheusImage = "%s/toil-prometheus:%s" % (registry, dockerTag) self.startDashboard(clusterName=clusterName, zone=region) # Always restart the mtail container, because metrics should start from scratch # for each workflow try: subprocess.check_call(["docker", "rm", "-f", "toil_mtail"]) except subprocess.CalledProcessError: pass try: self.mtailProc = subprocess.Popen(["docker", "run", "--rm", "--interactive", "--net=host", "--name", "toil_mtail", "-p", "3903:3903", self.mtailImage], stdin=subprocess.PIPE, stdout=subprocess.PIPE) except subprocess.CalledProcessError: logger.warn("Could not start toil metrics server.") self.mtailProc = None except KeyboardInterrupt: self.mtailProc.terminate() # On single machine, launch a node exporter instance to monitor CPU/RAM usage. # On AWS this is handled by the EC2 init script self.nodeExporterProc = None if not provisioner: try: self.nodeExporterProc = subprocess.Popen(["docker", "run", "--rm", "--net=host", "-p", "9100:9100", "-v", "/proc:/host/proc", "-v", "/sys:/host/sys", "-v", "/:/rootfs", "prom/node-exporter:0.12.0", "-collector.procfs", "/host/proc", "-collector.sysfs", "/host/sys", "-collector.filesystem.ignored-mount-points", "^/(sys|proc|dev|host|etc)($|/)"]) except subprocess.CalledProcessError: logger.warn( "Couldn't start node exporter, won't get RAM and CPU usage for dashboard.") self.nodeExporterProc = None except KeyboardInterrupt: self.nodeExporterProc.terminate() @staticmethod def _containerRunning(containerName): try: result = subprocess.check_output(["docker", "inspect", "-f", "'{{.State.Running}}'", containerName]).decode('utf-8') == "true" except subprocess.CalledProcessError: result = False return result def startDashboard(self, clusterName, zone): try: if not self._containerRunning("toil_prometheus"): try: subprocess.check_call(["docker", "rm", "-f", "toil_prometheus"]) except subprocess.CalledProcessError: pass subprocess.check_call(["docker", "run", "--name", "toil_prometheus", "--net=host", "-d", "-p", "9090:9090", self.prometheusImage, clusterName, zone]) if not self._containerRunning("toil_grafana"): try: subprocess.check_call(["docker", "rm", "-f", "toil_grafana"]) except subprocess.CalledProcessError: pass subprocess.check_call(["docker", "run", "--name", "toil_grafana", "-d", "-p=3000:3000", self.grafanaImage]) except subprocess.CalledProcessError: logger.warn("Could not start prometheus/grafana dashboard.") return # Add prometheus data source def requestPredicate(e): if isinstance(e, requests.exceptions.ConnectionError): return True return False try: for attempt in retry(delays=(0, 1, 1, 4, 16), predicate=requestPredicate): with attempt: requests.post('http://localhost:3000/api/datasources', auth=('admin', 'admin'), data='{"name":"DS_PROMETHEUS","type":"prometheus", \ "url":"http://localhost:9090", "access":"direct"}', headers={'content-type': 'application/json', "access": "direct"}) except requests.exceptions.ConnectionError: logger.debug( "Could not add data source to Grafana dashboard - no metrics will be displayed.") def log(self, message): if self.mtailProc: self.mtailProc.stdin.write(message + "\n") # Note: The mtail configuration (dashboard/mtail/toil.mtail) depends on these messages # remaining intact def logMissingJob(self): self.log("missing_job") def logClusterSize(self, nodeType, currentSize, desiredSize): self.log("current_size '%s' %i" % (nodeType, currentSize)) self.log("desired_size '%s' %i" % (nodeType, desiredSize)) def logQueueSize(self, queueSize): self.log("queue_size %i" % queueSize) def logIssuedJob(self, jobType): self.log("issued_job %s" % jobType) def logFailedJob(self, jobType): self.log("failed_job %s" % jobType) def logCompletedJob(self, jobType): self.log("completed_job %s" % jobType) def shutdown(self): if self.mtailProc: self.mtailProc.kill() if self.nodeExporterProc: self.nodeExporterProc.kill() # Nested functions can't have doctests so we have to make this global def parseSetEnv(l): """ Parses a list of strings of the form "NAME=VALUE" or just "NAME" into a dictionary. Strings of the latter from will result in dictionary entries whose value is None. :type l: list[str] :rtype: dict[str,str] >>> parseSetEnv([]) {} >>> parseSetEnv(['a']) {'a': None} >>> parseSetEnv(['a=']) {'a': ''} >>> parseSetEnv(['a=b']) {'a': 'b'} >>> parseSetEnv(['a=a', 'a=b']) {'a': 'b'} >>> parseSetEnv(['a=b', 'c=d']) {'a': 'b', 'c': 'd'} >>> parseSetEnv(['a=b=c']) {'a': 'b=c'} >>> parseSetEnv(['']) Traceback (most recent call last): ... ValueError: Empty name >>> parseSetEnv(['=1']) Traceback (most recent call last): ... ValueError: Empty name """ d = dict() for i in l: try: k, v = i.split('=', 1) except ValueError: k, v = i, None if not k: raise ValueError('Empty name') d[k] = v return d def iC(minValue, maxValue=sys.maxsize): # Returns function that checks if a given int is in the given half-open interval assert isinstance(minValue, int) and isinstance(maxValue, int) return lambda x: minValue <= x < maxValue def fC(minValue, maxValue=None): # Returns function that checks if a given float is in the given half-open interval assert isinstance(minValue, float) if maxValue is None: return lambda x: minValue <= x else: assert isinstance(maxValue, float) return lambda x: minValue <= x < maxValue def cacheDirName(workflowID): """ :return: Name of the cache directory. """ return 'cache-' + workflowID def getDirSizeRecursively(dirPath): """ This method will return the cumulative number of bytes occupied by the files on disk in the directory and its subdirectories. If the method is unable to access a file or directory (due to insufficient permissions, or due to the file or directory having been removed while this function was attempting to traverse it), the error will be handled internally, and a (possibly 0) lower bound on the size of the directory will be returned. The environment variable 'BLOCKSIZE'='512' is set instead of the much cleaner --block-size=1 because Apple can't handle it. :param str dirPath: A valid path to a directory or file. :return: Total size, in bytes, of the file or directory at dirPath. """ # du is often faster than using os.lstat(), sometimes significantly so. # The call: 'du -s /some/path' should give the number of 512-byte blocks # allocated with the environment variable: BLOCKSIZE='512' set, and we # multiply this by 512 to return the filesize in bytes. try: return int(subprocess.check_output(['du', '-s', dirPath], env=dict(os.environ, BLOCKSIZE='512')).decode('utf-8').split()[0]) * 512 except subprocess.CalledProcessError: # Something was inaccessible or went away return 0 def getFileSystemSize(dirPath): """ Return the free space, and total size of the file system hosting `dirPath`. :param str dirPath: A valid path to a directory. :return: free space and total size of file system :rtype: tuple """ assert os.path.exists(dirPath) diskStats = os.statvfs(dirPath) freeSpace = diskStats.f_frsize * diskStats.f_bavail diskSize = diskStats.f_frsize * diskStats.f_blocks return freeSpace, diskSize def safeUnpickleFromStream(stream): string = stream.read() return pickle.loads(string) toil-releases-3.24.0/src/toil/cwl/000077500000000000000000000000001362134276200167015ustar00rootroot00000000000000toil-releases-3.24.0/src/toil/cwl/__init__.py000066400000000000000000000000011362134276200210010ustar00rootroot00000000000000 toil-releases-3.24.0/src/toil/cwl/conftest.py000066400000000000000000000014111362134276200210750ustar00rootroot00000000000000# Copyright (C) 2015-2016 Regents of the University of California # # 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. # https://pytest.org/latest/example/pythoncollection.html collect_ignore = [] try: import cwltool except ImportError: collect_ignore.append("cwltoil.py") toil-releases-3.24.0/src/toil/cwl/cwltoil.py000077500000000000000000001601511362134276200207370ustar00rootroot00000000000000""" Implement support for Common Workflow Language (CWL) for Toil.""" # # Copyright (C) 2015 Curoverse, Inc # Copyright (C) 2016 UCSC Computational Genomics Lab # # 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. # For an overview of how this all works, see discussion in # docs/architecture.rst from builtins import range from builtins import object import abc import argparse import os import tempfile import json import sys import logging import copy import functools import shutil from typing import Text, Mapping, MutableSequence, MutableMapping import hashlib import uuid import datetime # Python 3 compatibility imports from six import iteritems, string_types from six.moves.urllib import parse as urlparse import six from schema_salad import validate from schema_salad.schema import Names import schema_salad.ref_resolver import cwltool.errors import cwltool.load_tool import cwltool.main import cwltool.workflow import cwltool.expression import cwltool.builder import cwltool.resolver import cwltool.stdfsaccess import cwltool.command_line_tool import cwltool.provenance from toil.jobStores.abstractJobStore import NoSuchJobStoreException from toil.fileStores import FileID from cwltool.loghandler import _logger as cwllogger from cwltool.loghandler import defaultStreamHandler from cwltool.pathmapper import (PathMapper, adjustDirObjs, adjustFileObjs, get_listing, MapperEnt, visit_class, normalizeFilesDirs) from cwltool.process import (shortname, fill_in_defaults, compute_checksums, add_sizes) from cwltool.secrets import SecretStore from cwltool.software_requirements import ( DependenciesConfiguration, get_container_from_software_requirements) from cwltool.utils import aslist from cwltool.mutation import MutationManager from toil.job import Job, Promise from toil.common import Config, Toil, addOptions from toil.version import baseVersion # Define internal jobs we should avoid submitting to batch systems and logging CWL_INTERNAL_JOBS = ("CWLJobWrapper", "CWLWorkflow", "CWLScatter", "CWLGather", "ResolveIndirect") # The job object passed into CWLJob and CWLWorkflow # is a dict mapping to tuple of (key, dict) # the final dict is derived by evaluating each # tuple looking up the key in the supplied dict. # # This is necessary because Toil jobs return a single value (a dict) # but CWL permits steps to have multiple output parameters that may # feed into multiple other steps. This transformation maps the key in the # output object to the correct key of the input object. class IndirectDict(dict): """Tag to indicate a dict is an IndirectDict that needs to resolved.""" pass @six.add_metaclass(abc.ABCMeta) class MergeInputs(object): """Base type for workflow step inputs that are connected to multiple upstream inputs that must be merged into a single array. """ def __init__(self, sources): self.sources = sources @abc.abstractmethod def resolve(self): """Resolves the inputs.""" class MergeInputsNested(MergeInputs): """Merge workflow step inputs that are connected to multiple upstream inputs based on the merge_nested behavior (as described in the CWL spec). """ def resolve(self): return [v[1][v[0]] for v in self.sources] class MergeInputsFlattened(MergeInputs): """Merge workflow step inputs that are connected to multiple upstream inputs based on the merge_flattened behavior (as described in the CWL spec). """ def resolve(self): result = [] for promise in self.sources: source = promise[1][promise[0]] if isinstance(source, MutableSequence): result.extend(source) else: result.append(source) return result class StepValueFrom(object): """A workflow step input which has a valueFrom expression attached to it, which is evaluated to produce the actual input object for the step. """ def __init__(self, expr, inner, req): self.expr = expr self.inner = inner self.req = req def do_eval(self, inputs, ctx): """Evalute ourselves.""" return cwltool.expression.do_eval( self.expr, inputs, self.req, None, None, {}, context=ctx) class DefaultWithSource(object): """A workflow step input that has both a source and a default value.""" def __init__(self, default, source): self.default = default self.source = source def resolve(self): """Determine the final input value.""" if self.source: if isinstance(self.source, tuple): result = self.source[1][0][self.source[0]] else: result = self.source[1][self.source[0]] if result: return result return self.default def _resolve_indirect_inner(maybe_idict): """Resolve the contents an indirect dictionary (containing promises) to produce a dictionary actual values, including merging multiple sources into a single input. """ if isinstance(maybe_idict, IndirectDict): result = {} metadata = {} for key, value in list(maybe_idict.items()): if isinstance(value, (MergeInputs, DefaultWithSource)): result[key] = value.resolve() else: if isinstance(value[1], tuple): if isinstance(value[1][0], tuple): result[key] = value[1][0][0].get(value[0]) metadata[key] = value[1][0][1] else: result[key] = value[1][0].get(value[0]) metadata[key] = value[1][1] else: result[key] = value[1].get(value[0]) return result, metadata return maybe_idict def resolve_indirect(pdict): """Resolve the contents an indirect dictionary (containing promises) and evaluate expressions to produce the dictionary of actual values. """ inner = IndirectDict() if isinstance(pdict, IndirectDict) else {} needs_eval = False if isinstance(pdict, tuple): #TODO should this return metadata return resolve_indirect(pdict[0]) for k, value in iteritems(pdict): if isinstance(value, StepValueFrom): inner[k] = value.inner needs_eval = True else: inner[k] = value res = _resolve_indirect_inner(inner) if needs_eval: ev = {} metadata = {} for k, value in iteritems(pdict): if isinstance(value, StepValueFrom): if isinstance(res, tuple): ev[k] = value.do_eval(res[0], res[0][k]) metadata[k] = res[1] else: ev[k] = value.do_eval(res, res[k]) else: if isinstance(res, tuple): ev[k] = res[0][k] metadata[k] = res[1] else: ev[k] = res[k] return ev, metadata return res def simplify_list(maybe_list): """Turn a length one list loaded by cwltool into a scalar. Anything else is passed as-is, by reference.""" if isinstance(maybe_list, MutableSequence): is_list = aslist(maybe_list) if len(is_list) == 1: return is_list[0] return maybe_list class ToilPathMapper(PathMapper): """ ToilPathMapper keeps track of a file's symbolic identifier (the Toil FileID), its local path on the host (the value returned by readGlobalFile) and the the location of the file inside the Docker container. """ def __init__(self, referenced_files, basedir, stagedir, separateDirs=True, get_file=None, stage_listing=False): self.get_file = get_file self.stage_listing = stage_listing super(ToilPathMapper, self).__init__( referenced_files, basedir, stagedir, separateDirs=separateDirs) def visit(self, obj, stagedir, basedir, copy=False, staged=False): # type: (Dict[Text, Any], Text, Text, bool, bool) -> None tgt = os.path.join(stagedir, obj["basename"]) if obj["location"] in self._pathmap: return if obj["class"] == "Directory": if obj["location"].startswith("file://"): resolved = schema_salad.ref_resolver.uri_file_path( obj["location"]) else: resolved = obj["location"] self._pathmap[obj["location"]] = MapperEnt( resolved, tgt, "WritableDirectory" if copy else "Directory", staged) if obj["location"].startswith("file://") \ and not self.stage_listing: staged = False self.visitlisting( obj.get("listing", []), tgt, basedir, copy=copy, staged=staged) elif obj["class"] == "File": loc = obj["location"] if "contents" in obj and obj["location"].startswith("_:"): self._pathmap[obj["location"]] = MapperEnt( obj["contents"], tgt, "CreateFile", staged) else: resolved = self.get_file(loc) if self.get_file else loc if resolved.startswith("file:"): resolved = schema_salad.ref_resolver.uri_file_path( resolved) self._pathmap[loc] = MapperEnt( resolved, tgt, "WritableFile" if copy else "File", staged) self.visitlisting(obj.get("secondaryFiles", []), stagedir, basedir, copy=copy, staged=staged) class ToilCommandLineTool(cwltool.command_line_tool.CommandLineTool): """Subclass the cwltool command line tool to provide the custom Toil.PathMapper. """ def make_path_mapper(self, reffiles, stagedir, runtimeContext, separateDirs): return ToilPathMapper( reffiles, runtimeContext.basedir, stagedir, separateDirs, runtimeContext.toil_get_file) def toil_make_tool(toolpath_object, loading_context): """Factory function passed to load_tool() which creates instances of the custom ToilCommandLineTool. """ if isinstance(toolpath_object, Mapping) \ and toolpath_object.get("class") == "CommandLineTool": return ToilCommandLineTool(toolpath_object, loading_context) return cwltool.workflow.default_make_tool(toolpath_object, loading_context) class ToilFsAccess(cwltool.stdfsaccess.StdFsAccess): """Custom filesystem access class which handles toil filestore references. """ def __init__(self, basedir, file_store=None): self.file_store = file_store super(ToilFsAccess, self).__init__(basedir) def _abs(self, path): if path.startswith("toilfs:"): return self.file_store.readGlobalFile(FileID.unpack(path[7:])) return super(ToilFsAccess, self)._abs(path) def toil_get_file(file_store, index, existing, file_store_id): """Get path to input file from Toil jobstore.""" if not file_store_id.startswith("toilfs:"): return file_store.jobStore.getPublicUrl(file_store.jobStore.importFile(file_store_id)) src_path = file_store.readGlobalFile(FileID.unpack(file_store_id[7:])) index[src_path] = file_store_id existing[file_store_id] = src_path return schema_salad.ref_resolver.file_uri(src_path) def write_file(writeFunc, index, existing, x): """Write a file into the Toil jobstore. 'existing' is a set of files retrieved as inputs from toil_get_file. This ensures they are mapped back as the same name if passed through. """ # Toil fileStore reference if x.startswith("toilfs:"): return x # File literal outputs with no path, we don't write these and will fail # with unsupportedRequirement when retrieving later with getFile elif x.startswith("_:"): return x else: x = existing.get(x, x) if x not in index: if not urlparse.urlparse(x).scheme: rp = os.path.realpath(x) else: rp = x try: index[x] = "toilfs:" + writeFunc(rp).pack() existing[index[x]] = x except Exception as e: cwllogger.error("Got exception '%s' while copying '%s'", e, x) raise return index[x] def uploadFile(uploadfunc, fileindex, existing, uf, skip_broken=False): """Update a file object so that the location is a reference to the toil file store, writing it to the file store if necessary. """ if uf["location"].startswith("toilfs:") or uf["location"].startswith("_:"): return if uf["location"] in fileindex: uf["location"] = fileindex[uf["location"]] return if not uf["location"] and uf["path"]: uf["location"] = schema_salad.ref_resolver.file_uri(uf["path"]) if uf["location"].startswith("file://") and not os.path.isfile(uf["location"][7:]): if skip_broken: return else: raise cwltool.errors.WorkflowException( "File is missing: %s" % uf["location"]) uf["location"] = write_file( uploadfunc, fileindex, existing, uf["location"]) def writeGlobalFileWrapper(file_store, fileuri): """Wrap writeGlobalFile to accepts file:// URIs""" return file_store.writeGlobalFile( schema_salad.ref_resolver.uri_file_path(fileuri)) class ResolveIndirect(Job): """A helper Job which accepts an indirect dict (containing promises) and produces a dictionary of actual values. """ def __init__(self, cwljob): super(ResolveIndirect, self).__init__() self.cwljob = cwljob def run(self, file_store): return resolve_indirect(self.cwljob) def toilStageFiles(file_store, cwljob, outdir, index, existing, export, destBucket=None): """Copy input files out of the global file store and update location and path.""" def _collectDirEntries(obj): # type: (Union[Dict[Text, Any], List[Dict[Text, Any]]]) -> Iterator[Dict[Text, Any]] if isinstance(obj, dict): if obj.get("class") in ("File", "Directory"): yield obj else: for sub_obj in obj.values(): for dir_entry in _collectDirEntries(sub_obj): yield dir_entry elif isinstance(obj, list): for sub_obj in obj: for dir_entry in _collectDirEntries(sub_obj): yield dir_entry jobfiles = list(_collectDirEntries(cwljob)) pm = ToilPathMapper( jobfiles, "", outdir, separateDirs=False, stage_listing=True) for _, p in pm.items(): if not p.staged: continue # Deal with bucket exports if destBucket: # Directories don't need to be created if we're exporting to # a bucket if p.type == "File": # Remove the staging directory from the filepath and # form the destination URL unstageTargetPath = p.target[len(outdir):] destUrl = '/'.join(s.strip('/') for s in [destBucket, unstageTargetPath]) file_store.exportFile(FileID.unpack(p.resolved[7:]), destUrl) continue if not os.path.exists(os.path.dirname(p.target)): os.makedirs(os.path.dirname(p.target), 0o0755) if p.type == "File": file_store.exportFile(FileID.unpack(p.resolved[7:]), "file://" + p.target) elif p.type == "Directory" and not os.path.exists(p.target): os.makedirs(p.target, 0o0755) elif p.type == "CreateFile": with open(p.target, "wb") as n: n.write(p.resolved.encode("utf-8")) def _check_adjust(f): f["location"] = schema_salad.ref_resolver.file_uri( pm.mapper(f["location"])[1]) if "contents" in f: del f["contents"] return f visit_class(cwljob, ("File", "Directory"), _check_adjust) class CWLJobWrapper(Job): """Wrap a CWL job that uses dynamic resources requirement. When executed, this creates a new child job which has the correct resource requirement set. """ def __init__(self, tool, cwljob, runtime_context): super(CWLJobWrapper, self).__init__( cores=1, memory=1024*1024, disk=8*1024) self.cwltool = remove_pickle_problems(tool) self.cwljob = cwljob self.runtime_context = runtime_context def run(self, file_store): resolved_cwljob = resolve_indirect(self.cwljob) metadata = {} if isinstance(resolved_cwljob, tuple): cwljob = resolved_cwljob[0] metadata = resolved_cwljob[1] else: cwljob = resolved_cwljob fill_in_defaults( self.cwltool.tool['inputs'], cwljob, self.runtime_context.make_fs_access( self.runtime_context.basedir or "")) realjob = CWLJob(self.cwltool, cwljob, self.runtime_context) self.addChild(realjob) return realjob.rv(), metadata class CWLJob(Job): """Execute a CWL tool using cwltool.executors.SingleJobExecutor""" def __init__(self, tool, cwljob, runtime_context, step_inputs=None): self.cwltool = remove_pickle_problems(tool) if runtime_context.builder: builder = runtime_context.builder else: builder = cwltool.builder.Builder( job=cwljob, files=[], bindings=[], schemaDefs={}, names=Names(), requirements=self.cwltool.requirements, hints=[], resources={}, mutation_manager=None, formatgraph=None, make_fs_access=runtime_context.make_fs_access, fs_access=runtime_context.make_fs_access(''), job_script_provider=None, timeout=runtime_context.eval_timeout, debug=False, js_console=False, force_docker_pull=False, loadListing=u'', outdir=u'', tmpdir=u'', stagedir=u'' ) req = tool.evalResources(builder, runtime_context) # pass the default of None if basecommand is empty unitName = self.cwltool.tool.get("baseCommand", None) if isinstance(unitName, (MutableSequence, tuple)): unitName = ' '.join(unitName) try: displayName = str(self.cwltool.tool['id']) except KeyError: displayName = None super(CWLJob, self).__init__( cores=req["cores"], memory=int(req["ram"]*(2**20)), disk=int((req["tmpdirSize"]*(2**20))+(req["outdirSize"]*(2**20))), unitName=unitName, displayName=displayName) self.cwljob = cwljob try: self.jobName = str(self.cwltool.tool['id']) except KeyError: # fall back to the Toil defined class name if the tool doesn't have # an identifier pass self.runtime_context = runtime_context self.step_inputs = step_inputs or self.cwltool.tool["inputs"] self.workdir = runtime_context.workdir def run(self, file_store): resolved_cwljob = resolve_indirect(self.cwljob) if isinstance(resolved_cwljob, tuple): cwljob, metadata = resolved_cwljob else: cwljob = resolved_cwljob metadata = {} fill_in_defaults( self.step_inputs, cwljob, self.runtime_context.make_fs_access("")) immobile_cwljob_dict = copy.deepcopy(cwljob) for inp_id in immobile_cwljob_dict.keys(): found = False for field in self.cwltool.inputs_record_schema['fields']: if field['name'] == inp_id: found = True if not found: cwljob.pop(inp_id) # Exports temporary directory for batch systems that reset TMPDIR os.environ["TMPDIR"] = os.path.realpath(file_store.getLocalTempDir()) outdir = os.path.join(file_store.getLocalTempDir(), "out") os.mkdir(outdir) # Just keep the temporary output prefix under the job's local temp dir, # next to the outdir. # # If we maintain our own system of nested temp directories, we won't # know when all the jobs using a higher-level directory are ready for # it to be deleted. The local temp dir, under Toil's workDir, will be # cleaned up by Toil. tmp_outdir_prefix = os.path.join(file_store.getLocalTempDir(), "tmp-out") index = {} existing = {} # Prepare the run instructions for cwltool runtime_context = self.runtime_context.copy() runtime_context.basedir = os.getcwd() runtime_context.outdir = outdir runtime_context.tmp_outdir_prefix = tmp_outdir_prefix runtime_context.tmpdir_prefix = file_store.getLocalTempDir() runtime_context.make_fs_access = functools.partial( ToilFsAccess, file_store=file_store) runtime_context.toil_get_file = functools.partial( toil_get_file, file_store, index, existing) process_uuid = uuid.uuid4() started_at = datetime.datetime.now() # Run the tool (output, status) = cwltool.executors.SingleJobExecutor().execute( self.cwltool, cwljob, runtime_context, cwllogger) ended_at = datetime.datetime.now() if status != "success": raise cwltool.errors.WorkflowException(status) adjustDirObjs(output, functools.partial( get_listing, cwltool.stdfsaccess.StdFsAccess(outdir), recursive=True)) adjustFileObjs(output, functools.partial( uploadFile, functools.partial(writeGlobalFileWrapper, file_store), index, existing)) metadata[process_uuid] = { 'started_at': started_at, 'ended_at': ended_at, 'job_order': cwljob, 'outputs': output, 'internal_name': self.jobName } return output, metadata def makeJob(tool, jobobj, step_inputs, runtime_context): """Create the correct Toil Job object for the CWL tool (workflow, job, or job wrapper for dynamic resource requirements.) """ if tool.tool["class"] == "Workflow": wfjob = CWLWorkflow(tool, jobobj, runtime_context) followOn = ResolveIndirect(wfjob.rv()) wfjob.addFollowOn(followOn) return (wfjob, followOn) else: # get_requirement resourceReq, _ = tool.get_requirement("ResourceRequirement") if resourceReq: for req in ("coresMin", "coresMax", "ramMin", "ramMax", "tmpdirMin", "tmpdirMax", "outdirMin", "outdirMax"): r = resourceReq.get(req) if isinstance(r, string_types) and ("$(" in r or "${" in r): # Found a dynamic resource requirement so use a job wrapper job = CWLJobWrapper(tool, jobobj, runtime_context) return (job, job) job = CWLJob(tool, jobobj, runtime_context) return (job, job) class CWLScatter(Job): """Implement workflow scatter step. When run, this creates a child job for each parameterization of the scatter. """ def __init__(self, step, cwljob, runtime_context): super(CWLScatter, self).__init__() self.step = step self.cwljob = cwljob self.runtime_context = runtime_context def flat_crossproduct_scatter(self, joborder, scatter_keys, outputs, postScatterEval): scatter_key = shortname(scatter_keys[0]) for n in range(0, len(joborder[scatter_key])): jo = copy.copy(joborder) jo[scatter_key] = joborder[scatter_key][n] if len(scatter_keys) == 1: jo = postScatterEval(jo) (subjob, followOn) = makeJob( self.step.embedded_tool, jo, None, self.runtime_context) self.addChild(subjob) outputs.append(followOn.rv()) else: self.flat_crossproduct_scatter( jo, scatter_keys[1:], outputs, postScatterEval) def nested_crossproduct_scatter(self, joborder, scatter_keys, postScatterEval): scatter_key = shortname(scatter_keys[0]) outputs = [] for n in range(0, len(joborder[scatter_key])): jo = copy.copy(joborder) jo[scatter_key] = joborder[scatter_key][n] if len(scatter_keys) == 1: jo = postScatterEval(jo) (subjob, followOn) = makeJob( self.step.embedded_tool, jo, None, self.runtime_context) self.addChild(subjob) outputs.append(followOn.rv()) else: outputs.append(self.nested_crossproduct_scatter( jo, scatter_keys[1:], postScatterEval)) return outputs def run(self, file_store): resolved_cwljob = resolve_indirect(self.cwljob) if isinstance(resolved_cwljob, tuple): cwljob, metadata = resolved_cwljob else: cwljob = resolved_cwljob if isinstance(self.step.tool["scatter"], string_types): scatter = [self.step.tool["scatter"]] else: scatter = self.step.tool["scatter"] scatterMethod = self.step.tool.get("scatterMethod", None) if len(scatter) == 1: scatterMethod = "dotproduct" outputs = [] valueFrom = {shortname(i["id"]): i["valueFrom"] for i in self.step.tool["inputs"] if "valueFrom" in i} def postScatterEval(io): shortio = {shortname(k): v for k, v in iteritems(io)} for k in valueFrom: io.setdefault(k, None) def valueFromFunc(k, v): if k in valueFrom: return cwltool.expression.do_eval( valueFrom[k], shortio, self.step.requirements, None, None, {}, context=v) else: return v return {k: valueFromFunc(k, v) for k, v in list(io.items())} if scatterMethod == "dotproduct": for i in range(0, len(cwljob[shortname(scatter[0])])): copyjob = copy.copy(cwljob) for sc in [shortname(x) for x in scatter]: copyjob[sc] = cwljob[sc][i] copyjob = postScatterEval(copyjob) (subjob, follow_on) = makeJob( self.step.embedded_tool, copyjob, None, self.runtime_context) self.addChild(subjob) outputs.append(follow_on.rv()) elif scatterMethod == "nested_crossproduct": outputs = self.nested_crossproduct_scatter( cwljob, scatter, postScatterEval) elif scatterMethod == "flat_crossproduct": self.flat_crossproduct_scatter( cwljob, scatter, outputs, postScatterEval) else: if scatterMethod: raise validate.ValidationException( "Unsupported complex scatter type '%s'" % scatterMethod) else: raise validate.ValidationException( "Must provide scatterMethod to scatter over multiple" " inputs.") return outputs, metadata class CWLGather(Job): """Follows on to a scatter. This gathers the outputs of each job in the scatter into an array for each output parameter. """ def __init__(self, step, outputs): super(CWLGather, self).__init__() self.step = step self.outputs = outputs def allkeys(self, obj, keys): if isinstance(obj, Mapping): for k in list(obj.keys()): keys.add(k) elif isinstance(obj, MutableSequence): for l in obj: self.allkeys(l, keys) def extract(self, obj, k): if isinstance(obj, Mapping): return obj.get(k) elif isinstance(obj, MutableSequence): cp = [] metadata = [] for l in obj: if isinstance(l, tuple): cp.append(self.extract(l[0], k)) metadata.append(self.extract(l[1], k)) else: result = self.extract(l, k) if isinstance(result, tuple): cp.append(result[0]) metadata.append(result[1]) else: cp.append(result) return cp, metadata elif isinstance(obj, tuple): return self.extract(obj[0], k) else: return [] def run(self, file_store): outobj = {} metadata = {} def sn(n): if isinstance(n, Mapping): return shortname(n["id"]) if isinstance(n, string_types): return shortname(n) for k in [sn(i) for i in self.step.tool["out"]]: result = self.extract(self.outputs, k) if isinstance(result, tuple): outobj[k], metadata[k] = result else: outobj[k] = result return outobj, metadata class SelfJob(object): """Fake job object to facilitate implementation of CWLWorkflow.run()""" def __init__(self, j, v): self.j = j self.v = v def rv(self): return self.v def addChild(self, c): return self.j.addChild(c) def hasChild(self, c): return self.j.hasChild(c) def remove_pickle_problems(obj): """doc_loader does not pickle correctly, causing Toil errors, remove from objects. """ if hasattr(obj, "doc_loader"): obj.doc_loader = None if hasattr(obj, "embedded_tool"): obj.embedded_tool = remove_pickle_problems(obj.embedded_tool) if hasattr(obj, "steps"): obj.steps = [remove_pickle_problems(s) for s in obj.steps] return obj def _link_merge_source(promises, in_out_obj, source_obj): to_merge = [(shortname(s), promises[s].rv()) for s in aslist(source_obj)] link_merge = in_out_obj.get("linkMerge", "merge_nested") if link_merge == "merge_nested": merged = MergeInputsNested(to_merge) elif link_merge == "merge_flattened": merged = MergeInputsFlattened(to_merge) else: raise validate.ValidationException( "Unsupported linkMerge '%s'" % link_merge) return merged class CWLWorkflow(Job): """Traverse a CWL workflow graph and create a Toil job graph with appropriate dependencies. """ def __init__(self, cwlwf, cwljob, runtime_context): super(CWLWorkflow, self).__init__() self.cwlwf = cwlwf self.cwljob = cwljob self.runtime_context = runtime_context self.cwlwf = remove_pickle_problems(self.cwlwf) def run(self, file_store): cwljob = resolve_indirect(self.cwljob) # `promises` dict # from: each parameter (workflow input or step output) # that may be used as a "source" for a step input workflow output # parameter # to: the job that will produce that value. promises = {} # `jobs` dict from step id to job that implements that step. jobs = {} for inp in self.cwlwf.tool["inputs"]: promises[inp["id"]] = SelfJob(self, cwljob) alloutputs_fufilled = False while not alloutputs_fufilled: # Iteratively go over the workflow steps, scheduling jobs as their # dependencies can be fufilled by upstream workflow inputs or # step outputs. Loop exits when the workflow outputs # are satisfied. alloutputs_fufilled = True for step in self.cwlwf.steps: if step.tool["id"] not in jobs: stepinputs_fufilled = True for inp in step.tool["inputs"]: if "source" in inp: for s in aslist(inp["source"]): if s not in promises: stepinputs_fufilled = False if stepinputs_fufilled: jobobj = {} for inp in step.tool["inputs"]: key = shortname(inp["id"]) if "source" in inp: inpSource = inp["source"] if inp.get("linkMerge") \ or len(aslist(inp["source"])) > 1: jobobj[key] =\ _link_merge_source(promises, inp, inpSource) else: if isinstance(inpSource, MutableSequence): # It seems that an input source with a # '#' in the name will be returned as a # CommentedSeq list by the yaml parser. inpSource = str(inpSource[0]) jobobj[key] = (shortname(inpSource), promises[inpSource].rv()) if "default" in inp: if key in jobobj: if isinstance(jobobj[key][1], Promise): d = copy.copy(inp["default"]) jobobj[key] = DefaultWithSource( d, jobobj[key]) else: if (isinstance(jobobj[key][1], tuple) and jobobj[key][1][0][jobobj[key][0]] is None) or (jobobj[key][1][ jobobj[key][0]] is None): d = copy.copy(inp["default"]) jobobj[key] = ( "default", {"default": d}) else: d = copy.copy(inp["default"]) jobobj[key] = ("default", {"default": d}) if "valueFrom" in inp \ and "scatter" not in step.tool: if key in jobobj: jobobj[key] = StepValueFrom( inp["valueFrom"], jobobj[key], self.cwlwf.requirements) else: jobobj[key] = StepValueFrom( inp["valueFrom"], ( "None", {"None": None}), self.cwlwf.requirements) if "scatter" in step.tool: wfjob = CWLScatter(step, IndirectDict(jobobj), self.runtime_context) followOn = CWLGather(step, wfjob.rv()) wfjob.addFollowOn(followOn) else: (wfjob, followOn) = makeJob( step.embedded_tool, IndirectDict(jobobj), step.tool["inputs"], self.runtime_context) jobs[step.tool["id"]] = followOn connected = False for inp in step.tool["inputs"]: for s in aslist(inp.get("source", [])): if (isinstance( promises[s], (CWLJobWrapper, CWLGather) ) and not promises[s].hasFollowOn(wfjob)): promises[s].addFollowOn(wfjob) connected = True if (not isinstance( promises[s], (CWLJobWrapper, CWLGather) ) and not promises[s].hasChild(wfjob)): promises[s].addChild(wfjob) connected = True if not connected: # the workflow step has default inputs only & isn't # connected to other jobs, so add it as child of # this workflow. self.addChild(wfjob) for out in step.tool["outputs"]: promises[out["id"]] = followOn for inp in step.tool["inputs"]: for source in aslist(inp.get("source", [])): if source not in promises: alloutputs_fufilled = False # may need a test for out in self.cwlwf.tool["outputs"]: if "source" in out: if out["source"] not in promises: alloutputs_fufilled = False outobj = {} for out in self.cwlwf.tool["outputs"]: key = shortname(out["id"]) if out.get("linkMerge") or len(aslist(out["outputSource"])) > 1: outobj[key] = _link_merge_source(promises, out, out["outputSource"]) else: # A CommentedSeq of length one still appears here rarely - # not clear why from the CWL code. When it does, it breaks # the execution by causing a non-hashable type exception. # We simplify the list into its first (and only) element. src = simplify_list(out["outputSource"]) outobj[key] = (shortname(src), promises[src].rv()) return IndirectDict(outobj) cwltool.process.supportedProcessRequirements = ( "DockerRequirement", "ExpressionEngineRequirement", "InlineJavascriptRequirement", "InitialWorkDirRequirement", "SchemaDefRequirement", "EnvVarRequirement", "CreateFileRequirement", "SubworkflowFeatureRequirement", "ScatterFeatureRequirement", "ShellCommandRequirement", "MultipleInputFeatureRequirement", "StepInputExpressionRequirement", "ResourceRequirement") def visitSteps(t, op): if isinstance(t, cwltool.workflow.Workflow): for s in t.steps: op(s.tool) visitSteps(s.embedded_tool, op) def main(args=None, stdout=sys.stdout): """Main method for toil-cwl-runner.""" cwllogger.removeHandler(defaultStreamHandler) config = Config() config.cwl = True parser = argparse.ArgumentParser() addOptions(parser, config) parser.add_argument("cwltool", type=str) parser.add_argument("cwljob", nargs=argparse.REMAINDER) # Will override the "jobStore" positional argument, enables # user to select jobStore or get a default from logic one below. parser.add_argument("--jobStore", type=str) parser.add_argument("--not-strict", action="store_true") parser.add_argument("--quiet", dest="logLevel", action="store_const", const="ERROR") parser.add_argument("--basedir", type=str) parser.add_argument("--outdir", type=str, default=os.getcwd()) parser.add_argument("--version", action='version', version=baseVersion) dockergroup = parser.add_mutually_exclusive_group() dockergroup.add_argument( "--user-space-docker-cmd", help="(Linux/OS X only) Specify a user space docker command (like " "udocker or dx-docker) that will be used to call 'pull' and 'run'") dockergroup.add_argument( "--singularity", action="store_true", default=False, help="[experimental] Use Singularity runtime for running containers. " "Requires Singularity v2.6.1+ and Linux with kernel version v3.18+ or " "with overlayfs support backported.") dockergroup.add_argument( "--no-container", action="store_true", help="Do not execute jobs in a " "Docker container, even when `DockerRequirement` " "is specified under `hints`.") dockergroup.add_argument( "--leave-container", action="store_false", default=True, help="Do not delete Docker container used by jobs after they exit", dest="rm_container") parser.add_argument( "--preserve-environment", type=str, nargs='+', help="Preserve specified environment variables when running" " CommandLineTools", metavar=("VAR1 VAR2"), default=("PATH",), dest="preserve_environment") parser.add_argument( "--preserve-entire-environment", action="store_true", help="Preserve all environment variable when running " "CommandLineTools.", default=False, dest="preserve_entire_environment") parser.add_argument( "--destBucket", type=str, help="Specify a cloud bucket endpoint for output files.") parser.add_argument( "--beta-dependency-resolvers-configuration", default=None) parser.add_argument( "--beta-dependencies-directory", default=None) parser.add_argument( "--beta-use-biocontainers", default=None, action="store_true") parser.add_argument( "--beta-conda-dependencies", default=None, action="store_true") parser.add_argument( "--tmpdir-prefix", type=Text, help="Path prefix for temporary directories", default="tmp") parser.add_argument( "--tmp-outdir-prefix", type=Text, help="Path prefix for intermediate output directories", default="tmp") parser.add_argument( "--force-docker-pull", action="store_true", default=False, dest="force_docker_pull", help="Pull latest docker image even if it is locally present") parser.add_argument( "--no-match-user", action="store_true", default=False, help="Disable passing the current uid to `docker run --user`") parser.add_argument( "--no-read-only", action="store_true", default=False, help="Do not set root directory in the container as read-only") parser.add_argument( "--strict-memory-limit", action="store_true", help="When running with " "software containers and the Docker engine, pass either the " "calculated memory allocation from ResourceRequirements or the " "default of 1 gigabyte to Docker's --memory option.") parser.add_argument( "--relax-path-checks", action="store_true", default=False, help="Relax requirements on path names to permit " "spaces and hash characters.", dest="relax_path_checks") parser.add_argument("--default-container", help="Specify a default docker container that will be " "used if the workflow fails to specify one.") if args is None: args = sys.argv[1:] provgroup = parser.add_argument_group("Options for recording provenance " "information of the execution") provgroup.add_argument("--provenance", help="Save provenance to specified folder as a " "Research Object that captures and aggregates " "workflow execution and data products.", type=Text) provgroup.add_argument("--enable-user-provenance", default=False, action="store_true", help="Record user account info as part of provenance.", dest="user_provenance") provgroup.add_argument("--disable-user-provenance", default=False, action="store_false", help="Do not record user account info in provenance.", dest="user_provenance") provgroup.add_argument("--enable-host-provenance", default=False, action="store_true", help="Record host info as part of provenance.", dest="host_provenance") provgroup.add_argument("--disable-host-provenance", default=False, action="store_false", help="Do not record host info in provenance.", dest="host_provenance") provgroup.add_argument( "--orcid", help="Record user ORCID identifier as part of " "provenance, e.g. https://orcid.org/0000-0002-1825-0097 " "or 0000-0002-1825-0097. Alternatively the environment variable " "ORCID may be set.", dest="orcid", default=os.environ.get("ORCID", ''), type=Text) provgroup.add_argument( "--full-name", help="Record full name of user as part of provenance, " "e.g. Josiah Carberry. You may need to use shell quotes to preserve " "spaces. Alternatively the environment variable CWL_FULL_NAME may " "be set.", dest="cwl_full_name", default=os.environ.get("CWL_FULL_NAME", ''), type=Text) # Problem: we want to keep our job store somewhere auto-generated based on # our options, unless overridden by... an option. So we will need to parse # options twice, because we need to feed the parser the job store. # Propose a local workdir, probably under /tmp. # mkdtemp actually creates the directory, but # toil requires that the directory not exist, # since it is going to be our jobstore, # so make it and delete it and allow # toil to create it again (!) workdir = tempfile.mkdtemp() os.rmdir(workdir) # we use workdir as default default jobStore: options = parser.parse_args([workdir] + args) # if tmpdir_prefix is not the default value, set workDir if unset, and move # workdir and the job store under it if options.tmpdir_prefix != 'tmp': workdir = tempfile.mkdtemp(dir=options.tmpdir_prefix) os.rmdir(workdir) # Re-parse arguments with the new default jobstore under the temp dir. # It still might be overridden by a --jobStore option options = parser.parse_args([workdir] + args) if options.workDir is None: # We need to override workDir because by default Toil will pick # somewhere under the system temp directory if unset, ignoring # --tmpdir-prefix. # # If set, workDir needs to exist, so we directly use the prefix options.workDir = options.tmpdir_prefix if options.provisioner and not options.jobStore: raise NoSuchJobStoreException( 'Please specify a jobstore with the --jobStore option when ' 'specifying a provisioner.') use_container = not options.no_container if options.logLevel: cwllogger.setLevel(options.logLevel) outdir = os.path.abspath(options.outdir) tmp_outdir_prefix = os.path.abspath(options.tmp_outdir_prefix) fileindex = {} existing = {} conf_file = getattr(options, "beta_dependency_resolvers_configuration", None) use_conda_dependencies = getattr(options, "beta_conda_dependencies", None) job_script_provider = None if conf_file or use_conda_dependencies: dependencies_configuration = DependenciesConfiguration(options) job_script_provider = dependencies_configuration options.default_container = None runtime_context = cwltool.context.RuntimeContext(vars(options)) runtime_context.find_default_container = functools.partial( find_default_container, options) runtime_context.workdir = workdir runtime_context.move_outputs = "leave" runtime_context.rm_tmpdir = False loading_context = cwltool.context.LoadingContext(vars(options)) if options.provenance: research_obj = cwltool.provenance.ResearchObject( temp_prefix_ro=options.tmp_outdir_prefix, orcid=options.orcid, full_name=options.cwl_full_name, fsaccess=runtime_context.make_fs_access('')) runtime_context.research_obj = research_obj with Toil(options) as toil: if options.restart: outobj = toil.restart() else: loading_context.hints = [{ "class": "ResourceRequirement", "coresMin": toil.config.defaultCores, "ramMin": toil.config.defaultMemory / (2**20), "outdirMin": toil.config.defaultDisk / (2**20), "tmpdirMin": 0 }] loading_context.construct_tool_object = toil_make_tool loading_context.resolver = cwltool.resolver.tool_resolver loading_context.strict = not options.not_strict options.workflow = options.cwltool options.job_order = options.cwljob uri, tool_file_uri = cwltool.load_tool.resolve_tool_uri( options.cwltool, loading_context.resolver, loading_context.fetcher_constructor) options.tool_help = None options.debug = options.logLevel == "DEBUG" job_order_object, options.basedir, jobloader = \ cwltool.main.load_job_order( options, sys.stdin, loading_context.fetcher_constructor, loading_context.overrides_list, tool_file_uri) loading_context, workflowobj, uri = cwltool.load_tool.fetch_document(uri, loading_context) loading_context, uri = cwltool.load_tool.resolve_and_validate_document(loading_context, workflowobj, uri) loading_context.overrides_list.extend(loading_context.metadata.get("cwltool:overrides", [])) document_loader = loading_context.loader metadata = loading_context.metadata processobj = document_loader.idx if options.provenance and runtime_context.research_obj: processobj['id'] = metadata['id'] processobj, metadata = loading_context.loader.resolve_ref(uri) runtime_context.research_obj.packed_workflow( cwltool.main.print_pack(document_loader, processobj, uri, metadata)) loading_context.overrides_list.extend( metadata.get("cwltool:overrides", [])) try: tool = cwltool.load_tool.make_tool(uri, loading_context) except cwltool.process.UnsupportedRequirement as err: logging.error(err) return 33 runtime_context.secret_store = SecretStore() initialized_job_order = cwltool.main.init_job_order( job_order_object, options, tool, jobloader, sys.stdout, secret_store=runtime_context.secret_store) fs_access = cwltool.stdfsaccess.StdFsAccess(options.basedir) fill_in_defaults( tool.tool["inputs"], initialized_job_order, fs_access) def path_to_loc(obj): if "location" not in obj and "path" in obj: obj["location"] = obj["path"] del obj["path"] def import_files(tool): visit_class(tool, ("File", "Directory"), path_to_loc) visit_class(tool, ("File", ), functools.partial( add_sizes, fs_access)) normalizeFilesDirs(tool) adjustDirObjs(tool, functools.partial( get_listing, fs_access, recursive=True)) adjustFileObjs(tool, functools.partial( uploadFile, toil.importFile, fileindex, existing, skip_broken=True)) tool.visit(import_files) for inp in tool.tool["inputs"]: def set_secondary(fileobj): if isinstance(fileobj, Mapping) and fileobj.get("class") == "File": if "secondaryFiles" not in fileobj: fileobj["secondaryFiles"] = [{"location": cwltool.builder.substitute(fileobj["location"], sf["pattern"]), "class": "File"} for sf in inp["secondaryFiles"]] if isinstance(fileobj, MutableSequence): for entry in fileobj: set_secondary(entry) if shortname(inp["id"]) in initialized_job_order and inp.get("secondaryFiles"): set_secondary(initialized_job_order[shortname(inp["id"])]) import_files(initialized_job_order) visitSteps(tool, import_files) try: runtime_context.use_container = use_container runtime_context.tmp_outdir_prefix = os.path.realpath( tmp_outdir_prefix) runtime_context.job_script_provider = job_script_provider runtime_context.force_docker_pull = options.force_docker_pull runtime_context.no_match_user = options.no_match_user runtime_context.no_read_only = options.no_read_only (wf1, _) = makeJob(tool, {}, None, runtime_context) except cwltool.process.UnsupportedRequirement as err: logging.error(err) return 33 wf1.cwljob = initialized_job_order result = toil.start(wf1) if isinstance(result, tuple): outobj, metadata = result else: outobj = result outobj = resolve_indirect(outobj) if isinstance(outobj, tuple): outobj, metadata = outobj # Stage files. Specify destination bucket if specified in CLI # options. If destination bucket not passed in, # options.destBucket's value will be None. toilStageFiles( toil, outobj, outdir, fileindex, existing, export=True, destBucket=options.destBucket) if runtime_context.research_obj is not None: runtime_context.research_obj.create_job(outobj, None, True) def remove_at_id(doc): if isinstance(doc, MutableMapping): for key in list(doc.keys()): if key == '@id': del doc[key] else: value = doc[key] if isinstance(value, MutableMapping): remove_at_id(value) if isinstance(value, MutableSequence): for entry in value: if isinstance(value, MutableMapping): remove_at_id(entry) remove_at_id(outobj) visit_class(outobj, ("File",), functools.partial( add_sizes, runtime_context.make_fs_access(''))) prov_dependencies = cwltool.main.prov_deps(workflowobj, document_loader, uri) runtime_context.research_obj.generate_snapshot(prov_dependencies) runtime_context.research_obj.close(options.provenance) if not options.destBucket: visit_class(outobj, ("File",), functools.partial( compute_checksums, cwltool.stdfsaccess.StdFsAccess(""))) visit_class(outobj, ("File", ), MutationManager().unset_generation) stdout.write(json.dumps(outobj, indent=4)) return 0 def find_default_container(args, builder): default_container = None if args.default_container: default_container = args.default_container elif args.beta_use_biocontainers: default_container = get_container_from_software_requirements( args, builder) return default_container toil-releases-3.24.0/src/toil/deferred.py000066400000000000000000000330021362134276200202440ustar00rootroot00000000000000# Copyright (C) 2015-2019 Regents of the University of California # # 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. from __future__ import absolute_import, print_function from future import standard_library standard_library.install_aliases() from builtins import map from builtins import str from builtins import range from builtins import object from collections import namedtuple from contextlib import contextmanager import dill import fcntl import logging import os import shutil import tempfile from toil.lib.misc import mkdir_p from toil.realtimeLogger import RealtimeLogger from toil.resource import ModuleDescriptor logger = logging.getLogger(__name__) class DeferredFunction(namedtuple('DeferredFunction', 'function args kwargs name module')): """ >>> df = DeferredFunction.create(defaultdict, None, {'x':1}, y=2) >>> df DeferredFunction(defaultdict, ...) >>> df.invoke() == defaultdict(None, x=1, y=2) True """ @classmethod def create(cls, function, *args, **kwargs): """ Capture the given callable and arguments as an instance of this class. :param callable function: The deferred action to take in the form of a function :param tuple args: Non-keyword arguments to the function :param dict kwargs: Keyword arguments to the function """ # The general principle is to deserialize as late as possible, i.e. when the function is # to be invoked, as that will avoid redundantly deserializing deferred functions for # concurrently running jobs when the cache state is loaded from disk. By implication we # should serialize as early as possible. We need to serialize the function as well as its # arguments. return cls(*list(map(dill.dumps, (function, args, kwargs))), name=function.__name__, module=ModuleDescriptor.forModule(function.__module__).globalize()) def invoke(self): """ Invoke the captured function with the captured arguments. """ logger.debug('Running deferred function %s.', self) self.module.makeLoadable() function, args, kwargs = list(map(dill.loads, (self.function, self.args, self.kwargs))) return function(*args, **kwargs) def __str__(self): return '%s(%s, ...)' % (self.__class__.__name__, self.name) __repr__ = __str__ class DeferredFunctionManager(object): """ Implements a deferred function system. Each Toil worker will have an instance of this class. When a job is executed, it will happen inside a context manager from this class. If the job registers any "deferred" functions, they will be executed when the context manager is exited. If the Python process terminates before properly exiting the context manager and running the deferred functions, and some other worker process enters or exits the per-job context manager of this class at a later time, or when the DeferredFunctionManager is shut down on the worker, the earlier job's deferred functions will be picked up and run. Note that deferred function cleanup is on a best-effort basis, and deferred functions may end up getting executed multiple times. Internally, deferred functions are serialized into files in the given directory, which are locked by the owning process. If that process dies, other processes can detect that the files are able to be locked, and will take them over. """ # Define what directory the state directory should actaully be, under the base STATE_DIR_STEM = 'deferred' # Have a prefix to distinguish our deferred functions from e.g. NFS # "silly rename" files, or other garbage that people put in our # directory PREFIX = 'func' # And a suffix to distingusidh in-progress from completed files WIP_SUFFIX = '.tmp' def __init__(self, stateDirBase): """ Create a new DeferredFunctionManager, sharing state with other instances in other processes using the given shared state directory. Uses a fixed path under that directory for state files. Creates it if not present. Note that if the current umask lets other people create files in that new directory, we are going to execute their code! The created directory will be left behind, because we never know if another worker will come along later on this node. """ # Work out where state files live self.stateDir = os.path.join(stateDirBase, self.STATE_DIR_STEM) mkdir_p(self.stateDir) # We need to get a state file, locked by us and not somebody scanning for abandoned state files. # So we suffix not-yet-ready ones with our suffix self.stateFD, self.stateFileName = tempfile.mkstemp(dir=self.stateDir, prefix=self.PREFIX, suffix=self.WIP_SUFFIX) # Lock the state file. The lock will automatically go away if our process does. try: fcntl.lockf(self.stateFD, fcntl.LOCK_EX | fcntl.LOCK_NB) except IOError as e: # Someone else might have locked it even though they should not have. raise RuntimeError("Could not lock deferred function state file %s: %s" % (self.stateFileName, str(e))) # Rename it to remove the suffix os.rename(self.stateFileName, self.stateFileName[:-len(self.WIP_SUFFIX)]) self.stateFileName = self.stateFileName[:-len(self.WIP_SUFFIX)] # Wrap the FD in a Python file object, which we will use to actually use it. # Problem: we can't be readable and writable at the same time. So we need two file objects. self.stateFileOut = os.fdopen(self.stateFD, 'wb') self.stateFileIn = open(self.stateFileName, 'rb') logger.debug("Running for file %s" % self.stateFileName) def __del__(self): """ Clean up our state on disk. We assume that the deferred functions we manage have all been executed, and none are currently recorded. """ logger.debug("Deleting %s" % self.stateFileName) # Hide the state from other processes os.unlink(self.stateFileName) # Unlock it fcntl.lockf(self.stateFD, fcntl.LOCK_UN) # Don't bother with close, destroying will close and it seems to maybe # have been GC'd already anyway. @contextmanager def open(self): """ Yields a single-argument function that allows for deferred functions of type :class:`toil.DeferredFunction` to be registered. We use this design so deferred functions can be registered only inside this context manager. Not thread safe. """ # Clean up other jobs before we run, so our job has a nice clean node self._runOrphanedDeferredFunctions() try: def defer(deferredFunction): # Just serialize defered functions one after the other. # If serializing later ones fails, eariler ones will still be intact. # We trust dill to protect sufficiently against partial reads later. logger.debug("Deferring function %s" % repr(deferredFunction)) dill.dump(deferredFunction, self.stateFileOut) # Flush before returning so we can guarantee the write is on disk if we die. self.stateFileOut.flush() logger.debug("Running job") yield defer finally: self._runOwnDeferredFunctions() self._runOrphanedDeferredFunctions() @classmethod def cleanupWorker(cls, stateDirBase): """ Called by the batch system when it shuts down the node, after all workers are done, if the batch system supports worker cleanup. Checks once more for orphaned deferred functions and runs them. """ logger.debug("Cleaning up deferred functions system") # Open up cleaner = cls(stateDirBase) # Do the final round of cleanup cleaner._runOrphanedDeferredFunctions() # Close all the files in there. del cleaner # Clean up the directory we have been using. # It might not be empty if .tmp files escaped: nobody can tell they # aren't just waiting to be locked. shutil.rmtree(os.path.join(stateDirBase, cls.STATE_DIR_STEM)) def _runDeferredFunction(self, deferredFunction): """ Run a deferred function (either our own or someone else's). Reports an error if it fails. """ try: deferredFunction.invoke() except Exception as err: # Report this in real time, if enabled. Otherwise the only place it ends up is the worker log. RealtimeLogger.error("Failed to run deferred function %s: %s", repr(deferredFunction), str(err)) except: RealtimeLogger.error("Failed to run deferred function %s", repr(deferredFunction)) def _runAllDeferredFunctions(self, fileObj): """ Read and run deferred functions until EOF from the given open file. """ try: while True: # Load each function deferredFunction = dill.load(fileObj) logger.debug("Loaded deferred function %s" % repr(deferredFunction)) # Run it self._runDeferredFunction(deferredFunction) except EOFError as e: # This is expected and means we read all the complete entries. logger.debug("Out of deferred functions!") pass def _runOwnDeferredFunctions(self): """ Run all of the deferred functions that were registered. """ logger.debug("Running own deferred functions") # Seek back to the start of our file self.stateFileIn.seek(0) # Read and run each function in turn self._runAllDeferredFunctions(self.stateFileIn) # Go back to the beginning and truncate, to prepare for a new set of deferred functions. self.stateFileIn.seek(0) self.stateFileOut.seek(0) self.stateFileOut.truncate() def _runOrphanedDeferredFunctions(self): """ Scan for files that aren't locked by anybody and run all their deferred functions, then clean them up. """ logger.debug("Running orphaned deferred functions") # Track whether we found any work to do. # We will keep looping as long as there is work to do. foundFiles = True while foundFiles: # Clear this out unless we find some work we can get ahold of. foundFiles = False for filename in os.listdir(self.stateDir): # Scan the whole directory for work nobody else owns. if filename.endswith(self.WIP_SUFFIX): # Skip files from instances that are still being set up continue if not filename.startswith(self.PREFIX): # Skip NFS deleted files and any other contaminants continue fullFilename = os.path.join(self.stateDir, filename) if fullFilename == self.stateFileName: # We would be able to lock our own file, and it would appear unowned. # So skip it. continue fd = None try: # Try locking each file. # The file may have vanished since we saw it, so we have to ignore failures. # We open in read write mode because the fcntl docs say you # might only be able to exclusively lock files opened for # writing. fd = os.open(fullFilename, os.O_RDWR) except OSError: # Maybe the file vanished. Try the next one continue try: fcntl.lockf(fd, fcntl.LOCK_EX | fcntl.LOCK_NB) except IOError: # File is still locked by someone else. # Look at the next file instead continue logger.debug("Locked file %s" % fullFilename) # File is locked successfully. Our problem now. foundFiles = True # Actually run all the stored deferred functions fileObj = os.fdopen(fd, 'rb') self._runAllDeferredFunctions(fileObj) try: # Ok we are done with this file. Get rid of it so nobody else does it. os.unlink(fullFilename) except OSError: # Maybe the file vanished. pass # Unlock it fcntl.lockf(fd, fcntl.LOCK_UN) # Now close it. This closes the backing file descriptor. See # fileObj.close() toil-releases-3.24.0/src/toil/fileStores/000077500000000000000000000000001362134276200202335ustar00rootroot00000000000000toil-releases-3.24.0/src/toil/fileStores/__init__.py000066400000000000000000000042711362134276200223500ustar00rootroot00000000000000# Copyright (C) 2015-2019 Regents of the University of California # # 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. from __future__ import absolute_import import os __all__ = ['fileStore', 'nonCachingFileStore', 'cachingFileStore'] class FileID(str): """ A small wrapper around Python's builtin string class. It is used to represent a file's ID in the file store, and has a size attribute that is the file's size in bytes. This object is returned by importFile and writeGlobalFile. Calls into the file store can use bare strings; size will be queried from the job store if unavailable in the ID. """ def __new__(cls, fileStoreID, *args): return super(FileID, cls).__new__(cls, fileStoreID) def __init__(self, fileStoreID, size): # Don't pass an argument to parent class's __init__. # In Python 3 we can have super(FileID, self) hand us object's __init__ which chokes on any arguments. super(FileID, self).__init__() self.size = size def pack(self): """ Pack the FileID into a string so it can be passed through external code. """ return '{}:{}'.format(self.size, self) @classmethod def forPath(cls, fileStoreID, filePath): return cls(fileStoreID, os.stat(filePath).st_size) @classmethod def unpack(cls, packedFileStoreID): """ Unpack the result of pack() into a FileID object. """ # Find the separating character (first instance) sepPos = packedFileStoreID.find(':') # Break up the packed value size = int(packedFileStoreID[:sepPos]) value = packedFileStoreID[(sepPos + 1):] # Create the FileID return cls(value, size) toil-releases-3.24.0/src/toil/fileStores/abstractFileStore.py000066400000000000000000000523621362134276200242350ustar00rootroot00000000000000# Copyright (C) 2015-2018 Regents of the University of California # # 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. from __future__ import absolute_import, print_function from future import standard_library standard_library.install_aliases() from builtins import map from builtins import str from builtins import range from builtins import object from abc import abstractmethod, ABCMeta from contextlib import contextmanager from fcntl import flock, LOCK_EX, LOCK_UN from functools import partial from hashlib import sha1 from threading import Thread, Semaphore, Event from future.utils import with_metaclass from six.moves.queue import Empty, Queue import base64 import dill import errno import logging import os import shutil import stat import tempfile import time import uuid from toil.lib.objects import abstractclassmethod from toil.lib.humanize import bytes2human from toil.common import cacheDirName, getDirSizeRecursively, getFileSystemSize from toil.lib.bioio import makePublicDir from toil.fileStores import FileID logger = logging.getLogger(__name__) class AbstractFileStore(with_metaclass(ABCMeta, object)): """ Interface used to allow user code run by Toil to read and write files. Also provides the interface to other Toil facilities used by user code, including: * normal (non-real-time) logging * finding the correct temporary directory for scratch work * importing and exporting files into and out of the workflow Stores user files in the jobStore, but keeps them separate from actual jobs. May implement caching. Passed as argument to the :meth:`toil.job.Job.run` method. Access to files is only permitted inside the context manager provided by :meth:`toil.fileStores.abstractFileStore.AbstractFileStore.open`. Also responsible for committing completed jobs back to the job store with an update operation, and allowing that commit operation to be waited for. """ # Variables used for syncing reads/writes _pendingFileWritesLock = Semaphore() _pendingFileWrites = set() _terminateEvent = Event() # Used to signify crashes in threads def __init__(self, jobStore, jobGraph, localTempDir, waitForPreviousCommit): """ Create a new file store object. :param toil.jobStores.abstractJobStore.AbstractJobStore jobStore: the job store in use for the current Toil run. :param toil.jobGraph.JobGraph jobGraph: the job graph object for the currently running job. :param str localTempDir: the per-worker local temporary directory, under which per-job directories will be created. :param waitForPreviousCommit: the waitForCommit method of the previous job's file store, when jobs are running in sequence on the same worker. Used to prevent this file store's startCommit and the previous job's startCommit methods from running at the same time and racing. If they did race, it might be possible for the later job to be fully marked as completed in the job store before the eralier job was. """ self.jobStore = jobStore self.jobGraph = jobGraph self.localTempDir = os.path.abspath(localTempDir) self.workFlowDir = os.path.dirname(self.localTempDir) self.jobName = self.jobGraph.command.split()[1] self.waitForPreviousCommit = waitForPreviousCommit self.loggingMessages = [] # Records file IDs of files deleted during the current job. Doesn't get # committed back until the job is completely successful, because if the # job is re-run it will need to be able to re-delete these files. # This is a set of str objects, not FileIDs. self.filesToDelete = set() # Records IDs of jobs that need to be deleted when the currently # running job is cleaned up. # May be modified by the worker to actually delete jobs! self.jobsToDelete = set() @staticmethod def createFileStore(jobStore, jobGraph, localTempDir, waitForPreviousCommit, caching): # Defer these imports until runtime, since these classes depend on us from toil.fileStores.cachingFileStore import CachingFileStore from toil.fileStores.nonCachingFileStore import NonCachingFileStore fileStoreCls = CachingFileStore if caching else NonCachingFileStore return fileStoreCls(jobStore, jobGraph, localTempDir, waitForPreviousCommit) @staticmethod def shutdownFileStore(workflowDir, workflowID): """ Carry out any necessary filestore-specific cleanup. This is a destructive operation and it is important to ensure that there are no other running processes on the system that are modifying or using the file store for this workflow. This is the intended to be the last call to the file store in a Toil run, called by the batch system cleanup function upon batch system shutdown. :param str workflowDir: The path to the cache directory :param str workflowID: The workflow ID for this invocation of the workflow """ # Defer these imports until runtime, since these classes depend on our file from toil.fileStores.cachingFileStore import CachingFileStore from toil.fileStores.nonCachingFileStore import NonCachingFileStore cacheDir = os.path.join(workflowDir, cacheDirName(workflowID)) if os.path.exists(cacheDir): # The presence of the cacheDir suggests this was a cached run. We don't need the cache lock # for any of this since this is the final cleanup of a job and there should be no other # conflicting processes using the cache. CachingFileStore.shutdown(cacheDir) else: # This absence of cacheDir suggests otherwise. NonCachingFileStore.shutdown(workflowDir) @abstractmethod @contextmanager def open(self, job): """ The context manager used to conduct tasks prior-to, and after a job has been run. File operations are only permitted inside the context manager. :param toil.job.Job job: The job instance of the toil job to run. """ raise NotImplementedError() # Functions related to temp files and directories def getLocalTempDir(self): """ Get a new local temporary directory in which to write files that persist for the duration of the job. :return: The absolute path to a new local temporary directory. This directory will exist for the duration of the job only, and is guaranteed to be deleted once the job terminates, removing all files it contains recursively. :rtype: str """ return os.path.abspath(tempfile.mkdtemp(prefix="t", dir=self.localTempDir)) def getLocalTempFile(self): """ Get a new local temporary file that will persist for the duration of the job. :return: The absolute path to a local temporary file. This file will exist for the duration of the job only, and is guaranteed to be deleted once the job terminates. :rtype: str """ handle, tmpFile = tempfile.mkstemp(prefix="tmp", suffix=".tmp", dir=self.localTempDir) os.close(handle) return os.path.abspath(tmpFile) def getLocalTempFileName(self): """ Get a valid name for a new local file. Don't actually create a file at the path. :return: Path to valid file :rtype: str """ # Create, and then delete a temp file. Creating will guarantee you a unique, unused # file name. There is a very, very, very low chance that another job will create the # same file name in the span of this one being deleted and then being used by the user. tempFile = self.getLocalTempFile() os.remove(tempFile) return tempFile # Functions related to reading, writing and removing files to/from the job store @abstractmethod def writeGlobalFile(self, localFileName, cleanup=False): """ Takes a file (as a path) and uploads it to the job store. :param string localFileName: The path to the local file to upload. :param bool cleanup: if True then the copy of the global file will be deleted once the job and all its successors have completed running. If not the global file must be deleted manually. :return: an ID that can be used to retrieve the file. :rtype: toil.fileStores.FileID """ raise NotImplementedError() @contextmanager def writeGlobalFileStream(self, cleanup=False): """ Similar to writeGlobalFile, but allows the writing of a stream to the job store. The yielded file handle does not need to and should not be closed explicitly. :param bool cleanup: is as in :func:`toil.fileStores.abstractFileStore.AbstractFileStore.writeGlobalFile`. :return: A context manager yielding a tuple of 1) a file handle which can be written to and 2) the toil.fileStores.FileID of the resulting file in the job store. """ # TODO: Make this work with FileID with self.jobStore.writeFileStream(None if not cleanup else self.jobGraph.jobStoreID) as (backingStream, fileStoreID): # We have a string version of the file ID, and the backing stream. # We need to yield a stream the caller can write to, and a FileID # that accurately reflects the size of the data written to the # stream. We assume the stream is not seekable. # Make and keep a reference to the file ID, which is currently empty fileID = FileID(fileStoreID, 0) # Wrap the stream to increment the file ID's size for each byte written wrappedStream = WriteWatchingStream(backingStream) # When the stream is written to, count the bytes def handle(numBytes): fileID.size += numBytes wrappedStream.onWrite(handle) yield wrappedStream, fileID @abstractmethod def readGlobalFile(self, fileStoreID, userPath=None, cache=True, mutable=False, symlink=False): """ Makes the file associated with fileStoreID available locally. If mutable is True, then a copy of the file will be created locally so that the original is not modified and does not change the file for other jobs. If mutable is False, then a link can be created to the file, saving disk resources. If a user path is specified, it is used as the destination. If a user path isn't specified, the file is stored in the local temp directory with an encoded name. The destination file must not be deleted by the user; it can only be deleted through deleteLocalFile. :param toil.fileStores.FileID or str fileStoreID: job store id for the file :param string userPath: a path to the name of file to which the global file will be copied or hard-linked (see below). :param bool cache: Described in :func:`toil.fileStores.CachingFileStore.readGlobalFile` :param bool mutable: Described in :func:`toil.fileStores.CachingFileStore.readGlobalFile` :return: An absolute path to a local, temporary copy of the file keyed by fileStoreID. :rtype: str """ raise NotImplementedError() @abstractmethod def readGlobalFileStream(self, fileStoreID): """ Similar to readGlobalFile, but allows a stream to be read from the job store. The yielded file handle does not need to and should not be closed explicitly. :return: a context manager yielding a file handle which can be read from. """ raise NotImplementedError() def getGlobalFileSize(self, fileStoreID): """ Get the size of the file pointed to by the given ID, in bytes. If a FileID or something else with a non-None 'size' field, gets that. Otherwise, asks the job store to poll the file's size. Note that the job store may overestimate the file's size, for example if it is encrypted and had to be augmented with an IV or other encryption framing. :param toil.fileStores.FileID or str fileStoreID: File ID for the file :return: File's size in bytes, as stored in the job store :rtype: int """ # First try and see if the size is still attached size = getattr(fileStoreID, 'size', None) if size is None: # It fell off # Someone is mixing FileStore and JobStore file APIs, or serializing FileIDs as strings. size = self.jobStore.getFileSize(fileStoreID) return size @abstractmethod def deleteLocalFile(self, fileStoreID): """ Deletes local copies of files associated with the provided job store ID. The files deleted are all those previously read from this file ID via readGlobalFile by the current job into the job's file-store-provided temp directory, plus the file that was written to create the given file ID, if it was written by the current job from the job's file-store-provided temp directory. :param toil.fileStores.FileID or str fileStoreID: File Store ID of the file to be deleted. """ raise NotImplementedError() @abstractmethod def deleteGlobalFile(self, fileStoreID): """ Deletes local files with the provided job store ID and then permanently deletes them from the job store. To ensure that the job can be restarted if necessary, the delete will not happen until after the job's run method has completed. :param toil.fileStores.FileID or str fileStoreID: the File Store ID of the file to be deleted. """ raise NotImplementedError() # Functions used to read and write files directly between a source url and the job store. def importFile(self, srcUrl, sharedFileName=None): return self.jobStore.importFile(srcUrl, sharedFileName=sharedFileName) def exportFile(self, jobStoreFileID, dstUrl): raise NotImplementedError() # A utility method for accessing filenames def _resolveAbsoluteLocalPath(self, filePath): """ Return the absolute path to filePath. This is a wrapper for os.path.abspath because mac OS symlinks /tmp and /var (the most common places for a default tempdir) to /private/tmp and /private/var respectively. :param str filePath: The absolute or relative path to the file. If relative, it must be relative to the local temp working dir :return: Absolute path to key :rtype: str """ if os.path.isabs(filePath): return os.path.abspath(filePath) else: return os.path.join(self.localTempDir, filePath) class _StateFile(object): """ Utility class to read and write dill-ed state dictionaries from/to a file into a namespace. """ def __init__(self, stateDict): assert isinstance(stateDict, dict) self.__dict__.update(stateDict) @abstractclassmethod @contextmanager def open(cls, outer=None): """ This is a context manager that state file and reads it into an object that is returned to the user in the yield. :param outer: Instance of the calling class (to use outer methods). """ raise NotImplementedError() @classmethod def _load(cls, fileName): """ Load the state of the cache from the state file :param str fileName: Path to the cache state file. :return: An instance of the state as a namespace. :rtype: _StateFile """ # Read the value from the cache state file then initialize and instance of # _CacheState with it. with open(fileName, 'rb') as fH: infoDict = dill.load(fH) return cls(infoDict) def write(self, fileName): """ Write the current state into a temporary file then atomically rename it to the main state file. :param str fileName: Path to the state file. """ with open(fileName + '.tmp', 'wb') as fH: # Based on answer by user "Mark" at: # http://stackoverflow.com/questions/2709800/how-to-pickle-yourself # We can't pickle nested classes. So we have to pickle the variables of the class # If we ever change this, we need to ensure it doesn't break FileID dill.dump(self.__dict__, fH) os.rename(fileName + '.tmp', fileName) # Functions related to logging def logToMaster(self, text, level=logging.INFO): """ Send a logging message to the leader. The message will also be \ logged by the worker at the same level. :param text: The string to log. :param int level: The logging level. """ logger.log(level=level, msg=("LOG-TO-MASTER: " + text)) self.loggingMessages.append(dict(text=text, level=level)) # Functions run after the completion of the job. @abstractmethod def startCommit(self, jobState=False): """ Update the status of the job on the disk. May start an asynchronous process. Call waitForCommit() to wait on that process. :param bool jobState: If True, commit the state of the FileStore's job, and file deletes. Otherwise, commit only file creates/updates. """ raise NotImplementedError() @abstractmethod def waitForCommit(self): """ Blocks while startCommit is running. This function is called by this job's successor to ensure that it does not begin modifying the job store until after this job has finished doing so. Might be called when startCommit is never called on a particular instance, in which case it does not block. :return: Always returns True :rtype: bool """ raise NotImplementedError() # Utility function used to identify if a pid is still running on the node. @staticmethod def _pidExists(pid): """ This will return True if the process associated with pid is still running on the machine. This is based on stackoverflow question 568271. :param int pid: ID of the process to check for :return: True/False :rtype: bool """ assert pid > 0 try: os.kill(pid, 0) except OSError as err: if err.errno == errno.ESRCH: # ESRCH == No such process return False else: raise else: return True @abstractclassmethod def shutdown(cls, dir_): """ Shutdown the filestore on this node. This is intended to be called on batch system shutdown. :param dir_: The implementation-specific directory containing the required information for shutting down the file store and removing all its state and all job local temp directories from the node. """ raise NotImplementedError() class WriteWatchingStream(object): """ A stream wrapping class that calls any functions passed to onWrite() with the number of bytes written for every write. Not seekable. """ def __init__(self, backingStream): """ Wrap the given backing stream. """ self.backingStream = backingStream # We have no write listeners yet self.writeListeners = [] def onWrite(self, listener): """ Call the given listener with the number of bytes written on every write. """ self.writeListeners.append(listener) # Implement the file API from https://docs.python.org/2.4/lib/bltin-file-objects.html def write(self, data): """ Write the given data to the file. """ # Do the write self.backingStream.write(data) for listener in self.writeListeners: # Send out notifications listener(len(data)) def writelines(self, datas): """ Write each string from the given iterable, without newlines. """ for data in datas: self.write(data) def flush(self): """ Flush the backing stream. """ self.backingStream.flush() def close(self): """ Close the backing stream. """ self.backingStream.close() toil-releases-3.24.0/src/toil/fileStores/cachingFileStore.py000066400000000000000000002404441362134276200240260ustar00rootroot00000000000000# Copyright (C) 2015-2018 Regents of the University of California # # 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. from __future__ import absolute_import, print_function from future import standard_library standard_library.install_aliases() from builtins import map from builtins import str from builtins import range from builtins import object from abc import abstractmethod, ABCMeta from collections import namedtuple, defaultdict from contextlib import contextmanager from fcntl import flock, LOCK_EX, LOCK_UN from functools import partial from future.utils import with_metaclass from six.moves.queue import Empty, Queue import base64 import dill import errno import hashlib import logging import os import re import shutil import sqlite3 import stat import sys import tempfile import threading import time import uuid from toil.common import cacheDirName, getDirSizeRecursively, getFileSystemSize from toil.lib.bioio import makePublicDir from toil.lib.humanize import bytes2human from toil.lib.misc import mkdir_p, robust_rmtree, atomic_copy, atomic_copyobj from toil.lib.objects import abstractclassmethod from toil.lib.retry import retry from toil.resource import ModuleDescriptor from toil.fileStores.abstractFileStore import AbstractFileStore from toil.fileStores import FileID logger = logging.getLogger(__name__) if sys.version_info[0] < 3: # Define a usable FileNotFoundError as will be raised by os.remove on a # nonexistent file. FileNotFoundError = OSError class CacheError(Exception): """ Error Raised if the user attempts to add a non-local file to cache """ def __init__(self, message): super(CacheError, self).__init__(message) class CacheUnbalancedError(CacheError): """ Raised if file store can't free enough space for caching """ message = 'Unable unable to free enough space for caching. This error frequently arises due ' \ 'to jobs using more disk than they have requested. Turn on debug logging to see ' \ 'more information leading up to this error through cache usage logs.' def __init__(self): super(CacheUnbalancedError, self).__init__(self.message) class IllegalDeletionCacheError(CacheError): """ Error raised if the caching code discovers a file that represents a reference to a cached file to have gone missing. This can be a big problem if a hard link is moved, because then the cache will be unable to evict the file it links to. Remember that files read with readGlobalFile may not be deleted by the user and need to be deleted with deleteLocalFile. """ def __init__(self, deletedFile): message = 'Cache tracked file (%s) has been deleted or moved by user ' \ ' without updating cache database. Use deleteLocalFile to ' \ 'delete such files.' % deletedFile super(IllegalDeletionCacheError, self).__init__(message) class InvalidSourceCacheError(CacheError): """ Error raised if the user attempts to add a non-local file to cache """ def __init__(self, message): super(InvalidSourceCacheError, self).__init__(message) class CachingFileStore(AbstractFileStore): """ A cache-enabled file store. Provides files that are read out as symlinks or hard links into a cache directory for the node, if permitted by the workflow. Also attempts to write files back to the backing JobStore asynchronously, after quickly taking them into the cache. Writes are only required to finish when the job's actual state after running is committed back to the job store. Internaly, manages caching using a database. Each node has its own database, shared between all the workers on the node. The database contains several tables: files contains one entry for each file in the cache. Each entry knows the path to its data on disk. It also knows its global file ID, its state, and its owning worker PID. If the owning worker dies, another worker will pick it up. It also knows its size. File states are: - "cached": happily stored in the cache. Reads can happen immediately. Owner is null. May be adopted and moved to state "deleting" by anyone, if it has no outstanding immutable references. - "downloading": in the process of being saved to the cache by a non-null owner. Reads must wait for the state to become "cached". If the worker dies, goes to state "deleting", because we don't know if it was fully downloaded or if anyone still needs it. No references can be created to a "downloading" file except by the worker responsible for downloading it. - "uploadable": stored in the cache and ready to be written to the job store by a non-null owner. Transitions to "uploading" when a (thread of) the owning worker process picks it up and begins uploading it, to free cache space or to commit a completed job. If the worker dies, goes to state "cached", because it may have outstanding immutable references from the dead-but-not-cleaned-up job that was going to write it. - "uploading": stored in the cache and being written to the job store by a non-null owner. Transitions to "cached" when successfully uploaded. If the worker dies, goes to state "cached", because it may have outstanding immutable references from the dead-but-not-cleaned-up job that was writing it. - "deleting": in the process of being removed from the cache by a non-null owner. Will eventually be removed from the database. refs contains one entry for each outstanding reference to a cached file (hard link, symlink, or full copy). The table name is refs instead of references because references is an SQL reserved word. It remembers what job ID has the reference, and the path the reference is at. References have three states: - "immutable": represents a hardlink or symlink to a file in the cache. Dedicates the file's size in bytes of the job's disk requirement to the cache, to be used to cache this file or to keep around other files without references. May be upgraded to "copying" if the link can't actually be created. - "copying": records that a file in the cache is in the process of being copied to a path. Will be upgraded to a mutable reference eventually. - "mutable": records that a file from the cache was copied to a certain path. Exist only to support deleteLocalFile's API. Only files with only mutable references (or no references) are eligible for eviction. jobs contains one entry for each job currently running. It keeps track of the job's ID, the worker that is supposed to be running the job, the job's disk requirement, and the job's local temp dir path that will need to be cleaned up. When workers check for jobs whose workers have died, they null out the old worker, and grab ownership of and clean up jobs and their references until the null-worker jobs are gone. properties contains key, value pairs for tracking total space available, and whether caching is free for this run. """ def __init__(self, jobStore, jobGraph, localTempDir, waitForPreviousCommit): super(CachingFileStore, self).__init__(jobStore, jobGraph, localTempDir, waitForPreviousCommit) # For testing, we have the ability to force caching to be non-free, by never linking from the file store self.forceNonFreeCaching = False # Also for testing, we have the ability to force a delay (in seconds) # during file download from the job store, in order to easily test the # behavior of the system when a download is in progress. self.forceDownloadDelay = None # When waiting for other running workers to download a file, or # otherwise progress, how long in seconds should we wait between # polling attempts? Our mechanism for polling involves an exclusive # lock on the database and conditional writes, so this should be high # enough that everyone isn't constantly contending for the lock. self.contentionBackoff = 15 # Variables related to caching # Decide where the cache directory will be. We put it next to the # local temp dirs for all of the jobs run on this machine. # At this point in worker startup, when we are setting up caching, # localTempDir is the worker directory, not the job directory. self.localCacheDir = os.path.join(os.path.dirname(localTempDir), cacheDirName(self.jobStore.config.workflowID)) # Since each worker has it's own unique CachingFileStore instance, and only one Job can run # at a time on a worker, we can track some stuff about the running job in ourselves. self.jobName = str(self.jobGraph) self.jobID = self.jobGraph.jobStoreID logger.debug('Starting job (%s) with ID (%s).', self.jobName, self.jobID) # When the job actually starts, we will fill this in with the job's disk requirement. self.jobDiskBytes = None # We need to track what attempt of the workflow we are, to prevent crosstalk between attempts' caches. self.workflowAttemptNumber = self.jobStore.config.workflowAttemptNumber # Make sure the cache directory exists mkdir_p(self.localCacheDir) # Connect to the cache database in there, or create it if not present. # We name it by workflow attempt number in case a previous attempt of # the workflow left one behind without cleaning up properly; we need to # be able to tell that from showing up on a machine where a cache has # already been created. self.dbPath = os.path.join(self.localCacheDir, 'cache-{}.db'.format(self.workflowAttemptNumber)) # We need to hold onto both a connection (to commit) and a cursor (to actually use the database) self.con = sqlite3.connect(self.dbPath, timeout=60.0) self.cur = self.con.cursor() # Note that sqlite3 automatically starts a transaction when we go to # modify the database. # To finish this transaction and let other people read our writes (or # write themselves), we need to COMMIT after every coherent set of # writes. # Set up the tables self._ensureTables(self.con) # Initialize the space accounting properties freeSpace, _ = getFileSystemSize(self.localCacheDir) self._write([('INSERT OR IGNORE INTO properties VALUES (?, ?)', ('maxSpace', freeSpace))]) # Space used by caching and by jobs is accounted with queries # We maintain an asynchronous upload thread, which gets kicked off when # we commit the job's completion. It will be None until then. When it # is running, it has exclusive control over our database connection, # because the job we exist for will have already completed. However, it # has to coordinate its activities with other CachingFileStore objects # in the same process (and thus sharing the same PID) and ensure that # only one of them is working on uploading any given file at any given # time. self.commitThread = None @staticmethod def _staticWrite(con, cur, operations): """ Write to the caching database, using the given connection. If we can't get an SQLite write lock on the database, retry with some backoff until we can. operations is a list of tuples of (sql string, optional tuple of values to substitute), or bare sql strings. All operations are executed in a single transaction, which is committed. :param sqlite3.Connection con: Connection to the cache database. :param sqlite3.Cursor cur: Cursor in the cache database. :param list operations: List of sql strings or tuples of (sql, optional values) to execute. :return: Number of rows modified by the last operation :rtype: int """ for attempt in retry(timeout=float('inf'), predicate=lambda e: isinstance(e, sqlite3.OperationalError) and 'is locked' in str(e)): # Try forever with backoff with attempt: try: for item in operations: if not isinstance(item, tuple): # Must be a single SQL string. Wrap it. item = (item,) # Parse out the command and the variables to substitute command = item[0] if len(item) < 2: args = () else: args = item[1] # Do it cur.execute(command, args) except Exception as e: logging.error('Error talking to caching database: %s', str(e)) # Try to make sure we don't somehow leave anything part-done if a # middle operation somehow fails. try: con.rollback() except: # But don't stop if we can't roll back. pass # Raise and maybe retry raise e else: # The transaction worked! # Now commit the transaction. con.commit() return cur.rowcount def _write(self, operations): """ Write to the caching database, using the instance's connection If we can't get an SQLite write lock on the database, retry with some backoff until we can. operations is a list of tuples of (sql string, optional tuple of values to substitute), or bare sql strings. All operations are executed in a single transaction, which is committed. :param list operations: List of sql strings or tuples of (sql, optional values) to execute. :return: Number of rows modified by the last operation :rtype: int """ return self._staticWrite(self.con, self.cur, operations) @classmethod def _ensureTables(cls, con): """ Ensure that the database tables we expect exist. :param sqlite3.Connection con: Connection to the cache database. """ # Get a cursor cur = con.cursor() cls._staticWrite(con, cur, [""" CREATE TABLE IF NOT EXISTS files ( id TEXT NOT NULL PRIMARY KEY, path TEXT UNIQUE NOT NULL, size INT NOT NULL, state TEXT NOT NULL, owner INT ) """, """ CREATE TABLE IF NOT EXISTS refs ( path TEXT NOT NULL, file_id TEXT NOT NULL, job_id TEXT NOT NULL, state TEXT NOT NULL, PRIMARY KEY (path, file_id) ) """, """ CREATE TABLE IF NOT EXISTS jobs ( id TEXT NOT NULL PRIMARY KEY, tempdir TEXT NOT NULL, disk INT NOT NULL, worker INT ) """, """ CREATE TABLE IF NOT EXISTS properties ( name TEXT NOT NULL PRIMARY KEY, value INT NOT NULL ) """]) # Caching-specific API def getCacheLimit(self): """ Return the total number of bytes to which the cache is limited. If no limit is available, raises an error. """ for row in self.cur.execute('SELECT value FROM properties WHERE name = ?', ('maxSpace',)): return row[0] raise RuntimeError('Unable to retrieve cache limit') def getCacheUsed(self): """ Return the total number of bytes used in the cache. If no value is available, raises an error. """ # Space never counts as used if caching is free if self.cachingIsFree(): return 0 for row in self.cur.execute('SELECT TOTAL(size) FROM files'): return row[0] raise RuntimeError('Unable to retrieve cache usage') def getCacheExtraJobSpace(self): """ Return the total number of bytes of disk space requested by jobs running against this cache but not yet used. We can get into a situation where the jobs on the node take up all its space, but then they want to write to or read from the cache. So when that happens, we need to debit space from them somehow... If no value is available, raises an error. """ # Total up the sizes of all the reads of files and subtract it from the total disk reservation of all jobs for row in self.cur.execute(""" SELECT ( (SELECT TOTAL(disk) FROM jobs) - (SELECT TOTAL(files.size) FROM refs INNER JOIN files ON refs.file_id = files.id WHERE refs.state == 'immutable') ) as result """): return row[0] raise RuntimeError('Unable to retrieve extra job space') def getCacheAvailable(self): """ Return the total number of free bytes available for caching, or, if negative, the total number of bytes of cached files that need to be evicted to free up enough space for all the currently scheduled jobs. If no value is available, raises an error. """ # Get the max space on our disk. # Subtract out the number of bytes of cached content. # Also subtract out the number of bytes of job disk requirements that # aren't being spent by those jobs on immutable references to cached # content. # Do a little report first for row in self.cur.execute("SELECT value FROM properties WHERE name = 'maxSpace'"): logger.debug('Max space: %d', row[0]) for row in self.cur.execute("SELECT TOTAL(size) FROM files"): logger.debug('Total file size: %d', row[0]) for row in self.cur.execute("SELECT TOTAL(disk) FROM jobs"): logger.debug('Total job disk requirement size: %d', row[0]) for row in self.cur.execute("SELECT TOTAL(files.size) FROM refs INNER JOIN files ON refs.file_id = files.id WHERE refs.state = 'immutable'"): logger.debug('Total immutable reference size: %d', row[0]) if self.cachingIsFree(): # If caching is free, we just say that all the space is always available. for row in self.cur.execute("SELECT value FROM properties WHERE name = 'maxSpace'"): return row[0] raise RuntimeError('Unable to retrieve available cache space') for row in self.cur.execute(""" SELECT ( (SELECT value FROM properties WHERE name = 'maxSpace') - (SELECT TOTAL(size) FROM files) - ((SELECT TOTAL(disk) FROM jobs) - (SELECT TOTAL(files.size) FROM refs INNER JOIN files ON refs.file_id = files.id WHERE refs.state = 'immutable')) ) as result """): return row[0] raise RuntimeError('Unable to retrieve available cache space') def getSpaceUsableForJobs(self): """ Return the total number of bytes that are not taken up by job requirements, ignoring files and file usage. We can't ever run more jobs than we actually have room for, even with caching. If not retrievable, raises an error. """ for row in self.cur.execute(""" SELECT ( (SELECT value FROM properties WHERE name = 'maxSpace') - (SELECT TOTAL(disk) FROM jobs) ) as result """): return row[0] raise RuntimeError('Unable to retrieve usabel space for jobs') def getCacheUnusedJobRequirement(self): """ Return the total number of bytes of disk space requested by the current job and not used by files the job is using in the cache. Mutable references don't count, but immutable/uploading ones do. If no value is available, raises an error. """ logger.debug('Get unused space for job %s', self.jobID) for row in self.cur.execute('SELECT * FROM files'): logger.debug('File record: %s', str(row)) for row in self.cur.execute('SELECT * FROM refs'): logger.debug('Ref record: %s', str(row)) for row in self.cur.execute('SELECT TOTAL(files.size) FROM refs INNER JOIN files ON refs.file_id = files.id WHERE refs.job_id = ? AND refs.state != ?', (self.jobID, 'mutable')): # Sum up all the sizes of our referenced files, then subtract that from how much we came in with return self.jobDiskBytes - row[0] raise RuntimeError('Unable to retrieve unused job requirement space') def adjustCacheLimit(self, newTotalBytes): """ Adjust the total cache size limit to the given number of bytes. """ self._write([('UPDATE properties SET value = ? WHERE name = ?', (newTotalBytes, 'maxSpace'))]) def fileIsCached(self, fileID): """ Return true if the given file is currently cached, and false otherwise. Note that this can't really be relied upon because a file may go cached -> deleting after you look at it. If you need to do something with the file you need to do it in a transaction. """ for row in self.cur.execute('SELECT COUNT(*) FROM files WHERE id = ? AND (state = ? OR state = ? OR state = ?)', (fileID, 'cached', 'uploadable', 'uploading')): return row[0] > 0 return False def getFileReaderCount(self, fileID): """ Return the number of current outstanding reads of the given file. Counts mutable references too. """ for row in self.cur.execute('SELECT COUNT(*) FROM refs WHERE file_id = ?', (fileID,)): return row[0] return 0 def cachingIsFree(self): """ Return true if files can be cached for free, without taking up space. Return false otherwise. This will be true when working with certain job stores in certain configurations, most notably the FileJobStore. """ for row in self.cur.execute('SELECT value FROM properties WHERE name = ?', ('freeCaching',)): return row[0] == 1 # Otherwise we need to set it from toil.jobStores.fileJobStore import FileJobStore if isinstance(self.jobStore, FileJobStore) and not self.forceNonFreeCaching: # Caching may be free since we are using a file job store. # Create an empty file. emptyID = self.jobStore.getEmptyFileStoreID() # Read it out to a generated name. destDir = tempfile.mkdtemp(dir=self.localCacheDir) cachedFile = os.path.join(destDir, 'sniffLinkCount') self.jobStore.readFile(emptyID, cachedFile, symlink=False) # Check the link count if os.stat(cachedFile).st_nlink == 2: # Caching must be free free = 1 else: # If we only have one link, caching costs disk. free = 0 # Clean up os.unlink(cachedFile) os.rmdir(destDir) self.jobStore.deleteFile(emptyID) else: # Caching is only ever free with the file job store free = 0 # Save to the database if we're the first to work this out self._write([('INSERT OR IGNORE INTO properties VALUES (?, ?)', ('freeCaching', free))]) # Return true if we said caching was free return free == 1 # Internal caching logic def _getNewCachingPath(self, fileStoreID): """ Get a path at which the given file ID can be cached. Will be unique for every call. The file will not be created if it does not exist. """ # Hash the file ID hasher = hashlib.sha1() hasher.update(fileStoreID.encode('utf-8')) # Get a unique temp file name, including the file ID's hash to make # sure we can never collide even though we are going to remove the # file. # TODO: use a de-slashed version of the ID instead? handle, path = tempfile.mkstemp(dir=self.localCacheDir, suffix=hasher.hexdigest()) os.close(handle) os.unlink(path) return path def _stealWorkFromTheDead(self): """ Take ownership of any files we can see whose owners have died. We don't actually process them here. We take action based on the states of files we own later. """ pid = os.getpid() # Get a list of all file owner processes on this node. # Exclude NULL because it comes out as 0 and we can't look for PID 0. owners = [] for row in self.cur.execute('SELECT DISTINCT owner FROM files WHERE owner IS NOT NULL'): owners.append(row[0]) # Work out which of them have died. # TODO: use GUIDs or something to account for PID re-use? deadOwners = [] for owner in owners: if not self._pidExists(owner): deadOwners.append(owner) for owner in deadOwners: # Try and adopt all the files that any dead owner had # If they were deleting, we delete. # If they were downloading, we delete. Any outstanding references # can't be in use since they are from the dead downloader. # If they were uploading or uploadable, we mark as cached even # though it never made it to the job store (and leave it unowned). # # Once the dead job that it was being uploaded from is cleaned up, # and there are no longer any immutable references, it will be # evicted as normal. Since the dead job can't have been marked # successfully completed (since the file is still not uploaded), # nobody is allowed to actually try and use the file. # # TODO: if we ever let other PIDs be responsible for writing our # files asynchronously, this will need to change. self._write([('UPDATE files SET owner = ?, state = ? WHERE owner = ? AND state = ?', (pid, 'deleting', owner, 'deleting')), ('UPDATE files SET owner = ?, state = ? WHERE owner = ? AND state = ?', (pid, 'deleting', owner, 'downloading')), ('UPDATE files SET owner = NULL, state = ? WHERE owner = ? AND (state = ? OR state = ?)', ('cached', owner, 'uploadable', 'uploading'))]) logger.debug('Tried to adopt file operations from dead worker %d', owner) @classmethod def _executePendingDeletions(cls, con, cur): """ Delete all the files that are registered in the database as in the process of being deleted from the cache by us. Returns the number of files that were deleted. Implemented as a class method so it can use the database connection appropriate to its thread without any chance of getting at the main thread's connection and cursor in self. :param sqlite3.Connection con: Connection to the cache database. :param sqlite3.Cursor cur: Cursor in the cache database. """ pid = os.getpid() # Remember the file IDs we are deleting deletedFiles = [] for row in cur.execute('SELECT id, path FROM files WHERE owner = ? AND state = ?', (pid, 'deleting')): # Grab everything we are supposed to delete and delete it fileID = row[0] filePath = row[1] try: os.unlink(filePath) except OSError: # Probably already deleted continue # Whether we deleted the file or just found out that it is gone, we # need to take credit for deleting it so that we remove it from the # database. deletedFiles.append(fileID) for fileID in deletedFiles: # Drop all the files. They should have stayed in deleting state. We move them from there to not present at all. # Also drop their references, if they had any from dead downloaders. cls._staticWrite(con, cur, [('DELETE FROM files WHERE id = ? AND state = ?', (fileID, 'deleting')), ('DELETE FROM refs WHERE file_id = ?', (fileID,))]) return len(deletedFiles) def _executePendingUploads(self, con, cur): """ Uploads all files in uploadable state that we own. Returns the number of files that were uploaded. Needs access to self to get at the job store for uploading files, but still needs to take con and cur so it can run in a thread with the thread's database connection. :param sqlite3.Connection con: Connection to the cache database. :param sqlite3.Cursor cur: Cursor in the cache database. """ # Work out who we are pid = os.getpid() # Record how many files we upload uploadedCount = 0 while True: # Try and find a file we might want to upload fileID = None filePath = None for row in cur.execute('SELECT id, path FROM files WHERE state = ? AND owner = ? LIMIT 1', ('uploadable', pid)): fileID = row[0] filePath = row[1] if fileID is None: # Nothing else exists to upload break # We need to set it to uploading in a way that we can detect that *we* won the update race instead of anyone else. rowCount = self._staticWrite(con, cur, [('UPDATE files SET state = ? WHERE id = ? AND state = ?', ('uploading', fileID, 'uploadable'))]) if rowCount != 1: # We didn't manage to update it. Someone else (a running job if # we are a committing thread, or visa versa) must have grabbed # it. logger.debug('Lost race to upload %s', fileID) # Try again to see if there is something else to grab. continue # Upload the file logger.debug('Actually executing upload for file %s', fileID) self.jobStore.updateFile(fileID, filePath) # Count it for the total uploaded files value we need to return uploadedCount += 1 # Remember that we uploaded it in the database self._staticWrite(con, cur, [('UPDATE files SET state = ?, owner = NULL WHERE id = ?', ('cached', fileID))]) return uploadedCount def _allocateSpaceForJob(self, newJobReqs): """ A new job is starting that needs newJobReqs space. We need to record that we have a job running now that needs this much space. We also need to evict enough stuff from the cache so that we have room for this job to fill up that much space even if it doesn't cache anything. localTempDir must have already been pointed to the job's temp dir. :param float newJobReqs: the total number of bytes that this job requires. """ # Put an entry in the database for this job being run on this worker. # This will take up space for us and potentially make the cache over-full. # But we won't actually let the job run and use any of this space until # the cache has been successfully cleared out. pid = os.getpid() self._write([('INSERT INTO jobs VALUES (?, ?, ?, ?)', (self.jobID, self.localTempDir, newJobReqs, pid))]) # Now we need to make sure that we can fit all currently cached files, # and the parts of the total job requirements not currently spent on # cached files, in under the total disk space limit. available = self.getCacheAvailable() logger.debug('Available space with job: %d bytes', available) if available >= 0: # We're fine on disk space return # Otherwise we need to clear stuff. self._freeUpSpace() @classmethod def _removeJob(cls, con, cur, jobID): """ Get rid of the job with the given ID. The job must be owned by us. Deletes the job's database entry, all its references, and its whole temporary directory. :param sqlite3.Connection con: Connection to the cache database. :param sqlite3.Cursor cur: Cursor in the cache database. :param str jobID: Hash-based ID of the job being removed. Not a Toil JobStore ID. """ # Get the job's temp dir for row in cur.execute('SELECT tempdir FROM jobs WHERE id = ?', (jobID,)): jobTemp = row[0] for row in cur.execute('SELECT path FROM refs WHERE job_id = ?', (jobID,)): try: # Delete all the reference files. os.unlink(row[0]) except OSError: # May not exist pass # And their database entries cls._staticWrite(con, cur, [('DELETE FROM refs WHERE job_id = ?', (jobID,))]) try: # Delete the job's temp directory to the extent that we can. shutil.rmtree(jobTemp) except OSError: pass # Strike the job from the database cls._staticWrite(con, cur, [('DELETE FROM jobs WHERE id = ?', (jobID,))]) def _deallocateSpaceForJob(self): """ Our current job that was using oldJobReqs space has finished. We need to record that the job is no longer running, so its space not taken up by files in the cache will be free. """ self._removeJob(self.con, self.cur, self.jobID) def _tryToFreeUpSpace(self): """ If disk space is overcommitted, try one round of collecting files to upload/download/delete/evict. Return whether we manage to get any space freed or not. """ # First we want to make sure that dead jobs aren't holding # references to files and keeping them from looking unused. self._removeDeadJobs(self.con) # Adopt work from any dead workers self._stealWorkFromTheDead() if self._executePendingDeletions(self.con, self.cur) > 0: # We actually had something to delete, which we deleted. # Maybe there is space now logger.debug('Successfully executed pending deletions to free space') return True if self._executePendingUploads(self.con, self.cur) > 0: # We had something to upload. Maybe it can be evicted now. logger.debug('Successfully executed pending uploads to free space') return True # Otherwise, not enough files could be found in deleting state to solve our problem. # We need to put something into the deleting state. # TODO: give other people time to finish their in-progress # evictions before starting more, or we might evict everything as # soon as we hit the cache limit. # Find something that has no non-mutable references and is not already being deleted. self.cur.execute(""" SELECT files.id FROM files WHERE files.state = 'cached' AND NOT EXISTS ( SELECT NULL FROM refs WHERE refs.file_id = files.id AND refs.state != 'mutable' ) LIMIT 1 """) row = self.cur.fetchone() if row is None: # Nothing can be evicted by us. # Someone else might be in the process of evicting something that will free up space for us too. # Or someone mught be uploading something and we have to wait for them to finish before it can be deleted. logger.debug('Could not find anything to evict! Cannot free up space!') return False # Otherwise we found an eviction candidate. fileID = row[0] # Work out who we are pid = os.getpid() # Try and grab it for deletion, subject to the condition that nothing has started reading it self._write([(""" UPDATE files SET owner = ?, state = ? WHERE id = ? AND state = ? AND owner IS NULL AND NOT EXISTS ( SELECT NULL FROM refs WHERE refs.file_id = files.id AND refs.state != 'mutable' ) """, (pid, 'deleting', fileID, 'cached'))]) logger.debug('Evicting file %s', fileID) # Whether we actually got it or not, try deleting everything we have to delete if self._executePendingDeletions(self.con, self.cur) > 0: # We deleted something logger.debug('Successfully executed pending deletions to free space') return True def _freeUpSpace(self): """ If disk space is overcomitted, block and evict eligible things from the cache until it is no longer overcommitted. """ availableSpace = self.getCacheAvailable() # Track how long we are willing to wait for cache space to free up without making progress evicting things before we give up. # This is the longes that we will wait for uploads and other deleters. patience = 10 while availableSpace < 0: # While there isn't enough space for the thing we want logger.debug('Cache is full (%d bytes free). Trying to free up space!', availableSpace) # Free up space. See if we made any progress progress = self._tryToFreeUpSpace() availableSpace = self.getCacheAvailable() if progress: # Reset our patience patience = 10 else: # See if we've been oversubscribed. jobSpace = self.getSpaceUsableForJobs() if jobSpace < 0: logger.critical('Jobs on this machine have oversubscribed our total available space (%d bytes)!', jobSpace) raise CacheUnbalancedError else: patience -= 1 if patience <= 0: logger.critical('Waited implausibly long for active uploads and deletes.') raise CacheUnbalancedError else: # Wait a bit and come back time.sleep(2) logger.debug('Cache has %d bytes free.', availableSpace) # Normal AbstractFileStore API @contextmanager def open(self, job): """ This context manager decorated method allows cache-specific operations to be conducted before and after the execution of a job in worker.py """ # Create a working directory for the job startingDir = os.getcwd() # Move self.localTempDir from the worker directory set up in __init__ to a per-job directory. self.localTempDir = makePublicDir(os.path.join(self.localTempDir, str(uuid.uuid4()))) # Check the status of all jobs on this node. If there are jobs that started and died before # cleaning up their presence from the database, clean them up ourselves. self._removeDeadJobs(self.con) # Get the requirements for the job. self.jobDiskBytes = job.disk logger.debug('Actually running job (%s) with ID (%s) which wants %d of our %d bytes.', self.jobName, self.jobID, self.jobDiskBytes, self.getCacheLimit()) # Register the current job as taking this much space, and evict files # from the cache to make room before letting the job run. self._allocateSpaceForJob(self.jobDiskBytes) try: os.chdir(self.localTempDir) yield finally: # See how much disk space is used at the end of the job. # Not a real peak disk usage, but close enough to be useful for warning the user. # TODO: Push this logic into the abstract file store diskUsed = getDirSizeRecursively(self.localTempDir) logString = ("Job {jobName} used {percent:.2f}% ({humanDisk}B [{disk}B] used, " "{humanRequestedDisk}B [{requestedDisk}B] requested) at the end of " "its run.".format(jobName=self.jobName, percent=(float(diskUsed) / self.jobDiskBytes * 100 if self.jobDiskBytes > 0 else 0.0), humanDisk=bytes2human(diskUsed), disk=diskUsed, humanRequestedDisk=bytes2human(self.jobDiskBytes), requestedDisk=self.jobDiskBytes)) self.logToMaster(logString, level=logging.DEBUG) if diskUsed > self.jobDiskBytes: self.logToMaster("Job used more disk than requested. Please reconsider modifying " "the user script to avoid the chance of failure due to " "incorrectly requested resources. " + logString, level=logging.WARNING) # Go back up to the per-worker local temp directory. os.chdir(startingDir) self.cleanupInProgress = True # Record that our job is no longer using its space, and clean up # its temp dir and database entry. self._deallocateSpaceForJob() def writeGlobalFile(self, localFileName, cleanup=False): # Work out the file itself absLocalFileName = self._resolveAbsoluteLocalPath(localFileName) # And get its size fileSize = os.stat(absLocalFileName).st_size # Work out who is making the file creatorID = self.jobGraph.jobStoreID # Create an empty file to get an ID. # TODO: this empty file could leak if we die now... fileID = self.jobStore.getEmptyFileStoreID(creatorID, cleanup) # Work out who we are pid = os.getpid() # Work out where the file ought to go in the cache cachePath = self._getNewCachingPath(fileID) # Create a file in uploadable state and a reference, in the same transaction. # Say the reference is an immutable reference self._write([('INSERT INTO files VALUES (?, ?, ?, ?, ?)', (fileID, cachePath, fileSize, 'uploadable', pid)), ('INSERT INTO refs VALUES (?, ?, ?, ?)', (absLocalFileName, fileID, creatorID, 'immutable'))]) if absLocalFileName.startswith(self.localTempDir): # We should link into the cache, because the upload is coming from our local temp dir try: # Try and hardlink the file into the cache. # This can only fail if the system doesn't have hardlinks, or the # file we're trying to link to has too many hardlinks to it # already, or something. os.link(absLocalFileName, cachePath) linkedToCache = True logger.debug('Linked file %s into cache at %s; deferring write to job store', localFileName, cachePath) # Don't do the upload now. Let it be deferred until later (when the job is committing). except OSError: # We couldn't make the link for some reason linkedToCache = False else: # The tests insist that if you are uploading a file from outside # the local temp dir, it should not be linked into the cache. linkedToCache = False if not linkedToCache: # If we can't do the link into the cache and upload from there, we # have to just upload right away. We can't guarantee sufficient # space to make a full copy in the cache, if we aren't allowed to # take this copy away from the writer. # Change the reference to 'mutable', which it will be. # And drop the file altogether. self._write([('UPDATE refs SET state = ? WHERE path = ? AND file_id = ?', ('mutable', absLocalFileName, fileID)), ('DELETE FROM files WHERE id = ?', (fileID,))]) # Save the file to the job store right now logger.debug('Actually executing upload for file %s', fileID) self.jobStore.updateFile(fileID, absLocalFileName) # Ship out the completed FileID object with its real size. return FileID.forPath(fileID, absLocalFileName) def readGlobalFile(self, fileStoreID, userPath=None, cache=True, mutable=False, symlink=False): if str(fileStoreID) in self.filesToDelete: # File has already been deleted raise FileNotFoundError('Attempted to read deleted file: {}'.format(fileStoreID)) if userPath is not None: # Validate the destination we got localFilePath = self._resolveAbsoluteLocalPath(userPath) if os.path.exists(localFilePath): raise RuntimeError(' File %s ' % localFilePath + ' exists. Cannot Overwrite.') else: # Make our own destination localFilePath = self.getLocalTempFileName() # Work out who we are pid = os.getpid() # And what job we are operating on behalf of readerID = self.jobGraph.jobStoreID if cache: # We want to use the cache if mutable: return self._readGlobalFileMutablyWithCache(fileStoreID, localFilePath, readerID) else: return self._readGlobalFileWithCache(fileStoreID, localFilePath, symlink, readerID) else: # We do not want to use the cache return self._readGlobalFileWithoutCache(fileStoreID, localFilePath, mutable, symlink, readerID) def _readGlobalFileWithoutCache(self, fileStoreID, localFilePath, mutable, symlink, readerID): """ Read a file without putting it into the cache. :param toil.fileStores.FileID fileStoreID: job store id for the file :param str localFilePath: absolute destination path. Already known not to exist. :param bool mutable: Whether a mutable copy should be created, instead of a hard link or symlink. :param bool symlink: Whether a symlink is acceptable. :param str readerID: Job ID of the job reading the file. :return: An absolute path to a local, temporary copy of or link to the file keyed by fileStoreID. :rtype: str """ # We would like to read directly from the backing job store, since # we don't want to cache the result. However, we may be trying to # read a file that is 'uploadable' or 'uploading' and hasn't hit # the backing job store yet. # Try and make a 'copying' reference to such a file self._write([('INSERT INTO refs SELECT ?, id, ?, ? FROM files WHERE id = ? AND (state = ? OR state = ?)', (localFilePath, readerID, 'copying', fileStoreID, 'uploadable', 'uploading'))]) # See if we got it have_reference = False for row in self.cur.execute('SELECT COUNT(*) FROM refs WHERE path = ? and file_id = ?', (localFilePath, fileStoreID)): have_reference = row[0] > 0 if have_reference: # If we succeed, copy the file. We know the job has space for it # because if we didn't do this we'd be getting a fresh copy from # the job store. # Find where the file is cached cachedPath = None for row in self.cur.execute('SELECT path FROM files WHERE id = ?', (fileStoreID,)): cachedPath = row[0] if cachedPath is None: raise RuntimeError('File %s went away while we had a reference to it!' % fileStoreID) if self.forceDownloadDelay is not None: # Wait around to simulate a big file for testing time.sleep(self.forceDownloadDelay) atomic_copy(cachedPath, localFilePath) # Change the reference to mutable self._write([('UPDATE refs SET state = ? WHERE path = ? and file_id = ?', ('mutable', localFilePath, fileStoreID))]) else: # If we fail, the file isn't cached here in 'uploadable' or # 'uploading' state, so that means it must actually be in the # backing job store, so we can get it from the backing job store. # Create a 'mutable' reference (even if we end up with a link) # so we can see this file in deleteLocalFile. self._write([('INSERT INTO refs VALUES (?, ?, ?, ?)', (localFilePath, fileStoreID, readerID, 'mutable'))]) if self.forceDownloadDelay is not None: # Wait around to simulate a big file for testing time.sleep(self.forceDownloadDelay) # Just read directly if mutable or self.forceNonFreeCaching: # Always copy with self.jobStore.readFileStream(fileStoreID) as inStream: atomic_copyobj(inStream, localFilePath) else: # Link or maybe copy self.jobStore.readFile(fileStoreID, localFilePath, symlink=symlink) # Now we got the file, somehow. return localFilePath def _downloadToCache(self, fileStoreID, cachedPath): """ Copy a file from the file store into the cache. Will hardlink if appropriate. :param toil.fileStores.FileID fileStoreID: job store id for the file :param str cachedPath: absolute destination path in the cache. Already known not to exist. """ if self.forceDownloadDelay is not None: # Wait around to simulate a big file for testing time.sleep(self.forceDownloadDelay) if self.forceNonFreeCaching: # Always copy with self.jobStore.readFileStream(fileStoreID) as inStream: atomic_copyobj(inStream, cachedPath) else: # Link or maybe copy self.jobStore.readFile(fileStoreID, cachedPath, symlink=False) def _readGlobalFileMutablyWithCache(self, fileStoreID, localFilePath, readerID): """ Read a mutable copy of a file, putting it into the cache if possible. :param toil.fileStores.FileID fileStoreID: job store id for the file :param str localFilePath: absolute destination path. Already known not to exist. :param str readerID: Job ID of the job reading the file. :return: An absolute path to a local, temporary copy of or link to the file keyed by fileStoreID. :rtype: str """ # Work out who we are pid = os.getpid() # Work out where to cache the file if it isn't cached already cachedPath = self._getNewCachingPath(fileStoreID) # Start a loop until we can do one of these while True: # Try and create a downloading entry if no entry exists logger.debug('Trying to make file record for id %s', fileStoreID) self._write([('INSERT OR IGNORE INTO files VALUES (?, ?, ?, ?, ?)', (fileStoreID, cachedPath, self.getGlobalFileSize(fileStoreID), 'downloading', pid))]) # See if we won the race self.cur.execute('SELECT COUNT(*) FROM files WHERE id = ? AND state = ? AND owner = ?', (fileStoreID, 'downloading', pid)) if self.cur.fetchone()[0] > 0: # We are responsible for downloading the file logger.debug('We are now responsible for downloading file %s', fileStoreID) # Make sure we have space for this download. self._freeUpSpace() # Do the download into the cache. self._downloadToCache(fileStoreID, cachedPath) # Now, we may have to immediately give away this file, because # we don't have space for two copies. # If so, we can't let it go to cached state, because someone # else might make a reference to it, and we may get stuck with # two readers, one cached copy, and space for two copies total. # Make the copying reference self._write([('INSERT INTO refs VALUES (?, ?, ?, ?)', (localFilePath, fileStoreID, readerID, 'copying'))]) # Fulfill it with a full copy or by giving away the cached copy self._fulfillCopyingReference(fileStoreID, cachedPath, localFilePath) # Now we're done return localFilePath else: logger.debug('Someone else is already responsible for file %s', fileStoreID) # A record already existed for this file. # Try and create an immutable or copying reference to an entry that # is in 'cached' or 'uploadable' or 'uploading' state. # It might be uploading because *we* are supposed to be uploading it. logger.debug('Trying to make reference to file %s', fileStoreID) self._write([('INSERT INTO refs SELECT ?, id, ?, ? FROM files WHERE id = ? AND (state = ? OR state = ? OR state = ?)', (localFilePath, readerID, 'copying', fileStoreID, 'cached', 'uploadable', 'uploading'))]) # See if we got it self.cur.execute('SELECT COUNT(*) FROM refs WHERE path = ? and file_id = ?', (localFilePath, fileStoreID)) if self.cur.fetchone()[0] > 0: # The file is cached and we can copy or link it logger.debug('Obtained reference to file %s', fileStoreID) # Get the path it is actually at in the cache, instead of where we wanted to put it for row in self.cur.execute('SELECT path FROM files WHERE id = ?', (fileStoreID,)): cachedPath = row[0] while self.getCacheAvailable() < 0: # Since we now have a copying reference, see if we have used too much space. # If so, try to free up some space by deleting or uploading, but # don't loop forever if we can't get enough. self._tryToFreeUpSpace() if self.getCacheAvailable() >= 0: # We made room break # See if we have no other references and we can give away the file. # Change it to downloading owned by us if we can grab it. self._write([(""" UPDATE files SET files.owner = ?, files.state = ? WHERE files.id = ? AND files.state = ? AND files.owner IS NULL AND NOT EXISTS ( SELECT NULL FROM refs WHERE refs.file_id = files.id AND refs.state != 'mutable' ) """, (pid, 'downloading', fileStoreID, 'cached'))]) if self._giveAwayDownloadingFile(fileStoreID, cachedPath, localFilePath): # We got ownership of the file and managed to give it away. return localFilePath # If we don't have space, and we couldn't make space, and we # couldn't get exclusive control of the file to give it away, we # need to wait for one of those people with references to the file # to finish and give it up. # TODO: work out if that will never happen somehow. time.sleep(self.contentionBackoff) # OK, now we have space to make a copy. if self.forceDownloadDelay is not None: # Wait around to simulate a big file for testing time.sleep(self.forceDownloadDelay) # Make the copy atomic_copy(cachedPath, localFilePath) # Change the reference to mutable self._write([('UPDATE refs SET state = ? WHERE path = ? AND file_id = ?', ('mutable', localFilePath, fileStoreID))]) # Now we're done return localFilePath else: # We didn't get a reference. Maybe it is still downloading. logger.debug('Could not obtain reference to file %s', fileStoreID) # Loop around again and see if either we can download it or we can get a reference to it. # If we didn't get a download or a reference, adopt and do work # from dead workers and loop again. # We may have to wait for someone else's download or delete to # finish. If they die, we will notice. self._removeDeadJobs(self.con) self._stealWorkFromTheDead() self._executePendingDeletions(self.con, self.cur) # Wait for other people's downloads to progress before re-polling. time.sleep(self.contentionBackoff) def _fulfillCopyingReference(self, fileStoreID, cachedPath, localFilePath): """ For use when you own a file in 'downloading' state, and have a 'copying' reference to it. Makes a full copy from the cache, and changes 'downloading' file state to 'cached', if space can be found, or gives away the cached copy if space cannot be found. :param toil.fileStores.FileID or str fileStoreID: job store id for the file :param str cachedPath: absolute source path in the cache. :param str localFilePath: absolute destination path. Already known not to exist. """ if self.getCacheAvailable() < 0: self._tryToFreeUpSpace() if self.getCacheAvailable() < 0: # No space for the cached copy and this copy. Give this copy away. assert self._giveAwayDownloadingFile(fileStoreID, cachedPath, localFilePath) return # Otherwise we have space for the cached copy and the user copy. # Expose this file as cached so other people can copy off of it too. # Change state from downloading to cached self._write([('UPDATE files SET state = ?, owner = NULL WHERE id = ?', ('cached', fileStoreID))]) if self.forceDownloadDelay is not None: # Wait around to simulate a big file for testing time.sleep(self.forceDownloadDelay) # Make our copy atomic_copy(cachedPath, localFilePath) # Change our reference to mutable self._write([('UPDATE refs SET state = ? WHERE path = ? AND file_id = ?', ('mutable', localFilePath, fileStoreID))]) # Now we're done return def _giveAwayDownloadingFile(self, fileStoreID, cachedPath, localFilePath): """ Move a downloaded file in 'downloading' state, owned by us, from the cache to a user-specified destination path. Used when there's no room for both a cached copy of the file and the user's actual mutable copy. Returns true if the file was moved, and false if the file was not owned by us in 'downloading' state. :param toil.fileStores.FileID or str fileStoreID: job store id for the file :param str cachedPath: absolute source path in the cache. :param str localFilePath: absolute destination path. Already known not to exist. :return: True if the file is successfully moved. False if the file is not owned by us in 'downloading' state. :rtype: bool """ # Work out who we are pid = os.getpid() # See if we actually own this file and can giove it away self.cur.execute('SELECT COUNT(*) FROM files WHERE id = ? AND state = ? AND owner = ?', (fileStoreID, 'downloading', pid)) if self.cur.fetchone()[0] > 0: # Now we have exclusive control of the cached copy of the file, so we can give it away. # Don't fake a delay here; this should be a rename always. # We are giving it away shutil.move(cachedPath, localFilePath) # Record that. self._write([('UPDATE refs SET state = ? WHERE path = ? AND file_id = ?', ('mutable', localFilePath, fileStoreID)), ('DELETE FROM files WHERE id = ?', (fileStoreID,))]) # Now we're done return True else: # We don't own this file in 'downloading' state return False def _createLinkFromCache(self, cachedPath, localFilePath, symlink=True): """ Create a hardlink or symlink from the given path in the cache to the given user-provided path. Destination must not exist. Only creates a symlink if a hardlink cannot be created and symlink is true. If no link can be created, returns False. Otherwise, returns True. :param str cachedPath: absolute source path in the cache. :param str localFilePath: absolute destination path. Already known not to exist. :param bool symlink: True if a symlink is allowed, False otherwise. :return: True if the file is successfully linked. False if the file cannot be linked. :rtype: bool """ try: # Try and make the hard link. os.link(cachedPath, localFilePath) return True except OSError: if symlink: # Or symlink try: os.symlink(cachedPath, localFilePath) return True except OSError: return False else: return False def _readGlobalFileWithCache(self, fileStoreID, localFilePath, symlink, readerID): """ Read a file, putting it into the cache if possible. :param toil.fileStores.FileID or str fileStoreID: job store id for the file :param str localFilePath: absolute destination path. Already known not to exist. :param bool symlink: Whether a symlink is acceptable. :param str readerID: Job ID of the job reading the file. :return: An absolute path to a local, temporary copy of or link to the file keyed by fileStoreID. :rtype: str """ # Now we know to use the cache, and that we don't require a mutable copy. # Work out who we are pid = os.getpid() # Work out where to cache the file if it isn't cached already cachedPath = self._getNewCachingPath(fileStoreID) # Start a loop until we can do one of these while True: # Try and create a downloading entry if no entry exists. # Make sure to create a reference at the same time if it succeeds, to bill it against our job's space. # Don't create the mutable reference yet because we might not necessarily be able to clear that space. logger.debug('Trying to make file record and reference for id %s', fileStoreID) self._write([('INSERT OR IGNORE INTO files VALUES (?, ?, ?, ?, ?)', (fileStoreID, cachedPath, self.getGlobalFileSize(fileStoreID), 'downloading', pid)), ('INSERT INTO refs SELECT ?, id, ?, ? FROM files WHERE id = ? AND state = ? AND owner = ?', (localFilePath, readerID, 'immutable', fileStoreID, 'downloading', pid))]) # See if we won the race self.cur.execute('SELECT COUNT(*) FROM files WHERE id = ? AND state = ? AND owner = ?', (fileStoreID, 'downloading', pid)) if self.cur.fetchone()[0] > 0: # We are responsible for downloading the file (and we have the reference) logger.debug('We are now responsible for downloading file %s', fileStoreID) # Make sure we have space for this download. self._freeUpSpace() # Do the download into the cache. self._downloadToCache(fileStoreID, cachedPath) # Try and make the link before we let the file go to cached state. # If we fail we may end up having to give away the file we just downloaded. if self._createLinkFromCache(cachedPath, localFilePath, symlink): # We made the link! # Change file state from downloading to cached so other people can use it self._write([('UPDATE files SET state = ?, owner = NULL WHERE id = ?', ('cached', fileStoreID))]) # Now we're done! return localFilePath else: # We could not make a link. We need to make a copy. # Change the reference to copying. self._write([('UPDATE refs SET state = ? WHERE path = ? AND file_id = ?', ('copying', localFilePath, fileStoreID))]) # Fulfill it with a full copy or by giving away the cached copy self._fulfillCopyingReference(fileStoreID, cachedPath, localFilePath) # Now we're done return localFilePath else: logger.debug('Someone else is already responsible for file %s', fileStoreID) # A record already existed for this file. # Try and create an immutable reference to an entry that # is in 'cached' or 'uploadable' or 'uploading' state. # It might be uploading because *we* are supposed to be uploading it. logger.debug('Trying to make reference to file %s', fileStoreID) self._write([('INSERT INTO refs SELECT ?, id, ?, ? FROM files WHERE id = ? AND (state = ? OR state = ? OR state = ?)', (localFilePath, readerID, 'immutable', fileStoreID, 'cached', 'uploadable', 'uploading'))]) # See if we got it self.cur.execute('SELECT COUNT(*) FROM refs WHERE path = ? and file_id = ?', (localFilePath, fileStoreID)) if self.cur.fetchone()[0] > 0: # The file is cached and we can copy or link it logger.debug('Obtained reference to file %s', fileStoreID) # Get the path it is actually at in the cache, instead of where we wanted to put it for row in self.cur.execute('SELECT path FROM files WHERE id = ?', (fileStoreID,)): cachedPath = row[0] if self._createLinkFromCache(cachedPath, localFilePath, symlink): # We managed to make the link return localFilePath else: # We can't make the link. We need a copy instead. # We could change the reference to copying, see if # there's space, make the copy, try and get ahold of # the file if there isn't space, and give it away, but # we already have code for that for mutable downloads, # so just clear the reference and download mutably. self._write([('DELETE FROM refs WHERE path = ? AND file_id = ?', (localFilePath, fileStoreID))]) return self._readGlobalFileMutablyWithCache(fileStoreID, localFilePath, readerID) else: logger.debug('Could not obtain reference to file %s', fileStoreID) # If we didn't get a download or a reference, adopt and do work from dead workers and loop again. # We may have to wait for someone else's download or delete to # finish. If they die, we will notice. self._removeDeadJobs(self.con) self._stealWorkFromTheDead() self._executePendingDeletions(self.con, self.cur) # Wait for other people's downloads to progress. time.sleep(self.contentionBackoff) def readGlobalFileStream(self, fileStoreID): if str(fileStoreID) in self.filesToDelete: # File has already been deleted raise FileNotFoundError('Attempted to read deleted file: {}'.format(fileStoreID)) # TODO: can we fulfil this from the cache if the file is in the cache? # I think we can because if a job is keeping the file data on disk due to having it open, it must be paying for it itself. return self.jobStore.readFileStream(fileStoreID) def deleteLocalFile(self, fileStoreID): # What job are we operating as? jobID = self.jobID # What paths did we delete deleted = [] # What's the first path, if any, that was missing? If we encounter a # missing ref file, we will raise an error about it and stop deleting # things. missingFile = None for row in self.cur.execute('SELECT path FROM refs WHERE file_id = ? AND job_id = ?', (fileStoreID, jobID)): # Delete all the files that are references to this cached file (even mutable copies) path = row[0] if path.startswith(self.localTempDir): # It is actually in the local temp dir where we are supposed to be deleting things try: os.remove(path) except FileNotFoundError as err: if err.errno != errno.ENOENT: # Something else went wrong raise # Otherwise, file is missing, but that's fine. missingFile = path break deleted.append(path) for path in deleted: # Drop the references self._write([('DELETE FROM refs WHERE file_id = ? AND job_id = ? AND path = ?', (fileStoreID, jobID, path))]) # Now space has been revoked from the cache because that job needs its space back. # That might result in stuff having to be evicted. self._freeUpSpace() if missingFile is not None: # Now throw an error about the file we couldn't find to delete, if # any. TODO: Only users who know to call deleteLocalFile will ever # see this. We also should check at the end of the job to make # sure all the refs are intact. raise IllegalDeletionCacheError(missingFile) def deleteGlobalFile(self, fileStoreID): # Delete local copies for this job self.deleteLocalFile(fileStoreID) # Work out who we are pid = os.getpid() # Make sure nobody else has references to it for row in self.cur.execute('SELECT job_id FROM refs WHERE file_id = ? AND state != ?', (fileStoreID, 'mutable')): raise RuntimeError('Deleted file ID %s which is still in use by job %s' % (fileStoreID, row[0])) # TODO: should we just let other jobs and the cache keep the file until # it gets evicted, and only delete at the back end? # Pop the file into deleting state owned by us if it exists self._write([('UPDATE files SET state = ?, owner = ? WHERE id = ?', ('deleting', pid, fileStoreID))]) # Finish the delete if the file is present self._executePendingDeletions(self.con, self.cur) # Add the file to the list of files to be deleted from the job store # once the run method completes. self.filesToDelete.add(str(fileStoreID)) self.logToMaster('Added file with ID \'%s\' to the list of files to be' % fileStoreID + ' globally deleted.', level=logging.DEBUG) def exportFile(self, jobStoreFileID, dstUrl): # First we need to make sure the file is actually in the job store if # we have it cached and need to upload it. # We don't have to worry about the case where a different process is # uploading it because we aren't supposed to have the ID from them # until they are done. # For safety and simplicity, we just execute all pending uploads now. self._executePendingUploads(self.con, self.cur) # Then we let the job store export. TODO: let the export come from the # cache? How would we write the URL? self.jobStore.exportFile(jobStoreFileID, dstUrl) def waitForCommit(self): # We need to block on the upload thread. # We may be called even if startCommit is not called. In that # case, a new instance of this class should have been created by the # worker and ought to pick up all our work by PID via the database, and # this instance doesn't actually have to commit. if self.commitThread is not None: self.commitThread.join() return True def startCommit(self, jobState=False): # If we already started a commit (maybe with a different parameter # value?) wait on it, so we can't forget to join it later. self.waitForCommit() # Start the commit thread self.commitThread = threading.Thread(target=self.startCommitThread, args=(jobState,)) self.commitThread.start() def startCommitThread(self, jobState): """ Run in a thread to actually commit the current job. """ # Make sure the previous job is committed, if any if self.waitForPreviousCommit is not None: self.waitForPreviousCommit() try: # Reconnect to the database from this thread. The main thread can # keep using self.con and self.cur. We need to do this because # SQLite objects are tied to a thread. con = sqlite3.connect(self.dbPath) cur = con.cursor() logger.debug('Committing file uploads asynchronously') # Finish all uploads self._executePendingUploads(con, cur) # Finish all deletions out of the cache (not from the job store) self._executePendingDeletions(con, cur) if jobState: # Do all the things that make this job not redoable logger.debug('Committing file deletes and job state changes asynchronously') # Indicate any files that should be deleted once the update of # the job wrapper is completed. self.jobGraph.filesToDelete = list(self.filesToDelete) # Complete the job self.jobStore.update(self.jobGraph) # Delete any remnant jobs list(map(self.jobStore.delete, self.jobsToDelete)) # Delete any remnant files list(map(self.jobStore.deleteFile, self.filesToDelete)) # Remove the files to delete list, having successfully removed the files if len(self.filesToDelete) > 0: self.jobGraph.filesToDelete = [] # Update, removing emptying files to delete self.jobStore.update(self.jobGraph) except: self._terminateEvent.set() raise @classmethod def shutdown(cls, dir_): """ :param dir_: The cache directory, containing cache state database. Job local temp directories will be removed due to their appearance in the database. """ if os.path.isdir(dir_): # There is a caching directory to clean up # We need the database for the most recent workflow attempt so we # can clean up job temp directories. # We don't have access to a class instance, nor do we have access # to the workflow attempt number that we would need in order to # find the right database by just going to it. We can't have a link # to the current database because opening SQLite databases under # multiple names breaks SQLite's atomicity guarantees (because you # can't find the journal). # So we just go and find the cache-n.db with the largest n value, # and use that. dbFilename = None dbAttempt = float('-inf') for dbCandidate in os.listdir(dir_): # For each thing in the directory match = re.match('cache-([0-9]+).db', dbCandidate) if match and int(match.group(1)) > dbAttempt: # If it looks like a caching database and it has a higher # number than any other one we have seen, use it. dbFilename = dbCandidate dbAttempt = int(match.group(1)) if dbFilename is not None: # We found a caching database logger.debug('Connecting to latest caching database %s for cleanup', dbFilename) dbPath = os.path.join(dir_, dbFilename) if os.path.exists(dbPath): try: # The database exists, see if we can open it con = sqlite3.connect(dbPath) except: # Probably someone deleted it. pass else: # We got a database connection # Create the tables if they don't exist so deletion of dead # jobs won't fail. cls._ensureTables(con) # Remove dead jobs and their job directories (not under the # cache) cls._removeDeadJobs(con) con.close() else: logger.debug('No caching database found in %s', dir_) # Whether or not we found a database, we need to clean up the cache # directory. Delete the state DB if any and everything cached. robust_rmtree(dir_) def __del__(self): """ Cleanup function that is run when destroying the class instance that ensures that all the file writing threads exit. """ self.waitForCommit() @classmethod def _removeDeadJobs(cls, con): """ Look at the state of all jobs registered in the database, and handle them (clean up the disk) :param sqlite3.Connection con: Connection to the cache database. """ # Get a cursor cur = con.cursor() # Work out our PID for taking ownership of jobs pid = os.getpid() # Get all the dead worker PIDs workers = [] for row in cur.execute('SELECT DISTINCT worker FROM jobs WHERE worker IS NOT NULL'): workers.append(row[0]) # Work out which of them are not currently running. # TODO: account for PID reuse somehow. deadWorkers = [] for worker in workers: if not cls._pidExists(worker): deadWorkers.append(worker) # Now we know which workers are dead. # Clear them off of the jobs they had. for deadWorker in deadWorkers: cls._staticWrite(con, cur, [('UPDATE jobs SET worker = NULL WHERE worker = ?', (deadWorker,))]) if len(deadWorkers) > 0: logger.debug('Reaped %d dead workers', len(deadWorkers)) while True: # Find an unowned job. # Don't take all of them; other people could come along and want to help us with the other jobs. cur.execute('SELECT id FROM jobs WHERE worker IS NULL LIMIT 1') row = cur.fetchone() if row is None: # We cleaned up all the jobs break jobID = row[0] # Try to own this job cls._staticWrite(con, cur, [('UPDATE jobs SET worker = ? WHERE id = ? AND worker IS NULL', (pid, jobID))]) # See if we won the race cur.execute('SELECT id, tempdir FROM jobs WHERE id = ? AND worker = ?', (jobID, pid)) row = cur.fetchone() if row is None: # We didn't win the race. Try another one. continue # If we did win, delete the job and its files and temp dir cls._removeJob(con, cur, jobID) logger.debug('Cleaned up orphanded job %s', jobID) # Now we have cleaned up all the jobs that belonged to dead workers that were dead when we entered this function. toil-releases-3.24.0/src/toil/fileStores/nonCachingFileStore.py000066400000000000000000000270501362134276200244750ustar00rootroot00000000000000# Copyright (C) 2015-2018 Regents of the University of California # # 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. from __future__ import absolute_import, print_function from future import standard_library standard_library.install_aliases() from builtins import map from builtins import str from builtins import range from builtins import object from abc import abstractmethod, ABCMeta from collections import namedtuple, defaultdict from contextlib import contextmanager from functools import partial from hashlib import sha1 from future.utils import with_metaclass import base64 import dill import errno import fcntl import logging import os import shutil import stat import sys import tempfile import time import uuid from toil.lib.misc import robust_rmtree from toil.lib.objects import abstractclassmethod from toil.lib.humanize import bytes2human from toil.common import cacheDirName, getDirSizeRecursively, getFileSystemSize from toil.lib.bioio import makePublicDir from toil.resource import ModuleDescriptor from toil.fileStores.abstractFileStore import AbstractFileStore from toil.fileStores import FileID logger = logging.getLogger(__name__) if sys.version_info[0] < 3: # Define a usable FileNotFoundError as will be raised by os.oprn on a # nonexistent parent directory. FileNotFoundError = OSError class NonCachingFileStore(AbstractFileStore): def __init__(self, jobStore, jobGraph, localTempDir, waitForPreviousCommit): super(NonCachingFileStore, self).__init__(jobStore, jobGraph, localTempDir, waitForPreviousCommit) # This will be defined in the `open` method. self.jobStateFile = None self.localFileMap = defaultdict(list) @contextmanager def open(self, job): jobReqs = job.disk startingDir = os.getcwd() self.localTempDir = makePublicDir(os.path.join(self.localTempDir, str(uuid.uuid4()))) self._removeDeadJobs(self.workFlowDir) self.jobStateFile = self._createJobStateFile() freeSpace, diskSize = getFileSystemSize(self.localTempDir) if freeSpace <= 0.1 * diskSize: logger.warning('Starting job %s with less than 10%% of disk space remaining.', self.jobName) try: os.chdir(self.localTempDir) yield finally: diskUsed = getDirSizeRecursively(self.localTempDir) logString = ("Job {jobName} used {percent:.2f}% ({humanDisk}B [{disk}B] used, " "{humanRequestedDisk}B [{requestedDisk}B] requested) at the end of " "its run.".format(jobName=self.jobName, percent=(float(diskUsed) / jobReqs * 100 if jobReqs > 0 else 0.0), humanDisk=bytes2human(diskUsed), disk=diskUsed, humanRequestedDisk=bytes2human(jobReqs), requestedDisk=jobReqs)) self.logToMaster(logString, level=logging.DEBUG) if diskUsed > jobReqs: self.logToMaster("Job used more disk than requested. Consider modifying the user " "script to avoid the chance of failure due to incorrectly " "requested resources. " + logString, level=logging.WARNING) os.chdir(startingDir) # Finally delete the job from the worker os.remove(self.jobStateFile) def writeGlobalFile(self, localFileName, cleanup=False): absLocalFileName = self._resolveAbsoluteLocalPath(localFileName) creatorID = self.jobGraph.jobStoreID fileStoreID = self.jobStore.writeFile(absLocalFileName, creatorID, cleanup) self.localFileMap[fileStoreID].append(absLocalFileName) return FileID.forPath(fileStoreID, absLocalFileName) def readGlobalFile(self, fileStoreID, userPath=None, cache=True, mutable=False, symlink=False): if userPath is not None: localFilePath = self._resolveAbsoluteLocalPath(userPath) if os.path.exists(localFilePath): raise RuntimeError(' File %s ' % localFilePath + ' exists. Cannot Overwrite.') else: localFilePath = self.getLocalTempFileName() self.jobStore.readFile(fileStoreID, localFilePath, symlink=symlink) self.localFileMap[fileStoreID].append(localFilePath) return localFilePath @contextmanager def readGlobalFileStream(self, fileStoreID): with self.jobStore.readFileStream(fileStoreID) as f: yield f def exportFile(self, jobStoreFileID, dstUrl): self.jobStore.exportFile(jobStoreFileID, dstUrl) def deleteLocalFile(self, fileStoreID): try: localFilePaths = self.localFileMap.pop(fileStoreID) except KeyError: raise OSError(errno.ENOENT, "Attempting to delete a non-local file") else: for localFilePath in localFilePaths: os.remove(localFilePath) def deleteGlobalFile(self, fileStoreID): try: self.deleteLocalFile(fileStoreID) except OSError as e: if e.errno == errno.ENOENT: # the file does not exist locally, so no local deletion necessary pass else: raise self.filesToDelete.add(str(fileStoreID)) def waitForCommit(self): # there is no asynchronicity in this file store so no need to block at all return True def startCommit(self, jobState=False): # Make sure the previous job is committed, if any if self.waitForPreviousCommit is not None: self.waitForPreviousCommit() if not jobState: # All our operations that need committing are job state related return try: # Indicate any files that should be deleted once the update of # the job wrapper is completed. self.jobGraph.filesToDelete = list(self.filesToDelete) # Complete the job self.jobStore.update(self.jobGraph) # Delete any remnant jobs list(map(self.jobStore.delete, self.jobsToDelete)) # Delete any remnant files list(map(self.jobStore.deleteFile, self.filesToDelete)) # Remove the files to delete list, having successfully removed the files if len(self.filesToDelete) > 0: self.jobGraph.filesToDelete = [] # Update, removing emptying files to delete self.jobStore.update(self.jobGraph) except: self._terminateEvent.set() raise def __del__(self): """ Cleanup function that is run when destroying the class instance. Nothing to do since there are no async write events. """ pass @classmethod def _removeDeadJobs(cls, nodeInfo, batchSystemShutdown=False): """ Look at the state of all jobs registered in the individual job state files, and handle them (clean up the disk) :param str nodeInfo: The location of the workflow directory on the node. :param bool batchSystemShutdown: Is the batch system in the process of shutting down? :return: """ for jobState in cls._getAllJobStates(nodeInfo): if not cls._pidExists(jobState['jobPID']): # We need to have a race to pick someone to clean up. try: # Open the directory dirFD = os.open(jobState['jobDir'], os.O_RDONLY) except FileNotFoundError: # The cleanup has happened and we can't contest for it continue try: # Try and lock it fcntl.lockf(dirFD, fcntl.LOCK_EX | fcntl.LOCK_NB) except IOError as e: # We lost the race. Someone else is alive and has it locked. os.close(dirFD) else: # We got it logger.warning('Detected that job (%s) prematurely terminated. Fixing the ' 'state of the job on disk.', jobState['jobName']) try: if not batchSystemShutdown: logger.debug("Deleting the stale working directory.") # Delete the old work directory if it still exists. Do this only during # the life of the program and dont' do it during the batch system # cleanup. Leave that to the batch system cleanup code. robust_rmtree(jobState['jobDir']) finally: fcntl.lockf(dirFD, fcntl.LOCK_UN) os.close(dirFD) @staticmethod def _getAllJobStates(workflowDir): """ Generator function that deserializes and yields the job state for every job on the node, one at a time. :param str workflowDir: The location of the workflow directory on the node. :return: dict with keys (jobName, jobPID, jobDir) :rtype: dict """ jobStateFiles = [] # Note that the directory tree may contain files whose names are not decodable to Unicode. # So we need to work in bytes. # We require that the job state files aren't in any of those directories. for root, dirs, files in os.walk(workflowDir.encode('utf-8')): for filename in files: if filename == '.jobState'.encode('utf-8'): jobStateFiles.append(os.path.join(root, filename).decode('utf-8')) for filename in jobStateFiles: try: yield NonCachingFileStore._readJobState(filename) except IOError as e: if e.errno == 2: # job finished & deleted its jobState file since the jobState files were discovered continue else: raise @staticmethod def _readJobState(jobStateFileName): with open(jobStateFileName, 'rb') as fH: state = dill.load(fH) return state def _createJobStateFile(self): """ Create the job state file for the current job and fill in the required values. :return: Path to the job state file :rtype: str """ jobStateFile = os.path.join(self.localTempDir, '.jobState') jobState = {'jobPID': os.getpid(), 'jobName': self.jobName, 'jobDir': self.localTempDir} with open(jobStateFile + '.tmp', 'wb') as fH: dill.dump(jobState, fH) os.rename(jobStateFile + '.tmp', jobStateFile) return jobStateFile @classmethod def shutdown(cls, dir_): """ :param dir_: The workflow directory that will contain all the individual worker directories. """ cls._removeDeadJobs(dir_, batchSystemShutdown=True) toil-releases-3.24.0/src/toil/job.py000066400000000000000000002422161362134276200172470ustar00rootroot00000000000000# Copyright (C) 2015-2018 Regents of the University of California # # 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. from __future__ import absolute_import, print_function from future import standard_library standard_library.install_aliases() from builtins import zip from builtins import map from builtins import str from builtins import object from builtins import super import collections import importlib import inspect import logging import sys import os import time import dill import tempfile try: import cPickle as pickle except ImportError: import pickle from abc import ABCMeta, abstractmethod from argparse import ArgumentParser, ArgumentDefaultsHelpFormatter from contextlib import contextmanager from io import BytesIO # Python 3 compatibility imports from six import iteritems, string_types from toil.lib.expando import Expando from toil.lib.humanize import human2bytes from toil.common import Toil, addOptions, safeUnpickleFromStream from toil.deferred import DeferredFunction from toil.fileStores import FileID from toil.lib.bioio import (setLoggingFromOptions, getTotalCpuTimeAndMemoryUsage, getTotalCpuTime) from toil.resource import ModuleDescriptor from future.utils import with_metaclass logger = logging.getLogger( __name__ ) class BaseJob(object): """ Inherit from this class to add job properties to an object. If the object doesn't specify explicit requirements, these properties will fall back to the configured defaults. If the value cannot be determined, an AttributeError is raised. """ def __init__(self, requirements, unitName, displayName=None, jobName=None): cores = requirements.get('cores') memory = requirements.get('memory') disk = requirements.get('disk') preemptable = requirements.get('preemptable') if unitName: assert isinstance(unitName, (str, bytes)) if jobName: assert isinstance(jobName, (str, bytes)) self.unitName = unitName self.displayName = displayName if displayName else self.__class__.__name__ self.jobName = jobName if jobName else self.__class__.__name__ self._cores = self._parseResource('cores', cores) self._memory = self._parseResource('memory', memory) self._disk = self._parseResource('disk', disk) self._preemptable = preemptable self._config = None @property def disk(self): """ The maximum number of bytes of disk the job will require to run. """ if self._disk is not None: return self._disk elif self._config is not None: return self._config.defaultDisk else: raise AttributeError("Default value for 'disk' cannot be determined") @property def memory(self): """ The maximum number of bytes of memory the job will require to run. """ if self._memory is not None: return self._memory elif self._config is not None: return self._config.defaultMemory else: raise AttributeError("Default value for 'memory' cannot be determined") @property def cores(self): """ The number of CPU cores required. """ if self._cores is not None: return self._cores elif self._config is not None: return self._config.defaultCores else: raise AttributeError("Default value for 'cores' cannot be determined") @property def preemptable(self): """ Whether the job can be run on a preemptable node. """ if self._preemptable is not None: return self._preemptable elif self._config is not None: return self._config.defaultPreemptable else: raise AttributeError("Default value for 'preemptable' cannot be determined") @property def _requirements(self): """ Gets a dictionary of all the object's resource requirements. Unset values are defaulted to None """ return {'memory': getattr(self, 'memory', None), 'cores': getattr(self, 'cores', None), 'disk': getattr(self, 'disk', None), 'preemptable': getattr(self, 'preemptable', None)} @staticmethod def _parseResource(name, value): """ Parse a Toil job's resource requirement value and apply resource-specific type checks. If the value is a string, a binary or metric unit prefix in it will be evaluated and the corresponding integral value will be returned. :param str name: The name of the resource :param None|str|float|int value: The resource value :rtype: int|float|None >>> Job._parseResource('cores', None) >>> Job._parseResource('cores', 1), Job._parseResource('disk', 1), \ Job._parseResource('memory', 1) (1, 1, 1) >>> Job._parseResource('cores', '1G'), Job._parseResource('disk', '1G'), \ Job._parseResource('memory', '1G') (1073741824, 1073741824, 1073741824) >>> Job._parseResource('cores', 1.1) 1.1 >>> Job._parseResource('disk', 1.1) # doctest: +IGNORE_EXCEPTION_DETAIL Traceback (most recent call last): ... TypeError: The 'disk' requirement does not accept values that are of >>> Job._parseResource('memory', object()) # doctest: +IGNORE_EXCEPTION_DETAIL Traceback (most recent call last): ... TypeError: The 'memory' requirement does not accept values that are of ... """ assert name in ('memory', 'disk', 'cores') if value is None: return value elif isinstance(value, (str, bytes)): value = human2bytes(value) if isinstance(value, int): return value elif isinstance(value, float) and name == 'cores': return value else: raise TypeError("The '%s' requirement does not accept values that are of %s" % (name, type(value))) def __str__(self): printedName = "'" + self.jobName + "'" if self.unitName: printedName += ' ' + self.unitName elif self.unitName == '': printedName += ' ' + 'user passed empty string for name' return printedName class JobNode(BaseJob): """ This object bridges the job graph, job, and batchsystem classes """ def __init__(self, requirements, jobName, unitName, jobStoreID, command, displayName=None, predecessorNumber=1): super().__init__(requirements=requirements, displayName=displayName, unitName=unitName, jobName=jobName) self.jobStoreID = jobStoreID self.predecessorNumber = predecessorNumber self.command = command def __str__(self): return super().__str__() + ' ' + self.jobStoreID def __hash__(self): return hash(self.jobStoreID) def __eq__(self, other): if isinstance(other, self.__class__): return self.__dict__ == other.__dict__ return NotImplemented def __ne__(self, other): if isinstance(other, self.__class__): return not self.__eq__(other) return NotImplemented def __repr__(self): return '%s( **%r )' % (self.__class__.__name__, self.__dict__) @classmethod def fromJobGraph(cls, jobGraph): """ Takes a job graph object and returns a job node object :param toil.jobGraph.JobGraph jobGraph: A job graph object to be transformed into a job node :return: A job node object :rtype: toil.job.JobNode """ return cls(jobStoreID=jobGraph.jobStoreID, requirements=jobGraph._requirements, command=jobGraph.command, jobName=jobGraph.jobName, unitName=jobGraph.unitName, displayName=jobGraph.displayName, predecessorNumber=jobGraph.predecessorNumber) @classmethod def fromJob(cls, job, command, predecessorNumber): """ Build a job node from a job object :param toil.job.Job job: the job object to be transformed into a job node :param str command: the JobNode's command :param int predecessorNumber: the number of predecessors that must finish successfully before the job can be scheduled :return: a JobNode object representing the job object parameter :rtype: toil.job.JobNode """ return cls(jobStoreID=None, requirements=job._requirements, command=command, jobName=job.jobName, unitName=job.unitName, displayName=job.displayName, predecessorNumber=predecessorNumber) class Job(BaseJob): """ Class represents a unit of work in toil. """ def __init__(self, memory=None, cores=None, disk=None, preemptable=None, unitName=None, checkpoint=False, displayName=None): """ This method must be called by any overriding constructor. :param memory: the maximum number of bytes of memory the job will require to run. :param cores: the number of CPU cores required. :param disk: the amount of local disk space required by the job, expressed in bytes. :param preemptable: if the job can be run on a preemptable node. :param checkpoint: if any of this job's successor jobs completely fails, exhausting all their retries, remove any successor jobs and rerun this job to restart the subtree. Job must be a leaf vertex in the job graph when initially defined, see :func:`toil.job.Job.checkNewCheckpointsAreCutVertices`. :type cores: int or string convertible by toil.lib.humanize.human2bytes to an int :type disk: int or string convertible by toil.lib.humanize.human2bytes to an int :type preemptable: bool :type cache: int or string convertible by toil.lib.humanize.human2bytes to an int :type memory: int or string convertible by toil.lib.humanize.human2bytes to an int """ requirements = {'memory': memory, 'cores': cores, 'disk': disk, 'preemptable': preemptable} super().__init__(requirements=requirements, unitName=unitName, displayName=displayName) self.checkpoint = checkpoint self.displayName = displayName if displayName is not None else self.__class__.__name__ #Private class variables #See Job.addChild self._children = [] #See Job.addFollowOn self._followOns = [] #See Job.addService self._services = [] #A follow-on, service or child of a job A, is a "direct successor" of A; if B #is a direct successor of A, then A is a "direct predecessor" of B. self._directPredecessors = set() # Note that self.__module__ is not necessarily this module, i.e. job.py. It is the module # defining the class self is an instance of, which may be a subclass of Job that may be # defined in a different module. self.userModule = ModuleDescriptor.forModule(self.__module__).globalize() # Maps index paths into composite return values to lists of IDs of files containing # promised values for those return value items. An index path is a tuple of indices that # traverses a nested data structure of lists, dicts, tuples or any other type supporting # the __getitem__() protocol.. The special key `()` (the empty tuple) represents the # entire return value. self._rvs = collections.defaultdict(list) self._promiseJobStore = None self._fileStore = None self._defer = None self._tempDir = None self._succeeded = True def run(self, fileStore): """ Override this function to perform work and dynamically create successor jobs. :param toil.fileStores.abstractFileStore.AbstractFileStore fileStore: Used to create local and globally sharable temporary files and to send log messages to the leader process. :return: The return value of the function can be passed to other jobs by means of :func:`toil.job.Job.rv`. """ pass def addChild(self, childJob): """ Adds childJob to be run as child of this job. Child jobs will be run \ directly after this job's :func:`toil.job.Job.run` method has completed. :param toil.job.Job childJob: :return: childJob :rtype: toil.job.Job """ self._children.append(childJob) childJob._addPredecessor(self) return childJob def hasChild(self, childJob): """ Check if childJob is already a child of this job. :param toil.job.Job childJob: :return: True if childJob is a child of the job, else False. :rtype: bool """ return childJob in self._children def addFollowOn(self, followOnJob): """ Adds a follow-on job, follow-on jobs will be run after the child jobs and \ their successors have been run. :param toil.job.Job followOnJob: :return: followOnJob :rtype: toil.job.Job """ self._followOns.append(followOnJob) followOnJob._addPredecessor(self) return followOnJob def hasFollowOn(self, followOnJob): """ Check if given job is already a follow-on of this job. :param toil.job.Job followOnJob: :return: True if the followOnJob is a follow-on of this job, else False. :rtype: bool """ return followOnJob in self._followOns def addService(self, service, parentService=None): """ Add a service. The :func:`toil.job.Job.Service.start` method of the service will be called after the run method has completed but before any successors are run. The service's :func:`toil.job.Job.Service.stop` method will be called once the successors of the job have been run. Services allow things like databases and servers to be started and accessed by jobs in a workflow. :raises toil.job.JobException: If service has already been made the child of a job or another service. :param toil.job.Job.Service service: Service to add. :param toil.job.Job.Service parentService: Service that will be started before 'service' is started. Allows trees of services to be established. parentService must be a service of this job. :return: a promise that will be replaced with the return value from :func:`toil.job.Job.Service.start` of service in any successor of the job. :rtype: toil.job.Promise """ if parentService is not None: # Do check to ensure that parentService is a service of this job def check(services): for jS in services: if jS.service == parentService or check(jS.service._childServices): return True return False if not check(self._services): raise JobException("Parent service is not a service of the given job") return parentService._addChild(service) else: if service._hasParent: raise JobException("The service already has a parent service") service._hasParent = True jobService = ServiceJob(service) self._services.append(jobService) return jobService.rv() ##Convenience functions for creating jobs def addChildFn(self, fn, *args, **kwargs): """ Adds a function as a child job. :param fn: Function to be run as a child job with ``*args`` and ``**kwargs`` as \ arguments to this function. See toil.job.FunctionWrappingJob for reserved \ keyword arguments used to specify resource requirements. :return: The new child job that wraps fn. :rtype: toil.job.FunctionWrappingJob """ if PromisedRequirement.convertPromises(kwargs): return self.addChild(PromisedRequirementFunctionWrappingJob.create(fn, *args, **kwargs)) else: return self.addChild(FunctionWrappingJob(fn, *args, **kwargs)) def addFollowOnFn(self, fn, *args, **kwargs): """ Adds a function as a follow-on job. :param fn: Function to be run as a follow-on job with ``*args`` and ``**kwargs`` as \ arguments to this function. See toil.job.FunctionWrappingJob for reserved \ keyword arguments used to specify resource requirements. :return: The new follow-on job that wraps fn. :rtype: toil.job.FunctionWrappingJob """ if PromisedRequirement.convertPromises(kwargs): return self.addFollowOn(PromisedRequirementFunctionWrappingJob.create(fn, *args, **kwargs)) else: return self.addFollowOn(FunctionWrappingJob(fn, *args, **kwargs)) def addChildJobFn(self, fn, *args, **kwargs): """ Adds a job function as a child job. See :class:`toil.job.JobFunctionWrappingJob` for a definition of a job function. :param fn: Job function to be run as a child job with ``*args`` and ``**kwargs`` as \ arguments to this function. See toil.job.JobFunctionWrappingJob for reserved \ keyword arguments used to specify resource requirements. :return: The new child job that wraps fn. :rtype: toil.job.JobFunctionWrappingJob """ if PromisedRequirement.convertPromises(kwargs): return self.addChild(PromisedRequirementJobFunctionWrappingJob.create(fn, *args, **kwargs)) else: return self.addChild(JobFunctionWrappingJob(fn, *args, **kwargs)) def addFollowOnJobFn(self, fn, *args, **kwargs): """ Add a follow-on job function. See :class:`toil.job.JobFunctionWrappingJob` for a definition of a job function. :param fn: Job function to be run as a follow-on job with ``*args`` and ``**kwargs`` as \ arguments to this function. See toil.job.JobFunctionWrappingJob for reserved \ keyword arguments used to specify resource requirements. :return: The new follow-on job that wraps fn. :rtype: toil.job.JobFunctionWrappingJob """ if PromisedRequirement.convertPromises(kwargs): return self.addFollowOn(PromisedRequirementJobFunctionWrappingJob.create(fn, *args, **kwargs)) else: return self.addFollowOn(JobFunctionWrappingJob(fn, *args, **kwargs)) @property def tempDir(self): """ Shortcut to calling :func:`job.fileStore.getLocalTempDir`. Temp dir is created on first call and will be returned for first and future calls :return: Path to tempDir. See `job.fileStore.getLocalTempDir` :rtype: str """ if self._tempDir is None: self._tempDir = self._fileStore.getLocalTempDir() return self._tempDir def log(self, text, level=logging.INFO): """ convenience wrapper for :func:`fileStore.logToMaster` """ self._fileStore.logToMaster(text, level) @staticmethod def wrapFn(fn, *args, **kwargs): """ Makes a Job out of a function. \ Convenience function for constructor of :class:`toil.job.FunctionWrappingJob`. :param fn: Function to be run with ``*args`` and ``**kwargs`` as arguments. \ See toil.job.JobFunctionWrappingJob for reserved keyword arguments used \ to specify resource requirements. :return: The new function that wraps fn. :rtype: toil.job.FunctionWrappingJob """ if PromisedRequirement.convertPromises(kwargs): return PromisedRequirementFunctionWrappingJob.create(fn, *args, **kwargs) else: return FunctionWrappingJob(fn, *args, **kwargs) @staticmethod def wrapJobFn(fn, *args, **kwargs): """ Makes a Job out of a job function. \ Convenience function for constructor of :class:`toil.job.JobFunctionWrappingJob`. :param fn: Job function to be run with ``*args`` and ``**kwargs`` as arguments. \ See toil.job.JobFunctionWrappingJob for reserved keyword arguments used \ to specify resource requirements. :return: The new job function that wraps fn. :rtype: toil.job.JobFunctionWrappingJob """ if PromisedRequirement.convertPromises(kwargs): return PromisedRequirementJobFunctionWrappingJob.create(fn, *args, **kwargs) else: return JobFunctionWrappingJob(fn, *args, **kwargs) def encapsulate(self): """ Encapsulates the job, see :class:`toil.job.EncapsulatedJob`. Convenience function for constructor of :class:`toil.job.EncapsulatedJob`. :return: an encapsulated version of this job. :rtype: toil.job.EncapsulatedJob """ return EncapsulatedJob(self) #################################################### #The following function is used for passing return values between #job run functions #################################################### def rv(self, *path): """ Creates a *promise* (:class:`toil.job.Promise`) representing a return value of the job's run method, or, in case of a function-wrapping job, the wrapped function's return value. :param (Any) path: Optional path for selecting a component of the promised return value. If absent or empty, the entire return value will be used. Otherwise, the first element of the path is used to select an individual item of the return value. For that to work, the return value must be a list, dictionary or of any other type implementing the `__getitem__()` magic method. If the selected item is yet another composite value, the second element of the path can be used to select an item from it, and so on. For example, if the return value is `[6,{'a':42}]`, `.rv(0)` would select `6` , `rv(1)` would select `{'a':3}` while `rv(1,'a')` would select `3`. To select a slice from a return value that is slicable, e.g. tuple or list, the path element should be a `slice` object. For example, assuming that the return value is `[6, 7, 8, 9]` then `.rv(slice(1, 3))` would select `[7, 8]`. Note that slicing really only makes sense at the end of path. :return: A promise representing the return value of this jobs :meth:`toil.job.Job.run` method. :rtype: toil.job.Promise """ return Promise(self, path) def registerPromise(self, path): if self._promiseJobStore is None: raise RuntimeError('Trying to pass a promise from a promising job that is not a ' + 'predecessor of the job receiving the promise') # TODO: can we guarantee self.jobStoreID is populated and so pass that here? with self._promiseJobStore.writeFileStream() as (fileHandle, jobStoreFileID): promise = UnfulfilledPromiseSentinel(str(self), False) pickle.dump(promise, fileHandle, pickle.HIGHEST_PROTOCOL) self._rvs[path].append(jobStoreFileID) return self._promiseJobStore.config.jobStore, jobStoreFileID def prepareForPromiseRegistration(self, jobStore): """ Ensure that a promise by this job (the promissor) can register with the promissor when another job referring to the promise (the promissee) is being serialized. The promissee holds the reference to the promise (usually as part of the the job arguments) and when it is being pickled, so will the promises it refers to. Pickling a promise triggers it to be registered with the promissor. :return: """ self._promiseJobStore = jobStore #################################################### #Cycle/connectivity checking #################################################### def checkJobGraphForDeadlocks(self): """ See :func:`toil.job.Job.checkJobGraphConnected`, :func:`toil.job.Job.checkJobGraphAcyclic` and :func:`toil.job.Job.checkNewCheckpointsAreLeafVertices` for more info. :raises toil.job.JobGraphDeadlockException: if the job graph is cyclic, contains multiple roots or contains checkpoint jobs that are not leaf vertices when defined (see :func:`toil.job.Job.checkNewCheckpointsAreLeaves`). """ self.checkJobGraphConnected() self.checkJobGraphAcylic() self.checkNewCheckpointsAreLeafVertices() def getRootJobs(self): """ :return: The roots of the connected component of jobs that contains this job. \ A root is a job with no predecessors. :rtype : set of toil.job.Job instances """ roots = set() visited = set() #Function to get the roots of a job def getRoots(job): if job not in visited: visited.add(job) if len(job._directPredecessors) > 0: list(map(lambda p : getRoots(p), job._directPredecessors)) else: roots.add(job) #The following call ensures we explore all successor edges. list(map(lambda c : getRoots(c), job._children + job._followOns)) getRoots(self) return roots def checkJobGraphConnected(self): """ :raises toil.job.JobGraphDeadlockException: if :func:`toil.job.Job.getRootJobs` does \ not contain exactly one root job. As execution always starts from one root job, having multiple root jobs will \ cause a deadlock to occur. """ rootJobs = self.getRootJobs() if len(rootJobs) != 1: raise JobGraphDeadlockException("Graph does not contain exactly one" " root job: %s" % rootJobs) def checkJobGraphAcylic(self): """ :raises toil.job.JobGraphDeadlockException: if the connected component \ of jobs containing this job contains any cycles of child/followOn dependencies \ in the *augmented job graph* (see below). Such cycles are not allowed \ in valid job graphs. A follow-on edge (A, B) between two jobs A and B is equivalent \ to adding a child edge to B from (1) A, (2) from each child of A, \ and (3) from the successors of each child of A. We call each such edge \ an edge an "implied" edge. The augmented job graph is a job graph including \ all the implied edges. For a job graph G = (V, E) the algorithm is ``O(|V|^2)``. It is ``O(|V| + |E|)`` for \ a graph with no follow-ons. The former follow-on case could be improved! """ #Get the root jobs roots = self.getRootJobs() if len(roots) == 0: raise JobGraphDeadlockException("Graph contains no root jobs due to cycles") #Get implied edges extraEdges = self._getImpliedEdges(roots) #Check for directed cycles in the augmented graph visited = set() for root in roots: root._checkJobGraphAcylicDFS([], visited, extraEdges) def checkNewCheckpointsAreLeafVertices(self): """ A checkpoint job is a job that is restarted if either it fails, or if any of \ its successors completely fails, exhausting their retries. A job is a leaf it is has no successors. A checkpoint job must be a leaf when initially added to the job graph. When its \ run method is invoked it can then create direct successors. This restriction is made to simplify implementation. :raises toil.job.JobGraphDeadlockException: if there exists a job being added to the graph for which \ checkpoint=True and which is not a leaf. """ roots = self.getRootJobs() # Roots jobs of component, these are preexisting jobs in the graph # All jobs in the component of the job graph containing self jobs = set() list(map(lambda x : x._dfs(jobs), roots)) # Check for each job for which checkpoint is true that it is a cut vertex or leaf for y in [x for x in jobs if x.checkpoint]: if y not in roots: # The roots are the prexisting jobs if not Job._isLeafVertex(y): raise JobGraphDeadlockException("New checkpoint job %s is not a leaf in the job graph" % y) def defer(self, function, *args, **kwargs): """ Register a deferred function, i.e. a callable that will be invoked after the current attempt at running this job concludes. A job attempt is said to conclude when the job function (or the :meth:`toil.job.Job.run` method for class-based jobs) returns, raises an exception or after the process running it terminates abnormally. A deferred function will be called on the node that attempted to run the job, even if a subsequent attempt is made on another node. A deferred function should be idempotent because it may be called multiple times on the same node or even in the same process. More than one deferred function may be registered per job attempt by calling this method repeatedly with different arguments. If the same function is registered twice with the same or different arguments, it will be called twice per job attempt. Examples for deferred functions are ones that handle cleanup of resources external to Toil, like Docker containers, files outside the work directory, etc. :param callable function: The function to be called after this job concludes. :param list args: The arguments to the function :param dict kwargs: The keyword arguments to the function """ if self._defer is None: raise Exception('A deferred function may only be registered with a job while that job is running.') self._defer(DeferredFunction.create(function, *args, **kwargs)) #################################################### #The following nested classes are used for #creating jobtrees (Job.Runner), #and defining a service (Job.Service) #################################################### class Runner(object): """ Used to setup and run Toil workflow. """ @staticmethod def getDefaultArgumentParser(): """ Get argument parser with added toil workflow options. :returns: The argument parser used by a toil workflow with added Toil options. :rtype: :class:`argparse.ArgumentParser` """ parser = ArgumentParser(formatter_class=ArgumentDefaultsHelpFormatter) Job.Runner.addToilOptions(parser) return parser @staticmethod def getDefaultOptions(jobStore): """ Get default options for a toil workflow. :param string jobStore: A string describing the jobStore \ for the workflow. :returns: The options used by a toil workflow. :rtype: argparse.ArgumentParser values object """ parser = Job.Runner.getDefaultArgumentParser() return parser.parse_args(args=[jobStore]) @staticmethod def addToilOptions(parser): """ Adds the default toil options to an :mod:`optparse` or :mod:`argparse` parser object. :param parser: Options object to add toil options to. :type parser: optparse.OptionParser or argparse.ArgumentParser """ addOptions(parser) @staticmethod def startToil(job, options): """ Deprecated by toil.common.Toil.start. Runs the toil workflow using the given options (see Job.Runner.getDefaultOptions and Job.Runner.addToilOptions) starting with this job. :param toil.job.Job job: root job of the workflow :raises: toil.leader.FailedJobsException if at the end of function \ their remain failed jobs. :return: The return value of the root job's run function. :rtype: Any """ setLoggingFromOptions(options) with Toil(options) as toil: if not options.restart: return toil.start(job) else: return toil.restart() class Service(with_metaclass(ABCMeta, BaseJob)): """ Abstract class used to define the interface to a service. """ def __init__(self, memory=None, cores=None, disk=None, preemptable=None, unitName=None): """ Memory, core and disk requirements are specified identically to as in \ :func:`toil.job.Job.__init__`. """ requirements = {'memory': memory, 'cores': cores, 'disk': disk, 'preemptable': preemptable} super().__init__(requirements=requirements, unitName=unitName) self._childServices = [] self._hasParent = False @abstractmethod def start(self, job): """ Start the service. :param toil.job.Job job: The underlying job that is being run. Can be used to register deferred functions, or to access the fileStore for creating temporary files. :returns: An object describing how to access the service. The object must be pickleable and will be used by jobs to access the service (see :func:`toil.job.Job.addService`). """ pass @abstractmethod def stop(self, job): """ Stops the service. Function can block until complete. :param toil.job.Job job: The underlying job that is being run. Can be used to register deferred functions, or to access the fileStore for creating temporary files. """ pass def check(self): """ Checks the service is still running. :raise exceptions.RuntimeError: If the service failed, this will cause the service job to be labeled failed. :returns: True if the service is still running, else False. If False then the service job will be terminated, and considered a success. Important point: if the service job exits due to a failure, it should raise a RuntimeError, not return False! """ pass def _addChild(self, service): """ Add a child service to start up after this service has started. This should not be called by the user, instead use :func:`toil.job.Job.Service.addService` with the ``parentService`` option. :raises toil.job.JobException: If service has already been made the child of a job or another service. :param toil.job.Job.Service service: Service to add as a "child" of this service :return: a promise that will be replaced with the return value from \ :func:`toil.job.Job.Service.start` of service after the service has started. :rtype: toil.job.Promise """ if service._hasParent: raise JobException("The service already has a parent service") service._parent = True jobService = ServiceJob(service) self._childServices.append(jobService) return jobService.rv() #################################################### #Private functions #################################################### def _addPredecessor(self, predecessorJob): """ Adds a predecessor job to the set of predecessor jobs. Raises a \ RuntimeError if the job is already a predecessor. """ if predecessorJob in self._directPredecessors: raise RuntimeError("The given job is already a predecessor of this job") self._directPredecessors.add(predecessorJob) @staticmethod def _isLeafVertex(job): return len(job._children) == 0 \ and len(job._followOns) == 0 \ and len(job._services) == 0 @classmethod def _loadUserModule(cls, userModule): """ Imports and returns the module object represented by the given module descriptor. :type userModule: ModuleDescriptor """ return userModule.load() @classmethod def _loadJob(cls, command, jobStore): """ Unpickles a :class:`toil.job.Job` instance by decoding command. The command is a reference to a jobStoreFileID containing the \ pickle file for the job and a list of modules which must be imported so that \ the Job can be successfully unpickled. \ See :func:`toil.job.Job._serialiseFirstJob` and \ :func:`toil.job.Job._makeJobGraphs` to see precisely how the Job is encoded \ in the command. :param string command: encoding of the job in the job store. :param toil.jobStores.abstractJobStore.AbstractJobStore jobStore: The job store. :returns: The job referenced by the command. :rtype: toil.job.Job """ commandTokens = command.split() assert "_toil" == commandTokens[0] userModule = ModuleDescriptor.fromCommand(commandTokens[2:]) logger.debug('Loading user module %s.', userModule) userModule = cls._loadUserModule(userModule) pickleFile = commandTokens[1] # Get a directory to download the job in directory = tempfile.mkdtemp() # Initialize a blank filename so the finally below can't fail due to a # missing variable filename = '' try: # Get a filename to download the job to. # Don't use mkstemp because we would need to delete and replace the # file. # Don't use a NamedTemporaryFile context manager because its # context manager exit will crash if we deleted it. filename = os.path.join(directory, 'job') # Download the job if pickleFile == "firstJob": jobStore.readSharedFile(pickleFile, filename) else: jobStore.readFile(pickleFile, filename) # Open and unpickle with open(filename, 'rb') as fileHandle: return cls._unpickle(userModule, fileHandle, jobStore.config) # TODO: We ought to just unpickle straight from a streaming read finally: # Clean up the file if os.path.exists(filename): os.unlink(filename) # Clean up the directory we put it in # TODO: we assume nobody else put anything in the directory if os.path.exists(directory): os.rmdir(directory) @classmethod def _unpickle(cls, userModule, fileHandle, config): """ Unpickles an object graph from the given file handle while loading symbols \ referencing the __main__ module from the given userModule instead. :param userModule: :param fileHandle: An open, binary-mode file handle. :returns: """ def filter_main(module_name, class_name): try: if module_name == '__main__': return getattr(userModule, class_name) else: return getattr(importlib.import_module(module_name), class_name) except: if module_name == '__main__': logger.debug('Failed getting %s from module %s.', class_name, userModule) else: logger.debug('Failed getting %s from module %s.', class_name, module_name) raise try: unpickler = pickle.Unpickler(fileHandle) # In Python 2 with cPickle we set "find_global" unpickler.find_global = filter_main except AttributeError: # In Python 3 find_global isn't real and we are supposed to # subclass unpickler and override find_class. We can't just replace # it. But with cPickle in Pyhton 2 we can't subclass Unpickler. class FilteredUnpickler(pickle.Unpickler): def find_class(self, module, name): return filter_main(module, name) unpickler = FilteredUnpickler(fileHandle) runnable = unpickler.load() assert isinstance(runnable, BaseJob) runnable._config = config return runnable def getUserScript(self): return self.userModule def _fulfillPromises(self, returnValues, jobStore): """ Sets the values for promises using the return values from this job's run() function. """ for path, promiseFileStoreIDs in iteritems(self._rvs): if not path: # Note that its possible for returnValues to be a promise, not an actual return # value. This is the case if the job returns a promise from another job. In # either case, we just pass it on. promisedValue = returnValues else: # If there is an path ... if isinstance(returnValues, Promise): # ... and the value itself is a Promise, we need to created a new, narrower # promise and pass it on. promisedValue = Promise(returnValues.job, path) else: # Otherwise, we just select the desired component of the return value. promisedValue = returnValues for index in path: promisedValue = promisedValue[index] for promiseFileStoreID in promiseFileStoreIDs: # File may be gone if the job is a service being re-run and the accessing job is # already complete. if jobStore.fileExists(promiseFileStoreID): with jobStore.updateFileStream(promiseFileStoreID) as fileHandle: pickle.dump(promisedValue, fileHandle, pickle.HIGHEST_PROTOCOL) # Functions associated with Job.checkJobGraphAcyclic to establish that the job graph does not # contain any cycles of dependencies: def _dfs(self, visited): """ Adds the job and all jobs reachable on a directed path from current node to the given set. """ if self not in visited: visited.add(self) for successor in self._children + self._followOns: successor._dfs(visited) def _checkJobGraphAcylicDFS(self, stack, visited, extraEdges): """ DFS traversal to detect cycles in augmented job graph. """ if self not in visited: visited.add(self) stack.append(self) for successor in self._children + self._followOns + extraEdges[self]: successor._checkJobGraphAcylicDFS(stack, visited, extraEdges) assert stack.pop() == self if self in stack: stack.append(self) raise JobGraphDeadlockException("A cycle of job dependencies has been detected '%s'" % stack) @staticmethod def _getImpliedEdges(roots): """ Gets the set of implied edges. See Job.checkJobGraphAcylic """ #Get nodes in job graph nodes = set() for root in roots: root._dfs(nodes) ##For each follow-on edge calculate the extra implied edges #Adjacency list of implied edges, i.e. map of jobs to lists of jobs #connected by an implied edge extraEdges = dict([(n, []) for n in nodes]) for job in nodes: if len(job._followOns) > 0: #Get set of jobs connected by a directed path to job, starting #with a child edge reacheable = set() for child in job._children: child._dfs(reacheable) #Now add extra edges for descendant in reacheable: extraEdges[descendant] += job._followOns[:] return extraEdges #################################################### #The following functions are used to serialise #a job graph to the jobStore #################################################### def _createEmptyJobGraphForJob(self, jobStore, command=None, predecessorNumber=0): """ Create an empty job for the job. """ # set _config to determine user determined default values for resource requirements self._config = jobStore.config return jobStore.create(JobNode.fromJob(self, command=command, predecessorNumber=predecessorNumber)) def _makeJobGraphs(self, jobGraph, jobStore): """ Creates a jobGraph for each job in the job graph, recursively. """ jobsToJobGraphs = {self:jobGraph} for successors in (self._followOns, self._children): jobs = [successor._makeJobGraphs2(jobStore, jobsToJobGraphs) for successor in successors] jobGraph.stack.append(jobs) return jobsToJobGraphs def _makeJobGraphs2(self, jobStore, jobsToJobGraphs): #Make the jobGraph for the job, if necessary if self not in jobsToJobGraphs: jobGraph = self._createEmptyJobGraphForJob(jobStore, predecessorNumber=len(self._directPredecessors)) jobsToJobGraphs[self] = jobGraph #Add followOns/children to be run after the current job. for successors in (self._followOns, self._children): jobs = [successor._makeJobGraphs2(jobStore, jobsToJobGraphs) for successor in successors] jobGraph.stack.append(jobs) else: jobGraph = jobsToJobGraphs[self] #The return is a tuple stored within a job.stack #The tuple is jobStoreID, memory, cores, disk, #The predecessorID is used to establish which predecessors have been #completed before running the given Job - it is just a unique ID #per predecessor return JobNode.fromJobGraph(jobGraph) def getTopologicalOrderingOfJobs(self): """ :returns: a list of jobs such that for all pairs of indices i, j for which i < j, \ the job at index i can be run before the job at index j. :rtype: list """ ordering = [] visited = set() def getRunOrder(job): #Do not add the job to the ordering until all its predecessors have been #added to the ordering for p in job._directPredecessors: if p not in visited: return if job not in visited: visited.add(job) ordering.append(job) list(map(getRunOrder, job._children + job._followOns)) getRunOrder(self) return ordering def _serialiseJob(self, jobStore, jobsToJobGraphs, rootJobGraph): """ Pickle a job and its jobGraph to disk. """ # Pickle the job so that its run method can be run at a later time. # Drop out the children/followOns/predecessors/services - which are # all recorded within the jobStore and do not need to be stored within # the job self._children, self._followOns, self._services = [], [], [] self._directPredecessors, self._promiseJobStore = set(), None # The pickled job is "run" as the command of the job, see worker # for the mechanism which unpickles the job and executes the Job.run # method. with jobStore.writeFileStream(rootJobGraph.jobStoreID, cleanup=True) as (fileHandle, fileStoreID): pickle.dump(self, fileHandle, pickle.HIGHEST_PROTOCOL) # Note that getUserScript() may have been overridden. This is intended. If we used # self.userModule directly, we'd be getting a reference to job.py if the job was # specified as a function (as opposed to a class) since that is where FunctionWrappingJob # is defined. What we really want is the module that was loaded as __main__, # and FunctionWrappingJob overrides getUserScript() to give us just that. Only then can # filter_main() in _unpickle( ) do its job of resolving any user-defined type or function. userScript = self.getUserScript().globalize() jobsToJobGraphs[self].command = ' '.join(('_toil', fileStoreID) + userScript.toCommand()) #Update the status of the jobGraph on disk jobStore.update(jobsToJobGraphs[self]) def _serialiseServices(self, jobStore, jobGraph, rootJobGraph): """ Serialises the services for a job. """ def processService(serviceJob, depth): # Extend the depth of the services if necessary if depth == len(jobGraph.services): jobGraph.services.append([]) # Recursively call to process child services for childServiceJob in serviceJob.service._childServices: processService(childServiceJob, depth+1) # Make a job wrapper serviceJobGraph = serviceJob._createEmptyJobGraphForJob(jobStore, predecessorNumber=1) # Create the start and terminate flags. # We can't associate these with the job they belong to because # that job hasn't necessarily been saved yet. serviceJobGraph.startJobStoreID = jobStore.getEmptyFileStoreID() serviceJobGraph.terminateJobStoreID = jobStore.getEmptyFileStoreID() serviceJobGraph.errorJobStoreID = jobStore.getEmptyFileStoreID() assert jobStore.fileExists(serviceJobGraph.startJobStoreID) assert jobStore.fileExists(serviceJobGraph.terminateJobStoreID) assert jobStore.fileExists(serviceJobGraph.errorJobStoreID) # Create the service job tuple j = ServiceJobNode(jobStoreID=serviceJobGraph.jobStoreID, memory=serviceJobGraph.memory, cores=serviceJobGraph.cores, disk=serviceJobGraph.disk, preemptable=serviceJobGraph.preemptable, startJobStoreID=serviceJobGraph.startJobStoreID, terminateJobStoreID=serviceJobGraph.terminateJobStoreID, errorJobStoreID=serviceJobGraph.errorJobStoreID, jobName=serviceJobGraph.jobName, unitName=serviceJobGraph.unitName, command=serviceJobGraph.command, predecessorNumber=serviceJobGraph.predecessorNumber) # Add the service job tuple to the list of services to run jobGraph.services[depth].append(j) # Break the links between the services to stop them being serialised together #childServices = serviceJob.service._childServices serviceJob.service._childServices = None assert serviceJob._services == [] #service = serviceJob.service # Pickle the job serviceJob.pickledService = pickle.dumps(serviceJob.service, protocol=pickle.HIGHEST_PROTOCOL) serviceJob.service = None # Serialise the service job and job wrapper serviceJob._serialiseJob(jobStore, { serviceJob:serviceJobGraph }, rootJobGraph) # Restore values #serviceJob.service = service #serviceJob.service._childServices = childServices for serviceJob in self._services: processService(serviceJob, 0) self._services = [] def _serialiseJobGraph(self, jobGraph, jobStore, returnValues, firstJob): """ Pickle the graph of jobs in the jobStore. The graph is not fully serialised \ until the jobGraph itself is written to disk, this is not performed by this \ function because of the need to coordinate this operation with other updates. \ """ #Check if the job graph has created #any cycles of dependencies or has multiple roots self.checkJobGraphForDeadlocks() #Create the jobGraphs for followOns/children with jobStore.batch(): jobsToJobGraphs = self._makeJobGraphs(jobGraph, jobStore) #Get an ordering on the jobs which we use for pickling the jobs in the #correct order to ensure the promises are properly established ordering = self.getTopologicalOrderingOfJobs() assert len(ordering) == len(jobsToJobGraphs) with jobStore.batch(): # Temporarily set the jobStore locators for the promise call back functions for job in ordering: job.prepareForPromiseRegistration(jobStore) def setForServices(serviceJob): serviceJob.prepareForPromiseRegistration(jobStore) for childServiceJob in serviceJob.service._childServices: setForServices(childServiceJob) for serviceJob in job._services: setForServices(serviceJob) ordering.reverse() assert self == ordering[-1] if firstJob: #If the first job we serialise all the jobs, including the root job for job in ordering: # Pickle the services for the job job._serialiseServices(jobStore, jobsToJobGraphs[job], jobGraph) # Now pickle the job job._serialiseJob(jobStore, jobsToJobGraphs, jobGraph) else: #We store the return values at this point, because if a return value #is a promise from another job, we need to register the promise #before we serialise the other jobs self._fulfillPromises(returnValues, jobStore) #Pickle the non-root jobs for job in ordering[:-1]: # Pickle the services for the job job._serialiseServices(jobStore, jobsToJobGraphs[job], jobGraph) # Pickle the job itself job._serialiseJob(jobStore, jobsToJobGraphs, jobGraph) # Pickle any services for the job self._serialiseServices(jobStore, jobGraph, jobGraph) def _serialiseFirstJob(self, jobStore): """ Serialises the root job. Returns the wrapping job. :param toil.jobStores.abstractJobStore.AbstractJobStore jobStore: """ # Check if the workflow root is a checkpoint but not a leaf vertex. # All other job vertices in the graph are checked by checkNewCheckpointsAreLeafVertices if self.checkpoint and not Job._isLeafVertex(self): raise JobGraphDeadlockException( 'New checkpoint job %s is not a leaf in the job graph' % self) # Create first jobGraph jobGraph = self._createEmptyJobGraphForJob(jobStore=jobStore, predecessorNumber=0) # Write the graph of jobs to disk self._serialiseJobGraph(jobGraph, jobStore, None, True) jobStore.update(jobGraph) # Store the name of the first job in a file in case of restart. Up to this point the # root job is not recoverable. FIXME: "root job" or "first job", which one is it? jobStore.setRootJob(jobGraph.jobStoreID) return jobGraph def _serialiseExistingJob(self, jobGraph, jobStore, returnValues): """ Serialise an existing job. """ self._serialiseJobGraph(jobGraph, jobStore, returnValues, False) #Drop the completed command, if not dropped already jobGraph.command = None #Merge any children (follow-ons) created in the initial serialisation #with children (follow-ons) created in the subsequent scale-up. assert len(jobGraph.stack) >= 4 combinedChildren = jobGraph.stack[-1] + jobGraph.stack[-3] combinedFollowOns = jobGraph.stack[-2] + jobGraph.stack[-4] jobGraph.stack = jobGraph.stack[:-4] if len(combinedFollowOns) > 0: jobGraph.stack.append(combinedFollowOns) if len(combinedChildren) > 0: jobGraph.stack.append(combinedChildren) #################################################### #Function which worker calls to ultimately invoke #a jobs Job.run method, and then handle created #children/followOn jobs #################################################### def _run(self, jobGraph, fileStore): return self.run(fileStore) @contextmanager def _executor(self, jobGraph, stats, fileStore): """ This is the core wrapping method for running the job within a worker. It sets up the stats and logging before yielding. After completion of the body, the function will finish up the stats and logging, and starts the async update process for the job. """ if stats is not None: startTime = time.time() startClock = getTotalCpuTime() baseDir = os.getcwd() yield # If the job is not a checkpoint job, add the promise files to delete # to the list of jobStoreFileIDs to delete if not self.checkpoint: for jobStoreFileID in Promise.filesToDelete: # Make sure to wrap the job store ID in a FileID object so the file store will accept it # TODO: talk directly to the job sotre here instead. fileStore.deleteGlobalFile(FileID(jobStoreFileID, 0)) else: # Else copy them to the job wrapper to delete later jobGraph.checkpointFilesToDelete = list(Promise.filesToDelete) Promise.filesToDelete.clear() # Now indicate the asynchronous update of the job can happen fileStore.startCommit(jobState=True) # Change dir back to cwd dir, if changed by job (this is a safety issue) if os.getcwd() != baseDir: os.chdir(baseDir) # Finish up the stats if stats is not None: totalCpuTime, totalMemoryUsage = getTotalCpuTimeAndMemoryUsage() stats.jobs.append( Expando( time=str(time.time() - startTime), clock=str(totalCpuTime - startClock), class_name=self._jobName(), memory=str(totalMemoryUsage) ) ) def _runner(self, jobGraph, jobStore, fileStore, defer): """ This method actually runs the job, and serialises the next jobs. :param class jobGraph: Instance of a jobGraph object :param class jobStore: Instance of the job store :param toil.fileStores.abstractFileStore.AbstractFileStore fileStore: Instance of a cached or uncached filestore :param defer: Function yielded by open() context manager of :class:`toil.DeferredFunctionManager`, which is called to register deferred functions. :return: """ # Make deferred function registration available during run(). self._defer = defer # Make fileStore available as an attribute during run() ... self._fileStore = fileStore # ... but also pass it to run() as an argument for backwards compatibility. returnValues = self._run(jobGraph, fileStore) # Clean up state changes made for run() self._defer = None self._fileStore = None # Serialize the new jobs defined by the run method to the jobStore self._serialiseExistingJob(jobGraph, jobStore, returnValues) def _jobName(self): """ :rtype : string, used as identifier of the job class in the stats report. """ return self.displayName class JobException(Exception): """ General job exception. """ def __init__(self, message): super().__init__(message) class JobGraphDeadlockException(JobException): """ An exception raised in the event that a workflow contains an unresolvable \ dependency, such as a cycle. See :func:`toil.job.Job.checkJobGraphForDeadlocks`. """ def __init__(self, string): super().__init__(string) class FunctionWrappingJob(Job): """ Job used to wrap a function. In its `run` method the wrapped function is called. """ def __init__(self, userFunction, *args, **kwargs): """ :param callable userFunction: The function to wrap. It will be called with ``*args`` and ``**kwargs`` as arguments. The keywords ``memory``, ``cores``, ``disk``, ``preemptable`` and ``checkpoint`` are reserved keyword arguments that if specified will be used to determine the resources required for the job, as :func:`toil.job.Job.__init__`. If they are keyword arguments to the function they will be extracted from the function definition, but may be overridden by the user (as you would expect). """ # Use the user-specified requirements, if specified, else grab the default argument # from the function, if specified, else default to None if sys.version_info >= (3, 0): argSpec = inspect.getfullargspec(userFunction) else: argSpec = inspect.getargspec(userFunction) if argSpec.defaults is None: argDict = {} else: argDict = dict(list(zip(argSpec.args[-len(argSpec.defaults):], argSpec.defaults))) def resolve(key, default=None, dehumanize=False): try: # First, try constructor arguments, ... value = kwargs.pop(key) except KeyError: try: # ..., then try default value for function keyword arguments, ... value = argDict[key] except KeyError: # ... and finally fall back to a default value. value = default # Optionally, convert strings with metric or binary prefixes. if dehumanize and isinstance(value, string_types): value = human2bytes(value) return value Job.__init__(self, memory=resolve('memory', dehumanize=True), cores=resolve('cores', dehumanize=True), disk=resolve('disk', dehumanize=True), preemptable=resolve('preemptable'), checkpoint=resolve('checkpoint', default=False), unitName=resolve('name', default=None)) self.userFunctionModule = ModuleDescriptor.forModule(userFunction.__module__).globalize() self.userFunctionName = str(userFunction.__name__) self.jobName = self.userFunctionName self._args = args self._kwargs = kwargs def _getUserFunction(self): logger.debug('Loading user function %s from module %s.', self.userFunctionName, self.userFunctionModule) userFunctionModule = self._loadUserModule(self.userFunctionModule) return getattr(userFunctionModule, self.userFunctionName) def run(self,fileStore): userFunction = self._getUserFunction( ) return userFunction(*self._args, **self._kwargs) def getUserScript(self): return self.userFunctionModule def _jobName(self): return ".".join((self.__class__.__name__,self.userFunctionModule.name,self.userFunctionName)) class JobFunctionWrappingJob(FunctionWrappingJob): """ A job function is a function whose first argument is a :class:`.Job` instance that is the wrapping job for the function. This can be used to add successor jobs for the function and perform all the functions the :class:`.Job` class provides. To enable the job function to get access to the :class:`toil.fileStores.abstractFileStore.AbstractFileStore` instance (see :func:`toil.job.Job.run`), it is made a variable of the wrapping job called fileStore. To specify a job's resource requirements the following default keyword arguments can be specified: - memory - disk - cores For example to wrap a function into a job we would call:: Job.wrapJobFn(myJob, memory='100k', disk='1M', cores=0.1) """ @property def fileStore(self): return self._fileStore def run(self, fileStore): userFunction = self._getUserFunction() rValue = userFunction(*((self,) + tuple(self._args)), **self._kwargs) return rValue class PromisedRequirementFunctionWrappingJob(FunctionWrappingJob): """ Handles dynamic resource allocation using :class:`toil.job.Promise` instances. Spawns child function using parent function parameters and fulfilled promised resource requirements. """ def __init__(self, userFunction, *args, **kwargs): self._promisedKwargs = kwargs.copy() # Replace resource requirements in intermediate job with small values. kwargs.update(dict(disk='1M', memory='32M', cores=0.1)) super().__init__(userFunction, *args, **kwargs) @classmethod def create(cls, userFunction, *args, **kwargs): """ Creates an encapsulated Toil job function with unfulfilled promised resource requirements. After the promises are fulfilled, a child job function is created using updated resource values. The subgraph is encapsulated to ensure that this child job function is run before other children in the workflow. Otherwise, a different child may try to use an unresolved promise return value from the parent. """ return EncapsulatedJob(cls(userFunction, *args, **kwargs)) def run(self, fileStore): # Assumes promises are fulfilled when parent job is run self.evaluatePromisedRequirements() userFunction = self._getUserFunction() return self.addChildFn(userFunction, *self._args, **self._promisedKwargs).rv() def evaluatePromisedRequirements(self): requirements = ["disk", "memory", "cores"] # Fulfill resource requirement promises for requirement in requirements: try: if isinstance(self._promisedKwargs[requirement], PromisedRequirement): self._promisedKwargs[requirement] = self._promisedKwargs[requirement].getValue() except KeyError: pass class PromisedRequirementJobFunctionWrappingJob(PromisedRequirementFunctionWrappingJob): """ Handles dynamic resource allocation for job functions. See :class:`toil.job.JobFunctionWrappingJob` """ def run(self, fileStore): self.evaluatePromisedRequirements() userFunction = self._getUserFunction() return self.addChildJobFn(userFunction, *self._args, **self._promisedKwargs).rv() class EncapsulatedJob(Job): """ A convenience Job class used to make a job subgraph appear to be a single job. Let A be the root job of a job subgraph and B be another job we'd like to run after A and all its successors have completed, for this use encapsulate:: # Job A and subgraph, Job B A, B = A(), B() A' = A.encapsulate() A'.addChild(B) # B will run after A and all its successors have completed, A and its subgraph of # successors in effect appear to be just one job. If the job being encapsulated has predecessors (e.g. is not the root job), then the encapsulated job will inherit these predecessors. If predecessors are added to the job being encapsulated after the encapsulated job is created then the encapsulating job will NOT inherit these predecessors automatically. Care should be exercised to ensure the encapsulated job has the proper set of predecessors. The return value of an encapsulatd job (as accessed by the :func:`toil.job.Job.rv` function) is the return value of the root job, e.g. A().encapsulate().rv() and A().rv() will resolve to the same value after A or A.encapsulate() has been run. """ def __init__(self, job): """ :param toil.job.Job job: the job to encapsulate. """ # Giving the root of the subgraph the same resources as the first job in the subgraph. Job.__init__(self, **job._requirements) # Ensure that the encapsulated job has the same direct predecessors as the job # being encapsulated. if job._directPredecessors: for job_ in job._directPredecessors: job_.addChild(self) self.encapsulatedJob = job Job.addChild(self, job) # Use small resource requirements for dummy Job instance. # But not too small, or the job won't have enough resources to safely start up Toil. self.encapsulatedFollowOn = Job(disk='100M', memory='512M', cores=0.1) Job.addFollowOn(self, self.encapsulatedFollowOn) def addChild(self, childJob): return Job.addChild(self.encapsulatedFollowOn, childJob) def addService(self, service, parentService=None): return Job.addService(self.encapsulatedFollowOn, service, parentService=parentService) def addFollowOn(self, followOnJob): return Job.addFollowOn(self.encapsulatedFollowOn, followOnJob) def rv(self, *path): return self.encapsulatedJob.rv(*path) def prepareForPromiseRegistration(self, jobStore): super().prepareForPromiseRegistration(jobStore) self.encapsulatedJob.prepareForPromiseRegistration(jobStore) def getUserScript(self): return self.encapsulatedJob.getUserScript() class ServiceJobNode(JobNode): def __init__(self, jobStoreID, memory, cores, disk, preemptable, startJobStoreID, terminateJobStoreID, errorJobStoreID, unitName, jobName, command, predecessorNumber): requirements = dict(memory=memory, cores=cores, disk=disk, preemptable=preemptable) super().__init__(unitName=unitName, jobName=jobName, requirements=requirements, jobStoreID=jobStoreID, command=command, predecessorNumber=predecessorNumber) self.startJobStoreID = startJobStoreID self.terminateJobStoreID = terminateJobStoreID self.errorJobStoreID = errorJobStoreID class ServiceJob(Job): """ Job used to wrap a :class:`toil.job.Job.Service` instance. """ def __init__(self, service): """ This constructor should not be called by a user. :param service: The service to wrap in a job. :type service: toil.job.Job.Service """ Job.__init__(self, **service._requirements) # service.__module__ is the module defining the class service is an instance of. self.serviceModule = ModuleDescriptor.forModule(service.__module__).globalize() #The service to run - this will be replace before serialization with a pickled version self.service = service self.pickledService = None self.jobName = service.jobName # This references the parent job wrapper. It is initialised just before # the job is run. It is used to access the start and terminate flags. self.jobGraph = None @property def fileStore(self): return self._fileStore def run(self, fileStore): # Unpickle the service logger.debug('Loading service module %s.', self.serviceModule) userModule = self._loadUserModule(self.serviceModule) service = self._unpickle( userModule, BytesIO( self.pickledService ), fileStore.jobStore.config ) #Start the service startCredentials = service.start(self) try: #The start credentials must be communicated to processes connecting to #the service, to do this while the run method is running we #cheat and set the return value promise within the run method self._fulfillPromises(startCredentials, fileStore.jobStore) self._rvs = {} # Set this to avoid the return values being updated after the #run method has completed! #Now flag that the service is running jobs can connect to it logger.debug("Removing the start jobStoreID to indicate that establishment of the service") assert self.jobGraph.startJobStoreID != None if fileStore.jobStore.fileExists(self.jobGraph.startJobStoreID): fileStore.jobStore.deleteFile(self.jobGraph.startJobStoreID) assert not fileStore.jobStore.fileExists(self.jobGraph.startJobStoreID) #Now block until we are told to stop, which is indicated by the removal #of a file assert self.jobGraph.terminateJobStoreID != None while True: # Check for the terminate signal if not fileStore.jobStore.fileExists(self.jobGraph.terminateJobStoreID): logger.debug("Detected that the terminate jobStoreID has been removed so exiting") if not fileStore.jobStore.fileExists(self.jobGraph.errorJobStoreID): raise RuntimeError("Detected the error jobStoreID has been removed so exiting with an error") break # Check the service's status and exit if failed or complete try: if not service.check(): logger.debug("The service has finished okay, exiting") break except RuntimeError: logger.debug("Detected termination of the service") raise time.sleep(fileStore.jobStore.config.servicePollingInterval) #Avoid excessive polling # Remove link to the jobGraph self.jobGraph = None logger.debug("Service is done") finally: # The stop function is always called service.stop(self) def _run(self, jobGraph, fileStore): # Set the jobGraph for the job self.jobGraph = jobGraph #Run the job returnValues = self.run(fileStore) assert jobGraph.stack == [] assert jobGraph.services == [] # Unset the jobGraph for the job self.jobGraph = None # Set the stack to mimic what would be expected for a non-service job (this is a hack) jobGraph.stack = [[], []] return returnValues def getUserScript(self): return self.serviceModule class Promise(object): """ References a return value from a :meth:`toil.job.Job.run` or :meth:`toil.job.Job.Service.start` method as a *promise* before the method itself is run. Let T be a job. Instances of :class:`.Promise` (termed a *promise*) are returned by T.rv(), which is used to reference the return value of T's run function. When the promise is passed to the constructor (or as an argument to a wrapped function) of a different, successor job the promise will be replaced by the actual referenced return value. This mechanism allows a return values from one job's run method to be input argument to job before the former job's run function has been executed. """ _jobstore = None """ Caches the job store instance used during unpickling to prevent it from being instantiated for each promise :type: toil.jobStores.abstractJobStore.AbstractJobStore """ filesToDelete = set() """ A set of IDs of files containing promised values when we know we won't need them anymore """ def __init__(self, job, path): """ :param Job job: the job whose return value this promise references :param path: see :meth:`.Job.rv` """ self.job = job self.path = path def __reduce__(self): """ Called during pickling when a promise (an instance of this class) is about to be be pickled. Returns the Promise class and construction arguments that will be evaluated during unpickling, namely the job store coordinates of a file that will hold the promised return value. By the time the promise is about to be unpickled, that file should be populated. """ # The allocation of the file in the job store is intentionally lazy, we only allocate an # empty file in the job store if the promise is actually being pickled. This is done so # that we do not allocate files for promises that are never used. jobStoreLocator, jobStoreFileID = self.job.registerPromise(self.path) # Returning a class object here causes the pickling machinery to attempt to instantiate # the class. We will catch that with __new__ and return an the actual return value instead. return self.__class__, (jobStoreLocator, jobStoreFileID) @staticmethod def __new__(cls, *args): assert len(args) == 2 if isinstance(args[0], Job): # Regular instantiation when promise is created, before it is being pickled return super().__new__(cls) else: # Attempted instantiation during unpickling, return promised value instead return cls._resolve(*args) @classmethod def _resolve(cls, jobStoreLocator, jobStoreFileID): # Initialize the cached job store if it was never initialized in the current process or # if it belongs to a different workflow that was run earlier in the current process. if cls._jobstore is None or cls._jobstore.config.jobStore != jobStoreLocator: cls._jobstore = Toil.resumeJobStore(jobStoreLocator) cls.filesToDelete.add(jobStoreFileID) with cls._jobstore.readFileStream(jobStoreFileID) as fileHandle: # If this doesn't work then the file containing the promise may not exist or be # corrupted value = safeUnpickleFromStream(fileHandle) return value class PromisedRequirement(object): def __init__(self, valueOrCallable, *args): """ Class for dynamically allocating job function resource requirements involving :class:`toil.job.Promise` instances. Use when resource requirements depend on the return value of a parent function. PromisedRequirements can be modified by passing a function that takes the :class:`.Promise` as input. For example, let f, g, and h be functions. Then a Toil workflow can be defined as follows:: A = Job.wrapFn(f) B = A.addChildFn(g, cores=PromisedRequirement(A.rv()) C = B.addChildFn(h, cores=PromisedRequirement(lambda x: 2*x, B.rv())) :param valueOrCallable: A single Promise instance or a function that takes \*args as input parameters. :param \*args: variable length argument list :type \*args: int or .Promise """ if hasattr(valueOrCallable, '__call__'): assert len(args) != 0, 'Need parameters for PromisedRequirement function.' func = valueOrCallable else: assert len(args) == 0, 'Define a PromisedRequirement function to handle multiple arguments.' func = lambda x: x args = [valueOrCallable] self._func = dill.dumps(func) self._args = list(args) def getValue(self): """ Returns PromisedRequirement value """ func = dill.loads(self._func) return func(*self._args) @staticmethod def convertPromises(kwargs): """ Returns True if reserved resource keyword is a Promise or PromisedRequirement instance. Converts Promise instance to PromisedRequirement. :param kwargs: function keyword arguments :return: bool """ for r in ["disk", "memory", "cores"]: if isinstance(kwargs.get(r), Promise): kwargs[r] = PromisedRequirement(kwargs[r]) return True elif isinstance(kwargs.get(r), PromisedRequirement): return True return False class UnfulfilledPromiseSentinel(object): """This should be overwritten by a proper promised value. Throws an exception when unpickled.""" def __init__(self, fulfillingJobName, unpickled): self.fulfillingJobName = fulfillingJobName @staticmethod def __setstate__(stateDict): """Only called when unpickling. This won't be unpickled unless the promise wasn't resolved, so we throw an exception.""" jobName = stateDict['fulfillingJobName'] raise RuntimeError("This job was passed a promise that wasn't yet resolved when it " "ran. The job {jobName} that fulfills this promise hasn't yet " "finished. This means that there aren't enough constraints to " "ensure the current job always runs after {jobName}. Consider adding a " "follow-on indirection between this job and its parent, or adding " "this job as a child/follow-on of {jobName}.".format(jobName=jobName)) toil-releases-3.24.0/src/toil/jobGraph.py000066400000000000000000000237401362134276200202300ustar00rootroot00000000000000# Copyright (C) 2015-2018 Regents of the University of California # # 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. from __future__ import absolute_import import logging from toil.job import JobNode logger = logging.getLogger(__name__) class JobGraph(JobNode): """ A class encapsulating the minimal state of a Toil job. Instances of this class are persisted in the job store and held in memory by the master. The actual state of job objects in user scripts is persisted separately since it may be much bigger than the state managed by this class and should therefore only be held in memory for brief periods of time. """ def __init__(self, command, memory, cores, disk, unitName, jobName, preemptable, jobStoreID, remainingRetryCount, predecessorNumber, filesToDelete=None, predecessorsFinished=None, stack=None, services=None, startJobStoreID=None, terminateJobStoreID=None, errorJobStoreID=None, logJobStoreFileID=None, checkpoint=None, checkpointFilesToDelete=None, chainedJobs=None): requirements = {'memory': memory, 'cores': cores, 'disk': disk, 'preemptable': preemptable} super(JobGraph, self).__init__(command=command, requirements=requirements, unitName=unitName, jobName=jobName, jobStoreID=jobStoreID, predecessorNumber=predecessorNumber) # The number of times the job should be retried if it fails This number is reduced by # retries until it is zero and then no further retries are made self.remainingRetryCount = remainingRetryCount # This variable is used in creating a graph of jobs. If a job crashes after an update to # the jobGraph but before the list of files to remove is deleted then this list can be # used to clean them up. self.filesToDelete = filesToDelete or [] # The number of predecessor jobs of a given job. A predecessor is a job which references # this job in its stack. self.predecessorNumber = predecessorNumber # The IDs of predecessors that have finished. When len(predecessorsFinished) == # predecessorNumber then the job can be run. self.predecessorsFinished = predecessorsFinished or set() # The list of successor jobs to run. Successor jobs are stored as jobNodes. Successor # jobs are run in reverse order from the stack. self.stack = stack or [] # A jobStoreFileID of the log file for a job. This will be none unless the job failed and # the logging has been captured to be reported on the leader. self.logJobStoreFileID = logJobStoreFileID # A list of lists of service jobs to run. Each sub list is a list of service jobs # descriptions, each of which is stored as a 6-tuple of the form (jobStoreId, memory, # cores, disk, startJobStoreID, terminateJobStoreID). self.services = services or [] # An empty file in the jobStore which when deleted is used to signal that the service # should cease. self.terminateJobStoreID = terminateJobStoreID # Similarly a empty file which when deleted is used to signal that the service is # established self.startJobStoreID = startJobStoreID # An empty file in the jobStore which when deleted is used to signal that the service # should terminate signaling an error. self.errorJobStoreID = errorJobStoreID # None, or a copy of the original command string used to reestablish the job after failure. self.checkpoint = checkpoint # Files that can not be deleted until the job and its successors have completed self.checkpointFilesToDelete = checkpointFilesToDelete # Names of jobs that were run as part of this job's invocation, starting with # this job self.chainedJobs = chainedJobs def __hash__(self): return hash(self.jobStoreID) def setupJobAfterFailure(self, config): """ Reduce the remainingRetryCount if greater than zero and set the memory to be at least as big as the default memory (in case of exhaustion of memory, which is common). """ self.remainingRetryCount = max(0, self.remainingRetryCount - 1) logger.warn("Due to failure we are reducing the remaining retry count of job %s with ID %s to %s", self, self.jobStoreID, self.remainingRetryCount) # Set the default memory to be at least as large as the default, in # case this was a malloc failure (we do this because of the combined # batch system) if self.memory < config.defaultMemory: self._memory = config.defaultMemory logger.warn("We have increased the memory of the failed job %s to the default of %s bytes", self, self.memory) if self.disk < config.defaultDisk: self._disk = config.defaultDisk logger.warn("We have increased the disk of the failed job %s to the default of %s bytes", self, self.disk) def restartCheckpoint(self, jobStore): """Restart a checkpoint after the total failure of jobs in its subtree. Writes the changes to the jobStore immediately. All the checkpoint's successors will be deleted, but its retry count will *not* be decreased. Returns a list with the IDs of any successors deleted. """ assert self.checkpoint is not None successorsDeleted = [] if self.stack or self.services or self.command != None: if self.command != None: assert self.command == self.checkpoint logger.debug("Checkpoint job already has command set to run") else: self.command = self.checkpoint jobStore.update(self) # Update immediately to ensure that checkpoint # is made before deleting any remaining successors if self.stack or self.services: # If the subtree of successors is not complete restart everything logger.debug("Checkpoint job has unfinished successor jobs, deleting the jobs on the stack: %s, services: %s " % (self.stack, self.services)) # Delete everything on the stack, as these represent successors to clean # up as we restart the queue def recursiveDelete(jobGraph2): # Recursive walk the stack to delete all remaining jobs for jobs in jobGraph2.stack + jobGraph2.services: for jobNode in jobs: if jobStore.exists(jobNode.jobStoreID): recursiveDelete(jobStore.load(jobNode.jobStoreID)) else: logger.debug("Job %s has already been deleted", jobNode) if jobGraph2 != self: logger.debug("Checkpoint is deleting old successor job: %s", jobGraph2.jobStoreID) jobStore.delete(jobGraph2.jobStoreID) successorsDeleted.append(jobGraph2.jobStoreID) recursiveDelete(self) self.stack = [ [], [] ] # Initialise the job to mimic the state of a job # that has been previously serialised but which as yet has no successors self.services = [] # Empty the services # Update the jobStore to avoid doing this twice on failure and make this clean. jobStore.update(self) return successorsDeleted def getLogFileHandle(self, jobStore): """ Returns a context manager that yields a file handle to the log file """ return jobStore.readFileStream(self.logJobStoreFileID) @classmethod def fromJobNode(cls, jobNode, jobStoreID, tryCount): """ Builds a job graph from a given job node :param toil.job.JobNode jobNode: a job node object to build into a job graph :param str jobStoreID: the job store ID to assign to the resulting job graph object :param int tryCount: the number of times the resulting job graph object can be retried after failure :return: The newly created job graph object :rtype: toil.jobGraph.JobGraph """ return cls(command=jobNode.command, jobStoreID=jobStoreID, remainingRetryCount=tryCount, predecessorNumber=jobNode.predecessorNumber, unitName=jobNode.unitName, jobName=jobNode.jobName, **jobNode._requirements) def __eq__(self, other): return ( isinstance(other, self.__class__) and self.remainingRetryCount == other.remainingRetryCount and self.jobStoreID == other.jobStoreID and self.filesToDelete == other.filesToDelete and self.stack == other.stack and self.predecessorNumber == other.predecessorNumber and self.predecessorsFinished == other.predecessorsFinished and self.logJobStoreFileID == other.logJobStoreFileID) toil-releases-3.24.0/src/toil/jobStores/000077500000000000000000000000001362134276200200665ustar00rootroot00000000000000toil-releases-3.24.0/src/toil/jobStores/__init__.py000066400000000000000000000000001362134276200221650ustar00rootroot00000000000000toil-releases-3.24.0/src/toil/jobStores/abstractJobStore.py000066400000000000000000001266451362134276200237310ustar00rootroot00000000000000# Copyright (C) 2015-2016 Regents of the University of California # # 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. from __future__ import absolute_import from future import standard_library standard_library.install_aliases() from builtins import str from builtins import map from builtins import object from builtins import super import shutil import re from abc import ABCMeta, abstractmethod from contextlib import contextmanager, closing from datetime import timedelta from uuid import uuid4 # Python 3 compatibility imports from six import itervalues from six.moves.urllib.request import urlopen import six.moves.urllib.parse as urlparse from toil.lib.retry import retry_http from toil.common import safeUnpickleFromStream from toil.fileStores import FileID from toil.job import JobException from toil.lib.memoize import memoize from toil.lib.objects import abstractclassmethod from future.utils import with_metaclass try: import cPickle as pickle except ImportError: import pickle import logging logger = logging.getLogger(__name__) class InvalidImportExportUrlException(Exception): def __init__(self, url): """ :param urlparse.ParseResult url: """ super().__init__("The URL '%s' is invalid." % url.geturl()) class NoSuchJobException(Exception): """Indicates that the specified job does not exist.""" def __init__(self, jobStoreID): """ :param str jobStoreID: the jobStoreID that was mistakenly assumed to exist """ super().__init__("The job '%s' does not exist." % jobStoreID) class ConcurrentFileModificationException(Exception): """Indicates that the file was attempted to be modified by multiple processes at once.""" def __init__(self, jobStoreFileID): """ :param str jobStoreFileID: the ID of the file that was modified by multiple workers or processes concurrently """ super().__init__('Concurrent update to file %s detected.' % jobStoreFileID) class NoSuchFileException(Exception): """Indicates that the specified file does not exist.""" def __init__(self, jobStoreFileID, customName=None, *extra): """ :param str jobStoreFileID: the ID of the file that was mistakenly assumed to exist :param str customName: optionally, an alternate name for the nonexistent file :param list extra: optional extra information to add to the error message """ # Having the extra argument may help resolve the __init__() takes at # most three arguments error reported in # https://github.com/DataBiosphere/toil/issues/2589#issuecomment-481912211 if customName is None: message = "File '%s' does not exist." % jobStoreFileID else: message = "File '%s' (%s) does not exist." % (customName, jobStoreFileID) if extra: # Append extra data. message += " Extra info: " + " ".join((str(x) for x in extra)) super().__init__(message) class NoSuchJobStoreException(Exception): """Indicates that the specified job store does not exist.""" def __init__(self, locator): super().__init__("The job store '%s' does not exist, so there is nothing to restart." % locator) class JobStoreExistsException(Exception): """Indicates that the specified job store already exists.""" def __init__(self, locator): super().__init__( "The job store '%s' already exists. Use --restart to resume the workflow, or remove " "the job store with 'toil clean' to start the workflow from scratch." % locator) class AbstractJobStore(with_metaclass(ABCMeta, object)): """ Represents the physical storage for the jobs and files in a Toil workflow. """ def __init__(self): """ Create an instance of the job store. The instance will not be fully functional until either :meth:`.initialize` or :meth:`.resume` is invoked. Note that the :meth:`.destroy` method may be invoked on the object with or without prior invocation of either of these two methods. """ self.__config = None def initialize(self, config): """ Create the physical storage for this job store, allocate a workflow ID and persist the given Toil configuration to the store. :param toil.common.Config config: the Toil configuration to initialize this job store with. The given configuration will be updated with the newly allocated workflow ID. :raises JobStoreExistsException: if the physical storage for this job store already exists """ assert config.workflowID is None config.workflowID = str(uuid4()) logger.debug("The workflow ID is: '%s'" % config.workflowID) self.__config = config self.writeConfig() def writeConfig(self): """ Persists the value of the :attr:`AbstractJobStore.config` attribute to the job store, so that it can be retrieved later by other instances of this class. """ with self.writeSharedFileStream('config.pickle', isProtected=False) as fileHandle: pickle.dump(self.__config, fileHandle, pickle.HIGHEST_PROTOCOL) def resume(self): """ Connect this instance to the physical storage it represents and load the Toil configuration into the :attr:`AbstractJobStore.config` attribute. :raises NoSuchJobStoreException: if the physical storage for this job store doesn't exist """ with self.readSharedFileStream('config.pickle') as fileHandle: config = safeUnpickleFromStream(fileHandle) assert config.workflowID is not None self.__config = config @property def config(self): """ The Toil configuration associated with this job store. :rtype: toil.common.Config """ return self.__config rootJobStoreIDFileName = 'rootJobStoreID' def setRootJob(self, rootJobStoreID): """ Set the root job of the workflow backed by this job store :param str rootJobStoreID: The ID of the job to set as root """ with self.writeSharedFileStream(self.rootJobStoreIDFileName) as f: f.write(rootJobStoreID.encode('utf-8')) def loadRootJob(self): """ Loads the root job in the current job store. :raises toil.job.JobException: If no root job is set or if the root job doesn't exist in this job store :return: The root job. :rtype: toil.jobGraph.JobGraph """ try: with self.readSharedFileStream(self.rootJobStoreIDFileName) as f: rootJobStoreID = f.read().decode('utf-8') except NoSuchFileException: raise JobException('No job has been set as the root in this job store') if not self.exists(rootJobStoreID): raise JobException("The root job '%s' doesn't exist. Either the Toil workflow " "is finished or has never been started" % rootJobStoreID) return self.load(rootJobStoreID) # FIXME: This is only used in tests, why do we have it? def createRootJob(self, *args, **kwargs): """ Create a new job and set it as the root job in this job store :rtype: toil.jobGraph.JobGraph """ rootJob = self.create(*args, **kwargs) self.setRootJob(rootJob.jobStoreID) return rootJob def getRootJobReturnValue(self): """ Parse the return value from the root job. Raises an exception if the root job hasn't fulfilled its promise yet. """ # Parse out the return value from the root job with self.readSharedFileStream('rootJobReturnValue') as fH: return safeUnpickleFromStream(fH) @property @memoize def _jobStoreClasses(self): """ A list of concrete AbstractJobStore implementations whose dependencies are installed. :rtype: list[AbstractJobStore] """ jobStoreClassNames = ( "toil.jobStores.fileJobStore.FileJobStore", "toil.jobStores.googleJobStore.GoogleJobStore", "toil.jobStores.aws.jobStore.AWSJobStore", "toil.jobStores.abstractJobStore.JobStoreSupport") jobStoreClasses = [] for className in jobStoreClassNames: moduleName, className = className.rsplit('.', 1) from importlib import import_module try: module = import_module(moduleName) except ImportError: logger.debug("Unable to import '%s' as is expected if the corresponding extra was " "omitted at installation time.", moduleName) else: jobStoreClass = getattr(module, className) jobStoreClasses.append(jobStoreClass) return jobStoreClasses def _findJobStoreForUrl(self, url, export=False): """ Returns the AbstractJobStore subclass that supports the given URL. :param urlparse.ParseResult url: The given URL :param bool export: The URL for :rtype: toil.jobStore.AbstractJobStore """ for jobStoreCls in self._jobStoreClasses: if jobStoreCls._supportsUrl(url, export): return jobStoreCls raise RuntimeError("No job store implementation supports %sporting for URL '%s'" % ('ex' if export else 'im', url.geturl())) def importFile(self, srcUrl, sharedFileName=None, hardlink=False): """ Imports the file at the given URL into job store. The ID of the newly imported file is returned. If the name of a shared file name is provided, the file will be imported as such and None is returned. Currently supported schemes are: - 's3' for objects in Amazon S3 e.g. s3://bucket/key - 'file' for local files e.g. file:///local/file/path - 'http' e.g. http://someurl.com/path - 'gs' e.g. gs://bucket/file :param str srcUrl: URL that points to a file or object in the storage mechanism of a supported URL scheme e.g. a blob in an AWS s3 bucket. :param str sharedFileName: Optional name to assign to the imported file within the job store :return: The jobStoreFileId of the imported file or None if sharedFileName was given :rtype: toil.fileStores.FileID or None """ # Note that the helper method _importFile is used to read from the source and write to # destination (which is the current job store in this case). To implement any # optimizations that circumvent this, the _importFile method should be overridden by # subclasses of AbstractJobStore. srcUrl = urlparse.urlparse(srcUrl) otherCls = self._findJobStoreForUrl(srcUrl) return self._importFile(otherCls, srcUrl, sharedFileName=sharedFileName, hardlink=hardlink) def _importFile(self, otherCls, url, sharedFileName=None, hardlink=False): """ Import the file at the given URL using the given job store class to retrieve that file. See also :meth:`.importFile`. This method applies a generic approach to importing: it asks the other job store class for a stream and writes that stream as either a regular or a shared file. :param AbstractJobStore otherCls: The concrete subclass of AbstractJobStore that supports reading from the given URL and getting the file size from the URL. :param urlparse.ParseResult url: The location of the file to import. :param str sharedFileName: Optional name to assign to the imported file within the job store :return The jobStoreFileId of imported file or None if sharedFileName was given :rtype: toil.fileStores.FileID or None """ if sharedFileName is None: with self.writeFileStream() as (writable, jobStoreFileID): otherCls._readFromUrl(url, writable) return FileID(jobStoreFileID, otherCls.getSize(url)) else: self._requireValidSharedFileName(sharedFileName) with self.writeSharedFileStream(sharedFileName) as writable: otherCls._readFromUrl(url, writable) return None def exportFile(self, jobStoreFileID, dstUrl): """ Exports file to destination pointed at by the destination URL. Refer to :meth:`.AbstractJobStore.importFile` documentation for currently supported URL schemes. Note that the helper method _exportFile is used to read from the source and write to destination. To implement any optimizations that circumvent this, the _exportFile method should be overridden by subclasses of AbstractJobStore. :param str jobStoreFileID: The id of the file in the job store that should be exported. :param str dstUrl: URL that points to a file or object in the storage mechanism of a supported URL scheme e.g. a blob in an AWS s3 bucket. """ dstUrl = urlparse.urlparse(dstUrl) otherCls = self._findJobStoreForUrl(dstUrl, export=True) self._exportFile(otherCls, jobStoreFileID, dstUrl) def _exportFile(self, otherCls, jobStoreFileID, url): """ Refer to exportFile docstring for information about this method. :param AbstractJobStore otherCls: The concrete subclass of AbstractJobStore that supports exporting to the given URL. Note that the type annotation here is not completely accurate. This is not an instance, it's a class, but there is no way to reflect that in :pep:`484` type hints. :param str jobStoreFileID: The id of the file that will be exported. :param urlparse.ParseResult url: The parsed URL of the file to export to. """ with self.readFileStream(jobStoreFileID) as readable: otherCls._writeToUrl(readable, url) @abstractclassmethod def getSize(cls, url): """ returns the size in bytes of the file at the given URL :param urlparse.ParseResult url: URL that points to a file or object in the storage mechanism of a supported URL scheme e.g. a blob in an AWS s3 bucket. """ raise NotImplementedError @abstractclassmethod def _readFromUrl(cls, url, writable): """ Reads the contents of the object at the specified location and writes it to the given writable stream. Refer to :func:`~AbstractJobStore.importFile` documentation for currently supported URL schemes. :param urlparse.ParseResult url: URL that points to a file or object in the storage mechanism of a supported URL scheme e.g. a blob in an AWS s3 bucket. :param writable: a writable stream """ raise NotImplementedError() @abstractclassmethod def _writeToUrl(cls, readable, url): """ Reads the contents of the given readable stream and writes it to the object at the specified location. Refer to AbstractJobStore.importFile documentation for currently supported URL schemes. :param urlparse.ParseResult url: URL that points to a file or object in the storage mechanism of a supported URL scheme e.g. a blob in an AWS s3 bucket. :param readable: a readable stream """ raise NotImplementedError() @abstractclassmethod def _supportsUrl(cls, url, export=False): """ Returns True if the job store supports the URL's scheme. Refer to AbstractJobStore.importFile documentation for currently supported URL schemes. :param bool export: Determines if the url is supported for exported :param urlparse.ParseResult url: a parsed URL that may be supported :return bool: returns true if the cls supports the URL """ raise NotImplementedError() @abstractmethod def destroy(self): """ The inverse of :meth:`.initialize`, this method deletes the physical storage represented by this instance. While not being atomic, this method *is* at least idempotent, as a means to counteract potential issues with eventual consistency exhibited by the underlying storage mechanisms. This means that if the method fails (raises an exception), it may (and should be) invoked again. If the underlying storage mechanism is eventually consistent, even a successful invocation is not an ironclad guarantee that the physical storage vanished completely and immediately. A successful invocation only guarantees that the deletion will eventually happen. It is therefore recommended to not immediately reuse the same job store location for a new Toil workflow. """ raise NotImplementedError() def getEnv(self): """ Returns a dictionary of environment variables that this job store requires to be set in order to function properly on a worker. :rtype: dict[str,str] """ return {} # Cleanup functions def clean(self, jobCache=None): """ Function to cleanup the state of a job store after a restart. Fixes jobs that might have been partially updated. Resets the try counts and removes jobs that are not successors of the current root job. :param dict[str,toil.jobGraph.JobGraph] jobCache: if a value it must be a dict from job ID keys to JobGraph object values. Jobs will be loaded from the cache (which can be downloaded from the job store in a batch) instead of piecemeal when recursed into. """ if jobCache is None: logger.warning("Cleaning jobStore recursively. This may be slow.") # Functions to get and check the existence of jobs, using the jobCache # if present def getJob(jobId): if jobCache is not None: try: return jobCache[jobId] except KeyError: return self.load(jobId) else: return self.load(jobId) def haveJob(jobId): if jobCache is not None: if jobId in jobCache: return True else: return self.exists(jobId) else: return self.exists(jobId) def getJobs(): if jobCache is not None: return itervalues(jobCache) else: return self.jobs() # Iterate from the root jobGraph and collate all jobs that are reachable from it # All other jobs returned by self.jobs() are orphaned and can be removed reachableFromRoot = set() def getConnectedJobs(jobGraph): if jobGraph.jobStoreID in reachableFromRoot: return reachableFromRoot.add(jobGraph.jobStoreID) # Traverse jobs in stack for jobs in jobGraph.stack: for successorJobStoreID in [x.jobStoreID for x in jobs]: if (successorJobStoreID not in reachableFromRoot and haveJob(successorJobStoreID)): getConnectedJobs(getJob(successorJobStoreID)) # Traverse service jobs for jobs in jobGraph.services: for serviceJobStoreID in [x.jobStoreID for x in jobs]: if haveJob(serviceJobStoreID): assert serviceJobStoreID not in reachableFromRoot reachableFromRoot.add(serviceJobStoreID) logger.debug("Checking job graph connectivity...") getConnectedJobs(self.loadRootJob()) logger.debug("%d jobs reachable from root." % len(reachableFromRoot)) # Cleanup jobs that are not reachable from the root, and therefore orphaned jobsToDelete = [x for x in getJobs() if x.jobStoreID not in reachableFromRoot] for jobGraph in jobsToDelete: # clean up any associated files before deletion for fileID in jobGraph.filesToDelete: # Delete any files that should already be deleted logger.warn("Deleting file '%s'. It is marked for deletion but has not yet been " "removed.", fileID) self.deleteFile(fileID) # Delete the job self.delete(jobGraph.jobStoreID) jobGraphsReachableFromRoot = {id: getJob(id) for id in reachableFromRoot} # Clean up any checkpoint jobs -- delete any successors it # may have launched, and restore the job to a pristine # state jobsDeletedByCheckpoints = set() for jobGraph in [jG for jG in jobGraphsReachableFromRoot.values() if jG.checkpoint is not None]: if jobGraph.jobStoreID in jobsDeletedByCheckpoints: # This is a checkpoint that was nested within an # earlier checkpoint, so it and all its successors are # already gone. continue logger.debug("Restarting checkpointed job %s" % jobGraph) deletedThisRound = jobGraph.restartCheckpoint(self) jobsDeletedByCheckpoints |= set(deletedThisRound) for jobID in jobsDeletedByCheckpoints: del jobGraphsReachableFromRoot[jobID] # Clean up jobs that are in reachable from the root for jobGraph in jobGraphsReachableFromRoot.values(): # jobGraphs here are necessarily in reachable from root. changed = [False] # This is a flag to indicate the jobGraph state has # changed # If the job has files to delete delete them. if len(jobGraph.filesToDelete) != 0: # Delete any files that should already be deleted for fileID in jobGraph.filesToDelete: logger.critical("Removing file in job store: %s that was " "marked for deletion but not previously removed" % fileID) self.deleteFile(fileID) jobGraph.filesToDelete = [] changed[0] = True # For a job whose command is already executed, remove jobs from the stack that are # already deleted. This cleans up the case that the jobGraph had successors to run, # but had not been updated to reflect this. if jobGraph.command is None: stackSizeFn = lambda: sum(map(len, jobGraph.stack)) startStackSize = stackSizeFn() # Remove deleted jobs jobGraph.stack = [[y for y in x if self.exists(y.jobStoreID)] for x in jobGraph.stack] # Remove empty stuff from the stack jobGraph.stack = [x for x in jobGraph.stack if len(x) > 0] # Check if anything got removed if stackSizeFn() != startStackSize: changed[0] = True # Cleanup any services that have already been finished. # Filter out deleted services and update the flags for services that exist # If there are services then renew # the start and terminate flags if they have been removed def subFlagFile(jobStoreID, jobStoreFileID, flag): if self.fileExists(jobStoreFileID): return jobStoreFileID # Make a new flag newFlag = self.getEmptyFileStoreID(jobStoreID, cleanup=False) # Load the jobGraph for the service and initialise the link serviceJobGraph = getJob(jobStoreID) if flag == 1: logger.debug("Recreating a start service flag for job: %s, flag: %s", jobStoreID, newFlag) serviceJobGraph.startJobStoreID = newFlag elif flag == 2: logger.debug("Recreating a terminate service flag for job: %s, flag: %s", jobStoreID, newFlag) serviceJobGraph.terminateJobStoreID = newFlag else: logger.debug("Recreating a error service flag for job: %s, flag: %s", jobStoreID, newFlag) assert flag == 3 serviceJobGraph.errorJobStoreID = newFlag # Update the service job on disk self.update(serviceJobGraph) changed[0] = True return newFlag servicesSizeFn = lambda: sum(map(len, jobGraph.services)) startServicesSize = servicesSizeFn() def replaceFlagsIfNeeded(serviceJobNode): serviceJobNode.startJobStoreID = subFlagFile(serviceJobNode.jobStoreID, serviceJobNode.startJobStoreID, 1) serviceJobNode.terminateJobStoreID = subFlagFile(serviceJobNode.jobStoreID, serviceJobNode.terminateJobStoreID, 2) serviceJobNode.errorJobStoreID = subFlagFile(serviceJobNode.jobStoreID, serviceJobNode.errorJobStoreID, 3) # jobGraph.services is a list of lists containing serviceNodes # remove all services that no longer exist services = jobGraph.services jobGraph.services = [] for serviceList in services: existingServices = [service for service in serviceList if self.exists(service.jobStoreID)] if existingServices: jobGraph.services.append(existingServices) list(map(lambda serviceList: list(map(replaceFlagsIfNeeded, serviceList)), jobGraph.services)) if servicesSizeFn() != startServicesSize: changed[0] = True # Reset the retry count of the jobGraph if jobGraph.remainingRetryCount != self._defaultTryCount(): jobGraph.remainingRetryCount = self._defaultTryCount() changed[0] = True # This cleans the old log file which may # have been left if the jobGraph is being retried after a jobGraph failure. if jobGraph.logJobStoreFileID != None: self.deleteFile(jobGraph.logJobStoreFileID) jobGraph.logJobStoreFileID = None changed[0] = True if changed[0]: # Update, but only if a change has occurred logger.critical("Repairing job: %s" % jobGraph.jobStoreID) self.update(jobGraph) # Remove any crufty stats/logging files from the previous run logger.debug("Discarding old statistics and logs...") # We have to manually discard the stream to avoid getting # stuck on a blocking write from the job store. def discardStream(stream): """Read the stream 4K at a time until EOF, discarding all input.""" while len(stream.read(4096)) != 0: pass self.readStatsAndLogging(discardStream) logger.debug("Job store is clean") # TODO: reloading of the rootJob may be redundant here return self.loadRootJob() ########################################## # The following methods deal with creating/loading/updating/writing/checking for the # existence of jobs ########################################## @contextmanager def batch(self): """ All calls to create() with this context manager active will be performed in a batch after the context manager is released. :rtype: None """ yield @abstractmethod def create(self, jobNode): """ Creates a job graph from the given job node & writes it to the job store. :rtype: toil.jobGraph.JobGraph """ raise NotImplementedError() @abstractmethod def exists(self, jobStoreID): """ Indicates whether the job with the specified jobStoreID exists in the job store :rtype: bool """ raise NotImplementedError() # One year should be sufficient to finish any pipeline ;-) publicUrlExpiration = timedelta(days=365) @abstractmethod def getPublicUrl(self, fileName): """ Returns a publicly accessible URL to the given file in the job store. The returned URL may expire as early as 1h after its been returned. Throw an exception if the file does not exist. :param str fileName: the jobStoreFileID of the file to generate a URL for :raise NoSuchFileException: if the specified file does not exist in this job store :rtype: str """ raise NotImplementedError() @abstractmethod def getSharedPublicUrl(self, sharedFileName): """ Differs from :meth:`getPublicUrl` in that this method is for generating URLs for shared files written by :meth:`writeSharedFileStream`. Returns a publicly accessible URL to the given file in the job store. The returned URL starts with 'http:', 'https:' or 'file:'. The returned URL may expire as early as 1h after its been returned. Throw an exception if the file does not exist. :param str sharedFileName: The name of the shared file to generate a publically accessible url for. :raise NoSuchFileException: raised if the specified file does not exist in the store :rtype: str """ raise NotImplementedError() @abstractmethod def load(self, jobStoreID): """ Loads the job referenced by the given ID and returns it. :param str jobStoreID: the ID of the job to load :raise NoSuchJobException: if there is no job with the given ID :rtype: toil.jobGraph.JobGraph """ raise NotImplementedError() @abstractmethod def update(self, job): """ Persists the job in this store atomically. :param toil.jobGraph.JobGraph job: the job to write to this job store """ raise NotImplementedError() @abstractmethod def delete(self, jobStoreID): """ Removes from store atomically, can not then subsequently call load(), write(), update(), etc. with the job. This operation is idempotent, i.e. deleting a job twice or deleting a non-existent job will succeed silently. :param str jobStoreID: the ID of the job to delete from this job store """ raise NotImplementedError() def jobs(self): """ Best effort attempt to return iterator on all jobs in the store. The iterator may not return all jobs and may also contain orphaned jobs that have already finished successfully and should not be rerun. To guarantee you get any and all jobs that can be run instead construct a more expensive ToilState object :return: Returns iterator on jobs in the store. The iterator may or may not contain all jobs and may contain invalid jobs :rtype: Iterator[toil.jobGraph.JobGraph] """ raise NotImplementedError() ########################################## # The following provide an way of creating/reading/writing/updating files # associated with a given job. ########################################## @abstractmethod def writeFile(self, localFilePath, jobStoreID=None, cleanup=False): """ Takes a file (as a path) and places it in this job store. Returns an ID that can be used to retrieve the file at a later time. The file is written in a atomic manner. It will not appear in the jobStore until the write has successfully completed. :param str localFilePath: the path to the local file that will be uploaded to the job store. :param str jobStoreID: the id of a job, or None. If specified, the may be associated with that job in a job-store-specific way. This may influence the returned ID. :param bool cleanup: Whether to attempt to delete the file when the job whose jobStoreID was given as jobStoreID is deleted with jobStore.delete(job). If jobStoreID was not given, does nothing. :raise ConcurrentFileModificationException: if the file was modified concurrently during an invocation of this method :raise NoSuchJobException: if the job specified via jobStoreID does not exist FIXME: some implementations may not raise this :return: an ID referencing the newly created file and can be used to read the file in the future. :rtype: str """ raise NotImplementedError() @abstractmethod @contextmanager def writeFileStream(self, jobStoreID=None, cleanup=False): """ Similar to writeFile, but returns a context manager yielding a tuple of 1) a file handle which can be written to and 2) the ID of the resulting file in the job store. The yielded file handle does not need to and should not be closed explicitly. The file is written in a atomic manner. It will not appear in the jobStore until the write has successfully completed. :param str jobStoreID: the id of a job, or None. If specified, the may be associated with that job in a job-store-specific way. This may influence the returned ID. :param bool cleanup: Whether to attempt to delete the file when the job whose jobStoreID was given as jobStoreID is deleted with jobStore.delete(job). If jobStoreID was not given, does nothing. :raise ConcurrentFileModificationException: if the file was modified concurrently during an invocation of this method :raise NoSuchJobException: if the job specified via jobStoreID does not exist FIXME: some implementations may not raise this :return: an ID that references the newly created file and can be used to read the file in the future. :rtype: str """ raise NotImplementedError() @abstractmethod def getEmptyFileStoreID(self, jobStoreID=None, cleanup=False): """ Creates an empty file in the job store and returns its ID. Call to fileExists(getEmptyFileStoreID(jobStoreID)) will return True. :param str jobStoreID: the id of a job, or None. If specified, the may be associated with that job in a job-store-specific way. This may influence the returned ID. :param bool cleanup: Whether to attempt to delete the file when the job whose jobStoreID was given as jobStoreID is deleted with jobStore.delete(job). If jobStoreID was not given, does nothing. :return: a jobStoreFileID that references the newly created file and can be used to reference the file in the future. :rtype: str """ raise NotImplementedError() @abstractmethod def readFile(self, jobStoreFileID, localFilePath, symlink=False): """ Copies or hard links the file referenced by jobStoreFileID to the given local file path. The version will be consistent with the last copy of the file written/updated. If the file in the job store is later modified via updateFile or updateFileStream, it is implementation-defined whether those writes will be visible at localFilePath. The file is copied in an atomic manner. It will not appear in the local file system until the copy has completed. The file at the given local path may not be modified after this method returns! :param str jobStoreFileID: ID of the file to be copied :param str localFilePath: the local path indicating where to place the contents of the given file in the job store :param bool symlink: whether the reader can tolerate a symlink. If set to true, the job store may create a symlink instead of a full copy of the file or a hard link. """ raise NotImplementedError() @abstractmethod @contextmanager def readFileStream(self, jobStoreFileID): """ Similar to readFile, but returns a context manager yielding a file handle which can be read from. The yielded file handle does not need to and should not be closed explicitly. :param str jobStoreFileID: ID of the file to get a readable file handle for """ raise NotImplementedError() @abstractmethod def deleteFile(self, jobStoreFileID): """ Deletes the file with the given ID from this job store. This operation is idempotent, i.e. deleting a file twice or deleting a non-existent file will succeed silently. :param str jobStoreFileID: ID of the file to delete """ raise NotImplementedError() @abstractmethod def fileExists(self, jobStoreFileID): """ Determine whether a file exists in this job store. :param str jobStoreFileID: an ID referencing the file to be checked :rtype: bool """ raise NotImplementedError() @abstractmethod def getFileSize(self, jobStoreFileID): """ Get the size of the given file in bytes, or 0 if it does not exist when queried. Note that job stores which encrypt files might return overestimates of file sizes, since the encrypted file may have been padded to the nearest block, augmented with an initialization vector, etc. :param str jobStoreFileID: an ID referencing the file to be checked :rtype: int """ raise NotImplementedError() @abstractmethod def updateFile(self, jobStoreFileID, localFilePath): """ Replaces the existing version of a file in the job store. Throws an exception if the file does not exist. :param str jobStoreFileID: the ID of the file in the job store to be updated :param str localFilePath: the local path to a file that will overwrite the current version in the job store :raise ConcurrentFileModificationException: if the file was modified concurrently during an invocation of this method :raise NoSuchFileException: if the specified file does not exist """ raise NotImplementedError() @abstractmethod def updateFileStream(self, jobStoreFileID): """ Replaces the existing version of a file in the job store. Similar to writeFile, but returns a context manager yielding a file handle which can be written to. The yielded file handle does not need to and should not be closed explicitly. :param str jobStoreFileID: the ID of the file in the job store to be updated :raise ConcurrentFileModificationException: if the file was modified concurrently during an invocation of this method :raise NoSuchFileException: if the specified file does not exist """ raise NotImplementedError() ########################################## # The following methods deal with shared files, i.e. files not associated # with specific jobs. ########################################## sharedFileNameRegex = re.compile(r'^[a-zA-Z0-9._-]+$') # FIXME: Rename to updateSharedFileStream @abstractmethod @contextmanager def writeSharedFileStream(self, sharedFileName, isProtected=None): """ Returns a context manager yielding a writable file handle to the global file referenced by the given name. File will be created in an atomic manner. :param str sharedFileName: A file name matching AbstractJobStore.fileNameRegex, unique within this job store :param bool isProtected: True if the file must be encrypted, None if it may be encrypted or False if it must be stored in the clear. :raise ConcurrentFileModificationException: if the file was modified concurrently during an invocation of this method """ raise NotImplementedError() @abstractmethod @contextmanager def readSharedFileStream(self, sharedFileName): """ Returns a context manager yielding a readable file handle to the global file referenced by the given name. :param str sharedFileName: A file name matching AbstractJobStore.fileNameRegex, unique within this job store """ raise NotImplementedError() @abstractmethod def writeStatsAndLogging(self, statsAndLoggingString): """ Adds the given statistics/logging string to the store of statistics info. :param str statsAndLoggingString: the string to be written to the stats file :raise ConcurrentFileModificationException: if the file was modified concurrently during an invocation of this method """ raise NotImplementedError() @abstractmethod def readStatsAndLogging(self, callback, readAll=False): """ Reads stats/logging strings accumulated by the writeStatsAndLogging() method. For each stats/logging string this method calls the given callback function with an open, readable file handle from which the stats string can be read. Returns the number of stats/logging strings processed. Each stats/logging string is only processed once unless the readAll parameter is set, in which case the given callback will be invoked for all existing stats/logging strings, including the ones from a previous invocation of this method. :param Callable callback: a function to be applied to each of the stats file handles found :param bool readAll: a boolean indicating whether to read the already processed stats files in addition to the unread stats files :raise ConcurrentFileModificationException: if the file was modified concurrently during an invocation of this method :return: the number of stats files processed :rtype: int """ raise NotImplementedError() ## Helper methods for subclasses def _defaultTryCount(self): return int(self.config.retryCount + 1) @classmethod def _validateSharedFileName(cls, sharedFileName): return bool(cls.sharedFileNameRegex.match(sharedFileName)) @classmethod def _requireValidSharedFileName(cls, sharedFileName): if not cls._validateSharedFileName(sharedFileName): raise ValueError("Not a valid shared file name: '%s'." % sharedFileName) class JobStoreSupport(with_metaclass(ABCMeta, AbstractJobStore)): @classmethod def _supportsUrl(cls, url, export=False): return url.scheme.lower() in ('http', 'https', 'ftp') and not export @classmethod def getSize(cls, url): if url.scheme.lower() == 'ftp': return None for attempt in retry_http(): with attempt: with closing(urlopen(url.geturl())) as readable: # just read the header for content length return int(readable.info().get('content-length')) @classmethod def _readFromUrl(cls, url, writable): for attempt in retry_http(): with attempt: with closing(urlopen(url.geturl())) as readable: shutil.copyfileobj(readable, writable) toil-releases-3.24.0/src/toil/jobStores/aws/000077500000000000000000000000001362134276200206605ustar00rootroot00000000000000toil-releases-3.24.0/src/toil/jobStores/aws/__init__.py000066400000000000000000000000001362134276200227570ustar00rootroot00000000000000toil-releases-3.24.0/src/toil/jobStores/aws/jobStore.py000066400000000000000000002027531362134276200230320ustar00rootroot00000000000000# Copyright (C) 2015-2016 Regents of the University of California # # 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. from __future__ import absolute_import from future import standard_library standard_library.install_aliases() from builtins import str from builtins import range from contextlib import contextmanager, closing import logging try: import cPickle as pickle except ImportError: import pickle import re import time import uuid import base64 import hashlib import itertools import urllib.parse import urllib.request, urllib.parse, urllib.error from io import BytesIO # Python 3 compatibility imports from six.moves import StringIO, reprlib from toil.lib.memoize import strict_bool from toil.lib.exceptions import panic from toil.lib.objects import InnerClass import boto3 import boto.s3 import boto.sdb from boto.exception import S3CreateError from boto.exception import SDBResponseError, S3ResponseError import botocore.session import botocore.credentials from toil.lib.compatibility import compat_bytes, compat_plain, USING_PYTHON2 from toil.lib.misc import AtomicFileCreate from toil.fileStores import FileID from toil.jobStores.abstractJobStore import (AbstractJobStore, NoSuchJobException, ConcurrentFileModificationException, NoSuchFileException, NoSuchJobStoreException, JobStoreExistsException) from toil.jobStores.aws.utils import (SDBHelper, retry_sdb, no_such_sdb_domain, sdb_unavailable, monkeyPatchSdbConnection, retry_s3, retryable_s3_errors, bucket_location_to_region, region_to_bucket_location, copyKeyMultipart, uploadFromPath, chunkedFileUpload, fileSizeAndTime) from toil.jobStores.utils import WritablePipe, ReadablePipe from toil.jobGraph import JobGraph import toil.lib.encryption as encryption # Make sure to use credential caching when talking to Amazon via boto3 # See https://github.com/boto/botocore/pull/1338/ botocore_session = botocore.session.get_session() botocore_session.get_component('credential_provider').get_provider('assume-role').cache = botocore.credentials.JSONFileCache() boto3_session = boto3.Session(botocore_session=botocore_session) s3_boto3_resource = boto3_session.resource('s3') s3_boto3_client = boto3_session.client('s3') log = logging.getLogger(__name__) class AWSJobStore(AbstractJobStore): """ A job store that uses Amazon's S3 for file storage and SimpleDB for storing job info and enforcing strong consistency on the S3 file storage. There will be SDB domains for jobs and files and a versioned S3 bucket for file contents. Job objects are pickled, compressed, partitioned into chunks of 1024 bytes and each chunk is stored as a an attribute of the SDB item representing the job. UUIDs are used to identify jobs and files. """ # Dots in bucket names should be avoided because bucket names are used in HTTPS bucket # URLs where the may interfere with the certificate common name. We use a double # underscore as a separator instead. # bucketNameRe = re.compile(r'^[a-z0-9][a-z0-9-]+[a-z0-9]$') # See http://docs.aws.amazon.com/AmazonS3/latest/dev/BucketRestrictions.html # minBucketNameLen = 3 maxBucketNameLen = 63 maxNameLen = 10 nameSeparator = '--' def __init__(self, locator, partSize=50 << 20): """ Create a new job store in AWS or load an existing one from there. :param int partSize: The size of each individual part used for multipart operations like upload and copy, must be >= 5 MiB but large enough to not exceed 10k parts for the whole file """ super(AWSJobStore, self).__init__() region, namePrefix = locator.split(':') if not self.bucketNameRe.match(namePrefix): raise ValueError("Invalid name prefix '%s'. Name prefixes must contain only digits, " "hyphens or lower-case letters and must not start or end in a " "hyphen." % namePrefix) # Reserve 13 for separator and suffix if len(namePrefix) > self.maxBucketNameLen - self.maxNameLen - len(self.nameSeparator): raise ValueError("Invalid name prefix '%s'. Name prefixes may not be longer than 50 " "characters." % namePrefix) if '--' in namePrefix: raise ValueError("Invalid name prefix '%s'. Name prefixes may not contain " "%s." % (namePrefix, self.nameSeparator)) log.debug("Instantiating %s for region %s and name prefix '%s'", self.__class__, region, namePrefix) self.locator = locator self.region = region self.namePrefix = namePrefix self.partSize = partSize self.jobsDomain = None self.filesDomain = None self.filesBucket = None self.db = self._connectSimpleDB() self.s3 = self._connectS3() def initialize(self, config): if self._registered: raise JobStoreExistsException(self.locator) self._registered = None try: self._bind(create=True) except: with panic(log): self.destroy() else: super(AWSJobStore, self).initialize(config) # Only register after job store has been full initialized self._registered = True @property def sseKeyPath(self): return self.config.sseKey def resume(self): if not self._registered: raise NoSuchJobStoreException(self.locator) self._bind(create=False) super(AWSJobStore, self).resume() def _bind(self, create=False, block=True, check_versioning_consistency=True): def qualify(name): assert len(name) <= self.maxNameLen return self.namePrefix + self.nameSeparator + name # The order in which this sequence of events happens is important. We can easily handle the # inability to bind a domain, but it is a little harder to handle some cases of binding the # jobstore bucket. Maintaining this order allows for an easier `destroy` method. if self.jobsDomain is None: self.jobsDomain = self._bindDomain(qualify('jobs'), create=create, block=block) if self.filesDomain is None: self.filesDomain = self._bindDomain(qualify('files'), create=create, block=block) if self.filesBucket is None: self.filesBucket = self._bindBucket(qualify('files'), create=create, block=block, versioning=True, check_versioning_consistency=check_versioning_consistency) @property def _registered(self): """ A optional boolean property indidcating whether this job store is registered. The registry is the authority on deciding if a job store exists or not. If True, this job store exists, if None the job store is transitioning from True to False or vice versa, if False the job store doesn't exist. :type: bool|None """ # The weird mapping of the SDB item attribute value to the property value is due to # backwards compatibility. 'True' becomes True, that's easy. Toil < 3.3.0 writes this at # the end of job store creation. Absence of either the registry, the item or the # attribute becomes False, representing a truly absent, non-existing job store. An # attribute value of 'False', which is what Toil < 3.3.0 writes at the *beginning* of job # store destruction, indicates a job store in transition, reflecting the fact that 3.3.0 # may leak buckets or domains even though the registry reports 'False' for them. We # can't handle job stores that were partially created by 3.3.0, though. registry_domain = self._bindDomain(domain_name='toil-registry', create=False, block=False) if registry_domain is None: return False else: for attempt in retry_sdb(): with attempt: attributes = registry_domain.get_attributes(item_name=self.namePrefix, attribute_name='exists', consistent_read=True) try: exists = attributes['exists'] except KeyError: return False else: if exists == 'True': return True elif exists == 'False': return None else: assert False @_registered.setter def _registered(self, value): registry_domain = self._bindDomain(domain_name='toil-registry', # Only create registry domain when registering or # transitioning a store create=value is not False, block=False) if registry_domain is None and value is False: pass else: for attempt in retry_sdb(): with attempt: if value is False: registry_domain.delete_attributes(item_name=self.namePrefix) else: if value is True: attributes = dict(exists='True') elif value is None: attributes = dict(exists='False') else: assert False registry_domain.put_attributes(item_name=self.namePrefix, attributes=attributes) def _checkItem(self, item): if "overlargeID" not in item: raise RuntimeError("overlargeID attribute isn't present: you are restarting" " an old, incompatible jobstore, or the jobstore logic is" " incorrect.") def _awsJobFromItem(self, item): self._checkItem(item) if item["overlargeID"]: assert self.fileExists(item["overlargeID"]) # This is an overlarge job, download the actual attributes # from the file store log.debug("Loading overlarge job from S3.") with self.readFileStream(item["overlargeID"]) as fh: binary = fh.read() else: binary, _ = SDBHelper.attributesToBinary(item) assert binary is not None job = pickle.loads(binary) return job def _awsJobToItem(self, job): binary = pickle.dumps(job, protocol=pickle.HIGHEST_PROTOCOL) if len(binary) > SDBHelper.maxBinarySize(extraReservedChunks=1): # Store as an overlarge job in S3 with self.writeFileStream() as (writable, fileID): writable.write(binary) item = SDBHelper.binaryToAttributes(None) item["overlargeID"] = fileID else: item = SDBHelper.binaryToAttributes(binary) item["overlargeID"] = "" return item jobsPerBatchInsert = 25 @contextmanager def batch(self): self._batchedJobGraphs = [] yield batches = [self._batchedJobGraphs[i:i + self.jobsPerBatchInsert] for i in range(0, len(self._batchedJobGraphs), self.jobsPerBatchInsert)] for batch in batches: items = {jobGraph.jobStoreID: self._awsJobToItem(jobGraph) for jobGraph in batch} for attempt in retry_sdb(): with attempt: assert self.jobsDomain.batch_put_attributes(items) self._batchedJobGraphs = None def create(self, jobNode): jobStoreID = self._newJobID() log.debug("Creating job %s for '%s'", jobStoreID, '' if jobNode.command is None else jobNode.command) job = JobGraph.fromJobNode(jobNode, jobStoreID=jobStoreID, tryCount=self._defaultTryCount()) if hasattr(self, "_batchedJobGraphs") and self._batchedJobGraphs is not None: self._batchedJobGraphs.append(job) else: item = self._awsJobToItem(job) for attempt in retry_sdb(): with attempt: assert self.jobsDomain.put_attributes(job.jobStoreID, item) return job def exists(self, jobStoreID): for attempt in retry_sdb(): with attempt: return bool(self.jobsDomain.get_attributes( item_name=compat_bytes(jobStoreID), attribute_name=[SDBHelper.presenceIndicator()], consistent_read=True)) def jobs(self): result = None for attempt in retry_sdb(): with attempt: result = list(self.jobsDomain.select( consistent_read=True, query="select * from `%s`" % self.jobsDomain.name)) assert result is not None for jobItem in result: yield self._awsJobFromItem(jobItem) def load(self, jobStoreID): item = None for attempt in retry_sdb(): with attempt: item = self.jobsDomain.get_attributes(compat_bytes(jobStoreID), consistent_read=True) if not item: raise NoSuchJobException(jobStoreID) job = self._awsJobFromItem(item) if job is None: raise NoSuchJobException(jobStoreID) log.debug("Loaded job %s", jobStoreID) return job def update(self, job): log.debug("Updating job %s", job.jobStoreID) item = self._awsJobToItem(job) for attempt in retry_sdb(): with attempt: assert self.jobsDomain.put_attributes(compat_bytes(job.jobStoreID), item) itemsPerBatchDelete = 25 def delete(self, jobStoreID): # remove job and replace with jobStoreId. log.debug("Deleting job %s", jobStoreID) # If the job is overlarge, delete its file from the filestore item = None for attempt in retry_sdb(): with attempt: item = self.jobsDomain.get_attributes(compat_bytes(jobStoreID), consistent_read=True) self._checkItem(item) if item["overlargeID"]: log.debug("Deleting job from filestore") self.deleteFile(item["overlargeID"]) for attempt in retry_sdb(): with attempt: self.jobsDomain.delete_attributes(item_name=compat_bytes(jobStoreID)) items = None for attempt in retry_sdb(): with attempt: items = list(self.filesDomain.select( consistent_read=True, query="select version from `%s` where ownerID='%s'" % ( self.filesDomain.name, jobStoreID))) assert items is not None if items: log.debug("Deleting %d file(s) associated with job %s", len(items), jobStoreID) n = self.itemsPerBatchDelete batches = [items[i:i + n] for i in range(0, len(items), n)] for batch in batches: itemsDict = {item.name: None for item in batch} for attempt in retry_sdb(): with attempt: self.filesDomain.batch_delete_attributes(itemsDict) for item in items: version = item.get('version') for attempt in retry_s3(): with attempt: if version: self.filesBucket.delete_key(key_name=compat_bytes(item.name), version_id=version) else: self.filesBucket.delete_key(key_name=compat_bytes(item.name)) def getEmptyFileStoreID(self, jobStoreID=None, cleanup=False): info = self.FileInfo.create(jobStoreID if cleanup else None) with info.uploadStream() as _: # Empty pass info.save() log.debug("Created %r.", info) return info.fileID def _importFile(self, otherCls, url, sharedFileName=None, hardlink=False): if issubclass(otherCls, AWSJobStore): srcKey = self._getKeyForUrl(url, existing=True) size = srcKey.size try: if sharedFileName is None: info = self.FileInfo.create(srcKey.name) else: self._requireValidSharedFileName(sharedFileName) jobStoreFileID = self._sharedFileID(sharedFileName) info = self.FileInfo.loadOrCreate(jobStoreFileID=jobStoreFileID, ownerID=str(self.sharedFileOwnerID), encrypted=None) info.copyFrom(srcKey) info.save() finally: srcKey.bucket.connection.close() return FileID(info.fileID, size) if sharedFileName is None else None else: return super(AWSJobStore, self)._importFile(otherCls, url, sharedFileName=sharedFileName) def _exportFile(self, otherCls, jobStoreFileID, url): if issubclass(otherCls, AWSJobStore): dstKey = self._getKeyForUrl(url) try: info = self.FileInfo.loadOrFail(jobStoreFileID) info.copyTo(dstKey) finally: dstKey.bucket.connection.close() else: super(AWSJobStore, self)._exportFile(otherCls, jobStoreFileID, url) @classmethod def getSize(cls, url): key = cls._getKeyForUrl(url, existing=True) try: return key.size finally: key.bucket.connection.close() @classmethod def _readFromUrl(cls, url, writable): srcKey = cls._getKeyForUrl(url, existing=True) try: srcKey.get_contents_to_file(writable) finally: srcKey.bucket.connection.close() @classmethod def _writeToUrl(cls, readable, url): dstKey = cls._getKeyForUrl(url) try: canDetermineSize = True try: readable.seek(0, 2) # go to the 0th byte from the end of the file, indicated by '2' fileSize = readable.tell() # tells the current position in file - in this case == size of file readable.seek(0) # go to the 0th byte from the start of the file except: canDetermineSize = False if canDetermineSize and fileSize > (5 * 1000 * 1000): # only use multipart when file is above 5 mb log.debug("Uploading %s with size %s, will use multipart uploading", dstKey.name, fileSize) chunkedFileUpload(readable=readable, bucket=dstKey.bucket, fileID=dstKey.name, file_size=fileSize) else: # we either don't know the size, or the size is small log.debug("Can not use multipart uploading for %s, uploading whole file at once", dstKey.name) dstKey.set_contents_from_string(readable.read()) finally: dstKey.bucket.connection.close() @staticmethod def _getKeyForUrl(url, existing=None): """ Extracts a key from a given s3:// URL. On return, but not on exceptions, this method leaks an S3Connection object. The caller is responsible to close that by calling key.bucket.connection.close(). :param bool existing: If True, key is expected to exist. If False, key is expected not to exists and it will be created. If None, the key will be created if it doesn't exist. :rtype: Key """ keyName = url.path[1:] bucketName = url.netloc # Get the bucket's region to avoid a redirect per request try: with closing(boto.connect_s3()) as s3: location = s3.get_bucket(bucketName).get_location() region = bucket_location_to_region(location) except S3ResponseError as e: if e.error_code == 'AccessDenied': s3 = boto.connect_s3() else: raise else: # Note that caller is responsible for closing the connection s3 = boto.s3.connect_to_region(region) try: bucket = s3.get_bucket(bucketName) key = bucket.get_key(keyName.encode('utf-8')) if existing is True: if key is None: raise RuntimeError("Key '%s' does not exist in bucket '%s'." % (keyName, bucketName)) elif existing is False: if key is not None: raise RuntimeError("Key '%s' exists in bucket '%s'." % (keyName, bucketName)) elif existing is None: pass else: assert False if key is None: key = bucket.new_key(keyName) except: with panic(): s3.close() else: return key @classmethod def _supportsUrl(cls, url, export=False): return url.scheme.lower() == 's3' def writeFile(self, localFilePath, jobStoreID=None, cleanup=False): info = self.FileInfo.create(jobStoreID if cleanup else None) info.upload(localFilePath, not self.config.disableJobStoreChecksumVerification) info.save() log.debug("Wrote %r of from %r", info, localFilePath) return info.fileID @contextmanager def writeFileStream(self, jobStoreID=None, cleanup=False): info = self.FileInfo.create(jobStoreID if cleanup else None) with info.uploadStream() as writable: yield writable, info.fileID info.save() log.debug("Wrote %r.", info) @contextmanager def writeSharedFileStream(self, sharedFileName, isProtected=None): self._requireValidSharedFileName(sharedFileName) info = self.FileInfo.loadOrCreate(jobStoreFileID=self._sharedFileID(sharedFileName), ownerID=str(self.sharedFileOwnerID), encrypted=isProtected) with info.uploadStream() as writable: yield writable info.save() log.debug("Wrote %r for shared file %r.", info, sharedFileName) def updateFile(self, jobStoreFileID, localFilePath): info = self.FileInfo.loadOrFail(jobStoreFileID) info.upload(localFilePath, not self.config.disableJobStoreChecksumVerification) info.save() log.debug("Wrote %r from path %r.", info, localFilePath) @contextmanager def updateFileStream(self, jobStoreFileID): info = self.FileInfo.loadOrFail(jobStoreFileID) with info.uploadStream() as writable: yield writable info.save() log.debug("Wrote %r from stream.", info) def fileExists(self, jobStoreFileID): return self.FileInfo.exists(jobStoreFileID) def getFileSize(self, jobStoreFileID): if not self.fileExists(jobStoreFileID): return 0 info = self.FileInfo.loadOrFail(jobStoreFileID) return info.getSize() def readFile(self, jobStoreFileID, localFilePath, symlink=False): info = self.FileInfo.loadOrFail(jobStoreFileID) log.debug("Reading %r into %r.", info, localFilePath) info.download(localFilePath, not self.config.disableJobStoreChecksumVerification) @contextmanager def readFileStream(self, jobStoreFileID): info = self.FileInfo.loadOrFail(jobStoreFileID) log.debug("Reading %r into stream.", info) with info.downloadStream() as readable: yield readable @contextmanager def readSharedFileStream(self, sharedFileName): self._requireValidSharedFileName(sharedFileName) jobStoreFileID = self._sharedFileID(sharedFileName) info = self.FileInfo.loadOrFail(jobStoreFileID, customName=sharedFileName) log.debug("Reading %r for shared file %r into stream.", info, sharedFileName) with info.downloadStream() as readable: yield readable def deleteFile(self, jobStoreFileID): info = self.FileInfo.load(jobStoreFileID) if info is None: log.debug("File %s does not exist, skipping deletion.", jobStoreFileID) else: info.delete() def writeStatsAndLogging(self, statsAndLoggingString): info = self.FileInfo.create(str(self.statsFileOwnerID)) with info.uploadStream(multipart=False) as writeable: if isinstance(statsAndLoggingString, str): # This stream is for binary data, so encode any non-encoded things statsAndLoggingString = statsAndLoggingString.encode('utf-8', errors='ignore') writeable.write(statsAndLoggingString) info.save() def readStatsAndLogging(self, callback, readAll=False): itemsProcessed = 0 for info in self._readStatsAndLogging(callback, self.statsFileOwnerID): info._ownerID = self.readStatsFileOwnerID info.save() itemsProcessed += 1 if readAll: for _ in self._readStatsAndLogging(callback, self.readStatsFileOwnerID): itemsProcessed += 1 return itemsProcessed def _readStatsAndLogging(self, callback, ownerId): items = None for attempt in retry_sdb(): with attempt: items = list(self.filesDomain.select( consistent_read=True, query="select * from `%s` where ownerID='%s'" % ( self.filesDomain.name, str(ownerId)))) assert items is not None for item in items: info = self.FileInfo.fromItem(item) with info.downloadStream() as readable: callback(readable) yield info def getPublicUrl(self, jobStoreFileID): info = self.FileInfo.loadOrFail(jobStoreFileID) if info.content is not None: with info.uploadStream(allowInlining=False) as f: f.write(info.content) for attempt in retry_s3(): with attempt: key = self.filesBucket.get_key(key_name=compat_bytes(jobStoreFileID), version_id=info.version) key.set_canned_acl('public-read') url = key.generate_url(query_auth=False, expires_in=self.publicUrlExpiration.total_seconds()) # boto doesn't properly remove the x-amz-security-token parameter when # query_auth is False when using an IAM role (see issue #2043). Including the # x-amz-security-token parameter without the access key results in a 403, # even if the resource is public, so we need to remove it. scheme, netloc, path, query, fragment = urllib.parse.urlsplit(url) params = urllib.parse.parse_qs(query) if 'x-amz-security-token' in params: del params['x-amz-security-token'] query = urllib.parse.urlencode(params, doseq=True) url = urllib.parse.urlunsplit((scheme, netloc, path, query, fragment)) return url def getSharedPublicUrl(self, sharedFileName): self._requireValidSharedFileName(sharedFileName) return self.getPublicUrl(self._sharedFileID(sharedFileName)) def _connectSimpleDB(self): """ :rtype: SDBConnection """ db = boto.sdb.connect_to_region(self.region) if db is None: raise ValueError("Could not connect to SimpleDB. Make sure '%s' is a valid SimpleDB region." % self.region) monkeyPatchSdbConnection(db) return db def _connectS3(self): """ :rtype: S3Connection """ s3 = boto.s3.connect_to_region(self.region) if s3 is None: raise ValueError("Could not connect to S3. Make sure '%s' is a valid S3 region." % self.region) return s3 def _bindBucket(self, bucket_name, create=False, block=True, versioning=False, check_versioning_consistency=True): """ Return the Boto Bucket object representing the S3 bucket with the given name. If the bucket does not exist and `create` is True, it will be created. :param str bucket_name: the name of the bucket to bind to :param bool create: Whether to create bucket the if it doesn't exist :param bool block: If False, return None if the bucket doesn't exist. If True, wait until bucket appears. Ignored if `create` is True. :rtype: Bucket|None :raises S3ResponseError: If `block` is True and the bucket still doesn't exist after the retry timeout expires. """ assert self.minBucketNameLen <= len(bucket_name) <= self.maxBucketNameLen assert self.bucketNameRe.match(bucket_name) log.debug("Binding to job store bucket '%s'.", bucket_name) def bucket_creation_pending(e): # https://github.com/BD2KGenomics/toil/issues/955 # https://github.com/BD2KGenomics/toil/issues/995 # https://github.com/BD2KGenomics/toil/issues/1093 return (isinstance(e, (S3CreateError, S3ResponseError)) and e.error_code in ('BucketAlreadyOwnedByYou', 'OperationAborted', 'NoSuchBucket')) bucketExisted = True for attempt in retry_s3(predicate=bucket_creation_pending): with attempt: try: bucket = self.s3.get_bucket(bucket_name, validate=True) except S3ResponseError as e: if e.error_code == 'NoSuchBucket': bucketExisted = False log.debug("Bucket '%s' does not exist.", bucket_name) if create: log.debug("Creating bucket '%s'.", bucket_name) location = region_to_bucket_location(self.region) bucket = self.s3.create_bucket(bucket_name, location=location) # It is possible for create_bucket to return but # for an immediate request for the bucket region to # produce an S3ResponseError with code # NoSuchBucket. We let that kick us back up to the # main retry loop. assert self.__getBucketRegion(bucket) == self.region elif block: raise else: return None elif e.status == 301: # This is raised if the user attempts to get a bucket in a region outside # the specified one, if the specified one is not `us-east-1`. The us-east-1 # server allows a user to use buckets from any region. bucket = self.s3.get_bucket(bucket_name, validate=False) raise BucketLocationConflictException(self.__getBucketRegion(bucket)) else: raise else: if self.__getBucketRegion(bucket) != self.region: raise BucketLocationConflictException(self.__getBucketRegion(bucket)) if versioning and not bucketExisted: # only call this method on bucket creation bucket.configure_versioning(True) # Now wait until versioning is actually on. Some uploads # would come back with no versions; maybe they were # happening too fast and this setting isn't sufficiently # consistent? time.sleep(1) while self._getBucketVersioning(bucket) != True: log.warning("Waiting for versioning activation on bucket '%s'...", bucket_name) time.sleep(1) elif check_versioning_consistency: # now test for versioning consistency # we should never see any of these errors since 'versioning' should always be true bucket_versioning = self._getBucketVersioning(bucket) if bucket_versioning != versioning: assert False, 'Cannot modify versioning on existing bucket' elif bucket_versioning is None: assert False, 'Cannot use a bucket with versioning suspended' if bucketExisted: log.debug("Using pre-existing job store bucket '%s'.", bucket_name) else: log.debug("Created new job store bucket '%s' with versioning state %s.", bucket_name, str(versioning)) return bucket def _bindDomain(self, domain_name, create=False, block=True): """ Return the Boto Domain object representing the SDB domain of the given name. If the domain does not exist and `create` is True, it will be created. :param str domain_name: the name of the domain to bind to :param bool create: True if domain should be created if it doesn't exist :param bool block: If False, return None if the domain doesn't exist. If True, wait until domain appears. This parameter is ignored if create is True. :rtype: Domain|None :raises SDBResponseError: If `block` is True and the domain still doesn't exist after the retry timeout expires. """ log.debug("Binding to job store domain '%s'.", domain_name) retryargs = dict(predicate=lambda e: no_such_sdb_domain(e) or sdb_unavailable(e)) if not block: retryargs['timeout'] = 15 for attempt in retry_sdb(**retryargs): with attempt: try: return self.db.get_domain(domain_name) except SDBResponseError as e: if no_such_sdb_domain(e): if create: return self.db.create_domain(domain_name) elif block: raise else: return None else: raise def _newJobID(self): return str(uuid.uuid4()) # A dummy job ID under which all shared files are stored sharedFileOwnerID = uuid.UUID('891f7db6-e4d9-4221-a58e-ab6cc4395f94') # A dummy job ID under which all unread stats files are stored statsFileOwnerID = uuid.UUID('bfcf5286-4bc7-41ef-a85d-9ab415b69d53') # A dummy job ID under which all read stats files are stored readStatsFileOwnerID = uuid.UUID('e77fc3aa-d232-4255-ae04-f64ee8eb0bfa') def _sharedFileID(self, sharedFileName): return str(uuid.uuid5(self.sharedFileOwnerID, sharedFileName)) @InnerClass class FileInfo(SDBHelper): """ Represents a file in this job store. """ outer = None """ :type: AWSJobStore """ def __init__(self, fileID, ownerID, encrypted, version=None, content=None, numContentChunks=0, checksum=None): """ :type fileID: str :param fileID: the file's ID :type ownerID: str :param ownerID: ID of the entity owning this file, typically a job ID aka jobStoreID :type encrypted: bool :param encrypted: whether the file is stored in encrypted form :type version: str|None :param version: a non-empty string containing the most recent version of the S3 object storing this file's content, None if the file is new, or empty string if the file is inlined. :type content: str|None :param content: this file's inlined content :type numContentChunks: int :param numContentChunks: the number of SDB domain attributes occupied by this files :type checksum: str|None :param checksum: the sha1 checksum of the file, if available. inlined content. Note that an inlined empty string still occupies one chunk. """ super(AWSJobStore.FileInfo, self).__init__() self._fileID = fileID self._ownerID = ownerID self.encrypted = encrypted self._version = version self._previousVersion = version self._content = content self._checksum = checksum self._numContentChunks = numContentChunks @property def fileID(self): return self._fileID @property def ownerID(self): return self._ownerID @property def version(self): return self._version @version.setter def version(self, version): # Version should only change once assert self._previousVersion == self._version self._version = version if version: self.content = None @property def previousVersion(self): return self._previousVersion @property def content(self): return self._content @property def checksum(self): return self._checksum @checksum.setter def checksum(self, checksum): self._checksum = checksum @content.setter def content(self, content): assert content is None or isinstance(content, bytes) self._content = content if content is not None: self.version = '' @classmethod def create(cls, ownerID): return cls(str(uuid.uuid4()), ownerID, encrypted=cls.outer.sseKeyPath is not None) @classmethod def presenceIndicator(cls): return 'encrypted' @classmethod def exists(cls, jobStoreFileID): for attempt in retry_sdb(): with attempt: return bool(cls.outer.filesDomain.get_attributes( item_name=compat_bytes(jobStoreFileID), attribute_name=[cls.presenceIndicator()], consistent_read=True)) @classmethod def load(cls, jobStoreFileID): for attempt in retry_sdb(): with attempt: self = cls.fromItem( cls.outer.filesDomain.get_attributes(item_name=compat_bytes(jobStoreFileID), consistent_read=True)) return self @classmethod def loadOrCreate(cls, jobStoreFileID, ownerID, encrypted): self = cls.load(jobStoreFileID) if encrypted is None: encrypted = cls.outer.sseKeyPath is not None if self is None: self = cls(jobStoreFileID, ownerID, encrypted=encrypted) else: assert self.fileID == jobStoreFileID assert self.ownerID == ownerID self.encrypted = encrypted return self @classmethod def loadOrFail(cls, jobStoreFileID, customName=None): """ :rtype: AWSJobStore.FileInfo :return: an instance of this class representing the file with the given ID :raises NoSuchFileException: if given file does not exist """ self = cls.load(jobStoreFileID) if self is None: raise NoSuchFileException(jobStoreFileID, customName=customName) else: return self @classmethod def fromItem(cls, item): """ Convert an SDB item to an instance of this class. :type item: Item """ assert item is not None # Strings come back from SDB as unicode def strOrNone(s): return s if s is None else str(s) # ownerID and encrypted are the only mandatory attributes ownerID = strOrNone(item.get('ownerID')) encrypted = item.get('encrypted') if ownerID is None: assert encrypted is None return None else: version = strOrNone(item['version']) checksum = strOrNone(item.get('checksum')) encrypted = strict_bool(encrypted) content, numContentChunks = cls.attributesToBinary(item) if encrypted: sseKeyPath = cls.outer.sseKeyPath if sseKeyPath is None: raise AssertionError('Content is encrypted but no key was provided.') if content is not None: content = encryption.decrypt(content, sseKeyPath) self = cls(fileID=item.name, ownerID=ownerID, encrypted=encrypted, version=version, content=content, numContentChunks=numContentChunks, checksum=checksum) return self def toItem(self): """ Convert this instance to an attribute dictionary suitable for SDB put_attributes(). :rtype: (dict,int) :return: the attributes dict and an integer specifying the the number of chunk attributes in the dictionary that are used for storing inlined content. """ content = self.content assert content is None or isinstance(content, bytes) if self.encrypted and content is not None: sseKeyPath = self.outer.sseKeyPath if sseKeyPath is None: raise AssertionError('Encryption requested but no key was provided.') content = encryption.encrypt(content, sseKeyPath) assert content is None or isinstance(content, bytes) attributes = self.binaryToAttributes(content) numChunks = attributes['numChunks'] attributes.update(dict(ownerID=self.ownerID, encrypted=self.encrypted, version=self.version or '', checksum=self.checksum or '')) return attributes, numChunks @classmethod def _reservedAttributes(cls): return 3 + super(AWSJobStore.FileInfo, cls)._reservedAttributes() @staticmethod def maxInlinedSize(): return 256 def save(self): attributes, numNewContentChunks = self.toItem() # False stands for absence expected = ['version', False if self.previousVersion is None else self.previousVersion] try: for attempt in retry_sdb(): with attempt: assert self.outer.filesDomain.put_attributes(item_name=compat_bytes(self.fileID), attributes=attributes, expected_value=expected) # clean up the old version of the file if necessary and safe if self.previousVersion and (self.previousVersion != self.version): for attempt in retry_s3(): with attempt: self.outer.filesBucket.delete_key(compat_bytes(self.fileID), version_id=self.previousVersion) self._previousVersion = self._version if numNewContentChunks < self._numContentChunks: residualChunks = range(numNewContentChunks, self._numContentChunks) attributes = [self._chunkName(i) for i in residualChunks] for attempt in retry_sdb(): with attempt: self.outer.filesDomain.delete_attributes(compat_bytes(self.fileID), attributes=attributes) self._numContentChunks = numNewContentChunks except SDBResponseError as e: if e.error_code == 'ConditionalCheckFailed': raise ConcurrentFileModificationException(self.fileID) else: raise def upload(self, localFilePath, calculateChecksum=True): file_size, file_time = fileSizeAndTime(localFilePath) if file_size <= self.maxInlinedSize(): with open(localFilePath, 'rb') as f: self.content = f.read() else: headers = self._s3EncryptionHeaders() self.checksum = self._get_file_checksum(localFilePath) if calculateChecksum else None self.version = uploadFromPath(localFilePath, partSize=self.outer.partSize, bucket=self.outer.filesBucket, fileID=compat_bytes(self.fileID), headers=headers) def _get_file_checksum(self, localFilePath): with open(localFilePath, 'rb') as f: checksum = hashlib.sha1() contents = f.read(1024 * 1024) while contents != b'': checksum.update(contents) contents = f.read(1024 * 1024) return 'sha1$%s' % checksum.hexdigest() @contextmanager def uploadStream(self, multipart=True, allowInlining=True): """ Context manager that gives out a binary-mode upload stream to upload data. """ # Note that we have to handle already having a content or a version # if we are overwriting something. # But make sure we don't have both. assert not (bool(self.version) and self.content is not None) info = self store = self.outer class MultiPartPipe(WritablePipe): def readFrom(self, readable): buf = readable.read(store.partSize) assert isinstance(buf, bytes) if allowInlining and len(buf) <= info.maxInlinedSize(): log.debug('Inlining content of %d bytes', len(buf)) info.content = buf else: headers = info._s3EncryptionHeaders() for attempt in retry_s3(): with attempt: log.debug('Starting multipart upload') upload = store.filesBucket.initiate_multipart_upload( key_name=compat_bytes(info.fileID), headers=headers) try: for part_num in itertools.count(): # There must be at least one part, even if the file is empty. if len(buf) == 0 and part_num > 0: break for attempt in retry_s3(): with attempt: log.debug('Uploading part %d of %d bytes', part_num + 1, len(buf)) if USING_PYTHON2: upload.upload_part_from_file(fp=StringIO(buf), # part numbers are 1-based part_num=part_num + 1, headers=headers) else: upload.upload_part_from_file(fp=BytesIO(buf), # part numbers are 1-based part_num=part_num + 1, headers=headers) if len(buf) == 0: break buf = readable.read(info.outer.partSize) assert isinstance(buf, bytes) except: with panic(log=log): for attempt in retry_s3(): with attempt: upload.cancel_upload() else: while store._getBucketVersioning(store.filesBucket) != True: log.warning('Versioning does not appear to be enabled yet. Deferring multipart upload completion...') time.sleep(1) for attempt in retry_s3(): with attempt: log.debug('Attempting to complete upload...') completed = upload.complete_upload() log.debug('Completed upload object of type %s: %s', str(type(completed)), repr(completed)) info.version = completed.version_id log.debug('Completed upload with version %s', str(info.version)) if info.version is None: # Somehow we don't know the version. Try and get it. for attempt in retry_s3(predicate=lambda e: retryable_s3_errors(e) or isinstance(e, AssertionError)): with attempt: key = store.filesBucket.get_key(compat_bytes(info.fileID), headers=headers) log.warning('Loaded key for upload with no version and got version %s', str(key.version_id)) info.version = key.version_id assert info.version is not None # Make sure we actually wrote something, even if an empty file assert (bool(info.version) or info.content is not None) class SinglePartPipe(WritablePipe): def readFrom(self, readable): buf = readable.read() assert isinstance(buf, bytes) dataLength = len(buf) if allowInlining and dataLength <= info.maxInlinedSize(): log.debug('Inlining content of %d bytes', len(buf)) info.content = buf else: key = store.filesBucket.new_key(key_name=compat_bytes(info.fileID)) buf = BytesIO(buf) headers = info._s3EncryptionHeaders() while store._getBucketVersioning(store.filesBucket) != True: log.warning('Versioning does not appear to be enabled yet. Deferring single part upload...') time.sleep(1) for attempt in retry_s3(): with attempt: log.debug('Uploading single part of %d bytes', dataLength) assert dataLength == key.set_contents_from_file(fp=buf, headers=headers) log.debug('Upload received version %s', str(key.version_id)) info.version = key.version_id if info.version is None: # Somehow we don't know the version for attempt in retry_s3(predicate=lambda e: retryable_s3_errors(e) or isinstance(e, AssertionError)): with attempt: key.reload() log.warning('Reloaded key with no version and got version %s', str(key.version_id)) info.version = key.version_id assert info.version is not None # Make sure we actually wrote something, even if an empty file assert (bool(info.version) or info.content is not None) pipe = MultiPartPipe() if multipart else SinglePartPipe() with pipe as writable: yield writable if not pipe.reader_done: log.debug('Version: {} Content: {}'.format(self.version, self.content)) raise RuntimeError('Escaped context manager without written data being read!') # We check our work to make sure we have exactly one of embedded # content or a real object version. if self.content is None: if not bool(self.version): log.debug('Version: {} Content: {}'.format(self.version, self.content)) raise RuntimeError('No content added and no version created') else: if bool(self.version): log.debug('Version: {} Content: {}'.format(self.version, self.content)) raise RuntimeError('Content added and version created') def copyFrom(self, srcKey): """ Copies contents of source key into this file. :param srcKey: The key that will be copied from """ assert srcKey.size is not None if srcKey.size <= self.maxInlinedSize(): self.content = srcKey.get_contents_as_string() else: self.version = copyKeyMultipart(srcBucketName=compat_plain(srcKey.bucket.name), srcKeyName=compat_plain(srcKey.name), srcKeyVersion=compat_plain(srcKey.version_id), dstBucketName=compat_plain(self.outer.filesBucket.name), dstKeyName=compat_plain(self._fileID), sseAlgorithm='AES256', sseKey=self._getSSEKey()) def copyTo(self, dstKey): """ Copies contents of this file to the given key. :param Key dstKey: The key to copy this file's content to """ if self.content is not None: for attempt in retry_s3(): with attempt: dstKey.set_contents_from_string(self.content) elif self.version: for attempt in retry_s3(): encrypted = True if self.outer.sseKeyPath else False if encrypted: srcKey = self.outer.filesBucket.get_key(compat_bytes(self.fileID), headers=self._s3EncryptionHeaders()) else: srcKey = self.outer.filesBucket.get_key(compat_bytes(self.fileID)) srcKey.version_id = self.version with attempt: copyKeyMultipart(srcBucketName=compat_plain(srcKey.bucket.name), srcKeyName=compat_plain(srcKey.name), srcKeyVersion=compat_plain(srcKey.version_id), dstBucketName=compat_plain(dstKey.bucket.name), dstKeyName=compat_plain(dstKey.name), copySourceSseAlgorithm='AES256', copySourceSseKey=self._getSSEKey()) else: assert False def download(self, localFilePath, verifyChecksum=True): if self.content is not None: with AtomicFileCreate(localFilePath) as tmpPath: with open(tmpPath, 'wb') as f: f.write(self.content) elif self.version: headers = self._s3EncryptionHeaders() key = self.outer.filesBucket.get_key(compat_bytes(self.fileID), validate=False) for attempt in retry_s3(): with attempt: with AtomicFileCreate(localFilePath) as tmpPath: key.get_contents_to_filename(tmpPath, version_id=self.version, headers=headers) if verifyChecksum and self.checksum: downloadedChecksum = self._get_file_checksum(localFilePath) if self.checksum != downloadedChecksum: raise AssertionError( 'Checksums do not match for file %s. Expected: %s Actual: %s' % ( localFilePath, self.checksum, downloadedChecksum)) else: assert False @contextmanager def downloadStream(self): info = self class DownloadPipe(ReadablePipe): def writeTo(self, writable): if info.content is not None: writable.write(info.content) elif info.version: headers = info._s3EncryptionHeaders() key = info.outer.filesBucket.get_key(compat_bytes(info.fileID), validate=False) for attempt in retry_s3(): with attempt: key.get_contents_to_file(writable, headers=headers, version_id=info.version) else: assert False with DownloadPipe() as readable: yield readable def delete(self): store = self.outer if self.previousVersion is not None: for attempt in retry_sdb(): with attempt: store.filesDomain.delete_attributes( compat_bytes(self.fileID), expected_values=['version', self.previousVersion]) if self.previousVersion: for attempt in retry_s3(): with attempt: store.filesBucket.delete_key(key_name=compat_bytes(self.fileID), version_id=self.previousVersion) def getSize(self): """ Return the size of the referenced item in bytes. """ if self.content is not None: return len(self.content) elif self.version: for attempt in retry_s3(): with attempt: key = self.outer.filesBucket.get_key(compat_bytes(self.fileID), validate=False) return key.size else: return 0 def _getSSEKey(self): sseKeyPath = self.outer.sseKeyPath if sseKeyPath is None: return None else: with open(sseKeyPath, 'rb') as f: sseKey = f.read() return sseKey def _s3EncryptionHeaders(self): if self.encrypted: sseKey = self._getSSEKey() assert sseKey is not None, 'Content is encrypted but no key was provided.' assert len(sseKey) == 32 encodedSseKey = base64.b64encode(sseKey).decode('utf-8') encodedSseKeyMd5 = base64.b64encode(hashlib.md5(sseKey).digest()).decode('utf-8') return {'x-amz-server-side-encryption-customer-algorithm': 'AES256', 'x-amz-server-side-encryption-customer-key': encodedSseKey, 'x-amz-server-side-encryption-customer-key-md5': encodedSseKeyMd5} else: return {} def __repr__(self): r = custom_repr d = (('fileID', r(self.fileID)), ('ownerID', r(self.ownerID)), ('encrypted', r(self.encrypted)), ('version', r(self.version)), ('previousVersion', r(self.previousVersion)), ('content', r(self.content)), ('checksum', r(self.checksum)), ('_numContentChunks', r(self._numContentChunks))) return "{}({})".format(type(self).__name__, ', '.join('%s=%s' % (k, v) for k, v in d)) versionings = dict(Enabled=True, Disabled=False, Suspended=None) def _getBucketVersioning(self, bucket): """ For newly created buckets get_versioning_status returns an empty dict. In the past we've seen None in this case. We map both to a return value of False. Otherwise, the 'Versioning' entry in the dictionary returned by get_versioning_status can be 'Enabled', 'Suspended' or 'Disabled' which we map to True, None and False respectively. Note that we've never seen a versioning status of 'Disabled', only the empty dictionary. Calling configure_versioning with False on a bucket will cause get_versioning_status to then return 'Suspended' even on a new bucket that never had versioning enabled. """ for attempt in retry_s3(): with attempt: status = bucket.get_versioning_status() return self.versionings[status['Versioning']] if status else False def __getBucketRegion(self, bucket): for attempt in retry_s3(): with attempt: return bucket_location_to_region(bucket.get_location()) def destroy(self): # FIXME: Destruction of encrypted stores only works after initialize() or .resume() # See https://github.com/BD2KGenomics/toil/issues/1041 try: self._bind(create=False, block=False, check_versioning_consistency=False) except BucketLocationConflictException: # If the unique jobstore bucket name existed, _bind would have raised a # BucketLocationConflictException before calling destroy. Calling _bind here again # would reraise the same exception so we need to catch and ignore that exception. pass # TODO: Add other failure cases to be ignored here. self._registered = None if self.filesBucket is not None: self._delete_bucket(self.filesBucket) self.filesBucket = None for name in 'filesDomain', 'jobsDomain': domain = getattr(self, name) if domain is not None: self._delete_domain(domain) setattr(self, name, None) self._registered = False def _delete_domain(self, domain): for attempt in retry_sdb(): with attempt: try: domain.delete() except SDBResponseError as e: if no_such_sdb_domain(e): pass else: raise def _delete_bucket(self, b): for attempt in retry_s3(): with attempt: try: for upload in b.list_multipart_uploads(): upload.cancel_upload() # TODO: upgrade this portion to boto3 bucket = s3_boto3_resource.Bucket(compat_bytes(b.name)) bucket.objects.all().delete() bucket.object_versions.delete() bucket.delete() except s3_boto3_resource.meta.client.exceptions.NoSuchBucket: pass except S3ResponseError as e: if e.error_code != 'NoSuchBucket': raise aRepr = reprlib.Repr() aRepr.maxstring = 38 # so UUIDs don't get truncated (36 for UUID plus 2 for quotes) custom_repr = aRepr.repr class BucketLocationConflictException(Exception): def __init__(self, bucketRegion): super(BucketLocationConflictException, self).__init__( 'A bucket with the same name as the jobstore was found in another region (%s). ' 'Cannot proceed as the unique bucket name is already in use.' % bucketRegion) toil-releases-3.24.0/src/toil/jobStores/aws/utils.py000066400000000000000000000370521362134276200224010ustar00rootroot00000000000000# Copyright (C) 2015-2016 Regents of the University of California # # 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. from __future__ import absolute_import from __future__ import division from builtins import str from builtins import next from builtins import range from past.utils import old_div from builtins import object import base64 import bz2 import os import socket import logging import types import itertools import errno from ssl import SSLError from six import iteritems from toil.lib.exceptions import panic from toil.lib.compatibility import compat_oldstr, compat_bytes, USING_PYTHON2 from toil.lib.retry import retry from boto.exception import (SDBResponseError, BotoServerError, S3ResponseError, S3CreateError, S3CopyError) import boto3 log = logging.getLogger(__name__) class SDBHelper(object): """ A mixin with methods for storing limited amounts of binary data in an SDB item >>> import os >>> H=SDBHelper >>> H.presenceIndicator() # doctest: +ALLOW_UNICODE u'numChunks' >>> H.binaryToAttributes(None)['numChunks'] 0 >>> H.attributesToBinary({u'numChunks': 0}) (None, 0) >>> H.binaryToAttributes(b'') # doctest: +ALLOW_UNICODE +ALLOW_BYTES {u'000': b'VQ==', u'numChunks': 1} >>> H.attributesToBinary({u'numChunks': 1, u'000': b'VQ=='}) # doctest: +ALLOW_BYTES (b'', 1) Good pseudo-random data is very likely smaller than its bzip2ed form. Subtract 1 for the type character, i.e 'C' or 'U', with which the string is prefixed. We should get one full chunk: >>> s = os.urandom(H.maxRawValueSize-1) >>> d = H.binaryToAttributes(s) >>> len(d), len(d['000']) (2, 1024) >>> H.attributesToBinary(d) == (s, 1) True One byte more and we should overflow four bytes into the second chunk, two bytes for base64-encoding the additional character and two bytes for base64-padding to the next quartet. >>> s += s[0:1] >>> d = H.binaryToAttributes(s) >>> len(d), len(d['000']), len(d['001']) (3, 1024, 4) >>> H.attributesToBinary(d) == (s, 2) True """ # The SDB documentation is not clear as to whether the attribute value size limit of 1024 # applies to the base64-encoded value or the raw value. It suggests that responses are # automatically encoded from which I conclude that the limit should apply to the raw, # unencoded value. However, there seems to be a discrepancy between how Boto computes the # request signature if a value contains a binary data, and how SDB does it. This causes # requests to fail signature verification, resulting in a 403. We therefore have to # base64-encode values ourselves even if that means we loose a quarter of capacity. maxAttributesPerItem = 256 maxValueSize = 1024 # in python2 1 / 2 == 0, in python 3 1 / 2 == 0.5 # old_div implents the python2 behavior in both 2 & 3 maxRawValueSize = old_div(maxValueSize * 3, 4) # Just make sure we don't have a problem with padding or integer truncation: assert len(base64.b64encode(b' ' * maxRawValueSize)) == 1024 assert len(base64.b64encode(b' ' * (1 + maxRawValueSize))) > 1024 @classmethod def _reservedAttributes(cls): """ Override in subclass to reserve a certain number of attributes that can't be used for chunks. """ return 1 @classmethod def _maxChunks(cls): return cls.maxAttributesPerItem - cls._reservedAttributes() @classmethod def maxBinarySize(cls, extraReservedChunks=0): return (cls._maxChunks() - extraReservedChunks) * cls.maxRawValueSize - 1 # for the 'C' or 'U' prefix @classmethod def _maxEncodedSize(cls): return cls._maxChunks() * cls.maxValueSize @classmethod def binaryToAttributes(cls, binary): """ Turn a bytestring, or None, into SimpleDB attributes. """ if binary is None: return {u'numChunks': 0} assert isinstance(binary, bytes) assert len(binary) <= cls.maxBinarySize() # The use of compression is just an optimization. We can't include it in the maxValueSize # computation because the compression ratio depends on the input. compressed = bz2.compress(binary) if len(compressed) > len(binary): compressed = b'U' + binary else: compressed = b'C' + compressed encoded = base64.b64encode(compressed) assert len(encoded) <= cls._maxEncodedSize() n = cls.maxValueSize chunks = (encoded[i:i + n] for i in range(0, len(encoded), n)) attributes = {cls._chunkName(i): chunk for i, chunk in enumerate(chunks)} attributes.update({u'numChunks': len(attributes)}) return attributes @classmethod def _chunkName(cls, i): return str(i).zfill(3) @classmethod def _isValidChunkName(cls, s): return len(s) == 3 and s.isdigit() @classmethod def presenceIndicator(cls): """ The key that is guaranteed to be present in the return value of binaryToAttributes(). Assuming that binaryToAttributes() is used with SDB's PutAttributes, the return value of this method could be used to detect the presence/absence of an item in SDB. """ return u'numChunks' @classmethod def attributesToBinary(cls, attributes): """ :rtype: (str|None,int) :return: the binary data and the number of chunks it was composed from """ chunks = [(int(k), v) for k, v in iteritems(attributes) if cls._isValidChunkName(k)] chunks.sort() numChunks = int(attributes[u'numChunks']) if numChunks: if USING_PYTHON2: serializedJob = b''.join(v for k, v in chunks) else: serializedJob = b''.join(v.encode() for k, v in chunks) compressed = base64.b64decode(serializedJob) if compressed[0] == b'C'[0]: binary = bz2.decompress(compressed[1:]) elif compressed[0] == b'U'[0]: binary = compressed[1:] else: raise RuntimeError('Unexpected prefix {}'.format(compressed[0])) else: binary = None return binary, numChunks from boto.sdb.connection import SDBConnection def fileSizeAndTime(localFilePath): file_stat = os.stat(localFilePath) return file_stat.st_size, file_stat.st_mtime def uploadFromPath(localFilePath, partSize, bucket, fileID, headers): """ Uploads a file to s3, using multipart uploading if applicable :param str localFilePath: Path of the file to upload to s3 :param int partSize: max size of each part in the multipart upload, in bytes :param boto.s3.Bucket bucket: the s3 bucket to upload to :param str fileID: the name of the file to upload to :param headers: http headers to use when uploading - generally used for encryption purposes :return: version of the newly uploaded file """ file_size, file_time = fileSizeAndTime(localFilePath) if file_size <= partSize: key = bucket.new_key(key_name=compat_bytes(fileID)) key.name = fileID for attempt in retry_s3(): with attempt: key.set_contents_from_filename(localFilePath, headers=headers) version = key.version_id else: with open(localFilePath, 'rb') as f: version = chunkedFileUpload(f, bucket, fileID, file_size, headers, partSize) for attempt in retry_s3(): with attempt: key = bucket.get_key(compat_bytes(fileID), headers=headers, version_id=version) assert key.size == file_size # Make reasonably sure that the file wasn't touched during the upload assert fileSizeAndTime(localFilePath) == (file_size, file_time) return version def chunkedFileUpload(readable, bucket, fileID, file_size, headers=None, partSize=50 << 20): for attempt in retry_s3(): with attempt: upload = bucket.initiate_multipart_upload( key_name=compat_bytes(fileID), headers=headers) try: start = 0 part_num = itertools.count() while start < file_size: end = min(start + partSize, file_size) assert readable.tell() == start for attempt in retry_s3(): with attempt: upload.upload_part_from_file(fp=readable, part_num=next(part_num) + 1, size=end - start, headers=headers) start = end assert readable.tell() == file_size == start except: with panic(log=log): for attempt in retry_s3(): with attempt: upload.cancel_upload() else: for attempt in retry_s3(): with attempt: version = upload.complete_upload().version_id return version def copyKeyMultipart(srcBucketName, srcKeyName, srcKeyVersion, dstBucketName, dstKeyName, sseAlgorithm=None, sseKey=None, copySourceSseAlgorithm=None, copySourceSseKey=None): """ Copies a key from a source key to a destination key in multiple parts. Note that if the destination key exists it will be overwritten implicitly, and if it does not exist a new key will be created. If the destination bucket does not exist an error will be raised. :param str srcBucketName: The name of the bucket to be copied from. :param str srcKeyName: The name of the key to be copied from. :param str srcKeyVersion: The version of the key to be copied from. :param str dstBucketName: The name of the destination bucket for the copy. :param str dstKeyName: The name of the destination key that will be created or overwritten. :param str sseAlgorithm: Server-side encryption algorithm for the destination. :param str sseKey: Server-side encryption key for the destination. :param str copySourceSseAlgorithm: Server-side encryption algorithm for the source. :param str copySourceSseKey: Server-side encryption key for the source. :rtype: str :return: The version of the copied file (or None if versioning is not enabled for dstBucket). """ s3 = boto3.resource('s3') dstBucket = s3.Bucket(compat_oldstr(dstBucketName)) dstObject = dstBucket.Object(compat_oldstr(dstKeyName)) copySource = {'Bucket': compat_oldstr(srcBucketName), 'Key': compat_oldstr(srcKeyName)} if srcKeyVersion is not None: copySource['VersionId'] = compat_oldstr(srcKeyVersion) # The boto3 functions don't allow passing parameters as None to # indicate they weren't provided. So we have to do a bit of work # to ensure we only provide the parameters when they are actually # required. destEncryptionArgs = {} if sseKey is not None: destEncryptionArgs.update({'SSECustomerAlgorithm': sseAlgorithm, 'SSECustomerKey': sseKey}) copyEncryptionArgs = {} if copySourceSseKey is not None: copyEncryptionArgs.update({'CopySourceSSECustomerAlgorithm': copySourceSseAlgorithm, 'CopySourceSSECustomerKey': copySourceSseKey}) copyEncryptionArgs.update(destEncryptionArgs) dstObject.copy(copySource, ExtraArgs=copyEncryptionArgs) # Wait until the object exists before calling head_object object_summary = s3.ObjectSummary(dstObject.bucket_name, dstObject.key) object_summary.wait_until_exists(**destEncryptionArgs) # Unfortunately, boto3's managed copy doesn't return the version # that it actually copied to. So we have to check immediately # after, leaving open the possibility that it may have been # modified again in the few seconds since the copy finished. There # isn't much we can do about it. info = boto3.client('s3').head_object(Bucket=dstObject.bucket_name, Key=dstObject.key, **destEncryptionArgs) return info.get('VersionId', None) def _put_attributes_using_post(self, domain_or_name, item_name, attributes, replace=True, expected_value=None): """ Monkey-patched version of SDBConnection.put_attributes that uses POST instead of GET The GET version is subject to the URL length limit which kicks in before the 256 x 1024 limit for attribute values. Using POST prevents that. https://github.com/BD2KGenomics/toil/issues/502 """ domain, domain_name = self.get_domain_and_name(domain_or_name) params = {'DomainName': domain_name, 'ItemName': item_name} self._build_name_value_list(params, attributes, replace) if expected_value: self._build_expected_value(params, expected_value) # The addition of the verb keyword argument is the only difference to put_attributes (Hannes) return self.get_status('PutAttributes', params, verb='POST') def monkeyPatchSdbConnection(sdb): """ :type sdb: SDBConnection """ sdb.put_attributes = types.MethodType(_put_attributes_using_post, sdb) default_delays = (0, 1, 1, 4, 16, 64) default_timeout = 300 def connection_reset(e): # For some reason we get 'error: [Errno 104] Connection reset by peer' where the # English description suggests that errno is 54 (ECONNRESET) while the actual # errno is listed as 104. To be safe, we check for both: return isinstance(e, socket.error) and e.errno in (errno.ECONNRESET, 104) def sdb_unavailable(e): return isinstance(e, BotoServerError) and e.status == 503 def no_such_sdb_domain(e): return (isinstance(e, SDBResponseError) and e.error_code and e.error_code.endswith('NoSuchDomain')) def retryable_ssl_error(e): # https://github.com/BD2KGenomics/toil/issues/978 return isinstance(e, SSLError) and e.reason == 'DECRYPTION_FAILED_OR_BAD_RECORD_MAC' def retryable_sdb_errors(e): return (sdb_unavailable(e) or no_such_sdb_domain(e) or connection_reset(e) or retryable_ssl_error(e)) def retry_sdb(delays=default_delays, timeout=default_timeout, predicate=retryable_sdb_errors): return retry(delays=delays, timeout=timeout, predicate=predicate) def retryable_s3_errors(e): return ((isinstance(e, (S3CreateError, S3ResponseError)) and e.status == 409 and 'try again' in e.message) or connection_reset(e) or (isinstance(e, BotoServerError) and e.status == 500) # Throttling response sometimes received on bucket creation or (isinstance(e, BotoServerError) and e.status == 503 and e.code == 'SlowDown') or (isinstance(e, S3CopyError) and 'try again' in e.message)) def retry_s3(delays=default_delays, timeout=default_timeout, predicate=retryable_s3_errors): return retry(delays=delays, timeout=timeout, predicate=predicate) def region_to_bucket_location(region): return '' if region == 'us-east-1' else region def bucket_location_to_region(location): return 'us-east-1' if location == '' else location toil-releases-3.24.0/src/toil/jobStores/conftest.py000066400000000000000000000013771362134276200222750ustar00rootroot00000000000000# Copyright (C) 2015-2016 Regents of the University of California # # 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. # https://pytest.org/latest/example/pythoncollection.html collect_ignore = [] try: import boto except ImportError: collect_ignore.append("aws") toil-releases-3.24.0/src/toil/jobStores/fileJobStore.py000066400000000000000000001070251362134276200230340ustar00rootroot00000000000000# Copyright (C) 2015-2016 Regents of the University of California # # 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. # python 2/3 compatibility from __future__ import absolute_import from builtins import range # standard library from contextlib import contextmanager import logging import random import shutil import os import re import tempfile import stat import errno import time try: import cPickle as pickle except ImportError: import pickle # toil dependencies from toil.fileStores import FileID from toil.lib.bioio import absSymPath from toil.lib.misc import mkdir_p, robust_rmtree, AtomicFileCreate, atomic_copy, atomic_copyobj from toil.jobStores.abstractJobStore import (AbstractJobStore, NoSuchJobException, NoSuchFileException, JobStoreExistsException, NoSuchJobStoreException) from toil.jobGraph import JobGraph logger = logging.getLogger( __name__ ) class FileJobStore(AbstractJobStore): """ A job store that uses a directory on a locally attached file system. To be compatible with distributed batch systems, that file system must be shared by all worker nodes. """ # Valid chars for the creation of temporary "spray" directories. # Note that on case-insensitive filesystems we're twice as likely to use # letter directories as number directories. validDirs = "ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789" validDirsSet = set(validDirs) # What prefix should be on the per-job job directories, to distinguish them # from the spray directories? JOB_DIR_PREFIX = 'instance' # What prefix do we put on the per-job-name directories we sort jobs into? JOB_NAME_DIR_PREFIX = 'kind-' # 10Mb RAM chunks when reading/writing files BUFFER_SIZE = 10485760 # 10Mb def __init__(self, path, fanOut=1000): """ :param str path: Path to directory holding the job store :param int fanOut: Number of items to have in a directory before making subdirectories """ super(FileJobStore, self).__init__() self.jobStoreDir = absSymPath(path) logger.debug("Path to job store directory is '%s'.", self.jobStoreDir) # Directory where actual job files go, and their job-associated temp files self.jobsDir = os.path.join(self.jobStoreDir, 'jobs') # Directory where stats files go self.statsDir = os.path.join(self.jobStoreDir, 'stats') # Directory where non-job-associated files for the file store go self.filesDir = os.path.join(self.jobStoreDir, 'files/no-job') # Directory where job-associated files for the file store go. # Each per-job directory in here will have separate directories for # files to clean up and files to not clean up when the job is deleted. self.jobFilesDir = os.path.join(self.jobStoreDir, 'files/for-job') # Directory where shared files go self.sharedFilesDir = os.path.join(self.jobStoreDir, 'files/shared') self.fanOut = fanOut self.linkImports = None def __repr__(self): return 'FileJobStore({})'.format(self.jobStoreDir) def initialize(self, config): try: os.mkdir(self.jobStoreDir) except OSError as e: if e.errno == errno.EEXIST: raise JobStoreExistsException(self.jobStoreDir) else: raise mkdir_p(self.jobsDir) mkdir_p(self.statsDir) mkdir_p(self.filesDir) mkdir_p(self.jobFilesDir) mkdir_p(self.sharedFilesDir) self.linkImports = config.linkImports super(FileJobStore, self).initialize(config) def resume(self): if not os.path.isdir(self.jobStoreDir): raise NoSuchJobStoreException(self.jobStoreDir) super(FileJobStore, self).resume() def destroy(self): if os.path.exists(self.jobStoreDir): robust_rmtree(self.jobStoreDir) ########################################## # The following methods deal with creating/loading/updating/writing/checking for the # existence of jobs ########################################## def create(self, jobNode): # Get the job's name. We want to group jobs with the same name together. # This will be e.g. the function name for wrapped-function jobs. # Make sure to render it filename-safe usefulFilename = self._makeStringFilenameSafe(jobNode.jobName) # Make a unique temp directory under a directory for this job name, # possibly sprayed across multiple levels of subdirectories. absJobDir = tempfile.mkdtemp(prefix=self.JOB_DIR_PREFIX, dir=self._getArbitraryJobsDirForName(usefulFilename)) # Make the job to save job = JobGraph.fromJobNode(jobNode, jobStoreID=self._getJobIdFromDir(absJobDir), tryCount=self._defaultTryCount()) if hasattr(self, "_batchedJobGraphs") and self._batchedJobGraphs is not None: # Save it later self._batchedJobGraphs.append(job) else: # Save it now self.update(job) return job @contextmanager def batch(self): self._batchedJobGraphs = [] yield for jobGraph in self._batchedJobGraphs: self.update(jobGraph) self._batchedJobGraphs = None def waitForExists(self, jobStoreID, maxTries=35, sleepTime=1): """Spin-wait and block for a file to appear before returning False if it does not. The total max wait time is maxTries * sleepTime. The current default is tuned to match Linux NFS defaults where the client's cache of the directory listing on the server is supposed to become coherent within 30 sec. Delayes beyond that would probably indicate a pathologically slow file system that just should not be used for the jobStore. The warning will be sent to the log only on the first retry. In practice, the need for retries happens rarely, but it does happen over the course of large workflows with a jobStore on a busy NFS.""" for iTry in range(1,maxTries+1): jobFile = self._getJobFileName(jobStoreID) if os.path.exists(jobFile): return True if iTry >= maxTries: return False elif iTry == 1: logger.warning(("Job file `{}` for job `{}` does not exist (yet). We will try #{} more times with {}s " "intervals.").format(jobFile, jobStoreID, maxTries - iTry, sleepTime)) time.sleep(sleepTime) return False def exists(self, jobStoreID): return os.path.exists(self._getJobFileName(jobStoreID)) def getPublicUrl(self, jobStoreFileID): self._checkJobStoreFileID(jobStoreFileID) jobStorePath = self._getFilePathFromId(jobStoreFileID) if os.path.exists(jobStorePath): return 'file:' + jobStorePath else: raise NoSuchFileException(jobStoreFileID) def getSharedPublicUrl(self, sharedFileName): jobStorePath = os.path.join(self.sharedFilesDir, sharedFileName) if os.path.exists(jobStorePath): return 'file:' + jobStorePath else: raise NoSuchFileException(sharedFileName) def load(self, jobStoreID): self._checkJobStoreId(jobStoreID) # Load a valid version of the job jobFile = self._getJobFileName(jobStoreID) with open(jobFile, 'rb') as fileHandle: job = pickle.load(fileHandle) # The following cleans up any issues resulting from the failure of the # job during writing by the batch system. if os.path.isfile(jobFile + ".new"): logger.warn("There was a .new file for the job: %s", jobStoreID) os.remove(jobFile + ".new") job.setupJobAfterFailure(self.config) return job def update(self, job): # The job is serialised to a file suffixed by ".new" # The file is then moved to its correct path. # Atomicity guarantees use the fact the underlying file systems "move" # function is atomic. with open(self._getJobFileName(job.jobStoreID) + ".new", 'wb') as f: pickle.dump(job, f) # This should be atomic for the file system os.rename(self._getJobFileName(job.jobStoreID) + ".new", self._getJobFileName(job.jobStoreID)) def delete(self, jobStoreID): # The jobStoreID is the relative path to the directory containing the job, # removing this directory deletes the job. if self.exists(jobStoreID): # Remove the job-associated files in need of cleanup, which may or # may not live under the job's directory. robust_rmtree(self._getJobFilesCleanupDir(jobStoreID)) # Remove the job's directory itself. robust_rmtree(self._getJobDirFromId(jobStoreID)) def jobs(self): # Walk through list of temporary directories searching for jobs. # Jobs are files that start with 'job'. # Note that this also catches jobWhatever.new which exists if an update # is in progress. for tempDir in self._jobDirectories(): for i in os.listdir(tempDir): logger.warning('Job Dir: %s' % i) if i.startswith(self.JOB_DIR_PREFIX): # This is a job instance directory try: yield self.load(self._getJobIdFromDir(os.path.join(tempDir, i))) except NoSuchJobException: # An orphaned job may leave an empty or incomplete job file which we can safely ignore pass ########################################## # Functions that deal with temporary files associated with jobs ########################################## @contextmanager def optionalHardCopy(self, hardlink): if hardlink: saved = self.linkImports self.linkImports = False yield if hardlink: self.linkImports = saved def _copyOrLink(self, srcURL, destPath): # linking is not done be default because of issue #1755 srcPath = self._extractPathFromUrl(srcURL) if self.linkImports: os.symlink(os.path.realpath(srcPath), destPath) else: atomic_copy(srcPath, destPath) def _importFile(self, otherCls, url, sharedFileName=None, hardlink=False): if issubclass(otherCls, FileJobStore): if sharedFileName is None: absPath = self._getUniqueFilePath(url.path) # use this to get a valid path to write to in job store with self.optionalHardCopy(hardlink): self._copyOrLink(url, absPath) # TODO: os.stat(absPath).st_size consistently gives values lower than # getDirSizeRecursively() return FileID(self._getFileIdFromPath(absPath), os.stat(absPath).st_size) else: self._requireValidSharedFileName(sharedFileName) path = self._getSharedFilePath(sharedFileName) with self.optionalHardCopy(hardlink): self._copyOrLink(url, path) return None else: return super(FileJobStore, self)._importFile(otherCls, url, sharedFileName=sharedFileName) def _exportFile(self, otherCls, jobStoreFileID, url): if issubclass(otherCls, FileJobStore): atomic_copy(self._getFilePathFromId(jobStoreFileID), self._extractPathFromUrl(url)) else: super(FileJobStore, self)._exportFile(otherCls, jobStoreFileID, url) @classmethod def getSize(cls, url): return os.stat(cls._extractPathFromUrl(url)).st_size @classmethod def _readFromUrl(cls, url, writable): """ Writes the contents of a file to a source (writes url to writable) using a ~10Mb buffer. :param str url: A path as a string of the file to be read from. :param object writable: An open file object to write to. """ # we use a ~10Mb buffer to improve speed with open(cls._extractPathFromUrl(url), 'rb') as readable: shutil.copyfileobj(readable, writable, length=cls.BUFFER_SIZE) @classmethod def _writeToUrl(cls, readable, url): """ Writes the contents of a file to a source (writes readable to url) using a ~10Mb buffer. :param str url: A path as a string of the file to be written to. :param object readable: An open file object to read from. """ # we use a ~10Mb buffer to improve speed atomic_copyobj(readable, cls._extractPathFromUrl(url), length=cls.BUFFER_SIZE) @staticmethod def _extractPathFromUrl(url): """ :return: local file path of file pointed at by the given URL """ if url.netloc != '' and url.netloc != 'localhost': raise RuntimeError("The URL '%s' is invalid" % url.geturl()) return url.netloc + url.path @classmethod def _supportsUrl(cls, url, export=False): return url.scheme.lower() == 'file' def _makeStringFilenameSafe(self, arbitraryString): """ Given an arbitrary string, produce a filename-safe though not necessarily unique string based on it. The input string may be discarded altogether and replaced with any other nonempty filename-safe string. :param str arbitraryString: An arbitrary string :return: A filename-safe string """ # We will fill this in with the filename-safe parts we find. parts = [] for substring in re.findall("[A-Za-z0-9._-]+", arbitraryString): # Collect all the matching substrings parts.append(substring) if len(parts) == 0: parts.append("UNPRINTABLE") # Glue it all together return '_'.join(parts) def writeFile(self, localFilePath, jobStoreID=None, cleanup=False): absPath = self._getUniqueFilePath(localFilePath, jobStoreID, cleanup) relPath = self._getFileIdFromPath(absPath) atomic_copy(localFilePath, absPath) return relPath @contextmanager def writeFileStream(self, jobStoreID=None, cleanup=False): absPath = self._getUniqueFilePath('stream', jobStoreID, cleanup) relPath = self._getFileIdFromPath(absPath) with open(absPath, 'wb') as f: # Don't yield while holding an open file descriptor to the temp # file. That can result in temp files still being open when we try # to clean ourselves up, somehow, for certain workloads. yield f, relPath def getEmptyFileStoreID(self, jobStoreID=None, cleanup=False): with self.writeFileStream(jobStoreID, cleanup) as (fileHandle, jobStoreFileID): return jobStoreFileID def updateFile(self, jobStoreFileID, localFilePath): self._checkJobStoreFileID(jobStoreFileID) jobStoreFilePath = self._getFilePathFromId(jobStoreFileID) if os.path.samefile(jobStoreFilePath, localFilePath): # The files are already the same file. We can't copy on eover the other. return atomic_copy(localFilePath, jobStoreFilePath) def readFile(self, jobStoreFileID, localFilePath, symlink=False): self._checkJobStoreFileID(jobStoreFileID) jobStoreFilePath = self._getFilePathFromId(jobStoreFileID) localDirPath = os.path.dirname(localFilePath) if not symlink and os.path.islink(localFilePath): # We had a symlink and want to clobber it with a hardlink or copy. os.unlink(localFilePath) if os.path.exists(localFilePath) and os.path.samefile(jobStoreFilePath, localFilePath): # The files are already the same: same name, hardlinked, or # symlinked. There is nothing to do, and trying to shutil.copyfile # one over the other will fail. return if symlink: # If the reader will accept a symlink, so always give them one. # There's less that can go wrong. try: os.symlink(jobStoreFilePath, localFilePath) # It worked! return except OSError as e: if e.errno == errno.EEXIST: # Overwrite existing file, emulating shutil.copyfile(). os.unlink(localFilePath) # It would be very unlikely to fail again for same reason but possible # nonetheless in which case we should just give up. os.symlink(jobStoreFilePath, localFilePath) # Now we succeeded and don't need to copy return else: raise # If we get here, symlinking isn't an option. if os.stat(jobStoreFilePath).st_dev == os.stat(localDirPath).st_dev: # It is possible that we can hard link the file. # Note that even if the device numbers match, we can end up trying # to create a "cross-device" link. try: os.link(jobStoreFilePath, localFilePath) # It worked! return except OSError as e: if e.errno == errno.EEXIST: # Overwrite existing file, emulating shutil.copyfile(). os.unlink(localFilePath) # It would be very unlikely to fail again for same reason but possible # nonetheless in which case we should just give up. os.link(jobStoreFilePath, localFilePath) # Now we succeeded and don't need to copy return elif e.errno == errno.EXDEV: # It's a cross-device link even though it didn't appear to be. # Just keep going and hit the file copy case. pass else: logger.critical('Unexpected OSError when reading file from job store') logger.critical('jobStoreFilePath: ' + jobStoreFilePath + ' ' + str(os.path.exists(jobStoreFilePath))) logger.critical('localFilePath: ' + localFilePath + ' ' + str(os.path.exists(localFilePath))) raise # If we get here, neither a symlink nor a hardlink will work. # Make a complete copy. atomic_copy(jobStoreFilePath, localFilePath) def deleteFile(self, jobStoreFileID): if not self.fileExists(jobStoreFileID): return os.remove(self._getFilePathFromId(jobStoreFileID)) def fileExists(self, jobStoreFileID): absPath = self._getFilePathFromId(jobStoreFileID) if (not absPath.startswith(self.jobsDir) and not absPath.startswith(self.filesDir) and not absPath.startswith(self.jobFilesDir)): # Don't even look for it, it is out of bounds. raise NoSuchFileException(jobStoreFileID) try: st = os.stat(absPath) except os.error: return False if not stat.S_ISREG(st.st_mode): raise NoSuchFileException(jobStoreFileID) return True def getFileSize(self, jobStoreFileID): # Duplicate a bunch of fileExists to save on stat calls absPath = self._getFilePathFromId(jobStoreFileID) if (not absPath.startswith(self.jobsDir) and not absPath.startswith(self.filesDir) and not absPath.startswith(self.jobFilesDir)): # Don't even look for it, it is out of bounds. raise NoSuchFileException(jobStoreFileID) try: st = os.stat(absPath) except os.error: return 0 return st.st_size @contextmanager def updateFileStream(self, jobStoreFileID): self._checkJobStoreFileID(jobStoreFileID) # File objects are context managers (CM) so we could simply return what open returns. # However, it is better to wrap it in another CM so as to prevent users from accessing # the file object directly, without a with statement. with open(self._getFilePathFromId(jobStoreFileID), 'wb') as f: yield f @contextmanager def readFileStream(self, jobStoreFileID): self._checkJobStoreFileID(jobStoreFileID) with open(self._getFilePathFromId(jobStoreFileID), 'rb') as f: yield f ########################################## # The following methods deal with shared files, i.e. files not associated # with specific jobs. ########################################## def _getSharedFilePath(self, sharedFileName): return os.path.join(self.sharedFilesDir, sharedFileName) @contextmanager def writeSharedFileStream(self, sharedFileName, isProtected=None): # the isProtected parameter has no effect on the fileStore self._requireValidSharedFileName(sharedFileName) with AtomicFileCreate(self._getSharedFilePath(sharedFileName)) as tmpSharedFilePath: with open(tmpSharedFilePath, 'wb') as f: yield f @contextmanager def readSharedFileStream(self, sharedFileName): self._requireValidSharedFileName(sharedFileName) try: with open(self._getSharedFilePath(sharedFileName), 'rb') as f: yield f except IOError as e: if e.errno == errno.ENOENT: raise NoSuchFileException(sharedFileName) else: raise def writeStatsAndLogging(self, statsAndLoggingString): # Temporary files are placed in the stats directory tree fd, tempStatsFile = tempfile.mkstemp(prefix="stats", suffix=".new", dir=self._getArbitraryStatsDir()) writeFormat = 'w' if isinstance(statsAndLoggingString, str) else 'wb' with open(tempStatsFile, writeFormat) as f: f.write(statsAndLoggingString) os.close(fd) os.rename(tempStatsFile, tempStatsFile[:-4]) # This operation is atomic def readStatsAndLogging(self, callback, readAll=False): numberOfFilesProcessed = 0 for tempDir in self._statsDirectories(): for tempFile in os.listdir(tempDir): if tempFile.startswith('stats'): absTempFile = os.path.join(tempDir, tempFile) if os.path.isfile(absTempFile): if readAll or not tempFile.endswith('.new'): with open(absTempFile, 'rb') as fH: callback(fH) numberOfFilesProcessed += 1 newName = tempFile.rsplit('.', 1)[0] + '.new' newAbsTempFile = os.path.join(tempDir, newName) # Mark this item as read os.rename(absTempFile, newAbsTempFile) return numberOfFilesProcessed ########################################## # Private methods ########################################## def _getJobDirFromId(self, jobStoreID): """ Find the directory for a job, which holds its job file. :param str jobStoreID: ID of a job, which is a relative to self.jobsDir. :rtype : string, string is the absolute path to a job directory inside self.jobsDir. """ return os.path.join(self.jobsDir, jobStoreID) def _getJobIdFromDir(self, absPath): """ :param str absPath: The absolute path to a job directory under self.jobsDir which represents a job. :rtype : string, string is the job ID, which is a path relative to self.jobsDir """ return absPath[len(self.jobsDir)+1:] def _getJobFileName(self, jobStoreID): """ Return the path to the file containing the serialised JobGraph instance for the given job. :rtype: str """ return os.path.join(self._getJobDirFromId(jobStoreID), "job") def _getJobFilesDir(self, jobStoreID): """ Return the path to the directory that should hold files made by the given job that should survive its deletion. This directory will only be created if files are to be put in it. :rtype : string, string is the absolute path to the job's files directory """ return os.path.join(self.jobFilesDir, jobStoreID) def _getJobFilesCleanupDir(self, jobStoreID): """ Return the path to the directory that should hold files made by the given job that will be deleted when the job is deleted. This directory will only be created if files are to be put in it. It may or may not be a subdirectory of the job's own directory. :rtype : string, string is the absolute path to the job's cleanup files directory """ return os.path.join(self.jobFilesDir, jobStoreID, "cleanup") def _checkJobStoreId(self, jobStoreID): """ Raises a NoSuchJobException if the job with ID jobStoreID does not exist. """ if not self.waitForExists(jobStoreID,30): raise NoSuchJobException(jobStoreID) def _getFilePathFromId(self, jobStoreFileID): """ :param str jobStoreFileID: The ID of a file :rtype : string, string is the absolute path that that file should appear at on disk, under either self.jobsDir if it is to be cleaned up with a job, or self.filesDir otherwise. """ # We just make the file IDs paths under the job store overall. absPath = os.path.join(self.jobStoreDir, jobStoreFileID) # Don't validate here, we are called by the validation logic return absPath def _getFileIdFromPath(self, absPath): """ :param str absPath: The absolute path of a file. :rtype : string, string is the file ID. """ return absPath[len(self.jobStoreDir)+1:] def _checkJobStoreFileID(self, jobStoreFileID): """ :raise NoSuchFileException: if the file with ID jobStoreFileID does not exist or is not a file """ if not self.fileExists(jobStoreFileID): raise NoSuchFileException(jobStoreFileID) def _getArbitraryJobsDirForName(self, jobNameSlug): """ Gets a temporary directory in a multi-level hierarchy in self.jobsDir. The directory is not unique and may already have other jobs' directories in it. We organize them at the top level by job name, to be user-inspectable. We make sure to prepend a string so that job names can't collide with spray directory names. :param str jobNameSlug: A partial filename derived from the job name. Used as the first level of the directory hierarchy. :rtype : string, path to temporary directory in which to place files/directories. """ if len(os.listdir(self.jobsDir)) > self.fanOut: # Make sure that we don't over-fill the root with too many unique job names. # Go in a subdirectory tree, and then go by job name and make another tree. return self._getDynamicSprayDir(os.path.join(self._getDynamicSprayDir(self.jobsDir), self.JOB_NAME_DIR_PREFIX + jobNameSlug)) else: # Just go in the root return self._getDynamicSprayDir(os.path.join(self.jobsDir, self.JOB_NAME_DIR_PREFIX + jobNameSlug)) def _getArbitraryStatsDir(self): """ Gets a temporary directory in a multi-level hierarchy in self.statsDir. The directory is not unique and may already have other stats files in it. :rtype : string, path to temporary directory in which to place files/directories. """ return self._getDynamicSprayDir(self.statsDir) def _getArbitraryFilesDir(self): """ Gets a temporary directory in a multi-level hierarchy in self.filesDir. The directory is not unique and may already have other user files in it. :rtype : string, path to temporary directory in which to place files/directories. """ return self._getDynamicSprayDir(self.filesDir) def _getDynamicSprayDir(self, root): """ Gets a temporary directory in a possibly multi-level hierarchy of directories under the given root. Each time a directory in the hierarchy starts to fill up, additional hierarchy levels are created under it, and we randomly "spray" further files and directories across them. We can't actually enforce that we never go over our internal limit for files in a directory, because any number of calls to this function can be happening simultaneously. But we can enforce that, once too many files are visible on disk, only subdirectories will be created. The returned directory will exist, and may contain other data already. The caller may not create any files or directories in the returned directory with single-character names that are in self.validDirs. :param str root : directory to put the hierarchy under, which will fill first. :rtype : string, path to temporary directory in which to place files/directories. """ tempDir = root # Make sure the root exists mkdir_p(tempDir) while len(os.listdir(tempDir)) >= self.fanOut: # We need to use a layer of directories under here to avoid over-packing the directory tempDir = os.path.join(tempDir, random.choice(self.validDirs)) mkdir_p(tempDir) # When we get here, we found a sufficiently empty directory return tempDir def _walkDynamicSprayDir(self, root): """ Walks over a directory tree filled in by _getDynamicSprayDir. Yields each directory _getDynamicSprayDir has ever returned, and no directories it has not returned (besides the root). If the caller looks in the directory, they must ignore subdirectories with single-character names in self.validDirs. :param str root : directory the hierarchy was put under :rtype : an iterator over directories """ # Always yield the root. # The caller is responsible for dealing with it if it has gone away. yield root children = [] try: # Look for children children = os.listdir(root) except: # Don't care if they are gone pass for child in children: # Go over all the children if child not in self.validDirsSet: # Only look at our reserved names we use for fan-out continue # We made this directory, so go look in it childPath = os.path.join(root, child) # Recurse for item in self._walkDynamicSprayDir(childPath): yield item def _jobDirectories(self): """ :rtype : an iterator to the temporary directories containing job files. They may also contain directories containing more job files. """ # Walking the job directories is more complicated. # We have one layer of spray (which is sometimes bypassed, but that's OK), then a job name, then another layer. # We can tell the job name directories from the spray directories because they start with self.JOB_NAME_DIR_PREFIX. # We never look at the directories containing the job name directories, # so they aren't mistaken for the leaf-level per-job job directories. for jobHoldingDir in self._walkDynamicSprayDir(self.jobsDir): # For every directory in the first spray, look at children children = [] try: children = os.listdir(jobHoldingDir) except: pass for jobNameDir in children: if not jobNameDir.startswith(self.JOB_NAME_DIR_PREFIX): continue # Now we have only the directories that are named after jobs. Look inside them. for inner in self._walkDynamicSprayDir(os.path.join(jobHoldingDir, jobNameDir)): yield inner def _statsDirectories(self): """ :rtype : an iterator to the temporary directories containing stats files. They may also contain directories containing more stats files. """ return self._walkDynamicSprayDir(self.statsDir) def _getUniqueFilePath(self, fileName, jobStoreID=None, cleanup=False): """ Create unique file name within a jobStore directory or tmp directory. :param fileName: A file name, which can be a full path as only the basename will be used. :param jobStoreID: If given, the path returned will be in a directory including the job's ID as part of its path. :param bool cleanup: If True and jobStoreID is set, the path will be in a place such that it gets deleted when the job is deleted. :return: The full path with a unique file name. """ # Give the file a unique directory that either will be cleaned up with a job or won't. directory = self._getFileDirectory(jobStoreID, cleanup) # And then a path under it uniquePath = os.path.join(directory, os.path.basename(fileName)) # No need to check if it exists already; it is in a unique directory. return uniquePath def _getFileDirectory(self, jobStoreID=None, cleanup=False): """ Get a new empty directory path for a file to be stored at. :param str jobStoreID: If the jobStoreID is not None, the file wil be associated with the job with that ID. :param bool cleanup: If cleanup is also True, this directory will be cleaned up when the job is deleted. :rtype :string, string is the absolute path to a directory to put the file in. """ if jobStoreID != None: # Make a temporary file within the job's files directory # Make sure the job is legit self._checkJobStoreId(jobStoreID) # Find where all its created files should live, depending on if # they need to go away when the job is deleted or not. jobFilesDir = self._getJobFilesDir(jobStoreID) if not cleanup \ else self._getJobFilesCleanupDir(jobStoreID) # Lazily create the parent directory. # We don't want our tree filled with confusingly empty directories. mkdir_p(jobFilesDir) # Then make a temp directory inside it return tempfile.mkdtemp(prefix='file-', dir=jobFilesDir) else: # Make a temporary file within the non-job-associated files hierarchy return tempfile.mkdtemp(prefix='file-', dir=self._getArbitraryFilesDir()) toil-releases-3.24.0/src/toil/jobStores/googleJobStore.py000066400000000000000000000466041362134276200233760ustar00rootroot00000000000000# Copyright (C) 2015-2016 Regents of the University of California # # 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. from __future__ import absolute_import from functools import wraps from future import standard_library standard_library.install_aliases() from builtins import str from contextlib import contextmanager import uuid import logging import time import os from toil import pickle from toil.lib.misc import AtomicFileCreate from toil.lib.retry import retry from toil.lib.compatibility import compat_bytes from google.cloud import storage, exceptions from google.api_core.exceptions import GoogleAPICallError, InternalServerError, ServiceUnavailable from toil.lib.misc import truncExpBackoff # Python 3 compatibility imports from six.moves import StringIO from toil.jobStores.abstractJobStore import (AbstractJobStore, NoSuchJobException, NoSuchFileException, NoSuchJobStoreException, JobStoreExistsException, ConcurrentFileModificationException) from toil.jobStores.utils import WritablePipe, ReadablePipe from toil.jobGraph import JobGraph log = logging.getLogger(__name__) GOOGLE_STORAGE = 'gs' # TODO # - needed to run 'gsutil config' to get 'gs_oauth2_refresh_token' in the boto file # - needed to copy client_id and client_secret to the oauth section # - Azure uses bz2 compression with pickling. Is this useful here? # - better way to assign job ids? - currently 'job'+uuid def googleRetryPredicate(e): """ necessary because under heavy load google may throw TooManyRequests: 429 The project exceeded the rate limit for creating and deleting buckets. or numerous other server errors which need to be retried. """ if isinstance(e, GoogleAPICallError) and e.code == 429: return True if isinstance(e, InternalServerError) or isinstance(e, ServiceUnavailable): return True return False def googleRetry(f): """ This decorator retries the wrapped function if google throws any angry service errors. It should wrap any function that makes use of the Google Client API """ @wraps(f) def wrapper(*args, **kwargs): for attempt in retry(delays=truncExpBackoff(), timeout=300, predicate=googleRetryPredicate): with attempt: return f(*args, **kwargs) return wrapper class GoogleJobStore(AbstractJobStore): nodeServiceAccountJson = '/root/service_account.json' def __init__(self, locator): super(GoogleJobStore, self).__init__() try: projectID, namePrefix = locator.split(":", 1) except ValueError: # we don't have a specified projectID namePrefix = locator projectID = None self.locator = locator self.projectID = projectID self.bucketName = namePrefix+"--toil" log.debug("Instantiating google jobStore with name: %s", self.bucketName) # this is a :class:`~google.cloud.storage.bucket.Bucket` self.bucket = None self.statsBaseID = 'f16eef0c-b597-4b8b-9b0c-4d605b4f506c' self.statsReadPrefix = '_' self.readStatsBaseID = self.statsReadPrefix+self.statsBaseID self.sseKey = None # Determine if we have an override environment variable for our credentials. # We don't pull out the filename; we just see if a name is there. self.credentialsFromEnvironment = bool(os.getenv('GOOGLE_APPLICATION_CREDENTIALS', False)) if self.credentialsFromEnvironment and not os.path.exists(os.getenv('GOOGLE_APPLICATION_CREDENTIALS')): # If the file is missing, complain. # This variable holds a file name and not any sensitive data itself. log.warning("File '%s' from GOOGLE_APPLICATION_CREDENTIALS is unavailable! " "We may not be able to authenticate!", os.getenv('GOOGLE_APPLICATION_CREDENTIALS')) if not self.credentialsFromEnvironment and os.path.exists(self.nodeServiceAccountJson): # load credentials from a particular file on GCE nodes if an override path is not set self.storageClient = storage.Client.from_service_account_json(self.nodeServiceAccountJson) else: # Either a filename is specified, or our fallback file isn't there. # See if Google can work out how to authenticate. self.storageClient = storage.Client() @googleRetry def initialize(self, config=None): try: self.bucket = self.storageClient.create_bucket(self.bucketName) except exceptions.Conflict: raise JobStoreExistsException(self.locator) super(GoogleJobStore, self).initialize(config) # set up sever side encryption after we set up config in super if self.config.sseKey is not None: with open(self.config.sseKey) as f: self.sseKey = compat_bytes(f.read()) assert len(self.sseKey) == 32 @googleRetry def resume(self): try: self.bucket = self.storageClient.get_bucket(self.bucketName) except exceptions.NotFound: raise NoSuchJobStoreException(self.locator) super(GoogleJobStore, self).resume() @googleRetry def destroy(self): try: self.bucket = self.storageClient.get_bucket(self.bucketName) except exceptions.NotFound: # just return if not connect to physical storage. Needed for idempotency return try: self.bucket.delete(force=True) # throws ValueError if bucket has more than 256 objects. Then we must delete manually except ValueError: self.bucket.delete_blobs(self.bucket.list_blobs()) self.bucket.delete() # if ^ throws a google.cloud.exceptions.Conflict, then we should have a deletion retry mechanism. # google freaks out if we call delete multiple times on the bucket obj, so after success # just set to None. self.bucket = None def create(self, jobNode): jobStoreID = self._newJobID() log.debug("Creating job %s for '%s'", jobStoreID, '' if jobNode.command is None else jobNode.command) job = JobGraph.fromJobNode(jobNode, jobStoreID=jobStoreID, tryCount=self._defaultTryCount()) if hasattr(self, "_batchedJobGraphs") and self._batchedJobGraphs is not None: self._batchedJobGraphs.append(job) else: self._writeString(jobStoreID, pickle.dumps(job, protocol=pickle.HIGHEST_PROTOCOL)) # UPDATE: bz2.compress( return job def _newJobID(self): return "job"+str(uuid.uuid4()) @googleRetry def exists(self, jobStoreID): return self.bucket.blob(compat_bytes(jobStoreID), encryption_key=self.sseKey).exists() @googleRetry def getPublicUrl(self, fileName): blob = self.bucket.get_blob(compat_bytes(fileName), encryption_key=self.sseKey) if blob is None: raise NoSuchFileException(fileName) return blob.generate_signed_url(self.publicUrlExpiration) def getSharedPublicUrl(self, sharedFileName): return self.getPublicUrl(sharedFileName) def load(self, jobStoreID): try: jobString = self._readContents(jobStoreID) except NoSuchFileException: raise NoSuchJobException(jobStoreID) return pickle.loads(jobString) # UPDATE bz2.decompress( def update(self, job): self._writeString(job.jobStoreID, pickle.dumps(job, protocol=pickle.HIGHEST_PROTOCOL), update=True) @googleRetry def delete(self, jobStoreID): self._delete(jobStoreID) # best effort delete associated files for blob in self.bucket.list_blobs(prefix=compat_bytes(jobStoreID)): self._delete(blob.name) def getEnv(self): """ Return a dict of environment variables to send out to the workers so they can load the job store. """ env = {} if self.credentialsFromEnvironment: # Send along the environment variable that points to the credentials file. # It must be available in the same place on all nodes. env['GOOGLE_APPLICATION_CREDENTIALS'] = os.getenv('GOOGLE_APPLICATION_CREDENTIALS') return env @googleRetry def jobs(self): for blob in self.bucket.list_blobs(prefix=b'job'): jobStoreID = blob.name if len(jobStoreID) == 39: # 'job' + uuid length yield self.load(jobStoreID) def writeFile(self, localFilePath, jobStoreID=None, cleanup=False): fileID = self._newID(isFile=True, jobStoreID=jobStoreID if cleanup else None) with open(localFilePath) as f: self._writeFile(fileID, f) return fileID @contextmanager def writeFileStream(self, jobStoreID=None, cleanup=False): fileID = self._newID(isFile=True, jobStoreID=jobStoreID if cleanup else None) with self._uploadStream(fileID, update=False) as writable: yield writable, fileID def getEmptyFileStoreID(self, jobStoreID=None, cleanup=False): fileID = self._newID(isFile=True, jobStoreID=jobStoreID if cleanup else None) self._writeFile(fileID, StringIO("")) return fileID @googleRetry def readFile(self, jobStoreFileID, localFilePath, symlink=False): # used on non-shared files which will be encrypted if available # checking for JobStoreID existence if not self.fileExists(jobStoreFileID): raise NoSuchFileException(jobStoreFileID) with AtomicFileCreate(localFilePath) as tmpPath: with open(tmpPath, 'w') as writeable: blob = self.bucket.get_blob(compat_bytes(jobStoreFileID), encryption_key=self.sseKey) blob.download_to_file(writeable) @contextmanager def readFileStream(self, jobStoreFileID): with self.readSharedFileStream(jobStoreFileID, isProtected=True) as readable: yield readable def deleteFile(self, jobStoreFileID): self._delete(jobStoreFileID) @googleRetry def fileExists(self, jobStoreFileID): return self.bucket.blob(compat_bytes(jobStoreFileID), encryption_key=self.sseKey).exists() @googleRetry def getFileSize(self, jobStoreFileID): if not self.fileExists(jobStoreFileID): return 0 return self.bucket.get_blob(compat_bytes(jobStoreFileID), encryption_key=self.sseKey).size def updateFile(self, jobStoreFileID, localFilePath): with open(localFilePath) as f: self._writeFile(jobStoreFileID, f, update=True) @contextmanager def updateFileStream(self, jobStoreFileID): with self._uploadStream(jobStoreFileID, update=True) as writable: yield writable @contextmanager def writeSharedFileStream(self, sharedFileName, isProtected=True): with self._uploadStream(sharedFileName, encrypt=isProtected, update=True) as writable: yield writable @contextmanager def readSharedFileStream(self, sharedFileName, isProtected=True): with self._downloadStream(sharedFileName, encrypt=isProtected) as readable: yield readable @classmethod @googleRetry def _getBlobFromURL(cls, url, exists=False): """ Gets the blob specified by the url. caution: makes no api request. blob may not ACTUALLY exist :param urlparse.ParseResult url: the URL :param bool exists: if True, then syncs local blob object with cloud and raises exceptions if it doesn't exist remotely :return: the blob requested :rtype: :class:`~google.cloud.storage.blob.Blob` """ bucketName = url.netloc fileName = url.path # remove leading '/', which can cause problems if fileName is a path if fileName.startswith('/'): fileName = fileName[1:] storageClient = storage.Client() bucket = storageClient.get_bucket(bucketName) blob = bucket.blob(compat_bytes(fileName)) if exists: if not blob.exists(): raise NoSuchFileException # sync with cloud so info like size is available blob.reload() return blob @classmethod def getSize(cls, url): return cls._getBlobFromURL(url, exists=True).size @classmethod def _readFromUrl(cls, url, writable): blob = cls._getBlobFromURL(url, exists=True) blob.download_to_file(writable) @classmethod def _supportsUrl(cls, url, export=False): return url.scheme.lower() == 'gs' @classmethod def _writeToUrl(cls, readable, url): blob = cls._getBlobFromURL(url) blob.upload_from_file(readable) def writeStatsAndLogging(self, statsAndLoggingString): statsID = self.statsBaseID + str(uuid.uuid4()) log.debug("Writing stats file: %s", statsID) with self._uploadStream(statsID, encrypt=False, update=False) as f: f.write(statsAndLoggingString) @googleRetry def readStatsAndLogging(self, callback, readAll=False): prefix = self.readStatsBaseID if readAll else self.statsBaseID filesRead = 0 lastTry = False while True: filesReadThisLoop = 0 # prefix seems broken for blob in self.bucket.list_blobs(prefix=compat_bytes(prefix)): try: with self.readSharedFileStream(blob.name) as readable: log.debug("Reading stats file: %s", blob.name) callback(readable) filesReadThisLoop += 1 if not readAll: # rename this file by copying it and deleting the old version to avoid # rereading it newID = self.readStatsBaseID + blob.name[len(self.statsBaseID):] # NOTE: just copies then deletes old. self.bucket.rename_blob(blob, compat_bytes(newID)) except NoSuchFileException: log.debug("Stats file not found: %s", blob.name) if readAll: # The readAll parameter is only by the toil stats util after the completion of the # pipeline. Assume that this means the bucket is in a consistent state when readAll # is passed. return filesReadThisLoop if filesReadThisLoop == 0: # Listing is unfortunately eventually consistent so we can't be 100% sure there # really aren't any stats files left to read if lastTry: # this was our second try, we are reasonably sure there aren't any stats # left to gather break # Try one more time in a couple seconds time.sleep(5) lastTry = True continue else: lastTry = False filesRead += filesReadThisLoop return filesRead @staticmethod def _newID(isFile=False, jobStoreID=None): if isFile and jobStoreID: # file associated with job return jobStoreID+str(uuid.uuid4()) elif isFile: # nonassociated file return str(uuid.uuid4()) else: # job id return "job"+str(uuid.uuid4()) @googleRetry def _delete(self, jobStoreFileID): if self.fileExists(jobStoreFileID): self.bucket.get_blob(compat_bytes(jobStoreFileID)).delete() # remember, this is supposed to be idempotent, so we don't do anything # if the file doesn't exist @googleRetry def _readContents(self, jobStoreID): """ To be used on files representing jobs only. Which will be encrypted if possible. :param jobStoreID: the ID of the job :type jobStoreID: str :return: contents of the job file :rtype: string """ job = self.bucket.get_blob(compat_bytes(jobStoreID), encryption_key=self.sseKey) if job is None: raise NoSuchJobException(jobStoreID) return job.download_as_string() @googleRetry def _writeFile(self, jobStoreID, fileObj, update=False, encrypt=True): blob = self.bucket.blob(compat_bytes(jobStoreID), encryption_key=self.sseKey if encrypt else None) if not update: # TODO: should probably raise a special exception and be added to all jobStores assert not blob.exists() else: if not blob.exists(): raise NoSuchFileException(jobStoreID) blob.upload_from_file(fileObj) def _writeString(self, jobStoreID, stringToUpload, **kwarg): self._writeFile(jobStoreID, StringIO(stringToUpload), **kwarg) @contextmanager @googleRetry def _uploadStream(self, fileName, update=False, encrypt=True): """ Yields a context manager that can be used to write to the bucket with a stream. See :class:`~toil.jobStores.utils.WritablePipe` for an example. Will throw assertion error if the file shouldn't be updated and yet exists. :param fileName: name of file to be inserted into bucket :type fileName: str :param update: whether or not the file is to be updated :type update: bool :param encrypt: whether or not the file is encrypted :type encrypt: bool :return: an instance of WritablePipe. :rtype: :class:`~toil.jobStores.utils.writablePipe` """ blob = self.bucket.blob(compat_bytes(fileName), encryption_key=self.sseKey if encrypt else None) class UploadPipe(WritablePipe): def readFrom(self, readable): if not update: assert not blob.exists() blob.upload_from_file(readable) with UploadPipe() as writable: yield writable @contextmanager @googleRetry def _downloadStream(self, fileName, encrypt=True): """ Yields a context manager that can be used to read from the bucket with a stream. See :class:`~toil.jobStores.utils.WritablePipe` for an example. :param fileName: name of file in bucket to be read :type fileName: str :param encrypt: whether or not the file is encrypted :type encrypt: bool :return: an instance of ReadablePipe. :rtype: :class:`~toil.jobStores.utils.ReadablePipe` """ blob = self.bucket.get_blob(compat_bytes(fileName), encryption_key=self.sseKey if encrypt else None) if blob is None: raise NoSuchFileException(fileName) class DownloadPipe(ReadablePipe): def writeTo(self, writable): try: blob.download_to_file(writable) finally: writable.close() with DownloadPipe() as readable: yield readable toil-releases-3.24.0/src/toil/jobStores/utils.py000066400000000000000000000213061362134276200216020ustar00rootroot00000000000000from builtins import object import codecs import logging import os import errno from abc import ABCMeta from abc import abstractmethod from toil.lib.threading import ExceptionalThread from future.utils import with_metaclass log = logging.getLogger(__name__) class WritablePipe(with_metaclass(ABCMeta, object)): """ An object-oriented wrapper for os.pipe. Clients should subclass it, implement :meth:`.readFrom` to consume the readable end of the pipe, then instantiate the class as a context manager to get the writable end. See the example below. >>> import sys, shutil >>> class MyPipe(WritablePipe): ... def readFrom(self, readable): ... shutil.copyfileobj(codecs.getreader('utf-8')(readable), sys.stdout) >>> with MyPipe() as writable: ... _ = writable.write('Hello, world!\\n'.encode('utf-8')) Hello, world! Each instance of this class creates a thread and invokes the readFrom method in that thread. The thread will be join()ed upon normal exit from the context manager, i.e. the body of the `with` statement. If an exception occurs, the thread will not be joined but a well-behaved :meth:`.readFrom` implementation will terminate shortly thereafter due to the pipe having been closed. Now, exceptions in the reader thread will be reraised in the main thread: >>> class MyPipe(WritablePipe): ... def readFrom(self, readable): ... raise RuntimeError('Hello, world!') >>> with MyPipe() as writable: ... pass Traceback (most recent call last): ... RuntimeError: Hello, world! More complicated, less illustrative tests: Same as above, but provving that handles are closed: >>> x = os.dup(0); os.close(x) >>> class MyPipe(WritablePipe): ... def readFrom(self, readable): ... raise RuntimeError('Hello, world!') >>> with MyPipe() as writable: ... pass Traceback (most recent call last): ... RuntimeError: Hello, world! >>> y = os.dup(0); os.close(y); x == y True Exceptions in the body of the with statement aren't masked, and handles are closed: >>> x = os.dup(0); os.close(x) >>> class MyPipe(WritablePipe): ... def readFrom(self, readable): ... pass >>> with MyPipe() as writable: ... raise RuntimeError('Hello, world!') Traceback (most recent call last): ... RuntimeError: Hello, world! >>> y = os.dup(0); os.close(y); x == y True """ @abstractmethod def readFrom(self, readable): """ Implement this method to read data from the pipe. :param file readable: the file object representing the readable end of the pipe. Do not explicitly invoke the close() method of the object, that will be done automatically. """ raise NotImplementedError() def _reader(self): with os.fdopen(self.readable_fh, 'rb') as readable: # TODO: If the reader somehow crashes here, both threads might try # to close readable_fh. Fortunately we don't do anything that # should be able to fail here. self.readable_fh = None # signal to parent thread that we've taken over self.readFrom(readable) self.reader_done = True def __init__(self): super(WritablePipe, self).__init__() self.readable_fh = None self.writable = None self.thread = None self.reader_done = False def __enter__(self): self.readable_fh, writable_fh = os.pipe() self.writable = os.fdopen(writable_fh, 'wb') self.thread = ExceptionalThread(target=self._reader) self.thread.start() return self.writable def __exit__(self, exc_type, exc_val, exc_tb): # Closeing the writable end will send EOF to the readable and cause the reader thread # to finish. # TODO: Can close() fail? If so, whould we try and clean up after the reader? self.writable.close() try: if self.thread is not None: # reraises any exception that was raised in the thread self.thread.join() except Exception as e: if exc_type is None: # Only raise the child exception if there wasn't # already an exception in the main thread raise else: log.error('Swallowing additional exception in reader thread: %s', str(e)) finally: # The responsibility for closing the readable end is generally that of the reader # thread. To cover the small window before the reader takes over we also close it here. readable_fh = self.readable_fh if readable_fh is not None: # Close the file handle. The reader thread must be dead now. os.close(readable_fh) class ReadablePipe(with_metaclass(ABCMeta, object)): """ An object-oriented wrapper for os.pipe. Clients should subclass it, implement :meth:`.writeTo` to place data into the writable end of the pipe, then instantiate the class as a context manager to get the writable end. See the example below. >>> import sys, shutil >>> class MyPipe(ReadablePipe): ... def writeTo(self, writable): ... writable.write('Hello, world!\\n'.encode('utf-8')) >>> with MyPipe() as readable: ... shutil.copyfileobj(codecs.getreader('utf-8')(readable), sys.stdout) Hello, world! Each instance of this class creates a thread and invokes the :meth:`.writeTo` method in that thread. The thread will be join()ed upon normal exit from the context manager, i.e. the body of the `with` statement. If an exception occurs, the thread will not be joined but a well-behaved :meth:`.writeTo` implementation will terminate shortly thereafter due to the pipe having been closed. Now, exceptions in the reader thread will be reraised in the main thread: >>> class MyPipe(ReadablePipe): ... def writeTo(self, writable): ... raise RuntimeError('Hello, world!') >>> with MyPipe() as readable: ... pass Traceback (most recent call last): ... RuntimeError: Hello, world! More complicated, less illustrative tests: Same as above, but provving that handles are closed: >>> x = os.dup(0); os.close(x) >>> class MyPipe(ReadablePipe): ... def writeTo(self, writable): ... raise RuntimeError('Hello, world!') >>> with MyPipe() as readable: ... pass Traceback (most recent call last): ... RuntimeError: Hello, world! >>> y = os.dup(0); os.close(y); x == y True Exceptions in the body of the with statement aren't masked, and handles are closed: >>> x = os.dup(0); os.close(x) >>> class MyPipe(ReadablePipe): ... def writeTo(self, writable): ... pass >>> with MyPipe() as readable: ... raise RuntimeError('Hello, world!') Traceback (most recent call last): ... RuntimeError: Hello, world! >>> y = os.dup(0); os.close(y); x == y True """ @abstractmethod def writeTo(self, writable): """ Implement this method to read data from the pipe. :param file writable: the file object representing the writable end of the pipe. Do not explicitly invoke the close() method of the object, that will be done automatically. """ raise NotImplementedError() def _writer(self): try: with os.fdopen(self.writable_fh, 'wb') as writable: self.writeTo(writable) except IOError as e: # The other side of the pipe may have been closed by the # reading thread, which is OK. if e.errno != errno.EPIPE: raise def __init__(self): super(ReadablePipe, self).__init__() self.writable_fh = None self.readable = None self.thread = None def __enter__(self): readable_fh, self.writable_fh = os.pipe() self.readable = os.fdopen(readable_fh, 'rb') self.thread = ExceptionalThread(target=self._writer) self.thread.start() return self.readable def __exit__(self, exc_type, exc_val, exc_tb): # Close the read end of the pipe. The writing thread may # still be writing to the other end, but this will wake it up # if that's the case. self.readable.close() try: if self.thread is not None: # reraises any exception that was raised in the thread self.thread.join() except: if exc_type is None: # Only raise the child exception if there wasn't # already an exception in the main thread raise toil-releases-3.24.0/src/toil/leader.py000066400000000000000000001462071362134276200177340ustar00rootroot00000000000000# Copyright (C) 2015-2018 Regents of the University of California # # 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. """ The leader script (of the leader/worker pair) for running jobs. """ from __future__ import absolute_import from __future__ import division from future import standard_library standard_library.install_aliases() from builtins import str from builtins import object from builtins import super import logging import time import os import glob from toil.lib.humanize import bytes2human from toil import resolveEntryPoint try: from toil.cwl.cwltoil import CWL_INTERNAL_JOBS except ImportError: # CWL extra not installed CWL_INTERNAL_JOBS = () from toil.jobStores.abstractJobStore import NoSuchJobException from toil.lib.throttle import LocalThrottle from toil.provisioners.clusterScaler import ScalerThread from toil.serviceManager import ServiceManager from toil.statsAndLogging import StatsAndLogging from toil.job import JobNode, ServiceJobNode from toil.toilState import ToilState from toil.common import Toil, ToilMetrics logger = logging.getLogger( __name__ ) ############################################################################### # Implementation Notes # # Multiple predecessors: # There is special-case handling for jobs with multiple predecessors as a # performance optimization. This minimize number of expensive loads of # jobGraphs from jobStores. However, this special case could be unnecessary. # The jobGraph is loaded to update predecessorsFinished, in # _checkSuccessorReadyToRunMultiplePredecessors, however it doesn't appear to # write the jobGraph back the jobStore. Thus predecessorsFinished may really # be leader state and could moved out of the jobGraph. This would make this # special-cases handling unnecessary and simplify the leader. # Issue #2136 ############################################################################### #################################################### # Exception thrown by the Leader class when one or more jobs fails #################################################### class FailedJobsException(Exception): def __init__(self, jobStoreLocator, failedJobs, jobStore): msg = "The job store '%s' contains %i failed jobs" % (jobStoreLocator, len(failedJobs)) try: msg += ": %s" % ", ".join((str(failedJob) for failedJob in failedJobs)) for jobNode in failedJobs: job = jobStore.load(jobNode.jobStoreID) if job.logJobStoreFileID: msg += "\n=========> Failed job %s \n" % jobNode with job.getLogFileHandle(jobStore) as fH: msg += fH.read().decode('utf-8') msg += "<=========\n" # catch failures to prepare more complex details and only return the basics except: logger.exception('Exception when compiling information about failed jobs') super().__init__() self.jobStoreLocator = jobStoreLocator self.numberOfFailedJobs = len(failedJobs) #################################################### # Exception thrown by the Leader class when a deadlock is encountered due to insufficient # resources to run the workflow #################################################### class DeadlockException(Exception): def __init__(self, msg): msg = "Deadlock encountered: " + msg super().__init__() #################################################### ##Following class represents the leader #################################################### class Leader(object): """ Class that encapsulates the logic of the leader. """ def __init__(self, config, batchSystem, provisioner, jobStore, rootJob, jobCache=None): """ :param toil.common.Config config: :param toil.batchSystems.abstractBatchSystem.AbstractBatchSystem batchSystem: :param toil.provisioners.abstractProvisioner.AbstractProvisioner provisioner :param toil.jobStores.abstractJobStore.AbstractJobStore jobStore: :param toil.jobGraph.JobGraph rootJob If jobCache is passed, it must be a dict from job ID to pre-existing JobGraph objects. Jobs will be loaded from the cache (which can be downloaded from the jobStore in a batch) during the construction of the ToilState object. """ # Object containing parameters for the run self.config = config # The job store self.jobStore = jobStore self.jobStoreLocator = config.jobStore # Get a snap shot of the current state of the jobs in the jobStore self.toilState = ToilState(jobStore, rootJob, jobCache=jobCache) logger.debug("Found %s jobs to start and %i jobs with successors to run", len(self.toilState.updatedJobs), len(self.toilState.successorCounts)) # Batch system self.batchSystem = batchSystem assert len(self.batchSystem.getIssuedBatchJobIDs()) == 0 # Batch system must start with no active jobs! logger.debug("Checked batch system has no running jobs and no updated jobs") # Map of batch system IDs to IssuedJob tuples self.jobBatchSystemIDToIssuedJob = {} # Number of preemptible jobs currently being run by batch system self.preemptableJobsIssued = 0 # Tracking the number service jobs issued, # this is used limit the number of services issued to the batch system self.serviceJobsIssued = 0 self.serviceJobsToBeIssued = [] # A queue of service jobs that await scheduling #Equivalents for service jobs to be run on preemptible nodes self.preemptableServiceJobsIssued = 0 self.preemptableServiceJobsToBeIssued = [] # Timing of the jobGraph rescuing method self.timeSinceJobsLastRescued = None # Hash to store number of times a job is lost by the batch system, # used to decide if to reissue an apparently missing job self.reissueMissingJobs_missingHash = {} # Class used to create/destroy nodes in the cluster, may be None if # using a statically defined cluster self.provisioner = provisioner # Create cluster scaling thread if the provisioner is not None self.clusterScaler = None if self.provisioner is not None and len(self.provisioner.nodeTypes) > 0: self.clusterScaler = ScalerThread(self.provisioner, self, self.config) # A service manager thread to start and terminate services self.serviceManager = ServiceManager(jobStore, self.toilState) # A thread to manage the aggregation of statistics and logging from the run self.statsAndLogging = StatsAndLogging(self.jobStore, self.config) # Set used to monitor deadlocked jobs self.potentialDeadlockedJobs = set() self.potentialDeadlockTime = 0 # A dashboard that runs on the leader node in AWS clusters to track the state # of the cluster self.toilMetrics = None # internal jobs we should not expose at top level debugging self.debugJobNames = ("CWLJob", "CWLWorkflow", "CWLScatter", "CWLGather", "ResolveIndirect") self.deadlockThrottler = LocalThrottle(self.config.deadlockWait) def run(self): """ This runs the leader process to issue and manage jobs. :raises: toil.leader.FailedJobsException if at the end of function their remain \ failed jobs :return: The return value of the root job's run function. :rtype: Any """ # Start the stats/logging aggregation thread self.statsAndLogging.start() if self.config.metrics: self.toilMetrics = ToilMetrics(provisioner=self.provisioner) try: # Start service manager thread self.serviceManager.start() try: # Create cluster scaling processes if not None if self.clusterScaler is not None: self.clusterScaler.start() try: # Run the main loop self.innerLoop() finally: if self.clusterScaler is not None: logger.debug('Waiting for workers to shutdown.') startTime = time.time() self.clusterScaler.shutdown() logger.debug('Worker shutdown complete in %s seconds.', time.time() - startTime) finally: # Ensure service manager thread is properly shutdown self.serviceManager.shutdown() finally: # Ensure the stats and logging thread is properly shutdown self.statsAndLogging.shutdown() if self.toilMetrics: self.toilMetrics.shutdown() # Filter the failed jobs self.toilState.totalFailedJobs = [j for j in self.toilState.totalFailedJobs if self.jobStore.exists(j.jobStoreID)] try: self.create_status_sentinel_file(self.toilState.totalFailedJobs) except IOError as e: logger.debug('Error from importFile with hardlink=True: {}'.format(e)) logger.info("Finished toil run %s" % ("successfully." if not self.toilState.totalFailedJobs \ else ("with %s failed jobs." % len(self.toilState.totalFailedJobs)))) if len(self.toilState.totalFailedJobs): logger.info("Failed jobs at end of the run: %s", ' '.join(str(job) for job in self.toilState.totalFailedJobs)) # Cleanup if len(self.toilState.totalFailedJobs) > 0: raise FailedJobsException(self.config.jobStore, self.toilState.totalFailedJobs, self.jobStore) return self.jobStore.getRootJobReturnValue() def create_status_sentinel_file(self, fail): """Create a file in the jobstore indicating failure or success.""" logName = 'failed.log' if fail else 'succeeded.log' localLog = os.path.join(os.getcwd(), logName) open(localLog, 'w').close() self.jobStore.importFile('file://' + localLog, logName, hardlink=True) if os.path.exists(localLog): # Bandaid for Jenkins tests failing stochastically and unexplainably. os.remove(localLog) def _handledFailedSuccessor(self, jobNode, jobGraph, successorJobStoreID): """Deal with the successor having failed. Return True if there are still active successors. Return False if all successors have failed and the job is queued to run to handle the failed successors.""" logger.debug("Successor job: %s of job: %s has failed """ "predecessors", jobNode, jobGraph) # Add the job to the set having failed successors self.toilState.hasFailedSuccessors.add(jobGraph.jobStoreID) # Reduce active successor count and remove the successor as an active successor of the job self.toilState.successorCounts[jobGraph.jobStoreID] -= 1 assert self.toilState.successorCounts[jobGraph.jobStoreID] >= 0 self.toilState.successorJobStoreIDToPredecessorJobs[successorJobStoreID].remove(jobGraph) if len(self.toilState.successorJobStoreIDToPredecessorJobs[successorJobStoreID]) == 0: self.toilState.successorJobStoreIDToPredecessorJobs.pop(successorJobStoreID) # If the job now has no active successors add to active jobs # so it can be processed as a job with failed successors if self.toilState.successorCounts[jobGraph.jobStoreID] == 0: logger.debug("Job: %s has no successors to run " "and some are failed, adding to list of jobs " "with failed successors", jobGraph) self.toilState.successorCounts.pop(jobGraph.jobStoreID) self.toilState.updatedJobs.add((jobGraph, 0)) return False def _checkSuccessorReadyToRunMultiplePredecessors(self, jobGraph, jobNode, successorJobStoreID): """Handle the special cases of checking if a successor job is ready to run when there are multiple predecessors""" # See implementation note at the top of this file for discussion of multiple predecessors logger.debug("Successor job: %s of job: %s has multiple " "predecessors", jobNode, jobGraph) # Get the successor job graph, which is caches if successorJobStoreID not in self.toilState.jobsToBeScheduledWithMultiplePredecessors: self.toilState.jobsToBeScheduledWithMultiplePredecessors[successorJobStoreID] = self.jobStore.load(successorJobStoreID) successorJobGraph = self.toilState.jobsToBeScheduledWithMultiplePredecessors[successorJobStoreID] # Add the jobGraph as a finished predecessor to the successor successorJobGraph.predecessorsFinished.add(jobGraph.jobStoreID) # If the successor is in the set of successors of failed jobs if successorJobStoreID in self.toilState.failedSuccessors: if not self._handledFailedSuccessor(jobNode, jobGraph, successorJobStoreID): return False # If the successor job's predecessors have all not all completed then # ignore the jobGraph as is not yet ready to run assert len(successorJobGraph.predecessorsFinished) <= successorJobGraph.predecessorNumber if len(successorJobGraph.predecessorsFinished) < successorJobGraph.predecessorNumber: return False else: # Remove the successor job from the cache self.toilState.jobsToBeScheduledWithMultiplePredecessors.pop(successorJobStoreID) return True def _makeJobSuccessorReadyToRun(self, jobGraph, jobNode): """make a successor job ready to run, returning False if they should not yet be run""" successorJobStoreID = jobNode.jobStoreID #Build map from successor to predecessors. if successorJobStoreID not in self.toilState.successorJobStoreIDToPredecessorJobs: self.toilState.successorJobStoreIDToPredecessorJobs[successorJobStoreID] = [] self.toilState.successorJobStoreIDToPredecessorJobs[successorJobStoreID].append(jobGraph) if jobNode.predecessorNumber > 1: return self._checkSuccessorReadyToRunMultiplePredecessors(jobGraph, jobNode, successorJobStoreID) else: return True def _runJobSuccessors(self, jobGraph): assert len(jobGraph.stack[-1]) > 0 logger.debug("Job: %s has %i successors to schedule", jobGraph.jobStoreID, len(jobGraph.stack[-1])) #Record the number of successors that must be completed before #the jobGraph can be considered again assert jobGraph.jobStoreID not in self.toilState.successorCounts self.toilState.successorCounts[jobGraph.jobStoreID] = len(jobGraph.stack[-1]) # For each successor schedule if all predecessors have been completed successors = [] for jobNode in jobGraph.stack[-1]: if self._makeJobSuccessorReadyToRun(jobGraph, jobNode): successors.append(jobNode) self.issueJobs(successors) def _processFailedSuccessors(self, jobGraph): """Some of the jobs successors failed then either fail the job or restart it if it has retries left and is a checkpoint job""" if jobGraph.jobStoreID in self.toilState.servicesIssued: # The job has services running, signal for them to be killed # once they are killed then the jobGraph will be re-added to # the updatedJobs set and then scheduled to be removed logger.debug("Telling job: %s to terminate its services due to successor failure", jobGraph.jobStoreID) self.serviceManager.killServices(self.toilState.servicesIssued[jobGraph.jobStoreID], error=True) elif jobGraph.jobStoreID in self.toilState.successorCounts: # The job has non-service jobs running wait for them to finish # the job will be re-added to the updated jobs when these jobs # are done logger.debug("Job %s with ID: %s with failed successors still has successor jobs running", jobGraph, jobGraph.jobStoreID) elif jobGraph.checkpoint is not None and jobGraph.remainingRetryCount > 1: # If the job is a checkpoint and has remaining retries then reissue it. # The logic behind using > 1 rather than > 0 here: Since this job has # been tried once (without decreasing its retry count as the job # itself was successful), and its subtree failed, it shouldn't be retried # unless it has more than 1 try. logger.warn('Job: %s is being restarted as a checkpoint after the total ' 'failure of jobs in its subtree.', jobGraph.jobStoreID) self.issueJob(JobNode.fromJobGraph(jobGraph)) else: # Mark it totally failed logger.debug("Job %s is being processed as completely failed", jobGraph.jobStoreID) self.processTotallyFailedJob(jobGraph) def _processReadyJob(self, jobGraph, resultStatus): logger.debug('Updating status of job %s with ID %s: with result status: %s', jobGraph, jobGraph.jobStoreID, resultStatus) if jobGraph in self.serviceManager.jobGraphsWithServicesBeingStarted: # This stops a job with services being issued by the serviceManager from # being considered further in this loop. This catch is necessary because # the job's service's can fail while being issued, causing the job to be # added to updated jobs. logger.debug("Got a job to update which is still owned by the service " "manager: %s", jobGraph.jobStoreID) elif jobGraph.jobStoreID in self.toilState.hasFailedSuccessors: self._processFailedSuccessors(jobGraph) elif jobGraph.command is not None or resultStatus != 0: # The jobGraph has a command it must be run before any successors. # Similarly, if the job previously failed we rerun it, even if it doesn't have a # command to run, to eliminate any parts of the stack now completed. isServiceJob = jobGraph.jobStoreID in self.toilState.serviceJobStoreIDToPredecessorJob # If the job has run out of retries or is a service job whose error flag has # been indicated, fail the job. if (jobGraph.remainingRetryCount == 0 or isServiceJob and not self.jobStore.fileExists(jobGraph.errorJobStoreID)): self.processTotallyFailedJob(jobGraph) logger.warn("Job %s with ID %s is completely failed", jobGraph, jobGraph.jobStoreID) else: # Otherwise try the job again self.issueJob(JobNode.fromJobGraph(jobGraph)) elif len(jobGraph.services) > 0: # the job has services to run, which have not been started, start them # Build a map from the service jobs to the job and a map # of the services created for the job assert jobGraph.jobStoreID not in self.toilState.servicesIssued self.toilState.servicesIssued[jobGraph.jobStoreID] = {} for serviceJobList in jobGraph.services: for serviceTuple in serviceJobList: serviceID = serviceTuple.jobStoreID assert serviceID not in self.toilState.serviceJobStoreIDToPredecessorJob self.toilState.serviceJobStoreIDToPredecessorJob[serviceID] = jobGraph self.toilState.servicesIssued[jobGraph.jobStoreID][serviceID] = serviceTuple # Use the service manager to start the services self.serviceManager.scheduleServices(jobGraph) logger.debug("Giving job: %s to service manager to schedule its jobs", jobGraph.jobStoreID) elif len(jobGraph.stack) > 0: # There are exist successors to run self._runJobSuccessors(jobGraph) elif jobGraph.jobStoreID in self.toilState.servicesIssued: logger.debug("Telling job: %s to terminate its services due to the " "successful completion of its successor jobs", jobGraph) self.serviceManager.killServices(self.toilState.servicesIssued[jobGraph.jobStoreID], error=False) else: #There are no remaining tasks to schedule within the jobGraph, but #we schedule it anyway to allow it to be deleted. Remove the job #TODO: An alternative would be simple delete it here and add it to the #list of jobs to process, or (better) to create an asynchronous #process that deletes jobs and then feeds them back into the set #of jobs to be processed if jobGraph.remainingRetryCount > 0: self.issueJob(JobNode.fromJobGraph(jobGraph)) logger.debug("Job: %s is empty, we are scheduling to clean it up", jobGraph.jobStoreID) else: self.processTotallyFailedJob(jobGraph) logger.warn("Job: %s is empty but completely failed - something is very wrong", jobGraph.jobStoreID) def _processReadyJobs(self): """Process jobs that are ready to be scheduled/have successors to schedule""" logger.debug('Built the jobs list, currently have %i jobs to update and %i jobs issued', len(self.toilState.updatedJobs), self.getNumberOfJobsIssued()) updatedJobs = self.toilState.updatedJobs # The updated jobs to consider below self.toilState.updatedJobs = set() # Resetting the list for the next set for jobGraph, resultStatus in updatedJobs: self._processReadyJob(jobGraph, resultStatus) def _startServiceJobs(self): """Start any service jobs available from the service manager""" self.issueQueingServiceJobs() while True: serviceJob = self.serviceManager.getServiceJobsToStart(0) # Stop trying to get jobs when function returns None if serviceJob is None: break logger.debug('Launching service job: %s', serviceJob) self.issueServiceJob(serviceJob) def _processJobsWithRunningServices(self): """Get jobs whose services have started""" while True: jobGraph = self.serviceManager.getJobGraphWhoseServicesAreRunning(0) if jobGraph is None: # Stop trying to get jobs when function returns None break logger.debug('Job: %s has established its services.', jobGraph.jobStoreID) jobGraph.services = [] self.toilState.updatedJobs.add((jobGraph, 0)) def _gatherUpdatedJobs(self, updatedJobTuple): """Gather any new, updated jobGraph from the batch system""" jobID, result, wallTime = updatedJobTuple # easy, track different state try: updatedJob = self.jobBatchSystemIDToIssuedJob[jobID] except KeyError: logger.warn("A result seems to already have been processed " "for job %s", jobID) else: if result == 0: cur_logger = (logger.debug if str(updatedJob.jobName).startswith(CWL_INTERNAL_JOBS) else logger.info) cur_logger('Job ended: %s', updatedJob) if self.toilMetrics: self.toilMetrics.logCompletedJob(updatedJob) else: logger.warn('Job failed with exit value %i: %s', result, updatedJob) self.processFinishedJob(jobID, result, wallTime=wallTime) def _processLostJobs(self): """Process jobs that have gone awry""" # In the case that there is nothing happening (no updated jobs to # gather for rescueJobsFrequency seconds) check if there are any jobs # that have run too long (see self.reissueOverLongJobs) or which have # gone missing from the batch system (see self.reissueMissingJobs) if ((time.time() - self.timeSinceJobsLastRescued) >= self.config.rescueJobsFrequency): # We only rescue jobs every N seconds, and when we have apparently # exhausted the current jobGraph supply self.reissueOverLongJobs() logger.info("Reissued any over long jobs") hasNoMissingJobs = self.reissueMissingJobs() if hasNoMissingJobs: self.timeSinceJobsLastRescued = time.time() else: # This means we'll try again in a minute, providing things are quiet self.timeSinceJobsLastRescued += 60 logger.debug("Rescued any (long) missing jobs") def innerLoop(self): """ The main loop for processing jobs by the leader. """ self.timeSinceJobsLastRescued = time.time() while self.toilState.updatedJobs or \ self.getNumberOfJobsIssued() or \ self.serviceManager.jobsIssuedToServiceManager: if self.toilState.updatedJobs: self._processReadyJobs() # deal with service-related jobs self._startServiceJobs() self._processJobsWithRunningServices() # check in with the batch system updatedJobTuple = self.batchSystem.getUpdatedBatchJob(maxWait=2) if updatedJobTuple is not None: self._gatherUpdatedJobs(updatedJobTuple) else: self._processLostJobs() # Check on the associated threads and exit if a failure is detected self.statsAndLogging.check() self.serviceManager.check() # the cluster scaler object will only be instantiated if autoscaling is enabled if self.clusterScaler is not None: self.clusterScaler.check() if len(self.toilState.updatedJobs) == 0 and self.deadlockThrottler.throttle(wait=False): # Nothing happened this round and it's been long # enough since we last checked. Check for deadlocks. self.checkForDeadlocks() logger.debug("Finished the main loop: no jobs left to run.") # Consistency check the toil state assert self.toilState.updatedJobs == set() assert self.toilState.successorCounts == {} assert self.toilState.successorJobStoreIDToPredecessorJobs == {} assert self.toilState.serviceJobStoreIDToPredecessorJob == {} assert self.toilState.servicesIssued == {} # assert self.toilState.jobsToBeScheduledWithMultiplePredecessors # These are not properly emptied yet # assert self.toilState.hasFailedSuccessors == set() # These are not properly emptied yet def checkForDeadlocks(self): """ Checks if the system is deadlocked running service jobs. """ totalRunningJobs = len(self.batchSystem.getRunningBatchJobIDs()) totalServicesIssued = self.serviceJobsIssued + self.preemptableServiceJobsIssued # If there are no updated jobs and at least some jobs running if totalServicesIssued >= totalRunningJobs and totalRunningJobs > 0: serviceJobs = [x for x in list(self.jobBatchSystemIDToIssuedJob.keys()) if isinstance(self.jobBatchSystemIDToIssuedJob[x], ServiceJobNode)] runningServiceJobs = set([x for x in serviceJobs if self.serviceManager.isRunning(self.jobBatchSystemIDToIssuedJob[x])]) assert len(runningServiceJobs) <= totalRunningJobs # If all the running jobs are active services then we have a potential deadlock if len(runningServiceJobs) == totalRunningJobs: # We wait self.config.deadlockWait seconds before declaring the system deadlocked if self.potentialDeadlockedJobs != runningServiceJobs: self.potentialDeadlockedJobs = runningServiceJobs self.potentialDeadlockTime = time.time() elif time.time() - self.potentialDeadlockTime >= self.config.deadlockWait: raise DeadlockException("The system is service deadlocked - all %d running jobs are active services" % totalRunningJobs) else: # We have observed non-service jobs running, so reset the potential deadlock self.potentialDeadlockedJobs = set() self.potentialDeadlockTime = 0 else: # We have observed non-service jobs running, so reset the potential deadlock self.potentialDeadlockedJobs = set() self.potentialDeadlockTime = 0 def issueJob(self, jobNode): """Add a job to the queue of jobs.""" jobNode.command = ' '.join((resolveEntryPoint('_toil_worker'), jobNode.jobName, self.jobStoreLocator, jobNode.jobStoreID)) # jobBatchSystemID is an int that is an incremented counter for each job jobBatchSystemID = self.batchSystem.issueBatchJob(jobNode) self.jobBatchSystemIDToIssuedJob[jobBatchSystemID] = jobNode if jobNode.preemptable: # len(jobBatchSystemIDToIssuedJob) should always be greater than or equal to preemptableJobsIssued, # so increment this value after the job is added to the issuedJob dict self.preemptableJobsIssued += 1 cur_logger = logger.debug if jobNode.jobName.startswith(CWL_INTERNAL_JOBS) else logger.info cur_logger("Issued job %s with job batch system ID: " "%s and cores: %s, disk: %s, and memory: %s", jobNode, str(jobBatchSystemID), int(jobNode.cores), bytes2human(jobNode.disk), bytes2human(jobNode.memory)) if self.toilMetrics: self.toilMetrics.logIssuedJob(jobNode) self.toilMetrics.logQueueSize(self.getNumberOfJobsIssued()) def issueJobs(self, jobs): """Add a list of jobs, each represented as a jobNode object.""" for job in jobs: self.issueJob(job) def issueServiceJob(self, jobNode): """ Issue a service job, putting it on a queue if the maximum number of service jobs to be scheduled has been reached. """ if jobNode.preemptable: self.preemptableServiceJobsToBeIssued.append(jobNode) else: self.serviceJobsToBeIssued.append(jobNode) self.issueQueingServiceJobs() def issueQueingServiceJobs(self): """Issues any queuing service jobs up to the limit of the maximum allowed.""" while len(self.serviceJobsToBeIssued) > 0 and self.serviceJobsIssued < self.config.maxServiceJobs: self.issueJob(self.serviceJobsToBeIssued.pop()) self.serviceJobsIssued += 1 while len(self.preemptableServiceJobsToBeIssued) > 0 and self.preemptableServiceJobsIssued < self.config.maxPreemptableServiceJobs: self.issueJob(self.preemptableServiceJobsToBeIssued.pop()) self.preemptableServiceJobsIssued += 1 def getNumberOfJobsIssued(self, preemptable=None): """ Gets number of jobs that have been added by issueJob(s) and not removed by removeJob :param None or boolean preemptable: If none, return all types of jobs. If true, return just the number of preemptable jobs. If false, return just the number of non-preemptable jobs. """ if preemptable is None: return len(self.jobBatchSystemIDToIssuedJob) elif preemptable: return self.preemptableJobsIssued else: assert len(self.jobBatchSystemIDToIssuedJob) >= self.preemptableJobsIssued return len(self.jobBatchSystemIDToIssuedJob) - self.preemptableJobsIssued def removeJob(self, jobBatchSystemID): """Removes a job from the system.""" assert jobBatchSystemID in self.jobBatchSystemIDToIssuedJob jobNode = self.jobBatchSystemIDToIssuedJob[jobBatchSystemID] if jobNode.preemptable: # len(jobBatchSystemIDToIssuedJob) should always be greater than or equal to preemptableJobsIssued, # so decrement this value before removing the job from the issuedJob map assert self.preemptableJobsIssued > 0 self.preemptableJobsIssued -= 1 del self.jobBatchSystemIDToIssuedJob[jobBatchSystemID] # If service job if jobNode.jobStoreID in self.toilState.serviceJobStoreIDToPredecessorJob: # Decrement the number of services if jobNode.preemptable: self.preemptableServiceJobsIssued -= 1 else: self.serviceJobsIssued -= 1 return jobNode def getJobs(self, preemptable=None): jobs = self.jobBatchSystemIDToIssuedJob.values() if preemptable is not None: jobs = [job for job in jobs if job.preemptable == preemptable] return jobs def killJobs(self, jobsToKill): """ Kills the given set of jobs and then sends them for processing """ if len(jobsToKill) > 0: self.batchSystem.killBatchJobs(jobsToKill) for jobBatchSystemID in jobsToKill: self.processFinishedJob(jobBatchSystemID, 1) #Following functions handle error cases for when jobs have gone awry with the batch system. def reissueOverLongJobs(self): """ Check each issued job - if it is running for longer than desirable issue a kill instruction. Wait for the job to die then we pass the job to processFinishedJob. """ maxJobDuration = self.config.maxJobDuration jobsToKill = [] if maxJobDuration < 10000000: # We won't bother doing anything if rescue time > 16 weeks. runningJobs = self.batchSystem.getRunningBatchJobIDs() for jobBatchSystemID in list(runningJobs.keys()): if runningJobs[jobBatchSystemID] > maxJobDuration: logger.warn("The job: %s has been running for: %s seconds, more than the " "max job duration: %s, we'll kill it", str(self.jobBatchSystemIDToIssuedJob[jobBatchSystemID].jobStoreID), str(runningJobs[jobBatchSystemID]), str(maxJobDuration)) jobsToKill.append(jobBatchSystemID) self.killJobs(jobsToKill) def reissueMissingJobs(self, killAfterNTimesMissing=3): """ Check all the current job ids are in the list of currently running batch system jobs. If a job is missing, we mark it as so, if it is missing for a number of runs of this function (say 10).. then we try deleting the job (though its probably lost), we wait then we pass the job to processFinishedJob. """ runningJobs = set(self.batchSystem.getIssuedBatchJobIDs()) jobBatchSystemIDsSet = set(list(self.jobBatchSystemIDToIssuedJob.keys())) #Clean up the reissueMissingJobs_missingHash hash, getting rid of jobs that have turned up missingJobIDsSet = set(list(self.reissueMissingJobs_missingHash.keys())) for jobBatchSystemID in missingJobIDsSet.difference(jobBatchSystemIDsSet): self.reissueMissingJobs_missingHash.pop(jobBatchSystemID) logger.warn("Batch system id: %s is no longer missing", str(jobBatchSystemID)) assert runningJobs.issubset(jobBatchSystemIDsSet) #Assert checks we have #no unexpected jobs running jobsToKill = [] for jobBatchSystemID in set(jobBatchSystemIDsSet.difference(runningJobs)): jobStoreID = self.jobBatchSystemIDToIssuedJob[jobBatchSystemID].jobStoreID if jobBatchSystemID in self.reissueMissingJobs_missingHash: self.reissueMissingJobs_missingHash[jobBatchSystemID] += 1 else: self.reissueMissingJobs_missingHash[jobBatchSystemID] = 1 timesMissing = self.reissueMissingJobs_missingHash[jobBatchSystemID] logger.warn("Job store ID %s with batch system id %s is missing for the %i time", jobStoreID, str(jobBatchSystemID), timesMissing) if self.toilMetrics: self.toilMetrics.logMissingJob() if timesMissing == killAfterNTimesMissing: self.reissueMissingJobs_missingHash.pop(jobBatchSystemID) jobsToKill.append(jobBatchSystemID) self.killJobs(jobsToKill) return len( self.reissueMissingJobs_missingHash ) == 0 #We use this to inform #if there are missing jobs def processRemovedJob(self, issuedJob, resultStatus): if resultStatus != 0: logger.warn("Despite the batch system claiming failure the " "job %s seems to have finished and been removed", issuedJob) self._updatePredecessorStatus(issuedJob.jobStoreID) def processFinishedJob(self, batchSystemID, resultStatus, wallTime=None): """ Function reads a processed jobGraph file and updates its state. """ jobNode = self.removeJob(batchSystemID) jobStoreID = jobNode.jobStoreID if wallTime is not None and self.clusterScaler is not None: self.clusterScaler.addCompletedJob(jobNode, wallTime) if self.jobStore.exists(jobStoreID): logger.debug("Job %s continues to exist (i.e. has more to do)", jobNode) try: jobGraph = self.jobStore.load(jobStoreID) except NoSuchJobException: # Avoid importing AWSJobStore as the corresponding extra might be missing if self.jobStore.__class__.__name__ == 'AWSJobStore': # We have a ghost job - the job has been deleted but a stale read from # SDB gave us a false positive when we checked for its existence. # Process the job from here as any other job removed from the job store. # This is a temporary work around until https://github.com/BD2KGenomics/toil/issues/1091 # is completed logger.warn('Got a stale read from SDB for job %s', jobNode) self.processRemovedJob(jobNode, resultStatus) return else: raise if jobGraph.logJobStoreFileID is not None: with jobGraph.getLogFileHandle(self.jobStore) as logFileStream: # more memory efficient than read().striplines() while leaving off the # trailing \n left when using readlines() # http://stackoverflow.com/a/15233739 StatsAndLogging.logWithFormatting(jobStoreID, logFileStream, method=logger.warn, message='The job seems to have left a log file, indicating failure: %s' % jobGraph) if self.config.writeLogs or self.config.writeLogsGzip: with jobGraph.getLogFileHandle(self.jobStore) as logFileStream: StatsAndLogging.writeLogFiles(jobGraph.chainedJobs, logFileStream, self.config, failed=True) if resultStatus != 0: # If the batch system returned a non-zero exit code then the worker # is assumed not to have captured the failure of the job, so we # reduce the retry count here. if jobGraph.logJobStoreFileID is None: logger.warn("No log file is present, despite job failing: %s", jobNode) # Look for any standard output/error files created by the batch system workflowDir = Toil.getWorkflowDir(self.config.workflowID, self.config.workDir) batchSystemFilePrefix = 'toil_job_{}_batch_'.format(batchSystemID) batchSystemFileGlob = os.path.join(workflowDir, batchSystemFilePrefix + '*.log') batchSystemFiles = glob.glob(batchSystemFileGlob) for batchSystemFile in batchSystemFiles: try: batchSystemFileStream = open(batchSystemFile, 'rb') except: logger.warn('The batch system left a file %s, but it could not be opened' % batchSystemFile) else: with batchSystemFileStream: if os.path.getsize(batchSystemFile) > 0: StatsAndLogging.logWithFormatting(jobStoreID, batchSystemFileStream, method=logger.warn, message='The batch system left a non-empty file %s:' % batchSystemFile) if self.config.writeLogs or self.config.writeLogsGzip: batchSystemFileRoot, _ = os.path.splitext(os.path.basename(batchSystemFile)) jobNames = jobGraph.chainedJobs if jobNames is None: # For jobs that fail this way, jobGraph.chainedJobs is not guaranteed to be set jobNames = [str(jobGraph)] jobNames = [jobName + '_' + batchSystemFileRoot for jobName in jobNames] batchSystemFileStream.seek(0) StatsAndLogging.writeLogFiles(jobNames, batchSystemFileStream, self.config, failed=True) else: logger.warn('The batch system left an empty file %s' % batchSystemFile) jobGraph.setupJobAfterFailure(self.config) self.jobStore.update(jobGraph) elif jobStoreID in self.toilState.hasFailedSuccessors: # If the job has completed okay, we can remove it from the list of jobs with failed successors self.toilState.hasFailedSuccessors.remove(jobStoreID) self.toilState.updatedJobs.add((jobGraph, resultStatus)) #Now we know the #jobGraph is done we can add it to the list of updated jobGraph files logger.debug("Added job: %s to active jobs", jobGraph) else: #The jobGraph is done self.processRemovedJob(jobNode, resultStatus) @staticmethod def getSuccessors(jobGraph, alreadySeenSuccessors, jobStore): """ Gets successors of the given job by walking the job graph recursively. Any successor in alreadySeenSuccessors is ignored and not traversed. Returns the set of found successors. This set is added to alreadySeenSuccessors. """ successors = set() def successorRecursion(jobGraph): # For lists of successors for successorList in jobGraph.stack: # For each successor in list of successors for successorJobNode in successorList: # If successor not already visited if successorJobNode.jobStoreID not in alreadySeenSuccessors: # Add to set of successors successors.add(successorJobNode.jobStoreID) alreadySeenSuccessors.add(successorJobNode.jobStoreID) # Recurse if job exists # (job may not exist if already completed) if jobStore.exists(successorJobNode.jobStoreID): successorRecursion(jobStore.load(successorJobNode.jobStoreID)) successorRecursion(jobGraph) # Recurse from jobGraph return successors def processTotallyFailedJob(self, jobGraph): """ Processes a totally failed job. """ # Mark job as a totally failed job self.toilState.totalFailedJobs.add(JobNode.fromJobGraph(jobGraph)) if self.toilMetrics: self.toilMetrics.logFailedJob(jobGraph) if jobGraph.jobStoreID in self.toilState.serviceJobStoreIDToPredecessorJob: # Is # a service job logger.debug("Service job is being processed as a totally failed job: %s", jobGraph) predecesssorJobGraph = self.toilState.serviceJobStoreIDToPredecessorJob[jobGraph.jobStoreID] # This removes the service job as a service of the predecessor # and potentially makes the predecessor active self._updatePredecessorStatus(jobGraph.jobStoreID) # Remove the start flag, if it still exists. This indicates # to the service manager that the job has "started", this prevents # the service manager from deadlocking while waiting self.jobStore.deleteFile(jobGraph.startJobStoreID) # Signal to any other services in the group that they should # terminate. We do this to prevent other services in the set # of services from deadlocking waiting for this service to start properly if predecesssorJobGraph.jobStoreID in self.toilState.servicesIssued: self.serviceManager.killServices(self.toilState.servicesIssued[predecesssorJobGraph.jobStoreID], error=True) logger.debug("Job: %s is instructing all the services of its parent job to quit", jobGraph) self.toilState.hasFailedSuccessors.add(predecesssorJobGraph.jobStoreID) # This ensures that the # job will not attempt to run any of it's successors on the stack else: # Is a non-service job assert jobGraph.jobStoreID not in self.toilState.servicesIssued # Traverse failed job's successor graph and get the jobStoreID of new successors. # Any successor already in toilState.failedSuccessors will not be traversed # All successors traversed will be added to toilState.failedSuccessors and returned # as a set (unseenSuccessors). unseenSuccessors = self.getSuccessors(jobGraph, self.toilState.failedSuccessors, self.jobStore) logger.debug("Found new failed successors: %s of job: %s", " ".join( unseenSuccessors), jobGraph) # For each newly found successor for successorJobStoreID in unseenSuccessors: # If the successor is a successor of other jobs that have already tried to schedule it if successorJobStoreID in self.toilState.successorJobStoreIDToPredecessorJobs: # For each such predecessor job # (we remove the successor from toilState.successorJobStoreIDToPredecessorJobs to avoid doing # this multiple times for each failed predecessor) for predecessorJob in self.toilState.successorJobStoreIDToPredecessorJobs.pop(successorJobStoreID): # Reduce the predecessor job's successor count. self.toilState.successorCounts[predecessorJob.jobStoreID] -= 1 # Indicate that it has failed jobs. self.toilState.hasFailedSuccessors.add(predecessorJob.jobStoreID) logger.debug("Marking job: %s as having failed successors (found by " "reading successors failed job)", predecessorJob) # If the predecessor has no remaining successors, add to list of active jobs assert self.toilState.successorCounts[predecessorJob.jobStoreID] >= 0 if self.toilState.successorCounts[predecessorJob.jobStoreID] == 0: self.toilState.updatedJobs.add((predecessorJob, 0)) # Remove the predecessor job from the set of jobs with successors. self.toilState.successorCounts.pop(predecessorJob.jobStoreID) # If the job has predecessor(s) if jobGraph.jobStoreID in self.toilState.successorJobStoreIDToPredecessorJobs: # For each predecessor of the job for predecessorJobGraph in self.toilState.successorJobStoreIDToPredecessorJobs[jobGraph.jobStoreID]: # Mark the predecessor as failed self.toilState.hasFailedSuccessors.add(predecessorJobGraph.jobStoreID) logger.debug("Totally failed job: %s is marking direct predecessor: %s " "as having failed jobs", jobGraph, predecessorJobGraph) self._updatePredecessorStatus(jobGraph.jobStoreID) def _updatePredecessorStatus(self, jobStoreID): """ Update status of predecessors for finished successor job. """ if jobStoreID in self.toilState.serviceJobStoreIDToPredecessorJob: # Is a service job predecessorJob = self.toilState.serviceJobStoreIDToPredecessorJob.pop(jobStoreID) self.toilState.servicesIssued[predecessorJob.jobStoreID].pop(jobStoreID) if len(self.toilState.servicesIssued[predecessorJob.jobStoreID]) == 0: # Predecessor job has # all its services terminated self.toilState.servicesIssued.pop(predecessorJob.jobStoreID) # The job has no running services self.toilState.updatedJobs.add((predecessorJob, 0)) # Now we know # the job is done we can add it to the list of updated job files elif jobStoreID not in self.toilState.successorJobStoreIDToPredecessorJobs: #We have reach the root job assert len(self.toilState.updatedJobs) == 0 assert len(self.toilState.successorJobStoreIDToPredecessorJobs) == 0 assert len(self.toilState.successorCounts) == 0 logger.debug("Reached root job %s so no predecessors to clean up" % jobStoreID) else: # Is a non-root, non-service job logger.debug("Cleaning the predecessors of %s" % jobStoreID) # For each predecessor for predecessorJob in self.toilState.successorJobStoreIDToPredecessorJobs.pop(jobStoreID): # Reduce the predecessor's number of successors by one to indicate the # completion of the jobStoreID job self.toilState.successorCounts[predecessorJob.jobStoreID] -= 1 # If the predecessor job is done and all the successors are complete if self.toilState.successorCounts[predecessorJob.jobStoreID] == 0: # Remove it from the set of jobs with active successors self.toilState.successorCounts.pop(predecessorJob.jobStoreID) if predecessorJob.jobStoreID not in self.toilState.hasFailedSuccessors: # Pop stack at this point, as we can get rid of its successors predecessorJob.stack.pop() # Now we know the job is done we can add it to the list of updated job files assert predecessorJob not in self.toilState.updatedJobs self.toilState.updatedJobs.add((predecessorJob, 0)) toil-releases-3.24.0/src/toil/lib/000077500000000000000000000000001362134276200166625ustar00rootroot00000000000000toil-releases-3.24.0/src/toil/lib/__init__.py000066400000000000000000000012131362134276200207700ustar00rootroot00000000000000# Copyright (C) 2015-2016 Regents of the University of California # # 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. from __future__ import absolute_import toil-releases-3.24.0/src/toil/lib/bioio.py000066400000000000000000000300131362134276200203320ustar00rootroot00000000000000# Copyright (C) 2015-2016 Regents of the University of California # # 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. from __future__ import absolute_import from builtins import range from builtins import object import socket import sys import os import logging import resource import logging.handlers import tempfile import random import math import shutil from argparse import ArgumentParser from optparse import OptionContainer, OptionGroup from toil import subprocess # Python 3 compatibility imports from six.moves import xrange from six import string_types import xml.etree.cElementTree as ET from xml.dom import minidom # For making stuff pretty defaultLogLevel = logging.INFO logger = logging.getLogger(__name__) rootLogger = logging.getLogger() toilLogger = logging.getLogger('toil') def getLogLevelString(logger=None): if logger is None: logger = rootLogger return logging.getLevelName(logger.getEffectiveLevel()) __loggingFiles = [] def addLoggingFileHandler(fileName, rotatingLogging=False): if fileName in __loggingFiles: return __loggingFiles.append(fileName) if rotatingLogging: handler = logging.handlers.RotatingFileHandler(fileName, maxBytes=1000000, backupCount=1) else: handler = logging.FileHandler(fileName) rootLogger.addHandler(handler) return handler def setLogLevel(level, logger=None): """ Sets the log level to a given string level (like "INFO"). Operates on the root logger by default, but another logger can be specified instead. """ if logger is None: logger = rootLogger level = level.upper() if level == "OFF": level = "CRITICAL" # Note that getLevelName works in both directions, numeric to textual and textual to numeric numericLevel = logging.getLevelName(level) assert logging.getLevelName(numericLevel) == level logger.setLevel(numericLevel) # There are quite a few cases where we expect AWS requests to fail, but it seems # that boto handles these by logging the error *and* raising an exception. We # don't want to confuse the user with those error messages. logging.getLogger( 'boto' ).setLevel( logging.CRITICAL ) def logFile(fileName, printFunction=logger.info): """Writes out a formatted version of the given log file """ printFunction("Reporting file: %s" % fileName) shortName = fileName.split("/")[-1] fileHandle = open(fileName, 'r') line = fileHandle.readline() while line != '': if line[-1] == '\n': line = line[:-1] printFunction("%s:\t%s" % (shortName, line)) line = fileHandle.readline() fileHandle.close() def logStream(fileHandle, shortName, printFunction=logger.info): """Writes out a formatted version of the given log stream. """ printFunction("Reporting file: %s" % shortName) line = fileHandle.readline() while line != '': if line[-1] == '\n': line = line[:-1] printFunction("%s:\t%s" % (shortName, line)) line = fileHandle.readline() fileHandle.close() def addLoggingOptions(parser): # Wrapper function that allows toil to be used with both the optparse and # argparse option parsing modules if isinstance(parser, ArgumentParser): group = parser.add_argument_group("Logging Options", "Options that control logging") _addLoggingOptions(group.add_argument) else: raise RuntimeError("Unanticipated class passed to " "addLoggingOptions(), %s. Expecting " "argparse.ArgumentParser" % parser.__class__) supportedLogLevels = (logging.CRITICAL, logging.ERROR, logging.WARNING, logging.INFO, logging.DEBUG) def _addLoggingOptions(addOptionFn): """ Adds logging options """ # BEFORE YOU ADD OR REMOVE OPTIONS TO THIS FUNCTION, KNOW THAT YOU MAY ONLY USE VARIABLES ACCEPTED BY BOTH # optparse AND argparse FOR EXAMPLE, YOU MAY NOT USE default=%default OR default=%(default)s defaultLogLevelName = logging.getLevelName( defaultLogLevel ) addOptionFn("--logOff", dest="logLevel", default=defaultLogLevelName, action="store_const", const="CRITICAL", help="Same as --logCritical") for level in supportedLogLevels: levelName = logging.getLevelName(level) levelNameCapitalized = levelName.capitalize() addOptionFn("--log" + levelNameCapitalized, dest="logLevel", default=defaultLogLevelName, action="store_const", const=levelName, help="Turn on logging at level %s and above. (default is %s)" % (levelName, defaultLogLevelName)) addOptionFn("--logLevel", dest="logLevel", default=defaultLogLevelName, help=("Log at given level (may be either OFF (or CRITICAL), ERROR, WARN (or WARNING), INFO or DEBUG). " "(default is %s)" % defaultLogLevelName)) addOptionFn("--logFile", dest="logFile", help="File to log in") addOptionFn("--rotatingLogging", dest="logRotating", action="store_true", default=False, help="Turn on rotating logging, which prevents log files getting too big.") def setLoggingFromOptions(options): """ Sets the logging from a dictionary of name/value options. """ formatStr = ' '.join([socket.gethostname(), '%(asctime)s', '%(threadName)s', '%(levelname)s', '%(name)s:', '%(message)s']) logging.basicConfig(format=formatStr) rootLogger.setLevel(defaultLogLevel) if options.logLevel is not None: setLogLevel(options.logLevel) else: # Ensure that any other log level overrides are in effect even if no log level is explicitly set setLogLevel(getLogLevelString()) logger.debug("Root logger is at level '%s', 'toil' logger at level '%s'.", getLogLevelString(logger=rootLogger), getLogLevelString(logger=toilLogger)) if options.logFile is not None: addLoggingFileHandler(options.logFile, rotatingLogging=options.logRotating) logger.debug("Logging to file '%s'." % options.logFile) def system(command): """ A convenience wrapper around subprocess.check_call that logs the command before passing it on. The command can be either a string or a sequence of strings. If it is a string shell=True will be passed to subprocess.check_call. :type command: str | sequence[string] """ logger.debug('Running: %r', command) subprocess.check_call(command, shell=isinstance(command, string_types), bufsize=-1) def getTotalCpuTimeAndMemoryUsage(): """ Gives the total cpu time of itself and all its children, and the maximum RSS memory usage of itself and its single largest child. """ me = resource.getrusage(resource.RUSAGE_SELF) childs = resource.getrusage(resource.RUSAGE_CHILDREN) totalCPUTime = me.ru_utime + me.ru_stime + childs.ru_utime + childs.ru_stime totalMemoryUsage = me.ru_maxrss + childs.ru_maxrss return totalCPUTime, totalMemoryUsage def getTotalCpuTime(): """Gives the total cpu time, including the children. """ return getTotalCpuTimeAndMemoryUsage()[0] def getTotalMemoryUsage(): """Gets the amount of memory used by the process and its largest child. """ return getTotalCpuTimeAndMemoryUsage()[1] def absSymPath(path): """like os.path.abspath except it doesn't dereference symlinks """ curr_path = os.getcwd() return os.path.normpath(os.path.join(curr_path, path)) ######################################################### ######################################################### ######################################################### #testing settings ######################################################### ######################################################### ######################################################### class TestStatus(object): ###Global variables used by testing framework to run tests. TEST_SHORT = 0 TEST_MEDIUM = 1 TEST_LONG = 2 TEST_VERY_LONG = 3 TEST_STATUS = TEST_SHORT SAVE_ERROR_LOCATION = None def getTestStatus(): return TestStatus.TEST_STATUS getTestStatus = staticmethod(getTestStatus) def setTestStatus(status): assert status in (TestStatus.TEST_SHORT, TestStatus.TEST_MEDIUM, TestStatus.TEST_LONG, TestStatus.TEST_VERY_LONG) TestStatus.TEST_STATUS = status setTestStatus = staticmethod(setTestStatus) def getSaveErrorLocation(): """Location to in which to write inputs which created test error. """ return TestStatus.SAVE_ERROR_LOCATION getSaveErrorLocation = staticmethod(getSaveErrorLocation) def setSaveErrorLocation(dir): """Set location in which to write inputs which created test error. """ logger.debug("Location to save error files in: %s" % dir) assert os.path.isdir(dir) TestStatus.SAVE_ERROR_LOCATION = dir setSaveErrorLocation = staticmethod(setSaveErrorLocation) def getTestSetup(shortTestNo=1, mediumTestNo=5, longTestNo=100, veryLongTestNo=0): if TestStatus.TEST_STATUS == TestStatus.TEST_SHORT: return shortTestNo elif TestStatus.TEST_STATUS == TestStatus.TEST_MEDIUM: return mediumTestNo elif TestStatus.TEST_STATUS == TestStatus.TEST_LONG: return longTestNo else: #Used for long example tests return veryLongTestNo getTestSetup = staticmethod(getTestSetup) def getPathToDataSets(): """This method is used to store the location of the path where all the data sets used by tests for analysis are kept. These are not kept in the distrbution itself for reasons of size. """ assert "SON_TRACE_DATASETS" in os.environ return os.environ["SON_TRACE_DATASETS"] getPathToDataSets = staticmethod(getPathToDataSets) def getBasicOptionParser( parser=None): if parser is None: parser = ArgumentParser() addLoggingOptions(parser) parser.add_argument("--tempDirRoot", dest="tempDirRoot", type=str, help="Path to where temporary directory containing all temp files are created, by default uses the current working directory as the base.", default=tempfile.gettempdir()) return parser def parseBasicOptions(parser): """Setups the standard things from things added by getBasicOptionParser. """ options = parser.parse_args() setLoggingFromOptions(options) #Set up the temp dir root if options.tempDirRoot == "None": # FIXME: Really, a string containing the word None? options.tempDirRoot = tempfile.gettempdir() return options def getRandomAlphaNumericString(length=10): """Returns a random alpha numeric string of the given length. """ return "".join([ random.choice('0123456789ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz') for i in range(0, length) ]) def makePublicDir(dirName): """Makes a given subdirectory if it doesn't already exist, making sure it is public. """ if not os.path.exists(dirName): os.mkdir(dirName) os.chmod(dirName, 0o777) return dirName def getTempFile(suffix="", rootDir=None): """Returns a string representing a temporary file, that must be manually deleted """ if rootDir is None: handle, tmpFile = tempfile.mkstemp(suffix) os.close(handle) return tmpFile else: tmpFile = os.path.join(rootDir, "tmp_" + getRandomAlphaNumericString() + suffix) open(tmpFile, 'w').close() os.chmod(tmpFile, 0o777) #Ensure everyone has access to the file. return tmpFile toil-releases-3.24.0/src/toil/lib/compatibility.py000066400000000000000000000011551362134276200221070ustar00rootroot00000000000000from __future__ import absolute_import, division, print_function, unicode_literals from past.builtins import str as oldstr import sys USING_PYTHON2 = True if sys.version_info < (3, 0) else False def compat_oldstr(s): if USING_PYTHON2: return oldstr(s) else: return s.decode('utf-8') if isinstance(s, bytes) else s def compat_bytes(s): if USING_PYTHON2: return bytes(s) else: return s.decode('utf-8') if isinstance(s, bytes) else s def compat_plain(s): if USING_PYTHON2: return s else: return s.decode('utf-8') if isinstance(s, bytes) else s toil-releases-3.24.0/src/toil/lib/context.py000066400000000000000000000470251362134276200207300ustar00rootroot00000000000000# coding=utf-8 from six import iteritems import json import os import urllib import re import logging import inspect try: from urllib.parse import unquote except ImportError: from urllib import unquote from boto import iam, sns, sqs, vpc from boto.exception import BotoServerError from boto.s3.connection import S3Connection from boto.sqs.connection import SQSConnection from boto.sns.connection import SNSConnection from boto.vpc import VPCConnection from boto.iam.connection import IAMConnection from boto.utils import get_instance_metadata from toil.lib.memoize import memoize from toil.lib.ec2 import UserError log = logging.getLogger(__name__) class Context(object): """ Encapsulates all EC2-specific settings used by components in this project """ availability_zone_re = re.compile(r'^([a-z]{2}-[a-z]+-[1-9][0-9]*)([a-z])$') name_prefix_re = re.compile(r'^(/([0-9a-zA-Z.-][_0-9a-zA-Z.-]*))*') name_re = re.compile(name_prefix_re.pattern + '/?$') namespace_re = re.compile(name_prefix_re.pattern + '/$') def __init__(self, availability_zone, namespace): """ Create an Context object. :param availability_zone: The availability zone to place EC2 resources like volumes and instances into. The AWS region to operate in is implied by this parameter since the region is a prefix of the availability zone string :param namespace: The prefix for names of EC2 resources. The namespace is string starting in '/' followed by zero or more components, separated by '/'. Components are non-empty strings consisting only of alphanumeric characters, '.', '-' or '_' and that don't start with '_'. The namespace argument is restricted to ASCII and will be converted to a non-unicode string if available. Unicode strings that can't be encoded as ASCII will be rejected. A note about our namespaces vs IAM's resource paths. IAM paths don't provide namespace isolation. In other words, it is not possible to have two users of the same name in two different paths. The by itself name has to be unique. For that reason, IAM resource paths are pretty much useless. >>> ctx = Context( 'us-west-1b', None ) Traceback (most recent call last): .... ValueError: Need namespace >>> Context('us-west-1b', namespace='/').namespace '/' >>> Context('us-west-1b', namespace='/foo/').namespace '/foo/' >>> Context('us-west-1b', namespace='/foo/bar/').namespace '/foo/bar/' >>> Context('us-west-1b', namespace='') Traceback (most recent call last): .... ValueError: Invalid namespace '' >>> Context('us-west-1b', namespace='foo') Traceback (most recent call last): .... ValueError: Invalid namespace 'foo' >>> Context('us-west-1b', namespace='/foo') Traceback (most recent call last): .... ValueError: Invalid namespace '/foo' >>> Context('us-west-1b', namespace='//foo/') Traceback (most recent call last): .... ValueError: Invalid namespace '//foo/' >>> Context('us-west-1b', namespace='/foo//') Traceback (most recent call last): .... ValueError: Invalid namespace '/foo//' >>> Context('us-west-1b', namespace='han//nes') Traceback (most recent call last): .... ValueError: Invalid namespace 'han//nes' >>> Context('us-west-1b', namespace='/_foo/') Traceback (most recent call last): .... ValueError: Invalid namespace '/_foo/' >>> Context('us-west-1b', namespace=u'/foo/').namespace # doctest: +ALLOW_UNICODE '/foo/' >>> Context('us-west-1b', namespace=u'/föo/').namespace # doctest: +ELLIPSIS Traceback (most recent call last): .... ValueError: 'ascii' codec can't encode ...: ordinal not in range(128) >>> import string >>> component = string.ascii_letters + string.digits + '-_.' >>> namespace = '/' + component + '/' >>> Context('us-west-1b', namespace=namespace).namespace == namespace True """ super(Context, self).__init__() self.__iam = None self.__vpc = None self.__s3 = None self.__sns = None self.__sqs = None self.availability_zone = availability_zone m = self.availability_zone_re.match(availability_zone) if not m: raise ValueError("Can't extract region from availability zone '%s'" % availability_zone) self.region = m.group(1) if namespace is None: raise ValueError('Need namespace') try: # Encode the namespace as ASCII, so we know it is representable in ASCII. # But keep using it as text. namespace.encode('ascii') except UnicodeEncodeError as e: raise ValueError(e) namespace = self.resolve_me(str(namespace)) if not re.match(self.namespace_re, namespace): raise ValueError("Invalid namespace '%s'" % namespace) self.namespace = namespace @property def iam(self): """ :rtype: IAMConnection """ if self.__iam is None: self.__iam = self.__aws_connect(iam, 'universal') return self.__iam # VPCConnection extends EC2Connection so we can use one instance of the former for both @property def vpc(self): """ :rtype: VPCConnection """ if self.__vpc is None: self.__vpc = self.__aws_connect(vpc) return self.__vpc # ec2 = vpc works, too, but confuses the type hinter in PyCharm @property def ec2(self): """ :rtype: VPCConnection """ return self.vpc @property def s3(self): """ :rtype: S3Connection """ if self.__s3 is None: # We let S3 route buckets to regions for us. If we connected to a specific region, # bucket lookups (HEAD request against bucket URL) would fail with 301 status but # without a Location header. self.__s3 = S3Connection() return self.__s3 @property def sns(self): """ :rtype: SNSConnection """ if self.__sns is None: self.__sns = self.__aws_connect(sns) return self.__sns @property def sqs(self): """ :rtype: SQSConnection """ if self.__sqs is None: self.__sqs = self.__aws_connect(sqs) return self.__sqs def __aws_connect(self, aws_module, region=None, **kwargs): if region is None: region = self.region conn = aws_module.connect_to_region(region, **kwargs) if conn is None: raise RuntimeError("%s couldn't connect to region %s" % ( aws_module.__name__, region)) return conn def __enter__(self): return self def __exit__(self, exc_type, exc_val, exc_tb): self.close() def close(self): if self.__vpc is not None: self.__vpc.close() if self.__s3 is not None: self.__s3.close() if self.__iam is not None: self.__iam.close() if self.__sns is not None: self.__sns.close() if self.__sqs is not None: self.__sqs.close() @staticmethod def is_absolute_name(name): """ Returns True if the given name starts with a namespace. """ return name[0:1] == '/' class InvalidPathError(ValueError): def __init__(self, invalid_path): super(Context.InvalidPathError, self).__init__("Invalid path '%s'" % invalid_path) def absolute_name(self, name): """ Returns the absolute form of the specified resource name. If the specified name is already absolute, that name will be returned unchanged, otherwise the given name will be prefixed with the namespace this object was configured with. Relative names starting with underscores are disallowed. >>> ctx = Context( 'us-west-1b', namespace='/' ) >>> ctx.absolute_name('bar') '/bar' >>> ctx.absolute_name('/bar') '/bar' >>> ctx.absolute_name('') '/' >>> ctx.absolute_name('/') '/' >>> ctx.absolute_name('_bar') # doctest: +IGNORE_EXCEPTION_DETAIL Traceback (most recent call last): ... InvalidPathError: Invalid path '/_bar' >>> ctx.absolute_name('/_bar') # doctest: +IGNORE_EXCEPTION_DETAIL Traceback (most recent call last): ... InvalidPathError: Invalid path '/_bar' >>> ctx = Context( 'us-west-1b', namespace='/foo/' ) >>> ctx.absolute_name('bar') '/foo/bar' >>> ctx.absolute_name('bar/') '/foo/bar/' >>> ctx.absolute_name('bar1/bar2') '/foo/bar1/bar2' >>> ctx.absolute_name('/bar') '/bar' >>> ctx.absolute_name('') '/foo/' >>> ctx.absolute_name('/') '/' >>> ctx.absolute_name('_bar') # doctest: +IGNORE_EXCEPTION_DETAIL Traceback (most recent call last): ... InvalidPathError: Invalid path '/foo/_bar' >>> ctx.absolute_name('/_bar') # doctest: +IGNORE_EXCEPTION_DETAIL Traceback (most recent call last): ... InvalidPathError: Invalid path '/_bar' """ if self.is_absolute_name(name): result = name else: result = self.namespace + name if not self.name_re.match(result): raise self.InvalidPathError(result) return result def to_aws_name(self, name): """ Returns a transliteration of the name that safe to use for resource names on AWS. If the given name is relative, it converted to its absolute form before the transliteration. The transliteration uses two consequitive '_' to encode a single '_' and a single '_' to separate the name components. AWS-safe names are by definition absolute such that the leading separator can be removed. This leads to fairly readable AWS-safe names, especially for names in the root namespace, where the transliteration is the identity function if the input does not contain any '_'. This scheme only works if name components don't start with '_'. Without that condition, '/_' would become '___' the inverse of which is '_/'. >>> ctx = Context( 'us-west-1b', namespace='/' ) >>> ctx.to_aws_name( 'foo' ) 'foo' >>> ctx.from_aws_name( 'foo' ) 'foo' Illegal paths that would introduce ambiguity need to raise an exception >>> ctx.to_aws_name('/_') # doctest: +IGNORE_EXCEPTION_DETAIL Traceback (most recent call last): ... InvalidPathError: Invalid path '/_' >>> ctx.to_aws_name('/_/') # doctest: +IGNORE_EXCEPTION_DETAIL Traceback (most recent call last): ... InvalidPathError: Invalid path '/_/' >>> ctx.from_aws_name('___') # doctest: +IGNORE_EXCEPTION_DETAIL Traceback (most recent call last): ... InvalidPathError: Invalid path '/_/' >>> ctx.to_aws_name( 'foo_bar') 'foo__bar' >>> ctx.from_aws_name( 'foo__bar') 'foo_bar' >>> ctx.to_aws_name( '/sub_ns/foo_bar') 'sub__ns_foo__bar' >>> ctx.to_aws_name( 'sub_ns/foo_bar') 'sub__ns_foo__bar' >>> ctx.from_aws_name( 'sub__ns_foo__bar' ) 'sub_ns/foo_bar' >>> ctx.to_aws_name( 'g_/' ) 'g___' >>> ctx.from_aws_name( 'g___' ) 'g_/' >>> ctx = Context( 'us-west-1b', namespace='/this_ns/' ) >>> ctx.to_aws_name( 'foo' ) 'this__ns_foo' >>> ctx.from_aws_name( 'this__ns_foo' ) 'foo' >>> ctx.to_aws_name( 'foo_bar') 'this__ns_foo__bar' >>> ctx.from_aws_name( 'this__ns_foo__bar') 'foo_bar' >>> ctx.to_aws_name( '/other_ns/foo_bar' ) 'other__ns_foo__bar' >>> ctx.from_aws_name( 'other__ns_foo__bar' ) '/other_ns/foo_bar' >>> ctx.to_aws_name( 'other_ns/foo_bar' ) 'this__ns_other__ns_foo__bar' >>> ctx.from_aws_name( 'this__ns_other__ns_foo__bar' ) 'other_ns/foo_bar' >>> ctx.to_aws_name( '/this_ns/foo_bar' ) 'this__ns_foo__bar' >>> ctx.from_aws_name( 'this__ns_foo__bar' ) 'foo_bar' """ name = self.absolute_name(name) assert name.startswith('/') return name[1:].replace('_', '__').replace('/', '_') def from_aws_name(self, name): """ The inverse of to_aws_name(), except that the namespace is stripped from the input if it is relative to this context's name space. >>> zone = 'us-west-1b' >>> Context( zone, namespace='/foo/' ).from_aws_name('bar__x') '/bar_x' >>> Context( zone, namespace='/foo_x/' ).from_aws_name('foo__x_bar') 'bar' >>> Context( zone, namespace='/' ).from_aws_name('foo__x_bar__x') 'foo_x/bar_x' >>> Context( zone, namespace='/bla/' ).from_aws_name('foo__x_bar__x') '/foo_x/bar_x' """ name = '_'.join(s.replace('_', '/') for s in name.split('__')) name = '/' + name if not self.name_re.match(name): raise self.InvalidPathError(name) if name.startswith(self.namespace): name = name[len(self.namespace):] return name def base_name(self, name): """ Return the last component of a name, absolute or relative. >>> ctx = Context( 'us-west-1b', namespace='/foo/bar/') >>> ctx.base_name('') '' >>> ctx.base_name('/') '' >>> ctx.base_name('/a') 'a' >>> ctx.base_name('/a/') '' >>> ctx.base_name('/a/b') 'b' >>> ctx.base_name('/a/b/') '' """ return name.split('/')[-1] def contains_name(self, name): return not self.is_absolute_name(name) or name.startswith(self.namespace) def contains_aws_name(self, aws_name): """ >>> def c(n): return Context( 'us-west-1b', namespace=n) >>> c('/foo/' ).contains_aws_name('bar_x') False >>> c('/foo/' ).contains_aws_name('foo_x') True >>> c('/foo/' ).contains_aws_name('foo_bar_x') True >>> c('/foo/' ).contains_aws_name('bar_foo_x') False >>> c('/' ).contains_aws_name('bar_x') True >>> c('/' ).contains_aws_name('foo_x') True >>> c('/' ).contains_aws_name('foo_bar_x') True >>> c('/' ).contains_aws_name('bar_foo_x') True """ return self.contains_name(self.from_aws_name(aws_name)) def try_contains_aws_name(self, aws_name): try: return self.contains_aws_name(aws_name) except self.InvalidPathError: return False @property @memoize def account(self): try: arn = self.iam.get_user().arn except BaseException: # Agent boxes run with IAM role credentials instead of user credentials. arn = get_instance_metadata()['iam']['info']['InstanceProfileArn'] _, partition, service, region, account, resource = arn.split(':', 6) return account ssh_pubkey_s3_key_prefix = 'ssh_pubkey:' @property @memoize def iam_user_name(self): try: return self.iam.get_user().user_name except BaseException: log.warning("IAMConnection.get_user() failed.", exc_info=True) return None current_user_placeholder = '__me__' @staticmethod def drop_hostname(email): """ >>> Context.drop_hostname("foo") 'foo' >>> Context.drop_hostname("foo@bar.com") 'foo' >>> Context.drop_hostname("") '' >>> Context.drop_hostname("@") '' """ try: n = email.index("@") except ValueError: return email else: return email[0:n] def resolve_me(self, s, drop_hostname=True): placeholder = self.current_user_placeholder if placeholder in s: try: me = os.environ['CGCLOUD_ME'] except KeyError: me = self.iam_user_name if not me: raise UserError( "Can't determine current IAM user name. Be sure to put valid AWS credentials " "in ~/.boto or ~/.aws/credentials. For details, refer to %s. On an EC2 " "instance that is authorized via IAM roles, you can set the CGCLOUD_ME " "environment variable (uncommon)." % 'http://boto.readthedocs.org/en/latest/boto_config_tut.html') if drop_hostname: me = self.drop_hostname(me) return s.replace(placeholder, me) else: return s def setup_iam_ec2_role(self, role_name, policies): aws_role_name = self.to_aws_name(role_name) try: self.iam.create_role(aws_role_name, assume_role_policy_document=json.dumps({ "Version": "2012-10-17", "Statement": [{ "Effect": "Allow", "Principal": {"Service": ["ec2.amazonaws.com"]}, "Action": ["sts:AssumeRole"]} ]})) except BotoServerError as e: if e.status == 409 and e.error_code == 'EntityAlreadyExists': pass else: raise self.__setup_entity_policies(aws_role_name, policies, list_policies=self.iam.list_role_policies, delete_policy=self.iam.delete_role_policy, get_policy=self.iam.get_role_policy, put_policy=self.iam.put_role_policy) return aws_role_name def __setup_entity_policies(self, entity_name, policies, list_policies, delete_policy, get_policy, put_policy): # Delete superfluous policies policy_names = set(list_policies(entity_name).policy_names) for policy_name in policy_names.difference(set(list(policies.keys()))): delete_policy(entity_name, policy_name) # Create expected policies for policy_name, policy in iteritems(policies): current_policy = None try: current_policy = json.loads(unquote( get_policy(entity_name, policy_name).policy_document)) except BotoServerError as e: if e.status == 404 and e.error_code == 'NoSuchEntity': pass else: raise if current_policy != policy: put_policy(entity_name, policy_name, json.dumps(policy)) _agent_topic_name = "cgcloud-agent-notifications" def _pager(self, requestor_callable, result_attribute_name): marker = None while True: result = requestor_callable(marker=marker) for p in getattr(result, result_attribute_name): yield p if result.is_truncated == 'true': marker = result.marker else: break def local_roles(self): return [r for r in self._get_all_roles() if self.try_contains_aws_name(r.role_name)] def _get_all_roles(self): return self._pager(self.iam.list_roles, 'roles') toil-releases-3.24.0/src/toil/lib/docker.py000066400000000000000000000402041362134276200205030ustar00rootroot00000000000000from __future__ import absolute_import try: # In Python 3 we have this quote from shlex import quote except ImportError: # But in 2.7 we have this deprecated one from pipes import quote import docker import base64 import requests import logging import os import sys from docker.errors import create_api_error_from_http_exception from docker.errors import ContainerError from docker.errors import ImageNotFound from docker.errors import NotFound logger = logging.getLogger(__name__) FORGO = 0 STOP = 1 RM = 2 def dockerCheckOutput(*args, **kwargs): raise RuntimeError("dockerCheckOutput() using subprocess.check_output() has been removed, " "please switch to apiDockerCall().") def dockerCall(*args, **kwargs): raise RuntimeError("dockerCall() using subprocess.check_output() has been removed, " "please switch to apiDockerCall().") def subprocessDockerCall(*args, **kwargs): raise RuntimeError("subprocessDockerCall() has been removed, " "please switch to apiDockerCall().") def apiDockerCall(job, image, parameters=None, deferParam=None, volumes=None, working_dir=None, containerName=None, entrypoint=None, detach=False, log_config=None, auto_remove=None, remove=False, user=None, environment=None, stdout=None, stderr=False, streamfile=None, timeout=365 * 24 * 60 * 60, **kwargs): """ A toil wrapper for the python docker API. Docker API Docs: https://docker-py.readthedocs.io/en/stable/index.html Docker API Code: https://github.com/docker/docker-py This implements docker's python API within toil so that calls are run as jobs, with the intention that failed/orphaned docker jobs be handled appropriately. Example of using dockerCall in toil to index a FASTA file with SAMtools: def toil_job(job): working_dir = job.fileStore.getLocalTempDir() path = job.fileStore.readGlobalFile(ref_id, os.path.join(working_dir, 'ref.fasta') parameters = ['faidx', path] apiDockerCall(job, image='quay.io/ucgc_cgl/samtools:latest', working_dir=working_dir, parameters=parameters) Note that when run with detatch=False, or with detatch=True and stdout=True or stderr=True, this is a blocking call. When run with detatch=True and without output capture, the container is started and returned without waiting for it to finish. :param toil.Job.job job: The Job instance for the calling function. :param str image: Name of the Docker image to be used. (e.g. 'quay.io/ucsc_cgl/samtools:latest') :param list[str] parameters: A list of string elements. If there are multiple elements, these will be joined with spaces. This handling of multiple elements provides backwards compatibility with previous versions which called docker using subprocess.check_call(). **If list of lists: list[list[str]], then treat as successive commands chained with pipe. :param str working_dir: The working directory. :param int deferParam: Action to take on the container upon job completion. FORGO (0) leaves the container untouched and running. STOP (1) Sends SIGTERM, then SIGKILL if necessary to the container. RM (2) Immediately send SIGKILL to the container. This is the default behavior if defer is set to None. :param str name: The name/ID of the container. :param str entrypoint: Prepends commands sent to the container. See: https://docker-py.readthedocs.io/en/stable/containers.html :param bool detach: Run the container in detached mode. (equivalent to '-d') :param bool stdout: Return logs from STDOUT when detach=False (default: True). Block and capture stdout to a file when detach=True (default: False). Output capture defaults to output.log, and can be specified with the "streamfile" kwarg. :param bool stderr: Return logs from STDERR when detach=False (default: False). Block and capture stderr to a file when detach=True (default: False). Output capture defaults to output.log, and can be specified with the "streamfile" kwarg. :param str streamfile: Collect container output to this file if detach=True and stderr and/or stdout are True. Defaults to "output.log". :param dict log_config: Specify the logs to return from the container. See: https://docker-py.readthedocs.io/en/stable/containers.html :param bool remove: Remove the container on exit or not. :param str user: The container will be run with the privileges of the user specified. Can be an actual name, such as 'root' or 'lifeisaboutfishtacos', or it can be the uid or gid of the user ('0' is root; '1000' is an example of a less privileged uid or gid), or a complement of the uid:gid (RECOMMENDED), such as '0:0' (root user : root group) or '1000:1000' (some other user : some other user group). :param environment: Allows one to set environment variables inside of the container, such as: :param int timeout: Use the given timeout in seconds for interactions with the Docker daemon. Note that the underlying docker module is not always able to abort ongoing reads and writes in order to respect the timeout. Defaults to 1 year (i.e. wait essentially indefinitely). :param kwargs: Additional keyword arguments supplied to the docker API's run command. The list is 75 keywords total, for examples and full documentation see: https://docker-py.readthedocs.io/en/stable/containers.html :returns: Returns the standard output/standard error text, as requested, when detatch=False. Returns the underlying docker.models.containers.Container object from the Docker API when detatch=True. """ # make certain that files have the correct permissions thisUser = os.getuid() thisGroup = os.getgid() if user is None: user = str(thisUser) + ":" + str(thisGroup) if containerName is None: containerName = getContainerName(job) if working_dir is None: working_dir = os.getcwd() if volumes is None: volumes = {working_dir: {'bind': '/data', 'mode': 'rw'}} if parameters is None: parameters = [] # If 'parameters' is a list of lists, treat each list as a separate command # and chain with pipes. if len(parameters) > 0 and type(parameters[0]) is list: if entrypoint is None: entrypoint = ['/bin/bash', '-c'] chain_params = \ [' '.join((quote(arg) for arg in command)) \ for command in parameters] command = ' | '.join(chain_params) pipe_prefix = "set -eo pipefail && " command = [pipe_prefix + command] logger.debug("Calling docker with: " + repr(command)) # If 'parameters' is a normal list, join all elements into a single string # element, quoting and escaping each element. # Example: ['echo','the Oread'] becomes: ["echo 'the Oread'"] # Note that this is still a list, and the docker API prefers this as best # practice: # http://docker-py.readthedocs.io/en/stable/containers.html elif len(parameters) > 0 and type(parameters) is list: command = ' '.join((quote(arg) for arg in parameters)) logger.debug("Calling docker with: " + repr(command)) # If the 'parameters' lists are empty, they are respecified as None, which # tells the API to simply create and run the container else: entrypoint = None command = None working_dir = os.path.abspath(working_dir) # Ensure the user has passed a valid value for deferParam assert deferParam in (None, FORGO, STOP, RM), \ 'Please provide a valid value for deferParam.' client = docker.from_env(version='auto', timeout=timeout) if deferParam == STOP: job.defer(dockerStop, containerName) if deferParam == FORGO: remove = False elif deferParam == RM: remove = True job.defer(dockerKill, containerName) elif remove is True: job.defer(dockerKill, containerName) if auto_remove is None: auto_remove = remove try: if detach is False: # When detach is False, this returns stdout normally: # >>> client.containers.run("ubuntu:latest", "echo hello world") # 'hello world\n' if stdout is None: stdout = True out = client.containers.run(image=image, command=command, working_dir=working_dir, entrypoint=entrypoint, name=containerName, detach=False, volumes=volumes, auto_remove=auto_remove, stdout=stdout, stderr=stderr, remove=remove, log_config=log_config, user=user, environment=environment, **kwargs) return out else: if (stdout or stderr) and log_config is None: logger.warn('stdout or stderr specified, but log_config is not set. ' 'Defaulting to "journald".') log_config = dict(type='journald') if stdout is None: stdout = False # When detach is True, this returns a container object: # >>> client.containers.run("bfirsh/reticulate-splines", detach=True) # container = client.containers.run(image=image, command=command, working_dir=working_dir, entrypoint=entrypoint, name=containerName, detach=True, volumes=volumes, auto_remove=auto_remove, stdout=stdout, stderr=stderr, remove=remove, log_config=log_config, user=user, environment=environment, **kwargs) if stdout or stderr: if streamfile is None: streamfile = 'output.log' for line in container.logs(stdout=stdout, stderr=stderr, stream=True): # stream=True makes this loop blocking; we will loop until # the container stops and there is no more output. with open(streamfile, 'w') as f: f.write(line) # If we didn't capture output, the caller will need to .wait() on # the container to know when it is done. Even if we did capture # output, the caller needs the container to get at the exit code. return container except ContainerError: logger.error("Docker had non-zero exit. Check your command: " + repr(command)) raise except ImageNotFound: logger.error("Docker image not found.") raise except requests.exceptions.HTTPError as e: logger.error("The server returned an error.") raise create_api_error_from_http_exception(e) def dockerKill(container_name, gentleKill=False, timeout=365 * 24 * 60 * 60): """ Immediately kills a container. Equivalent to "docker kill": https://docs.docker.com/engine/reference/commandline/kill/ :param container_name: Name of the container being killed. :param client: The docker API client object to call. :param int timeout: Use the given timeout in seconds for interactions with the Docker daemon. Note that the underlying docker module is not always able to abort ongoing reads and writes in order to respect the timeout. Defaults to 1 year (i.e. wait essentially indefinitely). """ client = docker.from_env(version='auto', timeout=timeout) try: this_container = client.containers.get(container_name) while this_container.status == 'running': if gentleKill is False: client.containers.get(container_name).kill() else: client.containers.get(container_name).stop() this_container = client.containers.get(container_name) except NotFound: logger.debug("Attempted to stop container, but container != exist: ", container_name) except requests.exceptions.HTTPError as e: logger.debug("Attempted to stop container, but server gave an error: ", container_name) raise create_api_error_from_http_exception(e) def dockerStop(container_name): """ Gracefully kills a container. Equivalent to "docker stop": https://docs.docker.com/engine/reference/commandline/stop/ :param container_name: Name of the container being stopped. :param client: The docker API client object to call. """ dockerKill(container_name, gentleKill=True) def containerIsRunning(container_name, timeout=365 * 24 * 60 * 60): """ Checks whether the container is running or not. :param container_name: Name of the container being checked. :returns: True if status is 'running', False if status is anything else, and None if the container does not exist. :param int timeout: Use the given timeout in seconds for interactions with the Docker daemon. Note that the underlying docker module is not always able to abort ongoing reads and writes in order to respect the timeout. Defaults to 1 year (i.e. wait essentially indefinitely). """ client = docker.from_env(version='auto', timeout=timeout) try: this_container = client.containers.get(container_name) if this_container.status == 'running': return True else: # this_container.status == 'exited', 'restarting', or 'paused' return False except NotFound: return None except requests.exceptions.HTTPError as e: logger.debug("Server error attempting to call container: ", container_name) raise create_api_error_from_http_exception(e) def getContainerName(job): """Create a random string including the job name, and return it.""" return '--'.join([str(job), base64.b64encode(os.urandom(9), b'-_').decode('utf-8')])\ .replace("'", '').replace('"', '').replace('_', '') toil-releases-3.24.0/src/toil/lib/ec2.py000066400000000000000000000231501362134276200177060ustar00rootroot00000000000000import logging import time from collections import Iterator from operator import attrgetter from past.builtins import map from toil.lib.exceptions import panic from toil.lib.retry import retry from boto.ec2.instance import Instance from boto.ec2.spotinstancerequest import SpotInstanceRequest from boto.exception import EC2ResponseError a_short_time = 5 a_long_time = 60 * 60 log = logging.getLogger(__name__) class UserError(RuntimeError): def __init__(self, message=None, cause=None): if (message is None) == (cause is None): raise RuntimeError("Must pass either message or cause.") super( UserError, self).__init__( message if cause is None else cause.message) def not_found(e): return e.error_code.endswith('.NotFound') def retry_ec2(t=a_short_time, retry_for=10 * a_short_time, retry_while=not_found): return retry(delays=(t, t, t * 2, t * 4), timeout=retry_for, predicate=retry_while) class UnexpectedResourceState(Exception): def __init__(self, resource, to_state, state): super(UnexpectedResourceState, self).__init__( "Expected state of %s to be '%s' but got '%s'" % (resource, to_state, state)) def wait_transition(resource, from_states, to_state, state_getter=attrgetter('state')): """ Wait until the specified EC2 resource (instance, image, volume, ...) transitions from any of the given 'from' states to the specified 'to' state. If the instance is found in a state other that the to state or any of the from states, an exception will be thrown. :param resource: the resource to monitor :param from_states: a set of states that the resource is expected to be in before the transition occurs :param to_state: the state of the resource when this method returns """ state = state_getter(resource) while state in from_states: time.sleep(a_short_time) for attempt in retry_ec2(): with attempt: resource.update(validate=True) state = state_getter(resource) if state != to_state: raise UnexpectedResourceState(resource, to_state, state) def wait_instances_running(ec2, instances): """ Wait until no instance in the given iterable is 'pending'. Yield every instance that entered the running state as soon as it does. :param boto.ec2.connection.EC2Connection ec2: the EC2 connection to use for making requests :param Iterator[Instance] instances: the instances to wait on :rtype: Iterator[Instance] """ running_ids = set() other_ids = set() while True: pending_ids = set() for i in instances: if i.state == 'pending': pending_ids.add(i.id) elif i.state == 'running': assert i.id not in running_ids running_ids.add(i.id) yield i else: assert i.id not in other_ids other_ids.add(i.id) yield i log.info('%i instance(s) pending, %i running, %i other.', *map(len, (pending_ids, running_ids, other_ids))) if not pending_ids: break seconds = max(a_short_time, min(len(pending_ids), 10 * a_short_time)) log.info('Sleeping for %is', seconds) time.sleep(seconds) for attempt in retry_ec2(): with attempt: instances = ec2.get_only_instances(list(pending_ids)) def wait_spot_requests_active(ec2, requests, timeout=None, tentative=False): """ Wait until no spot request in the given iterator is in the 'open' state or, optionally, a timeout occurs. Yield spot requests as soon as they leave the 'open' state. :param Iterator[SpotInstanceRequest] requests: :param float timeout: Maximum time in seconds to spend waiting or None to wait forever. If a timeout occurs, the remaining open requests will be cancelled. :param bool tentative: if True, give up on a spot request at the earliest indication of it not being fulfilled immediately :rtype: Iterator[list[SpotInstanceRequest]] """ if timeout is not None: timeout = time.time() + timeout active_ids = set() other_ids = set() open_ids = None def cancel(): log.warning('Cancelling remaining %i spot requests.', len(open_ids)) ec2.cancel_spot_instance_requests(list(open_ids)) def spot_request_not_found(e): error_code = 'InvalidSpotInstanceRequestID.NotFound' return isinstance(e, EC2ResponseError) and e.error_code == error_code try: while True: open_ids, eval_ids, fulfill_ids = set(), set(), set() batch = [] for r in requests: if r.state == 'open': open_ids.add(r.id) if r.status.code == 'pending-evaluation': eval_ids.add(r.id) elif r.status.code == 'pending-fulfillment': fulfill_ids.add(r.id) else: log.info( 'Request %s entered status %s indicating that it will not be ' 'fulfilled anytime soon.', r.id, r.status.code) elif r.state == 'active': assert r.id not in active_ids active_ids.add(r.id) batch.append(r) else: assert r.id not in other_ids other_ids.add(r.id) batch.append(r) if batch: yield batch log.info('%i spot requests(s) are open (%i of which are pending evaluation and %i ' 'are pending fulfillment), %i are active and %i are in another state.', *map(len, (open_ids, eval_ids, fulfill_ids, active_ids, other_ids))) if not open_ids or tentative and not eval_ids and not fulfill_ids: break sleep_time = 2 * a_short_time if timeout is not None and time.time() + sleep_time >= timeout: log.warning('Timed out waiting for spot requests.') break log.info('Sleeping for %is', sleep_time) time.sleep(sleep_time) for attempt in retry_ec2(retry_while=spot_request_not_found): with attempt: requests = ec2.get_all_spot_instance_requests( list(open_ids)) except BaseException: if open_ids: with panic(log): cancel() raise else: if open_ids: cancel() def create_spot_instances(ec2, price, image_id, spec, num_instances=1, timeout=None, tentative=False, tags=None): """ :rtype: Iterator[list[Instance]] """ def spotRequestNotFound(e): return getattr(e, 'error_code', None) == "InvalidSpotInstanceRequestID.NotFound" for attempt in retry_ec2(retry_for=a_long_time, retry_while=inconsistencies_detected): with attempt: requests = ec2.request_spot_instances( price, image_id, count=num_instances, **spec) if tags is not None: for requestID in (request.id for request in requests): for attempt in retry_ec2(retry_while=spotRequestNotFound): with attempt: ec2.create_tags([requestID], tags) num_active, num_other = 0, 0 # noinspection PyUnboundLocalVariable,PyTypeChecker # request_spot_instances's type annotation is wrong for batch in wait_spot_requests_active(ec2, requests, timeout=timeout, tentative=tentative): instance_ids = [] for request in batch: if request.state == 'active': instance_ids.append(request.instance_id) num_active += 1 else: log.info( 'Request %s in unexpected state %s.', request.id, request.state) num_other += 1 if instance_ids: # This next line is the reason we batch. It's so we can get multiple instances in # a single request. yield ec2.get_only_instances(instance_ids) if not num_active: message = 'None of the spot requests entered the active state' if tentative: log.warning(message + '.') else: raise RuntimeError(message) if num_other: log.warning('%i request(s) entered a state other than active.', num_other) def inconsistencies_detected(e): if getattr(e, 'code', None) == 'InvalidGroup.NotFound': return True m = getattr(e, 'error_message', '').lower() return 'invalid iam instance profile' in m or 'no associated iam roles' in m def create_ondemand_instances(ec2, image_id, spec, num_instances=1): """ Requests the RunInstances EC2 API call but accounts for the race between recently created instance profiles, IAM roles and an instance creation that refers to them. :rtype: list[Instance] """ instance_type = spec['instance_type'] log.info('Creating %s instance(s) ... ', instance_type) for attempt in retry_ec2(retry_for=a_long_time, retry_while=inconsistencies_detected): with attempt: return ec2.run_instances(image_id, min_count=num_instances, max_count=num_instances, **spec).instances toil-releases-3.24.0/src/toil/lib/ec2nodes.py000066400000000000000000000300631362134276200207400ustar00rootroot00000000000000# Copyright (C) 2015-2018 Regents of the University of California # # 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. from __future__ import absolute_import from six import iteritems import requests import os import json import datetime import logging import textwrap logger = logging.getLogger(__name__) dirname = os.path.dirname(__file__) EC2Regions = {'us-west-1': 'US West (N. California)', 'us-west-2': 'US West (Oregon)', 'us-east-1': 'US East (N. Virginia)', 'us-east-2': 'US East (Ohio)', 'us-gov-west-1': 'AWS GovCloud (US)', 'ca-central-1': 'Canada (Central)', 'ap-northeast-1': 'Asia Pacific (Tokyo)', 'ap-northeast-2': 'Asia Pacific (Seoul)', 'ap-northeast-3': 'Asia Pacific (Osaka-Local)', 'ap-southeast-1': 'Asia Pacific (Singapore)', 'ap-southeast-2': 'Asia Pacific (Sydney)', 'ap-south-1': 'Asia Pacific (Mumbai)', 'eu-west-1': 'EU (Ireland)', 'eu-west-2': 'EU (London)', 'eu-west-3': 'EU (Paris)', 'eu-central-1': 'EU (Frankfurt)', 'sa-east-1': 'South America (Sao Paulo)'} class InstanceType(object): __slots__ = ('name', 'cores', 'memory', 'disks', 'disk_capacity') def __init__(self, name, cores, memory, disks, disk_capacity): self.name = name # the API name of the instance type self.cores = cores # the number of cores self.memory = memory # RAM in GiB self.disks = disks # the number of ephemeral (aka 'instance store') volumes self.disk_capacity = disk_capacity # the capacity of each ephemeral volume in GiB def __str__(self): return ("Type: {}\n" "Cores: {}\n" "Disks: {}\n" "Memory: {}\n" "Disk Capacity: {}\n" "".format( self.name, self.cores, self.disks, self.memory, self.disk_capacity)) def __eq__(self, other): if (self.name == other.name and self.cores == other.cores and self.memory == other.memory and self.disks == other.disks and self.disk_capacity == other.disk_capacity): return True return False def isNumber(s): """ Determines if a unicode string (that may include commas) is a number. :param s: Any unicode string. :return: True if s represents a number, False otherwise. """ s = s.replace(',', '') try: float(s) return True except ValueError: pass try: import unicodedata unicodedata.numeric(s) return True except (TypeError, ValueError) as e: pass return False def parseStorage(storageData): """ Parses EC2 JSON storage param string into a number. Examples: "2 x 160 SSD" "3 x 2000 HDD" "EBS only" "1 x 410" "8 x 1.9 NVMe SSD" "900 GB NVMe SSD" :param str storageData: EC2 JSON storage param string. :return: Two floats representing: (# of disks), and (disk_capacity in GiB of each disk). """ if storageData == "EBS only": return [0, 0] else: specs = storageData.strip().split() if isNumber(specs[0]) and specs[1] == 'x' and isNumber(specs[2]): return float(specs[0].replace(',', '')), float(specs[2].replace(',', '')) elif isNumber(specs[0]) and specs[1] == 'GB' and specs[2] == 'NVMe' and specs[3] == 'SSD': return 1, float(specs[0].replace(',', '')) else: raise RuntimeError('EC2 JSON format has likely changed. Error parsing disk specs.') def parseMemory(memAttribute): """ Returns EC2 'memory' string as a float. Format should always be '#' GiB (example: '244 GiB' or '1,952 GiB'). Amazon loves to put commas in their numbers, so we have to accommodate that. If the syntax ever changes, this will raise. :param memAttribute: EC2 JSON memory param string. :return: A float representing memory in GiB. """ mem = memAttribute.replace(',', '').split() if mem[1] == 'GiB': return float(mem[0]) else: raise RuntimeError('EC2 JSON format has likely changed. Error parsing memory.') def fetchEC2Index(filename): """Downloads and writes the AWS Billing JSON to a file using the AWS pricing API. See: https://aws.amazon.com/blogs/aws/new-aws-price-list-api/ :return: A dict of InstanceType objects, where the key is the string: aws instance name (example: 't2.micro'), and the value is an InstanceType object representing that aws instance name. """ print('Downloading ~1Gb AWS billing file to parse for information.\n') response = requests.get('https://pricing.us-east-1.amazonaws.com/offers/v1.0/aws/AmazonEC2/current/index.json') if response.ok: with open(filename, 'w') as f: f.write(str(json.dumps(json.loads(response.text), indent=4))) print('Download completed successfully!\n') else: raise RuntimeError('Error: ' + str(response) + ' :: ' + str(response.text)) def fetchEC2InstanceDict(awsBillingJson, region): """ Takes a JSON and returns a list of InstanceType objects representing EC2 instance params. :param region: :return: """ ec2InstanceList = [] for k, v in iteritems(awsBillingJson['products']): i = v['attributes'] # NOTES: # # 3 tenant types: 'Host' (always $0.00; just a template?) # 'Dedicated' (toil does not support; these are pricier) # 'Shared' (AWS default and what toil uses) # # The same instance can appear with multiple "operation" values; # "RunInstances" is normal # "RunInstances:" is e.g. Linux with MS SQL Server installed. if (i.get('location') == region and i.get('tenancy') == 'Shared' and i.get('operatingSystem') == 'Linux' and i.get('operation') == 'RunInstances'): normal_use = i.get('usagetype').endswith('BoxUsage:' + i['instanceType']) # not reserved or unused if normal_use: disks, disk_capacity = parseStorage(v["attributes"]["storage"]) instance = InstanceType(name=i["instanceType"], cores=i["vcpu"], memory=parseMemory(i["memory"]), disks=disks, disk_capacity=disk_capacity) if instance in ec2InstanceList: raise RuntimeError('EC2 JSON format has likely changed. ' 'Duplicate instance {} found.'.format(instance)) ec2InstanceList.append(instance) print('Finished for ' + str(region) + '. ' + str(len(ec2InstanceList)) + ' added.') return dict((_.name, _) for _ in ec2InstanceList) def updateStaticEC2Instances(): """ Generates a new python file of fetchable EC2 Instances by region with current prices and specs. Takes a few (~3+) minutes to run (you'll need decent internet). :return: Nothing. Writes a new 'generatedEC2Lists.py' file. """ print("Updating Toil's EC2 lists to the most current version from AWS's bulk API.\n" "This may take a while, depending on your internet connection (~1Gb file).\n") origFile = os.path.join(dirname, 'generatedEC2Lists.py') # original assert os.path.exists(origFile) # use a temporary file until all info is fetched genFile = os.path.join(dirname, 'generatedEC2Lists_tmp.py') # temp if os.path.exists(genFile): os.remove(genFile) # filepath to store the aws json request (will be cleaned up) # this is done because AWS changes their json format from time to time # and debugging is faster with the file stored locally awsJsonIndex = os.path.join(dirname, 'index.json') if not os.path.exists(awsJsonIndex): fetchEC2Index(filename=awsJsonIndex) else: print('Reusing previously downloaded json @: ' + awsJsonIndex) with open(awsJsonIndex, 'r') as f: awsProductDict = json.loads(f.read()) currentEC2List = [] instancesByRegion = {} for regionNickname in EC2Regions: currentEC2Dict = fetchEC2InstanceDict(awsProductDict, region=EC2Regions[regionNickname]) for instanceName, instanceTypeObj in iteritems(currentEC2Dict): if instanceTypeObj not in currentEC2List: currentEC2List.append(instanceTypeObj) instancesByRegion.setdefault(regionNickname, []).append(instanceName) # write provenance note, copyright and imports with open(genFile, 'w') as f: f.write(textwrap.dedent(''' # !!! AUTOGENERATED FILE !!! # Update with: src/toil/utils/toilUpdateEC2Instances.py # # Copyright (C) 2015-{year} UCSC Computational Genomics Lab # # 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. from six import iteritems from toil.lib.ec2nodes import InstanceType\n\n\n''').format(year=datetime.date.today().strftime("%Y"))[1:]) # write header of total EC2 instance type list genString = "# {num} Instance Types. Generated {date}.\n".format( num=str(len(currentEC2List)), date=str(datetime.datetime.now())) genString = genString + "E2Instances = {\n" sortedCurrentEC2List = sorted(currentEC2List, key=lambda x: x.name) # write the list of all instances types for i in sortedCurrentEC2List: z = " '{name}': InstanceType(name='{name}', cores={cores}, memory={memory}, disks={disks}, disk_capacity={disk_capacity})," \ "\n".format(name=i.name, cores=i.cores, memory=i.memory, disks=i.disks, disk_capacity=i.disk_capacity) genString = genString + z genString = genString + '}\n\n' genString = genString + 'regionDict = {\n' for regionName, instanceList in iteritems(instancesByRegion): genString = genString + " '{regionName}': [".format(regionName=regionName) for instance in sorted(instanceList): genString = genString + "'{instance}', ".format(instance=instance) if genString.endswith(', '): genString = genString[:-2] genString = genString + '],\n' if genString.endswith(',\n'): genString = genString[:-len(',\n')] genString = genString + '}\n' with open(genFile, 'a+') as f: f.write(genString) # append key for fetching at the end regionKey = '\nec2InstancesByRegion = dict((region, [E2Instances[i] for i in instances]) for region, instances in iteritems(regionDict))\n' with open(genFile, 'a+') as f: f.write(regionKey) # delete the original file if os.path.exists(origFile): os.remove(origFile) # replace the instance list with a current list os.rename(genFile, origFile) # delete the aws billing json file if os.path.exists(awsJsonIndex): os.remove(awsJsonIndex) toil-releases-3.24.0/src/toil/lib/encryption/000077500000000000000000000000001362134276200210545ustar00rootroot00000000000000toil-releases-3.24.0/src/toil/lib/encryption/__init__.py000066400000000000000000000013301362134276200231620ustar00rootroot00000000000000from __future__ import absolute_import # Copyright (C) 2015-2016 Regents of the University of California # # 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. try: from ._nacl import * except ImportError: from ._dummy import * toil-releases-3.24.0/src/toil/lib/encryption/_dummy.py000066400000000000000000000020561362134276200227230ustar00rootroot00000000000000# Copyright (C) 2015-2016 Regents of the University of California # # 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. overhead = 0 # noinspection PyUnusedLocal def encrypt(message, keyPath): _bail() # noinspection PyUnusedLocal def decrypt(ciphertext, keyPath): _bail() def _bail(): raise NotImplementedError("Encryption support is not installed. Consider re-installing toil " "with the 'encryption' extra along with any other extras you might " "want, e.g. 'pip install toil[encryption,...]'.") toil-releases-3.24.0/src/toil/lib/encryption/_nacl.py000066400000000000000000000072501362134276200225060ustar00rootroot00000000000000# Copyright (C) 2015-2016 Regents of the University of California # # 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. from builtins import str import nacl from nacl.secret import SecretBox # 16-byte MAC plus a nonce is added to every message. overhead = 16 + SecretBox.NONCE_SIZE def encrypt(message, keyPath): """ Encrypts a message given a path to a local file containing a key. :param message: The message to be encrypted. :param keyPath: A path to a file containing a 256-bit key (and nothing else). :type message: bytes :type keyPath: str :rtype: bytes A constant overhead is added to every encrypted message (for the nonce and MAC). >>> import tempfile >>> k = tempfile.mktemp() >>> with open(k, 'wb') as f: ... _ = f.write(nacl.utils.random(SecretBox.KEY_SIZE)) >>> message = 'test'.encode('utf-8') >>> len(encrypt(message, k)) == overhead + len(message) True >>> import os >>> os.remove(k) """ with open(keyPath, 'rb') as f: key = f.read() if len(key) != SecretBox.KEY_SIZE: raise ValueError("Key is %d bytes, but must be exactly %d bytes" % (len(key), SecretBox.KEY_SIZE)) sb = SecretBox(key) # We generate the nonce using secure random bits. For long enough # nonce size, the chance of a random nonce collision becomes # *much* smaller than the chance of a subtle coding error causing # a nonce reuse. Currently the nonce size is 192 bits--the chance # of a collision is astronomically low. (This approach is # recommended in the libsodium documentation.) nonce = nacl.utils.random(SecretBox.NONCE_SIZE) assert len(nonce) == SecretBox.NONCE_SIZE return bytes(sb.encrypt(message, nonce)) def decrypt(ciphertext, keyPath): """ Decrypts a given message that was encrypted with the encrypt() method. :param ciphertext: The encrypted message (as a string). :param keyPath: A path to a file containing a 256-bit key (and nothing else). :type ciphertext: bytes :type keyPath: str :rtype: bytes Raises an error if ciphertext was modified >>> import tempfile >>> k = tempfile.mktemp() >>> with open(k, 'wb') as f: ... _ = f.write(nacl.utils.random(SecretBox.KEY_SIZE)) >>> ciphertext = encrypt("testMessage".encode('utf-8'), k) >>> ciphertext = b'5' + ciphertext[1:] >>> decrypt(ciphertext, k) # doctest: +IGNORE_EXCEPTION_DETAIL Traceback (most recent call last): ... CryptoError: Decryption failed. Ciphertext failed verification Otherwise works correctly >>> decrypt(encrypt("testMessage".encode('utf-8'), k), k).decode('utf-8') in (u'testMessage', b'testMessage', 'testMessage') # doctest: +ALLOW_UNICODE True >>> import os >>> os.remove(k) """ with open(keyPath, 'rb') as f: key = f.read() if len(key) != SecretBox.KEY_SIZE: raise ValueError("Key is %d bytes, but must be exactly %d bytes" % (len(key), SecretBox.KEY_SIZE)) sb = SecretBox(key) # The nonce is kept with the message. return sb.decrypt(ciphertext) toil-releases-3.24.0/src/toil/lib/encryption/conftest.py000066400000000000000000000002371362134276200232550ustar00rootroot00000000000000# https://pytest.org/latest/example/pythoncollection.html collect_ignore = [] try: import nacl except ImportError: collect_ignore.append("_nacl.py") toil-releases-3.24.0/src/toil/lib/exceptions.py000066400000000000000000000040731362134276200214210ustar00rootroot00000000000000# Copyright (C) 2015-2018 Regents of the University of California # # 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. # 5.14.2018: copied into Toil from https://github.com/BD2KGenomics/bd2k-python-lib from __future__ import absolute_import from future.utils import raise_ from builtins import object import sys class panic( object ): """ The Python idiom for reraising a primary exception fails when the except block raises a secondary exception, e.g. while trying to cleanup. In that case the original exception is lost and the secondary exception is reraised. The solution seems to be to save the primary exception info as returned from sys.exc_info() and then reraise that. This is a contextmanager that should be used like this try: # do something that can fail except: with panic( log ): # do cleanup that can also fail If a logging logger is passed to panic(), any secondary Exception raised within the with block will be logged. Otherwise those exceptions are swallowed. At the end of the with block the primary exception will be reraised. """ def __init__( self, log=None ): super( panic, self ).__init__( ) self.log = log self.exc_info = None def __enter__( self ): self.exc_info = sys.exc_info( ) def __exit__( self, *exc_info ): if self.log is not None and exc_info and exc_info[ 0 ]: self.log.warning( "Exception during panic", exc_info=exc_info ) exc_type, exc_value, traceback = self.exc_info raise_(exc_type, exc_value, traceback) toil-releases-3.24.0/src/toil/lib/expando.py000066400000000000000000000056411362134276200207000ustar00rootroot00000000000000# Copyright (C) 2015-2018 Regents of the University of California # # 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. # 5.14.2018: copied into Toil from https://github.com/BD2KGenomics/bd2k-python-lib from __future__ import absolute_import class Expando(dict): """ Pass inital attributes to the constructor: >>> o = Expando(foo=42) >>> o.foo 42 Dynamically create new attributes: >>> o.bar = 'hi' >>> o.bar 'hi' Expando is a dictionary: >>> isinstance(o,dict) True >>> o['foo'] 42 Works great with JSON: >>> import json >>> s='{"foo":42}' >>> o = json.loads(s,object_hook=Expando) >>> o.foo 42 >>> o.bar = 'hi' >>> o.bar 'hi' And since Expando is a dict, it serializes back to JSON just fine: >>> json.dumps(o, sort_keys=True) '{"bar": "hi", "foo": 42}' Attributes can be deleted, too: >>> o = Expando(foo=42) >>> o.foo 42 >>> del o.foo >>> o.foo Traceback (most recent call last): ... AttributeError: 'Expando' object has no attribute 'foo' >>> o['foo'] Traceback (most recent call last): ... KeyError: 'foo' >>> del o.foo Traceback (most recent call last): ... AttributeError: foo And copied: >>> o = Expando(foo=42) >>> p = o.copy() >>> isinstance(p,Expando) True >>> o == p True >>> o is p False Same with MagicExpando ... >>> o = MagicExpando() >>> o.foo.bar = 42 >>> p = o.copy() >>> isinstance(p,MagicExpando) True >>> o == p True >>> o is p False ... but the copy is shallow: >>> o.foo is p.foo True """ def __init__( self, *args, **kwargs ): super( Expando, self ).__init__( *args, **kwargs ) self.__slots__ = None self.__dict__ = self def copy(self): return type(self)(self) class MagicExpando(Expando): """ Use MagicExpando for chained attribute access. The first time a missing attribute is accessed, it will be set to a new child MagicExpando. >>> o=MagicExpando() >>> o.foo = 42 >>> o {'foo': 42} >>> o.bar.hello = 'hi' >>> o.bar {'hello': 'hi'} """ def __getattribute__( self, name ): try: return super( Expando, self ).__getattribute__( name ) except AttributeError: child = self.__class__( ) self[name] = child return child toil-releases-3.24.0/src/toil/lib/fnmatch.py000066400000000000000000000110441362134276200206540ustar00rootroot00000000000000# Copyright (C) 2015-2018 Regents of the University of California # # 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. # 5.14.2018: copied into Toil from https://github.com/BD2KGenomics/bd2k-python-lib from __future__ import absolute_import import re # Same as Python's fnmatch with the following differences: # - '/' doesn't match '*' # - added '**' to match anything # - added some unit tests """Filename matching with shell patterns. fnmatch(FILENAME, PATTERN) matches according to the local convention. fnmatchcase(FILENAME, PATTERN) always takes case in account. The functions operate by translating the pattern into a regular expression. They cache the compiled regular expressions for speed. The function translate(PATTERN) returns a regular expression corresponding to PATTERN. (It does not compile it.) """ __all__ = ["filter", "fnmatch", "fnmatchcase", "translate"] _cache = {} _MAXCACHE = 100 def _purge( ): """Clear the pattern cache""" _cache.clear( ) def fnmatch( name, pat ): """Test whether FILENAME matches PATTERN. Patterns are Unix shell style: * matches everything ? matches any single character [seq] matches any character in seq [!seq] matches any char not in seq An initial period in FILENAME is not special. Both FILENAME and PATTERN are first case-normalized if the operating system requires it. If you don't want this, use fnmatchcase(FILENAME, PATTERN). >>> fnmatch('bar', '*' ) True >>> fnmatch('foo/bar', '*' ) False >>> fnmatch('foo/bar', '**' ) True >>> fnmatch('foo/bar', '*/*' ) True >>> fnmatch('foo/bar', '**/*' ) True >>> fnmatch('/bar', '**/*' ) True >>> fnmatch('/', '**' ) True >>> fnmatch('/', '*' ) False """ import os name = os.path.normcase( name ) pat = os.path.normcase( pat ) return fnmatchcase( name, pat ) def filter( names, pat ): """Return the subset of the list NAMES that match PAT""" import os, posixpath result = [ ] pat = os.path.normcase( pat ) if not pat in _cache: res = translate( pat ) if len( _cache ) >= _MAXCACHE: _cache.clear( ) _cache[ pat ] = re.compile( res ) match = _cache[ pat ].match if os.path is posixpath: # normcase on posix is NOP. Optimize it away from the loop. for name in names: if match( name ): result.append( name ) else: for name in names: if match( os.path.normcase( name ) ): result.append( name ) return result def fnmatchcase( name, pat ): """Test whether FILENAME matches PATTERN, including case. This is a version of fnmatch() which doesn't case-normalize its arguments. """ if not pat in _cache: res = translate( pat ) if len( _cache ) >= _MAXCACHE: _cache.clear( ) _cache[ pat ] = re.compile( res ) return _cache[ pat ].match( name ) is not None def translate( pat ): """Translate a shell PATTERN to a regular expression. There is no way to quote meta-characters. """ i, n = 0, len( pat ) res = '' while i < n: c = pat[ i ] i += 1 if c == '*': if i < len(pat) and pat[i] == '*': i += 1 res += '.*' else: res += '[^/]*' elif c == '?': res += '.' elif c == '[': j = i if j < n and pat[ j ] == '!': j += 1 if j < n and pat[ j ] == ']': j += 1 while j < n and pat[ j ] != ']': j += 1 if j >= n: res += '\\[' else: stuff = pat[ i:j ].replace( '\\', '\\\\' ) i = j + 1 if stuff[ 0 ] == '!': stuff = '^' + stuff[ 1: ] elif stuff[ 0 ] == '^': stuff = '\\' + stuff res = '%s[%s]' % (res, stuff) else: res = res + re.escape( c ) return res + '\Z(?ms)' toil-releases-3.24.0/src/toil/lib/generatedEC2Lists.py000066400000000000000000002332021362134276200225050ustar00rootroot00000000000000# !!! AUTOGENERATED FILE !!! # Update with: src/toil/utils/toilUpdateEC2Instances.py # # Copyright (C) 2015-2020 UCSC Computational Genomics Lab # # 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. from six import iteritems from toil.lib.ec2nodes import InstanceType # 271 Instance Types. Generated 2020-02-07 12:22:28.845267. E2Instances = { 'a1.2xlarge': InstanceType(name='a1.2xlarge', cores=8, memory=16.0, disks=0, disk_capacity=0), 'a1.4xlarge': InstanceType(name='a1.4xlarge', cores=16, memory=32.0, disks=0, disk_capacity=0), 'a1.large': InstanceType(name='a1.large', cores=2, memory=4.0, disks=0, disk_capacity=0), 'a1.medium': InstanceType(name='a1.medium', cores=1, memory=2.0, disks=0, disk_capacity=0), 'a1.metal': InstanceType(name='a1.metal', cores=16, memory=32.0, disks=0, disk_capacity=0), 'a1.xlarge': InstanceType(name='a1.xlarge', cores=4, memory=8.0, disks=0, disk_capacity=0), 'c1.medium': InstanceType(name='c1.medium', cores=2, memory=1.7, disks=1.0, disk_capacity=350.0), 'c1.xlarge': InstanceType(name='c1.xlarge', cores=8, memory=7.0, disks=4.0, disk_capacity=420.0), 'c3.2xlarge': InstanceType(name='c3.2xlarge', cores=8, memory=15.0, disks=2.0, disk_capacity=80.0), 'c3.4xlarge': InstanceType(name='c3.4xlarge', cores=16, memory=30.0, disks=2.0, disk_capacity=160.0), 'c3.8xlarge': InstanceType(name='c3.8xlarge', cores=36, memory=60.0, disks=2.0, disk_capacity=320.0), 'c3.large': InstanceType(name='c3.large', cores=2, memory=3.75, disks=2.0, disk_capacity=16.0), 'c3.xlarge': InstanceType(name='c3.xlarge', cores=4, memory=7.5, disks=2.0, disk_capacity=40.0), 'c4.2xlarge': InstanceType(name='c4.2xlarge', cores=8, memory=15.0, disks=0, disk_capacity=0), 'c4.4xlarge': InstanceType(name='c4.4xlarge', cores=16, memory=30.0, disks=0, disk_capacity=0), 'c4.8xlarge': InstanceType(name='c4.8xlarge', cores=36, memory=60.0, disks=0, disk_capacity=0), 'c4.large': InstanceType(name='c4.large', cores=2, memory=3.75, disks=0, disk_capacity=0), 'c4.xlarge': InstanceType(name='c4.xlarge', cores=4, memory=7.5, disks=0, disk_capacity=0), 'c5.12xlarge': InstanceType(name='c5.12xlarge', cores=48, memory=96.0, disks=0, disk_capacity=0), 'c5.18xlarge': InstanceType(name='c5.18xlarge', cores=72, memory=144.0, disks=0, disk_capacity=0), 'c5.24xlarge': InstanceType(name='c5.24xlarge', cores=96, memory=192.0, disks=0, disk_capacity=0), 'c5.2xlarge': InstanceType(name='c5.2xlarge', cores=8, memory=16.0, disks=0, disk_capacity=0), 'c5.4xlarge': InstanceType(name='c5.4xlarge', cores=16, memory=32.0, disks=0, disk_capacity=0), 'c5.9xlarge': InstanceType(name='c5.9xlarge', cores=36, memory=72.0, disks=0, disk_capacity=0), 'c5.large': InstanceType(name='c5.large', cores=2, memory=4.0, disks=0, disk_capacity=0), 'c5.metal': InstanceType(name='c5.metal', cores=96, memory=192.0, disks=0, disk_capacity=0), 'c5.xlarge': InstanceType(name='c5.xlarge', cores=4, memory=8.0, disks=0, disk_capacity=0), 'c5d.12xlarge': InstanceType(name='c5d.12xlarge', cores=48, memory=96.0, disks=2.0, disk_capacity=900.0), 'c5d.18xlarge': InstanceType(name='c5d.18xlarge', cores=72, memory=144.0, disks=2.0, disk_capacity=900.0), 'c5d.24xlarge': InstanceType(name='c5d.24xlarge', cores=96, memory=192.0, disks=4.0, disk_capacity=900.0), 'c5d.2xlarge': InstanceType(name='c5d.2xlarge', cores=8, memory=16.0, disks=1.0, disk_capacity=200.0), 'c5d.4xlarge': InstanceType(name='c5d.4xlarge', cores=16, memory=32.0, disks=1.0, disk_capacity=400.0), 'c5d.9xlarge': InstanceType(name='c5d.9xlarge', cores=36, memory=72.0, disks=1.0, disk_capacity=900.0), 'c5d.large': InstanceType(name='c5d.large', cores=2, memory=4.0, disks=1.0, disk_capacity=50.0), 'c5d.metal': InstanceType(name='c5d.metal', cores=96, memory=192.0, disks=4.0, disk_capacity=900.0), 'c5d.xlarge': InstanceType(name='c5d.xlarge', cores=4, memory=8.0, disks=1.0, disk_capacity=100.0), 'c5n.18xlarge': InstanceType(name='c5n.18xlarge', cores=72, memory=192.0, disks=0, disk_capacity=0), 'c5n.2xlarge': InstanceType(name='c5n.2xlarge', cores=8, memory=21.0, disks=0, disk_capacity=0), 'c5n.4xlarge': InstanceType(name='c5n.4xlarge', cores=16, memory=42.0, disks=0, disk_capacity=0), 'c5n.9xlarge': InstanceType(name='c5n.9xlarge', cores=36, memory=96.0, disks=0, disk_capacity=0), 'c5n.large': InstanceType(name='c5n.large', cores=2, memory=5.25, disks=0, disk_capacity=0), 'c5n.metal': InstanceType(name='c5n.metal', cores=72, memory=192.0, disks=0, disk_capacity=0), 'c5n.xlarge': InstanceType(name='c5n.xlarge', cores=4, memory=10.5, disks=0, disk_capacity=0), 'cc2.8xlarge': InstanceType(name='cc2.8xlarge', cores=32, memory=60.5, disks=4.0, disk_capacity=840.0), 'cr1.8xlarge': InstanceType(name='cr1.8xlarge', cores=32, memory=244.0, disks=2.0, disk_capacity=120.0), 'd2.2xlarge': InstanceType(name='d2.2xlarge', cores=8, memory=61.0, disks=6.0, disk_capacity=2000.0), 'd2.4xlarge': InstanceType(name='d2.4xlarge', cores=16, memory=122.0, disks=12.0, disk_capacity=2000.0), 'd2.8xlarge': InstanceType(name='d2.8xlarge', cores=36, memory=244.0, disks=24.0, disk_capacity=2000.0), 'd2.xlarge': InstanceType(name='d2.xlarge', cores=4, memory=30.5, disks=3.0, disk_capacity=2000.0), 'f1.16xlarge': InstanceType(name='f1.16xlarge', cores=64, memory=976.0, disks=4.0, disk_capacity=940.0), 'f1.2xlarge': InstanceType(name='f1.2xlarge', cores=8, memory=122.0, disks=1.0, disk_capacity=470.0), 'f1.4xlarge': InstanceType(name='f1.4xlarge', cores=16, memory=244.0, disks=1.0, disk_capacity=940.0), 'g2.2xlarge': InstanceType(name='g2.2xlarge', cores=8, memory=15.0, disks=1.0, disk_capacity=60.0), 'g2.8xlarge': InstanceType(name='g2.8xlarge', cores=32, memory=60.0, disks=2.0, disk_capacity=120.0), 'g3.16xlarge': InstanceType(name='g3.16xlarge', cores=64, memory=488.0, disks=0, disk_capacity=0), 'g3.4xlarge': InstanceType(name='g3.4xlarge', cores=16, memory=122.0, disks=0, disk_capacity=0), 'g3.8xlarge': InstanceType(name='g3.8xlarge', cores=32, memory=244.0, disks=0, disk_capacity=0), 'g3s.xlarge': InstanceType(name='g3s.xlarge', cores=4, memory=30.5, disks=0, disk_capacity=0), 'g4dn.12xlarge': InstanceType(name='g4dn.12xlarge', cores=48, memory=192.0, disks=1, disk_capacity=900.0), 'g4dn.16xlarge': InstanceType(name='g4dn.16xlarge', cores=64, memory=256.0, disks=1, disk_capacity=900.0), 'g4dn.2xlarge': InstanceType(name='g4dn.2xlarge', cores=8, memory=32.0, disks=1, disk_capacity=225.0), 'g4dn.4xlarge': InstanceType(name='g4dn.4xlarge', cores=16, memory=64.0, disks=1, disk_capacity=225.0), 'g4dn.8xlarge': InstanceType(name='g4dn.8xlarge', cores=32, memory=128.0, disks=1, disk_capacity=900.0), 'g4dn.xlarge': InstanceType(name='g4dn.xlarge', cores=4, memory=16.0, disks=1, disk_capacity=125.0), 'h1.16xlarge': InstanceType(name='h1.16xlarge', cores=64, memory=256.0, disks=8.0, disk_capacity=2000.0), 'h1.2xlarge': InstanceType(name='h1.2xlarge', cores=8, memory=32.0, disks=1.0, disk_capacity=2000.0), 'h1.4xlarge': InstanceType(name='h1.4xlarge', cores=16, memory=64.0, disks=2.0, disk_capacity=2000.0), 'h1.8xlarge': InstanceType(name='h1.8xlarge', cores=32, memory=128.0, disks=4.0, disk_capacity=2000.0), 'hs1.8xlarge': InstanceType(name='hs1.8xlarge', cores=16, memory=117.0, disks=24.0, disk_capacity=2000.0), 'i2.2xlarge': InstanceType(name='i2.2xlarge', cores=8, memory=61.0, disks=2.0, disk_capacity=800.0), 'i2.4xlarge': InstanceType(name='i2.4xlarge', cores=16, memory=122.0, disks=4.0, disk_capacity=800.0), 'i2.8xlarge': InstanceType(name='i2.8xlarge', cores=32, memory=244.0, disks=8.0, disk_capacity=800.0), 'i2.xlarge': InstanceType(name='i2.xlarge', cores=4, memory=30.5, disks=1.0, disk_capacity=800.0), 'i3.16xlarge': InstanceType(name='i3.16xlarge', cores=64, memory=488.0, disks=8.0, disk_capacity=1900.0), 'i3.2xlarge': InstanceType(name='i3.2xlarge', cores=8, memory=61.0, disks=1.0, disk_capacity=1900.0), 'i3.4xlarge': InstanceType(name='i3.4xlarge', cores=16, memory=122.0, disks=2.0, disk_capacity=1900.0), 'i3.8xlarge': InstanceType(name='i3.8xlarge', cores=32, memory=244.0, disks=4.0, disk_capacity=1900.0), 'i3.large': InstanceType(name='i3.large', cores=2, memory=15.25, disks=1.0, disk_capacity=475.0), 'i3.metal': InstanceType(name='i3.metal', cores=64, memory=512.0, disks=8.0, disk_capacity=1900.0), 'i3.xlarge': InstanceType(name='i3.xlarge', cores=4, memory=30.5, disks=1.0, disk_capacity=950.0), 'i3en.12xlarge': InstanceType(name='i3en.12xlarge', cores=48, memory=384.0, disks=4.0, disk_capacity=7500.0), 'i3en.24xlarge': InstanceType(name='i3en.24xlarge', cores=96, memory=768.0, disks=8.0, disk_capacity=7500.0), 'i3en.2xlarge': InstanceType(name='i3en.2xlarge', cores=8, memory=64.0, disks=2.0, disk_capacity=2500.0), 'i3en.3xlarge': InstanceType(name='i3en.3xlarge', cores=12, memory=96.0, disks=1.0, disk_capacity=7500.0), 'i3en.6xlarge': InstanceType(name='i3en.6xlarge', cores=24, memory=192.0, disks=2.0, disk_capacity=7500.0), 'i3en.large': InstanceType(name='i3en.large', cores=2, memory=16.0, disks=1.0, disk_capacity=1250.0), 'i3en.metal': InstanceType(name='i3en.metal', cores=96, memory=768.0, disks=8.0, disk_capacity=7500.0), 'i3en.xlarge': InstanceType(name='i3en.xlarge', cores=4, memory=32.0, disks=1.0, disk_capacity=2500.0), 'inf1.24xlarge': InstanceType(name='inf1.24xlarge', cores=96, memory=192.0, disks=0, disk_capacity=0), 'inf1.2xlarge': InstanceType(name='inf1.2xlarge', cores=8, memory=16.0, disks=0, disk_capacity=0), 'inf1.6xlarge': InstanceType(name='inf1.6xlarge', cores=24, memory=48.0, disks=0, disk_capacity=0), 'inf1.xlarge': InstanceType(name='inf1.xlarge', cores=4, memory=8.0, disks=0, disk_capacity=0), 'm1.large': InstanceType(name='m1.large', cores=2, memory=7.5, disks=2.0, disk_capacity=420.0), 'm1.medium': InstanceType(name='m1.medium', cores=1, memory=3.75, disks=1.0, disk_capacity=410.0), 'm1.xlarge': InstanceType(name='m1.xlarge', cores=4, memory=15.0, disks=4.0, disk_capacity=420.0), 'm2.2xlarge': InstanceType(name='m2.2xlarge', cores=4, memory=34.2, disks=1.0, disk_capacity=850.0), 'm2.4xlarge': InstanceType(name='m2.4xlarge', cores=8, memory=68.4, disks=2.0, disk_capacity=840.0), 'm2.xlarge': InstanceType(name='m2.xlarge', cores=2, memory=17.1, disks=1.0, disk_capacity=420.0), 'm3.2xlarge': InstanceType(name='m3.2xlarge', cores=8, memory=30.0, disks=2.0, disk_capacity=80.0), 'm3.large': InstanceType(name='m3.large', cores=2, memory=7.5, disks=1.0, disk_capacity=32.0), 'm3.medium': InstanceType(name='m3.medium', cores=1, memory=3.75, disks=1.0, disk_capacity=4.0), 'm3.xlarge': InstanceType(name='m3.xlarge', cores=4, memory=15.0, disks=2.0, disk_capacity=40.0), 'm4.10xlarge': InstanceType(name='m4.10xlarge', cores=40, memory=160.0, disks=0, disk_capacity=0), 'm4.16xlarge': InstanceType(name='m4.16xlarge', cores=64, memory=256.0, disks=0, disk_capacity=0), 'm4.2xlarge': InstanceType(name='m4.2xlarge', cores=8, memory=32.0, disks=0, disk_capacity=0), 'm4.4xlarge': InstanceType(name='m4.4xlarge', cores=16, memory=64.0, disks=0, disk_capacity=0), 'm4.large': InstanceType(name='m4.large', cores=2, memory=8.0, disks=0, disk_capacity=0), 'm4.xlarge': InstanceType(name='m4.xlarge', cores=4, memory=16.0, disks=0, disk_capacity=0), 'm5.12xlarge': InstanceType(name='m5.12xlarge', cores=48, memory=192.0, disks=0, disk_capacity=0), 'm5.16xlarge': InstanceType(name='m5.16xlarge', cores=64, memory=256.0, disks=0, disk_capacity=0), 'm5.24xlarge': InstanceType(name='m5.24xlarge', cores=96, memory=384.0, disks=0, disk_capacity=0), 'm5.2xlarge': InstanceType(name='m5.2xlarge', cores=8, memory=32.0, disks=0, disk_capacity=0), 'm5.4xlarge': InstanceType(name='m5.4xlarge', cores=16, memory=64.0, disks=0, disk_capacity=0), 'm5.8xlarge': InstanceType(name='m5.8xlarge', cores=32, memory=128.0, disks=0, disk_capacity=0), 'm5.large': InstanceType(name='m5.large', cores=2, memory=8.0, disks=0, disk_capacity=0), 'm5.metal': InstanceType(name='m5.metal', cores=96, memory=384.0, disks=0, disk_capacity=0), 'm5.xlarge': InstanceType(name='m5.xlarge', cores=4, memory=16.0, disks=0, disk_capacity=0), 'm5a.12xlarge': InstanceType(name='m5a.12xlarge', cores=48, memory=192.0, disks=0, disk_capacity=0), 'm5a.16xlarge': InstanceType(name='m5a.16xlarge', cores=64, memory=256.0, disks=0, disk_capacity=0), 'm5a.24xlarge': 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'm5ad.4xlarge': InstanceType(name='m5ad.4xlarge', cores=16, memory=64.0, disks=2.0, disk_capacity=300.0), 'm5ad.8xlarge': InstanceType(name='m5ad.8xlarge', cores=32, memory=128.0, disks=2.0, disk_capacity=600.0), 'm5ad.large': InstanceType(name='m5ad.large', cores=2, memory=8.0, disks=1.0, disk_capacity=75.0), 'm5ad.xlarge': InstanceType(name='m5ad.xlarge', cores=4, memory=16.0, disks=1.0, disk_capacity=150.0), 'm5d.12xlarge': InstanceType(name='m5d.12xlarge', cores=48, memory=192.0, disks=2.0, disk_capacity=900.0), 'm5d.16xlarge': InstanceType(name='m5d.16xlarge', cores=64, memory=256.0, disks=4.0, disk_capacity=600.0), 'm5d.24xlarge': InstanceType(name='m5d.24xlarge', cores=96, memory=384.0, disks=4.0, disk_capacity=900.0), 'm5d.2xlarge': InstanceType(name='m5d.2xlarge', cores=8, memory=32.0, disks=1.0, disk_capacity=300.0), 'm5d.4xlarge': InstanceType(name='m5d.4xlarge', cores=16, memory=64.0, disks=2.0, disk_capacity=300.0), 'm5d.8xlarge': InstanceType(name='m5d.8xlarge', cores=32, memory=128.0, disks=2.0, disk_capacity=600.0), 'm5d.large': InstanceType(name='m5d.large', cores=2, memory=8.0, disks=1.0, disk_capacity=75.0), 'm5d.metal': InstanceType(name='m5d.metal', cores=96, memory=384.0, disks=4.0, disk_capacity=900.0), 'm5d.xlarge': InstanceType(name='m5d.xlarge', cores=4, memory=16.0, disks=1.0, disk_capacity=150.0), 'm5dn.12xlarge': InstanceType(name='m5dn.12xlarge', cores=48, memory=192.0, disks=2.0, disk_capacity=900.0), 'm5dn.16xlarge': InstanceType(name='m5dn.16xlarge', cores=64, memory=256.0, disks=4.0, disk_capacity=600.0), 'm5dn.24xlarge': InstanceType(name='m5dn.24xlarge', cores=96, memory=384.0, disks=4.0, disk_capacity=900.0), 'm5dn.2xlarge': InstanceType(name='m5dn.2xlarge', cores=8, memory=32.0, disks=1.0, disk_capacity=300.0), 'm5dn.4xlarge': InstanceType(name='m5dn.4xlarge', cores=16, memory=64.0, disks=2.0, disk_capacity=300.0), 'm5dn.8xlarge': InstanceType(name='m5dn.8xlarge', cores=32, memory=128.0, disks=2.0, disk_capacity=600.0), 'm5dn.large': InstanceType(name='m5dn.large', cores=2, memory=8.0, disks=1.0, disk_capacity=75.0), 'm5dn.xlarge': InstanceType(name='m5dn.xlarge', cores=4, memory=16.0, disks=1.0, disk_capacity=150.0), 'm5n.12xlarge': InstanceType(name='m5n.12xlarge', cores=48, memory=192.0, disks=0, disk_capacity=0), 'm5n.16xlarge': InstanceType(name='m5n.16xlarge', cores=64, memory=256.0, disks=0, disk_capacity=0), 'm5n.24xlarge': InstanceType(name='m5n.24xlarge', cores=96, memory=384.0, disks=0, disk_capacity=0), 'm5n.2xlarge': InstanceType(name='m5n.2xlarge', cores=8, memory=32.0, disks=0, disk_capacity=0), 'm5n.4xlarge': InstanceType(name='m5n.4xlarge', cores=16, memory=64.0, disks=0, disk_capacity=0), 'm5n.8xlarge': InstanceType(name='m5n.8xlarge', cores=32, memory=128.0, disks=0, disk_capacity=0), 'm5n.large': InstanceType(name='m5n.large', cores=2, memory=8.0, disks=0, disk_capacity=0), 'm5n.xlarge': InstanceType(name='m5n.xlarge', cores=4, memory=16.0, disks=0, disk_capacity=0), 'm6g.12xlarge': InstanceType(name='m6g.12xlarge', cores=48, memory=192.0, disks=0, disk_capacity=0), 'm6g.16xlarge': InstanceType(name='m6g.16xlarge', cores=64, memory=256.0, disks=0, disk_capacity=0), 'm6g.2xlarge': InstanceType(name='m6g.2xlarge', cores=8, memory=32.0, disks=0, disk_capacity=0), 'm6g.4xlarge': InstanceType(name='m6g.4xlarge', cores=16, memory=64.0, disks=0, disk_capacity=0), 'm6g.8xlarge': InstanceType(name='m6g.8xlarge', cores=32, memory=128.0, disks=0, disk_capacity=0), 'm6g.large': InstanceType(name='m6g.large', cores=2, memory=8.0, disks=0, disk_capacity=0), 'm6g.medium': InstanceType(name='m6g.medium', cores=1, memory=4.0, disks=0, disk_capacity=0), 'm6g.xlarge': InstanceType(name='m6g.xlarge', cores=4, memory=16.0, disks=0, disk_capacity=0), 'p2.16xlarge': InstanceType(name='p2.16xlarge', cores=64, memory=732.0, disks=0, disk_capacity=0), 'p2.8xlarge': InstanceType(name='p2.8xlarge', cores=32, memory=488.0, disks=0, disk_capacity=0), 'p2.xlarge': InstanceType(name='p2.xlarge', cores=4, memory=61.0, disks=0, disk_capacity=0), 'p3.16xlarge': InstanceType(name='p3.16xlarge', cores=64, memory=488.0, disks=0, disk_capacity=0), 'p3.2xlarge': InstanceType(name='p3.2xlarge', cores=8, memory=61.0, disks=0, disk_capacity=0), 'p3.8xlarge': InstanceType(name='p3.8xlarge', cores=32, memory=244.0, disks=0, disk_capacity=0), 'p3dn.24xlarge': InstanceType(name='p3dn.24xlarge', cores=96, memory=768.0, disks=2.0, disk_capacity=900.0), 'r3.2xlarge': InstanceType(name='r3.2xlarge', cores=8, memory=61.0, disks=1.0, disk_capacity=160.0), 'r3.4xlarge': InstanceType(name='r3.4xlarge', cores=16, memory=122.0, disks=1.0, disk_capacity=320.0), 'r3.8xlarge': InstanceType(name='r3.8xlarge', cores=32, memory=244.0, disks=2.0, disk_capacity=320.0), 'r3.large': InstanceType(name='r3.large', cores=2, memory=15.25, disks=1.0, disk_capacity=32.0), 'r3.xlarge': InstanceType(name='r3.xlarge', cores=4, memory=30.5, disks=1.0, disk_capacity=80.0), 'r4.16xlarge': InstanceType(name='r4.16xlarge', cores=64, memory=488.0, disks=0, disk_capacity=0), 'r4.2xlarge': InstanceType(name='r4.2xlarge', cores=8, memory=61.0, disks=0, disk_capacity=0), 'r4.4xlarge': InstanceType(name='r4.4xlarge', cores=16, memory=122.0, disks=0, disk_capacity=0), 'r4.8xlarge': InstanceType(name='r4.8xlarge', cores=32, memory=244.0, disks=0, disk_capacity=0), 'r4.large': InstanceType(name='r4.large', cores=2, memory=15.25, disks=0, disk_capacity=0), 'r4.xlarge': InstanceType(name='r4.xlarge', cores=4, memory=30.5, disks=0, disk_capacity=0), 'r5.12xlarge': InstanceType(name='r5.12xlarge', cores=48, memory=384.0, disks=0, disk_capacity=0), 'r5.16xlarge': InstanceType(name='r5.16xlarge', cores=64, memory=512.0, disks=0, disk_capacity=0), 'r5.24xlarge': InstanceType(name='r5.24xlarge', cores=96, memory=768.0, disks=0, disk_capacity=0), 'r5.2xlarge': InstanceType(name='r5.2xlarge', cores=8, memory=64.0, disks=0, disk_capacity=0), 'r5.4xlarge': InstanceType(name='r5.4xlarge', cores=16, memory=128.0, disks=0, disk_capacity=0), 'r5.8xlarge': InstanceType(name='r5.8xlarge', cores=32, memory=256.0, disks=0, disk_capacity=0), 'r5.large': InstanceType(name='r5.large', cores=2, memory=16.0, disks=0, disk_capacity=0), 'r5.metal': InstanceType(name='r5.metal', cores=96, memory=768.0, disks=0, disk_capacity=0), 'r5.xlarge': InstanceType(name='r5.xlarge', cores=4, memory=32.0, disks=0, disk_capacity=0), 'r5a.12xlarge': InstanceType(name='r5a.12xlarge', cores=48, memory=384.0, disks=0, disk_capacity=0), 'r5a.16xlarge': InstanceType(name='r5a.16xlarge', cores=64, memory=512.0, disks=0, disk_capacity=0), 'r5a.24xlarge': InstanceType(name='r5a.24xlarge', cores=96, memory=768.0, disks=0, disk_capacity=0), 'r5a.2xlarge': InstanceType(name='r5a.2xlarge', cores=8, memory=64.0, disks=0, disk_capacity=0), 'r5a.4xlarge': InstanceType(name='r5a.4xlarge', cores=16, memory=128.0, disks=0, disk_capacity=0), 'r5a.8xlarge': InstanceType(name='r5a.8xlarge', cores=32, memory=256.0, disks=0, disk_capacity=0), 'r5a.large': InstanceType(name='r5a.large', cores=2, memory=16.0, disks=0, disk_capacity=0), 'r5a.xlarge': InstanceType(name='r5a.xlarge', cores=4, memory=32.0, disks=0, disk_capacity=0), 'r5ad.12xlarge': InstanceType(name='r5ad.12xlarge', cores=48, memory=384.0, disks=2.0, disk_capacity=900.0), 'r5ad.16xlarge': InstanceType(name='r5ad.16xlarge', cores=64, memory=512.0, disks=4.0, disk_capacity=600.0), 'r5ad.24xlarge': InstanceType(name='r5ad.24xlarge', cores=96, memory=768.0, disks=4.0, disk_capacity=900.0), 'r5ad.2xlarge': InstanceType(name='r5ad.2xlarge', cores=8, memory=64.0, disks=1.0, disk_capacity=300.0), 'r5ad.4xlarge': InstanceType(name='r5ad.4xlarge', cores=16, memory=128.0, disks=2.0, disk_capacity=300.0), 'r5ad.8xlarge': InstanceType(name='r5ad.8xlarge', cores=32, memory=256.0, disks=2.0, disk_capacity=600.0), 'r5ad.large': InstanceType(name='r5ad.large', cores=2, memory=16.0, disks=1.0, disk_capacity=75.0), 'r5ad.xlarge': InstanceType(name='r5ad.xlarge', cores=4, memory=32.0, disks=1.0, disk_capacity=150.0), 'r5d.12xlarge': InstanceType(name='r5d.12xlarge', cores=48, memory=384.0, disks=2.0, disk_capacity=900.0), 'r5d.16xlarge': InstanceType(name='r5d.16xlarge', cores=64, memory=512.0, disks=4.0, disk_capacity=600.0), 'r5d.24xlarge': InstanceType(name='r5d.24xlarge', cores=96, memory=768.0, disks=4.0, disk_capacity=900.0), 'r5d.2xlarge': InstanceType(name='r5d.2xlarge', cores=8, memory=64.0, disks=1.0, disk_capacity=300.0), 'r5d.4xlarge': InstanceType(name='r5d.4xlarge', cores=16, memory=128.0, disks=2.0, disk_capacity=300.0), 'r5d.8xlarge': InstanceType(name='r5d.8xlarge', cores=32, memory=256.0, disks=2.0, disk_capacity=600.0), 'r5d.large': InstanceType(name='r5d.large', cores=2, memory=16.0, disks=1.0, disk_capacity=75.0), 'r5d.metal': InstanceType(name='r5d.metal', cores=96, memory=768.0, disks=4.0, disk_capacity=900.0), 'r5d.xlarge': InstanceType(name='r5d.xlarge', cores=4, memory=32.0, disks=1.0, disk_capacity=150.0), 'r5dn.12xlarge': InstanceType(name='r5dn.12xlarge', cores=48, memory=384.0, disks=2.0, disk_capacity=900.0), 'r5dn.16xlarge': InstanceType(name='r5dn.16xlarge', cores=64, memory=512.0, disks=4.0, disk_capacity=600.0), 'r5dn.24xlarge': InstanceType(name='r5dn.24xlarge', cores=96, memory=768.0, disks=4.0, disk_capacity=900.0), 'r5dn.2xlarge': InstanceType(name='r5dn.2xlarge', cores=8, memory=64.0, disks=1.0, disk_capacity=300.0), 'r5dn.4xlarge': InstanceType(name='r5dn.4xlarge', cores=16, memory=128.0, disks=2.0, disk_capacity=300.0), 'r5dn.8xlarge': InstanceType(name='r5dn.8xlarge', cores=32, memory=256.0, disks=2.0, disk_capacity=600.0), 'r5dn.large': InstanceType(name='r5dn.large', cores=2, memory=16.0, disks=1.0, disk_capacity=75.0), 'r5dn.xlarge': InstanceType(name='r5dn.xlarge', cores=4, memory=32.0, disks=1.0, disk_capacity=150.0), 'r5n.12xlarge': InstanceType(name='r5n.12xlarge', cores=48, memory=384.0, disks=0, disk_capacity=0), 'r5n.16xlarge': InstanceType(name='r5n.16xlarge', cores=64, memory=512.0, disks=0, disk_capacity=0), 'r5n.24xlarge': InstanceType(name='r5n.24xlarge', cores=96, memory=768.0, disks=0, disk_capacity=0), 'r5n.2xlarge': InstanceType(name='r5n.2xlarge', cores=8, memory=64.0, disks=0, disk_capacity=0), 'r5n.4xlarge': InstanceType(name='r5n.4xlarge', cores=16, memory=128.0, disks=0, disk_capacity=0), 'r5n.8xlarge': InstanceType(name='r5n.8xlarge', cores=32, memory=256.0, disks=0, disk_capacity=0), 'r5n.large': InstanceType(name='r5n.large', cores=2, memory=16.0, disks=0, disk_capacity=0), 'r5n.xlarge': InstanceType(name='r5n.xlarge', cores=4, memory=32.0, disks=0, disk_capacity=0), 't1.micro': InstanceType(name='t1.micro', cores=1, memory=0.613, disks=0, disk_capacity=0), 't2.2xlarge': InstanceType(name='t2.2xlarge', cores=8, memory=32.0, disks=0, disk_capacity=0), 't2.large': InstanceType(name='t2.large', cores=2, memory=8.0, disks=0, disk_capacity=0), 't2.medium': InstanceType(name='t2.medium', cores=2, memory=4.0, disks=0, disk_capacity=0), 't2.micro': InstanceType(name='t2.micro', cores=1, memory=1.0, disks=0, disk_capacity=0), 't2.nano': InstanceType(name='t2.nano', cores=1, memory=0.5, disks=0, disk_capacity=0), 't2.small': InstanceType(name='t2.small', cores=1, memory=2.0, disks=0, disk_capacity=0), 't2.xlarge': InstanceType(name='t2.xlarge', cores=4, memory=16.0, disks=0, disk_capacity=0), 't3.2xlarge': InstanceType(name='t3.2xlarge', cores=8, memory=32.0, disks=0, disk_capacity=0), 't3.large': InstanceType(name='t3.large', cores=2, memory=8.0, disks=0, disk_capacity=0), 't3.medium': InstanceType(name='t3.medium', cores=2, memory=4.0, disks=0, disk_capacity=0), 't3.micro': InstanceType(name='t3.micro', cores=2, memory=1.0, disks=0, disk_capacity=0), 't3.nano': InstanceType(name='t3.nano', cores=2, memory=0.5, disks=0, disk_capacity=0), 't3.small': InstanceType(name='t3.small', cores=2, memory=2.0, disks=0, disk_capacity=0), 't3.xlarge': InstanceType(name='t3.xlarge', cores=4, memory=16.0, disks=0, disk_capacity=0), 't3a.2xlarge': InstanceType(name='t3a.2xlarge', cores=8, memory=32.0, disks=0, disk_capacity=0), 't3a.large': InstanceType(name='t3a.large', cores=2, memory=8.0, disks=0, disk_capacity=0), 't3a.medium': InstanceType(name='t3a.medium', cores=2, memory=4.0, disks=0, disk_capacity=0), 't3a.micro': InstanceType(name='t3a.micro', cores=2, memory=1.0, disks=0, disk_capacity=0), 't3a.nano': InstanceType(name='t3a.nano', cores=2, memory=0.5, disks=0, disk_capacity=0), 't3a.small': InstanceType(name='t3a.small', cores=2, memory=2.0, disks=0, disk_capacity=0), 't3a.xlarge': InstanceType(name='t3a.xlarge', cores=4, memory=16.0, disks=0, disk_capacity=0), 'x1.16xlarge': InstanceType(name='x1.16xlarge', cores=64, memory=976.0, disks=1.0, disk_capacity=1920.0), 'x1.32xlarge': InstanceType(name='x1.32xlarge', cores=128, memory=1952.0, disks=2.0, disk_capacity=1920.0), 'x1e.16xlarge': InstanceType(name='x1e.16xlarge', cores=64, memory=1952.0, disks=1.0, disk_capacity=1920.0), 'x1e.2xlarge': InstanceType(name='x1e.2xlarge', cores=8, memory=244.0, disks=1.0, disk_capacity=240.0), 'x1e.32xlarge': InstanceType(name='x1e.32xlarge', cores=128, memory=3904.0, disks=2.0, disk_capacity=1920.0), 'x1e.4xlarge': InstanceType(name='x1e.4xlarge', cores=16, memory=488.0, disks=1.0, disk_capacity=480.0), 'x1e.8xlarge': InstanceType(name='x1e.8xlarge', cores=32, memory=976.0, disks=1.0, disk_capacity=960.0), 'x1e.xlarge': InstanceType(name='x1e.xlarge', cores=4, memory=122.0, disks=1.0, disk_capacity=120.0), 'z1d.12xlarge': InstanceType(name='z1d.12xlarge', cores=48, memory=384.0, disks=2.0, disk_capacity=900.0), 'z1d.2xlarge': InstanceType(name='z1d.2xlarge', cores=8, memory=64.0, disks=1.0, disk_capacity=300.0), 'z1d.3xlarge': InstanceType(name='z1d.3xlarge', cores=12, memory=96.0, disks=1.0, disk_capacity=450.0), 'z1d.6xlarge': InstanceType(name='z1d.6xlarge', cores=24, memory=192.0, disks=1.0, disk_capacity=900.0), 'z1d.large': InstanceType(name='z1d.large', cores=2, memory=16.0, disks=1.0, disk_capacity=75.0), 'z1d.metal': InstanceType(name='z1d.metal', cores=48, memory=384.0, disks=2.0, disk_capacity=900.0), 'z1d.xlarge': InstanceType(name='z1d.xlarge', cores=4, memory=32.0, disks=1.0, disk_capacity=150.0), } regionDict = { 'us-west-1': ['c1.medium', 'c1.xlarge', 'c3.2xlarge', 'c3.4xlarge', 'c3.8xlarge', 'c3.large', 'c3.xlarge', 'c4.2xlarge', 'c4.4xlarge', 'c4.8xlarge', 'c4.large', 'c4.xlarge', 'c5.12xlarge', 'c5.18xlarge', 'c5.24xlarge', 'c5.2xlarge', 'c5.4xlarge', 'c5.9xlarge', 'c5.large', 'c5.metal', 'c5.xlarge', 'c5d.12xlarge', 'c5d.18xlarge', 'c5d.24xlarge', 'c5d.2xlarge', 'c5d.4xlarge', 'c5d.9xlarge', 'c5d.large', 'c5d.metal', 'c5d.xlarge', 'c5n.18xlarge', 'c5n.2xlarge', 'c5n.4xlarge', 'c5n.9xlarge', 'c5n.large', 'c5n.metal', 'c5n.xlarge', 'd2.2xlarge', 'd2.4xlarge', 'd2.8xlarge', 'd2.xlarge', 'f1.16xlarge', 'f1.2xlarge', 'f1.4xlarge', 'g2.2xlarge', 'g2.8xlarge', 'g3.16xlarge', 'g3.4xlarge', 'g3.8xlarge', 'g3s.xlarge', 'g4dn.12xlarge', 'g4dn.16xlarge', 'g4dn.2xlarge', 'g4dn.4xlarge', 'g4dn.8xlarge', 'g4dn.xlarge', 'i2.2xlarge', 'i2.4xlarge', 'i2.8xlarge', 'i2.xlarge', 'i3.16xlarge', 'i3.2xlarge', 'i3.4xlarge', 'i3.8xlarge', 'i3.large', 'i3.metal', 'i3.xlarge', 'i3en.12xlarge', 'i3en.24xlarge', 'i3en.2xlarge', 'i3en.3xlarge', 'i3en.6xlarge', 'i3en.large', 'i3en.metal', 'i3en.xlarge', 'm1.large', 'm1.medium', 'm1.xlarge', 'm2.2xlarge', 'm2.4xlarge', 'm2.xlarge', 'm3.2xlarge', 'm3.large', 'm3.medium', 'm3.xlarge', 'm4.10xlarge', 'm4.16xlarge', 'm4.2xlarge', 'm4.4xlarge', 'm4.large', 'm4.xlarge', 'm5.12xlarge', 'm5.16xlarge', 'm5.24xlarge', 'm5.2xlarge', 'm5.4xlarge', 'm5.8xlarge', 'm5.large', 'm5.metal', 'm5.xlarge', 'm5a.12xlarge', 'm5a.16xlarge', 'm5a.24xlarge', 'm5a.2xlarge', 'm5a.4xlarge', 'm5a.8xlarge', 'm5a.large', 'm5a.xlarge', 'm5ad.12xlarge', 'm5ad.16xlarge', 'm5ad.24xlarge', 'm5ad.2xlarge', 'm5ad.4xlarge', 'm5ad.8xlarge', 'm5ad.large', 'm5ad.xlarge', 'm5d.12xlarge', 'm5d.16xlarge', 'm5d.24xlarge', 'm5d.2xlarge', 'm5d.4xlarge', 'm5d.8xlarge', 'm5d.large', 'm5d.metal', 'm5d.xlarge', 'r3.2xlarge', 'r3.4xlarge', 'r3.8xlarge', 'r3.large', 'r3.xlarge', 'r4.16xlarge', 'r4.2xlarge', 'r4.4xlarge', 'r4.8xlarge', 'r4.large', 'r4.xlarge', 'r5.12xlarge', 'r5.16xlarge', 'r5.24xlarge', 'r5.2xlarge', 'r5.4xlarge', 'r5.8xlarge', 'r5.large', 'r5.metal', 'r5.xlarge', 'r5a.12xlarge', 'r5a.16xlarge', 'r5a.24xlarge', 'r5a.2xlarge', 'r5a.4xlarge', 'r5a.8xlarge', 'r5a.large', 'r5a.xlarge', 'r5ad.12xlarge', 'r5ad.16xlarge', 'r5ad.24xlarge', 'r5ad.2xlarge', 'r5ad.4xlarge', 'r5ad.8xlarge', 'r5ad.large', 'r5ad.xlarge', 'r5d.12xlarge', 'r5d.16xlarge', 'r5d.24xlarge', 'r5d.2xlarge', 'r5d.4xlarge', 'r5d.8xlarge', 'r5d.large', 'r5d.metal', 'r5d.xlarge', 't1.micro', 't2.2xlarge', 't2.large', 't2.medium', 't2.micro', 't2.nano', 't2.small', 't2.xlarge', 't3.2xlarge', 't3.large', 't3.medium', 't3.micro', 't3.nano', 't3.small', 't3.xlarge', 't3a.2xlarge', 't3a.large', 't3a.medium', 't3a.micro', 't3a.nano', 't3a.small', 't3a.xlarge', 'z1d.12xlarge', 'z1d.2xlarge', 'z1d.3xlarge', 'z1d.6xlarge', 'z1d.large', 'z1d.metal', 'z1d.xlarge'], 'us-west-2': ['a1.2xlarge', 'a1.4xlarge', 'a1.large', 'a1.medium', 'a1.metal', 'a1.xlarge', 'c1.medium', 'c1.xlarge', 'c3.2xlarge', 'c3.4xlarge', 'c3.8xlarge', 'c3.large', 'c3.xlarge', 'c4.2xlarge', 'c4.4xlarge', 'c4.8xlarge', 'c4.large', 'c4.xlarge', 'c5.12xlarge', 'c5.18xlarge', 'c5.24xlarge', 'c5.2xlarge', 'c5.4xlarge', 'c5.9xlarge', 'c5.large', 'c5.metal', 'c5.xlarge', 'c5d.12xlarge', 'c5d.18xlarge', 'c5d.24xlarge', 'c5d.2xlarge', 'c5d.4xlarge', 'c5d.9xlarge', 'c5d.large', 'c5d.metal', 'c5d.xlarge', 'c5n.18xlarge', 'c5n.2xlarge', 'c5n.4xlarge', 'c5n.9xlarge', 'c5n.large', 'c5n.metal', 'c5n.xlarge', 'cc2.8xlarge', 'cr1.8xlarge', 'd2.2xlarge', 'd2.4xlarge', 'd2.8xlarge', 'd2.xlarge', 'f1.16xlarge', 'f1.2xlarge', 'f1.4xlarge', 'g2.2xlarge', 'g2.8xlarge', 'g3.16xlarge', 'g3.4xlarge', 'g3.8xlarge', 'g3s.xlarge', 'g4dn.12xlarge', 'g4dn.16xlarge', 'g4dn.2xlarge', 'g4dn.4xlarge', 'g4dn.8xlarge', 'g4dn.xlarge', 'h1.16xlarge', 'h1.2xlarge', 'h1.4xlarge', 'h1.8xlarge', 'hs1.8xlarge', 'i2.2xlarge', 'i2.4xlarge', 'i2.8xlarge', 'i2.xlarge', 'i3.16xlarge', 'i3.2xlarge', 'i3.4xlarge', 'i3.8xlarge', 'i3.large', 'i3.metal', 'i3.xlarge', 'i3en.12xlarge', 'i3en.24xlarge', 'i3en.2xlarge', 'i3en.3xlarge', 'i3en.6xlarge', 'i3en.large', 'i3en.metal', 'i3en.xlarge', 'inf1.24xlarge', 'inf1.2xlarge', 'inf1.6xlarge', 'inf1.xlarge', 'm1.large', 'm1.medium', 'm1.xlarge', 'm2.2xlarge', 'm2.4xlarge', 'm2.xlarge', 'm3.2xlarge', 'm3.large', 'm3.medium', 'm3.xlarge', 'm4.10xlarge', 'm4.16xlarge', 'm4.2xlarge', 'm4.4xlarge', 'm4.large', 'm4.xlarge', 'm5.12xlarge', 'm5.16xlarge', 'm5.24xlarge', 'm5.2xlarge', 'm5.4xlarge', 'm5.8xlarge', 'm5.large', 'm5.metal', 'm5.xlarge', 'm5a.12xlarge', 'm5a.16xlarge', 'm5a.24xlarge', 'm5a.2xlarge', 'm5a.4xlarge', 'm5a.8xlarge', 'm5a.large', 'm5a.xlarge', 'm5ad.12xlarge', 'm5ad.16xlarge', 'm5ad.24xlarge', 'm5ad.2xlarge', 'm5ad.4xlarge', 'm5ad.8xlarge', 'm5ad.large', 'm5ad.xlarge', 'm5d.12xlarge', 'm5d.16xlarge', 'm5d.24xlarge', 'm5d.2xlarge', 'm5d.4xlarge', 'm5d.8xlarge', 'm5d.large', 'm5d.metal', 'm5d.xlarge', 'm5dn.12xlarge', 'm5dn.16xlarge', 'm5dn.24xlarge', 'm5dn.2xlarge', 'm5dn.4xlarge', 'm5dn.8xlarge', 'm5dn.large', 'm5dn.xlarge', 'm5n.12xlarge', 'm5n.16xlarge', 'm5n.24xlarge', 'm5n.2xlarge', 'm5n.4xlarge', 'm5n.8xlarge', 'm5n.large', 'm5n.xlarge', 'p2.16xlarge', 'p2.8xlarge', 'p2.xlarge', 'p3.16xlarge', 'p3.2xlarge', 'p3.8xlarge', 'p3dn.24xlarge', 'r3.2xlarge', 'r3.4xlarge', 'r3.8xlarge', 'r3.large', 'r3.xlarge', 'r4.16xlarge', 'r4.2xlarge', 'r4.4xlarge', 'r4.8xlarge', 'r4.large', 'r4.xlarge', 'r5.12xlarge', 'r5.16xlarge', 'r5.24xlarge', 'r5.2xlarge', 'r5.4xlarge', 'r5.8xlarge', 'r5.large', 'r5.metal', 'r5.xlarge', 'r5a.12xlarge', 'r5a.16xlarge', 'r5a.24xlarge', 'r5a.2xlarge', 'r5a.4xlarge', 'r5a.8xlarge', 'r5a.large', 'r5a.xlarge', 'r5ad.12xlarge', 'r5ad.16xlarge', 'r5ad.24xlarge', 'r5ad.2xlarge', 'r5ad.4xlarge', 'r5ad.8xlarge', 'r5ad.large', 'r5ad.xlarge', 'r5d.12xlarge', 'r5d.16xlarge', 'r5d.24xlarge', 'r5d.2xlarge', 'r5d.4xlarge', 'r5d.8xlarge', 'r5d.large', 'r5d.metal', 'r5d.xlarge', 'r5dn.12xlarge', 'r5dn.16xlarge', 'r5dn.24xlarge', 'r5dn.2xlarge', 'r5dn.4xlarge', 'r5dn.8xlarge', 'r5dn.large', 'r5dn.xlarge', 'r5n.12xlarge', 'r5n.16xlarge', 'r5n.24xlarge', 'r5n.2xlarge', 'r5n.4xlarge', 'r5n.8xlarge', 'r5n.large', 'r5n.xlarge', 't1.micro', 't2.2xlarge', 't2.large', 't2.medium', 't2.micro', 't2.nano', 't2.small', 't2.xlarge', 't3.2xlarge', 't3.large', 't3.medium', 't3.micro', 't3.nano', 't3.small', 't3.xlarge', 't3a.2xlarge', 't3a.large', 't3a.medium', 't3a.micro', 't3a.nano', 't3a.small', 't3a.xlarge', 'x1.16xlarge', 'x1.32xlarge', 'x1e.16xlarge', 'x1e.2xlarge', 'x1e.32xlarge', 'x1e.4xlarge', 'x1e.8xlarge', 'x1e.xlarge', 'z1d.12xlarge', 'z1d.2xlarge', 'z1d.3xlarge', 'z1d.6xlarge', 'z1d.large', 'z1d.metal', 'z1d.xlarge'], 'us-east-1': ['a1.2xlarge', 'a1.4xlarge', 'a1.large', 'a1.medium', 'a1.metal', 'a1.xlarge', 'c1.medium', 'c1.xlarge', 'c3.2xlarge', 'c3.4xlarge', 'c3.8xlarge', 'c3.large', 'c3.xlarge', 'c4.2xlarge', 'c4.4xlarge', 'c4.8xlarge', 'c4.large', 'c4.xlarge', 'c5.12xlarge', 'c5.18xlarge', 'c5.24xlarge', 'c5.2xlarge', 'c5.4xlarge', 'c5.9xlarge', 'c5.large', 'c5.metal', 'c5.xlarge', 'c5d.12xlarge', 'c5d.18xlarge', 'c5d.24xlarge', 'c5d.2xlarge', 'c5d.4xlarge', 'c5d.9xlarge', 'c5d.large', 'c5d.metal', 'c5d.xlarge', 'c5n.18xlarge', 'c5n.2xlarge', 'c5n.4xlarge', 'c5n.9xlarge', 'c5n.large', 'c5n.metal', 'c5n.xlarge', 'cc2.8xlarge', 'cr1.8xlarge', 'd2.2xlarge', 'd2.4xlarge', 'd2.8xlarge', 'd2.xlarge', 'f1.16xlarge', 'f1.2xlarge', 'f1.4xlarge', 'g2.2xlarge', 'g2.8xlarge', 'g3.16xlarge', 'g3.4xlarge', 'g3.8xlarge', 'g3s.xlarge', 'g4dn.12xlarge', 'g4dn.16xlarge', 'g4dn.2xlarge', 'g4dn.4xlarge', 'g4dn.8xlarge', 'g4dn.xlarge', 'h1.16xlarge', 'h1.2xlarge', 'h1.4xlarge', 'h1.8xlarge', 'hs1.8xlarge', 'i2.2xlarge', 'i2.4xlarge', 'i2.8xlarge', 'i2.xlarge', 'i3.16xlarge', 'i3.2xlarge', 'i3.4xlarge', 'i3.8xlarge', 'i3.large', 'i3.metal', 'i3.xlarge', 'i3en.12xlarge', 'i3en.24xlarge', 'i3en.2xlarge', 'i3en.3xlarge', 'i3en.6xlarge', 'i3en.large', 'i3en.metal', 'i3en.xlarge', 'inf1.24xlarge', 'inf1.2xlarge', 'inf1.6xlarge', 'inf1.xlarge', 'm1.large', 'm1.medium', 'm1.xlarge', 'm2.2xlarge', 'm2.4xlarge', 'm2.xlarge', 'm3.2xlarge', 'm3.large', 'm3.medium', 'm3.xlarge', 'm4.10xlarge', 'm4.16xlarge', 'm4.2xlarge', 'm4.4xlarge', 'm4.large', 'm4.xlarge', 'm5.12xlarge', 'm5.16xlarge', 'm5.24xlarge', 'm5.2xlarge', 'm5.4xlarge', 'm5.8xlarge', 'm5.large', 'm5.metal', 'm5.xlarge', 'm5a.12xlarge', 'm5a.16xlarge', 'm5a.24xlarge', 'm5a.2xlarge', 'm5a.4xlarge', 'm5a.8xlarge', 'm5a.large', 'm5a.xlarge', 'm5ad.12xlarge', 'm5ad.24xlarge', 'm5ad.2xlarge', 'm5ad.4xlarge', 'm5ad.large', 'm5ad.xlarge', 'm5d.12xlarge', 'm5d.16xlarge', 'm5d.24xlarge', 'm5d.2xlarge', 'm5d.4xlarge', 'm5d.8xlarge', 'm5d.large', 'm5d.metal', 'm5d.xlarge', 'm5dn.12xlarge', 'm5dn.16xlarge', 'm5dn.24xlarge', 'm5dn.2xlarge', 'm5dn.4xlarge', 'm5dn.8xlarge', 'm5dn.large', 'm5dn.xlarge', 'm5n.12xlarge', 'm5n.16xlarge', 'm5n.24xlarge', 'm5n.2xlarge', 'm5n.4xlarge', 'm5n.8xlarge', 'm5n.large', 'm5n.xlarge', 'm6g.12xlarge', 'm6g.16xlarge', 'm6g.2xlarge', 'm6g.4xlarge', 'm6g.8xlarge', 'm6g.large', 'm6g.medium', 'm6g.xlarge', 'p2.16xlarge', 'p2.8xlarge', 'p2.xlarge', 'p3.16xlarge', 'p3.2xlarge', 'p3.8xlarge', 'p3dn.24xlarge', 'r3.2xlarge', 'r3.4xlarge', 'r3.8xlarge', 'r3.large', 'r3.xlarge', 'r4.16xlarge', 'r4.2xlarge', 'r4.4xlarge', 'r4.8xlarge', 'r4.large', 'r4.xlarge', 'r5.12xlarge', 'r5.16xlarge', 'r5.24xlarge', 'r5.2xlarge', 'r5.4xlarge', 'r5.8xlarge', 'r5.large', 'r5.metal', 'r5.xlarge', 'r5a.12xlarge', 'r5a.16xlarge', 'r5a.24xlarge', 'r5a.2xlarge', 'r5a.4xlarge', 'r5a.8xlarge', 'r5a.large', 'r5a.xlarge', 'r5ad.12xlarge', 'r5ad.24xlarge', 'r5ad.2xlarge', 'r5ad.4xlarge', 'r5ad.large', 'r5ad.xlarge', 'r5d.12xlarge', 'r5d.16xlarge', 'r5d.24xlarge', 'r5d.2xlarge', 'r5d.4xlarge', 'r5d.8xlarge', 'r5d.large', 'r5d.metal', 'r5d.xlarge', 'r5dn.12xlarge', 'r5dn.16xlarge', 'r5dn.24xlarge', 'r5dn.2xlarge', 'r5dn.4xlarge', 'r5dn.8xlarge', 'r5dn.large', 'r5dn.xlarge', 'r5n.12xlarge', 'r5n.16xlarge', 'r5n.24xlarge', 'r5n.2xlarge', 'r5n.4xlarge', 'r5n.8xlarge', 'r5n.large', 'r5n.xlarge', 't1.micro', 't2.2xlarge', 't2.large', 't2.medium', 't2.micro', 't2.nano', 't2.small', 't2.xlarge', 't3.2xlarge', 't3.large', 't3.medium', 't3.micro', 't3.nano', 't3.small', 't3.xlarge', 't3a.2xlarge', 't3a.large', 't3a.medium', 't3a.micro', 't3a.nano', 't3a.small', 't3a.xlarge', 'x1.16xlarge', 'x1.32xlarge', 'x1e.16xlarge', 'x1e.2xlarge', 'x1e.32xlarge', 'x1e.4xlarge', 'x1e.8xlarge', 'x1e.xlarge', 'z1d.12xlarge', 'z1d.2xlarge', 'z1d.3xlarge', 'z1d.6xlarge', 'z1d.large', 'z1d.metal', 'z1d.xlarge'], 'us-east-2': ['a1.2xlarge', 'a1.4xlarge', 'a1.large', 'a1.medium', 'a1.metal', 'a1.xlarge', 'c4.2xlarge', 'c4.4xlarge', 'c4.8xlarge', 'c4.large', 'c4.xlarge', 'c5.12xlarge', 'c5.18xlarge', 'c5.24xlarge', 'c5.2xlarge', 'c5.4xlarge', 'c5.9xlarge', 'c5.large', 'c5.metal', 'c5.xlarge', 'c5d.12xlarge', 'c5d.18xlarge', 'c5d.24xlarge', 'c5d.2xlarge', 'c5d.4xlarge', 'c5d.9xlarge', 'c5d.large', 'c5d.metal', 'c5d.xlarge', 'c5n.18xlarge', 'c5n.2xlarge', 'c5n.4xlarge', 'c5n.9xlarge', 'c5n.large', 'c5n.metal', 'c5n.xlarge', 'd2.2xlarge', 'd2.4xlarge', 'd2.8xlarge', 'd2.xlarge', 'g3.16xlarge', 'g3.4xlarge', 'g3.8xlarge', 'g3s.xlarge', 'g4dn.12xlarge', 'g4dn.16xlarge', 'g4dn.2xlarge', 'g4dn.4xlarge', 'g4dn.8xlarge', 'g4dn.xlarge', 'h1.16xlarge', 'h1.2xlarge', 'h1.4xlarge', 'h1.8xlarge', 'i2.2xlarge', 'i2.4xlarge', 'i2.8xlarge', 'i2.xlarge', 'i3.16xlarge', 'i3.2xlarge', 'i3.4xlarge', 'i3.8xlarge', 'i3.large', 'i3.metal', 'i3.xlarge', 'i3en.12xlarge', 'i3en.24xlarge', 'i3en.2xlarge', 'i3en.3xlarge', 'i3en.6xlarge', 'i3en.large', 'i3en.metal', 'i3en.xlarge', 'm4.10xlarge', 'm4.16xlarge', 'm4.2xlarge', 'm4.4xlarge', 'm4.large', 'm4.xlarge', 'm5.12xlarge', 'm5.16xlarge', 'm5.24xlarge', 'm5.2xlarge', 'm5.4xlarge', 'm5.8xlarge', 'm5.large', 'm5.metal', 'm5.xlarge', 'm5a.12xlarge', 'm5a.16xlarge', 'm5a.24xlarge', 'm5a.2xlarge', 'm5a.4xlarge', 'm5a.8xlarge', 'm5a.large', 'm5a.xlarge', 'm5ad.12xlarge', 'm5ad.24xlarge', 'm5ad.2xlarge', 'm5ad.4xlarge', 'm5ad.large', 'm5ad.xlarge', 'm5d.12xlarge', 'm5d.16xlarge', 'm5d.24xlarge', 'm5d.2xlarge', 'm5d.4xlarge', 'm5d.8xlarge', 'm5d.large', 'm5d.metal', 'm5d.xlarge', 'm5dn.12xlarge', 'm5dn.16xlarge', 'm5dn.24xlarge', 'm5dn.2xlarge', 'm5dn.4xlarge', 'm5dn.8xlarge', 'm5dn.large', 'm5dn.xlarge', 'm5n.12xlarge', 'm5n.16xlarge', 'm5n.24xlarge', 'm5n.2xlarge', 'm5n.4xlarge', 'm5n.8xlarge', 'm5n.large', 'm5n.xlarge', 'p2.16xlarge', 'p2.8xlarge', 'p2.xlarge', 'p3.16xlarge', 'p3.2xlarge', 'p3.8xlarge', 'r3.2xlarge', 'r3.4xlarge', 'r3.8xlarge', 'r3.large', 'r3.xlarge', 'r4.16xlarge', 'r4.2xlarge', 'r4.4xlarge', 'r4.8xlarge', 'r4.large', 'r4.xlarge', 'r5.12xlarge', 'r5.16xlarge', 'r5.24xlarge', 'r5.2xlarge', 'r5.4xlarge', 'r5.8xlarge', 'r5.large', 'r5.metal', 'r5.xlarge', 'r5a.12xlarge', 'r5a.16xlarge', 'r5a.24xlarge', 'r5a.2xlarge', 'r5a.4xlarge', 'r5a.8xlarge', 'r5a.large', 'r5a.xlarge', 'r5ad.12xlarge', 'r5ad.24xlarge', 'r5ad.2xlarge', 'r5ad.4xlarge', 'r5ad.large', 'r5ad.xlarge', 'r5d.12xlarge', 'r5d.16xlarge', 'r5d.24xlarge', 'r5d.2xlarge', 'r5d.4xlarge', 'r5d.8xlarge', 'r5d.large', 'r5d.metal', 'r5d.xlarge', 'r5dn.12xlarge', 'r5dn.16xlarge', 'r5dn.24xlarge', 'r5dn.2xlarge', 'r5dn.4xlarge', 'r5dn.8xlarge', 'r5dn.large', 'r5dn.xlarge', 'r5n.12xlarge', 'r5n.16xlarge', 'r5n.24xlarge', 'r5n.2xlarge', 'r5n.4xlarge', 'r5n.8xlarge', 'r5n.large', 'r5n.xlarge', 't2.2xlarge', 't2.large', 't2.medium', 't2.micro', 't2.nano', 't2.small', 't2.xlarge', 't3.2xlarge', 't3.large', 't3.medium', 't3.micro', 't3.nano', 't3.small', 't3.xlarge', 't3a.2xlarge', 't3a.large', 't3a.medium', 't3a.micro', 't3a.nano', 't3a.small', 't3a.xlarge', 'x1.16xlarge', 'x1.32xlarge', 'x1e.16xlarge', 'x1e.2xlarge', 'x1e.32xlarge', 'x1e.4xlarge', 'x1e.8xlarge', 'x1e.xlarge', 'z1d.12xlarge', 'z1d.2xlarge', 'z1d.3xlarge', 'z1d.6xlarge', 'z1d.large', 'z1d.metal', 'z1d.xlarge'], 'us-gov-west-1': ['c1.medium', 'c1.xlarge', 'c3.2xlarge', 'c3.4xlarge', 'c3.8xlarge', 'c3.large', 'c3.xlarge', 'c4.2xlarge', 'c4.4xlarge', 'c4.8xlarge', 'c4.large', 'c4.xlarge', 'c5.12xlarge', 'c5.18xlarge', 'c5.24xlarge', 'c5.2xlarge', 'c5.4xlarge', 'c5.9xlarge', 'c5.large', 'c5.metal', 'c5.xlarge', 'c5d.12xlarge', 'c5d.18xlarge', 'c5d.24xlarge', 'c5d.2xlarge', 'c5d.4xlarge', 'c5d.9xlarge', 'c5d.large', 'c5d.metal', 'c5d.xlarge', 'c5n.18xlarge', 'c5n.2xlarge', 'c5n.4xlarge', 'c5n.9xlarge', 'c5n.large', 'c5n.metal', 'c5n.xlarge', 'cc2.8xlarge', 'd2.2xlarge', 'd2.4xlarge', 'd2.8xlarge', 'd2.xlarge', 'f1.16xlarge', 'f1.2xlarge', 'f1.4xlarge', 'g3.16xlarge', 'g3.4xlarge', 'g3.8xlarge', 'g4dn.12xlarge', 'g4dn.16xlarge', 'g4dn.2xlarge', 'g4dn.4xlarge', 'g4dn.8xlarge', 'g4dn.xlarge', 'hs1.8xlarge', 'i2.2xlarge', 'i2.4xlarge', 'i2.8xlarge', 'i2.xlarge', 'i3.16xlarge', 'i3.2xlarge', 'i3.4xlarge', 'i3.8xlarge', 'i3.large', 'i3.metal', 'i3.xlarge', 'i3en.12xlarge', 'i3en.24xlarge', 'i3en.2xlarge', 'i3en.3xlarge', 'i3en.6xlarge', 'i3en.large', 'i3en.xlarge', 'm1.large', 'm1.medium', 'm1.xlarge', 'm2.2xlarge', 'm2.4xlarge', 'm2.xlarge', 'm3.2xlarge', 'm3.large', 'm3.medium', 'm3.xlarge', 'm4.10xlarge', 'm4.16xlarge', 'm4.2xlarge', 'm4.4xlarge', 'm4.large', 'm4.xlarge', 'm5.12xlarge', 'm5.16xlarge', 'm5.24xlarge', 'm5.2xlarge', 'm5.4xlarge', 'm5.8xlarge', 'm5.large', 'm5.metal', 'm5.xlarge', 'm5a.12xlarge', 'm5a.16xlarge', 'm5a.24xlarge', 'm5a.2xlarge', 'm5a.4xlarge', 'm5a.8xlarge', 'm5a.large', 'm5a.xlarge', 'm5ad.12xlarge', 'm5ad.16xlarge', 'm5ad.24xlarge', 'm5ad.2xlarge', 'm5ad.4xlarge', 'm5ad.8xlarge', 'm5ad.large', 'm5ad.xlarge', 'm5d.12xlarge', 'm5d.16xlarge', 'm5d.24xlarge', 'm5d.2xlarge', 'm5d.4xlarge', 'm5d.8xlarge', 'm5d.large', 'm5d.metal', 'm5d.xlarge', 'p2.16xlarge', 'p2.8xlarge', 'p2.xlarge', 'p3.16xlarge', 'p3.2xlarge', 'p3.8xlarge', 'p3dn.24xlarge', 'r3.2xlarge', 'r3.4xlarge', 'r3.8xlarge', 'r3.large', 'r3.xlarge', 'r4.16xlarge', 'r4.2xlarge', 'r4.4xlarge', 'r4.8xlarge', 'r4.large', 'r4.xlarge', 'r5.12xlarge', 'r5.16xlarge', 'r5.24xlarge', 'r5.2xlarge', 'r5.4xlarge', 'r5.8xlarge', 'r5.large', 'r5.metal', 'r5.xlarge', 'r5a.12xlarge', 'r5a.16xlarge', 'r5a.24xlarge', 'r5a.2xlarge', 'r5a.4xlarge', 'r5a.8xlarge', 'r5a.large', 'r5a.xlarge', 'r5ad.12xlarge', 'r5ad.16xlarge', 'r5ad.24xlarge', 'r5ad.2xlarge', 'r5ad.4xlarge', 'r5ad.8xlarge', 'r5ad.large', 'r5ad.xlarge', 'r5d.12xlarge', 'r5d.16xlarge', 'r5d.24xlarge', 'r5d.2xlarge', 'r5d.4xlarge', 'r5d.8xlarge', 'r5d.large', 'r5d.metal', 'r5d.xlarge', 't1.micro', 't2.2xlarge', 't2.large', 't2.medium', 't2.micro', 't2.nano', 't2.small', 't2.xlarge', 't3.2xlarge', 't3.large', 't3.medium', 't3.micro', 't3.nano', 't3.small', 't3.xlarge', 't3a.2xlarge', 't3a.large', 't3a.medium', 't3a.micro', 't3a.nano', 't3a.small', 't3a.xlarge', 'x1.16xlarge', 'x1.32xlarge', 'x1e.16xlarge', 'x1e.2xlarge', 'x1e.32xlarge', 'x1e.4xlarge', 'x1e.8xlarge', 'x1e.xlarge'], 'ca-central-1': ['c4.2xlarge', 'c4.4xlarge', 'c4.8xlarge', 'c4.large', 'c4.xlarge', 'c5.12xlarge', 'c5.18xlarge', 'c5.24xlarge', 'c5.2xlarge', 'c5.4xlarge', 'c5.9xlarge', 'c5.large', 'c5.metal', 'c5.xlarge', 'c5d.12xlarge', 'c5d.18xlarge', 'c5d.24xlarge', 'c5d.2xlarge', 'c5d.4xlarge', 'c5d.9xlarge', 'c5d.large', 'c5d.metal', 'c5d.xlarge', 'c5n.18xlarge', 'c5n.2xlarge', 'c5n.4xlarge', 'c5n.9xlarge', 'c5n.large', 'c5n.metal', 'c5n.xlarge', 'd2.2xlarge', 'd2.4xlarge', 'd2.8xlarge', 'd2.xlarge', 'g3.16xlarge', 'g3.4xlarge', 'g3.8xlarge', 'g4dn.12xlarge', 'g4dn.16xlarge', 'g4dn.2xlarge', 'g4dn.4xlarge', 'g4dn.8xlarge', 'g4dn.xlarge', 'i3.16xlarge', 'i3.2xlarge', 'i3.4xlarge', 'i3.8xlarge', 'i3.large', 'i3.xlarge', 'i3en.12xlarge', 'i3en.24xlarge', 'i3en.2xlarge', 'i3en.3xlarge', 'i3en.6xlarge', 'i3en.large', 'i3en.metal', 'i3en.xlarge', 'm4.10xlarge', 'm4.16xlarge', 'm4.2xlarge', 'm4.4xlarge', 'm4.large', 'm4.xlarge', 'm5.12xlarge', 'm5.16xlarge', 'm5.24xlarge', 'm5.2xlarge', 'm5.4xlarge', 'm5.8xlarge', 'm5.large', 'm5.metal', 'm5.xlarge', 'm5a.12xlarge', 'm5a.16xlarge', 'm5a.24xlarge', 'm5a.2xlarge', 'm5a.4xlarge', 'm5a.8xlarge', 'm5a.large', 'm5a.xlarge', 'm5ad.12xlarge', 'm5ad.16xlarge', 'm5ad.24xlarge', 'm5ad.2xlarge', 'm5ad.4xlarge', 'm5ad.8xlarge', 'm5ad.large', 'm5ad.xlarge', 'm5d.12xlarge', 'm5d.16xlarge', 'm5d.24xlarge', 'm5d.2xlarge', 'm5d.4xlarge', 'm5d.8xlarge', 'm5d.large', 'm5d.metal', 'm5d.xlarge', 'p3.16xlarge', 'p3.2xlarge', 'p3.8xlarge', 'r4.16xlarge', 'r4.2xlarge', 'r4.4xlarge', 'r4.8xlarge', 'r4.large', 'r4.xlarge', 'r5.12xlarge', 'r5.16xlarge', 'r5.24xlarge', 'r5.2xlarge', 'r5.4xlarge', 'r5.8xlarge', 'r5.large', 'r5.metal', 'r5.xlarge', 'r5a.12xlarge', 'r5a.16xlarge', 'r5a.24xlarge', 'r5a.2xlarge', 'r5a.4xlarge', 'r5a.8xlarge', 'r5a.large', 'r5a.xlarge', 'r5ad.12xlarge', 'r5ad.16xlarge', 'r5ad.24xlarge', 'r5ad.2xlarge', 'r5ad.4xlarge', 'r5ad.8xlarge', 'r5ad.large', 'r5ad.xlarge', 'r5d.12xlarge', 'r5d.16xlarge', 'r5d.24xlarge', 'r5d.2xlarge', 'r5d.4xlarge', 'r5d.8xlarge', 'r5d.large', 'r5d.metal', 'r5d.xlarge', 't2.2xlarge', 't2.large', 't2.medium', 't2.micro', 't2.nano', 't2.small', 't2.xlarge', 't3.2xlarge', 't3.large', 't3.medium', 't3.micro', 't3.nano', 't3.small', 't3.xlarge', 't3a.2xlarge', 't3a.large', 't3a.medium', 't3a.micro', 't3a.nano', 't3a.small', 't3a.xlarge', 'x1.16xlarge', 'x1.32xlarge', 'x1e.16xlarge', 'x1e.2xlarge', 'x1e.32xlarge', 'x1e.4xlarge', 'x1e.8xlarge', 'x1e.xlarge'], 'ap-northeast-1': ['a1.2xlarge', 'a1.4xlarge', 'a1.large', 'a1.medium', 'a1.metal', 'a1.xlarge', 'c1.medium', 'c1.xlarge', 'c3.2xlarge', 'c3.4xlarge', 'c3.8xlarge', 'c3.large', 'c3.xlarge', 'c4.2xlarge', 'c4.4xlarge', 'c4.8xlarge', 'c4.large', 'c4.xlarge', 'c5.12xlarge', 'c5.18xlarge', 'c5.24xlarge', 'c5.2xlarge', 'c5.4xlarge', 'c5.9xlarge', 'c5.large', 'c5.metal', 'c5.xlarge', 'c5d.12xlarge', 'c5d.18xlarge', 'c5d.24xlarge', 'c5d.2xlarge', 'c5d.4xlarge', 'c5d.9xlarge', 'c5d.large', 'c5d.metal', 'c5d.xlarge', 'c5n.18xlarge', 'c5n.2xlarge', 'c5n.4xlarge', 'c5n.9xlarge', 'c5n.large', 'c5n.metal', 'c5n.xlarge', 'cc2.8xlarge', 'cr1.8xlarge', 'd2.2xlarge', 'd2.4xlarge', 'd2.8xlarge', 'd2.xlarge', 'g2.2xlarge', 'g2.8xlarge', 'g3.16xlarge', 'g3.4xlarge', 'g3.8xlarge', 'g3s.xlarge', 'g4dn.12xlarge', 'g4dn.16xlarge', 'g4dn.2xlarge', 'g4dn.4xlarge', 'g4dn.8xlarge', 'g4dn.xlarge', 'hs1.8xlarge', 'i2.2xlarge', 'i2.4xlarge', 'i2.8xlarge', 'i2.xlarge', 'i3.16xlarge', 'i3.2xlarge', 'i3.4xlarge', 'i3.8xlarge', 'i3.large', 'i3.metal', 'i3.xlarge', 'i3en.12xlarge', 'i3en.24xlarge', 'i3en.2xlarge', 'i3en.3xlarge', 'i3en.6xlarge', 'i3en.large', 'i3en.metal', 'i3en.xlarge', 'm1.large', 'm1.medium', 'm1.xlarge', 'm2.2xlarge', 'm2.4xlarge', 'm2.xlarge', 'm3.2xlarge', 'm3.large', 'm3.medium', 'm3.xlarge', 'm4.10xlarge', 'm4.16xlarge', 'm4.2xlarge', 'm4.4xlarge', 'm4.large', 'm4.xlarge', 'm5.12xlarge', 'm5.16xlarge', 'm5.24xlarge', 'm5.2xlarge', 'm5.4xlarge', 'm5.8xlarge', 'm5.large', 'm5.metal', 'm5.xlarge', 'm5a.12xlarge', 'm5a.16xlarge', 'm5a.24xlarge', 'm5a.2xlarge', 'm5a.4xlarge', 'm5a.8xlarge', 'm5a.large', 'm5a.xlarge', 'm5ad.12xlarge', 'm5ad.16xlarge', 'm5ad.24xlarge', 'm5ad.2xlarge', 'm5ad.4xlarge', 'm5ad.8xlarge', 'm5ad.large', 'm5ad.xlarge', 'm5d.12xlarge', 'm5d.16xlarge', 'm5d.24xlarge', 'm5d.2xlarge', 'm5d.4xlarge', 'm5d.8xlarge', 'm5d.large', 'm5d.metal', 'm5d.xlarge', 'm5dn.12xlarge', 'm5dn.16xlarge', 'm5dn.24xlarge', 'm5dn.2xlarge', 'm5dn.4xlarge', 'm5dn.8xlarge', 'm5dn.large', 'm5dn.xlarge', 'm5n.12xlarge', 'm5n.16xlarge', 'm5n.24xlarge', 'm5n.2xlarge', 'm5n.4xlarge', 'm5n.8xlarge', 'm5n.large', 'm5n.xlarge', 'p2.16xlarge', 'p2.8xlarge', 'p2.xlarge', 'p3.16xlarge', 'p3.2xlarge', 'p3.8xlarge', 'p3dn.24xlarge', 'r3.2xlarge', 'r3.4xlarge', 'r3.8xlarge', 'r3.large', 'r3.xlarge', 'r4.16xlarge', 'r4.2xlarge', 'r4.4xlarge', 'r4.8xlarge', 'r4.large', 'r4.xlarge', 'r5.12xlarge', 'r5.16xlarge', 'r5.24xlarge', 'r5.2xlarge', 'r5.4xlarge', 'r5.8xlarge', 'r5.large', 'r5.metal', 'r5.xlarge', 'r5a.12xlarge', 'r5a.16xlarge', 'r5a.24xlarge', 'r5a.2xlarge', 'r5a.4xlarge', 'r5a.8xlarge', 'r5a.large', 'r5a.xlarge', 'r5ad.12xlarge', 'r5ad.16xlarge', 'r5ad.24xlarge', 'r5ad.2xlarge', 'r5ad.4xlarge', 'r5ad.8xlarge', 'r5ad.large', 'r5ad.xlarge', 'r5d.12xlarge', 'r5d.16xlarge', 'r5d.24xlarge', 'r5d.2xlarge', 'r5d.4xlarge', 'r5d.8xlarge', 'r5d.large', 'r5d.metal', 'r5d.xlarge', 'r5dn.12xlarge', 'r5dn.16xlarge', 'r5dn.24xlarge', 'r5dn.2xlarge', 'r5dn.4xlarge', 'r5dn.8xlarge', 'r5dn.large', 'r5dn.xlarge', 'r5n.12xlarge', 'r5n.16xlarge', 'r5n.24xlarge', 'r5n.2xlarge', 'r5n.4xlarge', 'r5n.8xlarge', 'r5n.large', 'r5n.xlarge', 't1.micro', 't2.2xlarge', 't2.large', 't2.medium', 't2.micro', 't2.nano', 't2.small', 't2.xlarge', 't3.2xlarge', 't3.large', 't3.medium', 't3.micro', 't3.nano', 't3.small', 't3.xlarge', 't3a.2xlarge', 't3a.large', 't3a.medium', 't3a.micro', 't3a.nano', 't3a.small', 't3a.xlarge', 'x1.16xlarge', 'x1.32xlarge', 'x1e.16xlarge', 'x1e.2xlarge', 'x1e.32xlarge', 'x1e.4xlarge', 'x1e.8xlarge', 'x1e.xlarge', 'z1d.12xlarge', 'z1d.2xlarge', 'z1d.3xlarge', 'z1d.6xlarge', 'z1d.large', 'z1d.metal', 'z1d.xlarge'], 'ap-northeast-2': ['c3.2xlarge', 'c3.4xlarge', 'c3.8xlarge', 'c3.large', 'c3.xlarge', 'c4.2xlarge', 'c4.4xlarge', 'c4.8xlarge', 'c4.large', 'c4.xlarge', 'c5.12xlarge', 'c5.18xlarge', 'c5.24xlarge', 'c5.2xlarge', 'c5.4xlarge', 'c5.9xlarge', 'c5.large', 'c5.xlarge', 'c5d.12xlarge', 'c5d.18xlarge', 'c5d.24xlarge', 'c5d.2xlarge', 'c5d.4xlarge', 'c5d.9xlarge', 'c5d.large', 'c5d.metal', 'c5d.xlarge', 'c5n.18xlarge', 'c5n.2xlarge', 'c5n.4xlarge', 'c5n.9xlarge', 'c5n.large', 'c5n.metal', 'c5n.xlarge', 'd2.2xlarge', 'd2.4xlarge', 'd2.8xlarge', 'd2.xlarge', 'g2.2xlarge', 'g2.8xlarge', 'g3.16xlarge', 'g3.4xlarge', 'g3.8xlarge', 'g3s.xlarge', 'g4dn.12xlarge', 'g4dn.16xlarge', 'g4dn.2xlarge', 'g4dn.4xlarge', 'g4dn.8xlarge', 'g4dn.xlarge', 'i2.2xlarge', 'i2.4xlarge', 'i2.8xlarge', 'i2.xlarge', 'i3.16xlarge', 'i3.2xlarge', 'i3.4xlarge', 'i3.8xlarge', 'i3.large', 'i3.xlarge', 'i3en.12xlarge', 'i3en.24xlarge', 'i3en.2xlarge', 'i3en.3xlarge', 'i3en.6xlarge', 'i3en.large', 'i3en.metal', 'i3en.xlarge', 'm3.2xlarge', 'm3.large', 'm3.medium', 'm3.xlarge', 'm4.10xlarge', 'm4.16xlarge', 'm4.2xlarge', 'm4.4xlarge', 'm4.large', 'm4.xlarge', 'm5.12xlarge', 'm5.16xlarge', 'm5.24xlarge', 'm5.2xlarge', 'm5.4xlarge', 'm5.8xlarge', 'm5.large', 'm5.metal', 'm5.xlarge', 'm5a.12xlarge', 'm5a.16xlarge', 'm5a.24xlarge', 'm5a.2xlarge', 'm5a.4xlarge', 'm5a.8xlarge', 'm5a.large', 'm5a.xlarge', 'm5ad.12xlarge', 'm5ad.16xlarge', 'm5ad.24xlarge', 'm5ad.2xlarge', 'm5ad.4xlarge', 'm5ad.8xlarge', 'm5ad.large', 'm5ad.xlarge', 'm5d.12xlarge', 'm5d.16xlarge', 'm5d.24xlarge', 'm5d.2xlarge', 'm5d.4xlarge', 'm5d.8xlarge', 'm5d.large', 'm5d.metal', 'm5d.xlarge', 'p2.16xlarge', 'p2.8xlarge', 'p2.xlarge', 'p3.16xlarge', 'p3.2xlarge', 'p3.8xlarge', 'r3.2xlarge', 'r3.4xlarge', 'r3.8xlarge', 'r3.large', 'r3.xlarge', 'r4.16xlarge', 'r4.2xlarge', 'r4.4xlarge', 'r4.8xlarge', 'r4.large', 'r4.xlarge', 'r5.12xlarge', 'r5.16xlarge', 'r5.24xlarge', 'r5.2xlarge', 'r5.4xlarge', 'r5.8xlarge', 'r5.large', 'r5.metal', 'r5.xlarge', 'r5a.12xlarge', 'r5a.16xlarge', 'r5a.24xlarge', 'r5a.2xlarge', 'r5a.4xlarge', 'r5a.8xlarge', 'r5a.large', 'r5a.xlarge', 'r5ad.12xlarge', 'r5ad.16xlarge', 'r5ad.24xlarge', 'r5ad.2xlarge', 'r5ad.4xlarge', 'r5ad.8xlarge', 'r5ad.large', 'r5ad.xlarge', 'r5d.12xlarge', 'r5d.16xlarge', 'r5d.24xlarge', 'r5d.2xlarge', 'r5d.4xlarge', 'r5d.8xlarge', 'r5d.large', 'r5d.metal', 'r5d.xlarge', 't2.2xlarge', 't2.large', 't2.medium', 't2.micro', 't2.nano', 't2.small', 't2.xlarge', 't3.2xlarge', 't3.large', 't3.medium', 't3.micro', 't3.nano', 't3.small', 't3.xlarge', 't3a.2xlarge', 't3a.large', 't3a.medium', 't3a.micro', 't3a.nano', 't3a.small', 't3a.xlarge', 'x1.16xlarge', 'x1.32xlarge', 'x1e.16xlarge', 'x1e.2xlarge', 'x1e.32xlarge', 'x1e.4xlarge', 'x1e.8xlarge', 'x1e.xlarge', 'z1d.12xlarge', 'z1d.2xlarge', 'z1d.3xlarge', 'z1d.6xlarge', 'z1d.large', 'z1d.metal', 'z1d.xlarge'], 'ap-northeast-3': ['c4.2xlarge', 'c4.4xlarge', 'c4.8xlarge', 'c4.large', 'c4.xlarge', 'c5.18xlarge', 'c5.2xlarge', 'c5.4xlarge', 'c5.9xlarge', 'c5.large', 'c5.xlarge', 'c5d.18xlarge', 'c5d.2xlarge', 'c5d.4xlarge', 'c5d.9xlarge', 'c5d.large', 'c5d.xlarge', 'd2.2xlarge', 'd2.4xlarge', 'd2.8xlarge', 'd2.xlarge', 'i3.16xlarge', 'i3.2xlarge', 'i3.4xlarge', 'i3.8xlarge', 'i3.large', 'i3.xlarge', 'm4.10xlarge', 'm4.16xlarge', 'm4.2xlarge', 'm4.4xlarge', 'm4.large', 'm4.xlarge', 'm5.12xlarge', 'm5.16xlarge', 'm5.24xlarge', 'm5.2xlarge', 'm5.4xlarge', 'm5.8xlarge', 'm5.large', 'm5.metal', 'm5.xlarge', 'm5d.12xlarge', 'm5d.16xlarge', 'm5d.24xlarge', 'm5d.2xlarge', 'm5d.4xlarge', 'm5d.8xlarge', 'm5d.large', 'm5d.metal', 'm5d.xlarge', 'r4.16xlarge', 'r4.2xlarge', 'r4.4xlarge', 'r4.8xlarge', 'r4.large', 'r4.xlarge', 'r5.12xlarge', 'r5.16xlarge', 'r5.24xlarge', 'r5.2xlarge', 'r5.4xlarge', 'r5.8xlarge', 'r5.large', 'r5.metal', 'r5.xlarge', 'r5d.12xlarge', 'r5d.16xlarge', 'r5d.24xlarge', 'r5d.2xlarge', 'r5d.4xlarge', 'r5d.8xlarge', 'r5d.large', 'r5d.metal', 'r5d.xlarge', 't2.2xlarge', 't2.large', 't2.medium', 't2.micro', 't2.nano', 't2.small', 't2.xlarge', 't3.2xlarge', 't3.large', 't3.medium', 't3.micro', 't3.nano', 't3.small', 't3.xlarge'], 'ap-southeast-1': ['a1.2xlarge', 'a1.4xlarge', 'a1.large', 'a1.medium', 'a1.metal', 'a1.xlarge', 'c1.medium', 'c1.xlarge', 'c3.2xlarge', 'c3.4xlarge', 'c3.8xlarge', 'c3.large', 'c3.xlarge', 'c4.2xlarge', 'c4.4xlarge', 'c4.8xlarge', 'c4.large', 'c4.xlarge', 'c5.12xlarge', 'c5.18xlarge', 'c5.24xlarge', 'c5.2xlarge', 'c5.4xlarge', 'c5.9xlarge', 'c5.large', 'c5.metal', 'c5.xlarge', 'c5d.12xlarge', 'c5d.18xlarge', 'c5d.24xlarge', 'c5d.2xlarge', 'c5d.4xlarge', 'c5d.9xlarge', 'c5d.large', 'c5d.metal', 'c5d.xlarge', 'c5n.18xlarge', 'c5n.2xlarge', 'c5n.4xlarge', 'c5n.9xlarge', 'c5n.large', 'c5n.metal', 'c5n.xlarge', 'd2.2xlarge', 'd2.4xlarge', 'd2.8xlarge', 'd2.xlarge', 'g2.2xlarge', 'g2.8xlarge', 'g3.16xlarge', 'g3.4xlarge', 'g3.8xlarge', 'g4dn.12xlarge', 'g4dn.16xlarge', 'g4dn.2xlarge', 'g4dn.4xlarge', 'g4dn.8xlarge', 'g4dn.xlarge', 'hs1.8xlarge', 'i2.2xlarge', 'i2.4xlarge', 'i2.8xlarge', 'i2.xlarge', 'i3.16xlarge', 'i3.2xlarge', 'i3.4xlarge', 'i3.8xlarge', 'i3.large', 'i3.xlarge', 'i3en.12xlarge', 'i3en.24xlarge', 'i3en.2xlarge', 'i3en.3xlarge', 'i3en.6xlarge', 'i3en.large', 'i3en.xlarge', 'm1.large', 'm1.medium', 'm1.xlarge', 'm2.2xlarge', 'm2.4xlarge', 'm2.xlarge', 'm3.2xlarge', 'm3.large', 'm3.medium', 'm3.xlarge', 'm4.10xlarge', 'm4.16xlarge', 'm4.2xlarge', 'm4.4xlarge', 'm4.large', 'm4.xlarge', 'm5.12xlarge', 'm5.16xlarge', 'm5.24xlarge', 'm5.2xlarge', 'm5.4xlarge', 'm5.8xlarge', 'm5.large', 'm5.metal', 'm5.xlarge', 'm5a.12xlarge', 'm5a.16xlarge', 'm5a.24xlarge', 'm5a.2xlarge', 'm5a.4xlarge', 'm5a.8xlarge', 'm5a.large', 'm5a.xlarge', 'm5ad.12xlarge', 'm5ad.16xlarge', 'm5ad.24xlarge', 'm5ad.2xlarge', 'm5ad.4xlarge', 'm5ad.8xlarge', 'm5ad.large', 'm5ad.xlarge', 'm5d.12xlarge', 'm5d.16xlarge', 'm5d.24xlarge', 'm5d.2xlarge', 'm5d.4xlarge', 'm5d.8xlarge', 'm5d.large', 'm5d.metal', 'm5d.xlarge', 'm5dn.12xlarge', 'm5dn.16xlarge', 'm5dn.24xlarge', 'm5dn.2xlarge', 'm5dn.4xlarge', 'm5dn.8xlarge', 'm5dn.large', 'm5dn.xlarge', 'm5n.12xlarge', 'm5n.16xlarge', 'm5n.24xlarge', 'm5n.2xlarge', 'm5n.4xlarge', 'm5n.8xlarge', 'm5n.large', 'm5n.xlarge', 'p2.16xlarge', 'p2.8xlarge', 'p2.xlarge', 'p3.16xlarge', 'p3.2xlarge', 'p3.8xlarge', 'r3.2xlarge', 'r3.4xlarge', 'r3.8xlarge', 'r3.large', 'r3.xlarge', 'r4.16xlarge', 'r4.2xlarge', 'r4.4xlarge', 'r4.8xlarge', 'r4.large', 'r4.xlarge', 'r5.12xlarge', 'r5.16xlarge', 'r5.24xlarge', 'r5.2xlarge', 'r5.4xlarge', 'r5.8xlarge', 'r5.large', 'r5.metal', 'r5.xlarge', 'r5a.12xlarge', 'r5a.16xlarge', 'r5a.24xlarge', 'r5a.2xlarge', 'r5a.4xlarge', 'r5a.8xlarge', 'r5a.large', 'r5a.xlarge', 'r5ad.12xlarge', 'r5ad.16xlarge', 'r5ad.24xlarge', 'r5ad.2xlarge', 'r5ad.4xlarge', 'r5ad.8xlarge', 'r5ad.large', 'r5ad.xlarge', 'r5d.12xlarge', 'r5d.16xlarge', 'r5d.24xlarge', 'r5d.2xlarge', 'r5d.4xlarge', 'r5d.8xlarge', 'r5d.large', 'r5d.metal', 'r5d.xlarge', 'r5dn.12xlarge', 'r5dn.16xlarge', 'r5dn.24xlarge', 'r5dn.2xlarge', 'r5dn.4xlarge', 'r5dn.8xlarge', 'r5dn.large', 'r5dn.xlarge', 'r5n.12xlarge', 'r5n.16xlarge', 'r5n.24xlarge', 'r5n.2xlarge', 'r5n.4xlarge', 'r5n.8xlarge', 'r5n.large', 'r5n.xlarge', 't1.micro', 't2.2xlarge', 't2.large', 't2.medium', 't2.micro', 't2.nano', 't2.small', 't2.xlarge', 't3.2xlarge', 't3.large', 't3.medium', 't3.micro', 't3.nano', 't3.small', 't3.xlarge', 't3a.2xlarge', 't3a.large', 't3a.medium', 't3a.micro', 't3a.nano', 't3a.small', 't3a.xlarge', 'x1.16xlarge', 'x1.32xlarge', 'x1e.16xlarge', 'x1e.2xlarge', 'x1e.32xlarge', 'x1e.4xlarge', 'x1e.8xlarge', 'x1e.xlarge', 'z1d.12xlarge', 'z1d.2xlarge', 'z1d.3xlarge', 'z1d.6xlarge', 'z1d.large', 'z1d.metal', 'z1d.xlarge'], 'ap-southeast-2': ['a1.2xlarge', 'a1.4xlarge', 'a1.large', 'a1.medium', 'a1.metal', 'a1.xlarge', 'c1.medium', 'c1.xlarge', 'c3.2xlarge', 'c3.4xlarge', 'c3.8xlarge', 'c3.large', 'c3.xlarge', 'c4.2xlarge', 'c4.4xlarge', 'c4.8xlarge', 'c4.large', 'c4.xlarge', 'c5.12xlarge', 'c5.18xlarge', 'c5.24xlarge', 'c5.2xlarge', 'c5.4xlarge', 'c5.9xlarge', 'c5.large', 'c5.metal', 'c5.xlarge', 'c5d.12xlarge', 'c5d.18xlarge', 'c5d.24xlarge', 'c5d.2xlarge', 'c5d.4xlarge', 'c5d.9xlarge', 'c5d.large', 'c5d.metal', 'c5d.xlarge', 'c5n.18xlarge', 'c5n.2xlarge', 'c5n.4xlarge', 'c5n.9xlarge', 'c5n.large', 'c5n.metal', 'c5n.xlarge', 'd2.2xlarge', 'd2.4xlarge', 'd2.8xlarge', 'd2.xlarge', 'f1.16xlarge', 'f1.2xlarge', 'f1.4xlarge', 'g2.2xlarge', 'g2.8xlarge', 'g3.16xlarge', 'g3.4xlarge', 'g3.8xlarge', 'g3s.xlarge', 'g4dn.12xlarge', 'g4dn.16xlarge', 'g4dn.2xlarge', 'g4dn.4xlarge', 'g4dn.8xlarge', 'g4dn.xlarge', 'hs1.8xlarge', 'i2.2xlarge', 'i2.4xlarge', 'i2.8xlarge', 'i2.xlarge', 'i3.16xlarge', 'i3.2xlarge', 'i3.4xlarge', 'i3.8xlarge', 'i3.large', 'i3.xlarge', 'i3en.12xlarge', 'i3en.24xlarge', 'i3en.2xlarge', 'i3en.3xlarge', 'i3en.6xlarge', 'i3en.large', 'i3en.metal', 'i3en.xlarge', 'm1.large', 'm1.medium', 'm1.xlarge', 'm2.2xlarge', 'm2.4xlarge', 'm2.xlarge', 'm3.2xlarge', 'm3.large', 'm3.medium', 'm3.xlarge', 'm4.10xlarge', 'm4.16xlarge', 'm4.2xlarge', 'm4.4xlarge', 'm4.large', 'm4.xlarge', 'm5.12xlarge', 'm5.16xlarge', 'm5.24xlarge', 'm5.2xlarge', 'm5.4xlarge', 'm5.8xlarge', 'm5.large', 'm5.metal', 'm5.xlarge', 'm5a.12xlarge', 'm5a.16xlarge', 'm5a.24xlarge', 'm5a.2xlarge', 'm5a.4xlarge', 'm5a.8xlarge', 'm5a.large', 'm5a.xlarge', 'm5ad.12xlarge', 'm5ad.16xlarge', 'm5ad.24xlarge', 'm5ad.2xlarge', 'm5ad.4xlarge', 'm5ad.8xlarge', 'm5ad.large', 'm5ad.xlarge', 'm5d.12xlarge', 'm5d.16xlarge', 'm5d.24xlarge', 'm5d.2xlarge', 'm5d.4xlarge', 'm5d.8xlarge', 'm5d.large', 'm5d.metal', 'm5d.xlarge', 'p2.16xlarge', 'p2.8xlarge', 'p2.xlarge', 'p3.16xlarge', 'p3.2xlarge', 'p3.8xlarge', 'r3.2xlarge', 'r3.4xlarge', 'r3.8xlarge', 'r3.large', 'r3.xlarge', 'r4.16xlarge', 'r4.2xlarge', 'r4.4xlarge', 'r4.8xlarge', 'r4.large', 'r4.xlarge', 'r5.12xlarge', 'r5.16xlarge', 'r5.24xlarge', 'r5.2xlarge', 'r5.4xlarge', 'r5.8xlarge', 'r5.large', 'r5.metal', 'r5.xlarge', 'r5a.12xlarge', 'r5a.16xlarge', 'r5a.24xlarge', 'r5a.2xlarge', 'r5a.4xlarge', 'r5a.8xlarge', 'r5a.large', 'r5a.xlarge', 'r5ad.12xlarge', 'r5ad.16xlarge', 'r5ad.24xlarge', 'r5ad.2xlarge', 'r5ad.4xlarge', 'r5ad.8xlarge', 'r5ad.large', 'r5ad.xlarge', 'r5d.12xlarge', 'r5d.16xlarge', 'r5d.24xlarge', 'r5d.2xlarge', 'r5d.4xlarge', 'r5d.8xlarge', 'r5d.large', 'r5d.metal', 'r5d.xlarge', 't1.micro', 't2.2xlarge', 't2.large', 't2.medium', 't2.micro', 't2.nano', 't2.small', 't2.xlarge', 't3.2xlarge', 't3.large', 't3.medium', 't3.micro', 't3.nano', 't3.small', 't3.xlarge', 't3a.2xlarge', 't3a.large', 't3a.medium', 't3a.micro', 't3a.nano', 't3a.small', 't3a.xlarge', 'x1.16xlarge', 'x1.32xlarge', 'x1e.16xlarge', 'x1e.2xlarge', 'x1e.32xlarge', 'x1e.4xlarge', 'x1e.8xlarge', 'x1e.xlarge', 'z1d.12xlarge', 'z1d.2xlarge', 'z1d.3xlarge', 'z1d.6xlarge', 'z1d.large', 'z1d.metal', 'z1d.xlarge'], 'ap-south-1': ['a1.2xlarge', 'a1.4xlarge', 'a1.large', 'a1.medium', 'a1.metal', 'a1.xlarge', 'c4.2xlarge', 'c4.4xlarge', 'c4.8xlarge', 'c4.large', 'c4.xlarge', 'c5.12xlarge', 'c5.18xlarge', 'c5.24xlarge', 'c5.2xlarge', 'c5.4xlarge', 'c5.9xlarge', 'c5.large', 'c5.metal', 'c5.xlarge', 'c5d.18xlarge', 'c5d.2xlarge', 'c5d.4xlarge', 'c5d.9xlarge', 'c5d.large', 'c5d.xlarge', 'c5n.18xlarge', 'c5n.2xlarge', 'c5n.4xlarge', 'c5n.9xlarge', 'c5n.large', 'c5n.metal', 'c5n.xlarge', 'd2.2xlarge', 'd2.4xlarge', 'd2.8xlarge', 'd2.xlarge', 'g4dn.12xlarge', 'g4dn.16xlarge', 'g4dn.2xlarge', 'g4dn.4xlarge', 'g4dn.8xlarge', 'g4dn.xlarge', 'i2.2xlarge', 'i2.4xlarge', 'i2.8xlarge', 'i2.xlarge', 'i3.16xlarge', 'i3.2xlarge', 'i3.4xlarge', 'i3.8xlarge', 'i3.large', 'i3.xlarge', 'm4.10xlarge', 'm4.16xlarge', 'm4.2xlarge', 'm4.4xlarge', 'm4.large', 'm4.xlarge', 'm5.12xlarge', 'm5.16xlarge', 'm5.24xlarge', 'm5.2xlarge', 'm5.4xlarge', 'm5.8xlarge', 'm5.large', 'm5.metal', 'm5.xlarge', 'm5a.12xlarge', 'm5a.16xlarge', 'm5a.24xlarge', 'm5a.2xlarge', 'm5a.4xlarge', 'm5a.8xlarge', 'm5a.large', 'm5a.xlarge', 'm5ad.12xlarge', 'm5ad.16xlarge', 'm5ad.24xlarge', 'm5ad.2xlarge', 'm5ad.4xlarge', 'm5ad.8xlarge', 'm5ad.large', 'm5ad.xlarge', 'm5d.12xlarge', 'm5d.16xlarge', 'm5d.24xlarge', 'm5d.2xlarge', 'm5d.4xlarge', 'm5d.8xlarge', 'm5d.large', 'm5d.metal', 'm5d.xlarge', 'p2.16xlarge', 'p2.8xlarge', 'p2.xlarge', 'r3.2xlarge', 'r3.4xlarge', 'r3.8xlarge', 'r3.large', 'r3.xlarge', 'r4.16xlarge', 'r4.2xlarge', 'r4.4xlarge', 'r4.8xlarge', 'r4.large', 'r4.xlarge', 'r5.12xlarge', 'r5.16xlarge', 'r5.24xlarge', 'r5.2xlarge', 'r5.4xlarge', 'r5.8xlarge', 'r5.large', 'r5.metal', 'r5.xlarge', 'r5a.12xlarge', 'r5a.16xlarge', 'r5a.24xlarge', 'r5a.2xlarge', 'r5a.4xlarge', 'r5a.8xlarge', 'r5a.large', 'r5a.xlarge', 'r5ad.12xlarge', 'r5ad.16xlarge', 'r5ad.24xlarge', 'r5ad.2xlarge', 'r5ad.4xlarge', 'r5ad.8xlarge', 'r5ad.large', 'r5ad.xlarge', 'r5d.12xlarge', 'r5d.16xlarge', 'r5d.24xlarge', 'r5d.2xlarge', 'r5d.4xlarge', 'r5d.8xlarge', 'r5d.large', 'r5d.metal', 'r5d.xlarge', 't2.2xlarge', 't2.large', 't2.medium', 't2.micro', 't2.nano', 't2.small', 't2.xlarge', 't3.2xlarge', 't3.large', 't3.medium', 't3.micro', 't3.nano', 't3.small', 't3.xlarge', 't3a.2xlarge', 't3a.large', 't3a.medium', 't3a.micro', 't3a.nano', 't3a.small', 't3a.xlarge', 'x1.16xlarge', 'x1.32xlarge', 'x1e.16xlarge', 'x1e.2xlarge', 'x1e.32xlarge', 'x1e.4xlarge', 'x1e.8xlarge', 'x1e.xlarge', 'z1d.12xlarge', 'z1d.2xlarge', 'z1d.3xlarge', 'z1d.6xlarge', 'z1d.large', 'z1d.metal', 'z1d.xlarge'], 'eu-west-1': ['a1.2xlarge', 'a1.4xlarge', 'a1.large', 'a1.medium', 'a1.metal', 'a1.xlarge', 'c1.medium', 'c1.xlarge', 'c3.2xlarge', 'c3.4xlarge', 'c3.8xlarge', 'c3.large', 'c3.xlarge', 'c4.2xlarge', 'c4.4xlarge', 'c4.8xlarge', 'c4.large', 'c4.xlarge', 'c5.12xlarge', 'c5.18xlarge', 'c5.24xlarge', 'c5.2xlarge', 'c5.4xlarge', 'c5.9xlarge', 'c5.large', 'c5.metal', 'c5.xlarge', 'c5d.12xlarge', 'c5d.18xlarge', 'c5d.24xlarge', 'c5d.2xlarge', 'c5d.4xlarge', 'c5d.9xlarge', 'c5d.large', 'c5d.metal', 'c5d.xlarge', 'c5n.18xlarge', 'c5n.2xlarge', 'c5n.4xlarge', 'c5n.9xlarge', 'c5n.large', 'c5n.metal', 'c5n.xlarge', 'cc2.8xlarge', 'cr1.8xlarge', 'd2.2xlarge', 'd2.4xlarge', 'd2.8xlarge', 'd2.xlarge', 'f1.16xlarge', 'f1.2xlarge', 'f1.4xlarge', 'g2.2xlarge', 'g2.8xlarge', 'g3.16xlarge', 'g3.4xlarge', 'g3.8xlarge', 'g3s.xlarge', 'g4dn.12xlarge', 'g4dn.16xlarge', 'g4dn.2xlarge', 'g4dn.4xlarge', 'g4dn.8xlarge', 'g4dn.xlarge', 'h1.16xlarge', 'h1.2xlarge', 'h1.4xlarge', 'h1.8xlarge', 'hs1.8xlarge', 'i2.2xlarge', 'i2.4xlarge', 'i2.8xlarge', 'i2.xlarge', 'i3.16xlarge', 'i3.2xlarge', 'i3.4xlarge', 'i3.8xlarge', 'i3.large', 'i3.metal', 'i3.xlarge', 'i3en.12xlarge', 'i3en.24xlarge', 'i3en.2xlarge', 'i3en.3xlarge', 'i3en.6xlarge', 'i3en.large', 'i3en.metal', 'i3en.xlarge', 'm1.large', 'm1.medium', 'm1.xlarge', 'm2.2xlarge', 'm2.4xlarge', 'm2.xlarge', 'm3.2xlarge', 'm3.large', 'm3.medium', 'm3.xlarge', 'm4.10xlarge', 'm4.16xlarge', 'm4.2xlarge', 'm4.4xlarge', 'm4.large', 'm4.xlarge', 'm5.12xlarge', 'm5.16xlarge', 'm5.24xlarge', 'm5.2xlarge', 'm5.4xlarge', 'm5.8xlarge', 'm5.large', 'm5.metal', 'm5.xlarge', 'm5a.12xlarge', 'm5a.16xlarge', 'm5a.24xlarge', 'm5a.2xlarge', 'm5a.4xlarge', 'm5a.8xlarge', 'm5a.large', 'm5a.xlarge', 'm5ad.12xlarge', 'm5ad.16xlarge', 'm5ad.24xlarge', 'm5ad.2xlarge', 'm5ad.4xlarge', 'm5ad.8xlarge', 'm5ad.large', 'm5ad.xlarge', 'm5d.12xlarge', 'm5d.16xlarge', 'm5d.24xlarge', 'm5d.2xlarge', 'm5d.4xlarge', 'm5d.8xlarge', 'm5d.large', 'm5d.metal', 'm5d.xlarge', 'm5dn.12xlarge', 'm5dn.16xlarge', 'm5dn.24xlarge', 'm5dn.2xlarge', 'm5dn.4xlarge', 'm5dn.8xlarge', 'm5dn.large', 'm5dn.xlarge', 'm5n.12xlarge', 'm5n.16xlarge', 'm5n.24xlarge', 'm5n.2xlarge', 'm5n.4xlarge', 'm5n.8xlarge', 'm5n.large', 'm5n.xlarge', 'p2.16xlarge', 'p2.8xlarge', 'p2.xlarge', 'p3.16xlarge', 'p3.2xlarge', 'p3.8xlarge', 'p3dn.24xlarge', 'r3.2xlarge', 'r3.4xlarge', 'r3.8xlarge', 'r3.large', 'r3.xlarge', 'r4.16xlarge', 'r4.2xlarge', 'r4.4xlarge', 'r4.8xlarge', 'r4.large', 'r4.xlarge', 'r5.12xlarge', 'r5.16xlarge', 'r5.24xlarge', 'r5.2xlarge', 'r5.4xlarge', 'r5.8xlarge', 'r5.large', 'r5.metal', 'r5.xlarge', 'r5a.12xlarge', 'r5a.16xlarge', 'r5a.24xlarge', 'r5a.2xlarge', 'r5a.4xlarge', 'r5a.8xlarge', 'r5a.large', 'r5a.xlarge', 'r5ad.12xlarge', 'r5ad.16xlarge', 'r5ad.24xlarge', 'r5ad.2xlarge', 'r5ad.4xlarge', 'r5ad.8xlarge', 'r5ad.large', 'r5ad.xlarge', 'r5d.12xlarge', 'r5d.16xlarge', 'r5d.24xlarge', 'r5d.2xlarge', 'r5d.4xlarge', 'r5d.8xlarge', 'r5d.large', 'r5d.metal', 'r5d.xlarge', 'r5dn.12xlarge', 'r5dn.16xlarge', 'r5dn.24xlarge', 'r5dn.2xlarge', 'r5dn.4xlarge', 'r5dn.8xlarge', 'r5dn.large', 'r5dn.xlarge', 'r5n.12xlarge', 'r5n.16xlarge', 'r5n.24xlarge', 'r5n.2xlarge', 'r5n.4xlarge', 'r5n.8xlarge', 'r5n.large', 'r5n.xlarge', 't1.micro', 't2.2xlarge', 't2.large', 't2.medium', 't2.micro', 't2.nano', 't2.small', 't2.xlarge', 't3.2xlarge', 't3.large', 't3.medium', 't3.micro', 't3.nano', 't3.small', 't3.xlarge', 't3a.2xlarge', 't3a.large', 't3a.medium', 't3a.micro', 't3a.nano', 't3a.small', 't3a.xlarge', 'x1.16xlarge', 'x1.32xlarge', 'x1e.16xlarge', 'x1e.2xlarge', 'x1e.32xlarge', 'x1e.4xlarge', 'x1e.8xlarge', 'x1e.xlarge', 'z1d.12xlarge', 'z1d.2xlarge', 'z1d.3xlarge', 'z1d.6xlarge', 'z1d.large', 'z1d.metal', 'z1d.xlarge'], 'eu-west-2': ['c4.2xlarge', 'c4.4xlarge', 'c4.8xlarge', 'c4.large', 'c4.xlarge', 'c5.12xlarge', 'c5.18xlarge', 'c5.24xlarge', 'c5.2xlarge', 'c5.4xlarge', 'c5.9xlarge', 'c5.large', 'c5.metal', 'c5.xlarge', 'c5d.12xlarge', 'c5d.18xlarge', 'c5d.24xlarge', 'c5d.2xlarge', 'c5d.4xlarge', 'c5d.9xlarge', 'c5d.large', 'c5d.metal', 'c5d.xlarge', 'd2.2xlarge', 'd2.4xlarge', 'd2.8xlarge', 'd2.xlarge', 'g3.16xlarge', 'g3.4xlarge', 'g3.8xlarge', 'g3s.xlarge', 'g4dn.12xlarge', 'g4dn.16xlarge', 'g4dn.2xlarge', 'g4dn.4xlarge', 'g4dn.8xlarge', 'g4dn.xlarge', 'i3.16xlarge', 'i3.2xlarge', 'i3.4xlarge', 'i3.8xlarge', 'i3.large', 'i3.xlarge', 'i3en.12xlarge', 'i3en.24xlarge', 'i3en.2xlarge', 'i3en.3xlarge', 'i3en.6xlarge', 'i3en.large', 'i3en.metal', 'i3en.xlarge', 'm4.10xlarge', 'm4.16xlarge', 'm4.2xlarge', 'm4.4xlarge', 'm4.large', 'm4.xlarge', 'm5.12xlarge', 'm5.16xlarge', 'm5.24xlarge', 'm5.2xlarge', 'm5.4xlarge', 'm5.8xlarge', 'm5.large', 'm5.metal', 'm5.xlarge', 'm5a.12xlarge', 'm5a.16xlarge', 'm5a.24xlarge', 'm5a.2xlarge', 'm5a.4xlarge', 'm5a.8xlarge', 'm5a.large', 'm5a.xlarge', 'm5ad.12xlarge', 'm5ad.16xlarge', 'm5ad.24xlarge', 'm5ad.2xlarge', 'm5ad.4xlarge', 'm5ad.8xlarge', 'm5ad.large', 'm5ad.xlarge', 'm5d.12xlarge', 'm5d.16xlarge', 'm5d.24xlarge', 'm5d.2xlarge', 'm5d.4xlarge', 'm5d.8xlarge', 'm5d.large', 'm5d.metal', 'm5d.xlarge', 'p3.16xlarge', 'p3.2xlarge', 'p3.8xlarge', 'r4.16xlarge', 'r4.2xlarge', 'r4.4xlarge', 'r4.8xlarge', 'r4.large', 'r4.xlarge', 'r5.12xlarge', 'r5.16xlarge', 'r5.24xlarge', 'r5.2xlarge', 'r5.4xlarge', 'r5.8xlarge', 'r5.large', 'r5.metal', 'r5.xlarge', 'r5a.12xlarge', 'r5a.16xlarge', 'r5a.24xlarge', 'r5a.2xlarge', 'r5a.4xlarge', 'r5a.8xlarge', 'r5a.large', 'r5a.xlarge', 'r5ad.12xlarge', 'r5ad.16xlarge', 'r5ad.24xlarge', 'r5ad.2xlarge', 'r5ad.4xlarge', 'r5ad.8xlarge', 'r5ad.large', 'r5ad.xlarge', 'r5d.12xlarge', 'r5d.16xlarge', 'r5d.24xlarge', 'r5d.2xlarge', 'r5d.4xlarge', 'r5d.8xlarge', 'r5d.large', 'r5d.metal', 'r5d.xlarge', 't2.2xlarge', 't2.large', 't2.medium', 't2.micro', 't2.nano', 't2.small', 't2.xlarge', 't3.2xlarge', 't3.large', 't3.medium', 't3.micro', 't3.nano', 't3.small', 't3.xlarge', 't3a.2xlarge', 't3a.large', 't3a.medium', 't3a.micro', 't3a.nano', 't3a.small', 't3a.xlarge', 'x1.16xlarge', 'x1.32xlarge', 'z1d.12xlarge', 'z1d.2xlarge', 'z1d.3xlarge', 'z1d.6xlarge', 'z1d.large', 'z1d.metal', 'z1d.xlarge'], 'eu-west-3': ['c5.12xlarge', 'c5.18xlarge', 'c5.24xlarge', 'c5.2xlarge', 'c5.4xlarge', 'c5.9xlarge', 'c5.large', 'c5.metal', 'c5.xlarge', 'c5d.18xlarge', 'c5d.2xlarge', 'c5d.4xlarge', 'c5d.9xlarge', 'c5d.large', 'c5d.xlarge', 'd2.2xlarge', 'd2.4xlarge', 'd2.8xlarge', 'd2.xlarge', 'g4dn.12xlarge', 'g4dn.16xlarge', 'g4dn.2xlarge', 'g4dn.4xlarge', 'g4dn.8xlarge', 'g4dn.xlarge', 'i3.16xlarge', 'i3.2xlarge', 'i3.4xlarge', 'i3.8xlarge', 'i3.large', 'i3.xlarge', 'i3en.12xlarge', 'i3en.24xlarge', 'i3en.2xlarge', 'i3en.3xlarge', 'i3en.6xlarge', 'i3en.large', 'i3en.metal', 'i3en.xlarge', 'm5.12xlarge', 'm5.16xlarge', 'm5.24xlarge', 'm5.2xlarge', 'm5.4xlarge', 'm5.8xlarge', 'm5.large', 'm5.metal', 'm5.xlarge', 'm5a.12xlarge', 'm5a.16xlarge', 'm5a.24xlarge', 'm5a.2xlarge', 'm5a.4xlarge', 'm5a.8xlarge', 'm5a.large', 'm5a.xlarge', 'm5ad.12xlarge', 'm5ad.16xlarge', 'm5ad.24xlarge', 'm5ad.2xlarge', 'm5ad.4xlarge', 'm5ad.8xlarge', 'm5ad.large', 'm5ad.xlarge', 'm5d.12xlarge', 'm5d.16xlarge', 'm5d.24xlarge', 'm5d.2xlarge', 'm5d.4xlarge', 'm5d.8xlarge', 'm5d.large', 'm5d.metal', 'm5d.xlarge', 'r4.16xlarge', 'r4.2xlarge', 'r4.4xlarge', 'r4.8xlarge', 'r4.large', 'r4.xlarge', 'r5.12xlarge', 'r5.16xlarge', 'r5.24xlarge', 'r5.2xlarge', 'r5.4xlarge', 'r5.8xlarge', 'r5.large', 'r5.metal', 'r5.xlarge', 'r5a.12xlarge', 'r5a.16xlarge', 'r5a.24xlarge', 'r5a.2xlarge', 'r5a.4xlarge', 'r5a.8xlarge', 'r5a.large', 'r5a.xlarge', 'r5ad.12xlarge', 'r5ad.16xlarge', 'r5ad.24xlarge', 'r5ad.2xlarge', 'r5ad.4xlarge', 'r5ad.8xlarge', 'r5ad.large', 'r5ad.xlarge', 'r5d.12xlarge', 'r5d.16xlarge', 'r5d.24xlarge', 'r5d.2xlarge', 'r5d.4xlarge', 'r5d.8xlarge', 'r5d.large', 'r5d.metal', 'r5d.xlarge', 't2.2xlarge', 't2.large', 't2.medium', 't2.micro', 't2.nano', 't2.small', 't2.xlarge', 't3.2xlarge', 't3.large', 't3.medium', 't3.micro', 't3.nano', 't3.small', 't3.xlarge', 't3a.2xlarge', 't3a.large', 't3a.medium', 't3a.micro', 't3a.nano', 't3a.small', 't3a.xlarge', 'x1.16xlarge', 'x1.32xlarge'], 'eu-central-1': ['a1.2xlarge', 'a1.4xlarge', 'a1.large', 'a1.medium', 'a1.metal', 'a1.xlarge', 'c3.2xlarge', 'c3.4xlarge', 'c3.8xlarge', 'c3.large', 'c3.xlarge', 'c4.2xlarge', 'c4.4xlarge', 'c4.8xlarge', 'c4.large', 'c4.xlarge', 'c5.12xlarge', 'c5.18xlarge', 'c5.24xlarge', 'c5.2xlarge', 'c5.4xlarge', 'c5.9xlarge', 'c5.large', 'c5.metal', 'c5.xlarge', 'c5d.12xlarge', 'c5d.18xlarge', 'c5d.24xlarge', 'c5d.2xlarge', 'c5d.4xlarge', 'c5d.9xlarge', 'c5d.large', 'c5d.metal', 'c5d.xlarge', 'c5n.18xlarge', 'c5n.2xlarge', 'c5n.4xlarge', 'c5n.9xlarge', 'c5n.large', 'c5n.metal', 'c5n.xlarge', 'd2.2xlarge', 'd2.4xlarge', 'd2.8xlarge', 'd2.xlarge', 'g2.2xlarge', 'g2.8xlarge', 'g3.16xlarge', 'g3.4xlarge', 'g3.8xlarge', 'g3s.xlarge', 'g4dn.12xlarge', 'g4dn.16xlarge', 'g4dn.2xlarge', 'g4dn.4xlarge', 'g4dn.8xlarge', 'g4dn.xlarge', 'i2.2xlarge', 'i2.4xlarge', 'i2.8xlarge', 'i2.xlarge', 'i3.16xlarge', 'i3.2xlarge', 'i3.4xlarge', 'i3.8xlarge', 'i3.large', 'i3.metal', 'i3.xlarge', 'i3en.12xlarge', 'i3en.24xlarge', 'i3en.2xlarge', 'i3en.3xlarge', 'i3en.6xlarge', 'i3en.large', 'i3en.metal', 'i3en.xlarge', 'm3.2xlarge', 'm3.large', 'm3.medium', 'm3.xlarge', 'm4.10xlarge', 'm4.16xlarge', 'm4.2xlarge', 'm4.4xlarge', 'm4.large', 'm4.xlarge', 'm5.12xlarge', 'm5.16xlarge', 'm5.24xlarge', 'm5.2xlarge', 'm5.4xlarge', 'm5.8xlarge', 'm5.large', 'm5.metal', 'm5.xlarge', 'm5a.12xlarge', 'm5a.16xlarge', 'm5a.24xlarge', 'm5a.2xlarge', 'm5a.4xlarge', 'm5a.8xlarge', 'm5a.large', 'm5a.xlarge', 'm5ad.12xlarge', 'm5ad.16xlarge', 'm5ad.24xlarge', 'm5ad.2xlarge', 'm5ad.4xlarge', 'm5ad.8xlarge', 'm5ad.large', 'm5ad.xlarge', 'm5d.12xlarge', 'm5d.16xlarge', 'm5d.24xlarge', 'm5d.2xlarge', 'm5d.4xlarge', 'm5d.8xlarge', 'm5d.large', 'm5d.metal', 'm5d.xlarge', 'm5dn.12xlarge', 'm5dn.16xlarge', 'm5dn.24xlarge', 'm5dn.2xlarge', 'm5dn.4xlarge', 'm5dn.8xlarge', 'm5dn.large', 'm5dn.xlarge', 'm5n.12xlarge', 'm5n.16xlarge', 'm5n.24xlarge', 'm5n.2xlarge', 'm5n.4xlarge', 'm5n.8xlarge', 'm5n.large', 'm5n.xlarge', 'p2.16xlarge', 'p2.8xlarge', 'p2.xlarge', 'p3.16xlarge', 'p3.2xlarge', 'p3.8xlarge', 'r3.2xlarge', 'r3.4xlarge', 'r3.8xlarge', 'r3.large', 'r3.xlarge', 'r4.16xlarge', 'r4.2xlarge', 'r4.4xlarge', 'r4.8xlarge', 'r4.large', 'r4.xlarge', 'r5.12xlarge', 'r5.16xlarge', 'r5.24xlarge', 'r5.2xlarge', 'r5.4xlarge', 'r5.8xlarge', 'r5.large', 'r5.metal', 'r5.xlarge', 'r5a.12xlarge', 'r5a.16xlarge', 'r5a.24xlarge', 'r5a.2xlarge', 'r5a.4xlarge', 'r5a.8xlarge', 'r5a.large', 'r5a.xlarge', 'r5ad.12xlarge', 'r5ad.16xlarge', 'r5ad.24xlarge', 'r5ad.2xlarge', 'r5ad.4xlarge', 'r5ad.8xlarge', 'r5ad.large', 'r5ad.xlarge', 'r5d.12xlarge', 'r5d.16xlarge', 'r5d.24xlarge', 'r5d.2xlarge', 'r5d.4xlarge', 'r5d.8xlarge', 'r5d.large', 'r5d.metal', 'r5d.xlarge', 'r5dn.12xlarge', 'r5dn.16xlarge', 'r5dn.24xlarge', 'r5dn.2xlarge', 'r5dn.4xlarge', 'r5dn.8xlarge', 'r5dn.large', 'r5dn.xlarge', 'r5n.12xlarge', 'r5n.16xlarge', 'r5n.24xlarge', 'r5n.2xlarge', 'r5n.4xlarge', 'r5n.8xlarge', 'r5n.large', 'r5n.xlarge', 't2.2xlarge', 't2.large', 't2.medium', 't2.micro', 't2.nano', 't2.small', 't2.xlarge', 't3.2xlarge', 't3.large', 't3.medium', 't3.micro', 't3.nano', 't3.small', 't3.xlarge', 't3a.2xlarge', 't3a.large', 't3a.medium', 't3a.micro', 't3a.nano', 't3a.small', 't3a.xlarge', 'x1.16xlarge', 'x1.32xlarge', 'x1e.16xlarge', 'x1e.2xlarge', 'x1e.32xlarge', 'x1e.4xlarge', 'x1e.8xlarge', 'x1e.xlarge', 'z1d.12xlarge', 'z1d.2xlarge', 'z1d.3xlarge', 'z1d.6xlarge', 'z1d.large', 'z1d.metal', 'z1d.xlarge'], 'sa-east-1': ['c1.medium', 'c1.xlarge', 'c3.2xlarge', 'c3.4xlarge', 'c3.8xlarge', 'c3.large', 'c3.xlarge', 'c4.2xlarge', 'c4.4xlarge', 'c4.8xlarge', 'c4.large', 'c4.xlarge', 'c5.12xlarge', 'c5.18xlarge', 'c5.24xlarge', 'c5.2xlarge', 'c5.4xlarge', 'c5.9xlarge', 'c5.large', 'c5.metal', 'c5.xlarge', 'c5d.12xlarge', 'c5d.18xlarge', 'c5d.24xlarge', 'c5d.2xlarge', 'c5d.4xlarge', 'c5d.9xlarge', 'c5d.large', 'c5d.metal', 'c5d.xlarge', 'g4dn.12xlarge', 'g4dn.16xlarge', 'g4dn.2xlarge', 'g4dn.4xlarge', 'g4dn.8xlarge', 'g4dn.xlarge', 'i3.16xlarge', 'i3.2xlarge', 'i3.4xlarge', 'i3.8xlarge', 'i3.large', 'i3.xlarge', 'i3en.12xlarge', 'i3en.24xlarge', 'i3en.2xlarge', 'i3en.3xlarge', 'i3en.6xlarge', 'i3en.large', 'i3en.metal', 'i3en.xlarge', 'm1.large', 'm1.medium', 'm1.xlarge', 'm2.2xlarge', 'm2.4xlarge', 'm2.xlarge', 'm3.2xlarge', 'm3.large', 'm3.medium', 'm3.xlarge', 'm4.10xlarge', 'm4.16xlarge', 'm4.2xlarge', 'm4.4xlarge', 'm4.large', 'm4.xlarge', 'm5.12xlarge', 'm5.16xlarge', 'm5.24xlarge', 'm5.2xlarge', 'm5.4xlarge', 'm5.8xlarge', 'm5.large', 'm5.metal', 'm5.xlarge', 'm5a.12xlarge', 'm5a.16xlarge', 'm5a.24xlarge', 'm5a.2xlarge', 'm5a.4xlarge', 'm5a.8xlarge', 'm5a.large', 'm5a.xlarge', 'm5ad.12xlarge', 'm5ad.16xlarge', 'm5ad.24xlarge', 'm5ad.2xlarge', 'm5ad.4xlarge', 'm5ad.8xlarge', 'm5ad.large', 'm5ad.xlarge', 'm5d.12xlarge', 'm5d.16xlarge', 'm5d.24xlarge', 'm5d.2xlarge', 'm5d.4xlarge', 'm5d.8xlarge', 'm5d.large', 'm5d.metal', 'm5d.xlarge', 'r3.2xlarge', 'r3.4xlarge', 'r3.8xlarge', 'r3.large', 'r3.xlarge', 'r4.16xlarge', 'r4.2xlarge', 'r4.4xlarge', 'r4.8xlarge', 'r4.large', 'r4.xlarge', 'r5.12xlarge', 'r5.16xlarge', 'r5.24xlarge', 'r5.2xlarge', 'r5.4xlarge', 'r5.8xlarge', 'r5.large', 'r5.metal', 'r5.xlarge', 'r5a.12xlarge', 'r5a.16xlarge', 'r5a.24xlarge', 'r5a.2xlarge', 'r5a.4xlarge', 'r5a.8xlarge', 'r5a.large', 'r5a.xlarge', 'r5ad.12xlarge', 'r5ad.16xlarge', 'r5ad.24xlarge', 'r5ad.2xlarge', 'r5ad.4xlarge', 'r5ad.8xlarge', 'r5ad.large', 'r5ad.xlarge', 'r5d.12xlarge', 'r5d.16xlarge', 'r5d.24xlarge', 'r5d.2xlarge', 'r5d.4xlarge', 'r5d.8xlarge', 'r5d.large', 'r5d.metal', 'r5d.xlarge', 't1.micro', 't2.2xlarge', 't2.large', 't2.medium', 't2.micro', 't2.nano', 't2.small', 't2.xlarge', 't3.2xlarge', 't3.large', 't3.medium', 't3.micro', 't3.nano', 't3.small', 't3.xlarge', 't3a.2xlarge', 't3a.large', 't3a.medium', 't3a.micro', 't3a.nano', 't3a.small', 't3a.xlarge', 'x1.16xlarge', 'x1.32xlarge']} ec2InstancesByRegion = dict((region, [E2Instances[i] for i in instances]) for region, instances in iteritems(regionDict)) toil-releases-3.24.0/src/toil/lib/humanize.py000066400000000000000000000042711362134276200210600ustar00rootroot00000000000000# http://code.activestate.com/recipes/578019-bytes-to-human-human-to-bytes-converter/ """ Bytes-to-human / human-to-bytes converter. Based on: http://goo.gl/kTQMs Working with Python 2.x and 3.x. Author: Giampaolo Rodola' License: MIT """ from __future__ import division # see: http://goo.gl/kTQMs from past.utils import old_div SYMBOLS = { 'customary' : ('', 'K', 'M', 'G', 'T', 'P', 'E', 'Z', 'Y'), 'customary_ext' : ('byte', 'kilo', 'mega', 'giga', 'tera', 'peta', 'exa', 'zetta', 'iotta'), 'iec' : ('Bi', 'Ki', 'Mi', 'Gi', 'Ti', 'Pi', 'Ei', 'Zi', 'Yi'), 'iec_ext' : ('byte', 'kibi', 'mebi', 'gibi', 'tebi', 'pebi', 'exbi', 'zebi', 'yobi'), } def bytes2human(n, fmt='%(value).1f %(symbol)s', symbols='customary'): """ Convert n bytes into a human readable string based on format. symbols can be either "customary", "customary_ext", "iec" or "iec_ext", see: http://goo.gl/kTQMs """ n = int(n) if n < 0: raise ValueError("n < 0") symbols = SYMBOLS[symbols] prefix = {} for i, s in enumerate(symbols[1:]): prefix[s] = 1 << (i+1)*10 for symbol in reversed(symbols[1:]): if n >= prefix[symbol]: value = old_div(float(n), prefix[symbol]) return fmt % locals() return fmt % dict(symbol=symbols[0], value=n) def human2bytes(s): """ Attempts to guess the string format based on default symbols set and return the corresponding bytes as an integer. When unable to recognize the format ValueError is raised. """ init = s num = "" while s and s[0:1].isdigit() or s[0:1] == '.': num += s[0] s = s[1:] num = float(num) letter = s.strip() for name, sset in list(SYMBOLS.items()): if letter in sset: break else: if letter == 'k': # treat 'k' as an alias for 'K' as per: http://goo.gl/kTQMs sset = SYMBOLS['customary'] letter = letter.upper() else: raise ValueError("can't interpret %r" % init) prefix = {sset[0]:1} for i, s in enumerate(sset[1:]): prefix[s] = 1 << (i+1)*10 return int(num * prefix[letter]) toil-releases-3.24.0/src/toil/lib/iterables.py000066400000000000000000000070761362134276200212200ustar00rootroot00000000000000# Copyright (C) 2015-2018 Regents of the University of California # # 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. # 5.14.2018: copied into Toil from https://github.com/BD2KGenomics/bd2k-python-lib from __future__ import absolute_import from builtins import map from builtins import object try: from itertools import zip_longest except: from itertools import izip_longest as zip_longest def flatten( iterables ): """ Flatten an iterable, except for string elements. """ for it in iterables: if isinstance(it, str): yield it else: for element in it: yield element # noinspection PyPep8Naming class concat(object): """ A literal iterable that lets you combine sequence literals (lists, set) with generators or list comprehensions. Instead of >>> [ -1 ] + [ x * 2 for x in range( 3 ) ] + [ -1 ] [-1, 0, 2, 4, -1] you can write >>> list( concat( -1, ( x * 2 for x in range( 3 ) ), -1 ) ) [-1, 0, 2, 4, -1] This is slightly shorter (not counting the list constructor) and does not involve array construction or concatenation. Note that concat() flattens (or chains) all iterable arguments into a single result iterable: >>> from builtins import range >>> list( concat( 1, range( 2, 4 ), 4 ) ) [1, 2, 3, 4] It only does so one level deep. If you need to recursively flatten a data structure, check out crush(). If you want to prevent that flattening for an iterable argument, wrap it in concat(): >>> from builtins import range >>> list( concat( 1, concat( range( 2, 4 ) ), 4 ) ) [1, range(2, 4), 4] Some more example. >>> list( concat() ) # empty concat [] >>> list( concat( 1 ) ) # non-iterable [1] >>> list( concat( concat() ) ) # empty iterable [] >>> list( concat( concat( 1 ) ) ) # singleton iterable [1] >>> list( concat( 1, concat( 2 ), 3 ) ) # flattened iterable [1, 2, 3] >>> list( concat( 1, [2], 3 ) ) # flattened iterable [1, 2, 3] >>> list( concat( 1, concat( [2] ), 3 ) ) # protecting an iterable from being flattened [1, [2], 3] >>> list( concat( 1, concat( [2], 3 ), 4 ) ) # protection only works with a single argument [1, 2, 3, 4] >>> list( concat( 1, 2, concat( 3, 4 ), 5, 6 ) ) [1, 2, 3, 4, 5, 6] >>> list( concat( 1, 2, concat( [ 3, 4 ] ), 5, 6 ) ) [1, 2, [3, 4], 5, 6] Note that while strings are technically iterable, concat() does not flatten them. >>> list( concat( 'ab' ) ) ['ab'] >>> list( concat( concat( 'ab' ) ) ) ['ab'] """ def __init__( self, *args ): super( concat, self ).__init__( ) self.args = args def __iter__( self ): def expand( x ): if isinstance( x, concat ) and len( x.args ) == 1: i = x.args elif not isinstance(x, str): try: i = x.__iter__( ) except AttributeError: i = x, else: i = x return i return flatten( map( expand, self.args ) ) toil-releases-3.24.0/src/toil/lib/memoize.py000066400000000000000000000143241362134276200207050ustar00rootroot00000000000000# Copyright (C) 2015-2018 Regents of the University of California # # 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. # 5.14.2018: copied into Toil from https://github.com/BD2KGenomics/bd2k-python-lib from __future__ import absolute_import import datetime import re from functools import wraps from threading import Lock def memoize(f): """ A decorator that memoizes a function result based on its parameters. For example, this can be used in place of lazy initialization. If the decorating function is invoked by multiple threads, the decorated function may be called more than once with the same arguments. """ # TODO: Recommend that f's arguments be immutable memory = {} @wraps(f) def new_f(*args): try: return memory[args] except KeyError: r = f(*args) memory[args] = r return r return new_f def sync_memoize(f): """ Like memoize, but guarantees that decorated function is only called once, even when multiple threads are calling the decorating function with multiple parameters. """ # TODO: Think about an f that is recursive memory = {} lock = Lock() @wraps(f) def new_f(*args): try: return memory[args] except KeyError: # on cache misses, retry with lock held with lock: try: return memory[args] except KeyError: r = f(*args) memory[args] = r return r return new_f def properties(obj): """ Returns a dictionary with one entry per attribute of the given object. The key being the attribute name and the value being the attribute value. Attributes starting in two underscores will be ignored. This function is an alternative to vars() which only returns instance variables, not properties. Note that methods are returned as well but the value in the dictionary is the method, not the return value of the method. >>> class Foo(): ... def __init__(self): ... self.var = 1 ... @property ... def prop(self): ... return self.var + 1 ... def meth(self): ... return self.var + 2 >>> foo = Foo() >>> properties(foo) == {'var': 1, 'prop': 2, 'meth': foo.meth} True Note how the entry for prop is not a bound method (i.e. the getter) but a the return value of that getter. """ return dict((attr, getattr(obj, attr)) for attr in dir(obj) if not attr.startswith('__')) def rfc3339_datetime_re(anchor=True): """ Returns a regular expression for syntactic validation of ISO date-times, RFC-3339 date-times to be precise. >>> bool( rfc3339_datetime_re().match('2013-11-06T15:56:39Z') ) True >>> bool( rfc3339_datetime_re().match('2013-11-06T15:56:39.123Z') ) True >>> bool( rfc3339_datetime_re().match('2013-11-06T15:56:39-08:00') ) True >>> bool( rfc3339_datetime_re().match('2013-11-06T15:56:39.123+11:00') ) True It anchors the matching to the beginning and end of a string by default ... >>> bool( rfc3339_datetime_re().search('bla 2013-11-06T15:56:39Z bla') ) False ... but that can be changed: >>> bool( rfc3339_datetime_re( anchor=False ).search('bla 2013-11-06T15:56:39Z bla') ) True >>> bool( rfc3339_datetime_re( anchor=False ).match('2013-11-06T15:56:39Z bla') ) True Keep in mind that re.match() always anchors at the beginning: >>> bool( rfc3339_datetime_re( anchor=False ).match('bla 2013-11-06T15:56:39Z') ) False It does not check whether the actual value is a semantically valid datetime: >>> bool( rfc3339_datetime_re().match('9999-99-99T99:99:99.9-99:99') ) True If the regular expression matches, each component of the matching value will be exposed as a captured group in the match object. >>> rfc3339_datetime_re().match('2013-11-06T15:56:39Z').groups() ('2013', '11', '06', '15', '56', '39', None, 'Z') >>> rfc3339_datetime_re().match('2013-11-06T15:56:39.123Z').groups() ('2013', '11', '06', '15', '56', '39', '123', 'Z') >>> rfc3339_datetime_re().match('2013-11-06T15:56:39.123-08:30').groups() ('2013', '11', '06', '15', '56', '39', '123', '-08:30') """ return re.compile( ('^' if anchor else '') + '(\d{4})-(\d{2})-(\d{2})T(\d{2}):(\d{2}):(\d{2})(?:\.(\d+))?(Z|[+-]\d{2}:\d{2})' + ('$' if anchor else '')) def parse_iso_utc(s): """ Parses an ISO time with a hard-coded Z for zulu-time (UTC) at the end. Other timezones are not supported. :param str s: the ISO-formatted time :rtype: datetime.datetime :return: an timezone-naive datetime object >>> parse_iso_utc('2016-04-27T00:28:04.000Z') datetime.datetime(2016, 4, 27, 0, 28, 4) >>> parse_iso_utc('2016-04-27T00:28:04Z') datetime.datetime(2016, 4, 27, 0, 28, 4) >>> parse_iso_utc('2016-04-27T00:28:04X') Traceback (most recent call last): ... ValueError: Not a valid ISO datetime in UTC: 2016-04-27T00:28:04X """ m = rfc3339_datetime_re().match(s) if not m: raise ValueError( 'Not a valid ISO datetime in UTC: ' + s ) else: fmt = '%Y-%m-%dT%H:%M:%S' + ('.%f' if m.group(7) else '') + 'Z' return datetime.datetime.strptime(s, fmt) def strict_bool(s): """Variant of bool() that only accepts two possible string values.""" if s == 'True': return True elif s == 'False': return False else: raise ValueError(s) def less_strict_bool(x): """Idempotent and None-safe version of strict_bool.""" if x is None: return False elif x is True or x is False: return x else: return strict_bool(x) toil-releases-3.24.0/src/toil/lib/message.py000066400000000000000000000033531362134276200206640ustar00rootroot00000000000000import base64 import json class UnknownVersion(Exception): def __init__(self, version): super(UnknownVersion, self).__init__("Unknown message version %d" % version) self.version = version class Message(object): """ A message, mostly for passing information about events to agents. The message version is used to differentiate between incompatible message formats. For example, adding a field is a compatible change if there is a default value for that field, and does not require incrementing the version. Message consumers should ignore versions they don't understand. """ TYPE_UPDATE_SSH_KEYS = 1 @classmethod def from_sqs(cls, sqs_message): """ :param sqs_message: the SQS message to initializes this instance from, assuiming that the SQS message originates from a SQS queue that is subscribed to an SNS topic :type sqs_message: SQSMessage :return: the parsed message or None if the message is of an unkwown version :rtype: Message """ sns_message = json.loads(sqs_message.get_body()) return Message.from_sns(sns_message['Message']) @classmethod def from_sns(cls, message): return cls.from_dict(json.loads(base64.standard_b64decode(message))) @classmethod def from_dict(cls, message): version = message['version'] if version == 1: return cls(type=message['type']) else: raise UnknownVersion(version) def __init__(self, type): super(Message, self).__init__() self.type = type def to_dict(self): return dict(version=1, type=self.type) def to_sns(self): return base64.standard_b64encode(json.dumps(self.to_dict())) toil-releases-3.24.0/src/toil/lib/misc.py000066400000000000000000000161041362134276200201710ustar00rootroot00000000000000import random from six.moves import xrange from math import sqrt import errno import os import shutil import sys import time import socket from contextlib import contextmanager if sys.version_info[0] < 3: # Define a usable FileNotFoundError as will be raised by os.remove on a # nonexistent file. FileNotFoundError = OSError def mkdir_p(path): """The equivalent of mkdir -p""" try: os.makedirs(path) except OSError as exc: if exc.errno == errno.EEXIST and os.path.isdir(path): pass else: raise def robust_rmtree(path): """ Robustly tries to delete paths. Continues silently if the path to be removed is already gone, or if it goes away while this function is executing. May raise an error if a path changes between file and directory while the function is executing, or if a permission error is encountered. path may be str, bytes, or unicode. """ if not isinstance(path, bytes): # Internally we must work in bytes, in case we find an undecodeable # filename. path = path.encode('utf-8') if not os.path.exists(path): # Nothing to do! return if not os.path.islink(path) and os.path.isdir(path): # It is or has been a directory try: children = os.listdir(path) except FileNotFoundError: # Directory went away return # We assume the directory going away while we have it open won't upset # the listdir iterator. for child in children: # Get the path for each child item in the directory child_path = os.path.join(path, child) # Remove it if still present robust_rmtree(child_path) try: # Actually remove the directory once the children are gone os.rmdir(path) except FileNotFoundError: # Directory went away return else: # It is not or was not a directory. try: # Unlink it as a normal file os.unlink(path) except FileNotFoundError: # File went away return def mean(xs): """ Return the mean value of a sequence of values. >>> mean([2,4,4,4,5,5,7,9]) 5.0 >>> mean([9,10,11,7,13]) 10.0 >>> mean([1,1,10,19,19]) 10.0 >>> mean([10,10,10,10,10]) 10.0 >>> mean([1,"b"]) Traceback (most recent call last): ... ValueError: Input can't have non-numeric elements >>> mean([]) Traceback (most recent call last): ... ValueError: Input can't be empty """ try: return sum(xs) / float(len(xs)) except TypeError: raise ValueError("Input can't have non-numeric elements") except ZeroDivisionError: raise ValueError("Input can't be empty") def std_dev(xs): """ Returns the standard deviation of the given iterable of numbers. From http://rosettacode.org/wiki/Standard_deviation#Python An empty list, or a list with non-numeric elements will raise a TypeError. >>> std_dev([2,4,4,4,5,5,7,9]) 2.0 >>> std_dev([9,10,11,7,13]) 2.0 >>> std_dev([1,1,10,19,19]) 8.049844718999243 >>> std_dev({1,1,10,19,19}) == std_dev({19,10,1}) True >>> std_dev([10,10,10,10,10]) 0.0 >>> std_dev([1,"b"]) Traceback (most recent call last): ... ValueError: Input can't have non-numeric elements >>> std_dev([]) Traceback (most recent call last): ... ValueError: Input can't be empty """ m = mean(xs) # this checks our pre-conditions, too return sqrt(sum((x - m) ** 2 for x in xs) / float(len(xs))) def partition_seq(seq, size): """ Splits a sequence into an iterable of subsequences. All subsequences are of the given size, except the last one, which may be smaller. If the input list is modified while the returned list is processed, the behavior of the program is undefined. :param seq: the list to split :param size: the desired size of the sublists, must be > 0 :type size: int :return: an iterable of sublists >>> list(partition_seq("",1)) [] >>> list(partition_seq("abcde",2)) ['ab', 'cd', 'e'] >>> list(partition_seq("abcd",2)) ['ab', 'cd'] >>> list(partition_seq("abcde",1)) ['a', 'b', 'c', 'd', 'e'] >>> list(partition_seq("abcde",0)) Traceback (most recent call last): ... ValueError: Size must be greater than 0 >>> l=[1,2,3,4] >>> i = iter( partition_seq(l,2) ) >>> l.pop(0) 1 >>> next(i) [2, 3] """ if size < 1: raise ValueError('Size must be greater than 0') return (seq[pos:pos + size] for pos in xrange(0, len(seq), size)) def truncExpBackoff(): # as recommended here https://forums.aws.amazon.com/thread.jspa?messageID=406788#406788 # and here https://cloud.google.com/storage/docs/xml-api/reference-status yield 0 t = 1 while t < 1024: # google suggests this dither yield t + random.random() t *= 2 while True: yield t def atomic_tmp_file(final_path): """Return a tmp file name to use with atomic_install. This will be in the same directory as final_path. The temporary file will have the same extension as finalPath. It the final path is in /dev (/dev/null, /dev/stdout), it is returned unchanged and atomic_tmp_install will do nothing.""" final_dir = os.path.dirname(os.path.normpath(final_path)) # can be empty if final_dir == '/dev': return final_path final_basename = os.path.basename(final_path) final_ext = os.path.splitext(final_path)[1] base_name = "{}.{}.{}.tmp{}".format(final_basename, socket.gethostname(), os.getpid(), final_ext) return os.path.join(final_dir, base_name) def atomic_install(tmp_path, final_path): "atomic install of tmp_path as final_path" if os.path.dirname(os.path.normpath(final_path)) != '/dev': os.rename(tmp_path, final_path) @contextmanager def AtomicFileCreate(final_path, keep=False): """Context manager to create a temporary file. Entering returns path to the temporary file in the same directory as finalPath. If the code in context succeeds, the file renamed to its actually name. If an error occurs, the file is not installed and is removed unless keep is specified. """ tmp_path = atomic_tmp_file(final_path) try: yield tmp_path atomic_install(tmp_path, final_path) except Exception as ex: if not keep: try: os.unlink(tmp_path) except Exception: pass raise def atomic_copy(src_path, dest_path): """Copy a file using posix atomic creations semantics.""" with AtomicFileCreate(dest_path) as dest_path_tmp: shutil.copyfile(src_path, dest_path_tmp) def atomic_copyobj(src_fh, dest_path, length=16384): """Copy an open file using posix atomic creations semantics.""" with AtomicFileCreate(dest_path) as dest_path_tmp: with open(dest_path_tmp, 'wb') as dest_path_fh: shutil.copyfileobj(src_fh, dest_path_fh, length=length) toil-releases-3.24.0/src/toil/lib/objects.py000066400000000000000000000167011362134276200206720ustar00rootroot00000000000000# Copyright (C) 2015-2018 Regents of the University of California # # 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. # 5.14.2018: copied into Toil from https://github.com/BD2KGenomics/bd2k-python-lib from __future__ import absolute_import from builtins import object from toil.lib.memoize import sync_memoize class abstractclassmethod(classmethod): """ This class defines a decorator that allows the decorated class to be both an abstract method and a class method. Shamelessly stolen from http://stackoverflow.com/questions/11217878/python-2-7-combine-abc-abstractmethod-and-classmethod >>> from abc import ABCMeta >>> class DemoABC: ... __metaclass__ = ABCMeta ... ... @abstractclassmethod ... def from_int(cls, n): ... return cls() >>> class DemoConcrete(DemoABC): ... @classmethod ... def from_int(cls, n): ... return cls(2*n) ... ... def __init__(self, n): ... print ('Initializing with %s' % n) >>> d = DemoConcrete(5) # Succeeds by calling a concrete __init__() Initializing with 5 >>> d = DemoConcrete.from_int(5) # Succeeds by calling a concrete from_int() Initializing with 10 """ __isabstractmethod__ = True def __init__(self, callable): callable.__isabstractmethod__ = True super(abstractclassmethod, self).__init__(callable) class abstractstaticmethod(staticmethod): """ This class defines a decorator that allows the decorated class to be both an abstract method and a static method. Based on code found at http://stackoverflow.com/questions/11217878/python-2-7-combine-abc-abstractmethod-and-classmethod >>> from abc import ABCMeta >>> class DemoABC: ... __metaclass__ = ABCMeta ... ... @abstractstaticmethod ... def f(n): ... raise NotImplementedError() >>> class DemoConcrete(DemoABC): ... @staticmethod ... def f(n): ... return 2*n >>> d = DemoABC.f(5) # Fails because f() is not implemented Traceback (most recent call last): ... NotImplementedError >>> DemoConcrete.f(5) # Succeeds by calling a concrete f() 10 """ __isabstractmethod__ = True def __init__(self, callable): callable.__isabstractmethod__ = True super(abstractstaticmethod, self).__init__(callable) class InnerClass(object): """ Note that this is EXPERIMENTAL code. A nested class (the inner class) decorated with this will have an additional attribute called 'outer' referencing the instance of the nesting class (the outer class) that was used to create the inner class. The outer instance does not need to be passed to the inner class's constructor, it will be set magically. Shamelessly stolen from http://stackoverflow.com/questions/2278426/inner-classes-how-can-i-get-the-outer-class-object-at-construction-time#answer-2278595. with names made more descriptive (I hope) and added caching of the BoundInner classes. Caveat: Within the inner class, self.__class__ will not be the inner class but a dynamically created subclass thereof. It's name will be the same as that of the inner class, but its __module__ will be different. There will be one such dynamic subclass per inner class and instance of outer class, if that outer class instance created any instances of inner the class. >>> class Outer(object): ... def new_inner(self): ... # self is an instance of the outer class ... inner = self.Inner() ... # the inner instance's 'outer' attribute is set to the outer instance ... assert inner.outer is self ... return inner ... @InnerClass ... class Inner(object): ... def get_outer(self): ... return self.outer ... @classmethod ... def new_inner(cls): ... return cls() >>> o = Outer() >>> i = o.new_inner() >>> i # doctest: +ELLIPSIS bound to >>> i.get_outer() # doctest: +ELLIPSIS Now with inheritance for both inner and outer: >>> class DerivedOuter(Outer): ... def new_inner(self): ... return self.DerivedInner() ... @InnerClass ... class DerivedInner(Outer.Inner): ... def get_outer(self): ... assert super( DerivedOuter.DerivedInner, self ).get_outer() == self.outer ... return self.outer >>> derived_outer = DerivedOuter() >>> derived_inner = derived_outer.new_inner() >>> derived_inner # doctest: +ELLIPSIS bound to >>> derived_inner.get_outer() # doctest: +ELLIPSIS Test a static references: >>> Outer.Inner # doctest: +ELLIPSIS >>> DerivedOuter.Inner # doctest: +ELLIPSIS >>> DerivedOuter.DerivedInner #doctest: +ELLIPSIS Can't decorate top-level classes. Unfortunately, this is detected when the instance is created, not when the class is defined. >>> @InnerClass ... class Foo(object): ... pass >>> Foo() Traceback (most recent call last): ... RuntimeError: Inner classes must be nested in another class. All inner instances should refer to a single outer instance: >>> o = Outer() >>> o.new_inner().outer == o == o.new_inner().outer True All inner instances should be of the same class ... >>> o.new_inner().__class__ == o.new_inner().__class__ True ... but that class isn't the inner class ... >>> o.new_inner().__class__ != Outer.Inner True ... but a subclass of the inner class. >>> isinstance( o.new_inner(), Outer.Inner ) True Static and class methods, e.g. should work, too >>> o.Inner.new_inner().outer == o True """ def __init__(self, inner_class): super(InnerClass, self).__init__() self.inner_class = inner_class # noinspection PyUnusedLocal def __get__(self, instance, owner): # No need to wrap a static reference, i.e one that is made via 'Outer.' rather than 'self.' if instance is None: return self.inner_class else: return self._bind( instance ) @sync_memoize def _bind( self, _outer): class BoundInner(self.inner_class): outer = _outer def __repr__(self): return "%s bound to %s" % (super(BoundInner, self).__repr__(), repr(_outer)) BoundInner.__name__ = self.inner_class.__name__ BoundInner.__module__ = self.inner_class.__module__ return BoundInner def __call__(*args, **kwargs): raise RuntimeError("Inner classes must be nested in another class.") toil-releases-3.24.0/src/toil/lib/retry.py000066400000000000000000000130471362134276200204060ustar00rootroot00000000000000# Copyright (C) 2015-2018 Regents of the University of California # # 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. # 5.14.2018: copied into Toil from https://github.com/BD2KGenomics/bd2k-python-lib from __future__ import absolute_import from future import standard_library standard_library.install_aliases() from builtins import next from contextlib import contextmanager import time import urllib.request, urllib.error, urllib.parse try: from httplib import BadStatusLine except ImportError: # This has moved in Python 3 from http.client import BadStatusLine import logging log = logging.getLogger( __name__ ) # noinspection PyUnusedLocal def never( exception ): return False def retry( delays=(0, 1, 1, 4, 16, 64), timeout=300, predicate=never ): """ Retry an operation while the failure matches a given predicate and until a given timeout expires, waiting a given amount of time in between attempts. This function is a generator that yields contextmanagers. See doctests below for example usage. :param Iterable[float] delays: an interable yielding the time in seconds to wait before each retried attempt, the last element of the iterable will be repeated. :param float timeout: a overall timeout that should not be exceeded for all attempts together. This is a best-effort mechanism only and it won't abort an ongoing attempt, even if the timeout expires during that attempt. :param Callable[[Exception],bool] predicate: a unary callable returning True if another attempt should be made to recover from the given exception. The default value for this parameter will prevent any retries! :return: a generator yielding context managers, one per attempt :rtype: Iterator Retry for a limited amount of time: >>> true = lambda _:True >>> false = lambda _:False >>> i = 0 >>> for attempt in retry( delays=[0], timeout=.1, predicate=true ): ... with attempt: ... i += 1 ... raise RuntimeError('foo') Traceback (most recent call last): ... RuntimeError: foo >>> i > 1 True If timeout is 0, do exactly one attempt: >>> i = 0 >>> for attempt in retry( timeout=0 ): ... with attempt: ... i += 1 ... raise RuntimeError( 'foo' ) Traceback (most recent call last): ... RuntimeError: foo >>> i 1 Don't retry on success: >>> i = 0 >>> for attempt in retry( delays=[0], timeout=.1, predicate=true ): ... with attempt: ... i += 1 >>> i 1 Don't retry on unless predicate returns True: >>> i = 0 >>> for attempt in retry( delays=[0], timeout=.1, predicate=false): ... with attempt: ... i += 1 ... raise RuntimeError( 'foo' ) Traceback (most recent call last): ... RuntimeError: foo >>> i 1 """ if timeout > 0: go = [ None ] @contextmanager def repeated_attempt( delay ): try: yield except Exception as e: if time.time( ) + delay < expiration and predicate( e ): log.info( 'Got %s, trying again in %is.', e, delay ) time.sleep( delay ) else: raise else: go.pop( ) delays = iter( delays ) expiration = time.time( ) + timeout delay = next( delays ) while go: yield repeated_attempt( delay ) delay = next( delays, delay ) else: @contextmanager def single_attempt( ): yield yield single_attempt( ) default_delays = (0, 1, 1, 4, 16, 64) default_timeout = 300 def retryable_http_error( e ): """ Determine if an error encountered during an HTTP download is likely to go away if we try again. """ if isinstance( e, urllib.error.HTTPError ) and e.code in ('503', '408', '500'): # The server returned one of: # 503 Service Unavailable # 408 Request Timeout # 500 Internal Server Error return True if isinstance( e, BadStatusLine ): # The server didn't return a valid response at all return True return False def retry_http( delays=default_delays, timeout=default_timeout, predicate=retryable_http_error ): """ >>> i = 0 >>> for attempt in retry_http(timeout=5): # doctest: +IGNORE_EXCEPTION_DETAIL ... with attempt: ... i += 1 ... raise urllib.error.HTTPError('http://www.test.com', '408', 'some message', {}, None) Traceback (most recent call last): ... HTTPError: HTTP Error 408: some message >>> i > 1 True >>> i = 0 >>> for attempt in retry_http(timeout=5): # doctest: +IGNORE_EXCEPTION_DETAIL ... with attempt: ... i += 1 ... raise BadStatusLine('sad-cloud.gif') Traceback (most recent call last): ... BadStatusLine: sad-cloud.gif >>> i > 1 True """ return retry( delays=delays, timeout=timeout, predicate=predicate ) toil-releases-3.24.0/src/toil/lib/threading.py000066400000000000000000000123121362134276200212000ustar00rootroot00000000000000# Copyright (C) 2015-2018 Regents of the University of California # # 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. # 5.14.2018: copied into Toil from https://github.com/BD2KGenomics/bd2k-python-lib from __future__ import absolute_import from future.utils import raise_ from builtins import range import logging import math import sys import threading import traceback if sys.version_info >= (3, 0): from threading import BoundedSemaphore else: from threading import _BoundedSemaphore as BoundedSemaphore import psutil log = logging.getLogger(__name__) class BoundedEmptySemaphore( BoundedSemaphore ): """ A bounded semaphore that is initially empty. """ def __init__( self, value=1, verbose=None ): super( BoundedEmptySemaphore, self ).__init__( value, verbose ) for i in range( value ): assert self.acquire( blocking=False ) class ExceptionalThread(threading.Thread): """ A thread whose join() method re-raises exceptions raised during run(). While join() is idempotent, the exception is only during the first invocation of join() that successfully joined the thread. If join() times out, no exception will be re reraised even though an exception might already have occured in run(). When subclassing this thread, override tryRun() instead of run(). >>> def f(): ... assert 0 >>> t = ExceptionalThread(target=f) >>> t.start() >>> t.join() Traceback (most recent call last): ... AssertionError >>> class MyThread(ExceptionalThread): ... def tryRun( self ): ... assert 0 >>> t = MyThread() >>> t.start() >>> t.join() Traceback (most recent call last): ... AssertionError """ exc_info = None def run( self ): try: self.tryRun( ) except: self.exc_info = sys.exc_info( ) raise def tryRun( self ): super( ExceptionalThread, self ).run( ) def join( self, *args, **kwargs ): super( ExceptionalThread, self ).join( *args, **kwargs ) if not self.is_alive( ) and self.exc_info is not None: type, value, traceback = self.exc_info self.exc_info = None raise_(type, value, traceback) # noinspection PyPep8Naming class defaultlocal(threading.local): """ Thread local storage with default values for each field in each thread >>> >>> l = defaultlocal( foo=42 ) >>> def f(): print(l.foo) >>> t = threading.Thread(target=f) >>> t.start() ; t.join() 42 """ def __init__( self, **kwargs ): super( defaultlocal, self ).__init__( ) self.__dict__.update( kwargs ) def cpu_count(): """ Get the rounded-up integer number of whole CPUs available. Counts hyperthreads as CPUs. Uses the system's actual CPU count, or the current v1 cgroup's quota per period, if the quota is set. Ignores the cgroup's cpu shares value, because it's extremely difficult to interpret. See https://github.com/kubernetes/kubernetes/issues/81021. Caches result for efficiency. :return: Integer count of available CPUs, minimum 1. :rtype: int """ cached = getattr(cpu_count, 'result', None) if cached is not None: # We already got a CPU count. return cached # Get the fallback answer of all the CPUs on the machine total_machine_size = psutil.cpu_count(logical=True) log.debug('Total machine size: %d cores', total_machine_size) try: with open('/sys/fs/cgroup/cpu/cpu.cfs_quota_us', 'r') as stream: # Read the quota quota = int(stream.read()) log.debug('CPU quota: %d', quota) if quota == -1: # Assume we can use the whole machine return total_machine_size with open('/sys/fs/cgroup/cpu/cpu.cfs_period_us', 'r') as stream: # Read the period in which we are allowed to burn the quota period = int(stream.read()) log.debug('CPU quota period: %d', period) # The thread count is how many multiples of a wall clcok period we can burn in that period. cgroup_size = int(math.ceil(float(quota)/float(period))) log.debug('Cgroup size in cores: %d', cgroup_size) except: # We can't actually read these cgroup fields. Maybe we are a mac or something. log.debug('Could not inspect cgroup: %s', traceback.format_exc()) cgroup_size = float('inf') # Return the smaller of the actual thread count and the cgroup's limit, minimum 1. result = max(1, min(cgroup_size, total_machine_size)) log.debug('cpu_count: %s', str(result)) # Make sure to remember it for the next call setattr(cpu_count, 'result', result) return result toil-releases-3.24.0/src/toil/lib/throttle.py000066400000000000000000000162061362134276200211060ustar00rootroot00000000000000# Copyright (C) 2015-2018 Regents of the University of California # # 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. # 5.14.2018: copied into Toil from https://github.com/BD2KGenomics/bd2k-python-lib from __future__ import absolute_import from builtins import object import time import threading from toil.lib.threading import BoundedEmptySemaphore class GlobalThrottle(object): """ A thread-safe rate limiter that throttles all threads globally. This should be used to regulate access to a global resource. It can be used as a function/method decorator or as a simple object, using the throttle() method. The token generation starts with the first call to throttle() or the decorated function. Each subsequent call to throttle() will then acquire a token, possibly having to wait until one becomes available. The number of unused tokens will not exceed a limit given at construction time. This is a very basic mechanism to prevent the resource from becoming swamped after longer pauses. """ def __init__( self, min_interval, max_unused ): self.min_interval = min_interval self.semaphore = BoundedEmptySemaphore( max_unused ) self.thread_start_lock = threading.Lock( ) self.thread_started = False self.thread = threading.Thread( target=self.generator ) self.thread.daemon = True def generator( self ): while True: try: self.semaphore.release( ) except ValueError: pass time.sleep( self.min_interval ) def throttle( self, wait=True ): """ If the wait parameter is True, this method returns True after suspending the current thread as necessary to ensure that no less than the configured minimum interval passed since the most recent time an invocation of this method returned True in any thread. If the wait parameter is False, this method immediatly returns True if at least the configured minimum interval has passed since the most recent time this method returned True in any thread, or False otherwise. """ # I think there is a race in Thread.start(), hence the lock with self.thread_start_lock: if not self.thread_started: self.thread.start( ) self.thread_started = True return self.semaphore.acquire( blocking=wait ) def __call__( self, function ): def wrapper( *args, **kwargs ): self.throttle( ) return function( *args, **kwargs ) return wrapper class LocalThrottle(object): """ A thread-safe rate limiter that throttles each thread independently. Can be used as a function or method decorator or as a simple object, via its .throttle() method. The use as a decorator is deprecated in favor of throttle(). """ def __init__( self, min_interval ): """ Initialize this local throttle. :param min_interval: The minimum interval in seconds between invocations of the throttle method or, if this throttle is used as a decorator, invocations of the decorated method. """ self.min_interval = min_interval self.per_thread = threading.local( ) self.per_thread.last_invocation = None def throttle( self, wait=True ): """ If the wait parameter is True, this method returns True after suspending the current thread as necessary to ensure that no less than the configured minimum interval has passed since the last invocation of this method in the current thread returned True. If the wait parameter is False, this method immediatly returns True (if at least the configured minimum interval has passed since the last time this method returned True in the current thread) or False otherwise. """ now = time.time( ) last_invocation = self.per_thread.last_invocation if last_invocation is not None: interval = now - last_invocation if interval < self.min_interval: if wait: remainder = self.min_interval - interval time.sleep( remainder ) else: return False self.per_thread.last_invocation = now return True def __call__( self, function ): def wrapper( *args, **kwargs ): self.throttle( ) return function( *args, **kwargs ) return wrapper class throttle(object): """ A context manager for ensuring that the execution of its body takes at least a given amount of time, sleeping if necessary. It is a simpler version of LocalThrottle if used as a decorator. Ensures that body takes at least the given amount of time. >>> start = time.time() >>> with throttle(1): ... pass >>> 1 <= time.time() - start <= 1.1 True Ditto when used as a decorator. >>> @throttle(1) ... def f(): ... pass >>> start = time.time() >>> f() >>> 1 <= time.time() - start <= 1.1 True If the body takes longer by itself, don't throttle. >>> start = time.time() >>> with throttle(1): ... time.sleep(2) >>> 2 <= time.time() - start <= 2.1 True Ditto when used as a decorator. >>> @throttle(1) ... def f(): ... time.sleep(2) >>> start = time.time() >>> f() >>> 2 <= time.time() - start <= 2.1 True If an exception occurs, don't throttle. >>> start = time.time() >>> try: ... with throttle(1): ... raise ValueError('foo') ... except ValueError: ... end = time.time() ... raise Traceback (most recent call last): ... ValueError: foo >>> 0 <= end - start <= 0.1 True Ditto when used as a decorator. >>> @throttle(1) ... def f(): ... raise ValueError('foo') >>> start = time.time() >>> try: ... f() ... except ValueError: ... end = time.time() ... raise Traceback (most recent call last): ... ValueError: foo >>> 0 <= end - start <= 0.1 True """ def __init__( self, min_interval ): self.min_interval = min_interval def __enter__( self ): self.start = time.time( ) def __exit__( self, exc_type, exc_val, exc_tb ): if exc_type is None: duration = time.time( ) - self.start remainder = self.min_interval - duration if remainder > 0: time.sleep( remainder ) def __call__( self, function ): def wrapper( *args, **kwargs ): with self: return function( *args, **kwargs ) return wrapper toil-releases-3.24.0/src/toil/provisioners/000077500000000000000000000000001362134276200206565ustar00rootroot00000000000000toil-releases-3.24.0/src/toil/provisioners/.gitignore000066400000000000000000000000371362134276200226460ustar00rootroot00000000000000# Generated by Ansible *.retry toil-releases-3.24.0/src/toil/provisioners/__init__.py000066400000000000000000000036571362134276200230020ustar00rootroot00000000000000# Copyright (C) 2015-2016 Regents of the University of California # # 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. from __future__ import absolute_import import logging logger = logging.getLogger(__name__) def clusterFactory(provisioner, clusterName=None, zone=None, nodeStorage=50, sseKey=None): """ :param clusterName: The name of the cluster. :param provisioner: The cloud type of the cluster. :param zone: The cloud zone :return: A cluster object for the the cloud type. """ if provisioner == 'aws': try: from toil.provisioners.aws.awsProvisioner import AWSProvisioner except ImportError: logger.error('The aws extra must be installed to use this provisioner') raise return AWSProvisioner(clusterName, zone, nodeStorage, sseKey) elif provisioner == 'gce': try: from toil.provisioners.gceProvisioner import GCEProvisioner except ImportError: logger.error('The google extra must be installed to use this provisioner') raise return GCEProvisioner(clusterName, zone, nodeStorage, sseKey) else: raise RuntimeError("Invalid provisioner '%s'" % provisioner) class NoSuchClusterException(Exception): """Indicates that the specified cluster does not exist.""" def __init__(self, clusterName): super(NoSuchClusterException, self).__init__("The cluster '%s' could not be found" % clusterName) toil-releases-3.24.0/src/toil/provisioners/abstractProvisioner.py000066400000000000000000000354231362134276200253020ustar00rootroot00000000000000# Copyright (C) 2015-2018 Regents of the University of California # # 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. from future.utils import with_metaclass from abc import ABCMeta, abstractmethod from builtins import object from functools import total_ordering import logging import os.path from toil import subprocess from toil import applianceSelf, customDockerInitCmd from toil.lib.retry import never a_short_time = 5 log = logging.getLogger(__name__) @total_ordering class Shape(object): """ Represents a job or a node's "shape", in terms of the dimensions of memory, cores, disk and wall-time allocation. The wallTime attribute stores the number of seconds of a node allocation, e.g. 3600 for AWS. FIXME: and for jobs? The memory and disk attributes store the number of bytes required by a job (or provided by a node) in RAM or on disk (SSD or HDD), respectively. """ def __init__(self, wallTime, memory, cores, disk, preemptable): self.wallTime = wallTime self.memory = memory self.cores = cores self.disk = disk self.preemptable = preemptable def __eq__(self, other): return (self.wallTime == other.wallTime and self.memory == other.memory and self.cores == other.cores and self.disk == other.disk and self.preemptable == other.preemptable) def greater_than(self, other): if self.preemptable < other.preemptable: return True elif self.preemptable > other.preemptable: return False elif self.memory > other.memory: return True elif self.memory < other.memory: return False elif self.cores > other.cores: return True elif self.cores < other.cores: return False elif self.disk > other.disk: return True elif self.disk < other.disk: return False elif self.wallTime > other.wallTime: return True elif self.wallTime < other.wallTime: return False else: return False def __gt__(self, other): return self.greater_than(other) def __repr__(self): return "Shape(wallTime=%s, memory=%s, cores=%s, disk=%s, preemptable=%s)" % \ (self.wallTime, self.memory, self.cores, self.disk, self.preemptable) def __str__(self): return self.__repr__() def __hash__(self): # Since we replaced __eq__ we need to replace __hash__ as well. return hash( (self.wallTime, self.memory, self.cores, self.disk, self.preemptable)) class AbstractProvisioner(with_metaclass(ABCMeta, object)): """ An abstract base class to represent the interface for provisioning worker nodes to use in a Toil cluster. """ LEADER_HOME_DIR = '/root/' # home directory in the Toil appliance on an instance def __init__(self, clusterName=None, zone=None, nodeStorage=50): """ Initialize provisioner. :param clusterName: The cluster identifier. :param zone: The zone the cluster runs in. :param nodeStorage: The amount of storage on the worker instances, in gigabytes. """ self.clusterName = clusterName self._zone = zone self._nodeStorage = nodeStorage self._leaderPrivateIP = None def readClusterSettings(self): """ Initialize class from an existing cluster. This method assumes that the instance we are running on is the leader. """ raise NotImplementedError def setAutoscaledNodeTypes(self, nodeTypes): """ Set node types, shapes and spot bids. Preemptable nodes will have the form "type:spotBid". :param nodeTypes: A list of node types """ self._spotBidsMap = {} self.nodeShapes = [] self.nodeTypes = [] for nodeTypeStr in nodeTypes: nodeBidTuple = nodeTypeStr.split(":") if len(nodeBidTuple) == 2: # This is a preemptable node type, with a spot bid nodeType, bid = nodeBidTuple self.nodeTypes.append(nodeType) self.nodeShapes.append(self.getNodeShape(nodeType, preemptable=True)) self._spotBidsMap[nodeType] = bid else: self.nodeTypes.append(nodeTypeStr) self.nodeShapes.append(self.getNodeShape(nodeTypeStr, preemptable=False)) @staticmethod def retryPredicate(e): """ Return true if the exception e should be retried by the cluster scaler. For example, should return true if the exception was due to exceeding an API rate limit. The error will be retried with exponential backoff. :param e: exception raised during execution of setNodeCount :return: boolean indicating whether the exception e should be retried """ return never(e) @abstractmethod def launchCluster(self, leaderNodeType, leaderStorage, owner, **kwargs): """ Initialize a cluster and create a leader node. :param leaderNodeType: The leader instance. :param leaderStorage: The amount of disk to allocate to the leader in gigabytes. :param owner: Tag identifying the owner of the instances. """ raise NotImplementedError @abstractmethod def addNodes(self, nodeType, numNodes, preemptable, spotBid=None): """ Used to add worker nodes to the cluster :param numNodes: The number of nodes to add :param preemptable: whether or not the nodes will be preemptable :param spotBid: The bid for preemptable nodes if applicable (this can be set in config, also). :return: number of nodes successfully added """ raise NotImplementedError @abstractmethod def terminateNodes(self, nodes): """ Terminate the nodes represented by given Node objects :param nodes: list of Node objects """ raise NotImplementedError @abstractmethod def getLeader(self): """ :return: The leader node. """ raise NotImplementedError @abstractmethod def getProvisionedWorkers(self, nodeType, preemptable): """ Gets all nodes of the given preemptability from the provisioner. Includes both static and autoscaled nodes. :param preemptable: Boolean value indicating whether to return preemptable nodes or non-preemptable nodes :return: list of Node objects """ raise NotImplementedError @abstractmethod def getNodeShape(self, nodeType=None, preemptable=False): """ The shape of a preemptable or non-preemptable node managed by this provisioner. The node shape defines key properties of a machine, such as its number of cores or the time between billing intervals. :param str nodeType: Node type name to return the shape of. :rtype: Shape """ raise NotImplementedError @abstractmethod def destroyCluster(self): """ Terminates all nodes in the specified cluster and cleans up all resources associated with the cluser. :param clusterName: identifier of the cluster to terminate. """ raise NotImplementedError def _setSSH(self): """ Generate a key pair, save it in /root/.ssh/id_rsa.pub, and return the public key. The file /root/.sshSuccess is used to prevent this operation from running twice. :return Public key. """ if not os.path.exists('/root/.sshSuccess'): subprocess.check_call(['ssh-keygen', '-f', '/root/.ssh/id_rsa', '-t', 'rsa', '-N', '']) with open('/root/.sshSuccess', 'w') as f: f.write('written here because of restrictive permissions on .ssh dir') os.chmod('/root/.ssh', 0o700) subprocess.check_call(['bash', '-c', 'eval $(ssh-agent) && ssh-add -k']) with open('/root/.ssh/id_rsa.pub') as f: masterPublicKey = f.read() masterPublicKey = masterPublicKey.split(' ')[1] # take 'body' of key # confirm it really is an RSA public key assert masterPublicKey.startswith('AAAAB3NzaC1yc2E'), masterPublicKey return masterPublicKey cloudConfigTemplate = """#cloud-config write_files: - path: "/home/core/volumes.sh" permissions: "0777" owner: "root" content: | #!/bin/bash set -x ephemeral_count=0 drives="" directories="toil mesos docker cwl" for drive in /dev/xvd{{a..z}} /dev/nvme{{0..26}}n1; do echo checking for $drive if [ -b $drive ]; then echo found it if mount | grep $drive; then echo "already mounted, likely a root device" else ephemeral_count=$((ephemeral_count + 1 )) drives="$drives $drive" echo increased ephemeral count by one fi fi done if (("$ephemeral_count" == "0" )); then echo no ephemeral drive for directory in $directories; do sudo mkdir -p /var/lib/$directory done exit 0 fi sudo mkdir /mnt/ephemeral if (("$ephemeral_count" == "1" )); then echo one ephemeral drive to mount sudo mkfs.ext4 -F $drives sudo mount $drives /mnt/ephemeral fi if (("$ephemeral_count" > "1" )); then echo multiple drives for drive in $drives; do dd if=/dev/zero of=$drive bs=4096 count=1024 done sudo mdadm --create -f --verbose /dev/md0 --level=0 --raid-devices=$ephemeral_count $drives # determine force flag sudo mkfs.ext4 -F /dev/md0 sudo mount /dev/md0 /mnt/ephemeral fi for directory in $directories; do sudo mkdir -p /mnt/ephemeral/var/lib/$directory sudo mkdir -p /var/lib/$directory sudo mount --bind /mnt/ephemeral/var/lib/$directory /var/lib/$directory done coreos: update: reboot-strategy: off units: - name: "volume-mounting.service" command: "start" content: | [Unit] Description=mounts ephemeral volumes & bind mounts toil directories Before=docker.service [Service] Type=oneshot Restart=no ExecStart=/usr/bin/bash /home/core/volumes.sh - name: "toil-{role}.service" command: "start" content: | [Unit] Description=toil-{role} container After=docker.service [Service] Restart=on-failure RestartSec=2 ExecStartPre=-/usr/bin/docker rm toil_{role} ExecStart=/usr/bin/docker run \ --entrypoint={entrypoint} \ --net=host \ -v /var/run/docker.sock:/var/run/docker.sock \ -v /var/lib/mesos:/var/lib/mesos \ -v /var/lib/docker:/var/lib/docker \ -v /var/lib/toil:/var/lib/toil \ -v /var/lib/cwl:/var/lib/cwl \ -v /tmp:/tmp \ --name=toil_{role} \ {dockerImage} \ {mesosArgs} - name: "node-exporter.service" command: "start" content: | [Unit] Description=node-exporter container After=docker.service [Service] Restart=on-failure RestartSec=2 ExecStartPre=-/usr/bin/docker rm node_exporter ExecStart=/usr/bin/docker run \ -p 9100:9100 \ -v /proc:/host/proc \ -v /sys:/host/sys \ -v /:/rootfs \ --name node-exporter \ --restart always \ prom/node-exporter:v0.15.2 \ --path.procfs /host/proc \ --path.sysfs /host/sys \ --collector.filesystem.ignored-mount-points ^/(sys|proc|dev|host|etc)($|/) """ sshTemplate = """ssh_authorized_keys: - "ssh-rsa {sshKey}" """ # If keys are rsynced, then the mesos-slave needs to be started after the keys have been # transferred. The waitForKey.sh script loops on the new VM until it finds the keyPath file, then it starts the # mesos-slave. If there are multiple keys to be transferred, then the last one to be transferred must be # set to keyPath. MESOS_LOG_DIR = '--log_dir=/var/lib/mesos ' LEADER_DOCKER_ARGS = '--registry=in_memory --cluster={name}' # --no-systemd_enable_support is necessary in Ubuntu 16.04 (otherwise, # Mesos attempts to contact systemd but can't find its run file) WORKER_DOCKER_ARGS = '--work_dir=/var/lib/mesos --master={ip}:5050 --attributes=preemptable:{preemptable} --no-hostname_lookup --no-systemd_enable_support' def _getCloudConfigUserData(self, role, masterPublicKey=None, keyPath=None, preemptable=False): """ Return the text (not bytes) user data to pass to a provisioned node. """ if role == 'leader': entryPoint = 'mesos-master' mesosArgs = self.MESOS_LOG_DIR + self.LEADER_DOCKER_ARGS.format(name=self.clusterName) elif role == 'worker': entryPoint = 'mesos-slave' mesosArgs = self.MESOS_LOG_DIR + self.WORKER_DOCKER_ARGS.format(ip=self._leaderPrivateIP, preemptable=preemptable) else: raise RuntimeError("Unknown role %s" % role) template = self.cloudConfigTemplate if masterPublicKey: template += self.sshTemplate if keyPath: mesosArgs = keyPath + ' ' + mesosArgs entryPoint = "waitForKey.sh" customDockerInitCommand = customDockerInitCmd() if customDockerInitCommand: mesosArgs = " ".join(["'" + customDockerInitCommand + "'", entryPoint, mesosArgs]) entryPoint = "customDockerInit.sh" templateArgs = dict(role=role, dockerImage=applianceSelf(), entrypoint=entryPoint, sshKey=masterPublicKey, # ignored if None mesosArgs=mesosArgs) userData = template.format(**templateArgs) return userData toil-releases-3.24.0/src/toil/provisioners/ansibleDriver.py000066400000000000000000000041071362134276200240230ustar00rootroot00000000000000# Copyright (C) 2015 UCSC Computational Genomics Lab # # 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. import logging import os import subprocess from toil.provisioners.abstractProvisioner import AbstractProvisioner logger = logging.getLogger(__name__) class AnsibleDriver(AbstractProvisioner): """ Wrapper class for Ansible calls. """ def __init__(self, playbooks, clusterName, zone, nodeStorage): self.playbooks = playbooks super(AnsibleDriver, self).__init__(clusterName, zone, nodeStorage) def callPlaybook(self, playbook, ansibleArgs, wait=True, tags=["all"]): """ Run a playbook. :param playbook: An Ansible playbook to run. :param ansibleArgs: Arguments to pass to the playbook. :param wait: Wait for the play to finish if true. :param tags: Control tags for the play. """ playbook = os.path.join(self.playbooks, playbook) # Path to playbook being executed verbosity = "-vvvvv" if logger.isEnabledFor(logging.DEBUG) else "-v" command = ["ansible-playbook", verbosity, "--tags", ",".join(tags), "--extra-vars"] command.append(" ".join(["=".join(i) for i in ansibleArgs.items()])) # Arguments being passed to playbook command.append(playbook) logger.debug("Executing Ansible call `%s`", " ".join(command)) p = subprocess.Popen(command) if wait: p.communicate() if p.returncode != 0: # FIXME: parse error codes raise RuntimeError("Ansible reported an error when executing playbook %s" % playbook) toil-releases-3.24.0/src/toil/provisioners/aws/000077500000000000000000000000001362134276200214505ustar00rootroot00000000000000toil-releases-3.24.0/src/toil/provisioners/aws/__init__.py000066400000000000000000000247421362134276200235720ustar00rootroot00000000000000# Copyright (C) 2015 UCSC Computational Genomics Lab # # 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. import logging import os from collections import namedtuple from difflib import get_close_matches from operator import attrgetter import datetime from toil.lib.misc import std_dev, mean from six import string_types from six.moves.urllib.request import urlopen from six.moves.urllib.error import URLError logger = logging.getLogger(__name__) ZoneTuple = namedtuple('ZoneTuple', ['name', 'price_deviation']) def runningOnEC2(): def file_begins_with(path, prefix): with open(path) as f: return f.read(len(prefix)) == prefix hv_uuid_path = '/sys/hypervisor/uuid' if os.path.exists(hv_uuid_path) and file_begins_with(hv_uuid_path, 'ec2'): return True # Some instances do not have the /sys/hypervisor/uuid file, so check the identity document instead. # See https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/instance-identity-documents.html try: urlopen('http://169.254.169.254/latest/dynamic/instance-identity/document', timeout=1) return True except URLError: return False def zoneToRegion(zone): """Get a region (e.g. us-west-2) from a zone (e.g. us-west-1c).""" from toil.lib.context import Context return Context.availability_zone_re.match(zone).group(1) def getSpotZone(spotBid, nodeType, ctx): return _getCurrentAWSZone(spotBid, nodeType, ctx) def getCurrentAWSZone(): return _getCurrentAWSZone() def _getCurrentAWSZone(spotBid=None, nodeType=None, ctx=None): zone = None try: import boto from boto.utils import get_instance_metadata except ImportError: pass else: zone = os.environ.get('TOIL_AWS_ZONE', None) if not zone and runningOnEC2(): try: zone = get_instance_metadata()['placement']['availability-zone'] except KeyError: pass if not zone and spotBid: # if spot bid is present, all the other parameters must be as well assert bool(spotBid) == bool(nodeType) == bool(ctx) # if the zone is unset and we are using the spot market, optimize our # choice based on the spot history return optimize_spot_bid(ctx=ctx, instance_type=nodeType, spot_bid=float(spotBid)) if not zone: zone = boto.config.get('Boto', 'ec2_region_name') if zone is not None: zone += 'a' # derive an availability zone in the region return zone def choose_spot_zone(zones, bid, spot_history): """ Returns the zone to put the spot request based on, in order of priority: 1) zones with prices currently under the bid 2) zones with the most stable price :param list[boto.ec2.zone.Zone] zones: :param float bid: :param list[boto.ec2.spotpricehistory.SpotPriceHistory] spot_history: :rtype: str :return: the name of the selected zone >>> from collections import namedtuple >>> FauxHistory = namedtuple('FauxHistory', ['price', 'availability_zone']) >>> ZoneTuple = namedtuple('ZoneTuple', ['name']) >>> zones = [ZoneTuple('us-west-2a'), ZoneTuple('us-west-2b')] >>> spot_history = [FauxHistory(0.1, 'us-west-2a'), \ FauxHistory(0.2, 'us-west-2a'), \ FauxHistory(0.3, 'us-west-2b'), \ FauxHistory(0.6, 'us-west-2b')] >>> choose_spot_zone(zones, 0.15, spot_history) 'us-west-2a' >>> spot_history=[FauxHistory(0.3, 'us-west-2a'), \ FauxHistory(0.2, 'us-west-2a'), \ FauxHistory(0.1, 'us-west-2b'), \ FauxHistory(0.6, 'us-west-2b')] >>> choose_spot_zone(zones, 0.15, spot_history) 'us-west-2b' >>> spot_history=[FauxHistory(0.1, 'us-west-2a'), \ FauxHistory(0.7, 'us-west-2a'), \ FauxHistory(0.1, 'us-west-2b'), \ FauxHistory(0.6, 'us-west-2b')] >>> choose_spot_zone(zones, 0.15, spot_history) 'us-west-2b' """ # Create two lists of tuples of form: [(zone.name, std_deviation), ...] one for zones # over the bid price and one for zones under bid price. Each are sorted by increasing # standard deviation values. markets_under_bid, markets_over_bid = [], [] for zone in zones: zone_histories = [zone_history for zone_history in spot_history if zone_history.availability_zone == zone.name] if zone_histories: price_deviation = std_dev([history.price for history in zone_histories]) recent_price = zone_histories[0].price else: price_deviation, recent_price = 0.0, bid zone_tuple = ZoneTuple(name=zone.name, price_deviation=price_deviation) (markets_over_bid, markets_under_bid)[recent_price < bid].append(zone_tuple) return min(markets_under_bid or markets_over_bid, key=attrgetter('price_deviation')).name def optimize_spot_bid(ctx, instance_type, spot_bid): """ Check whether the bid is sane and makes an effort to place the instance in a sensible zone. """ spot_history = _get_spot_history(ctx, instance_type) if spot_history: _check_spot_bid(spot_bid, spot_history) zones = ctx.ec2.get_all_zones() most_stable_zone = choose_spot_zone(zones, spot_bid, spot_history) logger.debug("Placing spot instances in zone %s.", most_stable_zone) return most_stable_zone def _check_spot_bid(spot_bid, spot_history): """ Prevents users from potentially over-paying for instances Note: this checks over the whole region, not a particular zone :param spot_bid: float :type spot_history: list[SpotPriceHistory] :raises UserError: if bid is > 2X the spot price's average >>> from collections import namedtuple >>> FauxHistory = namedtuple( "FauxHistory", [ "price", "availability_zone" ] ) >>> spot_data = [ FauxHistory( 0.1, "us-west-2a" ), \ FauxHistory( 0.2, "us-west-2a" ), \ FauxHistory( 0.3, "us-west-2b" ), \ FauxHistory( 0.6, "us-west-2b" ) ] >>> # noinspection PyProtectedMember >>> _check_spot_bid( 0.1, spot_data ) >>> # noinspection PyProtectedMember # >>> Box._check_spot_bid( 2, spot_data ) Traceback (most recent call last): ... UserError: Your bid $ 2.000000 is more than double this instance type's average spot price ($ 0.300000) over the last week """ average = mean([datum.price for datum in spot_history]) if spot_bid > average * 2: logger.warn("Your bid $ %f is more than double this instance type's average " "spot price ($ %f) over the last week", spot_bid, average) def _get_spot_history(ctx, instance_type): """ Returns list of 1,000 most recent spot market data points represented as SpotPriceHistory objects. Note: The most recent object/data point will be first in the list. :rtype: list[SpotPriceHistory] """ one_week_ago = datetime.datetime.now() - datetime.timedelta(days=7) spot_data = ctx.ec2.get_spot_price_history(start_time=one_week_ago.isoformat(), instance_type=instance_type, product_description="Linux/UNIX") spot_data.sort(key=attrgetter("timestamp"), reverse=True) return spot_data ec2FullPolicy = dict(Version="2012-10-17", Statement=[ dict(Effect="Allow", Resource="*", Action="ec2:*")]) s3FullPolicy = dict(Version="2012-10-17", Statement=[ dict(Effect="Allow", Resource="*", Action="s3:*")]) sdbFullPolicy = dict(Version="2012-10-17", Statement=[ dict(Effect="Allow", Resource="*", Action="sdb:*")]) iamFullPolicy = dict(Version="2012-10-17", Statement=[ dict(Effect="Allow", Resource="*", Action="iam:*")]) def checkValidNodeTypes(provisioner, nodeTypes): """ Raises if an invalid nodeType is specified for aws or gce. :param str provisioner: 'aws' or 'gce' to specify which cloud provisioner used. :param nodeTypes: A list of node types. Example: ['t2.micro', 't2.medium'] :return: Nothing. Raises if invalid nodeType. """ # TODO: Move out of "aws.__init__.py" >.> if not nodeTypes: return if not isinstance(nodeTypes, list): nodeTypes = [nodeTypes] if not isinstance(nodeTypes[0], string_types): return # check if a valid node type for aws from toil.lib.generatedEC2Lists import E2Instances, regionDict if provisioner == 'aws': from toil.provisioners.aws import getCurrentAWSZone currentZone = getCurrentAWSZone() if not currentZone: currentZone = 'us-west-2' else: currentZone = currentZone[:-1] # adds something like 'a' or 'b' to the end # check if instance type exists in this region for nodeType in nodeTypes: if nodeType and ':' in nodeType: nodeType = nodeType.split(':')[0] if nodeType not in regionDict[currentZone]: # They probably misspelled it and can't tell. close = get_close_matches(nodeType, regionDict[currentZone], 1) if len(close) > 0: helpText = ' Did you mean ' + close[0] + '?' else: helpText = '' raise RuntimeError('Invalid nodeType (%s) specified for AWS in region: %s.%s' '' % (nodeType, currentZone, helpText)) elif provisioner == 'gce': for nodeType in nodeTypes: if nodeType and ':' in nodeType: nodeType = nodeType.split(':')[0] try: E2Instances[nodeType] raise RuntimeError("It looks like you've specified an AWS nodeType with the " "{} provisioner. Please specify an {} nodeType." "".format(provisioner, provisioner)) except KeyError: pass else: raise RuntimeError("Invalid provisioner: {}".format(provisioner)) toil-releases-3.24.0/src/toil/provisioners/aws/awsProvisioner.py000066400000000000000000000730361362134276200250650ustar00rootroot00000000000000# Copyright (C) 2015 UCSC Computational Genomics Lab # # 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. from functools import wraps from builtins import str from builtins import range import time import string # Python 3 compatibility imports from _ssl import SSLError from six import iteritems, text_type from toil.lib.memoize import memoize import boto.ec2 from boto.ec2.blockdevicemapping import BlockDeviceMapping, BlockDeviceType from boto.exception import BotoServerError, EC2ResponseError from boto.utils import get_instance_metadata from toil.lib.ec2 import (a_short_time, create_ondemand_instances, create_spot_instances, wait_instances_running, wait_transition) from toil.lib.misc import truncExpBackoff from toil.provisioners.abstractProvisioner import AbstractProvisioner, Shape from toil.provisioners.aws import * from toil.lib.context import Context from toil.lib.retry import retry from toil.lib.memoize import less_strict_bool from toil.provisioners import NoSuchClusterException from toil.provisioners.node import Node from toil.lib.generatedEC2Lists import E2Instances logger = logging.getLogger(__name__) logging.getLogger("boto").setLevel(logging.CRITICAL) # Role name (used as the suffix) for EC2 instance profiles that are automatically created by Toil. _INSTANCE_PROFILE_ROLE_NAME = 'toil' # The tag key that specifies the Toil node type ("leader" or "worker") so that # leader vs. worker nodes can be robustly identified. _TOIL_NODE_TYPE_TAG_KEY = 'ToilNodeType' def awsRetryPredicate(e): if not isinstance(e, BotoServerError): return False # boto/AWS gives multiple messages for the same error... if e.status == 503 and 'Request limit exceeded' in e.body: return True elif e.status == 400 and 'Rate exceeded' in e.body: return True elif e.status == 400 and 'NotFound' in e.body: # EC2 can take a while to propagate instance IDs to all servers. return True elif e.status == 400 and e.error_code == 'Throttling': return True return False def awsFilterImpairedNodes(nodes, ec2): # if TOIL_AWS_NODE_DEBUG is set don't terminate nodes with # failing status checks so they can be debugged nodeDebug = less_strict_bool(os.environ.get('TOIL_AWS_NODE_DEBUG')) if not nodeDebug: return nodes nodeIDs = [node.id for node in nodes] statuses = ec2.get_all_instance_status(instance_ids=nodeIDs) statusMap = {status.id: status.instance_status for status in statuses} healthyNodes = [node for node in nodes if statusMap.get(node.id, None) != 'impaired'] impairedNodes = [node.id for node in nodes if statusMap.get(node.id, None) == 'impaired'] logger.warn('TOIL_AWS_NODE_DEBUG is set and nodes %s have failed EC2 status checks so ' 'will not be terminated.', ' '.join(impairedNodes)) return healthyNodes def awsRetry(f): """ This decorator retries the wrapped function if aws throws unexpected errors errors. It should wrap any function that makes use of boto """ @wraps(f) def wrapper(*args, **kwargs): for attempt in retry(delays=truncExpBackoff(), timeout=300, predicate=awsRetryPredicate): with attempt: return f(*args, **kwargs) return wrapper class InvalidClusterStateException(Exception): pass class AWSProvisioner(AbstractProvisioner): """ Implements an AWS provisioner using the boto libraries. """ def __init__(self, clusterName, zone, nodeStorage, sseKey): super(AWSProvisioner, self).__init__(clusterName, zone, nodeStorage) self.cloud = 'aws' self._sseKey = sseKey if not zone: self._zone = getCurrentAWSZone() if clusterName: self._buildContext() # create connection (self._ctx) else: self._readClusterSettings() def _readClusterSettings(self): """ Reads the cluster settings from the instance metadata, which assumes the instance is the leader. """ instanceMetaData = get_instance_metadata() region = zoneToRegion(self._zone) conn = boto.ec2.connect_to_region(region) instance = conn.get_all_instances(instance_ids=[instanceMetaData["instance-id"]])[0].instances[0] self.clusterName = str(instance.tags["Name"]) self._buildContext() self._subnetID = instance.subnet_id self._leaderPrivateIP = instanceMetaData['local-ipv4'] # this is PRIVATE IP self._keyName = list(instanceMetaData['public-keys'].keys())[0] self._tags = self.getLeader().tags self._masterPublicKey = self._setSSH() self._leaderProfileArn = instanceMetaData['iam']['info']['InstanceProfileArn'] def launchCluster(self, leaderNodeType, leaderStorage, owner, **kwargs): """ In addition to the parameters inherited from the abstractProvisioner, the AWS launchCluster takes the following parameters: keyName: The key used to communicate with instances vpcSubnet: A subnet (optional). """ if 'keyName' not in kwargs: raise RuntimeError("A keyPairName is required for the AWS provisioner.") self._keyName = kwargs['keyName'] self._vpcSubnet = kwargs.get('vpcSubnet') profileArn = kwargs.get('awsEc2ProfileArn') or self._getProfileArn() # the security group name is used as the cluster identifier sgs = self._createSecurityGroup() bdm = self._getBlockDeviceMapping(E2Instances[leaderNodeType], rootVolSize=leaderStorage) self._masterPublicKey = 'AAAAB3NzaC1yc2Enoauthorizedkeyneeded' # dummy key userData = self._getCloudConfigUserData('leader', self._masterPublicKey) if isinstance(userData, text_type): # Spot-market provisioning requires bytes for user data. # We probably won't have a spot-market leader, but who knows! userData = userData.encode('utf-8') specKwargs = {'key_name': self._keyName, 'security_group_ids': [sg.id for sg in sgs], 'instance_type': leaderNodeType, 'user_data': userData, 'block_device_map': bdm, 'instance_profile_arn': profileArn, 'placement': self._zone} if self._vpcSubnet: specKwargs["subnet_id"] = self._vpcSubnet instances = create_ondemand_instances(self._ctx.ec2, image_id=self._discoverAMI(), spec=specKwargs, num_instances=1) # wait for the leader to finish setting up leader = instances[0] wait_instances_running(self._ctx.ec2, [leader]) self._waitForIP(leader) leaderNode = Node(publicIP=leader.ip_address, privateIP=leader.private_ip_address, name=leader.id, launchTime=leader.launch_time, nodeType=leaderNodeType, preemptable=False, tags=leader.tags) leaderNode.waitForNode('toil_leader') defaultTags = {'Name': self.clusterName, 'Owner': owner, _TOIL_NODE_TYPE_TAG_KEY: 'leader'} if kwargs['userTags']: defaultTags.update(kwargs['userTags']) # if we running launch cluster we need to save this data as it won't be generated # from the metadata. This data is needed to launch worker nodes. self._leaderPrivateIP = leader.private_ip_address self._addTags([leader], defaultTags) self._tags = leader.tags self._subnetID = leader.subnet_id def getNodeShape(self, nodeType, preemptable=False): instanceType = E2Instances[nodeType] disk = instanceType.disks * instanceType.disk_capacity * 2 ** 30 if disk == 0: # This is an EBS-backed instance. We will use the root # volume, so add the amount of EBS storage requested for # the root volume disk = self._nodeStorage * 2 ** 30 #Underestimate memory by 100M to prevent autoscaler from disagreeing with #mesos about whether a job can run on a particular node type memory = (instanceType.memory - 0.1) * 2** 30 return Shape(wallTime=60 * 60, memory=memory, cores=instanceType.cores, disk=disk, preemptable=preemptable) @staticmethod def retryPredicate(e): return awsRetryPredicate(e) def destroyCluster(self): """ Terminate instances and delete the profile and security group. """ assert self._ctx def expectedShutdownErrors(e): return e.status == 400 and 'dependent object' in e.body def destroyInstances(instances): """ Similar to _terminateInstances, except that it also cleans up any resources associated with the instances (e.g. IAM profiles). """ self._deleteIAMProfiles(instances) self._terminateInstances(instances) # We should terminate the leader first in case a workflow is still running in the cluster. # The leader may create more instances while we're terminating the workers. vpcId = None try: leader = self.getLeader(returnRawInstance=True) vpcId = leader.vpc_id logger.info('Terminating the leader first ...') destroyInstances([leader]) logger.info('Now terminating any remaining workers ...') except (NoSuchClusterException, InvalidClusterStateException): # It's ok if the leader is not found. We'll terminate any remaining # instances below anyway. pass instances = self._getNodesInCluster(nodeType=None, both=True) spotIDs = self._getSpotRequestIDs() if spotIDs: self._ctx.ec2.cancel_spot_instance_requests(request_ids=spotIDs) instancesToTerminate = awsFilterImpairedNodes(instances, self._ctx.ec2) if instancesToTerminate: vpcId = vpcId or instancesToTerminate[0].vpc_id destroyInstances(instancesToTerminate) if len(instances) == len(instancesToTerminate): logger.debug('Deleting security group...') removed = False for attempt in retry(timeout=300, predicate=expectedShutdownErrors): with attempt: for sg in self._ctx.ec2.get_all_security_groups(): if sg.name == self.clusterName and vpcId and sg.vpc_id == vpcId: try: self._ctx.ec2.delete_security_group(group_id=sg.id) removed = True except BotoServerError as e: if e.error_code == 'InvalidGroup.NotFound': pass else: raise if removed: logger.debug('... Succesfully deleted security group') else: assert len(instances) > len(instancesToTerminate) # the security group can't be deleted until all nodes are terminated logger.warning('The TOIL_AWS_NODE_DEBUG environment variable is set and some nodes ' 'have failed health checks. As a result, the security group & IAM ' 'roles will not be deleted.') def terminateNodes(self, nodes): instanceIDs = [x.name for x in nodes] self._terminateIDs(instanceIDs) def addNodes(self, nodeType, numNodes, preemptable, spotBid=None): assert self._leaderPrivateIP if preemptable and not spotBid: if self._spotBidsMap and nodeType in self._spotBidsMap: spotBid = self._spotBidsMap[nodeType] else: raise RuntimeError("No spot bid given for a preemptable node request.") instanceType = E2Instances[nodeType] bdm = self._getBlockDeviceMapping(instanceType, rootVolSize=self._nodeStorage) keyPath = self._sseKey if self._sseKey else None userData = self._getCloudConfigUserData('worker', self._masterPublicKey, keyPath, preemptable) if isinstance(userData, text_type): # Spot-market provisioning requires bytes for user data. userData = userData.encode('utf-8') sgs = [sg for sg in self._ctx.ec2.get_all_security_groups() if sg.name == self.clusterName] kwargs = {'key_name': self._keyName, 'security_group_ids': [sg.id for sg in sgs], 'instance_type': instanceType.name, 'user_data': userData, 'block_device_map': bdm, 'instance_profile_arn': self._leaderProfileArn, 'placement': self._zone, 'subnet_id': self._subnetID} instancesLaunched = [] for attempt in retry(predicate=awsRetryPredicate): with attempt: # after we start launching instances we want to ensure the full setup is done # the biggest obstacle is AWS request throttling, so we retry on these errors at # every request in this method if not preemptable: logger.debug('Launching %s non-preemptable nodes', numNodes) instancesLaunched = create_ondemand_instances(self._ctx.ec2, image_id=self._discoverAMI(), spec=kwargs, num_instances=numNodes) else: logger.debug('Launching %s preemptable nodes', numNodes) kwargs['placement'] = getSpotZone(spotBid, instanceType.name, self._ctx) # force generator to evaluate instancesLaunched = list(create_spot_instances(ec2=self._ctx.ec2, price=spotBid, image_id=self._discoverAMI(), tags={'clusterName': self.clusterName}, spec=kwargs, num_instances=numNodes, tentative=True) ) # flatten the list instancesLaunched = [item for sublist in instancesLaunched for item in sublist] for attempt in retry(predicate=awsRetryPredicate): with attempt: wait_instances_running(self._ctx.ec2, instancesLaunched) self._tags[_TOIL_NODE_TYPE_TAG_KEY] = 'worker' AWSProvisioner._addTags(instancesLaunched, self._tags) if self._sseKey: for i in instancesLaunched: self._waitForIP(i) node = Node(publicIP=i.ip_address, privateIP=i.private_ip_address, name=i.id, launchTime=i.launch_time, nodeType=i.instance_type, preemptable=preemptable, tags=i.tags) node.waitForNode('toil_worker') node.coreRsync([self._sseKey, ':' + self._sseKey], applianceName='toil_worker') logger.debug('Launched %s new instance(s)', numNodes) return len(instancesLaunched) def getProvisionedWorkers(self, nodeType, preemptable): assert self._leaderPrivateIP entireCluster = self._getNodesInCluster(both=True, nodeType=nodeType) logger.debug('All nodes in cluster: %s', entireCluster) workerInstances = [i for i in entireCluster if i.private_ip_address != self._leaderPrivateIP] logger.debug('All workers found in cluster: %s', workerInstances) workerInstances = [i for i in workerInstances if preemptable != (i.spot_instance_request_id is None)] logger.debug('%spreemptable workers found in cluster: %s', 'non-' if not preemptable else '', workerInstances) workerInstances = awsFilterImpairedNodes(workerInstances, self._ctx.ec2) return [Node(publicIP=i.ip_address, privateIP=i.private_ip_address, name=i.id, launchTime=i.launch_time, nodeType=i.instance_type, preemptable=preemptable, tags=i.tags) for i in workerInstances] def _buildContext(self): if self._zone is None: self._zone = getCurrentAWSZone() if self._zone is None: raise RuntimeError( 'Could not determine availability zone. Ensure that one of the following ' 'is true: the --zone flag is set, the TOIL_AWS_ZONE environment variable ' 'is set, ec2_region_name is set in the .boto file, or that ' 'you are running on EC2.') logger.debug("Building AWS context in zone %s for cluster %s" % (self._zone, self.clusterName)) self._ctx = Context(availability_zone=self._zone, namespace=self._toNameSpace()) @memoize def _discoverAMI(self): def descriptionMatches(ami): return ami.description is not None and 'stable 1855.5.0' in ami.description coreOSAMI = os.environ.get('TOIL_AWS_AMI') if coreOSAMI is not None: return coreOSAMI for attempt in retry(predicate=lambda e: isinstance(e, SSLError)): # SSLError is thrown when get_all_images times out with attempt: # 679593333241 is the aws marketplace account amis = self._ctx.ec2.get_all_images(owners=['679593333241'], filters={'name': 'CoreOS-stable-1855.5.0-hvm-0d1e0bd0-eaea-4397-9a3a-c56f861d2a14-ami-0f74e41ea6c13f74b.4'}) coreOSAMI = [ami for ami in amis if descriptionMatches(ami)] logger.debug('Found the following matching AMIs: %s', coreOSAMI) assert len(coreOSAMI) == 1, coreOSAMI return coreOSAMI.pop().id def _toNameSpace(self): assert isinstance(self.clusterName, (str, bytes)) if any((char.isupper() for char in self.clusterName)) or '_' in self.clusterName: raise RuntimeError("The cluster name must be lowercase and cannot contain the '_' " "character.") namespace = self.clusterName if not namespace.startswith('/'): namespace = '/' + namespace + '/' return namespace.replace('-', '/') def getLeader(self, wait=False, returnRawInstance=False): assert self._ctx instances = self._getNodesInCluster(nodeType=None, both=True) instances.sort(key=lambda x: x.launch_time) try: leader = instances[0] # assume leader was launched first except IndexError: raise NoSuchClusterException(self.clusterName) if (leader.tags.get(_TOIL_NODE_TYPE_TAG_KEY) or 'leader') != 'leader': raise InvalidClusterStateException( 'Invalid cluster state! The first launched instance appears not to be the leader ' 'as it is missing the "leader" tag. The safest recovery is to destroy the cluster ' 'and restart the job. Incorrect Leader ID: %s' % leader.id ) leaderNode = Node(publicIP=leader.ip_address, privateIP=leader.private_ip_address, name=leader.id, launchTime=leader.launch_time, nodeType=None, preemptable=False, tags=leader.tags) if wait: logger.debug("Waiting for toil_leader to enter 'running' state...") wait_instances_running(self._ctx.ec2, [leader]) logger.debug('... toil_leader is running') self._waitForIP(leader) leaderNode.waitForNode('toil_leader') return leader if returnRawInstance else leaderNode @classmethod @awsRetry def _addTag(cls, instance, key, value): instance.add_tag(key, value) @classmethod def _addTags(cls, instances, tags): for instance in instances: for key, value in iteritems(tags): cls._addTag(instance, key, value) @classmethod def _waitForIP(cls, instance): """ Wait until the instances has a public IP address assigned to it. :type instance: boto.ec2.instance.Instance """ logger.debug('Waiting for ip...') while True: time.sleep(a_short_time) instance.update() if instance.ip_address or instance.public_dns_name or instance.private_ip_address: logger.debug('...got ip') break def _terminateInstances(self, instances): instanceIDs = [x.id for x in instances] self._terminateIDs(instanceIDs) logger.info('... Waiting for instance(s) to shut down...') for instance in instances: wait_transition(instance, {'pending', 'running', 'shutting-down'}, 'terminated') logger.info('Instance(s) terminated.') @awsRetry def _terminateIDs(self, instanceIDs): assert self._ctx logger.info('Terminating instance(s): %s', instanceIDs) self._ctx.ec2.terminate_instances(instance_ids=instanceIDs) logger.info('Instance(s) terminated.') def _deleteIAMProfiles(self, instances): assert self._ctx instanceProfiles = [x.instance_profile['arn'] for x in instances] for profile in instanceProfiles: # boto won't look things up by the ARN so we have to parse it to get # the profile name profileName = profile.rsplit('/')[-1] # Only delete profiles that were automatically created by Toil. if profileName != self._ctx.to_aws_name(_INSTANCE_PROFILE_ROLE_NAME): continue try: profileResult = self._ctx.iam.get_instance_profile(profileName) except BotoServerError as e: if e.status == 404: return else: raise # wade through EC2 response object to get what we want profileResult = profileResult['get_instance_profile_response'] profileResult = profileResult['get_instance_profile_result'] profile = profileResult['instance_profile'] # this is based off of our 1:1 mapping of profiles to roles role = profile['roles']['member']['role_name'] try: self._ctx.iam.remove_role_from_instance_profile(profileName, role) except BotoServerError as e: if e.status == 404: pass else: raise policyResults = self._ctx.iam.list_role_policies(role) policyResults = policyResults['list_role_policies_response'] policyResults = policyResults['list_role_policies_result'] policies = policyResults['policy_names'] for policyName in policies: try: self._ctx.iam.delete_role_policy(role, policyName) except BotoServerError as e: if e.status == 404: pass else: raise try: self._ctx.iam.delete_role(role) except BotoServerError as e: if e.status == 404: pass else: raise try: self._ctx.iam.delete_instance_profile(profileName) except BotoServerError as e: if e.status == 404: pass else: raise @classmethod def _getBlockDeviceMapping(cls, instanceType, rootVolSize=50): # determine number of ephemeral drives via cgcloud-lib (actually this is moved into toil's lib bdtKeys = [''] + ['/dev/xvd{}'.format(c) for c in string.ascii_lowercase[1:]] bdm = BlockDeviceMapping() # Change root volume size to allow for bigger Docker instances root_vol = BlockDeviceType(delete_on_termination=True) root_vol.size = rootVolSize bdm["/dev/xvda"] = root_vol # The first disk is already attached for us so start with 2nd. # Disk count is weirdly a float in our instance database, so make it an int here. for disk in range(1, int(instanceType.disks) + 1): bdm[bdtKeys[disk]] = BlockDeviceType( ephemeral_name='ephemeral{}'.format(disk - 1)) # ephemeral counts start at 0 logger.debug('Device mapping: %s', bdm) return bdm @awsRetry def _getNodesInCluster(self, nodeType=None, preemptable=False, both=False): assert self._ctx allInstances = self._ctx.ec2.get_only_instances(filters={'instance.group-name': self.clusterName}) def instanceFilter(i): # filter by type only if nodeType is true rightType = not nodeType or i.instance_type == nodeType rightState = i.state == 'running' or i.state == 'pending' return rightType and rightState filteredInstances = [i for i in allInstances if instanceFilter(i)] if not preemptable and not both: return [i for i in filteredInstances if i.spot_instance_request_id is None] elif preemptable and not both: return [i for i in filteredInstances if i.spot_instance_request_id is not None] elif both: return filteredInstances def _getSpotRequestIDs(self): assert self._ctx requests = self._ctx.ec2.get_all_spot_instance_requests() tags = self._ctx.ec2.get_all_tags({'tag:': {'clusterName': self.clusterName}}) idsToCancel = [tag.id for tag in tags] return [request for request in requests if request.id in idsToCancel] def _createSecurityGroup(self): assert self._ctx def groupNotFound(e): retry = (e.status == 400 and 'does not exist in default VPC' in e.body) return retry vpcId = None if self._vpcSubnet: conn = boto.connect_vpc(region=self._ctx.ec2.region) subnets = conn.get_all_subnets(subnet_ids=[self._vpcSubnet]) if len(subnets) > 0: vpcId = subnets[0].vpc_id # security group create/get. ssh + all ports open within the group try: web = self._ctx.ec2.create_security_group(self.clusterName, 'Toil appliance security group', vpc_id=vpcId) except EC2ResponseError as e: if e.status == 400 and 'already exists' in e.body: pass # group exists- nothing to do else: raise else: for attempt in retry(predicate=groupNotFound, timeout=300): with attempt: # open port 22 for ssh-ing web.authorize(ip_protocol='tcp', from_port=22, to_port=22, cidr_ip='0.0.0.0/0') for attempt in retry(predicate=groupNotFound, timeout=300): with attempt: # the following authorizes all TCP access within the web security group web.authorize(ip_protocol='tcp', from_port=0, to_port=65535, src_group=web) for attempt in retry(predicate=groupNotFound, timeout=300): with attempt: # We also want to open up UDP, both for user code and for the RealtimeLogger web.authorize(ip_protocol='udp', from_port=0, to_port=65535, src_group=web) out = [] for sg in self._ctx.ec2.get_all_security_groups(): if sg.name == self.clusterName and (vpcId is None or sg.vpc_id == vpcId): out.append(sg) return out @awsRetry def _getProfileArn(self): assert self._ctx def addRoleErrors(e): return e.status == 404 policy = dict(iam_full=iamFullPolicy, ec2_full=ec2FullPolicy, s3_full=s3FullPolicy, sbd_full=sdbFullPolicy) iamRoleName = self._ctx.setup_iam_ec2_role(role_name=_INSTANCE_PROFILE_ROLE_NAME, policies=policy) try: profile = self._ctx.iam.get_instance_profile(iamRoleName) except BotoServerError as e: if e.status == 404: profile = self._ctx.iam.create_instance_profile(iamRoleName) profile = profile.create_instance_profile_response.create_instance_profile_result else: raise else: profile = profile.get_instance_profile_response.get_instance_profile_result profile = profile.instance_profile profile_arn = profile.arn if len(profile.roles) > 1: raise RuntimeError('Did not expect profile to contain more than one role') elif len(profile.roles) == 1: # this should be profile.roles[0].role_name if profile.roles.member.role_name == iamRoleName: return profile_arn else: self._ctx.iam.remove_role_from_instance_profile(iamRoleName, profile.roles.member.role_name) for attempt in retry(predicate=addRoleErrors): with attempt: self._ctx.iam.add_role_to_instance_profile(iamRoleName, iamRoleName) return profile_arn toil-releases-3.24.0/src/toil/provisioners/clusterScaler.py000066400000000000000000001365301362134276200240530ustar00rootroot00000000000000# Copyright (C) 2015-2018 Regents of the University of California # # 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. from __future__ import absolute_import from __future__ import division from future import standard_library standard_library.install_aliases() from builtins import str from builtins import map from builtins import object import json import logging import os import time from collections import defaultdict from toil.lib.retry import retry from toil.lib.threading import ExceptionalThread from toil.lib.throttle import throttle from itertools import islice from toil.batchSystems.abstractBatchSystem import AbstractScalableBatchSystem, NodeInfo from toil.provisioners.abstractProvisioner import Shape from toil.job import ServiceJobNode from toil.common import defaultTargetTime logger = logging.getLogger(__name__) class BinPackedFit(object): """ If jobShapes is a set of tasks with run requirements (mem/disk/cpu), and nodeShapes is a sorted list of available computers to run these jobs on, this function attempts to return a dictionary representing the minimum set of computerNode computers needed to run the tasks in jobShapes. Uses a first fit decreasing (FFD) bin packing like algorithm to calculate an approximate minimum number of nodes that will fit the given list of jobs. BinPackingFit assumes the ordered list, nodeShapes, is ordered for "node preference" outside of BinPackingFit beforehand. So when virtually "creating" nodes, the first node within nodeShapes that fits the job is the one that's added. :param list nodeShapes: The properties of an atomic node allocation, in terms of wall-time, memory, cores, disk, and whether it is preemptable or not. :param targetTime: The time before which all jobs should at least be started. :returns: The minimum number of minimal node allocations estimated to be required to run all the jobs in jobShapes. """ def __init__(self, nodeShapes, targetTime=defaultTargetTime): self.nodeShapes = sorted(nodeShapes) self.targetTime = targetTime self.nodeReservations = {nodeShape:[] for nodeShape in nodeShapes} def binPack(self, jobShapes): """Pack a list of jobShapes into the fewest nodes reasonable. Can be run multiple times.""" # TODO: Check for redundancy with batchsystems.mesos.JobQueue() sorting logger.debug('Running bin packing for node shapes %s and %s job(s).', self.nodeShapes, len(jobShapes)) # Sort in descending order from largest to smallest. The FFD like-strategy will pack the # jobs in order from longest to shortest. jobShapes.sort() jobShapes.reverse() assert len(jobShapes) == 0 or jobShapes[0] >= jobShapes[-1] for jS in jobShapes: self.addJobShape(jS) def addJobShape(self, jobShape): """ Function adds the job to the first node reservation in which it will fit (this is the bin-packing aspect). """ chosenNodeShape = None for nodeShape in self.nodeShapes: if NodeReservation(nodeShape).fits(jobShape): # This node shape is the first that fits this jobShape chosenNodeShape = nodeShape break if chosenNodeShape is None: logger.warning("Couldn't fit job with requirements %r into any nodes in the nodeTypes " "list." % jobShape) return # grab current list of job objects appended to this nodeType nodeReservations = self.nodeReservations[chosenNodeShape] for nodeReservation in nodeReservations: if nodeReservation.attemptToAddJob(jobShape, chosenNodeShape, self.targetTime): # We succeeded adding the job to this node reservation. Now we're done. return reservation = NodeReservation(chosenNodeShape) currentTimeAllocated = chosenNodeShape.wallTime adjustEndingReservationForJob(reservation, jobShape, 0) self.nodeReservations[chosenNodeShape].append(reservation) # Extend the reservation if necessary to cover the job's entire runtime. while currentTimeAllocated < jobShape.wallTime: extendThisReservation = NodeReservation(reservation.shape) currentTimeAllocated += chosenNodeShape.wallTime reservation.nReservation = extendThisReservation reservation = extendThisReservation def getRequiredNodes(self): """ Returns a dict from node shape to number of nodes required to run the packed jobs. """ return {nodeShape:len(self.nodeReservations[nodeShape]) for nodeShape in self.nodeShapes} class NodeReservation(object): """ Represents a node "reservation": the amount of resources that we expect to be available on a given node at each point in time. To represent the resources available in a reservation, we represent a reservation as a linked list of NodeReservations, each giving the resources free within a single timeslice. """ def __init__(self, shape): # The wall-time of this slice and resources available in this timeslice self.shape = shape # The next portion of the reservation (None if this is the end) self.nReservation = None def __str__(self): return "-------------------\n" \ "Current Reservation\n" \ "-------------------\n" \ "Shape wallTime: %s\n" \ "Shape memory: %s\n" \ "Shape cores: %s\n" \ "Shape disk: %s\n" \ "Shape preempt: %s\n" \ "\n" \ "nReserv wallTime: %s\n" \ "nReserv memory: %s\n" \ "nReserv cores: %s\n" \ "nReserv disk: %s\n" \ "nReserv preempt: %s\n" \ "\n" \ "Time slices: %s\n" \ "\n" % \ (self.shape.wallTime, self.shape.memory, self.shape.cores, self.shape.disk, self.shape.preemptable, self.nReservation.shape.wallTime if self.nReservation is not None else str(None), self.nReservation.shape.memory if self.nReservation is not None else str(None), self.nReservation.shape.cores if self.nReservation is not None else str(None), self.nReservation.shape.disk if self.nReservation is not None else str(None), self.nReservation.shape.preemptable if self.nReservation is not None else str(None), str(len(self.shapes()))) def fits(self, jobShape): """Check if a job shape's resource requirements will fit within this allocation.""" return jobShape.memory <= self.shape.memory and \ jobShape.cores <= self.shape.cores and \ jobShape.disk <= self.shape.disk and \ (jobShape.preemptable or not self.shape.preemptable) def shapes(self): """Get all time-slice shapes, in order, from this reservation on.""" shapes = [] curRes = self while curRes is not None: shapes.append(curRes.shape) curRes = curRes.nReservation return shapes def subtract(self, jobShape): """ Subtracts the resources necessary to run a jobShape from the reservation. """ self.shape = Shape(self.shape.wallTime, self.shape.memory - jobShape.memory, self.shape.cores - jobShape.cores, self.shape.disk - jobShape.disk, self.shape.preemptable) def attemptToAddJob(self, jobShape, nodeShape, targetTime): """ Attempt to pack a job into this reservation timeslice and/or the reservations after it. jobShape is the Shape of the job requirements, nodeShape is the Shape of the node this is a reservation for, and targetTime is the maximum time to wait before starting this job. """ # starting slice of time that we can fit in so far startingReservation = self # current end of the slices we can fit in so far endingReservation = startingReservation # the amount of runtime of the job currently covered by slices availableTime = 0 # total time from when the instance started up to startingReservation startingReservationTime = 0 while True: # True == can run the job (resources & preemptable only; NO time) if endingReservation.fits(jobShape): # add the time left available on the reservation availableTime += endingReservation.shape.wallTime # does the job time fit in the reservation's remaining time? if availableTime >= jobShape.wallTime: timeSlice = 0 while startingReservation != endingReservation: # removes resources only (NO time) from startingReservation startingReservation.subtract(jobShape) # set aside the timeSlice timeSlice += startingReservation.shape.wallTime startingReservation = startingReservation.nReservation assert jobShape.wallTime - timeSlice <= startingReservation.shape.wallTime adjustEndingReservationForJob(endingReservation, jobShape, timeSlice) # Packed the job. return True # If the job would fit, but is longer than the total node allocation # extend the node allocation elif endingReservation.nReservation == None and startingReservation == self: # Extend the node reservation to accommodate jobShape endingReservation.nReservation = NodeReservation(nodeShape) # can't run the job with the current resources else: if startingReservationTime + availableTime + endingReservation.shape.wallTime <= targetTime: startingReservation = endingReservation.nReservation startingReservationTime += availableTime + endingReservation.shape.wallTime availableTime = 0 else: break endingReservation = endingReservation.nReservation if endingReservation is None: # Reached the end of the reservation without success so stop trying to # add to reservation break # Couldn't pack the job. return False def adjustEndingReservationForJob(reservation, jobShape, wallTime): """ Add a job to an ending reservation that ends at wallTime, splitting the reservation if the job doesn't fill the entire timeslice. """ if jobShape.wallTime - wallTime < reservation.shape.wallTime: # This job only partially fills one of the slices. Create a new slice. reservation.shape, nS = split(reservation.shape, jobShape, jobShape.wallTime - wallTime) nS.nReservation = reservation.nReservation reservation.nReservation = nS else: # This job perfectly fits within the boundaries of the slices. reservation.subtract(jobShape) def split(nodeShape, jobShape, wallTime): """ Partition a node allocation into two to fit the job, returning the modified shape of the node and a new node reservation for the extra time that the job didn't fill. """ return (Shape(wallTime, nodeShape.memory - jobShape.memory, nodeShape.cores - jobShape.cores, nodeShape.disk - jobShape.disk, nodeShape.preemptable), NodeReservation(Shape(nodeShape.wallTime - wallTime, nodeShape.memory, nodeShape.cores, nodeShape.disk, nodeShape.preemptable))) def binPacking(nodeShapes, jobShapes, goalTime): bpf = BinPackedFit(nodeShapes, goalTime) bpf.binPack(jobShapes) return bpf.getRequiredNodes() class ClusterScaler(object): def __init__(self, provisioner, leader, config): """ Class manages automatically scaling the number of worker nodes. :param AbstractProvisioner provisioner: Provisioner instance to scale. :param toil.leader.Leader leader: :param Config config: Config object from which to draw parameters. """ self.provisioner = provisioner self.leader = leader self.config = config self.static = {} # Dictionary of job names to their average runtime, used to estimate wall time of queued # jobs for bin-packing self.jobNameToAvgRuntime = {} self.jobNameToNumCompleted = {} self.totalAvgRuntime = 0.0 self.totalJobsCompleted = 0 self.targetTime = config.targetTime if self.targetTime <= 0: raise RuntimeError('targetTime (%s) must be a positive integer!' % self.targetTime) self.betaInertia = config.betaInertia if not 0.0 <= self.betaInertia <= 0.9: raise RuntimeError('betaInertia (%f) must be between 0.0 and 0.9!' % self.betaInertia) self.nodeTypes = provisioner.nodeTypes self.nodeShapes = provisioner.nodeShapes self.nodeShapeToType = dict(zip(self.nodeShapes, self.nodeTypes)) self.ignoredNodes = set() # A *deficit* exists when we have more jobs that can run on preemptable # nodes than we have preemptable nodes. In order to not block these jobs, # we want to increase the number of non-preemptable nodes that we have and # need for just non-preemptable jobs. However, we may still # prefer waiting for preemptable instances to come available. # To accommodate this, we set the delta to the difference between the number # of provisioned preemptable nodes and the number of nodes that were requested. # Then, when provisioning non-preemptable nodes of the same type, we attempt to # make up the deficit. self.preemptableNodeDeficit = {nodeType:0 for nodeType in self.nodeTypes} # Keeps track of the last raw (i.e. float, not limited by # max/min nodes) estimates of the number of nodes needed for # each node shape. NB: we start with an estimate of 0, so # scaling up is smoothed as well. self.previousWeightedEstimate = {nodeShape:0.0 for nodeShape in self.nodeShapes} assert len(self.nodeShapes) > 0 # Minimum/maximum number of either preemptable or non-preemptable nodes in the cluster minNodes = config.minNodes if minNodes is None: minNodes = [0 for node in self.nodeTypes] maxNodes = config.maxNodes while len(maxNodes) < len(self.nodeTypes): # Pad out the max node counts if we didn't get one per type. maxNodes.append(maxNodes[0]) while len(minNodes) < len(self.nodeTypes): # Pad out the min node counts with 0s, so we can have fewer than # the node types without crashing. minNodes.append(0) self.minNodes = dict(zip(self.nodeShapes, minNodes)) self.maxNodes = dict(zip(self.nodeShapes, maxNodes)) self.nodeShapes.sort() #Node shape to number of currently provisioned nodes totalNodes = defaultdict(int) if isinstance(leader.batchSystem, AbstractScalableBatchSystem): for preemptable in (True, False): nodes = [] for nodeShape, nodeType in self.nodeShapeToType.items(): nodes_thisType = leader.provisioner.getProvisionedWorkers(nodeType=nodeType, preemptable=preemptable) totalNodes[nodeShape] += len(nodes_thisType) nodes.extend(nodes_thisType) self.setStaticNodes(nodes, preemptable) logger.debug('Starting with the following nodes in the cluster: %s' % totalNodes) if not sum(config.maxNodes) > 0: raise RuntimeError('Not configured to create nodes of any type.') def _round(self, number): """ Helper function for rounding-as-taught-in-school (X.5 rounds to X+1 if positive). Python 3 now rounds 0.5 to whichever side is even (i.e. 2.5 rounds to 2). :param int number: a float to round. :return: closest integer to number, rounding ties away from 0. """ sign = 1 if number >= 0 else -1 rounded = int(round(number)) nextRounded = int(round(number + 1 * sign)) if nextRounded == rounded: # We rounded X.5 to even, and it was also away from 0. return rounded elif nextRounded == rounded + 1 * sign: # We rounded normally (we are in Python 2) return rounded elif nextRounded == rounded + 2 * sign: # We rounded X.5 to even, but it was towards 0. # Go away from 0 instead. return rounded + 1 * sign else: # If we get here, something has gone wrong. raise RuntimeError("Could not round {}".format(number)) def getAverageRuntime(self, jobName, service=False): if service: # We short-circuit service jobs and assume that they will # take a very long time, because if they are assumed to # take a short time, we may try to pack multiple services # into the same core/memory/disk "reservation", one after # the other. That could easily lead to underprovisioning # and a deadlock, because often multiple services need to # be running at once for any actual work to get done. return self.targetTime * 24 + 3600 if jobName in self.jobNameToAvgRuntime: #Have seen jobs of this type before, so estimate #the runtime based on average of previous jobs of this type return self.jobNameToAvgRuntime[jobName] elif self.totalAvgRuntime > 0: #Haven't seen this job yet, so estimate its runtime as #the average runtime of all completed jobs return self.totalAvgRuntime else: #Have no information whatsoever return 1.0 def addCompletedJob(self, job, wallTime): """ Adds the shape of a completed job to the queue, allowing the scalar to use the last N completed jobs in factoring how many nodes are required in the cluster. :param toil.job.JobNode job: The memory, core and disk requirements of the completed job :param int wallTime: The wall-time taken to complete the job in seconds. """ #Adjust average runtimes to include this job. if job.jobName in self.jobNameToAvgRuntime: prevAvg = self.jobNameToAvgRuntime[job.jobName] prevNum = self.jobNameToNumCompleted[job.jobName] self.jobNameToAvgRuntime[job.jobName] = float(prevAvg*prevNum + wallTime)/(prevNum + 1) self.jobNameToNumCompleted[job.jobName] += 1 else: self.jobNameToAvgRuntime[job.jobName] = wallTime self.jobNameToNumCompleted[job.jobName] = 1 self.totalJobsCompleted += 1 self.totalAvgRuntime = float(self.totalAvgRuntime * (self.totalJobsCompleted - 1) + \ wallTime)/self.totalJobsCompleted def setStaticNodes(self, nodes, preemptable): """ Used to track statically provisioned nodes. This method must be called before any auto-scaled nodes are provisioned. These nodes are treated differently than auto-scaled nodes in that they should not be automatically terminated. :param nodes: list of Node objects """ prefix = 'non-' if not preemptable else '' logger.debug("Adding %s to %spreemptable static nodes", nodes, prefix) if nodes is not None: self.static[preemptable] = {node.privateIP : node for node in nodes} def getStaticNodes(self, preemptable): """ Returns nodes set in setStaticNodes(). :param preemptable: :return: Statically provisioned nodes. """ return self.static[preemptable] def smoothEstimate(self, nodeShape, estimatedNodeCount): """ Smooth out fluctuations in the estimate for this node compared to previous runs. Returns an integer. """ weightedEstimate = (1 - self.betaInertia) * estimatedNodeCount + \ self.betaInertia * self.previousWeightedEstimate[nodeShape] self.previousWeightedEstimate[nodeShape] = weightedEstimate return self._round(weightedEstimate) def getEstimatedNodeCounts(self, queuedJobShapes, currentNodeCounts): """ Given the resource requirements of queued jobs and the current size of the cluster, returns a dict mapping from nodeShape to the number of nodes we want in the cluster right now. """ nodesToRunQueuedJobs = binPacking(jobShapes=queuedJobShapes, nodeShapes=self.nodeShapes, goalTime=self.targetTime) estimatedNodeCounts = {} for nodeShape in self.nodeShapes: nodeType = self.nodeShapeToType[nodeShape] logger.debug("Nodes of type %s to run queued jobs = " "%s" % (nodeType, nodesToRunQueuedJobs[nodeShape])) # Actual calculation of the estimated number of nodes required estimatedNodeCount = 0 if nodesToRunQueuedJobs[nodeShape] == 0 \ else max(1, self._round(nodesToRunQueuedJobs[nodeShape])) logger.debug("Estimating %i nodes of shape %s" % (estimatedNodeCount, nodeShape)) # Use inertia parameter to smooth out fluctuations according to an exponentially # weighted moving average. estimatedNodeCount = self.smoothEstimate(nodeShape, estimatedNodeCount) # If we're scaling a non-preemptable node type, we need to see if we have a # deficit of preemptable nodes of this type that we should compensate for. if not nodeShape.preemptable: compensation = self.config.preemptableCompensation assert 0.0 <= compensation <= 1.0 # The number of nodes we provision as compensation for missing preemptable # nodes is the product of the deficit (the number of preemptable nodes we did # _not_ allocate) and configuration preference. compensationNodes = self._round(self.preemptableNodeDeficit[nodeType] * compensation) if compensationNodes > 0: logger.debug('Adding %d non-preemptable nodes of type %s to compensate for a ' 'deficit of %d preemptable ones.', compensationNodes, nodeType, self.preemptableNodeDeficit[nodeType]) estimatedNodeCount += compensationNodes logger.debug("Currently %i nodes of type %s in cluster" % (currentNodeCounts[nodeShape], nodeType)) if self.leader.toilMetrics: self.leader.toilMetrics.logClusterSize(nodeType=nodeType, currentSize=currentNodeCounts[nodeShape], desiredSize=estimatedNodeCount) # Bound number using the max and min node parameters if estimatedNodeCount > self.maxNodes[nodeShape]: logger.debug('Limiting the estimated number of necessary %s (%s) to the ' 'configured maximum (%s).', nodeType, estimatedNodeCount, self.maxNodes[nodeShape]) estimatedNodeCount = self.maxNodes[nodeShape] elif estimatedNodeCount < self.minNodes[nodeShape]: logger.debug('Raising the estimated number of necessary %s (%s) to the ' 'configured minimum (%s).', nodeType, estimatedNodeCount, self.minNodes[nodeShape]) estimatedNodeCount = self.minNodes[nodeShape] estimatedNodeCounts[nodeShape] = estimatedNodeCount return estimatedNodeCounts def updateClusterSize(self, estimatedNodeCounts): """ Given the desired and current size of the cluster, attempts to launch/remove instances to get to the desired size. Also attempts to remove ignored nodes that were marked for graceful removal. Returns the new size of the cluster. """ newNodeCounts = defaultdict(int) for nodeShape, estimatedNodeCount in estimatedNodeCounts.items(): nodeType = self.nodeShapeToType[nodeShape] newNodeCount = self.setNodeCount(nodeType=nodeType, numNodes=estimatedNodeCount, preemptable=nodeShape.preemptable) # If we were scaling up a preemptable node type and failed to meet # our target, we will attempt to compensate for the deficit while scaling # non-preemptable nodes of this type. if nodeShape.preemptable: if newNodeCount < estimatedNodeCount: deficit = estimatedNodeCount - newNodeCount logger.debug('Preemptable scaler detected deficit of %d nodes of type %s.' % (deficit, nodeType)) self.preemptableNodeDeficit[nodeType] = deficit else: self.preemptableNodeDeficit[nodeType] = 0 newNodeCounts[nodeShape] = newNodeCount #Attempt to terminate any nodes that we previously designated for #termination, but which still had workers running. self._terminateIgnoredNodes() return newNodeCounts def setNodeCount(self, nodeType, numNodes, preemptable=False, force=False): """ Attempt to grow or shrink the number of preemptable or non-preemptable worker nodes in the cluster to the given value, or as close a value as possible, and, after performing the necessary additions or removals of worker nodes, return the resulting number of preemptable or non-preemptable nodes currently in the cluster. :param str nodeType: The node type to add or remove. :param int numNodes: Desired size of the cluster :param bool preemptable: whether the added nodes will be preemptable, i.e. whether they may be removed spontaneously by the underlying platform at any time. :param bool force: If False, the provisioner is allowed to deviate from the given number of nodes. For example, when downsizing a cluster, a provisioner might leave nodes running if they have active jobs running on them. :rtype: int :return: the number of worker nodes in the cluster after making the necessary adjustments. This value should be, but is not guaranteed to be, close or equal to the `numNodes` argument. It represents the closest possible approximation of the actual cluster size at the time this method returns. """ for attempt in retry(predicate=self.provisioner.retryPredicate): with attempt: workerInstances = self.getNodes(preemptable=preemptable) logger.debug("Cluster contains %i instances" % len(workerInstances)) # Reduce to nodes of the correct type workerInstances = {node:workerInstances[node] for node in workerInstances if node.nodeType == nodeType} ignoredNodes = [node for node in workerInstances if node.privateIP in self.ignoredNodes] numIgnoredNodes = len(ignoredNodes) numCurrentNodes = len(workerInstances) logger.debug("Cluster contains %i instances of type %s (%i ignored and draining jobs until " "they can be safely terminated)" % (numCurrentNodes, nodeType, numIgnoredNodes)) if not force: delta = numNodes - (numCurrentNodes - numIgnoredNodes) else: delta = numNodes - numCurrentNodes if delta > 0 and numIgnoredNodes > 0: # We can un-ignore a few nodes to compensate for the additional nodes we want. numNodesToUnignore = min(delta, numIgnoredNodes) logger.debug('Unignoring %i nodes because we want to scale back up again.' % numNodesToUnignore) delta -= numNodesToUnignore for node in ignoredNodes[:numNodesToUnignore]: self.ignoredNodes.remove(node.privateIP) self.leader.batchSystem.unignoreNode(node.privateIP) if delta > 0: logger.info('Adding %i %s nodes to get to desired cluster size of %i.', delta, 'preemptable' if preemptable else 'non-preemptable', numNodes) numNodes = numCurrentNodes + self._addNodes(nodeType, numNodes=delta, preemptable=preemptable) elif delta < 0: logger.info('Removing %i %s nodes to get to desired cluster size of %i.', -delta, 'preemptable' if preemptable else 'non-preemptable', numNodes) numNodes = numCurrentNodes - self._removeNodes(workerInstances, nodeType = nodeType, numNodes=-delta, preemptable=preemptable, force=force) else: if not force: logger.debug('Cluster (minus ignored nodes) already at desired size of %i. Nothing to do.', numNodes) else: logger.debug('Cluster already at desired size of %i. Nothing to do.', numNodes) return numNodes def _addNodes(self, nodeType, numNodes, preemptable): return self.provisioner.addNodes(nodeType=nodeType, numNodes=numNodes, preemptable=preemptable) def _removeNodes(self, nodeToNodeInfo, nodeType, numNodes, preemptable=False, force=False): # If the batch system is scalable, we can use the number of currently running workers on # each node as the primary criterion to select which nodes to terminate. if isinstance(self.leader.batchSystem, AbstractScalableBatchSystem): # Unless forced, exclude nodes with running workers. Note that it is possible for # the batch system to report stale nodes for which the corresponding instance was # terminated already. There can also be instances that the batch system doesn't have # nodes for yet. We'll ignore those, too, unless forced. nodeToNodeInfo = self.getNodes(preemptable) #Filter down to nodes of the correct node type nodeToNodeInfo = {node:nodeToNodeInfo[node] for node in nodeToNodeInfo if node.nodeType == nodeType} nodesToTerminate = self.chooseNodes(nodeToNodeInfo, force, preemptable=preemptable) nodesToTerminate = nodesToTerminate[:numNodes] # Join nodes and instances on private IP address. logger.debug('Nodes considered to terminate: %s', ' '.join(map(str, nodeToNodeInfo))) #Tell the batch system to stop sending jobs to these nodes for (node, nodeInfo) in nodesToTerminate: self.ignoredNodes.add(node.privateIP) self.leader.batchSystem.ignoreNode(node.privateIP) if not force: # Filter out nodes with jobs still running. These # will be terminated in _removeIgnoredNodes later on # once all jobs have finished, but they will be ignored by # the batch system and cluster scaler from now on nodesToTerminate = [(node,nodeInfo) for (node,nodeInfo) in nodesToTerminate if nodeInfo is not None and nodeInfo.workers < 1] nodesToTerminate = {node:nodeInfo for (node, nodeInfo) in nodesToTerminate} nodeToNodeInfo = nodesToTerminate else: # Without load info all we can do is sort instances by time left in billing cycle. nodeToNodeInfo = sorted(nodeToNodeInfo, key=lambda x: x.remainingBillingInterval()) nodeToNodeInfo = [instance for instance in islice(nodeToNodeInfo, numNodes)] logger.debug('Terminating %i instance(s).', len(nodeToNodeInfo)) if nodeToNodeInfo: for node in nodeToNodeInfo: if node.privateIP in self.ignoredNodes: self.ignoredNodes.remove(node.privateIP) self.leader.batchSystem.unignoreNode(node.privateIP) self.provisioner.terminateNodes(nodeToNodeInfo) return len(nodeToNodeInfo) def _terminateIgnoredNodes(self): #Try to terminate any straggling nodes that we designated for #termination, but which still has workers running nodeToNodeInfo = self.getNodes(preemptable=None) #Remove any nodes that have already been terminated from the list # of ignored nodes allNodeIPs = [node.privateIP for node in nodeToNodeInfo] terminatedIPs = set([ip for ip in self.ignoredNodes if ip not in allNodeIPs]) for ip in terminatedIPs: self.ignoredNodes.remove(ip) self.leader.batchSystem.unignoreNode(ip) logger.debug("There are %i nodes being ignored by the batch system, " "checking if they can be terminated" % len(self.ignoredNodes)) nodeToNodeInfo = {node:nodeToNodeInfo[node] for node in nodeToNodeInfo if node.privateIP in self.ignoredNodes} nodeToNodeInfo = {node:nodeToNodeInfo[node] for node in nodeToNodeInfo if nodeToNodeInfo[node] is not None and nodeToNodeInfo[node].workers < 1} for node in nodeToNodeInfo: self.ignoredNodes.remove(node.privateIP) self.leader.batchSystem.unignoreNode(node.privateIP) if len(nodeToNodeInfo) > 0: logger.debug("Terminating %i nodes that were being ignored by the batch system." "" % len(nodeToNodeInfo)) self.provisioner.terminateNodes(nodeToNodeInfo) def chooseNodes(self, nodeToNodeInfo, force=False, preemptable=False): nodesToTerminate = [] for node, nodeInfo in list(nodeToNodeInfo.items()): if node is None: logger.debug("Node with info %s was not found in our node list", nodeInfo) continue staticNodes = self.getStaticNodes(preemptable) prefix = 'non-' if not preemptable else '' if node.privateIP in staticNodes: # we don't want to automatically terminate any statically # provisioned nodes logger.debug("Found %s in %spreemptable static nodes", node.privateIP, prefix) continue else: logger.debug("Did not find %s in %spreemptable static nodes", node.privateIP, prefix) pass nodesToTerminate.append((node, nodeInfo)) # Sort nodes by number of workers and time left in billing cycle nodesToTerminate.sort(key=lambda node_nodeInfo: ( node_nodeInfo[1].workers if node_nodeInfo[1] else 1, node_nodeInfo[0].remainingBillingInterval())) return nodesToTerminate def getNodes(self, preemptable): """ Returns a dictionary mapping node identifiers of preemptable or non-preemptable nodes to NodeInfo objects, one for each node. This method is the definitive source on nodes in cluster, & is responsible for consolidating cluster state between the provisioner & batch system. :param bool preemptable: If True (False) only (non-)preemptable nodes will be returned. If None, all nodes will be returned. :rtype: dict[Node, NodeInfo] """ def _getInfo(allMesosNodes, ip): info = None try: info = allMesosNodes[ip] except KeyError: # never seen by mesos - 1 of 3 possibilities: # 1) node is still launching mesos & will come online soon # 2) no jobs have been assigned to this worker. This means the executor was never # launched, so we don't even get an executorInfo back indicating 0 workers running # 3) mesos crashed before launching, worker will never come online # In all 3 situations it's safe to fake executor info with 0 workers, since in all # cases there are no workers running. info = NodeInfo(coresTotal=1, coresUsed=0, requestedCores=0, memoryTotal=1, memoryUsed=0, requestedMemory=0, workers=0) else: # Node was tracked but we haven't seen this in the last 10 minutes inUse = self.leader.batchSystem.nodeInUse(ip) if not inUse and info: # The node hasn't reported in the last 10 minutes & last we know # there weren't any tasks running. We will fake executorInfo with no # worker to reflect this, since otherwise this node will never # be considered for termination info.workers = 0 else: pass # despite the node not reporting to mesos jobs may still be running # so we can't terminate the node return info allMesosNodes = self.leader.batchSystem.getNodes(preemptable, timeout=None) recentMesosNodes = self.leader.batchSystem.getNodes(preemptable) provisionerNodes = self.provisioner.getProvisionedWorkers(nodeType=None, preemptable=preemptable) if len(recentMesosNodes) != len(provisionerNodes): logger.debug("Consolidating state between mesos and provisioner") nodeToInfo = {} # fixme: what happens if awsFilterImpairedNodes is used? # if this assertion is false it means that user-managed nodes are being # used that are outside the provisioner's control # this would violate many basic assumptions in autoscaling so it currently not allowed for node, ip in ((node, node.privateIP) for node in provisionerNodes): info = None if ip not in recentMesosNodes: logger.debug("Worker node at %s is not reporting executor information", ip) # we don't have up to date information about the node info = _getInfo(allMesosNodes, ip) else: # mesos knows about the ip & we have up to date information - easy! info = recentMesosNodes[ip] # add info to dict to return nodeToInfo[node] = info return nodeToInfo def shutDown(self): logger.debug('Forcing provisioner to reduce cluster size to zero.') for nodeShape in self.nodeShapes: preemptable = nodeShape.preemptable nodeType = self.nodeShapeToType[nodeShape] self.setNodeCount(nodeType=nodeType, numNodes=0, preemptable=preemptable, force=True) class ScalerThread(ExceptionalThread): """ A thread that automatically scales the number of either preemptable or non-preemptable worker nodes according to the resource requirements of the queued jobs. The scaling calculation is essentially as follows: start with 0 estimated worker nodes. For each queued job, check if we expect it can be scheduled into a worker node before a certain time (currently one hour). Otherwise, attempt to add a single new node of the smallest type that can fit that job. At each scaling decision point a comparison between the current, C, and newly estimated number of nodes is made. If the absolute difference is less than beta * C then no change is made, else the size of the cluster is adapted. The beta factor is an inertia parameter that prevents continual fluctuations in the number of nodes. """ def __init__(self, provisioner, leader, config): """ :param ClusterScaler scaler: the parent class """ super(ScalerThread, self).__init__(name='scaler') self.scaler = ClusterScaler(provisioner, leader, config) # Indicates that the scaling thread should shutdown self.stop = False self.stats = None if config.clusterStats: logger.debug("Starting up cluster statistics...") self.stats = ClusterStats(leader.config.clusterStats, leader.batchSystem, provisioner.clusterName) for preemptable in [True, False]: self.stats.startStats(preemptable=preemptable) logger.debug("...Cluster stats started.") def check(self): """ Attempt to join any existing scaler threads that may have died or finished. This insures any exceptions raised in the threads are propagated in a timely fashion. """ try: self.join(timeout=0) except Exception as e: logger.exception(e) raise def shutdown(self): """ Shutdown the cluster. """ self.stop = True if self.stats: self.stats.shutDownStats() self.join() def addCompletedJob(self, job, wallTime): self.scaler.addCompletedJob(job, wallTime) def tryRun(self): while not self.stop: with throttle(self.scaler.config.scaleInterval): try: queuedJobs = self.scaler.leader.getJobs() queuedJobShapes = [ Shape(wallTime=self.scaler.getAverageRuntime( jobName=job.jobName, service=isinstance(job, ServiceJobNode)), memory=job.memory, cores=job.cores, disk=job.disk, preemptable=job.preemptable) for job in queuedJobs] currentNodeCounts = {} for nodeShape in self.scaler.nodeShapes: nodeType = self.scaler.nodeShapeToType[nodeShape] currentNodeCounts[nodeShape] = len( self.scaler.leader.provisioner.getProvisionedWorkers(nodeType=nodeType, preemptable=nodeShape.preemptable)) estimatedNodeCounts = self.scaler.getEstimatedNodeCounts(queuedJobShapes, currentNodeCounts) self.scaler.updateClusterSize(estimatedNodeCounts) if self.stats: self.stats.checkStats() except: logger.exception("Exception encountered in scaler thread. Making a best-effort " "attempt to keep going, but things may go wrong from now on.") self.scaler.shutDown() class ClusterStats(object): def __init__(self, path, batchSystem, clusterName): logger.debug("Initializing cluster statistics") self.stats = {} self.statsThreads = [] self.statsPath = path self.stop = False self.clusterName = clusterName self.batchSystem = batchSystem self.scaleable = isinstance(self.batchSystem, AbstractScalableBatchSystem) \ if batchSystem else False def shutDownStats(self): if self.stop: return def getFileName(): extension = '.json' file = '%s-stats' % self.clusterName counter = 0 while True: suffix = str(counter).zfill(3) + extension fullName = os.path.join(self.statsPath, file + suffix) if not os.path.exists(fullName): return fullName counter += 1 if self.statsPath and self.scaleable: self.stop = True for thread in self.statsThreads: thread.join() fileName = getFileName() with open(fileName, 'w') as f: json.dump(self.stats, f) def startStats(self, preemptable): thread = ExceptionalThread(target=self._gatherStats, args=[preemptable]) thread.start() self.statsThreads.append(thread) def checkStats(self): for thread in self.statsThreads: # propagate any errors raised in the threads execution thread.join(timeout=0) def _gatherStats(self, preemptable): def toDict(nodeInfo): # convert NodeInfo object to dict to improve JSON output return dict(memory=nodeInfo.memoryUsed, cores=nodeInfo.coresUsed, memoryTotal=nodeInfo.memoryTotal, coresTotal=nodeInfo.coresTotal, requestedCores=nodeInfo.requestedCores, requestedMemory=nodeInfo.requestedMemory, workers=nodeInfo.workers, time=time.time() # add time stamp ) if self.scaleable: logger.debug("Starting to gather statistics") stats = {} try: while not self.stop: nodeInfo = self.batchSystem.getNodes(preemptable) for nodeIP in list(nodeInfo.keys()): nodeStats = nodeInfo[nodeIP] if nodeStats is not None: nodeStats = toDict(nodeStats) try: # if the node is already registered update the dictionary with the # newly reported stats stats[nodeIP].append(nodeStats) except KeyError: # create a new entry for the node stats[nodeIP] = [nodeStats] time.sleep(60) finally: threadName = 'Preemptable' if preemptable else 'Non-preemptable' logger.debug('%s provisioner stats thread shut down successfully.', threadName) self.stats[threadName] = stats toil-releases-3.24.0/src/toil/provisioners/gceProvisioner.py000066400000000000000000000531521362134276200242340ustar00rootroot00000000000000# Copyright (C) 2015 UCSC Computational Genomics Lab # # 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. from builtins import range import os import time import threading import json import requests import uuid import logging from libcloud.compute.types import Provider from libcloud.compute.providers import get_driver from libcloud.compute.drivers.gce import GCEFailedNode from toil.provisioners.abstractProvisioner import AbstractProvisioner, Shape from toil.provisioners import NoSuchClusterException from toil.jobStores.googleJobStore import GoogleJobStore from toil.provisioners.node import Node logger = logging.getLogger(__name__) logging.getLogger("urllib3.connectionpool").setLevel(logging.WARNING) class GCEProvisioner(AbstractProvisioner): """ Implements a Google Compute Engine Provisioner using libcloud. """ NODE_BOTO_PATH = "/root/.boto" # boto file path on instances SOURCE_IMAGE = (b'projects/coreos-cloud/global/images/family/coreos-stable') def __init__(self, clusterName, zone, nodeStorage, sseKey): super(GCEProvisioner, self).__init__(clusterName, zone, nodeStorage) self.cloud = 'gce' self._sseKey = sseKey # If the clusterName is not given, then Toil must be running on the leader # and should read the settings from the instance meta-data. if clusterName: self._readCredentials() else: self._readClusterSettings() def _readClusterSettings(self): """ Read the cluster settings from the instance, which should be the leader. See https://cloud.google.com/compute/docs/storing-retrieving-metadata for details about reading the metadata. """ metadata_server = "http://metadata/computeMetadata/v1/instance/" metadata_flavor = {'Metadata-Flavor': 'Google'} zone = requests.get(metadata_server + 'zone', headers = metadata_flavor).text self._zone = zone.split('/')[-1] project_metadata_server = "http://metadata/computeMetadata/v1/project/" self._projectId = requests.get(project_metadata_server + 'project-id', headers = metadata_flavor).text # From a GCE instance, these values can be blank. Only the projectId is needed self._googleJson = '' self._clientEmail = '' self._tags = requests.get(metadata_server + 'description', headers = metadata_flavor).text tags = json.loads(self._tags) self.clusterName = tags['clusterName'] self._gceDriver = self._getDriver() self._instanceGroup = self._gceDriver.ex_get_instancegroup(self.clusterName, zone=self._zone) leader = self.getLeader() self._leaderPrivateIP = leader.privateIP # generate a public key for the leader, which is used to talk to workers self._masterPublicKey = self._setSSH() # The location of the Google credentials file on instances. self._credentialsPath = GoogleJobStore.nodeServiceAccountJson self._keyName = 'core' # key name leader users to communicate with works self._botoPath = self.NODE_BOTO_PATH # boto credentials (used if reading an AWS bucket) def _readCredentials(self): """ Get the credentials from the file specified by GOOGLE_APPLICATION_CREDENTIALS. """ self._googleJson = os.getenv('GOOGLE_APPLICATION_CREDENTIALS') if not self._googleJson: raise RuntimeError('GOOGLE_APPLICATION_CREDENTIALS not set.') try: with open(self._googleJson) as jsonFile: self.googleConnectionParams = json.loads(jsonFile.read()) except: raise RuntimeError('GCEProvisioner: Could not parse the Google service account json file %s' % self._googleJson) self._projectId = self.googleConnectionParams['project_id'] self._clientEmail = self.googleConnectionParams['client_email'] self._credentialsPath = self._googleJson self._masterPublicKey = None self._gceDriver = self._getDriver() def launchCluster(self, leaderNodeType, leaderStorage, owner, **kwargs): """ In addition to the parameters inherited from the abstractProvisioner, the Google launchCluster takes the following parameters: keyName: The key used to communicate with instances botoPath: Boto credentials for reading an AWS jobStore (optional). vpcSubnet: A subnet (optional). """ if 'keyName' not in kwargs: raise RuntimeError("A keyPairName is required for the GCE provisioner.") self._keyName = kwargs['keyName'] if 'botoPath' in kwargs: self._botoPath = kwargs['botoPath'] self._vpcSubnet = kwargs['vpcSubnet'] if 'vpcSubnet' in kwargs else None # Throws an error if cluster exists self._instanceGroup = self._gceDriver.ex_create_instancegroup(self.clusterName, self._zone) logger.debug('Launching leader') # GCE doesn't have a dictionary tags field. The tags field is just a string list. # Therefore, dumping tags into the description. tags = {'Owner': self._keyName, 'clusterName': self.clusterName} if 'userTags' in kwargs: tags.update(kwargs['userTags']) self._tags = json.dumps(tags) userData = self._getCloudConfigUserData('leader') metadata = {'items': [{'key': 'user-data', 'value': userData}]} imageType = 'coreos-stable' sa_scopes = [{'scopes': ['compute', 'storage-full']}] disk = {} disk['initializeParams'] = { 'sourceImage': self.SOURCE_IMAGE, 'diskSizeGb' : leaderStorage } disk.update({'boot': True, 'autoDelete': True }) name= 'l' + str(uuid.uuid4()) leader = self._gceDriver.create_node(name, leaderNodeType, imageType, location=self._zone, ex_service_accounts=sa_scopes, ex_metadata=metadata, ex_subnetwork=self._vpcSubnet, ex_disks_gce_struct = [disk], description=self._tags, ex_preemptible=False) self._instanceGroup.add_instances([leader]) self._leaderPrivateIP = leader.private_ips[0] # needed if adding workers #self.subnetID = leader.subnet_id #TODO: get subnetID # Wait for the appliance to start and inject credentials. leaderNode = Node(publicIP=leader.public_ips[0], privateIP=leader.private_ips[0], name=leader.name, launchTime=leader.created_at, nodeType=leader.size, preemptable=False, tags=self._tags) leaderNode.waitForNode('toil_leader', keyName=self._keyName) leaderNode.copySshKeys(self._keyName) leaderNode.injectFile(self._credentialsPath, GoogleJobStore.nodeServiceAccountJson, 'toil_leader') if self._botoPath: leaderNode.injectFile(self._botoPath, self.NODE_BOTO_PATH, 'toil_leader') logger.debug('Launched leader') def getNodeShape(self, nodeType, preemptable=False): # TODO: read this value only once sizes = self._gceDriver.list_sizes(location=self._zone) sizes = [x for x in sizes if x.name == nodeType] assert len(sizes) == 1 instanceType = sizes[0] disk = 0 #instanceType.disks * instanceType.disk_capacity * 2 ** 30 if disk == 0: # This is an EBS-backed instance. We will use the root # volume, so add the amount of EBS storage requested forhe root volume disk = self._nodeStorage * 2 ** 30 # Ram is in M. #Underestimate memory by 100M to prevent autoscaler from disagreeing with #mesos about whether a job can run on a particular node type memory = (instanceType.ram/1000 - 0.1) * 2** 30 return Shape(wallTime=60 * 60, memory=memory, cores=instanceType.extra['guestCpus'], disk=disk, preemptable=preemptable) @staticmethod def retryPredicate(e): """ Not used by GCE """ return False def destroyCluster(self): """ Try a few times to terminate all of the instances in the group. """ logger.debug("Destroying cluster %s" % self.clusterName) instancesToTerminate = self._getNodesInCluster() attempts = 0 while instancesToTerminate and attempts < 3: self._terminateInstances(instances=instancesToTerminate) instancesToTerminate = self._getNodesInCluster() attempts += 1 # remove group instanceGroup = self._gceDriver.ex_get_instancegroup(self.clusterName, zone=self._zone) instanceGroup.destroy() def terminateNodes(self, nodes): nodeNames = [n.name for n in nodes] instances = self._getNodesInCluster() instancesToKill = [i for i in instances if i.name in nodeNames] self._terminateInstances(instancesToKill) def addNodes(self, nodeType, numNodes, preemptable, spotBid=None): assert self._leaderPrivateIP # If keys are rsynced, then the mesos-slave needs to be started after the keys have been # transferred. The waitForKey.sh script loops on the new VM until it finds the keyPath file, then it starts the # mesos-slave. If there are multiple keys to be transferred, then the last one to be transferred must be # set to keyPath. keyPath = None botoExists = False if self._botoPath is not None and os.path.exists(self._botoPath): keyPath = self.NODE_BOTO_PATH botoExists = True elif self._sseKey: keyPath = self._sseKey if not preemptable: logger.debug('Launching %s non-preemptable nodes', numNodes) else: logger.debug('Launching %s preemptable nodes', numNodes) #kwargs["subnet_id"] = self.subnetID if self.subnetID else self._getClusterInstance(self.instanceMetaData).subnet_id userData = self._getCloudConfigUserData('worker', self._masterPublicKey, keyPath, preemptable) metadata = {'items': [{'key': 'user-data', 'value': userData}]} imageType = 'coreos-stable' sa_scopes = [{'scopes': ['compute', 'storage-full']}] disk = {} disk['initializeParams'] = { 'sourceImage': self.SOURCE_IMAGE, 'diskSizeGb' : self._nodeStorage } disk.update({'boot': True, 'autoDelete': True }) # TODO: # - bug in gce.py for ex_create_multiple_nodes (erroneously, doesn't allow image and disk to specified) # - ex_create_multiple_nodes is limited to 1000 nodes # - use a different function # - or write a loop over the rest of this function, with 1K nodes max on each iteration #instancesLaunched = driver.ex_create_multiple_nodes( retries = 0 workersCreated = 0 # Try a few times to create the requested number of workers while numNodes-workersCreated > 0 and retries < 3: instancesLaunched = self.ex_create_multiple_nodes( '', nodeType, imageType, numNodes-workersCreated, location=self._zone, ex_service_accounts=sa_scopes, ex_metadata=metadata, ex_disks_gce_struct = [disk], description=self._tags, ex_preemptible = preemptable ) failedWorkers = [] for instance in instancesLaunched: if isinstance(instance, GCEFailedNode): logger.error("Worker failed to launch with code %s. Error message: %s" % (instance.code, instance.error)) continue node = Node(publicIP=instance.public_ips[0], privateIP=instance.private_ips[0], name=instance.name, launchTime=instance.created_at, nodeType=instance.size, preemptable=False, tags=self._tags) #FIXME: what should tags be set to? try: self._injectWorkerFiles(node, botoExists) logger.debug("Created worker %s" % node.publicIP) self._instanceGroup.add_instances([instance]) workersCreated += 1 except Exception as e: logger.error("Failed to configure worker %s. Error message: %s" % (node.name, e)) failedWorkers.append(instance) if failedWorkers: logger.error("Terminating %d failed workers" % len(failedWorkers)) self._terminateInstances(failedWorkers) retries += 1 logger.debug('Launched %d new instance(s)', numNodes) if numNodes != workersCreated: logger.error("Failed to launch %d worker(s)", numNodes-workersCreated) return workersCreated def getProvisionedWorkers(self, nodeType, preemptable): assert self._leaderPrivateIP entireCluster = self._getNodesInCluster(nodeType=nodeType) logger.debug('All nodes in cluster: %s', entireCluster) workerInstances = [] for instance in entireCluster: scheduling = instance.extra.get('scheduling') # If this field is not found in the extra meta-data, assume the node is not preemptable. if scheduling and scheduling.get('preemptible', False) != preemptable: continue isWorker = True for ip in instance.private_ips: if ip == self._leaderPrivateIP: isWorker = False break # don't include the leader if isWorker and instance.state == 'running': workerInstances.append(instance) logger.debug('All workers found in cluster: %s', workerInstances) return [Node(publicIP=i.public_ips[0], privateIP=i.private_ips[0], name=i.name, launchTime=i.created_at, nodeType=i.size, preemptable=preemptable, tags=None) for i in workerInstances] def getLeader(self): instances = self._getNodesInCluster() instances.sort(key=lambda x: x.created_at) try: leader = instances[0] # assume leader was launched first except IndexError: raise NoSuchClusterException(self.clusterName) return Node(publicIP=leader.public_ips[0], privateIP=leader.private_ips[0], name=leader.name, launchTime=leader.created_at, nodeType=leader.size, preemptable=False, tags=None) def _injectWorkerFiles(self, node, botoExists): """ Set up the credentials on the worker. """ node.waitForNode('toil_worker', keyName=self._keyName) node.copySshKeys(self._keyName) node.injectFile(self._credentialsPath, GoogleJobStore.nodeServiceAccountJson, 'toil_worker') if self._sseKey: node.injectFile(self._sseKey, self._sseKey, 'toil_worker') if botoExists: node.injectFile(self._botoPath, self.NODE_BOTO_PATH, 'toil_worker') def _getNodesInCluster(self, nodeType=None): instanceGroup = self._gceDriver.ex_get_instancegroup(self.clusterName, zone=self._zone) instances = instanceGroup.list_instances() if nodeType: instances = [instance for instance in instances if instance.size == nodeType] return instances def _getDriver(self): """ Connect to GCE """ driverCls = get_driver(Provider.GCE) return driverCls(self._clientEmail, self._googleJson, project=self._projectId, datacenter=self._zone) def _terminateInstances(self, instances): def worker(driver, instance): logger.debug('Terminating instance: %s', instance.name) driver.destroy_node(instance) threads = [] for instance in instances: t = threading.Thread(target=worker, args=(self._gceDriver,instance)) threads.append(t) t.start() logger.debug('... Waiting for instance(s) to shut down...') for t in threads: t.join() # MONKEY PATCH - This function was copied form libcloud to fix a bug. DEFAULT_TASK_COMPLETION_TIMEOUT = 180 def ex_create_multiple_nodes( self, base_name, size, image, number, location=None, ex_network='default', ex_subnetwork=None, ex_tags=None, ex_metadata=None, ignore_errors=True, use_existing_disk=True, poll_interval=2, external_ip='ephemeral', ex_disk_type='pd-standard', ex_disk_auto_delete=True, ex_service_accounts=None, timeout=DEFAULT_TASK_COMPLETION_TIMEOUT, description=None, ex_can_ip_forward=None, ex_disks_gce_struct=None, ex_nic_gce_struct=None, ex_on_host_maintenance=None, ex_automatic_restart=None, ex_image_family=None, ex_preemptible=None): """ Monkey patch to gce.py in libcloud to allow disk and images to be specified. Also changed name to a uuid below. The prefix 'wp' identifies preemptable nodes and 'wn' non-preemptable nodes. """ # if image and ex_disks_gce_struct: # raise ValueError("Cannot specify both 'image' and " # "'ex_disks_gce_struct'.") driver = self._getDriver() if image and ex_image_family: raise ValueError("Cannot specify both 'image' and " "'ex_image_family'") location = location or driver.zone if not hasattr(location, 'name'): location = driver.ex_get_zone(location) if not hasattr(size, 'name'): size = driver.ex_get_size(size, location) if not hasattr(ex_network, 'name'): ex_network = driver.ex_get_network(ex_network) if ex_subnetwork and not hasattr(ex_subnetwork, 'name'): ex_subnetwork = \ driver.ex_get_subnetwork(ex_subnetwork, region=driver._get_region_from_zone( location)) if ex_image_family: image = driver.ex_get_image_from_family(ex_image_family) if image and not hasattr(image, 'name'): image = driver.ex_get_image(image) if not hasattr(ex_disk_type, 'name'): ex_disk_type = driver.ex_get_disktype(ex_disk_type, zone=location) node_attrs = {'size': size, 'image': image, 'location': location, 'network': ex_network, 'subnetwork': ex_subnetwork, 'tags': ex_tags, 'metadata': ex_metadata, 'ignore_errors': ignore_errors, 'use_existing_disk': use_existing_disk, 'external_ip': external_ip, 'ex_disk_type': ex_disk_type, 'ex_disk_auto_delete': ex_disk_auto_delete, 'ex_service_accounts': ex_service_accounts, 'description': description, 'ex_can_ip_forward': ex_can_ip_forward, 'ex_disks_gce_struct': ex_disks_gce_struct, 'ex_nic_gce_struct': ex_nic_gce_struct, 'ex_on_host_maintenance': ex_on_host_maintenance, 'ex_automatic_restart': ex_automatic_restart, 'ex_preemptible': ex_preemptible} # List for holding the status information for disk/node creation. status_list = [] for i in range(number): name = 'wp' if ex_preemptible else 'wn' name += str(uuid.uuid4()) #'%s-%03d' % (base_name, i) status = {'name': name, 'node_response': None, 'node': None} status_list.append(status) start_time = time.time() complete = False while not complete: if (time.time() - start_time >= timeout): raise Exception("Timeout (%s sec) while waiting for multiple " "instances") complete = True time.sleep(poll_interval) for status in status_list: # Create the node or check status if already in progress. if not status['node']: if not status['node_response']: driver._multi_create_node(status, node_attrs) else: driver._multi_check_node(status, node_attrs) # If any of the nodes have not been created (or failed) we are # not done yet. if not status['node']: complete = False # Return list of nodes node_list = [] for status in status_list: node_list.append(status['node']) return node_list toil-releases-3.24.0/src/toil/provisioners/node.py000066400000000000000000000310131362134276200221530ustar00rootroot00000000000000# Copyright (C) 2015-2018 Regents of the University of California # # 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. from past.builtins import map from builtins import object from itertools import count import logging import pipes import socket import datetime import time from toil import subprocess from toil.lib.memoize import parse_iso_utc a_short_time = 5 logger = logging.getLogger(__name__) class Node(object): maxWaitTime = 5*60 def __init__(self, publicIP, privateIP, name, launchTime, nodeType, preemptable, tags=None): self.publicIP = publicIP self.privateIP = privateIP self.effectiveIP = self.publicIP or self.privateIP self.name = name self.launchTime = launchTime self.nodeType = nodeType self.preemptable = preemptable self.tags = tags def __str__(self): return "%s at %s" % (self.name, self.effectiveIP) def __repr__(self): return str(self) def __hash__(self): return hash(self.effectiveIP) def remainingBillingInterval(self): """ If the node has a launch time, this function returns a floating point value between 0 and 1.0 representing how far we are into the current billing cycle for the given instance. If the return value is .25, we are one quarter into the billing cycle, with three quarters remaining before we will be charged again for that instance. Assumes a billing cycle of one hour. :return: Float from 0 -> 1.0 representing percentage of pre-paid time left in cycle. """ if self.launchTime: now = datetime.datetime.utcnow() delta = now - parse_iso_utc(self.launchTime) return 1 - delta.total_seconds() / 3600.0 % 1.0 else: return 1 def waitForNode(self, role, keyName='core'): self._waitForSSHPort() # wait here so docker commands can be used reliably afterwards self._waitForSSHKeys(keyName=keyName) self._waitForDockerDaemon(keyName=keyName) self._waitForAppliance(role=role, keyName=keyName) def copySshKeys(self, keyName): """ Copy authorized_keys file to the core user from the keyName user.""" if keyName == 'core': return # No point. # Make sure that keys are there. self._waitForSSHKeys(keyName=keyName) # copy keys to core user so that the ssh calls will work # - normal mechanism failed unless public key was in the google-ssh format # - even so, the key wasn't copied correctly to the core account keyFile = '/home/%s/.ssh/authorized_keys' % keyName self.sshInstance('/usr/bin/sudo', '/usr/bin/cp', keyFile, '/home/core/.ssh', user=keyName) self.sshInstance('/usr/bin/sudo', '/usr/bin/chown', 'core', '/home/core/.ssh/authorized_keys', user=keyName) def injectFile(self, fromFile, toFile, role): """ rysnc a file to the vm with the given role """ maxRetries = 10 for retry in range(maxRetries): try: self.coreRsync([fromFile, ":" + toFile], applianceName=role) return True except Exception as e: logger.debug("Rsync to new node failed, trying again. Error message: %s" % e) time.sleep(10*retry) raise RuntimeError("Failed to inject file %s to %s with ip %s" % (fromFile, role, self.effectiveIP) ) def _waitForSSHKeys(self, keyName='core'): # the propagation of public ssh keys vs. opening the SSH port is racey, so this method blocks until # the keys are propagated and the instance can be SSH into startTime = time.time() while True: if time.time() - startTime > self.maxWaitTime: raise RuntimeError("Key propagation failed on machine with ip %s" % self.effectiveIP) try: logger.info('Attempting to establish SSH connection...') self.sshInstance('ps', sshOptions=['-oBatchMode=yes'], user=keyName) except RuntimeError: logger.info('Connection rejected, waiting for public SSH key to be propagated. Trying again in 10s.') time.sleep(10) else: logger.info('...SSH connection established.') # ssh succeeded return def _waitForDockerDaemon(self, keyName='core'): logger.info('Waiting for docker on %s to start...', self.effectiveIP) sleepTime = 10 startTime = time.time() while True: if time.time() - startTime > self.maxWaitTime: raise RuntimeError("Docker daemon failed to start on machine with ip %s" % self.effectiveIP) try: output = self.sshInstance('/usr/bin/ps', 'auxww', sshOptions=['-oBatchMode=yes'], user=keyName) if b'dockerd' in output: # docker daemon has started logger.info('Docker daemon running') break else: logger.info('... Still waiting for docker daemon, trying in %s sec...' % sleepTime) time.sleep(sleepTime) except RuntimeError: logger.info("Wait for docker daemon failed ssh, trying again.") sleepTime += 20 def _waitForAppliance(self, role, keyName='core'): logger.info('Waiting for %s Toil appliance to start...', role) sleepTime = 20 startTime = time.time() while True: if time.time() - startTime > self.maxWaitTime: raise RuntimeError("Appliance failed to start on machine with ip %s" " Check if the appliance is valid, e.g. check if the environment variable" " TOIL_APPLIANCE_SELF is set correctly and the container exists." % self.effectiveIP) try: output = self.sshInstance('/usr/bin/docker', 'ps', sshOptions=['-oBatchMode=yes'], user=keyName) if type(role) != type(output): # We need to encode the role as bytes role = bytes(role, encoding='utf-8') if role in output: logger.info('...Toil appliance started') break else: logger.info('...Still waiting for appliance, trying again in %s sec...' % sleepTime) time.sleep(sleepTime) except RuntimeError: # ignore exceptions, keep trying logger.info("Wait for appliance failed ssh, trying again.") sleepTime += 20 def _waitForSSHPort(self): """ Wait until the instance represented by this box is accessible via SSH. :return: the number of unsuccessful attempts to connect to the port before a the first success """ logger.debug('Waiting for ssh port to open...') for i in count(): s = socket.socket(socket.AF_INET, socket.SOCK_STREAM) try: s.settimeout(a_short_time) s.connect((self.effectiveIP, 22)) logger.debug('...ssh port open') return i except socket.error: pass finally: s.close() def sshAppliance(self, *args, **kwargs): """ :param args: arguments to execute in the appliance :param kwargs: tty=bool tells docker whether or not to create a TTY shell for interactive SSHing. The default value is False. Input=string is passed as input to the Popen call. """ kwargs['appliance'] = True return self.coreSSH(*args, **kwargs) def sshInstance(self, *args, **kwargs): """ Run a command on the instance. Returns the binary output of the command. """ kwargs['collectStdout'] = True return self.coreSSH(*args, **kwargs) def coreSSH(self, *args, **kwargs): """ If strict=False, strict host key checking will be temporarily disabled. This is provided as a convenience for internal/automated functions and ought to be set to True whenever feasible, or whenever the user is directly interacting with a resource (e.g. rsync-cluster or ssh-cluster). Assumed to be False by default. kwargs: input, tty, appliance, collectStdout, sshOptions, strict """ commandTokens = ['ssh', '-t'] strict = kwargs.pop('strict', False) if not strict: kwargs['sshOptions'] = ['-oUserKnownHostsFile=/dev/null', '-oStrictHostKeyChecking=no'] \ + kwargs.get('sshOptions', []) sshOptions = kwargs.pop('sshOptions', None) # Forward ports: # 3000 for Grafana dashboard # 9090 for Prometheus dashboard # 5050 for Mesos dashboard (although to talk to agents you will need a proxy) commandTokens.extend(['-L', '3000:localhost:3000', \ '-L', '9090:localhost:9090', \ '-L', '5050:localhost:5050']) if sshOptions: # add specified options to ssh command assert isinstance(sshOptions, list) commandTokens.extend(sshOptions) # specify host user = kwargs.pop('user', 'core') # CHANGED: Is this needed? commandTokens.append('%s@%s' % (user,str(self.effectiveIP))) appliance = kwargs.pop('appliance', None) if appliance: # run the args in the appliance tty = kwargs.pop('tty', None) ttyFlag = '-t' if tty else '' commandTokens += ['docker', 'exec', '-i', ttyFlag, 'toil_leader'] inputString = kwargs.pop('input', None) if inputString is not None: kwargs['stdin'] = subprocess.PIPE collectStdout = kwargs.pop('collectStdout', None) if collectStdout: kwargs['stdout'] = subprocess.PIPE kwargs['stderr'] = subprocess.PIPE logger.debug('Node %s: %s', self.effectiveIP, ' '.join(args)) args = list(map(pipes.quote, args)) commandTokens += args logger.debug('Full command %s', ' '.join(commandTokens)) popen = subprocess.Popen(commandTokens, **kwargs) stdout, stderr = popen.communicate(input=inputString) # at this point the process has already exited, no need for a timeout resultValue = popen.wait() # ssh has been throwing random 255 errors - why? if resultValue != 0: logger.debug('SSH Error (%s) %s' % (resultValue, stderr)) raise RuntimeError('Executing the command "%s" on the appliance returned a non-zero ' 'exit code %s with stdout %s and stderr %s' % (' '.join(args), resultValue, stdout, stderr)) return stdout def coreRsync(self, args, applianceName='toil_leader', **kwargs): remoteRsync = "docker exec -i %s rsync" % applianceName # Access rsync inside appliance parsedArgs = [] sshCommand = "ssh" strict = kwargs.pop('strict', False) if not strict: sshCommand = "ssh -oUserKnownHostsFile=/dev/null -oStrictHostKeyChecking=no" hostInserted = False # Insert remote host address for i in args: if i.startswith(":") and not hostInserted: user = kwargs.pop('user', 'core') # CHANGED: Is this needed? i = ("%s@%s" % (user, self.effectiveIP)) + i hostInserted = True elif i.startswith(":") and hostInserted: raise ValueError("Cannot rsync between two remote hosts") parsedArgs.append(i) if not hostInserted: raise ValueError("No remote host found in argument list") command = ['rsync', '-e', sshCommand, '--rsync-path', remoteRsync] logger.debug("Running %r.", command + parsedArgs) return subprocess.check_call(command + parsedArgs) toil-releases-3.24.0/src/toil/realtimeLogger.py000066400000000000000000000225041362134276200214330ustar00rootroot00000000000000# Copyright (C) 2015-2018 Regents of the University of California # # 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. """ Implements a real-time UDP-based logging system that user scripts can use for debugging. """ from __future__ import absolute_import from future import standard_library standard_library.install_aliases() from builtins import object from builtins import super import os import os.path import json import logging import logging.handlers import threading from six.moves import socketserver as SocketServer from future.utils import with_metaclass import toil.lib.bioio from toil.batchSystems.options import getPublicIP log = logging.getLogger(__name__) class LoggingDatagramHandler(SocketServer.BaseRequestHandler): """ Receive logging messages from the jobs and display them on the leader. Uses bare JSON message encoding. """ def handle(self): """ Handle a single message. SocketServer takes care of splitting out the messages. Messages are JSON-encoded logging module records. """ # Unpack the data from the request data, socket = self.request try: # Parse it as JSON message_attrs = json.loads(data.decode('utf-8')) # Fluff it up into a proper logging record record = logging.makeLogRecord(message_attrs) if isinstance(record.args, list): # Going through JSON turned tuples into lists. Lazy formatting # means this might have happened to all the arguments. We need # to fix this at least for the root list of format string # arguments, or formatting will fail # # TODO: Protect the arguments better by actually pickling # instead of using JSON? # # TODO: Format the message on the sending side? record.args = tuple(record.args) except: # Complain someone is sending us bad logging data logging.error("Malformed log message from {}".format(self.client_address[0])) else: # Log level filtering should have been done on the remote end. The handle() method # skips it on this end. log.handle(record) class JSONDatagramHandler(logging.handlers.DatagramHandler): """ Send logging records over UDP serialized as JSON. They have to fit in a single UDP datagram, so don't try to log more than 64kb at once. """ def makePickle(self, record): """ Actually, encode the record as bare JSON instead. """ return json.dumps(record.__dict__).encode('utf-8') class RealtimeLoggerMetaclass(type): """ Metaclass for RealtimeLogger that lets you do things like RealtimeLogger.warning(), RealtimeLogger.info(), etc. """ def __getattr__(self, name): """ If a real attribute can't be found, try one of the logging methods on the actual logger object. """ return getattr(self.getLogger(), name) class RealtimeLogger(with_metaclass(RealtimeLoggerMetaclass, object)): """ Provides a logger that logs over UDP to the leader. To use in a Toil job, do: >>> from toil.realtimeLogger import RealtimeLogger >>> RealtimeLogger.info("This logging message goes straight to the leader") That's all a user of Toil would need to do. On the leader, Job.Runner.startToil() automatically starts the UDP server by using an instance of this class as a context manager. """ # The names of all environment variables used by this class are prefixed with this string envPrefix = "TOIL_RT_LOGGING_" # Avoid duplicating the default level everywhere defaultLevel = 'INFO' # State maintained on server and client lock = threading.RLock() # Server-side state # The leader keeps a server and thread loggingServer = None serverThread = None initialized = 0 # Client-side state logger = None @classmethod def _startLeader(cls, batchSystem, level=defaultLevel): with cls.lock: if cls.initialized == 0: cls.initialized += 1 if level: log.info('Starting real-time logging.') # Start up the logging server cls.loggingServer = SocketServer.ThreadingUDPServer( server_address=('0.0.0.0', 0), RequestHandlerClass=LoggingDatagramHandler) # Set up a thread to do all the serving in the background and exit when we do cls.serverThread = threading.Thread(target=cls.loggingServer.serve_forever) cls.serverThread.daemon = True cls.serverThread.start() # Set options for logging in the environment so they get sent out to jobs ip = getPublicIP() port = cls.loggingServer.server_address[1] def _setEnv(name, value): name = cls.envPrefix + name os.environ[name] = value batchSystem.setEnv(name) _setEnv('ADDRESS', '%s:%i' % (ip, port)) _setEnv('LEVEL', level) else: log.debug('Real-time logging disabled') else: if level: log.warning('Ignoring nested request to start real-time logging') @classmethod def _stopLeader(cls): """ Stop the server on the leader. """ with cls.lock: assert cls.initialized > 0 cls.initialized -= 1 if cls.initialized == 0: if cls.loggingServer: log.info('Stopping real-time logging server.') cls.loggingServer.shutdown() cls.loggingServer = None if cls.serverThread: log.info('Joining real-time logging server thread.') cls.serverThread.join() cls.serverThread = None for k in list(os.environ.keys()): if k.startswith(cls.envPrefix): os.environ.pop(k) @classmethod def getLogger(cls): """ Get the logger that logs real-time to the leader. Note that if the returned logger is used on the leader, you will see the message twice, since it still goes to the normal log handlers, too. """ # Only do the setup once, so we don't add a handler every time we log. Use a lock to do # so safely even if we're being called in different threads. Use double-checked locking # to reduce the overhead introduced by the lock. if cls.logger is None: with cls.lock: if cls.logger is None: cls.logger = logging.getLogger('toil-rt') try: level = os.environ[cls.envPrefix + 'LEVEL'] except KeyError: # There is no server running on the leader, so suppress most log messages # and skip the UDP stuff. cls.logger.setLevel(logging.CRITICAL) else: # Adopt the logging level set on the leader. toil.lib.bioio.setLogLevel(level, cls.logger) try: address = os.environ[cls.envPrefix + 'ADDRESS'] except KeyError: pass else: # We know where to send messages to, so send them. host, port = address.split(':') cls.logger.addHandler(JSONDatagramHandler(host, int(port))) return cls.logger def __init__(self, batchSystem, level=defaultLevel): """ A context manager that starts up the UDP server. Should only be invoked on the leader. Python logging should have already been configured. This method takes an optional log level, as a string level name, from the set supported by bioio. If the level is None, False or the empty string, real-time logging will be disabled, i.e. no UDP server will be started on the leader and log messages will be suppressed on the workers. Note that this is different from passing level='OFF', which is equivalent to level='CRITICAL' and does not disable the server. """ super().__init__() self.__level = level self.__batchSystem = batchSystem def __enter__(self): RealtimeLogger._startLeader(self.__batchSystem, level=self.__level) # noinspection PyUnusedLocal def __exit__(self, exc_type, exc_val, exc_tb): RealtimeLogger._stopLeader() toil-releases-3.24.0/src/toil/resource.py000066400000000000000000000562351362134276200203300ustar00rootroot00000000000000# Copyright (C) 2015-2018 Regents of the University of California # # 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. from __future__ import absolute_import from future import standard_library standard_library.install_aliases() from builtins import map import errno import hashlib import importlib import json import logging import os import shutil import sys from collections import namedtuple from contextlib import closing from io import BytesIO from pydoc import locate from tempfile import mkdtemp from urllib.error import HTTPError from zipfile import ZipFile # Python 3 compatibility imports from toil.lib.retry import retry from six.moves.urllib.request import urlopen from toil.lib.memoize import strict_bool from toil.lib.iterables import concat from toil.version import exactPython from toil import inVirtualEnv log = logging.getLogger(__name__) class Resource(namedtuple('Resource', ('name', 'pathHash', 'url', 'contentHash'))): """ Represents a file or directory that will be deployed to each node before any jobs in the user script are invoked. Each instance is a namedtuple with the following elements: The pathHash element contains the MD5 (in hexdigest form) of the path to the resource on the leader node. The path, and therefore its hash is unique within a job store. The url element is a "file:" or "http:" URL at which the resource can be obtained. The contentHash element is an MD5 checksum of the resource, allowing for validation and caching of resources. If the resource is a regular file, the type attribute will be 'file'. If the resource is a directory, the type attribute will be 'dir' and the URL will point at a ZIP archive of that directory. """ resourceEnvNamePrefix = 'JTRES_' rootDirPathEnvName = resourceEnvNamePrefix + 'ROOT' @classmethod def create(cls, jobStore, leaderPath): """ Saves the content of the file or directory at the given path to the given job store and returns a resource object representing that content for the purpose of obtaining it again at a generic, public URL. This method should be invoked on the leader node. :param toil.jobStores.abstractJobStore.AbstractJobStore jobStore: :param str leaderPath: :rtype: Resource """ pathHash = cls._pathHash(leaderPath) contentHash = hashlib.md5() # noinspection PyProtectedMember with cls._load(leaderPath) as src: with jobStore.writeSharedFileStream(sharedFileName=pathHash, isProtected=False) as dst: userScript = src.read() contentHash.update(userScript) dst.write(userScript) return cls(name=os.path.basename(leaderPath), pathHash=pathHash, url=jobStore.getSharedPublicUrl(sharedFileName=pathHash), contentHash=contentHash.hexdigest()) def refresh(self, jobStore): return type(self)(name=self.name, pathHash=self.pathHash, url=jobStore.getSharedPublicUrl(sharedFileName=self.pathHash), contentHash=self.contentHash) @classmethod def prepareSystem(cls): """ Prepares this system for the downloading and lookup of resources. This method should only be invoked on a worker node. It is idempotent but not thread-safe. """ try: resourceRootDirPath = os.environ[cls.rootDirPathEnvName] except KeyError: # Create directory holding local copies of requested resources ... resourceRootDirPath = mkdtemp() # .. and register its location in an environment variable such that child processes # can find it. os.environ[cls.rootDirPathEnvName] = resourceRootDirPath assert os.path.isdir(resourceRootDirPath) @classmethod def cleanSystem(cls): """ Removes all downloaded, localized resources """ resourceRootDirPath = os.environ[cls.rootDirPathEnvName] os.environ.pop(cls.rootDirPathEnvName) shutil.rmtree(resourceRootDirPath) for k, v in list(os.environ.items()): if k.startswith(cls.resourceEnvNamePrefix): os.environ.pop(k) def register(self): """ Register this resource for later retrieval via lookup(), possibly in a child process. """ os.environ[self.resourceEnvNamePrefix + self.pathHash] = self.pickle() @classmethod def lookup(cls, leaderPath): """ Returns a resource object representing a resource created from a file or directory at the given path on the leader. This method should be invoked on the worker. The given path does not need to refer to an existing file or directory on the worker, it only identifies the resource within an instance of toil. This method returns None if no resource for the given path exists. :rtype: Resource """ pathHash = cls._pathHash(leaderPath) try: path_key = cls.resourceEnvNamePrefix + pathHash s = os.environ[path_key] except KeyError: log.warning("'%s' may exist, but is not yet referenced by the worker (KeyError from os.environ[]).", str(path_key)) return None else: self = cls.unpickle(s) assert self.pathHash == pathHash return self def download(self, callback=None): """ Downloads this resource from its URL to a file on the local system. This method should only be invoked on a worker node after the node was setup for accessing resources via prepareSystem(). """ dirPath = self.localDirPath if not os.path.exists(dirPath): tempDirPath = mkdtemp(dir=os.path.dirname(dirPath), prefix=self.contentHash + "-") self._save(tempDirPath) if callback is not None: callback(tempDirPath) try: os.rename(tempDirPath, dirPath) except OSError as e: # If dirPath already exists & is non-empty either ENOTEMPTY or EEXIST will be raised if e.errno == errno.ENOTEMPTY or e.errno == errno.EEXIST: # Another process beat us to it. # TODO: This is correct but inefficient since multiple processes download the resource redundantly pass else: raise @property def localPath(self): """ The path to resource on the worker. The file or directory at the returned path may or may not yet exist. Invoking download() will ensure that it does. """ raise NotImplementedError @property def localDirPath(self): """ The path to the directory containing the resource on the worker. """ rootDirPath = os.environ[self.rootDirPathEnvName] return os.path.join(rootDirPath, self.contentHash) def pickle(self): return self.__class__.__module__ + "." + self.__class__.__name__ + ':' + json.dumps(self) @classmethod def unpickle(cls, s): """ :rtype: Resource """ className, _json = s.split(':', 1) return locate(className)(*json.loads(_json)) @classmethod def _pathHash(cls, path): return hashlib.md5(path.encode('utf-8')).hexdigest() @classmethod def _load(cls, path): """ Returns a readable file-like object for the given path. If the path refers to a regular file, this method returns the result of invoking open() on the given path. If the path refers to a directory, this method returns a ZIP file with all files and subdirectories in the directory at the given path. :type path: str :rtype: io.FileIO """ raise NotImplementedError() def _save(self, dirPath): """ Save this resource to the directory at the given parent path. :type dirPath: str """ raise NotImplementedError() def _download(self, dstFile): """ Download this resource from its URL to the given file object. :type dstFile: io.BytesIO|io.FileIO """ for attempt in retry(predicate=lambda e: isinstance(e, HTTPError) and e.code == 400): with attempt: with closing(urlopen(self.url)) as content: buf = content.read() contentHash = hashlib.md5(buf) assert contentHash.hexdigest() == self.contentHash dstFile.write(buf) class FileResource(Resource): """ A resource read from a file on the leader. """ @classmethod def _load(cls, path): return open(path) def _save(self, dirPath): with open(os.path.join(dirPath, self.name), mode='w') as localFile: self._download(localFile) @property def localPath(self): return os.path.join(self.localDirPath, self.name) class DirectoryResource(Resource): """ A resource read from a directory on the leader. The URL will point to a ZIP archive of the directory. All files in that directory (and any subdirectories) will be included. The directory may be a package but it does not need to be. """ @classmethod def _load(cls, path): """ :type path: str """ bytesIO = BytesIO() initfile = os.path.join(path, '__init__.py') if os.path.isfile(initfile): # This is a package directory. To emulate # PyZipFile.writepy's behavior, we need to keep everything # relative to this path's parent directory. rootDir = os.path.dirname(path) else: # This is a simple user script (with possibly a few helper files) rootDir = path skipdirList = ['/tmp', '/var', '/etc', '/bin', '/sbin', '/home', '/dev', '/sys', '/usr', '/run'] if path not in skipdirList: with ZipFile(file=bytesIO, mode='w') as zipFile: for dirName, _, fileList in os.walk(path): for fileName in fileList: try: fullPath = os.path.join(dirName, fileName) zipFile.write(fullPath, os.path.relpath(fullPath, rootDir)) except IOError: log.critical('Cannot access and read the file at path: %s' % fullPath) sys.exit(1) else: log.critical("Couldn't package the directory at %s for hot deployment. Would recommend to create a \ subdirectory (ie %s/MYDIR_HERE/)" % (path, path)) sys.exit(1) bytesIO.seek(0) return bytesIO def _save(self, dirPath): bytesIO = BytesIO() self._download(bytesIO) bytesIO.seek(0) with ZipFile(file=bytesIO, mode='r') as zipFile: zipFile.extractall(path=dirPath) @property def localPath(self): return self.localDirPath class VirtualEnvResource(DirectoryResource): """ A resource read from a virtualenv on the leader. All modules and packages found in the virtualenv's site-packages directory will be included. """ @classmethod def _load(cls, path): """ :type path: str """ assert os.path.basename(path) == 'site-packages' bytesIO = BytesIO() with ZipFile(file=bytesIO, mode='w') as zipFile: for dirName, _, fileList in os.walk(path): zipFile.write(dirName) for fileName in fileList: fullPath = os.path.join(dirName, fileName) zipFile.write(fullPath, os.path.relpath(fullPath, path)) bytesIO.seek(0) return bytesIO class ModuleDescriptor(namedtuple('ModuleDescriptor', ('dirPath', 'name', 'fromVirtualEnv'))): """ A path to a Python module decomposed into a namedtuple of three elements, namely - dirPath, the path to the directory that should be added to sys.path before importing the module, - moduleName, the fully qualified name of the module with leading package names separated by dot and >>> import toil.resource >>> ModuleDescriptor.forModule('toil.resource') # doctest: +ELLIPSIS ModuleDescriptor(dirPath='/.../src', name='toil.resource', fromVirtualEnv=False) >>> import subprocess, tempfile, os >>> dirPath = tempfile.mkdtemp() >>> path = os.path.join( dirPath, 'foo.py' ) >>> with open(path,'w') as f: ... _ = f.write('from toil.resource import ModuleDescriptor\\n' ... 'print(ModuleDescriptor.forModule(__name__))') >>> subprocess.check_output([ sys.executable, path ]) # doctest: +ELLIPSIS +ALLOW_BYTES b"ModuleDescriptor(dirPath='...', name='foo', fromVirtualEnv=False)\\n" >>> from shutil import rmtree >>> rmtree( dirPath ) Now test a collision. 'collections' is part of the standard library in Python 2 and 3. >>> dirPath = tempfile.mkdtemp() >>> path = os.path.join( dirPath, 'collections.py' ) >>> with open(path,'w') as f: ... _ = f.write('from toil.resource import ModuleDescriptor\\n' ... 'ModuleDescriptor.forModule(__name__)') This should fail and return exit status 1 due to the collision with the built-in module: >>> subprocess.call([ sys.executable, path ]) 1 Clean up >>> rmtree( dirPath ) """ @classmethod def forModule(cls, name): """ Return an instance of this class representing the module of the given name. If the given module name is "__main__", it will be translated to the actual file name of the top-level script without the .py or .pyc extension. This method assumes that the module with the specified name has already been loaded. """ module = sys.modules[name] filePath = os.path.abspath(module.__file__) filePath = filePath.split(os.path.sep) filePath[-1], extension = os.path.splitext(filePath[-1]) if not extension in ('.py', '.pyc'): raise Exception('The name of a user script/module must end in .py or .pyc.') if name == '__main__': log.debug("Discovering real name of module") # User script/module was invoked as the main program if module.__package__: # Invoked as a module via python -m foo.bar log.debug("Script was invoked as a module") name = [filePath.pop()] for package in reversed(module.__package__.split('.')): dirPathTail = filePath.pop() assert dirPathTail == package name.append(dirPathTail) name = '.'.join(reversed(name)) dirPath = os.path.sep.join(filePath) else: # Invoked as a script via python foo/bar.py name = filePath.pop() dirPath = os.path.sep.join(filePath) cls._check_conflict(dirPath, name) else: # User module was imported. Determine the directory containing the top-level package if filePath[-1] == '__init__': # module is a subpackage filePath.pop() for package in reversed(name.split('.')): dirPathTail = filePath.pop() assert dirPathTail == package dirPath = os.path.sep.join(filePath) log.debug("Module dir is %s", dirPath) if not os.path.isdir(dirPath): raise Exception('Bad directory path %s for module %s. Note that hot-deployment does not support .egg-link files yet, or scripts located in the root directory.' % (dirPath, name)) fromVirtualEnv = inVirtualEnv() and dirPath.startswith(sys.prefix) return cls(dirPath=dirPath, name=name, fromVirtualEnv=fromVirtualEnv) @classmethod def _check_conflict(cls, dirPath, name): """ Check whether the module of the given name conflicts with another module on the sys.path. :param dirPath: the directory from which the module was originally loaded :param name: the mpdule name """ old_sys_path = sys.path try: sys.path = [d for d in old_sys_path if os.path.realpath(d) != os.path.realpath(dirPath)] try: colliding_module = importlib.import_module(name) except ImportError: pass else: raise ResourceException( "The user module '%s' collides with module '%s from '%s'." % ( name, colliding_module.__name__, colliding_module.__file__)) finally: sys.path = old_sys_path @property def belongsToToil(self): """ True if this module is part of the Toil distribution """ return self.name.startswith('toil.') def saveAsResourceTo(self, jobStore): """ Store the file containing this module--or even the Python package directory hierarchy containing that file--as a resource to the given job store and return the corresponding resource object. Should only be called on a leader node. :type jobStore: toil.jobStores.abstractJobStore.AbstractJobStore :rtype: toil.resource.Resource """ return self._getResourceClass().create(jobStore, self._resourcePath) def _getResourceClass(self): """ Return the concrete subclass of Resource that's appropriate for auto-deploying this module. """ if self.fromVirtualEnv: subcls = VirtualEnvResource elif os.path.isdir(self._resourcePath): subcls = DirectoryResource elif os.path.isfile(self._resourcePath): subcls = FileResource elif os.path.exists(self._resourcePath): raise AssertionError("Neither a file or a directory: '%s'" % self._resourcePath) else: raise AssertionError("No such file or directory: '%s'" % self._resourcePath) return subcls def localize(self): """ Check if this module was saved as a resource. If it was, return a new module descriptor that points to a local copy of that resource. Should only be called on a worker node. On the leader, this method returns this resource, i.e. self. :rtype: toil.resource.Resource """ if not self._runningOnWorker(): log.warning('The localize() method should only be invoked on a worker.') resource = Resource.lookup(self._resourcePath) if resource is None: return self else: def stash(tmpDirPath): # Save the original dirPath such that we can restore it in globalize() with open(os.path.join(tmpDirPath, '.stash'), 'w') as f: f.write('1' if self.fromVirtualEnv else '0') f.write(self.dirPath) resource.download(callback=stash) return self.__class__(dirPath=resource.localDirPath, name=self.name, fromVirtualEnv=self.fromVirtualEnv) def _runningOnWorker(self): try: mainModule = sys.modules['__main__'] except KeyError: log.warning('Cannot determine main program module.') return False else: # If __file__ is not a valid attribute, it's because # toil is being run interactively, in which case # we can reasonably assume that we are not running # on a worker node. try: mainModuleFile = os.path.basename(mainModule.__file__) except AttributeError: return False workerModuleFiles = concat(('worker' + ext for ext in self.moduleExtensions), '_toil_worker') # the setuptools entry point return mainModuleFile in workerModuleFiles def globalize(self): """ Reverse the effect of localize(). """ try: with open(os.path.join(self.dirPath, '.stash')) as f: fromVirtualEnv = [False, True][int(f.read(1))] dirPath = f.read() except IOError as e: if e.errno == errno.ENOENT: if self._runningOnWorker(): log.warning("Can't globalize module %r.", self) return self else: raise else: return self.__class__(dirPath=dirPath, name=self.name, fromVirtualEnv=fromVirtualEnv) @property def _resourcePath(self): """ The path to the directory that should be used when shipping this module and its siblings around as a resource. """ if self.fromVirtualEnv: return self.dirPath elif '.' in self.name: return os.path.join(self.dirPath, self._rootPackage()) else: initName = self._initModuleName(self.dirPath) if initName: raise ResourceException( "Toil does not support loading a user script from a package directory. You " "may want to remove %s from %s or invoke the user script as a module via " "'PYTHONPATH=\"%s\" %s -m %s.%s'." % tuple(concat(initName, self.dirPath, exactPython, os.path.split(self.dirPath), self.name))) return self.dirPath moduleExtensions = ('.py', '.pyc', '.pyo') @classmethod def _initModuleName(cls, dirPath): for extension in cls.moduleExtensions: name = '__init__' + extension if os.path.exists(os.path.join(dirPath, name)): return name return None def _rootPackage(self): try: head, tail = self.name.split('.', 1) except ValueError: raise ValueError('%r is stand-alone module.' % self) else: return head def toCommand(self): return tuple(map(str, self)) @classmethod def fromCommand(cls, command): assert len(command) == 3 return cls(dirPath=command[0], name=command[1], fromVirtualEnv=strict_bool(command[2])) def makeLoadable(self): module = self if self.belongsToToil else self.localize() if module.dirPath not in sys.path: sys.path.append(module.dirPath) return module def load(self): module = self.makeLoadable() try: return importlib.import_module(module.name) except ImportError: log.error('Failed to import user module %r from sys.path (%r).', module, sys.path) raise class ResourceException(Exception): pass toil-releases-3.24.0/src/toil/serviceManager.py000066400000000000000000000251711362134276200214270ustar00rootroot00000000000000# Copyright (C) 2015-2018 Regents of the University of California # # 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. from __future__ import absolute_import from builtins import map from builtins import object import logging import time from threading import Thread, Event from toil.lib.throttle import throttle # Python 3 compatibility imports from six.moves.queue import Empty, Queue logger = logging.getLogger( __name__ ) class ServiceManager( object ): """ Manages the scheduling of services. """ def __init__(self, jobStore, toilState): logger.debug("Initializing service manager") self.jobStore = jobStore self.toilState = toilState self.jobGraphsWithServicesBeingStarted = set() self._terminate = Event() # This is used to terminate the thread associated # with the service manager self._jobGraphsWithServicesToStart = Queue() # This is the input queue of # jobGraphs that have services that need to be started self._jobGraphsWithServicesThatHaveStarted = Queue() # This is the output queue # of jobGraphs that have services that are already started self._serviceJobGraphsToStart = Queue() # This is the queue of services for the # batch system to start self.jobsIssuedToServiceManager = 0 # The number of jobs the service manager # is scheduling # Start a thread that starts the services of jobGraphs in the # jobsWithServicesToStart input queue and puts the jobGraphs whose services # are running on the jobGraphssWithServicesThatHaveStarted output queue self._serviceStarter = Thread(target=self._startServices, args=(self._jobGraphsWithServicesToStart, self._jobGraphsWithServicesThatHaveStarted, self._serviceJobGraphsToStart, self._terminate, self.jobStore)) def start(self): """ Start the service scheduling thread. """ self._serviceStarter.start() def scheduleServices(self, jobGraph): """ Schedule the services of a job asynchronously. When the job's services are running the jobGraph for the job will be returned by toil.leader.ServiceManager.getJobGraphsWhoseServicesAreRunning. :param toil.jobGraph.JobGraph jobGraph: wrapper of job with services to schedule. """ # Add jobGraph to set being processed by the service manager self.jobGraphsWithServicesBeingStarted.add(jobGraph) # Add number of jobs managed by ServiceManager self.jobsIssuedToServiceManager += sum(map(len, jobGraph.services)) + 1 # The plus one accounts for the root job # Asynchronously schedule the services self._jobGraphsWithServicesToStart.put(jobGraph) def getJobGraphWhoseServicesAreRunning(self, maxWait): """ :param float maxWait: Time in seconds to wait to get a jobGraph before returning :return: a jobGraph added to scheduleServices whose services are running, or None if no such job is available. :rtype: JobGraph """ try: jobGraph = self._jobGraphsWithServicesThatHaveStarted.get(timeout=maxWait) self.jobGraphsWithServicesBeingStarted.remove(jobGraph) assert self.jobsIssuedToServiceManager >= 0 self.jobsIssuedToServiceManager -= 1 return jobGraph except Empty: return None def getServiceJobsToStart(self, maxWait): """ :param float maxWait: Time in seconds to wait to get a job before returning. :return: a tuple of (serviceJobStoreID, memory, cores, disk, ..) representing a service job to start. :rtype: toil.job.ServiceJobNode """ try: serviceJob = self._serviceJobGraphsToStart.get(timeout=maxWait) assert self.jobsIssuedToServiceManager >= 0 self.jobsIssuedToServiceManager -= 1 return serviceJob except Empty: return None def killServices(self, services, error=False): """ :param dict services: Maps service jobStoreIDs to the communication flags for the service """ for serviceJobStoreID in services: serviceJob = services[serviceJobStoreID] if error: self.jobStore.deleteFile(serviceJob.errorJobStoreID) self.jobStore.deleteFile(serviceJob.terminateJobStoreID) def isActive(self, serviceJobNode): """ Returns true if the service job has not been told to terminate. :rtype: boolean """ return self.jobStore.fileExists(serviceJobNode.terminateJobStoreID) def isRunning(self, serviceJobNode): """ Returns true if the service job has started and is active :rtype: boolean """ return (not self.jobStore.fileExists(serviceJobNode.startJobStoreID)) and self.isActive(serviceJobNode) def check(self): """ Check on the service manager thread. :raise RuntimeError: If the underlying thread has quit. """ if not self._serviceStarter.is_alive(): raise RuntimeError("Service manager has quit") def shutdown(self): """ Cleanly terminate worker threads starting and killing services. Will block until all services are started and blocked. """ logger.debug('Waiting for service manager thread to finish ...') startTime = time.time() self._terminate.set() self._serviceStarter.join() # Kill any services still running to avoid deadlock for services in list(self.toilState.servicesIssued.values()): self.killServices(services, error=True) logger.debug('... finished shutting down the service manager. Took %s seconds', time.time() - startTime) @staticmethod def _startServices(jobGraphsWithServicesToStart, jobGraphsWithServicesThatHaveStarted, serviceJobsToStart, terminate, jobStore): """ Thread used to schedule services. """ servicesThatAreStarting = set() servicesRemainingToStartForJob = {} serviceToJobGraph = {} while True: with throttle(1.0): if terminate.is_set(): logger.debug('Received signal to quit starting services.') break try: jobGraph = jobGraphsWithServicesToStart.get_nowait() if len(jobGraph.services) > 1: # Have to fall back to the old blocking behavior to # ensure entire service "groups" are issued as a whole. blockUntilServiceGroupIsStarted(jobGraph, jobGraphsWithServicesThatHaveStarted, serviceJobsToStart, terminate, jobStore) continue # Found a new job that needs to schedule its services. for serviceJob in jobGraph.services[0]: serviceToJobGraph[serviceJob] = jobGraph servicesRemainingToStartForJob[jobGraph] = len(jobGraph.services[0]) # Issue the service jobs all at once. for serviceJob in jobGraph.services[0]: logger.debug("Service manager is starting service job: %s, start ID: %s", serviceJob, serviceJob.startJobStoreID) serviceJobsToStart.put(serviceJob) # We should now start to monitor these services to see if # they've started yet. servicesThatAreStarting.update(jobGraph.services[0]) except Empty: # No new jobs that need services scheduled. pass for serviceJob in list(servicesThatAreStarting): if not jobStore.fileExists(serviceJob.startJobStoreID): # Service has started! servicesThatAreStarting.remove(serviceJob) parentJob = serviceToJobGraph[serviceJob] servicesRemainingToStartForJob[parentJob] -= 1 assert servicesRemainingToStartForJob[parentJob] >= 0 del serviceToJobGraph[serviceJob] # Find if any jobGraphs have had *all* their services started. jobGraphsToRemove = set() for jobGraph, remainingServices in servicesRemainingToStartForJob.items(): if remainingServices == 0: jobGraphsWithServicesThatHaveStarted.put(jobGraph) jobGraphsToRemove.add(jobGraph) for jobGraph in jobGraphsToRemove: del servicesRemainingToStartForJob[jobGraph] def blockUntilServiceGroupIsStarted(jobGraph, jobGraphsWithServicesThatHaveStarted, serviceJobsToStart, terminate, jobStore): # Start the service jobs in batches, waiting for each batch # to become established before starting the next batch for serviceJobList in jobGraph.services: for serviceJob in serviceJobList: logger.debug("Service manager is starting service job: %s, start ID: %s", serviceJob, serviceJob.startJobStoreID) assert jobStore.fileExists(serviceJob.startJobStoreID) # At this point the terminateJobStoreID and errorJobStoreID could have been deleted! serviceJobsToStart.put(serviceJob) # Wait until all the services of the batch are running for serviceJob in serviceJobList: while jobStore.fileExists(serviceJob.startJobStoreID): # Sleep to avoid thrashing time.sleep(1.0) # Check if the thread should quit if terminate.is_set(): return # Add the jobGraph to the output queue of jobs whose services have been started jobGraphsWithServicesThatHaveStarted.put(jobGraph) toil-releases-3.24.0/src/toil/statsAndLogging.py000066400000000000000000000153251362134276200215640ustar00rootroot00000000000000# Copyright (C) 2015-2018 Regents of the University of California # # 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. from __future__ import absolute_import from builtins import str from builtins import object import gzip import json import logging import os import time from threading import Thread, Event from toil.lib.expando import Expando from toil.lib.bioio import getTotalCpuTime logger = logging.getLogger( __name__ ) class StatsAndLogging( object ): """ Class manages a thread that aggregates statistics and logging information on a toil run. """ def __init__(self, jobStore, config): self._stop = Event() self._worker = Thread(target=self.statsAndLoggingAggregator, args=(jobStore, self._stop, config)) def start(self): """ Start the stats and logging thread. """ self._worker.start() @classmethod def logWithFormatting(cls, jobStoreID, jobLogs, method=logger.debug, message=None): if message is not None: method(message) if isinstance(jobStoreID, bytes): jobStoreID = jobStoreID.decode('utf-8') for line in jobLogs: if isinstance(line, bytes): line = line.decode('utf-8') method('%s %s', jobStoreID, line.rstrip('\n')) @classmethod def writeLogFiles(cls, jobNames, jobLogList, config, failed=False): def createName(logPath, jobName, logExtension, failed=False): logName = jobName.replace('-', '--') logName = logName.replace('/', '-') logName = logName.replace(' ', '_') logName = logName.replace("'", '') logName = logName.replace('"', '') # Add a "failed_" prefix to logs from failed jobs. logName = ('failed_' if failed else '') + logName counter = 0 while True: suffix = str(counter).zfill(3) + logExtension fullName = os.path.join(logPath, logName + suffix) # The maximum file name size in the default HFS+ file system is 255 UTF-16 encoding units, so basically 255 characters if len(fullName) >= 255: return fullName[:(255-len(suffix))] + suffix if not os.path.exists(fullName): return fullName counter += 1 mainFileName = jobNames[0] extension = '.log' if config.writeLogs: path = config.writeLogs writeFn = open elif config.writeLogsGzip: path = config.writeLogsGzip writeFn = gzip.open extension += '.gz' else: # we don't have anywhere to write the logs, return now return fullName = createName(path, mainFileName, extension, failed) with writeFn(fullName, 'wb') as f: for l in jobLogList: try: l = l.decode('utf-8') except AttributeError: pass if not l.endswith('\n'): l += '\n' f.write(l.encode('utf-8')) for alternateName in jobNames[1:]: # There are chained jobs in this output - indicate this with a symlink # of the job's name to this file name = createName(path, alternateName, extension, failed) os.symlink(os.path.relpath(fullName, path), name) @classmethod def statsAndLoggingAggregator(cls, jobStore, stop, config): """ The following function is used for collating stats/reporting log messages from the workers. Works inside of a thread, collates as long as the stop flag is not True. """ # Overall timing startTime = time.time() startClock = getTotalCpuTime() def callback(fileHandle): statsStr = fileHandle.read() if not isinstance(statsStr, str): statsStr = statsStr.decode() stats = json.loads(statsStr, object_hook=Expando) try: logs = stats.workers.logsToMaster except AttributeError: # To be expected if there were no calls to logToMaster() pass else: for message in logs: logger.log(int(message.level), 'Got message from job at time %s: %s', time.strftime('%m-%d-%Y %H:%M:%S'), message.text) try: logs = stats.logs except AttributeError: pass else: # we may have multiple jobs per worker jobNames = logs.names messages = logs.messages cls.logWithFormatting(jobNames[0], messages, message='Received Toil worker log. Disable debug level logging to hide this output') cls.writeLogFiles(jobNames, messages, config=config) while True: # This is a indirect way of getting a message to the thread to exit if stop.is_set(): jobStore.readStatsAndLogging(callback) break if jobStore.readStatsAndLogging(callback) == 0: time.sleep(0.5) # Avoid cycling too fast # Finish the stats file text = json.dumps(dict(total_time=str(time.time() - startTime), total_clock=str(getTotalCpuTime() - startClock)), ensure_ascii=True) jobStore.writeStatsAndLogging(text) def check(self): """ Check on the stats and logging aggregator. :raise RuntimeError: If the underlying thread has quit. """ if not self._worker.is_alive(): raise RuntimeError("Stats and logging thread has quit") def shutdown(self): """ Finish up the stats/logging aggregation thread """ logger.debug('Waiting for stats and logging collator thread to finish ...') startTime = time.time() self._stop.set() self._worker.join() logger.debug('... finished collating stats and logs. Took %s seconds', time.time() - startTime) # in addition to cleaning on exceptions, onError should clean if there are any failed jobs toil-releases-3.24.0/src/toil/test/000077500000000000000000000000001362134276200170735ustar00rootroot00000000000000toil-releases-3.24.0/src/toil/test/__init__.py000066400000000000000000001056301362134276200212110ustar00rootroot00000000000000# Copyright (C) 2015-2018 Regents of the University of California # # 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. from __future__ import absolute_import from builtins import next from builtins import str import logging import os import re import shutil import signal import sys import tempfile import threading import time import unittest import uuid from future.utils import with_metaclass from abc import ABCMeta, abstractmethod from contextlib import contextmanager from inspect import getsource from textwrap import dedent from unittest.util import strclass from six import iteritems, itervalues from six.moves.urllib.request import urlopen from toil.lib.memoize import memoize from toil.lib.iterables import concat from toil.lib.threading import ExceptionalThread, cpu_count from toil.lib.misc import mkdir_p from toil.provisioners.aws import runningOnEC2 from toil import subprocess from toil import which from toil import toilPackageDirPath, applianceSelf from toil.version import distVersion logging.basicConfig(level=logging.DEBUG) log = logging.getLogger(__name__) class ToilTest(unittest.TestCase): """ A common base class for Toil tests. Please have every test case directly or indirectly inherit this one. When running tests you may optionally set the TOIL_TEST_TEMP environment variable to the path of a directory where you want temporary test files be placed. The directory will be created if it doesn't exist. The path may be relative in which case it will be assumed to be relative to the project root. If TOIL_TEST_TEMP is not defined, temporary files and directories will be created in the system's default location for such files and any temporary files or directories left over from tests will be removed automatically removed during tear down. Otherwise, left-over files will not be removed. """ _tempBaseDir = None _tempDirs = None @classmethod def setUpClass(cls): super(ToilTest, cls).setUpClass() cls._tempDirs = [] tempBaseDir = os.environ.get('TOIL_TEST_TEMP', None) if tempBaseDir is not None and not os.path.isabs(tempBaseDir): tempBaseDir = os.path.abspath(os.path.join(cls._projectRootPath(), tempBaseDir)) mkdir_p(tempBaseDir) cls._tempBaseDir = tempBaseDir @classmethod def tearDownClass(cls): if cls._tempBaseDir is None: while cls._tempDirs: tempDir = cls._tempDirs.pop() if os.path.exists(tempDir): shutil.rmtree(tempDir) else: cls._tempDirs = [] super(ToilTest, cls).tearDownClass() def setUp(self): log.info("Setting up %s ...", self.id()) super(ToilTest, self).setUp() def tearDown(self): super(ToilTest, self).tearDown() log.info("Tore down %s", self.id()) @classmethod def awsRegion(cls): """ Use us-west-2 unless running on EC2, in which case use the region in which the instance is located """ return cls._region() if runningOnEC2() else 'us-west-2' @classmethod def _availabilityZone(cls): """ Used only when running on EC2. Query this instance's metadata to determine in which availability zone it is running. """ zone = urlopen('http://169.254.169.254/latest/meta-data/placement/availability-zone').read() return zone if not isinstance(zone, bytes) else zone.decode('utf-8') @classmethod @memoize def _region(cls): """ Used only when running on EC2. Determines in what region this instance is running. The region will not change over the life of the instance so the result is memoized to avoid unnecessary work. """ region = re.match(r'^([a-z]{2}-[a-z]+-[1-9][0-9]*)([a-z])$', cls._availabilityZone()) assert region return region.group(1) @classmethod def _getUtilScriptPath(cls, script_name): return os.path.join(toilPackageDirPath(), 'utils', script_name + '.py') @classmethod def _projectRootPath(cls): """ Returns the path to the project root, i.e. the directory that typically contains the .git and src subdirectories. This method has limited utility. It only works if in "develop" mode, since it assumes the existence of a src subdirectory which, in a regular install wouldn't exist. Then again, in that mode project root has no meaning anyways. """ assert re.search(r'__init__\.pyc?$', __file__) projectRootPath = os.path.dirname(os.path.abspath(__file__)) packageComponents = __name__.split('.') expectedSuffix = os.path.join('src', *packageComponents) assert projectRootPath.endswith(expectedSuffix) projectRootPath = projectRootPath[:-len(expectedSuffix)] return projectRootPath def _createTempDir(self, purpose=None): return self._createTempDirEx(self._testMethodName, purpose) @classmethod def _createTempDirEx(cls, *names): prefix = ['toil', 'test', strclass(cls)] prefix.extend([_f for _f in names if _f]) prefix.append('') temp_dir_path = os.path.realpath(tempfile.mkdtemp(dir=cls._tempBaseDir, prefix='-'.join(prefix))) cls._tempDirs.append(temp_dir_path) return temp_dir_path def _getTestJobStorePath(self): path = self._createTempDir(purpose='jobstore') # We only need a unique path, directory shouldn't actually exist. This of course is racy # and insecure because another thread could now allocate the same path as a temporary # directory. However, the built-in tempfile module randomizes the name temp dir suffixes # reasonably well (1 in 63 ^ 6 chance of collision), making this an unlikely scenario. os.rmdir(path) return path @classmethod def _getSourceDistribution(cls): """ Find the sdist tarball for this project, check whether it is up-to date and return the path to it. :rtype: str """ sdistPath = os.path.join(cls._projectRootPath(), 'dist', 'toil-%s.tar.gz' % distVersion) assert os.path.isfile(sdistPath), "Can't find Toil source distribution at %s. Run 'make sdist'." % sdistPath excluded = set(cls._run('git', 'ls-files', '--others', '-i', '--exclude-standard', capture=True, cwd=cls._projectRootPath()).splitlines()) dirty = cls._run('find', 'src', '-type', 'f', '-newer', sdistPath, capture=True, cwd=cls._projectRootPath()).splitlines() assert all(path.startswith('src') for path in dirty) dirty = set(dirty) dirty.difference_update(excluded) assert not dirty, "Run 'make clean_sdist sdist'. Files newer than %s: %r" % (sdistPath, list(dirty)) return sdistPath @classmethod def _run(cls, command, *args, **kwargs): """ Run a command. Convenience wrapper for subprocess.check_call and subprocess.check_output. :param str command: The command to be run. :param str args: Any arguments to be passed to the command. :param Any kwargs: keyword arguments for subprocess.Popen constructor. Pass capture=True to have the process' stdout returned. Pass input='some string' to feed input to the process' stdin. :rtype: None|str :return: The output of the process' stdout if capture=True was passed, None otherwise. """ args = list(concat(command, args)) log.info('Running %r', args) capture = kwargs.pop('capture', False) _input = kwargs.pop('input', None) if capture: kwargs['stdout'] = subprocess.PIPE if _input is not None: kwargs['stdin'] = subprocess.PIPE popen = subprocess.Popen(args, **kwargs) stdout, stderr = popen.communicate(input=_input) assert stderr is None if popen.returncode != 0: raise subprocess.CalledProcessError(popen.returncode, args) if capture: return stdout def _getScriptSource(self, callable_): """ Returns the source code of the body of given callable as a string, dedented. This is a naught but incredibly useful trick that lets you embed user scripts as nested functions and expose them to the syntax checker of your IDE. """ return dedent('\n'.join(getsource(callable_).split('\n')[1:])) try: # noinspection PyUnresolvedReferences import pytest.mark except ImportError: # noinspection PyUnusedLocal def _mark_test(name, test_item): return test_item else: def _mark_test(name, test_item): return getattr(pytest.mark, name)(test_item) def needs_rsync3(test_item): """ Use as a decorator before test classes or methods that depend on any features used in rsync version 3.0.0+ Necessary because :meth:`utilsTest.testAWSProvisionerUtils` uses option `--protect-args` which is only available in rsync 3 """ test_item = _mark_test('rsync', test_item) try: versionInfo = subprocess.check_output(['rsync', '--version']).decode('utf-8') if int(versionInfo.split()[2].split('.')[0]) < 3: # output looks like: 'rsync version 2.6.9 ...' return unittest.skip('This test depends on rsync version 3.0.0+.')(test_item) except subprocess.CalledProcessError: return unittest.skip('rsync needs to be installed to run this test.')(test_item) return test_item def needs_aws_s3(test_item): """Use as a decorator before test classes or methods to run only if AWS S3 is usable.""" # TODO: we just check for generic access to the AWS account test_item = _mark_test('aws-s3', test_item) try: from boto import config boto_credentials = config.get('Credentials', 'aws_access_key_id') except ImportError: return unittest.skip("Install Toil with the 'aws' extra to include this test.")(test_item) if not (boto_credentials or os.path.exists(os.path.expanduser('~/.aws/credentials')) or runningOnEC2()): return unittest.skip("Configure AWS credentials to include this test.")(test_item) return test_item def needs_aws_ec2(test_item): """Use as a decorator before test classes or methods to run only if AWS EC2 is usable.""" # Assume we need S3 as well as EC2 test_item = _mark_test('aws-ec2', needs_aws_s3(test_item)) if not os.getenv('TOIL_AWS_KEYNAME'): # In addition to S3 we also need an SSH key to deploy with. # TODO: We assume that if this is set we have EC2 access. return unittest.skip("Set TOIL_AWS_KEYNAME to an AWS-stored SSH key to include this test.")(test_item) return test_item def travis_test(test_item): test_item = _mark_test('travis', test_item) if os.environ.get('TRAVIS') != 'true': return unittest.skip("Set TRAVIS='true' to include this test.")(test_item) return test_item def needs_google(test_item): """Use as a decorator before test classes or methods to run only if Google is usable.""" test_item = _mark_test('google', test_item) try: from boto import config except ImportError: return unittest.skip("Install Toil with the 'google' extra to include this test.")(test_item) if not os.getenv('TOIL_GOOGLE_PROJECTID'): return unittest.skip("Set TOIL_GOOGLE_PROJECTID to include this test.")(test_item) elif not config.get('Credentials'): # TODO: Deprecate this check? Needed by only by the ancients. return unittest.skip("Configure ~/.boto with Google Cloud credentials to include this test.")(test_item) return test_item def needs_gridengine(test_item): """Use as a decorator before test classes or methods to run only if GridEngine is installed.""" test_item = _mark_test('gridengine', test_item) if which('qhost'): return test_item return unittest.skip("Install GridEngine to include this test.")(test_item) def needs_torque(test_item): """Use as a decorator before test classes or methods to run only ifPBS/Torque is installed.""" test_item = _mark_test('torque', test_item) if which('pbsnodes'): return test_item return unittest.skip("Install PBS/Torque to include this test.")(test_item) def needs_kubernetes(test_item): """Use as a decorator before test classes or methods to run only if Kubernetes is installed.""" test_item = _mark_test('kubernetes', test_item) try: import kubernetes kubernetes.config.load_kube_config() except ImportError: return unittest.skip("Install Toil with the 'kubernetes' extra to include this test.")(test_item) except TypeError: return unittest.skip("Configure Kubernetes (~/.kube/config) to include this test.")(test_item) return test_item def needs_mesos(test_item): """Use as a decorator before test classes or methods to run only if Mesos is installed.""" test_item = _mark_test('mesos', test_item) if not (which('mesos-master') or which('mesos-slave')): return unittest.skip("Install Mesos (and Toil with the 'mesos' extra) to include this test.")(test_item) try: import pymesos import psutil except ImportError: return unittest.skip("Install Mesos (and Toil with the 'mesos' extra) to include this test.")(test_item) return test_item def needs_parasol(test_item): """Use as decorator so tests are only run if Parasol is installed.""" test_item = _mark_test('parasol', test_item) if which('parasol'): return test_item return unittest.skip("Install Parasol to include this test.")(test_item) def needs_slurm(test_item): """Use as a decorator before test classes or methods to run only if Slurm is installed.""" test_item = _mark_test('slurm', test_item) if which('squeue'): return test_item return unittest.skip("Install Slurm to include this test.")(test_item) def needs_htcondor(test_item): """Use a decorator before test classes or methods to run only if the HTCondor is installed.""" test_item = _mark_test('htcondor', test_item) try: import htcondor htcondor.Collector(os.getenv('TOIL_HTCONDOR_COLLECTOR')).query(constraint='False') except ImportError: return unittest.skip("Install the HTCondor Python bindings to include this test.")(test_item) except IOError: return unittest.skip("HTCondor must be running to include this test.")(test_item) except RuntimeError: return unittest.skip("HTCondor must be installed and configured to include this test.")(test_item) else: return test_item def needs_lsf(test_item): """ Use as a decorator before test classes or methods to only run them if LSF is installed. """ test_item = _mark_test('lsf', test_item) if which('bsub'): return test_item else: return unittest.skip("Install LSF to include this test.")(test_item) def needs_docker(test_item): """ Use as a decorator before test classes or methods to only run them if docker is installed and docker-based tests are enabled. """ test_item = _mark_test('docker', test_item) if os.getenv('TOIL_SKIP_DOCKER', '').lower() == 'true': return unittest.skip('Skipping docker test.')(test_item) if which('docker'): return test_item else: return unittest.skip("Install docker to include this test.")(test_item) def needs_encryption(test_item): """ Use as a decorator before test classes or methods to only run them if PyNaCl is installed and configured. """ test_item = _mark_test('encryption', test_item) try: # noinspection PyUnresolvedReferences import nacl except ImportError: return unittest.skip( "Install Toil with the 'encryption' extra to include this test.")(test_item) else: return test_item def needs_cwl(test_item): """ Use as a decorator before test classes or methods to only run them if CWLTool is installed and configured. """ test_item = _mark_test('cwl', test_item) try: # noinspection PyUnresolvedReferences import cwltool except ImportError: return unittest.skip("Install Toil with the 'cwl' extra to include this test.")(test_item) else: return test_item def needs_appliance(test_item): """ Use as a decorator before test classes or methods to only run them if the Toil appliance Docker image is downloaded. """ import json test_item = _mark_test('appliance', test_item) if os.getenv('TOIL_SKIP_DOCKER', '').lower() == 'true': return unittest.skip('Skipping docker test.')(test_item) if which('docker'): image = applianceSelf() try: images = subprocess.check_output(['docker', 'inspect', image]).decode('utf-8') except subprocess.CalledProcessError: images = [] else: images = {i['Id'] for i in json.loads(images) if image in i['RepoTags']} if len(images) == 0: return unittest.skip("Cannot find appliance image %s. Use 'make test' target to " "automatically build appliance, or just run 'make docker' " "prior to running this test." % image)(test_item) elif len(images) == 1: return test_item else: assert False, 'Expected `docker inspect` to return zero or one image.' else: return unittest.skip('Install Docker to include this test.')(test_item) def needs_downloadable_appliance(test_item): """ Use as a decorator before test classes or methods to only run them if the Toil appliance Docker image ought to be available for download. For now, this just skips if running on Python 3. TODO: When the appliance build is set up for Python 3 (when https://github.com/DataBiosphere/toil/issues/2742 is fixed), this behavior should be changed. """ if sys.version_info[0] == 2: return test_item else: return unittest.skip("Skipping test that needs Toil Appliance, available only for Python 2")(test_item) def integrative(test_item): """ Use this to decorate integration tests so as to skip them during regular builds. We define integration tests as A) involving other, non-Toil software components that we develop and/or B) having a higher cost (time or money). Note that brittleness does not qualify a test for being integrative. Neither does involvement of external services such as AWS, since that would cover most of Toil's test. """ test_item = _mark_test('integrative', test_item) if os.getenv('TOIL_TEST_INTEGRATIVE', '').lower() == 'true': return test_item else: return unittest.skip('Set TOIL_TEST_INTEGRATIVE="True" to include this integration test, ' 'or run `make integration_test_local` to run all integration tests.')(test_item) def slow(test_item): """ Use this decorator to identify tests that are slow and not critical. Skip if TOIL_TEST_QUICK is true. """ test_item = _mark_test('slow', test_item) if os.environ.get('TOIL_TEST_QUICK', '').lower() != 'true': return test_item else: return unittest.skip('Skipped because TOIL_TEST_QUICK is "True"')(test_item) methodNamePartRegex = re.compile('^[a-zA-Z_0-9]+$') @contextmanager def timeLimit(seconds): """ http://stackoverflow.com/a/601168 Use to limit the execution time of a function. Raises an exception if the execution of the function takes more than the specified amount of time. :param seconds: maximum allowable time, in seconds >>> import time >>> with timeLimit(2): ... time.sleep(1) >>> import time >>> with timeLimit(1): ... time.sleep(2) Traceback (most recent call last): ... RuntimeError: Timed out """ # noinspection PyUnusedLocal def signal_handler(signum, frame): raise RuntimeError('Timed out') signal.signal(signal.SIGALRM, signal_handler) signal.alarm(seconds) try: yield finally: signal.alarm(0) def make_tests(generalMethod, targetClass, **kwargs): """ This method dynamically generates test methods using the generalMethod as a template. Each generated function is the result of a unique combination of parameters applied to the generalMethod. Each of the parameters has a corresponding string that will be used to name the method. These generated functions are named in the scheme: test_[generalMethodName]___[ firstParamaterName]_[someValueName]__[secondParamaterName]_... The arguments following the generalMethodName should be a series of one or more dictionaries of the form {str : type, ...} where the key represents the name of the value. The names will be used to represent the permutation of values passed for each parameter in the generalMethod. The generated method names will list the parameters in lexicographic order by parameter name. :param generalMethod: A method that will be parameterized with values passed as kwargs. Note that the generalMethod must be a regular method. :param targetClass: This represents the class to which the generated test methods will be bound. If no targetClass is specified the class of the generalMethod is assumed the target. :param kwargs: a series of dictionaries defining values, and their respective names where each keyword is the name of a parameter in generalMethod. >>> class Foo: ... def has(self, num, letter): ... return num, letter ... ... def hasOne(self, num): ... return num >>> class Bar(Foo): ... pass >>> make_tests(Foo.has, Bar, num={'one':1, 'two':2}, letter={'a':'a', 'b':'b'}) >>> b = Bar() Note that num comes lexicographically before letter and so appears first in the generated method names. >>> assert b.test_has__letter_a__num_one() == b.has(1, 'a') >>> assert b.test_has__letter_b__num_one() == b.has(1, 'b') >>> assert b.test_has__letter_a__num_two() == b.has(2, 'a') >>> assert b.test_has__letter_b__num_two() == b.has(2, 'b') >>> f = Foo() >>> hasattr(f, 'test_has__num_one__letter_a') # should be false because Foo has no test methods False """ def pop(d): """ Pops an arbitrary key value pair from a given dict. :param d: a dictionary :return: the popped key, value tuple """ k, v = next(iter(iteritems(kwargs))) d.pop(k) return k, v def permuteIntoLeft(left, rParamName, right): """ Permutes values in right dictionary into each parameter: value dict pair in the left dictionary. Such that the left dictionary will contain a new set of keys each of which is a combination of one of its original parameter-value names appended with some parameter-value name from the right dictionary. Each original key in the left is deleted from the left dictionary after the permutation of the key and every parameter-value name from the right has been added to the left dictionary. For example if left is {'__PrmOne_ValName':{'ValName':Val}} and right is {'rValName1':rVal1, 'rValName2':rVal2} then left will become {'__PrmOne_ValName__rParamName_rValName1':{'ValName':Val. 'rValName1':rVal1}, '__PrmOne_ValName__rParamName_rValName2':{'ValName':Val. 'rValName2':rVal2}} :param left: A dictionary pairing each paramNameValue to a nested dictionary that contains each ValueName and value pair described in the outer dict's paramNameValue key. :param rParamName: The name of the parameter that each value in the right dict represents. :param right: A dict that pairs 1 or more valueNames and values for the rParamName parameter. """ for prmValName, lDict in list(left.items()): for rValName, rVal in list(right.items()): nextPrmVal = ('__%s_%s' % (rParamName, rValName.lower())) if methodNamePartRegex.match(nextPrmVal) is None: raise RuntimeError("The name '%s' cannot be used in a method name" % pvName) aggDict = dict(lDict) aggDict[rParamName] = rVal left[prmValName + nextPrmVal] = aggDict left.pop(prmValName) def insertMethodToClass(): """Generate and insert test methods.""" def fx(self, prms=prms): if prms is not None: return generalMethod(self, **prms) else: return generalMethod(self) methodName = 'test_%s%s' % (generalMethod.__name__, prmNames) setattr(targetClass, methodName, fx) if len(kwargs) > 0: # Define order of kwargs. # We keep them in reverse order of how we use them for efficient pop. sortedKwargs = sorted(list(kwargs.items()), reverse=True) # create first left dict left = {} prmName, vals = sortedKwargs.pop() for valName, val in list(vals.items()): pvName = '__%s_%s' % (prmName, valName.lower()) if methodNamePartRegex.match(pvName) is None: raise RuntimeError("The name '%s' cannot be used in a method name" % pvName) left[pvName] = {prmName: val} # get cartesian product while len(sortedKwargs) > 0: permuteIntoLeft(left, *sortedKwargs.pop()) # set class attributes targetClass = targetClass or generalMethod.__class__ for prmNames, prms in list(left.items()): insertMethodToClass() else: prms = None prmNames = "" insertMethodToClass() @contextmanager def tempFileContaining(content, suffix=''): """ Write a file with the given contents, and keep it on disk as long as the context is active. :param str content: The contents of the file. :param str suffix: The extension to use for the temporary file. """ fd, path = tempfile.mkstemp(suffix=suffix) try: encoded = content.encode('utf-8') assert os.write(fd, encoded) == len(encoded) except: os.close(fd) raise else: os.close(fd) yield path finally: os.unlink(path) class ApplianceTestSupport(ToilTest): """ A Toil test that runs a user script on a minimal cluster of appliance containers, i.e. one leader container and one worker container. """ @contextmanager def _applianceCluster(self, mounts=None, numCores=None): """ A context manager for creating and tearing down an appliance cluster. :param dict|None mounts: Dictionary mapping host paths to container paths. Both the leader and the worker container will be started with one -v argument per dictionary entry, as in -v KEY:VALUE. Beware that if KEY is a path to a directory, its entire content will be deleted when the cluster is torn down. :param int numCores: The number of cores to be offered by the Mesos slave process running in the worker container. :rtype: (ApplianceTestSupport.Appliance, ApplianceTestSupport.Appliance) :return: A tuple of the form `(leader, worker)` containing the Appliance instances representing the respective appliance containers """ if numCores is None: numCores = cpu_count() # The last container to stop (and the first to start) should clean the mounts. with self.LeaderThread(self, mounts, cleanMounts=True) as leader: with self.WorkerThread(self, mounts, numCores) as worker: yield leader, worker class Appliance(with_metaclass(ABCMeta, ExceptionalThread)): @abstractmethod def _getRole(self): return 'leader' @abstractmethod def _containerCommand(self): raise NotImplementedError() @abstractmethod def _entryPoint(self): raise NotImplementedError() # Lock is used because subprocess is NOT thread safe: http://tinyurl.com/pkp5pgq lock = threading.Lock() def __init__(self, outer, mounts, cleanMounts=False): """ :param ApplianceTestSupport outer: """ assert all(' ' not in v for v in itervalues(mounts)), 'No spaces allowed in mounts' super(ApplianceTestSupport.Appliance, self).__init__() self.outer = outer self.mounts = mounts self.cleanMounts = cleanMounts self.containerName = str(uuid.uuid4()) self.popen = None def __enter__(self): with self.lock: image = applianceSelf() # Omitting --rm, it's unreliable, see https://github.com/docker/docker/issues/16575 args = list(concat('docker', 'run', '--entrypoint=' + self._entryPoint(), '--net=host', '-i', '--name=' + self.containerName, ['--volume=%s:%s' % mount for mount in iteritems(self.mounts)], image, self._containerCommand())) log.info('Running %r', args) self.popen = subprocess.Popen(args) self.start() self.__wait_running() return self # noinspection PyUnusedLocal def __exit__(self, exc_type, exc_val, exc_tb): try: try: self.outer._run('docker', 'stop', self.containerName) self.join() finally: if self.cleanMounts: self.__cleanMounts() finally: self.outer._run('docker', 'rm', '-f', self.containerName) return False # don't swallow exception def __wait_running(self): log.info("Waiting for %s container process to appear. " "Expect to see 'Error: No such image or container'.", self._getRole()) while self.isAlive(): try: running = self.outer._run('docker', 'inspect', '--format={{ .State.Running }}', self.containerName, capture=True).strip() except subprocess.CalledProcessError: pass else: if 'true' == running: break time.sleep(1) def __cleanMounts(self): """ Deletes all files in every mounted directory. Without this step, we risk leaking files owned by root on the host. To avoid races, this method should be called after the appliance container was stopped, otherwise the running container might still be writing files. """ # Delete all files within each mounted directory, but not the directory itself. cmd = 'shopt -s dotglob && rm -rf ' + ' '.join(v + '/*' for k, v in iteritems(self.mounts) if os.path.isdir(k)) self.outer._run('docker', 'run', '--rm', '--entrypoint=/bin/bash', applianceSelf(), '-c', cmd) def tryRun(self): self.popen.wait() log.info('Exiting %s', self.__class__.__name__) def runOnAppliance(self, *args, **kwargs): # Check if thread is still alive. Note that ExceptionalThread.join raises the # exception that occurred in the thread. self.join(timeout=0) # noinspection PyProtectedMember self.outer._run('docker', 'exec', '-i', self.containerName, *args, **kwargs) def writeToAppliance(self, path, contents): self.runOnAppliance('tee', path, input=contents) def deployScript(self, path, packagePath, script): """ Deploy a Python module on the appliance. :param path: the path (absolute or relative to the WORDIR of the appliance container) to the root of the package hierarchy where the given module should be placed. The given directory should be on the Python path. :param packagePath: the desired fully qualified module name (dotted form) of the module :param str|callable script: the contents of the Python module. If a callable is given, its source code will be extracted. This is a convenience that lets you embed user scripts into test code as nested function. """ if callable(script): script = self.outer._getScriptSource(script) packagePath = packagePath.split('.') packages, module = packagePath[:-1], packagePath[-1] for package in packages: path += '/' + package self.runOnAppliance('mkdir', '-p', path) self.writeToAppliance(path + '/__init__.py', '') self.writeToAppliance(path + '/' + module + '.py', script) class LeaderThread(Appliance): def _entryPoint(self): return 'mesos-master' def _getRole(self): return 'leader' def _containerCommand(self): return ['--registry=in_memory', '--ip=127.0.0.1', '--port=5050', '--allocation_interval=500ms'] class WorkerThread(Appliance): def __init__(self, outer, mounts, numCores): self.numCores = numCores super(ApplianceTestSupport.WorkerThread, self).__init__(outer, mounts) def _entryPoint(self): return 'mesos-slave' def _getRole(self): return 'worker' def _containerCommand(self): return ['--work_dir=/var/lib/mesos', '--ip=127.0.0.1', '--master=127.0.0.1:5050', '--attributes=preemptable:False', '--resources=cpus(*):%i' % self.numCores, '--no-hostname_lookup', '--no-systemd_enable_support'] toil-releases-3.24.0/src/toil/test/batchSystems/000077500000000000000000000000001362134276200215445ustar00rootroot00000000000000toil-releases-3.24.0/src/toil/test/batchSystems/__init__.py000066400000000000000000000012131362134276200236520ustar00rootroot00000000000000# Copyright (C) 2015-2016 Regents of the University of California # # 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. from __future__ import absolute_import toil-releases-3.24.0/src/toil/test/batchSystems/batchSystemTest.py000066400000000000000000001135341362134276200252530ustar00rootroot00000000000000# Copyright (C) 2015-2016 Regents of the University of California # # 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. from __future__ import absolute_import from __future__ import division from builtins import map from builtins import str from builtins import range from builtins import object from past.utils import old_div from abc import ABCMeta, abstractmethod from fractions import Fraction from inspect import getsource import logging import os import fcntl import itertools import tempfile from textwrap import dedent import time import sys from toil import subprocess from unittest import skipIf from toil.common import Config # Don't import any batch systems here that depend on extras # in order to import properly. Import them later, in tests # protected by annotations. from toil.batchSystems.mesos.test import MesosTestSupport from toil.batchSystems.parasolTestSupport import ParasolTestSupport from toil.batchSystems.parasol import ParasolBatchSystem from toil.batchSystems.singleMachine import SingleMachineBatchSystem from toil.batchSystems.abstractBatchSystem import (InsufficientSystemResources, BatchSystemSupport) from toil.job import Job, JobNode from toil.lib.threading import cpu_count from toil.test import (ToilTest, needs_aws_s3, needs_lsf, needs_kubernetes, needs_mesos, needs_parasol, needs_gridengine, needs_slurm, needs_torque, needs_htcondor, needs_downloadable_appliance, slow, tempFileContaining, travis_test) from future.utils import with_metaclass log = logging.getLogger(__name__) # How many cores should be utilized by this test. The test will fail if the running system # doesn't have at least that many cores. numCores = 2 preemptable = False defaultRequirements = dict(memory=int(100e6), cores=1, disk=1000, preemptable=preemptable) class hidden(object): """ Hide abstract base class from unittest's test case loader http://stackoverflow.com/questions/1323455/python-unit-test-with-base-and-sub-class#answer-25695512 """ class AbstractBatchSystemTest(with_metaclass(ABCMeta, ToilTest)): """ A base test case with generic tests that every batch system should pass. Cannot assume that the batch system actually executes commands on the local machine/filesystem. """ @abstractmethod def createBatchSystem(self): """ :rtype: AbstractBatchSystem """ raise NotImplementedError def supportsWallTime(self): return False @classmethod def createConfig(cls): """ Returns a dummy config for the batch system tests. We need a workflowID to be set up since we are running tests without setting up a jobstore. This is the class version to be used when an instance is not available. :rtype: toil.common.Config """ config = Config() from uuid import uuid4 config.workflowID = str(uuid4()) config.cleanWorkDir = 'always' return config def _createConfig(self): """ Returns a dummy config for the batch system tests. We need a workflowID to be set up since we are running tests without setting up a jobstore. :rtype: toil.common.Config """ return self.createConfig() @classmethod def setUpClass(cls): super(hidden.AbstractBatchSystemTest, cls).setUpClass() logging.basicConfig(level=logging.DEBUG) def setUp(self): super(hidden.AbstractBatchSystemTest, self).setUp() self.config = self._createConfig() self.batchSystem = self.createBatchSystem() self.tempDir = self._createTempDir('testFiles') def tearDown(self): self.batchSystem.shutdown() super(hidden.AbstractBatchSystemTest, self).tearDown() def testAvailableCores(self): self.assertTrue(cpu_count() >= numCores) def testRunJobs(self): jobNode1 = JobNode(command='sleep 1000', jobName='test1', unitName=None, jobStoreID='1', requirements=defaultRequirements) jobNode2 = JobNode(command='sleep 1000', jobName='test2', unitName=None, jobStoreID='2', requirements=defaultRequirements) job1 = self.batchSystem.issueBatchJob(jobNode1) job2 = self.batchSystem.issueBatchJob(jobNode2) issuedIDs = self._waitForJobsToIssue(2) self.assertEqual(set(issuedIDs), {job1, job2}) # Now at some point we want these jobs to become running # But since we may be testing against a live cluster (Kubernetes) # we want to handle weird cases and high cluster load as much as we can. # Wait a bit for any Dockers to download and for the # jobs to have a chance to start. # TODO: We insist on neither of these ever finishing when we test # getUpdatedBatchJob, and the sleep time is longer than the time we # should spend waiting for both to start, so if our cluster can # only run one job at a time, we will fail the test. runningJobIDs = self._waitForJobsToStart(2, tries=120) self.assertEqual(set(runningJobIDs), {job1, job2}) # Killing the jobs instead of allowing them to complete means this test can run very # quickly if the batch system issues and starts the jobs quickly. self.batchSystem.killBatchJobs([job1, job2]) self.assertEqual({}, self.batchSystem.getRunningBatchJobIDs()) # Issue a job and then allow it to finish by itself, causing it to be added to the # updated jobs queue. # We would like to have this touch something on the filesystem and # then check for it having happened, but we can't guarantee that # the batch system will run against the same filesystem we are # looking at. jobNode3 = JobNode(command="mktemp -d", jobName='test3', unitName=None, jobStoreID='3', requirements=defaultRequirements) job3 = self.batchSystem.issueBatchJob(jobNode3) jobID, exitStatus, wallTime = self.batchSystem.getUpdatedBatchJob(maxWait=1000) log.info('Third job completed: {} {} {}'.format(jobID, exitStatus, wallTime)) # Since the first two jobs were killed, the only job in the updated jobs queue should # be job 3. If the first two jobs were (incorrectly) added to the queue, this will # fail with jobID being equal to job1 or job2. self.assertEqual(jobID, job3) self.assertEqual(exitStatus, 0) if self.supportsWallTime(): self.assertTrue(wallTime > 0) else: self.assertIsNone(wallTime) # TODO: Work out a way to check if the job we asked to run actually ran. # Don't just believe the batch system, but don't assume it ran on this machine either. self.assertFalse(self.batchSystem.getUpdatedBatchJob(0)) # Make sure killBatchJobs can handle jobs that don't exist self.batchSystem.killBatchJobs([10]) def testSetEnv(self): # Parasol disobeys shell rules and stupidly splits the command at # the space character into arguments before exec'ing it, whether # the space is quoted, escaped or not. script_shell = 'if [ "x${FOO}" == "xbar" ] ; then exit 23 ; else exit 42 ; fi' # Escape the semicolons script_protected = script_shell.replace(';', '\;') # Turn into a string which convinces bash to take all args and paste them back together and run them command = "bash -c \"\\${@}\" bash eval " + script_protected jobNode4 = JobNode(command=command, jobName='test4', unitName=None, jobStoreID='4', requirements=defaultRequirements) job4 = self.batchSystem.issueBatchJob(jobNode4) jobID, exitStatus, wallTime = self.batchSystem.getUpdatedBatchJob(maxWait=1000) self.assertEqual(exitStatus, 42) self.assertEqual(jobID, job4) # Now set the variable and ensure that it is present self.batchSystem.setEnv('FOO', 'bar') jobNode5 = JobNode(command=command, jobName='test5', unitName=None, jobStoreID='5', requirements=defaultRequirements) job5 = self.batchSystem.issueBatchJob(jobNode5) jobID, exitStatus, wallTime = self.batchSystem.getUpdatedBatchJob(maxWait=1000) self.assertEqual(exitStatus, 23) self.assertEqual(jobID, job5) def testCheckResourceRequest(self): if isinstance(self.batchSystem, BatchSystemSupport): checkResourceRequest = self.batchSystem.checkResourceRequest self.assertRaises(InsufficientSystemResources, checkResourceRequest, memory=1000, cores=200, disk=1e9) self.assertRaises(InsufficientSystemResources, checkResourceRequest, memory=5, cores=200, disk=1e9) self.assertRaises(InsufficientSystemResources, checkResourceRequest, memory=1001e9, cores=1, disk=1e9) self.assertRaises(InsufficientSystemResources, checkResourceRequest, memory=5, cores=1, disk=2e9) self.assertRaises(AssertionError, checkResourceRequest, memory=None, cores=1, disk=1000) self.assertRaises(AssertionError, checkResourceRequest, memory=10, cores=None, disk=1000) checkResourceRequest(memory=10, cores=1, disk=100) def testScalableBatchSystem(self): # If instance of scalable batch system pass def _waitForJobsToIssue(self, numJobs): issuedIDs = [] for it in range(20): issuedIDs = self.batchSystem.getIssuedBatchJobIDs() if len(issuedIDs) == numJobs: break time.sleep(1) return issuedIDs def _waitForJobsToStart(self, numJobs, tries=20): """ Loop until the given number of distinct jobs are in the running state, or until the given number of tries is exhausted (with 1 second polling period). Returns the list of IDs that are running. """ runningIDs = [] # prevent an endless loop, give it a few tries for it in range(tries): running = self.batchSystem.getRunningBatchJobIDs() log.info('Running jobs now: {}'.format(running)) runningIDs = list(running.keys()) if len(runningIDs) == numJobs: break time.sleep(1) return runningIDs class AbstractBatchSystemJobTest(with_metaclass(ABCMeta, ToilTest)): """ An abstract base class for batch system tests that use a full Toil workflow rather than using the batch system directly. """ cpuCount = cpu_count() allocatedCores = sorted({1, 2, cpuCount}) sleepTime = 5 @abstractmethod def getBatchSystemName(self): """ :rtype: (str, AbstractBatchSystem) """ raise NotImplementedError def getOptions(self, tempDir): """ Configures options for Toil workflow and makes job store. :param str tempDir: path to test directory :return: Toil options object """ options = Job.Runner.getDefaultOptions(self._getTestJobStorePath()) options.logLevel = "DEBUG" options.batchSystem = self.batchSystemName options.workDir = tempDir options.maxCores = self.cpuCount return options def setUp(self): self.batchSystemName = self.getBatchSystemName() super(hidden.AbstractBatchSystemJobTest, self).setUp() def tearDown(self): super(hidden.AbstractBatchSystemJobTest, self).tearDown() @slow def testJobConcurrency(self): """ Tests that the batch system is allocating core resources properly for concurrent tasks. """ for coresPerJob in self.allocatedCores: tempDir = self._createTempDir('testFiles') options = self.getOptions(tempDir) counterPath = os.path.join(tempDir, 'counter') resetCounters(counterPath) value, maxValue = getCounters(counterPath) assert (value, maxValue) == (0, 0) root = Job() for _ in range(self.cpuCount): root.addFollowOn(Job.wrapFn(measureConcurrency, counterPath, self.sleepTime, cores=coresPerJob, memory='1M', disk='1Mi')) Job.Runner.startToil(root, options) _, maxValue = getCounters(counterPath) self.assertEqual(maxValue, old_div(self.cpuCount, coresPerJob)) class AbstractGridEngineBatchSystemTest(AbstractBatchSystemTest): """ An abstract class to reduce redundancy between Grid Engine, Slurm, and other similar batch systems """ def _createConfig(self): config = super(hidden.AbstractGridEngineBatchSystemTest, self)._createConfig() # can't use _getTestJobStorePath since that method removes the directory config.jobStore = 'file:' + self._createTempDir('jobStore') return config @needs_kubernetes @needs_aws_s3 @needs_downloadable_appliance class KubernetesBatchSystemTest(hidden.AbstractBatchSystemTest): """ Tests against the Kubernetes batch system """ def supportsWallTime(self): return True def createBatchSystem(self): # We know we have Kubernetes so we can import the batch system from toil.batchSystems.kubernetes import KubernetesBatchSystem return KubernetesBatchSystem(config=self.config, maxCores=numCores, maxMemory=1e9, maxDisk=2001) @slow @needs_mesos class MesosBatchSystemTest(hidden.AbstractBatchSystemTest, MesosTestSupport): """ Tests against the Mesos batch system """ def createConfig(cls): """ needs to set mesosMasterAddress to localhost for testing since the default is now the private IP address """ config = super(MesosBatchSystemTest, cls).createConfig() config.mesosMasterAddress = 'localhost:5050' return config def supportsWallTime(self): return True def createBatchSystem(self): # We know we have Mesos so we can import the batch system from toil.batchSystems.mesos.batchSystem import MesosBatchSystem self._startMesos(numCores) return MesosBatchSystem(config=self.config, maxCores=numCores, maxMemory=1e9, maxDisk=1001) def tearDown(self): self._stopMesos() super(MesosBatchSystemTest, self).tearDown() def testIgnoreNode(self): self.batchSystem.ignoreNode('localhost') jobNode = JobNode(command='sleep 1000', jobName='test2', unitName=None, jobStoreID='1', requirements=defaultRequirements) job = self.batchSystem.issueBatchJob(jobNode) issuedID = self._waitForJobsToIssue(1) self.assertEqual(set(issuedID), {job}) # Wait until a job starts or we go a while without that happening runningJobIDs = self._waitForJobsToStart(1, tries=20) # Make sure job is NOT running self.assertEqual(set(runningJobIDs), set({})) @travis_test class SingleMachineBatchSystemTest(hidden.AbstractBatchSystemTest): """ Tests against the single-machine batch system """ def supportsWallTime(self): return True def createBatchSystem(self): return SingleMachineBatchSystem(config=self.config, maxCores=numCores, maxMemory=1e9, maxDisk=2001) @slow class MaxCoresSingleMachineBatchSystemTest(ToilTest): """ This test ensures that single machine batch system doesn't exceed the configured number cores """ @classmethod def setUpClass(cls): super(MaxCoresSingleMachineBatchSystemTest, cls).setUpClass() logging.basicConfig(level=logging.DEBUG) def setUp(self): super(MaxCoresSingleMachineBatchSystemTest, self).setUp() def writeTempFile(s): fd, path = tempfile.mkstemp() try: encoded = s.encode('utf-8') assert os.write(fd, encoded) == len(encoded) except: os.unlink(path) raise else: return path finally: os.close(fd) # Write initial value of counter file containing a tuple of two integers (i, n) where i # is the number of currently executing tasks and n the maximum observed value of i self.counterPath = writeTempFile('0,0') def script(): import os, sys, fcntl, time def count(delta): """ Adjust the first integer value in a file by the given amount. If the result exceeds the second integer value, set the second one to the first. """ fd = os.open(sys.argv[1], os.O_RDWR) try: fcntl.flock(fd, fcntl.LOCK_EX) try: s = os.read(fd, 10).decode('utf-8') value, maxValue = list(map(int, s.split(u','))) value += delta if value > maxValue: maxValue = value os.lseek(fd, 0, 0) os.ftruncate(fd, 0) os.write(fd, '{},{}'.format(value, maxValue).encode('utf-8')) finally: fcntl.flock(fd, fcntl.LOCK_UN) finally: os.close(fd) # Without the second argument, increment counter, sleep one second and decrement. # Othwerise, adjust the counter by the given delta, which can be useful for services. if len(sys.argv) < 3: count(1) try: time.sleep(1) finally: count(-1) else: count(int(sys.argv[2])) self.scriptPath = writeTempFile(dedent('\n'.join(getsource(script).split('\n')[1:]))) def tearDown(self): os.unlink(self.scriptPath) os.unlink(self.counterPath) def scriptCommand(self): return ' '.join([sys.executable, self.scriptPath, self.counterPath]) def test(self): # We'll use fractions to avoid rounding errors. Remember that not every fraction can be # represented as a floating point number. F = Fraction # This test isn't general enough to cover every possible value of minCores in # SingleMachineBatchSystem. Instead we hard-code a value and assert it. minCores = F(1, 10) self.assertEqual(float(minCores), SingleMachineBatchSystem.minCores) for maxCores in {F(minCores), minCores * 10, F(1), F(numCores, 2), F(numCores)}: for coresPerJob in {F(minCores), F(minCores * 10), F(1), F(maxCores, 2), F(maxCores)}: for load in (F(1, 10), F(1), F(10)): jobs = int(maxCores / coresPerJob * load) if jobs >= 1 and minCores <= coresPerJob < maxCores: self.assertEqual(maxCores, float(maxCores)) bs = SingleMachineBatchSystem( config=hidden.AbstractBatchSystemTest.createConfig(), maxCores=float(maxCores), # Ensure that memory or disk requirements don't get in the way. maxMemory=jobs * 10, maxDisk=jobs * 10) try: jobIds = set() for i in range(0, int(jobs)): jobIds.add(bs.issueBatchJob(JobNode(command=self.scriptCommand(), requirements=dict( cores=float( coresPerJob), memory=1, disk=1, preemptable=preemptable), jobName=str(i), unitName='', jobStoreID=str(i)))) self.assertEqual(len(jobIds), jobs) while jobIds: job = bs.getUpdatedBatchJob(maxWait=10) self.assertIsNotNone(job) jobId, status, wallTime = job self.assertEqual(status, 0) # would raise KeyError on absence jobIds.remove(jobId) finally: bs.shutdown() concurrentTasks, maxConcurrentTasks = getCounters(self.counterPath) self.assertEqual(concurrentTasks, 0) log.info('maxCores: {maxCores}, ' 'coresPerJob: {coresPerJob}, ' 'load: {load}'.format(**locals())) # This is the key assertion: expectedMaxConcurrentTasks = min(old_div(maxCores, coresPerJob), jobs) self.assertEqual(maxConcurrentTasks, expectedMaxConcurrentTasks) resetCounters(self.counterPath) @skipIf(SingleMachineBatchSystem.numCores < 3, 'Need at least three cores to run this test') def testServices(self): options = Job.Runner.getDefaultOptions(self._getTestJobStorePath()) options.logDebug = True options.maxCores = 3 self.assertTrue(options.maxCores <= SingleMachineBatchSystem.numCores) Job.Runner.startToil(Job.wrapJobFn(parentJob, self.scriptCommand()), options) with open(self.counterPath, 'r+') as f: s = f.read() log.info('Counter is %s', s) self.assertEqual(getCounters(self.counterPath), (0, 3)) # Toil can use only top-level functions so we have to add them here: def parentJob(job, cmd): job.addChildJobFn(childJob, cmd) def childJob(job, cmd): job.addService(Service(cmd)) job.addChildJobFn(grandChildJob, cmd) subprocess.check_call(cmd, shell=True) def grandChildJob(job, cmd): job.addService(Service(cmd)) job.addChildFn(greatGrandChild, cmd) subprocess.check_call(cmd, shell=True) def greatGrandChild(cmd): subprocess.check_call(cmd, shell=True) class Service(Job.Service): def __init__(self, cmd): super(Service, self).__init__() self.cmd = cmd def start(self, fileStore): subprocess.check_call(self.cmd + ' 1', shell=True) def check(self): return True def stop(self, fileStore): subprocess.check_call(self.cmd + ' -1', shell=True) @slow @needs_parasol class ParasolBatchSystemTest(hidden.AbstractBatchSystemTest, ParasolTestSupport): """ Tests the Parasol batch system """ def supportsWallTime(self): return True def _createConfig(self): config = super(ParasolBatchSystemTest, self)._createConfig() # can't use _getTestJobStorePath since that method removes the directory config.jobStore = self._createTempDir('jobStore') return config def createBatchSystem(self): memory = int(3e9) self._startParasol(numCores=numCores, memory=memory) return ParasolBatchSystem(config=self.config, maxCores=numCores, maxMemory=memory, maxDisk=1001) def tearDown(self): super(ParasolBatchSystemTest, self).tearDown() self._stopParasol() def testBatchResourceLimits(self): jobNode1 = JobNode(command="sleep 1000", requirements=dict(memory=1 << 30, cores=1, disk=1000, preemptable=preemptable), jobName='testResourceLimits', unitName=None, jobStoreID='1') job1 = self.batchSystem.issueBatchJob(jobNode1) self.assertIsNotNone(job1) jobNode2 = JobNode(command="sleep 1000", requirements=dict(memory=2 << 30, cores=1, disk=1000, preemptable=preemptable), jobName='testResourceLimits', unitName=None, jobStoreID='2') job2 = self.batchSystem.issueBatchJob(jobNode2) self.assertIsNotNone(job2) batches = self._getBatchList() self.assertEqual(len(batches), 2) # It would be better to directly check that the batches have the correct memory and cpu # values, but Parasol seems to slightly change the values sometimes. self.assertNotEqual(batches[0]['ram'], batches[1]['ram']) # Need to kill one of the jobs because there are only two cores available self.batchSystem.killBatchJobs([job2]) job3 = self.batchSystem.issueBatchJob(jobNode1) self.assertIsNotNone(job3) batches = self._getBatchList() self.assertEqual(len(batches), 1) def _parseBatchString(self, batchString): import re batchInfo = dict() memPattern = re.compile("(\d+\.\d+)([kgmbt])") items = batchString.split() batchInfo["cores"] = int(items[7]) memMatch = memPattern.match(items[8]) ramValue = float(memMatch.group(1)) ramUnits = memMatch.group(2) ramConversion = {'b': 1e0, 'k': 1e3, 'm': 1e6, 'g': 1e9, 't': 1e12} batchInfo["ram"] = ramValue * ramConversion[ramUnits] return batchInfo def _getBatchList(self): # noinspection PyUnresolvedReferences exitStatus, batchLines = self.batchSystem._runParasol(['list', 'batches']) self.assertEqual(exitStatus, 0) return [self._parseBatchString(line) for line in batchLines[1:] if line] @slow @needs_gridengine class GridEngineBatchSystemTest(hidden.AbstractGridEngineBatchSystemTest): """ Tests against the GridEngine batch system """ def createBatchSystem(self): from toil.batchSystems.gridengine import GridEngineBatchSystem return GridEngineBatchSystem(config=self.config, maxCores=numCores, maxMemory=1000e9, maxDisk=1e9) def tearDown(self): super(GridEngineBatchSystemTest, self).tearDown() # Cleanup GridEngine output log file from qsub from glob import glob for f in glob('toil_job*.o*'): os.unlink(f) @slow @needs_slurm class SlurmBatchSystemTest(hidden.AbstractGridEngineBatchSystemTest): """ Tests against the Slurm batch system """ def createBatchSystem(self): from toil.batchSystems.slurm import SlurmBatchSystem return SlurmBatchSystem(config=self.config, maxCores=numCores, maxMemory=1000e9, maxDisk=1e9) def tearDown(self): super(SlurmBatchSystemTest, self).tearDown() # Cleanup 'slurm-%j.out' produced by sbatch from glob import glob for f in glob('slurm-*.out'): os.unlink(f) @slow @needs_lsf class LSFBatchSystemTest(hidden.AbstractGridEngineBatchSystemTest): """ Tests against the LSF batch system """ def createBatchSystem(self): from toil.batchSystems.lsf import LSFBatchSystem return LSFBatchSystem(config=self.config, maxCores=numCores, maxMemory=1000e9, maxDisk=1e9) @slow @needs_torque class TorqueBatchSystemTest(hidden.AbstractGridEngineBatchSystemTest): """ Tests against the Torque batch system """ def _createDummyConfig(self): config = super(TorqueBatchSystemTest, self)._createDummyConfig() # can't use _getTestJobStorePath since that method removes the directory config.jobStore = self._createTempDir('jobStore') return config def createBatchSystem(self): from toil.batchSystems.torque import TorqueBatchSystem return TorqueBatchSystem(config=self.config, maxCores=numCores, maxMemory=1000e9, maxDisk=1e9) def tearDown(self): super(TorqueBatchSystemTest, self).tearDown() # Cleanup 'toil_job-%j.out' produced by sbatch from glob import glob for f in glob('toil_job_*.[oe]*'): os.unlink(f) @slow @needs_htcondor class HTCondorBatchSystemTest(hidden.AbstractGridEngineBatchSystemTest): """ Tests against the HTCondor batch system """ def createBatchSystem(self): from toil.batchSystems.htcondor import HTCondorBatchSystem return HTCondorBatchSystem(config=self.config, maxCores=numCores, maxMemory=1000e9, maxDisk=1e9) def tearDown(self): super(HTCondorBatchSystemTest, self).tearDown() @travis_test class SingleMachineBatchSystemJobTest(hidden.AbstractBatchSystemJobTest): """ Tests Toil workflow against the SingleMachine batch system """ def getBatchSystemName(self): return "singleMachine" @slow def testConcurrencyWithDisk(self): """ Tests that the batch system is allocating disk resources properly """ tempDir = self._createTempDir('testFiles') options = Job.Runner.getDefaultOptions(self._getTestJobStorePath()) options.workDir = tempDir from toil import physicalDisk availableDisk = physicalDisk('', toilWorkflowDir=options.workDir) options.batchSystem = self.batchSystemName counterPath = os.path.join(tempDir, 'counter') resetCounters(counterPath) value, maxValue = getCounters(counterPath) assert (value, maxValue) == (0, 0) root = Job() # Physically, we're asking for 50% of disk and 50% of disk + 500bytes in the two jobs. The # batchsystem should not allow the 2 child jobs to run concurrently. root.addChild(Job.wrapFn(measureConcurrency, counterPath, self.sleepTime, cores=1, memory='1M', disk=old_div(availableDisk,2))) root.addChild(Job.wrapFn(measureConcurrency, counterPath, self.sleepTime, cores=1, memory='1M', disk=(old_div(availableDisk, 2)) + 500)) Job.Runner.startToil(root, options) _, maxValue = getCounters(counterPath) self.assertEqual(maxValue, 1) @skipIf(SingleMachineBatchSystem.numCores < 4, 'Need at least four cores to run this test') @slow def testNestedResourcesDoNotBlock(self): """ Resources are requested in the order Memory > Cpu > Disk. Test that inavailability of cpus for one job that is scheduled does not block another job that can run. """ tempDir = self._createTempDir('testFiles') options = Job.Runner.getDefaultOptions(self._getTestJobStorePath()) options.workDir = tempDir options.maxCores = 4 from toil import physicalMemory availableMemory = physicalMemory() options.batchSystem = self.batchSystemName outFile = os.path.join(tempDir, 'counter') open(outFile, 'w').close() root = Job() blocker = Job.wrapFn(_resourceBlockTestAuxFn, outFile=outFile, sleepTime=30, writeVal='b', cores=2, memory='1M', disk='1M') firstJob = Job.wrapFn(_resourceBlockTestAuxFn, outFile=outFile, sleepTime=5, writeVal='fJ', cores=1, memory='1M', disk='1M') secondJob = Job.wrapFn(_resourceBlockTestAuxFn, outFile=outFile, sleepTime=10, writeVal='sJ', cores=1, memory='1M', disk='1M') # Should block off 50% of memory while waiting for it's 3 cores firstJobChild = Job.wrapFn(_resourceBlockTestAuxFn, outFile=outFile, sleepTime=0, writeVal='fJC', cores=3, memory=int(old_div(availableMemory,2)), disk='1M') # These two shouldn't be able to run before B because there should be only # (50% of memory - 1M) available (firstJobChild should be blocking 50%) secondJobChild = Job.wrapFn(_resourceBlockTestAuxFn, outFile=outFile, sleepTime=5, writeVal='sJC', cores=2, memory=int(old_div(availableMemory,1.5)), disk='1M') secondJobGrandChild = Job.wrapFn(_resourceBlockTestAuxFn, outFile=outFile, sleepTime=5, writeVal='sJGC', cores=2, memory=int(old_div(availableMemory,1.5)), disk='1M') root.addChild(blocker) root.addChild(firstJob) root.addChild(secondJob) firstJob.addChild(firstJobChild) secondJob.addChild(secondJobChild) secondJobChild.addChild(secondJobGrandChild) """ The tree is: root / | \ b fJ sJ | | fJC sJC | sJGC But the order of execution should be root > b , fJ, sJ > sJC > sJGC > fJC since fJC cannot run till bl finishes but sJC and sJGC can(fJC blocked by disk). If the resource acquisition is written properly, then fJC which is scheduled before sJC and sJGC should not block them, and should only run after they finish. """ Job.Runner.startToil(root, options) with open(outFile) as oFH: outString = oFH.read() # The ordering of b, fJ and sJ is non-deterministic since they are scheduled at the same # time. We look for all possible permutations. possibleStarts = tuple([''.join(x) for x in itertools.permutations(['b', 'fJ', 'sJ'])]) assert outString.startswith(possibleStarts) assert outString.endswith('sJCsJGCfJC') def _resourceBlockTestAuxFn(outFile, sleepTime, writeVal): """ Write a value to the out file and then sleep for requested seconds. :param str outFile: File to write to :param int sleepTime: Time to sleep for :param str writeVal: Character to write """ with open(outFile, 'a') as oFH: fcntl.flock(oFH, fcntl.LOCK_EX) oFH.write(writeVal) time.sleep(sleepTime) @slow @needs_mesos class MesosBatchSystemJobTest(hidden.AbstractBatchSystemJobTest, MesosTestSupport): """ Tests Toil workflow against the Mesos batch system """ def getOptions(self, tempDir): options = super(MesosBatchSystemJobTest, self).getOptions(tempDir) options.mesosMasterAddress = 'localhost:5050' return options def getBatchSystemName(self): self._startMesos(self.cpuCount) return "mesos" def tearDown(self): self._stopMesos() def measureConcurrency(filepath, sleep_time=3): """ Run in parallel to determine the number of concurrent tasks. This code was copied from toil.batchSystemTestMaxCoresSingleMachineBatchSystemTest :param str filepath: path to counter file :param int sleep_time: number of seconds to sleep before counting down :return int max concurrency value: """ count(1, filepath) try: time.sleep(sleep_time) finally: return count(-1, filepath) def count(delta, file_path): """ Increments counter file and returns the max number of times the file has been modified. Counter data must be in the form: concurrent tasks, max concurrent tasks (counter should be initialized to 0,0) :param int delta: increment value :param str file_path: path to shared counter file :return int max concurrent tasks: """ fd = os.open(file_path, os.O_RDWR) try: fcntl.flock(fd, fcntl.LOCK_EX) try: s = os.read(fd, 10) value, maxValue = list(map(int, s.decode('utf-8').split(','))) value += delta if value > maxValue: maxValue = value os.lseek(fd, 0, 0) os.ftruncate(fd, 0) os.write(fd, ','.join(map(str, (value, maxValue))).encode('utf-8')) finally: fcntl.flock(fd, fcntl.LOCK_UN) finally: os.close(fd) return maxValue def getCounters(path): with open(path, 'r+') as f: s = f.read() concurrentTasks, maxConcurrentTasks = list(map(int, s.split(','))) return concurrentTasks, maxConcurrentTasks def resetCounters(path): with open(path, "w") as f: f.write("0,0") f.close() toil-releases-3.24.0/src/toil/test/cactus/000077500000000000000000000000001362134276200203555ustar00rootroot00000000000000toil-releases-3.24.0/src/toil/test/cactus/pestis.tar.gz000066400000000000000000257657251362134276200230500ustar00rootroot00000000000000‹Ë¬Zpestis.tarì½Ûr\I–¦—Ý=2Mn™Ì¤ éJ14›ª®Q’ €à)»Ø’Ó™t’É3=L3XA"ÀˆAòIæZO0¡ç˜'‘ûú¿å;@‚,¦¦²Fê2Iûà‡uøÿ­Ø8-–ãÅ·—¶n¦ãáW¿Ã×ÚÚÚµ+WöïÕ«öïÚƦþ­_—77ë—7._]ßؼvmm°¶¾¹~uí«ÁÚï1˜¿ŽËá¼ eg{1úÜqå°½½Ï¼¯© Ú¿ÿùúïþ×ÿþ«¿ÿ꫇ÃÁãçƒ_|Õ×¾úºüÙ(þsùSþ/_vÉó3¾­gü§òçþ‡ü]ÿúÿ²3;¼4<:šŒ.½>·Óåx:úêõ·kk××ÿéÊðÚõá½Ëÿ”f³ýÉè?¾ÝX‹óÙ᨞ñO›·®]Ûü~óÚÅïÃõÍ‹›—ãæÅ›×7.ÞXÛ¼¾yys=\] …%ú—üu$ÿÇû¿ý]îñ—ü¿úËþ¿¶~õ«Á•ße4|ý+÷ÿöÿÒÖöd¶ó*ÏLJë—ÞNþ*÷(ëqusó“û¿±~­îÿúÕÍ+—/ol^.ûõÚÕËçñÿoòõñÿßÜùÊâÿ¿yûe—ìã¿ñõÕ?üçù{^/+úïûø8Zw‡Ëáw¯Þ¾·þ|0šî”p¿¨×ºôÕgòÅöÑd¼X®­ý_÷÷[ÿó?üËåÑâ»o¿=Ž'‡Ëåpçàp4]^Ú·4r¼ÍwfÓe}¥\íÛþ€o¿]ûöÿ8ßÜøÃøÕÍáåÍËkÛ{Ã?¼Nn–ãþ°<¸¹~e´scýÚîåáÎöÞæÞúÊëãÝ›k—Öÿ°;^Ý\ ÷F˜†½¾·õòúædñîåµ?¼?ùÃb¸»»=\Þ ÒËÝû7¯þxpr¼~ëÅÝ'ïï½xûûûë'¯/>?üzkkksvpíé݇ó£×÷Ož^|ûÃîÁ<_¿8ýåÅÁÓwkÇÓé§_‡wå»/6Ÿý´8¾½µ¸ú~òêúÎæÛ·Ÿ¯]Ýúqwùøýãï½umëÇ÷‹;¯fï¶Ýóúqx}xåÆ›Å|ãêOO®ž¼:yöò^Þ»qëîÞÛ'¿î_¼;\ûþÉ‹g'k³W^?x4»öüÁA¸{ýÁ÷Ïww÷vÒ—¿Ü›Ü^no¤í­píÅÝÝ¿ºq}÷á“÷oSxp÷Ú½µwû£÷y÷}¼öþ—ëáéÖ½ïOÞ=£û¯n¿ºü|ïàh6¹Ÿ}¸{ñáÅô"?ypmòâÍO[ÃG'?ß¿:yýdíåƒÃ͇éÕæÖÛÞ<¼Ÿ6ï=}÷Óf|ñ8¼»?¼r0{ðóîÖÁÞ›|øþùγŸ~Ø\†ïy¹qïò½w?]\¼¹|åí»å“ï¼›¾¹ëý‹‡“»³ôrïÉþå×÷ÇËw/þðþÖ/žÎòÓ“G“Û[7v¯?:(†5yûrxðäÙ½’òÞ,6¼ºúbïþüÆý½Í;oö¶wâõã+^n?¹{gýÆ‹ñ«ÑÝtq.>=øåäàÁ›Ý×O®ýt÷×õ—¯ïïï쿹÷ò×½ŸæGW†?Ýz½ÿó«ýgO¯þ¸stÿîíõ½W'[ÿÓ¿[õœÀ,¿þl6ÿÕ¿ýêø‡ÿ çü;¼ôN;í?üŸç¨ì_Ú×ùÿwÈþ)ÿö·yõÃüåʵóüÿ·øúó¿»xqÆ‹Á/ –óÑhP3ãp<] –£ÁQÉ°%-æåÇÙ`g¸³<^lÍgûóÑb1~3ºtônpñâ?w\g4(p9œîŒò,ìîæÙ³Ùl&ãýiÍ®ýÕ决“ÁáñÎÁ`ôv9–ߌæû£rj»F½åp2)ÇŒ¦åÛrñt°s0žìÎË+³=ä¼ÜdPN-HƒÑ8žÍ_핳ãlº7ÞÿìÈn^(ÙûÂ?w_ÿ¹Ì¾¶\ vG{ÃãÉòáèp6wóÂáhw||¨Ÿ.ø›Ë˜'Ã2ìÏŽo^Xÿø$^/·ýÚ×oaëφóÑ `•][ú²+óÙÄæ;<œ—Õ,³?´ †ÓÝÁÎѱ½¹;ÞÛ+°©¼ÿr¶½ŒËº Þ(ë¬Ë•¼d«4”Û–!ø´LÆËå¤Íb£³ ƒÕݼpùJÿÎöxß_¾ÒŸð-WþÒ ­ZØÁpYéhT¦3›ŽÞMfe[GËñNÛ½Kƒç£«¦ûvê劷µ²õºkƒ“ñd2؛͋í¥r€–†£VLQLʘzãìW§¸X¹K1– e|#Í`y2³ï®”oŠÕ6.”ÏíÛòú^¹Nýþò•º<_ÿùÛ¶$õ'w£ù¨xV¹×b6,‡û§×ëpVvöÝ·;£W6›ñôèx9XŒ^k€Û£2瑼ļ­N£¿úÞx¾X~t]¥_¶ÃNfóÝj_£2ÿwƒ½aìà`4Ü•çOÇå¦ß †õ¼òsù^†1ž—‘–1 ÷êõ泓Å`4ŸÏÊîŽ÷ÚÑÓ™n¶3\Œ>¦',£ÃíÉ»»ÇÛƒÙÑr\ŒáËé£ép»ìÔŸÊ7‹ã€Îu _³é¤xÆäè`8=>Í‹ •¡ýqëß þx±þõ]ù«¾réå¦eïwª ~c¾ÔæX¦±7x7;ìΦ\–%_VÛ¬»1|U–ºø#ocGî”W—Çóœ˜03¨dæ³=µ 6e ‡¸Óª7^XÙ³û³í›ìðmxwmK>Zµzµo?i[u哲µïŸ—.¯Ê¼Å´í‹Qµ¼ºÄeÅ;qª•§ƒ_~ÌÊÚÏ{‹+«g^,gGÅxËVn§Ãål>NJ˜?šÌu%JL:Žç'ãÅŠ¹.ÎZšãi9ÜÎÁñôÕóñûâH—=•fóººyö|xX8!Î÷E ùÁÜËYãé“b(³ÝÐ. ìýÇGËÅÍ?^¼¸XŽŽn^.c–9íÏŽ7ÇÇGÃoÖ×ÖêŸòÎñt¿àß²f/–½™¿;XRz8^Þ|5}3 çÓïÖK¨ü£ÅH}Ù=6 YØÆ, ú:¬Y®ü™ÏŽËBþa0;^ò½Åo3ùz\Yéùp9ÚGÈZ¹ä=­Ãd‹ï>>¬¾}g2œ¾*—ýÎ,e2šî/êVïñz‹1–+·‹ØWyÙGT²…|%4yÛ‡ãiÝNݵÌx|x\&T^©÷>žîÌŠ–«ÍGûuì§ïøÿAÑî? ›®Cüh¬ª£*ëVcä^á&u„ŒÚ›8{”¹„ôÅÁl²{zœ{5^T[.cÝ.QŒD{2žîÎN>¸Oõ Ã‚3Ã75ã”y ÷Gƒ¾9X·W’ÚV¢ïÖYŸ¾ÂÖ₧í~¥‡'C%ÿP·q¦úú~€ËÇ1L ÖjÖtö„¶)ô;ã;RO×ôêhk$ܯ¶wúmrõß³¯ÿ˜»ß-N/j‰ÓÛå´r³6ÄÅÑhg\Ž2Ç7ÃÉñHfV–Äàå\qú#ÃÿcKË{ÓÝÑdñ`6-ær\%ä2c¨jXei?X·ùþq¯O¯J tOJ*-°­,Z˜”%^h{»Çå¦;Å`vûå8ÓL àïãÝ7ƒz@ÉruajZ9ªë¹šôOŸ\PYIÙ–¥eÛ•l×UáfÅØC«ÐxéÔ¾ÖE¿Uƒ~Éö•?'¸Ödzú6¬ûJì,Ǭ}ò "]=æÓµ@S»ôéÃz÷üÜ°>4MAú¿x¸ù䧮»º¹5#¾xµ\ŒæÕ×Ï"@vÈb´,\Ó÷oŠÝ€YBfÌÚÕî œ:–[! 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tacaccgact agaaattctt gtgcaagcac taattgaaag cggttggcct agagtgttac cggtttgtat agctgagcgc gtctcttgcc ctgatcaaag gttcattttc tctactttgg aagacgttgt ggaagaatac aacaagtacg agtctctccc ccctggtttg ctgattactg gatacagttg taataccctt cgcaacaccg cgtaactatc tatatgaatt attttccctt tattatatgt agtaggttcg tctttaatct tcctttagca agtcttttac tgttttcgac ctcaatgttc atgttcttag gttgttttgg ataatatgcg gtcagtttaa tcttcgttgt ttcttcttaa aatatttatt catggtttaa tttttggttt gtacttgttc aggggccagt tcattattta ctctgtttgt atacagcagt tcttttattt ttagtatgat tttaatttaa aacaattcta atggtcaaaa a toil-releases-3.24.0/src/toil/test/cwl/2.fastq000066400000000000000000000004001362134276200210530ustar00rootroot00000000000000@EAS54_6_R1_2_1_413_324 CCCTTCTTGTCTTCAGCGTTTCTCC + ;;3;;;;;;;;;;;;7;;;;;;;88 @EAS54_6_R1_2_1_540_792 TTGGCAGGCCAAGGCCGATGGATCA + ;;;;;;;;;;;7;;;;;-;;;3;83 @EAS54_6_R1_2_1_443_348 GTTGCTTCTGGCGTGGGTGGGGGGG +EAS54_6_R1_2_1_443_348 ;;;;;;;;;;;9;7;;.7;393333 toil-releases-3.24.0/src/toil/test/cwl/__init__.py000066400000000000000000000000001362134276200217570ustar00rootroot00000000000000toil-releases-3.24.0/src/toil/test/cwl/conftest.py000066400000000000000000000012721362134276200220610ustar00rootroot00000000000000# Copyright (C) 2015-2016 Regents of the University of California # # 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. # https://pytest.org/latest/example/pythoncollection.html collect_ignore = ["spec"] toil-releases-3.24.0/src/toil/test/cwl/cwlTest.py000066400000000000000000000315141362134276200216630ustar00rootroot00000000000000# Copyright (C) 2015 Curoverse, Inc # # 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. from __future__ import absolute_import from __future__ import print_function import json import os import sys import unittest import re import shutil import zipfile import pytest import uuid from future.moves.urllib.request import urlretrieve from six.moves import StringIO from six import u as str from six import text_type pkg_root = os.path.abspath(os.path.join(os.path.dirname(__file__), '..')) # noqa sys.path.insert(0, pkg_root) # noqa from toil import subprocess from toil.test import (ToilTest, needs_cwl, slow, needs_docker, needs_lsf, needs_mesos, needs_parasol, needs_gridengine, needs_slurm, needs_torque) @needs_cwl class CWLTest(ToilTest): def setUp(self): """Runs anew before each test to create farm fresh temp dirs.""" from builtins import str as normal_str self.outDir = os.path.join('/tmp/', 'toil-cwl-test-' + normal_str(uuid.uuid4())) os.makedirs(self.outDir) self.rootDir = self._projectRootPath() self.cwlSpec = os.path.join(self.rootDir, 'src/toil/test/cwl/spec') self.workDir = os.path.join(self.cwlSpec, 'v1.0') # The latest cwl git commit hash from https://github.com/common-workflow-language/common-workflow-language. # Update it to get the latest tests. testhash = 'a062055fddcc7d7d9dbc53d28288e3ccb9a800d8' url = 'https://github.com/common-workflow-language/common-workflow-language/archive/%s.zip' % testhash if not os.path.exists(self.cwlSpec): urlretrieve(url, 'spec.zip') with zipfile.ZipFile('spec.zip', 'r') as z: z.extractall() shutil.move('common-workflow-language-%s' % testhash, self.cwlSpec) os.remove('spec.zip') def tearDown(self): """Clean up outputs.""" if os.path.exists(self.outDir): shutil.rmtree(self.outDir) unittest.TestCase.tearDown(self) def _tester(self, cwlfile, jobfile, expect, main_args=[], out_name="output"): from toil.cwl import cwltoil st = StringIO() main_args = main_args[:] main_args.extend(['--outdir', self.outDir, os.path.join(self.rootDir, cwlfile), os.path.join(self.rootDir, jobfile)]) cwltoil.main(main_args, stdout=st) out = json.loads(st.getvalue()) out[out_name].pop("http://commonwl.org/cwltool#generation", None) out[out_name].pop("nameext", None) out[out_name].pop("nameroot", None) self.assertEqual(out, expect) def _debug_worker_tester(self, cwlfile, jobfile, expect): from toil.cwl import cwltoil st = StringIO() cwltoil.main(['--debugWorker', '--outdir', self.outDir, os.path.join(self.rootDir, cwlfile), os.path.join(self.rootDir, jobfile)], stdout=st) out = json.loads(st.getvalue()) out["output"].pop("http://commonwl.org/cwltool#generation", None) out["output"].pop("nameext", None) out["output"].pop("nameroot", None) self.assertEqual(out, expect) def revsort(self, cwl_filename, tester_fn): tester_fn('src/toil/test/cwl/' + cwl_filename, 'src/toil/test/cwl/revsort-job.json', self._expected_revsort_output(self.outDir)) def download(self,inputs, tester_fn): input_location = os.path.join('src/toil/test/cwl',inputs) tester_fn('src/toil/test/cwl/download.cwl', input_location, self._expected_download_output(self.outDir)) def test_run_revsort(self): self.revsort('revsort.cwl', self._tester) def test_run_revsort2(self): self.revsort('revsort2.cwl', self._tester) def test_run_revsort_debug_worker(self): self.revsort('revsort.cwl', self._debug_worker_tester) def test_run_s3(self): self.download('download_s3.json', self._tester) def test_run_http(self): self.download('download_http.json', self._tester) def test_run_https(self): self.download('download_https.json', self._tester) @slow def test_bioconda(self): self._tester('src/toil/test/cwl/seqtk_seq.cwl', 'src/toil/test/cwl/seqtk_seq_job.json', self._expected_seqtk_output(self.outDir), main_args=["--beta-conda-dependencies"], out_name="output1") @needs_docker def test_biocontainers(self): # currently the galaxy lib seems to have some str/bytestring errors? # TODO: fix to work on python 3.6 on gitlab if sys.version_info < (3, 0): self._tester('src/toil/test/cwl/seqtk_seq.cwl', 'src/toil/test/cwl/seqtk_seq_job.json', self._expected_seqtk_output(self.outDir), main_args=["--beta-use-biocontainers"], out_name="output1") @slow def test_restart(self): """Enable restarts with CWLtoil -- run failing test, re-run correct test. """ from toil.cwl import cwltoil from toil.jobStores.abstractJobStore import NoSuchJobStoreException from toil.leader import FailedJobsException outDir = self._createTempDir() cwlDir = os.path.join(self._projectRootPath(), "src", "toil", "test", "cwl") cmd = ['--outdir', outDir, '--jobStore', os.path.join(outDir, 'jobStore'), "--no-container", os.path.join(cwlDir, "revsort.cwl"), os.path.join(cwlDir, "revsort-job.json")] def path_without_rev(): return ":".join([d for d in os.environ["PATH"].split(":") if not os.path.exists(os.path.join(d, "rev"))]) orig_path = os.environ["PATH"] # Force a failure and half finished job by removing `rev` from the PATH os.environ["PATH"] = path_without_rev() try: cwltoil.main(cmd) self.fail("Expected problem job with incorrect PATH did not fail") except FailedJobsException: pass # Finish the job with a correct PATH os.environ["PATH"] = orig_path cwltoil.main(["--restart"] + cmd) # Should fail because previous job completed successfully try: cwltoil.main(["--restart"] + cmd) self.fail("Restart with missing directory did not fail") except NoSuchJobStoreException: pass @slow @pytest.mark.timeout(2400) # Cannot work until we fix https://github.com/DataBiosphere/toil/issues/2801 @pytest.mark.xfail def test_run_conformance_with_caching(self): self.test_run_conformance(caching=True) @slow @pytest.mark.timeout(2400) def test_run_conformance(self, batchSystem=None, caching=False): try: cmd = ['cwltest', '--tool', 'toil-cwl-runner', '--test=conformance_test_v1.0.yaml', '--timeout=2400', '--basedir=' + self.workDir] if batchSystem: cmd.extend(["--batchSystem", batchSystem]) if caching: cmd.extend(['--', '--disableCaching="False"']) subprocess.check_output(cmd, cwd=self.workDir, stderr=subprocess.STDOUT) except subprocess.CalledProcessError as e: only_unsupported = False # check output -- if we failed but only have unsupported features, we're okay p = re.compile(r"(?P\d+) failures, (?P\d+) unsupported features") error_log = e.output if isinstance(e.output, bytes): # py2/3 string handling error_log = e.output.decode('utf-8') for line in error_log.split('\n'): m = p.search(line) if m: if int(m.group("failures")) == 0 and int(m.group("unsupported")) > 0: only_unsupported = True break if not only_unsupported: print(error_log) raise e @slow @needs_lsf @unittest.skip # Cannot work until we fix https://github.com/DataBiosphere/toil/issues/2801 @pytest.mark.xfail def test_lsf_cwl_conformance_with_caching(self): return self.test_run_conformance(batchSystem="LSF", caching=True) @slow @needs_slurm @unittest.skip # Cannot work until we fix https://github.com/DataBiosphere/toil/issues/2801 @pytest.mark.xfail def test_slurm_cwl_conformance_with_caching(self): return self.test_run_conformance(batchSystem="Slurm", caching=True) @slow @needs_torque @unittest.skip # Cannot work until we fix https://github.com/DataBiosphere/toil/issues/2801 @pytest.mark.xfail def test_torque_cwl_conformance_with_caching(self): return self.test_run_conformance(batchSystem="Torque", caching=True) @slow @needs_gridengine @unittest.skip # Cannot work until we fix https://github.com/DataBiosphere/toil/issues/2801 @pytest.mark.xfail def test_gridengine_cwl_conformance_with_caching(self): return self.test_run_conformance(batchSystem="gridEngine", caching=True) @slow @needs_mesos @unittest.skip # Cannot work until we fix https://github.com/DataBiosphere/toil/issues/2801 @pytest.mark.xfail def test_mesos_cwl_conformance_with_caching(self): return self.test_run_conformance(batchSystem="mesos", caching=True) @slow @needs_parasol @unittest.skip # Cannot work until we fix https://github.com/DataBiosphere/toil/issues/2801 @pytest.mark.xfail def test_parasol_cwl_conformance_with_caching(self): return self.test_run_conformance(batchSystem="parasol", caching=True) @slow @needs_lsf @unittest.skip def test_lsf_cwl_conformance(self): return self.test_run_conformance(batchSystem="LSF") @slow @needs_slurm @unittest.skip def test_slurm_cwl_conformance(self): return self.test_run_conformance(batchSystem="Slurm") @slow @needs_torque @unittest.skip def test_torque_cwl_conformance(self): return self.test_run_conformance(batchSystem="Torque") @slow @needs_gridengine @unittest.skip def test_gridengine_cwl_conformance(self): return self.test_run_conformance(batchSystem="gridEngine") @slow @needs_mesos @unittest.skip def test_mesos_cwl_conformance(self): return self.test_run_conformance(batchSystem="mesos") @slow @needs_parasol @unittest.skip def test_parasol_cwl_conformance(self): return self.test_run_conformance(batchSystem="parasol") @staticmethod def _expected_seqtk_output(outDir): # Having unicode string literals isn't necessary for the assertion but # makes for a less noisy diff in case the assertion fails. loc = 'file://' + os.path.join(outDir, 'out') loc = str(loc) if not isinstance(loc, text_type) else loc # py2/3 return { u'output1': { u'location': loc, u'checksum': u'sha1$322e001e5a99f19abdce9f02ad0f02a17b5066c2', u'basename': u'out', u'class': u'File', u'size': 150}} @staticmethod def _expected_revsort_output(outDir): # Having unicode string literals isn't necessary for the assertion but # makes for a less noisy diff in case the assertion fails. loc = 'file://' + os.path.join(outDir, 'output.txt') loc = str(loc) if not isinstance(loc, text_type) else loc # py2/3 return { u'output': { u'location': loc, u'basename': u'output.txt', u'size': 1111, u'class': u'File', u'checksum': u'sha1$b9214658cc453331b62c2282b772a5c063dbd284'}} @staticmethod def _expected_download_output(outDir): # Having unicode string literals isn't necessary for the assertion but # makes for a less noisy diff in case the assertion fails. loc = 'file://' + os.path.join(outDir, 'output.txt') loc = str(loc) if not isinstance(loc, text_type) else loc # py2/3 return { u'output': { u'location': loc, u'basename': u'output.txt', u'size': 0, u'class': u'File', u'checksum': u'sha1$da39a3ee5e6b4b0d3255bfef95601890afd80709'}} toil-releases-3.24.0/src/toil/test/cwl/download.cwl000066400000000000000000000006141362134276200221770ustar00rootroot00000000000000# Example command line program wrapper for the Unix tool "sort" # demonstrating command line flags. class: CommandLineTool doc: "Download a file from different cloud environments" cwlVersion: v1.0 inputs: - id: input type: File inputBinding: position: 1 outputs: output: type: File outputBinding: glob: output.txt baseCommand: ["test","-f"] stdout: output.txt toil-releases-3.24.0/src/toil/test/cwl/download_http.json000066400000000000000000000001641362134276200234220ustar00rootroot00000000000000{ "input": { "class": "File", "location": "http://toil-datasets.s3.amazonaws.com/wdl_templates.zip" } } toil-releases-3.24.0/src/toil/test/cwl/download_https.json000066400000000000000000000001651362134276200236060ustar00rootroot00000000000000{ "input": { "class": "File", "location": "https://toil-datasets.s3.amazonaws.com/wdl_templates.zip" } } toil-releases-3.24.0/src/toil/test/cwl/download_s3.json000066400000000000000000000001411362134276200227630ustar00rootroot00000000000000{ "input": { "class": "File", "location": "s3://toil-datasets/wdl_templates.zip" } } toil-releases-3.24.0/src/toil/test/cwl/revsort-job.json000066400000000000000000000001021362134276200230200ustar00rootroot00000000000000{ "input": { "class": "File", "path": "whale.txt" } } toil-releases-3.24.0/src/toil/test/cwl/revsort.cwl000066400000000000000000000037461362134276200221050ustar00rootroot00000000000000# # This is a two-step workflow which uses "revtool" and "sorttool" defined above. # class: Workflow doc: "Reverse the lines in a document, then sort those lines." cwlVersion: v1.0 # Requirements & hints specify prerequisites and extensions to the workflow. # In this example, DockerRequirement specifies a default Docker container # in which the command line tools will execute. hints: - class: DockerRequirement dockerPull: debian:8 # The inputs array defines the structure of the input object that describes # the inputs to the workflow. # # The "reverse_sort" input parameter demonstrates the "default" field. If the # field "reverse_sort" is not provided in the input object, the default value will # be used. inputs: input: type: File doc: "The input file to be processed." reverse_sort: type: boolean default: true doc: "If true, reverse (decending) sort" # The "outputs" array defines the structure of the output object that describes # the outputs of the workflow. # # Each output field must be connected to the output of one of the workflow # steps using the "connect" field. Here, the parameter "#output" of the # workflow comes from the "#sorted" output of the "sort" step. outputs: output: type: File outputSource: sorted/output doc: "The output with the lines reversed and sorted." # The "steps" array lists the executable steps that make up the workflow. # The tool to execute each step is listed in the "run" field. # # In the first step, the "inputs" field of the step connects the upstream # parameter "#input" of the workflow to the input parameter of the tool # "revtool.cwl#input" # # In the second step, the "inputs" field of the step connects the output # parameter "#reversed" from the first step to the input parameter of the # tool "sorttool.cwl#input". steps: rev: in: input: input out: [output] run: revtool.cwl sorted: in: input: rev/output reverse: reverse_sort out: [output] run: sorttool.cwl toil-releases-3.24.0/src/toil/test/cwl/revsort2.cwl000066400000000000000000000037471362134276200221700ustar00rootroot00000000000000# # This is a two-step workflow which uses "revtool" and "sorttool" defined above. # class: Workflow doc: "Reverse the lines in a document, then sort those lines." cwlVersion: v1.0 # Requirements & hints specify prerequisites and extensions to the workflow. # In this example, DockerRequirement specifies a default Docker container # in which the command line tools will execute. hints: - class: DockerRequirement dockerPull: debian:8 # The inputs array defines the structure of the input object that describes # the inputs to the workflow. # # The "reverse_sort" input parameter demonstrates the "default" field. If the # field "reverse_sort" is not provided in the input object, the default value will # be used. inputs: input: type: File doc: "The input file to be processed." reverse_sort: type: boolean default: true doc: "If true, reverse (decending) sort" # The "outputs" array defines the structure of the output object that describes # the outputs of the workflow. # # Each output field must be connected to the output of one of the workflow # steps using the "connect" field. Here, the parameter "#output" of the # workflow comes from the "#sorted" output of the "sort" step. outputs: output: type: File outputSource: sorted/output doc: "The output with the lines reversed and sorted." # The "steps" array lists the executable steps that make up the workflow. # The tool to execute each step is listed in the "run" field. # # In the first step, the "inputs" field of the step connects the upstream # parameter "#input" of the workflow to the input parameter of the tool # "revtool.cwl#input" # # In the second step, the "inputs" field of the step connects the output # parameter "#reversed" from the first step to the input parameter of the # tool "sorttool.cwl#input". steps: rev: in: input: input out: [output] run: revtool2.cwl sorted: in: input: rev/output reverse: reverse_sort out: [output] run: sorttool.cwl toil-releases-3.24.0/src/toil/test/cwl/revtool.cwl000066400000000000000000000024251362134276200220640ustar00rootroot00000000000000# # Simplest example command line program wrapper for the Unix tool "rev". # class: CommandLineTool cwlVersion: v1.0 doc: "Reverse each line using the `rev` command" # The "inputs" array defines the structure of the input object that describes # the inputs to the underlying program. Here, there is one input field # defined that will be called "input" and will contain a "File" object. # # The input binding indicates that the input value should be turned into a # command line argument. In this example inputBinding is an empty object, # which indicates that the file name should be added to the command line at # a default location. inputs: input: type: File inputBinding: {} # The "outputs" array defines the structure of the output object that # describes the outputs of the underlying program. Here, there is one # output field defined that will be called "output", must be a "File" type, # and after the program executes, the output value will be the file # output.txt in the designated output directory. outputs: output: type: File outputBinding: glob: output.txt # The actual program to execute. baseCommand: rev # Specify that the standard output stream must be redirected to a file called # output.txt in the designated output directory. stdout: output.txt toil-releases-3.24.0/src/toil/test/cwl/revtool2.cwl000066400000000000000000000013771362134276200221530ustar00rootroot00000000000000# # Simplest example command line program wrapper for the Unix tool "rev". # class: CommandLineTool cwlVersion: v1.0 doc: "Reverse each line using the `rev` command" requirements: InlineJavascriptRequirement: {} # A lengthy process to test premature execution of descendent steps ResourceRequirement: ramMin: | ${ var start = new Date().getTime(); while (new Date().getTime() < start + 10000); return inputs.input.size + 1536; } inputs: input: type: File inputBinding: {} outputs: output: type: File outputBinding: glob: output.txt baseCommand: rev # Specify that the standard output stream must be redirected to a file called # output.txt in the designated output directory. stdout: output.txt toil-releases-3.24.0/src/toil/test/cwl/seqtk_seq.cwl000066400000000000000000000006241362134276200223700ustar00rootroot00000000000000cwlVersion: v1.0 class: CommandLineTool id: "seqtk_seq" doc: "Convert to FASTA (seqtk)" inputs: - id: input1 type: File inputBinding: position: 1 prefix: "-a" outputs: - id: output1 type: File outputBinding: glob: out baseCommand: ["seqtk", "seq"] arguments: [] stdout: out hints: SoftwareRequirement: packages: - package: seqtk version: - r93 toil-releases-3.24.0/src/toil/test/cwl/seqtk_seq_job.json000066400000000000000000000001051362134276200234000ustar00rootroot00000000000000{ "input1": { "class": "File", "location": "2.fastq" } } toil-releases-3.24.0/src/toil/test/cwl/sorttool.cwl000066400000000000000000000020441362134276200222540ustar00rootroot00000000000000# Example command line program wrapper for the Unix tool "sort" # demonstrating command line flags. class: CommandLineTool doc: "Sort lines using the `sort` command" cwlVersion: v1.0 # This example is similar to the previous one, with an additional input # parameter called "reverse". It is a boolean parameter, which is # intepreted as a command line flag. The value of "prefix" is used for # flag to put on the command line if "reverse" is true, if "reverse" is # false, no flag is added. # # This example also introduced the "position" field. This indicates the # sorting order of items on the command line. Lower numbers are placed # before higher numbers. Here, the "--reverse" flag (if present) will be # added to the command line before the input file path. inputs: - id: reverse type: boolean inputBinding: position: 1 prefix: "--reverse" - id: input type: File inputBinding: position: 2 outputs: - id: output type: File outputBinding: glob: output.txt baseCommand: sort stdout: output.txt toil-releases-3.24.0/src/toil/test/cwl/whale.txt000066400000000000000000000021271362134276200215230ustar00rootroot00000000000000Call me Ishmael. Some years ago--never mind how long precisely--having little or no money in my purse, and nothing particular to interest me on shore, I thought I would sail about a little and see the watery part of the world. It is a way I have of driving off the spleen and regulating the circulation. Whenever I find myself growing grim about the mouth; whenever it is a damp, drizzly November in my soul; whenever I find myself involuntarily pausing before coffin warehouses, and bringing up the rear of every funeral I meet; and especially whenever my hypos get such an upper hand of me, that it requires a strong moral principle to prevent me from deliberately stepping into the street, and methodically knocking people's hats off--then, I account it high time to get to sea as soon as I can. This is my substitute for pistol and ball. With a philosophical flourish Cato throws himself upon his sword; I quietly take to the ship. There is nothing surprising in this. If they but knew it, almost all men in their degree, some time or other, cherish very nearly the same feelings towards the ocean with me. toil-releases-3.24.0/src/toil/test/docs/000077500000000000000000000000001362134276200200235ustar00rootroot00000000000000toil-releases-3.24.0/src/toil/test/docs/__init__.py000066400000000000000000000000001362134276200221220ustar00rootroot00000000000000toil-releases-3.24.0/src/toil/test/docs/scripts/000077500000000000000000000000001362134276200215125ustar00rootroot00000000000000toil-releases-3.24.0/src/toil/test/docs/scripts/cwlExampleFiles/000077500000000000000000000000001362134276200245765ustar00rootroot00000000000000toil-releases-3.24.0/src/toil/test/docs/scripts/cwlExampleFiles/hello.cwl000066400000000000000000000003531362134276200264110ustar00rootroot00000000000000cwlVersion: v1.0 class: CommandLineTool baseCommand: echo stdout: output.txt inputs: - id: message type: string inputBinding: position: 1 outputs: - id: output type: File outputBinding: glob: output.txt toil-releases-3.24.0/src/toil/test/docs/scripts/cwlExampleFiles/hello1.yml000066400000000000000000000000261362134276200265030ustar00rootroot00000000000000message: Hello world! toil-releases-3.24.0/src/toil/test/docs/scripts/cwlExampleFiles/hello2.yml000066400000000000000000000000261362134276200265040ustar00rootroot00000000000000message: Hello world! toil-releases-3.24.0/src/toil/test/docs/scripts/cwlExampleFiles/hello3.yml000066400000000000000000000000261362134276200265050ustar00rootroot00000000000000message: Hello world! toil-releases-3.24.0/src/toil/test/docs/scripts/stagingExampleFiles/000077500000000000000000000000001362134276200254455ustar00rootroot00000000000000toil-releases-3.24.0/src/toil/test/docs/scripts/stagingExampleFiles/in.txt000066400000000000000000000000071362134276200266110ustar00rootroot00000000000000Hello, toil-releases-3.24.0/src/toil/test/docs/scripts/stagingExampleFiles/out.txt000066400000000000000000000000001362134276200270030ustar00rootroot00000000000000toil-releases-3.24.0/src/toil/test/docs/scripts/tutorial_arguments.py000066400000000000000000000011011362134276200260050ustar00rootroot00000000000000from toil.common import Toil from toil.job import Job class HelloWorld(Job): def __init__(self, message): Job.__init__(self, memory="2G", cores=2, disk="3G") self.message = message def run(self, fileStore): return "Hello, world!, here's a message: %s" % self.message if __name__=="__main__": parser = Job.Runner.getDefaultArgumentParser() options = parser.parse_args() options.logLevel = "OFF" options.clean = "always" hello_job = HelloWorld("Woot") with Toil(options) as toil: print(toil.start(hello_job)) toil-releases-3.24.0/src/toil/test/docs/scripts/tutorial_cwlexample.py000066400000000000000000000037611362134276200261570ustar00rootroot00000000000000from toil.job import Job from toil.common import Toil import subprocess import os def initialize_jobs(job): job.fileStore.logToMaster('initialize_jobs') def runQC(job, cwl_file, cwl_filename, yml_file, yml_filename, outputs_dir, output_num): job.fileStore.logToMaster("runQC") tempDir = job.fileStore.getLocalTempDir() cwl = job.fileStore.readGlobalFile(cwl_file, userPath=os.path.join(tempDir, cwl_filename)) yml = job.fileStore.readGlobalFile(yml_file, userPath=os.path.join(tempDir, yml_filename)) subprocess.check_call(["cwltoil", cwl, yml]) output_filename = "output.txt" output_file = job.fileStore.writeGlobalFile(output_filename) job.fileStore.readGlobalFile(output_file, userPath=os.path.join(outputs_dir, "sample_" + output_num + "_" + output_filename)) return output_file if __name__ == "__main__": options = Job.Runner.getDefaultOptions("./toilWorkflowRun") options.logLevel = "INFO" options.clean = "always" with Toil(options) as toil: # specify the folder where the cwl and yml files live inputs_dir = os.path.join(os.path.dirname(os.path.abspath(__file__)), "cwlExampleFiles") # specify where you wish the outputs to be written outputs_dir = os.path.join(os.path.dirname(os.path.abspath(__file__)), "cwlExampleFiles") job0 = Job.wrapJobFn(initialize_jobs) cwl_filename = "hello.cwl" cwl_file = toil.importFile("file://" + os.path.abspath(os.path.join(inputs_dir, cwl_filename))) # add list of yml config inputs here or import and construct from file yml_files = ["hello1.yml", "hello2.yml", "hello3.yml"] i = 0 for yml in yml_files: i = i + 1 yml_file = toil.importFile("file://" + os.path.abspath(os.path.join(inputs_dir, yml))) yml_filename = yml job = Job.wrapJobFn(runQC, cwl_file, cwl_filename, yml_file, yml_filename, outputs_dir, output_num=str(i)) job0.addChild(job) toil.start(job0) toil-releases-3.24.0/src/toil/test/docs/scripts/tutorial_discoverfiles.py000066400000000000000000000016461362134276200266570ustar00rootroot00000000000000import subprocess import os from toil.common import Toil from toil.job import Job class discoverFiles(Job): """Views files at a specified path using ls.""" def __init__(self, path, *args, **kwargs): self.path = path super(discoverFiles, self).__init__(*args, **kwargs) def run(self, fileStore): if os.path.exists(self.path): subprocess.check_call(["ls", self.path]) def main(): options = Job.Runner.getDefaultArgumentParser().parse_args() options.clean = "always" job1 = discoverFiles(path="/sys/", displayName='sysFiles') job2 = discoverFiles(path=os.path.expanduser("~"), displayName='userFiles') job3 = discoverFiles(path="/tmp/") job1.addChild(job2) job2.addChild(job3) with Toil(options) as toil: if not toil.options.restart: toil.start(job1) else: toil.restart() if __name__ == '__main__': main() toil-releases-3.24.0/src/toil/test/docs/scripts/tutorial_docker.py000066400000000000000000000007451362134276200252640ustar00rootroot00000000000000from toil.common import Toil from toil.job import Job from toil.lib.docker import apiDockerCall import os align = Job.wrapJobFn(apiDockerCall, image='ubuntu', working_dir=os.getcwd(), parameters=['ls', '-lha']) if __name__=="__main__": options = Job.Runner.getDefaultOptions("./toilWorkflowRun") options.logLevel = "INFO" options.clean = "always" with Toil(options) as toil: toil.start(align) toil-releases-3.24.0/src/toil/test/docs/scripts/tutorial_dynamic.py000066400000000000000000000010511362134276200254300ustar00rootroot00000000000000from toil.common import Toil from toil.job import Job def binaryStringFn(job, depth, message=""): if depth > 0: job.addChildJobFn(binaryStringFn, depth-1, message + "0") job.addChildJobFn(binaryStringFn, depth-1, message + "1") else: job.log("Binary string: {}".format(message)) if __name__=="__main__": options = Job.Runner.getDefaultOptions("./toilWorkflowRun") options.logLevel = "INFO" options.clean = "always" with Toil(options) as toil: toil.start(Job.wrapJobFn(binaryStringFn, depth=5)) toil-releases-3.24.0/src/toil/test/docs/scripts/tutorial_encapsulation.py000066400000000000000000000011661362134276200266600ustar00rootroot00000000000000from toil.common import Toil from toil.job import Job if __name__=="__main__": # A is a job with children and follow-ons, for example: A = Job() A.addChild(Job()) A.addFollowOn(Job()) # B is a job which needs to run after A and its successors B = Job() # The way to do this without encapsulation is to make a parent of A, Ap, and make B a follow-on of Ap. Ap = Job() Ap.addChild(A) Ap.addFollowOn(B) options = Job.Runner.getDefaultOptions("./toilWorkflowRun") options.logLevel = "INFO" options.clean = "always" with Toil(options) as toil: print(toil.start(Ap)) toil-releases-3.24.0/src/toil/test/docs/scripts/tutorial_encapsulation2.py000066400000000000000000000010651362134276200267400ustar00rootroot00000000000000from toil.common import Toil from toil.job import Job if __name__=="__main__": # A A = Job() A.addChild(Job()) A.addFollowOn(Job()) # Encapsulate A A = A.encapsulate() # B is a job which needs to run after A and its successors B = Job() # With encapsulation A and its successor subgraph appear to be a single job, hence: A.addChild(B) options = Job.Runner.getDefaultOptions("./toilWorkflowRun") options.logLevel = "INFO" options.clean = "always" with Toil(options) as toil: print(toil.start(A)) toil-releases-3.24.0/src/toil/test/docs/scripts/tutorial_helloworld.py000066400000000000000000000006571362134276200261720ustar00rootroot00000000000000from toil.common import Toil from toil.job import Job def helloWorld(message, memory="1G", cores=1, disk="1G"): return "Hello, world!, here's a message: %s" % message if __name__ == "__main__": parser = Job.Runner.getDefaultArgumentParser() options = parser.parse_args() options.clean = "always" with Toil(options) as toil: output = toil.start(Job.wrapFn(helloWorld, "You did it!")) print(output) toil-releases-3.24.0/src/toil/test/docs/scripts/tutorial_invokeworkflow.py000066400000000000000000000010541362134276200270750ustar00rootroot00000000000000from toil.common import Toil from toil.job import Job class HelloWorld(Job): def __init__(self, message): Job.__init__(self, memory="2G", cores=2, disk="3G") self.message = message def run(self, fileStore): return "Hello, world!, here's a message: %s" % self.message if __name__=="__main__": options = Job.Runner.getDefaultOptions("./toilWorkflowRun") options.logLevel = "OFF" options.clean = "always" hello_job = HelloWorld("Woot") with Toil(options) as toil: print(toil.start(hello_job)) toil-releases-3.24.0/src/toil/test/docs/scripts/tutorial_invokeworkflow2.py000066400000000000000000000011751362134276200271630ustar00rootroot00000000000000from toil.job import Job from toil.common import Toil class HelloWorld(Job): def __init__(self, message): Job.__init__(self, memory="2G", cores=2, disk="3G") self.message = message def run(self, fileStore): self.log("Hello, world!, I have a message: {}".format(self.message)) if __name__=="__main__": options = Job.Runner.getDefaultOptions("./toilWorkflowRun") options.logLevel = "INFO" options.clean = "always" with Toil(options) as toil: if not toil.options.restart: job = HelloWorld("Woot!") toil.start(job) else: toil.restart() toil-releases-3.24.0/src/toil/test/docs/scripts/tutorial_jobfunctions.py000066400000000000000000000006361362134276200265170ustar00rootroot00000000000000from toil.common import Toil from toil.job import Job def helloWorld(job, message): job.log("Hello world, I have a message: {}".format(message)) if __name__=="__main__": options = Job.Runner.getDefaultOptions("./toilWorkflowRun") options.logLevel = "INFO" options.clean = "always" hello_job = Job.wrapJobFn(helloWorld, "Woot!") with Toil(options) as toil: toil.start(hello_job) toil-releases-3.24.0/src/toil/test/docs/scripts/tutorial_managing.py000066400000000000000000000013201362134276200255640ustar00rootroot00000000000000from toil.common import Toil from toil.job import Job class LocalFileStoreJob(Job): def run(self, fileStore): # self.TempDir will always contain the name of a directory within the allocated disk space reserved for the job scratchDir = self.tempDir # Similarly create a temporary file. scratchFile = fileStore.getLocalTempFile() if __name__=="__main__": options = Job.Runner.getDefaultOptions("./toilWorkflowRun") options.logLevel = "INFO" options.clean = "always" # Create an instance of FooJob which will have at least 2 gigabytes of storage space. j = LocalFileStoreJob(disk="2G") #Run the workflow with Toil(options) as toil: toil.start(j) toil-releases-3.24.0/src/toil/test/docs/scripts/tutorial_managing2.py000066400000000000000000000040531362134276200256540ustar00rootroot00000000000000from toil.common import Toil from toil.job import Job import os import sys def globalFileStoreJobFn(job): job.log("The following example exercises all the methods provided" " by the toil.fileStores.abstractFileStore.AbstractFileStore class") # Create a local temporary file. scratchFile = job.fileStore.getLocalTempFile() # Write something in the scratch file. with open(scratchFile, 'w') as fH: fH.write("What a tangled web we weave") # Write a copy of the file into the file-store; fileID is the key that can be used to retrieve the file. # This write is asynchronous by default fileID = job.fileStore.writeGlobalFile(scratchFile) # Write another file using a stream; fileID2 is the # key for this second file. with job.fileStore.writeGlobalFileStream(cleanup=True) as (fH, fileID2): if sys.version_info >= (3, 0): # if python 3 fH.write(b"Out brief candle") else: # if python 2 fH.write("Out brief candle") # Now read the first file; scratchFile2 is a local copy of the file that is read-only by default. scratchFile2 = job.fileStore.readGlobalFile(fileID) # Read the second file to a desired location: scratchFile3. scratchFile3 = os.path.join(job.tempDir, "foo.txt") job.fileStore.readGlobalFile(fileID2, userPath=scratchFile3) # Read the second file again using a stream. with job.fileStore.readGlobalFileStream(fileID2) as fH: print(fH.read()) #This prints "Out brief candle" # Delete the first file from the global file-store. job.fileStore.deleteGlobalFile(fileID) # It is unnecessary to delete the file keyed by fileID2 because we used the cleanup flag, # which removes the file after this job and all its successors have run (if the file still exists) if __name__=="__main__": options = Job.Runner.getDefaultOptions("./toilWorkflowRun") options.logLevel = "INFO" options.clean = "always" with Toil(options) as toil: toil.start(Job.wrapJobFn(globalFileStoreJobFn)) toil-releases-3.24.0/src/toil/test/docs/scripts/tutorial_multiplejobs.py000066400000000000000000000012071362134276200265200ustar00rootroot00000000000000from toil.common import Toil from toil.job import Job def helloWorld(job, message, memory="2G", cores=2, disk="3G"): job.log("Hello world, I have a message: {}".format(message)) if __name__=="__main__": options = Job.Runner.getDefaultOptions("./toilWorkflowRun") options.logLevel = "INFO" options.clean = "always" j1 = Job.wrapJobFn(helloWorld, "first") j2 = Job.wrapJobFn(helloWorld, "second or third") j3 = Job.wrapJobFn(helloWorld, "second or third") j4 = Job.wrapJobFn(helloWorld, "last") j1.addChild(j2) j1.addChild(j3) j1.addFollowOn(j4) with Toil(options) as toil: toil.start(j1) toil-releases-3.24.0/src/toil/test/docs/scripts/tutorial_multiplejobs2.py000066400000000000000000000011241362134276200266000ustar00rootroot00000000000000from toil.common import Toil from toil.job import Job def helloWorld(job, message, memory="2G", cores=2, disk="3G"): job.log("Hello world, I have a message: {}".format(message)) if __name__=="__main__": options = Job.Runner.getDefaultOptions("./toilWorkflowRun") options.logLevel = "INFO" options.clean = "always" j1 = Job.wrapJobFn(helloWorld, "first") j2 = j1.addChildJobFn(helloWorld, "second or third") j3 = j1.addChildJobFn(helloWorld, "second or third") j4 = j1.addFollowOnJobFn(helloWorld, "last") with Toil(options) as toil: toil.start(j1) toil-releases-3.24.0/src/toil/test/docs/scripts/tutorial_multiplejobs3.py000066400000000000000000000011451362134276200266040ustar00rootroot00000000000000from toil.common import Toil from toil.job import Job def helloWorld(job, message, memory="2G", cores=2, disk="3G"): job.log("Hello world, I have a message: {}".format(message)) if __name__=="__main__": options = Job.Runner.getDefaultOptions("./toilWorkflowRun") options.logLevel = "INFO" options.clean = "always" j1 = Job.wrapJobFn(helloWorld, "first") j2 = j1.addChildJobFn(helloWorld, "second or third") j3 = j1.addChildJobFn(helloWorld, "second or third") j4 = j2.addChildJobFn(helloWorld, "last") j3.addChild(j4) with Toil(options) as toil: toil.start(j1) toil-releases-3.24.0/src/toil/test/docs/scripts/tutorial_promises.py000066400000000000000000000006721362134276200256550ustar00rootroot00000000000000from toil.common import Toil from toil.job import Job def fn(job, i): job.log("i is: %s" % i, level=100) return i+1 if __name__=="__main__": options = Job.Runner.getDefaultOptions("./toilWorkflowRun") options.logLevel = "INFO" options.clean = "always" j1 = Job.wrapJobFn(fn, 1) j2 = j1.addChildJobFn(fn, j1.rv()) j3 = j1.addFollowOnJobFn(fn, j2.rv()) with Toil(options) as toil: toil.start(j1) toil-releases-3.24.0/src/toil/test/docs/scripts/tutorial_promises2.py000066400000000000000000000012021362134276200257250ustar00rootroot00000000000000from toil.common import Toil from toil.job import Job def binaryStrings(job, depth, message=""): if depth > 0: s = [ job.addChildJobFn(binaryStrings, depth-1, message + "0").rv(), job.addChildJobFn(binaryStrings, depth-1, message + "1").rv() ] return job.addFollowOnFn(merge, s).rv() return [message] def merge(strings): return strings[0] + strings[1] if __name__=="__main__": options = Job.Runner.getDefaultOptions("./toilWorkflowRun") options.loglevel = "OFF" options.clean = "always" with Toil(options) as toil: print(toil.start(Job.wrapJobFn(binaryStrings, depth=5))) toil-releases-3.24.0/src/toil/test/docs/scripts/tutorial_quickstart.py000066400000000000000000000007211362134276200262010ustar00rootroot00000000000000from toil.common import Toil from toil.job import Job def helloWorld(message, memory="2G", cores=2, disk="3G"): return "Hello, world!, here's a message: %s" % message if __name__=="__main__": options = Job.Runner.getDefaultOptions("./toilWorkflowRun") options.logLevel = "OFF" options.clean = "always" hello_job = Job.wrapFn(helloWorld, "Woot") with Toil(options) as toil: print(toil.start(hello_job)) #Prints Hello, world!, ... toil-releases-3.24.0/src/toil/test/docs/scripts/tutorial_requirements.py000066400000000000000000000015541362134276200265370ustar00rootroot00000000000000from toil.common import Toil from toil.job import Job, PromisedRequirement import os def parentJob(job): downloadJob = Job.wrapJobFn(stageFn, "File://"+os.path.realpath(__file__), cores=0.1, memory='32M', disk='1M') job.addChild(downloadJob) analysis = Job.wrapJobFn(analysisJob, fileStoreID=downloadJob.rv(0), disk=PromisedRequirement(downloadJob.rv(1))) job.addFollowOn(analysis) def stageFn(job, url, cores=1): importedFile = job.fileStore.importFile(url) return importedFile, importedFile.size def analysisJob(job, fileStoreID, cores=2): # now do some analysis on the file pass if __name__ == "__main__": options = Job.Runner.getDefaultOptions("./toilWorkflowRun") options.logLevel = "INFO" options.clean = "always" with Toil(options) as toil: toil.start(Job.wrapJobFn(parentJob)) toil-releases-3.24.0/src/toil/test/docs/scripts/tutorial_services.py000066400000000000000000000017661362134276200256440ustar00rootroot00000000000000from toil.common import Toil from toil.job import Job class DemoService(Job.Service): def start(self, fileStore): # Start up a database/service here # Return a value that enables another process to connect to the database return "loginCredentials" def check(self): # A function that if it returns False causes the service to quit # If it raises an exception the service is killed and an error is reported return True def stop(self, fileStore): # Cleanup the database here pass j = Job() s = DemoService() loginCredentialsPromise = j.addService(s) def dbFn(loginCredentials): # Use the login credentials returned from the service's start method to connect to the service pass j.addChildFn(dbFn, loginCredentialsPromise) if __name__=="__main__": options = Job.Runner.getDefaultOptions("./toilWorkflowRun") options.logLevel = "INFO" options.clean = "always" with Toil(options) as toil: toil.start(j) toil-releases-3.24.0/src/toil/test/docs/scripts/tutorial_staging.py000066400000000000000000000021621362134276200254440ustar00rootroot00000000000000import os from toil.common import Toil from toil.job import Job class HelloWorld(Job): def __init__(self, id): Job.__init__(self, memory="2G", cores=2, disk="3G") self.inputFileID = id def run(self, fileStore): with self.fileStore.readGlobalFileStream(self.inputFileID) as fi: with self.fileStore.writeGlobalFileStream() as (fo, outputFileID): fo.write(fi.read() + 'World!') return outputFileID if __name__=="__main__": options = Job.Runner.getDefaultOptions("./toilWorkflowRun") options.logLevel = "INFO" options.clean = "always" with Toil(options) as toil: if not toil.options.restart: ioFileDirectory = os.path.join(os.path.dirname(os.path.abspath(__file__)), "stagingExampleFiles") inputFileID = toil.importFile("file://" + os.path.abspath(os.path.join(ioFileDirectory, "in.txt"))) outputFileID = toil.start(HelloWorld(inputFileID)) else: outputFileID = toil.restart() toil.exportFile(outputFileID, "file://" + os.path.abspath(os.path.join(ioFileDirectory, "out.txt"))) toil-releases-3.24.0/src/toil/test/docs/scripts/tutorial_wdlexample.py000066400000000000000000000040661362134276200261570ustar00rootroot00000000000000from toil.job import Job from toil.common import Toil import subprocess import os def initialize_jobs(job): job.fileStore.logToMaster("initialize_jobs") def runQC(job, wdl_file, wdl_filename, json_file, json_filename, outputs_dir, jar_loc,output_num): job.fileStore.logToMaster("runQC") tempDir = job.fileStore.getLocalTempDir() wdl = job.fileStore.readGlobalFile(wdl_file, userPath=os.path.join(tempDir, wdl_filename)) json = job.fileStore.readGlobalFile(json_file, userPath=os.path.join(tempDir, json_filename)) subprocess.check_call(["java","-jar",jar_loc,"run",wdl,"--inputs",json]) output_filename = "output.txt" output_file = job.fileStore.writeGlobalFile(outputs_dir + output_filename) job.fileStore.readGlobalFile(output_file, userPath=os.path.join(outputs_dir, "sample_" + output_num + "_" + output_filename)) return output_file if __name__ == "__main__": options = Job.Runner.getDefaultOptions("./toilWorkflowRun") options.logLevel = "INFO" options.clean = "always" with Toil(options) as toil: # specify the folder where the wdl and json files live inputs_dir = "wdlExampleFiles/" # specify where you wish the outputs to be written outputs_dir = "wdlExampleFiles/" # specify the location of your cromwell jar jar_loc = os.path.abspath("wdlExampleFiles/cromwell-35.jar") job0 = Job.wrapJobFn(initialize_jobs) wdl_filename = "hello.wdl" wdl_file = toil.importFile("file://" + os.path.abspath(os.path.join(inputs_dir, wdl_filename))) # add list of yml config inputs here or import and construct from file json_files = ["hello1.json", "hello2.json", "hello3.json"] i = 0 for json in json_files: i = i + 1 json_file = toil.importFile("file://" + os.path.join(inputs_dir, json)) json_filename = json job = Job.wrapJobFn(runQC, wdl_file, wdl_filename, json_file, json_filename, outputs_dir, jar_loc, output_num=str(i)) job0.addChild(job) toil.start(job0) toil-releases-3.24.0/src/toil/test/docs/scriptsTest.py000066400000000000000000000136621362134276200227340ustar00rootroot00000000000000from __future__ import absolute_import import unittest import os import re import sys import shutil pkg_root = os.path.abspath(os.path.join(os.path.dirname(__file__), '..')) # noqa sys.path.insert(0, pkg_root) # noqa from toil import subprocess from toil.test import ToilTest from toil.test import needs_cwl from toil.version import python class ToilDocumentationTest(ToilTest): """Tests for scripts in the toil tutorials.""" @classmethod def setUpClass(cls): cls.directory = os.path.dirname(os.path.abspath(__file__)) def tearDown(self): # src/toil/test/docs/scripts/cwlExampleFiles/sample_1_output.txt output_files = ["sample_1_output.txt", "sample_2_output.txt", "sample_3_output.txt"] for output in output_files: output_file = os.path.join(self.directory, 'scripts/cwlExampleFiles', output) if os.path.exists(output_file): os.remove(output_file) jobstores = ['./toilWorkflowRun', '/mnt/ephemeral/workspace/toil-pull-requests/toilWorkflowRun'] for jobstore in jobstores: if os.path.exists(jobstore): shutil.rmtree(jobstore) unittest.TestCase.tearDown(self) """Just check the exit code""" def checkExitCode(self, script): program = os.path.join(self.directory, "scripts", script) process = subprocess.Popen([python, program, "file:my-jobstore", "--clean=always"], stdout=subprocess.PIPE, stderr=subprocess.PIPE) stdout, stderr = process.communicate() assert process.returncode == 0, stderr if isinstance(stdout, bytes): return stdout.decode('utf-8') + ' ' + stderr.decode('utf-8') return stdout + ' ' + stderr """Check the exit code and the output""" def checkExpectedOut(self, script, expectedOutput): outerr = self.checkExitCode(script) # Check that the expected output is there index = outerr.find(expectedOutput) self.assertGreater(index, -1, "Expected:\n{}\nOutput:\n{}".format(expectedOutput, outerr)) """Check the exit code and look for a pattern""" def checkExpectedPattern(self, script, expectedPattern): outerr = self.checkExitCode(script) # Check that the expected output pattern is there pattern = re.compile(expectedPattern, re.DOTALL) n = re.search(pattern, outerr) self.assertNotEqual(n, None, "Pattern:\n{}\nOutput:\n{}".format(expectedPattern, outerr)) @needs_cwl def testCwlexample(self): self.checkExitCode("tutorial_cwlexample.py") def testDiscoverfiles(self): self.checkExitCode("tutorial_discoverfiles.py") def testDynamic(self): self.checkExitCode("tutorial_dynamic.py") def testEncapsulation(self): self.checkExitCode("tutorial_encapsulation.py") def testEncapsulation2(self): self.checkExitCode("tutorial_encapsulation2.py") def testHelloworld(self): self.checkExpectedOut("tutorial_helloworld.py", "Hello, world!, here's a message: You did it!\n") def testInvokeworkflow(self): self.checkExpectedOut("tutorial_invokeworkflow.py", "Hello, world!, here's a message: Woot\n") def testInvokeworkflow2(self): self.checkExpectedOut("tutorial_invokeworkflow2.py", "Hello, world!, I have a message: Woot!\n") def testJobFunctions(self): self.checkExpectedOut("tutorial_jobfunctions.py", "Hello world, I have a message: Woot!\n") def testManaging(self): self.checkExitCode("tutorial_managing.py") def testManaging2(self): self.checkExitCode("tutorial_managing2.py") def testMultiplejobs(self): self.checkExpectedPattern("tutorial_multiplejobs.py", "Hello world, I have a message: first.*Hello world, I have a message: " "second or third.*Hello world, I have a message: second or third.*Hello world," " I have a message: last") def testMultiplejobs2(self): self.checkExpectedPattern("tutorial_multiplejobs2.py", "Hello world, I have a message: first.*Hello world, I have a message: " "second or third.*Hello world, I have a message: second or third.*Hello world," " I have a message: last") def testMultiplejobs3(self): self.checkExpectedPattern("tutorial_multiplejobs3.py", "Hello world, I have a message: first.*Hello world, I have a message: " "second or third.*Hello world, I have a message: second or third.*Hello world," " I have a message: last") def testPromises2(self): self.checkExpectedOut("tutorial_promises2.py", "['00000', '00001', '00010', '00011', '00100', '00101', '00110', '00111', '01000'," " '01001', '01010', '01011', '01100', '01101', '01110', '01111', '10000', '10001', " "'10010', '10011', '10100', '10101', '10110', '10111', '11000', '11001', '11010', " "'11011', '11100', '11101', '11110', '11111']") def testQuickstart(self): self.checkExpectedOut("tutorial_quickstart.py", "Hello, world!, here's a message: Woot\n") def testRequirements(self): self.checkExitCode("tutorial_requirements.py") def testArguments(self): self.checkExpectedOut("tutorial_arguments.py", "Hello, world!, here's a message: Woot") """@needs_docker # timing out; likely need to update docker on toil def testDocker(self): self.checkExitCode("tutorial_docker.py")""" def testPromises(self): self.checkExpectedPattern("tutorial_promises.py", "i is: 1.*i is: 2.*i is: 3") def testServices(self): self.checkExitCode("tutorial_services.py") """Needs cromwell jar file to run def testWdlexample(self): self.checkExitCode("tutorial_wdlexample.py")""" if __name__ == "__main__": unittest.main() toil-releases-3.24.0/src/toil/test/jobStores/000077500000000000000000000000001362134276200210455ustar00rootroot00000000000000toil-releases-3.24.0/src/toil/test/jobStores/__init__.py000066400000000000000000000012131362134276200231530ustar00rootroot00000000000000# Copyright (C) 2015-2016 Regents of the University of California # # 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. from __future__ import absolute_import toil-releases-3.24.0/src/toil/test/jobStores/jobStoreTest.py000066400000000000000000001702671362134276200240630ustar00rootroot00000000000000# Copyright (C) 2015-2016 Regents of the University of California # # 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. from __future__ import absolute_import from __future__ import division from future import standard_library standard_library.install_aliases() from builtins import range from builtins import str from past.utils import old_div from builtins import object import socketserver import pytest import hashlib import logging import threading import os import sys import shutil import tempfile import time import uuid from stubserver import FTPStubServer from abc import abstractmethod, ABCMeta from itertools import chain, islice from threading import Thread from unittest import skip from six.moves.queue import Queue from six.moves import SimpleHTTPServer, StringIO from six import iteritems import six.moves.urllib.parse as urlparse from six.moves.urllib.request import urlopen, Request from toil.lib.memoize import memoize from toil.lib.exceptions import panic # noinspection PyPackageRequirements # (installed by `make prepare`) from mock import patch from toil.lib.compatibility import USING_PYTHON2 from toil.common import Config, Toil from toil.fileStores import FileID from toil.job import Job, JobNode from toil.jobStores.abstractJobStore import (NoSuchJobException, NoSuchFileException) from toil.jobStores.fileJobStore import FileJobStore from toil.statsAndLogging import StatsAndLogging from toil.test import (ToilTest, needs_aws_s3, needs_encryption, make_tests, needs_google, travis_test, slow) from future.utils import with_metaclass # Need googleRetry decorator even if google is not available, so make one up. # Unconventional use of decorator to determine if google is enabled by seeing if # it returns the parameter passed in. if needs_google(needs_google) is needs_google: from toil.jobStores.googleJobStore import googleRetry else: def googleRetry(x): return x logger = logging.getLogger(__name__) def tearDownModule(): AbstractJobStoreTest.Test.cleanUpExternalStores() class AbstractJobStoreTest(object): """ Hide abstract base class from unittest's test case loader http://stackoverflow.com/questions/1323455/python-unit-test-with-base-and-sub-class#answer-25695512 """ class Test(with_metaclass(ABCMeta, ToilTest)): @classmethod def setUpClass(cls): super(AbstractJobStoreTest.Test, cls).setUpClass() logging.basicConfig(level=logging.DEBUG) logging.getLogger('boto').setLevel(logging.CRITICAL) # The use of @memoize ensures that we only have one instance of per class even with the # generative import/export tests attempts to instantiate more. This in turn enables us to # share the external stores (buckets, blob store containers, local directory, etc.) used # for testing import export. While the constructor arguments are included in the # memoization key, I have only ever seen one case: ('test', ). The worst that can happen # if other values are also used is that there will be more external stores and less sharing # of them. They will still all be cleaned-up. @classmethod @memoize def __new__(cls, *args): return super(AbstractJobStoreTest.Test, cls).__new__(cls) def _createConfig(self): return Config() @abstractmethod def _createJobStore(self): """ :rtype: AbstractJobStore """ raise NotImplementedError() def setUp(self): super(AbstractJobStoreTest.Test, self).setUp() self.namePrefix = 'jobstore-test-' + str(uuid.uuid4()) self.config = self._createConfig() # Jobstores to be used in testing. # jobstore_initialized is created with a particular configuration, as creating by self._createConfig() # jobstore_resume_noconfig is created with the resume() method. resume() will look for a previously # instantiated jobstore, and initialize the jobstore calling it with the found config. In this case, # jobstore_resume_noconfig will be initialized with the config from jobstore_initialized. self.jobstore_initialized = self._createJobStore() self.jobstore_initialized.initialize(self.config) self.jobstore_resumed_noconfig = self._createJobStore() self.jobstore_resumed_noconfig.resume() # Requirements for jobs to be created. self.arbitraryRequirements = {'memory': 1, 'disk': 2, 'cores': 1, 'preemptable': False} self.arbitraryJob = JobNode(command='command', jobStoreID=None, jobName='arbitrary', unitName=None, requirements=self.arbitraryRequirements) self.parentJobReqs = dict(memory=12, cores=34, disk=35, preemptable=True) self.childJobReqs1 = dict(memory=23, cores=45, disk=46, preemptable=True) self.childJobReqs2 = dict(memory=34, cores=56, disk=57, preemptable=False) def tearDown(self): self.jobstore_initialized.destroy() self.jobstore_resumed_noconfig.destroy() super(AbstractJobStoreTest.Test, self).tearDown() @travis_test def testInitialState(self): """Ensure proper handling of nonexistant files.""" self.assertFalse(self.jobstore_initialized.exists('nonexistantFile')) self.assertRaises(NoSuchJobException, self.jobstore_initialized.load, 'nonexistantFile') @travis_test def testJobCreation(self): """ Test creation of a job. Does the job exist in the jobstore it is supposed to be in? Are its attributes what is expected? """ jobstore = self.jobstore_initialized # Create a job and verify its existence/properties aJobNode = JobNode(command='parent1', requirements=self.parentJobReqs, jobName='test1', unitName='onParent', jobStoreID=None, predecessorNumber=0) job = jobstore.create(aJobNode) self.assertTrue(jobstore.exists(job.jobStoreID)) self.assertEqual(job.command, 'parent1') self.assertEqual(job.memory, self.parentJobReqs['memory']) self.assertEqual(job.cores, self.parentJobReqs['cores']) self.assertEqual(job.disk, self.parentJobReqs['disk']) self.assertEqual(job.preemptable, self.parentJobReqs['preemptable']) self.assertEqual(job.jobName, 'test1') self.assertEqual(job.unitName, 'onParent') self.assertEqual(job.stack, []) self.assertEqual(job.predecessorNumber, 0) self.assertEqual(job.predecessorsFinished, set()) self.assertEqual(job.logJobStoreFileID, None) @travis_test def testConfigEquality(self): """ Ensure that the command line configurations are successfully loaded and stored. In setUp() self.jobstore1 is created and initialized. In this test, after creating newJobStore, .resume() will look for a previously instantiated job store and load its config options. This is expected to be equal but not the same object. """ newJobStore = self._createJobStore() newJobStore.resume() self.assertEqual(newJobStore.config, self.config) self.assertIsNot(newJobStore.config, self.config) @travis_test def testJobLoadEquality(self): """Tests that a job loaded into one jobstore from another can be used equivalently by another.""" # Create a job on the first jobstore. jobNode1 = JobNode(command='jobstore1', requirements=self.parentJobReqs, jobName='test1', unitName='onJS1', jobStoreID=None, predecessorNumber=0) job1 = self.jobstore_initialized.create(jobNode1) # Load it onto the second jobstore job2 = self.jobstore_resumed_noconfig.load(job1.jobStoreID) self.assertEqual(job1, job2) @travis_test def testChildLoadingEquality(self): """Test that loading a child job operates as expected.""" aJobNode = JobNode(command='parent1', requirements=self.parentJobReqs, jobName='test1', unitName='onParent', jobStoreID=None, predecessorNumber=0) jobNodeOnChild = JobNode(command='child1', requirements=self.childJobReqs1, jobName='test2', unitName='onChild1', jobStoreID=None) job = self.jobstore_initialized.create(aJobNode) childJob = self.jobstore_initialized.create(jobNodeOnChild) job.stack.append(childJob) self.jobstore_initialized.update(job) self.assertEqual(self.jobstore_initialized.load(childJob.jobStoreID), childJob) @travis_test def testPersistantFilesToDelete(self): """ Make sure that updating a job carries over filesToDelete. The following demonstrates the job update pattern, where files to be deleted are referenced in "filesToDelete" array, which is persisted to disk first. If things go wrong during the update, this list of files to delete is used to remove the unneeded files. """ # Create a job. jobNode = JobNode(command='job1', requirements=self.parentJobReqs, jobName='test1', unitName='onJS1', jobStoreID=None, predecessorNumber=0) job = self.jobstore_initialized.create(jobNode) job.filesToDelete = ['1', '2'] self.jobstore_initialized.update(job) self.assertEqual(self.jobstore_initialized.load(job.jobStoreID).filesToDelete, ['1', '2']) @travis_test def testUpdateBehavior(self): """Tests the proper behavior during updating jobs.""" jobstore1 = self.jobstore_initialized jobstore2 = self.jobstore_resumed_noconfig aJobNode = JobNode(command='parent1', requirements=self.parentJobReqs, jobName='test1', unitName='onParent', jobStoreID=None, predecessorNumber=0) jobNodeOnChild1 = JobNode(command='child1', requirements=self.childJobReqs1, jobName='test2', unitName='onChild1', jobStoreID=None) jobNodeOnChild2 = JobNode(command='child2', requirements=self.childJobReqs2, jobName='test3', unitName='onChild2', jobStoreID=None) job1 = jobstore1.create(aJobNode) job2 = jobstore2.load(job1.jobStoreID) # Create child jobs. childJob1 = jobstore2.create(jobNodeOnChild1) childJob2 = jobstore2.create(jobNodeOnChild2) # Add them to job2. job2.stack.append((childJob1, childJob2)) jobstore2.update(job2) # Check equivalence between jobstore1 and jobstore2. # While job1 and job2 share a jobStoreID, job1 has not been "refreshed" to show the newly added child jobs. self.assertNotEqual(job2, job1) # Reload parent job on jobstore, "refreshing" the job. job1 = jobstore1.load(job1.jobStoreID) self.assertEqual(job2, job1) # Load children on jobstore and check equivalence self.assertEqual(jobstore1.load(childJob1.jobStoreID), childJob1) self.assertEqual(jobstore1.load(childJob2.jobStoreID), childJob2) self.assertEqual(job1, job2) # The jobs should both have children now... self.assertIsNot(job1, job2) # but should not be the same. @travis_test def testChangingJobStoreID(self): """ Tests that changing the jobStoreID makes jobs unequivalent. Create two job trees, jobstore1 & jobstore2 consisting of a parent and 5 child jobs. The children of jobstore2 will be copied from jobstore1. Changing the jobstoreFileID on each child on jobstore1 will cause them to be different jobs. After updating the children of jobstore2, they should be equal. """ jobstore1 = self.jobstore_initialized jobstore2 = self.jobstore_resumed_noconfig # Create a job aJobNode = JobNode(command='parent1', requirements=self.parentJobReqs, jobName='test1', unitName='onParent', jobStoreID=None, predecessorNumber=0) # Load the job onto the two jobstores. parentJob1 = jobstore1.create(aJobNode) parentJob2 = jobstore2.load(parentJob1.jobStoreID) # Create an array of child jobs for each jobstore. for i in range(0, 5): jobNodeOnChild1 = JobNode(command='child' + str(i), requirements=self.childJobReqs1, jobName='test' + str(i), unitName='onChild1', jobStoreID=None) aChildJob = jobstore1.create(jobNodeOnChild1) parentJob1.stack.append(aChildJob) jobstore2.load(aChildJob.jobStoreID) # Compare children before and after update. for childJob in parentJob2.stack: self.assertEqual(childJob, jobstore1.load(childJob.jobStoreID)) childJob.logJobStoreFileID = str(uuid.uuid4()) childJob.remainingRetryCount = 66 self.assertNotEqual(childJob, jobstore1.load(childJob.jobStoreID)) # Update the children on the second jobstore. for childJob in parentJob2.stack: jobstore2.update(childJob) # Check that the jobs are equivalent after being reloaded. for childJob in parentJob2.stack: self.assertEqual(jobstore1.load(childJob.jobStoreID), childJob) self.assertEqual(jobstore2.load(childJob.jobStoreID), childJob) @travis_test def testJobDeletions(self): """Tests the consequences of deleting jobs.""" # A local jobstore object for testing. jobstore = self.jobstore_initialized jobNodeOnParent = JobNode(command='job1', requirements=self.parentJobReqs, jobName='test1', unitName='onJob', jobStoreID=None, predecessorNumber=0) # Create jobs job = jobstore.create(jobNodeOnParent) # Create child Jobs jobNodeOnChild1 = JobNode(command='child1', requirements=self.childJobReqs1, jobName='test2', unitName='onChild1', jobStoreID=None) jobNodeOnChild2 = JobNode(command='job1', requirements=self.childJobReqs2, jobName='test3', unitName='onChild2', jobStoreID=None) # Add children to parent. child1 = jobstore.create(jobNodeOnChild1) child2 = jobstore.create(jobNodeOnChild2) job.stack.append((child1, child2)) jobstore.update(job) # Reminder: We are accessing the -1st element because we just appended. # However, there should only be one element. childJobs = [jobstore.load(childNode.jobStoreID) for childNode in job.stack[-1]] # Test job iterator - the results of the iterator are effected by eventual # consistency. We cannot guarantee all jobs will appear but we can assert that all # jobs that show up are a subset of all existing jobs. If we had deleted jobs before # this we would have to worry about ghost jobs appearing and this assertion would not # be valid self.assertTrue(set(childJobs + [job]) >= set(jobstore.jobs())) # Test job deletions # First delete parent, this should have no effect on the children self.assertTrue(jobstore.exists(job.jobStoreID)) jobstore.delete(job.jobStoreID) self.assertFalse(jobstore.exists(job.jobStoreID)) # Check the deletion of children for childJob in childJobs: self.assertTrue(jobstore.exists(childJob.jobStoreID)) jobstore.delete(childJob.jobStoreID) self.assertFalse(jobstore.exists(childJob.jobStoreID)) self.assertRaises(NoSuchJobException, jobstore.load, childJob.jobStoreID) try: with jobstore.readSharedFileStream('missing') as _: pass self.fail('Expecting NoSuchFileException') except NoSuchFileException: pass @travis_test def testSharedFiles(self): """Tests the sharing of files.""" jobstore1 = self.jobstore_initialized jobstore2 = self.jobstore_resumed_noconfig bar = 'bar' if sys.version_info >= (3, 0): bar = b'bar' with jobstore1.writeSharedFileStream('foo') as f: f.write(bar) # ... read that file on worker, ... with jobstore2.readSharedFileStream('foo') as f: self.assertEqual(bar, f.read()) # ... and read it again on jobstore1. with jobstore1.readSharedFileStream('foo') as f: self.assertEqual(bar, f.read()) with jobstore1.writeSharedFileStream('nonEncrypted', isProtected=False) as f: f.write(bar) self.assertUrl(jobstore1.getSharedPublicUrl('nonEncrypted')) self.assertRaises(NoSuchFileException, jobstore1.getSharedPublicUrl, 'missing') @travis_test def testPerJobFiles(self): """Tests the behavior of files on jobs.""" jobstore1 = self.jobstore_initialized jobstore2 = self.jobstore_resumed_noconfig # Create jobNodeOnJS1 jobNodeOnJobStore1 = JobNode(command='job1', requirements=self.parentJobReqs, jobName='test1', unitName='onJobStore1', jobStoreID=None, predecessorNumber=0) # First recreate job jobOnJobStore1 = jobstore1.create(jobNodeOnJobStore1) fileOne = jobstore2.getEmptyFileStoreID(jobOnJobStore1.jobStoreID, cleanup=True) # Check file exists self.assertTrue(jobstore2.fileExists(fileOne)) self.assertTrue(jobstore1.fileExists(fileOne)) one = 'one' two = 'two' three = 'three' if sys.version_info >= (3, 0): one = b'one' two = b'two' three = b'three' # ... write to the file on jobstore2, ... with jobstore2.updateFileStream(fileOne) as f: f.write(one) # ... read the file as a stream on the jobstore1, .... with jobstore1.readFileStream(fileOne) as f: self.assertEqual(f.read(), one) # ... and copy it to a temporary physical file on the jobstore1. fh, path = tempfile.mkstemp() try: os.close(fh) tmpPath = path + '.read-only' jobstore1.readFile(fileOne, tmpPath) try: shutil.copyfile(tmpPath, path) finally: os.unlink(tmpPath) with open(path, 'rb+') as f: self.assertEqual(f.read(), one) # Write a different string to the local file ... f.seek(0) f.truncate(0) f.write(two) # ... and create a second file from the local file. fileTwo = jobstore1.writeFile(path, jobOnJobStore1.jobStoreID, cleanup=True) with jobstore2.readFileStream(fileTwo) as f: self.assertEqual(f.read(), two) # Now update the first file from the local file ... jobstore1.updateFile(fileOne, path) with jobstore2.readFileStream(fileOne) as f: self.assertEqual(f.read(), two) finally: os.unlink(path) # Create a third file to test the last remaining method. with jobstore2.writeFileStream(jobOnJobStore1.jobStoreID, cleanup=True) as (f, fileThree): f.write(three) with jobstore1.readFileStream(fileThree) as f: self.assertEqual(f.read(), three) # Delete a file explicitly but leave files for the implicit deletion through the parent jobstore2.deleteFile(fileOne) # Check the file is gone # for store in jobstore2, jobstore1: self.assertFalse(store.fileExists(fileOne)) self.assertRaises(NoSuchFileException, store.readFile, fileOne, '') try: with store.readFileStream(fileOne) as _: pass self.fail('Expecting NoSuchFileException') except NoSuchFileException: pass @travis_test def testStatsAndLogging(self): """Tests behavior of reading and writting stats and logging.""" jobstore1 = self.jobstore_initialized jobstore2 = self.jobstore_resumed_noconfig jobNodeOnJobStore1 = JobNode(command='job1', requirements=self.parentJobReqs, jobName='test1', unitName='onJobStore1', jobStoreID=None, predecessorNumber=0) jobOnJobStore1 = jobstore1.create(jobNodeOnJobStore1) # Test stats and logging stats = None one = b'one' if not USING_PYTHON2 else 'one' two = b'two' if not USING_PYTHON2 else 'two' # Allows stats to be read/written to/from in read/writeStatsAndLogging. def callback(f2): stats.add(f2.read()) # Collects stats and logging messages. stats = set() # No stats or logging added yet. Expect nothing. self.assertEqual(0, jobstore1.readStatsAndLogging(callback)) self.assertEqual(set(), stats) # Test writing and reading. jobstore2.writeStatsAndLogging(one) self.assertEqual(1, jobstore1.readStatsAndLogging(callback)) self.assertEqual({one}, stats) self.assertEqual(0, jobstore1.readStatsAndLogging(callback)) # readStatsAndLogging purges saved stats etc jobstore2.writeStatsAndLogging(one) jobstore2.writeStatsAndLogging(two) stats = set() self.assertEqual(2, jobstore1.readStatsAndLogging(callback)) self.assertEqual({one, two}, stats) largeLogEntry = os.urandom(self._largeLogEntrySize()) stats = set() jobstore2.writeStatsAndLogging(largeLogEntry) self.assertEqual(1, jobstore1.readStatsAndLogging(callback)) self.assertEqual({largeLogEntry}, stats) # test the readAll parameter self.assertEqual(4, jobstore1.readStatsAndLogging(callback, readAll=True)) # Delete parent jobstore1.delete(jobOnJobStore1.jobStoreID) self.assertFalse(jobstore1.exists(jobOnJobStore1.jobStoreID)) # TODO: Who deletes the shared files? @travis_test def testWriteLogFiles(self): """Test writing log files.""" jobNames = ['testStatsAndLogging_writeLogFiles'] jobLogList = ['string', b'bytes', '', b'newline\n'] config = self._createConfig() setattr(config, 'writeLogs', '.') setattr(config, 'writeLogsGzip', None) StatsAndLogging.writeLogFiles(jobNames, jobLogList, config) jobLogFile = os.path.join(config.writeLogs, jobNames[0] + '000.log') self.assertTrue(os.path.isfile(jobLogFile)) with open(jobLogFile, 'r') as f: self.assertEqual(f.read(), 'string\nbytes\n\nnewline\n') os.remove(jobLogFile) @travis_test def testBatchCreate(self): """Test creation of many jobs.""" jobstore = self.jobstore_initialized jobRequirements = dict(memory=12, cores=34, disk=35, preemptable=True) jobGraphs = [] with jobstore.batch(): for i in range(100): overlargeJobNode = JobNode(command='overlarge', requirements=jobRequirements, jobName='test-overlarge', unitName='onJobStore', jobStoreID=None, predecessorNumber=0) jobGraphs.append(jobstore.create(overlargeJobNode)) for jobGraph in jobGraphs: self.assertTrue(jobstore.exists(jobGraph.jobStoreID)) @travis_test def testGrowingAndShrinkingJob(self): """Make sure jobs update correctly if they grow/shrink.""" # Make some very large data, large enough to trigger # overlarge job creation if that's a thing # (i.e. AWSJobStore) arbitraryLargeData = os.urandom(500000) job = self.jobstore_initialized.create(self.arbitraryJob) # Make the job grow job.foo_attribute = arbitraryLargeData self.jobstore_initialized.update(job) check_job = self.jobstore_initialized.load(job.jobStoreID) self.assertEqual(check_job.foo_attribute, arbitraryLargeData) # Make the job shrink back close to its original size job.foo_attribute = None self.jobstore_initialized.update(job) check_job = self.jobstore_initialized.load(job.jobStoreID) self.assertEqual(check_job.foo_attribute, None) def _prepareTestFile(self, store, size=None): """ Generates a URL that can be used to point at a test file in the storage mechanism used by the job store under test by this class. Optionally creates a file at that URL. :param: store: an object referencing the store, same type as _createExternalStore's return value :param int size: The size of the test file to be created. :return: the URL, or a tuple (url, md5) where md5 is the file's hexadecimal MD5 digest :rtype: str|(str,str) """ raise NotImplementedError() @abstractmethod def _hashTestFile(self, url): """ Returns hexadecimal MD5 digest of the contents of the file pointed at by the URL. """ raise NotImplementedError() @abstractmethod def _createExternalStore(self): raise NotImplementedError() @abstractmethod def _cleanUpExternalStore(self, store): """ :param: store: an object referencing the store, same type as _createExternalStore's return value """ raise NotImplementedError() externalStoreCache = {} def _externalStore(self): try: store = self.externalStoreCache[self] except KeyError: logger.debug('Creating new external store for %s', self) store = self.externalStoreCache[self] = self._createExternalStore() else: logger.debug('Reusing external store for %s', self) return store @classmethod def cleanUpExternalStores(cls): for test, store in iteritems(cls.externalStoreCache): logger.debug('Cleaning up external store for %s.', test) test._cleanUpExternalStore(store) mpTestPartSize = 5 << 20 @classmethod def makeImportExportTests(cls): testClasses = [FileJobStoreTest, AWSJobStoreTest, GoogleJobStoreTest] activeTestClassesByName = {testCls.__name__: testCls for testCls in testClasses if not getattr(testCls, '__unittest_skip__', False)} def testImportExportFile(self, otherCls, size): """ :param AbstractJobStoreTest.Test self: the current test case :param AbstractJobStoreTest.Test otherCls: the test case class for the job store to import from or export to :param int size: the size of the file to test importing/exporting with """ # Prepare test file in other job store self.jobstore_initialized.partSize = cls.mpTestPartSize # The string in otherCls() is arbitrary as long as it returns a class that has access # to ._externalStore() and ._prepareTestFile() other = otherCls('testSharedFiles') store = other._externalStore() srcUrl, srcMd5 = other._prepareTestFile(store, size) # Import into job store under test jobStoreFileID = self.jobstore_initialized.importFile(srcUrl) self.assertTrue(isinstance(jobStoreFileID, FileID)) with self.jobstore_initialized.readFileStream(jobStoreFileID) as f: fileMD5 = hashlib.md5(f.read()).hexdigest() self.assertEqual(fileMD5, srcMd5) # Export back into other job store dstUrl = other._prepareTestFile(store) self.jobstore_initialized.exportFile(jobStoreFileID, dstUrl) self.assertEqual(fileMD5, other._hashTestFile(dstUrl)) if otherCls.__name__ == 'FileJobStoreTest': # Remove local Files os.remove(srcUrl[7:]) os.remove(dstUrl[7:]) make_tests(testImportExportFile, cls, otherCls=activeTestClassesByName, size=dict(zero=0, one=1, oneMiB=2 ** 20, partSizeMinusOne=cls.mpTestPartSize - 1, partSize=cls.mpTestPartSize, partSizePlusOne=cls.mpTestPartSize + 1)) def testImportSharedFile(self, otherCls): """ :param AbstractJobStoreTest.Test self: the current test case :param AbstractJobStoreTest.Test otherCls: the test case class for the job store to import from or export to """ # Prepare test file in other job store self.jobstore_initialized.partSize = cls.mpTestPartSize other = otherCls('testSharedFiles') store = other._externalStore() srcUrl, srcMd5 = other._prepareTestFile(store, 42) # Import into job store under test self.assertIsNone(self.jobstore_initialized.importFile(srcUrl, sharedFileName='foo')) with self.jobstore_initialized.readSharedFileStream('foo') as f: fileMD5 = hashlib.md5(f.read()).hexdigest() self.assertEqual(fileMD5, srcMd5) if otherCls.__name__ == 'FileJobStoreTest': # Remove local Files os.remove(srcUrl[7:]) make_tests(testImportSharedFile, cls, otherCls=activeTestClassesByName) @travis_test def testImportHttpFile(self): '''Test importing a file over HTTP.''' http = socketserver.TCPServer(('', 0), StubHttpRequestHandler) try: httpThread = threading.Thread(target=http.serve_forever) httpThread.start() try: assignedPort = http.server_address[1] url = 'http://localhost:%d' % assignedPort with self.jobstore_initialized.readFileStream( self.jobstore_initialized.importFile(url)) as readable: f1 = readable.read() f2 = StubHttpRequestHandler.fileContents if isinstance(f1, bytes) and not isinstance(f2, bytes): f1 = f1.decode() if isinstance(f2, bytes) and not isinstance(f1, bytes): f1 = f1.encode() self.assertEqual(f1, f2) finally: http.shutdown() httpThread.join() finally: http.server_close() @travis_test def testImportFtpFile(self): '''Test importing a file over FTP''' ftpfile = {'name': 'foo', 'content': 'foo bar baz qux'} ftp = FTPStubServer(0) ftp.run() try: ftp.add_file(**ftpfile) assignedPort = ftp.server.server_address[1] url = 'ftp://user1:passwd@localhost:%d/%s' % (assignedPort, ftpfile['name']) with self.jobstore_initialized.readFileStream(self.jobstore_initialized.importFile(url)) as readable: imported_content = readable.read() # python 2/3 string/bytestring compat if isinstance(imported_content, bytes): imported_content = imported_content.decode('utf-8') self.assertEqual(imported_content, ftpfile['content']) finally: ftp.stop() @slow def testFileDeletion(self): """ Intended to cover the batch deletion of items in the AWSJobStore, but it doesn't hurt running it on the other job stores. """ n = self._batchDeletionSize() for numFiles in (1, n - 1, n, n + 1, 2 * n): job = self.jobstore_initialized.create(self.arbitraryJob) fileIDs = [self.jobstore_initialized.getEmptyFileStoreID(job.jobStoreID, cleanup=True) for _ in range(0, numFiles)] self.jobstore_initialized.delete(job.jobStoreID) for fileID in fileIDs: # NB: the fooStream() methods return context managers self.assertRaises(NoSuchFileException, self.jobstore_initialized.readFileStream(fileID).__enter__) @slow def testMultipartUploads(self): """ This test is meant to cover multi-part uploads in the AWSJobStore but it doesn't hurt running it against the other job stores as well. """ # http://unix.stackexchange.com/questions/11946/how-big-is-the-pipe-buffer bufSize = 65536 partSize = self._partSize() self.assertEqual(partSize % bufSize, 0) job = self.jobstore_initialized.create(self.arbitraryJob) # Test file/stream ending on part boundary and within a part for partsPerFile in (1, 2.33): checksum = hashlib.md5() checksumQueue = Queue(2) # FIXME: Having a separate thread is probably overkill here def checksumThreadFn(): while True: _buf = checksumQueue.get() if _buf is None: break checksum.update(_buf) # Multipart upload from stream checksumThread = Thread(target=checksumThreadFn) checksumThread.start() try: # Should not block. On Linux, /dev/random blocks when it's running low on entropy with open('/dev/urandom', 'rb') as readable: with self.jobstore_initialized.writeFileStream(job.jobStoreID, cleanup=True) as ( writable, fileId): for i in range(int(partSize * partsPerFile / bufSize)): buf = readable.read(bufSize) checksumQueue.put(buf) writable.write(buf) finally: checksumQueue.put(None) checksumThread.join() before = checksum.hexdigest() # Verify checksum = hashlib.md5() with self.jobstore_initialized.readFileStream(fileId) as readable: while True: buf = readable.read(bufSize) if not buf: break checksum.update(buf) after = checksum.hexdigest() self.assertEqual(before, after) # Multi-part upload from file checksum = hashlib.md5() fh, path = tempfile.mkstemp() try: with os.fdopen(fh, 'wb+') as writable: with open('/dev/urandom', 'rb') as readable: for i in range(int(partSize * partsPerFile / bufSize)): buf = readable.read(bufSize) writable.write(buf) checksum.update(buf) fileId = self.jobstore_initialized.writeFile(path, job.jobStoreID, cleanup=True) finally: os.unlink(path) before = checksum.hexdigest() # Verify checksum = hashlib.md5() with self.jobstore_initialized.readFileStream(fileId) as readable: while True: buf = readable.read(bufSize) if not buf: break checksum.update(buf) after = checksum.hexdigest() self.assertEqual(before, after) self.jobstore_initialized.delete(job.jobStoreID) @travis_test def testZeroLengthFiles(self): '''Test reading and writing of empty files.''' job = self.jobstore_initialized.create(self.arbitraryJob) nullFile = self.jobstore_initialized.writeFile('/dev/null', job.jobStoreID, cleanup=True) with self.jobstore_initialized.readFileStream(nullFile) as f: assert not f.read() with self.jobstore_initialized.writeFileStream(job.jobStoreID, cleanup=True) as (f, nullStream): pass with self.jobstore_initialized.readFileStream(nullStream) as f: assert not f.read() self.jobstore_initialized.delete(job.jobStoreID) @slow def testLargeFile(self): '''Test the reading and writing of large files.''' # Write a large file. dirPath = self._createTempDir() filePath = os.path.join(dirPath, 'large') hashIn = hashlib.md5() with open(filePath, 'wb') as f: for i in range(0, 10): buf = os.urandom(self._partSize()) f.write(buf) hashIn.update(buf) # Load the file into a jobstore. job = self.jobstore_initialized.create(self.arbitraryJob) jobStoreFileID = self.jobstore_initialized.writeFile(filePath, job.jobStoreID, cleanup=True) # Remove the local file. os.unlink(filePath) # Write a local copy of the file from the jobstore. self.jobstore_initialized.readFile(jobStoreFileID, filePath) # Reread the file to confirm success. hashOut = hashlib.md5() with open(filePath, 'rb') as f: while True: buf = f.read(self._partSize()) if not buf: break hashOut.update(buf) self.assertEqual(hashIn.digest(), hashOut.digest()) def assertUrl(self, url): prefix, path = url.split(':', 1) if prefix == 'file': self.assertTrue(os.path.exists(path)) else: try: urlopen(Request(url)) except: self.fail() @slow def testCleanCache(self): # Make a bunch of jobs jobstore = self.jobstore_initialized # Create parent job rootJob = jobstore.createRootJob(self.arbitraryJob) # Create a bunch of child jobs for i in range(100): child = jobstore.create(self.arbitraryJob) rootJob.stack.append([child]) jobstore.update(rootJob) # See how long it takes to clean with no cache noCacheStart = time.time() jobstore.clean() noCacheEnd = time.time() noCacheTime = noCacheEnd - noCacheStart # Make sure we have all the jobs: root and children. self.assertEqual(len(list(jobstore.jobs())), 101) # See how long it takes to clean with cache jobCache = {jobGraph.jobStoreID: jobGraph for jobGraph in jobstore.jobs()} cacheStart = time.time() jobstore.clean(jobCache) cacheEnd = time.time() cacheTime = cacheEnd - cacheStart logger.debug("Without cache: %f, with cache: %f.", noCacheTime, cacheTime) # Running with the cache should be faster. self.assertTrue(cacheTime <= noCacheTime) # NB: the 'thread' method seems to be needed here to actually # ensure the timeout is raised, probably because the only # "live" thread doesn't hold the GIL. @travis_test @pytest.mark.timeout(45, method='thread') def testPartialReadFromStream(self): """Test whether readFileStream will deadlock on a partial read.""" job = self.jobstore_initialized.create(self.arbitraryJob) with self.jobstore_initialized.writeFileStream(job.jobStoreID, cleanup=True) as (f, fileID): # Write enough data to make sure the writer thread # will get blocked on the write. Technically anything # greater than the pipe buffer size plus the libc # buffer size (64K + 4K(?)) should trigger this bug, # but this gives us a lot of extra room just to be sure. # python 3 requires self.fileContents to be a bytestring a = 'a' if sys.version_info >= (3, 0): a = b'a' f.write(a * 300000) with self.jobstore_initialized.readFileStream(fileID) as f: self.assertEqual(f.read(1), a) # If it times out here, there's a deadlock @abstractmethod def _corruptJobStore(self): """ Deletes some part of the physical storage represented by a job store. """ raise NotImplementedError() @slow def testDestructionOfCorruptedJobStore(self): self._corruptJobStore() jobstore = self._createJobStore() jobstore.destroy() # Note that self.jobstore_initialized.destroy() is done as part of shutdown @travis_test def testDestructionIdempotence(self): # Jobstore is fully initialized self.jobstore_initialized.destroy() # Create a second instance for the same physical storage but do not .initialize() or # .resume() it. cleaner = self._createJobStore() cleaner.destroy() # And repeat self.jobstore_initialized.destroy() cleaner = self._createJobStore() cleaner.destroy() @travis_test def testEmptyFileStoreIDIsReadable(self): """Simply creates an empty fileStoreID and attempts to read from it.""" id = self.jobstore_initialized.getEmptyFileStoreID() fh, path = tempfile.mkstemp() try: self.jobstore_initialized.readFile(id, path) self.assertTrue(os.path.isfile(path)) finally: os.unlink(path) def _largeLogEntrySize(self): """ Sub-classes may want to override these in order to maximize test coverage """ return 1 * 1024 * 1024 def _batchDeletionSize(self): return 10 def _partSize(self): return 5 * 1024 * 1024 class AbstractEncryptedJobStoreTest(object): # noinspection PyAbstractClass class Test(with_metaclass(ABCMeta, AbstractJobStoreTest.Test)): """ A test of job stores that use encryption """ def setUp(self): # noinspection PyAttributeOutsideInit self.sseKeyDir = tempfile.mkdtemp() super(AbstractEncryptedJobStoreTest.Test, self).setUp() def tearDown(self): super(AbstractEncryptedJobStoreTest.Test, self).tearDown() shutil.rmtree(self.sseKeyDir) def _createConfig(self): config = super(AbstractEncryptedJobStoreTest.Test, self)._createConfig() sseKeyFile = os.path.join(self.sseKeyDir, 'keyFile') with open(sseKeyFile, 'w') as f: f.write('01234567890123456789012345678901') config.sseKey = sseKeyFile # config.attrib['sse_key'] = sseKeyFile return config def testEncrypted(self): """ Create an encrypted file. Read it in encrypted mode then try with encryption off to ensure that it fails. """ phrase = 'This file is encrypted.'.encode('utf-8') fileName = 'foo' with self.jobstore_initialized.writeSharedFileStream(fileName, isProtected=True) as f: f.write(phrase) with self.jobstore_initialized.readSharedFileStream(fileName) as f: self.assertEqual(phrase, f.read()) # disable encryption self.jobstore_initialized.config.sseKey = None try: with self.jobstore_initialized.readSharedFileStream(fileName) as f: self.assertEqual(phrase, f.read()) except AssertionError as e: self.assertEqual("Content is encrypted but no key was provided.", e.args[0]) else: self.fail("Read encryption content with encryption off.") class FileJobStoreTest(AbstractJobStoreTest.Test): def _createJobStore(self): # Make a FileJobStore with an artificially low fan out threshold, to # make sure to test fan out logic return FileJobStore(self.namePrefix, fanOut=2) def _corruptJobStore(self): assert isinstance(self.jobstore_initialized, FileJobStore) # type hint shutil.rmtree(self.jobstore_initialized.jobStoreDir) def _prepareTestFile(self, dirPath, size=None): import binascii fileName = 'testfile_%s' % uuid.uuid4() localFilePath = dirPath + fileName url = 'file://%s' % localFilePath if size is None: return url else: content = os.urandom(size) with open(localFilePath, 'wb') as writable: writable.write(content) return url, hashlib.md5(content).hexdigest() def _hashTestFile(self, url): localFilePath = FileJobStore._extractPathFromUrl(urlparse.urlparse(url)) with open(localFilePath, 'rb') as f: return hashlib.md5(f.read()).hexdigest() def _createExternalStore(self): return tempfile.mkdtemp() def _cleanUpExternalStore(self, dirPath): shutil.rmtree(dirPath) @travis_test def testPreserveFileName(self): "Check that the fileID ends with the given file name." fh, path = tempfile.mkstemp() try: os.close(fh) job = self.jobstore_initialized.create(self.arbitraryJob) fileID = self.jobstore_initialized.writeFile(path, job.jobStoreID, cleanup=True) self.assertTrue(fileID.endswith(os.path.basename(path))) finally: os.unlink(path) @needs_google class GoogleJobStoreTest(AbstractJobStoreTest.Test): projectID = os.getenv('TOIL_GOOGLE_PROJECTID') headers = {"x-goog-project-id": projectID} def _createJobStore(self): from toil.jobStores.googleJobStore import GoogleJobStore return GoogleJobStore(GoogleJobStoreTest.projectID + ":" + self.namePrefix) def _corruptJobStore(self): # The Google job store has only one resource, the bucket, so we can't corrupt it without # fully deleting it. pass def _prepareTestFile(self, bucket, size=None): from toil.jobStores.googleJobStore import GoogleJobStore fileName = 'testfile_%s' % uuid.uuid4() url = 'gs://%s/%s' % (bucket.name, fileName) if size is None: return url read_type = 'r' if USING_PYTHON2 else 'rb' with open('/dev/urandom', read_type) as readable: if USING_PYTHON2: contents = readable.read(size) else: contents = str(readable.read(size)) GoogleJobStore._writeToUrl(StringIO(contents), urlparse.urlparse(url)) return url, hashlib.md5(contents).hexdigest() def _hashTestFile(self, url): from toil.jobStores.googleJobStore import GoogleJobStore contents = GoogleJobStore._getBlobFromURL(urlparse.urlparse(url)).download_as_string() return hashlib.md5(contents).hexdigest() @googleRetry def _createExternalStore(self): from google.cloud import storage bucketName = ("import-export-test-" + str(uuid.uuid4())) storageClient = storage.Client() return storageClient.create_bucket(bucketName) @googleRetry def _cleanUpExternalStore(self, bucket): # this is copied from googleJobStore.destroy try: bucket.delete(force=True) # throws ValueError if bucket has more than 256 objects. Then we must delete manually except ValueError: bucket.delete_blobs(bucket.list_blobs) bucket.delete() @needs_aws_s3 class AWSJobStoreTest(AbstractJobStoreTest.Test): def _createJobStore(self): from toil.jobStores.aws.jobStore import AWSJobStore partSize = self._partSize() return AWSJobStore(self.awsRegion() + ':' + self.namePrefix, partSize=partSize) def _corruptJobStore(self): from toil.jobStores.aws.jobStore import AWSJobStore assert isinstance(self.jobstore_initialized, AWSJobStore) # type hinting self.jobstore_initialized.destroy() def testSDBDomainsDeletedOnFailedJobstoreBucketCreation(self): """ This test ensures that SDB domains bound to a jobstore are deleted if the jobstore bucket failed to be created. We simulate a failed jobstore bucket creation by using a bucket in a different region with the same name. """ from boto.sdb import connect_to_region from boto.s3.connection import Location, S3Connection from boto.exception import S3ResponseError from toil.jobStores.aws.jobStore import BucketLocationConflictException from toil.jobStores.aws.utils import retry_s3 externalAWSLocation = Location.USWest for testRegion in 'us-east-1', 'us-west-2': # We run this test twice, once with the default s3 server us-east-1 as the test region # and once with another server (us-west-2). The external server is always us-west-1. # This incidentally tests that the BucketLocationConflictException is thrown when using # both the default, and a non-default server. testJobStoreUUID = str(uuid.uuid4()) # Create the bucket at the external region s3 = S3Connection() for attempt in retry_s3(delays=(2, 5, 10, 30, 60), timeout=600): with attempt: bucket = s3.create_bucket('domain-test-' + testJobStoreUUID + '--files', location=externalAWSLocation) options = Job.Runner.getDefaultOptions('aws:' + testRegion + ':domain-test-' + testJobStoreUUID) options.logLevel = 'DEBUG' try: with Toil(options) as toil: pass except BucketLocationConflictException: # Catch the expected BucketLocationConflictException and ensure that the bound # domains don't exist in SDB. sdb = connect_to_region(self.awsRegion()) next_token = None allDomainNames = [] while True: domains = sdb.get_all_domains(max_domains=100, next_token=next_token) allDomainNames.extend([x.name for x in domains]) next_token = domains.next_token if next_token is None: break self.assertFalse([d for d in allDomainNames if testJobStoreUUID in d]) else: self.fail() finally: try: for attempt in retry_s3(): with attempt: s3.delete_bucket(bucket=bucket) except S3ResponseError as e: # The actual HTTP code of the error is in status. # See https://github.com/boto/boto/blob/91ba037e54ef521c379263b0ac769c66182527d7/boto/exception.py#L77-L80 # See also: https://github.com/boto/boto/blob/91ba037e54ef521c379263b0ac769c66182527d7/boto/exception.py#L154-L156 if e.status == 404: # The bucket doesn't exist; maybe a failed delete actually succeeded. pass else: raise @slow def testInlinedFiles(self): from toil.jobStores.aws.jobStore import AWSJobStore jobstore = self.jobstore_initialized for encrypted in (True, False): n = AWSJobStore.FileInfo.maxInlinedSize() sizes = (1, old_div(n, 2), n - 1, n, n + 1, 2 * n) for size in chain(sizes, islice(reversed(sizes), 1)): s = os.urandom(size) with jobstore.writeSharedFileStream('foo') as f: f.write(s) with jobstore.readSharedFileStream('foo') as f: self.assertEqual(s, f.read()) def testOverlargeJob(self): jobstore = self.jobstore_initialized jobRequirements = dict(memory=12, cores=34, disk=35, preemptable=True) overlargeJobNode = JobNode(command='overlarge', requirements=jobRequirements, jobName='test-overlarge', unitName='onJobStore', jobStoreID=None, predecessorNumber=0) # Make the pickled size of the job larger than 256K read_type = 'r' if USING_PYTHON2 else 'rb' with open("/dev/urandom", read_type) as random: if USING_PYTHON2: overlargeJobNode.jobName = random.read(512 * 1024) else: overlargeJobNode.jobName = str(random.read(512 * 1024)) overlargeJob = jobstore.create(overlargeJobNode) self.assertTrue(jobstore.exists(overlargeJob.jobStoreID)) overlargeJobDownloaded = jobstore.load(overlargeJob.jobStoreID) jobsInJobStore = [job for job in jobstore.jobs()] self.assertEqual(jobsInJobStore, [overlargeJob]) jobstore.delete(overlargeJob.jobStoreID) def _prepareTestFile(self, bucket, size=None): fileName = 'testfile_%s' % uuid.uuid4() url = 's3://%s/%s' % (bucket.name, fileName) if size is None: return url read_type = 'r' if USING_PYTHON2 else 'rb' with open('/dev/urandom', read_type) as readable: if USING_PYTHON2: bucket.new_key(fileName).set_contents_from_string(readable.read(size)) else: bucket.new_key(fileName).set_contents_from_string(str(readable.read(size))) return url, hashlib.md5(bucket.get_key(fileName).get_contents_as_string()).hexdigest() def _hashTestFile(self, url): from toil.jobStores.aws.jobStore import AWSJobStore key = AWSJobStore._getKeyForUrl(urlparse.urlparse(url), existing=True) try: contents = key.get_contents_as_string() finally: key.bucket.connection.close() return hashlib.md5(contents).hexdigest() def _createExternalStore(self): import boto.s3 from toil.jobStores.aws.utils import region_to_bucket_location s3 = boto.s3.connect_to_region(self.awsRegion()) try: return s3.create_bucket(bucket_name='import-export-test-%s' % uuid.uuid4(), location=region_to_bucket_location(self.awsRegion())) except: with panic(log=logger): s3.close() def _cleanUpExternalStore(self, bucket): try: for key in bucket.list(): key.delete() bucket.delete() finally: bucket.connection.close() def _largeLogEntrySize(self): from toil.jobStores.aws.jobStore import AWSJobStore # So we get into the else branch of reader() in uploadStream(multiPart=False): return AWSJobStore.FileInfo.maxBinarySize() * 2 def _batchDeletionSize(self): from toil.jobStores.aws.jobStore import AWSJobStore return AWSJobStore.itemsPerBatchDelete @needs_aws_s3 class InvalidAWSJobStoreTest(ToilTest): def testInvalidJobStoreName(self): from toil.jobStores.aws.jobStore import AWSJobStore self.assertRaises(ValueError, AWSJobStore, 'us-west-2:a--b') self.assertRaises(ValueError, AWSJobStore, 'us-west-2:' + ('a' * 100)) self.assertRaises(ValueError, AWSJobStore, 'us-west-2:a_b') @needs_aws_s3 @needs_encryption @slow class EncryptedAWSJobStoreTest(AWSJobStoreTest, AbstractEncryptedJobStoreTest.Test): pass class StubHttpRequestHandler(SimpleHTTPServer.SimpleHTTPRequestHandler): fileContents = 'A good programmer looks both ways before crossing a one-way street' def do_GET(self): self.send_response(200) self.send_header("Content-type", "text/plain") self.send_header("Content-length", len(self.fileContents)) self.end_headers() # python 3 requires self.fileContents to be a bytestring if sys.version_info >= (3, 0): self.fileContents = self.fileContents.encode('utf-8') self.wfile.write(self.fileContents) AbstractJobStoreTest.Test.makeImportExportTests() toil-releases-3.24.0/src/toil/test/lib/000077500000000000000000000000001362134276200176415ustar00rootroot00000000000000toil-releases-3.24.0/src/toil/test/lib/__init__.py000066400000000000000000000000001362134276200217400ustar00rootroot00000000000000toil-releases-3.24.0/src/toil/test/lib/dockerTest.py000066400000000000000000000325451362134276200223330ustar00rootroot00000000000000# Copyright (C) 2015-2018 Regents of the University of California # # 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. from __future__ import absolute_import import logging import signal import time import os import sys import uuid import docker from threading import Thread from docker.errors import ContainerError from toil.test import mkdir_p from toil.job import Job from toil.leader import FailedJobsException from toil.test import ToilTest, slow, needs_docker from toil.lib.docker import apiDockerCall, containerIsRunning, dockerKill from toil.lib.docker import FORGO, STOP, RM logger = logging.getLogger(__name__) @needs_docker class DockerTest(ToilTest): """ Tests dockerCall and ensures no containers are left around. When running tests you may optionally set the TOIL_TEST_TEMP environment variable to the path of a directory where you want temporary test files be placed. The directory will be created if it doesn't exist. The path may be relative in which case it will be assumed to be relative to the project root. If TOIL_TEST_TEMP is not defined, temporary files and directories will be created in the system's default location for such files and any temporary files or directories left over from tests will be removed automatically removed during tear down. Otherwise, left-over files will not be removed. """ def setUp(self): self.tempDir = self._createTempDir(purpose='tempDir') self.dockerTestLogLevel = 'INFO' def testDockerClean(self, disableCaching=True, detached=True, rm=True, deferParam=None): """ Run the test container that creates a file in the work dir, and sleeps for 5 minutes. Ensure that the calling job gets SIGKILLed after a minute, leaving behind the spooky/ghost/zombie container. Ensure that the container is killed on batch system shutdown (through the deferParam mechanism). """ # We need to test the behaviour of `deferParam` with `rm` and # `detached`. We do not look at the case where `rm` and `detached` are # both True. This is the truth table for the different combinations at # the end of the test. R = Running, X = Does not exist, E = Exists but # not running. # None FORGO STOP RM # rm X R X X # detached R R E X # Neither R R E X data_dir = os.path.join(self.tempDir, 'data') working_dir = os.path.join(self.tempDir, 'working') test_file = os.path.join(working_dir, 'test.txt') mkdir_p(data_dir) mkdir_p(working_dir) options = Job.Runner.getDefaultOptions(os.path.join(self.tempDir, 'jobstore')) options.logLevel = self.dockerTestLogLevel options.workDir = working_dir options.clean = 'always' options.disableCaching = disableCaching # No base64 logic since it might create a name starting with a `-`. container_name = uuid.uuid4().hex A = Job.wrapJobFn(_testDockerCleanFn, working_dir, detached, rm, deferParam, container_name) try: Job.Runner.startToil(A, options) except FailedJobsException: # The file created by spooky_container would remain in the directory # and since it was created inside the container, it would have had # uid and gid == 0 (root) which may cause problems when docker # attempts to clean up the jobstore. file_stats = os.stat(test_file) assert file_stats.st_gid != 0 assert file_stats.st_uid != 0 if (rm and (deferParam != FORGO)) or deferParam == RM: # These containers should not exist assert containerIsRunning(container_name) is None, \ 'Container was not removed.' elif deferParam == STOP: # These containers should exist but be non-running assert containerIsRunning(container_name) == False, \ 'Container was not stopped.' else: # These containers will be running assert containerIsRunning(container_name) == True, \ 'Container was not running.' client = docker.from_env(version='auto') dockerKill(container_name, client) try: os.remove(test_file) except: pass def testDockerClean_CRx_FORGO(self): self.testDockerClean(disableCaching=True, detached=False, rm=True, deferParam=FORGO) def testDockerClean_CRx_STOP(self): self.testDockerClean(disableCaching=True, detached=False, rm=True, deferParam=STOP) def testDockerClean_CRx_RM(self): self.testDockerClean(disableCaching=True, detached=False, rm=True, deferParam=RM) @slow def testDockerClean_CRx_None(self): self.testDockerClean(disableCaching=True, detached=False, rm=True, deferParam=None) @slow def testDockerClean_CxD_FORGO(self): self.testDockerClean(disableCaching=True, detached=True, rm=False, deferParam=FORGO) @slow def testDockerClean_CxD_STOP(self): self.testDockerClean(disableCaching=True, detached=True, rm=False, deferParam=STOP) @slow def testDockerClean_CxD_RM(self): self.testDockerClean(disableCaching=True, detached=True, rm=False, deferParam=RM) @slow def testDockerClean_CxD_None(self): self.testDockerClean(disableCaching=True, detached=True, rm=False, deferParam=None) @slow def testDockerClean_Cxx_FORGO(self): self.testDockerClean(disableCaching=True, detached=False, rm=False, deferParam=FORGO) @slow def testDockerClean_Cxx_STOP(self): self.testDockerClean(disableCaching=True, detached=False, rm=False, deferParam=STOP) @slow def testDockerClean_Cxx_RM(self): self.testDockerClean(disableCaching=True, detached=False, rm=False, deferParam=RM) @slow def testDockerClean_Cxx_None(self): self.testDockerClean(disableCaching=True, detached=False, rm=False, deferParam=None) @slow def testDockerClean_xRx_FORGO(self): self.testDockerClean(disableCaching=False, detached=False, rm=True, deferParam=FORGO) @slow def testDockerClean_xRx_STOP(self): self.testDockerClean(disableCaching=False, detached=False, rm=True, deferParam=STOP) @slow def testDockerClean_xRx_RM(self): self.testDockerClean(disableCaching=False, detached=False, rm=True, deferParam=RM) @slow def testDockerClean_xRx_None(self): self.testDockerClean(disableCaching=False, detached=False, rm=True, deferParam=None) @slow def testDockerClean_xxD_FORGO(self): self.testDockerClean(disableCaching=False, detached=True, rm=False, deferParam=FORGO) @slow def testDockerClean_xxD_STOP(self): self.testDockerClean(disableCaching=False, detached=True, rm=False, deferParam=STOP) @slow def testDockerClean_xxD_RM(self): self.testDockerClean(disableCaching=False, detached=True, rm=False, deferParam=RM) @slow def testDockerClean_xxD_None(self): self.testDockerClean(disableCaching=False, detached=True, rm=False, deferParam=None) @slow def testDockerClean_xxx_FORGO(self): self.testDockerClean(disableCaching=False, detached=False, rm=False, deferParam=FORGO) @slow def testDockerClean_xxx_STOP(self): self.testDockerClean(disableCaching=False, detached=False, rm=False, deferParam=STOP) @slow def testDockerClean_xxx_RM(self): self.testDockerClean(disableCaching=False, detached=False, rm=False, deferParam=RM) @slow def testDockerClean_xxx_None(self): self.testDockerClean(disableCaching=False, detached=False, rm=False, deferParam=None) def testDockerPipeChain(self, disableCaching=True): """ Test for piping API for dockerCall(). Using this API (activated when list of argument lists is given as parameters), commands a piped together into a chain. ex: parameters=[ ['printf', 'x\n y\n'], ['wc', '-l'] ] should execute: printf 'x\n y\n' | wc -l """ options = Job.Runner.getDefaultOptions(os.path.join(self.tempDir, 'jobstore')) options.logLevel = self.dockerTestLogLevel options.workDir = self.tempDir options.clean = 'always' options.caching = disableCaching A = Job.wrapJobFn(_testDockerPipeChainFn) rv = Job.Runner.startToil(A, options) logger.info('Container pipeline result: %s', repr(rv)) if sys.version_info >= (3, 0): rv = rv.decode('utf-8') assert rv.strip() == '2' def testDockerPipeChainErrorDetection(self, disableCaching=True): """ By default, executing cmd1 | cmd2 | ... | cmdN, will only return an error if cmdN fails. This can lead to all manor of errors being silently missed. This tests to make sure that the piping API for dockerCall() throws an exception if non-last commands in the chain fail. """ options = Job.Runner.getDefaultOptions(os.path.join(self.tempDir, 'jobstore')) options.logLevel = self.dockerTestLogLevel options.workDir = self.tempDir options.clean = 'always' options.caching = disableCaching A = Job.wrapJobFn(_testDockerPipeChainErrorFn) rv = Job.Runner.startToil(A, options) assert rv == True def testNonCachingDockerChain(self): self.testDockerPipeChain(disableCaching=False) def testNonCachingDockerChainErrorDetection(self): self.testDockerPipeChainErrorDetection(disableCaching=False) def _testDockerCleanFn(job, working_dir, detached=None, rm=None, deferParam=None, containerName=None): """ Test function for test docker_clean. Runs a container with given flags and then dies leaving behind a zombie container. :param toil.job.Job job: job :param working_dir: See `work_dir=` in :func:`dockerCall` :param bool rm: See `rm=` in :func:`dockerCall` :param bool detached: See `detached=` in :func:`dockerCall` :param int deferParam: See `deferParam=` in :func:`dockerCall` :param str containerName: See `container_name=` in :func:`dockerCall` """ def killSelf(): test_file = os.path.join(working_dir, 'test.txt') # Kill the worker once we are sure the docker container is started while not os.path.exists(test_file): logger.debug('Waiting on the file created by spooky_container.') time.sleep(1) # By the time we reach here, we are sure the container is running. time.sleep(1) os.kill(os.getpid(), signal.SIGKILL) t = Thread(target=killSelf) # Make it a daemon thread so that thread failure doesn't hang tests. t.daemon = True t.start() apiDockerCall(job, image='quay.io/ucsc_cgl/spooky_test', working_dir=working_dir, deferParam=deferParam, containerName=containerName, detach=detached, remove=rm, privileged=True) def _testDockerPipeChainFn(job): """Return the result of a simple pipe chain. Should be 2.""" parameters = [['printf', 'x\n y\n'], ['wc', '-l']] return apiDockerCall(job, image='ubuntu:latest', parameters=parameters, privileged=True) def _testDockerPipeChainErrorFn(job): """Return True if the command exit 1 | wc -l raises a ContainerError.""" parameters = [ ['exit', '1'], ['wc', '-l'] ] try: apiDockerCall(job, image='quay.io/ucsc_cgl/spooky_test', parameters=parameters) except ContainerError: return True return False toil-releases-3.24.0/src/toil/test/mesos/000077500000000000000000000000001362134276200202215ustar00rootroot00000000000000toil-releases-3.24.0/src/toil/test/mesos/MesosDataStructuresTest.py000066400000000000000000000062651362134276200254300ustar00rootroot00000000000000# Copyright (C) 2015-2018 Regents of the University of California # # 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. from builtins import str from builtins import range import uuid import random from toil.test import ToilTest, travis_test class DataStructuresTest(ToilTest): def _getJob(self, cores=1, memory=1000, disk=5000, preemptable=True): from toil.batchSystems.mesos import MesosShape from toil.batchSystems.mesos import ToilJob resources = MesosShape(wallTime=0, cores=cores, memory=memory, disk=disk, preemptable=preemptable) job = ToilJob(jobID=str(uuid.uuid4()), name=str(uuid.uuid4()), resources=resources, command="do nothing", userScript=None, environment=None, workerCleanupInfo=None) return job @travis_test def testJobQueue(self, testJobs=1000): """ The mesos JobQueue sorts MesosShape objects by requirement and this test ensures that that sorting is what is expected: non-preemptible jobs groups first, with priority given to large jobs. """ from toil.batchSystems.mesos import JobQueue jobQueue = JobQueue() for jobNum in range(0, testJobs): testJob = self._getJob(cores=random.choice(list(range(10))), preemptable=random.choice([True, False])) jobQueue.insertJob(testJob, testJob.resources) sortedTypes = jobQueue.sortedTypes self.assertGreaterEqual(20, len(sortedTypes)) self.assertTrue(all(sortedTypes[i] <= sortedTypes[i + 1] for i in range(len(sortedTypes) - 1))) preemptable = sortedTypes.pop(0).preemptable for jtype in sortedTypes: # all non preemptable jobTypes must be first in sorted order if preemptable: # all the rest of the jobTypes must be preemptable as well assert jtype.preemptable elif jtype.preemptable: # we have reached our first preemptable job preemptable = jtype.preemptable # make sure proper number of jobs are in queue self.assertEqual(len(jobQueue.jobIDs()), testJobs) testJob = self._getJob(cores=random.choice(list(range(10)))) jobQueue.insertJob(testJob, testJob.resources) testJobs += 1 self.assertEqual(len(jobQueue.jobIDs()), testJobs) tmpJob = None while not jobQueue.typeEmpty(testJob.resources): testJobs -= 1 tmpJob = jobQueue.nextJobOfType(testJob.resources) self.assertEqual(len(jobQueue.jobIDs()), testJobs) # Ensure FIFO self.assertIs(testJob, tmpJob) toil-releases-3.24.0/src/toil/test/mesos/__init__.py000066400000000000000000000012131362134276200223270ustar00rootroot00000000000000# Copyright (C) 2015-2016 Regents of the University of California # # 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. from __future__ import absolute_import toil-releases-3.24.0/src/toil/test/mesos/helloWorld.py000066400000000000000000000042741362134276200227150ustar00rootroot00000000000000# Copyright (C) 2015-2016 Regents of the University of California # # 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. """ A simple user script for Toil """ from __future__ import absolute_import import argparse import os from toil.common import Toil from toil.job import Job childMessage = "The child job is now running!" parentMessage = "The parent job is now running!" def hello_world(job): job.fileStore.logToMaster(parentMessage) with open('foo_bam.txt', 'w') as handle: handle.write('\nThis is a triumph...\n') # Assign FileStoreID to a given file foo_bam = job.fileStore.writeGlobalFile('foo_bam.txt') # Spawn child job.addChildJobFn(hello_world_child, foo_bam, memory=100, cores=0.5, disk="3G") def hello_world_child(job, hw): path = job.fileStore.readGlobalFile(hw) job.fileStore.logToMaster(childMessage) # NOTE: path and the udpated file are stored to /tmp # If we want to SAVE our changes to this tmp file, we must write it out. with open(path, 'r') as r: with open('bar_bam.txt', 'w') as handle: for line in r.readlines(): handle.write(line) # Assign FileStoreID to a given file # can also use: job.updateGlobalFile() given the FileStoreID instantiation. job.fileStore.writeGlobalFile('bar_bam.txt') def main(): # Boilerplate -- startToil requires options parser = argparse.ArgumentParser() Job.Runner.addToilOptions(parser) options = parser.parse_args() # Create object that contains our FileStoreIDs # Launch first toil Job i = Job.wrapJobFn(hello_world, memory=100, cores=0.5, disk="3G") with Toil(options) as toil: toil.start(i) if __name__ == '__main__': main() toil-releases-3.24.0/src/toil/test/mesos/stress.py000066400000000000000000000042331362134276200221200ustar00rootroot00000000000000# Copyright (C) 2015-2016 Regents of the University of California # # 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. from __future__ import absolute_import from builtins import range import sys from argparse import ArgumentParser from toil.job import Job def touchFile( fileStore ): with fileStore.writeGlobalFileStream() as (f, id): f.write( "This is a triumph" ) class LongTestJob(Job): def __init__(self, numJobs): Job.__init__(self, memory=100000, cores=0.01) self.numJobs = numJobs def run(self, fileStore): for i in range(0,self.numJobs): self.addChild(HelloWorldJob(i)) self.addFollowOn(LongTestFollowOn()) class LongTestFollowOn(Job): def __init__(self): Job.__init__(self, memory=1000000, cores=0.01) def run(self, fileStore): touchFile( fileStore ) class HelloWorldJob(Job): def __init__(self,i): Job.__init__(self, memory=100000, cores=0.01) self.i=i def run(self, fileStore): touchFile( fileStore ) self.addFollowOn(HelloWorldFollowOn(self.i)) class HelloWorldFollowOn(Job): def __init__(self,i): Job.__init__(self, memory=200000, cores=0.01) self.i = i def run(self, fileStore): touchFile( fileStore) def main(numJobs): # Boilerplate -- startToil requires options parser = ArgumentParser() Job.Runner.addToilOptions(parser) options = parser.parse_args( args=['./toilTest'] ) options.batchSystem="mesos" options.mesosMasterAddress="localhost:5050" # Launch first toil Job i = LongTestJob( numJobs ) Job.Runner.startToil(i, options ) if __name__=="__main__": main(numJobs=5) toil-releases-3.24.0/src/toil/test/provisioners/000077500000000000000000000000001362134276200216355ustar00rootroot00000000000000toil-releases-3.24.0/src/toil/test/provisioners/__init__.py000066400000000000000000000012131362134276200237430ustar00rootroot00000000000000# Copyright (C) 2015-2016 Regents of the University of California # # 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. from __future__ import absolute_import toil-releases-3.24.0/src/toil/test/provisioners/aws/000077500000000000000000000000001362134276200224275ustar00rootroot00000000000000toil-releases-3.24.0/src/toil/test/provisioners/aws/__init__.py000066400000000000000000000011271362134276200245410ustar00rootroot00000000000000# Copyright (C) 2015 UCSC Computational Genomics Lab # # 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. toil-releases-3.24.0/src/toil/test/provisioners/aws/awsProvisionerTest.py000066400000000000000000000403321362134276200266750ustar00rootroot00000000000000# Copyright (C) 2015 UCSC Computational Genomics Lab # # 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. import logging import os import time from abc import abstractmethod from inspect import getsource from textwrap import dedent from uuid import uuid4 import pytest from builtins import next from builtins import range from builtins import str from toil import subprocess from toil.provisioners import clusterFactory from toil.version import exactPython from toil.test import needs_aws_ec2, integrative, ToilTest, needs_appliance, timeLimit, slow log = logging.getLogger(__name__) @needs_aws_ec2 @integrative @needs_appliance @slow class AbstractAWSAutoscaleTest(ToilTest): def sshUtil(self, command): subprocess.check_call(['toil', 'ssh-cluster', '--insecure', '-p=aws', self.clusterName] + command) def rsyncUtil(self, src, dest): subprocess.check_call(['toil', 'rsync-cluster', '--insecure', '-p=aws', self.clusterName] + [src, dest]) def destroyClusterUtil(self): subprocess.check_call(['toil', 'destroy-cluster', '-p=aws', self.clusterName]) def createClusterUtil(self, args=None): args = [] if args is None else args subprocess.check_call(['toil', 'launch-cluster', '-p=aws', '-z=us-west-2a', '--keyPairName=%s' % self.keyName, '--leaderNodeType=t2.medium', self.clusterName] + args) def cleanJobStoreUtil(self): subprocess.check_call(['toil', 'clean', self.jobStore]) def __init__(self, methodName): super(AbstractAWSAutoscaleTest, self).__init__(methodName=methodName) self.keyName = os.getenv('TOIL_AWS_KEYNAME') self.instanceTypes = ["m3.large"] self.clusterName = 'aws-provisioner-test-' + str(uuid4()) self.numWorkers = ['2'] self.numSamples = 2 self.spotBid = 0.15 def setUp(self): super(AbstractAWSAutoscaleTest, self).setUp() def tearDown(self): super(AbstractAWSAutoscaleTest, self).tearDown() self.destroyClusterUtil() self.cleanJobStoreUtil() def getMatchingRoles(self): return list(self.cluster._ctx.local_roles()) def launchCluster(self): self.createClusterUtil() def getRootVolID(self): instances = self.cluster._getNodesInCluster(nodeType=None, both=True) instances.sort(key=lambda x: x.launch_time) leader = instances[0] # assume leader was launched first from boto.ec2.blockdevicemapping import BlockDeviceType rootBlockDevice = leader.block_device_mapping["/dev/xvda"] assert isinstance(rootBlockDevice, BlockDeviceType) return rootBlockDevice.volume_id @abstractmethod def _getScript(self): """Download the test script needed by the inheriting unit test class.""" raise NotImplementedError() @abstractmethod def _runScript(self, toilOptions): """ Modify the provided Toil options to suit the test Toil script, then run the script with those arguments. :param toilOptions: List of Toil command line arguments. This list may need to be modified to suit the test script's requirements. """ raise NotImplementedError() def _test(self, preemptableJobs=False): """Does the work of the testing. Many features' tests are thrown in here in no particular order.""" self.launchCluster() # get the leader so we know the IP address - we don't need to wait since create cluster # already insures the leader is running self.cluster = clusterFactory(provisioner='aws', clusterName=self.clusterName) self.leader = self.cluster.getLeader() assert len(self.getMatchingRoles()) == 1 # --never-download prevents silent upgrades to pip, wheel and setuptools venv_command = ['virtualenv', '--system-site-packages', '--python', exactPython, '--never-download', '/home/venv'] self.sshUtil(venv_command) upgrade_command = ['/home/venv/bin/pip', 'install', 'setuptools==28.7.1'] self.sshUtil(upgrade_command) yaml_command = ['/home/venv/bin/pip', 'install', 'pyyaml==3.12'] self.sshUtil(yaml_command) self._getScript() toilOptions = [self.jobStore, '--batchSystem=mesos', '--workDir=/var/lib/toil', '--clean=always', '--retryCount=2', '--clusterStats=/home/', '--logDebug', '--logFile=/home/sort.log', '--provisioner=aws'] toilOptions.extend(['--nodeTypes=' + ",".join(self.instanceTypes), '--maxNodes=%s' % ",".join(self.numWorkers)]) if preemptableJobs: toilOptions.extend(['--defaultPreemptable']) self._runScript(toilOptions) assert len(self.getMatchingRoles()) == 1 # check stats self.sshUtil(['/home/venv/bin/python', '-c', 'import json; import os; ' 'json.load(open("/home/" + [f for f in os.listdir("/home/") if f.endswith(".json")].pop()))']) from boto.exception import EC2ResponseError volumeID = self.getRootVolID() self.cluster.destroyCluster() for attempt in range(6): # https://github.com/BD2KGenomics/toil/issues/1567 # retry this for up to 1 minute until the volume disappears try: self.cluster._ctx.ec2.get_all_volumes(volume_ids=[volumeID]) time.sleep(10) except EC2ResponseError as e: if e.status == 400 and 'InvalidVolume.NotFound' in e.code: break else: raise else: self.fail('Volume with ID %s was not cleaned up properly' % volumeID) assert len(self.getMatchingRoles()) == 0 @pytest.mark.timeout(1800) class AWSAutoscaleTest(AbstractAWSAutoscaleTest): def __init__(self, name): super(AWSAutoscaleTest, self).__init__(name) self.clusterName = 'provisioner-test-' + str(uuid4()) self.requestedLeaderStorage = 80 def setUp(self): super(AWSAutoscaleTest, self).setUp() self.jobStore = 'aws:%s:autoscale-%s' % (self.awsRegion(), uuid4()) def _getScript(self): fileToSort = os.path.join(os.getcwd(), str(uuid4())) with open(fileToSort, 'w') as f: # Fixme: making this file larger causes the test to hang f.write('01234567890123456789012345678901') self.rsyncUtil(os.path.join(self._projectRootPath(), 'src/toil/test/sort/sort.py'), ':/home/sort.py') self.rsyncUtil(fileToSort, ':/home/sortFile') os.unlink(fileToSort) def _runScript(self, toilOptions): runCommand = ['/home/venv/bin/python', '/home/sort.py', '--fileToSort=/home/sortFile', '--sseKey=/home/sortFile'] runCommand.extend(toilOptions) self.sshUtil(runCommand) def launchCluster(self): # add arguments to test that we can specify leader storage self.createClusterUtil(args=['--leaderStorage', str(self.requestedLeaderStorage)]) def getRootVolID(self): """ Adds in test to check that EBS volume is build with adequate size. Otherwise is functionally equivalent to parent. :return: volumeID """ volumeID = super(AWSAutoscaleTest, self).getRootVolID() rootVolume = self.cluster._ctx.ec2.get_all_volumes(volume_ids=[volumeID])[0] # test that the leader is given adequate storage self.assertGreaterEqual(rootVolume.size, self.requestedLeaderStorage) return volumeID @integrative @needs_aws_ec2 def testAutoScale(self): self.instanceTypes = ["m3.large"] self.numWorkers = ['2'] self._test() @integrative @needs_aws_ec2 def testSpotAutoScale(self): self.instanceTypes = ["m3.large:%f" % self.spotBid] self.numWorkers = ['2'] self._test(preemptableJobs=True) @pytest.mark.timeout(1200) class AWSStaticAutoscaleTest(AWSAutoscaleTest): """ Runs the tests on a statically provisioned cluster with autoscaling enabled. """ def __init__(self, name): super(AWSStaticAutoscaleTest, self).__init__(name) self.requestedNodeStorage = 20 def launchCluster(self): from toil.lib.ec2 import wait_instances_running from boto.ec2.blockdevicemapping import BlockDeviceType self.createClusterUtil(args=['--leaderStorage', str(self.requestedLeaderStorage), '--nodeTypes', ",".join(self.instanceTypes), '-w', ",".join(self.numWorkers), '--nodeStorage', str(self.requestedLeaderStorage)]) self.cluster = clusterFactory(provisioner='aws', clusterName=self.clusterName) nodes = self.cluster._getNodesInCluster(both=True) nodes.sort(key=lambda x: x.launch_time) # assuming that leader is first workers = nodes[1:] # test that two worker nodes were created self.assertEqual(2, len(workers)) # test that workers have expected storage size # just use the first worker worker = workers[0] worker = next(wait_instances_running(self.cluster._ctx.ec2, [worker])) rootBlockDevice = worker.block_device_mapping["/dev/xvda"] self.assertTrue(isinstance(rootBlockDevice, BlockDeviceType)) rootVolume = self.cluster._ctx.ec2.get_all_volumes(volume_ids=[rootBlockDevice.volume_id])[0] self.assertGreaterEqual(rootVolume.size, self.requestedNodeStorage) def _runScript(self, toilOptions): runCommand = ['/home/venv/bin/python', '/home/sort.py', '--fileToSort=/home/sortFile'] runCommand.extend(toilOptions) self.sshUtil(runCommand) @pytest.mark.timeout(1200) class AWSAutoscaleTestMultipleNodeTypes(AbstractAWSAutoscaleTest): def __init__(self, name): super(AWSAutoscaleTestMultipleNodeTypes, self).__init__(name) self.clusterName = 'provisioner-test-' + str(uuid4()) def setUp(self): super(AWSAutoscaleTestMultipleNodeTypes, self).setUp() self.jobStore = 'aws:%s:autoscale-%s' % (self.awsRegion(), uuid4()) def _getScript(self): sseKeyFile = os.path.join(os.getcwd(), 'keyFile') with open(sseKeyFile, 'w') as f: f.write('01234567890123456789012345678901') self.rsyncUtil(os.path.join(self._projectRootPath(), 'src/toil/test/sort/sort.py'), ':/home/sort.py') self.rsyncUtil(sseKeyFile, ':/home/keyFile') os.unlink(sseKeyFile) def _runScript(self, toilOptions): #Set memory requirements so that sort jobs can be run # on small instances, but merge jobs must be run on large # instances runCommand = ['/home/venv/bin/python', '/home/sort.py', '--fileToSort=/home/s3am/bin/asadmin', '--sortMemory=0.6G', '--mergeMemory=3.0G'] runCommand.extend(toilOptions) runCommand.append('--sseKey=/home/keyFile') self.sshUtil(runCommand) @integrative @needs_aws_ec2 def testAutoScale(self): self.instanceTypes = ["t2.small", "m3.large"] self.numWorkers = ['2', '1'] self._test() @pytest.mark.timeout(1200) class AWSRestartTest(AbstractAWSAutoscaleTest): """ This test insures autoscaling works on a restarted Toil run """ def __init__(self, name): super(AWSRestartTest, self).__init__(name) self.clusterName = 'restart-test-' + str(uuid4()) def setUp(self): super(AWSRestartTest, self).setUp() self.instanceTypes = ['t2.micro'] self.numWorkers = ['1'] self.scriptName = "/home/restartScript.py" self.jobStore = 'aws:%s:restart-%s' % (self.awsRegion(), uuid4()) def _getScript(self): def restartScript(): from toil.job import Job import argparse import os def f0(job): if 'FAIL' in os.environ: raise RuntimeError('failed on purpose') if __name__ == '__main__': parser = argparse.ArgumentParser() Job.Runner.addToilOptions(parser) options = parser.parse_args() rootJob = Job.wrapJobFn(f0, cores=0.5, memory='50 M', disk='50 M') Job.Runner.startToil(rootJob, options) script = dedent('\n'.join(getsource(restartScript).split('\n')[1:])) # use appliance ssh method instead of sshutil so we can specify input param cluster = clusterFactory(provisioner='aws', clusterName=self.clusterName) leader = cluster.getLeader() leader.sshAppliance('tee', self.scriptName, input=script) def _runScript(self, toilOptions): # clean = onSuccess disallowedOptions = ['--clean=always', '--retryCount=2'] newOptions = [option for option in toilOptions if option not in disallowedOptions] try: # include a default memory - on restart the minimum memory requirement is the default, usually 2 GB command = ['/home/venv/bin/python', self.scriptName, '-e', 'FAIL=true', '--defaultMemory=50000000'] command.extend(newOptions) self.sshUtil(command) except subprocess.CalledProcessError: pass else: self.fail('Command succeeded when we expected failure') with timeLimit(600): command = ['/home/venv/bin/python', self.scriptName, '--restart', '--defaultMemory=50000000'] command.extend(toilOptions) self.sshUtil(command) @integrative def testAutoScaledCluster(self): self._test() @pytest.mark.timeout(1200) class PreemptableDeficitCompensationTest(AbstractAWSAutoscaleTest): def __init__(self, name): super(PreemptableDeficitCompensationTest, self).__init__(name) self.clusterName = 'deficit-test-' + str(uuid4()) def setUp(self): super(PreemptableDeficitCompensationTest, self).setUp() self.instanceTypes = ['m3.large:0.01', "m3.large"] # instance needs to be available on the spot market self.numWorkers = ['1','1'] self.jobStore = 'aws:%s:deficit-%s' % (self.awsRegion(), uuid4()) def test(self): self._test(preemptableJobs=True) def _getScript(self): def userScript(): from toil.job import Job from toil.common import Toil # Because this is the only job in the pipeline and because it is preemptable, # there will be no non-preemptable jobs. The non-preemptable scaler will therefore # not request any nodes initially. And since we made it impossible for the # preemptable scaler to allocate any nodes (using an abnormally low spot bid), # we will observe a deficit of preemptable nodes that the non-preemptable scaler will # compensate for by spinning up non-preemptable nodes instead. # def job(job, disk='10M', cores=1, memory='10M', preemptable=True): pass if __name__ == '__main__': options = Job.Runner.getDefaultArgumentParser().parse_args() with Toil(options) as toil: if toil.config.restart: toil.restart() else: toil.start(Job.wrapJobFn(job)) script = dedent('\n'.join(getsource(userScript).split('\n')[1:])) # use appliance ssh method instead of sshutil so we can specify input param cluster = clusterFactory(provisioner='aws', clusterName=self.clusterName) leader = cluster.getLeader() leader.sshAppliance('tee', '/home/userScript.py', input=script) def _runScript(self, toilOptions): toilOptions.extend(['--preemptableCompensation=1.0']) command = ['/home/venv/bin/python', '/home/userScript.py'] command.extend(toilOptions) self.sshUtil(command) toil-releases-3.24.0/src/toil/test/provisioners/clusterScalerTest.py000066400000000000000000001131001362134276200256560ustar00rootroot00000000000000# Copyright (C) 2015-2018 Regents of the University of California # # 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. from __future__ import absolute_import from __future__ import division from builtins import map from builtins import object from builtins import range from past.utils import old_div import time import datetime from contextlib import contextmanager from threading import Thread, Event import logging import random import types import uuid from collections import defaultdict from mock import MagicMock # Python 3 compatibility imports from six.moves.queue import Empty, Queue from six import iteritems from toil.job import JobNode, Job from toil.lib.humanize import human2bytes as h2b from toil.test import ToilTest, slow, travis_test from toil.batchSystems.abstractBatchSystem import (AbstractScalableBatchSystem, NodeInfo, AbstractBatchSystem) from toil.provisioners.node import Node from toil.provisioners.abstractProvisioner import AbstractProvisioner, Shape from toil.provisioners.clusterScaler import (ClusterScaler, ScalerThread, BinPackedFit, NodeReservation) from toil.common import Config, defaultTargetTime logger = logging.getLogger(__name__) # simplified c4.8xlarge (preemptable) c4_8xlarge_preemptable = Shape(wallTime=3600, memory=h2b('60G'), cores=36, disk=h2b('100G'), preemptable=True) # simplified c4.8xlarge (non-preemptable) c4_8xlarge = Shape(wallTime=3600, memory=h2b('60G'), cores=36, disk=h2b('100G'), preemptable=False) # simplified r3.8xlarge (non-preemptable) r3_8xlarge = Shape(wallTime=3600, memory=h2b('260G'), cores=32, disk=h2b('600G'), preemptable=False) # simplified t2.micro (non-preemptable) t2_micro = Shape(wallTime=3600, memory=h2b('1G'), cores=1, disk=h2b('8G'), preemptable=False) class BinPackingTest(ToilTest): def setUp(self): self.nodeShapes = [c4_8xlarge_preemptable, r3_8xlarge] self.bpf = BinPackedFit(self.nodeShapes) @travis_test def testPackingOneShape(self): """Pack one shape and check that the resulting reservations look sane.""" self.bpf.nodeReservations[c4_8xlarge_preemptable] = [NodeReservation(c4_8xlarge_preemptable)] self.bpf.addJobShape(Shape(wallTime=1000, cores=2, memory=h2b('1G'), disk=h2b('2G'), preemptable=True)) self.assertEqual(self.bpf.nodeReservations[r3_8xlarge], []) self.assertEqual([x.shapes() for x in self.bpf.nodeReservations[c4_8xlarge_preemptable]], [[Shape(wallTime=1000, memory=h2b('59G'), cores=34, disk=h2b('98G'), preemptable=True), Shape(wallTime=2600, memory=h2b('60G'), cores=36, disk=h2b('100G'), preemptable=True)]]) @travis_test def testSorting(self): """ Test that sorting is correct: preemptable, then memory, then cores, then disk, then wallTime. """ shapeList = [c4_8xlarge_preemptable, r3_8xlarge, c4_8xlarge, c4_8xlarge, t2_micro, t2_micro, c4_8xlarge, r3_8xlarge, r3_8xlarge, t2_micro] shapeList.sort() assert shapeList == [c4_8xlarge_preemptable, t2_micro, t2_micro, t2_micro, c4_8xlarge, c4_8xlarge, c4_8xlarge, r3_8xlarge, r3_8xlarge, r3_8xlarge] @travis_test def testAddingInitialNode(self): """Pack one shape when no nodes are available and confirm that we fit one node properly.""" self.bpf.addJobShape(Shape(wallTime=1000, cores=2, memory=h2b('1G'), disk=h2b('2G'), preemptable=True)) self.assertEqual([x.shapes() for x in self.bpf.nodeReservations[c4_8xlarge_preemptable]], [[Shape(wallTime=1000, memory=h2b('59G'), cores=34, disk=h2b('98G'), preemptable=True), Shape(wallTime=2600, memory=h2b('60G'), cores=36, disk=h2b('100G'), preemptable=True)]]) @travis_test def testLowTargetTime(self): """ Test that a low targetTime (0) parallelizes jobs aggressively (1000 queued jobs require 1000 nodes). Ideally, low targetTime means: Start quickly and maximize parallelization after the cpu/disk/mem have been packed. Disk/cpu/mem packing is prioritized first, so we set job resource reqs so that each t2.micro (1 cpu/8G disk/1G RAM) can only run one job at a time with its resources. Each job is parametrized to take 300 seconds, so (the minimum of) 1 of them should fit into each node's 0 second window, so we expect 1000 nodes. """ allocation = self.run1000JobsOnMicros(jobCores=1, jobMem=h2b('1G'), jobDisk=h2b('1G'), jobTime=300, globalTargetTime=0) self.assertEqual(allocation, {t2_micro: 1000}) @travis_test def testHighTargetTime(self): """ Test that a high targetTime (3600 seconds) maximizes packing within the targetTime. Ideally, high targetTime means: Maximize packing within the targetTime after the cpu/disk/mem have been packed. Disk/cpu/mem packing is prioritized first, so we set job resource reqs so that each t2.micro (1 cpu/8G disk/1G RAM) can only run one job at a time with its resources. Each job is parametrized to take 300 seconds, so 12 of them should fit into each node's 3600 second window. 1000/12 = 83.33, so we expect 84 nodes. """ allocation = self.run1000JobsOnMicros(jobCores=1, jobMem=h2b('1G'), jobDisk=h2b('1G'), jobTime=300, globalTargetTime=3600) self.assertEqual(allocation, {t2_micro: 84}) @travis_test def testZeroResourceJobs(self): """ Test that jobs requiring zero cpu/disk/mem pack first, regardless of targetTime. Disk/cpu/mem packing is prioritized first, so we set job resource reqs so that each t2.micro (1 cpu/8G disk/1G RAM) can run a seemingly infinite number of jobs with its resources. Since all jobs should pack cpu/disk/mem-wise on a t2.micro, we expect only one t2.micro to be provisioned. If we raise this, as in testLowTargetTime, it will launch 1000 t2.micros. """ allocation = self.run1000JobsOnMicros(jobCores=0, jobMem=0, jobDisk=0, jobTime=300, globalTargetTime=0) self.assertEqual(allocation, {t2_micro: 1}) @travis_test def testLongRunningJobs(self): """ Test that jobs with long run times (especially service jobs) are aggressively parallelized. This is important, because services are one case where the degree of parallelization really, really matters. If you have multiple services, they may all need to be running simultaneously before any real work can be done. Despite setting globalTargetTime=3600, this should launch 1000 t2.micros because each job's estimated runtime (30000 seconds) extends well beyond 3600 seconds. """ allocation = self.run1000JobsOnMicros(jobCores=1, jobMem=h2b('1G'), jobDisk=h2b('1G'), jobTime=30000, globalTargetTime=3600) self.assertEqual(allocation, {t2_micro: 1000}) def run1000JobsOnMicros(self, jobCores, jobMem, jobDisk, jobTime, globalTargetTime): """Test packing 1000 jobs on t2.micros. Depending on the targetTime and resources, these should pack differently. """ nodeShapes = [t2_micro] bpf = BinPackedFit(nodeShapes, targetTime=globalTargetTime) for _ in range(1000): bpf.addJobShape(Shape(wallTime=jobTime, memory=jobMem, cores=jobCores, disk=jobDisk, preemptable=False)) return bpf.getRequiredNodes() @travis_test def testPathologicalCase(self): """Test a pathological case where only one node can be requested to fit months' worth of jobs. If the reservation is extended to fit a long job, and the bin-packer naively searches through all the reservation slices to find the first slice that fits, it will happily assign the first slot that fits the job, even if that slot occurs days in the future. """ # Add one job that partially fills an r3.8xlarge for 1000 hours self.bpf.addJobShape(Shape(wallTime=3600000, memory=h2b('10G'), cores=0, disk=h2b('10G'), preemptable=False)) for _ in range(500): # Add 500 CPU-hours worth of jobs that fill an r3.8xlarge self.bpf.addJobShape(Shape(wallTime=3600, memory=h2b('26G'), cores=32, disk=h2b('60G'), preemptable=False)) # Hopefully we didn't assign just one node to cover all those jobs. self.assertNotEqual(self.bpf.getRequiredNodes(), {r3_8xlarge: 1, c4_8xlarge_preemptable: 0}) @travis_test def testJobTooLargeForAllNodes(self): """ If a job is too large for all node types, the scaler should print a warning, but definitely not crash. """ # Takes more RAM than an r3.8xlarge largerThanR3 = Shape(wallTime=3600, memory=h2b('360G'), cores=32, disk=h2b('600G'), preemptable=False) self.bpf.addJobShape(largerThanR3) # If we got here we didn't crash. class ClusterScalerTest(ToilTest): def setUp(self): super(ClusterScalerTest, self).setUp() self.config = Config() self.config.targetTime = 1800 self.config.nodeTypes = ['r3.8xlarge', 'c4.8xlarge:0.6'] # Set up a stub provisioner with some nodeTypes and nodeShapes. try: # In Python 3 we can use a SimpleNamespace as a mock provisioner self.provisioner = types.SimpleNamespace() except: # In Python 2 we should just be able to tack fields onto an object. # But this has been known to produce: # AttributeError: 'newobject' object has no attribute 'nodeTypes' # So we use an Argparse Namespace instead. import argparse self.provisioner = argparse.Namespace() setattr(self.provisioner, 'nodeTypes', ['r3.8xlarge', 'c4.8xlarge']) setattr(self.provisioner, 'nodeShapes', [r3_8xlarge, c4_8xlarge_preemptable]) setattr(self.provisioner, 'setStaticNodes', lambda _, __: None) setattr(self.provisioner, 'retryPredicate', lambda _: False) self.leader = MockBatchSystemAndProvisioner(self.config, 1) @travis_test def testRounding(self): """ Test to make sure the ClusterScaler's rounding rounds properly. """ # Get a ClusterScaler self.config.targetTime = 1 self.config.betaInertia = 0.0 self.config.maxNodes = [2, 3] scaler = ClusterScaler(self.provisioner, self.leader, self.config) # Exact integers round to themselves self.assertEqual(scaler._round(0.0), 0) self.assertEqual(scaler._round(1.0), 1) self.assertEqual(scaler._round(-1.0), -1) self.assertEqual(scaler._round(123456789101112.13), 123456789101112) # Decimals other than X.5 round to the side they are closer to self.assertEqual(scaler._round(1E-10), 0) self.assertEqual(scaler._round(0.5 + 1E-15), 1) self.assertEqual(scaler._round(-0.9), -1) self.assertEqual(scaler._round(-0.4), 0) # Decimals at exactly X.5 round away from 0 self.assertEqual(scaler._round(0.5), 1) self.assertEqual(scaler._round(-0.5), -1) self.assertEqual(scaler._round(2.5), 3) self.assertEqual(scaler._round(-2.5), -3) self.assertEqual(scaler._round(15.5), 16) self.assertEqual(scaler._round(-15.5), -16) self.assertEqual(scaler._round(123456789101112.5), 123456789101113) @travis_test def testMaxNodes(self): """ Set the scaler to be very aggressive, give it a ton of jobs, and make sure it doesn't go over maxNodes. """ self.config.targetTime = 1 self.config.betaInertia = 0.0 self.config.maxNodes = [2, 3] scaler = ClusterScaler(self.provisioner, self.leader, self.config) jobShapes = [Shape(wallTime=3600, cores=2, memory=h2b('1G'), disk=h2b('2G'), preemptable=True)] * 1000 jobShapes.extend([Shape(wallTime=3600, cores=2, memory=h2b('1G'), disk=h2b('2G'), preemptable=False)] * 1000) estimatedNodeCounts = scaler.getEstimatedNodeCounts(jobShapes, defaultdict(int)) self.assertEqual(estimatedNodeCounts[r3_8xlarge], 2) self.assertEqual(estimatedNodeCounts[c4_8xlarge_preemptable], 3) @travis_test def testMinNodes(self): """ Without any jobs queued, the scaler should still estimate "minNodes" nodes. """ self.config.betaInertia = 0.0 self.config.minNodes = [2, 3] scaler = ClusterScaler(self.provisioner, self.leader, self.config) jobShapes = [] estimatedNodeCounts = scaler.getEstimatedNodeCounts(jobShapes, defaultdict(int)) self.assertEqual(estimatedNodeCounts[r3_8xlarge], 2) self.assertEqual(estimatedNodeCounts[c4_8xlarge_preemptable], 3) @travis_test def testPreemptableDeficitResponse(self): """ When a preemptable deficit was detected by a previous run of the loop, the scaler should add non-preemptable nodes to compensate in proportion to preemptableCompensation. """ self.config.targetTime = 1 self.config.betaInertia = 0.0 self.config.maxNodes = [10, 10] # This should mean that one non-preemptable node is launched # for every two preemptable nodes "missing". self.config.preemptableCompensation = 0.5 # In this case, we want to explicitly set up the config so # that we can have preemptable and non-preemptable nodes of # the same type. That is the only situation where # preemptableCompensation applies. self.config.nodeTypes = ['c4.8xlarge:0.6', 'c4.8xlarge'] self.provisioner.nodeTypes = ['c4.8xlarge', 'c4.8xlarge'] self.provisioner.nodeShapes = [c4_8xlarge_preemptable, c4_8xlarge] scaler = ClusterScaler(self.provisioner, self.leader, self.config) # Simulate a situation where a previous run caused a # "deficit" of 5 preemptable nodes (e.g. a spot bid was lost) scaler.preemptableNodeDeficit['c4.8xlarge'] = 5 # Add a bunch of preemptable jobs (so the bin-packing # estimate for the non-preemptable node should still be 0) jobShapes = [Shape(wallTime=3600, cores=2, memory=h2b('1G'), disk=h2b('2G'), preemptable=True)] * 1000 estimatedNodeCounts = scaler.getEstimatedNodeCounts(jobShapes, defaultdict(int)) # We don't care about the estimated size of the preemptable # nodes. All we want to know is if we responded to the deficit # properly: 0.5 * 5 (preemptableCompensation * the deficit) = 3 (rounded up). self.assertEqual(estimatedNodeCounts[self.provisioner.nodeShapes[1]], 3) @travis_test def testPreemptableDeficitIsSet(self): """ Make sure that updateClusterSize sets the preemptable deficit if it can't launch preemptable nodes properly. That way, the deficit can be communicated to the next run of estimateNodeCount. """ # Mock out addNodes. We want to pretend it had trouble # launching all 5 nodes, and could only launch 3. self.provisioner.addNodes = MagicMock(return_value=3) # Pretend there are no nodes in the cluster right now self.provisioner.getProvisionedWorkers = MagicMock(return_value=[]) # In this case, we want to explicitly set up the config so # that we can have preemptable and non-preemptable nodes of # the same type. That is the only situation where # preemptableCompensation applies. self.config.nodeTypes = ['c4.8xlarge:0.6', 'c4.8xlarge'] self.provisioner.nodeTypes = ['c4.8xlarge', 'c4.8xlarge'] self.provisioner.nodeShapes = [c4_8xlarge_preemptable, c4_8xlarge] scaler = ClusterScaler(self.provisioner, self.leader, self.config) estimatedNodeCounts = {c4_8xlarge_preemptable: 5, c4_8xlarge: 0} scaler.updateClusterSize(estimatedNodeCounts) self.assertEqual(scaler.preemptableNodeDeficit['c4.8xlarge'], 2) self.provisioner.addNodes.assert_called_once() # OK, now pretend this is a while later, and actually launched # the nodes properly. The deficit should disappear self.provisioner.addNodes = MagicMock(return_value=5) scaler.updateClusterSize(estimatedNodeCounts) self.assertEqual(scaler.preemptableNodeDeficit['c4.8xlarge'], 0) @travis_test def testNoLaunchingIfDeltaAlreadyMet(self): """ Check that the scaler doesn't try to launch "0" more instances if the delta was able to be met by unignoring nodes. """ # We have only one node type for simplicity self.provisioner.nodeTypes = ['c4.8xlarge'] self.provisioner.nodeShapes = [c4_8xlarge] scaler = ClusterScaler(self.provisioner, self.leader, self.config) # Pretend there is one ignored worker in the cluster self.provisioner.getProvisionedWorkers = MagicMock( return_value=[Node('127.0.0.1', '127.0.0.1', 'testNode', datetime.datetime.now().isoformat(), nodeType='c4.8xlarge', preemptable=True)]) scaler.ignoredNodes.add('127.0.0.1') # Exercise the updateClusterSize logic self.provisioner.addNodes = MagicMock() scaler.updateClusterSize({c4_8xlarge: 1}) self.assertFalse(self.provisioner.addNodes.called, "addNodes was called when no new nodes were needed") self.assertEqual(len(scaler.ignoredNodes), 0, "The scaler didn't unignore an ignored node when " "scaling up") @travis_test def testBetaInertia(self): # This is really high, but makes things easy to calculate. self.config.betaInertia = 0.5 scaler = ClusterScaler(self.provisioner, self.leader, self.config) # OK, smoothing things this much should get us 50% of the way to 100. self.assertEqual(scaler.smoothEstimate(c4_8xlarge_preemptable, 100), 50) # Now we should be at 75%. self.assertEqual(scaler.smoothEstimate(c4_8xlarge_preemptable, 100), 75) # We should eventually converge on our estimate as long as betaInertia is below 1. for _ in range(1000): scaler.smoothEstimate(c4_8xlarge_preemptable, 100) self.assertEqual(scaler.smoothEstimate(c4_8xlarge_preemptable, 100), 100) class ScalerThreadTest(ToilTest): def _testClusterScaling(self, config, numJobs, numPreemptableJobs, jobShape): """ Test the ClusterScaler class with different patterns of job creation. Tests ascertain that autoscaling occurs and that all the jobs are run. """ # First do simple test of creating 100 preemptable and non-premptable jobs and check the # jobs are completed okay, then print the amount of worker time expended and the total # number of worker nodes used. mock = MockBatchSystemAndProvisioner(config, secondsPerJob=2.0) mock.start() clusterScaler = ScalerThread(mock, mock, config) clusterScaler.start() try: # Add 100 jobs to complete list(map(lambda x: mock.addJob(jobShape=jobShape), list(range(numJobs)))) list(map(lambda x: mock.addJob(jobShape=jobShape, preemptable=True), list(range(numPreemptableJobs)))) # Add some completed jobs for preemptable in (True, False): if preemptable and numPreemptableJobs > 0 or not preemptable and numJobs > 0: # Add 1000 random jobs for _ in range(1000): x = mock.getNodeShape(nodeType=jobShape) iJ = JobNode(jobStoreID=1, requirements=dict( memory=random.choice(list(range(1, x.memory))), cores=random.choice(list(range(1, x.cores))), disk=random.choice(list(range(1, x.disk))), preemptable=preemptable), command=None, jobName='testClusterScaling', unitName='') clusterScaler.addCompletedJob(iJ, random.choice(list(range(1, x.wallTime)))) startTime = time.time() # Wait while the cluster processes the jobs while (mock.getNumberOfJobsIssued(preemptable=False) > 0 or mock.getNumberOfJobsIssued(preemptable=True) > 0 or mock.getNumberOfNodes() > 0 or mock.getNumberOfNodes(preemptable=True) > 0): logger.debug("Running, non-preemptable queue size: %s, non-preemptable workers: %s, " "preemptable queue size: %s, preemptable workers: %s" % (mock.getNumberOfJobsIssued(preemptable=False), mock.getNumberOfNodes(preemptable=False), mock.getNumberOfJobsIssued(preemptable=True), mock.getNumberOfNodes(preemptable=True))) clusterScaler.check() time.sleep(0.5) logger.debug("We waited %s for cluster to finish" % (time.time() - startTime)) finally: clusterScaler.shutdown() mock.shutDown() # Print some info about the autoscaling logger.debug("Total-jobs: %s: Max-workers: %s, " "Total-worker-time: %s, Worker-time-per-job: %s" % (mock.totalJobs, sum(mock.maxWorkers.values()), mock.totalWorkerTime, old_div(mock.totalWorkerTime, mock.totalJobs) if mock.totalJobs > 0 else 0.0)) @slow def testClusterScaling(self): """ Test scaling for a batch of non-preemptable jobs and no preemptable jobs (makes debugging easier). """ config = Config() # Make defaults dummy values config.defaultMemory = 1 config.defaultCores = 1 config.defaultDisk = 1 # No preemptable nodes/jobs config.maxPreemptableNodes = [] # No preemptable nodes # Non-preemptable parameters config.nodeTypes = [Shape(20, 10, 10, 10, False)] config.minNodes = [0] config.maxNodes = [10] # Algorithm parameters config.targetTime = defaultTargetTime config.betaInertia = 0.1 config.scaleInterval = 3 self._testClusterScaling(config, numJobs=100, numPreemptableJobs=0, jobShape=config.nodeTypes[0]) @slow def testClusterScalingMultipleNodeTypes(self): smallNode = Shape(20, 5, 10, 10, False) mediumNode = Shape(20, 10, 10, 10, False) largeNode = Shape(20, 20, 10, 10, False) numJobs = 100 config = Config() # Make defaults dummy values config.defaultMemory = 1 config.defaultCores = 1 config.defaultDisk = 1 # No preemptable nodes/jobs config.preemptableNodeTypes = [] config.minPreemptableNodes = [] config.maxPreemptableNodes = [] # No preemptable nodes # Make sure the node types don't have to be ordered config.nodeTypes = [largeNode, smallNode, mediumNode] config.minNodes = [0, 0, 0] config.maxNodes = [10, 10] # test expansion of this list # Algorithm parameters config.targetTime = defaultTargetTime config.betaInertia = 0.1 config.scaleInterval = 3 mock = MockBatchSystemAndProvisioner(config, secondsPerJob=2.0) clusterScaler = ScalerThread(mock, mock, config) clusterScaler.start() mock.start() try: # Add small jobs list(map(lambda x: mock.addJob(jobShape=smallNode), list(range(numJobs)))) list(map(lambda x: mock.addJob(jobShape=mediumNode), list(range(numJobs)))) # Add medium completed jobs for i in range(1000): iJ = JobNode(jobStoreID=1, requirements=dict( memory=random.choice(range(smallNode.memory, mediumNode.memory)), cores=mediumNode.cores, disk=largeNode.cores, preemptable=False), command=None, jobName='testClusterScaling', unitName='') clusterScaler.addCompletedJob(iJ, random.choice(range(1, 10))) while mock.getNumberOfJobsIssued() > 0 or mock.getNumberOfNodes() > 0: logger.debug("%i nodes currently provisioned" % mock.getNumberOfNodes()) # Make sure there are no large nodes self.assertEqual(mock.getNumberOfNodes(nodeType=largeNode), 0) clusterScaler.check() time.sleep(0.5) finally: clusterScaler.shutdown() mock.shutDown() # Make sure jobs ran on both the small and medium node types self.assertTrue(mock.totalJobs > 0) self.assertTrue(mock.maxWorkers[smallNode] > 0) self.assertTrue(mock.maxWorkers[mediumNode] > 0) self.assertEqual(mock.maxWorkers[largeNode], 0) @slow def testClusterScalingWithPreemptableJobs(self): """ Test scaling simultaneously for a batch of preemptable and non-preemptable jobs. """ config = Config() jobShape = Shape(20, 10, 10, 10, False) preemptableJobShape = Shape(20, 10, 10, 10, True) # Make defaults dummy values config.defaultMemory = 1 config.defaultCores = 1 config.defaultDisk = 1 # non-preemptable node parameters config.nodeTypes = [jobShape, preemptableJobShape] config.minNodes = [0, 0] config.maxNodes = [10, 10] # Algorithm parameters config.targetTime = defaultTargetTime config.betaInertia = 0.9 config.scaleInterval = 3 self._testClusterScaling(config, numJobs=100, numPreemptableJobs=100, jobShape=jobShape) # noinspection PyAbstractClass class MockBatchSystemAndProvisioner(AbstractScalableBatchSystem, AbstractProvisioner): """ Mimics a job batcher, provisioner and scalable batch system """ def __init__(self, config, secondsPerJob): super(MockBatchSystemAndProvisioner, self).__init__('clusterName') # To mimic parallel preemptable and non-preemptable queues # for jobs we create two parallel instances of the following class self.config = config self.secondsPerJob = secondsPerJob self.provisioner = self self.batchSystem = self self.nodeTypes = config.nodeTypes self.nodeShapes = self.nodeTypes self.nodeShapes.sort() self.jobQueue = Queue() self.updatedJobsQueue = Queue() self.jobBatchSystemIDToIssuedJob = {} self.totalJobs = 0 # Count of total jobs processed self.totalWorkerTime = 0.0 # Total time spent in worker threads self.toilMetrics = None self.nodesToWorker = {} # Map from Node to instances of the Worker class self.workers = {nodeShape: [] for nodeShape in self.nodeShapes} # Instances of the Worker class self.maxWorkers = {nodeShape: 0 for nodeShape in self.nodeShapes} # Maximum number of workers self.running = False self.leaderThread = Thread(target=self._leaderFn) def start(self): self.running = True self.leaderThread.start() def shutDown(self): self.running = False self.leaderThread.join() # Stub out all AbstractBatchSystem methods since they are never called for name, value in iteritems(AbstractBatchSystem.__dict__): if getattr(value, '__isabstractmethod__', False): exec('def %s(): pass' % name) # Without this, the class would end up with .name and .value attributes del name, value # AbstractScalableBatchSystem methods def nodeInUse(self, nodeIP): return False def ignoreNode(self, nodeAddress): pass def unignoreNode(self, nodeAddress): pass @contextmanager def nodeFiltering(self, filter): nodes = self.getProvisionedWorkers(preemptable=True, nodeType=None) + self.getProvisionedWorkers( preemptable=False, nodeType=None) yield nodes # AbstractProvisioner methods def getProvisionedWorkers(self, nodeType=None, preemptable=None): """ Returns a list of Node objects, each representing a worker node in the cluster :param preemptable: If True only return preemptable nodes else return non-preemptable nodes :return: list of Node """ nodesToWorker = self.nodesToWorker if nodeType: return [node for node in nodesToWorker if node.nodeType == nodeType] else: return list(nodesToWorker.keys()) def terminateNodes(self, nodes): self._removeNodes(nodes) def remainingBillingInterval(self, node): pass def addJob(self, jobShape, preemptable=False): """ Add a job to the job queue """ self.totalJobs += 1 jobID = uuid.uuid4() self.jobBatchSystemIDToIssuedJob[jobID] = Job(memory=jobShape.memory, cores=jobShape.cores, disk=jobShape.disk, preemptable=preemptable) self.jobQueue.put(jobID) # JobBatcher functionality def getNumberOfJobsIssued(self, preemptable=None): if preemptable is not None: jobList = [job for job in list(self.jobQueue.queue) if self.jobBatchSystemIDToIssuedJob[job].preemptable == preemptable] return len(jobList) else: return self.jobQueue.qsize() def getJobs(self): return self.jobBatchSystemIDToIssuedJob.values() # AbstractScalableBatchSystem functionality def getNodes(self, preemptable=False, timeout=None): nodes = dict() for node in self.nodesToWorker: if node.preemptable == preemptable: worker = self.nodesToWorker[node] nodes[node.privateIP] = NodeInfo(coresTotal=0, coresUsed=0, requestedCores=1, memoryTotal=0, memoryUsed=0, requestedMemory=1, workers=1 if worker.busyEvent.is_set() else 0) return nodes # AbstractProvisioner functionality def addNodes(self, nodeType, numNodes, preemptable): self._addNodes(numNodes=numNodes, nodeType=nodeType, preemptable=preemptable) return self.getNumberOfNodes(nodeType=nodeType, preemptable=preemptable) def getNodeShape(self, nodeType, preemptable=False): # Assume node shapes and node types are the same thing for testing return nodeType def getWorkersInCluster(self, nodeShape): return self.workers[nodeShape] def launchCluster(self, leaderNodeType, keyName, userTags=None, vpcSubnet=None, leaderStorage=50, nodeStorage=50, botoPath=None, **kwargs): pass def destroyCluster(self): pass def getLeader(self): pass def _leaderFn(self): while self.running: updatedJobID = None try: updatedJobID = self.updatedJobsQueue.get(timeout=1.0) except Empty: continue if updatedJobID: del self.jobBatchSystemIDToIssuedJob[updatedJobID] time.sleep(0.1) def _addNodes(self, numNodes, nodeType, preemptable=False): nodeShape = self.getNodeShape(nodeType=nodeType, preemptable=preemptable) class Worker(object): def __init__(self, jobQueue, updatedJobsQueue, secondsPerJob): self.busyEvent = Event() self.stopEvent = Event() def workerFn(): while True: if self.stopEvent.is_set(): return try: jobID = jobQueue.get(timeout=1.0) except Empty: continue updatedJobsQueue.put(jobID) self.busyEvent.set() time.sleep(secondsPerJob) self.busyEvent.clear() self.startTime = time.time() self.worker = Thread(target=workerFn) self.worker.start() def stop(self): self.stopEvent.set() self.worker.join() return time.time() - self.startTime for _ in range(numNodes): node = Node('127.0.0.1', uuid.uuid4(), 'testNode', datetime.datetime.now().isoformat()+'Z', nodeType=nodeType, preemptable=preemptable) self.nodesToWorker[node] = Worker(self.jobQueue, self.updatedJobsQueue, self.secondsPerJob) self.workers[nodeShape].append(self.nodesToWorker[node]) self.maxWorkers[nodeShape] = max(self.maxWorkers[nodeShape], len(self.workers[nodeShape])) def _removeNodes(self, nodes): logger.debug("Removing nodes. %s workers and %s to terminate.", len(self.nodesToWorker), len(nodes)) for node in nodes: logger.debug("removed node") try: nodeShape = self.getNodeShape(node.nodeType, node.preemptable) worker = self.nodesToWorker.pop(node) self.workers[nodeShape].pop() self.totalWorkerTime += worker.stop() except KeyError: # Node isn't our responsibility pass def getNumberOfNodes(self, nodeType=None, preemptable=None): if nodeType: nodeShape = self.getNodeShape(nodeType=nodeType, preemptable=preemptable) return len(self.workers[nodeShape]) else: return len(self.nodesToWorker) toil-releases-3.24.0/src/toil/test/provisioners/gceProvisionerTest.py000066400000000000000000000316421362134276200260530ustar00rootroot00000000000000# Copyright (C) 2015 UCSC Computational Genomics Lab # # 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. from builtins import str import logging import os from toil import subprocess from toil.version import exactPython from abc import abstractmethod import pytest from uuid import uuid4 from toil.test import needs_google, integrative, ToilTest, needs_appliance, timeLimit, slow log = logging.getLogger(__name__) @needs_google @integrative @needs_appliance @slow class AbstractGCEAutoscaleTest(ToilTest): projectID = os.getenv('TOIL_GOOGLE_PROJECTID') def sshUtil(self, command): baseCommand = ['toil', 'ssh-cluster', '--insecure', '-p=gce', self.clusterName] callCommand = baseCommand + command subprocess.check_call(callCommand) def rsyncUtil(self, src, dest): baseCommand = ['toil', 'rsync-cluster', '--insecure', '-p=gce', self.clusterName] callCommand = baseCommand + [src, dest] subprocess.check_call(callCommand) def destroyClusterUtil(self): callCommand = ['toil', 'destroy-cluster', '-p=gce', self.clusterName] subprocess.check_call(callCommand) def createClusterUtil(self, args=None): if args is None: args = [] callCommand = ['toil', 'launch-cluster', self.clusterName, '-p=gce', '--keyPairName=%s' % self.keyName, '--leaderNodeType=%s' % self.leaderInstanceType, '--zone=%s' % self.googleZone] if self.botoDir is not None: callCommand += ['--boto=%s' % self.botoDir] callCommand = callCommand + args if args else callCommand log.info("createClusterUtil: %s" % ''.join(callCommand)) subprocess.check_call(callCommand) def cleanJobStoreUtil(self): callCommand = ['toil', 'clean', self.jobStore] subprocess.check_call(callCommand) def __init__(self, methodName): super(AbstractGCEAutoscaleTest, self).__init__(methodName=methodName) # TODO: add TOIL_GOOGLE_KEYNAME to needs_google or ssh with SA account self.keyName = os.getenv('TOIL_GOOGLE_KEYNAME') # TODO: remove this when switching to google jobstore self.botoDir = os.getenv('TOIL_BOTO_DIR') # TODO: get this from SA account or add an environment variable self.googleZone = 'us-west1-a' self.leaderInstanceType = 'n1-standard-1' self.instanceTypes = ["n1-standard-2"] self.numWorkers = ['2'] self.numSamples = 2 self.spotBid = 0.15 def setUp(self): super(AbstractGCEAutoscaleTest, self).setUp() def tearDown(self): super(AbstractGCEAutoscaleTest, self).tearDown() self.destroyClusterUtil() self.cleanJobStoreUtil() #def getMatchingRoles(self, clusterName): # ctx = AWSProvisioner._buildContext(clusterName) # roles = list(ctx.local_roles()) # return roles def launchCluster(self): self.createClusterUtil() @abstractmethod def _getScript(self): """ Download the test script needed by the inheriting unit test class. """ raise NotImplementedError() @abstractmethod def _runScript(self, toilOptions): """ Modify the provided Toil options to suit the test Toil script, then run the script with those arguments. :param toilOptions: List of Toil command line arguments. This list may need to be modified to suit the test script's requirements. """ raise NotImplementedError() def _test(self, preemptableJobs=False): """ Does the work of the testing. Many features' test are thrown in here is no particular order """ self.launchCluster() # TODO: What is the point of this test? #assert len(self.getMatchingRoles(self.clusterName)) == 1 # TODO: Add a check of leader and node storage size if set. # --never-download prevents silent upgrades to pip, wheel and setuptools venv_command = ['virtualenv', '--system-site-packages', '--never-download', '--python', exactPython, '/home/venv'] self.sshUtil(venv_command) upgrade_command = ['/home/venv/bin/pip', 'install', 'setuptools==28.7.1'] self.sshUtil(upgrade_command) yaml_command = ['/home/venv/bin/pip', 'install', 'pyyaml==3.12'] self.sshUtil(yaml_command) self._getScript() toilOptions = [self.jobStore, '--batchSystem=mesos', '--workDir=/var/lib/toil', '--clean=always', '--retryCount=2', '--clusterStats=/home/', '--logDebug', '--logFile=/home/sort.log', '--provisioner=gce'] toilOptions.extend(['--nodeTypes=' + ",".join(self.instanceTypes), '--maxNodes=%s' % ",".join(self.numWorkers)]) if preemptableJobs: toilOptions.extend(['--defaultPreemptable']) self._runScript(toilOptions) #TODO: Does this just check if it is still running? #assert len(self.getMatchingRoles(self.clusterName)) == 1 checkStatsCommand = ['/home/venv/bin/python', '-c', 'import json; import os; ' 'json.load(open("/home/" + [f for f in os.listdir("/home/") ' 'if f.endswith(".json")].pop()))' ] self.sshUtil(checkStatsCommand) # TODO: Add a check to make sure everything is cleaned up. @pytest.mark.timeout(1600) class GCEAutoscaleTest(AbstractGCEAutoscaleTest): def __init__(self, name): super(GCEAutoscaleTest, self).__init__(name) self.clusterName = 'provisioner-test-' + str(uuid4()) self.requestedLeaderStorage = 80 def setUp(self): super(GCEAutoscaleTest, self).setUp() self.jobStore = 'google:%s:autoscale-%s' % (self.projectID, uuid4()) def _getScript(self): # TODO: Isn't this the key file? fileToSort = os.path.join(os.getcwd(), str(uuid4())) with open(fileToSort, 'w') as f: # Fixme: making this file larger causes the test to hang f.write('01234567890123456789012345678901') self.rsyncUtil(os.path.join(self._projectRootPath(), 'src/toil/test/sort/sort.py'), ':/home/sort.py') self.rsyncUtil(fileToSort, ':/home/sortFile') os.unlink(fileToSort) def _runScript(self, toilOptions): runCommand = ['/home/venv/bin/python', '/home/sort.py', '--fileToSort=/home/sortFile'] #'--sseKey=/home/sortFile'] runCommand.extend(toilOptions) log.info("_runScript: %s" % ''.join(runCommand)) self.sshUtil(runCommand) def launchCluster(self): # add arguments to test that we can specify leader storage self.createClusterUtil(args=['--leaderStorage', str(self.requestedLeaderStorage)]) # TODO: aren't these checks inherited? @integrative @needs_google def testAutoScale(self): self.instanceTypes = ["n1-standard-2"] self.numWorkers = ['2'] self._test() @integrative @needs_google def testSpotAutoScale(self): self.instanceTypes = ["n1-standard-2:%f" % self.spotBid] # Some spot workers have a stopped state after being started, strangely. # This could be the natural preemption process, but it seems too rapid. self.numWorkers = ['3'] # Try 3 to account for a stopped node. self._test(preemptableJobs=True) @pytest.mark.timeout(1600) class GCEStaticAutoscaleTest(GCEAutoscaleTest): """ Runs the tests on a statically provisioned cluster with autoscaling enabled. """ def __init__(self, name): super(GCEStaticAutoscaleTest, self).__init__(name) self.requestedNodeStorage = 20 def launchCluster(self): self.createClusterUtil(args=['--leaderStorage', str(self.requestedLeaderStorage), '--nodeTypes', ",".join(self.instanceTypes), '-w', ",".join(self.numWorkers), '--nodeStorage', str(self.requestedLeaderStorage)]) # TODO: check the number of workers and their storage #nodes = AWSProvisioner._getNodesInCluster(ctx, self.clusterName, both=True) #nodes.sort(key=lambda x: x.launch_time) # assuming that leader is first #workers = nodes[1:] # test that two worker nodes were created #self.assertEqual(2, len(workers)) # test that workers have expected storage size # just use the first worker #worker = workers[0] #worker = next(wait_instances_running(ctx.ec2, [worker])) #rootBlockDevice = worker.block_device_mapping["/dev/xvda"] #self.assertTrue(isinstance(rootBlockDevice, BlockDeviceType)) #rootVolume = ctx.ec2.get_all_volumes(volume_ids=[rootBlockDevice.volume_id])[0] #self.assertGreaterEqual(rootVolume.size, self.requestedNodeStorage) def _runScript(self, toilOptions): runCommand = ['/home/venv/bin/python', '/home/sort.py', '--fileToSort=/home/sortFile'] runCommand.extend(toilOptions) log.info("_runScript: %s" % ''.join(runCommand)) self.sshUtil(runCommand) @pytest.mark.timeout(1800) class GCEAutoscaleTestMultipleNodeTypes(AbstractGCEAutoscaleTest): def __init__(self, name): super(GCEAutoscaleTestMultipleNodeTypes, self).__init__(name) self.clusterName = 'provisioner-test-' + str(uuid4()) def setUp(self): super(GCEAutoscaleTestMultipleNodeTypes, self).setUp() self.jobStore = 'google:%s:multinode-%s' % (self.projectID, uuid4()) def _getScript(self): sseKeyFile = os.path.join(os.getcwd(), 'keyFile') with open(sseKeyFile, 'w') as f: f.write('01234567890123456789012345678901') self.rsyncUtil(os.path.join(self._projectRootPath(), 'src/toil/test/sort/sort.py'), ':/home/sort.py') self.rsyncUtil(sseKeyFile, ':/home/keyFile') os.unlink(sseKeyFile) def _runScript(self, toilOptions): #Set memory requirements so that sort jobs can be run # on small instances, but merge jobs must be run on large # instances runCommand = ['/home/venv/bin/python', '/home/sort.py', '--fileToSort=/home/s3am/bin/asadmin', '--sortMemory=0.6G', '--mergeMemory=3.0G'] runCommand.extend(toilOptions) #runCommand.append('--sseKey=/home/keyFile') log.info("_runScript: %s" % ''.join(runCommand)) self.sshUtil(runCommand) @integrative @needs_google def testAutoScale(self): self.instanceTypes = ["n1-standard-2", "n1-standard-4"] self.numWorkers = ['2','1'] self._test() @pytest.mark.timeout(1800) class GCERestartTest(AbstractGCEAutoscaleTest): """ This test insures autoscaling works on a restarted Toil run """ def __init__(self, name): super(GCERestartTest, self).__init__(name) self.clusterName = 'restart-test-' + str(uuid4()) def setUp(self): super(GCERestartTest, self).setUp() self.instanceTypes = ['n1-standard-1'] self.numWorkers = ['1'] self.scriptName = "/home/restartScript.py" # TODO: replace this with a google job store zone = 'us-west-2' self.jobStore = 'google:%s:restart-%s' % (self.projectID, uuid4()) def _getScript(self): self.rsyncUtil(os.path.join(self._projectRootPath(), 'src/toil/test/provisioners/restartScript.py'), ':'+self.scriptName) def _runScript(self, toilOptions): # clean = onSuccess disallowedOptions = ['--clean=always', '--retryCount=2'] newOptions = [option for option in toilOptions if option not in disallowedOptions] try: # include a default memory - on restart the minimum memory requirement is the default, usually 2 GB command = ['/home/venv/bin/python', self.scriptName, '-e', 'FAIL=true', '--defaultMemory=50000000'] command.extend(newOptions) self.sshUtil(command) except subprocess.CalledProcessError: pass else: self.fail('Command succeeded when we expected failure') with timeLimit(1200): command = ['/home/venv/bin/python', self.scriptName, '--restart', '--defaultMemory=50000000'] command.extend(toilOptions) self.sshUtil(command) @integrative def testAutoScaledCluster(self): self._test() toil-releases-3.24.0/src/toil/test/provisioners/restartScript.py000066400000000000000000000006131362134276200250600ustar00rootroot00000000000000from toil.job import Job import argparse import os def f0(job): if 'FAIL' in os.environ: raise RuntimeError('failed on purpose') if __name__ == '__main__': parser = argparse.ArgumentParser() Job.Runner.addToilOptions(parser) options = parser.parse_args() rootJob = Job.wrapJobFn(f0, cores=0.5, memory='50 M', disk='50 M') Job.Runner.startToil(rootJob, options) toil-releases-3.24.0/src/toil/test/sort/000077500000000000000000000000001362134276200200625ustar00rootroot00000000000000toil-releases-3.24.0/src/toil/test/sort/__init__.py000066400000000000000000000012131362134276200221700ustar00rootroot00000000000000# Copyright (C) 2015-2016 Regents of the University of California # # 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. from __future__ import absolute_import toil-releases-3.24.0/src/toil/test/sort/sort.py000077500000000000000000000252541362134276200214360ustar00rootroot00000000000000# Copyright (C) 2015-2016 Regents of the University of California # # 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. """A demonstration of toil. Sorts the lines of a file into ascending order by doing a parallel merge sort. """ from __future__ import absolute_import from __future__ import division from builtins import range from past.utils import old_div from argparse import ArgumentParser import codecs import os import random import logging import shutil from toil.common import Toil from toil.job import Job from toil.realtimeLogger import RealtimeLogger defaultLines = 1000 defaultLineLen = 50 sortMemory = '600M' def setup(job, inputFile, N, downCheckpoints, options): """ Sets up the sort. Returns the FileID of the sorted file """ RealtimeLogger.info("Starting the merge sort") return job.addChildJobFn(down, inputFile, N, 'root', downCheckpoints, options = options, preemptable=True, memory=sortMemory).rv() def down(job, inputFileStoreID, N, path, downCheckpoints, options, memory=sortMemory): """ Input is a file, a subdivision size N, and a path in the hierarchy of jobs. If the range is larger than a threshold N the range is divided recursively and a follow on job is then created which merges back the results else the file is sorted and placed in the output. """ RealtimeLogger.info("Down job starting: %s" % path) # Read the file inputFile = job.fileStore.readGlobalFile(inputFileStoreID, cache=False) length = os.path.getsize(inputFile) if length > N: # We will subdivide the file RealtimeLogger.critical("Splitting file: %s of size: %s" % (inputFileStoreID, length)) # Split the file into two copies midPoint = getMidPoint(inputFile, 0, length) t1 = job.fileStore.getLocalTempFile() with open(t1, 'w') as fH: fH.write(copySubRangeOfFile(inputFile, 0, midPoint+1)) t2 = job.fileStore.getLocalTempFile() with open(t2, 'w') as fH: fH.write(copySubRangeOfFile(inputFile, midPoint+1, length)) # Call down recursively. By giving the rv() of the two jobs as inputs to the follow-on job, up, # we communicate the dependency without hindering concurrency. result = job.addFollowOnJobFn(up, job.addChildJobFn(down, job.fileStore.writeGlobalFile(t1), N, path + '/0', downCheckpoints, checkpoint=downCheckpoints, options=options, preemptable=True, memory=options.sortMemory).rv(), job.addChildJobFn(down, job.fileStore.writeGlobalFile(t2), N, path + '/1', downCheckpoints, checkpoint=downCheckpoints, options=options, preemptable=True, memory=options.mergeMemory).rv(), path + '/up', preemptable=True, options=options, memory=options.sortMemory).rv() else: # We can sort this bit of the file RealtimeLogger.critical("Sorting file: %s of size: %s" % (inputFileStoreID, length)) # Sort the copy and write back to the fileStore shutil.copyfile(inputFile, inputFile + '.sort') sort(inputFile + '.sort') result = job.fileStore.writeGlobalFile(inputFile + '.sort') RealtimeLogger.info("Down job finished: %s" % path) return result def up(job, inputFileID1, inputFileID2, path, options, memory=sortMemory): """ Merges the two files and places them in the output. """ RealtimeLogger.info("Up job starting: %s" % path) with job.fileStore.writeGlobalFileStream() as (fileHandle, outputFileStoreID): fileHandle = codecs.getwriter('utf-8')(fileHandle) with job.fileStore.readGlobalFileStream(inputFileID1) as inputFileHandle1: inputFileHandle1 = codecs.getreader('utf-8')(inputFileHandle1) with job.fileStore.readGlobalFileStream(inputFileID2) as inputFileHandle2: inputFileHandle2 = codecs.getreader('utf-8')(inputFileHandle2) RealtimeLogger.info("Merging %s and %s to %s" % (inputFileID1, inputFileID2, outputFileStoreID)) merge(inputFileHandle1, inputFileHandle2, fileHandle) # Cleanup up the input files - these deletes will occur after the completion is successful. job.fileStore.deleteGlobalFile(inputFileID1) job.fileStore.deleteGlobalFile(inputFileID2) RealtimeLogger.info("Up job finished: %s" % path) return outputFileStoreID def sort(file): """Sorts the given file.""" with open(file, 'r') as f: lines = f.readlines() lines.sort() with open(file, 'w') as f: for line in lines: f.write(line) def merge(fileHandle1, fileHandle2, outputFileHandle): """ Merges together two files maintaining sorted order. All handles must be text-mode streams. """ line2 = fileHandle2.readline() for line1 in fileHandle1.readlines(): while len(line2) != 0 and line2 <= line1: outputFileHandle.write(line2) line2 = fileHandle2.readline() outputFileHandle.write(line1) while len(line2) != 0: outputFileHandle.write(line2) line2 = fileHandle2.readline() def copySubRangeOfFile(inputFile, fileStart, fileEnd): """ Copies the range (in bytes) between fileStart and fileEnd to the given output file handle. """ with open(inputFile, 'r') as fileHandle: fileHandle.seek(fileStart) data = fileHandle.read(fileEnd - fileStart) assert len(data) == fileEnd - fileStart return data def getMidPoint(file, fileStart, fileEnd): """ Finds the point in the file to split. Returns an int i such that fileStart <= i < fileEnd """ with open(file, 'r') as f: midPoint = old_div((fileStart + fileEnd), 2) assert midPoint >= fileStart f.seek(midPoint) line = f.readline() assert len(line) >= 1 if len(line) + midPoint < fileEnd: return midPoint + len(line) - 1 f.seek(fileStart) line = f.readline() assert len(line) >= 1 assert len(line) + fileStart <= fileEnd return len(line) + fileStart - 1 def makeFileToSort(fileName, lines=defaultLines, lineLen=defaultLineLen): with open(fileName, 'w') as f: for _ in range(lines): line = "".join(random.choice('actgACTGNXYZ') for _ in range(lineLen - 1)) + '\n' f.write(line) def main(options=None): if not options: # deal with command line arguments parser = ArgumentParser() Job.Runner.addToilOptions(parser) parser.add_argument('--numLines', default=defaultLines, help='Number of lines in file to sort.', type=int) parser.add_argument('--lineLength', default=defaultLineLen, help='Length of lines in file to sort.', type=int) parser.add_argument("--fileToSort", help="The file you wish to sort") parser.add_argument("--outputFile", help="Where the sorted output will go") parser.add_argument("--overwriteOutput", help="Write over the output file if it already exists.", default=True) parser.add_argument("--N", dest="N", help="The threshold below which a serial sort function is used to sort file. " "All lines must of length less than or equal to N or program will fail", default=10000) parser.add_argument('--downCheckpoints', action='store_true', help='If this option is set, the workflow will make checkpoints on its way through' 'the recursive "down" part of the sort') parser.add_argument("--sortMemory", dest="sortMemory", help="Memory for jobs that sort chunks of the file.", default=None) parser.add_argument("--mergeMemory", dest="mergeMemory", help="Memory for jobs that collate results.", default=None) options = parser.parse_args() if not hasattr(options, "sortMemory") or not options.sortMemory: options.sortMemory = sortMemory if not hasattr(options, "mergeMemory") or not options.mergeMemory: options.mergeMemory = sortMemory # do some input verification sortedFileName = options.outputFile or "sortedFile.txt" if not options.overwriteOutput and os.path.exists(sortedFileName): print("the output file {} already exists. Delete it to run the sort example again or use --overwriteOutput=True".format(sortedFileName)) exit() fileName = options.fileToSort if options.fileToSort is None: # make the file ourselves fileName = 'fileToSort.txt' if os.path.exists(fileName): print("Sorting existing file: {}".format(fileName)) else: print('No sort file specified. Generating one automatically called: {}.'.format(fileName)) makeFileToSort(fileName=fileName, lines=options.numLines, lineLen=options.lineLength) else: if not os.path.exists(options.fileToSort): raise RuntimeError("File to sort does not exist: %s" % options.fileToSort) if int(options.N) <= 0: raise RuntimeError("Invalid value of N: %s" % options.N) # Now we are ready to run with Toil(options) as workflow: sortedFileURL = 'file://' + os.path.abspath(sortedFileName) if not workflow.options.restart: sortFileURL = 'file://' + os.path.abspath(fileName) sortFileID = workflow.importFile(sortFileURL) sortedFileID = workflow.start(Job.wrapJobFn(setup, sortFileID, int(options.N), options.downCheckpoints, options=options, memory=sortMemory)) else: sortedFileID = workflow.restart() workflow.exportFile(sortedFileID, sortedFileURL) if __name__ == '__main__': main() toil-releases-3.24.0/src/toil/test/sort/sortTest.py000077500000000000000000000304541362134276200222740ustar00rootroot00000000000000# Copyright (C) 2015-2018 Regents of the University of California # # 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. from __future__ import absolute_import, print_function from builtins import str from builtins import range import unittest import os import random import shutil from contextlib import contextmanager from uuid import uuid4 import logging from toil import subprocess from toil import resolveEntryPoint from toil.batchSystems.parasolTestSupport import ParasolTestSupport from toil.common import Toil from toil.job import Job from toil.lib.bioio import getLogLevelString from toil.batchSystems.mesos.test import MesosTestSupport from toil.test.sort.sort import merge, sort, copySubRangeOfFile, getMidPoint, makeFileToSort, main from toil.test import (ToilTest, needs_aws_ec2, needs_mesos, needs_parasol, needs_gridengine, needs_torque, needs_google, slow) from toil.jobStores.abstractJobStore import NoSuchJobStoreException, JobStoreExistsException from toil.leader import FailedJobsException log = logging.getLogger(__name__) defaultLineLen = int(os.environ.get('TOIL_TEST_SORT_LINE_LEN', 10)) defaultLines = int(os.environ.get('TOIL_TEST_SORT_LINES', 10)) defaultN = int(os.environ.get('TOIL_TEST_SORT_N', defaultLineLen * defaultLines / 5)) @contextmanager def runMain(options): """ make sure the output file is deleted every time main is run """ main(options) yield if os.path.exists(options.outputFile): os.remove(options.outputFile) @slow class SortTest(ToilTest, MesosTestSupport, ParasolTestSupport): """ Tests Toil by sorting a file in parallel on various combinations of job stores and batch systems. """ def setUp(self): super(SortTest, self).setUp() self.tempDir = self._createTempDir(purpose='tempDir') self.outputFile = os.path.join(self.tempDir, 'sortedFile.txt') self.inputFile = os.path.join(self.tempDir, "fileToSort.txt") def tearDown(self): if os.path.exists(self.tempDir): shutil.rmtree(self.tempDir) ToilTest.tearDown(self) def _toilSort(self, jobStoreLocator, batchSystem, lines=defaultLines, N=defaultN, testNo=1, lineLen=defaultLineLen, retryCount=2, badWorker=0.5, downCheckpoints=False, disableCaching=False): """ Generate a file consisting of the given number of random lines, each line of the given length. Sort the file with Toil by splitting the file recursively until each part is less than the given number of bytes, sorting each part and merging them back together. Then verify the result. :param jobStoreLocator: The location of the job store. :param batchSystem: the name of the batch system :param lines: the number of random lines to generate :param N: the size in bytes of each split :param testNo: the number of repeats of this test :param lineLen: the length of each random line in the file """ for test in range(testNo): try: # Specify options options = Job.Runner.getDefaultOptions(jobStoreLocator) options.logLevel = getLogLevelString() options.retryCount = retryCount options.batchSystem = batchSystem options.clean = "never" options.badWorker = badWorker options.badWorkerFailInterval = 0.05 options.disableCaching = disableCaching # This is required because mesosMasterAddress now defaults to the IP of the machine # that is starting the workflow while the mesos *tests* run locally. if batchSystem == 'mesos': options.mesosMasterAddress = 'localhost:5050' options.downCheckpoints = downCheckpoints options.N = N options.outputFile = self.outputFile options.fileToSort = self.inputFile options.overwriteOutput = True options.realTimeLogging = True # Make the file to sort makeFileToSort(options.fileToSort, lines=lines, lineLen=lineLen) # First make our own sorted version with open(options.fileToSort, 'r') as fileHandle: l = fileHandle.readlines() l.sort() # Check we get an exception if we try to restart a workflow that doesn't exist options.restart = True with self.assertRaises(NoSuchJobStoreException): with runMain(options): # Now check the file is properly sorted.. with open(options.outputFile, 'r') as fileHandle: l2 = fileHandle.readlines() self.assertEqual(l, l2) options.restart = False # Now actually run the workflow try: with runMain(options): pass i = 0 except FailedJobsException as e: i = e.numberOfFailedJobs # Check we get an exception if we try to run without restart on an existing store with self.assertRaises(JobStoreExistsException): with runMain(options): pass options.restart = True # This loop tests the restart behavior totalTrys = 1 while i != 0: options.useExistingOptions = random.random() > 0.5 try: with runMain(options): pass i = 0 except FailedJobsException as e: i = e.numberOfFailedJobs if totalTrys > 32: # p(fail after this many restarts) = 0.5**32 self.fail('Exceeded a reasonable number of restarts') totalTrys += 1 finally: subprocess.check_call([resolveEntryPoint('toil'), 'clean', jobStoreLocator]) # final test to make sure the jobStore was actually deleted self.assertRaises(NoSuchJobStoreException, Toil.resumeJobStore, jobStoreLocator) @needs_aws_ec2 def testAwsSingle(self): self._toilSort(jobStoreLocator=self._awsJobStore(), batchSystem='singleMachine') @needs_aws_ec2 @needs_mesos def testAwsMesos(self): self._startMesos() try: self._toilSort(jobStoreLocator=self._awsJobStore(), batchSystem="mesos") finally: self._stopMesos() @needs_mesos def testFileMesos(self): self._startMesos() try: self._toilSort(jobStoreLocator=self._getTestJobStorePath(), batchSystem="mesos") finally: self._stopMesos() @needs_google def testGoogleSingle(self): self._toilSort(jobStoreLocator=self._googleJobStore(), batchSystem="singleMachine") @needs_google @needs_mesos def testGoogleMesos(self): self._startMesos() try: self._toilSort(jobStoreLocator=self._googleJobStore(), batchSystem="mesos") finally: self._stopMesos() def testFileSingle(self): self._toilSort(jobStoreLocator=self._getTestJobStorePath(), batchSystem='singleMachine') def testFileSingleNonCaching(self): self._toilSort(jobStoreLocator=self._getTestJobStorePath(), batchSystem='singleMachine', disableCaching=True) def testFileSingleCheckpoints(self): self._toilSort(jobStoreLocator=self._getTestJobStorePath(), batchSystem='singleMachine', retryCount=2, downCheckpoints=True) def testFileSingle10000(self): self._toilSort(jobStoreLocator=self._getTestJobStorePath(), batchSystem='singleMachine', lines=10000, N=10000) @needs_gridengine @unittest.skip('GridEngine does not support shared caching') def testFileGridEngine(self): self._toilSort(jobStoreLocator=self._getTestJobStorePath(), batchSystem='gridengine') @needs_torque @unittest.skip('PBS/Torque does not support shared caching') def testFileTorqueEngine(self): self._toilSort(jobStoreLocator=self._getTestJobStorePath(), batchSystem='torque') @needs_parasol @unittest.skip("skipping until parasol support is less flaky (see github issue #449") def testFileParasol(self): self._startParasol() try: self._toilSort(jobStoreLocator=self._getTestJobStorePath(), batchSystem='parasol') finally: self._stopParasol() # The following functions test the functions in the test testNo = 5 def testSort(self): for test in range(self.testNo): tempFile1 = os.path.join(self.tempDir, "fileToSort.txt") makeFileToSort(tempFile1) lines1 = self._loadFile(tempFile1) lines1.sort() sort(tempFile1) with open(tempFile1, 'r') as f: lines2 = f.readlines() self.assertEqual(lines1, lines2) def testMerge(self): for test in range(self.testNo): tempFile1 = os.path.join(self.tempDir, "fileToSort1.txt") tempFile2 = os.path.join(self.tempDir, "fileToSort2.txt") tempFile3 = os.path.join(self.tempDir, "mergedFile.txt") makeFileToSort(tempFile1) makeFileToSort(tempFile2) sort(tempFile1) sort(tempFile2) with open(tempFile3, 'w') as fileHandle: with open(tempFile1) as tempFileHandle1: with open(tempFile2) as tempFileHandle2: merge(tempFileHandle1, tempFileHandle2, fileHandle) lines1 = self._loadFile(tempFile1) + self._loadFile(tempFile2) lines1.sort() with open(tempFile3, 'r') as f: lines2 = f.readlines() self.assertEqual(lines1, lines2) def testCopySubRangeOfFile(self): for test in range(self.testNo): tempFile = os.path.join(self.tempDir, "fileToSort1.txt") outputFile = os.path.join(self.tempDir, "outputFileToSort1.txt") makeFileToSort(tempFile, lines=10, lineLen=defaultLineLen) fileSize = os.path.getsize(tempFile) assert fileSize > 0 fileStart = random.choice(range(0, fileSize)) fileEnd = random.choice(range(fileStart, fileSize)) with open(outputFile, 'w') as f: f.write(copySubRangeOfFile(tempFile, fileStart, fileEnd)) with open(outputFile, 'r') as f: l = f.read() with open(tempFile, 'r') as f: l2 = f.read()[fileStart:fileEnd] self.assertEqual(l, l2) def testGetMidPoint(self): for test in range(self.testNo): makeFileToSort(self.inputFile) with open(self.inputFile, 'r') as f: sorted_contents = f.read() fileSize = os.path.getsize(self.inputFile) midPoint = getMidPoint(self.inputFile, 0, fileSize) print("the mid point is %i of a file of %i bytes" % (midPoint, fileSize)) assert midPoint < fileSize assert sorted_contents[midPoint] == '\n' assert midPoint >= 0 # Support methods def _awsJobStore(self): return 'aws:%s:sort-test-%s' % (self.awsRegion(), uuid4()) def _googleJobStore(self): projectID = os.getenv('TOIL_GOOGLE_PROJECTID') return 'google:%s:sort-test-%s' % (projectID, str(uuid4())) def _loadFile(self, path): with open(path, 'r') as f: return f.readlines() toil-releases-3.24.0/src/toil/test/src/000077500000000000000000000000001362134276200176625ustar00rootroot00000000000000toil-releases-3.24.0/src/toil/test/src/__init__.py000066400000000000000000000012131362134276200217700ustar00rootroot00000000000000# Copyright (C) 2015-2016 Regents of the University of California # # 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. from __future__ import absolute_import toil-releases-3.24.0/src/toil/test/src/autoDeploymentTest.py000066400000000000000000000570651362134276200241220ustar00rootroot00000000000000# coding=utf-8 from builtins import str from builtins import object import logging import sys from contextlib import contextmanager from toil.lib.iterables import concat from toil import subprocess from toil.version import exactPython from toil.test import needs_mesos, ApplianceTestSupport, needs_appliance, slow log = logging.getLogger(__name__) @needs_mesos @needs_appliance @slow class AutoDeploymentTest(ApplianceTestSupport): """ Tests various auto-deployment scenarios. Using the appliance, i.e. a docker container, for these tests allows for running worker processes on the same node as the leader process while keeping their file systems separate from each other and the leader process. Separate file systems are crucial to prove that auto-deployment does its job. """ def setUp(self): logging.basicConfig(level=logging.INFO) super(AutoDeploymentTest, self).setUp() @contextmanager def _venvApplianceCluster(self): """ Creates an appliance cluster with a virtualenv at './venv' on the leader and a temporary directory on the host mounted at /data in the leader and worker containers. """ dataDirPath = self._createTempDir(purpose='data') with self._applianceCluster(mounts={dataDirPath: '/data'}) as (leader, worker): leader.runOnAppliance('virtualenv', '--system-site-packages', '--never-download', # prevent silent upgrades to pip etc '--python', exactPython, 'venv') leader.runOnAppliance('venv/bin/pip', 'list') # For diagnostic purposes yield leader, worker # TODO: Are we sure the python in the appliance we are testing is the same # as the one we are testing from? If not, how can we get the version it is? sitePackages = 'venv/lib/{}/site-packages'.format(exactPython) def testRestart(self): """ Test whether auto-deployment works on restart. """ with self._venvApplianceCluster() as (leader, worker): def userScript(): from toil.job import Job from toil.common import Toil # noinspection PyUnusedLocal def job(job, disk='10M', cores=1, memory='10M'): assert False if __name__ == '__main__': options = Job.Runner.getDefaultArgumentParser().parse_args() with Toil(options) as toil: if toil.config.restart: toil.restart() else: toil.start(Job.wrapJobFn(job)) userScript = self._getScriptSource(userScript) leader.deployScript(path=self.sitePackages, packagePath='foo.bar', script=userScript) pythonArgs = ['venv/bin/python', '-m', 'foo.bar'] toilArgs = ['--logDebug', '--batchSystem=mesos', '--mesosMaster=localhost:5050', '--defaultMemory=10M', '/data/jobstore'] command = concat(pythonArgs, toilArgs) self.assertRaises(subprocess.CalledProcessError, leader.runOnAppliance, *command) # Deploy an updated version of the script ... userScript = userScript.replace('assert False', 'assert True') leader.deployScript(path=self.sitePackages, packagePath='foo.bar', script=userScript) # ... and restart Toil. command = concat(pythonArgs, '--restart', toilArgs) leader.runOnAppliance(*command) def testSplitRootPackages(self): """ Test whether auto-deployment works with a virtualenv in which jobs are defined in completely separate branches of the package hierarchy. Initially, auto-deployment did deploy the entire virtualenv but jobs could only be defined in one branch of the package hierarchy. We define a branch as the maximum set of fully qualified package paths that share the same first component. IOW, a.b and a.c are in the same branch, while a.b and d.c are not. """ with self._venvApplianceCluster() as (leader, worker): # Deploy the library module with job definitions def libraryModule(): # noinspection PyUnusedLocal def libraryJob(job): open('/data/foo.txt', 'w').close() leader.deployScript(path=self.sitePackages, packagePath='toil_lib.foo', script=libraryModule) # Deploy the user script def userScript(): from toil.job import Job from toil.common import Toil # noinspection PyUnresolvedReferences from toil_lib.foo import libraryJob # noinspection PyUnusedLocal def job(job, disk='10M', cores=1, memory='10M'): # Double the requirements to prevent chaining as chaining might hide problems # in auto-deployment code. job.addChildJobFn(libraryJob, disk='20M', cores=cores, memory=memory) if __name__ == '__main__': options = Job.Runner.getDefaultArgumentParser().parse_args() with Toil(options) as toil: if toil.config.restart: toil.restart() else: toil.start(Job.wrapJobFn(job)) leader.deployScript(path=self.sitePackages, packagePath='toil_script.bar', script=userScript) # Assert that output file isn't there worker.runOnAppliance('test', '!', '-f', '/data/foo.txt') # Just being paranoid self.assertRaises(subprocess.CalledProcessError, worker.runOnAppliance, 'test', '-f', '/data/foo.txt') leader.runOnAppliance('venv/bin/python', '-m', 'toil_script.bar', '--logDebug', '--batchSystem=mesos', '--mesosMaster=localhost:5050', '--defaultMemory=10M', '/data/jobstore') # Assert that out output file is there worker.runOnAppliance('test', '-f', '/data/foo.txt') def testUserTypesInJobFunctionArgs(self): """ Test encapsulated, function-wrapping jobs where the function arguments reference user-defined types. Mainly written to cover https://github.com/BD2KGenomics/toil/issues/1259 but then also revealed https://github.com/BD2KGenomics/toil/issues/1278. """ with self._venvApplianceCluster() as (leader, worker): def userScript(): from toil.job import Job from toil.common import Toil # A user-defined type, i.e. a type defined in the user script class X(object): pass # noinspection PyUnusedLocal def job(job, x, disk='10M', cores=1, memory='10M'): return x if __name__ == '__main__': options = Job.Runner.getDefaultArgumentParser().parse_args() x = X() with Toil(options) as toil: r = toil.start(Job.wrapJobFn(job, x).encapsulate()) # Assert that the return value is of type X, but not X from the __main__ # module but X from foo.bar, the canonical name for the user module. The # translation from __main__ to foo.bar is a side effect of auto-deployment. assert r.__class__ is not X import foo.bar assert r.__class__ is foo.bar.X # Assert that a copy was made. This is a side effect of pickling/unpickling. assert x is not r userScript = self._getScriptSource(userScript) leader.deployScript(path=self.sitePackages, packagePath='foo.bar', script=userScript) leader.runOnAppliance('venv/bin/python', '-m', 'foo.bar', '--logDebug', '--batchSystem=mesos', '--mesosMaster=localhost:5050', '--defaultMemory=10M', '--defaultDisk=10M', '/data/jobstore') def testDeferralWithConcurrentEncapsulation(self): """ Ensure that the following DAG succeeds: ┌───────────┠│ Root (W1) │ └───────────┘ │ ┌──────────┴─────────┠▼ â–¼ ┌────────────────┠┌────────────────────┠│ Deferring (W2) │ │ Encapsulating (W3) │â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— └────────────────┘ └────────────────────┘ â•‘ │ â•‘ â–¼ â–¼ ┌───────────────────┠┌────────────────┠│ Encapsulated (W3) │ │ Follow-on (W6) │ └───────────────────┘ └────────────────┘ │ │ ┌───────┴────────┠│ â–¼ â–¼ â–¼ ┌──────────────┠┌──────────────┠┌──────────────┠│ Dummy 1 (W4) │ │ Dummy 2 (W5) │ │ Last (W6) │ └──────────────┘ └──────────────┘ └──────────────┘ The Wn numbers denote the worker processes that a particular job is run in. `Deferring` adds a deferred function and then runs for a long time. The deferred function will be present in the cache state for the duration of `Deferred`. `Follow-on` is the generic Job instance that's added by encapsulating a job. It runs on the same worker node but in a separate worker process, as the first job in that worker. Because … 1) it is the first job in its worker process (the user script has not been made available on the sys.path by a previous job in that worker) and 2) it shares the cache state with the `Deferring` job and 3) it is an instance of Job (and so does not introduce the user script to sys.path itself), … it might cause problems with deserializing a defered function defined in the user script. `Encapsulated` has two children to ensure that `Follow-on` is run in a separate worker. """ with self._venvApplianceCluster() as (leader, worker): def userScript(): import time import logging from toil.job import Job from toil.common import Toil log = logging.getLogger(__name__) def root(rootJob): def nullFile(): return rootJob.fileStore.jobStore.importFile('file:///dev/null') startFile = nullFile() endFile = nullFile() rootJob.addChildJobFn(deferring, startFile, endFile) encapsulatedJob = Job.wrapJobFn(encapsulated, startFile) encapsulatedJob.addChildFn(dummy) encapsulatedJob.addChildFn(dummy) encapsulatingJob = encapsulatedJob.encapsulate() rootJob.addChild(encapsulatingJob) encapsulatingJob.addChildJobFn(last, endFile) def dummy(): pass def deferred(): pass # noinspection PyUnusedLocal def deferring(job, startFile, endFile): job.defer(deferred) job.fileStore.jobStore.deleteFile(startFile) timeout = time.time() + 10 while job.fileStore.jobStore.fileExists(endFile): assert time.time() < timeout time.sleep(1) def encapsulated(job, startFile): timeout = time.time() + 10 while job.fileStore.jobStore.fileExists(startFile): assert time.time() < timeout time.sleep(1) def last(job, endFile): job.fileStore.jobStore.deleteFile(endFile) if __name__ == '__main__': options = Job.Runner.getDefaultArgumentParser().parse_args() with Toil(options) as toil: rootJob = Job.wrapJobFn(root) toil.start(rootJob) userScript = self._getScriptSource(userScript) leader.deployScript(path=self.sitePackages, packagePath='foo.bar', script=userScript) leader.runOnAppliance('venv/bin/python', '-m', 'foo.bar', '--logDebug', '--batchSystem=mesos', '--mesosMaster=localhost:5050', '--retryCount=0', '--defaultMemory=10M', '--defaultDisk=10M', '/data/jobstore') def testDeferralWithFailureAndEncapsulation(self): """ Ensure that the following DAG succeeds: ┌───────────┠│ Root (W1) │ └───────────┘ │ ┌──────────┴─────────┠▼ â–¼ ┌────────────────┠┌────────────────────┠│ Deferring (W2) │ │ Encapsulating (W3) │â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— └────────────────┘ └────────────────────┘ â•‘ │ â•‘ â–¼ â–¼ ┌───────────────────┠┌────────────────┠│ Encapsulated (W3) │â•â•â•â•â•â•â•â•â•â•â•â•â•— │ Follow-on (W7) │ └───────────────────┘ â•‘ └────────────────┘ │ â•‘ ┌──────┴──────┠║ â–¼ â–¼ â–¼ ┌────────────â”┌────────────┠┌──────────────┠│ Dummy (W4) ││ Dummy (W5) │ │ Trigger (W6) │ └────────────┘└────────────┘ └──────────────┘ `Trigger` causes `Deferring` to crash. `Follow-on` runs next, detects `Deferring`'s left-overs and runs the deferred function. `Follow-on` is an instance of `Job` and the first job in its worker process. This test ensures that despite these circumstances, the user script is loaded before the deferred functions defined in it are being run. `Encapsulated` has two children to ensure that `Follow-on` is run in a new worker. That's the only way to guarantee that the user script has not been loaded yet, which would cause the test to succeed coincidentally. We want to test that auto-deploying and loading of the user script are done properly *before* deferred functions are being run and before any jobs have been executed by that worker. """ with self._venvApplianceCluster() as (leader, worker): def userScript(): import os import time from toil.job import Job from toil.common import Toil from toil.leader import FailedJobsException TIMEOUT = 10 def root(rootJob): def nullFile(): return rootJob.fileStore.jobStore.importFile('file:///dev/null') startFile = nullFile() endFile = nullFile() rootJob.addChildJobFn(deferring, startFile, endFile) encapsulatedJob = Job.wrapJobFn(encapsulated, startFile) encapsulatedJob.addChildFn(dummy) encapsulatedJob.addChildFn(dummy) encapsulatedJob.addFollowOnJobFn(trigger, endFile) encapsulatingJob = encapsulatedJob.encapsulate() rootJob.addChild(encapsulatingJob) def dummy(): pass def deferredFile(config): """ Return path to a file at the root of the job store, exploiting the fact that the job store is shared between leader and worker container. """ prefix = 'file:' locator = config.jobStore assert locator.startswith(prefix) return os.path.join(locator[len(prefix):], 'testDeferredFile') def deferred(deferredFilePath): """ The deferred function that is supposed to run. """ os.unlink(deferredFilePath) # noinspection PyUnusedLocal def deferring(job, startFile, endFile): """ A job that adds the deferred function and then crashes once the `trigger` job tells it to. """ job.defer(deferred, deferredFile(job._config)) jobStore = job.fileStore.jobStore jobStore.deleteFile(startFile) with jobStore.updateFileStream(endFile) as fH: fH.write(str(os.getpid())) timeout = time.time() + TIMEOUT while jobStore.fileExists(endFile): assert time.time() < timeout time.sleep(1) os.kill(os.getpid(), 9) def encapsulated(job, startFile): """ A job that waits until the `deferring` job is running and waiting to be crashed. """ timeout = time.time() + TIMEOUT while job.fileStore.jobStore.fileExists(startFile): assert time.time() < timeout time.sleep(1) def trigger(job, endFile): """ A job that determines the PID of the worker running the `deferring` job, tells the `deferring` job to crash and then waits for the corresponding worker process to end. By waiting we can be sure that the `follow-on` job finds the left-overs of the `deferring` job. """ import errno jobStore = job.fileStore.jobStore with jobStore.readFileStream(endFile) as fH: pid = int(fH.read()) os.kill(pid, 0) jobStore.deleteFile(endFile) timeout = time.time() + TIMEOUT while True: try: os.kill(pid, 0) except OSError as e: if e.errno == errno.ESRCH: break else: raise else: assert time.time() < timeout time.sleep(1) def tryUnlink(deferredFilePath): try: os.unlink(deferredFilePath) except OSError as e: if e.errno == errno.ENOENT: pass else: raise if __name__ == '__main__': import errno options = Job.Runner.getDefaultArgumentParser().parse_args() with Toil(options) as toil: deferredFilePath = deferredFile(toil.config) open(deferredFilePath, 'w').close() try: assert os.path.exists(deferredFilePath) try: toil.start(Job.wrapJobFn(root)) except FailedJobsException as e: assert e.numberOfFailedJobs == 2 # `root` and `deferring` assert not os.path.exists(deferredFilePath), \ 'Apparently, the deferred function did not run.' else: assert False, 'Workflow should not have succeeded.' finally: tryUnlink(deferredFilePath) userScript = self._getScriptSource(userScript) leader.deployScript(path=self.sitePackages, packagePath='foo.bar', script=userScript) leader.runOnAppliance('venv/bin/python', '-m', 'foo.bar', '--logDebug', '--batchSystem=mesos', '--mesosMaster=localhost:5050', '--retryCount=0', '--defaultMemory=10M', '--defaultDisk=10M', '/data/jobstore') toil-releases-3.24.0/src/toil/test/src/checkpointTest.py000066400000000000000000000107321362134276200232260ustar00rootroot00000000000000# Copyright (C) 2015-2017 Regents of the University of California # # 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. from __future__ import absolute_import from toil.job import Job from toil.test import ToilTest, slow, travis_test from toil.leader import FailedJobsException from toil.jobStores.abstractJobStore import NoSuchFileException class CheckpointTest(ToilTest): @travis_test def testCheckpointNotRetried(self): """A checkpoint job should not be retried if the workflow has a retryCount of 0.""" options = Job.Runner.getDefaultOptions(self._getTestJobStorePath()) options.retryCount = 0 # We set the workflow to *succeed* if the checkpointed job is # retried despite the retry count of 0. So, if the workflow # fails, this test succeeds. # This ends up being a bit confusing, but it's the easiest way # to check that the job wasn't retried short of parsing the # log. with self.assertRaises(FailedJobsException): Job.Runner.startToil(CheckRetryCount(numFailuresBeforeSuccess=1), options) @slow def testCheckpointRetriedOnce(self): """A checkpoint job should be retried exactly once if the workflow has a retryCount of 1.""" options = Job.Runner.getDefaultOptions(self._getTestJobStorePath()) options.retryCount = 1 # This should succeed (the checkpoint should be retried once, then succeed) try: Job.Runner.startToil(CheckRetryCount(numFailuresBeforeSuccess=1), options) except FailedJobsException: self.fail("The checkpoint job wasn't retried enough times.") # This should fail (the checkpoint should be retried once, then fail again) with self.assertRaises(FailedJobsException): Job.Runner.startToil(CheckRetryCount(numFailuresBeforeSuccess=2), options) @slow def testCheckpointedRestartSucceeds(self): """A checkpointed job should succeed on restart of a failed run if its child job succeeds.""" options = Job.Runner.getDefaultOptions(self._getTestJobStorePath()) # The child job should fail the first time with self.assertRaises(FailedJobsException): Job.Runner.startToil(CheckpointFailsFirstTime(), options) # The second time, everything should work options.restart = True try: Job.Runner.startToil(CheckpointFailsFirstTime(), options) except FailedJobsException: self.fail("Checkpointed workflow restart doesn't clean failures.") class CheckRetryCount(Job): """Fail N times, succeed on the next try.""" def __init__(self, numFailuresBeforeSuccess): super(CheckRetryCount, self).__init__(checkpoint=True) self.numFailuresBeforeSuccess = numFailuresBeforeSuccess def getNumRetries(self, fileStore): """Mark a retry in the fileStore, and return the number of retries so far.""" try: with fileStore.jobStore.readSharedFileStream("checkpointRun") as f: timesRun = int(f.read().decode('utf-8')) except NoSuchFileException: timesRun = 0 with fileStore.jobStore.writeSharedFileStream("checkpointRun") as f: f.write(str(timesRun + 1).encode('utf-8')) return timesRun def run(self, fileStore): retryCount = self.getNumRetries(fileStore) fileStore.logToMaster(str(retryCount)) if retryCount < self.numFailuresBeforeSuccess: self.addChild(AlwaysFail()) class AlwaysFail(Job): def run(self, fileStore): raise RuntimeError(":(") class CheckpointFailsFirstTime(Job): def __init__(self): super(CheckpointFailsFirstTime, self).__init__(checkpoint=True) def run(self, fileStore): self.addChild(FailOnce()) class FailOnce(Job): """Fail the first time the workflow is run, but succeed thereafter.""" def run(self, fileStore): if fileStore.jobStore.config.workflowAttemptNumber < 1: raise RuntimeError("first time around") toil-releases-3.24.0/src/toil/test/src/deferredFunctionTest.py000066400000000000000000000323571362134276200243740ustar00rootroot00000000000000# Copyright (C) 2015-2016 Regents of the University of California # # 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. from __future__ import absolute_import from __future__ import print_function from builtins import str from builtins import range from builtins import object import filecmp from abc import abstractmethod, ABCMeta from struct import pack, unpack from uuid import uuid4 from toil.job import Job from toil.fileStores.cachingFileStore import IllegalDeletionCacheError, CacheUnbalancedError, CachingFileStore from toil.test import ToilTest, slow, travis_test from toil.leader import FailedJobsException from toil.lib.threading import cpu_count from toil.jobStores.abstractJobStore import NoSuchFileException import collections import inspect import os import random import signal import time import pytest # Python 3 compatibility imports from six.moves import xrange from future.utils import with_metaclass # Some tests take too long on the AWS jobstore and are unquitable for CI. They can be # be run during manual tests by setting this to False. testingIsAutomatic = True class DeferredFunctionTest(with_metaclass(ABCMeta, ToilTest)): """ Test the deferred function system. """ # This determines what job store type to use. jobStoreType = 'file' def _getTestJobStore(self): if self.jobStoreType == 'file': return self._getTestJobStorePath() elif self.jobStoreType == 'aws': return 'aws:%s:cache-tests-%s' % (self.awsRegion(), uuid4()) elif self.jobStoreType == 'google': projectID = os.getenv('TOIL_GOOGLE_PROJECTID') return 'google:%s:cache-tests-%s' % (projectID, str(uuid4())) else: raise RuntimeError('Illegal job store type.') def setUp(self): super(DeferredFunctionTest, self).setUp() testDir = self._createTempDir() self.options = Job.Runner.getDefaultOptions(self._getTestJobStore()) self.options.logLevel = 'INFO' self.options.workDir = testDir self.options.clean = 'always' self.options.logFile = os.path.join(testDir, 'logFile') # Tests for the various defer possibilities @travis_test def testDeferredFunctionRunsWithMethod(self): """ Refer docstring in _testDeferredFunctionRuns. Test with Method """ self._testDeferredFunctionRuns(_writeNonLocalFilesMethod) @travis_test def testDeferredFunctionRunsWithClassMethod(self): """ Refer docstring in _testDeferredFunctionRuns. Test with Class Method """ self._testDeferredFunctionRuns(_writeNonLocalFilesClassMethod) @travis_test def testDeferredFunctionRunsWithLambda(self): """ Refer docstring in _testDeferredFunctionRuns. Test with Lambda """ self._testDeferredFunctionRuns(_writeNonLocalFilesLambda) def _testDeferredFunctionRuns(self, callableFn): """ Create 2 files. Make a job that writes data to them. Register a deferred function that deletes the two files (one passed as an arg, and one as a kwarg) and later assert that the files have been deleted. :param function callableFn: The function to use in the test. :return: None """ workdir = self._createTempDir(purpose='nonLocalDir') nonLocalFile1 = os.path.join(workdir, str(uuid4())) nonLocalFile2 = os.path.join(workdir, str(uuid4())) open(nonLocalFile1, 'w').close() open(nonLocalFile2, 'w').close() assert os.path.exists(nonLocalFile1) assert os.path.exists(nonLocalFile2) A = Job.wrapJobFn(callableFn, files=(nonLocalFile1, nonLocalFile2)) Job.Runner.startToil(A, self.options) assert not os.path.exists(nonLocalFile1) assert not os.path.exists(nonLocalFile2) @slow def testDeferredFunctionRunsWithFailures(self): """ Create 2 non local filesto use as flags. Create a job that registers a function that deletes one non local file. If that file exists, the job SIGKILLs itself. If it doesn't exist, the job registers a second deferred function to delete the second non local file and exits normally. Initially the first file exists, so the job should SIGKILL itself and neither deferred function will run (in fact, the second should not even be registered). On the restart, the first deferred function should run and the first file should not exist, but the second one should. We assert the presence of the second, then register the second deferred function and exit normally. At the end of the test, neither file should exist. Incidentally, this also tests for multiple registered deferred functions, and the case where a deferred function fails (since the first file doesn't exist on the retry). """ self.options.retryCount = 1 workdir = self._createTempDir(purpose='nonLocalDir') nonLocalFile1 = os.path.join(workdir, str(uuid4())) nonLocalFile2 = os.path.join(workdir, str(uuid4())) open(nonLocalFile1, 'w').close() open(nonLocalFile2, 'w').close() assert os.path.exists(nonLocalFile1) assert os.path.exists(nonLocalFile2) A = Job.wrapJobFn(_deferredFunctionRunsWithFailuresFn, files=(nonLocalFile1, nonLocalFile2)) Job.Runner.startToil(A, self.options) assert not os.path.exists(nonLocalFile1) assert not os.path.exists(nonLocalFile2) @slow def testNewJobsCanHandleOtherJobDeaths(self): """ Create 2 non-local files and then create 2 jobs. The first job registers a deferred job to delete the second non-local file, deletes the first non-local file and then kills itself. The second job waits for the first file to be deleted, then sleeps for a few seconds and then spawns a child. the child of the second does nothing. However starting it should handle the untimely demise of the first job and run the registered deferred function that deletes the first file. We assert the absence of the two files at the end of the run. """ # Check to make sure we can run two jobs in parallel cpus = cpu_count() assert cpus >= 2, "Not enough CPUs to run two tasks at once" # There can be no retries self.options.retryCount = 0 workdir = self._createTempDir(purpose='nonLocalDir') nonLocalFile1 = os.path.join(workdir, str(uuid4())) nonLocalFile2 = os.path.join(workdir, str(uuid4())) open(nonLocalFile1, 'w').close() open(nonLocalFile2, 'w').close() assert os.path.exists(nonLocalFile1) assert os.path.exists(nonLocalFile2) files = [nonLocalFile1, nonLocalFile2] root = Job() # A and B here must run in parallel for this to work A = Job.wrapJobFn(_testNewJobsCanHandleOtherJobDeaths_A, files=files, cores=1) B = Job.wrapJobFn(_testNewJobsCanHandleOtherJobDeaths_B, files=files, cores=1) C = Job.wrapJobFn(_testNewJobsCanHandleOtherJobDeaths_C, files=files, expectedResult=False, cores=1) root.addChild(A) root.addChild(B) B.addChild(C) try: Job.Runner.startToil(root, self.options) except FailedJobsException as e: pass @travis_test def testBatchSystemCleanupCanHandleWorkerDeaths(self): """ Create a non-local files. Create a job that registers a deferred job to delete the file and then kills itself. Assert that the file is missing after the pipeline fails. """ # There can be no retries self.options.retryCount = 0 workdir = self._createTempDir(purpose='nonLocalDir') nonLocalFile1 = os.path.join(workdir, str(uuid4())) nonLocalFile2 = os.path.join(workdir, str(uuid4())) # The first file has to be non zero or meseeks will go into an infinite sleep file1 = open(nonLocalFile1, 'w') file1.write('test') file1.close() open(nonLocalFile2, 'w').close() assert os.path.exists(nonLocalFile1) assert os.path.exists(nonLocalFile2) A = Job.wrapJobFn(_testNewJobsCanHandleOtherJobDeaths_A, files=(nonLocalFile1, nonLocalFile2)) try: Job.Runner.startToil(A, self.options) except FailedJobsException: pass assert not os.path.exists(nonLocalFile1) assert not os.path.exists(nonLocalFile2) def _writeNonLocalFilesMethod(job, files): """ Write some data to 2 files. Pass them to a registered deferred method. :param tuple files: the tuple of the two files to work with :return: None """ for nlf in files: with open(nlf, 'wb') as nonLocalFileHandle: nonLocalFileHandle.write(os.urandom(1 * 1024 * 1024)) job.defer(_deleteMethods._deleteFileMethod, files[0], nlf=files[1]) return None def _writeNonLocalFilesClassMethod(job, files): """ Write some data to 2 files. Pass them to a registered deferred class method. :param tuple files: the tuple of the two files to work with :return: None """ for nlf in files: with open(nlf, 'wb') as nonLocalFileHandle: nonLocalFileHandle.write(os.urandom(1 * 1024 * 1024)) job.defer(_deleteMethods._deleteFileClassMethod, files[0], nlf=files[1]) return None def _writeNonLocalFilesLambda(job, files): """ Write some data to 2 files. Pass them to a registered deferred Lambda. :param tuple files: the tuple of the two files to work with :return: None """ lmd = lambda x, nlf: [os.remove(x), os.remove(nlf)] for nlf in files: with open(nlf, 'wb') as nonLocalFileHandle: nonLocalFileHandle.write(os.urandom(1 * 1024 * 1024)) job.defer(lmd, files[0], nlf=files[1]) return None def _deferredFunctionRunsWithFailuresFn(job, files): """ Refer testDeferredFunctionRunsWithFailures :param tuple files: the tuple of the two files to work with :return: None """ job.defer(_deleteFile, files[0]) if os.path.exists(files[0]): os.kill(os.getpid(), signal.SIGKILL) else: assert os.path.exists(files[1]) job.defer(_deleteFile, files[1]) def _deleteFile(nonLocalFile, nlf=None): """ Delete nonLocalFile and nlf :param str nonLocalFile: :param str nlf: :return: None """ os.remove(nonLocalFile) if nlf is not None: os.remove(nlf) def _testNewJobsCanHandleOtherJobDeaths_A(job, files): """ Defer deletion of files[1], then wait for _testNewJobsCanHandleOtherJobDeaths_B to start up, and finally delete files[0] before sigkilling self. :param tuple files: the tuple of the two files to work with :return: None """ # Write the pid to files[1] such that we can be sure that this process has died before # we spawn the next job that will do the cleanup. with open(files[1], 'w') as fileHandle: fileHandle.write(str(os.getpid())) job.defer(_deleteFile, files[1]) while os.stat(files[0]).st_size == 0: time.sleep(0.5) os.remove(files[0]) os.kill(os.getpid(), signal.SIGKILL) def _testNewJobsCanHandleOtherJobDeaths_B(job, files): # Write something to files[0] such that we can be sure that this process has started # before _testNewJobsCanHandleOtherJobDeaths_A kills itself. with open(files[0], 'w') as fileHandle: fileHandle.write(str(os.getpid())) while os.path.exists(files[0]): time.sleep(0.5) # Get the pid of _testNewJobsCanHandleOtherJobDeaths_A and wait for it to truly be dead. with open(files[1], 'r') as fileHandle: meeseeksPID = int(fileHandle.read()) while CachingFileStore._pidExists(meeseeksPID): time.sleep(0.5) # Now that we are convinced that_testNewJobsCanHandleOtherJobDeaths_A has died, we can # spawn the next job return None def _testNewJobsCanHandleOtherJobDeaths_C(job, files, expectedResult): """ Asserts whether the files exist or not. :param Job job: Job :param list files: list of files to test :param bool expectedResult: Are we expecting the files to exist or not? """ for testFile in files: assert os.path.exists(testFile) is expectedResult class _deleteMethods(object): @staticmethod def _deleteFileMethod(nonLocalFile, nlf=None): """ Delete nonLocalFile and nlf :return: None """ os.remove(nonLocalFile) if nlf is not None: os.remove(nlf) @classmethod def _deleteFileClassMethod(cls, nonLocalFile, nlf=None): """ Delete nonLocalFile and nlf :return: None """ os.remove(nonLocalFile) if nlf is not None: os.remove(nlf) toil-releases-3.24.0/src/toil/test/src/dockerCheckTest.py000066400000000000000000000101461362134276200233030ustar00rootroot00000000000000# Copyright (C) 2015-2018 Regents of the University of California # # 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. from __future__ import absolute_import, print_function from toil.test import ToilTest, needs_appliance from toil import checkDockerImageExists, parseDockerAppliance from docker.errors import ImageNotFound # requires internet @needs_appliance class dockerCheckTests(ToilTest): """ Tests initial checking of whether a docker image exists in the specified repository or not. """ def setUp(self): pass def testOfficialUbuntuRepo(self): """Image exists. This should pass.""" ubuntu_repo = 'ubuntu:latest' assert checkDockerImageExists(ubuntu_repo) def testBroadDockerRepo(self): """Image exists. This should pass.""" broad_repo = 'broadinstitute/genomes-in-the-cloud:2.0.0' assert checkDockerImageExists(broad_repo) def testBroadDockerRepoBadTag(self): """Bad tag. This should raise.""" broad_repo = 'broadinstitute/genomes-in-the-cloud:-----' with self.assertRaises(ImageNotFound): checkDockerImageExists(broad_repo) def testNonexistentRepo(self): """Bad image. This should raise.""" nonexistent_repo = '------:-----' with self.assertRaises(ImageNotFound): checkDockerImageExists(nonexistent_repo) def testToilQuayRepo(self): """Image exists. Should pass.""" toil_repo = 'quay.io/ucsc_cgl/toil:latest' assert checkDockerImageExists(toil_repo) def testBadQuayRepoNTag(self): """Bad repo and tag. This should raise.""" nonexistent_quay_repo = 'quay.io/--------:---' with self.assertRaises(ImageNotFound): checkDockerImageExists(nonexistent_quay_repo) def testBadQuayRepo(self): """Bad repo. This should raise.""" nonexistent_quay_repo = 'quay.io/--------:latest' with self.assertRaises(ImageNotFound): checkDockerImageExists(nonexistent_quay_repo) def testBadQuayTag(self): """Bad tag. This should raise.""" nonexistent_quay_repo = 'quay.io/ucsc_cgl/toil:---' with self.assertRaises(ImageNotFound): checkDockerImageExists(nonexistent_quay_repo) def testGoogleRepo(self): """Image exists. Should pass.""" google_repo = 'gcr.io/google-containers/busybox:latest' assert checkDockerImageExists(google_repo) def testBadGoogleRepo(self): """Bad repo and tag. This should raise.""" nonexistent_google_repo = 'gcr.io/google-containers/--------:---' with self.assertRaises(ImageNotFound): checkDockerImageExists(nonexistent_google_repo) def testApplianceParser(self): """Test that a specified appliance is parsed correctly.""" docker_list = ['ubuntu:latest', 'ubuntu', 'broadinstitute/genomes-in-the-cloud:2.0.0', 'quay.io/ucsc_cgl/toil:latest', 'gcr.io/google-containers/busybox:latest'] parsings = [] for image in docker_list: registryName, imageName, tag = parseDockerAppliance(image) parsings.append([registryName, imageName, tag]) expected_parsings = [['docker.io', 'ubuntu', 'latest'], ['docker.io', 'ubuntu', 'latest'], ['docker.io', 'broadinstitute/genomes-in-the-cloud', '2.0.0'], ['quay.io', 'ucsc_cgl/toil', 'latest'], ['gcr.io', 'google-containers/busybox', 'latest']] assert parsings == expected_parsings toil-releases-3.24.0/src/toil/test/src/fileStoreTest.py000066400000000000000000001616761362134276200230510ustar00rootroot00000000000000# Copyright (C) 2015-2016 Regents of the University of California # # 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. from __future__ import absolute_import from __future__ import print_function from builtins import str from builtins import range from builtins import object import filecmp from abc import abstractmethod, ABCMeta from struct import pack, unpack from uuid import uuid4 from toil.job import Job from toil.fileStores import FileID from toil.fileStores.cachingFileStore import IllegalDeletionCacheError, CacheUnbalancedError, CachingFileStore from toil.test import ToilTest, needs_aws_ec2, needs_google, slow, travis_test from toil.leader import FailedJobsException from toil.jobStores.abstractJobStore import NoSuchFileException from toil.realtimeLogger import RealtimeLogger import collections import datetime import inspect import logging import os import random import signal import sys import time import pytest import subprocess # Python 3 compatibility imports from six.moves import xrange from future.utils import with_metaclass if sys.version_info[0] < 3: # Define a usable FileNotFoundError as will be raised by os.remove on a # nonexistent file. FileNotFoundError = OSError # Some tests take too long on the AWS jobstore and are unquitable for CI. They can be # be run during manual tests by setting this to False. testingIsAutomatic = True logger = logging.getLogger(__name__) class hidden(object): """ Hiding the abstract test classes from the Unittest loader so it can be inherited in different test suites for the different job stores. """ class AbstractFileStoreTest(with_metaclass(ABCMeta, ToilTest)): """ An abstract base class for testing the various general functions described in :class:toil.fileStores.abstractFileStore.AbstractFileStore """ # This is overwritten in the inheriting classs jobStoreType = None def _getTestJobStore(self): if self.jobStoreType == 'file': return self._getTestJobStorePath() elif self.jobStoreType == 'aws': return 'aws:%s:cache-tests-%s' % (self.awsRegion(), str(uuid4())) elif self.jobStoreType == 'google': projectID = os.getenv('TOIL_GOOGLE_PROJECTID') return 'google:%s:cache-tests-%s' % (projectID, str(uuid4())) else: raise RuntimeError('Illegal job store type.') def setUp(self): super(hidden.AbstractFileStoreTest, self).setUp() testDir = self._createTempDir() self.options = Job.Runner.getDefaultOptions(self._getTestJobStore()) self.options.logLevel = 'DEBUG' self.options.realTimeLogging = True self.options.workDir = testDir self.options.clean = 'always' self.options.logFile = os.path.join(testDir, 'logFile') @staticmethod def _uselessFunc(job): """ I do nothing. Don't judge me. """ return None # Sanity test @travis_test def testToilIsNotBroken(self): """ Runs a simple DAG to test if if any features other that caching were broken. """ A = Job.wrapJobFn(self._uselessFunc) B = Job.wrapJobFn(self._uselessFunc) C = Job.wrapJobFn(self._uselessFunc) D = Job.wrapJobFn(self._uselessFunc) A.addChild(B) A.addChild(C) B.addChild(D) C.addChild(D) Job.Runner.startToil(A, self.options) # Test filestore operations. This is a slightly less intense version of the cache specific # test `testReturnFileSizes` @slow def testFileStoreOperations(self): """ Write a couple of files to the jobstore. Delete a couple of them. Read back written and locally deleted files. """ workdir = self._createTempDir(purpose='nonLocalDir') F = Job.wrapJobFn(self._testFileStoreOperations, nonLocalDir=workdir, numIters=30, disk='2G') Job.Runner.startToil(F, self.options) @staticmethod def _testFileStoreOperations(job, nonLocalDir, numIters=100): """ Aux function for testFileStoreOperations Conduct numIters operations. """ work_dir = job.fileStore.getLocalTempDir() writtenFiles = {} # fsID: (size, isLocal) localFileIDs = set() # Add one file for the sake of having something in the job store writeFileSize = random.randint(0, 30) cls = hidden.AbstractNonCachingFileStoreTest fsId, _ = cls._writeFileToJobStore(job, isLocalFile=True, nonLocalDir=nonLocalDir, fileMB=writeFileSize) writtenFiles[fsId] = writeFileSize localFileIDs.add(list(writtenFiles.keys())[0]) i = 0 while i <= numIters: randVal = random.random() if randVal < 0.33: # Write writeFileSize = random.randint(0, 30) isLocalFile = True if random.random() <= 0.5 else False fsID, _ = cls._writeFileToJobStore(job, isLocalFile=isLocalFile, nonLocalDir=nonLocalDir, fileMB=writeFileSize) writtenFiles[fsID] = writeFileSize localFileIDs.add(fsID) else: if len(writtenFiles) == 0: continue else: fsID, rdelFileSize = random.choice(list(writtenFiles.items())) rdelRandVal = random.random() if randVal < 0.66: # Read mutable = True if random.random() <= 0.5 else False cache = True if random.random() <= 0.5 else False job.fileStore.readGlobalFile(fsID, '/'.join([work_dir, str(uuid4())]), cache=cache, mutable=mutable) localFileIDs.add(fsID) else: # Delete if rdelRandVal <= 0.5: # Local Delete if fsID not in localFileIDs: continue job.fileStore.deleteLocalFile(fsID) else: # Global Delete job.fileStore.deleteGlobalFile(fsID) writtenFiles.pop(fsID) if fsID in localFileIDs: localFileIDs.remove(fsID) i += 1 @staticmethod def _writeFileToJobStore(job, isLocalFile, nonLocalDir=None, fileMB=1): """ This function creates a file and writes it to the jobstore. :param bool isLocalFile: Is the file local(T) or Non-Local(F)? :param str nonLocalDir: A dir to write the file to. If unspecified, a local directory is created. :param int fileMB: Size of the created file in MB """ if isLocalFile: work_dir = job.fileStore.getLocalTempDir() else: assert nonLocalDir is not None work_dir = nonLocalDir with open(os.path.join(work_dir, str(uuid4())), 'wb') as testFile: testFile.write(os.urandom(fileMB * 1024 * 1024)) return job.fileStore.writeGlobalFile(testFile.name), testFile class AbstractNonCachingFileStoreTest(with_metaclass(ABCMeta, AbstractFileStoreTest)): """ Abstract tests for the the various functions in :class:toil.fileStores.nonCachingFileStore.NonCachingFileStore. These tests are general enough that they can also be used for :class:toil.fileStores.CachingFileStore. """ def setUp(self): super(hidden.AbstractNonCachingFileStoreTest, self).setUp() self.options.disableCaching = True class AbstractCachingFileStoreTest(with_metaclass(ABCMeta, AbstractFileStoreTest)): """ Abstract tests for the the various cache-related functions in :class:toil.fileStores.cachingFileStore.CachingFileStore. """ def setUp(self): super(hidden.AbstractCachingFileStoreTest, self).setUp() self.options.disableCaching = False @slow def testExtremeCacheSetup(self): """ Try to create the cache with bad worker active and then have 10 child jobs try to run in the chain. This tests whether the cache is created properly even when the job crashes randomly. """ if testingIsAutomatic and self.jobStoreType != 'file': self.skipTest("To save time") self.options.retryCount = 20 self.options.badWorker = 0.5 self.options.badWorkerFailInterval = 0.1 for test in range(0, 20): E = Job.wrapJobFn(self._uselessFunc) F = Job.wrapJobFn(self._uselessFunc) jobs = {} for i in range(0, 10): jobs[i] = Job.wrapJobFn(self._uselessFunc) E.addChild(jobs[i]) jobs[i].addChild(F) Job.Runner.startToil(E, self.options) @slow def testCacheEvictionPartialEvict(self): """ Ensure the cache eviction happens as expected. Two files (20MB and 30MB) are written sequentially into the job store in separate jobs. The cache max is force set to 50MB. A Third Job requests 10MB of disk requiring eviction of the 1st file. Ensure that the behavior is as expected. """ self._testValidityOfCacheEvictTest() # Explicitly set clean to always so even the failed cases get cleaned (This will # overwrite the value set in setUp if it is ever changed in the future) self.options.clean = 'always' self._testCacheEviction(file1MB=20, file2MB=30, diskRequestMB=10) @slow def testCacheEvictionTotalEvict(self): """ Ensure the cache eviction happens as expected. Two files (20MB and 30MB) are written sequentially into the job store in separate jobs. The cache max is force set to 50MB. A Third Job requests 10MB of disk requiring eviction of the 1st file. Ensure that the behavior is as expected. """ self._testValidityOfCacheEvictTest() # Explicitly set clean to always so even the failed cases get cleaned (This will # overwrite the value set in setUp if it is ever changed in the future) self.options.clean = 'always' self._testCacheEviction(file1MB=20, file2MB=30, diskRequestMB=30) @slow def testCacheEvictionFailCase(self): """ Ensure the cache eviction happens as expected. Two files (20MB and 30MB) are written sequentially into the job store in separate jobs. The cache max is force set to 50MB. A Third Job requests 10MB of disk requiring eviction of the 1st file. Ensure that the behavior is as expected. """ self._testValidityOfCacheEvictTest() # Explicitly set clean to always so even the failed cases get cleaned (This will # overwrite the value set in setUp if it is ever changed in the future) self.options.clean = 'always' self._testCacheEviction(file1MB=20, file2MB=30, diskRequestMB=60) def _testValidityOfCacheEvictTest(self): # If the job store and cache are on the same file system, file # sizes are accounted for by the job store and are not reflected in # the cache hence this test is redundant (caching will be free). if not self.options.jobStore.startswith(('aws', 'google')): workDirDev = os.stat(self.options.workDir).st_dev jobStoreDev = os.stat(os.path.dirname(self.options.jobStore)).st_dev if workDirDev == jobStoreDev: self.skipTest('Job store and working directory are on the same filesystem.') def _testCacheEviction(self, file1MB, file2MB, diskRequestMB): """ Ensure the cache eviction happens as expected. Two files (20MB and 30MB) are written sequentially into the job store in separate jobs. The cache max is force set to 50MB. A Third Job requests either 10, 30 or 60MB -- requiring eviction of 1 file, both files, or results in an error due to lack of space, respectively. Ensure that the behavior is as expected. """ self.options.retryCount = 0 if diskRequestMB > 50: # This can be non int as it will never reach _probeJobReqs expectedResult = 'Fail' else: expectedResult = 50 - file1MB if diskRequestMB <= file1MB else 0 try: A = Job.wrapJobFn(self._writeFileToJobStoreWithAsserts, isLocalFile=True, fileMB=file1MB) # Sleep for 1 second after writing the first file so that their ctimes are # guaranteed to be distinct for the purpose of this test. B = Job.wrapJobFn(self._sleepy, timeToSleep=1) C = Job.wrapJobFn(self._writeFileToJobStoreWithAsserts, isLocalFile=True, fileMB=file2MB) D = Job.wrapJobFn(self._adjustCacheLimit, newTotalMB=50, disk='0M') E = Job.wrapJobFn(self._uselessFunc, disk=''.join([str(diskRequestMB), 'M'])) # Set it to > 2GB such that the cleanup jobs don't die in the non-fail cases F = Job.wrapJobFn(self._adjustCacheLimit, newTotalMB=5000, disk='10M') G = Job.wrapJobFn(self._probeJobReqs, sigmaJob=100, cached=expectedResult, disk='100M') A.addChild(B) B.addChild(C) C.addChild(D) D.addChild(E) E.addChild(F) F.addChild(G) Job.Runner.startToil(A, self.options) except FailedJobsException as err: with open(self.options.logFile) as f: logContents = f.read() if CacheUnbalancedError.message in logContents: self.assertEqual(expectedResult, 'Fail') else: self.fail('Toil did not raise the expected CacheUnbalancedError but failed for some other reason') @staticmethod def _writeFileToJobStoreWithAsserts(job, isLocalFile, nonLocalDir=None, fileMB=1, expectAsyncUpload=True): """ This function creates a file and writes it to the jobstore. :param bool isLocalFile: Is the file local(T) (i.e. in the file store managed temp dir) or Non-Local(F)? Non-local files should not be cached. :param str nonLocalDir: A dir to write the file to. If unspecified, a local directory is created. :param int fileMB: Size of the created file in MB :param bool expectAsyncUpload: Whether we expect the upload to hit the job store later(T) or immediately(F) """ cls = hidden.AbstractNonCachingFileStoreTest fsID, testFile = cls._writeFileToJobStore(job, isLocalFile, nonLocalDir, fileMB) actual = os.stat(testFile.name).st_nlink # If the caching is free, the job store must have hard links to # everything the file store has. expectJobStoreLink = job.fileStore.cachingIsFree() # How many links ought this file to have? expected = 1 if isLocalFile: # We expect a hard link into the cache and not a copy expected += 1 if expectJobStoreLink and not expectAsyncUpload: # We also expect a link in the job store expected += 1 assert actual == expected, 'Should have %d links. Got %d.' % (expected, actual) logger.info('Uploaded %s with %d links', fsID, actual) if not isLocalFile: # Make sure it isn't cached if we don't want it to be assert not job.fileStore.fileIsCached(fsID), "File uploaded from non-local-temp directory %s should not be cached" % nonLocalDir return fsID @staticmethod def _sleepy(job, timeToSleep): """ I'm waiting for prince charming... but only for timeToSleep seconds. :param int timeToSleep: Time in seconds """ time.sleep(timeToSleep) @staticmethod def _adjustCacheLimit(job, newTotalMB): """ This function tells the cache to adopt a new "total" value = newTotalMB, changing the maximum cache disk space allowed for the run. :param int newTotalMB: New total cache disk space limit in MB. """ # Convert to bytes and pass on to the actual cache job.fileStore.adjustCacheLimit(float(newTotalMB * 1024 * 1024)) @staticmethod def _probeJobReqs(job, total=None, cached=None, sigmaJob=None): """ Probes the cacheLockFile to ensure the values for total, disk and cache are as expected. Can also specify combinations of the requirements if desired. :param int total: Expected Total Space available for caching in MB. :param int cached: Expected Total size of files in the cache in MB. :param int sigmaJob: Expected sum of job requirements in MB. """ RealtimeLogger.info('Probing job requirements') valueDict = locals() assert (total or cached or sigmaJob) # Work out which function to call for which value toCall = {'total': job.fileStore.getCacheLimit, 'cached': job.fileStore.getCacheUsed, 'sigmaJob': job.fileStore.getCacheExtraJobSpace} for value in ('total', 'cached', 'sigmaJob'): # If the value wasn't provided, it is None and should be ignored if valueDict[value] is None: continue RealtimeLogger.info('Probing cache state: %s', value) expectedBytes = valueDict[value] * 1024 * 1024 cacheInfoBytes = toCall[value]() RealtimeLogger.info('Got %d for %s; expected %d', cacheInfoBytes, value, expectedBytes) assert cacheInfoBytes == expectedBytes, 'Testing %s: Expected ' % value + \ '%s but got %s.' % (expectedBytes, cacheInfoBytes) @slow def testAsyncWriteWithCaching(self): """ Ensure the Async Writing of files happens as expected. The first Job forcefully modifies the cache size to 1GB. The second asks for 1GB of disk and writes a 900MB file into cache then rewrites it to the job store triggering an async write since the two unique jobstore IDs point to the same local file. Also, the second write is not cached since the first was written to cache, and there "isn't enough space" to cache the second. Imediately assert that the second write isn't cached, and is being asynchronously written to the job store. Attempting to get the file from the jobstore should not fail. """ self.options.retryCount = 0 self.options.logLevel = 'DEBUG' A = Job.wrapJobFn(self._adjustCacheLimit, newTotalMB=1024, disk='1G') B = Job.wrapJobFn(self._doubleWriteFileToJobStore, fileMB=850, disk='900M') C = Job.wrapJobFn(self._readFromJobStoreWithoutAssertions, fsID=B.rv(), disk='1G') # Set it to > 2GB such that the cleanup jobs don't die. D = Job.wrapJobFn(self._adjustCacheLimit, newTotalMB=5000, disk='1G') A.addChild(B) B.addChild(C) C.addChild(D) Job.Runner.startToil(A, self.options) @staticmethod def _doubleWriteFileToJobStore(job, fileMB): """ Write a local file to job store, then write it again. The second should trigger an async write. :param job: job :param fileMB: File Size :return: Job store file ID for second written file """ job.fileStore.logToMaster('Double writing a file into job store') work_dir = job.fileStore.getLocalTempDir() with open(os.path.join(work_dir, str(uuid4())), 'wb') as testFile: testFile.write(os.urandom(fileMB * 1024 * 1024)) job.fileStore.logToMaster('Writing copy 1 and discarding ID') job.fileStore.writeGlobalFile(testFile.name) job.fileStore.logToMaster('Writing copy 2 and saving ID') fsID = job.fileStore.writeGlobalFile(testFile.name) job.fileStore.logToMaster('Copy 2 ID: {}'.format(fsID)) hidden.AbstractCachingFileStoreTest._readFromJobStoreWithoutAssertions(job, fsID) job.fileStore.logToMaster('Writing copy 3 and returning ID') return job.fileStore.writeGlobalFile(testFile.name) @staticmethod def _readFromJobStoreWithoutAssertions(job, fsID): """ Reads a file from the job store. That will be all, thank you. :param job: job :param fsID: Job store file ID for the read file :return: None """ job.fileStore.logToMaster('Reading the written file') job.fileStore.readGlobalFile(fsID) # writeGlobalFile tests @travis_test def testWriteNonLocalFileToJobStore(self): """ Write a file not in localTempDir to the job store. Such a file should not be cached. Ensure the file is not cached. """ workdir = self._createTempDir(purpose='nonLocalDir') A = Job.wrapJobFn(self._writeFileToJobStoreWithAsserts, isLocalFile=False, nonLocalDir=workdir) Job.Runner.startToil(A, self.options) @travis_test def testWriteLocalFileToJobStore(self): """ Write a file from the localTempDir to the job store. Such a file will be cached by default. Ensure the file is cached. """ A = Job.wrapJobFn(self._writeFileToJobStoreWithAsserts, isLocalFile=True) Job.Runner.startToil(A, self.options) # readGlobalFile tests @travis_test def testReadCacheMissFileFromJobStoreWithoutCachingReadFile(self): """ Read a file from the file store that does not have a corresponding cached copy. Do not cache the read file. Ensure the number of links on the file are appropriate. """ self._testCacheMissFunction(cacheReadFile=False) @travis_test def testReadCacheMissFileFromJobStoreWithCachingReadFile(self): """ Read a file from the file store that does not have a corresponding cached copy. Cache the read file. Ensure the number of links on the file are appropriate. """ self._testCacheMissFunction(cacheReadFile=True) def _testCacheMissFunction(self, cacheReadFile): """ This is the function that actually does what the 2 cache miss functions want. :param cacheReadFile: Does the read file need to be cached(T) or not(F) """ workdir = self._createTempDir(purpose='nonLocalDir') A = Job.wrapJobFn(self._writeFileToJobStoreWithAsserts, isLocalFile=False, nonLocalDir=workdir) B = Job.wrapJobFn(self._readFromJobStore, isCachedFile=False, cacheReadFile=cacheReadFile, fsID=A.rv()) A.addChild(B) Job.Runner.startToil(A, self.options) @staticmethod def _readFromJobStore(job, isCachedFile, cacheReadFile, fsID, isTest=True): """ Read a file from the filestore. If the file was cached, ensure it was hard linked correctly. If it wasn't, ensure it was put into cache. Note that we may see hard links when we don't expect it based on caching, because immutable reads from the FileJobStore can be fulfilled by hardlinks. We only do immutable reads. :param bool isCachedFile: Flag. Was the read file read from cache(T)? If so, we look for a hard link. :param bool cacheReadFile: Should the the file that is read be cached(T)? :param str fsID: job store file ID :param bool isTest: Is this being run as a test(T) or an accessory to another test(F)? """ work_dir = job.fileStore.getLocalTempDir() wantHardLink = False if isCachedFile: outfile = job.fileStore.readGlobalFile(fsID, '/'.join([work_dir, 'temp']), mutable=False) wantHardLink = True else: if cacheReadFile: outfile = job.fileStore.readGlobalFile(fsID, '/'.join([work_dir, 'temp']), cache=True, mutable=False) wantHardLink = True else: assert not job.fileStore.fileIsCached(fsID), "File mistakenly cached before read" outfile = job.fileStore.readGlobalFile(fsID, '/'.join([work_dir, 'temp']), cache=False, mutable=False) assert not job.fileStore.fileIsCached(fsID), "File mistakenly cached after read" wantHardLink = False if isTest: actual = os.stat(outfile).st_nlink if wantHardLink: assert actual > 1, 'Should have multiple links for file that was %s and %s. Got %i.' % ('cached' if isCachedFile else 'not cached', 'saved' if cacheReadFile else 'not saved', actual) # We need to accept harf links even if we don't want them, # because we may get them straight from the FileJobStore since # we asked for immutable reads. return None else: return outfile @travis_test def testReadCachHitFileFromJobStore(self): """ Read a file from the file store that has a corresponding cached copy. Ensure the number of links on the file are appropriate. """ A = Job.wrapJobFn(self._writeFileToJobStoreWithAsserts, isLocalFile=True) B = Job.wrapJobFn(self._readFromJobStore, isCachedFile=True, cacheReadFile=None, fsID=A.rv()) A.addChild(B) Job.Runner.startToil(A, self.options) @slow def testMultipleJobsReadSameCacheHitGlobalFile(self): """ Write a local file to the job store (hence adding a copy to cache), then have 10 jobs read it. Assert cached file size never goes up, assert unused job required disk space is always: (a multiple of job reqs) - (number of current file readers * filesize). At the end, assert the cache shows unused job-required space = 0. """ self._testMultipleJobsReadGlobalFileFunction(cacheHit=True) @slow def testMultipleJobsReadSameCacheMissGlobalFile(self): """ Write a non-local file to the job store(hence no cached copy), then have 10 jobs read it. Assert cached file size never goes up, assert unused job required disk space is always: (a multiple of job reqs) - (number of current file readers * filesize). At the end, assert the cache shows unused job-required space = 0. """ self._testMultipleJobsReadGlobalFileFunction(cacheHit=False) def _testMultipleJobsReadGlobalFileFunction(self, cacheHit): """ This function does what the two Multiple File reading tests want to do :param bool cacheHit: Is the test for the CacheHit case(T) or cacheMiss case(F) """ dirPurpose = 'tempWriteDir' if cacheHit else 'nonLocalDir' workdir = self._createTempDir(purpose=dirPurpose) with open(os.path.join(workdir, 'test'), 'w') as x: x.write(str(0)) A = Job.wrapJobFn(self._writeFileToJobStoreWithAsserts, isLocalFile=cacheHit, nonLocalDir=workdir, fileMB=256) B = Job.wrapJobFn(self._probeJobReqs, sigmaJob=100, disk='100M') jobs = {} for i in range(0, 10): jobs[i] = Job.wrapJobFn(self._multipleFileReader, diskMB=1024, fsID=A.rv(), maxWriteFile=os.path.abspath(x.name), disk='1G', memory='10M', cores=1) A.addChild(jobs[i]) jobs[i].addChild(B) Job.Runner.startToil(A, self.options) with open(x.name, 'r') as y: assert int(y.read()) > 2 @staticmethod def _multipleFileReader(job, diskMB, fsID, maxWriteFile): """ Read a file from the job store immutable and explicitly ask to have it in the cache. If caching files is free, assert used cache space is zero, else assert it is equal to the read file. Also assert the sum job reqs + (number of readers of file * filesize) is and integer multiple of the disk requirements provided to this job. :param int diskMB: disk requirements provided to the job :param str fsID: job store file ID :param str maxWriteFile: path to file where the max number of concurrent readers of file will be written """ work_dir = job.fileStore.getLocalTempDir() outfile = job.fileStore.readGlobalFile(fsID, '/'.join([work_dir, 'temp']), cache=True, mutable=False) diskBytes = diskMB * 1024 * 1024 fileStats = os.stat(outfile) fileSize = fileStats.st_size currentReaders = job.fileStore.getFileReaderCount(fsID) extraJobSpace = job.fileStore.getCacheExtraJobSpace() usedCache = job.fileStore.getCacheUsed() logger.info('Extra job space: %s', str(extraJobSpace)) logger.info('Current file readers: %s', str(currentReaders)) logger.info('File size: %s', str(fileSize)) logger.info('Job disk bytes: %s', str(diskBytes)) logger.info('Used cache: %s', str(usedCache)) with open(maxWriteFile, 'r+') as x: prev_max = int(x.read()) x.seek(0) x.truncate() x.write(str(max(prev_max, currentReaders))) if job.fileStore.cachingIsFree(): # No space should be used when caching is free assert usedCache == 0.0 else: # The right amount of space should be used otherwise assert usedCache == fileSize # Make sure that there's no over-usage of job requirements assert ((extraJobSpace + currentReaders * fileSize) % diskBytes) == 0.0 # Sleep so there's no race conditions where a job ends before another can get a hold of # the file time.sleep(3) @staticmethod def _writeExportGlobalFile(job): fileName = os.path.join(job.fileStore.getLocalTempDir(), 'testfile') with open(fileName, 'wb') as f: f.write(os.urandom(1024 * 30000)) # 30 Mb outputFile = os.path.join(job.fileStore.getLocalTempDir(), 'exportedFile') job.fileStore.exportFile(job.fileStore.writeGlobalFile(fileName), 'File://' + outputFile) if not filecmp.cmp(fileName, outputFile): logger.warning('Source file: %s', str(os.stat(fileName))) logger.warning('Destination file: %s', str(os.stat(outputFile))) raise RuntimeError("File {} did not properly get copied to {}".format(fileName, outputFile)) @slow def testFileStoreExportFile(self): # Tests that files written to job store can be immediately exported # motivated by https://github.com/BD2KGenomics/toil/issues/1469 root = Job.wrapJobFn(self._writeExportGlobalFile) Job.Runner.startToil(root, self.options) # Testing for the return of file sizes to the sigma job pool. @slow def testReturnFileSizes(self): """ Write a couple of files to the jobstore. Delete a couple of them. Read back written and locally deleted files. Ensure that after every step that the cache is in a valid state. """ workdir = self._createTempDir(purpose='nonLocalDir') F = Job.wrapJobFn(self._returnFileTestFn, jobDisk=2 * 1024 * 1024 * 1024, initialCachedSize=0, nonLocalDir=workdir, disk='2G') Job.Runner.startToil(F, self.options) @slow def testReturnFileSizesWithBadWorker(self): """ Write a couple of files to the jobstore. Delete a couple of them. Read back written and locally deleted files. Ensure that after every step that the cache is in a valid state. """ self.options.retryCount = 20 self.options.badWorker = 0.5 self.options.badWorkerFailInterval = 0.1 workdir = self._createTempDir(purpose='nonLocalDir') F = Job.wrapJobFn(self._returnFileTestFn, jobDisk=2 * 1024 * 1024 * 1024, initialCachedSize=0, nonLocalDir=workdir, numIters=30, disk='2G') Job.Runner.startToil(F, self.options) @staticmethod def _returnFileTestFn(job, jobDisk, initialCachedSize, nonLocalDir, numIters=100): """ Aux function for jobCacheTest.testReturnFileSizes Conduct numIters operations and ensure the cache has the right amount of data in it at all times. Track the cache calculations even thought they won't be used in filejobstore Assumes nothing is evicted from the cache. :param float jobDisk: The value of disk passed to this job. """ cached = initialCachedSize RealtimeLogger.info('Expecting %d bytes cached initially', cached) work_dir = job.fileStore.getLocalTempDir() writtenFiles = {} # fsID: (size, isLocal) localFileIDs = collections.defaultdict(list) # fsid: local/non-local/mutable/immutable # Add one file for the sake of having something in the job store writeFileSize = random.randint(0, 30) jobDisk -= writeFileSize * 1024 * 1024 # We keep jobDisk in sync with the amount of free space the job # still has that the file store doesn't know it has used. cls = hidden.AbstractCachingFileStoreTest fsId = cls._writeFileToJobStoreWithAsserts(job, isLocalFile=True, fileMB=writeFileSize) writtenFiles[fsId] = writeFileSize if job.fileStore.fileIsCached(list(writtenFiles.keys())[0]): cached += writeFileSize * 1024 * 1024 RealtimeLogger.info('Expecting %d bytes cached because file of %d MB is cached', cached, writeFileSize) else: RealtimeLogger.info('Expecting %d bytes cached because file of %d MB is not cached', cached, writeFileSize) localFileIDs[list(writtenFiles.keys())[0]].append('local') RealtimeLogger.info('Checking for %d bytes cached', cached) cls._requirementsConcur(job, jobDisk, cached) i = 0 while i <= numIters: randVal = random.random() if randVal < 0.33: # Write RealtimeLogger.info('Writing a file') writeFileSize = random.randint(0, 30) if random.random() <= 0.5: # Write a local file RealtimeLogger.info('Writing a local file of %d MB', writeFileSize) fsID = cls._writeFileToJobStoreWithAsserts(job, isLocalFile=True, fileMB=writeFileSize) writtenFiles[fsID] = writeFileSize localFileIDs[fsID].append('local') jobDisk -= writeFileSize * 1024 * 1024 if job.fileStore.fileIsCached(fsID): cached += writeFileSize * 1024 * 1024 RealtimeLogger.info('Expecting %d bytes cached because file of %d MB is cached', cached, writeFileSize) else: RealtimeLogger.info('Expecting %d bytes cached because file of %d MB is not cached', cached, writeFileSize) else: # Write a non-local file RealtimeLogger.info('Writing a non-local file of %d MB', writeFileSize) fsID = cls._writeFileToJobStoreWithAsserts(job, isLocalFile=False, nonLocalDir=nonLocalDir, fileMB=writeFileSize) writtenFiles[fsID] = writeFileSize localFileIDs[fsID].append('non-local') # No change to the job since there was no caching RealtimeLogger.info('Checking for %d bytes cached', cached) cls._requirementsConcur(job, jobDisk, cached) else: if len(writtenFiles) == 0: continue else: fsID, rdelFileSize = random.choice(list(writtenFiles.items())) rdelRandVal = random.random() fileWasCached = job.fileStore.fileIsCached(fsID) if randVal < 0.66: # Read RealtimeLogger.info('Reading a file with size %d and previous cache status %s', rdelFileSize, str(fileWasCached)) if rdelRandVal <= 0.5: # Read as mutable, uncached RealtimeLogger.info('Reading as mutable and uncached; should still have %d bytes cached', cached) job.fileStore.readGlobalFile(fsID, '/'.join([work_dir, str(uuid4())]), mutable=True, cache=False) localFileIDs[fsID].append('mutable') # No change because the file wasn't cached else: # Read as immutable RealtimeLogger.info('Reading as immutable and cacheable') job.fileStore.readGlobalFile(fsID, '/'.join([work_dir, str(uuid4())]), mutable=False, cache=True) localFileIDs[fsID].append('immutable') jobDisk -= rdelFileSize * 1024 * 1024 if not fileWasCached: if job.fileStore.fileIsCached(fsID): RealtimeLogger.info('File was not cached before and is now. Should have %d bytes cached', cached) cached += rdelFileSize * 1024 * 1024 else: RealtimeLogger.info('File was not cached before and still is not now. ' 'Should still have %d bytes cached', cached) else: RealtimeLogger.info('File was cached before. Should still have %d bytes cached', cached) cls._requirementsConcur(job, jobDisk, cached) else: # Delete if rdelRandVal <= 0.5: # Local Delete if fsID not in list(localFileIDs.keys()): continue RealtimeLogger.info('Deleting a file locally') job.fileStore.deleteLocalFile(fsID) else: # Global Delete RealtimeLogger.info('Deleting a file globally') job.fileStore.deleteGlobalFile(fsID) try: job.fileStore.readGlobalFile(fsID) except FileNotFoundError as err: pass except: raise RuntimeError('Got wrong error type for read of deleted file') else: raise RuntimeError('Able to read deleted file') writtenFiles.pop(fsID) if fsID in list(localFileIDs.keys()): for lFID in localFileIDs[fsID]: if lFID not in ('non-local', 'mutable'): jobDisk += rdelFileSize * 1024 * 1024 localFileIDs.pop(fsID) if fileWasCached: if not job.fileStore.fileIsCached(fsID): cached -= rdelFileSize * 1024 * 1024 RealtimeLogger.info('File was cached before and is not now. Should have %d bytes cached', cached) else: RealtimeLogger.info('File was cached before and still is cached now. ' 'Should still have %d bytes cached', cached) else: RealtimeLogger.info('File was not cached before deletion. Should still have %d bytes cached', cached) cls._requirementsConcur(job, jobDisk, cached) i += 1 return jobDisk, cached @staticmethod def _requirementsConcur(job, jobDisk, cached): """ Assert the values for job disk and total cached file sizes tracked by the file store are equal to the values we expect. """ used = job.fileStore.getCacheUsed() if not job.fileStore.cachingIsFree(): RealtimeLogger.info('Caching is not free; %d bytes are used and %d bytes are expected', used, cached) assert used == cached, 'Cache should have %d bytes used, but actually has %d bytes used' % (cached, used) else: RealtimeLogger.info('Caching is free; %d bytes are used and %d bytes would be expected if caching were not free', used, cached) assert used == 0, 'Cache should have nothing in it, but actually has %d bytes used' % used jobUnused = job.fileStore.getCacheUnusedJobRequirement() assert jobUnused == jobDisk, 'Job should have %d bytes of disk for non-FileStore use but the FileStore reports %d' % (jobDisk, jobUnused) # Testing the resumability of a failed worker @slow def testControlledFailedWorkerRetry(self): """ Conduct a couple of job store operations. Then die. Ensure that the restarted job is tracking values in the cache state file appropriately. """ workdir = self._createTempDir(purpose='nonLocalDir') self.options.retryCount = 1 jobDiskBytes = 2 * 1024 * 1024 * 1024 F = Job.wrapJobFn(self._controlledFailTestFn, jobDisk=jobDiskBytes, testDir=workdir, disk=jobDiskBytes) G = Job.wrapJobFn(self._probeJobReqs, sigmaJob=100, disk='100M') F.addChild(G) Job.Runner.startToil(F, self.options) @staticmethod def _controlledFailTestFn(job, jobDisk, testDir): """ This is the aux function for the controlled failed worker test. It does a couple of cache operations, fails, then checks whether the new worker starts with the expected value, and whether it computes cache statistics correctly. :param float jobDisk: Disk space supplied for this job :param str testDir: Testing directory """ # Make sure we actually have the disk size we are supposed to job.fileStore.logToMaster('Job is running with %d bytes of disk, %d requested' % (job.disk, jobDisk)) assert job.disk == jobDisk, 'Job was scheduled with %d bytes but requested %d' % (job.disk, jobDisk) cls = hidden.AbstractCachingFileStoreTest if os.path.exists(os.path.join(testDir, 'testfile.test')): with open(os.path.join(testDir, 'testfile.test'), 'rb') as fH: cached = unpack('d', fH.read())[0] RealtimeLogger.info('Loaded expected cache size of %d from testfile.test', cached) cls._requirementsConcur(job, jobDisk, cached) cls._returnFileTestFn(job, jobDisk, cached, testDir, 20) else: RealtimeLogger.info('Expecting cache size of 0 because testfile.test is absent') modifiedJobReqs, cached = cls._returnFileTestFn(job, jobDisk, 0, testDir, 20) with open(os.path.join(testDir, 'testfile.test'), 'wb') as fH: fH.write(pack('d', cached)) RealtimeLogger.info('Wrote cache size of %d to testfile.test', cached) os.kill(os.getpid(), signal.SIGKILL) @slow def testRemoveLocalMutablyReadFile(self): """ If a mutably read file is deleted by the user, it is ok. """ self._deleteLocallyReadFilesFn(readAsMutable=True) @slow def testRemoveLocalImmutablyReadFile(self): """ If an immutably read file is deleted by the user, it is not ok. """ self._deleteLocallyReadFilesFn(readAsMutable=False) def _deleteLocallyReadFilesFn(self, readAsMutable): self.options.retryCount = 0 A = Job.wrapJobFn(self._writeFileToJobStoreWithAsserts, isLocalFile=True, memory='10M') B = Job.wrapJobFn(self._removeReadFileFn, A.rv(), readAsMutable=readAsMutable, memory='20M') A.addChild(B) Job.Runner.startToil(A, self.options) @staticmethod def _removeReadFileFn(job, fileToDelete, readAsMutable): """ Accept a file. Run os.remove on it. Then attempt to delete it locally. This will raise an error for files read immutably. Then write a new file to the jobstore and try to do the same. This should always raise an error :param fileToDelete: File written to the job store that is tracked by the cache """ work_dir = job.fileStore.getLocalTempDir() # Are we processing the read file or the written file? processsingReadFile = True # Read in the file outfile = job.fileStore.readGlobalFile(fileToDelete, os.path.join(work_dir, 'temp'), mutable=readAsMutable) tempfile = os.path.join(work_dir, 'tmp.tmp') # The first time we run this loop, processsingReadFile is True and fileToDelete is the # file read from the job store. The second time, processsingReadFile is False and # fileToDelete is one that was just written in to the job store. Ensure the correct # behaviour is seen in both conditions. while True: os.rename(outfile, tempfile) try: job.fileStore.deleteLocalFile(fileToDelete) except IllegalDeletionCacheError: job.fileStore.logToMaster('Detected a deleted file %s.' % fileToDelete) os.rename(tempfile, outfile) else: # If we are processing the write test, or if we are testing the immutably read # file, we should not reach here. assert processsingReadFile and readAsMutable if processsingReadFile: processsingReadFile = False # Write a file with open(os.path.join(work_dir, str(uuid4())), 'wb') as testFile: testFile.write(os.urandom(1 * 1024 * 1024)) fileToDelete = job.fileStore.writeGlobalFile(testFile.name) outfile = testFile.name else: break @travis_test def testDeleteLocalFile(self): """ Test the deletion capabilities of deleteLocalFile """ self.options.retryCount = 0 workdir = self._createTempDir(purpose='nonLocalDir') A = Job.wrapJobFn(self._deleteLocalFileFn, nonLocalDir=workdir) Job.Runner.startToil(A, self.options) @staticmethod def _deleteLocalFileFn(job, nonLocalDir): """ Test deleteLocalFile on a local write, non-local write, read, mutable read, and bogus jobstore IDs. """ work_dir = job.fileStore.getLocalTempDir() # Write local file with open(os.path.join(work_dir, str(uuid4())), 'wb') as localFile: localFile.write(os.urandom(1 * 1024 * 1024)) localFsID = job.fileStore.writeGlobalFile(localFile.name) # write Non-Local File with open(os.path.join(nonLocalDir, str(uuid4())), 'wb') as nonLocalFile: nonLocalFile.write(os.urandom(1 * 1024 * 1024)) nonLocalFsID = job.fileStore.writeGlobalFile(nonLocalFile.name) # Delete fsid of local file. The file should be deleted job.fileStore.deleteLocalFile(localFsID) assert not os.path.exists(localFile.name) # Delete fsid of non-local file. The file should persist job.fileStore.deleteLocalFile(nonLocalFsID) assert os.path.exists(nonLocalFile.name) # Read back one file and then delete it readBackFile1 = job.fileStore.readGlobalFile(localFsID) job.fileStore.deleteLocalFile(localFsID) assert not os.path.exists(readBackFile1) # Read back one file with 2 different names and then delete it. Assert both get deleted readBackFile1 = job.fileStore.readGlobalFile(localFsID) readBackFile2 = job.fileStore.readGlobalFile(localFsID) job.fileStore.deleteLocalFile(localFsID) assert not os.path.exists(readBackFile1) assert not os.path.exists(readBackFile2) # Try to get a non-FileID that doesn't exist. try: job.fileStore.readGlobalFile('bogus') except NoSuchFileException: # TODO: We would like to require TypeError, but for Cactus # support we have to accept non-FileIDs. pass else: raise RuntimeError("Managed to get a file from a non-FileID") # Try to get a FileID for something that doesn't exist try: job.fileStore.readGlobalFile(FileID('bogus', 4096)) except NoSuchFileException: pass else: raise RuntimeError("Managed to read a non-existent file") @travis_test def testSimultaneousReadsUncachedStream(self): """ Test many simultaneous read attempts on a file created via a stream directly to the job store. """ self.options.retryCount = 0 self.options.disableChaining = True # Make a file parent = Job.wrapJobFn(self._createUncachedFileStream) # Now make a bunch of children fight over it for i in range(30): parent.addChildJobFn(self._readFileWithDelay, parent.rv()) Job.Runner.startToil(parent, self.options) @staticmethod def _createUncachedFileStream(job): """ Create and return a FileID for a non-cached file written via a stream. """ messageBytes = 'This is a test file\n'.encode('utf-8') with job.fileStore.jobStore.writeFileStream() as (out, idString): # Write directly to the job store so the caching file store doesn't even see it. # TODO: If we ever change how the caching file store does its IDs we will have to change this. out.write(messageBytes) # Now make a file ID fileID = FileID(idString, len(messageBytes)) return fileID @staticmethod def _readFileWithDelay(job, fileID, cores=0.1, memory=50 * 1024 * 1024, disk=50 * 1024 * 1024): """ Read a file from the CachingFileStore with a delay imposed on the download. Should create contention. Has low requirements so we can run a lot of copies at once. """ # Make sure the file store delays # Delay needs to be longer than the timeout for sqlite locking in the file store. job.fileStore.forceDownloadDelay = 120 readStart = datetime.datetime.now() logger.debug('Begin read at %s', str(readStart)) localPath = job.fileStore.readGlobalFile(fileID, cache=True, mutable=True) readEnd = datetime.datetime.now() logger.debug('End read at %s: took %f seconds', str(readEnd), (readEnd - readStart).total_seconds()) with open(localPath, 'rb') as fh: text = fh.read().decode('utf-8').strip() logger.debug('Got file contents: %s', text) class NonCachingFileStoreTestWithFileJobStore(hidden.AbstractNonCachingFileStoreTest): jobStoreType = 'file' @pytest.mark.timeout(1000) class CachingFileStoreTestWithFileJobStore(hidden.AbstractCachingFileStoreTest): jobStoreType = 'file' @needs_aws_ec2 class NonCachingFileStoreTestWithAwsJobStore(hidden.AbstractNonCachingFileStoreTest): jobStoreType = 'aws' @slow @needs_aws_ec2 @pytest.mark.timeout(1000) class CachingFileStoreTestWithAwsJobStore(hidden.AbstractCachingFileStoreTest): jobStoreType = 'aws' @needs_google class NonCachingFileStoreTestWithGoogleJobStore(hidden.AbstractNonCachingFileStoreTest): jobStoreType = 'google' @slow @needs_google @pytest.mark.timeout(1000) class CachingFileStoreTestWithGoogleJobStore(hidden.AbstractCachingFileStoreTest): jobStoreType = 'google' def _exportStaticMethodAsGlobalFunctions(cls): """ Define utility functions because Toil can't pickle static methods. Note that this relies on the convention that the first argument of a job function is named 'job'. """ for name, kind, clazz, value in inspect.classify_class_attrs(cls): if kind == 'static method' and name != '__new__': # __new__ became static in 3.7 method = value.__func__ args = inspect.getargspec(method).args if args and args[0] == 'job': globals()[name] = method _exportStaticMethodAsGlobalFunctions(hidden.AbstractFileStoreTest) _exportStaticMethodAsGlobalFunctions(hidden.AbstractCachingFileStoreTest) _exportStaticMethodAsGlobalFunctions(hidden.AbstractNonCachingFileStoreTest) toil-releases-3.24.0/src/toil/test/src/helloWorldTest.py000066400000000000000000000034141362134276200232110ustar00rootroot00000000000000# Copyright (C) 2015-2016 Regents of the University of California # # 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. from __future__ import absolute_import from toil.job import Job from toil.test import ToilTest, travis_test class HelloWorldTest(ToilTest): @travis_test def testHelloWorld(self): options = Job.Runner.getDefaultOptions(self._getTestJobStorePath()) options.logLevel = "INFO" Job.Runner.startToil(HelloWorld(), options) class HelloWorld(Job): def __init__(self): Job.__init__(self, memory=100000, cores=2, disk="3G") def run(self, fileStore): fileID = self.addChildJobFn(childFn, cores=1, memory="1M", disk="3G").rv() self.addFollowOn(FollowOn(fileID)) def childFn(job): with job.fileStore.writeGlobalFileStream() as (fH, fileID): fH.write("Hello, World!".encode('utf-8')) return fileID class FollowOn(Job): def __init__(self,fileId): Job.__init__(self) self.fileId=fileId def run(self, fileStore): tempDir = fileStore.getLocalTempDir() tempFilePath = "/".join([tempDir,"LocalCopy"]) with fileStore.readGlobalFileStream(self.fileId) as globalFile: with open(tempFilePath, "wb") as localFile: localFile.write(globalFile.read()) toil-releases-3.24.0/src/toil/test/src/importExportFileTest.py000066400000000000000000000110651362134276200244130ustar00rootroot00000000000000# Copyright (C) 2015-2016 Regents of the University of California # # 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. from __future__ import absolute_import from builtins import str import uuid import os from toil.common import Toil from toil.job import Job from toil.leader import FailedJobsException from toil.test import ToilTest, slow, travis_test from toil.fileStores import FileID from toil.common import getDirSizeRecursively class ImportExportFileTest(ToilTest): def setUp(self): super(ImportExportFileTest, self).setUp() self._tempDir = self._createTempDir() self.dstFile = '%s/%s' % (self._tempDir, 'out') def _importExportFile(self, options, fail): with Toil(options) as toil: if not options.restart: srcFile = '%s/%s%s' % (self._tempDir, 'in', str(uuid.uuid4())) with open(srcFile, 'w') as f: f.write('Hello') inputFileID = toil.importFile('file://' + srcFile) # Make sure that importFile returns the fileID wrapper self.assertIsInstance(inputFileID, FileID) self.assertEqual(os.stat(srcFile).st_size, inputFileID.size) # Write a boolean that determines whether the job fails. failFilePath = '%s/%s%s' % (self._tempDir, 'failfile', str(uuid.uuid4())) with open(failFilePath, 'wb') as f: f.write(str(fail).encode('utf-8')) self.failFileID = toil.importFile('file://' + failFilePath) outputFileID = toil.start(RestartingJob(inputFileID, self.failFileID)) else: # Set up job for failure # TODO: We're hackily updating this file without using the # correct FileStore interface. User code should not do this! with toil._jobStore.updateFileStream(self.failFileID) as f: f.write('False'.encode('utf-8')) outputFileID = toil.restart() toil.exportFile(outputFileID, 'file://' + self.dstFile) with open(self.dstFile, 'r') as f: assert f.read() == "HelloWorld!" def _importExport(self, restart): options = Job.Runner.getDefaultOptions(self._getTestJobStorePath()) options.logLevel = "INFO" if restart: try: self._importExportFile(options, fail=True) except FailedJobsException: options.restart = True self._importExportFile(options, fail=False) @slow def testImportExportRestartTrue(self): self._importExport(restart=True) @travis_test def testImportExportRestartFalse(self): self._importExport(restart=False) @travis_test def testImportSharedFileName(self): options = Job.Runner.getDefaultOptions(self._getTestJobStorePath()) options.logLevel = "DEBUG" sharedFileName = 'someSharedFile' with Toil(options) as toil: srcFile = '%s/%s%s' % (self._tempDir, 'in', uuid.uuid4()) with open(srcFile, 'w') as f: f.write('some data') toil.importFile('file://' + srcFile, sharedFileName=sharedFileName) with toil._jobStore.readSharedFileStream(sharedFileName) as f: self.assertEqual(f.read().decode('utf-8'), 'some data') class RestartingJob(Job): def __init__(self, inputFileID, failFileID): Job.__init__(self, memory=100000, cores=1, disk="1M") self.inputFileID = inputFileID self.failFileID = failFileID def run(self, fileStore): with fileStore.readGlobalFileStream(self.failFileID) as failValue: if failValue.read().decode('utf-8') == 'True': raise RuntimeError('planned exception') else: with fileStore.readGlobalFileStream(self.inputFileID) as fi: with fileStore.writeGlobalFileStream() as (fo, outputFileID): fo.write((fi.read().decode('utf-8') + 'World!').encode('utf-8')) return outputFileID toil-releases-3.24.0/src/toil/test/src/jobEncapsulationTest.py000066400000000000000000000046701362134276200244030ustar00rootroot00000000000000# Copyright (C) 2015-2016 Regents of the University of California # # 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. from __future__ import absolute_import import os from toil.lib.bioio import getTempFile from toil.job import Job as T from toil.test import ToilTest, travis_test from toil.test.src.jobTest import fn1Test as f class JobEncapsulationTest(ToilTest): """ Tests testing the EncapsulationJob class """ @travis_test def testEncapsulation(self): """ Tests the Job.encapsulation method, which uses the EncapsulationJob class. """ # Temporary file outFile = getTempFile(rootDir=self._createTempDir()) try: # Encapsulate a job graph a = T.wrapJobFn(encapsulatedJobFn, "A", outFile) a = a.encapsulate() # Now add children/follow to the encapsulated graph d = T.wrapFn(f, a.rv(), outFile) e = T.wrapFn(f, d.rv(), outFile) a.addChild(d) a.addFollowOn(e) # Create the runner for the workflow. options = T.Runner.getDefaultOptions(self._getTestJobStorePath()) options.logLevel = "INFO" # Run the workflow, the return value being the number of failed jobs T.Runner.startToil(a, options) # Check output self.assertEqual(open(outFile, 'r').readline(), "ABCDE") finally: os.remove(outFile) @travis_test def testAddChildEncapsulate(self): """ Make sure that the encapsulate child does not have two parents with unique roots. """ # Temporary file a = T.wrapFn(noOp) b = T.wrapFn(noOp) a.addChild(b).encapsulate() self.assertEqual(len(a.getRootJobs()), 1) def noOp(): pass def encapsulatedJobFn(job, string, outFile): a = job.addChildFn(f, string, outFile) b = a.addFollowOnFn(f, a.rv(), outFile) return b.rv() toil-releases-3.24.0/src/toil/test/src/jobFileStoreTest.py000066400000000000000000000210251362134276200234630ustar00rootroot00000000000000# Copyright (C) 2015-2016 Regents of the University of California # # 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. from __future__ import absolute_import from builtins import range import codecs import random import os import errno # Python 3 compatibility imports from six.moves import xrange from toil.common import Toil from toil.job import Job from toil.fileStores import FileID from toil.test import ToilTest, slow, travis_test PREFIX_LENGTH=200 # TODO: This test is ancient and while similar tests exist in `fileStoreTest.py`, none of them look # at the contents of read files and thus we will let this test remain as-is. class JobFileStoreTest(ToilTest): """ Tests testing the methods defined in :class:toil.fileStores.abstractFileStore.AbstractFileStore. """ @travis_test def testCachingFileStore(self): options = Job.Runner.getDefaultOptions(self._getTestJobStorePath()) with Toil(options) as workflow: workflow.start(Job.wrapJobFn(simpleFileStoreJob)) @travis_test def testNonCachingFileStore(self): options = Job.Runner.getDefaultOptions(self._getTestJobStorePath()) options.disableCaching = True with Toil(options) as workflow: workflow.start(Job.wrapJobFn(simpleFileStoreJob)) @travis_test def _testJobFileStore(self, retryCount=0, badWorker=0.0, stringNo=1, stringLength=1000000, testNo=2): """ Creates a chain of jobs, each reading and writing files using the toil.fileStores.abstractFileStore.AbstractFileStore interface. Verifies the files written are always what we expect. """ for test in range(testNo): #Make a list of random strings, each of 100k chars and hash the first 200 #base prefix to the string def randomString(): chars = "ABCDEFGHIJKLMNOPQRSTUVWXYZ" s = "".join([random.choice(chars) for i in range(stringLength)]) return s[:PREFIX_LENGTH], s #Total length is 2 million characters (20 strings of length 100K each) testStrings = dict([randomString() for i in range(stringNo)]) options = Job.Runner.getDefaultOptions(self._getTestJobStorePath()) options.logLevel = "INFO" options.retryCount=retryCount options.badWorker=badWorker options.badWorkerFailInterval = 1.0 chainLength = 10 # Run the workflow, the return value being the number of failed jobs Job.Runner.startToil(Job.wrapJobFn(fileTestJob, [], testStrings, chainLength), options) def testJobFileStore(self): """ Tests case that about half the files are cached """ self._testJobFileStore(retryCount=0, badWorker=0.0, stringNo=5, stringLength=1000000) @slow def testJobFileStoreWithBadWorker(self): """ Tests case that about half the files are cached and the worker is randomly failing. """ self._testJobFileStore(retryCount=100, badWorker=0.5, stringNo=5, stringLength=1000000) def fileTestJob(job, inputFileStoreIDs, testStrings, chainLength): """ Test job exercises toil.fileStores.abstractFileStore.AbstractFileStore functions """ outputFileStoreIds = [] #Strings passed to the next job in the chain #Load the input jobStoreFileIDs and check that they map to the #same set of random input strings, exercising the different functions in the fileStore interface for fileStoreID in inputFileStoreIDs: if random.random() > 0.5: #Read the file for the fileStoreID, randomly picking a way to invoke readGlobalFile if random.random() > 0.5: tempFile = job.fileStore.readGlobalFile(fileStoreID, job.fileStore.getLocalTempFileName() if random.random() > 0.5 else None, cache=random.random() > 0.5) with open(tempFile, 'r') as fH: string = fH.readline() else: #Check the local file is as we expect with job.fileStore.readGlobalFileStream(fileStoreID) as fH: # File streams are binary in Python 3 and can't do readline. # But a StreamReader for UTF-8 is exactly the adapter we need. fH = codecs.getreader('utf-8')(fH) string = fH.readline() #Check the string we get back is what we expect assert testStrings[string[:PREFIX_LENGTH]] == string #This allows the file to be passed to the next job outputFileStoreIds.append(fileStoreID) else: #This tests deletion job.fileStore.deleteGlobalFile(fileStoreID) #Fill out the output strings until we have the same number as the input strings #exercising different ways of writing files to the file store while len(outputFileStoreIds) < len(testStrings): #Pick a string and write it into a file testString = random.choice(list(testStrings.values())) if random.random() > 0.5: #Make a local copy of the file tempFile = job.fileStore.getLocalTempFile() if random.random() > 0.5 \ else os.path.join(job.fileStore.getLocalTempDir(), "temp.txt") with open(tempFile, 'w') as fH: fH.write(testString) #Write a local copy of the file using the local file fileStoreID = job.fileStore.writeGlobalFile(tempFile) # Make sure it returned a valid and correct FileID with the right size assert isinstance(fileStoreID, FileID) assert fileStoreID.size == len(testString.encode('utf-8')) outputFileStoreIds.append(fileStoreID) else: #Use the writeGlobalFileStream method to write the file with job.fileStore.writeGlobalFileStream() as (fH, fileStoreID): fH.write(testString.encode('utf-8')) outputFileStoreIds.append(fileStoreID) #Make sure it returned a valid and correct FileID with the right size assert isinstance(fileStoreID, FileID) assert fileStoreID.size == len(testString.encode('utf-8')) if chainLength > 0: #Make a child that will read these files and check it gets the same results job.addChildJobFn(fileTestJob, outputFileStoreIds, testStrings, chainLength-1) fileStoreString = "Testing writeGlobalFile" streamingFileStoreString = "Testing writeGlobalFileStream" def simpleFileStoreJob(job): localFilePath = os.path.join(job.fileStore.getLocalTempDir(), "parentTemp.txt") with open(localFilePath, 'w') as f: f.write(fileStoreString) testID1 = job.fileStore.writeGlobalFile(localFilePath) testID2 = None with job.fileStore.writeGlobalFileStream() as (f, fileID): f.write(streamingFileStoreString.encode('utf-8')) testID2 = fileID job.addChildJobFn(fileStoreChild, testID1, testID2) def fileStoreChild(job, testID1, testID2): with job.fileStore.readGlobalFileStream(testID1) as f: assert(f.read().decode('utf-8') == fileStoreString) localFilePath = os.path.join(job.fileStore.getLocalTempDir(), "childTemp.txt") job.fileStore.readGlobalFile(testID2, localFilePath) with open(localFilePath, 'r') as f: assert(f.read() == streamingFileStoreString) job.fileStore.deleteLocalFile(testID2) try: job.fileStore.deleteLocalFile(testID1) except OSError as e: if e.errno == errno.ENOENT: # indicates that the file was not found pass else: raise else: raise RuntimeError("Deleting a non-existant file did not throw an exception") for fileID in (testID1, testID2): job.fileStore.deleteGlobalFile(fileID) toil-releases-3.24.0/src/toil/test/src/jobGraphTest.py000066400000000000000000000062071362134276200226350ustar00rootroot00000000000000# Copyright (C) 2015-2016 Regents of the University of California # # 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. from __future__ import absolute_import import os from argparse import ArgumentParser from toil.common import Toil from toil.job import Job from toil.test import ToilTest, travis_test from toil.jobGraph import JobGraph class JobGraphTest(ToilTest): def setUp(self): super(JobGraphTest, self).setUp() self.jobStorePath = self._getTestJobStorePath() parser = ArgumentParser() Job.Runner.addToilOptions(parser) options = parser.parse_args(args=[self.jobStorePath]) self.toil = Toil(options) self.assertEqual( self.toil, self.toil.__enter__() ) def tearDown(self): self.toil.__exit__(None, None, None) self.toil._jobStore.destroy() self.assertFalse(os.path.exists(self.jobStorePath)) super(JobGraphTest, self).tearDown() @travis_test def testJob(self): """ Tests functions of a job. """ command = "by your command" memory = 2^32 disk = 2^32 cores = 1 preemptable = 1 jobStoreID = 100 remainingRetryCount = 5 predecessorNumber = 0 j = JobGraph(command=command, memory=memory, cores=cores, disk=disk, preemptable=preemptable, jobStoreID=jobStoreID, remainingRetryCount=remainingRetryCount, predecessorNumber=predecessorNumber, jobName='testJobGraph', unitName='noName') #Check attributes # self.assertEqual(j.command, command) self.assertEqual(j.memory, memory) self.assertEqual(j.disk, disk) self.assertEqual(j.cores, cores) self.assertEqual(j.preemptable, preemptable) self.assertEqual(j.jobStoreID, jobStoreID) self.assertEqual(j.remainingRetryCount, remainingRetryCount) self.assertEqual(j.predecessorNumber, predecessorNumber) self.assertEqual(j.stack, []) self.assertEqual(j.predecessorsFinished, set()) self.assertEqual(j.logJobStoreFileID, None) #Check equals function j2 = JobGraph(command=command, memory=memory, cores=cores, disk=disk, preemptable=preemptable, jobStoreID=jobStoreID, remainingRetryCount=remainingRetryCount, predecessorNumber=predecessorNumber, jobName='testJobGraph', unitName='noName') self.assertEqual(j, j2) #Change an attribute and check not equal j.predecessorsFinished = {"1", "2"} self.assertNotEqual(j, j2) ###TODO test other functionality toil-releases-3.24.0/src/toil/test/src/jobServiceTest.py000066400000000000000000000354341362134276200232000ustar00rootroot00000000000000# Copyright (C) 2015-2016 Regents of the University of California # # 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. from __future__ import absolute_import, print_function from builtins import zip from builtins import map from builtins import range import codecs import os import random import traceback import unittest # Python 3 compatibility imports from six.moves import xrange from toil.lib.bioio import getTempFile from toil.job import Job from toil.test import ToilTest, slow import time import sys from threading import Thread, Event import logging logger = logging.getLogger( __name__ ) from unittest import skipIf from toil.batchSystems.singleMachine import SingleMachineBatchSystem from toil.leader import FailedJobsException, DeadlockException class JobServiceTest(ToilTest): """ Tests testing the Job.Service class """ @slow def testServiceSerialization(self): """ Tests that a service can receive a promise without producing a serialization error. """ job = Job() service = ToySerializableService("woot") startValue = job.addService(service) # Add a first service to job subService = ToySerializableService(startValue) # Now create a child of # that service that takes the start value promise from the parent service job.addService(subService, parentService=service) # This should work if # serialization on services is working correctly. self.runToil(job) @slow def testService(self, checkpoint=False): """ Tests the creation of a Job.Service with random failures of the worker. """ for test in range(2): outFile = getTempFile(rootDir=self._createTempDir()) # Temporary file messageInt = random.randint(1, sys.maxsize) try: # Wire up the services/jobs t = Job.wrapJobFn(serviceTest, outFile, messageInt, checkpoint=checkpoint) # Run the workflow repeatedly until success self.runToil(t) # Check output self.assertEqual(int(open(outFile, 'r').readline()), messageInt) finally: os.remove(outFile) @slow @skipIf(SingleMachineBatchSystem.numCores < 4, 'Need at least four cores to run this test') def testServiceDeadlock(self): """ Creates a job with more services than maxServices, checks that deadlock is detected. """ outFile = getTempFile(rootDir=self._createTempDir()) try: def makeWorkflow(): job = Job() r1 = job.addService(ToySerializableService("woot1")) r2 = job.addService(ToySerializableService("woot2")) r3 = job.addService(ToySerializableService("woot3")) job.addChildFn(fnTest, [ r1, r2, r3 ], outFile) return job # This should fail as too few services available try: self.runToil(makeWorkflow(), badWorker=0.0, maxServiceJobs=2, deadlockWait=5) except DeadlockException: print("Got expected deadlock exception") else: assert 0 # This should pass, as adequate services available self.runToil(makeWorkflow(), maxServiceJobs=3) # Check we get expected output assert open(outFile, 'r').read() == "woot1 woot2 woot3" finally: os.remove(outFile) def testServiceWithCheckpoints(self): """ Tests the creation of a Job.Service with random failures of the worker, making the root job use checkpointing to restart the subtree. """ self.testService(checkpoint=True) @slow @skipIf(SingleMachineBatchSystem.numCores < 4, 'Need at least four cores to run this test') def testServiceRecursive(self, checkpoint=True): """ Tests the creation of a Job.Service, creating a chain of services and accessing jobs. Randomly fails the worker. """ for test in range(1): # Temporary file outFile = getTempFile(rootDir=self._createTempDir()) messages = [ random.randint(1, sys.maxsize) for i in range(3) ] try: # Wire up the services/jobs t = Job.wrapJobFn(serviceTestRecursive, outFile, messages, checkpoint=checkpoint) # Run the workflow repeatedly until success self.runToil(t) # Check output self.assertEqual(list(map(int, open(outFile, 'r').readlines())), messages) finally: os.remove(outFile) @slow @skipIf(SingleMachineBatchSystem.numCores < 4, 'Need at least four cores to run this test') def testServiceParallelRecursive(self, checkpoint=True): """ Tests the creation of a Job.Service, creating parallel chains of services and accessing jobs. Randomly fails the worker. """ for test in range(1): # Temporary file outFiles = [ getTempFile(rootDir=self._createTempDir()) for j in range(2) ] messageBundles = [ [ random.randint(1, sys.maxsize) for i in range(3) ] for j in range(2) ] try: # Wire up the services/jobs t = Job.wrapJobFn(serviceTestParallelRecursive, outFiles, messageBundles, checkpoint=True) # Run the workflow repeatedly until success self.runToil(t, retryCount=2) # Check output for (messages, outFile) in zip(messageBundles, outFiles): self.assertEqual(list(map(int, open(outFile, 'r').readlines())), messages) finally: list(map(os.remove, outFiles)) def runToil(self, rootJob, retryCount=1, badWorker=0.5, badWorkedFailInterval=0.1, maxServiceJobs=sys.maxsize, deadlockWait=60): # Create the runner for the workflow. options = Job.Runner.getDefaultOptions(self._getTestJobStorePath()) options.logLevel = "DEBUG" options.retryCount = retryCount options.badWorker = badWorker options.badWorkerFailInterval = badWorkedFailInterval options.servicePollingInterval = 1 options.maxServiceJobs = maxServiceJobs options.deadlockWait=deadlockWait # Run the workflow totalTrys = 0 while True: try: Job.Runner.startToil(rootJob, options) break except FailedJobsException as e: i = e.numberOfFailedJobs if totalTrys > 50: #p(fail after this many restarts) = 0.5**32 self.fail() #Exceeded a reasonable number of restarts totalTrys += 1 options.restart = True def serviceTest(job, outFile, messageInt): """ Creates one service and one accessing job, which communicate with two files to establish that both run concurrently. """ #Clean out out-file open(outFile, 'w').close() randInt = random.randint(1, sys.maxsize) # We create a random number that is added to messageInt and subtracted by the serviceAccessor, to prove that # when service test is checkpointed and restarted there is never a connection made between an earlier service and later serviceAccessor, or vice versa. job.addChildJobFn(serviceAccessor, job.addService(ToyService(messageInt + randInt)), outFile, randInt) def serviceTestRecursive(job, outFile, messages): """ Creates a chain of services and accessing jobs, each paired together. """ if len(messages) > 0: #Clean out out-file open(outFile, 'w').close() randInt = random.randint(1, sys.maxsize) service = ToyService(messages[0] + randInt) child = job.addChildJobFn(serviceAccessor, job.addService(service), outFile, randInt) for i in range(1, len(messages)): randInt = random.randint(1, sys.maxsize) service2 = ToyService(messages[i] + randInt, cores=0.1) child = child.addChildJobFn(serviceAccessor, job.addService(service2, parentService=service), outFile, randInt, cores=0.1) service = service2 def serviceTestParallelRecursive(job, outFiles, messageBundles): """ Creates multiple chains of services and accessing jobs. """ for messages, outFile in zip(messageBundles, outFiles): #Clean out out-file open(outFile, 'w').close() if len(messages) > 0: randInt = random.randint(1, sys.maxsize) service = ToyService(messages[0] + randInt) child = job.addChildJobFn(serviceAccessor, job.addService(service), outFile, randInt) for i in range(1, len(messages)): randInt = random.randint(1, sys.maxsize) service2 = ToyService(messages[i] + randInt, cores=0.1) child = child.addChildJobFn(serviceAccessor, job.addService(service2, parentService=service), outFile, randInt, cores=0.1) service = service2 class ToyService(Job.Service): def __init__(self, messageInt, *args, **kwargs): """ While established the service repeatedly: - reads an integer i from the inJobStoreFileID file - writes i and messageInt to the outJobStoreFileID file """ Job.Service.__init__(self, *args, **kwargs) self.messageInt = messageInt def start(self, job): assert self.disk is not None assert self.memory is not None assert self.cores is not None self.terminate = Event() self.error = Event() # Note that service jobs are special and do not necessarily have job.jobStoreID. # So we don't associate these files with this job. inJobStoreID = job.fileStore.jobStore.getEmptyFileStoreID() outJobStoreID = job.fileStore.jobStore.getEmptyFileStoreID() self.serviceThread = Thread(target=self.serviceWorker, args=(job.fileStore.jobStore, self.terminate, self.error, inJobStoreID, outJobStoreID, self.messageInt)) self.serviceThread.start() return (inJobStoreID, outJobStoreID) def stop(self, job): self.terminate.set() self.serviceThread.join() def check(self): if self.error.isSet(): raise RuntimeError("Service worker failed") return True @staticmethod def serviceWorker(jobStore, terminate, error, inJobStoreID, outJobStoreID, messageInt): try: while True: if terminate.isSet(): # Quit if we've got the terminate signal logger.debug("Service worker being told to quit") return time.sleep(0.2) # Sleep to avoid thrashing # Try reading a line from the input file try: with jobStore.readFileStream(inJobStoreID) as fH: fH = codecs.getreader('utf-8')(fH) line = fH.readline() except: logger.debug("Something went wrong reading a line: %s", traceback.format_exc()) raise if len(line.strip()) == 0: # Don't try and make an integer out of nothing continue # Try converting the input line into an integer try: inputInt = int(line) except ValueError: logger.debug("Tried casting input line '%s' to integer but got error: %s", line, traceback.format_exc()) continue # Write out the resulting read integer and the message with jobStore.updateFileStream(outJobStoreID) as fH: fH.write(("%s %s\n" % (inputInt, messageInt)).encode('utf-8')) logger.debug("Service worker did useful work") except: logger.debug("Error in service worker: %s", traceback.format_exc()) error.set() raise def serviceAccessor(job, communicationFiles, outFile, randInt): """ Writes a random integer iinto the inJobStoreFileID file, then tries 10 times reading from outJobStoreFileID to get a pair of integers, the first equal to i the second written into the outputFile. """ inJobStoreFileID, outJobStoreFileID = communicationFiles # Get a random integer key = random.randint(1, sys.maxsize) # Write the integer into the file logger.debug("Writing key to inJobStoreFileID") with job.fileStore.jobStore.updateFileStream(inJobStoreFileID) as fH: fH.write(("%s\n" % key).encode('utf-8')) logger.debug("Trying to read key and message from outJobStoreFileID") for i in range(10): # Try 10 times over time.sleep(0.2) #Avoid thrashing # Try reading an integer from the input file and writing out the message with job.fileStore.jobStore.readFileStream(outJobStoreFileID) as fH: fH = codecs.getreader('utf-8')(fH) line = fH.readline() tokens = line.split() if len(tokens) != 2: continue key2, message = tokens if int(key2) == key: logger.debug("Matched key's: %s, writing message: %s with randInt: %s" % (key, int(message) - randInt, randInt)) with open(outFile, 'a') as fH: fH.write("%s\n" % (int(message) - randInt)) return assert 0 # Job failed to get info from the service class ToySerializableService(Job.Service): def __init__(self, messageInt, *args, **kwargs): """ Trivial service for testing serialization. """ Job.Service.__init__(self, *args, **kwargs) self.messageInt = messageInt def start(self, job): return self.messageInt def stop(self, job): pass def check(self): return True def fnTest(strings, outputFile): """ Function concatenates the strings together and writes them to the output file """ with open(outputFile, 'w') as fH: fH.write(" ".join(strings)) toil-releases-3.24.0/src/toil/test/src/jobTest.py000066400000000000000000000660251362134276200216570ustar00rootroot00000000000000# Copyright (C) 2015-2016 Regents of the University of California # # 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. from __future__ import absolute_import, print_function from __future__ import division from builtins import chr from builtins import map from builtins import str from builtins import range from past.utils import old_div import unittest import logging import os import random # Python 3 compatibility imports from six.moves import xrange from toil.common import Toil from toil.leader import FailedJobsException from toil.lib.bioio import getTempFile from toil.job import Job, JobGraphDeadlockException, JobFunctionWrappingJob from toil.test import ToilTest, slow, travis_test logger = logging.getLogger(__name__) class JobTest(ToilTest): """ Tests testing the job class """ @classmethod def setUpClass(cls): super(JobTest, cls).setUpClass() logging.basicConfig(level=logging.DEBUG) @slow def testStatic(self): """ Create a DAG of jobs non-dynamically and run it. DAG is: A -> F \------- B -> D \ \ \ ------- C -> E Follow on is marked by -> """ outFile = getTempFile(rootDir=self._createTempDir()) try: # Create the jobs A = Job.wrapFn(fn1Test, "A", outFile) B = Job.wrapFn(fn1Test, A.rv(), outFile) C = Job.wrapFn(fn1Test, B.rv(), outFile) D = Job.wrapFn(fn1Test, C.rv(), outFile) E = Job.wrapFn(fn1Test, D.rv(), outFile) F = Job.wrapFn(fn1Test, E.rv(), outFile) # Connect them into a workflow A.addChild(B) A.addChild(C) B.addChild(C) B.addFollowOn(E) C.addFollowOn(D) A.addFollowOn(F) # Create the runner for the workflow. options = Job.Runner.getDefaultOptions(self._getTestJobStorePath()) options.logLevel = "INFO" options.retryCount = 100 options.badWorker = 0.5 options.badWorkerFailInterval = 0.01 # Run the workflow, the return value being the number of failed jobs Job.Runner.startToil(A, options) # Check output self.assertEqual(open(outFile, 'r').readline(), "ABCDEFG") finally: os.remove(outFile) @travis_test def testStatic2(self): """ Create a DAG of jobs non-dynamically and run it. DAG is: A -> F \------- B -> D \ \ \ ------- C -> E Follow on is marked by -> """ outFile = getTempFile(rootDir=self._createTempDir()) try: # Create the jobs A = Job.wrapFn(fn1Test, "A", outFile) B = Job.wrapFn(fn1Test, A.rv(), outFile) C = Job.wrapFn(fn1Test, B.rv(), outFile) D = Job.wrapFn(fn1Test, C.rv(), outFile) # Connect them into a workflow A.addChild(B) A.addFollowOn(C) C.addChild(D) # Create the runner for the workflow. options = Job.Runner.getDefaultOptions(self._getTestJobStorePath()) options.logLevel = "INFO" options.retryCount = 100 options.badWorker = 0.5 options.badWorkerFailInterval = 0.01 # Run the workflow, the return value being the number of failed jobs Job.Runner.startToil(A, options) # Check output self.assertEqual(open(outFile, 'r').readline(), "ABCDE") finally: os.remove(outFile) @slow def testTrivialDAGConsistency(self): options = Job.Runner.getDefaultOptions(self._createTempDir() + '/jobStore') options.clean = 'always' options.logLevel = 'debug' i = Job.wrapJobFn(trivialParent) with Toil(options) as toil: try: toil.start(i) except FailedJobsException: # we expect this exception to be raised pass else: self.fail() @travis_test def testDAGConsistency(self): options = Job.Runner.getDefaultOptions(self._createTempDir() + '/jobStore') options.clean = 'always' i = Job.wrapJobFn(parent) with Toil(options) as toil: try: toil.start(i) except FailedJobsException: # we expect this exception to be raised pass else: self.fail() @slow def testSiblingDAGConsistency(self): """ Slightly more complex case. The stranded job's predecessors are siblings instead of parent/child. """ options = Job.Runner.getDefaultOptions(self._createTempDir() + '/jobStore') options.clean = 'always' options.logLevel = 'debug' i = Job.wrapJobFn(diamond) with Toil(options) as toil: try: toil.start(i) except FailedJobsException: # we expect this exception to be raised pass else: self.fail() @travis_test def testDeadlockDetection(self): """ Randomly generate job graphs with various types of cycle in them and check they cause an exception properly. Also check that multiple roots causes a deadlock exception. """ for test in range(10): # Make a random DAG for the set of child edges nodeNumber = random.choice(range(2, 20)) childEdges = self.makeRandomDAG(nodeNumber) # Get an adjacency list representation and check is acyclic adjacencyList = self.getAdjacencyList(nodeNumber, childEdges) self.assertTrue(self.isAcyclic(adjacencyList)) # Add in follow-on edges - these are returned as a list, and as a set of augmented # edges in the adjacency list # edges in the adjacency list followOnEdges = self.addRandomFollowOnEdges(adjacencyList) self.assertTrue(self.isAcyclic(adjacencyList)) # Make the job graph rootJob = self.makeJobGraph(nodeNumber, childEdges, followOnEdges, None) rootJob.checkJobGraphAcylic() # This should not throw an exception rootJob.checkJobGraphConnected() # Nor this # Check root detection explicitly self.assertEqual(rootJob.getRootJobs(), {rootJob}) # Test making multiple roots childEdges2 = childEdges.copy() childEdges2.add((nodeNumber, 1)) # This creates an extra root at "nodeNumber" rootJob2 = self.makeJobGraph(nodeNumber + 1, childEdges2, followOnEdges, None, False) try: rootJob2.checkJobGraphConnected() self.assertTrue(False) # Multiple roots were not detected except JobGraphDeadlockException: pass # This is the expected behaviour def checkChildEdgeCycleDetection(fNode, tNode): childEdges.add((fNode, tNode)) # Create a cycle adjacencyList[fNode].add(tNode) self.assertTrue(not self.isAcyclic(adjacencyList)) try: self.makeJobGraph(nodeNumber, childEdges, followOnEdges, None).checkJobGraphAcylic() self.assertTrue(False) # A cycle was not detected except JobGraphDeadlockException: pass # This is the expected behaviour # Remove the edges childEdges.remove((fNode, tNode)) adjacencyList[fNode].remove(tNode) # Check is now acyclic again self.makeJobGraph(nodeNumber, childEdges, followOnEdges, None, False).checkJobGraphAcylic() def checkFollowOnEdgeCycleDetection(fNode, tNode): followOnEdges.add((fNode, tNode)) # Create a cycle try: self.makeJobGraph(nodeNumber, childEdges, followOnEdges, None, False).checkJobGraphAcylic() # self.assertTrue(False) #The cycle was not detected except JobGraphDeadlockException: pass # This is the expected behaviour # Remove the edges followOnEdges.remove((fNode, tNode)) # Check is now acyclic again self.makeJobGraph(nodeNumber, childEdges, followOnEdges, None, False).checkJobGraphAcylic() # Now try adding edges that create a cycle # Pick a random existing order relationship fNode, tNode = self.getRandomEdge(nodeNumber) while tNode not in self.reachable(fNode, adjacencyList): fNode, tNode = self.getRandomEdge(nodeNumber) # Try creating a cycle of child edges checkChildEdgeCycleDetection(tNode, fNode) # Try adding a self child edge node = random.choice(range(nodeNumber)) checkChildEdgeCycleDetection(node, node) # Try adding a follow on edge from a descendant to an ancestor checkFollowOnEdgeCycleDetection(tNode, fNode) # Try adding a self follow on edge checkFollowOnEdgeCycleDetection(node, node) # Try adding a follow on edge between two nodes with shared descendants fNode, tNode = self.getRandomEdge(nodeNumber) if (len(self.reachable(tNode, adjacencyList) .intersection(self.reachable(fNode, adjacencyList))) > 0 and (fNode, tNode) not in childEdges and (fNode, tNode) not in followOnEdges): checkFollowOnEdgeCycleDetection(fNode, tNode) @slow def testNewCheckpointIsLeafVertexNonRootCase(self): """ Test for issue #1465: Detection of checkpoint jobs that are not leaf vertices identifies leaf vertices incorrectly Test verification of new checkpoint jobs being leaf verticies, starting with the following baseline workflow: Parent | Child # Checkpoint=True """ def createWorkflow(): rootJob = Job.wrapJobFn(simpleJobFn, "Parent") childCheckpointJob = rootJob.addChildJobFn(simpleJobFn, "Child", checkpoint=True) return rootJob, childCheckpointJob self.runNewCheckpointIsLeafVertexTest(createWorkflow) @slow def testNewCheckpointIsLeafVertexRootCase(self): """ Test for issue #1466: Detection of checkpoint jobs that are not leaf vertices omits the workflow root job Test verification of a new checkpoint job being leaf vertex, starting with a baseline workflow of a single, root job: Root # Checkpoint=True """ def createWorkflow(): rootJob = Job.wrapJobFn(simpleJobFn, "Root", checkpoint=True) return rootJob, rootJob self.runNewCheckpointIsLeafVertexTest(createWorkflow) def runNewCheckpointIsLeafVertexTest(self, createWorkflowFn): """ Test verification that a checkpoint job is a leaf vertex using both valid and invalid cases. :param createWorkflowFn: function to create and new workflow and return a tuple of: 0) the workflow root job 1) a checkpoint job to test within the workflow """ logger.debug('Test checkpoint job that is a leaf vertex') self.runCheckpointVertexTest(*createWorkflowFn(), expectedException=None) logger.debug('Test checkpoint job that is not a leaf vertex due to the presence of a service') self.runCheckpointVertexTest(*createWorkflowFn(), checkpointJobService=TrivialService("LeafTestService"), expectedException=JobGraphDeadlockException) logger.debug('Test checkpoint job that is not a leaf vertex due to the presence of a child job') self.runCheckpointVertexTest(*createWorkflowFn(), checkpointJobChild=Job.wrapJobFn( simpleJobFn, "LeafTestChild"), expectedException=JobGraphDeadlockException) logger.debug('Test checkpoint job that is not a leaf vertex due to the presence of a follow-on job') self.runCheckpointVertexTest(*createWorkflowFn(), checkpointJobFollowOn=Job.wrapJobFn( simpleJobFn, "LeafTestFollowOn"), expectedException=JobGraphDeadlockException) def runCheckpointVertexTest(self, workflowRootJob, checkpointJob, checkpointJobService=None, checkpointJobChild=None, checkpointJobFollowOn=None, expectedException=None): """ Modifies the checkpoint job according to the given parameters then runs the workflow, checking for the expected exception, if any. """ self.assertTrue(checkpointJob.checkpoint) if checkpointJobService is not None: checkpointJob.addService(checkpointJobService) if checkpointJobChild is not None: checkpointJob.addChild(checkpointJobChild) if checkpointJobFollowOn is not None: checkpointJob.addFollowOn(checkpointJobFollowOn) # Run the workflow and check for the expected behavior options = Job.Runner.getDefaultOptions(self._getTestJobStorePath()) options.logLevel = "INFO" if expectedException is None: Job.Runner.startToil(workflowRootJob, options) else: try: Job.Runner.startToil(workflowRootJob, options) self.fail("The expected exception was not thrown") except expectedException as ex: logger.debug("The expected exception was thrown: %s", repr(ex)) @slow def testEvaluatingRandomDAG(self): """ Randomly generate test input then check that the job graph can be run successfully, using the existence of promises to validate the run. """ jobStore = self._getTestJobStorePath() for test in range(5): # Temporary file tempDir = self._createTempDir(purpose='tempDir') # Make a random DAG for the set of child edges nodeNumber = random.choice(range(2, 8)) childEdges = self.makeRandomDAG(nodeNumber) # Get an adjacency list representation and check is acyclic adjacencyList = self.getAdjacencyList(nodeNumber, childEdges) self.assertTrue(self.isAcyclic(adjacencyList)) # Add in follow on edges - these are returned as a list, and as a set of augmented # edges in the adjacency list followOnEdges = self.addRandomFollowOnEdges(adjacencyList) self.assertTrue(self.isAcyclic(adjacencyList)) # Make the job graph rootJob = self.makeJobGraph(nodeNumber, childEdges, followOnEdges, tempDir) # Run the job graph options = Job.Runner.getDefaultOptions("%s.%i" % (jobStore, test)) options.logLevel = "DEBUG" options.retryCount = 1 options.badWorker = 0.25 options.badWorkerFailInterval = 0.01 # Now actually run the workflow try: with Toil(options) as toil: toil.start(rootJob) numberOfFailedJobs = 0 except FailedJobsException as e: numberOfFailedJobs = e.numberOfFailedJobs # Restart until successful or failed totalTrys = 1 options.restart = True while numberOfFailedJobs != 0: try: with Toil(options) as toil: toil.restart() numberOfFailedJobs = 0 except FailedJobsException as e: numberOfFailedJobs = e.numberOfFailedJobs if totalTrys > 32: #p(fail after this many restarts) ~= 0.5**32 self.fail() #Exceeded a reasonable number of restarts totalTrys += 1 # For each job check it created a valid output file and add the ordering # relationships contained within the output file to the ordering relationship, # so we can check they are compatible with the relationships defined by the job DAG. ordering = None for i in range(nodeNumber): with open(os.path.join(tempDir, str(i)), 'r') as fH: ordering = list(map(int, fH.readline().split())) self.assertEqual(int(ordering[-1]), i) for j in ordering[:-1]: adjacencyList[int(j)].add(i) # Check the ordering retains an acyclic graph if not self.isAcyclic(adjacencyList): print("ORDERING", ordering) print("CHILD EDGES", childEdges) print("FOLLOW ON EDGES", followOnEdges) print("ADJACENCY LIST", adjacencyList) self.assertTrue(self.isAcyclic(adjacencyList)) @staticmethod def getRandomEdge(nodeNumber): assert nodeNumber > 1 fNode = random.choice(range(nodeNumber - 1)) return fNode, random.choice(range(fNode+1, nodeNumber)) @staticmethod def makeRandomDAG(nodeNumber): """ Makes a random dag with "nodeNumber" nodes in which all nodes are connected. Return value is list of edges, each of form (a, b), where a and b are integers >= 0 < nodeNumber referring to nodes and the edge is from a to b. """ # Pick number of total edges to create edgeNumber = random.choice(range(nodeNumber - 1, 1 + old_div((nodeNumber * (nodeNumber - 1)), 2))) # Make a spanning tree of edges so that nodes are connected edges = set([(random.choice(range(i)), i) for i in range(1, nodeNumber)]) # Add extra random edges until there are edgeNumber edges while len(edges) < edgeNumber: edges.add(JobTest.getRandomEdge(nodeNumber)) return edges @staticmethod def getAdjacencyList(nodeNumber, edges): """ Make adjacency list representation of edges """ adjacencyList = [set() for _ in range(nodeNumber)] for fNode, tNode in edges: adjacencyList[fNode].add(tNode) return adjacencyList def reachable(self, node, adjacencyList, followOnAdjacencyList=None): """ Find the set of nodes reachable from this node (including the node). Return is a set of integers. """ visited = set() def dfs(fNode): if fNode not in visited: visited.add(fNode) list(map(dfs, adjacencyList[fNode])) if followOnAdjacencyList is not None: list(map(dfs, followOnAdjacencyList[fNode])) dfs(node) return visited def addRandomFollowOnEdges(self, childAdjacencyList): """ Adds random follow on edges to the graph, represented as an adjacency list. The follow on edges are returned as a set and their augmented edges are added to the adjacency list. """ def makeAugmentedAdjacencyList(): augmentedAdjacencyList = [childAdjacencyList[i].union(followOnAdjacencyList[i]) for i in range(len(childAdjacencyList))] def addImpliedEdges(node, followOnEdges): # Let node2 be a child of node or a successor of a child of node. # For all node2 the following adds an edge to the augmented # adjacency list from node2 to each followOn of node visited = set() def f(node2): if node2 not in visited: visited.add(node2) for i in followOnEdges: augmentedAdjacencyList[node2].add(i) list(map(f, childAdjacencyList[node2])) list(map(f, followOnAdjacencyList[node2])) list(map(f, childAdjacencyList[node])) for node in range(len(followOnAdjacencyList)): addImpliedEdges(node, followOnAdjacencyList[node]) return augmentedAdjacencyList followOnEdges = set() followOnAdjacencyList = [set() for i in childAdjacencyList] # Loop to create the follow on edges (try 1000 times) while random.random() > 0.001: fNode, tNode = JobTest.getRandomEdge(len(childAdjacencyList)) # Make an adjacency list including augmented edges and proposed # follow on edge # Add the new follow on edge followOnAdjacencyList[fNode].add(tNode) augmentedAdjacencyList = makeAugmentedAdjacencyList() # If the augmented adjacency doesn't contain a cycle then add the follow on edge to # the list of follow ons else remove the follow on edge from the follow on adjacency # list. if self.isAcyclic(augmentedAdjacencyList): followOnEdges.add((fNode, tNode)) else: followOnAdjacencyList[fNode].remove(tNode) # Update adjacency list adding in augmented edges childAdjacencyList[:] = makeAugmentedAdjacencyList()[:] return followOnEdges def makeJobGraph(self, nodeNumber, childEdges, followOnEdges, outPath, addServices=True): """ Converts a DAG into a job graph. childEdges and followOnEdges are the lists of child and followOn edges. """ # Map of jobs to the list of promises they have jobsToPromisesMap = {} def makeJob(string): promises = [] job = Job.wrapFn(fn2Test, promises, string, None if outPath is None else os.path.join(outPath, string)) jobsToPromisesMap[job] = promises return job # Make the jobs jobs = [makeJob(str(i)) for i in range(nodeNumber)] # Make the edges for fNode, tNode in childEdges: jobs[fNode].addChild(jobs[tNode]) for fNode, tNode in followOnEdges: jobs[fNode].addFollowOn(jobs[tNode]) # Map of jobs to return values jobsToRvs = dict([(job, job.addService(TrivialService(job.rv())) if addServices else job.rv()) for job in jobs]) def getRandomPredecessor(job): predecessor = random.choice(list(job._directPredecessors)) while random.random() > 0.5 and len(predecessor._directPredecessors) > 0: predecessor = random.choice(list(predecessor._directPredecessors)) return predecessor # Connect up set of random promises compatible with graph while random.random() > 0.01: job = random.choice(list(jobsToPromisesMap.keys())) promises = jobsToPromisesMap[job] if len(job._directPredecessors) > 0: predecessor = getRandomPredecessor(job) promises.append(jobsToRvs[predecessor]) return jobs[0] def isAcyclic(self, adjacencyList): """ Returns true if there are any cycles in the graph, which is represented as an adjacency list. """ def cyclic(fNode, visited, stack): if fNode not in visited: visited.add(fNode) assert fNode not in stack stack.append(fNode) for tNode in adjacencyList[fNode]: if cyclic(tNode, visited, stack): return True assert stack.pop() == fNode return fNode in stack visited = set() for i in range(len(adjacencyList)): if cyclic(i, visited, []): return False return True def simpleJobFn(job, value): job.fileStore.logToMaster(value) def fn1Test(string, outputFile): """ Function appends the next character after the last character in the given string to the string, writes the string to a file, and returns it. For example, if string is "AB", we will write and return "ABC". """ rV = string + chr(ord(string[-1]) + 1) with open(outputFile, 'w') as fH: fH.write(rV) return rV def fn2Test(pStrings, s, outputFile): """ Function concatenates the strings in pStrings and s, in that order, and writes the result to the output file. Returns s. """ with open(outputFile, 'w') as fH: fH.write(" ".join(pStrings) + " " + s) return s def trivialParent(job): strandedJob = JobFunctionWrappingJob(child) failingJob = JobFunctionWrappingJob(errorChild) job.addChild(failingJob) job.addChild(strandedJob) failingJob.addChild(strandedJob) def parent(job): childJob = JobFunctionWrappingJob(child) strandedJob = JobFunctionWrappingJob(child) failingJob = JobFunctionWrappingJob(errorChild) job.addChild(childJob) job.addChild(strandedJob) childJob.addChild(failingJob) failingJob.addChild(strandedJob) def diamond(job): childJob = JobFunctionWrappingJob(child) strandedJob = JobFunctionWrappingJob(child) failingJob = JobFunctionWrappingJob(errorChild) job.addChild(childJob) job.addChild(failingJob) childJob.addChild(strandedJob) failingJob.addChild(strandedJob) def child(job): assert job.cores is not None assert job.disk is not None assert job.memory is not None assert job.preemptable is not None def errorChild(job): raise RuntimeError('Child failure') class TrivialService(Job.Service): def __init__(self, message, *args, **kwargs): """ Service that does nothing, used to check for deadlocks """ Job.Service.__init__(self, *args, **kwargs) self.message = message def start(self, job): return self.message def stop(self, job): pass def check(self): pass if __name__ == '__main__': unittest.main() toil-releases-3.24.0/src/toil/test/src/miscTests.py000066400000000000000000000165141362134276200222210ustar00rootroot00000000000000# Copyright (C) 2015-2018 Regents of the University of California # # 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. from __future__ import absolute_import, print_function from future.utils import raise_ from builtins import range from uuid import uuid4 import os import random import tempfile import logging import inspect import sys from toil.lib.exceptions import panic from toil.common import getNodeID from toil.lib.misc import atomic_tmp_file, atomic_install, AtomicFileCreate from toil.test import ToilTest, slow, travis_test log = logging.getLogger(__name__) logging.basicConfig() class MiscTests(ToilTest): """ This class contains miscellaneous tests that don't have enough content to be their own test file, and that don't logically fit in with any of the other test suites. """ def setUp(self): super(MiscTests, self).setUp() self.testDir = self._createTempDir() @travis_test def testIDStability(self): prevNodeID = None for i in range(10, 1): nodeID = getNodeID() self.assertEqual(nodeID, prevNodeID) prevNodeID = nodeID @slow def testGetSizeOfDirectoryWorks(self): '''A test to make sure toil.common.getDirSizeRecursively does not underestimate the amount of disk space needed. Disk space allocation varies from system to system. The computed value should always be equal to or slightly greater than the creation value. This test generates a number of random directories and randomly sized files to test this using getDirSizeRecursively. ''' from toil.common import getDirSizeRecursively # a list of the directories used in the test directories = [self.testDir] # A dict of {FILENAME: FILESIZE} for all files used in the test files = {} # Create a random directory structure for i in range(0,10): directories.append(tempfile.mkdtemp(dir=random.choice(directories), prefix='test')) # Create 50 random file entries in different locations in the directories. 75% of the time # these are fresh files of sixe [1, 10] MB and 25% of the time they are hard links to old # files. while len(files) <= 50: fileName = os.path.join(random.choice(directories), self._getRandomName()) if random.randint(0,100) < 75: # Create a fresh file in the range of 1-10 MB fileSize = int(round(random.random(), 2) * 10 * 1024 * 1024) with open(fileName, 'wb') as fileHandle: fileHandle.write(os.urandom(fileSize)) files[fileName] = fileSize else: # Link to one of the previous files if len(files) == 0: continue linkSrc = random.choice(list(files.keys())) os.link(linkSrc, fileName) files[fileName] = 'Link to %s' % linkSrc computedDirectorySize = getDirSizeRecursively(self.testDir) totalExpectedSize = sum([x for x in list(files.values()) if isinstance(x, int)]) self.assertGreaterEqual(computedDirectorySize, totalExpectedSize) @staticmethod def _getRandomName(): return uuid4().hex def _get_test_out_file(self, tail): outf = os.path.join(self.testDir, self.id() + "." + tail) if os.path.exists(outf): os.unlink(outf) return outf def _write_test_file(self, outf_tmp): with open(outf_tmp, "w") as fh: fh.write(self.id() + '\n') def test_atomic_install(self): outf = self._get_test_out_file(".foo.gz") outf_tmp = atomic_tmp_file(outf) self._write_test_file(outf_tmp) atomic_install(outf_tmp, outf) self.assertTrue(os.path.exists(outf)) def test_atomic_install_dev(self): devn = '/dev/null' tmp = atomic_tmp_file(devn) self.assertEqual(tmp, devn) atomic_install(tmp, devn) def test_atomic_context_ok(self): outf = self._get_test_out_file(".tar") with AtomicFileCreate(outf) as outf_tmp: self._write_test_file(outf_tmp) self.assertTrue(os.path.exists(outf)) def test_atomic_context_error(self): outf = self._get_test_out_file(".tar") try: with AtomicFileCreate(outf) as outf_tmp: self._write_test_file(outf_tmp) raise Exception("stop!") except Exception as ex: self.assertEqual(str(ex), "stop!") self.assertFalse(os.path.exists(outf)) class TestPanic(ToilTest): @travis_test def test_panic_by_hand(self): try: self.try_and_panic_by_hand() except: self.__assert_raised_exception_is_primary() @travis_test def test_panic(self): try: self.try_and_panic() except: self.__assert_raised_exception_is_primary() @travis_test def test_panic_with_secondary(self): try: self.try_and_panic_with_secondary() except: self.__assert_raised_exception_is_primary() @travis_test def test_nested_panic(self): try: self.try_and_nested_panic_with_secondary() except: self.__assert_raised_exception_is_primary() def try_and_panic_by_hand(self): try: self.line_of_primary_exc = inspect.currentframe().f_lineno + 1 raise ValueError("primary") except Exception: exc_type, exc_value, exc_traceback = sys.exc_info() try: raise RuntimeError("secondary") except Exception: pass raise_(exc_type, exc_value, exc_traceback) def try_and_panic(self): try: self.line_of_primary_exc = inspect.currentframe().f_lineno + 1 raise ValueError("primary") except: with panic(log): pass def try_and_panic_with_secondary(self): try: self.line_of_primary_exc = inspect.currentframe().f_lineno + 1 raise ValueError("primary") except: with panic( log ): raise RuntimeError("secondary") def try_and_nested_panic_with_secondary(self): try: self.line_of_primary_exc = inspect.currentframe().f_lineno + 1 raise ValueError("primary") except: with panic( log ): with panic( log ): raise RuntimeError("secondary") def __assert_raised_exception_is_primary(self): exc_type, exc_value, exc_traceback = sys.exc_info() self.assertEqual(exc_type, ValueError) self.assertEqual(str(exc_value), "primary") while exc_traceback.tb_next is not None: exc_traceback = exc_traceback.tb_next self.assertEqual(exc_traceback.tb_lineno, self.line_of_primary_exc) toil-releases-3.24.0/src/toil/test/src/promisedRequirementTest.py000066400000000000000000000220671362134276200251460ustar00rootroot00000000000000# Copyright (C) 2015-2016 Regents of the University of California # # 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. from __future__ import absolute_import, print_function from __future__ import division from builtins import range from builtins import object from past.utils import old_div import os import logging import time import toil.test.batchSystems.batchSystemTest as batchSystemTest from toil.job import Job from toil.job import PromisedRequirement from toil.test import needs_mesos, slow, travis_test from toil.batchSystems.mesos.test import MesosTestSupport log = logging.getLogger(__name__) class hidden(object): """ Hide abstract base class from unittest's test case loader. http://stackoverflow.com/questions/1323455/python-unit-test-with-base-and-sub-class#answer-25695512 """ class AbstractPromisedRequirementsTest(batchSystemTest.hidden.AbstractBatchSystemJobTest): """ An abstract base class for testing Toil workflows with promised requirements. """ @slow def testConcurrencyDynamic(self): """ Asserts that promised core resources are allocated properly using a dynamic Toil workflow """ for coresPerJob in self.allocatedCores: log.debug('Testing %d cores per job with CPU count %d', coresPerJob, self.cpuCount) tempDir = self._createTempDir('testFiles') counterPath = self.getCounterPath(tempDir) root = Job.wrapJobFn(maxConcurrency, self.cpuCount, counterPath, coresPerJob, cores=1, memory='1M', disk='1M') values = Job.Runner.startToil(root, self.getOptions(tempDir)) maxValue = max(values) self.assertEqual(maxValue, old_div(self.cpuCount, coresPerJob)) @slow def testConcurrencyStatic(self): """ Asserts that promised core resources are allocated properly using a static DAG """ for coresPerJob in self.allocatedCores: log.debug('Testing %d cores per job with CPU count %d', coresPerJob, self.cpuCount) tempDir = self._createTempDir('testFiles') counterPath = self.getCounterPath(tempDir) root = Job() one = Job.wrapFn(getOne, cores=0.1, memory='32M', disk='1M') thirtyTwoMb = Job.wrapFn(getThirtyTwoMb, cores=0.1, memory='32M', disk='1M') root.addChild(one) root.addChild(thirtyTwoMb) for _ in range(self.cpuCount): root.addFollowOn(Job.wrapFn(batchSystemTest.measureConcurrency, counterPath, cores=PromisedRequirement(lambda x: x * coresPerJob, one.rv()), memory=PromisedRequirement(thirtyTwoMb.rv()), disk='1M')) Job.Runner.startToil(root, self.getOptions(tempDir)) _, maxValue = batchSystemTest.getCounters(counterPath) self.assertEqual(maxValue, old_div(self.cpuCount, coresPerJob)) def getOptions(self, tempDir, caching=True): options = super(hidden.AbstractPromisedRequirementsTest, self).getOptions(tempDir) # defaultCores defaults to 1 - this is coincidentally the core requirement relied upon by this # test, so we change defaultCores to 2 to make the test more strict options.defaultCores = 2 if not caching: options.disableCaching = True return options def getCounterPath(self, tempDir): """ Returns path to a counter file :param str tempDir: path to test directory :return: path to counter file """ counterPath = os.path.join(tempDir, 'counter') batchSystemTest.resetCounters(counterPath) minValue, maxValue = batchSystemTest.getCounters(counterPath) assert (minValue, maxValue) == (0, 0) return counterPath @travis_test def testJobConcurrency(self): pass @travis_test def testPromisesWithJobStoreFileObjects(self, caching=True): """ Check whether FileID objects are being pickled properly when used as return values of functions. Then ensure that lambdas of promised FileID objects can be used to describe the requirements of a subsequent job. This type of operation will be used commonly in Toil scripts. :return: None """ file1 = 1024 file2 = 512 F1 = Job.wrapJobFn(_writer, file1) F2 = Job.wrapJobFn(_writer, file2) G = Job.wrapJobFn(_follower, file1 + file2, disk=PromisedRequirement(lambda x, y: x.size + y.size, F1.rv(), F2.rv())) F1.addChild(F2) F2.addChild(G) Job.Runner.startToil(F1, self.getOptions(self._createTempDir('testFiles'), caching=caching)) @travis_test def testPromisesWithNonCachingFileStore(self): self.testPromisesWithJobStoreFileObjects(caching=False) @slow def testPromiseRequirementRaceStatic(self): """ Checks for a race condition when using promised requirements and child job functions. """ A = Job.wrapJobFn(logDiskUsage, 'A', sleep=5, disk=PromisedRequirement(1024)) B = Job.wrapJobFn(logDiskUsage, 'B', disk=PromisedRequirement(lambda x: x + 1024, A.rv())) A.addChild(B) Job.Runner.startToil(A, self.getOptions(self._createTempDir('testFiles'))) def _writer(job, fileSize): ''' Write a local file and return the FileID obtained from running writeGlobalFile on it. :param job job: job :param int fileSize: Size of the file in bytes :returns: the result of writeGlobalFile on a locally created file :rtype: job.FileID ''' with open(job.fileStore.getLocalTempFileName(), 'wb') as fH: fH.write(os.urandom(fileSize)) return job.fileStore.writeGlobalFile(fH.name) def _follower(job, expectedDisk): """ This job follows the _writer jobs and ensures the expected disk is used. :param job job: job :param expectedDisk: Expect disk to be used by this job :return: None """ assert job.disk == expectedDisk def maxConcurrency(job, cpuCount, filename, coresPerJob): """ Returns the max number of concurrent tasks when using a PromisedRequirement instance to allocate the number of cores per job. :param int cpuCount: number of available cpus :param str filename: path to counter file :param int coresPerJob: number of cores assigned to each job :return int max concurrency value: """ one = job.addChildFn(getOne, cores=0.1, memory='32M', disk='1M') thirtyTwoMb = job.addChildFn(getThirtyTwoMb, cores=0.1, memory='32M', disk='1M') values = [] for _ in range(cpuCount): value = job.addFollowOnFn(batchSystemTest.measureConcurrency, filename, cores=PromisedRequirement(lambda x: x * coresPerJob, one.rv()), memory=PromisedRequirement(thirtyTwoMb.rv()), disk='1M').rv() values.append(value) return values def getOne(): return 1 def getThirtyTwoMb(): return '32M' def logDiskUsage(job, funcName, sleep=0): """ Logs the job's disk usage to master and sleeps for specified amount of time. :return: job function's disk usage """ diskUsage = job.disk job.fileStore.logToMaster('{}: {}'.format(funcName, diskUsage)) time.sleep(sleep) return diskUsage class SingleMachinePromisedRequirementsTest(hidden.AbstractPromisedRequirementsTest): """ Tests against the SingleMachine batch system """ def getBatchSystemName(self): return "singleMachine" def tearDown(self): pass @needs_mesos class MesosPromisedRequirementsTest(hidden.AbstractPromisedRequirementsTest, MesosTestSupport): """ Tests against the Mesos batch system """ def getOptions(self, tempDir, caching=True): options = super(MesosPromisedRequirementsTest, self).getOptions(tempDir, caching=caching) options.mesosMasterAddress = 'localhost:5050' return options def getBatchSystemName(self): self._startMesos(self.cpuCount) return "mesos" def tearDown(self): self._stopMesos() toil-releases-3.24.0/src/toil/test/src/promisesTest.py000066400000000000000000000046721362134276200227460ustar00rootroot00000000000000# Copyright (C) 2015-2016 Regents of the University of California # # 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. from __future__ import absolute_import from builtins import range from toil.job import Job from toil.test import ToilTest, travis_test class CachedUnpicklingJobStoreTest(ToilTest): """ https://github.com/BD2KGenomics/toil/issues/817 """ @travis_test def test(self): """ Runs two identical Toil workflows with different job store paths """ for _ in range(2): options = Job.Runner.getDefaultOptions(self._getTestJobStorePath()) options.logLevel = 'INFO' root = Job.wrapJobFn(parent) Job.Runner.startToil(root, options) def parent(job): return job.addChildFn(child).rv() def child(): return 1 class ChainedIndexedPromisesTest(ToilTest): """ https://github.com/BD2KGenomics/toil/issues/1021 """ @travis_test def test(self): options = Job.Runner.getDefaultOptions(self._getTestJobStorePath()) options.logLevel = 'INFO' root = Job.wrapJobFn(a) self.assertEqual(Job.Runner.startToil(root, options), 42) def a(job): return job.addChild(job.wrapJobFn(b)).rv(0) def b(job): return job.addChild(job.wrapFn(c)).rv() def c(): return 42, 43 class PathIndexingPromiseTest(ToilTest): """ Test support for indexing promises of arbitrarily nested data structures of lists, dicts and tuples, or any other object supporting the __getitem__() protocol. """ @travis_test def test(self): options = Job.Runner.getDefaultOptions(self._getTestJobStorePath()) options.logLevel = 'INFO' root = Job.wrapJobFn(d) self.assertEqual(Job.Runner.startToil(root, options), ('b', 43, 3)) def d(job): child = job.addChild(job.wrapFn(e)) return child.rv('a'), child.rv(42), child.rv('c', 2) def e(): return {'a': 'b', 42: 43, 'c': [1, 2, 3]} toil-releases-3.24.0/src/toil/test/src/realtimeLoggerTest.py000066400000000000000000000043071362134276200240420ustar00rootroot00000000000000# Copyright (C) 2015-2016 Regents of the University of California # # 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. from __future__ import absolute_import from toil.job import Job from toil.test import ToilTest, travis_test import logging from toil.realtimeLogger import RealtimeLogger class RealtimeLoggerTest(ToilTest): @travis_test def testRealtimeLogger(self): options = Job.Runner.getDefaultOptions(self._getTestJobStorePath()) options.realTimeLogging = True options.logLevel = 'INFO' detector = MessageDetector() # Set up a log message detector to the root logger logging.getLogger().addHandler(detector) Job.Runner.startToil(LogTest(), options) # We need the message we're supposed to see self.assertTrue(detector.detected) # But not the message that shouldn't be logged. self.assertFalse(detector.overLogged) class MessageDetector(logging.StreamHandler): """ Detect the secret message and set a flag. """ def __init__(self): self.detected = False # Have we seen the message we want? self.overLogged = False # Have we seen the message we don't want? super(MessageDetector, self).__init__() def emit(self, record): if record.msg == 'This should be logged at info level': self.detected = True if record.msg == 'This should be logged at debug level': self.overLogged = True class LogTest(Job): def __init__(self): Job.__init__(self, memory=100000, cores=2, disk='3G') def run(self, fileStore): RealtimeLogger.info('This should be logged at info level') RealtimeLogger.debug('This should be logged at debug level') toil-releases-3.24.0/src/toil/test/src/regularLogTest.py000066400000000000000000000106211362134276200231770ustar00rootroot00000000000000from __future__ import print_function # Copyright (C) 2015-2016 Regents of the University of California # # 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. import logging import mimetypes import sys import os from toil import subprocess from toil.test import ToilTest, slow, travis_test from toil.test.mesos import helloWorld logging.basicConfig(level=logging.DEBUG) logger = logging.getLogger(__name__) class RegularLogTest(ToilTest): def setUp(self): super(RegularLogTest, self).setUp() self.tempDir = self._createTempDir(purpose='tempDir') def _getFiles(self, dir): return [os.path.join(dir, f) for f in os.listdir(dir) if os.path.isfile(os.path.join(dir, f))] def _assertFileTypeExists(self, dir, extension, encoding=None): # an encoding of None implies no compression logger.info("Checking for %s file in %s", extension, dir) onlyFiles = self._getFiles(dir) logger.info("Found: %s", str(os.listdir(dir))) onlyLogs = [f for f in onlyFiles if f.endswith(extension)] logger.info("Found matching: %s", str(onlyLogs)) assert onlyLogs if encoding is not None: for log in onlyLogs: with open(log, "rb") as f: logger.info("Checking for encoding %s on file %s", str(encoding), log) if encoding == "gzip": # Check for gzip magic header '\x1f\x8b' assert f.read().startswith(b'\x1f\x8b') else: mime = mimetypes.guess_type(log) self.assertEqual(mime[1], encoding) @slow def testLogToMaster(self): toilOutput = subprocess.check_output([sys.executable, '-m', helloWorld.__name__, './toilTest', '--clean=always', '--logLevel=info'], stderr=subprocess.STDOUT) assert helloWorld.childMessage in toilOutput.decode('utf-8') @travis_test def testWriteLogs(self): subprocess.check_call([sys.executable, '-m', helloWorld.__name__, './toilTest', '--clean=always', '--logLevel=debug', '--writeLogs=%s' % self.tempDir]) self._assertFileTypeExists(self.tempDir, '.log') @slow def testWriteGzipLogs(self): subprocess.check_call([sys.executable, '-m', helloWorld.__name__, './toilTest', '--clean=always', '--logLevel=debug', '--writeLogsGzip=%s' % self.tempDir]) self._assertFileTypeExists(self.tempDir, '.log.gz', 'gzip') @slow def testMultipleLogToMaster(self): toilOutput = subprocess.check_output([sys.executable, '-m', helloWorld.__name__, './toilTest', '--clean=always', '--logLevel=info'], stderr=subprocess.STDOUT) assert helloWorld.parentMessage in toilOutput.decode('utf-8') @travis_test def testRegularLog(self): toilOutput = subprocess.check_output([sys.executable, '-m', helloWorld.__name__, './toilTest', '--clean=always', '--batchSystem=singleMachine', '--logLevel=debug'], stderr=subprocess.STDOUT) assert "single machine batch system" in toilOutput.decode('utf-8') toil-releases-3.24.0/src/toil/test/src/resourceTest.py000066400000000000000000000247721362134276200227370ustar00rootroot00000000000000# Copyright (C) 2015-2018 Regents of the University of California # # 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. from __future__ import absolute_import import importlib import os import sys from inspect import getsource from io import BytesIO from textwrap import dedent from zipfile import ZipFile from toil.test import mkdir_p from mock import MagicMock, patch from toil import subprocess from toil import inVirtualEnv from toil.resource import ModuleDescriptor, Resource, ResourceException from toil.test import ToilTest, tempFileContaining, travis_test from toil.version import exactPython class ResourceTest(ToilTest): """ Test module descriptors and resources derived from them. """ @travis_test def testStandAlone(self): self._testExternal(moduleName='userScript', pyFiles=('userScript.py', 'helper.py')) @travis_test def testPackage(self): self._testExternal(moduleName='foo.userScript', pyFiles=('foo/__init__.py', 'foo/userScript.py', 'foo/bar/__init__.py', 'foo/bar/helper.py')) @travis_test def testVirtualEnv(self): self._testExternal(moduleName='foo.userScript', virtualenv=True, pyFiles=('foo/__init__.py', 'foo/userScript.py', 'foo/bar/__init__.py', 'foo/bar/helper.py', 'de/pen/dency.py', 'de/__init__.py', 'de/pen/__init__.py')) @travis_test def testStandAloneInPackage(self): self.assertRaises(ResourceException, self._testExternal, moduleName='userScript', pyFiles=('__init__.py', 'userScript.py', 'helper.py')) def _testExternal(self, moduleName, pyFiles, virtualenv=False): dirPath = self._createTempDir() if virtualenv: self.assertTrue(inVirtualEnv()) # --never-download prevents silent upgrades to pip, wheel and setuptools subprocess.check_call(['virtualenv', '--never-download', '--python', exactPython, dirPath]) sitePackages = os.path.join(dirPath, 'lib', exactPython, 'site-packages') # tuple assignment is necessary to make this line immediately precede the try: oldPrefix, sys.prefix, dirPath = sys.prefix, dirPath, sitePackages else: oldPrefix = None try: for relPath in pyFiles: path = os.path.join(dirPath, relPath) mkdir_p(os.path.dirname(path)) with open(path, 'w') as f: f.write('pass\n') sys.path.append(dirPath) try: userScript = importlib.import_module(moduleName) try: self._test(userScript.__name__, expectedContents=pyFiles, allowExtraContents=True) finally: del userScript while moduleName: del sys.modules[moduleName] self.assertFalse(moduleName in sys.modules) moduleName = '.'.join(moduleName.split('.')[:-1]) finally: sys.path.remove(dirPath) finally: if oldPrefix: sys.prefix = oldPrefix @travis_test def testBuiltIn(self): # Create a ModuleDescriptor for the module containing ModuleDescriptor, i.e. toil.resource module_name = ModuleDescriptor.__module__ self.assertEqual(module_name, 'toil.resource') self._test(module_name, shouldBelongToToil=True) def _test(self, module_name, shouldBelongToToil=False, expectedContents=None, allowExtraContents=True): module = ModuleDescriptor.forModule(module_name) # Assert basic attributes and properties self.assertEqual(module.belongsToToil, shouldBelongToToil) self.assertEqual(module.name, module_name) if shouldBelongToToil: self.assertTrue(module.dirPath.endswith('/src')) # Before the module is saved as a resource, localize() and globalize() are identity # methods. This should log.warnings. self.assertIs(module.localize(), module) self.assertIs(module.globalize(), module) # Create a mock job store ... jobStore = MagicMock() # ... to generate a fake URL for the resource ... url = 'file://foo.zip' jobStore.getSharedPublicUrl.return_value = url # ... and save the resource to it. resource = module.saveAsResourceTo(jobStore) # Ensure that the URL generation method is actually called, ... jobStore.getSharedPublicUrl.assert_called_once_with(sharedFileName=resource.pathHash) # ... and that ensure that writeSharedFileStream is called. jobStore.writeSharedFileStream.assert_called_once_with(sharedFileName=resource.pathHash, isProtected=False) # Now it gets a bit complicated: Ensure that the context manager returned by the # jobStore's writeSharedFileStream() method is entered and that the file handle yielded # by the context manager is written to once with the zipped source tree from which # 'toil.resource' was orginally imported. Keep the zipped tree around such that we can # mock the download later. file_handle = jobStore.writeSharedFileStream.return_value.__enter__.return_value # The first 0 index selects the first call of write(), the second 0 selects positional # instead of keyword arguments, and the third 0 selects the first positional, i.e. the # contents. This is a bit brittle since it assumes that all the data is written in a # single call to write(). If more calls are made we can easily concatenate them. zipFile = file_handle.write.call_args_list[0][0][0] self.assertTrue(zipFile.startswith(b'PK')) # the magic header for ZIP files # Check contents if requested if expectedContents is not None: with ZipFile(BytesIO(zipFile)) as _zipFile: actualContents = set(_zipFile.namelist()) if allowExtraContents: self.assertTrue(actualContents.issuperset(expectedContents)) else: self.assertEqual(actualContents, expectedContents) self.assertEqual(resource.url, url) # Now we're on the worker. Prepare the storage for localized resources Resource.prepareSystem() try: # Register the resource for subsequent lookup. resource.register() # Lookup the resource and ensure that the result is equal to but not the same as the # original resource. Lookup will also be used when we localize the module that was # originally used to create the resource. localResource = Resource.lookup(module._resourcePath) self.assertEqual(resource, localResource) self.assertIsNot(resource, localResource) # Now show that we can localize the module using the registered resource. Set up a mock # urlopen() that yields the zipped tree ... mock_urlopen = MagicMock() mock_urlopen.return_value.read.return_value = zipFile with patch('toil.resource.urlopen', mock_urlopen): # ... and use it to download and unpack the resource localModule = module.localize() # The name should be equal between original and localized resource ... self.assertEqual(module.name, localModule.name) # ... but the directory should be different. self.assertNotEqual(module.dirPath, localModule.dirPath) # Show that we can 'undo' localization. This is necessary when the user script's jobs # are invoked on the worker where they generate more child jobs. self.assertEqual(localModule.globalize(), module) finally: Resource.cleanSystem() @travis_test def testNonPyStandAlone(self): """ Asserts that Toil enforces the user script to have a .py or .pyc extension because that's the only way auto-deployment can re-import the module on a worker. See https://github.com/BD2KGenomics/toil/issues/631 and https://github.com/BD2KGenomics/toil/issues/858 """ def script(): import argparse from toil.job import Job from toil.common import Toil def fn(): pass if __name__ == '__main__': parser = argparse.ArgumentParser() Job.Runner.addToilOptions(parser) options = parser.parse_args() job = Job.wrapFn(fn, memory='10M', cores=0.1, disk='10M') with Toil(options) as toil: toil.start(job) scriptBody = dedent('\n'.join(getsource(script).split('\n')[1:])) shebang = '#! %s\n' % sys.executable with tempFileContaining(shebang + scriptBody) as scriptPath: self.assertFalse(scriptPath.endswith(('.py', '.pyc'))) os.chmod(scriptPath, 0o755) jobStorePath = scriptPath + '.jobStore' process = subprocess.Popen([scriptPath, jobStorePath], stderr=subprocess.PIPE) stdout, stderr = process.communicate() self.assertTrue('The name of a user script/module must end in .py or .pyc.' in stderr.decode('utf-8')) self.assertNotEqual(0, process.returncode) self.assertFalse(os.path.exists(jobStorePath)) toil-releases-3.24.0/src/toil/test/src/restartDAGTest.py000066400000000000000000000140151362134276200230750ustar00rootroot00000000000000# Copyright (C) 2015-2016 Regents of the University of California # # 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. from __future__ import absolute_import import logging from toil.common import Toil from toil.job import Job from toil.leader import FailedJobsException from toil.test import ToilTest, slow import inspect import os import shutil import signal logger = logging.getLogger(__name__) class RestartDAGTest(ToilTest): """ Tests that restarted job DAGs don't run children of jobs that failed in the first run till the parent completes successfully in the restart. """ def setUp(self): super(RestartDAGTest, self).setUp() self.tempDir = self._createTempDir(purpose='tempDir') self.testJobStore = self._getTestJobStorePath() def tearDown(self): super(RestartDAGTest, self).tearDown() shutil.rmtree(self.testJobStore) @slow def testRestartedWorkflowSchedulesCorrectJobsOnFailedParent(self): self._testRestartedWorkflowSchedulesCorrectJobs('raise') @slow def testRestartedWorkflowSchedulesCorrectJobsOnKilledParent(self): self._testRestartedWorkflowSchedulesCorrectJobs('kill') def _testRestartedWorkflowSchedulesCorrectJobs(self, failType): """ Creates a diamond DAG /->passingParent-\ root |-->child \->failingParent--/ where root and passingParent are guaranteed to pass, while failingParent will fail. child should not run on start or restart and we assert that by ensuring that a file create iff child is run is not present on the system. :param str failType: Does failingParent fail on an assertionError, or is it killed. """ # Specify options options = Job.Runner.getDefaultOptions(self.testJobStore) options.logLevel = 'DEBUG' options.retryCount = 0 options.clean = "never" parentFile = os.path.join(self.tempDir, 'parent') childFile = os.path.join(self.tempDir, 'child') # Make the first job root = Job.wrapJobFn(passingFn) passingParent = Job.wrapJobFn(passingFn) failingParent = Job.wrapJobFn(failingFn, failType=failType, fileName=parentFile) child = Job.wrapJobFn(passingFn, fileName=childFile) # define the DAG root.addChild(passingParent) root.addChild(failingParent) passingParent.addChild(child) failingParent.addChild(child) failReasons = [] assert not os.path.exists(childFile) # Run the test for runMode in 'start', 'restart': self.errorRaised = None try: with Toil(options) as toil: if runMode == 'start': toil.start(root) else: toil.restart() except Exception as e: logger.exception(e) self.errorRaised = e finally: # The processing of an AssertionError and FailedJobsException is the same so we do # it together in this finally clause. if self.errorRaised is not None: if not os.path.exists(parentFile): failReasons.append('The failing parent file did not exist on toil "%s".' % runMode) if os.path.exists(childFile): failReasons.append('The child file existed. i.e. the child was run on ' 'toil "%s".' % runMode) if isinstance(self.errorRaised, FailedJobsException): if self.errorRaised.numberOfFailedJobs != 3: failReasons.append('FailedJobsException was raised on toil "%s" but ' 'the number of failed jobs (%s) was not 3.' % (runMode, self.errorRaised.numberOfFailedJobs)) elif isinstance(self.errorRaised, AssertionError): failReasons.append('Toil raised an AssertionError instead of a ' 'FailedJobsException on toil "%s".' % runMode) else: failReasons.append("Toil raised error: %s" % self.errorRaised) self.errorRaised = None options.restart = True else: self.fail('No errors were raised on toil "%s".' % runMode) if failReasons: self.fail('Test failed for (%s) reasons:\n\t%s' % (len(failReasons), '\n\t'.join(failReasons))) def passingFn(job, fileName=None): """ This function is guaranteed to pass as it does nothing out of the ordinary. If fileName is provided, it will be created. :param str fileName: The name of a file that must be created if provided. """ if fileName is not None: # Emulates system touch. open(fileName, 'w').close() def failingFn(job, failType, fileName): """ This function is guaranteed to fail via a raised assertion, or an os.kill :param job: Job :param str failType: 'raise' or 'kill :param str fileName: The name of a file that must be created. """ assert failType in ('raise', 'kill') # Use that function to avoid code redundancy passingFn(job, fileName) if failType == 'raise': assert False else: os.kill(os.getpid(), signal.SIGKILL) toil-releases-3.24.0/src/toil/test/src/resumabilityTest.py000066400000000000000000000060321362134276200236060ustar00rootroot00000000000000# Copyright (C) 2016 UCSC Computational Genomics Lab # # 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. from __future__ import absolute_import from builtins import range import os # Python 3 compatibility imports from six.moves import xrange from toil.job import Job from toil.test import ToilTest, slow from toil.jobStores.abstractJobStore import NoSuchFileException from toil.leader import FailedJobsException @slow class ResumabilityTest(ToilTest): """ https://github.com/BD2KGenomics/toil/issues/808 """ def test(self): """ Tests that a toil workflow that fails once can be resumed without a NoSuchJobException. """ options = Job.Runner.getDefaultOptions(self._getTestJobStorePath()) options.logLevel = "INFO" options.retryCount = 0 root = Job.wrapJobFn(parent) with self.assertRaises(FailedJobsException): # This one is intended to fail. Job.Runner.startToil(root, options) # Resume the workflow. Unfortunately, we have to check for # this bug using the logging output, since although the # NoSuchJobException causes the worker to fail, the batch # system code notices that the job has been deleted despite # the failure and avoids the failure. options.restart = True tempDir = self._createTempDir() options.logFile = os.path.join(tempDir, "log.txt") Job.Runner.startToil(root, options) with open(options.logFile) as f: logString = f.read() # We are looking for e.g. "Batch system is reporting that # the jobGraph with batch system ID: 1 and jobGraph # store ID: n/t/jobwbijqL failed with exit value 1" self.assertTrue("failed with exit value" not in logString) def parent(job): """ Set up a bunch of dummy child jobs, and a bad job that needs to be restarted as the follow on. """ for _ in range(5): job.addChildJobFn(goodChild) job.addFollowOnJobFn(badChild) def goodChild(job): """ Does nothing. """ return def badChild(job): """ Fails the first time it's run, succeeds the second time. """ try: with job.fileStore.jobStore.readSharedFileStream("alreadyRun") as fileHandle: fileHandle.read() except NoSuchFileException as ex: with job.fileStore.jobStore.writeSharedFileStream("alreadyRun", isProtected=False) as fileHandle: fileHandle.write(b"failed once\n") raise RuntimeError("this is an expected error: {}".format(str(ex))) toil-releases-3.24.0/src/toil/test/src/retainTempDirTest.py000066400000000000000000000111471362134276200236470ustar00rootroot00000000000000# Copyright (C) 2015-2016 Regents of the University of California # # 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. from __future__ import absolute_import, print_function import os import shutil from toil.job import Job from toil.leader import FailedJobsException from toil.test import ToilTest, travis_test class CleanWorkDirTest(ToilTest): """ Tests testing :class:toil.fileStores.abstractFileStore.AbstractFileStore """ def setUp(self): super(CleanWorkDirTest, self).setUp() self.testDir = self._createTempDir() def tearDown(self): super(CleanWorkDirTest, self).tearDown() shutil.rmtree(self.testDir) @travis_test def testNever(self): retainedTempData = self._runAndReturnWorkDir("never", job=tempFileTestJob) self.assertNotEqual(retainedTempData, [], "The worker's temporary workspace was deleted despite " "cleanWorkDir being set to 'never'") @travis_test def testAlways(self): retainedTempData = self._runAndReturnWorkDir("always", job=tempFileTestJob) self.assertEqual(retainedTempData, [], "The worker's temporary workspace was not deleted despite " "cleanWorkDir being set to 'always'") @travis_test def testOnErrorWithError(self): retainedTempData = self._runAndReturnWorkDir("onError", job=tempFileTestErrorJob, expectError=True) self.assertEqual(retainedTempData, [], "The worker's temporary workspace was not deleted despite " "an error occurring and cleanWorkDir being set to 'onError'") @travis_test def testOnErrorWithNoError(self): retainedTempData = self._runAndReturnWorkDir("onError", job=tempFileTestJob) self.assertNotEqual(retainedTempData, [], "The worker's temporary workspace was deleted despite " "no error occurring and cleanWorkDir being set to 'onError'") @travis_test def testOnSuccessWithError(self): retainedTempData = self._runAndReturnWorkDir("onSuccess", job=tempFileTestErrorJob, expectError=True) self.assertNotEqual(retainedTempData, [], "The worker's temporary workspace was deleted despite " "an error occurring and cleanWorkDir being set to 'onSuccesss'") @travis_test def testOnSuccessWithSuccess(self): retainedTempData = self._runAndReturnWorkDir("onSuccess", job=tempFileTestJob) self.assertEqual(retainedTempData, [], "The worker's temporary workspace was not deleted despite " "a successful job execution and cleanWorkDir being set to 'onSuccesss'") def _runAndReturnWorkDir(self, cleanWorkDir, job, expectError=False): """ Runs toil with the specified job and cleanWorkDir setting. expectError determines whether the test's toil run is expected to succeed, and the test will fail if that expectation is not met. returns the contents of the workDir after completion of the run """ options = Job.Runner.getDefaultOptions(self._getTestJobStorePath()) options.workDir = self.testDir options.clean = "always" options.cleanWorkDir = cleanWorkDir A = Job.wrapJobFn(job) if expectError: self._launchError(A, options) else: self._launchRegular(A, options) return os.listdir(self.testDir) def _launchRegular(self, A, options): Job.Runner.startToil(A, options) def _launchError(self, A, options): try: Job.Runner.startToil(A, options) except FailedJobsException: pass # we expect a job to fail here else: self.fail("Toil run succeeded unexpectedly") def tempFileTestJob(job): with open(job.fileStore.getLocalTempFile(), "w") as f: f.write("test file retention") def tempFileTestErrorJob(job): with open(job.fileStore.getLocalTempFile(), "w") as f: f.write("test file retention") raise RuntimeError() # test failure toil-releases-3.24.0/src/toil/test/src/systemTest.py000066400000000000000000000043111362134276200224170ustar00rootroot00000000000000from builtins import range import errno import multiprocessing import os import tempfile from functools import partial from toil.lib.threading import cpu_count from toil.test import ToilTest, travis_test class SystemTest(ToilTest): """ Test various assumptions about the operating system's behavior """ @travis_test def testAtomicityOfNonEmptyDirectoryRenames(self): for _ in range(100): parent = self._createTempDir(purpose='parent') child = os.path.join(parent, 'child') # Use processes (as opposed to threads) to prevent GIL from ordering things artificially pool = multiprocessing.Pool() try: numTasks = cpu_count() * 10 grandChildIds = pool.map_async( func=partial(_testAtomicityOfNonEmptyDirectoryRenamesTask, parent, child), iterable=list(range(numTasks))) grandChildIds = grandChildIds.get() finally: pool.close() pool.join() self.assertEqual(len(grandChildIds), numTasks) # Assert that we only had one winner grandChildIds = [n for n in grandChildIds if n is not None] self.assertEqual(len(grandChildIds), 1) # Assert that the winner's grandChild wasn't silently overwritten by a looser expectedGrandChildId = grandChildIds[0] actualGrandChild = os.path.join(child, 'grandChild') actualGrandChildId = os.stat(actualGrandChild).st_ino self.assertEqual(actualGrandChildId, expectedGrandChildId) def _testAtomicityOfNonEmptyDirectoryRenamesTask(parent, child, _): tmpChildDir = tempfile.mkdtemp(dir=parent, prefix='child', suffix='.tmp') grandChild = os.path.join(tmpChildDir, 'grandChild') open(grandChild, 'w').close() grandChildId = os.stat(grandChild).st_ino try: os.rename(tmpChildDir, child) except OSError as e: if e.errno == errno.ENOTEMPTY or e.errno == errno.EEXIST: os.unlink(grandChild) os.rmdir(tmpChildDir) return None else: raise else: # We won the race return grandChildId toil-releases-3.24.0/src/toil/test/src/toilContextManagerTest.py000066400000000000000000000061401362134276200247040ustar00rootroot00000000000000# Copyright (C) 2015-2016 Regents of the University of California # # 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. from __future__ import absolute_import import os from toil.lib.bioio import getTempFile from toil.common import Toil, ToilContextManagerException from toil.job import Job from toil.test import ToilTest, slow @slow class ToilContextManagerTest(ToilTest): def setUp(self): self.exportPath = getTempFile() def tearDown(self): os.remove(self.exportPath) def testContextManger(self): options = Job.Runner.getDefaultOptions(self._getTestJobStorePath()) options.logLevel = 'INFO' with Toil(options) as toil: toil.start(HelloWorld()) def testNoContextManger(self): options = Job.Runner.getDefaultOptions(self._getTestJobStorePath()) options.logLevel = 'INFO' toil = Toil(options) self.assertRaises(ToilContextManagerException, toil.start, HelloWorld()) def testExportAfterFailedExport(self): options = Job.Runner.getDefaultOptions(self._getTestJobStorePath()) try: with Toil(options) as toil: _ = toil.start(HelloWorld()) # oh no, an error! :( raise RuntimeError("we died after workflow completion but before our export finished") except RuntimeError: pass options.restart = True with Toil(options) as toil: fileID = toil.restart() print(fileID) # Hopefully the error didn't cause us to lose all our work! toil.exportFile(fileID, 'file://' + self.exportPath) with open(self.exportPath) as f: # The file should have all our content self.assertEqual(f.read(), "Hello, World!") class HelloWorld(Job): def __init__(self): Job.__init__(self, memory=100000, cores=2, disk='1M') def run(self, fileStore): fileID = self.addChildJobFn(childFn, cores=1, memory='1M', disk='1M').rv() return self.addFollowOn(FollowOn(fileID)).rv() def childFn(job): with job.fileStore.writeGlobalFileStream() as (fH, fileID): fH.write("Hello, World!".encode('utf-8')) return fileID class FollowOn(Job): def __init__(self, fileId): Job.__init__(self) self.fileId = fileId def run(self, fileStore): tempDir = fileStore.getLocalTempDir() tempFilePath = "/".join([tempDir, 'LocalCopy']) with fileStore.readGlobalFileStream(self.fileId) as globalFile: with open(tempFilePath, "wb") as localFile: localFile.write(globalFile.read()) return self.fileId toil-releases-3.24.0/src/toil/test/src/userDefinedJobArgTypeTest.py000066400000000000000000000057511362134276200252700ustar00rootroot00000000000000# Copyright (C) 2015-2016 Regents of the University of California # # 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. from __future__ import absolute_import from builtins import object import sys from toil import subprocess from toil.job import Job from toil.test import ToilTest, slow, travis_test class UserDefinedJobArgTypeTest(ToilTest): """ Test for issue #423 (Toil can't unpickle classes defined in user scripts) and variants thereof. https://github.com/BD2KGenomics/toil/issues/423 """ def setUp(self): super(UserDefinedJobArgTypeTest, self).setUp() options = Job.Runner.getDefaultOptions(self._getTestJobStorePath()) options.logLevel = "INFO" options.foo = Foo() self.options = options @travis_test def testJobFunction(self): """Test with first job being a function""" Job.Runner.startToil(Job.wrapJobFn(jobFunction, 0, Foo()), self.options) @slow def testJobClass(self): """Test with first job being an instance of a class""" Job.Runner.startToil(JobClass(0, Foo()), self.options) @travis_test def testJobFunctionFromMain(self): """Test with first job being a function defined in __main__""" self._testFromMain() @travis_test def testJobClassFromMain(self): """Test with first job being an instance of a class defined in __main__""" self._testFromMain() def _testFromMain(self): testMethodName = self.id().split('.')[-1] self.assertTrue(testMethodName.endswith('FromMain')) subprocess.check_call([sys.executable, '-m', self.__module__, testMethodName[:-8]]) class JobClass(Job): def __init__(self, level, foo): Job.__init__(self, memory=100000, cores=2, disk="300M") self.level = level self.foo = foo def run(self, fileStore): self.foo.assertIsCopy() if self.level < 2: self.addChildJobFn(jobFunction, self.level + 1, Foo(), cores=1, memory="1M", disk="300M") def jobFunction(job, level, foo): foo.assertIsCopy() if level < 2: job.addChild(JobClass(level + 1, Foo())) class Foo(object): def __init__(self): super(Foo, self).__init__() self.original_id = id(self) def assertIsCopy(self): assert self.original_id != id(self) def main(): testMethodName = sys.argv[1] test = UserDefinedJobArgTypeTest(testMethodName) test.setUpClass() test.debug() test.tearDownClass() toil-releases-3.24.0/src/toil/test/src/workerTest.py000066400000000000000000000104631362134276200224110ustar00rootroot00000000000000# Copyright (C) 2015-2018 Regents of the University of California # # 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. import pickle from toil.common import Config from toil.job import Job from toil.jobGraph import JobGraph from toil.jobStores.fileJobStore import FileJobStore from toil.test import ToilTest, travis_test from toil.worker import nextChainableJobGraph class WorkerTests(ToilTest): """Test miscellaneous units of the worker.""" def setUp(self): super(WorkerTests, self).setUp() path = self._getTestJobStorePath() self.jobStore = FileJobStore(path) self.config = Config() self.config.jobStore = 'file:%s' % path self.jobStore.initialize(self.config) self.jobGraphNumber = 0 @travis_test def testNextChainableJobGraph(self): """Make sure chainable/non-chainable jobs are identified correctly.""" def createJobGraph(memory, cores, disk, preemptable, checkpoint): """Create a fake-ish Job and JobGraph pair, and return the jobGraph.""" name = 'jobGraph%d' % self.jobGraphNumber self.jobGraphNumber += 1 job = Job() job.checkpoint = checkpoint # The job doesn't have a jobStoreID yet, so we can't tag the file with self.jobStore.writeFileStream() as (f, fileStoreID): pickle.dump(job, f, pickle.HIGHEST_PROTOCOL) command = '_toil %s fooCommand toil True' % fileStoreID jobGraph = JobGraph(command=command, memory=memory, cores=cores, disk=disk, unitName=name, jobName=name, preemptable=preemptable, jobStoreID=name, remainingRetryCount=1, predecessorNumber=1) return self.jobStore.create(jobGraph) # Identical non-checkpoint jobs should be chainable. jobGraph1 = createJobGraph(1, 2, 3, True, False) jobGraph2 = createJobGraph(1, 2, 3, True, False) jobGraph1.stack = [[jobGraph2]] self.assertEqual(jobGraph2, nextChainableJobGraph(jobGraph1, self.jobStore)) # Identical checkpoint jobs should not be chainable. jobGraph1 = createJobGraph(1, 2, 3, True, False) jobGraph2 = createJobGraph(1, 2, 3, True, True) jobGraph1.stack = [[jobGraph2]] self.assertEqual(None, nextChainableJobGraph(jobGraph1, self.jobStore)) # If there is no child we should get nothing to chain. jobGraph1 = createJobGraph(1, 2, 3, True, False) jobGraph1.stack = [] self.assertEqual(None, nextChainableJobGraph(jobGraph1, self.jobStore)) # If there are 2 or more children we should get nothing to chain. jobGraph1 = createJobGraph(1, 2, 3, True, False) jobGraph2 = createJobGraph(1, 2, 3, True, False) jobGraph3 = createJobGraph(1, 2, 3, True, False) jobGraph1.stack = [[jobGraph2, jobGraph3]] self.assertEqual(None, nextChainableJobGraph(jobGraph1, self.jobStore)) # If there is an increase in resource requirements we should get nothing to chain. reqs = {'memory': 1, 'cores': 2, 'disk': 3, 'preemptable': True, 'checkpoint': False} for increased_attribute in ('memory', 'cores', 'disk'): jobGraph1 = createJobGraph(**reqs) reqs[increased_attribute] += 1 jobGraph2 = createJobGraph(**reqs) jobGraph1.stack = [[jobGraph2]] self.assertEqual(None, nextChainableJobGraph(jobGraph1, self.jobStore)) # A change in preemptability from True to False should be disallowed. jobGraph1 = createJobGraph(1, 2, 3, True, False) jobGraph2 = createJobGraph(1, 2, 3, False, True) jobGraph1.stack = [[jobGraph2]] self.assertEqual(None, nextChainableJobGraph(jobGraph1, self.jobStore)) toil-releases-3.24.0/src/toil/test/utils/000077500000000000000000000000001362134276200202335ustar00rootroot00000000000000toil-releases-3.24.0/src/toil/test/utils/ABCWorkflowDebug/000077500000000000000000000000001362134276200233225ustar00rootroot00000000000000toil-releases-3.24.0/src/toil/test/utils/ABCWorkflowDebug/B_file.txt000066400000000000000000000000021362134276200252330ustar00rootroot00000000000000B toil-releases-3.24.0/src/toil/test/utils/ABCWorkflowDebug/debugWorkflow.py000066400000000000000000000154761362134276200265320ustar00rootroot00000000000000from toil.job import Job from toil.common import Toil from toil.version import python from toil import subprocess import os import logging logger = logging.getLogger(__name__) ''' This workflow's purpose is to create files and jobs for viewing using stats, status, and printDot() in toilDebugTest.py. It's intended for future use in a debugging tutorial containing a broken job. It is also a minor integration test. ''' def initialize_jobs(job): ''' Stub function used to start a toil workflow since toil workflows can only start with one job (but afterwards can run many in parallel). ''' job.fileStore.logToMaster('''initialize_jobs''') def writeA(job, mkFile): '''Runs a program, and writes a string 'A' into A.txt using mkFile.py.''' job.fileStore.logToMaster('''writeA''') # temp folder for the run tempDir = job.fileStore.getLocalTempDir() # import files try: mkFile_fs = job.fileStore.readGlobalFile(mkFile[0], userPath=os.path.join(tempDir, mkFile[1])) except: mkFile_fs = os.path.join(tempDir, mkFile[1]) # make a file (A.txt) and writes a string 'A' into it using 'mkFile.py' content = 'A' cmd = python + ' ' + mkFile_fs + ' ' + 'A.txt' + ' ' + content this_process = subprocess.Popen(cmd, shell=True, stdout=subprocess.PIPE) this_process.wait() # get the output file and return it as a tuple of location + name output_filename = 'A.txt' output_file = job.fileStore.writeGlobalFile(output_filename) A1 = (output_file, output_filename) rvDict = {"A1": A1} return rvDict def writeB(job, mkFile, B_file): ''' Runs a program, extracts a string 'B' from an existing file, B_file.txt, and writes it into B.txt using mkFile.py. ''' job.fileStore.logToMaster('''writeB''') # temp folder for the run tempDir = job.fileStore.getLocalTempDir() # import files try: mkFile_fs = job.fileStore.readGlobalFile(mkFile[0], userPath=os.path.join(tempDir, mkFile[1])) except: mkFile_fs = os.path.join(tempDir, mkFile[1]) try: B_file_fs = job.fileStore.readGlobalFile(B_file[0], userPath=os.path.join(tempDir, B_file[1])) except: B_file_fs = os.path.join(tempDir, B_file[1]) # make a file (B.txt) and write the contents of 'B_file.txt' into it using 'mkFile.py' with open(B_file_fs, "r") as f: file_contents = '' for line in f: file_contents = file_contents + line cmd = python + ' ' + mkFile_fs + ' ' + 'B.txt' + ' ' + file_contents this_process = subprocess.Popen(cmd, shell=True, stdout=subprocess.PIPE) this_process.wait() # get the output file and return it as a tuple of location + name output_filename = 'B.txt' output_file = job.fileStore.writeGlobalFile(output_filename) B1 = (output_file, output_filename) rvDict = {"B1": B1} return rvDict def writeC(job): '''Creates/writes a file, C.txt, containing the string 'C'.''' job.fileStore.logToMaster('''writeC''') # temp folder for the run tempDir = job.fileStore.getLocalTempDir() # get the output file and return it as a tuple of location + name output_filename = os.path.join(tempDir, 'C.txt') with open(output_filename, 'w') as f: f.write('C') output_file = job.fileStore.writeGlobalFile(output_filename) C1 = (output_file, output_filename) rvDict = {"C1": C1} return rvDict def writeABC(job, A_dict, B_dict, C_dict, filepath): '''Takes 3 files (specified as dictionaries) and writes their contents to ABC.txt.''' job.fileStore.logToMaster('''writeABC''') # temp folder for the run tempDir = job.fileStore.getLocalTempDir() # import files try: A_fs = job.fileStore.readGlobalFile(A_dict['A1'][0], userPath=os.path.join(tempDir, A_dict['A1'][1])) except: A_fs = os.path.join(tempDir, A_dict['A1'][1]) try: B_fs = job.fileStore.readGlobalFile(B_dict['B1'][0], userPath=os.path.join(tempDir, B_dict['B1'][1])) except: B_fs = os.path.join(tempDir, B_dict['B1'][1]) try: C_fs = job.fileStore.readGlobalFile(C_dict['C1'][0], userPath=os.path.join(tempDir, C_dict['C1'][1])) except: C_fs = os.path.join(tempDir, C_dict['C1'][1]) file_contents = '' with open(A_fs, "r") as f: for line in f: file_contents = file_contents + line with open(B_fs, "r") as f: for line in f: file_contents = file_contents + line with open(C_fs, "r") as f: for line in f: file_contents = file_contents + line with open(os.path.join(tempDir, 'ABC.txt'), 'w') as f: f.write(file_contents) # get the output file and return it as a tuple of location + name output_filename = os.path.join(tempDir, 'ABC.txt') output_file = job.fileStore.writeGlobalFile(output_filename) job.fileStore.exportFile(output_file, "file://" + filepath) def finalize_jobs(job, num): '''Does nothing but should be recorded in stats, status, and printDot().''' job.fileStore.logToMaster('''finalize_jobs''') def broken_job(job, num): '''A job that will always fail. To be used for a tutorial.''' job.fileStore.logToMaster('''broken_job''') file = toil.importFile(None) if __name__=="__main__": options = Job.Runner.getDefaultOptions("./toilWorkflowRun") # options.clean = "always" options.stats = True options.logLevel = "INFO" with Toil(options) as toil: B_file0 = toil.importFile("file://" + os.path.abspath("src/toil/test/utils/ABCWorkflowDebug/B_file.txt")) B_file0_preserveThisFilename = "B_file.txt" B_file = (B_file0, B_file0_preserveThisFilename) file_maker0 = toil.importFile("file://" + os.path.abspath("src/toil/test/utils/ABCWorkflowDebug/mkFile.py")) file_maker0_preserveThisFilename = "mkFile.py" file_maker = (file_maker0, file_maker0_preserveThisFilename) filepath = os.path.abspath("src/toil/test/utils/ABCWorkflowDebug/ABC.txt") job0 = Job.wrapJobFn(initialize_jobs) job1 = Job.wrapJobFn(writeA, file_maker) job2 = Job.wrapJobFn(writeB, file_maker, B_file) job3 = Job.wrapJobFn(writeC) job4 = Job.wrapJobFn(writeABC, job1.rv(), job2.rv(), job3.rv(), filepath) job5 = Job.wrapJobFn(finalize_jobs, 1) job6 = Job.wrapJobFn(finalize_jobs, 2) job7 = Job.wrapJobFn(finalize_jobs, 3) job8 = Job.wrapJobFn(finalize_jobs, 4) # write files 'A.txt', 'B.txt', and 'C.txt' job0.addChild(job1) job1.addChild(job2) job2.addChild(job3) # finally use 'A.txt', 'B.txt', and 'C.txt' to write ABC.txt job0.addFollowOn(job4) # these jobs do nothing, but should display in status job4.addChild(job5) job4.addChild(job6) job4.addChild(job7) job4.addChild(job8) toil.start(job0) toil-releases-3.24.0/src/toil/test/utils/ABCWorkflowDebug/mkFile.py000066400000000000000000000006611362134276200251060ustar00rootroot00000000000000import argparse def main(): parser = argparse.ArgumentParser(description='Creates a file and writes into it.') parser.add_argument('file_name', help='File name to be written to.') parser.add_argument('contents', help='A string to be written into the file.') args, unknown_args = parser.parse_known_args() with open(args.file_name, "w") as f: f.write(args.contents) if __name__=="__main__": main() toil-releases-3.24.0/src/toil/test/utils/ABCWorkflowDebug/sleep.cwl000066400000000000000000000002671362134276200251460ustar00rootroot00000000000000cwlVersion: v1.0 class: CommandLineTool baseCommand: sleep stdout: output.txt inputs: message: type: int inputBinding: position: 1 outputs: output: type: stdout toil-releases-3.24.0/src/toil/test/utils/ABCWorkflowDebug/sleep.yaml000066400000000000000000000000151362134276200253120ustar00rootroot00000000000000message: 100 toil-releases-3.24.0/src/toil/test/utils/__init__.py000066400000000000000000000012131362134276200223410ustar00rootroot00000000000000# Copyright (C) 2015-2016 Regents of the University of California # # 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. from __future__ import absolute_import toil-releases-3.24.0/src/toil/test/utils/toilDebugTest.py000066400000000000000000000104701362134276200233650ustar00rootroot00000000000000# Copyright (C) 2018 Regents of the University of California # # 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. from __future__ import absolute_import import unittest import os import shutil import logging from toil import subprocess from toil.test import ToilTest, slow, travis_test from toil.utils.toilDebugFile import recursiveGlob logger = logging.getLogger(__name__) class ToilDebugFileTest(ToilTest): """A set of test cases for toilwdl.py""" def setUp(self): """Initial set up of variables for the test.""" subprocess.check_call(['python', os.path.abspath('src/toil/test/utils/ABCWorkflowDebug/debugWorkflow.py')]) self.jobStoreDir = os.path.abspath('toilWorkflowRun') self.tempDir = self._createTempDir(purpose='tempDir') def tearDown(self): """Default tearDown for unittest.""" shutil.rmtree(self.jobStoreDir) ABC = os.path.abspath('src/toil/test/utils/ABCWorkflowDebug/ABC.txt') if os.path.exists(ABC): os.remove(ABC) unittest.TestCase.tearDown(self) @slow def testJobStoreContents(self): """Test toilDebugFile.printContentsOfJobStore(). Runs a workflow that imports 'B.txt' and 'mkFile.py' into the jobStore. 'A.txt', 'C.txt', 'ABC.txt' are then created. This checks to make sure these contents are found in the jobStore and printed.""" contents = ['A.txt', 'B.txt', 'C.txt', 'ABC.txt', 'mkFile.py'] subprocess.check_call(['python', os.path.abspath('src/toil/utils/toilDebugFile.py'), self.jobStoreDir, '--listFilesInJobStore=True']) jobstoreFileContents = os.path.abspath('jobstore_files.txt') files = [] match = 0 with open(jobstoreFileContents, 'r') as f: for line in f: files.append(line.strip()) for xfile in files: for expected_file in contents: if xfile.endswith(expected_file): match = match + 1 logger.debug(files) logger.debug(contents) logger.debug(match) # C.txt will match twice (once with 'C.txt', and once with 'ABC.txt') assert match == 6 os.remove(jobstoreFileContents) # expected run time = 4s @travis_test def testFetchJobStoreFiles(self): """Test toilDebugFile.fetchJobStoreFiles() without using symlinks.""" self.fetchFiles(symLink=False) # expected run time = 4s @travis_test def testFetchJobStoreFilesWSymlinks(self): """Test toilDebugFile.fetchJobStoreFiles() using symlinks.""" self.fetchFiles(symLink=True) def fetchFiles(self, symLink): """ Fn for testFetchJobStoreFiles() and testFetchJobStoreFilesWSymlinks(). Runs a workflow that imports 'B.txt' and 'mkFile.py' into the jobStore. 'A.txt', 'C.txt', 'ABC.txt' are then created. This test then attempts to get a list of these files and copy them over into ./src from the jobStore, confirm that they are present, and then delete them. """ contents = ['A.txt', 'B.txt', 'C.txt', 'ABC.txt', 'mkFile.py'] outputDir = os.path.abspath('src') cmd = ['python', os.path.abspath('src/toil/utils/toilDebugFile.py'), self.jobStoreDir, '--fetch', '*A.txt', '*B.txt', '*C.txt', '*ABC.txt', '*mkFile.py', '--localFilePath=' + os.path.abspath('src'), '--useSymlinks=' + str(symLink)] subprocess.check_call(cmd) for xfile in contents: matchingFilesFound = recursiveGlob(outputDir, '*' + xfile) self.assertGreaterEqual(len(matchingFilesFound), 1) for fileFound in matchingFilesFound: assert fileFound.endswith(xfile) and os.path.exists(fileFound) if fileFound.endswith('-' + xfile): os.remove(fileFound) toil-releases-3.24.0/src/toil/test/utils/utilsTest.py000066400000000000000000000377171362134276200226240ustar00rootroot00000000000000# Copyright (C) 2015-2018 Regents of the University of California # # 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. from __future__ import absolute_import from builtins import str import os import sys import uuid import shutil import tempfile import pytest import logging pkg_root = os.path.abspath(os.path.join(os.path.dirname(__file__), '..')) # noqa sys.path.insert(0, pkg_root) # noqa import time import psutil import toil import toil.test.sort.sort from toil import subprocess from toil import resolveEntryPoint from toil.job import Job from toil.utils.toilStatus import ToilStatus from toil.lib.bioio import getTempFile, system from toil.test import ToilTest, needs_aws_ec2, needs_rsync3, integrative, slow, needs_cwl, needs_docker, travis_test from toil.test.sort.sortTest import makeFileToSort from toil.utils.toilStats import getStats, processData from toil.common import Toil, Config from toil.provisioners import clusterFactory from toil.version import python logger = logging.getLogger(__name__) class UtilsTest(ToilTest): """ Tests the utilities that toil ships with, e.g. stats and status, in conjunction with restart functionality. """ def setUp(self): super(UtilsTest, self).setUp() self.tempDir = self._createTempDir() self.tempFile = getTempFile(rootDir=self.tempDir) self.outputFile = 'someSortedStuff.txt' self.toilDir = os.path.join(self.tempDir, "jobstore") self.assertFalse(os.path.exists(self.toilDir)) self.lines = 1000 self.lineLen = 10 self.N = 1000 makeFileToSort(self.tempFile, self.lines, self.lineLen) # First make our own sorted version with open(self.tempFile, 'r') as fileHandle: self.correctSort = fileHandle.readlines() self.correctSort.sort() self.sort_workflow_cmd = [python, '-m', 'toil.test.sort.sort', 'file:' + self.toilDir, '--clean=never', '--numLines=1', '--lineLength=1'] def tearDown(self): if os.path.exists(self.tempDir): shutil.rmtree(self.tempDir) if os.path.exists(self.toilDir): shutil.rmtree(self.toilDir) for f in ['fileToSort.txt', 'sortedFile.txt', 'output.txt']: if os.path.exists(f): os.remove(f) ToilTest.tearDown(self) @property def toilMain(self): return resolveEntryPoint('toil') @property def cleanCommand(self): return [self.toilMain, 'clean', self.toilDir] @property def statsCommand(self): return [self.toilMain, 'stats', self.toilDir, '--pretty'] def statusCommand(self, failIfNotComplete=False): commandTokens = [self.toilMain, 'status', self.toilDir] if failIfNotComplete: commandTokens.append('--failIfNotComplete') return commandTokens @needs_rsync3 @pytest.mark.timeout(1200) @needs_aws_ec2 @integrative @slow def testAWSProvisionerUtils(self): """ Runs a number of the cluster utilities in sequence. Launches a cluster with custom tags. Verifies the tags exist. ssh's into the cluster. Does some weird string comparisons. Makes certain that TOIL_WORKDIR is set as expected in the ssh'ed cluster. Rsyncs a file and verifies it exists on the leader. Destroys the cluster. :return: """ # TODO: Run these for the other clouds. clusterName = 'cluster-utils-test' + str(uuid.uuid4()) keyName = os.getenv('TOIL_AWS_KEYNAME') try: from toil.provisioners.aws.awsProvisioner import AWSProvisioner # launch master with an assortment of custom tags system([self.toilMain, 'launch-cluster', '-t', 'key1=value1', '-t', 'key2=value2', '--tag', 'key3=value3', '--leaderNodeType=m3.medium', '--keyPairName=' + keyName, clusterName, '--provisioner=aws', '--zone=us-west-2a', '--logLevel=DEBUG']) cluster = clusterFactory(provisioner='aws', clusterName=clusterName) leader = cluster.getLeader() # check that the leader carries the appropriate tags tags = {'key1': 'value1', 'key2': 'value2', 'key3': 'value3', 'Name': clusterName, 'Owner': keyName} for key in tags: self.assertEqual(tags[key], leader.tags.get(key)) # Test strict host key checking # Doesn't work when run locally. if keyName == 'jenkins@jenkins-master': try: leader.sshAppliance(strict=True) except RuntimeError: pass else: self.fail("Host key verification passed where it should have failed") # Add the host key to known_hosts so that the rest of the tests can # pass without choking on the verification prompt. leader.sshAppliance('bash', strict=True, sshOptions=['-oStrictHostKeyChecking=no']) system([self.toilMain, 'ssh-cluster', '--provisioner=aws', clusterName]) testStrings = ["'foo'", '"foo"', ' foo', '$PATH', '"', "'", '\\', '| cat', '&& cat', '; cat'] for test in testStrings: logger.debug('Testing SSH with special string: %s', test) compareTo = "import sys; assert sys.argv[1]==%r" % test leader.sshAppliance(python, '-', test, input=compareTo) try: leader.sshAppliance('nonsenseShouldFail') except RuntimeError: pass else: self.fail('The remote command failed silently where it should have raised an error') leader.sshAppliance(python, '-c', "import os; assert os.environ['TOIL_WORKDIR']=='/var/lib/toil'") # `toil rsync-cluster` # Testing special characters - string.punctuation fname = '!"#$%&\'()*+,-.;<=>:\ ?@[\\\\]^_`{|}~' testData = os.urandom(3 * (10**6)) with tempfile.NamedTemporaryFile(suffix=fname) as tmpFile: relpath = os.path.basename(tmpFile.name) tmpFile.write(testData) tmpFile.flush() # Upload file to leader leader.coreRsync(args=[tmpFile.name, ":"]) # Ensure file exists leader.sshAppliance("test", "-e", relpath) tmpDir = tempfile.mkdtemp() # Download the file again and make sure it's the same file # `--protect-args` needed because remote bash chokes on special characters leader.coreRsync(args=["--protect-args", ":" + relpath, tmpDir]) with open(os.path.join(tmpDir, relpath), "r") as f: self.assertEqual(f.read(), testData, "Downloaded file does not match original file") finally: system([self.toilMain, 'destroy-cluster', '--provisioner=aws', clusterName]) try: shutil.rmtree(tmpDir) except NameError: pass @slow def testUtilsSort(self): """ Tests the status and stats commands of the toil command line utility using the sort example with the --restart flag. """ # Get the sort command to run toilCommand = [sys.executable, '-m', toil.test.sort.sort.__name__, self.toilDir, '--logLevel=DEBUG', '--fileToSort', self.tempFile, '--outputFile', self.outputFile, '--N', str(self.N), '--stats', '--retryCount=2', '--badWorker=0.5', '--badWorkerFailInterval=0.05'] # Try restarting it to check that a JobStoreException is thrown self.assertRaises(subprocess.CalledProcessError, system, toilCommand + ['--restart']) # Check that trying to run it in restart mode does not create the jobStore self.assertFalse(os.path.exists(self.toilDir)) # Status command # Run the script for the first time try: system(toilCommand) finished = True except subprocess.CalledProcessError: # This happens when the script fails due to having unfinished jobs system(self.statusCommand()) self.assertRaises(subprocess.CalledProcessError, system, self.statusCommand(failIfNotComplete=True)) finished = False self.assertTrue(os.path.exists(self.toilDir)) # Try running it without restart and check an exception is thrown self.assertRaises(subprocess.CalledProcessError, system, toilCommand) # Now restart it until done totalTrys = 1 while not finished: try: system(toilCommand + ['--restart']) finished = True except subprocess.CalledProcessError: # This happens when the script fails due to having unfinished jobs system(self.statusCommand()) self.assertRaises(subprocess.CalledProcessError, system, self.statusCommand(failIfNotComplete=True)) if totalTrys > 16: self.fail() # Exceeded a reasonable number of restarts totalTrys += 1 # Check the toil status command does not issue an exception system(self.statusCommand()) # Check we can run 'toil stats' system(self.statsCommand) # Check the file is properly sorted with open(self.outputFile, 'r') as fileHandle: l2 = fileHandle.readlines() self.assertEqual(self.correctSort, l2) # Delete output file before next step os.remove(self.outputFile) # Check we can run 'toil clean' system(self.cleanCommand) @slow def testUtilsStatsSort(self): """ Tests the stats commands on a complete run of the stats test. """ # Get the sort command to run toilCommand = [sys.executable, '-m', toil.test.sort.sort.__name__, self.toilDir, '--logLevel=DEBUG', '--fileToSort', self.tempFile, '--outputFile', self.outputFile, '--N', str(self.N), '--stats', '--retryCount=99', '--badWorker=0.5', '--badWorkerFailInterval=0.01'] # Run the script for the first time system(toilCommand) self.assertTrue(os.path.exists(self.toilDir)) # Check we can run 'toil stats' system(self.statsCommand) # Check the file is properly sorted with open(self.outputFile, 'r') as fileHandle: l2 = fileHandle.readlines() self.assertEqual(self.correctSort, l2) # Delete output file os.remove(self.outputFile) @travis_test def testUnicodeSupport(self): options = Job.Runner.getDefaultOptions(self._getTestJobStorePath()) options.clean = 'always' options.logLevel = 'debug' Job.Runner.startToil(Job.wrapFn(printUnicodeCharacter), options) @slow def testMultipleJobsPerWorkerStats(self): """ Tests case where multiple jobs are run on 1 worker to ensure that all jobs report back their data """ options = Job.Runner.getDefaultOptions(self._getTestJobStorePath()) options.clean = 'never' options.stats = True Job.Runner.startToil(RunTwoJobsPerWorker(), options) config = Config() config.setOptions(options) jobStore = Toil.resumeJobStore(config.jobStore) stats = getStats(jobStore) collatedStats = processData(jobStore.config, stats) self.assertTrue(len(collatedStats.job_types) == 2, "Some jobs are not represented in the stats.") def check_status(self, status, status_fn, seconds=10): i = 0.0 while status_fn(self.toilDir) != status: time.sleep(0.5) i += 0.5 if i > seconds: s = status_fn(self.toilDir) self.assertEqual(s, status, 'Status took longer than 10 seconds to fetch: %s' % s) @travis_test def testGetPIDStatus(self): """Test that ToilStatus.getPIDStatus() behaves as expected.""" wf = subprocess.Popen(self.sort_workflow_cmd) self.check_status('RUNNING', status_fn=ToilStatus.getPIDStatus) wf.wait() self.check_status('COMPLETED', status_fn=ToilStatus.getPIDStatus) # TODO: we need to reach into the FileJobStore's files and # delete this shared file. We assume we know its internal layout. os.remove(os.path.join(self.toilDir, 'files/shared/pid.log')) self.check_status('QUEUED', status_fn=ToilStatus.getPIDStatus) @travis_test def testGetStatusFailedToilWF(self): """ Test that ToilStatus.getStatus() behaves as expected with a failing Toil workflow. While this workflow could be called by importing and evoking its main function, doing so would remove the opportunity to test the 'RUNNING' functionality of getStatus(). """ # --badWorker is set to force failure. wf = subprocess.Popen(self.sort_workflow_cmd + ['--badWorker=1']) self.check_status('RUNNING', status_fn=ToilStatus.getStatus) wf.wait() self.check_status('ERROR', status_fn=ToilStatus.getStatus) @needs_cwl @needs_docker def testGetStatusFailedCWLWF(self): """Test that ToilStatus.getStatus() behaves as expected with a failing CWL workflow.""" # --badWorker is set to force failure. cmd = ['toil-cwl-runner', '--jobStore', self.toilDir, '--clean=never', '--badWorker=1', 'src/toil/test/cwl/sorttool.cwl', '--reverse', '--input', 'src/toil/test/cwl/whale.txt'] wf = subprocess.Popen(cmd) self.check_status('RUNNING', status_fn=ToilStatus.getStatus) wf.wait() self.check_status('ERROR', status_fn=ToilStatus.getStatus) @needs_cwl @needs_docker def testGetStatusSuccessfulCWLWF(self): """Test that ToilStatus.getStatus() behaves as expected with a successful CWL workflow.""" cmd = ['toil-cwl-runner', '--jobStore', self.toilDir, '--clean=never', 'src/toil/test/cwl/sorttool.cwl', '--reverse', '--input', 'src/toil/test/cwl/whale.txt'] wf = subprocess.Popen(cmd) self.check_status('RUNNING', status_fn=ToilStatus.getStatus) wf.wait() self.check_status('COMPLETED', status_fn=ToilStatus.getStatus) def printUnicodeCharacter(): # We want to get a unicode character to stdout but we can't print it directly because of # Python encoding issues. To work around this we print in a separate Python process. See # http://stackoverflow.com/questions/492483/setting-the-correct-encoding-when-piping-stdout-in-python subprocess.check_call([sys.executable, '-c', "print('\\xc3\\xbc')"]) class RunTwoJobsPerWorker(Job): """ Runs child job with same resources as self in an attempt to chain the jobs on the same worker """ def __init__(self): Job.__init__(self) def run(self, fileStore): self.addChildFn(printUnicodeCharacter) toil-releases-3.24.0/src/toil/test/wdl/000077500000000000000000000000001362134276200176615ustar00rootroot00000000000000toil-releases-3.24.0/src/toil/test/wdl/__init__.py000066400000000000000000000000001362134276200217600ustar00rootroot00000000000000toil-releases-3.24.0/src/toil/test/wdl/conftest.py000066400000000000000000000014201362134276200220550ustar00rootroot00000000000000# Copyright (C) 2017 Regents of the University of California # # 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. # https://pytest.org/latest/example/pythoncollection.html collect_ignore = [] try: import toil.wdl.wdl_parser except ImportError: collect_ignore.append("toilwdl.py") toil-releases-3.24.0/src/toil/test/wdl/md5sum/000077500000000000000000000000001362134276200210735ustar00rootroot00000000000000toil-releases-3.24.0/src/toil/test/wdl/md5sum/md5sum.input000066400000000000000000000001031362134276200233600ustar00rootroot00000000000000this is the test file that will be used when calculating an md5sum toil-releases-3.24.0/src/toil/test/wdl/md5sum/md5sum.json000066400000000000000000000001001362134276200231670ustar00rootroot00000000000000{"ga4ghMd5.inputFile": "src/toil/test/wdl/md5sum/md5sum.input"} toil-releases-3.24.0/src/toil/test/wdl/md5sum/md5sum.wdl000066400000000000000000000005251362134276200230170ustar00rootroot00000000000000task md5 { File inputFile command { /bin/my_md5sum ${inputFile} } output { File value = "md5sum.txt" } runtime { docker: "quay.io/briandoconnor/dockstore-tool-md5sum:1.0.4" cpu: 1 memory: "512 MB" disks: "local-disk 10 HDD" } } workflow ga4ghMd5 { File inputFile call md5 { input: inputFile=inputFile } } toil-releases-3.24.0/src/toil/test/wdl/test.csv000066400000000000000000000000221362134276200213470ustar00rootroot000000000000001,2,3 4,5,6 7,8,9 toil-releases-3.24.0/src/toil/test/wdl/test.tsv000066400000000000000000000000221362134276200213700ustar00rootroot000000000000001 2 3 4 5 6 7 8 9 toil-releases-3.24.0/src/toil/test/wdl/testfiles/000077500000000000000000000000001362134276200216635ustar00rootroot00000000000000toil-releases-3.24.0/src/toil/test/wdl/testfiles/vocab.json000066400000000000000000000000031362134276200236410ustar00rootroot00000000000000{} toil-releases-3.24.0/src/toil/test/wdl/testfiles/vocab.wdl000066400000000000000000000037131362134276200234710ustar00rootroot00000000000000workflow vocabulary { ##################################################################### # $primitive_type = ('Boolean' | 'Int' | 'Float' | 'File' | 'String') Boolean bool1 Int int1 Float float1 File file1 String string1 Boolean bool2 = true Int int2 = 1 Float float2 = 1.1 File file2 = 'src/toil/test/wdl/test.tsv' String string2 = 'x' Boolean bool3 = true Int int3 = 1 Float float3 = 1.1 File file3 = 'src/toil/test/wdl/test.csv' String string3 = 'x' ##################################################################### # $array_type = 'Array' '[' ($primitive_type | $object_type | $array_type) ']' Array[Boolean] arraybool1 Array[Int] arrayint1 Array[Float] arrayfloat1 Array[File] arrayfile1 Array[String] arraystring1 Array[Array[Boolean]] arrayarraybool1 Array[Array[Int]] arrayarrayint1 Array[Array[Float]] arrayarrayfloat1 Array[Array[File]] arrayarrayfile1 Array[Array[String]] arrayarraystring1 ##################################################################### # $type_postfix_quantifier = '?' | '+' String joinedstring = string2 + string3 + "x" Int joinedint = int2 + int3 + 1 Float joinedfloat = float2 + float3 + 1.1 Boolean? boolo1 Int? into1 Float? floato1 File? fileo1 String? stringo1 Boolean? boolo2 = true Int? into2 = 1 Float? floato2 = 1.1 File? fileo2 = 'src/toil/test/wdl/test.csv' String? stringo2 = 'x' ##################################################################### # $object_type = 'Object' # $map_type = 'Map' '[' $primitive_type ',' ($primitive_type | $array_type | $map_type | $object_type) ']' # currently unsupported ##################################################################### # demonstrate function usage Int additional_disk = select_first([into1, 20]) Int num_of_bqsr_scatters = length([1,1,1,1]) Int bqsr_divisor = if int3 > 1 then additional_disk else 1 Float disk_size = (floato2 / bqsr_divisor) + additional_disk } toil-releases-3.24.0/src/toil/test/wdl/toilwdlTest.py000066400000000000000000000604441362134276200225610ustar00rootroot00000000000000from __future__ import absolute_import from six import iteritems import unittest import os from toil import subprocess from toil.version import exactPython import toil.wdl.wdl_parser as wdl_parser from toil.wdl.wdl_analysis import AnalyzeWDL from toil.wdl.wdl_synthesis import SynthesizeWDL from toil.wdl.wdl_functions import generate_docker_bashscript_file from toil.wdl.wdl_functions import select_first from toil.wdl.wdl_functions import sub from toil.wdl.wdl_functions import size from toil.wdl.wdl_functions import glob from toil.wdl.wdl_functions import process_and_read_file from toil.wdl.wdl_functions import process_infile from toil.wdl.wdl_functions import process_outfile from toil.wdl.wdl_functions import abspath_file from toil.wdl.wdl_functions import combine_dicts from toil.wdl.wdl_functions import parse_memory from toil.wdl.wdl_functions import parse_cores from toil.wdl.wdl_functions import parse_disk from toil.wdl.wdl_functions import read_string from toil.wdl.wdl_functions import read_int from toil.wdl.wdl_functions import read_float from toil.wdl.wdl_functions import defined from toil.wdl.wdl_functions import read_tsv from toil.wdl.wdl_functions import read_csv from toil.wdl.wdl_functions import basename from toil.test import ToilTest, slow, needs_docker from toil import urlretrieve import zipfile import shutil import uuid class ToilWdlIntegrationTest(ToilTest): """A set of test cases for toilwdl.py""" def setUp(self): """Runs anew before each test to create farm fresh temp dirs.""" self.output_dir = os.path.join('/tmp/', 'toil-wdl-test-' + str(uuid.uuid4())) os.makedirs(self.output_dir) @classmethod def setUpClass(cls): """Runs once for all tests.""" cls.program = os.path.abspath("src/toil/wdl/toilwdl.py") cls.test_directory = os.path.abspath("src/toil/test/wdl/") cls.encode_data = os.path.join(cls.test_directory, "ENCODE_data.zip") cls.encode_data_dir = os.path.join(cls.test_directory, "ENCODE_data") cls.wdl_data = os.path.join(cls.test_directory, "wdl_templates.zip") cls.wdl_data_dir = os.path.join(cls.test_directory, "wdl_templates") cls.gatk_data = os.path.join(cls.test_directory, "GATK_data.zip") cls.gatk_data_dir = os.path.join(cls.test_directory, "GATK_data") # GATK tests will not run on jenkins b/c GATK.jar needs Java 7 # and jenkins only has Java 6 (12-16-2017). # Set this to true to run the GATK integration tests locally. cls.manual_integration_tests = False # Delete the test datasets after running the tests. # Jenkins requires this to not error on "untracked files". # Set to true if running tests locally and you don't want to # redownload the data each time you run the test. cls.jenkins = True cls.fetch_and_unzip_from_s3(filename='ENCODE_data.zip', data=cls.encode_data, data_dir=cls.encode_data_dir) cls.fetch_and_unzip_from_s3(filename='wdl_templates.zip', data=cls.wdl_data, data_dir=cls.wdl_data_dir) # these tests require Java 7 (GATK.jar); jenkins has Java 6 and so must # be run manually as integration tests (12.16.2017) if cls.manual_integration_tests: cls.fetch_and_unzip_from_s3(filename='GATK_data.zip', data=cls.gatk_data, data_dir=cls.gatk_data_dir) def tearDown(self): """Clean up outputs.""" remove_outputs(self.output_dir) jobstores = ['./toilWorkflowRun', '/mnt/ephemeral/workspace/toil-pull-requests/toilWorkflowRun'] for jobstore in jobstores: if os.path.exists(jobstore): shutil.rmtree(jobstore) unittest.TestCase.tearDown(self) @classmethod def tearDownClass(cls): """Clean up (shared) inputs.""" if cls.jenkins: if os.path.exists(cls.gatk_data): os.remove(cls.gatk_data) if os.path.exists(cls.gatk_data_dir): shutil.rmtree(cls.gatk_data_dir) if os.path.exists(cls.wdl_data): os.remove(cls.wdl_data) if os.path.exists(cls.wdl_data_dir): shutil.rmtree(cls.wdl_data_dir) if os.path.exists(cls.encode_data): os.remove(cls.encode_data) if os.path.exists(cls.encode_data_dir): shutil.rmtree(cls.encode_data_dir) @needs_docker def testMD5sum(self): '''Test if toilwdl produces the same outputs as known good outputs for WDL's GATK tutorial #1.''' wdl = os.path.abspath('src/toil/test/wdl/md5sum/md5sum.wdl') inputfile = os.path.abspath('src/toil/test/wdl/md5sum/md5sum.input') json = os.path.abspath('src/toil/test/wdl/md5sum/md5sum.json') subprocess.check_call([exactPython, self.program, wdl, json, '-o', self.output_dir]) md5sum_output = os.path.join(self.output_dir, 'md5sum.txt') assert os.path.exists(md5sum_output) os.unlink(md5sum_output) # estimated run time <1 sec def testFn_SelectFirst(self): """Test the wdl built-in functional equivalent of 'select_first()', which returns the first value in a list that is not None.""" assert select_first(['somestring', 'anotherstring', None, '', 1]) == 'somestring' assert select_first([None, '', 1, 'somestring']) == 1 assert select_first([2, 1, '', 'somestring', None, '']) == 2 assert select_first(['', 2, 1, 'somestring', None, '']) == 2 # estimated run time <1 sec def testFn_Size(self): """Test the wdl built-in functional equivalent of 'size()', which returns a file's size based on the path.""" from toil.job import Job from toil.common import Toil options = Job.Runner.getDefaultOptions('./toilWorkflowRun') options.clean = 'always' with Toil(options) as toil: small = process_infile(os.path.abspath('src/toil/test/wdl/testfiles/vocab.wdl'), toil) small_file = size(small) large = process_infile(self.encode_data, toil) larger_file = size(large) larger_file_in_mb = size(large, 'mb') assert small_file >= 1800, small_file assert larger_file >= 70000000, larger_file assert larger_file_in_mb >= 70, larger_file_in_mb # estimated run time <1 sec def testFn_Basename(self): assert basename('/home/quokka/git/delete/toil/src/toil/wdl/toilwdl.py', '.py') == 'toilwdl' assert basename('/home/quokka/git/delete/toil/src/toil/wdl/toilwdl.py') == 'toilwdl.py' assert basename('toilwdl.py', '.py') == 'toilwdl' assert basename('toilwdl.py') == 'toilwdl.py' # estimated run time <1 sec def testFn_Glob(self): """Test the wdl built-in functional equivalent of 'glob()', which finds all files with a pattern in a directory.""" vocab_location = glob('vocab.wdl', os.path.abspath('src/toil')) assert vocab_location == [os.path.abspath('src/toil/test/wdl/testfiles/vocab.wdl')], str(vocab_location) wdl_locations = glob('wdl_*.py', os.path.abspath('src/toil')) wdl_that_should_exist = [os.path.abspath('src/toil/wdl/wdl_analysis.py'), os.path.abspath('src/toil/wdl/wdl_synthesis.py'), os.path.abspath('src/toil/wdl/wdl_functions.py'), os.path.abspath('src/toil/wdl/wdl_parser.py')] # make sure the files match the expected files for location in wdl_that_should_exist: assert location in wdl_locations, '{} not in {}!'.format(str(location), str(wdl_locations)) # make sure the same number of files were found as expected assert len(wdl_that_should_exist) == len(wdl_locations), '{} != {}'.format(str(len(wdl_locations)), str(len(wdl_that_should_exist))) # estimated run time <1 sec def testFn_ParseMemory(self): """Test the wdl built-in functional equivalent of 'parse_memory()', which parses a specified memory input to an int output. The input can be a string or an int or a float and may include units such as 'Gb' or 'mib' as a separate argument.""" assert parse_memory(2147483648) == 2147483648, str(parse_memory(2147483648)) assert parse_memory('2147483648') == 2147483648, str(parse_memory(2147483648)) assert parse_memory('2GB') == 2000000000, str(parse_memory('2GB')) assert parse_memory('2GiB') == 2147483648, str(parse_memory('2GiB')) assert parse_memory('1 GB') == 1000000000, str(parse_memory('1 GB')) assert parse_memory('1 GiB') == 1073741824, str(parse_memory('1 GiB')) # estimated run time <1 sec def testFn_ParseCores(self): """Test the wdl built-in functional equivalent of 'parse_cores()', which parses a specified disk input to an int output. The input can be a string or an int.""" assert parse_cores(1) == 1 assert parse_cores('1') == 1 # estimated run time <1 sec def testFn_ParseDisk(self): """Test the wdl built-in functional equivalent of 'parse_disk()', which parses a specified disk input to an int output. The input can be a string or an int or a float and may include units such as 'Gb' or 'mib' as a separate argument. The minimum returned value is 2147483648 bytes.""" # check minimum returned value assert parse_disk('1') == 2147483648, str(parse_disk('1')) assert parse_disk(1) == 2147483648, str(parse_disk(1)) assert parse_disk(2200000001) == 2200000001, str(parse_disk(2200000001)) assert parse_disk('2200000001') == 2200000001, str(parse_disk('2200000001')) assert parse_disk('/mnt/my_mnt 3 SSD, /mnt/my_mnt2 500 HDD') == 503000000000, str(parse_disk('/mnt/my_mnt 3 SSD, /mnt/my_mnt2 500 HDD')) assert parse_disk('local-disk 10 SSD') == 10000000000, str(parse_disk('local-disk 10 SSD')) assert parse_disk('/mnt/ 10 HDD') == 10000000000, str(parse_disk('/mnt/ 10 HDD')) assert parse_disk('/mnt/ 1000 HDD') == 1000000000000, str(parse_disk('/mnt/ 1000 HDD')) # estimated run time <1 sec def testPrimitives(self): '''Test if toilwdl correctly interprets some basic declarations.''' wdl = os.path.abspath('src/toil/test/wdl/testfiles/vocab.wdl') json = os.path.abspath('src/toil/test/wdl/testfiles/vocab.json') aWDL = AnalyzeWDL(wdl, json, self.output_dir) with open(wdl, 'r') as wdl: wdl_string = wdl.read() ast = wdl_parser.parse(wdl_string).ast() aWDL.create_tasks_dict(ast) aWDL.create_workflows_dict(ast) no_declaration = ['bool1', 'int1', 'float1', 'file1', 'string1'] collection_counter = [] for name, declaration in iteritems(aWDL.workflows_dictionary['vocabulary']['wf_declarations']): if name in no_declaration: collection_counter.append(name) assert not declaration['value'] if name == 'bool2': collection_counter.append(name) assert declaration['value'] == 'True', declaration['value'] assert declaration['type'] == 'Boolean', declaration['type'] if name == 'int2': collection_counter.append(name) assert declaration['value'] == '1', declaration['value'] assert declaration['type'] == 'Int', declaration['type'] if name == 'float2': collection_counter.append(name) assert declaration['value'] == '1.1', declaration['value'] assert declaration['type'] == 'Float', declaration['type'] if name == 'file2': collection_counter.append(name) assert declaration['value'] == "'src/toil/test/wdl/test.tsv'", declaration['value'] assert declaration['type'] == 'File', declaration['type'] if name == 'string2': collection_counter.append(name) assert declaration['value'] == "'x'", declaration['value'] assert declaration['type'] == 'String', declaration['type'] assert collection_counter == ['bool1', 'int1', 'float1', 'file1', 'string1', 'bool2', 'int2', 'float2', 'file2', 'string2'] # estimated run time 27 sec @slow def testTut01(self): '''Test if toilwdl produces the same outputs as known good outputs for WDL's GATK tutorial #1.''' if self.manual_integration_tests: wdl = os.path.abspath("src/toil/test/wdl/wdl_templates/t01/helloHaplotypeCaller.wdl") json = os.path.abspath("src/toil/test/wdl/wdl_templates/t01/helloHaplotypeCaller_inputs.json") ref_dir = os.path.abspath("src/toil/test/wdl/wdl_templates/t01/output/") subprocess.check_call([exactPython, self.program, wdl, json, '-o', self.output_dir]) compare_runs(self.output_dir, ref_dir) # estimated run time 28 sec @slow def testTut02(self): '''Test if toilwdl produces the same outputs as known good outputs for WDL's GATK tutorial #2.''' if self.manual_integration_tests: wdl = os.path.abspath("src/toil/test/wdl/wdl_templates/t02/simpleVariantSelection.wdl") json = os.path.abspath("src/toil/test/wdl/wdl_templates/t02/simpleVariantSelection_inputs.json") ref_dir = os.path.abspath("src/toil/test/wdl/wdl_templates/t02/output/") subprocess.check_call([exactPython, self.program, wdl, json, '-o', self.output_dir]) compare_runs(self.output_dir, ref_dir) # estimated run time 60 sec @slow def testTut03(self): '''Test if toilwdl produces the same outputs as known good outputs for WDL's GATK tutorial #3.''' if self.manual_integration_tests: wdl = os.path.abspath("src/toil/test/wdl/wdl_templates/t03/simpleVariantDiscovery.wdl") json = os.path.abspath("src/toil/test/wdl/wdl_templates/t03/simpleVariantDiscovery_inputs.json") ref_dir = os.path.abspath("src/toil/test/wdl/wdl_templates/t03/output/") subprocess.check_call([exactPython, self.program, wdl, json, '-o', self.output_dir]) compare_runs(self.output_dir, ref_dir) # estimated run time 175 sec @slow def testTut04(self): '''Test if toilwdl produces the same outputs as known good outputs for WDL's GATK tutorial #4.''' if self.manual_integration_tests: wdl = os.path.abspath("src/toil/test/wdl/wdl_templates/t04/jointCallingGenotypes.wdl") json = os.path.abspath("src/toil/test/wdl/wdl_templates/t04/jointCallingGenotypes_inputs.json") ref_dir = os.path.abspath("src/toil/test/wdl/wdl_templates/t04/output/") subprocess.check_call([exactPython, self.program, wdl, json, '-o', self.output_dir]) compare_runs(self.output_dir, ref_dir) # estimated run time 80 sec @slow @needs_docker def testENCODE(self): '''Test if toilwdl produces the same outputs as known good outputs for a short ENCODE run.''' wdl = os.path.abspath( "src/toil/test/wdl/wdl_templates/testENCODE/encode_mapping_workflow.wdl") json = os.path.abspath( "src/toil/test/wdl/wdl_templates/testENCODE/encode_mapping_workflow.wdl.json") ref_dir = os.path.abspath( "src/toil/test/wdl/wdl_templates/testENCODE/output/") subprocess.check_call( [exactPython, self.program, wdl, json, '--docker_user=None', '--out_dir', self.output_dir]) compare_runs(self.output_dir, ref_dir) # estimated run time 2 sec def testPipe(self): '''Test basic bash input functionality with a pipe.''' wdl = os.path.abspath( "src/toil/test/wdl/wdl_templates/testPipe/call.wdl") json = os.path.abspath( "src/toil/test/wdl/wdl_templates/testPipe/call.json") ref_dir = os.path.abspath( "src/toil/test/wdl/wdl_templates/testPipe/output/") subprocess.check_call( [exactPython, self.program, wdl, json, '--out_dir', self.output_dir]) compare_runs(self.output_dir, ref_dir) # estimated run time <1 sec def testCSV(self): default_csv_output = [['1', '2', '3'], ['4', '5', '6'], ['7', '8', '9']] csv_array = read_csv(os.path.abspath('src/toil/test/wdl/test.csv')) assert csv_array == default_csv_output # estimated run time <1 sec def testTSV(self): default_tsv_output = [['1', '2', '3'], ['4', '5', '6'], ['7', '8', '9']] tsv_array = read_tsv(os.path.abspath('src/toil/test/wdl/test.tsv')) assert tsv_array == default_tsv_output # estimated run time <1 sec def testJSON(self): default_json_dict_output = { u'helloHaplotypeCaller.haplotypeCaller.RefIndex': u'"src/toil/test/wdl/GATK_data/ref/human_g1k_b37_20.fasta.fai"', u'helloHaplotypeCaller.haplotypeCaller.sampleName': u'"WDL_tut1_output"', u'helloHaplotypeCaller.haplotypeCaller.inputBAM': u'"src/toil/test/wdl/GATK_data/inputs/NA12878_wgs_20.bam"', u'helloHaplotypeCaller.haplotypeCaller.bamIndex': u'"src/toil/test/wdl/GATK_data/inputs/NA12878_wgs_20.bai"', u'helloHaplotypeCaller.haplotypeCaller.GATK': u'"src/toil/test/wdl/GATK_data/GenomeAnalysisTK.jar"', u'helloHaplotypeCaller.haplotypeCaller.RefDict': u'"src/toil/test/wdl/GATK_data/ref/human_g1k_b37_20.dict"', u'helloHaplotypeCaller.haplotypeCaller.RefFasta': u'"src/toil/test/wdl/GATK_data/ref/human_g1k_b37_20.fasta"'} t = AnalyzeWDL( "src/toil/test/wdl/wdl_templates/t01/helloHaplotypeCaller.wdl", "src/toil/test/wdl/wdl_templates/t01/helloHaplotypeCaller_inputs.json", self.output_dir) json_dict = t.dict_from_JSON("src/toil/test/wdl/wdl_templates/t01/helloHaplotypeCaller_inputs.json") assert json_dict == default_json_dict_output, (str(json_dict) + '\nAssertionError: ' + str(default_json_dict_output)) @classmethod def fetch_and_unzip_from_s3(cls, filename, data, data_dir): if not os.path.exists(data): s3_loc = os.path.join('http://toil-datasets.s3.amazonaws.com/', filename) urlretrieve(s3_loc, data) # extract the compressed data if not already extracted if not os.path.exists(data_dir): with zipfile.ZipFile(data, 'r') as zip_ref: zip_ref.extractall(cls.test_directory) def remove_outputs(output_dir): '''Remove the outputs generated by various unittests. These are created in the current working directory, which on jenkins is the main toil folder. They must be removed so that jenkins does not think we have untracked files in our github repo.''' encode_outputs = ['ENCFF000VOL_chr21.fq.gz', 'ENCFF000VOL_chr21.raw.srt.bam', 'ENCFF000VOL_chr21.raw.srt.bam.flagstat.qc', 'ENCFF000VOL_chr21.raw.srt.dup.qc', 'ENCFF000VOL_chr21.raw.srt.filt.nodup.srt.final.bam', 'ENCFF000VOL_chr21.raw.srt.filt.nodup.srt.final.bam.bai', 'ENCFF000VOL_chr21.raw.srt.filt.nodup.srt.final.filt.nodup.sample.15.SE.tagAlign.gz', 'ENCFF000VOL_chr21.raw.srt.filt.nodup.srt.final.filt.nodup.sample.15.SE.tagAlign.gz.cc.plot.pdf', 'ENCFF000VOL_chr21.raw.srt.filt.nodup.srt.final.filt.nodup.sample.15.SE.tagAlign.gz.cc.qc', 'ENCFF000VOL_chr21.raw.srt.filt.nodup.srt.final.flagstat.qc', 'ENCFF000VOL_chr21.raw.srt.filt.nodup.srt.final.pbc.qc', 'ENCFF000VOL_chr21.raw.srt.filt.nodup.srt.final.SE.tagAlign.gz', 'ENCFF000VOL_chr21.sai', 'test.txt', 'filter_qc.json', 'filter_qc.log', 'GRCh38_chr21_bwa.tar.gz', 'mapping.json', 'mapping.log', 'post_mapping.json', 'post_mapping.log', 'wdl-stats.log', 'xcor.json', 'xcor.log', 'toilwdl_compiled.pyc', 'toilwdl_compiled.py'] other_log_outputs = ['post_processing.log', 'md5.log'] outputs = encode_outputs + other_log_outputs for output in outputs: output = os.path.abspath(output) if os.path.exists(output): os.remove(output) if os.path.exists(output_dir): shutil.rmtree(output_dir) def compare_runs(output_dir, ref_dir): """ Takes two directories and compares all of the files between those two directories, asserting that they match. - Ignores outputs.txt, which contains a list of the outputs in the folder. - Compares line by line, unless the file is a .vcf file. - Ignores potentially date-stamped comments (lines starting with '#'). - Ignores quality scores in .vcf files and only checks that they found the same variants. This is due to assumed small observed rounding differences between systems. :param ref_dir: The first directory to compare (with output_dir). :param output_dir: The second directory to compare (with ref_dir). """ reference_output_files = os.listdir(ref_dir) for file in reference_output_files: if file != 'outputs.txt': test_output_files = os.listdir(output_dir) filepath = os.path.join(ref_dir, file) with open(filepath, 'r') as default_file: good_data = [] for line in default_file: if not line.startswith('#'): good_data.append(line) for test_file in test_output_files: if file == test_file: test_filepath = os.path.join(output_dir, file) if file.endswith(".vcf"): compare_vcf_files(filepath1=filepath, filepath2=test_filepath) else: with open(test_filepath, 'r') as test_file: test_data = [] for line in test_file: if not line.startswith('#'): test_data.append(line) assert good_data == test_data, "File does not match: %r" % file def compare_vcf_files(filepath1, filepath2): """ Asserts that two .vcf files contain the same variant findings. - Ignores potentially date-stamped comments (lines starting with '#'). - Ignores quality scores in .vcf files and only checks that they found the same variants. This is due to assumed small observed rounding differences between systems. VCF File Column Contents: 1: #CHROM 2: POS 3: ID 4: REF 5: ALT 6: QUAL 7: FILTER 8: INFO :param filepath1: First .vcf file to compare. :param filepath2: Second .vcf file to compare. """ with open(filepath1, 'r') as default_file: good_data = [] for line in default_file: line = line.strip() if not line.startswith('#'): good_data.append(line.split('\t')) with open(filepath2, 'r') as test_file: test_data = [] for line in test_file: line = line.strip() if not line.startswith('#'): test_data.append(line.split('\t')) for i in range(len(test_data)): if test_data[i] != good_data[i]: for j in range(len(test_data[i])): # Only compare chromosome, position, ID, reference, and alts. # Quality score may vary (<1%) between systems because of # (assumed) rounding differences. Same for the "info" sect. if j < 5: assert test_data[i][j] == good_data[i][j], "File does not match: %r" % filepath1 if __name__ == "__main__": unittest.main() # run all tests toil-releases-3.24.0/src/toil/toilState.py000066400000000000000000000201121362134276200204320ustar00rootroot00000000000000# Copyright (C) 2015-2018 Regents of the University of California # # 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. from __future__ import absolute_import from builtins import object import logging logger = logging.getLogger(__name__) class ToilState(object): """ Represents a snapshot of the jobs in the jobStore. Used by the leader to manage the batch. """ def __init__(self, jobStore, rootJob, jobCache=None): """ Loads the state from the jobStore, using the rootJob as the source of the job graph. The jobCache is a map from jobStoreIDs to jobGraphs or None. Is used to speed up the building of the state. :param toil.jobStores.abstractJobStore.AbstractJobStore jobStore :param toil.jobWrapper.JobGraph rootJob """ # This is a hash of jobs, referenced by jobStoreID, to their predecessor jobs. self.successorJobStoreIDToPredecessorJobs = {} # Hash of jobStoreIDs to counts of numbers of successors issued. # There are no entries for jobs without successors in this map. self.successorCounts = {} # This is a hash of service jobs, referenced by jobStoreID, to their predecessor job self.serviceJobStoreIDToPredecessorJob = {} # Hash of jobStoreIDs mapping to services issued for the job self.servicesIssued = {} # Jobs that are ready to be processed self.updatedJobs = set() # The set of totally failed jobs - this needs to be filtered at the # end to remove jobs that were removed by checkpoints self.totalFailedJobs = set() # Jobs (as jobStoreIDs) with successors that have totally failed self.hasFailedSuccessors = set() # The set of successors of failed jobs as a set of jobStoreIds self.failedSuccessors = set() # Set of jobs that have multiple predecessors that have one or more predecessors # finished, but not all of them. This acts as a cache for these jobs. # Stored as hash from jobStoreIDs to job graphs self.jobsToBeScheduledWithMultiplePredecessors = {} ##Algorithm to build this information self._buildToilState(rootJob, jobStore, jobCache) def _buildToilState(self, jobGraph, jobStore, jobCache=None): """ Traverses tree of jobs from the root jobGraph (rootJob) building the ToilState class. If jobCache is passed, it must be a dict from job ID to JobGraph object. Jobs will be loaded from the cache (which can be downloaded from the jobStore in a batch) instead of piecemeal when recursed into. :param jobGraph: Object representing a job. :param jobStore: Object inheriting toil.jobStores.abstractJobStore.AbstractJobStore. :param jobCache: :return: """ def getJob(jobId): if jobCache is not None: if jobId in jobCache: return jobCache[jobId] return jobStore.load(jobId) # If the jobGraph has a command, is a checkpoint, has services or is ready to be # deleted it is ready to be processed if jobGraph.command is not None or jobGraph.checkpoint is not None or jobGraph.services or not jobGraph.stack: logger.debug('Found job to run: %s, with command: %s, with checkpoint: %s, ' 'with services: %s, with stack: %s', jobGraph.jobStoreID, jobGraph.command is not None, jobGraph.checkpoint is not None, len(jobGraph.services) > 0, len(jobGraph.stack) == 0) self.updatedJobs.add((jobGraph, 0)) if jobGraph.checkpoint is not None: jobGraph.command = jobGraph.checkpoint else: # There exist successors logger.debug("Adding job: %s to the state with %s successors" % (jobGraph.jobStoreID, len(jobGraph.stack[-1]))) # Record the number of successors self.successorCounts[jobGraph.jobStoreID] = len(jobGraph.stack[-1]) def processSuccessorWithMultiplePredecessors(successorJobGraph): # If jobGraph is not reported as complete by the successor if jobGraph.jobStoreID not in successorJobGraph.predecessorsFinished: # Update the successor's status to mark the predecessor complete successorJobGraph.predecessorsFinished.add(jobGraph.jobStoreID) # If the successor has no predecessors to finish assert len(successorJobGraph.predecessorsFinished) <= successorJobGraph.predecessorNumber if len(successorJobGraph.predecessorsFinished) == successorJobGraph.predecessorNumber: # It is ready to be run, so remove it from the cache self.jobsToBeScheduledWithMultiplePredecessors.pop(successorJobStoreID) # Recursively consider the successor self._buildToilState(successorJobGraph, jobStore, jobCache=jobCache) # For each successor for successorJobNode in jobGraph.stack[-1]: successorJobStoreID = successorJobNode.jobStoreID # If the successor jobGraph does not yet point back at a # predecessor we have not yet considered it if successorJobStoreID not in self.successorJobStoreIDToPredecessorJobs: # Add the job as a predecessor self.successorJobStoreIDToPredecessorJobs[successorJobStoreID] = [jobGraph] # If predecessor number > 1 then the successor has multiple predecessors if successorJobNode.predecessorNumber > 1: # We load the successor job successorJobGraph = getJob(successorJobStoreID) # We put the successor job in the cache of successor jobs with multiple predecessors assert successorJobStoreID not in self.jobsToBeScheduledWithMultiplePredecessors self.jobsToBeScheduledWithMultiplePredecessors[successorJobStoreID] = successorJobGraph # Process successor processSuccessorWithMultiplePredecessors(successorJobGraph) else: # The successor has only the jobGraph as a predecessor so # recursively consider the successor self._buildToilState(getJob(successorJobStoreID), jobStore, jobCache=jobCache) else: # We've already seen the successor # Add the job as a predecessor assert jobGraph not in self.successorJobStoreIDToPredecessorJobs[successorJobStoreID] self.successorJobStoreIDToPredecessorJobs[successorJobStoreID].append(jobGraph) # If the successor has multiple predecessors if successorJobStoreID in self.jobsToBeScheduledWithMultiplePredecessors: # Get the successor from cache successorJobGraph = self.jobsToBeScheduledWithMultiplePredecessors[successorJobStoreID] # Process successor processSuccessorWithMultiplePredecessors(successorJobGraph) toil-releases-3.24.0/src/toil/utils/000077500000000000000000000000001362134276200172545ustar00rootroot00000000000000toil-releases-3.24.0/src/toil/utils/__init__.py000066400000000000000000000033601362134276200213670ustar00rootroot00000000000000from __future__ import absolute_import from toil import version import logging import os logger = logging.getLogger(__name__) def addBasicProvisionerOptions(parser): parser.add_argument("--version", action='version', version=version) parser.add_argument('-p', "--provisioner", dest='provisioner', choices=['aws', 'gce'], required=False, default="aws", help="The provisioner for cluster auto-scaling. AWS and Google are currently supported") parser.add_argument('-z', '--zone', dest='zone', required=False, default=None, help="The availability zone of the master. This parameter can also be set via the 'TOIL_X_ZONE' " "environment variable, where X is AWS or GCE, or by the ec2_region_name parameter " "in your .boto file, or derived from the instance metadata if using this utility on an " "existing EC2 instance.") parser.add_argument("clusterName", help="The name that the cluster will be identifiable by. " "Must be lowercase and may not contain the '_' " "character.") return parser def getZoneFromEnv(provisioner): """ Find the zone specified in an environment variable. The user can specify zones in environment variables in lieu of writing them at the commandline every time. Given a provisioner, this method will look for the stored value and return it. :param str provisioner: One of the supported provisioners ('aws', 'gce') :rtype: str :return: None or the value stored in a 'TOIL_X_ZONE' environment variable. """ return os.environ.get('TOIL_' + provisioner.upper() + '_ZONE') toil-releases-3.24.0/src/toil/utils/toilClean.py000066400000000000000000000030411362134276200215360ustar00rootroot00000000000000# Copyright (C) 2015-2018 Regents of the University of California # # 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. """ Delete the job store used by a previous Toil workflow invocation """ from __future__ import absolute_import import logging from toil.lib.bioio import getBasicOptionParser from toil.lib.bioio import parseBasicOptions from toil.common import Toil, jobStoreLocatorHelp, Config from toil.version import version logger = logging.getLogger( __name__ ) def main(): parser = getBasicOptionParser() parser.add_argument("jobStore", type=str, help="The location of the job store to delete. " + jobStoreLocatorHelp) parser.add_argument("--version", action='version', version=version) config = Config() config.setOptions(parseBasicOptions(parser)) try: jobStore = Toil.getJobStore(config.jobStore) jobStore.destroy() logger.info("Successfully deleted the job store: %s" % config.jobStore) except: logger.info("Failed to delete the job store: %s" % config.jobStore) raise toil-releases-3.24.0/src/toil/utils/toilDebugFile.py000066400000000000000000000143021362134276200223440ustar00rootroot00000000000000# Copyright (C) 2017-2018 Regents of the University of California # # 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. """Debug tool for copying files contained in a toil jobStore. """ from __future__ import absolute_import import logging import fnmatch import os.path from toil.lib.bioio import getBasicOptionParser from toil.lib.bioio import parseBasicOptions from toil.common import Toil, jobStoreLocatorHelp, Config from toil.version import version logger = logging.getLogger( __name__ ) def recursiveGlob(directoryname, glob_pattern): ''' Walks through a directory and its subdirectories looking for files matching the glob_pattern and returns a list=[]. :param directoryname: Any accessible folder name on the filesystem. :param glob_pattern: A string like "*.txt", which would find all text files. :return: A list=[] of absolute filepaths matching the glob pattern. ''' directoryname = os.path.abspath(directoryname) matches = [] for root, dirnames, filenames in os.walk(directoryname): for filename in fnmatch.filter(filenames, glob_pattern): absolute_filepath = os.path.join(root, filename) matches.append(absolute_filepath) return matches def fetchJobStoreFiles(jobStore, options): """ Takes a list of file names as glob patterns, searches for these within a given directory, and attempts to take all of the files found and copy them into options.localFilePath. :param jobStore: A fileJobStore object. :param options.fetch: List of file glob patterns to search for in the jobStore and copy into options.localFilePath. :param options.localFilePath: Local directory to copy files into. :param options.jobStore: The path to the jobStore directory. """ for jobStoreFile in options.fetch: jobStoreHits = recursiveGlob(directoryname=options.jobStore, glob_pattern=jobStoreFile) for jobStoreFileID in jobStoreHits: logger.debug("Copying job store file: %s to %s", jobStoreFileID, options.localFilePath[0]) jobStore.readFile(jobStoreFileID, os.path.join(options.localFilePath[0], os.path.basename(jobStoreFileID)), symlink=options.useSymlinks) def printContentsOfJobStore(jobStorePath, nameOfJob=None): """ Fetch a list of all files contained in the jobStore directory input if nameOfJob is not declared, otherwise it only prints out the names of files for that specific job for which it can find a match. Also creates a logFile containing this same record of job files in the working directory. :param jobStorePath: Directory path to recursively look for files. :param nameOfJob: Default is None, which prints out all files in the jobStore. If specified, it will print all jobStore files that have been written to the jobStore by that job. """ if nameOfJob: glob = "*" + nameOfJob + "*" logFile = nameOfJob + "_fileset.txt" else: glob = "*" logFile = "jobstore_files.txt" nameOfJob = "" list_of_files = recursiveGlob(directoryname=jobStorePath, glob_pattern=glob) if os.path.exists(logFile): os.remove(logFile) for gfile in sorted(list_of_files): if not gfile.endswith('.new'): logger.debug(nameOfJob + "File: %s", os.path.basename(gfile)) with open(logFile, "a+") as f: f.write(os.path.basename(gfile)) f.write("\n") def main(): parser = getBasicOptionParser() parser.add_argument("jobStore", type=str, help="The location of the job store used by the workflow." + jobStoreLocatorHelp) parser.add_argument("--localFilePath", nargs=1, help="Location to which to copy job store files.") parser.add_argument("--fetch", nargs="+", help="List of job-store files to be copied locally." "Use either explicit names (i.e. 'data.txt'), or " "specify glob patterns (i.e. '*.txt')") parser.add_argument("--listFilesInJobStore", help="Prints a list of the current files in the jobStore.") parser.add_argument("--fetchEntireJobStore", help="Copy all job store files into a local directory.") parser.add_argument("--useSymlinks", help="Creates symlink 'shortcuts' of files in the localFilePath" " instead of hardlinking or copying, where possible. If this is" " not possible, it will copy the files (shutil.copyfile()).") parser.add_argument("--version", action='version', version=version) # Load the jobStore options = parseBasicOptions(parser) config = Config() config.setOptions(options) jobStore = Toil.resumeJobStore(config.jobStore) logger.debug("Connected to job store: %s", config.jobStore) if options.fetch: # Copy only the listed files locally logger.debug("Fetching local files: %s", options.fetch) fetchJobStoreFiles(jobStore=jobStore, options=options) elif options.fetchEntireJobStore: # Copy all jobStore files locally logger.debug("Fetching all local files.") options.fetch = "*" fetchJobStoreFiles(jobStore=jobStore, options=options) if options.listFilesInJobStore: # Log filenames and create a file containing these names in cwd printContentsOfJobStore(jobStorePath=options.jobStore) if __name__=="__main__": main() toil-releases-3.24.0/src/toil/utils/toilDebugJob.py000066400000000000000000000050431362134276200222010ustar00rootroot00000000000000# Copyright (C) 2017- Regents of the University of California # # 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. """Debug tool for running a toil job locally. """ from __future__ import absolute_import import logging from toil.lib.bioio import getBasicOptionParser from toil.lib.bioio import parseBasicOptions from toil.common import jobStoreLocatorHelp, Config, Toil from toil.version import version from toil.worker import workerScript from toil.utils.toilDebugFile import printContentsOfJobStore logger = logging.getLogger( __name__ ) def print_successor_jobs(): pass def main(): parser = getBasicOptionParser() parser.add_argument("jobStore", type=str, help="The location of the job store used by the workflow." + jobStoreLocatorHelp) parser.add_argument("jobID", nargs=1, help="The job store id of a job " "within the provided jobstore to run by itself.") parser.add_argument("--printJobInfo", nargs=1, help="Return information about this job to the user" " including preceding jobs, inputs, outputs, and runtime" " from the last known run.") parser.add_argument("--version", action='version', version=version) # Parse options options = parseBasicOptions(parser) config = Config() config.setOptions(options) # Load the job store jobStore = Toil.resumeJobStore(config.jobStore) if options.printJobInfo: printContentsOfJobStore(jobStorePath=options.jobStore, nameOfJob=options.printJobInfo) # TODO: Option to print list of successor jobs # TODO: Option to run job within python debugger, allowing step through of arguments # idea would be to have option to import pdb and set breakpoint at the start of the user's code # Run the job locally jobID = options.jobID[0] logger.debug("Going to run the following job locally: %s", jobID) workerScript(jobStore, config, jobID, jobID, redirectOutputToLogFile=False) logger.debug("Ran the following job locally: %s", jobID) toil-releases-3.24.0/src/toil/utils/toilDestroyCluster.py000066400000000000000000000022111362134276200235050ustar00rootroot00000000000000# Copyright (C) 2015 UCSC Computational Genomics Lab # # 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. """ Terminates the specified cluster and associated resources """ from toil.provisioners import clusterFactory from toil.lib.bioio import parseBasicOptions, getBasicOptionParser from toil.utils import addBasicProvisionerOptions def main(): parser = getBasicOptionParser() parser = addBasicProvisionerOptions(parser) config = parseBasicOptions(parser) cluster = clusterFactory(provisioner=config.provisioner, clusterName=config.clusterName, zone=config.zone) cluster.destroyCluster() toil-releases-3.24.0/src/toil/utils/toilKill.py000066400000000000000000000051701362134276200214140ustar00rootroot00000000000000# Copyright (C) 2015-2018 Regents of the University of California # # 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. """Kills rogue toil processes.""" from __future__ import absolute_import import logging import os import signal from toil.lib.bioio import getBasicOptionParser from toil.lib.bioio import parseBasicOptions from toil.common import Toil, jobStoreLocatorHelp, Config from toil.version import version logger = logging.getLogger( __name__ ) def main(): parser = getBasicOptionParser() parser.add_argument("jobStore", type=str, help="The location of the job store used by the workflow whose jobs should " "be killed." + jobStoreLocatorHelp) parser.add_argument("--version", action='version', version=version) options = parseBasicOptions(parser) config = Config() config.setOptions(options) config.jobStore = config.jobStore[5:] if config.jobStore.startswith('file:') else config.jobStore # ':' means an aws/google jobstore; use the old (broken?) method if ':' in config.jobStore: jobStore = Toil.resumeJobStore(config.jobStore) logger.info("Starting routine to kill running jobs in the toil workflow: %s", config.jobStore) # TODO: This behaviour is now broken src: https://github.com/DataBiosphere/toil/commit/a3d65fc8925712221e4cda116d1825d4a1e963a1 batchSystem = Toil.createBatchSystem(jobStore.config) # Should automatically kill existing jobs, so we're good. for jobID in batchSystem.getIssuedBatchJobIDs(): # Just in case we do it again. batchSystem.killBatchJobs(jobID) logger.info("All jobs SHOULD have been killed") # otherwise, kill the pid recorded in the jobstore else: pid_log = os.path.join(os.path.abspath(config.jobStore), 'pid.log') with open(pid_log, 'r') as f: pid2kill = f.read().strip() try: os.kill(int(pid2kill), signal.SIGKILL) logger.info("Toil process %s successfully terminated." % str(pid2kill)) except OSError: logger.error("Toil process %s could not be terminated." % str(pid2kill)) raise toil-releases-3.24.0/src/toil/utils/toilLaunchCluster.py000066400000000000000000000205731362134276200233010ustar00rootroot00000000000000# Copyright (C) 2015 UCSC Computational Genomics Lab # # 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. """ Launches a toil leader instance with the specified provisioner """ import logging from toil.lib.bioio import parseBasicOptions, getBasicOptionParser from toil.utils import addBasicProvisionerOptions, getZoneFromEnv from toil.provisioners import clusterFactory from toil.provisioners.aws import checkValidNodeTypes from toil import applianceSelf logger = logging.getLogger(__name__) def createTagsDict(tagList): tagsDict = dict() for tag in tagList: key, value = tag.split('=') tagsDict[key] = value return tagsDict def main(): parser = getBasicOptionParser() parser = addBasicProvisionerOptions(parser) parser.add_argument("--leaderNodeType", dest="leaderNodeType", required=True, help="Non-preemptable node type to use for the cluster leader.") parser.add_argument("--keyPairName", dest='keyPairName', help="On AWS, the name of the AWS key pair to include on the instance." " On Google/GCE, this is the ssh key pair.") parser.add_argument("--owner", dest='owner', help="The owner tag for all instances. If not given, the value in" " --keyPairName will be used if given.") parser.add_argument("--boto", dest='botoPath', help="The path to the boto credentials directory. This is transferred " "to all nodes in order to access the AWS jobStore from non-AWS instances.") parser.add_argument("-t", "--tag", metavar='NAME=VALUE', dest='tags', default=[], action='append', help="Tags are added to the AWS cluster for this node and all of its " "children. Tags are of the form:\n" " -t key1=value1 --tag key2=value2\n" "Multiple tags are allowed and each tag needs its own flag. By " "default the cluster is tagged with " " {\n" " \"Name\": clusterName,\n" " \"Owner\": IAM username\n" " }. ") parser.add_argument("--vpcSubnet", help="VPC subnet ID to launch cluster in. Uses default subnet if not " "specified. This subnet needs to have auto assign IPs turned on.") parser.add_argument("--nodeTypes", dest='nodeTypes', default=None, type=str, help="Comma-separated list of node types to create while launching the " "leader. The syntax for each node type depends on the provisioner " "used. For the aws provisioner this is the name of an EC2 instance " "type followed by a colon and the price in dollar to bid for a spot " "instance, for example 'c3.8xlarge:0.42'. Must also provide the " "--workers argument to specify how many workers of each node type " "to create.") parser.add_argument("-w", "--workers", dest='workers', default=None, type=str, help="Comma-separated list of the number of workers of each node type to " "launch alongside the leader when the cluster is created. This can be " "useful if running toil without auto-scaling but with need of more " "hardware support") parser.add_argument("--leaderStorage", dest='leaderStorage', type=int, default=50, help="Specify the size (in gigabytes) of the root volume for the leader " "instance. This is an EBS volume.") parser.add_argument("--nodeStorage", dest='nodeStorage', type=int, default=50, help="Specify the size (in gigabytes) of the root volume for any worker " "instances created when using the -w flag. This is an EBS volume.") parser.add_argument('--forceDockerAppliance', dest='forceDockerAppliance', action='store_true', default=False, help="Disables sanity checking the existence of the docker image specified " "by TOIL_APPLIANCE_SELF, which Toil uses to provision mesos for " "autoscaling.") parser.add_argument('--awsEc2ProfileArn', dest='awsEc2ProfileArn', default=None, type=str, help="If provided, the specified ARN is used as the instance profile for EC2 instances." "Useful for setting custom IAM profiles. If not specified, a new IAM role is created " "by default with sufficient access to perform basic cluster operations.") config = parseBasicOptions(parser) tagsDict = None if config.tags is None else createTagsDict(config.tags) checkValidNodeTypes(config.provisioner, config.nodeTypes) checkValidNodeTypes(config.provisioner, config.leaderNodeType) # checks the validity of TOIL_APPLIANCE_SELF before proceeding applianceSelf(forceDockerAppliance=config.forceDockerAppliance) spotBids = [] nodeTypes = [] preemptableNodeTypes = [] numNodes = [] numPreemptableNodes = [] if (config.nodeTypes or config.workers) and not (config.nodeTypes and config.workers): raise RuntimeError("The --nodeTypes and --workers options must be specified together,") if config.nodeTypes: nodeTypesList = config.nodeTypes.split(",") numWorkersList = config.workers.split(",") if not len(nodeTypesList) == len(numWorkersList): raise RuntimeError("List of node types must be the same length as the list of workers.") for nodeTypeStr, num in zip(nodeTypesList, numWorkersList): parsedBid = nodeTypeStr.split(':', 1) if len(nodeTypeStr) != len(parsedBid[0]): #Is a preemptable node preemptableNodeTypes.append(parsedBid[0]) spotBids.append(float(parsedBid[1])) numPreemptableNodes.append(int(num)) else: nodeTypes.append(nodeTypeStr) numNodes.append(int(num)) # set owner (default to keyPairName if not given) owner = 'toil' if config.owner: owner = config.owner elif config.keyPairName: owner = config.keyPairName # Check to see if the user specified a zone. If not, see if one is stored in an environment variable. config.zone = config.zone or getZoneFromEnv(config.provisioner) if not config.zone: raise RuntimeError('Please provide a value for --zone or set a default in the TOIL_' + config.provisioner.upper() + '_ZONE enviroment variable.') cluster = clusterFactory(provisioner=config.provisioner, clusterName=config.clusterName, zone=config.zone, nodeStorage=config.nodeStorage) cluster.launchCluster(leaderNodeType=config.leaderNodeType, leaderStorage=config.leaderStorage, owner=owner, keyName=config.keyPairName, botoPath=config.botoPath, userTags=tagsDict, vpcSubnet=config.vpcSubnet, awsEc2ProfileArn=config.awsEc2ProfileArn) for nodeType, workers in zip(nodeTypes, numNodes): cluster.addNodes(nodeType=nodeType, numNodes=workers, preemptable=False) for nodeType, workers, spotBid in zip(preemptableNodeTypes, numPreemptableNodes, spotBids): cluster.addNodes(nodeType=nodeType, numNodes=workers, preemptable=True, spotBid=spotBid) toil-releases-3.24.0/src/toil/utils/toilMain.py000077500000000000000000000042231362134276200214060ustar00rootroot00000000000000from __future__ import absolute_import, print_function from past.builtins import map from toil.version import version import pkg_resources import os import sys import re # Python 3 compatibility imports from six import iteritems, iterkeys def main(): modules = loadModules() try: command = sys.argv[1] except IndexError: printHelp(modules) else: if command == '--help': printHelp(modules) elif command == '--version': try: print(pkg_resources.get_distribution('toil').version) except: print("Version gathered from toil.version: "+version) else: try: module = modules[command] except KeyError: print("Unknown option '%s'. " "Pass --help to display usage information.\n" % command, file=sys.stderr) sys.exit(1) else: del sys.argv[1] module.main() def loadModules(): # noinspection PyUnresolvedReferences from toil.utils import (toilKill, toilStats, toilStatus, toilClean, toilLaunchCluster, toilDestroyCluster, toilSshCluster, toilRsyncCluster, toilDebugFile, toilDebugJob) commandMapping = { "-".join( map(lambda x : x.lower(), re.findall('[A-Z][^A-Z]*', name) )) : module for name, module in iteritems(locals())} return commandMapping def printHelp(modules): usage = ("\n" "Usage: {name} COMMAND ...\n" " {name} --help\n" " {name} COMMAND --help\n\n" "where COMMAND is one of the following:\n\n{descriptions}\n\n") print(usage.format( name=os.path.basename(sys.argv[0]), commands='|'.join(iterkeys(modules)), descriptions='\n'.join("%s - %s" % (n, str(m.__doc__).strip()) for n, m in iteritems(modules) if m is not None))) toil-releases-3.24.0/src/toil/utils/toilRsyncCluster.py000066400000000000000000000036661362134276200231710ustar00rootroot00000000000000# Copyright (C) 2015 UCSC Computational Genomics Lab # # 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. """ Rsyncs into the toil appliance container running on the leader of the cluster """ import argparse import logging from toil.lib.bioio import parseBasicOptions, getBasicOptionParser from toil.provisioners import clusterFactory from toil.utils import addBasicProvisionerOptions logger = logging.getLogger(__name__) def main(): parser = getBasicOptionParser() parser = addBasicProvisionerOptions(parser) parser.add_argument("--insecure", dest='insecure', action='store_true', required=False, help="Temporarily disable strict host key checking.") parser.add_argument("args", nargs=argparse.REMAINDER, help="Arguments to pass to" "`rsync`. Takes any arguments that rsync accepts. Specify the" " remote with a colon. For example, to upload `example.py`," " specify `toil rsync-cluster -p aws test-cluster example.py :`." "\nOr, to download a file from the remote:, `toil rsync-cluster" " -p aws test-cluster :example.py .`") config = parseBasicOptions(parser) cluster = clusterFactory(provisioner=config.provisioner, clusterName=config.clusterName, zone=config.zone) cluster.getLeader().coreRsync(args=config.args, strict=not config.insecure) toil-releases-3.24.0/src/toil/utils/toilSshCluster.py000066400000000000000000000034241362134276200226200ustar00rootroot00000000000000# Copyright (C) 2015 UCSC Computational Genomics Lab # # 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. """ SSHs into the toil appliance container running on the leader of the cluster """ import argparse import logging import sys from toil.provisioners import clusterFactory from toil.lib.bioio import parseBasicOptions, getBasicOptionParser from toil.utils import addBasicProvisionerOptions logger = logging.getLogger(__name__) def main(): parser = getBasicOptionParser() parser = addBasicProvisionerOptions(parser) parser.add_argument("--insecure", action='store_true', help="Temporarily disable strict host key checking.") parser.add_argument("--sshOption", dest='sshOptions', default=[], action='append', help="Pass an additional option to the SSH command.") parser.add_argument('args', nargs=argparse.REMAINDER) config = parseBasicOptions(parser) cluster = clusterFactory(provisioner=config.provisioner, clusterName=config.clusterName, zone=config.zone) command = config.args if config.args else ['bash'] cluster.getLeader().sshAppliance(*command, strict=not config.insecure, tty=sys.stdin.isatty(), sshOptions=config.sshOptions) toil-releases-3.24.0/src/toil/utils/toilStats.py000066400000000000000000000573031362134276200216240ustar00rootroot00000000000000# Copyright (C) 2015-2016 Regents of the University of California # # 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. """ Reports statistical data about a given Toil workflow. """ from __future__ import absolute_import, print_function from __future__ import division from builtins import str from builtins import range from past.utils import old_div from builtins import object from functools import partial import logging import json from toil.lib.bioio import getBasicOptionParser from toil.lib.bioio import parseBasicOptions from toil.common import Toil, jobStoreLocatorHelp, Config from toil.version import version from toil.lib.expando import Expando logger = logging.getLogger( __name__ ) class ColumnWidths(object): """ Convenience object that stores the width of columns for printing. Helps make things pretty. """ def __init__(self): self.categories = ["time", "clock", "wait", "memory"] self.fields_count = ["count", "min", "med", "ave", "max", "total"] self.fields = ["min", "med", "ave", "max", "total"] self.data = {} for category in self.categories: for field in self.fields_count: self.setWidth(category, field, 8) def title(self, category): """ Return the total printed length of this category item. """ return sum( [self.getWidth(category, x) for x in self.fields]) def getWidth(self, category, field): category = category.lower() return self.data["%s_%s" % (category, field)] def setWidth(self, category, field, width): category = category.lower() self.data["%s_%s" % (category, field)] = width def report(self): for c in self.categories: for f in self.fields: print('%s %s %d' % (c, f, self.getWidth(c, f))) def initializeOptions(parser): parser.add_argument("jobStore", type=str, help="The location of the job store used by the workflow for which " "statistics should be reported. " + jobStoreLocatorHelp) parser.add_argument("--outputFile", dest="outputFile", default=None, help="File in which to write results") parser.add_argument("--raw", action="store_true", default=False, help="output the raw json data.") parser.add_argument("--pretty", "--human", action="store_true", default=False, help=("if not raw, prettify the numbers to be " "human readable.")) parser.add_argument("--categories", help=("comma separated list from [time, clock, wait, " "memory]")) parser.add_argument("--sortCategory", default="time", help=("how to sort Job list. may be from [alpha, " "time, clock, wait, memory, count]. " "default=%(default)s")) parser.add_argument("--sortField", default="med", help=("how to sort Job list. may be from [min, " "med, ave, max, total]. " "default=%(default)s")) parser.add_argument("--sortReverse", "--reverseSort", default=False, action="store_true", help="reverse sort order.") parser.add_argument("--version", action='version', version=version) def checkOptions(options, parser): """ Check options, throw parser.error() if something goes wrong """ if options.jobStore == None: parser.error("Specify --jobStore") defaultCategories = ["time", "clock", "wait", "memory"] if options.categories is None: options.categories = defaultCategories else: options.categories = [x.lower() for x in options.categories.split(",")] for c in options.categories: if c not in defaultCategories: parser.error("Unknown category %s. Must be from %s" % (c, str(defaultCategories))) extraSort = ["count", "alpha"] if options.sortCategory is not None: if (options.sortCategory not in defaultCategories and options.sortCategory not in extraSort): parser.error("Unknown --sortCategory %s. Must be from %s" % (options.sortCategory, str(defaultCategories + extraSort))) sortFields = ["min", "med", "ave", "max", "total"] if options.sortField is not None: if (options.sortField not in sortFields): parser.error("Unknown --sortField %s. Must be from %s" % (options.sortField, str(sortFields))) def printJson(elem): """ Return a JSON formatted string """ prettyString = json.dumps(elem, indent=4, separators=(',',': ')) return prettyString def padStr(s, field=None): """ Pad the begining of a string with spaces, if necessary. """ if field is None: return s else: if len(s) >= field: return s else: return " " * (field - len(s)) + s def prettyMemory(k, field=None, isBytes=False): """ Given input k as kilobytes, return a nicely formatted string. """ if isBytes: k /= 1024 if k < 1024: return padStr("%gK" % k, field) if k < (1024 * 1024): return padStr("%.1fM" % (old_div(k, 1024.0)), field) if k < (1024 * 1024 * 1024): return padStr("%.1fG" % (k / 1024.0 / 1024.0), field) if k < (1024 * 1024 * 1024 * 1024): return padStr("%.1fT" % (k / 1024.0 / 1024.0 / 1024.0), field) if k < (1024 * 1024 * 1024 * 1024 * 1024): return padStr("%.1fP" % (k / 1024.0 / 1024.0 / 1024.0 / 1024.0), field) def prettyTime(t, field=None): """ Given input t as seconds, return a nicely formatted string. """ from math import floor pluralDict = {True: "s", False: ""} if t < 120: return padStr("%ds" % t, field) if t < 120 * 60: m = floor(old_div(t, 60.)) s = t % 60 return padStr("%dm%ds" % (m, s), field) if t < 25 * 60 * 60: h = floor(t / 60. / 60.) m = floor(old_div((t - (h * 60. * 60.)), 60.)) s = t % 60 return padStr("%dh%gm%ds" % (h, m, s), field) if t < 7 * 24 * 60 * 60: d = floor(t / 24. / 60. / 60.) h = floor((t - (d * 24. * 60. * 60.)) / 60. / 60.) m = floor(old_div((t - (d * 24. * 60. * 60.) - (h * 60. * 60.)), 60.)) s = t % 60 dPlural = pluralDict[d > 1] return padStr("%dday%s%dh%dm%ds" % (d, dPlural, h, m, s), field) w = floor(t / 7. / 24. / 60. / 60.) d = floor((t - (w * 7 * 24 * 60 * 60)) / 24. / 60. / 60.) h = floor((t - (w * 7. * 24. * 60. * 60.) - (d * 24. * 60. * 60.)) / 60. / 60.) m = floor(old_div((t - (w * 7. * 24. * 60. * 60.) - (d * 24. * 60. * 60.) - (h * 60. * 60.)), 60.)) s = t % 60 wPlural = pluralDict[w > 1] dPlural = pluralDict[d > 1] return padStr("%dweek%s%dday%s%dh%dm%ds" % (w, wPlural, d, dPlural, h, m, s), field) def reportTime(t, options, field=None): """ Given t seconds, report back the correct format as string. """ if options.pretty: return prettyTime(t, field=field) else: if field is not None: return "%*.2f" % (field, t) else: return "%.2f" % t def reportMemory(k, options, field=None, isBytes=False): """ Given k kilobytes, report back the correct format as string. """ if options.pretty: return prettyMemory(int(k), field=field, isBytes=isBytes) else: if isBytes: k /= 1024. if field is not None: return "%*dK" % (field - 1, k) # -1 for the "K" else: return "%dK" % int(k) def reportNumber(n, options, field=None): """ Given n an integer, report back the correct format as string. """ if field is not None: return "%*g" % (field, n) else: return "%g" % n def refineData(root, options): """ walk down from the root and gather up the important bits. """ worker = root.worker job = root.jobs jobTypesTree = root.job_types jobTypes = [] for childName in jobTypesTree: jobTypes.append(jobTypesTree[childName]) return root, worker, job, jobTypes def sprintTag(key, tag, options, columnWidths=None): """ Generate a pretty-print ready string from a JTTag(). """ if columnWidths is None: columnWidths = ColumnWidths() header = " %7s " % decorateTitle("Count", options) sub_header = " %7s " % "n" tag_str = " %s" % reportNumber(tag.total_number, options, field=7) out_str = "" if key == "job": out_str += " %-12s | %7s%7s%7s%7s\n" % ("Worker Jobs", "min", "med", "ave", "max") worker_str = "%s| " % (" " * 14) for t in [tag.min_number_per_worker, tag.median_number_per_worker, tag.average_number_per_worker, tag.max_number_per_worker]: worker_str += reportNumber(t, options, field=7) out_str += worker_str + "\n" if "time" in options.categories: header += "| %*s " % (columnWidths.title("time"), decorateTitle("Time", options)) sub_header += decorateSubHeader("Time", columnWidths, options) tag_str += " | " for t, width in [ (tag.min_time, columnWidths.getWidth("time", "min")), (tag.median_time, columnWidths.getWidth("time", "med")), (tag.average_time, columnWidths.getWidth("time", "ave")), (tag.max_time, columnWidths.getWidth("time", "max")), (tag.total_time, columnWidths.getWidth("time", "total")), ]: tag_str += reportTime(t, options, field=width) if "clock" in options.categories: header += "| %*s " % (columnWidths.title("clock"), decorateTitle("Clock", options)) sub_header += decorateSubHeader("Clock", columnWidths, options) tag_str += " | " for t, width in [ (tag.min_clock, columnWidths.getWidth("clock", "min")), (tag.median_clock, columnWidths.getWidth("clock", "med")), (tag.average_clock, columnWidths.getWidth("clock", "ave")), (tag.max_clock, columnWidths.getWidth("clock", "max")), (tag.total_clock, columnWidths.getWidth("clock", "total")), ]: tag_str += reportTime(t, options, field=width) if "wait" in options.categories: header += "| %*s " % (columnWidths.title("wait"), decorateTitle("Wait", options)) sub_header += decorateSubHeader("Wait", columnWidths, options) tag_str += " | " for t, width in [ (tag.min_wait, columnWidths.getWidth("wait", "min")), (tag.median_wait, columnWidths.getWidth("wait", "med")), (tag.average_wait, columnWidths.getWidth("wait", "ave")), (tag.max_wait, columnWidths.getWidth("wait", "max")), (tag.total_wait, columnWidths.getWidth("wait", "total")), ]: tag_str += reportTime(t, options, field=width) if "memory" in options.categories: header += "| %*s " % (columnWidths.title("memory"), decorateTitle("Memory", options)) sub_header += decorateSubHeader("Memory", columnWidths, options) tag_str += " | " for t, width in [ (tag.min_memory, columnWidths.getWidth("memory", "min")), (tag.median_memory, columnWidths.getWidth("memory", "med")), (tag.average_memory, columnWidths.getWidth("memory", "ave")), (tag.max_memory, columnWidths.getWidth("memory", "max")), (tag.total_memory, columnWidths.getWidth("memory", "total")), ]: tag_str += reportMemory(t, options, field=width) out_str += header + "\n" out_str += sub_header + "\n" out_str += tag_str + "\n" return out_str def decorateTitle(title, options): """ Add a marker to TITLE if the TITLE is sorted on. """ if title.lower() == options.sortCategory: return "%s*" % title else: return title def decorateSubHeader(title, columnWidths, options): """ Add a marker to the correct field if the TITLE is sorted on. """ title = title.lower() if title != options.sortCategory: s = "| %*s%*s%*s%*s%*s " % ( columnWidths.getWidth(title, "min"), "min", columnWidths.getWidth(title, "med"), "med", columnWidths.getWidth(title, "ave"), "ave", columnWidths.getWidth(title, "max"), "max", columnWidths.getWidth(title, "total"), "total") return s else: s = "| " for field, width in [("min", columnWidths.getWidth(title, "min")), ("med", columnWidths.getWidth(title, "med")), ("ave", columnWidths.getWidth(title, "ave")), ("max", columnWidths.getWidth(title, "max")), ("total", columnWidths.getWidth(title, "total"))]: if options.sortField == field: s += "%*s*" % (width - 1, field) else: s += "%*s" % (width, field) s += " " return s def get(tree, name): """ Return a float value attribute NAME from TREE. """ if name in tree: value = tree[name] else: return float("nan") try: a = float(value) except ValueError: a = float("nan") return a def sortJobs(jobTypes, options): """ Return a jobTypes all sorted. """ longforms = {"med": "median", "ave": "average", "min": "min", "total": "total", "max": "max",} sortField = longforms[options.sortField] if (options.sortCategory == "time" or options.sortCategory == "clock" or options.sortCategory == "wait" or options.sortCategory == "memory" ): return sorted( jobTypes, key=lambda tag: getattr(tag, "%s_%s" % (sortField, options.sortCategory)), reverse=options.sortReverse) elif options.sortCategory == "alpha": return sorted( jobTypes, key=lambda tag: tag.name, reverse=options.sortReverse) elif options.sortCategory == "count": return sorted(jobTypes, key=lambda tag: tag.total_number, reverse=options.sortReverse) def reportPrettyData(root, worker, job, job_types, options): """ print the important bits out. """ out_str = "Batch System: %s\n" % root.batch_system out_str += ("Default Cores: %s Default Memory: %s\n" "Max Cores: %s\n" % ( reportNumber(get(root, "default_cores"), options), reportMemory(get(root, "default_memory"), options, isBytes=True), reportNumber(get(root, "max_cores"), options), )) out_str += ("Total Clock: %s Total Runtime: %s\n" % ( reportTime(get(root, "total_clock"), options), reportTime(get(root, "total_run_time"), options), )) job_types = sortJobs(job_types, options) columnWidths = computeColumnWidths(job_types, worker, job, options) out_str += "Worker\n" out_str += sprintTag("worker", worker, options, columnWidths=columnWidths) out_str += "Job\n" out_str += sprintTag("job", job, options, columnWidths=columnWidths) for t in job_types: out_str += " %s\n" % t.name out_str += sprintTag(t.name, t, options, columnWidths=columnWidths) return out_str def computeColumnWidths(job_types, worker, job, options): """ Return a ColumnWidths() object with the correct max widths. """ cw = ColumnWidths() for t in job_types: updateColumnWidths(t, cw, options) updateColumnWidths(worker, cw, options) updateColumnWidths(job, cw, options) return cw def updateColumnWidths(tag, cw, options): """ Update the column width attributes for this tag's fields. """ longforms = {"med": "median", "ave": "average", "min": "min", "total": "total", "max": "max",} for category in ["time", "clock", "wait", "memory"]: if category in options.categories: for field in ["min", "med", "ave", "max", "total"]: t = getattr(tag, "%s_%s" % (longforms[field], category)) if category in ["time", "clock", "wait"]: s = reportTime(t, options, field=cw.getWidth(category, field)).strip() else: s = reportMemory(t, options, field=cw.getWidth(category, field), isBytes=True).strip() if len(s) >= cw.getWidth(category, field): # this string is larger than max, width must be increased cw.setWidth(category, field, len(s) + 1) def buildElement(element, items, itemName): """ Create an element for output. """ def assertNonnegative(i,name): if i < 0: raise RuntimeError("Negative value %s reported for %s" %(i,name) ) else: return float(i) itemTimes = [] itemClocks = [] itemMemory = [] for item in items: # If something lacks an entry, assume it used none of that thing. # This avoids crashing when jobs e.g. aren't done. itemTimes.append(assertNonnegative(float(item.get("time", 0)), "time")) itemClocks.append(assertNonnegative(float(item.get("clock", 0)), "clock")) itemMemory.append(assertNonnegative(float(item.get("memory", 0)), "memory")) assert len(itemClocks) == len(itemTimes) == len(itemMemory) itemWaits=[] for index in range(0,len(itemTimes)): itemWaits.append(itemTimes[index] - itemClocks[index]) itemWaits.sort() itemTimes.sort() itemClocks.sort() itemMemory.sort() if len(itemTimes) == 0: itemTimes.append(0) itemClocks.append(0) itemWaits.append(0) itemMemory.append(0) element[itemName]=Expando( total_number=float(len(items)), total_time=float(sum(itemTimes)), median_time=float(itemTimes[old_div(len(itemTimes),2)]), average_time=float(old_div(sum(itemTimes),len(itemTimes))), min_time=float(min(itemTimes)), max_time=float(max(itemTimes)), total_clock=float(sum(itemClocks)), median_clock=float(itemClocks[old_div(len(itemClocks),2)]), average_clock=float(old_div(sum(itemClocks),len(itemClocks))), min_clock=float(min(itemClocks)), max_clock=float(max(itemClocks)), total_wait=float(sum(itemWaits)), median_wait=float(itemWaits[old_div(len(itemWaits),2)]), average_wait=float(old_div(sum(itemWaits),len(itemWaits))), min_wait=float(min(itemWaits)), max_wait=float(max(itemWaits)), total_memory=float(sum(itemMemory)), median_memory=float(itemMemory[old_div(len(itemMemory),2)]), average_memory=float(old_div(sum(itemMemory),len(itemMemory))), min_memory=float(min(itemMemory)), max_memory=float(max(itemMemory)), name=itemName ) return element[itemName] def createSummary(element, containingItems, containingItemName, getFn): itemCounts = [len(getFn(containingItem)) for containingItem in containingItems] itemCounts.sort() if len(itemCounts) == 0: itemCounts.append(0) element["median_number_per_%s" % containingItemName] = itemCounts[old_div(len(itemCounts), 2)] element["average_number_per_%s" % containingItemName] = old_div(float(sum(itemCounts)), len(itemCounts)) element["min_number_per_%s" % containingItemName] = min(itemCounts) element["max_number_per_%s" % containingItemName] = max(itemCounts) def getStats(jobStore): """ Collect and return the stats and config data. """ def aggregateStats(fileHandle,aggregateObject): try: stats = json.load(fileHandle, object_hook=Expando) for key in list(stats.keys()): if key in aggregateObject: aggregateObject[key].append(stats[key]) else: aggregateObject[key]=[stats[key]] except ValueError: logger.critical("File %s contains corrupted json. Skipping file." % fileHandle) pass # The file is corrupted. aggregateObject = Expando() callBack = partial(aggregateStats, aggregateObject=aggregateObject) jobStore.readStatsAndLogging(callBack, readAll=True) return aggregateObject def processData(config, stats): """ Collate the stats and report """ if 'total_time' not in stats or 'total_clock' not in stats: # toil job not finished yet stats.total_time = [0.0] stats.total_clock = [0.0] stats.total_time = sum([float(number) for number in stats.total_time]) stats.total_clock = sum([float(number) for number in stats.total_clock]) collatedStatsTag = Expando(total_run_time=stats.total_time, total_clock=stats.total_clock, batch_system=config.batchSystem, default_memory=str(config.defaultMemory), default_cores=str(config.defaultCores), max_cores=str(config.maxCores) ) # Add worker info worker = [_f for _f in getattr(stats, 'workers', []) if _f] jobs = [_f for _f in getattr(stats, 'jobs', []) if _f] jobs = [item for sublist in jobs for item in sublist] def fn4(job): try: return list(jobs) except TypeError: return [] buildElement(collatedStatsTag, worker, "worker") createSummary(buildElement(collatedStatsTag, jobs, "jobs"), getattr(stats, 'workers', []), "worker", fn4) # Get info for each job jobNames = set() for job in jobs: jobNames.add(job.class_name) jobTypesTag = Expando() collatedStatsTag.job_types = jobTypesTag for jobName in jobNames: jobTypes = [ job for job in jobs if job.class_name == jobName ] buildElement(jobTypesTag, jobTypes, jobName) collatedStatsTag.name = "collatedStatsTag" return collatedStatsTag def reportData(tree, options): # Now dump it all out to file if options.raw: out_str = printJson(tree) else: root, worker, job, job_types = refineData(tree, options) out_str = reportPrettyData(root, worker, job, job_types, options) if options.outputFile is not None: fileHandle = open(options.outputFile, "w") fileHandle.write(out_str) fileHandle.close() # Now dump onto the screen print(out_str) def main(): """ Reports stats on the workflow, use with --stats option to toil. """ parser = getBasicOptionParser() initializeOptions(parser) options = parseBasicOptions(parser) checkOptions(options, parser) config = Config() config.setOptions(options) jobStore = Toil.resumeJobStore(config.jobStore) stats = getStats(jobStore) collatedStatsTag = processData(jobStore.config, stats) reportData(collatedStatsTag, options) toil-releases-3.24.0/src/toil/utils/toilStatus.py000066400000000000000000000356501362134276200220120ustar00rootroot00000000000000# Copyright (C) 2015-2016 Regents of the University of California # # 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. """Tool for reporting on job status. """ # python 2/3 compatibility imports from __future__ import absolute_import from __future__ import print_function from six.moves import xrange from past.builtins import map from functools import reduce # standard library import logging import sys import os # toil imports from toil.lib.bioio import getBasicOptionParser from toil.lib.bioio import parseBasicOptions from toil.common import Toil, jobStoreLocatorHelp, Config from toil.jobStores.abstractJobStore import NoSuchJobStoreException, NoSuchFileException from toil.job import JobException from toil.version import version logger = logging.getLogger(__name__) class ToilStatus(): """Tool for reporting on job status.""" def __init__(self, jobStoreName, specifiedJobs=None): self.jobStoreName = jobStoreName self.jobStore = Toil.resumeJobStore(jobStoreName) if specifiedJobs is None: rootJob = self.fetchRootJob() logger.info('Traversing the job graph gathering jobs. This may take a couple of minutes.') self.jobsToReport = self.traverseJobGraph(rootJob) else: self.jobsToReport = self.fetchUserJobs(specifiedJobs) def print_dot_chart(self): """Print a dot output graph representing the workflow.""" print("digraph toil_graph {") print("# This graph was created from job-store: %s" % self.jobStoreName) # Make job IDs to node names map jobsToNodeNames = dict(enumerate(map(lambda job: job.jobStoreID, self.jobsToReport))) # Print the nodes for job in set(self.jobsToReport): print('%s [label="%s %s"];' % ( jobsToNodeNames[job.jobStoreID], job.jobName, job.jobStoreID)) # Print the edges for job in set(self.jobsToReport): for level, jobList in enumerate(job.stack): for childJob in jobList: # Check, b/c successor may be finished / not in the set of jobs if childJob.jobStoreID in jobsToNodeNames: print('%s -> %s [label="%i"];' % ( jobsToNodeNames[job.jobStoreID], jobsToNodeNames[childJob.jobStoreID], level)) print("}") def printJobLog(self): """Takes a list of jobs, finds their log files, and prints them to the terminal.""" for job in self.jobsToReport: if job.logJobStoreFileID is not None: msg = "LOG_FILE_OF_JOB:%s LOG: =======>\n" % job with job.getLogFileHandle(self.jobStore) as fH: msg += fH.read() msg += "<=========" else: msg = "LOG_FILE_OF_JOB:%s LOG: Job has no log file" % job print(msg) def printJobChildren(self): """Takes a list of jobs, and prints their successors.""" for job in self.jobsToReport: children = "CHILDREN_OF_JOB:%s " % job for level, jobList in enumerate(job.stack): for childJob in jobList: children += "\t(CHILD_JOB:%s,PRECEDENCE:%i)" % (childJob, level) print(children) def printAggregateJobStats(self, properties, childNumber): """Prints a job's ID, log file, remaining tries, and other properties.""" for job in self.jobsToReport: lf = lambda x: "%s:%s" % (x, str(x in properties)) print("\t".join(("JOB:%s" % job, "LOG_FILE:%s" % job.logJobStoreFileID, "TRYS_REMAINING:%i" % job.remainingRetryCount, "CHILD_NUMBER:%s" % childNumber, lf("READY_TO_RUN"), lf("IS_ZOMBIE"), lf("HAS_SERVICES"), lf("IS_SERVICE")))) def report_on_jobs(self): """ Gathers information about jobs such as its child jobs and status. :returns jobStats: Pairings of a useful category and a list of jobs which fall into it. :rtype dict: """ hasChildren = [] readyToRun = [] zombies = [] hasLogFile = [] hasServices = [] services = [] properties = set() for job in self.jobsToReport: if job.logJobStoreFileID is not None: hasLogFile.append(job) childNumber = reduce(lambda x, y: x + y, map(len, job.stack) + [0]) if childNumber > 0: # Total number of successors > 0 hasChildren.append(job) properties.add("HAS_CHILDREN") elif job.command is not None: # Job has no children and a command to run. Indicates job could be run. readyToRun.append(job) properties.add("READY_TO_RUN") else: # Job has no successors and no command, so is a zombie job. zombies.append(job) properties.add("IS_ZOMBIE") if job.services: hasServices.append(job) properties.add("HAS_SERVICES") if job.startJobStoreID or job.terminateJobStoreID or job.errorJobStoreID: # These attributes are only set in service jobs services.append(job) properties.add("IS_SERVICE") jobStats = {'hasChildren': hasChildren, 'readyToRun': readyToRun, 'zombies': zombies, 'hasServices': hasServices, 'services': services, 'hasLogFile': hasLogFile, 'properties': properties, 'childNumber': childNumber} return jobStats @staticmethod def getPIDStatus(jobStoreName): """ Determine the status of a process with a particular pid. Checks to see if a process exists or not. :return: A string indicating the status of the PID of the workflow as stored in the jobstore. :rtype: str """ try: jobstore = Toil.resumeJobStore(jobStoreName) except NoSuchJobStoreException: return 'QUEUED' except NoSuchFileException: return 'QUEUED' try: with jobstore.readSharedFileStream('pid.log') as pidFile: pid = int(pidFile.read()) try: os.kill(pid, 0) # Does not kill process when 0 is passed. except OSError: # Process not found, must be done. return 'COMPLETED' else: return 'RUNNING' except NoSuchFileException: pass return 'QUEUED' @staticmethod def getStatus(jobStoreName): """ Determine the status of a workflow. If the jobstore does not exist, this returns 'QUEUED', assuming it has not been created yet. Checks for the existence of files created in the toil.Leader.run(). In toil.Leader.run(), if a workflow completes with failed jobs, 'failed.log' is created, otherwise 'succeeded.log' is written. If neither of these exist, the leader is still running jobs. :return: A string indicating the status of the workflow. ['COMPLETED', 'RUNNING', 'ERROR', 'QUEUED'] :rtype: str """ try: jobstore = Toil.resumeJobStore(jobStoreName) except NoSuchJobStoreException: return 'QUEUED' except NoSuchFileException: return 'QUEUED' try: with jobstore.readSharedFileStream('succeeded.log') as successful: pass return 'COMPLETED' except NoSuchFileException: try: with jobstore.readSharedFileStream('failed.log') as failed: pass return 'ERROR' except NoSuchFileException: pass return 'RUNNING' def fetchRootJob(self): """ Fetches the root job from the jobStore that provides context for all other jobs. Exactly the same as the jobStore.loadRootJob() function, but with a different exit message if the root job is not found (indicating the workflow ran successfully to completion and certain stats cannot be gathered from it meaningfully such as which jobs are left to run). :raises JobException: if the root job does not exist. """ try: return self.jobStore.loadRootJob() except JobException: print('Root job is absent. The workflow has may have completed successfully.', file=sys.stderr) raise def fetchUserJobs(self, jobs): """ Takes a user input array of jobs, verifies that they are in the jobStore and returns the array of jobsToReport. :param list jobs: A list of jobs to be verified. :returns jobsToReport: A list of jobs which are verified to be in the jobStore. """ jobsToReport = [] for jobID in jobs: try: jobsToReport.append(self.jobStore.load(jobID)) except JobException: print('The job %s could not be found.' % jobID, file=sys.stderr) raise return jobsToReport def traverseJobGraph(self, rootJob, jobsToReport=None, foundJobStoreIDs=None): """ Find all current jobs in the jobStore and return them as an Array. :param jobNode rootJob: The root job of the workflow. :param list jobsToReport: A list of jobNodes to be added to and returned. :param set foundJobStoreIDs: A set of jobStoreIDs used to keep track of jobStoreIDs encountered in traversal. :returns jobsToReport: The list of jobs currently in the job graph. """ if jobsToReport is None: jobsToReport = [] if foundJobStoreIDs is None: foundJobStoreIDs = set() if rootJob.jobStoreID in foundJobStoreIDs: return jobsToReport foundJobStoreIDs.add(rootJob.jobStoreID) jobsToReport.append(rootJob) # Traverse jobs in stack for jobs in rootJob.stack: for successorJobStoreID in [x.jobStoreID for x in jobs]: if successorJobStoreID not in foundJobStoreIDs and self.jobStore.exists(successorJobStoreID): self.traverseJobGraph(self.jobStore.load(successorJobStoreID), jobsToReport, foundJobStoreIDs) # Traverse service jobs for jobs in rootJob.services: for serviceJobStoreID in [x.jobStoreID for x in jobs]: if self.jobStore.exists(serviceJobStoreID): if serviceJobStoreID in foundJobStoreIDs: raise RuntimeError('Service job was unexpectedly found while traversing ') foundJobStoreIDs.add(serviceJobStoreID) jobsToReport.append(self.jobStore.load(serviceJobStoreID)) return jobsToReport def main(): """Reports the state of a Toil workflow.""" parser = getBasicOptionParser() parser.add_argument("jobStore", type=str, help="The location of a job store that holds the information about the " "workflow whose status is to be reported on." + jobStoreLocatorHelp) parser.add_argument("--failIfNotComplete", action="store_true", help="Return exit value of 1 if toil jobs not all completed. default=%(default)s", default=False) parser.add_argument("--noAggStats", dest="stats", action="store_false", help="Do not print overall, aggregate status of workflow.", default=True) parser.add_argument("--printDot", action="store_true", help="Print dot formatted description of the graph. If using --jobs will " "restrict to subgraph including only those jobs. default=%(default)s", default=False) parser.add_argument("--jobs", nargs='+', help="Restrict reporting to the following jobs (allows subsetting of the report).", default=None) parser.add_argument("--printPerJobStats", action="store_true", help="Print info about each job. default=%(default)s", default=False) parser.add_argument("--printLogs", action="store_true", help="Print the log files of jobs (if they exist). default=%(default)s", default=False) parser.add_argument("--printChildren", action="store_true", help="Print children of each job. default=%(default)s", default=False) parser.add_argument("--version", action='version', version=version) options = parseBasicOptions(parser) if len(sys.argv) == 1: parser.print_help() sys.exit(0) config = Config() config.setOptions(options) try: status = ToilStatus(config.jobStore, options.jobs) except NoSuchJobStoreException: print('No job store found.') return except JobException: # Workflow likely complete, user informed in ToilStatus() return jobStats = status.report_on_jobs() # Info to be reported. hasChildren = jobStats['hasChildren'] readyToRun = jobStats['readyToRun'] zombies = jobStats['zombies'] hasServices = jobStats['hasServices'] services = jobStats['services'] hasLogFile = jobStats['hasLogFile'] properties = jobStats['properties'] childNumber = jobStats['childNumber'] if options.printPerJobStats: status.printAggregateJobStats(properties, childNumber) if options.printLogs: status.printJobLog() if options.printChildren: status.printJobChildren() if options.printDot: status.print_dot_chart() if options.stats: print('Of the %i jobs considered, ' 'there are %i jobs with children, ' '%i jobs ready to run, ' '%i zombie jobs, ' '%i jobs with services, ' '%i services, ' 'and %i jobs with log files currently in %s.' % (len(status.jobsToReport), len(hasChildren), len(readyToRun), len(zombies), len(hasServices), len(services), len(hasLogFile), status.jobStore)) if len(status.jobsToReport) > 0 and options.failIfNotComplete: # Upon workflow completion, all jobs will have been removed from job store exit(1) toil-releases-3.24.0/src/toil/utils/toilUpdateEC2Instances.py000066400000000000000000000024571362134276200241120ustar00rootroot00000000000000# Copyright (C) 2015-2016 Regents of the University of California # # 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. """ Updates Toil's internal list of EC2 instance types. """ from __future__ import absolute_import import logging import socket from toil.lib.ec2nodes import updateStaticEC2Instances logger = logging.getLogger( __name__ ) def internetConnection(): """ Returns True if there is an internet connection present, and False otherwise. :return: """ try: socket.create_connection(("www.stackoverflow.com", 80)) return True except OSError: pass return False def main(): if not internetConnection(): raise RuntimeError('No internet. Updating the EC2 Instance list requires internet.') updateStaticEC2Instances() if __name__=="__main__": main() toil-releases-3.24.0/src/toil/wdl/000077500000000000000000000000001362134276200167025ustar00rootroot00000000000000toil-releases-3.24.0/src/toil/wdl/__init__.py000066400000000000000000000000001362134276200210010ustar00rootroot00000000000000toil-releases-3.24.0/src/toil/wdl/toilwdl.py000066400000000000000000000151741362134276200207420ustar00rootroot00000000000000# Copyright (C) 2018 UCSC Computational Genomics Lab # # 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. from __future__ import absolute_import from __future__ import print_function from __future__ import division import argparse import os import logging import sys from toil import subprocess from toil.wdl.wdl_analysis import AnalyzeWDL from toil.wdl.wdl_synthesis import SynthesizeWDL, write_AST import toil.wdl.wdl_parser as wdl_parser wdllogger = logging.getLogger(__name__) def main(): ''' A program to run WDL input files using native Toil scripts. Calls two files, described below, wdl_analysis.py and wdl_synthesis.py: wdl_analysis reads the wdl, json, and extraneous files and restructures them into 2 intermediate data structures before writing (python dictionaries): "wf_dictionary": containing the parsed workflow information. "tasks_dictionary": containing the parsed task information. wdl_synthesis takes the "wf_dictionary" and "tasks_dictionary" and uses them to write a native python script for use with Toil. Requires a WDL file, and a JSON file. The WDL file contains ordered commands, and the JSON file contains input values for those commands. To run in Toil, these two files must be parsed, restructured into python dictionaries, and then compiled into a Toil formatted python script. This compiled Toil script is deleted after running unless the user specifies: "--dont_delete_compiled" as an option. The WDL parser was auto-generated from the Broad's current WDL grammar file: https://github.com/openwdl/wdl/blob/master/parsers/grammar.hgr using Scott Frazer's Hermes: https://github.com/scottfrazer/hermes Thank you Scott Frazer! Currently in alpha testing, and known to work with the Broad's GATK tutorial set for WDL on their main wdl site: software.broadinstitute.org/wdl/documentation/topic?name=wdl-tutorials And ENCODE's WDL workflow: github.com/ENCODE-DCC/pipeline-container/blob/master/local-workflows/encode_mapping_workflow.wdl Additional support to be broadened to include more features soon. ''' parser = argparse.ArgumentParser(description='Runs WDL files with toil.') parser.add_argument('wdl_file', help='A WDL workflow file.') parser.add_argument('secondary_file', help='A secondary data file (json).') parser.add_argument("--jobStore", type=str, required=False, default=None) parser.add_argument('-o', '--outdir', required=False, default=os.getcwd(), help='Optionally specify the directory that outputs ' 'are written to. Default is the current working dir.') parser.add_argument('--dev_mode', required=False, default=False, help='1. Creates "AST.out", which holds the printed AST and ' '"mappings.out", which holds the parsed task, workflow ' 'dictionaries that were generated. ' '2. Saves the compiled toil script generated from the ' 'wdl/json files from deletion. ' '3. Skips autorunning the compiled python file.') parser.add_argument('--docker_user', required=False, default='root', help='The user permissions that the docker containers will be run ' 'with (and the permissions set on any output files produced). ' 'Default is "root". Setting this to None will set this to ' 'the current user.') parser.add_argument("--destBucket", type=str, required=False, default=False, help="Specify a cloud bucket endpoint for output files.") # wdl_run_args is an array containing all of the unknown arguments not # specified by the parser in this main. All of these will be passed down in # check_call later to run the compiled toil file. args, wdl_run_args = parser.parse_known_args() wdl_file_path = os.path.abspath(args.wdl_file) args.secondary_file = os.path.abspath(args.secondary_file) args.outdir = os.path.abspath(args.outdir) if args.dev_mode: write_AST(wdl_file_path, args.outdir) aWDL = AnalyzeWDL(wdl_file_path, args.secondary_file, args.outdir) # read secondary file; create dictionary to hold variables if args.secondary_file.endswith('.json'): aWDL.dict_from_JSON(args.secondary_file) elif args.secondary_file.endswith('.yml') or args.secondary_file.endswith('.yaml'): aWDL.dict_from_YML(args.secondary_file) # json only atm else: raise RuntimeError('Unsupported Secondary File Type. Use json.') # parse the wdl AST into 2 dictionaries with open(wdl_file_path, 'r') as wdl: wdl_string = wdl.read() ast = wdl_parser.parse(wdl_string).ast() aWDL.create_tasks_dict(ast) aWDL.create_workflows_dict(ast) sWDL = SynthesizeWDL(aWDL.tasks_dictionary, aWDL.workflows_dictionary, args.outdir, aWDL.json_dict, args.docker_user, args.jobStore, args.destBucket) # use the AST dictionaries to write 4 strings # these are the future 4 sections of the compiled toil python file module_section = sWDL.write_modules() fn_section = sWDL.write_functions() main_section = sWDL.write_main() # write 3 strings to a python output file sWDL.write_python_file(module_section, fn_section, main_section, sWDL.output_file) if args.dev_mode: wdllogger.debug('WDL file compiled to toil script.') sWDL.write_mappings(aWDL) else: wdllogger.debug('WDL file compiled to toil script. Running now.') exe = sys.executable if sys.executable else 'python' cmd = [exe, sWDL.output_file] cmd.extend(wdl_run_args) subprocess.check_call(cmd) os.remove(sWDL.output_file) if __name__ == '__main__': main() toil-releases-3.24.0/src/toil/wdl/wdl_analysis.py000066400000000000000000001313141362134276200217500ustar00rootroot00000000000000# Copyright (C) 2018 UCSC Computational Genomics Lab # # 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. from __future__ import absolute_import from __future__ import print_function from __future__ import division from past.builtins import basestring import json import os import logging from collections import OrderedDict import toil.wdl.wdl_parser as wdl_parser wdllogger = logging.getLogger(__name__) class AnalyzeWDL: ''' Analyzes a wdl file, and associated json and/or extraneous files and restructures them into 2 intermediate data structures (python dictionaries): "workflows_dictionary": containing the parsed workflow information. "tasks_dictionary": containing the parsed task information. These are then fed into wdl_synthesis.py which uses them to write a native python script for use with Toil. Requires a WDL file, and a JSON file. The WDL file contains ordered commands, and the JSON file contains input values for those commands. In addition, this also takes potential accessory files like csv/tsv potentially also containing variables which need to be incorporated. ''' def __init__(self, wdl_filename, secondary_filename, output_directory): # inputs self.wdl_file = wdl_filename self.secondary_file = secondary_filename self.output_directory = output_directory if not os.path.exists(self.output_directory): try: os.makedirs(self.output_directory) except: raise OSError( 'Could not create directory. Insufficient permissions or disk space most likely.') self.output_file = os.path.join(self.output_directory, 'toilwdl_compiled.py') # only json is required; tsv/csv are optional self.json_dict = {} # holds task skeletons from WDL task objects self.tasks_dictionary = OrderedDict() # holds workflow structure from WDL workflow objects self.workflows_dictionary = OrderedDict() # unique iterator to add to cmd names self.command_number = 0 # unique iterator to add to call names self.call_number = 0 # unique iterator to add to scatter names self.scatter_number = 0 # unique iterator to add to if names self.if_number = 0 def find_asts(self, ast_root, name): ''' Finds an AST node with the given name and the entire subtree under it. A function borrowed from scottfrazer. Thank you Scott Frazer! :param ast_root: The WDL AST. The whole thing generally, but really any portion that you wish to search. :param name: The name of the subtree you're looking for, like "Task". :return: nodes representing the AST subtrees matching the "name" given. ''' nodes = [] if isinstance(ast_root, wdl_parser.AstList): for node in ast_root: nodes.extend(self.find_asts(node, name)) elif isinstance(ast_root, wdl_parser.Ast): if ast_root.name == name: nodes.append(ast_root) for attr_name, attr in ast_root.attributes.items(): nodes.extend(self.find_asts(attr, name)) return nodes def dict_from_YML(self, YML_file): ''' Not written yet. Use JSON. It's better anyway. :param YML_file: A yml file with extension '*.yml' or '*.yaml'. :return: Nothing. ''' raise NotImplementedError('.y(a)ml support is currently underwhelming.') def dict_from_JSON(self, JSON_file): ''' Takes a WDL-mapped json file and creates a dict containing the bindings. The 'return' value is only used for unittests. :param JSON_file: A required JSON file containing WDL variable bindings. :return: Returns the self.json_dict purely for unittests. ''' # TODO: Add context support for variables within multiple wdl files with open(JSON_file) as data_file: data = json.load(data_file) for d in data: if isinstance(data[d], basestring): self.json_dict[d] = '"' + data[d] + '"' else: self.json_dict[d] = data[d] return self.json_dict def create_tasks_dict(self, ast): ''' Parse each "Task" in the AST. This will create self.tasks_dictionary, where each task name is a key. :return: Creates the self.tasks_dictionary necessary for much of the parser. Returning it is only necessary for unittests. ''' tasks = self.find_asts(ast, 'Task') for task in tasks: self.parse_task(task) return self.tasks_dictionary def parse_task(self, task): ''' Parses a WDL task AST subtree. Currently looks at and parses 4 sections: 1. Declarations (e.g. string x = 'helloworld') 2. Commandline (a bash command with dynamic variables inserted) 3. Runtime (docker image; disk; CPU; RAM; etc.) 4. Outputs (expected return values/files) :param task: An AST subtree of a WDL "Task". :return: Returns nothing but adds a task to the self.tasks_dictionary necessary for much of the parser. ''' task_name = task.attributes["name"].source_string # task declarations declaration_array = [] for declaration_subAST in task.attr("declarations"): declaration_array.append(self.parse_task_declaration(declaration_subAST)) self.tasks_dictionary.setdefault(task_name, OrderedDict())['inputs'] = declaration_array for section in task.attr("sections"): # task commandline entries section [command(s) to run] if section.name == "RawCommand": command_array = self.parse_task_rawcommand(section) self.tasks_dictionary.setdefault(task_name, OrderedDict())['raw_commandline'] = command_array # task runtime section (docker image; disk; CPU; RAM; etc.) if section.name == "Runtime": runtime_dict = self.parse_task_runtime(section.attr("map")) self.tasks_dictionary.setdefault(task_name, OrderedDict())['runtime'] = runtime_dict # task output filenames section (expected return values/files) if section.name == "Outputs": output_array = self.parse_task_outputs(section) self.tasks_dictionary.setdefault(task_name, OrderedDict())['outputs'] = output_array def parse_task_declaration(self, declaration_subAST): ''' Parses the declaration section of the WDL task AST subtree. Examples: String my_name String your_name Int two_chains_i_mean_names = 0 :param declaration_subAST: Some subAST representing a task declaration like: 'String file_name' :return: var_name, var_type, var_value Example: Input subAST representing: 'String file_name' Output: var_name='file_name', var_type='String', var_value=None ''' var_name = self.parse_declaration_name(declaration_subAST.attr("name")) var_type = self.parse_declaration_type(declaration_subAST.attr("type")) var_expressn = self.parse_declaration_expressn(declaration_subAST.attr("expression"), es='') return (var_name, var_type, var_expressn) def parse_task_rawcommand_attributes(self, code_snippet): """ :param code_snippet: :return: """ attr_dict = OrderedDict() if isinstance(code_snippet, wdl_parser.Terminal): raise NotImplementedError if isinstance(code_snippet, wdl_parser.Ast): raise NotImplementedError if isinstance(code_snippet, wdl_parser.AstList): for ast in code_snippet: if ast.name == 'CommandParameterAttr': # TODO rewrite if ast.attributes['value'].str == 'string': attr_dict[ast.attributes['key'].source_string] = "'" + ast.attributes['value'].source_string + "'" else: attr_dict[ast.attributes['key'].source_string] = ast.attributes['value'].source_string return attr_dict def parse_task_rawcommand(self, rawcommand_subAST): ''' Parses the rawcommand section of the WDL task AST subtree. Task "rawcommands" are divided into many parts. There are 2 types of parts: normal strings, & variables that can serve as changeable inputs. The following example command: 'echo ${variable1} ${variable2} > output_file.txt' Has 5 parts: Normal String: 'echo ' Variable Input: variable1 Normal String: ' ' Variable Input: variable2 Normal String: ' > output_file.txt' Variables can also have additional conditions, like 'sep', which is like the python ''.join() function and in WDL looks like: ${sep=" -V " GVCFs} and would be translated as: ' -V '.join(GVCFs). :param rawcommand_subAST: A subAST representing some bash command. :return: A list=[] of tuples=() representing the parts of the command: e.g. [(command_var, command_type, additional_conditions_list), ...] Where: command_var = 'GVCFs' command_type = 'variable' command_actions = {'sep': ' -V '} ''' command_array = [] for code_snippet in rawcommand_subAST.attributes["parts"]: # normal string if isinstance(code_snippet, wdl_parser.Terminal): command_var = "r'''" + code_snippet.source_string + "'''" # a variable like ${dinosaurDNA} if isinstance(code_snippet, wdl_parser.Ast): if code_snippet.name == 'CommandParameter': # change in the future? seems to be a different parameter but works for all cases it seems? code_expr = self.parse_declaration_expressn(code_snippet.attr('expr'), es='') code_attributes = self.parse_task_rawcommand_attributes(code_snippet.attr('attributes')) command_var = self.modify_cmd_expr_w_attributes(code_expr, code_attributes) if isinstance(code_snippet, wdl_parser.AstList): raise NotImplementedError command_array.append(command_var) return command_array def modify_cmd_expr_w_attributes(self, code_expr, code_attr): """ :param code_expr: :param code_attr: :return: """ for param in code_attr: if param == 'sep': code_expr = "{sep}.join(str(x) for x in {expr})".format(sep=code_attr[param], expr=code_expr) elif param == 'default': code_expr = "{expr} if {expr} else {default}".format(default=code_attr[param], expr=code_expr) else: raise NotImplementedError return code_expr def parse_task_runtime_key(self, i): """ :param runtime_subAST: :return: """ if isinstance(i, wdl_parser.Terminal): return i.source_string if isinstance(i, wdl_parser.Ast): raise NotImplementedError if isinstance(i, wdl_parser.AstList): raise NotImplementedError def parse_task_runtime(self, runtime_subAST): ''' Parses the runtime section of the WDL task AST subtree. The task "runtime" section currently supports context fields for a docker container, CPU resources, RAM resources, and disk resources. :param runtime_subAST: A subAST representing runtime parameters. :return: A list=[] of runtime attributes, for example: runtime_attributes = [('docker','quay.io/encode-dcc/map:v1.0'), ('cpu','2'), ('memory','17.1 GB'), ('disks','local-disk 420 HDD')] ''' runtime_attributes = OrderedDict() if isinstance(runtime_subAST, wdl_parser.Terminal): raise NotImplementedError elif isinstance(runtime_subAST, wdl_parser.Ast): raise NotImplementedError elif isinstance(runtime_subAST, wdl_parser.AstList): for ast in runtime_subAST: key = self.parse_task_runtime_key(ast.attr('key')) value = self.parse_declaration_expressn(ast.attr('value'), es='') if value.startswith('"'): value = self.translate_wdl_string_to_python_string(value[1:-1]) runtime_attributes[key] = value return runtime_attributes def parse_task_outputs(self, i): ''' Parse the WDL output section. Outputs are like declarations, with a type, name, and value. Examples: ------------ Simple Cases ------------ 'Int num = 7' var_name: 'num' var_type: 'Int' var_value: 7 String idea = 'Lab grown golden eagle burgers.' var_name: 'idea' var_type: 'String' var_value: 'Lab grown golden eagle burgers.' File ideaFile = 'goldenEagleStemCellStartUpDisrupt.txt' var_name: 'ideaFile' var_type: 'File' var_value: 'goldenEagleStemCellStartUpDisrupt.txt' ------------------- More Abstract Cases ------------------- Array[File] allOfMyTerribleIdeas = glob(*.txt)[0] var_name: 'allOfMyTerribleIdeas' var_type**: 'File' var_value: [*.txt] var_actions: {'index_lookup': '0', 'glob': 'None'} **toilwdl.py converts 'Array[File]' to 'ArrayFile' :return: output_array representing outputs generated by the job/task: e.g. x = [(var_name, var_type, var_value, var_actions), ...] ''' output_array = [] for j in i.attributes['attributes']: if j.name == 'Output': var_name = self.parse_declaration_name(j.attr("name")) var_type = self.parse_declaration_type(j.attr("type")) var_expressn = self.parse_declaration_expressn(j.attr("expression"), es='', output_expressn=True) if not (var_expressn.startswith('(') and var_expressn.endswith(')')): var_expressn = self.translate_wdl_string_to_python_string(var_expressn) output_array.append((var_name, var_type, var_expressn)) else: raise NotImplementedError return output_array def translate_wdl_string_to_python_string(self, some_string): ''' Parses a string representing a given job's output filename into something python can read. Replaces ${string}'s with normal variables and the rest with normal strings all concatenated with ' + '. Will not work with additional parameters, such as: ${default="foo" bar} or ${true="foo" false="bar" Boolean baz} This method expects to be passed only strings with some combination of "${abc}" and "abc" blocks. :param job: A list such that: (job priority #, job ID #, Job Skeleton Name, Job Alias) :param some_string: e.g. '${sampleName}.vcf' :return: output_string, e.g. 'sampleName + ".vcf"' ''' try: # add support for 'sep' output_string = '' edited_string = some_string.strip() if edited_string.find('${') != -1: continue_loop = True while (continue_loop): index_start = edited_string.find('${') index_end = edited_string.find('}', index_start) stringword = edited_string[:index_start] if index_start != 0: output_string = output_string + "'" + stringword + "' + " keyword = edited_string[index_start + 2:index_end] output_string = output_string + "str(" + keyword + ") + " edited_string = edited_string[index_end + 1:] if edited_string.find('${') == -1: continue_loop = False if edited_string: output_string = output_string + "'" + edited_string + "' + " else: output_string = "'" + edited_string + "'" if output_string.endswith(' + '): output_string = output_string[:-3] return output_string except: return '' def create_workflows_dict(self, ast): ''' Parse each "Workflow" in the AST. This will create self.workflows_dictionary, where each called job is a tuple key of the form: (priority#, job#, name, alias). :return: Creates the self.workflows_dictionary necessary for much of the parser. Returning it is only necessary for unittests. ''' workflows = self.find_asts(ast, 'Workflow') for workflow in workflows: self.parse_workflow(workflow) return self.workflows_dictionary def parse_workflow(self, workflow): ''' Parses a WDL workflow AST subtree. Currently looks at and parses 3 sections: 1. Declarations (e.g. string x = 'helloworld') 2. Calls (similar to a python def) 3. Scatter (which expects to map to a Call or multiple Calls) Returns nothing but creates the self.workflows_dictionary necessary for much of the parser. :param workflow: An AST subtree of a WDL "Workflow". :return: Returns nothing but adds a workflow to the self.workflows_dictionary necessary for much of the parser. ''' workflow_name = workflow.attr('name').source_string wf_declared_dict = OrderedDict() for section in workflow.attr("body"): if section.name == "Declaration": var_name, var_map = self.parse_workflow_declaration(section) wf_declared_dict[var_name] = var_map self.workflows_dictionary.setdefault(workflow_name, OrderedDict())['wf_declarations'] = wf_declared_dict if section.name == "Scatter": scattertask = self.parse_workflow_scatter(section) self.workflows_dictionary.setdefault(workflow_name, OrderedDict())['scatter' + str(self.scatter_number)] = scattertask self.scatter_number += 1 if section.name == "Call": task = self.parse_workflow_call(section) self.workflows_dictionary.setdefault(workflow_name, OrderedDict())['call' + str(self.call_number)] = task self.call_number += 1 if section.name == "If": task = self.parse_workflow_if(section) self.workflows_dictionary.setdefault(workflow_name, OrderedDict())['if' + str(self.if_number)] = task self.if_number += 1 def parse_workflow_if(self, ifAST): expression = self.parse_workflow_if_expression(ifAST.attr('expression')) body = self.parse_workflow_if_body(ifAST.attr('body')) return {'expression': expression, 'body': body} def parse_workflow_if_body(self, i): subworkflow_dict = OrderedDict() wf_declared_dict = OrderedDict() if isinstance(i, wdl_parser.Terminal): raise NotImplementedError elif isinstance(i, wdl_parser.Ast): raise NotImplementedError elif isinstance(i, wdl_parser.AstList): for ast in i: if ast.name == "Declaration": var_name, var_map = self.parse_workflow_declaration(ast) wf_declared_dict[var_name] = var_map subworkflow_dict['wf_declarations'] = wf_declared_dict if ast.name == "Scatter": scattertask = self.parse_workflow_scatter(ast) subworkflow_dict['scatter' + str(self.scatter_number)] = scattertask self.scatter_number += 1 if ast.name == "Call": task = self.parse_workflow_call(ast) subworkflow_dict['call' + str(self.call_number)] = task self.call_number += 1 if ast.name == "If": task = self.parse_workflow_if(ast) subworkflow_dict['if' + str(self.if_number)] = task self.if_number += 1 return subworkflow_dict def parse_workflow_if_expression(self, i): if isinstance(i, wdl_parser.Terminal): ifthis = i.source_string elif isinstance(i, wdl_parser.Ast): ifthis = self.parse_declaration_expressn(i, es='') elif isinstance(i, wdl_parser.AstList): raise NotImplementedError return ifthis def parse_workflow_scatter(self, scatterAST): item = self.parse_workflow_scatter_item(scatterAST.attr('item')) collection = self.parse_workflow_scatter_collection(scatterAST.attr('collection')) body = self.parse_workflow_scatter_body(scatterAST.attr('body')) return {'item': item, 'collection': collection, 'body': body} def parse_workflow_scatter_item(self, i): if isinstance(i, wdl_parser.Terminal): return i.source_string elif isinstance(i, wdl_parser.Ast): raise NotImplementedError elif isinstance(i, wdl_parser.AstList): raise NotImplementedError def parse_workflow_scatter_collection(self, i): if isinstance(i, wdl_parser.Terminal): return i.source_string elif isinstance(i, wdl_parser.Ast): return self.parse_declaration_expressn(i, es='') elif isinstance(i, wdl_parser.AstList): raise NotImplementedError def parse_workflow_scatter_body(self, i): if isinstance(i, wdl_parser.Terminal): raise NotImplementedError elif isinstance(i, wdl_parser.Ast): raise NotImplementedError elif isinstance(i, wdl_parser.AstList): scatterbody = OrderedDict() element = 0 for ast in i: if ast.name == "Declaration": var_name, var_map = self.parse_workflow_declaration(ast) scatterbody['variable' + str(element)] = var_map element += 1 if ast.name == "Scatter": scattertask = self.parse_workflow_scatter(ast) scatterbody['scatter' + str(self.scatter_number)] = scattertask self.scatter_number += 1 # TODO test this raise NotImplementedError if ast.name == "Call": task = self.parse_workflow_call(ast) scatterbody['call' + str(self.call_number)] = task self.call_number += 1 if ast.name == "If": task = self.parse_workflow_if(ast) scatterbody['if' + str(self.if_number)] = task self.if_number += 1 return scatterbody def parse_declaration_name(self, nameAST): """ Required. Nothing fancy here. Just the name of the workflow function. For example: "rnaseqexample" would be the following wdl workflow's name: workflow rnaseqexample {File y; call a {inputs: y}; call b;} task a {File y} task b {command{"echo 'ATCG'"}} :param nameAST: :return: """ if isinstance(nameAST, wdl_parser.Terminal): return nameAST.source_string elif isinstance(nameAST, wdl_parser.Ast): return nameAST.source_string elif isinstance(nameAST, wdl_parser.AstList): raise NotImplementedError def parse_declaration_type(self, typeAST): """ Required. Currently supported: Types are: Boolean, Float, Int, File, String, and Array[subtype]. OptionalTypes are: Boolean?, Float?, Int?, File?, String?, and Array[subtype]?. Python is not typed, so we don't need typing except to identify type: "File", which Toil needs to import, so we recursively travel down to the innermost type which will tell us if the variables are files that need importing. :param typeAST: :return: """ if isinstance(typeAST, wdl_parser.Terminal): return typeAST.source_string elif isinstance(typeAST, wdl_parser.Ast): if typeAST.name == 'Type': return self.parse_declaration_type(typeAST.attr('subtype')) elif typeAST.name == 'OptionalType': return self.parse_declaration_type(typeAST.attr('innerType')) else: raise NotImplementedError elif isinstance(typeAST, wdl_parser.AstList): for ast in typeAST: # TODO only ever seen one element lists. return self.parse_declaration_type(ast) def parse_declaration_expressn(self, expressionAST, es, output_expressn=False): """ Expressions are optional. Workflow declaration valid examples: File x or File x = '/x/x.tmp' :param expressionAST: :return: """ if not expressionAST: return None else: if isinstance(expressionAST, wdl_parser.Terminal): if expressionAST.str == 'boolean': if expressionAST.source_string == 'false': return 'False' elif expressionAST.source_string == 'true': return 'True' else: raise TypeError('Parsed boolean ({}) must be expressed as "true" or "false".' ''.format(expressionAST.source_string)) elif expressionAST.str == 'string' and not output_expressn: parsed_string = self.translate_wdl_string_to_python_string(expressionAST.source_string) return '{string}'.format(string=parsed_string) else: return '{string}'.format(string=expressionAST.source_string) elif isinstance(expressionAST, wdl_parser.Ast): if expressionAST.name == 'Add': es = es + self.parse_declaration_expressn_operator(expressionAST.attr('lhs'), expressionAST.attr('rhs'), es, operator=' + ') elif expressionAST.name == 'Subtract': es = es + self.parse_declaration_expressn_operator(expressionAST.attr('lhs'), expressionAST.attr('rhs'), es, operator=' - ') elif expressionAST.name == 'Multiply': es = es + self.parse_declaration_expressn_operator(expressionAST.attr('lhs'), expressionAST.attr('rhs'), es, operator=' * ') elif expressionAST.name == 'Divide': es = es + self.parse_declaration_expressn_operator(expressionAST.attr('lhs'), expressionAST.attr('rhs'), es, operator=' / ') elif expressionAST.name == 'GreaterThan': es = es + self.parse_declaration_expressn_operator(expressionAST.attr('lhs'), expressionAST.attr('rhs'), es, operator=' > ') elif expressionAST.name == 'LessThan': es = es + self.parse_declaration_expressn_operator(expressionAST.attr('lhs'), expressionAST.attr('rhs'), es, operator=' < ') elif expressionAST.name == 'FunctionCall': es = es + self.parse_declaration_expressn_fncall(expressionAST.attr('name'), expressionAST.attr('params'), es) elif expressionAST.name == 'TernaryIf': es = es + self.parse_declaration_expressn_ternaryif(expressionAST.attr('cond'), expressionAST.attr('iftrue'), expressionAST.attr('iffalse'), es) elif expressionAST.name == 'MemberAccess': es = es + self.parse_declaration_expressn_memberaccess(expressionAST.attr('lhs'), expressionAST.attr('rhs'), es) elif expressionAST.name == 'ArrayLiteral': es = es + self.parse_declaration_expressn_arrayliteral(expressionAST.attr('values'), es) elif expressionAST.name == 'TupleLiteral': es = es + self.parse_declaration_expressn_tupleliteral(expressionAST.attr('values'), es) elif expressionAST.name == 'ArrayOrMapLookup': es = es + self.parse_declaration_expressn_arraymaplookup(expressionAST.attr('lhs'), expressionAST.attr('rhs'), es) elif expressionAST.name == 'LogicalNot': es = es + self.parse_declaration_expressn_logicalnot(expressionAST.attr('expression'), es) else: raise NotImplementedError elif isinstance(expressionAST, wdl_parser.AstList): raise NotImplementedError return '(' + es + ')' def parse_declaration_expressn_logicalnot(self, exprssn, es): if isinstance(exprssn, wdl_parser.Terminal): es = es + exprssn.source_string elif isinstance(exprssn, wdl_parser.Ast): es = es + self.parse_declaration_expressn(exprssn, es='') elif isinstance(exprssn, wdl_parser.AstList): raise NotImplementedError return ' not ' + es def parse_declaration_expressn_arraymaplookup(self, lhsAST, rhsAST, es): """ :param lhsAST: :param rhsAST: :param es: :return: """ if isinstance(lhsAST, wdl_parser.Terminal): es = es + lhsAST.source_string elif isinstance(lhsAST, wdl_parser.Ast): # parenthesis must be removed because 'i[0]' works, but '(i)[0]' does not es = es + self.parse_declaration_expressn(lhsAST, es='')[1:-1] elif isinstance(lhsAST, wdl_parser.AstList): raise NotImplementedError if isinstance(rhsAST, wdl_parser.Terminal): indexnum = rhsAST.source_string elif isinstance(rhsAST, wdl_parser.Ast): raise NotImplementedError elif isinstance(rhsAST, wdl_parser.AstList): raise NotImplementedError return es + '[{index}]'.format(index=indexnum) def parse_declaration_expressn_memberaccess(self, lhsAST, rhsAST, es): """ Instead of "Class.variablename", use "Class.rv('variablename')". :param lhsAST: :param rhsAST: :param es: :return: """ if isinstance(lhsAST, wdl_parser.Terminal): es = es + lhsAST.source_string elif isinstance(lhsAST, wdl_parser.Ast): raise NotImplementedError elif isinstance(lhsAST, wdl_parser.AstList): raise NotImplementedError es = es + '_' if isinstance(rhsAST, wdl_parser.Terminal): es = es + rhsAST.source_string elif isinstance(rhsAST, wdl_parser.Ast): raise NotImplementedError elif isinstance(rhsAST, wdl_parser.AstList): raise NotImplementedError return es def parse_declaration_expressn_ternaryif(self, cond, iftrue, iffalse, es): """ Classic if statement. This needs to be rearranged. In wdl, this looks like: if then else In python, this needs to be: if else :param cond: :param iftrue: :param iffalse: :param es: :return: """ es = es + self.parse_declaration_expressn(iftrue, es='') es = es + ' if ' + self.parse_declaration_expressn(cond, es='') es = es + ' else ' + self.parse_declaration_expressn(iffalse, es='') return es def parse_declaration_expressn_tupleliteral(self, values, es): """ Same in python. Just a parenthesis enclosed tuple. :param values: :param es: :return: """ es = es + '(' for ast in values: es = es + self.parse_declaration_expressn(ast, es='') + ', ' if es.endswith(', '): es = es[:-2] return es + ')' def parse_declaration_expressn_arrayliteral(self, values, es): """ Same in python. Just a square bracket enclosed array. :param values: :param es: :return: """ es = es + '[' for ast in values: es = es + self.parse_declaration_expressn(ast, es='') + ', ' if es.endswith(', '): es = es[:-2] return es + ']' def parse_declaration_expressn_operator(self, lhsAST, rhsAST, es, operator): """ Simply joins the left and right hand arguments lhs and rhs with an operator. :param lhsAST: :param rhsAST: :param es: :param operator: :return: """ if isinstance(lhsAST, wdl_parser.Terminal): if lhsAST.str == 'string': es = es + '"{string}"'.format(string=lhsAST.source_string) else: es = es + '{string}'.format(string=lhsAST.source_string) elif isinstance(lhsAST, wdl_parser.Ast): es = es + self.parse_declaration_expressn(lhsAST, es='') elif isinstance(lhsAST, wdl_parser.AstList): raise NotImplementedError es = es + operator if isinstance(rhsAST, wdl_parser.Terminal): if rhsAST.str == 'string': es = es + '"{string}"'.format(string=rhsAST.source_string) else: es = es + '{string}'.format(string=rhsAST.source_string) elif isinstance(rhsAST, wdl_parser.Ast): es = es + self.parse_declaration_expressn(rhsAST, es='') elif isinstance(rhsAST, wdl_parser.AstList): raise NotImplementedError return es def parse_declaration_expressn_fncall(self, name, params, es): """ Parses out cromwell's built-in function calls. Some of these are special and need minor adjustments, for example length(), which is equivalent to python's len() function. Or sub, which is equivalent to re.sub(), but needs a rearrangement of input variables. Known to be supported: sub, size, read_tsv, length, select_first. :param name: :param params: :param es: :return: """ # name of the function if isinstance(name, wdl_parser.Terminal): if name.str: # use python's built-in for length() if name.source_string == 'length': es = es + 'len(' elif name.source_string == 'stdout': return es + 'stdout' else: es = es + name.source_string + '(' else: raise NotImplementedError elif isinstance(name, wdl_parser.Ast): raise NotImplementedError elif isinstance(name, wdl_parser.AstList): raise NotImplementedError # use python's re.sub() for sub() if name.source_string == 'sub': es_params = self.parse_declaration_expressn_fncall_SUBparams(params) else: es_params = self.parse_declaration_expressn_fncall_normalparams(params) if name.source_string == 'glob': return es + es_params + ', tempDir)' elif name.source_string == 'size': return es + es_params + ', fileStore=fileStore)' else: return es + es_params + ')' def parse_declaration_expressn_fncall_normalparams(self, params): # arguments passed to the function if isinstance(params, wdl_parser.Terminal): raise NotImplementedError elif isinstance(params, wdl_parser.Ast): raise NotImplementedError elif isinstance(params, wdl_parser.AstList): es_param = '' for ast in params: es_param = es_param + self.parse_declaration_expressn(ast, es='') + ', ' if es_param.endswith(', '): es_param = es_param[:-2] return es_param def parse_declaration_expressn_fncall_SUBparams(self, params): """ Needs rearrangement: 0 1 2 WDL native params: sub(input, pattern, replace) 1 2 0 Python's re.sub() params: sub(pattern, replace, input) :param params: :param es: :return: """ # arguments passed to the function if isinstance(params, wdl_parser.Terminal): raise NotImplementedError elif isinstance(params, wdl_parser.Ast): raise NotImplementedError elif isinstance(params, wdl_parser.AstList): assert len(params) == 3, ('sub() function requires exactly 3 arguments.') es_params0 = self.parse_declaration_expressn(params[0], es='') es_params1 = self.parse_declaration_expressn(params[1], es='') es_params2 = self.parse_declaration_expressn(params[2], es='') return es_params1 + ', ' + es_params2 + ', ' + es_params0 def parse_workflow_declaration(self, wf_declaration_subAST): ''' Parses a WDL declaration AST subtree into a string and a python dictionary containing its 'type' and 'value'. For example: var_name = refIndex var_map = {'type': File, 'value': bamIndex} :param wf_declaration_subAST: An AST subtree of a workflow declaration. :return: var_name, which is the name of the declared variable :return: var_map, a dictionary with keys for type and value. e.g. {'type': File, 'value': bamIndex} ''' var_map = OrderedDict() var_name = self.parse_declaration_name(wf_declaration_subAST.attr("name")) var_type = self.parse_declaration_type(wf_declaration_subAST.attr("type")) var_expressn = self.parse_declaration_expressn(wf_declaration_subAST.attr("expression"), es='') var_map['name'] = var_name var_map['type'] = var_type var_map['value'] = var_expressn return var_name, var_map def parse_workflow_call_taskname(self, i): """ Required. :param i: :return: """ if isinstance(i, wdl_parser.Terminal): return i.source_string elif isinstance(i, wdl_parser.Ast): raise NotImplementedError elif isinstance(i, wdl_parser.AstList): raise NotImplementedError def parse_workflow_call_taskalias(self, i): """ Required. :param i: :return: """ if isinstance(i, wdl_parser.Terminal): return i.source_string elif isinstance(i, wdl_parser.Ast): raise NotImplementedError elif isinstance(i, wdl_parser.AstList): raise NotImplementedError def parse_workflow_call_body_declarations(self, i): """ Have not seen this used, so expects to return "[]". :param i: :return: """ declaration_array = [] if isinstance(i, wdl_parser.Terminal): declaration_array = [i.source_string] elif isinstance(i, wdl_parser.Ast): raise NotImplementedError elif isinstance(i, wdl_parser.AstList): for ast in i: declaration_array.append(self.parse_task_declaration(ast)) # have not seen this used so raise to check if declaration_array: raise NotImplementedError return declaration_array def parse_workflow_call_body_io(self, i): """ Required. :param i: :return: """ if isinstance(i, wdl_parser.Terminal): raise NotImplementedError elif isinstance(i, wdl_parser.Ast): raise NotImplementedError elif isinstance(i, wdl_parser.AstList): for ast in i: assert len(i) == 1 if ast.name == 'Inputs': return self.parse_workflow_call_body_io_map(ast.attr('map')) else: raise NotImplementedError def parse_workflow_call_body_io_map(self, i): """ Required. :param i: :return: """ io_map = OrderedDict() if isinstance(i, wdl_parser.Terminal): raise NotImplementedError elif isinstance(i, wdl_parser.Ast): raise NotImplementedError elif isinstance(i, wdl_parser.AstList): for ast in i: if ast.name == 'IOMapping': key = self.parse_declaration_expressn(ast.attr("key"), es='') value = self.parse_declaration_expressn(ast.attr("value"), es='') io_map[key] = value else: raise NotImplementedError return io_map def parse_workflow_call_body(self, i): """ Required. :param i: :return: """ io_map = OrderedDict() if isinstance(i, wdl_parser.Terminal): return i.source_string # no io mappings; represents just a blank call elif isinstance(i, wdl_parser.Ast): if i.name == 'CallBody': declarations = self.parse_workflow_call_body_declarations(i.attr("declarations")) # have not seen this used io_map = self.parse_workflow_call_body_io(i.attr('io')) else: raise NotImplementedError elif isinstance(i, wdl_parser.AstList): raise NotImplementedError return io_map def parse_workflow_call(self, i): ''' Parses a WDL workflow call AST subtree to give the variable mappings for that particular job/task "call". :param i: WDL workflow job object :return: python dictionary of io mappings for that job call ''' task_being_called = self.parse_workflow_call_taskname(i.attr("task")) task_alias = self.parse_workflow_call_taskalias(i.attr("alias")) io_map = self.parse_workflow_call_body(i.attr("body")) if not task_alias: task_alias = task_being_called return {'task': task_being_called, 'alias': task_alias, 'io': io_map} toil-releases-3.24.0/src/toil/wdl/wdl_functions.py000066400000000000000000000444721362134276200221450ustar00rootroot00000000000000# Copyright (C) 2018 UCSC Computational Genomics Lab # # 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. from __future__ import absolute_import from __future__ import print_function from __future__ import division from past.builtins import basestring import fnmatch import os import logging import textwrap import csv from toil import subprocess wdllogger = logging.getLogger(__name__) def glob(glob_pattern, directoryname): ''' Walks through a directory and its subdirectories looking for files matching the glob_pattern and returns a list=[]. :param directoryname: Any accessible folder name on the filesystem. :param glob_pattern: A string like "*.txt", which would find all text files. :return: A list=[] of absolute filepaths matching the glob pattern. ''' matches = [] for root, dirnames, filenames in os.walk(directoryname): for filename in fnmatch.filter(filenames, glob_pattern): absolute_filepath = os.path.join(root, filename) matches.append(absolute_filepath) return matches def generate_docker_bashscript_file(temp_dir, docker_dir, globs, cmd, job_name): ''' Creates a bashscript to inject into a docker container for the job. This script wraps the job command(s) given in a bash script, hard links the outputs and returns an "rc" file containing the exit code. All of this is done in an effort to parallel the Broad's cromwell engine, which is the native WDL runner. As they've chosen to write and then run a bashscript for every command, so shall we. :param temp_dir: The current directory outside of docker to deposit the bashscript into, which will be the bind mount that docker loads files from into its own containerized filesystem. This is usually the tempDir created by this individual job using 'tempDir = job.fileStore.getLocalTempDir()'. :param docker_dir: The working directory inside of the docker container which is bind mounted to 'temp_dir'. By default this is 'data'. :param globs: A list of expected output files to retrieve as glob patterns that will be returned as hard links to the current working directory. :param cmd: A bash command to be written into the bash script and run. :param job_name: The job's name, only used to write in a file name identifying the script as written for that job. Will be used to call the script later. :return: Nothing, but it writes and deposits a bash script in temp_dir intended to be run inside of a docker container for this job. ''' wdl_copyright = heredoc_wdl(''' \n # Borrowed/rewritten from the Broad's Cromwell implementation. As # that is under a BSD-ish license, I include here the license off # of their GitHub repo. Thank you Broadies! # Copyright (c) 2015, Broad Institute, Inc. # All rights reserved. # Redistribution and use in source and binary forms, with or without # modification, are permitted provided that the following conditions are met: # * Redistributions of source code must retain the above copyright notice, this # list of conditions and the following disclaimer. # * Redistributions in binary form must reproduce the above copyright notice, # this list of conditions and the following disclaimer in the documentation # and/or other materials provided with the distribution. # * Neither the name Broad Institute, Inc. nor the names of its # contributors may be used to endorse or promote products derived from # this software without specific prior written permission. # THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" # AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE # IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE # DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE # FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL # DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR # SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER # CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, # OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE # OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE # make a temp directory w/identifier ''') prefix_dict = {"docker_dir": docker_dir, "cmd": cmd} bashfile_prefix = heredoc_wdl(''' tmpDir=$(mktemp -d /{docker_dir}/execution/tmp.XXXXXX) chmod 777 $tmpDir # set destination for java to deposit all of its files export _JAVA_OPTIONS=-Djava.io.tmpdir=$tmpDir export TMPDIR=$tmpDir ( cd /{docker_dir}/execution {cmd} ) # gather the input command return code echo $? > "$tmpDir/rc.tmp" ''', prefix_dict) bashfile_string = '#!/bin/bash' + wdl_copyright + bashfile_prefix begin_globbing_string = heredoc_wdl(''' ( mkdir "$tmpDir/globs" ''') bashfile_string = bashfile_string + begin_globbing_string for glob_input in globs: add_this_glob = \ '( ln -L ' + glob_input + \ ' "$tmpDir/globs" 2> /dev/null ) || ( ln ' + glob_input + \ ' "$tmpDir/globs" )\n' bashfile_string = bashfile_string + add_this_glob bashfile_suffix = heredoc_wdl(''' ) # flush RAM to disk sync mv "$tmpDir/rc.tmp" "$tmpDir/rc" chmod -R 777 $tmpDir ''') bashfile_string = bashfile_string + bashfile_suffix with open(os.path.join(temp_dir, job_name + '_script.sh'), 'w') as bashfile: bashfile.write(bashfile_string) def process_single_infile(f, fileStore): wdllogger.info('Importing {f} into the jobstore.'.format(f=f)) if f.startswith('http://') or f.startswith('https://') or \ f.startswith('file://') or f.startswith('wasb://'): filepath = fileStore.importFile(f) preserveThisFilename = os.path.basename(f) elif f.startswith('s3://'): try: filepath = fileStore.importFile(f) preserveThisFilename = os.path.basename(f) except: from toil.lib.ec2nodes import EC2Regions success = False for region in EC2Regions: try: html_path = 'http://s3.{}.amazonaws.com/'.format(region) + f[5:] filepath = fileStore.importFile(html_path) preserveThisFilename = os.path.basename(f) success = True except: pass if not success: raise RuntimeError('Unable to import: ' + f) elif f.startswith('gs://'): f = 'https://storage.googleapis.com/' + f[5:] filepath = fileStore.importFile(f) preserveThisFilename = os.path.basename(f) else: filepath = fileStore.importFile("file://" + os.path.abspath(f)) preserveThisFilename = os.path.basename(f) return (filepath, preserveThisFilename) def process_array_infile(af, fileStore): processed_array = [] for f in af: processed_array.append(process_infile(f, fileStore)) return processed_array def process_infile(f, fileStore): """ Takes an array of files or a single file and imports into the jobstore. This returns a tuple or an array of tuples replacing all previous path strings. Toil does not preserve a file's original name upon import and so the tuple keeps track of this with the format: '(filepath, preserveThisFilename)' :param f: String or an Array. The smallest element must be a string, so: an array of strings, an array of arrays of strings... etc. :param fileStore: The filestore object that is called to load files into the filestore. :return: A tuple or an array of tuples. """ # check if this has already been processed if isinstance(f, tuple): return f elif isinstance(f, list): return process_array_infile(f, fileStore) elif isinstance(f, basestring): return process_single_infile(f, fileStore) else: raise RuntimeError('Error processing file: '.format(str(f))) def sub(a, b, c): if isinstance(a, tuple): a = a[1] if isinstance(a, tuple): b = b[1] if isinstance(a, tuple): c = c[1] import re return re.sub(str(a), str(b), str(c)) def defined(i): if i: return True return False def process_single_outfile(f, fileStore, workDir, outDir): if os.path.exists(f): output_f_path = f elif os.path.exists(os.path.abspath(f)): output_f_path = os.path.abspath(f) elif os.path.exists(os.path.join(workDir, 'execution', f)): output_f_path = os.path.join(workDir, 'execution', f) elif os.path.exists(os.path.join('execution', f)): output_f_path = os.path.join('execution', f) elif os.path.exists(os.path.join(workDir, f)): output_f_path = os.path.join(workDir, f) else: tmp = subprocess.check_output(['ls', '-lha', workDir]).decode('utf-8') exe = subprocess.check_output(['ls', '-lha', os.path.join(workDir, 'execution')]).decode('utf-8') raise RuntimeError('OUTPUT FILE: {} was not found!\n' '{}\n\n' '{}\n'.format(f, tmp, exe)) output_file = fileStore.writeGlobalFile(output_f_path) preserveThisFilename = os.path.basename(output_f_path) fileStore.exportFile(output_file, "file://" + os.path.join(os.path.abspath(outDir), preserveThisFilename)) return (output_file, preserveThisFilename) def process_array_outfile(af, fileStore, workDir, outDir): processed_array = [] for f in af: processed_array.append(process_outfile(f, fileStore, workDir, outDir)) return processed_array def process_outfile(f, fileStore, workDir, outDir): if isinstance(f, list): return process_array_outfile(f, fileStore, workDir, outDir) elif isinstance(f, basestring): return process_single_outfile(f, fileStore, workDir, outDir) else: raise RuntimeError('Error processing file: '.format(str(f))) def abspath_single_file(f, cwd): if f == os.path.abspath(f): return f else: return os.path.join(cwd, f) def abspath_array_file(af, cwd): processed_array = [] for f in af: processed_array.append(abspath_file(f, cwd)) return processed_array def abspath_file(f, cwd): if not f: # in the case of "optional" files (same treatment in 'process_and_read_file()') # TODO: handle this at compile time, not here return '' # check if this has already been processed if isinstance(f, tuple): return f if isinstance(f, list): return abspath_array_file(f, cwd) elif isinstance(f, basestring): if f.startswith('s3://') or f.startswith('http://') or f.startswith('https://') or \ f.startswith('file://') or f.startswith('wasb://') or f.startswith('gs://'): return f return abspath_single_file(f, cwd) else: raise RuntimeError('Error processing file: ({}) of type: ({}).'.format(str(f), str(type(f)))) def read_single_file(f, tempDir, fileStore, docker=False): import os try: fpath = fileStore.readGlobalFile(f[0], userPath=os.path.join(tempDir, f[1])) except: fpath = os.path.join(tempDir, f[1]) return fpath def read_array_file(af, tempDir, fileStore, docker=False): processed_array = [] for f in af: processed_array.append(read_file(f, tempDir, fileStore, docker=docker)) return processed_array def read_file(f, tempDir, fileStore, docker=False): # check if this has already been processed if isinstance(f, tuple): return read_single_file(f, tempDir, fileStore, docker=docker) elif isinstance(f, list): return read_array_file(f, tempDir, fileStore, docker=docker) else: raise RuntimeError('Error processing file: '.format(str(f))) def process_and_read_file(f, tempDir, fileStore, docker=False): if not f: # in the case of "optional" files (same treatment in 'abspath_file()') # TODO: handle this at compile time, not here and change to the empty string return None processed_file = process_infile(f, fileStore) return read_file(processed_file, tempDir, fileStore, docker=docker) def return_bytes(unit='B'): num_bytes = 1 if unit.lower() in ['ki', 'kib']: num_bytes = 1 << 10 if unit.lower() in ['mi', 'mib']: num_bytes = 1 << 20 if unit.lower() in ['gi', 'gib']: num_bytes = 1 << 30 if unit.lower() in ['ti', 'tib']: num_bytes = 1 << 40 if unit.lower() in ['k', 'kb']: num_bytes = 1000 if unit.lower() in ['m', 'mb']: num_bytes = 1000 ** 2 if unit.lower() in ['g', 'gb']: num_bytes = 1000 ** 3 if unit.lower() in ['t', 'tb']: num_bytes = 1000 ** 4 return num_bytes def parse_memory(memory): """ Parses a string representing memory and returns an integer # of bytes. :param memory: :return: """ memory = str(memory) if 'None' in memory: return 2147483648 # toil's default try: import re raw_mem_split = re.split('([a-zA-Z]+)', memory) mem_split = [] for r in raw_mem_split: if r: mem_split.append(r.replace(' ', '')) if len(mem_split) == 1: return int(memory) if len(mem_split) == 2: num = mem_split[0] unit = mem_split[1] return int(float(num) * return_bytes(unit)) else: raise RuntimeError('Memory parsing failed: {}'.format(memory)) except: return 2147483648 # toil's default def parse_cores(cores): cores = str(cores) if 'None' in cores: return 1 # toil's default if cores: return float(cores) else: return 1 def parse_disk(disk): disk = str(disk) if 'None' in disk: return 2147483648 # toil's default try: total_disk = 0 disks = disk.split(',') for d in disks: d = d.strip().split(' ') if len(d) > 1: for part in d: if is_number(part): total_disk += parse_memory('{} GB'.format(part)) else: return parse_memory(d[0]) if parse_memory(d[0]) > 2147483648 else 2147483648 return total_disk if total_disk > 2147483648 else 2147483648 except: return 2147483648 # toil's default def is_number(s): try: float(s) return True except ValueError: return False def size(f, unit='B', fileStore=None): """ Returns the size of a file in bytes. :param f: Filename :param unit: Return the byte size in these units (gigabytes, etc.). :return: """ divisor = return_bytes(unit) fileID = process_infile(f, fileStore)[0] return fileID.size / divisor def select_first(values): for var in values: if var: return var raise ValueError('No defined variables found for select_first array: {}'.format(str(values))) def read_string(inputstring): if isinstance(inputstring, tuple): inputstring = inputstring[0] return str(inputstring) def read_float(inputstring): if isinstance(inputstring, tuple): inputstring = inputstring[0] return float(inputstring) def read_int(inputstring): if isinstance(inputstring, tuple): inputstring = inputstring[0] return int(inputstring) def combine_dicts(dict1, dict2): from six import iteritems combineddict= {} for k, v in iteritems(dict1): counter1 = 0 while isinstance(v, list): counter1 += 1 v = v[0] break for k, v in iteritems(dict2): counter2 = 0 while isinstance(v, list): counter2 += 1 v = v[0] break for k in dict1: if counter1 > counter2: combineddict[k] = dict1[k] combineddict[k].append(dict2[k]) elif counter1 < counter2: combineddict[k] = dict2[k] combineddict[k].append(dict1[k]) else: combineddict[k] = [dict1[k], dict2[k]] return combineddict def basename(path, suffix=None): """https://software.broadinstitute.org/wdl/documentation/article?id=10554""" path = path.strip() if suffix: suffix = suffix.strip() if path.endswith(suffix): path = path[:-len(suffix)] return os.path.basename(path) def heredoc_wdl(template, dictionary={}, indent=''): template = textwrap.dedent(template).format(**dictionary) return template.replace('\n', '\n' + indent) + '\n' def read_tsv(f, delimiter="\t"): ''' Take a tsv filepath and return an array; e.g. [[],[],[]]. For example, a file containing: 1 2 3 4 5 6 7 8 9 would return the array: [['1','2','3'], ['4','5','6'], ['7','8','9']] :param tsv_filepath: :return: tsv_array ''' tsv_array = [] with open(f, "r") as f: data_file = csv.reader(f, delimiter=delimiter) for line in data_file: tsv_array.append(line) return (tsv_array) def read_csv(f): ''' Take a csv filepath and return an array; e.g. [[],[],[]]. For example, a file containing: 1,2,3 4,5,6 7,8,9 would return the array: [['1','2','3'], ['4','5','6'], ['7','8','9']] :param csv_filepath: :return: csv_array ''' return read_tsv(f, delimiter=",") toil-releases-3.24.0/src/toil/wdl/wdl_parser.py000066400000000000000000004602751362134276200214340ustar00rootroot00000000000000################################################################################ # Copyright (c) 2015, Broad Institute, Inc. # All rights reserved. # # Redistribution and use in source and binary forms, with or without # modification, are permitted provided that the following conditions are met: # # * Redistributions of source code must retain the above copyright notice, this # list of conditions and the following disclaimer. # # * Redistributions in binary form must reproduce the above copyright notice, # this list of conditions and the following disclaimer in the documentation # and/or other materials provided with the distribution. # # * Neither the name Broad Institute, Inc. nor the names of its # contributors may be used to endorse or promote products derived from # this software without specific prior written permission. # # THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" # AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE # IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE # DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE # FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL # DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR # SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER # CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, # OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE # OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. # ################################################################################ # # This file was generated by Hermes Parser Generator on Sun Aug 13 18:58:49 2017 # # Hermes command: hermes generate grammar.hgr --name=wdl --header # Run from: . (relative to this file) # Hermes version: hermes-parser 2.0rc6 # # !!! DO NOT CHANGE THIS FILE DIRECTLY !!! # # If you wish to change something in this file, either change the grammar and # re-generate this file, or change the templates in Hermes and regenerate. # See the Hermes repository: http://github.com/scottfrazer/hermes # ################################################################################ import sys import os import re import base64 import argparse from builtins import chr from collections import OrderedDict # Common Code # def parse_tree_string(parsetree, indent=None, b64_source=True, indent_level=0, debug=False): indent_str = (' ' * indent * indent_level) if indent else '' if isinstance(parsetree, ParseTree): children = [parse_tree_string(child, indent, b64_source, indent_level+1, debug) for child in parsetree.children] debug_str = parsetree.debug_str() if debug else '' if indent is None or len(children) == 0: return '{0}({1}: {2}{3})'.format(indent_str, parsetree.nonterminal, debug_str, ', '.join(children)) else: return '{0}({1}:{2}\n{3}\n{4})'.format( indent_str, parsetree.nonterminal, debug_str, ',\n'.join(children), indent_str ) elif isinstance(parsetree, Terminal): return indent_str + parsetree.dumps(b64_source=b64_source) def ast_string(ast, indent=None, b64_source=True, indent_level=0): indent_str = (' ' * indent * indent_level) if indent else '' next_indent_str = (' ' * indent * (indent_level+1)) if indent else '' if isinstance(ast, Ast): children = OrderedDict([(k, ast_string(v, indent, b64_source, indent_level+1)) for k, v in ast.attributes.items()]) if indent is None: return '({0}: {1})'.format( ast.name, ', '.join('{0}={1}'.format(k, v) for k, v in children.items()) ) else: return '({0}:\n{1}\n{2})'.format( ast.name, ',\n'.join(['{0}{1}={2}'.format(next_indent_str, k, v) for k, v in children.items()]), indent_str ) elif isinstance(ast, list): children = [ast_string(element, indent, b64_source, indent_level+1) for element in ast] if indent is None or len(children) == 0: return '[{0}]'.format(', '.join(children)) else: return '[\n{1}\n{0}]'.format( indent_str, ',\n'.join(['{0}{1}'.format(next_indent_str, child) for child in children]), ) elif isinstance(ast, Terminal): return ast.dumps(b64_source=b64_source) class Terminal: def __init__(self, id, str, source_string, resource, line, col): self.__dict__.update(locals()) def getId(self): return self.id def ast(self): return self def dumps(self, b64_source=True, **kwargs): source_string = base64.b64encode(self.source_string.encode('utf-8')).decode('utf-8') if b64_source else self.source_string return '<{resource}:{line}:{col} {terminal} "{source}">'.format( resource=self.resource, line=self.line, col=self.col, terminal=self.str, source=source_string ) def __str__(self): return self.dumps() class NonTerminal(): def __init__(self, id, str): self.__dict__.update(locals()) self.list = False def __str__(self): return self.str class AstTransform: pass class AstTransformSubstitution(AstTransform): def __init__(self, idx): self.__dict__.update(locals()) def __repr__(self): return '$' + str(self.idx) def __str__(self): return self.__repr__() class AstTransformNodeCreator(AstTransform): def __init__( self, name, parameters ): self.__dict__.update(locals()) def __repr__( self ): return self.name + '( ' + ', '.join(['%s=$%s' % (k,str(v)) for k,v in self.parameters.items()]) + ' )' def __str__(self): return self.__repr__() class AstList(list): def ast(self): retval = [] for ast in self: retval.append(ast.ast()) return retval def dumps(self, indent=None, b64_source=True): args = locals() del args['self'] return ast_string(self, **args) class ParseTree(): def __init__(self, nonterminal): self.__dict__.update(locals()) self.children = [] self.astTransform = None self.isExpr = False self.isNud = False self.isPrefix = False self.isInfix = False self.nudMorphemeCount = 0 self.isExprNud = False # true for rules like _expr := {_expr} + {...} self.list_separator_id = None self.list = False def debug_str(self): from copy import deepcopy def h(v): if v == False or v is None: return str(v) from xtermcolor import colorize return colorize(str(v), ansi=190) d = deepcopy(self.__dict__) for key in ['self', 'nonterminal', 'children']: del d[key] f = {k: v for k, v in d.items() if v != False and v is not None} return ' [{}]'.format(', '.join(['{}={}'.format(k,h(v)) for k,v in f.items()])) def add(self, tree): self.children.append( tree ) def is_compound_nud(self): return isinstance(self.children[0], ParseTree) and \ self.children[0].isNud and \ not self.children[0].isPrefix and \ not self.isExprNud and \ not self.isInfix def ast(self): if self.list == True: r = AstList() if len(self.children) == 0: return r for child in self.children: if isinstance(child, Terminal) and self.list_separator_id is not None and child.id == self.list_separator_id: continue r.append(child.ast()) return r elif self.isExpr: if isinstance(self.astTransform, AstTransformSubstitution): return self.children[self.astTransform.idx].ast() elif isinstance(self.astTransform, AstTransformNodeCreator): parameters = OrderedDict() for name, idx in self.astTransform.parameters.items(): if idx == '$': child = self.children[0] elif self.is_compound_nud(): if idx < self.children[0].nudMorphemeCount: child = self.children[0].children[idx] else: index = idx - self.children[0].nudMorphemeCount + 1 child = self.children[index] elif len(self.children) == 1 and not isinstance(self.children[0], ParseTree) and not isinstance(self.children[0], list): return self.children[0] else: child = self.children[idx] parameters[name] = child.ast() return Ast(self.astTransform.name, parameters) else: if isinstance(self.astTransform, AstTransformSubstitution): return self.children[self.astTransform.idx].ast() elif isinstance(self.astTransform, AstTransformNodeCreator): parameters = OrderedDict() for name, idx in self.astTransform.parameters.items(): parameters[name] = self.children[idx].ast() return Ast(self.astTransform.name, parameters) elif len(self.children): return self.children[0].ast() else: return None def dumps(self, indent=None, b64_source=True, debug=False): args = locals() del args['self'] return parse_tree_string(self, **args) class Ast(): def __init__(self, name, attributes): self.__dict__.update(locals()) def attr(self, attr): return self.attributes[attr] def dumps(self, indent=None, b64_source=True): args = locals() del args['self'] return ast_string(self, **args) class SyntaxError(Exception): def __init__(self, message): self.__dict__.update(locals()) def __str__(self): return self.message class TokenStream(list): def __init__(self, arg=[]): super(TokenStream, self).__init__(arg) self.index = 0 def advance(self): self.index += 1 return self.current() def last(self): return self[-1] def current(self): try: return self[self.index] except IndexError: return None class DefaultSyntaxErrorHandler: def __init__(self): self.errors = [] def _error(self, string): error = SyntaxError(string) self.errors.append(error) return error def unexpected_eof(self): return self._error("Error: unexpected end of file") def excess_tokens(self): return self._error("Finished parsing without consuming all tokens.") def unexpected_symbol(self, nonterminal, actual_terminal, expected_terminals, rule): return self._error("Unexpected symbol (line {line}, col {col}) when parsing parse_{nt}. Expected {expected}, got {actual}.".format( line=actual_terminal.line, col=actual_terminal.col, nt=nonterminal, expected=', '.join(expected_terminals), actual=actual_terminal )) def no_more_tokens(self, nonterminal, expected_terminal, last_terminal): return self._error("No more tokens. Expecting " + expected_terminal) def invalid_terminal(self, nonterminal, invalid_terminal): return self._error("Invalid symbol ID: {} ({})".format(invalid_terminal.id, invalid_terminal.string)) def unrecognized_token(self, string, line, col): lines = string.split('\n') bad_line = lines[line-1] return self._error('Unrecognized token on line {}, column {}:\n\n{}\n{}'.format( line, col, bad_line, ''.join([' ' for x in range(col-1)]) + '^' )) def missing_list_items(self, method, required, found, last): return self._error("List for {} requires {} items but only {} were found.".format(method, required, found)) def missing_terminator(self, method, terminator, last): return self._error("List for "+method+" is missing a terminator") class ParserContext: def __init__(self, tokens, errors): self.__dict__.update(locals()) self.nonterminal_string = None self.rule_string = None # Parser Code # terminals = { 0: 'raw_cmd_start', 1: 'dash', 2: 'not_equal', 3: 'boolean', 4: 'float', 5: 'cmd_param_start', 6: 'task', 7: 'dot', 8: 'rsquare', 9: 'in', 10: 'workflow', 11: 'plus', 12: 'not', 13: 'meta', 14: 'equal', 15: 'lteq', 16: 'lbrace', 17: 'asterisk', 18: 'if', 19: 'raw_command', 20: 'lparen', 21: 'else', 22: 'output', 23: 'double_pipe', 24: 'double_equal', 25: 'while', 26: 'cmd_part', 27: 'cmd_attr_hint', 28: 'call', 29: 'parameter_meta', 30: 'raw_cmd_end', 31: 'then', 32: 'runtime', 33: 'qmark', 34: 'input', 35: 'e', 36: 'lt', 37: 'slash', 38: 'type_e', 39: 'integer', 40: 'cmd_param_end', 41: 'import', 42: 'string', 43: 'comma', 44: 'rbrace', 45: 'rparen', 46: 'lsquare', 47: 'double_ampersand', 48: 'type', 49: 'gt', 50: 'identifier', 51: 'scatter', 52: 'object', 53: 'as', 54: 'colon', 55: 'fqn', 56: 'gteq', 57: 'percent', 'raw_cmd_start': 0, 'dash': 1, 'not_equal': 2, 'boolean': 3, 'float': 4, 'cmd_param_start': 5, 'task': 6, 'dot': 7, 'rsquare': 8, 'in': 9, 'workflow': 10, 'plus': 11, 'not': 12, 'meta': 13, 'equal': 14, 'lteq': 15, 'lbrace': 16, 'asterisk': 17, 'if': 18, 'raw_command': 19, 'lparen': 20, 'else': 21, 'output': 22, 'double_pipe': 23, 'double_equal': 24, 'while': 25, 'cmd_part': 26, 'cmd_attr_hint': 27, 'call': 28, 'parameter_meta': 29, 'raw_cmd_end': 30, 'then': 31, 'runtime': 32, 'qmark': 33, 'input': 34, 'e': 35, 'lt': 36, 'slash': 37, 'type_e': 38, 'integer': 39, 'cmd_param_end': 40, 'import': 41, 'string': 42, 'comma': 43, 'rbrace': 44, 'rparen': 45, 'lsquare': 46, 'double_ampersand': 47, 'type': 48, 'gt': 49, 'identifier': 50, 'scatter': 51, 'object': 52, 'as': 53, 'colon': 54, 'fqn': 55, 'gteq': 56, 'percent': 57, } # table[nonterminal][terminal] = rule table = [ [-1, -1, -1, -1, -1, -1, 7, -1, -1, -1, 7, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 7, -1, -1, 7, -1, -1, -1, -1, -1, -1, 7, -1, -1, -1, -1, 6, -1, -1, -1, -1], [-1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1], [-1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 19, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1], [-1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 57, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1], [-1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1], [-1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 52, -1, -1, 51, -1, 52, -1, -1, -1, 52, -1, -1, 52, -1, -1, 52, 52, -1, -1, -1, -1, -1, -1, -1, -1, 52, -1, -1, -1, -1, -1, 52, -1, -1, -1, 52, -1, -1, 52, -1, -1, -1, -1, -1, -1], [-1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 17, -1, -1, -1, -1, -1, 13, -1, -1, 14, -1, -1, -1, -1, -1, -1, 16, -1, -1, 15, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1], [-1, -1, -1, -1, -1, -1, 4, -1, -1, -1, 3, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 5, -1, -1, -1, -1, -1, -1, -1, -1, -1, 5, -1, -1, -1, -1, -1, -1, -1, -1, -1], [-1, -1, -1, -1, -1, -1, -1, 68, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1], [-1, -1, -1, -1, -1, -1, -1, 65, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 66, -1, -1, -1, -1, -1, 66, -1, -1, -1, 66, -1, -1, -1, -1, -1, -1, 66, -1, -1], [-1, -1, -1, -1, -1, 23, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1], [-1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 27, -1, -1, -1, -1, -1, -1, -1, -1, -1, 27, -1, -1, -1, -1, -1, -1, -1, -1, -1], [-1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 67, -1, -1], [-1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 24, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1], [-1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 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-1, -1, -1, -1, -1, -1], [-1, -1, -1, -1, -1, -1, 35, -1, -1, -1, 35, -1, -1, 35, 34, -1, -1, -1, 35, 35, -1, -1, 35, -1, -1, 35, -1, -1, 35, 35, -1, -1, 35, -1, 35, -1, -1, -1, 35, -1, -1, -1, -1, -1, 35, -1, -1, -1, 35, -1, -1, 35, -1, -1, -1, -1, -1, -1], [-1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 40, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1], [-1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 73, -1, -1, -1, -1, -1, -1], [-1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 33, -1, -1, -1, -1, -1, -1, -1], [-1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 48, -1, -1, -1, -1, 44, -1, -1, -1, 46, -1, -1, 43, -1, -1, 41, 47, -1, -1, -1, -1, -1, -1, -1, -1, 42, -1, -1, -1, -1, -1, -1, -1, -1, -1, 42, -1, -1, 45, -1, -1, -1, -1, -1, -1], [-1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 29, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1], [-1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1], [-1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1], ] nonterminal_first = { 58: [53, -1], 59: [41, -1], 60: [19], 61: [34], 62: [-1, 48, 38, 55], 63: [16, -1], 64: [22, 29, 13, 32, 19], 65: [38, 10, 48, 6], 66: [7], 67: [-1, 7], 68: [5], 69: [38, 48], 70: [55], 71: [27], 72: [38, 48, -1], 73: [14], 74: [-1, 25, 38, 18, 28, 29, 48, 51, 13, 22], 75: [18], 76: [53], 77: [38, 48], 78: [5, 26], 79: [32], 80: [38, 48], 81: [13], 82: [29], 83: [50, -1], 84: [50, -1], 85: [28], 86: [22], 87: [50], 88: [16], 89: [34, -1], 90: [50], 91: [29, -1, 32, 19, 13, 22], 92: [13], 93: [1, 3, 4, 12, 11, 35, -1, 39, 16, 46, 18, 42, 50, 52, 20], 94: [35, 1, 3, 16, 39, 4, 46, 18, 42, 50, 12, 11, 52, 20], 95: [6], 96: [38, 48, -1], 97: [41], 98: [16], 99: [38, 48], 100: [50, -1], 101: [22], 102: [-1, 27], 103: [38, 48, -1], 104: [53, -1], 105: [53], 106: [5, -1, 26], 107: [38, 48, 55], 108: [-1, 6, 48, 38, 10, 41], 109: [25], 110: [-1, 38, 6, 48, 10], 111: [14, -1], 112: [10], 113: [51], 114: [50], 115: [25, 38, 18, 28, 29, 48, 51, 13, 22], 116: [29], 117: [1, 35, 3, 16, 39, 4, 46, 18, 42, 20, 12, 11, 52, 50], 118: [1, 3, 4, 20, 12, 11, 35, -1, 39, 16, 46, 18, 42, 52, 50], } nonterminal_follow = { 58: [48, 6, -1, 38, 10, 41], 59: [38, 10, 48, 6, -1], 60: [44, 29, 32, 19, 13, 22], 61: [44, 34], 62: [44], 63: [25, 38, 18, 28, 44, 29, 48, 51, 13, 22], 64: [44, 29, 32, 19, 13, 22], 65: [-1, 38, 48, 6, 10], 66: [44, 48, 38, 55], 67: [44, 48, 38, 55], 68: [30, 5, 26], 69: [38, 48, 44], 70: [44, 48, 38, 55], 71: [1, 3, 4, 27, 20, 12, 11, 35, 39, 16, 46, 18, 42, 52, 50], 72: [29, 32, 19, 34, 13, 22], 73: [25, -1, 28, 29, 6, 32, 10, 34, 13, 38, 18, 44, 48, 19, 51, 22], 74: [44], 75: [25, 38, 18, 28, 44, 29, 48, 51, 13, 22], 76: [25, 38, 16, 18, 28, 44, 29, 48, 51, 13, 22], 77: [44, 48, 38, 55], 78: [30, 5, 26], 79: [44, 29, 32, 19, 13, 22], 80: [50, 43, 8], 81: [25, 38, 18, 28, 44, 29, 48, 51, 13, 22], 82: [25, 38, 18, 28, 44, 29, 48, 51, 13, 22], 83: [44], 84: [44, 34], 85: [25, 38, 18, 28, 44, 29, 48, 51, 13, 22], 86: [44, 29, 32, 19, 13, 22], 87: [44, 43], 88: [25, 38, 18, 28, 44, 29, 48, 51, 13, 22], 89: [44], 90: [44, 34, 43], 91: [44], 92: [44, 29, 32, 19, 13, 22], 93: [44], 94: [44, 43], 95: [-1, 38, 48, 6, 10], 96: [8], 97: [48, 6, -1, 38, 10, 41], 98: [25, 38, 18, 28, 44, 29, 48, 32, 19, 51, 13, 22], 99: [25, -1, 28, 29, 6, 32, 10, 34, 13, 38, 18, 44, 48, 19, 51, 22], 100: [44], 101: [25, 38, 18, 28, 44, 29, 48, 51, 13, 22], 102: [1, 35, 3, 16, 39, 4, 46, 18, 42, 20, 12, 11, 52, 50], 103: [44], 104: [25, 38, 16, 18, 28, 44, 29, 48, 51, 13, 22], 105: [48, 6, -1, 38, 10, 41], 106: [30], 107: [44, 48, 38, 55], 108: [-1], 109: [25, 38, 18, 28, 44, 29, 48, 51, 13, 22], 110: [-1], 111: [25, -1, 28, 29, 6, 32, 10, 34, 13, 38, 18, 44, 48, 19, 51, 22], 112: [-1, 38, 48, 6, 10], 113: [25, 38, 18, 28, 44, 29, 48, 51, 13, 22], 114: [44, 50], 115: [25, 38, 18, 28, 44, 29, 48, 51, 13, 22], 116: [44, 29, 32, 19, 13, 22], 117: [1, -1, 2, 3, 4, 6, 11, 8, 12, 10, 13, 15, 16, 17, 18, 19, 21, 20, 22, 23, 24, 25, 27, 28, 29, 31, 32, 34, 36, 37, 35, 38, 39, 40, 46, 45, 43, 42, 44, 47, 48, 49, 50, 51, 52, 54, 55, 56, 57], 118: [45, 8], } rule_first = { 0: [-1, 41], 1: [38, -1, 10, 48, 6], 2: [-1, 38, 41, 48, 6, 10], 3: [10], 4: [6], 5: [38, 48], 6: [53], 7: [-1], 8: [41], 9: [53], 10: [38, -1, 48], 11: [-1, 29, 32, 19, 13, 22], 12: [6], 13: [19], 14: [22], 15: [32], 16: [29], 17: [13], 18: [5, -1, 26], 19: [19], 20: [26], 21: [5], 22: [-1, 27], 23: [5], 24: [27], 25: [38, -1, 48], 26: [22], 27: [38, 48], 28: [32], 29: [29], 30: [13], 31: [50, -1], 32: [16], 33: [50], 34: [14], 35: [-1], 36: [38, 48], 37: [14], 38: [1, 35, 3, 16, 39, 4, 46, 18, 42, 20, 12, 11, 52, 50], 39: [25, -1, 38, 18, 28, 29, 48, 51, 13, 22], 40: [10], 41: [28], 42: [38, 48], 43: [25], 44: [18], 45: [51], 46: [22], 47: [29], 48: [13], 49: [53], 50: [-1], 51: [16], 52: [-1], 53: [28], 54: [34, -1], 55: [16], 56: [50, -1], 57: [34], 58: [50], 59: [53], 60: [38, -1, 48, 55], 61: [22], 62: [38, 48], 63: [55], 64: [38, 48], 65: [7], 66: [-1], 67: [55], 68: [7], 69: [29], 70: [13], 71: [25], 72: [18], 73: [51], 74: [50], 75: [38, -1, 48], 76: [48], 77: [48], 78: [48], 79: [48], 80: [1, 35, 3, 16, 39, 4, 46, 18, 42, 20, 12, 11, 52, 50], 81: [1, 35, 3, 16, 39, 4, 46, 18, 42, 20, 12, 11, 52, 50], 82: [1, 35, 3, 16, 39, 4, 46, 18, 42, 20, 12, 11, 52, 50], 83: [1, 35, 3, 16, 39, 4, 46, 18, 42, 20, 12, 11, 52, 50], 84: [1, 35, 3, 16, 39, 4, 46, 18, 42, 20, 12, 11, 52, 50], 85: [1, 35, 3, 16, 39, 4, 46, 18, 42, 20, 12, 11, 52, 50], 86: [1, 35, 3, 16, 39, 4, 46, 18, 42, 20, 12, 11, 52, 50], 87: [1, 35, 3, 16, 39, 4, 46, 18, 42, 20, 12, 11, 52, 50], 88: [1, 35, 3, 16, 39, 4, 46, 18, 42, 20, 12, 11, 52, 50], 89: [1, 35, 3, 16, 39, 4, 46, 18, 42, 20, 12, 11, 52, 50], 90: [1, 35, 3, 16, 39, 4, 46, 18, 42, 20, 12, 11, 52, 50], 91: [1, 35, 3, 16, 39, 4, 46, 18, 42, 20, 12, 11, 52, 50], 92: [1, 35, 3, 16, 39, 4, 46, 18, 42, 20, 12, 11, 52, 50], 93: [12], 94: [11], 95: [1], 96: [1, 35, -1, 3, 16, 39, 4, 46, 18, 42, 20, 12, 11, 52, 50], 97: [50], 98: [50], 99: [50], 100: [50, -1], 101: [52], 102: [46], 103: [35, 1, -1, 3, 16, 39, 4, 46, 18, 42, 50, 12, 11, 52, 20], 104: [16], 105: [20], 106: [18], 107: [42], 108: [50], 109: [3], 110: [39], 111: [4], } nonterminal_rules = { 58: [ "$_gen2 = $import_namespace", "$_gen2 = :_empty", ], 59: [ "$_gen0 = list($import)", ], 60: [ "$command = :raw_command :raw_cmd_start $_gen5 :raw_cmd_end -> RawCommand( parts=$2 )", ], 61: [ "$call_input = :input :colon $_gen14 -> Inputs( map=$2 )", ], 62: [ "$_gen15 = list($wf_output)", ], 63: [ "$_gen12 = $call_body", "$_gen12 = :_empty", ], 64: [ "$sections = $command", "$sections = $outputs", "$sections = $runtime", "$sections = $parameter_meta", "$sections = $meta", ], 65: [ "$workflow_or_task_or_decl = $workflow", "$workflow_or_task_or_decl = $task", "$workflow_or_task_or_decl = $declaration", ], 66: [ "$wf_output_wildcard = :dot :asterisk -> $1", ], 67: [ "$_gen16 = $wf_output_wildcard", "$_gen16 = :_empty", ], 68: [ "$cmd_param = :cmd_param_start $_gen6 $e :cmd_param_end -> CommandParameter( attributes=$1, expr=$2 )", ], 69: [ "$output_kv = $type_e :identifier :equal $e -> Output( type=$0, name=$1, expression=$3 )", ], 70: [ "$wf_output_wildcard_syntax = :fqn $_gen16 -> WorkflowOutputWildcard( fqn=$0, wildcard=$1 )", ], 71: [ "$cmd_param_kv = :cmd_attr_hint :identifier :equal $e -> CommandParameterAttr( key=$1, value=$3 )", ], 72: [ "$_gen3 = list($declaration)", ], 73: [ "$setter = :equal $e -> $1", ], 74: [ "$_gen10 = list($wf_body_element)", ], 75: [ "$if_stmt = :if :lparen $e :rparen :lbrace $_gen10 :rbrace -> If( expression=$2, body=$5 )", ], 76: [ "$alias = :as :identifier -> $1", ], 77: [ "$wf_output_declaration_syntax = $type_e :identifier :equal $e -> WorkflowOutputDeclaration( type=$0, name=$1, expression=$3 )", ], 78: [ "$command_part = :cmd_part", "$command_part = $cmd_param", ], 79: [ "$runtime = :runtime $map -> Runtime( map=$1 )", ], 80: [ "$type_e = :type <=> :lsquare $_gen17 :rsquare -> Type( name=$0, subtype=$2 )", "$type_e = :type <=> :qmark -> OptionalType( innerType=$0 )", "$type_e = :type <=> :plus -> NonEmptyType( innerType=$0 )", "$type_e = :type", ], 81: [ "$wf_meta = :meta $map -> Meta( map=$1 )", ], 82: [ "$wf_parameter_meta = :parameter_meta $map -> ParameterMeta( map=$1 )", ], 83: [ "$_gen8 = list($kv)", ], 84: [ "$_gen14 = list($mapping, :comma)", ], 85: [ "$call = :call :fqn $_gen11 $_gen12 -> Call( task=$1, alias=$2, body=$3 )", ], 86: [ "$outputs = :output :lbrace $_gen7 :rbrace -> Outputs( attributes=$2 )", ], 87: [ "$object_kv = :identifier :colon $e -> ObjectKV( key=$0, value=$2 )", ], 88: [ "$call_body = :lbrace $_gen3 $_gen13 :rbrace -> CallBody( declarations=$1, io=$2 )", ], 89: [ "$_gen13 = list($call_input)", ], 90: [ "$mapping = :identifier :equal $e -> IOMapping( key=$0, value=$2 )", ], 91: [ "$_gen4 = list($sections)", ], 92: [ "$meta = :meta $map -> Meta( map=$1 )", ], 93: [ "$_gen20 = list($map_kv, :comma)", ], 94: [ "$map_kv = $e :colon $e -> MapLiteralKv( key=$0, value=$2 )", ], 95: [ "$task = :task :identifier :lbrace $_gen3 $_gen4 :rbrace -> Task( name=$1, declarations=$3, sections=$4 )", ], 96: [ "$_gen17 = list($type_e, :comma)", ], 97: [ "$import = :import :string $_gen2 -> Import( uri=$1, namespace=$2 )", ], 98: [ "$map = :lbrace $_gen8 :rbrace -> $1", ], 99: [ "$declaration = $type_e :identifier $_gen9 -> Declaration( type=$0, name=$1, expression=$2 )", ], 100: [ "$_gen19 = list($object_kv, :comma)", ], 101: [ "$wf_outputs = :output :lbrace $_gen15 :rbrace -> WorkflowOutputs( outputs=$2 )", ], 102: [ "$_gen6 = list($cmd_param_kv)", ], 103: [ "$_gen7 = list($output_kv)", ], 104: [ "$_gen11 = $alias", "$_gen11 = :_empty", ], 105: [ "$import_namespace = :as :identifier -> $1", ], 106: [ "$_gen5 = list($command_part)", ], 107: [ "$wf_output = $wf_output_declaration_syntax", "$wf_output = $wf_output_wildcard_syntax", ], 108: [ "$document = $_gen0 $_gen1 -> Namespace( imports=$0, body=$1 )", ], 109: [ "$while_loop = :while :lparen $e :rparen :lbrace $_gen10 :rbrace -> WhileLoop( expression=$2, body=$5 )", ], 110: [ "$_gen1 = list($workflow_or_task_or_decl)", ], 111: [ "$_gen9 = $setter", "$_gen9 = :_empty", ], 112: [ "$workflow = :workflow :identifier :lbrace $_gen10 :rbrace -> Workflow( name=$1, body=$3 )", ], 113: [ "$scatter = :scatter :lparen :identifier :in $e :rparen :lbrace $_gen10 :rbrace -> Scatter( item=$2, collection=$4, body=$7 )", ], 114: [ "$kv = :identifier :colon $e -> RuntimeAttribute( key=$0, value=$2 )", ], 115: [ "$wf_body_element = $call", "$wf_body_element = $declaration", "$wf_body_element = $while_loop", "$wf_body_element = $if_stmt", "$wf_body_element = $scatter", "$wf_body_element = $wf_outputs", "$wf_body_element = $wf_parameter_meta", "$wf_body_element = $wf_meta", ], 116: [ "$parameter_meta = :parameter_meta $map -> ParameterMeta( map=$1 )", ], 117: [ "$e = $e :double_pipe $e -> LogicalOr( lhs=$0, rhs=$2 )", "$e = $e :double_ampersand $e -> LogicalAnd( lhs=$0, rhs=$2 )", "$e = $e :double_equal $e -> Equals( lhs=$0, rhs=$2 )", "$e = $e :not_equal $e -> NotEquals( lhs=$0, rhs=$2 )", "$e = $e :lt $e -> LessThan( lhs=$0, rhs=$2 )", "$e = $e :lteq $e -> LessThanOrEqual( lhs=$0, rhs=$2 )", "$e = $e :gt $e -> GreaterThan( lhs=$0, rhs=$2 )", "$e = $e :gteq $e -> GreaterThanOrEqual( lhs=$0, rhs=$2 )", "$e = $e :plus $e -> Add( lhs=$0, rhs=$2 )", "$e = $e :dash $e -> Subtract( lhs=$0, rhs=$2 )", "$e = $e :asterisk $e -> Multiply( lhs=$0, rhs=$2 )", "$e = $e :slash $e -> Divide( lhs=$0, rhs=$2 )", "$e = $e :percent $e -> Remainder( lhs=$0, rhs=$2 )", "$e = :not $e -> LogicalNot( expression=$1 )", "$e = :plus $e -> UnaryPlus( expression=$1 )", "$e = :dash $e -> UnaryNegation( expression=$1 )", "$e = :identifier <=> :lparen $_gen18 :rparen -> FunctionCall( name=$0, params=$2 )", "$e = :identifier <=> :lsquare $e :rsquare -> ArrayOrMapLookup( lhs=$0, rhs=$2 )", "$e = :identifier <=> :dot :identifier -> MemberAccess( lhs=$0, rhs=$2 )", "$e = :object :lbrace $_gen19 :rbrace -> ObjectLiteral( map=$2 )", "$e = :lsquare $_gen18 :rsquare -> ArrayLiteral( values=$1 )", "$e = :lbrace $_gen20 :rbrace -> MapLiteral( map=$1 )", "$e = :lparen $_gen18 :rparen -> TupleLiteral( values=$1 )", "$e = :if $e :then $e :else $e -> TernaryIf( cond=$1, iftrue=$3, iffalse=$5 )", "$e = :string", "$e = :identifier", "$e = :boolean", "$e = :integer", "$e = :float", ], 118: [ "$_gen18 = list($e, :comma)", ], } rules = { 0: "$_gen0 = list($import)", 1: "$_gen1 = list($workflow_or_task_or_decl)", 2: "$document = $_gen0 $_gen1 -> Namespace( imports=$0, body=$1 )", 3: "$workflow_or_task_or_decl = $workflow", 4: "$workflow_or_task_or_decl = $task", 5: "$workflow_or_task_or_decl = $declaration", 6: "$_gen2 = $import_namespace", 7: "$_gen2 = :_empty", 8: "$import = :import :string $_gen2 -> Import( uri=$1, namespace=$2 )", 9: "$import_namespace = :as :identifier -> $1", 10: "$_gen3 = list($declaration)", 11: "$_gen4 = list($sections)", 12: "$task = :task :identifier :lbrace $_gen3 $_gen4 :rbrace -> Task( name=$1, declarations=$3, sections=$4 )", 13: "$sections = $command", 14: "$sections = $outputs", 15: "$sections = $runtime", 16: "$sections = $parameter_meta", 17: "$sections = $meta", 18: "$_gen5 = list($command_part)", 19: "$command = :raw_command :raw_cmd_start $_gen5 :raw_cmd_end -> RawCommand( parts=$2 )", 20: "$command_part = :cmd_part", 21: "$command_part = $cmd_param", 22: "$_gen6 = list($cmd_param_kv)", 23: "$cmd_param = :cmd_param_start $_gen6 $e :cmd_param_end -> CommandParameter( attributes=$1, expr=$2 )", 24: "$cmd_param_kv = :cmd_attr_hint :identifier :equal $e -> CommandParameterAttr( key=$1, value=$3 )", 25: "$_gen7 = list($output_kv)", 26: "$outputs = :output :lbrace $_gen7 :rbrace -> Outputs( attributes=$2 )", 27: "$output_kv = $type_e :identifier :equal $e -> Output( type=$0, name=$1, expression=$3 )", 28: "$runtime = :runtime $map -> Runtime( map=$1 )", 29: "$parameter_meta = :parameter_meta $map -> ParameterMeta( map=$1 )", 30: "$meta = :meta $map -> Meta( map=$1 )", 31: "$_gen8 = list($kv)", 32: "$map = :lbrace $_gen8 :rbrace -> $1", 33: "$kv = :identifier :colon $e -> RuntimeAttribute( key=$0, value=$2 )", 34: "$_gen9 = $setter", 35: "$_gen9 = :_empty", 36: "$declaration = $type_e :identifier $_gen9 -> Declaration( type=$0, name=$1, expression=$2 )", 37: "$setter = :equal $e -> $1", 38: "$map_kv = $e :colon $e -> MapLiteralKv( key=$0, value=$2 )", 39: "$_gen10 = list($wf_body_element)", 40: "$workflow = :workflow :identifier :lbrace $_gen10 :rbrace -> Workflow( name=$1, body=$3 )", 41: "$wf_body_element = $call", 42: "$wf_body_element = $declaration", 43: "$wf_body_element = $while_loop", 44: "$wf_body_element = $if_stmt", 45: "$wf_body_element = $scatter", 46: "$wf_body_element = $wf_outputs", 47: "$wf_body_element = $wf_parameter_meta", 48: "$wf_body_element = $wf_meta", 49: "$_gen11 = $alias", 50: "$_gen11 = :_empty", 51: "$_gen12 = $call_body", 52: "$_gen12 = :_empty", 53: "$call = :call :fqn $_gen11 $_gen12 -> Call( task=$1, alias=$2, body=$3 )", 54: "$_gen13 = list($call_input)", 55: "$call_body = :lbrace $_gen3 $_gen13 :rbrace -> CallBody( declarations=$1, io=$2 )", 56: "$_gen14 = list($mapping, :comma)", 57: "$call_input = :input :colon $_gen14 -> Inputs( map=$2 )", 58: "$mapping = :identifier :equal $e -> IOMapping( key=$0, value=$2 )", 59: "$alias = :as :identifier -> $1", 60: "$_gen15 = list($wf_output)", 61: "$wf_outputs = :output :lbrace $_gen15 :rbrace -> WorkflowOutputs( outputs=$2 )", 62: "$wf_output = $wf_output_declaration_syntax", 63: "$wf_output = $wf_output_wildcard_syntax", 64: "$wf_output_declaration_syntax = $type_e :identifier :equal $e -> WorkflowOutputDeclaration( type=$0, name=$1, expression=$3 )", 65: "$_gen16 = $wf_output_wildcard", 66: "$_gen16 = :_empty", 67: "$wf_output_wildcard_syntax = :fqn $_gen16 -> WorkflowOutputWildcard( fqn=$0, wildcard=$1 )", 68: "$wf_output_wildcard = :dot :asterisk -> $1", 69: "$wf_parameter_meta = :parameter_meta $map -> ParameterMeta( map=$1 )", 70: "$wf_meta = :meta $map -> Meta( map=$1 )", 71: "$while_loop = :while :lparen $e :rparen :lbrace $_gen10 :rbrace -> WhileLoop( expression=$2, body=$5 )", 72: "$if_stmt = :if :lparen $e :rparen :lbrace $_gen10 :rbrace -> If( expression=$2, body=$5 )", 73: "$scatter = :scatter :lparen :identifier :in $e :rparen :lbrace $_gen10 :rbrace -> Scatter( item=$2, collection=$4, body=$7 )", 74: "$object_kv = :identifier :colon $e -> ObjectKV( key=$0, value=$2 )", 75: "$_gen17 = list($type_e, :comma)", 76: "$type_e = :type <=> :lsquare $_gen17 :rsquare -> Type( name=$0, subtype=$2 )", 77: "$type_e = :type <=> :qmark -> OptionalType( innerType=$0 )", 78: "$type_e = :type <=> :plus -> NonEmptyType( innerType=$0 )", 79: "$type_e = :type", 80: "$e = $e :double_pipe $e -> LogicalOr( lhs=$0, rhs=$2 )", 81: "$e = $e :double_ampersand $e -> LogicalAnd( lhs=$0, rhs=$2 )", 82: "$e = $e :double_equal $e -> Equals( lhs=$0, rhs=$2 )", 83: "$e = $e :not_equal $e -> NotEquals( lhs=$0, rhs=$2 )", 84: "$e = $e :lt $e -> LessThan( lhs=$0, rhs=$2 )", 85: "$e = $e :lteq $e -> LessThanOrEqual( lhs=$0, rhs=$2 )", 86: "$e = $e :gt $e -> GreaterThan( lhs=$0, rhs=$2 )", 87: "$e = $e :gteq $e -> GreaterThanOrEqual( lhs=$0, rhs=$2 )", 88: "$e = $e :plus $e -> Add( lhs=$0, rhs=$2 )", 89: "$e = $e :dash $e -> Subtract( lhs=$0, rhs=$2 )", 90: "$e = $e :asterisk $e -> Multiply( lhs=$0, rhs=$2 )", 91: "$e = $e :slash $e -> Divide( lhs=$0, rhs=$2 )", 92: "$e = $e :percent $e -> Remainder( lhs=$0, rhs=$2 )", 93: "$e = :not $e -> LogicalNot( expression=$1 )", 94: "$e = :plus $e -> UnaryPlus( expression=$1 )", 95: "$e = :dash $e -> UnaryNegation( expression=$1 )", 96: "$_gen18 = list($e, :comma)", 97: "$e = :identifier <=> :lparen $_gen18 :rparen -> FunctionCall( name=$0, params=$2 )", 98: "$e = :identifier <=> :lsquare $e :rsquare -> ArrayOrMapLookup( lhs=$0, rhs=$2 )", 99: "$e = :identifier <=> :dot :identifier -> MemberAccess( lhs=$0, rhs=$2 )", 100: "$_gen19 = list($object_kv, :comma)", 101: "$e = :object :lbrace $_gen19 :rbrace -> ObjectLiteral( map=$2 )", 102: "$e = :lsquare $_gen18 :rsquare -> ArrayLiteral( values=$1 )", 103: "$_gen20 = list($map_kv, :comma)", 104: "$e = :lbrace $_gen20 :rbrace -> MapLiteral( map=$1 )", 105: "$e = :lparen $_gen18 :rparen -> TupleLiteral( values=$1 )", 106: "$e = :if $e :then $e :else $e -> TernaryIf( cond=$1, iftrue=$3, iffalse=$5 )", 107: "$e = :string", 108: "$e = :identifier", 109: "$e = :boolean", 110: "$e = :integer", 111: "$e = :float", } def is_terminal(id): return isinstance(id, int) and 0 <= id <= 57 def parse(tokens, errors=None, start=None): if errors is None: errors = DefaultSyntaxErrorHandler() if isinstance(tokens, str): tokens = lex(tokens, 'string', errors) ctx = ParserContext(tokens, errors) tree = parse_document(ctx) if tokens.current() != None: raise ctx.errors.excess_tokens() return tree def expect(ctx, terminal_id): current = ctx.tokens.current() if not current: raise ctx.errors.no_more_tokens(ctx.nonterminal, terminals[terminal_id], ctx.tokens.last()) if current.id != terminal_id: raise ctx.errors.unexpected_symbol(ctx.nonterminal, current, [terminals[terminal_id]], ctx.rule) next = ctx.tokens.advance() if next and not is_terminal(next.id): raise ctx.errors.invalid_terminal(ctx.nonterminal, next) return current # START definitions for expression parser: e infix_binding_power_e = { 23: 4000, # $e = $e :double_pipe $e -> LogicalOr( lhs=$0, rhs=$2 ) 47: 5000, # $e = $e :double_ampersand $e -> LogicalAnd( lhs=$0, rhs=$2 ) 24: 6000, # $e = $e :double_equal $e -> Equals( lhs=$0, rhs=$2 ) 2: 6000, # $e = $e :not_equal $e -> NotEquals( lhs=$0, rhs=$2 ) 36: 7000, # $e = $e :lt $e -> LessThan( lhs=$0, rhs=$2 ) 15: 7000, # $e = $e :lteq $e -> LessThanOrEqual( lhs=$0, rhs=$2 ) 49: 7000, # $e = $e :gt $e -> GreaterThan( lhs=$0, rhs=$2 ) 56: 7000, # $e = $e :gteq $e -> GreaterThanOrEqual( lhs=$0, rhs=$2 ) 11: 8000, # $e = $e :plus $e -> Add( lhs=$0, rhs=$2 ) 1: 8000, # $e = $e :dash $e -> Subtract( lhs=$0, rhs=$2 ) 17: 9000, # $e = $e :asterisk $e -> Multiply( lhs=$0, rhs=$2 ) 37: 9000, # $e = $e :slash $e -> Divide( lhs=$0, rhs=$2 ) 57: 9000, # $e = $e :percent $e -> Remainder( lhs=$0, rhs=$2 ) 20: 11000, # $e = :identifier <=> :lparen list($e, :comma) :rparen -> FunctionCall( name=$0, params=$2 ) 46: 12000, # $e = :identifier <=> :lsquare $e :rsquare -> ArrayOrMapLookup( lhs=$0, rhs=$2 ) 7: 13000, # $e = :identifier <=> :dot :identifier -> MemberAccess( lhs=$0, rhs=$2 ) } prefix_binding_power_e = { 12: 10000, # $e = :not $e -> LogicalNot( expression=$1 ) 11: 10000, # $e = :plus $e -> UnaryPlus( expression=$1 ) 1: 10000, # $e = :dash $e -> UnaryNegation( expression=$1 ) } def get_infix_binding_power_e(terminal_id): try: return infix_binding_power_e[terminal_id] except: return 0 def get_prefix_binding_power_e(terminal_id): try: return prefix_binding_power_e[terminal_id] except: return 0 def parse_e(ctx): return parse_e_internal(ctx, rbp=0) def parse_e_internal(ctx, rbp=0): left = nud_e(ctx) if isinstance(left, ParseTree): left.isExpr = True left.isNud = True while ctx.tokens.current() and rbp < get_infix_binding_power_e(ctx.tokens.current().id): left = led_e(left, ctx) if left: left.isExpr = True return left def nud_e(ctx): tree = ParseTree(NonTerminal(117, 'e')) current = ctx.tokens.current() ctx.nonterminal = "e" if not current: return tree elif current.id in rule_first[93]: # rule first == not # e first == dash, e, boolean, lbrace, integer, float, lsquare, if, string, lparen, not, plus, object, identifier # $e = :not $e -> LogicalNot( expression=$1 ) ctx.rule = rules[93] ast_parameters = OrderedDict([ ('expression', 1), ]) tree.astTransform = AstTransformNodeCreator('LogicalNot', ast_parameters) tree.nudMorphemeCount = 2 tree.add(expect(ctx, 12)) tree.add(parse_e_internal(ctx, get_prefix_binding_power_e(12))) tree.isPrefix = True elif current.id in rule_first[94]: # rule first == plus # e first == dash, e, boolean, lbrace, integer, float, lsquare, if, string, lparen, not, plus, object, identifier # $e = :plus $e -> UnaryPlus( expression=$1 ) ctx.rule = rules[94] ast_parameters = OrderedDict([ ('expression', 1), ]) tree.astTransform = AstTransformNodeCreator('UnaryPlus', ast_parameters) tree.nudMorphemeCount = 2 tree.add(expect(ctx, 11)) tree.add(parse_e_internal(ctx, get_prefix_binding_power_e(11))) tree.isPrefix = True elif current.id in rule_first[95]: # rule first == dash # e first == dash, e, boolean, lbrace, integer, float, lsquare, if, string, lparen, not, plus, object, identifier # $e = :dash $e -> UnaryNegation( expression=$1 ) ctx.rule = rules[95] ast_parameters = OrderedDict([ ('expression', 1), ]) tree.astTransform = AstTransformNodeCreator('UnaryNegation', ast_parameters) tree.nudMorphemeCount = 2 tree.add(expect(ctx, 1)) tree.add(parse_e_internal(ctx, get_prefix_binding_power_e(1))) tree.isPrefix = True elif current.id in rule_first[97]: # rule first == identifier # e first == dash, e, boolean, lbrace, integer, float, lsquare, if, string, lparen, not, plus, object, identifier # $e = :identifier <=> :lparen $_gen18 :rparen -> FunctionCall( name=$0, params=$2 ) ctx.rule = rules[97] tree.astTransform = AstTransformSubstitution(0) tree.nudMorphemeCount = 1 tree.add(expect(ctx, 50)) elif current.id in rule_first[98]: # rule first == identifier # e first == dash, e, boolean, lbrace, integer, float, lsquare, if, string, lparen, not, plus, object, identifier # $e = :identifier <=> :lsquare $e :rsquare -> ArrayOrMapLookup( lhs=$0, rhs=$2 ) ctx.rule = rules[98] tree.astTransform = AstTransformSubstitution(0) tree.nudMorphemeCount = 1 tree.add(expect(ctx, 50)) elif current.id in rule_first[99]: # rule first == identifier # e first == dash, e, boolean, lbrace, integer, float, lsquare, if, string, lparen, not, plus, object, identifier # $e = :identifier <=> :dot :identifier -> MemberAccess( lhs=$0, rhs=$2 ) ctx.rule = rules[99] tree.astTransform = AstTransformSubstitution(0) tree.nudMorphemeCount = 1 tree.add(expect(ctx, 50)) elif current.id in rule_first[101]: # rule first == object # e first == dash, e, boolean, lbrace, integer, float, lsquare, if, string, lparen, not, plus, object, identifier # $e = :object :lbrace $_gen19 :rbrace -> ObjectLiteral( map=$2 ) ctx.rule = rules[101] ast_parameters = OrderedDict([ ('map', 2), ]) tree.astTransform = AstTransformNodeCreator('ObjectLiteral', ast_parameters) tree.nudMorphemeCount = 4 tree.add(expect(ctx, 52)) tree.add(expect(ctx, 16)) tree.add(parse__gen19(ctx)) tree.add(expect(ctx, 44)) elif current.id in rule_first[102]: # rule first == lsquare # e first == dash, e, boolean, lbrace, integer, float, lsquare, if, string, lparen, not, plus, object, identifier # $e = :lsquare $_gen18 :rsquare -> ArrayLiteral( values=$1 ) ctx.rule = rules[102] ast_parameters = OrderedDict([ ('values', 1), ]) tree.astTransform = AstTransformNodeCreator('ArrayLiteral', ast_parameters) tree.nudMorphemeCount = 3 tree.add(expect(ctx, 46)) tree.add(parse__gen18(ctx)) tree.add(expect(ctx, 8)) elif current.id in rule_first[104]: # rule first == lbrace # e first == dash, e, boolean, lbrace, integer, float, lsquare, if, string, lparen, not, plus, object, identifier # $e = :lbrace $_gen20 :rbrace -> MapLiteral( map=$1 ) ctx.rule = rules[104] ast_parameters = OrderedDict([ ('map', 1), ]) tree.astTransform = AstTransformNodeCreator('MapLiteral', ast_parameters) tree.nudMorphemeCount = 3 tree.add(expect(ctx, 16)) tree.add(parse__gen20(ctx)) tree.add(expect(ctx, 44)) elif current.id in rule_first[105]: # rule first == lparen # e first == dash, e, boolean, lbrace, integer, float, lsquare, if, string, lparen, not, plus, object, identifier # $e = :lparen $_gen18 :rparen -> TupleLiteral( values=$1 ) ctx.rule = rules[105] ast_parameters = OrderedDict([ ('values', 1), ]) tree.astTransform = AstTransformNodeCreator('TupleLiteral', ast_parameters) tree.nudMorphemeCount = 3 tree.add(expect(ctx, 20)) tree.add(parse__gen18(ctx)) tree.add(expect(ctx, 45)) elif current.id in rule_first[106]: # rule first == if # e first == dash, e, boolean, lbrace, integer, float, lsquare, if, string, lparen, not, plus, object, identifier # $e = :if $e :then $e :else $e -> TernaryIf( cond=$1, iftrue=$3, iffalse=$5 ) ctx.rule = rules[106] ast_parameters = OrderedDict([ ('cond', 1), ('iftrue', 3), ('iffalse', 5), ]) tree.astTransform = AstTransformNodeCreator('TernaryIf', ast_parameters) tree.nudMorphemeCount = 6 tree.add(expect(ctx, 18)) tree.add(parse_e(ctx)) tree.add(expect(ctx, 31)) tree.add(parse_e(ctx)) tree.add(expect(ctx, 21)) tree.add(parse_e(ctx)) elif current.id in rule_first[107]: # rule first == string # e first == dash, e, boolean, lbrace, integer, float, lsquare, if, string, lparen, not, plus, object, identifier # $e = :string ctx.rule = rules[107] tree.astTransform = AstTransformSubstitution(0) tree.nudMorphemeCount = 1 tree.add(expect(ctx, 42)) elif current.id in rule_first[108]: # rule first == identifier # e first == dash, e, boolean, lbrace, integer, float, lsquare, if, string, lparen, not, plus, object, identifier # $e = :identifier ctx.rule = rules[108] tree.astTransform = AstTransformSubstitution(0) tree.nudMorphemeCount = 1 tree.add(expect(ctx, 50)) elif current.id in rule_first[109]: # rule first == boolean # e first == dash, e, boolean, lbrace, integer, float, lsquare, if, string, lparen, not, plus, object, identifier # $e = :boolean ctx.rule = rules[109] tree.astTransform = AstTransformSubstitution(0) tree.nudMorphemeCount = 1 tree.add(expect(ctx, 3)) elif current.id in rule_first[110]: # rule first == integer # e first == dash, e, boolean, lbrace, integer, float, lsquare, if, string, lparen, not, plus, object, identifier # $e = :integer ctx.rule = rules[110] tree.astTransform = AstTransformSubstitution(0) tree.nudMorphemeCount = 1 tree.add(expect(ctx, 39)) elif current.id in rule_first[111]: # rule first == float # e first == dash, e, boolean, lbrace, integer, float, lsquare, if, string, lparen, not, plus, object, identifier # $e = :float ctx.rule = rules[111] tree.astTransform = AstTransformSubstitution(0) tree.nudMorphemeCount = 1 tree.add(expect(ctx, 4)) return tree def led_e(left, ctx): tree = ParseTree(NonTerminal(117, 'e')) current = ctx.tokens.current() ctx.nonterminal = "e" if current.id == 23: # :double_pipe # $e = $e :double_pipe $e -> LogicalOr( lhs=$0, rhs=$2 ) ctx.rule = rules[80] ast_parameters = OrderedDict([ ('lhs', 0), ('rhs', 2), ]) tree.astTransform = AstTransformNodeCreator('LogicalOr', ast_parameters) tree.isExprNud = True tree.add(left) tree.add(expect(ctx, 23)) # :double_pipe modifier = 0 tree.isInfix = True tree.add(parse_e_internal(ctx, get_infix_binding_power_e(23) - modifier)) if current.id == 47: # :double_ampersand # $e = $e :double_ampersand $e -> LogicalAnd( lhs=$0, rhs=$2 ) ctx.rule = rules[81] ast_parameters = OrderedDict([ ('lhs', 0), ('rhs', 2), ]) tree.astTransform = AstTransformNodeCreator('LogicalAnd', ast_parameters) tree.isExprNud = True tree.add(left) tree.add(expect(ctx, 47)) # :double_ampersand modifier = 0 tree.isInfix = True tree.add(parse_e_internal(ctx, get_infix_binding_power_e(47) - modifier)) if current.id == 24: # :double_equal # $e = $e :double_equal $e -> Equals( lhs=$0, rhs=$2 ) ctx.rule = rules[82] ast_parameters = OrderedDict([ ('lhs', 0), ('rhs', 2), ]) tree.astTransform = AstTransformNodeCreator('Equals', ast_parameters) tree.isExprNud = True tree.add(left) tree.add(expect(ctx, 24)) # :double_equal modifier = 0 tree.isInfix = True tree.add(parse_e_internal(ctx, get_infix_binding_power_e(24) - modifier)) if current.id == 2: # :not_equal # $e = $e :not_equal $e -> NotEquals( lhs=$0, rhs=$2 ) ctx.rule = rules[83] ast_parameters = OrderedDict([ ('lhs', 0), ('rhs', 2), ]) tree.astTransform = AstTransformNodeCreator('NotEquals', ast_parameters) tree.isExprNud = True tree.add(left) tree.add(expect(ctx, 2)) # :not_equal modifier = 0 tree.isInfix = True tree.add(parse_e_internal(ctx, get_infix_binding_power_e(2) - modifier)) if current.id == 36: # :lt # $e = $e :lt $e -> LessThan( lhs=$0, rhs=$2 ) ctx.rule = rules[84] ast_parameters = OrderedDict([ ('lhs', 0), ('rhs', 2), ]) tree.astTransform = AstTransformNodeCreator('LessThan', ast_parameters) tree.isExprNud = True tree.add(left) tree.add(expect(ctx, 36)) # :lt modifier = 0 tree.isInfix = True tree.add(parse_e_internal(ctx, get_infix_binding_power_e(36) - modifier)) if current.id == 15: # :lteq # $e = $e :lteq $e -> LessThanOrEqual( lhs=$0, rhs=$2 ) ctx.rule = rules[85] ast_parameters = OrderedDict([ ('lhs', 0), ('rhs', 2), ]) tree.astTransform = AstTransformNodeCreator('LessThanOrEqual', ast_parameters) tree.isExprNud = True tree.add(left) tree.add(expect(ctx, 15)) # :lteq modifier = 0 tree.isInfix = True tree.add(parse_e_internal(ctx, get_infix_binding_power_e(15) - modifier)) if current.id == 49: # :gt # $e = $e :gt $e -> GreaterThan( lhs=$0, rhs=$2 ) ctx.rule = rules[86] ast_parameters = OrderedDict([ ('lhs', 0), ('rhs', 2), ]) tree.astTransform = AstTransformNodeCreator('GreaterThan', ast_parameters) tree.isExprNud = True tree.add(left) tree.add(expect(ctx, 49)) # :gt modifier = 0 tree.isInfix = True tree.add(parse_e_internal(ctx, get_infix_binding_power_e(49) - modifier)) if current.id == 56: # :gteq # $e = $e :gteq $e -> GreaterThanOrEqual( lhs=$0, rhs=$2 ) ctx.rule = rules[87] ast_parameters = OrderedDict([ ('lhs', 0), ('rhs', 2), ]) tree.astTransform = AstTransformNodeCreator('GreaterThanOrEqual', ast_parameters) tree.isExprNud = True tree.add(left) tree.add(expect(ctx, 56)) # :gteq modifier = 0 tree.isInfix = True tree.add(parse_e_internal(ctx, get_infix_binding_power_e(56) - modifier)) if current.id == 11: # :plus # $e = $e :plus $e -> Add( lhs=$0, rhs=$2 ) ctx.rule = rules[88] ast_parameters = OrderedDict([ ('lhs', 0), ('rhs', 2), ]) tree.astTransform = AstTransformNodeCreator('Add', ast_parameters) tree.isExprNud = True tree.add(left) tree.add(expect(ctx, 11)) # :plus modifier = 0 tree.isInfix = True tree.add(parse_e_internal(ctx, get_infix_binding_power_e(11) - modifier)) if current.id == 1: # :dash # $e = $e :dash $e -> Subtract( lhs=$0, rhs=$2 ) ctx.rule = rules[89] ast_parameters = OrderedDict([ ('lhs', 0), ('rhs', 2), ]) tree.astTransform = AstTransformNodeCreator('Subtract', ast_parameters) tree.isExprNud = True tree.add(left) tree.add(expect(ctx, 1)) # :dash modifier = 0 tree.isInfix = True tree.add(parse_e_internal(ctx, get_infix_binding_power_e(1) - modifier)) if current.id == 17: # :asterisk # $e = $e :asterisk $e -> Multiply( lhs=$0, rhs=$2 ) ctx.rule = rules[90] ast_parameters = OrderedDict([ ('lhs', 0), ('rhs', 2), ]) tree.astTransform = AstTransformNodeCreator('Multiply', ast_parameters) tree.isExprNud = True tree.add(left) tree.add(expect(ctx, 17)) # :asterisk modifier = 0 tree.isInfix = True tree.add(parse_e_internal(ctx, get_infix_binding_power_e(17) - modifier)) if current.id == 37: # :slash # $e = $e :slash $e -> Divide( lhs=$0, rhs=$2 ) ctx.rule = rules[91] ast_parameters = OrderedDict([ ('lhs', 0), ('rhs', 2), ]) tree.astTransform = AstTransformNodeCreator('Divide', ast_parameters) tree.isExprNud = True tree.add(left) tree.add(expect(ctx, 37)) # :slash modifier = 0 tree.isInfix = True tree.add(parse_e_internal(ctx, get_infix_binding_power_e(37) - modifier)) if current.id == 57: # :percent # $e = $e :percent $e -> Remainder( lhs=$0, rhs=$2 ) ctx.rule = rules[92] ast_parameters = OrderedDict([ ('lhs', 0), ('rhs', 2), ]) tree.astTransform = AstTransformNodeCreator('Remainder', ast_parameters) tree.isExprNud = True tree.add(left) tree.add(expect(ctx, 57)) # :percent modifier = 0 tree.isInfix = True tree.add(parse_e_internal(ctx, get_infix_binding_power_e(57) - modifier)) if current.id == 20: # :lparen # $e = :identifier <=> :lparen $_gen18 :rparen -> FunctionCall( name=$0, params=$2 ) ctx.rule = rules[97] ast_parameters = OrderedDict([ ('name', 0), ('params', 2), ]) tree.astTransform = AstTransformNodeCreator('FunctionCall', ast_parameters) tree.add(left) tree.add(expect(ctx, 20)) # :lparen tree.add(parse__gen18(ctx)) tree.add(expect(ctx, 45)) # :rparen if current.id == 46: # :lsquare # $e = :identifier <=> :lsquare $e :rsquare -> ArrayOrMapLookup( lhs=$0, rhs=$2 ) ctx.rule = rules[98] ast_parameters = OrderedDict([ ('lhs', 0), ('rhs', 2), ]) tree.astTransform = AstTransformNodeCreator('ArrayOrMapLookup', ast_parameters) tree.add(left) tree.add(expect(ctx, 46)) # :lsquare modifier = 0 tree.add(parse_e_internal(ctx, get_infix_binding_power_e(46) - modifier)) tree.add(expect(ctx, 8)) # :rsquare if current.id == 7: # :dot # $e = :identifier <=> :dot :identifier -> MemberAccess( lhs=$0, rhs=$2 ) ctx.rule = rules[99] ast_parameters = OrderedDict([ ('lhs', 0), ('rhs', 2), ]) tree.astTransform = AstTransformNodeCreator('MemberAccess', ast_parameters) tree.add(left) tree.add(expect(ctx, 7)) # :dot tree.add(expect(ctx, 50)) # :identifier return tree # END definitions for expression parser: e # START definitions for expression parser: type_e infix_binding_power_type_e = { 46: 1000, # $type_e = :type <=> :lsquare list($type_e, :comma) :rsquare -> Type( name=$0, subtype=$2 ) 33: 2000, # $type_e = :type <=> :qmark -> OptionalType( innerType=$0 ) 11: 3000, # $type_e = :type <=> :plus -> NonEmptyType( innerType=$0 ) } prefix_binding_power_type_e = { } def get_infix_binding_power_type_e(terminal_id): try: return infix_binding_power_type_e[terminal_id] except: return 0 def get_prefix_binding_power_type_e(terminal_id): try: return prefix_binding_power_type_e[terminal_id] except: return 0 def parse_type_e(ctx): return parse_type_e_internal(ctx, rbp=0) def parse_type_e_internal(ctx, rbp=0): left = nud_type_e(ctx) if isinstance(left, ParseTree): left.isExpr = True left.isNud = True while ctx.tokens.current() and rbp < get_infix_binding_power_type_e(ctx.tokens.current().id): left = led_type_e(left, ctx) if left: left.isExpr = True return left def nud_type_e(ctx): tree = ParseTree(NonTerminal(80, 'type_e')) current = ctx.tokens.current() ctx.nonterminal = "type_e" if not current: return tree if current.id in rule_first[76]: # rule first == type # e first == type_e, type # $type_e = :type <=> :lsquare $_gen17 :rsquare -> Type( name=$0, subtype=$2 ) ctx.rule = rules[76] tree.astTransform = AstTransformSubstitution(0) tree.nudMorphemeCount = 1 tree.add(expect(ctx, 48)) elif current.id in rule_first[77]: # rule first == type # e first == type_e, type # $type_e = :type <=> :qmark -> OptionalType( innerType=$0 ) ctx.rule = rules[77] tree.astTransform = AstTransformSubstitution(0) tree.nudMorphemeCount = 1 tree.add(expect(ctx, 48)) elif current.id in rule_first[78]: # rule first == type # e first == type_e, type # $type_e = :type <=> :plus -> NonEmptyType( innerType=$0 ) ctx.rule = rules[78] tree.astTransform = AstTransformSubstitution(0) tree.nudMorphemeCount = 1 tree.add(expect(ctx, 48)) elif current.id in rule_first[79]: # rule first == type # e first == type_e, type # $type_e = :type ctx.rule = rules[79] tree.astTransform = AstTransformSubstitution(0) tree.nudMorphemeCount = 1 tree.add(expect(ctx, 48)) return tree def led_type_e(left, ctx): tree = ParseTree(NonTerminal(80, 'type_e')) current = ctx.tokens.current() ctx.nonterminal = "type_e" if current.id == 46: # :lsquare # $type_e = :type <=> :lsquare $_gen17 :rsquare -> Type( name=$0, subtype=$2 ) ctx.rule = rules[76] ast_parameters = OrderedDict([ ('name', 0), ('subtype', 2), ]) tree.astTransform = AstTransformNodeCreator('Type', ast_parameters) tree.add(left) tree.add(expect(ctx, 46)) # :lsquare tree.add(parse__gen17(ctx)) tree.add(expect(ctx, 8)) # :rsquare if current.id == 33: # :qmark # $type_e = :type <=> :qmark -> OptionalType( innerType=$0 ) ctx.rule = rules[77] ast_parameters = OrderedDict([ ('innerType', 0), ]) tree.astTransform = AstTransformNodeCreator('OptionalType', ast_parameters) tree.add(left) tree.add(expect(ctx, 33)) # :qmark if current.id == 11: # :plus # $type_e = :type <=> :plus -> NonEmptyType( innerType=$0 ) ctx.rule = rules[78] ast_parameters = OrderedDict([ ('innerType', 0), ]) tree.astTransform = AstTransformNodeCreator('NonEmptyType', ast_parameters) tree.add(left) tree.add(expect(ctx, 11)) # :plus return tree # END definitions for expression parser: type_e def parse__gen0(ctx): tree = ParseTree(NonTerminal(59, '_gen0')) tree.list = True ctx.nonterminal = "_gen0" if ctx.tokens.current() is not None and \ ctx.tokens.current().id not in nonterminal_first[59] and \ ctx.tokens.current().id in nonterminal_follow[59]: return tree if ctx.tokens.current() is None: return tree minimum = 0 while minimum > 0 or \ (ctx.tokens.current() is not None and \ ctx.tokens.current().id in nonterminal_first.get(59)): tree.add(parse_import(ctx)) ctx.nonterminal = "_gen0" # Horrible -- because parse_* can reset this minimum = max(minimum - 1, 0) return tree def parse__gen1(ctx): tree = ParseTree(NonTerminal(110, '_gen1')) tree.list = True ctx.nonterminal = "_gen1" if ctx.tokens.current() is not None and \ ctx.tokens.current().id not in nonterminal_first[110] and \ ctx.tokens.current().id in nonterminal_follow[110]: return tree if ctx.tokens.current() is None: return tree minimum = 0 while minimum > 0 or \ (ctx.tokens.current() is not None and \ ctx.tokens.current().id in nonterminal_first.get(110)): tree.add(parse_workflow_or_task_or_decl(ctx)) ctx.nonterminal = "_gen1" # Horrible -- because parse_* can reset this minimum = max(minimum - 1, 0) return tree def parse__gen10(ctx): tree = ParseTree(NonTerminal(74, '_gen10')) tree.list = True ctx.nonterminal = "_gen10" if ctx.tokens.current() is not None and \ ctx.tokens.current().id not in nonterminal_first[74] and \ ctx.tokens.current().id in nonterminal_follow[74]: return tree if ctx.tokens.current() is None: return tree minimum = 0 while minimum > 0 or \ (ctx.tokens.current() is not None and \ ctx.tokens.current().id in nonterminal_first.get(74)): tree.add(parse_wf_body_element(ctx)) ctx.nonterminal = "_gen10" # Horrible -- because parse_* can reset this minimum = max(minimum - 1, 0) return tree def parse__gen13(ctx): tree = ParseTree(NonTerminal(89, '_gen13')) tree.list = True ctx.nonterminal = "_gen13" if ctx.tokens.current() is not None and \ ctx.tokens.current().id not in nonterminal_first[89] and \ ctx.tokens.current().id in nonterminal_follow[89]: return tree if ctx.tokens.current() is None: return tree minimum = 0 while minimum > 0 or \ (ctx.tokens.current() is not None and \ ctx.tokens.current().id in nonterminal_first.get(89)): tree.add(parse_call_input(ctx)) ctx.nonterminal = "_gen13" # Horrible -- because parse_* can reset this minimum = max(minimum - 1, 0) return tree def parse__gen14(ctx): tree = ParseTree(NonTerminal(84, '_gen14')) tree.list = True tree.list_separator_id = 43 ctx.nonterminal = "_gen14" if ctx.tokens.current() is not None and \ ctx.tokens.current().id not in nonterminal_first[84] and \ ctx.tokens.current().id in nonterminal_follow[84]: return tree if ctx.tokens.current() is None: return tree minimum = 0 while minimum > 0 or \ (ctx.tokens.current() is not None and \ ctx.tokens.current().id in nonterminal_first.get(84)): tree.add(parse_mapping(ctx)) ctx.nonterminal = "_gen14" # Horrible -- because parse_* can reset this if ctx.tokens.current() is not None and ctx.tokens.current().id == 43: tree.add(expect(ctx, 43)); else: break minimum = max(minimum - 1, 0) return tree def parse__gen15(ctx): tree = ParseTree(NonTerminal(62, '_gen15')) tree.list = True ctx.nonterminal = "_gen15" if ctx.tokens.current() is not None and \ ctx.tokens.current().id not in nonterminal_first[62] and \ ctx.tokens.current().id in nonterminal_follow[62]: return tree if ctx.tokens.current() is None: return tree minimum = 0 while minimum > 0 or \ (ctx.tokens.current() is not None and \ ctx.tokens.current().id in nonterminal_first.get(62)): tree.add(parse_wf_output(ctx)) ctx.nonterminal = "_gen15" # Horrible -- because parse_* can reset this minimum = max(minimum - 1, 0) return tree def parse__gen17(ctx): tree = ParseTree(NonTerminal(96, '_gen17')) tree.list = True tree.list_separator_id = 43 ctx.nonterminal = "_gen17" if ctx.tokens.current() is not None and \ ctx.tokens.current().id not in nonterminal_first[96] and \ ctx.tokens.current().id in nonterminal_follow[96]: return tree if ctx.tokens.current() is None: return tree minimum = 0 while minimum > 0 or \ (ctx.tokens.current() is not None and \ ctx.tokens.current().id in nonterminal_first.get(96)): tree.add(parse_type_e(ctx)) ctx.nonterminal = "_gen17" # Horrible -- because parse_* can reset this if ctx.tokens.current() is not None and ctx.tokens.current().id == 43: tree.add(expect(ctx, 43)); else: break minimum = max(minimum - 1, 0) return tree def parse__gen18(ctx): tree = ParseTree(NonTerminal(118, '_gen18')) tree.list = True tree.list_separator_id = 43 ctx.nonterminal = "_gen18" if ctx.tokens.current() is not None and \ ctx.tokens.current().id not in nonterminal_first[118] and \ ctx.tokens.current().id in nonterminal_follow[118]: return tree if ctx.tokens.current() is None: return tree minimum = 0 while minimum > 0 or \ (ctx.tokens.current() is not None and \ ctx.tokens.current().id in nonterminal_first.get(118)): tree.add(parse_e(ctx)) ctx.nonterminal = "_gen18" # Horrible -- because parse_* can reset this if ctx.tokens.current() is not None and ctx.tokens.current().id == 43: tree.add(expect(ctx, 43)); else: break minimum = max(minimum - 1, 0) return tree def parse__gen19(ctx): tree = ParseTree(NonTerminal(100, '_gen19')) tree.list = True tree.list_separator_id = 43 ctx.nonterminal = "_gen19" if ctx.tokens.current() is not None and \ ctx.tokens.current().id not in nonterminal_first[100] and \ ctx.tokens.current().id in nonterminal_follow[100]: return tree if ctx.tokens.current() is None: return tree minimum = 0 while minimum > 0 or \ (ctx.tokens.current() is not None and \ ctx.tokens.current().id in nonterminal_first.get(100)): tree.add(parse_object_kv(ctx)) ctx.nonterminal = "_gen19" # Horrible -- because parse_* can reset this if ctx.tokens.current() is not None and ctx.tokens.current().id == 43: tree.add(expect(ctx, 43)); else: break minimum = max(minimum - 1, 0) return tree def parse__gen20(ctx): tree = ParseTree(NonTerminal(93, '_gen20')) tree.list = True tree.list_separator_id = 43 ctx.nonterminal = "_gen20" if ctx.tokens.current() is not None and \ ctx.tokens.current().id not in nonterminal_first[93] and \ ctx.tokens.current().id in nonterminal_follow[93]: return tree if ctx.tokens.current() is None: return tree minimum = 0 while minimum > 0 or \ (ctx.tokens.current() is not None and \ ctx.tokens.current().id in nonterminal_first.get(93)): tree.add(parse_map_kv(ctx)) ctx.nonterminal = "_gen20" # Horrible -- because parse_* can reset this if ctx.tokens.current() is not None and ctx.tokens.current().id == 43: tree.add(expect(ctx, 43)); else: break minimum = max(minimum - 1, 0) return tree def parse__gen3(ctx): tree = ParseTree(NonTerminal(72, '_gen3')) tree.list = True ctx.nonterminal = "_gen3" if ctx.tokens.current() is not None and \ ctx.tokens.current().id not in nonterminal_first[72] and \ ctx.tokens.current().id in nonterminal_follow[72]: return tree if ctx.tokens.current() is None: return tree minimum = 0 while minimum > 0 or \ (ctx.tokens.current() is not None and \ ctx.tokens.current().id in nonterminal_first.get(72)): tree.add(parse_declaration(ctx)) ctx.nonterminal = "_gen3" # Horrible -- because parse_* can reset this minimum = max(minimum - 1, 0) return tree def parse__gen4(ctx): tree = ParseTree(NonTerminal(91, '_gen4')) tree.list = True ctx.nonterminal = "_gen4" if ctx.tokens.current() is not None and \ ctx.tokens.current().id not in nonterminal_first[91] and \ ctx.tokens.current().id in nonterminal_follow[91]: return tree if ctx.tokens.current() is None: return tree minimum = 0 while minimum > 0 or \ (ctx.tokens.current() is not None and \ ctx.tokens.current().id in nonterminal_first.get(91)): tree.add(parse_sections(ctx)) ctx.nonterminal = "_gen4" # Horrible -- because parse_* can reset this minimum = max(minimum - 1, 0) return tree def parse__gen5(ctx): tree = ParseTree(NonTerminal(106, '_gen5')) tree.list = True ctx.nonterminal = "_gen5" if ctx.tokens.current() is not None and \ ctx.tokens.current().id not in nonterminal_first[106] and \ ctx.tokens.current().id in nonterminal_follow[106]: return tree if ctx.tokens.current() is None: return tree minimum = 0 while minimum > 0 or \ (ctx.tokens.current() is not None and \ ctx.tokens.current().id in nonterminal_first.get(106)): tree.add(parse_command_part(ctx)) ctx.nonterminal = "_gen5" # Horrible -- because parse_* can reset this minimum = max(minimum - 1, 0) return tree def parse__gen6(ctx): tree = ParseTree(NonTerminal(102, '_gen6')) tree.list = True ctx.nonterminal = "_gen6" if ctx.tokens.current() is not None and \ ctx.tokens.current().id not in nonterminal_first[102] and \ ctx.tokens.current().id in nonterminal_follow[102]: return tree if ctx.tokens.current() is None: return tree minimum = 0 while minimum > 0 or \ (ctx.tokens.current() is not None and \ ctx.tokens.current().id in nonterminal_first.get(102)): tree.add(parse_cmd_param_kv(ctx)) ctx.nonterminal = "_gen6" # Horrible -- because parse_* can reset this minimum = max(minimum - 1, 0) return tree def parse__gen7(ctx): tree = ParseTree(NonTerminal(103, '_gen7')) tree.list = True ctx.nonterminal = "_gen7" if ctx.tokens.current() is not None and \ ctx.tokens.current().id not in nonterminal_first[103] and \ ctx.tokens.current().id in nonterminal_follow[103]: return tree if ctx.tokens.current() is None: return tree minimum = 0 while minimum > 0 or \ (ctx.tokens.current() is not None and \ ctx.tokens.current().id in nonterminal_first.get(103)): tree.add(parse_output_kv(ctx)) ctx.nonterminal = "_gen7" # Horrible -- because parse_* can reset this minimum = max(minimum - 1, 0) return tree def parse__gen8(ctx): tree = ParseTree(NonTerminal(83, '_gen8')) tree.list = True ctx.nonterminal = "_gen8" if ctx.tokens.current() is not None and \ ctx.tokens.current().id not in nonterminal_first[83] and \ ctx.tokens.current().id in nonterminal_follow[83]: return tree if ctx.tokens.current() is None: return tree minimum = 0 while minimum > 0 or \ (ctx.tokens.current() is not None and \ ctx.tokens.current().id in nonterminal_first.get(83)): tree.add(parse_kv(ctx)) ctx.nonterminal = "_gen8" # Horrible -- because parse_* can reset this minimum = max(minimum - 1, 0) return tree def parse__gen11(ctx): current = ctx.tokens.current() rule = table[46][current.id] if current else -1 tree = ParseTree(NonTerminal(104, '_gen11')) ctx.nonterminal = "_gen11" if current != None and current.id in nonterminal_follow[104] and current.id not in nonterminal_first[104]: return tree if current == None: return tree if rule == 49: # $_gen11 = $alias ctx.rule = rules[49] tree.astTransform = AstTransformSubstitution(0) subtree = parse_alias(ctx) tree.add(subtree) return tree return tree def parse__gen12(ctx): current = ctx.tokens.current() rule = table[5][current.id] if current else -1 tree = ParseTree(NonTerminal(63, '_gen12')) ctx.nonterminal = "_gen12" if current != None and current.id in nonterminal_follow[63] and current.id not in nonterminal_first[63]: return tree if current == None: return tree if rule == 51: # $_gen12 = $call_body ctx.rule = rules[51] tree.astTransform = AstTransformSubstitution(0) subtree = parse_call_body(ctx) tree.add(subtree) return tree return tree def parse__gen16(ctx): current = ctx.tokens.current() rule = table[9][current.id] if current else -1 tree = ParseTree(NonTerminal(67, '_gen16')) ctx.nonterminal = "_gen16" if current != None and current.id in nonterminal_follow[67] and current.id not in nonterminal_first[67]: return tree if current == None: return tree if rule == 65: # $_gen16 = $wf_output_wildcard ctx.rule = rules[65] tree.astTransform = AstTransformSubstitution(0) subtree = parse_wf_output_wildcard(ctx) tree.add(subtree) return tree return tree def parse__gen2(ctx): current = ctx.tokens.current() rule = table[0][current.id] if current else -1 tree = ParseTree(NonTerminal(58, '_gen2')) ctx.nonterminal = "_gen2" if current != None and current.id in nonterminal_follow[58] and current.id not in nonterminal_first[58]: return tree if current == None: return tree if rule == 6: # $_gen2 = $import_namespace ctx.rule = rules[6] tree.astTransform = AstTransformSubstitution(0) subtree = parse_import_namespace(ctx) tree.add(subtree) return tree return tree def parse__gen9(ctx): current = ctx.tokens.current() rule = table[53][current.id] if current else -1 tree = ParseTree(NonTerminal(111, '_gen9')) ctx.nonterminal = "_gen9" if current != None and current.id in nonterminal_follow[111] and current.id not in nonterminal_first[111]: return tree if current == None: return tree if rule == 34: # $_gen9 = $setter ctx.rule = rules[34] tree.astTransform = AstTransformSubstitution(0) subtree = parse_setter(ctx) tree.add(subtree) return tree return tree def parse_alias(ctx): current = ctx.tokens.current() rule = table[18][current.id] if current else -1 tree = ParseTree(NonTerminal(76, 'alias')) ctx.nonterminal = "alias" if current == None: raise ctx.errors.unexpected_eof() if rule == 59: # $alias = :as :identifier -> $1 ctx.rule = rules[59] tree.astTransform = AstTransformSubstitution(1) t = expect(ctx, 53) # :as tree.add(t) t = expect(ctx, 50) # :identifier tree.add(t) return tree raise ctx.errors.unexpected_symbol( ctx.nonterminal, ctx.tokens.current(), [terminals[x] for x in nonterminal_first[76] if x >=0], rules[59] ) def parse_call(ctx): current = ctx.tokens.current() rule = table[27][current.id] if current else -1 tree = ParseTree(NonTerminal(85, 'call')) ctx.nonterminal = "call" if current == None: raise ctx.errors.unexpected_eof() if rule == 53: # $call = :call :fqn $_gen11 $_gen12 -> Call( task=$1, alias=$2, body=$3 ) ctx.rule = rules[53] ast_parameters = OrderedDict([ ('task', 1), ('alias', 2), ('body', 3), ]) tree.astTransform = AstTransformNodeCreator('Call', ast_parameters) t = expect(ctx, 28) # :call tree.add(t) t = expect(ctx, 55) # :fqn tree.add(t) subtree = parse__gen11(ctx) tree.add(subtree) subtree = parse__gen12(ctx) tree.add(subtree) return tree raise ctx.errors.unexpected_symbol( ctx.nonterminal, ctx.tokens.current(), [terminals[x] for x in nonterminal_first[85] if x >=0], rules[53] ) def parse_call_body(ctx): current = ctx.tokens.current() rule = table[30][current.id] if current else -1 tree = ParseTree(NonTerminal(88, 'call_body')) ctx.nonterminal = "call_body" if current == None: raise ctx.errors.unexpected_eof() if rule == 55: # $call_body = :lbrace $_gen3 $_gen13 :rbrace -> CallBody( declarations=$1, io=$2 ) ctx.rule = rules[55] ast_parameters = OrderedDict([ ('declarations', 1), ('io', 2), ]) tree.astTransform = AstTransformNodeCreator('CallBody', ast_parameters) t = expect(ctx, 16) # :lbrace tree.add(t) subtree = parse__gen3(ctx) tree.add(subtree) subtree = parse__gen13(ctx) tree.add(subtree) t = expect(ctx, 44) # :rbrace tree.add(t) return tree raise ctx.errors.unexpected_symbol( ctx.nonterminal, ctx.tokens.current(), [terminals[x] for x in nonterminal_first[88] if x >=0], rules[55] ) def parse_call_input(ctx): current = ctx.tokens.current() rule = table[3][current.id] if current else -1 tree = ParseTree(NonTerminal(61, 'call_input')) ctx.nonterminal = "call_input" if current == None: raise ctx.errors.unexpected_eof() if rule == 57: # $call_input = :input :colon $_gen14 -> Inputs( map=$2 ) ctx.rule = rules[57] ast_parameters = OrderedDict([ ('map', 2), ]) tree.astTransform = AstTransformNodeCreator('Inputs', ast_parameters) t = expect(ctx, 34) # :input tree.add(t) t = expect(ctx, 54) # :colon tree.add(t) subtree = parse__gen14(ctx) tree.add(subtree) return tree raise ctx.errors.unexpected_symbol( ctx.nonterminal, ctx.tokens.current(), [terminals[x] for x in nonterminal_first[61] if x >=0], rules[57] ) def parse_cmd_param(ctx): current = ctx.tokens.current() rule = table[10][current.id] if current else -1 tree = ParseTree(NonTerminal(68, 'cmd_param')) ctx.nonterminal = "cmd_param" if current == None: raise ctx.errors.unexpected_eof() if rule == 23: # $cmd_param = :cmd_param_start $_gen6 $e :cmd_param_end -> CommandParameter( attributes=$1, expr=$2 ) ctx.rule = rules[23] ast_parameters = OrderedDict([ ('attributes', 1), ('expr', 2), ]) tree.astTransform = AstTransformNodeCreator('CommandParameter', ast_parameters) t = expect(ctx, 5) # :cmd_param_start tree.add(t) subtree = parse__gen6(ctx) tree.add(subtree) subtree = parse_e(ctx) tree.add(subtree) t = expect(ctx, 40) # :cmd_param_end tree.add(t) return tree raise ctx.errors.unexpected_symbol( ctx.nonterminal, ctx.tokens.current(), [terminals[x] for x in nonterminal_first[68] if x >=0], rules[23] ) def parse_cmd_param_kv(ctx): current = ctx.tokens.current() rule = table[13][current.id] if current else -1 tree = ParseTree(NonTerminal(71, 'cmd_param_kv')) ctx.nonterminal = "cmd_param_kv" if current == None: raise ctx.errors.unexpected_eof() if rule == 24: # $cmd_param_kv = :cmd_attr_hint :identifier :equal $e -> CommandParameterAttr( key=$1, value=$3 ) ctx.rule = rules[24] ast_parameters = OrderedDict([ ('key', 1), ('value', 3), ]) tree.astTransform = AstTransformNodeCreator('CommandParameterAttr', ast_parameters) t = expect(ctx, 27) # :cmd_attr_hint tree.add(t) t = expect(ctx, 50) # :identifier tree.add(t) t = expect(ctx, 14) # :equal tree.add(t) subtree = parse_e(ctx) tree.add(subtree) return tree raise ctx.errors.unexpected_symbol( ctx.nonterminal, ctx.tokens.current(), [terminals[x] for x in nonterminal_first[71] if x >=0], rules[24] ) def parse_command(ctx): current = ctx.tokens.current() rule = table[2][current.id] if current else -1 tree = ParseTree(NonTerminal(60, 'command')) ctx.nonterminal = "command" if current == None: raise ctx.errors.unexpected_eof() if rule == 19: # $command = :raw_command :raw_cmd_start $_gen5 :raw_cmd_end -> RawCommand( parts=$2 ) ctx.rule = rules[19] ast_parameters = OrderedDict([ ('parts', 2), ]) tree.astTransform = AstTransformNodeCreator('RawCommand', ast_parameters) t = expect(ctx, 19) # :raw_command tree.add(t) t = expect(ctx, 0) # :raw_cmd_start tree.add(t) subtree = parse__gen5(ctx) tree.add(subtree) t = expect(ctx, 30) # :raw_cmd_end tree.add(t) return tree raise ctx.errors.unexpected_symbol( ctx.nonterminal, ctx.tokens.current(), [terminals[x] for x in nonterminal_first[60] if x >=0], rules[19] ) def parse_command_part(ctx): current = ctx.tokens.current() rule = table[20][current.id] if current else -1 tree = ParseTree(NonTerminal(78, 'command_part')) ctx.nonterminal = "command_part" if current == None: raise ctx.errors.unexpected_eof() if rule == 20: # $command_part = :cmd_part ctx.rule = rules[20] tree.astTransform = AstTransformSubstitution(0) t = expect(ctx, 26) # :cmd_part tree.add(t) return tree elif rule == 21: # $command_part = $cmd_param ctx.rule = rules[21] tree.astTransform = AstTransformSubstitution(0) subtree = parse_cmd_param(ctx) tree.add(subtree) return tree raise ctx.errors.unexpected_symbol( ctx.nonterminal, ctx.tokens.current(), [terminals[x] for x in nonterminal_first[78] if x >=0], rules[21] ) def parse_declaration(ctx): current = ctx.tokens.current() rule = table[41][current.id] if current else -1 tree = ParseTree(NonTerminal(99, 'declaration')) ctx.nonterminal = "declaration" if current == None: raise ctx.errors.unexpected_eof() if rule == 36: # $declaration = $type_e :identifier $_gen9 -> Declaration( type=$0, name=$1, expression=$2 ) ctx.rule = rules[36] ast_parameters = OrderedDict([ ('type', 0), ('name', 1), ('expression', 2), ]) tree.astTransform = AstTransformNodeCreator('Declaration', ast_parameters) subtree = parse_type_e(ctx) tree.add(subtree) t = expect(ctx, 50) # :identifier tree.add(t) subtree = parse__gen9(ctx) tree.add(subtree) return tree raise ctx.errors.unexpected_symbol( ctx.nonterminal, ctx.tokens.current(), [terminals[x] for x in nonterminal_first[99] if x >=0], rules[36] ) def parse_document(ctx): current = ctx.tokens.current() rule = table[50][current.id] if current else -1 tree = ParseTree(NonTerminal(108, 'document')) ctx.nonterminal = "document" if current != None and current.id in nonterminal_follow[108] and current.id not in nonterminal_first[108]: return tree if current == None: return tree if rule == 2: # $document = $_gen0 $_gen1 -> Namespace( imports=$0, body=$1 ) ctx.rule = rules[2] ast_parameters = OrderedDict([ ('imports', 0), ('body', 1), ]) tree.astTransform = AstTransformNodeCreator('Namespace', ast_parameters) subtree = parse__gen0(ctx) tree.add(subtree) subtree = parse__gen1(ctx) tree.add(subtree) return tree return tree def parse_if_stmt(ctx): current = ctx.tokens.current() rule = table[17][current.id] if current else -1 tree = ParseTree(NonTerminal(75, 'if_stmt')) ctx.nonterminal = "if_stmt" if current == None: raise ctx.errors.unexpected_eof() if rule == 72: # $if_stmt = :if :lparen $e :rparen :lbrace $_gen10 :rbrace -> If( expression=$2, body=$5 ) ctx.rule = rules[72] ast_parameters = OrderedDict([ ('expression', 2), ('body', 5), ]) tree.astTransform = AstTransformNodeCreator('If', ast_parameters) t = expect(ctx, 18) # :if tree.add(t) t = expect(ctx, 20) # :lparen tree.add(t) subtree = parse_e(ctx) tree.add(subtree) t = expect(ctx, 45) # :rparen tree.add(t) t = expect(ctx, 16) # :lbrace tree.add(t) subtree = parse__gen10(ctx) tree.add(subtree) t = expect(ctx, 44) # :rbrace tree.add(t) return tree raise ctx.errors.unexpected_symbol( ctx.nonterminal, ctx.tokens.current(), [terminals[x] for x in nonterminal_first[75] if x >=0], rules[72] ) def parse_import(ctx): current = ctx.tokens.current() rule = table[39][current.id] if current else -1 tree = ParseTree(NonTerminal(97, 'import')) ctx.nonterminal = "import" if current == None: raise ctx.errors.unexpected_eof() if rule == 8: # $import = :import :string $_gen2 -> Import( uri=$1, namespace=$2 ) ctx.rule = rules[8] ast_parameters = OrderedDict([ ('uri', 1), ('namespace', 2), ]) tree.astTransform = AstTransformNodeCreator('Import', ast_parameters) t = expect(ctx, 41) # :import tree.add(t) t = expect(ctx, 42) # :string tree.add(t) subtree = parse__gen2(ctx) tree.add(subtree) return tree raise ctx.errors.unexpected_symbol( ctx.nonterminal, ctx.tokens.current(), [terminals[x] for x in nonterminal_first[97] if x >=0], rules[8] ) def parse_import_namespace(ctx): current = ctx.tokens.current() rule = table[47][current.id] if current else -1 tree = ParseTree(NonTerminal(105, 'import_namespace')) ctx.nonterminal = "import_namespace" if current == None: raise ctx.errors.unexpected_eof() if rule == 9: # $import_namespace = :as :identifier -> $1 ctx.rule = rules[9] tree.astTransform = AstTransformSubstitution(1) t = expect(ctx, 53) # :as tree.add(t) t = expect(ctx, 50) # :identifier tree.add(t) return tree raise ctx.errors.unexpected_symbol( ctx.nonterminal, ctx.tokens.current(), [terminals[x] for x in nonterminal_first[105] if x >=0], rules[9] ) def parse_kv(ctx): current = ctx.tokens.current() rule = table[56][current.id] if current else -1 tree = ParseTree(NonTerminal(114, 'kv')) ctx.nonterminal = "kv" if current == None: raise ctx.errors.unexpected_eof() if rule == 33: # $kv = :identifier :colon $e -> RuntimeAttribute( key=$0, value=$2 ) ctx.rule = rules[33] ast_parameters = OrderedDict([ ('key', 0), ('value', 2), ]) tree.astTransform = AstTransformNodeCreator('RuntimeAttribute', ast_parameters) t = expect(ctx, 50) # :identifier tree.add(t) t = expect(ctx, 54) # :colon tree.add(t) subtree = parse_e(ctx) tree.add(subtree) return tree raise ctx.errors.unexpected_symbol( ctx.nonterminal, ctx.tokens.current(), [terminals[x] for x in nonterminal_first[114] if x >=0], rules[33] ) def parse_map(ctx): current = ctx.tokens.current() rule = table[40][current.id] if current else -1 tree = ParseTree(NonTerminal(98, 'map')) ctx.nonterminal = "map" if current == None: raise ctx.errors.unexpected_eof() if rule == 32: # $map = :lbrace $_gen8 :rbrace -> $1 ctx.rule = rules[32] tree.astTransform = AstTransformSubstitution(1) t = expect(ctx, 16) # :lbrace tree.add(t) subtree = parse__gen8(ctx) tree.add(subtree) t = expect(ctx, 44) # :rbrace tree.add(t) return tree raise ctx.errors.unexpected_symbol( ctx.nonterminal, ctx.tokens.current(), [terminals[x] for x in nonterminal_first[98] if x >=0], rules[32] ) def parse_map_kv(ctx): current = ctx.tokens.current() rule = table[36][current.id] if current else -1 tree = ParseTree(NonTerminal(94, 'map_kv')) ctx.nonterminal = "map_kv" if current == None: raise ctx.errors.unexpected_eof() if rule == 38: # $map_kv = $e :colon $e -> MapLiteralKv( key=$0, value=$2 ) ctx.rule = rules[38] ast_parameters = OrderedDict([ ('key', 0), ('value', 2), ]) tree.astTransform = AstTransformNodeCreator('MapLiteralKv', ast_parameters) subtree = parse_e(ctx) tree.add(subtree) t = expect(ctx, 54) # :colon tree.add(t) subtree = parse_e(ctx) tree.add(subtree) return tree raise ctx.errors.unexpected_symbol( ctx.nonterminal, ctx.tokens.current(), [terminals[x] for x in nonterminal_first[94] if x >=0], rules[38] ) def parse_mapping(ctx): current = ctx.tokens.current() rule = table[32][current.id] if current else -1 tree = ParseTree(NonTerminal(90, 'mapping')) ctx.nonterminal = "mapping" if current == None: raise ctx.errors.unexpected_eof() if rule == 58: # $mapping = :identifier :equal $e -> IOMapping( key=$0, value=$2 ) ctx.rule = rules[58] ast_parameters = OrderedDict([ ('key', 0), ('value', 2), ]) tree.astTransform = AstTransformNodeCreator('IOMapping', ast_parameters) t = expect(ctx, 50) # :identifier tree.add(t) t = expect(ctx, 14) # :equal tree.add(t) subtree = parse_e(ctx) tree.add(subtree) return tree raise ctx.errors.unexpected_symbol( ctx.nonterminal, ctx.tokens.current(), [terminals[x] for x in nonterminal_first[90] if x >=0], rules[58] ) def parse_meta(ctx): current = ctx.tokens.current() rule = table[34][current.id] if current else -1 tree = ParseTree(NonTerminal(92, 'meta')) ctx.nonterminal = "meta" if current == None: raise ctx.errors.unexpected_eof() if rule == 30: # $meta = :meta $map -> Meta( map=$1 ) ctx.rule = rules[30] ast_parameters = OrderedDict([ ('map', 1), ]) tree.astTransform = AstTransformNodeCreator('Meta', ast_parameters) t = expect(ctx, 13) # :meta tree.add(t) subtree = parse_map(ctx) tree.add(subtree) return tree raise ctx.errors.unexpected_symbol( ctx.nonterminal, ctx.tokens.current(), [terminals[x] for x in nonterminal_first[92] if x >=0], rules[30] ) def parse_object_kv(ctx): current = ctx.tokens.current() rule = table[29][current.id] if current else -1 tree = ParseTree(NonTerminal(87, 'object_kv')) ctx.nonterminal = "object_kv" if current == None: raise ctx.errors.unexpected_eof() if rule == 74: # $object_kv = :identifier :colon $e -> ObjectKV( key=$0, value=$2 ) ctx.rule = rules[74] ast_parameters = OrderedDict([ ('key', 0), ('value', 2), ]) tree.astTransform = AstTransformNodeCreator('ObjectKV', ast_parameters) t = expect(ctx, 50) # :identifier tree.add(t) t = expect(ctx, 54) # :colon tree.add(t) subtree = parse_e(ctx) tree.add(subtree) return tree raise ctx.errors.unexpected_symbol( ctx.nonterminal, ctx.tokens.current(), [terminals[x] for x in nonterminal_first[87] if x >=0], rules[74] ) def parse_output_kv(ctx): current = ctx.tokens.current() rule = table[11][current.id] if current else -1 tree = ParseTree(NonTerminal(69, 'output_kv')) ctx.nonterminal = "output_kv" if current == None: raise ctx.errors.unexpected_eof() if rule == 27: # $output_kv = $type_e :identifier :equal $e -> Output( type=$0, name=$1, expression=$3 ) ctx.rule = rules[27] ast_parameters = OrderedDict([ ('type', 0), ('name', 1), ('expression', 3), ]) tree.astTransform = AstTransformNodeCreator('Output', ast_parameters) subtree = parse_type_e(ctx) tree.add(subtree) t = expect(ctx, 50) # :identifier tree.add(t) t = expect(ctx, 14) # :equal tree.add(t) subtree = parse_e(ctx) tree.add(subtree) return tree raise ctx.errors.unexpected_symbol( ctx.nonterminal, ctx.tokens.current(), [terminals[x] for x in nonterminal_first[69] if x >=0], rules[27] ) def parse_outputs(ctx): current = ctx.tokens.current() rule = table[28][current.id] if current else -1 tree = ParseTree(NonTerminal(86, 'outputs')) ctx.nonterminal = "outputs" if current == None: raise ctx.errors.unexpected_eof() if rule == 26: # $outputs = :output :lbrace $_gen7 :rbrace -> Outputs( attributes=$2 ) ctx.rule = rules[26] ast_parameters = OrderedDict([ ('attributes', 2), ]) tree.astTransform = AstTransformNodeCreator('Outputs', ast_parameters) t = expect(ctx, 22) # :output tree.add(t) t = expect(ctx, 16) # :lbrace tree.add(t) subtree = parse__gen7(ctx) tree.add(subtree) t = expect(ctx, 44) # :rbrace tree.add(t) return tree raise ctx.errors.unexpected_symbol( ctx.nonterminal, ctx.tokens.current(), [terminals[x] for x in nonterminal_first[86] if x >=0], rules[26] ) def parse_parameter_meta(ctx): current = ctx.tokens.current() rule = table[58][current.id] if current else -1 tree = ParseTree(NonTerminal(116, 'parameter_meta')) ctx.nonterminal = "parameter_meta" if current == None: raise ctx.errors.unexpected_eof() if rule == 29: # $parameter_meta = :parameter_meta $map -> ParameterMeta( map=$1 ) ctx.rule = rules[29] ast_parameters = OrderedDict([ ('map', 1), ]) tree.astTransform = AstTransformNodeCreator('ParameterMeta', ast_parameters) t = expect(ctx, 29) # :parameter_meta tree.add(t) subtree = parse_map(ctx) tree.add(subtree) return tree raise ctx.errors.unexpected_symbol( ctx.nonterminal, ctx.tokens.current(), [terminals[x] for x in nonterminal_first[116] if x >=0], rules[29] ) def parse_runtime(ctx): current = ctx.tokens.current() rule = table[21][current.id] if current else -1 tree = ParseTree(NonTerminal(79, 'runtime')) ctx.nonterminal = "runtime" if current == None: raise ctx.errors.unexpected_eof() if rule == 28: # $runtime = :runtime $map -> Runtime( map=$1 ) ctx.rule = rules[28] ast_parameters = OrderedDict([ ('map', 1), ]) tree.astTransform = AstTransformNodeCreator('Runtime', ast_parameters) t = expect(ctx, 32) # :runtime tree.add(t) subtree = parse_map(ctx) tree.add(subtree) return tree raise ctx.errors.unexpected_symbol( ctx.nonterminal, ctx.tokens.current(), [terminals[x] for x in nonterminal_first[79] if x >=0], rules[28] ) def parse_scatter(ctx): current = ctx.tokens.current() rule = table[55][current.id] if current else -1 tree = ParseTree(NonTerminal(113, 'scatter')) ctx.nonterminal = "scatter" if current == None: raise ctx.errors.unexpected_eof() if rule == 73: # $scatter = :scatter :lparen :identifier :in $e :rparen :lbrace $_gen10 :rbrace -> Scatter( item=$2, collection=$4, body=$7 ) ctx.rule = rules[73] ast_parameters = OrderedDict([ ('item', 2), ('collection', 4), ('body', 7), ]) tree.astTransform = AstTransformNodeCreator('Scatter', ast_parameters) t = expect(ctx, 51) # :scatter tree.add(t) t = expect(ctx, 20) # :lparen tree.add(t) t = expect(ctx, 50) # :identifier tree.add(t) t = expect(ctx, 9) # :in tree.add(t) subtree = parse_e(ctx) tree.add(subtree) t = expect(ctx, 45) # :rparen tree.add(t) t = expect(ctx, 16) # :lbrace tree.add(t) subtree = parse__gen10(ctx) tree.add(subtree) t = expect(ctx, 44) # :rbrace tree.add(t) return tree raise ctx.errors.unexpected_symbol( ctx.nonterminal, ctx.tokens.current(), [terminals[x] for x in nonterminal_first[113] if x >=0], rules[73] ) def parse_sections(ctx): current = ctx.tokens.current() rule = table[6][current.id] if current else -1 tree = ParseTree(NonTerminal(64, 'sections')) ctx.nonterminal = "sections" if current == None: raise ctx.errors.unexpected_eof() if rule == 13: # $sections = $command ctx.rule = rules[13] tree.astTransform = AstTransformSubstitution(0) subtree = parse_command(ctx) tree.add(subtree) return tree elif rule == 14: # $sections = $outputs ctx.rule = rules[14] tree.astTransform = AstTransformSubstitution(0) subtree = parse_outputs(ctx) tree.add(subtree) return tree elif rule == 15: # $sections = $runtime ctx.rule = rules[15] tree.astTransform = AstTransformSubstitution(0) subtree = parse_runtime(ctx) tree.add(subtree) return tree elif rule == 16: # $sections = $parameter_meta ctx.rule = rules[16] tree.astTransform = AstTransformSubstitution(0) subtree = parse_parameter_meta(ctx) tree.add(subtree) return tree elif rule == 17: # $sections = $meta ctx.rule = rules[17] tree.astTransform = AstTransformSubstitution(0) subtree = parse_meta(ctx) tree.add(subtree) return tree raise ctx.errors.unexpected_symbol( ctx.nonterminal, ctx.tokens.current(), [terminals[x] for x in nonterminal_first[64] if x >=0], rules[17] ) def parse_setter(ctx): current = ctx.tokens.current() rule = table[15][current.id] if current else -1 tree = ParseTree(NonTerminal(73, 'setter')) ctx.nonterminal = "setter" if current == None: raise ctx.errors.unexpected_eof() if rule == 37: # $setter = :equal $e -> $1 ctx.rule = rules[37] tree.astTransform = AstTransformSubstitution(1) t = expect(ctx, 14) # :equal tree.add(t) subtree = parse_e(ctx) tree.add(subtree) return tree raise ctx.errors.unexpected_symbol( ctx.nonterminal, ctx.tokens.current(), [terminals[x] for x in nonterminal_first[73] if x >=0], rules[37] ) def parse_task(ctx): current = ctx.tokens.current() rule = table[37][current.id] if current else -1 tree = ParseTree(NonTerminal(95, 'task')) ctx.nonterminal = "task" if current == None: raise ctx.errors.unexpected_eof() if rule == 12: # $task = :task :identifier :lbrace $_gen3 $_gen4 :rbrace -> Task( name=$1, declarations=$3, sections=$4 ) ctx.rule = rules[12] ast_parameters = OrderedDict([ ('name', 1), ('declarations', 3), ('sections', 4), ]) tree.astTransform = AstTransformNodeCreator('Task', ast_parameters) t = expect(ctx, 6) # :task tree.add(t) t = expect(ctx, 50) # :identifier tree.add(t) t = expect(ctx, 16) # :lbrace tree.add(t) subtree = parse__gen3(ctx) tree.add(subtree) subtree = parse__gen4(ctx) tree.add(subtree) t = expect(ctx, 44) # :rbrace tree.add(t) return tree raise ctx.errors.unexpected_symbol( ctx.nonterminal, ctx.tokens.current(), [terminals[x] for x in nonterminal_first[95] if x >=0], rules[12] ) def parse_wf_body_element(ctx): current = ctx.tokens.current() rule = table[57][current.id] if current else -1 tree = ParseTree(NonTerminal(115, 'wf_body_element')) ctx.nonterminal = "wf_body_element" if current == None: raise ctx.errors.unexpected_eof() if rule == 41: # $wf_body_element = $call ctx.rule = rules[41] tree.astTransform = AstTransformSubstitution(0) subtree = parse_call(ctx) tree.add(subtree) return tree elif rule == 42: # $wf_body_element = $declaration ctx.rule = rules[42] tree.astTransform = AstTransformSubstitution(0) subtree = parse_declaration(ctx) tree.add(subtree) return tree elif rule == 43: # $wf_body_element = $while_loop ctx.rule = rules[43] tree.astTransform = AstTransformSubstitution(0) subtree = parse_while_loop(ctx) tree.add(subtree) return tree elif rule == 44: # $wf_body_element = $if_stmt ctx.rule = rules[44] tree.astTransform = AstTransformSubstitution(0) subtree = parse_if_stmt(ctx) tree.add(subtree) return tree elif rule == 45: # $wf_body_element = $scatter ctx.rule = rules[45] tree.astTransform = AstTransformSubstitution(0) subtree = parse_scatter(ctx) tree.add(subtree) return tree elif rule == 46: # $wf_body_element = $wf_outputs ctx.rule = rules[46] tree.astTransform = AstTransformSubstitution(0) subtree = parse_wf_outputs(ctx) tree.add(subtree) return tree elif rule == 47: # $wf_body_element = $wf_parameter_meta ctx.rule = rules[47] tree.astTransform = AstTransformSubstitution(0) subtree = parse_wf_parameter_meta(ctx) tree.add(subtree) return tree elif rule == 48: # $wf_body_element = $wf_meta ctx.rule = rules[48] tree.astTransform = AstTransformSubstitution(0) subtree = parse_wf_meta(ctx) tree.add(subtree) return tree raise ctx.errors.unexpected_symbol( ctx.nonterminal, ctx.tokens.current(), [terminals[x] for x in nonterminal_first[115] if x >=0], rules[48] ) def parse_wf_meta(ctx): current = ctx.tokens.current() rule = table[23][current.id] if current else -1 tree = ParseTree(NonTerminal(81, 'wf_meta')) ctx.nonterminal = "wf_meta" if current == None: raise ctx.errors.unexpected_eof() if rule == 70: # $wf_meta = :meta $map -> Meta( map=$1 ) ctx.rule = rules[70] ast_parameters = OrderedDict([ ('map', 1), ]) tree.astTransform = AstTransformNodeCreator('Meta', ast_parameters) t = expect(ctx, 13) # :meta tree.add(t) subtree = parse_map(ctx) tree.add(subtree) return tree raise ctx.errors.unexpected_symbol( ctx.nonterminal, ctx.tokens.current(), [terminals[x] for x in nonterminal_first[81] if x >=0], rules[70] ) def parse_wf_output(ctx): current = ctx.tokens.current() rule = table[49][current.id] if current else -1 tree = ParseTree(NonTerminal(107, 'wf_output')) ctx.nonterminal = "wf_output" if current == None: raise ctx.errors.unexpected_eof() if rule == 62: # $wf_output = $wf_output_declaration_syntax ctx.rule = rules[62] tree.astTransform = AstTransformSubstitution(0) subtree = parse_wf_output_declaration_syntax(ctx) tree.add(subtree) return tree elif rule == 63: # $wf_output = $wf_output_wildcard_syntax ctx.rule = rules[63] tree.astTransform = AstTransformSubstitution(0) subtree = parse_wf_output_wildcard_syntax(ctx) tree.add(subtree) return tree raise ctx.errors.unexpected_symbol( ctx.nonterminal, ctx.tokens.current(), [terminals[x] for x in nonterminal_first[107] if x >=0], rules[63] ) def parse_wf_output_declaration_syntax(ctx): current = ctx.tokens.current() rule = table[19][current.id] if current else -1 tree = ParseTree(NonTerminal(77, 'wf_output_declaration_syntax')) ctx.nonterminal = "wf_output_declaration_syntax" if current == None: raise ctx.errors.unexpected_eof() if rule == 64: # $wf_output_declaration_syntax = $type_e :identifier :equal $e -> WorkflowOutputDeclaration( type=$0, name=$1, expression=$3 ) ctx.rule = rules[64] ast_parameters = OrderedDict([ ('type', 0), ('name', 1), ('expression', 3), ]) tree.astTransform = AstTransformNodeCreator('WorkflowOutputDeclaration', ast_parameters) subtree = parse_type_e(ctx) tree.add(subtree) t = expect(ctx, 50) # :identifier tree.add(t) t = expect(ctx, 14) # :equal tree.add(t) subtree = parse_e(ctx) tree.add(subtree) return tree raise ctx.errors.unexpected_symbol( ctx.nonterminal, ctx.tokens.current(), [terminals[x] for x in nonterminal_first[77] if x >=0], rules[64] ) def parse_wf_output_wildcard(ctx): current = ctx.tokens.current() rule = table[8][current.id] if current else -1 tree = ParseTree(NonTerminal(66, 'wf_output_wildcard')) ctx.nonterminal = "wf_output_wildcard" if current == None: raise ctx.errors.unexpected_eof() if rule == 68: # $wf_output_wildcard = :dot :asterisk -> $1 ctx.rule = rules[68] tree.astTransform = AstTransformSubstitution(1) t = expect(ctx, 7) # :dot tree.add(t) t = expect(ctx, 17) # :asterisk tree.add(t) return tree raise ctx.errors.unexpected_symbol( ctx.nonterminal, ctx.tokens.current(), [terminals[x] for x in nonterminal_first[66] if x >=0], rules[68] ) def parse_wf_output_wildcard_syntax(ctx): current = ctx.tokens.current() rule = table[12][current.id] if current else -1 tree = ParseTree(NonTerminal(70, 'wf_output_wildcard_syntax')) ctx.nonterminal = "wf_output_wildcard_syntax" if current == None: raise ctx.errors.unexpected_eof() if rule == 67: # $wf_output_wildcard_syntax = :fqn $_gen16 -> WorkflowOutputWildcard( fqn=$0, wildcard=$1 ) ctx.rule = rules[67] ast_parameters = OrderedDict([ ('fqn', 0), ('wildcard', 1), ]) tree.astTransform = AstTransformNodeCreator('WorkflowOutputWildcard', ast_parameters) t = expect(ctx, 55) # :fqn tree.add(t) subtree = parse__gen16(ctx) tree.add(subtree) return tree raise ctx.errors.unexpected_symbol( ctx.nonterminal, ctx.tokens.current(), [terminals[x] for x in nonterminal_first[70] if x >=0], rules[67] ) def parse_wf_outputs(ctx): current = ctx.tokens.current() rule = table[43][current.id] if current else -1 tree = ParseTree(NonTerminal(101, 'wf_outputs')) ctx.nonterminal = "wf_outputs" if current == None: raise ctx.errors.unexpected_eof() if rule == 61: # $wf_outputs = :output :lbrace $_gen15 :rbrace -> WorkflowOutputs( outputs=$2 ) ctx.rule = rules[61] ast_parameters = OrderedDict([ ('outputs', 2), ]) tree.astTransform = AstTransformNodeCreator('WorkflowOutputs', ast_parameters) t = expect(ctx, 22) # :output tree.add(t) t = expect(ctx, 16) # :lbrace tree.add(t) subtree = parse__gen15(ctx) tree.add(subtree) t = expect(ctx, 44) # :rbrace tree.add(t) return tree raise ctx.errors.unexpected_symbol( ctx.nonterminal, ctx.tokens.current(), [terminals[x] for x in nonterminal_first[101] if x >=0], rules[61] ) def parse_wf_parameter_meta(ctx): current = ctx.tokens.current() rule = table[24][current.id] if current else -1 tree = ParseTree(NonTerminal(82, 'wf_parameter_meta')) ctx.nonterminal = "wf_parameter_meta" if current == None: raise ctx.errors.unexpected_eof() if rule == 69: # $wf_parameter_meta = :parameter_meta $map -> ParameterMeta( map=$1 ) ctx.rule = rules[69] ast_parameters = OrderedDict([ ('map', 1), ]) tree.astTransform = AstTransformNodeCreator('ParameterMeta', ast_parameters) t = expect(ctx, 29) # :parameter_meta tree.add(t) subtree = parse_map(ctx) tree.add(subtree) return tree raise ctx.errors.unexpected_symbol( ctx.nonterminal, ctx.tokens.current(), [terminals[x] for x in nonterminal_first[82] if x >=0], rules[69] ) def parse_while_loop(ctx): current = ctx.tokens.current() rule = table[51][current.id] if current else -1 tree = ParseTree(NonTerminal(109, 'while_loop')) ctx.nonterminal = "while_loop" if current == None: raise ctx.errors.unexpected_eof() if rule == 71: # $while_loop = :while :lparen $e :rparen :lbrace $_gen10 :rbrace -> WhileLoop( expression=$2, body=$5 ) ctx.rule = rules[71] ast_parameters = OrderedDict([ ('expression', 2), ('body', 5), ]) tree.astTransform = AstTransformNodeCreator('WhileLoop', ast_parameters) t = expect(ctx, 25) # :while tree.add(t) t = expect(ctx, 20) # :lparen tree.add(t) subtree = parse_e(ctx) tree.add(subtree) t = expect(ctx, 45) # :rparen tree.add(t) t = expect(ctx, 16) # :lbrace tree.add(t) subtree = parse__gen10(ctx) tree.add(subtree) t = expect(ctx, 44) # :rbrace tree.add(t) return tree raise ctx.errors.unexpected_symbol( ctx.nonterminal, ctx.tokens.current(), [terminals[x] for x in nonterminal_first[109] if x >=0], rules[71] ) def parse_workflow(ctx): current = ctx.tokens.current() rule = table[54][current.id] if current else -1 tree = ParseTree(NonTerminal(112, 'workflow')) ctx.nonterminal = "workflow" if current == None: raise ctx.errors.unexpected_eof() if rule == 40: # $workflow = :workflow :identifier :lbrace $_gen10 :rbrace -> Workflow( name=$1, body=$3 ) ctx.rule = rules[40] ast_parameters = OrderedDict([ ('name', 1), ('body', 3), ]) tree.astTransform = AstTransformNodeCreator('Workflow', ast_parameters) t = expect(ctx, 10) # :workflow tree.add(t) t = expect(ctx, 50) # :identifier tree.add(t) t = expect(ctx, 16) # :lbrace tree.add(t) subtree = parse__gen10(ctx) tree.add(subtree) t = expect(ctx, 44) # :rbrace tree.add(t) return tree raise ctx.errors.unexpected_symbol( ctx.nonterminal, ctx.tokens.current(), [terminals[x] for x in nonterminal_first[112] if x >=0], rules[40] ) def parse_workflow_or_task_or_decl(ctx): current = ctx.tokens.current() rule = table[7][current.id] if current else -1 tree = ParseTree(NonTerminal(65, 'workflow_or_task_or_decl')) ctx.nonterminal = "workflow_or_task_or_decl" if current == None: raise ctx.errors.unexpected_eof() if rule == 3: # $workflow_or_task_or_decl = $workflow ctx.rule = rules[3] tree.astTransform = AstTransformSubstitution(0) subtree = parse_workflow(ctx) tree.add(subtree) return tree elif rule == 4: # $workflow_or_task_or_decl = $task ctx.rule = rules[4] tree.astTransform = AstTransformSubstitution(0) subtree = parse_task(ctx) tree.add(subtree) return tree elif rule == 5: # $workflow_or_task_or_decl = $declaration ctx.rule = rules[5] tree.astTransform = AstTransformSubstitution(0) subtree = parse_declaration(ctx) tree.add(subtree) return tree raise ctx.errors.unexpected_symbol( ctx.nonterminal, ctx.tokens.current(), [terminals[x] for x in nonterminal_first[65] if x >=0], rules[5] ) # Lexer Code # # START USER CODE def init(): return { 'context': None, 'replacements': { re.compile(r"\\n"): 0x000A, re.compile(r"\\r"): 0x000D, re.compile(r"\\b"): 0x0008, re.compile(r"\\t"): 0x0009, re.compile(r"\\a"): 0x0007, re.compile(r"\\v"): 0x000B, re.compile(r'\\"'): 0x0022, re.compile(r"\\'"): 0x0027, re.compile(r"\\\?"): 0x003F }, 'escapes': { re.compile(r'(\\([0-7]{1,3}))'): 8, re.compile(r'(\\[xX]([0-9a-fA-F]{1,4}))'): 16, re.compile(r'(\\[uU]([0-9a-fA-F]{4}))'): 16 } } def workflow(ctx, terminal, source_string, line, col): ctx.user_context['context'] = 'workflow' default_action(ctx, terminal, source_string, line, col) def task(ctx, terminal, source_string, line, col): ctx.user_context['context'] = 'task' default_action(ctx, terminal, source_string, line, col) def output(ctx, terminal, source_string, line, col): if ctx.user_context['context'] == 'workflow': ctx.stack.append('wf_output') default_action(ctx, terminal, source_string, line, col) def wdl_unescape(ctx, terminal, source_string, line, col): for regex, c in ctx.user_context['replacements'].items(): source_string = regex.sub(chr(c).encode('utf-8'), source_string) source_string = source_string.replace("\u005C\u005C", "\u005C") for regex, base in ctx.user_context['escapes'].items(): for escape_sequence, number in regex.findall(source_string): source_string = source_string.replace(escape_sequence, chr(int(number, base)).encode('utf-8')) default_action(ctx, terminal, source_string[1:-1], line, col) # END USER CODE def emit(ctx, terminal, source_string, line, col): if terminal: ctx.tokens.append(Terminal(terminals[terminal], terminal, source_string, ctx.resource, line, col)) def default_action(ctx, terminal, source_string, line, col): emit(ctx, terminal, source_string, line, col) def post_filter(tokens): return tokens def destroy(context): pass class LexerStackPush: def __init__(self, mode): self.mode = mode class LexerAction: def __init__(self, action): self.action = action class LexerContext: def __init__(self, string, resource, errors, user_context): self.__dict__.update(locals()) self.stack = ['default'] self.line = 1 self.col = 1 self.tokens = [] self.user_context = user_context self.re_match = None # https://docs.python.org/3/library/re.html#match-objects class HermesLexer: regex = { 'default': OrderedDict([ (re.compile(r'\s+'), [ # (terminal, group, function) ]), (re.compile(r'/\*(.*?)\*/', re.DOTALL), [ # (terminal, group, function) ]), (re.compile(r'#.*'), [ # (terminal, group, function) ]), (re.compile(r'task(?![a-zA-Z0-9_])'), [ # (terminal, group, function) ('task', 0, task), ]), (re.compile(r'(call)\s+'), [ # (terminal, group, function) ('call', 1, None), LexerStackPush('task_fqn'), ]), (re.compile(r'workflow(?![a-zA-Z0-9_])'), [ # (terminal, group, function) ('workflow', 0, workflow), ]), (re.compile(r'import(?![a-zA-Z0-9_])'), [ # (terminal, group, function) ('import', 0, None), ]), (re.compile(r'input(?![a-zA-Z0-9_])'), [ # (terminal, group, function) ('input', 0, None), ]), (re.compile(r'output(?![a-zA-Z0-9_])'), [ # (terminal, group, function) ('output', 0, output), ]), (re.compile(r'as(?![a-zA-Z0-9_])'), [ # (terminal, group, function) ('as', 0, None), ]), (re.compile(r'if(?![a-zA-Z0-9_])'), [ # (terminal, group, function) ('if', 0, None), ]), (re.compile(r'then(?![a-zA-Z0-9_])'), [ # (terminal, group, function) ('then', 0, None), ]), (re.compile(r'else(?![a-zA-Z0-9_])'), [ # (terminal, group, function) ('else', 0, None), ]), (re.compile(r'while(?![a-zA-Z0-9_])'), [ # (terminal, group, function) ('while', 0, None), ]), (re.compile(r'runtime(?![a-zA-Z0-9_])'), [ # (terminal, group, function) ('runtime', 0, None), ]), (re.compile(r'scatter(?![a-zA-Z0-9_])'), [ # (terminal, group, function) ('scatter', 0, None), LexerStackPush('scatter'), ]), (re.compile(r'command\s*(?=<<<)'), [ # (terminal, group, function) ('raw_command', 0, None), LexerStackPush('raw_command2'), ]), (re.compile(r'command\s*(?=\{)'), [ # (terminal, group, function) ('raw_command', 0, None), LexerStackPush('raw_command'), ]), (re.compile(r'parameter_meta(?![a-zA-Z0-9_])'), [ # (terminal, group, function) ('parameter_meta', 0, None), ]), (re.compile(r'meta(?![a-zA-Z0-9_])'), [ # (terminal, group, function) ('meta', 0, None), ]), (re.compile(r'(true|false)(?![a-zA-Z0-9_])'), [ # (terminal, group, function) ('boolean', 0, None), ]), (re.compile(r'(object)\s*(\{)'), [ # (terminal, group, function) ('object', 0, None), ('lbrace', 0, None), ]), (re.compile(r'(Array|Map|Object|Pair|Boolean|Int|Float|Uri|File|String)(?![a-zA-Z0-9_])(?![a-zA-Z0-9_])'), [ # (terminal, group, function) ('type', 0, None), ]), (re.compile(r'[a-zA-Z]([a-zA-Z0-9_])*'), [ # (terminal, group, function) ('identifier', 0, None), ]), (re.compile(r'"([^\\\"\n]|\\[\\"\'nrbtfav\?]|\\[0-7]{1,3}|\\x[0-9a-fA-F]+|\\[uU]([0-9a-fA-F]{4})([0-9a-fA-F]{4})?)*"'), [ # (terminal, group, function) ('string', 0, wdl_unescape), ]), (re.compile(r'\'([^\\\'\n]|\\[\\"\'nrbtfav\?]|\\[0-7]{1,3}|\\x[0-9a-fA-F]+|\\[uU]([0-9a-fA-F]{4})([0-9a-fA-F]{4})?)*\''), [ # (terminal, group, function) ('string', 0, wdl_unescape), ]), (re.compile(r':'), [ # (terminal, group, function) ('colon', 0, None), ]), (re.compile(r','), [ # (terminal, group, function) ('comma', 0, None), ]), (re.compile(r'=='), [ # (terminal, group, function) ('double_equal', 0, None), ]), (re.compile(r'\|\|'), [ # (terminal, group, function) ('double_pipe', 0, None), ]), (re.compile(r'\&\&'), [ # (terminal, group, function) ('double_ampersand', 0, None), ]), (re.compile(r'!='), [ # (terminal, group, function) ('not_equal', 0, None), ]), (re.compile(r'='), [ # (terminal, group, function) ('equal', 0, None), ]), (re.compile(r'\.'), [ # (terminal, group, function) ('dot', 0, None), ]), (re.compile(r'\{'), [ # (terminal, group, function) ('lbrace', 0, None), ]), (re.compile(r'\}'), [ # (terminal, group, function) ('rbrace', 0, None), ]), (re.compile(r'\('), [ # (terminal, group, function) ('lparen', 0, None), ]), (re.compile(r'\)'), [ # (terminal, group, function) ('rparen', 0, None), ]), (re.compile(r'\['), [ # (terminal, group, function) ('lsquare', 0, None), ]), (re.compile(r'\]'), [ # (terminal, group, function) ('rsquare', 0, None), ]), (re.compile(r'\+'), [ # (terminal, group, function) ('plus', 0, None), ]), (re.compile(r'\*'), [ # (terminal, group, function) ('asterisk', 0, None), ]), (re.compile(r'-'), [ # (terminal, group, function) ('dash', 0, None), ]), (re.compile(r'/'), [ # (terminal, group, function) ('slash', 0, None), ]), (re.compile(r'%'), [ # (terminal, group, function) ('percent', 0, None), ]), (re.compile(r'<='), [ # (terminal, group, function) ('lteq', 0, None), ]), (re.compile(r'<'), [ # (terminal, group, function) ('lt', 0, None), ]), (re.compile(r'>='), [ # (terminal, group, function) ('gteq', 0, None), ]), (re.compile(r'>'), [ # (terminal, group, function) ('gt', 0, None), ]), (re.compile(r'!'), [ # (terminal, group, function) ('not', 0, None), ]), (re.compile(r'\?'), [ # (terminal, group, function) ('qmark', 0, None), ]), (re.compile(r'-?[0-9]+\.[0-9]+'), [ # (terminal, group, function) ('float', 0, None), ]), (re.compile(r'[0-9]+'), [ # (terminal, group, function) ('integer', 0, None), ]), ]), 'wf_output': OrderedDict([ (re.compile(r'\s+'), [ # (terminal, group, function) ]), (re.compile(r'#.*'), [ # (terminal, group, function) ]), (re.compile(r'(Array|Map|Object|Pair|Boolean|Int|Float|Uri|File|String)(?![a-zA-Z0-9_])(?![a-zA-Z0-9_])'), [ # (terminal, group, function) ('type', 0, None), LexerAction('pop'), LexerStackPush('wf_output_declaration'), ]), (re.compile(r'\{'), [ # (terminal, group, function) ('lbrace', 0, None), ]), (re.compile(r'\}'), [ # (terminal, group, function) ('rbrace', 0, None), LexerAction('pop'), ]), (re.compile(r','), [ # (terminal, group, function) ('comma', 0, None), ]), (re.compile(r'\.'), [ # (terminal, group, function) ('dot', 0, None), ]), (re.compile(r'\*'), [ # (terminal, group, function) ('asterisk', 0, None), ]), (re.compile(r'[a-zA-Z]([a-zA-Z0-9_])*(\.[a-zA-Z]([a-zA-Z0-9_])*)*'), [ # (terminal, group, function) ('fqn', 0, None), ]), ]), 'wf_output_declaration': OrderedDict([ (re.compile(r'\s+'), [ # (terminal, group, function) ]), (re.compile(r'#.*'), [ # (terminal, group, function) ]), (re.compile(r'\}'), [ # (terminal, group, function) ('rbrace', 0, None), LexerAction('pop'), ]), (re.compile(r'\['), [ # (terminal, group, function) ('lsquare', 0, None), ]), (re.compile(r'\]'), [ # (terminal, group, function) ('rsquare', 0, None), ]), (re.compile(r'\+'), [ # (terminal, group, function) ('plus', 0, None), ]), (re.compile(r'\*'), [ # (terminal, group, function) ('asterisk', 0, None), ]), (re.compile(r'[0-9]+'), [ # (terminal, group, function) ('integer', 0, None), ]), (re.compile(r'(true|false)(?![a-zA-Z0-9_])'), [ # (terminal, group, function) ('boolean', 0, None), ]), (re.compile(r'if'), [ # (terminal, group, function) ('if', 0, None), ]), (re.compile(r'else'), [ # (terminal, group, function) ('else', 0, None), ]), (re.compile(r'then'), [ # (terminal, group, function) ('then', 0, None), ]), (re.compile(r'(Array|Map|Object|Pair|Boolean|Int|Float|Uri|File|String)(?![a-zA-Z0-9_])(?![a-zA-Z0-9_])'), [ # (terminal, group, function) ('type', 0, None), ]), (re.compile(r'[a-zA-Z]([a-zA-Z0-9_])*'), [ # (terminal, group, function) ('identifier', 0, None), ]), (re.compile(r':'), [ # (terminal, group, function) ('colon', 0, None), ]), (re.compile(r','), [ # (terminal, group, function) ('comma', 0, None), ]), (re.compile(r'\.'), [ # (terminal, group, function) ('dot', 0, None), ]), (re.compile(r'=='), [ # (terminal, group, function) ('double_equal', 0, None), ]), (re.compile(r'='), [ # (terminal, group, function) ('equal', 0, None), ]), (re.compile(r'\|\|'), [ # (terminal, group, function) ('double_pipe', 0, None), ]), (re.compile(r'\&\&'), [ # (terminal, group, function) ('double_ampersand', 0, None), ]), (re.compile(r'!='), [ # (terminal, group, function) ('not_equal', 0, None), ]), (re.compile(r'='), [ # (terminal, group, function) ('equal', 0, None), ]), (re.compile(r'\.'), [ # (terminal, group, function) ('dot', 0, None), ]), (re.compile(r'\{'), [ # (terminal, group, function) ('lbrace', 0, None), ]), (re.compile(r'\('), [ # (terminal, group, function) ('lparen', 0, None), ]), (re.compile(r'\)'), [ # (terminal, group, function) ('rparen', 0, None), ]), (re.compile(r'\['), [ # (terminal, group, function) ('lsquare', 0, None), ]), (re.compile(r'\]'), [ # (terminal, group, function) ('rsquare', 0, None), ]), (re.compile(r'\+'), [ # (terminal, group, function) ('plus', 0, None), ]), (re.compile(r'\*'), [ # (terminal, group, function) ('asterisk', 0, None), ]), (re.compile(r'-'), [ # (terminal, group, function) ('dash', 0, None), ]), (re.compile(r'/'), [ # (terminal, group, function) ('slash', 0, None), ]), (re.compile(r'%'), [ # (terminal, group, function) ('percent', 0, None), ]), (re.compile(r'<='), [ # (terminal, group, function) ('lteq', 0, None), ]), (re.compile(r'<'), [ # (terminal, group, function) ('lt', 0, None), ]), (re.compile(r'>='), [ # (terminal, group, function) ('gteq', 0, None), ]), (re.compile(r'>'), [ # (terminal, group, function) ('gt', 0, None), ]), (re.compile(r'!'), [ # (terminal, group, function) ('not', 0, None), ]), (re.compile(r'\?'), [ # (terminal, group, function) ('qmark', 0, None), ]), (re.compile(r'"([^\\\"\n]|\\[\\"\'nrbtfav\?]|\\[0-7]{1,3}|\\x[0-9a-fA-F]+|\\[uU]([0-9a-fA-F]{4})([0-9a-fA-F]{4})?)*"'), [ # (terminal, group, function) ('string', 0, wdl_unescape), ]), (re.compile(r'\'([^\\\'\n]|\\[\\"\'nrbtfav\?]|\\[0-7]{1,3}|\\x[0-9a-fA-F]+|\\[uU]([0-9a-fA-F]{4})([0-9a-fA-F]{4})?)*\''), [ # (terminal, group, function) ('string', 0, wdl_unescape), ]), (re.compile(r'-?[0-9]+\.[0-9]+'), [ # (terminal, group, function) ('float', 0, None), ]), (re.compile(r'[0-9]+'), [ # (terminal, group, function) ('integer', 0, None), ]), ]), 'task_fqn': OrderedDict([ (re.compile(r'\s+'), [ # (terminal, group, function) ]), (re.compile(r'[a-zA-Z]([a-zA-Z0-9_])*(\.[a-zA-Z]([a-zA-Z0-9_])*)*'), [ # (terminal, group, function) ('fqn', 0, None), LexerAction('pop'), ]), ]), 'scatter': OrderedDict([ (re.compile(r'\s+'), [ # (terminal, group, function) ]), (re.compile(r'\('), [ # (terminal, group, function) ('lparen', 0, None), ]), (re.compile(r'in(?![a-zA-Z0-9_])'), [ # (terminal, group, function) ('in', 0, None), LexerAction('pop'), ]), (re.compile(r'[a-zA-Z]([a-zA-Z0-9_])*'), [ # (terminal, group, function) ('identifier', 0, None), ]), ]), 'raw_command': OrderedDict([ (re.compile(r'\{'), [ # (terminal, group, function) ('raw_cmd_start', 0, None), ]), (re.compile(r'\}'), [ # (terminal, group, function) ('raw_cmd_end', 0, None), LexerAction('pop'), ]), (re.compile(r'\$\{'), [ # (terminal, group, function) ('cmd_param_start', 0, None), LexerStackPush('cmd_param'), ]), (re.compile(r'(.*?)(?=\$\{|\})', re.DOTALL), [ # (terminal, group, function) ('cmd_part', 0, None), ]), ]), 'raw_command2': OrderedDict([ (re.compile(r'<<<'), [ # (terminal, group, function) ('raw_cmd_start', 0, None), ]), (re.compile(r'>>>'), [ # (terminal, group, function) ('raw_cmd_end', 0, None), LexerAction('pop'), ]), (re.compile(r'\$\{'), [ # (terminal, group, function) ('cmd_param_start', 0, None), LexerStackPush('cmd_param'), ]), (re.compile(r'(.*?)(?=\$\{|>>>)', re.DOTALL), [ # (terminal, group, function) ('cmd_part', 0, None), ]), ]), 'cmd_param': OrderedDict([ (re.compile(r'\s+'), [ # (terminal, group, function) ]), (re.compile(r'\}'), [ # (terminal, group, function) ('cmd_param_end', 0, None), LexerAction('pop'), ]), (re.compile(r'\['), [ # (terminal, group, function) ('lsquare', 0, None), ]), (re.compile(r'\]'), [ # (terminal, group, function) ('rsquare', 0, None), ]), (re.compile(r'='), [ # (terminal, group, function) ('equal', 0, None), ]), (re.compile(r'\+'), [ # (terminal, group, function) ('plus', 0, None), ]), (re.compile(r'\*'), [ # (terminal, group, function) ('asterisk', 0, None), ]), (re.compile(r'[0-9]+'), [ # (terminal, group, function) ('integer', 0, None), ]), (re.compile(r'if'), [ # (terminal, group, function) ('if', 0, None), ]), (re.compile(r'else'), [ # (terminal, group, function) ('else', 0, None), ]), (re.compile(r'then'), [ # (terminal, group, function) ('then', 0, None), ]), (re.compile(r'[a-zA-Z]([a-zA-Z0-9_])*(?=\s*=)'), [ # (terminal, group, function) ('cmd_attr_hint', None, None), ('identifier', 0, None), ]), (re.compile(r'(true|false)(?![a-zA-Z0-9_])'), [ # (terminal, group, function) ('boolean', 0, None), ]), (re.compile(r'(Array|Map|Object|Pair|Boolean|Int|Float|Uri|File|String)(?![a-zA-Z0-9_])(?![a-zA-Z0-9_])'), [ # (terminal, group, function) ('type', 0, None), ]), (re.compile(r'[a-zA-Z]([a-zA-Z0-9_])*'), [ # (terminal, group, function) ('identifier', 0, None), ]), (re.compile(r':'), [ # (terminal, group, function) ('colon', 0, None), ]), (re.compile(r','), [ # (terminal, group, function) ('comma', 0, None), ]), (re.compile(r'\.'), [ # (terminal, group, function) ('dot', 0, None), ]), (re.compile(r'=='), [ # (terminal, group, function) ('double_equal', 0, None), ]), (re.compile(r'\|\|'), [ # (terminal, group, function) ('double_pipe', 0, None), ]), (re.compile(r'\&\&'), [ # (terminal, group, function) ('double_ampersand', 0, None), ]), (re.compile(r'!='), [ # (terminal, group, function) ('not_equal', 0, None), ]), (re.compile(r'='), [ # (terminal, group, function) ('equal', 0, None), ]), (re.compile(r'\.'), [ # (terminal, group, function) ('dot', 0, None), ]), (re.compile(r'\{'), [ # (terminal, group, function) ('lbrace', 0, None), ]), (re.compile(r'\('), [ # (terminal, group, function) ('lparen', 0, None), ]), (re.compile(r'\)'), [ # (terminal, group, function) ('rparen', 0, None), ]), (re.compile(r'\['), [ # (terminal, group, function) ('lsquare', 0, None), ]), (re.compile(r'\]'), [ # (terminal, group, function) ('rsquare', 0, None), ]), (re.compile(r'\+'), [ # (terminal, group, function) ('plus', 0, None), ]), (re.compile(r'\*'), [ # (terminal, group, function) ('asterisk', 0, None), ]), (re.compile(r'-'), [ # (terminal, group, function) ('dash', 0, None), ]), (re.compile(r'/'), [ # (terminal, group, function) ('slash', 0, None), ]), (re.compile(r'%'), [ # (terminal, group, function) ('percent', 0, None), ]), (re.compile(r'<='), [ # (terminal, group, function) ('lteq', 0, None), ]), (re.compile(r'<'), [ # (terminal, group, function) ('lt', 0, None), ]), (re.compile(r'>='), [ # (terminal, group, function) ('gteq', 0, None), ]), (re.compile(r'>'), [ # (terminal, group, function) ('gt', 0, None), ]), (re.compile(r'!'), [ # (terminal, group, function) ('not', 0, None), ]), (re.compile(r'"([^\\\"\n]|\\[\\"\'nrbtfav\?]|\\[0-7]{1,3}|\\x[0-9a-fA-F]+|\\[uU]([0-9a-fA-F]{4})([0-9a-fA-F]{4})?)*"'), [ # (terminal, group, function) ('string', 0, wdl_unescape), ]), (re.compile(r'\'([^\\\'\n]|\\[\\"\'nrbtfav\?]|\\[0-7]{1,3}|\\x[0-9a-fA-F]+|\\[uU]([0-9a-fA-F]{4})([0-9a-fA-F]{4})?)*\''), [ # (terminal, group, function) ('string', 0, wdl_unescape), ]), (re.compile(r'-?[0-9]+\.[0-9]+'), [ # (terminal, group, function) ('float', 0, None), ]), (re.compile(r'[0-9]+'), [ # (terminal, group, function) ('integer', 0, None), ]), ]), } def _advance_line_col(self, string, length, line, col): for i in range(length): if string[i] == '\n': line += 1 col = 1 else: col += 1 return (line, col) def _advance_string(self, ctx, string): (ctx.line, ctx.col) = self._advance_line_col(string, len(string), ctx.line, ctx.col) ctx.string = ctx.string[len(string):] def _next(self, ctx, debug=False): for regex, outputs in self.regex[ctx.stack[-1]].items(): if debug: from xtermcolor import colorize token_count = len(ctx.tokens) print('{1} ({2}, {3}) regex: {0}'.format( colorize(regex.pattern, ansi=40), colorize(ctx.string[:20].replace('\n', '\\n'), ansi=15), ctx.line, ctx.col) ) match = regex.match(ctx.string) if match: ctx.re_match = match for output in outputs: if isinstance(output, tuple): (terminal, group, function) = output function = function if function else default_action source_string = match.group(group) if group is not None else '' (group_line, group_col) = self._advance_line_col(ctx.string, match.start(group) if group else 0, ctx.line, ctx.col) function( ctx, terminal, source_string, group_line, group_col ) if debug: print(' matched: {}'.format(colorize(match.group(0).replace('\n', '\\n'), ansi=3))) for token in ctx.tokens[token_count:]: print(' emit: [{}] [{}, {}] [{}] stack:{} context:{}'.format( colorize(token.str, ansi=9), colorize(str(token.line), ansi=5), colorize(str(token.col), ansi=5), colorize(token.source_string, ansi=3), colorize(str(ctx.stack), ansi=4), colorize(str(ctx.user_context), ansi=13) )) token_count = len(ctx.tokens) if isinstance(output, LexerStackPush): ctx.stack.append(output.mode) if debug: print(' push on stack: {}'.format(colorize(output.mode, ansi=4))) if isinstance(output, LexerAction): if output.action == 'pop': mode = ctx.stack.pop() if debug: print(' pop off stack: {}'.format(colorize(mode, ansi=4))) self._advance_string(ctx, match.group(0)) return len(match.group(0)) > 0 return False def lex(self, string, resource, errors=None, debug=False): if errors is None: errors = DefaultSyntaxErrorHandler() string_copy = string user_context = init() ctx = LexerContext(string, resource, errors, user_context) while len(ctx.string): matched = self._next(ctx, debug) if matched == False: raise ctx.errors.unrecognized_token(string_copy, ctx.line, ctx.col) destroy(ctx.user_context) filtered = post_filter(ctx.tokens) return filtered def lex(source, resource, errors=None, debug=False): return TokenStream(HermesLexer().lex(source, resource, errors, debug)) toil-releases-3.24.0/src/toil/wdl/wdl_synthesis.py000066400000000000000000001260731362134276200221640ustar00rootroot00000000000000# Copyright (C) 2018 UCSC Computational Genomics Lab # # 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. from __future__ import absolute_import from __future__ import print_function from __future__ import division from six import iteritems import os import logging import toil.wdl.wdl_parser as wdl_parser from toil.wdl.wdl_functions import heredoc_wdl wdllogger = logging.getLogger(__name__) class SynthesizeWDL: ''' SynthesizeWDL takes the "workflows_dictionary" and "tasks_dictionary" produced by wdl_analysis.py and uses them to write a native python script for use with Toil. A WDL "workflow" section roughly corresponds to the python "main()" function, where functions are wrapped as Toil "jobs", output dependencies specified, and called. A WDL "task" section corresponds to a unique python function, which will be wrapped as a Toil "job" and defined outside of the "main()" function that calls it. Generally this handles breaking sections into their corresponding Toil counterparts. For example: write the imports, then write all functions defining jobs (which have subsections like: write header, define variables, read "File" types into the jobstore, docker call, etc.), then write the main and all of its subsections. ''' def __init__(self, tasks_dictionary, workflows_dictionary, output_directory, json_dict, docker_user, jobstore=None, destBucket=None): self.output_directory = output_directory self.output_file = os.path.join(self.output_directory, 'toilwdl_compiled.py') self.jobstore = jobstore if jobstore else './toilWorkflowRun' if docker_user != 'None': self.docker_user = "'" + docker_user + "'" else: self.docker_user = docker_user # only json is required; tsv/csv are optional self.json_dict = json_dict # holds task skeletons from WDL task objects self.tasks_dictionary = tasks_dictionary # holds workflow structure from WDL workflow objects self.workflows_dictionary = workflows_dictionary # unique iterator to add to cmd names self.cmd_num = 0 # deposit WDL outputs into a cloud bucket; optional self.destBucket = destBucket def write_modules(self): # string used to write imports to the file module_string = heredoc_wdl(''' from toil.job import Job from toil.common import Toil from toil.lib.docker import apiDockerCall from toil.wdl.wdl_functions import generate_docker_bashscript_file from toil.wdl.wdl_functions import select_first from toil.wdl.wdl_functions import sub from toil.wdl.wdl_functions import size from toil.wdl.wdl_functions import glob from toil.wdl.wdl_functions import process_and_read_file from toil.wdl.wdl_functions import process_infile from toil.wdl.wdl_functions import process_outfile from toil.wdl.wdl_functions import abspath_file from toil.wdl.wdl_functions import combine_dicts from toil.wdl.wdl_functions import parse_memory from toil.wdl.wdl_functions import parse_cores from toil.wdl.wdl_functions import parse_disk from toil.wdl.wdl_functions import read_string from toil.wdl.wdl_functions import read_int from toil.wdl.wdl_functions import read_float from toil.wdl.wdl_functions import read_tsv from toil.wdl.wdl_functions import read_csv from toil.wdl.wdl_functions import defined from toil.wdl.wdl_functions import basename import fnmatch import textwrap import subprocess import os import errno import time import shutil import shlex import uuid import logging asldijoiu23r8u34q89fho934t8u34fcurrentworkingdir = os.getcwd() logger = logging.getLogger(__name__) ''', {'jobstore': self.jobstore})[1:] return module_string def write_main(self): ''' Writes out a huge string representing the main section of the python compiled toil script. Currently looks at and writes 5 sections: 1. JSON Variables (includes importing and preparing files as tuples) 2. TSV Variables (includes importing and preparing files as tuples) 3. CSV Variables (includes importing and preparing files as tuples) 4. Wrapping each WDL "task" function as a toil job 5. List out children and encapsulated jobs by priority, then start job0. This should create variable declarations necessary for function calls. Map file paths appropriately and store them in the toil fileStore so that they are persistent from job to job. Create job wrappers for toil. And finally write out, and run the jobs in order of priority using the addChild and encapsulate commands provided by toil. :return: giant string containing the main def for the toil script. ''' main_section = '' # write out the main header main_header = self.write_main_header() main_section = main_section + main_header # write out the workflow declarations main_section = main_section + ' # WF Declarations\n' wf_declarations_to_write = self.write_main_wfdeclarations() main_section = main_section + wf_declarations_to_write # write toil job wrappers with input vars jobs_to_write = self.write_main_jobwrappers() main_section = main_section + jobs_to_write # loop to export all outputs to a cloud bucket if self.destBucket: main_destbucket = self.write_main_destbucket() main_section = main_section + main_destbucket return main_section def write_main_header(self): main_header = heredoc_wdl(''' if __name__=="__main__": options = Job.Runner.getDefaultOptions("{jobstore}") options.clean = 'always' with Toil(options) as fileStore: ''', {'jobstore': self.jobstore}) return main_header def write_main_wfdeclarations(self): main_section = '' for wfname, wf in iteritems(self.workflows_dictionary): if 'wf_declarations' in wf: for var, var_expressn in iteritems(wf['wf_declarations']): # check the json file for the expression's value # this is a higher priority and overrides anything written in the .wdl json_expressn = self.json_var(wf=wfname, var=var) if json_expressn: var_expressn['value'] = json_expressn # empty string if not var_expressn['value'] and (var_expressn['type'] in ['String', 'File']): main_section += ' {} = ""\n'.format(var) # None elif not var_expressn['value'] and not (var_expressn['type'] in ['String', 'File']): main_section += ' {} = None\n'.format(var) # import filepath into jobstore elif var_expressn['value'] and (var_expressn['type'] == 'File'): main_section += ' {} = process_infile({}, fileStore)\n'.format(var, var_expressn['value']) # normal declaration else: main_section += ' {} = {}\n'.format(var, var_expressn['value']) return main_section def write_main_jobwrappers(self): ''' Writes out 'jobs' as wrapped toil objects in preparation for calling. :return: A string representing this. ''' main_section = '' # toil cannot technically start with multiple jobs, so an empty # 'initialize_jobs' function is always called first to get around this main_section = main_section + '\n job0 = Job.wrapJobFn(initialize_jobs)\n' # declare each job in main as a wrapped toil function in order of priority for wf in self.workflows_dictionary: for assignment in self.workflows_dictionary[wf]: if assignment.startswith('call'): main_section += ' job0 = job0.encapsulate()\n' main_section += self.write_main_jobwrappers_call(self.workflows_dictionary[wf][assignment]) if assignment.startswith('scatter'): main_section += ' job0 = job0.encapsulate()\n' main_section += self.write_main_jobwrappers_scatter(self.workflows_dictionary[wf][assignment], assignment) if assignment.startswith('if'): main_section += ' if {}:\n'.format(self.workflows_dictionary[wf][assignment]['expression']) main_section += self.write_main_jobwrappers_if(self.workflows_dictionary[wf][assignment]['body']) main_section += '\n fileStore.start(job0)\n' return main_section def write_main_destbucket(self): ''' Writes out a loop for exporting outputs to a cloud bucket. :return: A string representing this. ''' main_section = heredoc_wdl(''' outdir = '{outdir}' onlyfiles = [os.path.join(outdir, f) for f in os.listdir(outdir) if os.path.isfile(os.path.join(outdir, f))] for output_f_path in onlyfiles: output_file = fileStore.writeGlobalFile(output_f_path) preserveThisFilename = os.path.basename(output_f_path) destUrl = '/'.join(s.strip('/') for s in [destBucket, preserveThisFilename]) fileStore.exportFile(output_file, destUrl) ''', {'outdir': self.output_directory}, indent=' ') return main_section def fetch_ignoredifs(self, assignments, breaking_assignment): ignore_ifs = [] for assignment in assignments: if assignment.startswith('call'): pass elif assignment.startswith('scatter'): pass elif assignment.startswith('if'): if not self.fetch_ignoredifs_chain(assignments[assignment]['body'], breaking_assignment): ignore_ifs.append(assignment) return ignore_ifs def fetch_ignoredifs_chain(self, assignments, breaking_assignment): for assignment in assignments: if assignment.startswith('call'): if assignment == breaking_assignment: return True if assignment.startswith('scatter'): if assignment == breaking_assignment: return True if assignment.startswith('if'): return self.fetch_ignoredifs_chain(assignments[assignment]['body'], breaking_assignment) return False def write_main_jobwrappers_if(self, if_statement): main_section = '' for assignment in if_statement: if assignment.startswith('call'): main_section += ' job0 = job0.encapsulate()\n' main_section += self.write_main_jobwrappers_call(if_statement[assignment]) if assignment.startswith('scatter'): main_section += ' job0 = job0.encapsulate()\n' main_section += self.write_main_jobwrappers_scatter(if_statement[assignment], assignment) if assignment.startswith('if'): main_section += ' if {}:\n'.format(if_statement[assignment]['expression']) main_section += self.write_main_jobwrappers_if(if_statement[assignment]['body']) main_section = self.indent_docstring(main_section) return main_section def write_main_jobwrappers_scatter(self, task, assignment): scatter_inputs = self.fetch_scatter_inputs(assignment) main_section = ' {scatter} = job0.addChild({scatter}Cls('.format(scatter=assignment) for var in scatter_inputs: main_section += var + '=' + var + ', ' if main_section.endswith(', '): main_section = main_section[:-2] main_section += '))\n' scatter_outputs = self.fetch_scatter_outputs(task) for var in scatter_outputs: main_section += ' {var} = {scatter}.rv("{var}")\n'.format(var=var['task'] + '_' + var['output'], scatter=assignment) return main_section def fetch_scatter_outputs(self, task): scatteroutputs = [] for var in task['body']: # TODO variable support if var.startswith('call'): if 'outputs' in self.tasks_dictionary[task['body'][var]['task']]: for output in self.tasks_dictionary[task['body'][var]['task']]['outputs']: scatteroutputs.append({'task': task['body'][var]['alias'], 'output': output[0]}) return scatteroutputs def fetch_scatter_inputs(self, assigned): for wf in self.workflows_dictionary: ignored_ifs = self.fetch_ignoredifs(self.workflows_dictionary[wf], assigned) # TODO support additional wfs break scatternamespace = [] for wfname, wf in iteritems(self.workflows_dictionary): if 'wf_declarations' in wf: for var in wf['wf_declarations']: scatternamespace.append(var) for wf in self.workflows_dictionary: for assignment in self.workflows_dictionary[wf]: if assignment == assigned: return scatternamespace elif assignment.startswith('call'): if 'outputs' in self.tasks_dictionary[self.workflows_dictionary[wf][assignment]['task']]: for output in self.tasks_dictionary[self.workflows_dictionary[wf][assignment]['task']]['outputs']: scatternamespace.append(self.workflows_dictionary[wf][assignment]['alias'] + '_' + output[0]) elif assignment.startswith('scatter'): for var in self.fetch_scatter_outputs(self.workflows_dictionary[wf][assignment]): scatternamespace.append(var['task'] + '_' + var['output']) elif assignment.startswith('if') and assignment not in ignored_ifs: new_list, cont_or_break = self.fetch_scatter_inputs_chain(self.workflows_dictionary[wf][assignment]['body'], assigned, ignored_ifs, inputs_list=[]) scatternamespace += new_list if not cont_or_break: return scatternamespace return scatternamespace def fetch_scatter_inputs_chain(self, inputs, assigned, ignored_ifs, inputs_list): for i in inputs: if i == assigned: return inputs_list, False elif i.startswith('call'): if 'outputs' in self.tasks_dictionary[inputs[i]['task']]: for output in self.tasks_dictionary[inputs[i]['task']]['outputs']: inputs_list.append(inputs[i]['alias'] + '_' + output[0]) elif i.startswith('scatter'): for var in self.fetch_scatter_outputs(inputs[i]): inputs_list.append(var['task'] + '_' + var['output']) elif i.startswith('if') and i not in ignored_ifs: inputs_list, cont_or_break = self.fetch_scatter_inputs_chain(inputs[i]['body'], assigned, ignored_ifs, inputs_list) if not cont_or_break: return inputs_list, False return inputs_list, True def write_main_jobwrappers_call(self, task): main_section = ' {} = job0.addChild({}Cls('.format(task['alias'], task['task']) for var in task['io']: main_section += var + '=' + task['io'][var] + ', ' if main_section.endswith(', '): main_section = main_section[:-2] main_section += '))\n' call_outputs = self.fetch_call_outputs(task) for var in call_outputs: main_section += ' {var} = {task}.rv("{output}")\n'.format(var=var['task'] + '_' + var['output'], task=var['task'], output=var['output']) return main_section def fetch_call_outputs(self, task): calloutputs = [] if 'outputs' in self.tasks_dictionary[task['task']]: for output in self.tasks_dictionary[task['task']]['outputs']: calloutputs.append({'task': task['alias'], 'output': output[0]}) return calloutputs def write_functions(self): ''' Writes out a python function for each WDL "task" object. :return: a giant string containing the meat of the job defs. ''' # toil cannot technically start with multiple jobs, so an empty # 'initialize_jobs' function is always called first to get around this fn_section = 'def initialize_jobs(job):\n' + \ ' job.fileStore.logToMaster("initialize_jobs")\n' for job in self.tasks_dictionary: fn_section += self.write_function(job) for wf in self.workflows_dictionary: for assignment in self.workflows_dictionary[wf]: if assignment.startswith('scatter'): fn_section += self.write_scatterfunction(self.workflows_dictionary[wf][assignment], assignment) if assignment.startswith('if'): fn_section += self.write_scatterfunctions_within_if(self.workflows_dictionary[wf][assignment]['body']) return fn_section def write_scatterfunctions_within_if(self, ifstatement): fn_section = '' for assignment in ifstatement: if assignment.startswith('scatter'): fn_section += self.write_scatterfunction(ifstatement[assignment], assignment) if assignment.startswith('if'): fn_section += self.write_scatterfunctions_within_if(ifstatement[assignment]['body']) return fn_section def write_scatterfunction(self, job, scattername): ''' Writes out a python function for each WDL "scatter" object. ''' scatter_outputs = self.fetch_scatter_outputs(job) # write the function header fn_section = self.write_scatterfunction_header(scattername) # write the scatter definitions fn_section += self.write_scatterfunction_lists(scatter_outputs) # write fn_section += self.write_scatterfunction_loop(job, scatter_outputs) # write the outputs for the task to return fn_section += self.write_scatterfunction_outputreturn(scatter_outputs) return fn_section def write_scatterfunction_header(self, scattername): """ :return: """ scatter_inputs = self.fetch_scatter_inputs(scattername) fn_section = '\n\nclass {jobname}Cls(Job):\n'.format(jobname=scattername) fn_section += ' def __init__(self, ' for input in scatter_inputs: fn_section += '{input}=None, '.format(input=input) fn_section += '*args, **kwargs):\n' fn_section += ' Job.__init__(self)\n\n' for input in scatter_inputs: fn_section += ' self.id_{input} = {input}\n'.format(input=input) fn_section += heredoc_wdl(''' def run(self, fileStore): fileStore.logToMaster("{jobname}") tempDir = fileStore.getLocalTempDir() try: os.makedirs(os.path.join(tempDir, 'execution')) except OSError as e: if e.errno != errno.EEXIST: raise ''', {'jobname': scattername}, indent=' ')[1:] for input in scatter_inputs: fn_section += ' {input} = self.id_{input}\n'.format(input=input) return fn_section def write_scatterfunction_outputreturn(self, scatter_outputs): """ :return: """ fn_section = '\n rvDict = {' for var in scatter_outputs: fn_section += '"{var}": {var}, '.format(var=var['task'] + '_' + var['output']) if fn_section.endswith(', '): fn_section = fn_section[:-2] fn_section += '}\n' fn_section += ' return rvDict\n\n' return fn_section[:-1] def write_scatterfunction_lists(self, scatter_outputs): """ :return: """ fn_section = '\n' for var in scatter_outputs: fn_section += ' {var} = []\n'.format(var=var['task'] + '_' + var['output']) return fn_section def write_scatterfunction_loop(self, job, scatter_outputs): """ :return: """ collection = job['collection'] item = job['item'] fn_section = ' for {item} in {collection}:\n'.format(item=item, collection=collection) previous_dependency = 'self' for statement in job['body']: if statement.startswith('call'): fn_section += self.write_scatter_callwrapper(job['body'][statement], previous_dependency) previous_dependency = 'job_' + job['body'][statement]['alias'] elif statement.startswith('variable'): fn_section += ' {var} = {expr}\n'.format(var=job['body'][statement]['name'], expr=job['body'][statement]['value']) for var in scatter_outputs: fn_section += ' {var}.append({task}.rv("{output}"))\n'.format(var=var['task'] + '_' + var['output'], task='job_' + var['task'], output=var['output']) return fn_section def write_scatter_callwrapper(self, job, previous_dependency): fn_section = ' job_{alias} = {pd}.addFollowOn({task}Cls('.format(alias=job['alias'], pd=previous_dependency, task=job['task']) for var in job['io']: fn_section += var + '=' + job['io'][var] + ', ' if fn_section.endswith(', '): fn_section = fn_section[:-2] fn_section += '))\n' return fn_section def fetch_scatter_varwrapper_inputs(self, job, scattername): varwrapper_inputs = self.fetch_scatter_inputs(scattername) for wf in self.workflows_dictionary: for assignment in self.workflows_dictionary[wf]: if assignment == scattername: for scatterassignment in self.workflows_dictionary[wf][assignment]['body']: if scatterassignment.startswith('variable'): if job['name'] == self.workflows_dictionary[wf][assignment]['body'][scatterassignment]['name']: varwrapper_inputs.append(self.workflows_dictionary[wf][assignment]['item']) return varwrapper_inputs else: varwrapper_inputs.append(self.workflows_dictionary[wf][assignment]['body'][scatterassignment]['name']) if scatterassignment.startswith('call'): varwrapper_inputs.append(self.workflows_dictionary[wf][assignment]['body'][scatterassignment]['alias']) varwrapper_inputs.append(self.workflows_dictionary[wf][assignment]['item']) return varwrapper_inputs def write_function(self, job): ''' Writes out a python function for each WDL "task" object. Each python function is a unit of work written out as a string in preparation to being written out to a file. In WDL, each "job" is called a "task". Each WDL task is written out in multiple steps: 1: Header and inputs (e.g. 'def mapping(self, input1, input2)') 2: Log job name (e.g. 'job.fileStore.logToMaster('initialize_jobs')') 3: Create temp dir (e.g. 'tempDir = fileStore.getLocalTempDir()') 4: import filenames and use readGlobalFile() to get files from the jobStore 5: Reformat commandline variables (like converting to ' '.join(files)). 6: Commandline call using subprocess.Popen(). 7: Write the section returning the outputs. Also logs stats. :return: a giant string containing the meat of the job defs for the toil script. ''' # write the function header fn_section = self.write_function_header(job) # write out commandline keywords fn_section += self.write_function_cmdline(job) if self.needsdocker(job): # write a bash script to inject into the docker fn_section += self.write_function_bashscriptline(job) # write a call to the docker API fn_section += self.write_function_dockercall(job) else: # write a subprocess call fn_section += self.write_function_subprocesspopen() # write the outputs for the definition to return fn_section += self.write_function_outputreturn(job, docker=self.needsdocker(job)) return fn_section def write_function_header(self, job): ''' Writes the header that starts each function, for example, this function can write and return: 'def write_function_header(self, job, job_declaration_array):' :param job: A list such that: (job priority #, job ID #, Job Skeleton Name, Job Alias) :param job_declaration_array: A list of all inputs that job requires. :return: A string representing this. ''' fn_section = '\n\nclass {jobname}Cls(Job):\n'.format(jobname=job) fn_section += ' def __init__(self, ' if 'inputs' in self.tasks_dictionary[job]: for i in self.tasks_dictionary[job]['inputs']: var = i[0] vartype = i[1] if vartype == 'String': fn_section += '{input}="", '.format(input=var) else: fn_section += '{input}=None, '.format(input=var) fn_section += '*args, **kwargs):\n' fn_section += ' super({jobname}Cls, self).__init__(*args, **kwargs)\n'.format(jobname=job) # TODO: Resolve inherent problems resolving resource requirements # In WDL, "local-disk " + 500 + " HDD" cannot be directly converted to python. # This needs a special handler. if 'runtime' in self.tasks_dictionary[job]: runtime_resources = [] if 'memory' in self.tasks_dictionary[job]['runtime']: runtime_resources.append('memory=memory') memory = self.tasks_dictionary[job]['runtime']['memory'] fn_section += ' memory=parse_memory({})\n'.format(memory) if 'cpu' in self.tasks_dictionary[job]['runtime']: runtime_resources.append('cores=cores') cores = self.tasks_dictionary[job]['runtime']['cpu'] fn_section += ' cores=parse_cores({})\n'.format(cores) if 'disks' in self.tasks_dictionary[job]['runtime']: runtime_resources.append('disk=disk') disk = self.tasks_dictionary[job]['runtime']['disks'] fn_section += ' disk=parse_disk({})\n'.format(disk) runtime_resources = ['self'] + runtime_resources fn_section += ' Job.__init__({})\n\n'.format(', '.join(runtime_resources)) if 'inputs' in self.tasks_dictionary[job]: for i in self.tasks_dictionary[job]['inputs']: var = i[0] var_expressn = i[2] json_expressn = self.json_var(task=job, var=var) # json declarations have priority and can overwrite # whatever is in the wdl file if json_expressn: var_expressn = json_expressn if not var_expressn: var_expressn = var fn_section += ' self.id_{} = {}\n'.format(var, var_expressn) fn_section += heredoc_wdl(''' def run(self, fileStore): fileStore.logToMaster("{jobname}") tempDir = fileStore.getLocalTempDir() try: os.makedirs(os.path.join(tempDir, 'execution')) except OSError as e: if e.errno != errno.EEXIST: raise ''', {'jobname': job}, indent=' ')[1:] if 'inputs' in self.tasks_dictionary[job]: for i in self.tasks_dictionary[job]['inputs']: var = i[0] var_type = i[1] docker_bool = str(self.needsdocker(job)) if var_type == 'File': fn_section += ' {} = process_and_read_file(abspath_file(self.id_{}, asldijoiu23r8u34q89fho934t8u34fcurrentworkingdir), tempDir, fileStore, docker={})\n'.format(var, var, docker_bool) else: fn_section += ' {} = self.id_{}\n'.format(var, var) return fn_section def json_var(self, var, task=None, wf=None): """ :param var: :param task: :param wf: :return: """ # default to the last workflow in the list if wf is None: for workflow in self.workflows_dictionary: wf = workflow for identifier in self.json_dict: # check task declarations if task: if identifier == '{}.{}.{}'.format(wf, task, var): return self.json_dict[identifier] # else check workflow declarations else: if identifier == '{}.{}'.format(wf, var): return self.json_dict[identifier] return None def write_function_bashscriptline(self, job): ''' Writes a function to create a bashscript for injection into the docker container. :param job_task_reference: The job referenced in WDL's Task section. :param job_alias: The actual job name to be written. :return: A string writing all of this. ''' fn_section = " generate_docker_bashscript_file(temp_dir=tempDir, docker_dir=tempDir, globs=[" # TODO: Add glob # if 'outputs' in self.tasks_dictionary[job]: # for output in self.tasks_dictionary[job]['outputs']: # fn_section += '({}), '.format(output[2]) if fn_section.endswith(', '): fn_section = fn_section[:-2] fn_section += "], cmd=cmd, job_name='{}')\n\n".format(str(job)) return fn_section def write_function_dockercall(self, job): ''' Writes a string containing the apiDockerCall() that will run the job. :param job_task_reference: The name of the job calling docker. :param docker_image: The corresponding name of the docker image. e.g. "ubuntu:latest" :return: A string containing the apiDockerCall() that will run the job. ''' docker_dict = {"docker_image": self.tasks_dictionary[job]['runtime']['docker'], "job_task_reference": job, "docker_user": str(self.docker_user)} docker_template = heredoc_wdl(''' stdout = apiDockerCall(self, image={docker_image}, working_dir=tempDir, parameters=[os.path.join(tempDir, "{job_task_reference}_script.sh")], entrypoint="/bin/bash", user={docker_user}, stderr=True, volumes={{tempDir: {{"bind": tempDir}}}}) writetype = 'wb' if isinstance(stdout, bytes) else 'w' with open(os.path.join(asldijoiu23r8u34q89fho934t8u34fcurrentworkingdir, '{job_task_reference}.log'), writetype) as f: f.write(stdout) ''', docker_dict, indent=' ')[1:] return docker_template def write_function_cmdline(self, job): ''' Write a series of commandline variables to be concatenated together eventually and either called with subprocess.Popen() or with apiDockerCall() if a docker image is called for. :param job: A list such that: (job priority #, job ID #, Job Skeleton Name, Job Alias) :return: A string representing this. ''' fn_section = '\n' cmd_array = [] if 'raw_commandline' in self.tasks_dictionary[job]: for cmd in self.tasks_dictionary[job]['raw_commandline']: if not cmd.startswith("r'''"): cmd = 'str({i} if not isinstance({i}, tuple) else process_and_read_file({i}, tempDir, fileStore)).strip("{nl}")'.format(i=cmd, nl=r"\n") fn_section = fn_section + heredoc_wdl(''' try: # Intended to deal with "optional" inputs that may not exist # TODO: handle this better command{num} = {cmd} except: command{num} = ''\n''', {'cmd': cmd, 'num': self.cmd_num}, indent=' ') cmd_array.append('command' + str(self.cmd_num)) self.cmd_num = self.cmd_num + 1 if cmd_array: fn_section += '\n cmd = ' for command in cmd_array: fn_section += '{command} + '.format(command=command) if fn_section.endswith(' + '): fn_section = fn_section[:-3] fn_section += '\n cmd = textwrap.dedent(cmd.strip("{nl}"))\n'.format(nl=r"\n") return fn_section def write_function_subprocesspopen(self): ''' Write a subprocess.Popen() call for this function and write it out as a string. :param job: A list such that: (job priority #, job ID #, Job Skeleton Name, Job Alias) :return: A string representing this. ''' fn_section = heredoc_wdl(''' this_process = subprocess.Popen(cmd, shell=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE) stdout, stderr = this_process.communicate()\n''', indent=' ') return fn_section def write_function_outputreturn(self, job, docker=False): ''' Find the output values that this function needs and write them out as a string. :param job: A list such that: (job priority #, job ID #, Job Skeleton Name, Job Alias) :param job_task_reference: The name of the job to look up values for. :return: A string representing this. ''' fn_section = '' if 'outputs' in self.tasks_dictionary[job]: return_values = [] for output in self.tasks_dictionary[job]['outputs']: output_name = output[0] output_type = output[1] output_value = output[2] if output_type == 'File': nonglob_dict = { "output_name": output_name, "expression": output_value, "out_dir": self.output_directory, "output_type": output_type} nonglob_template = heredoc_wdl(''' # output-type: {output_type} output_filename = {expression} {output_name} = process_outfile(output_filename, fileStore, tempDir, '{out_dir}') ''', nonglob_dict, indent=' ')[1:] fn_section += nonglob_template return_values.append(output_name) else: fn_section += ' {} = {}\n'.format(output_name, output_value) return_values.append(output_name) if return_values: fn_section += ' rvDict = {' for return_value in return_values: fn_section += '"{rv}": {rv}, '.format(rv=return_value) if fn_section.endswith(', '): fn_section = fn_section[:-2] if return_values: fn_section = fn_section + '}\n' if return_values: fn_section += ' return rvDict\n\n' return fn_section def indent_docstring(self, string2indent): split_string = string2indent.split('\n') new_string = '' for line in split_string: new_string += ' {}\n'.format(line) return new_string def needsdocker(self, job): """ :param job: :return: """ if 'runtime' in self.tasks_dictionary[job]: if 'docker' in self.tasks_dictionary[job]['runtime']: return True return False def write_python_file(self, module_section, fn_section, main_section, output_file): ''' Just takes three strings and writes them to output_file. :param module_section: A string of 'import modules'. :param fn_section: A string of python 'def functions()'. :param main_section: A string declaring toil options and main's header. :param job_section: A string import files into toil and declaring jobs. :param output_file: The file to write the compiled toil script to. ''' with open(output_file, 'w') as file: file.write(module_section) file.write(fn_section) file.write(main_section) def write_mappings(self, i): ''' Intended to take a ToilWDL_instance (i) and prints the final task dict, and workflow dict. Does not work by default with toil since Toil actively suppresses stdout during the run. :param i: A class object instance with the following dict variables: self.tasks_dictionary self.workflows_dictionary ''' from collections import OrderedDict class Formatter(object): def __init__(self): self.types = {} self.htchar = '\t' self.lfchar = '\n' self.indent = 0 self.set_formater(object, self.__class__.format_object) self.set_formater(dict, self.__class__.format_dict) self.set_formater(list, self.__class__.format_list) self.set_formater(tuple, self.__class__.format_tuple) def set_formater(self, obj, callback): self.types[obj] = callback def __call__(self, value, **args): for key in args: setattr(self, key, args[key]) formater = self.types[type(value) if type(value) in self.types else object] return formater(self, value, self.indent) def format_object(self, value, indent): return repr(value) def format_dict(self, value, indent): items = [ self.lfchar + self.htchar * (indent + 1) + repr(key) + ': ' + (self.types[type(value[key]) if type(value[key]) in self.types else object])(self, value[key], indent + 1) for key in value] return '{%s}' % (','.join(items) + self.lfchar + self.htchar * indent) def format_list(self, value, indent): items = [ self.lfchar + self.htchar * (indent + 1) + ( self.types[type(item) if type(item) in self.types else object])(self, item, indent + 1) for item in value] return '[%s]' % (','.join(items) + self.lfchar + self.htchar * indent) def format_tuple(self, value, indent): items = [ self.lfchar + self.htchar * (indent + 1) + ( self.types[type(item) if type(item) in self.types else object])(self, item, indent + 1) for item in value] return '(%s)' % (','.join(items) + self.lfchar + self.htchar * indent) pretty = Formatter() def format_ordereddict(self, value, indent): items = [ self.lfchar + self.htchar * (indent + 1) + "(" + repr(key) + ', ' + (self.types[ type(value[key]) if type(value[key]) in self.types else object ])(self, value[key], indent + 1) + ")" for key in value ] return 'OrderedDict([%s])' % (','.join(items) + self.lfchar + self.htchar * indent) pretty.set_formater(OrderedDict, format_ordereddict) with open('mappings.out', 'w') as f: f.write(pretty(i.tasks_dictionary)) f.write('\n\n\n\n\n\n') f.write(pretty(i.workflows_dictionary)) def write_AST(wdl_file, outdir=None): ''' Writes a file with the AST for a wdl file in the outdir. ''' if outdir is None: outdir = os.getcwd() with open(os.path.join(outdir, 'AST.out'), 'w') as f: with open(wdl_file, 'r') as wdl: wdl_string = wdl.read() ast = wdl_parser.parse(wdl_string).ast() f.write(ast.dumps(indent=2)) toil-releases-3.24.0/src/toil/worker.py000066400000000000000000000625201362134276200200040ustar00rootroot00000000000000# Copyright (C) 2015-2018 Regents of the University of California # # 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. from __future__ import absolute_import, print_function from future import standard_library standard_library.install_aliases() from builtins import str from builtins import map from builtins import filter import os import sys import copy import random import json import tempfile import traceback import time import signal import socket import logging import shutil from toil.lib.compatibility import USING_PYTHON2 from toil.lib.expando import MagicExpando from toil.common import Toil, safeUnpickleFromStream from toil.fileStores.abstractFileStore import AbstractFileStore from toil import logProcessContext from toil.job import Job from toil.lib.bioio import setLogLevel from toil.lib.bioio import getTotalCpuTime from toil.lib.bioio import getTotalCpuTimeAndMemoryUsage from toil.deferred import DeferredFunctionManager try: from toil.cwl.cwltoil import CWL_INTERNAL_JOBS except ImportError: # CWL extra not installed CWL_INTERNAL_JOBS = () logging.basicConfig() logger = logging.getLogger(__name__) def nextChainableJobGraph(jobGraph, jobStore): """Returns the next chainable jobGraph after this jobGraph if one exists, or None if the chain must terminate. """ #If no more jobs to run or services not finished, quit if len(jobGraph.stack) == 0 or len(jobGraph.services) > 0 or jobGraph.checkpoint != None: logger.debug("Stopping running chain of jobs: length of stack: %s, services: %s, checkpoint: %s", len(jobGraph.stack), len(jobGraph.services), jobGraph.checkpoint != None) return None #Get the next set of jobs to run jobs = jobGraph.stack[-1] assert len(jobs) > 0 #If there are 2 or more jobs to run in parallel we quit if len(jobs) >= 2: logger.debug("No more jobs can run in series by this worker," " it's got %i children", len(jobs)-1) return None #We check the requirements of the jobGraph to see if we can run it #within the current worker successorJobNode = jobs[0] if successorJobNode.memory > jobGraph.memory: logger.debug("We need more memory for the next job, so finishing") return None if successorJobNode.cores > jobGraph.cores: logger.debug("We need more cores for the next job, so finishing") return None if successorJobNode.disk > jobGraph.disk: logger.debug("We need more disk for the next job, so finishing") return None if successorJobNode.preemptable != jobGraph.preemptable: logger.debug("Preemptability is different for the next job, returning to the leader") return None if successorJobNode.predecessorNumber > 1: logger.debug("The jobGraph has multiple predecessors, we must return to the leader.") return None # Load the successor jobGraph successorJobGraph = jobStore.load(successorJobNode.jobStoreID) # Somewhat ugly, but check if job is a checkpoint job and quit if # so if successorJobGraph.command.startswith("_toil "): #Load the job successorJob = Job._loadJob(successorJobGraph.command, jobStore) # Check it is not a checkpoint if successorJob.checkpoint: logger.debug("Next job is checkpoint, so finishing") return None # Made it through! This job is chainable. return successorJobGraph def workerScript(jobStore, config, jobName, jobStoreID, redirectOutputToLogFile=True): """ Worker process script, runs a job. :param str jobName: The "job name" (a user friendly name) of the job to be run :param str jobStoreLocator: Specifies the job store to use :param str jobStoreID: The job store ID of the job to be run """ logging.basicConfig() setLogLevel(config.logLevel) ########################################## #Create the worker killer, if requested ########################################## logFileByteReportLimit = config.maxLogFileSize if config.badWorker > 0 and random.random() < config.badWorker: # We need to kill the process we are currently in, to simulate worker # failure. We don't want to just send SIGKILL, because we can't tell # that from a legitimate OOM on our CI runner. We're going to send # SIGUSR1 so our terminations are distinctive, and then SIGKILL if that # didn't stick. We definitely don't want to do this from *within* the # process we are trying to kill, so we fork off. TODO: We can still # leave the killing code running after the main Toil flow is done, but # since it's now in a process instead of a thread, the main Python # process won't wait around for its timeout to expire. I think this is # better than the old thread-based way where all of Toil would wait # around to be killed. killTarget = os.getpid() sleepTime = config.badWorkerFailInterval * random.random() if os.fork() == 0: # We are the child # Let the parent run some amount of time time.sleep(sleepTime) # Kill it gently os.kill(killTarget, signal.SIGUSR1) # Wait for that to stick time.sleep(0.01) try: # Kill it harder. Hope the PID hasn't already been reused. # If we succeeded the first time, this will OSError os.kill(killTarget, signal.SIGKILL) except OSError: pass # Exit without doing any of Toil's cleanup os._exit(0) # We don't need to reap the child. Either it kills us, or we finish # before it does. Either way, init will have to clean it up for us. ########################################## #Load the environment for the jobGraph ########################################## #First load the environment for the jobGraph. with jobStore.readSharedFileStream("environment.pickle") as fileHandle: environment = safeUnpickleFromStream(fileHandle) env_blacklist = { "TMPDIR", "TMP", "HOSTNAME", "HOSTTYPE", "HOME", "LOGNAME", "USER", "DISPLAY", "JAVA_HOME" } for i in environment: if i == "PATH": # Handle path specially. Sometimes e.g. leader may not include # /bin, but the Toil appliance needs it. if i in os.environ and os.environ[i] != '': # Use the provided PATH and then the local system's PATH os.environ[i] = environment[i] + ':' + os.environ[i] else: # Use the provided PATH only os.environ[i] = environment[i] elif i not in env_blacklist: os.environ[i] = environment[i] # sys.path is used by __import__ to find modules if "PYTHONPATH" in environment: for e in environment["PYTHONPATH"].split(':'): if e != '': sys.path.append(e) toilWorkflowDir = Toil.getWorkflowDir(config.workflowID, config.workDir) ########################################## #Setup the temporary directories. ########################################## # Dir to put all this worker's temp files in. localWorkerTempDir = tempfile.mkdtemp(dir=toilWorkflowDir) os.chmod(localWorkerTempDir, 0o755) ########################################## #Setup the logging ########################################## #This is mildly tricky because we don't just want to #redirect stdout and stderr for this Python process; we want to redirect it #for this process and all children. Consequently, we can't just replace #sys.stdout and sys.stderr; we need to mess with the underlying OS-level #file descriptors. See #When we start, standard input is file descriptor 0, standard output is #file descriptor 1, and standard error is file descriptor 2. # Do we even want to redirect output? Let the config make us not do it. redirectOutputToLogFile = redirectOutputToLogFile and not config.disableWorkerOutputCapture #What file do we want to point FDs 1 and 2 to? tempWorkerLogPath = os.path.join(localWorkerTempDir, "worker_log.txt") if redirectOutputToLogFile: # Announce that we are redirecting logging, and where it will now go. # This is important if we are trying to manually trace a faulty worker invocation. logger.info("Redirecting logging to %s", tempWorkerLogPath) sys.stdout.flush() sys.stderr.flush() # Save the original stdout and stderr (by opening new file descriptors # to the same files) origStdOut = os.dup(1) origStdErr = os.dup(2) # Open the file to send stdout/stderr to. logFh = os.open(tempWorkerLogPath, os.O_WRONLY | os.O_CREAT | os.O_APPEND) # Replace standard output with a descriptor for the log file os.dup2(logFh, 1) # Replace standard error with a descriptor for the log file os.dup2(logFh, 2) # Since we only opened the file once, all the descriptors duped from # the original will share offset information, and won't clobber each # others' writes. See . This # shouldn't matter, since O_APPEND seeks to the end of the file before # every write, but maybe there's something odd going on... # Close the descriptor we used to open the file os.close(logFh) debugging = logging.getLogger().isEnabledFor(logging.DEBUG) ########################################## #Worker log file trapped from here on in ########################################## workerFailed = False statsDict = MagicExpando() statsDict.jobs = [] statsDict.workers.logsToMaster = [] blockFn = lambda : True listOfJobs = [jobName] job = None try: #Put a message at the top of the log, just to make sure it's working. logger.info("---TOIL WORKER OUTPUT LOG---") sys.stdout.flush() logProcessContext(config) ########################################## #Connect to the deferred function system ########################################## deferredFunctionManager = DeferredFunctionManager(toilWorkflowDir) ########################################## #Load the jobGraph ########################################## jobGraph = jobStore.load(jobStoreID) listOfJobs[0] = str(jobGraph) logger.debug("Parsed job wrapper") ########################################## #Cleanup from any earlier invocation of the jobGraph ########################################## if jobGraph.command == None: logger.debug("Wrapper has no user job to run.") # Cleanup jobs already finished f = lambda jobs : [z for z in [[y for y in x if jobStore.exists(y.jobStoreID)] for x in jobs] if len(z) > 0] jobGraph.stack = f(jobGraph.stack) jobGraph.services = f(jobGraph.services) logger.debug("Cleaned up any references to completed successor jobs") #This cleans the old log file which may #have been left if the job is being retried after a job failure. oldLogFile = jobGraph.logJobStoreFileID if oldLogFile != None: jobGraph.logJobStoreFileID = None jobStore.update(jobGraph) #Update first, before deleting any files jobStore.deleteFile(oldLogFile) ########################################## # If a checkpoint exists, restart from the checkpoint ########################################## # The job is a checkpoint, and is being restarted after previously completing if jobGraph.checkpoint != None: logger.debug("Job is a checkpoint") # If the checkpoint still has extant jobs in its # (flattened) stack and services, its subtree didn't # complete properly. We handle the restart of the # checkpoint here, removing its previous subtree. if len([i for l in jobGraph.stack for i in l]) > 0 or len(jobGraph.services) > 0: logger.debug("Checkpoint has failed.") # Reduce the retry count assert jobGraph.remainingRetryCount >= 0 jobGraph.remainingRetryCount = max(0, jobGraph.remainingRetryCount - 1) jobGraph.restartCheckpoint(jobStore) # Otherwise, the job and successors are done, and we can cleanup stuff we couldn't clean # because of the job being a checkpoint else: logger.debug("The checkpoint jobs seems to have completed okay, removing any checkpoint files to delete.") #Delete any remnant files list(map(jobStore.deleteFile, list(filter(jobStore.fileExists, jobGraph.checkpointFilesToDelete)))) ########################################## #Setup the stats, if requested ########################################## if config.stats: startClock = getTotalCpuTime() startTime = time.time() while True: ########################################## #Run the jobGraph, if there is one ########################################## if jobGraph.command is not None: assert jobGraph.command.startswith("_toil ") logger.debug("Got a command to run: %s" % jobGraph.command) #Load the job job = Job._loadJob(jobGraph.command, jobStore) # If it is a checkpoint job, save the command if job.checkpoint: jobGraph.checkpoint = jobGraph.command # Create a fileStore object for the job fileStore = AbstractFileStore.createFileStore(jobStore, jobGraph, localWorkerTempDir, blockFn, caching=not config.disableCaching) with job._executor(jobGraph=jobGraph, stats=statsDict if config.stats else None, fileStore=fileStore): with deferredFunctionManager.open() as defer: with fileStore.open(job): # Get the next block function to wait on committing this job blockFn = fileStore.waitForCommit job._runner(jobGraph=jobGraph, jobStore=jobStore, fileStore=fileStore, defer=defer) # When the job succeeds, start committing files immediately. fileStore.startCommit(jobState=False) # Accumulate messages from this job & any subsequent chained jobs statsDict.workers.logsToMaster += fileStore.loggingMessages else: #The command may be none, in which case #the jobGraph is either a shell ready to be deleted or has #been scheduled after a failure to cleanup logger.debug("No user job to run, so finishing") break if AbstractFileStore._terminateEvent.isSet(): raise RuntimeError("The termination flag is set") ########################################## #Establish if we can run another jobGraph within the worker ########################################## successorJobGraph = nextChainableJobGraph(jobGraph, jobStore) if successorJobGraph is None or config.disableChaining: # Can't chain any more jobs. # TODO: why don't we commit the last job's file store? Won't # its async uploads never necessarily finish? # If we do call startCommit here it messes with the job # itself and Toil thinks the job needs to run again. break ########################################## #We have a single successor job that is not a checkpoint job. #We transplant the successor jobGraph command and stack #into the current jobGraph object so that it can be run #as if it were a command that were part of the current jobGraph. #We can then delete the successor jobGraph in the jobStore, as it is #wholly incorporated into the current jobGraph. ########################################## # add the successor to the list of jobs run listOfJobs.append(str(successorJobGraph)) #Clone the jobGraph and its stack jobGraph = copy.deepcopy(jobGraph) #Remove the successor jobGraph jobGraph.stack.pop() #Transplant the command and stack to the current jobGraph jobGraph.command = successorJobGraph.command jobGraph.stack += successorJobGraph.stack # include some attributes for better identification of chained jobs in # logging output jobGraph.unitName = successorJobGraph.unitName jobGraph.jobName = successorJobGraph.jobName assert jobGraph.memory >= successorJobGraph.memory assert jobGraph.cores >= successorJobGraph.cores #Build a fileStore to update the job fileStore = AbstractFileStore.createFileStore(jobStore, jobGraph, localWorkerTempDir, blockFn, caching=not config.disableCaching) #Update blockFn blockFn = fileStore.waitForCommit #Add successorJobGraph to those to be deleted fileStore.jobsToDelete.add(successorJobGraph.jobStoreID) #This will update the job once the previous job is done fileStore.startCommit(jobState=True) #Clone the jobGraph and its stack again, so that updates to it do #not interfere with this update jobGraph = copy.deepcopy(jobGraph) logger.debug("Starting the next job") ########################################## #Finish up the stats ########################################## if config.stats: totalCPUTime, totalMemoryUsage = getTotalCpuTimeAndMemoryUsage() statsDict.workers.time = str(time.time() - startTime) statsDict.workers.clock = str(totalCPUTime - startClock) statsDict.workers.memory = str(totalMemoryUsage) # log the worker log path here so that if the file is truncated the path can still be found if redirectOutputToLogFile: logger.info("Worker log can be found at %s. Set --cleanWorkDir to retain this log", localWorkerTempDir) logger.info("Finished running the chain of jobs on this node, we ran for a total of %f seconds", time.time() - startTime) ########################################## #Trapping where worker goes wrong ########################################## except: #Case that something goes wrong in worker traceback.print_exc() logger.error("Exiting the worker because of a failed job on host %s", socket.gethostname()) AbstractFileStore._terminateEvent.set() ########################################## #Wait for the asynchronous chain of writes/updates to finish ########################################## blockFn() ########################################## #All the asynchronous worker/update threads must be finished now, #so safe to test if they completed okay ########################################## if AbstractFileStore._terminateEvent.isSet(): jobGraph = jobStore.load(jobStoreID) jobGraph.setupJobAfterFailure(config) workerFailed = True if job and jobGraph.remainingRetryCount == 0: job._succeeded = False ########################################## #Cleanup ########################################## # Close the worker logging # Flush at the Python level sys.stdout.flush() sys.stderr.flush() if redirectOutputToLogFile: # Flush at the OS level os.fsync(1) os.fsync(2) # Close redirected stdout and replace with the original standard output. os.dup2(origStdOut, 1) # Close redirected stderr and replace with the original standard error. os.dup2(origStdErr, 2) # sys.stdout and sys.stderr don't need to be modified at all. We don't # need to call redirectLoggerStreamHandlers since they still log to # sys.stderr # Close our extra handles to the original standard output and standard # error streams, so we don't leak file handles. os.close(origStdOut) os.close(origStdErr) # Now our file handles are in exactly the state they were in before. # Copy back the log file to the global dir, if needed. # Note that we work with bytes instead of characters so we can seek # relative to the end (since Python won't decode Unicode backward, or even # interpret seek offsets in characters for us). TODO: We may get invalid or # just different Unicode by breaking up a character at the boundary! if workerFailed and redirectOutputToLogFile: jobGraph.logJobStoreFileID = jobStore.getEmptyFileStoreID(jobGraph.jobStoreID, cleanup=True) jobGraph.chainedJobs = listOfJobs with jobStore.updateFileStream(jobGraph.logJobStoreFileID) as w: with open(tempWorkerLogPath, 'rb') as f: if os.path.getsize(tempWorkerLogPath) > logFileByteReportLimit !=0: if logFileByteReportLimit > 0: f.seek(-logFileByteReportLimit, 2) # seek to last tooBig bytes of file elif logFileByteReportLimit < 0: f.seek(logFileByteReportLimit, 0) # seek to first tooBig bytes of file # Dump the possibly-invalid-Unicode bytes into the log file w.write(f.read()) # TODO load file using a buffer jobStore.update(jobGraph) elif ((debugging or (config.writeLogsFromAllJobs and not jobName.startswith(CWL_INTERNAL_JOBS))) and redirectOutputToLogFile): # write log messages with open(tempWorkerLogPath, 'rb') as logFile: if os.path.getsize(tempWorkerLogPath) > logFileByteReportLimit != 0: if logFileByteReportLimit > 0: logFile.seek(-logFileByteReportLimit, 2) # seek to last tooBig bytes of file elif logFileByteReportLimit < 0: logFile.seek(logFileByteReportLimit, 0) # seek to first tooBig bytes of file # Make sure lines are Unicode so they can be JSON serialized as part of the dict. # We may have damaged the Unicode text by cutting it at an arbitrary byte so we drop bad characters. logMessages = [line.decode('utf-8', 'skip') for line in logFile.read().splitlines()] statsDict.logs.names = listOfJobs statsDict.logs.messages = logMessages if (debugging or config.stats or statsDict.workers.logsToMaster) and not workerFailed: # We have stats/logging to report back if USING_PYTHON2: jobStore.writeStatsAndLogging(json.dumps(statsDict, ensure_ascii=True)) else: jobStore.writeStatsAndLogging(json.dumps(statsDict, ensure_ascii=True).encode()) #Remove the temp dir cleanUp = config.cleanWorkDir if cleanUp == 'always' or (cleanUp == 'onSuccess' and not workerFailed) or (cleanUp == 'onError' and workerFailed): shutil.rmtree(localWorkerTempDir) #This must happen after the log file is done with, else there is no place to put the log if (not workerFailed) and jobGraph.command == None and len(jobGraph.stack) == 0 and len(jobGraph.services) == 0: # We can now safely get rid of the jobGraph jobStore.delete(jobGraph.jobStoreID) def main(argv=None): if argv is None: argv = sys.argv # Do a little argument validation, in case someone tries to run us manually. if len(argv) < 4: if len(argv) < 1: sys.stderr.write("Error: Toil worker invoked without its own name\n") sys.exit(1) else: sys.stderr.write("Error: usage: %s JOB_NAME JOB_STORE_LOCATOR JOB_STORE_ID\n" % argv[0]) sys.exit(1) # Parse input args jobName = argv[1] jobStoreLocator = argv[2] jobStoreID = argv[3] ########################################## #Load the jobStore/config file ########################################## jobStore = Toil.resumeJobStore(jobStoreLocator) config = jobStore.config # Call the worker workerScript(jobStore, config, jobName, jobStoreID) toil-releases-3.24.0/version_template.py000066400000000000000000000124121362134276200203100ustar00rootroot00000000000000# Copyright (C) 2015-2018 Regents of the University of California # # 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 script is a template for src/toil/version.py. Running it without arguments echoes all globals, i.e. module attributes. Constant assignments will be echoed verbatim while callables will be invoked and their result echoed as an assignment using the function name as the left-hand side and the return value of the function as right-hand side. To prevent a module attribute from being echoed, start or end the attribute name with an underscore. To print the value of a single symbol, pass the name of that attribute to the script as a command line argument. You can also import the expand_ function and invoke it directly with either no or exactly one argument.""" # Note to maintainers: # # - don't import at module level unless you want the imported value to be # included in the output # - only import from the Python standard run-time library (you can't have any # dependencies) # - don't import even standard modules at global scope without renaming them # to have leading/trailing underscores baseVersion = '3.24.0' cgcloudVersion = '1.6.0a1.dev393' def version(): """ A version identifier that includes the full-legth commit SHA1 and an optional suffix to indicate that the working copy is dirty. """ return '-'.join(filter(None, [distVersion(), currentCommit(), ('dirty' if dirty() else None)])) def distVersion(): """The distribution version identifying a published release on PyPI.""" from pkg_resources import parse_version if isinstance(parse_version(baseVersion), tuple): raise RuntimeError("Setuptools version 8.0 or newer required. Update by running " "'pip install setuptools --upgrade'") return baseVersion def exactPython(): """ Returns the Python command for the exact version of Python we are installed for. Something like 'python2.7' or 'python3.6'. """ import sys return 'python{}.{}'.format(sys.version_info[0], sys.version_info[1]) def python(): """ Returns the Python command for the general version of Python we are installed for. Something like 'python2.7' or 'python3'. We assume all Python 3s are sufficiently intercompatible that we can just use 'python3' here for all of them. This is useful because the Toil Docker appliance is only built for particular Python versions, and we would like workflows to work with a variety of leader Python versions. """ return exactPython() def _pythonVersionSuffix(): """ Returns a short string identifying the running version of Python. Toil appliances running the same Toil version but on different versions of Python as returned by this function are not compatible. """ import sys # For now, we assume all Python 3 releases are intercompatible. # We also only tag the Python 2 releases specially, since Python 2 is old and busted. return '-py{}.{}'.format(sys.version_info[0], sys.version_info[1]) def dockerTag(): """The primary tag of the Docker image for the appliance. This uniquely identifies the appliance image.""" return version() + _pythonVersionSuffix() def currentCommit(): import os from subprocess import check_output try: git_root_dir = os.path.dirname(os.path.abspath(__file__)) output = check_output('git log --pretty=oneline -n 1 -- {}'.format(git_root_dir), shell=True, cwd=git_root_dir).decode('utf-8').split()[0] except: # Return this if we are not in a git environment. return '000' if isinstance(output, bytes): return output.decode('utf-8') return str(output) def dockerRegistry(): import os return os.getenv('TOIL_DOCKER_REGISTRY', 'quay.io/ucsc_cgl') def dockerName(): import os return os.getenv('TOIL_DOCKER_NAME', 'toil') def dirty(): import os from subprocess import call try: git_root_dir = os.path.dirname(os.path.abspath(__file__)) return 0 != call('(git diff --exit-code && git diff --cached --exit-code) > /dev/null', shell=True, cwd=git_root_dir) except: return False # In case the git call fails. def expand_(name=None): variables = {k: v for k, v in globals().items() if not k.startswith('_') and not k.endswith('_')} def resolve(k): v = variables[k] if callable(v): v = v() return v if name is None: return ''.join("%s = %s\n" % (k, repr(resolve(k))) for k, v in variables.items()) else: return resolve(name) def _main(): import sys sys.stdout.write(expand_(*sys.argv[1:])) if __name__ == '__main__': _main()