azure-pipelines.yml

# Python package
# Create and test a Python package on multiple Python versions.
# Add steps that analyze code, save the dist with the build record, publish to a PyPI-compatible index, and more:
# https://docs.microsoft.com/en-us/azure/devops/pipelines/languages/python?view=vsts

# Capabilities and limitations:
# https://docs.microsoft.com/en-us/azure/devops/pipelines/agents/hosted?view=vsts&tabs=yaml#capabilities-and-limitations
# - Provide at least 10 GB of storage for your source and build outputs.
# - Can run jobs for up to 360 minutes (6 hours).

# Notes on pipeline definitions:
#
# the number after @ in task definition indicates the azure internal version of the specific task, e.g:
# - task: CondaEnvironment@1
# means use azure's CondaEnvironment's version 1, so need to check the docs for each specific task's desired (usually latest) version. If later 1.2 is released then use:
# - task: CondaEnvironment@1.2
# instead
#
# job name must match r'\w+' (no '-', but '_' ok)
#
# Build environments: Available vmImage values: 'Ubuntu-16.04', 'macOS-10.13', 'VS2017-Win2016'
#

jobs:

################
### Linux CI ###
################


- job: 'Linux_PyPI'

  pool:
    vmImage: 'Ubuntu-16.04'

  # Run the pipeline with multiple Python versions
  strategy:
    matrix:
      Python36:
        python.version: '3.6'
      Python37:
        python.version: '3.7'
    # Increase the maxParallel value to simultaneously run the job for all versions in the matrix (max 10 for free open-source)
    maxParallel: 4

  steps:
    # Set the UsePythonVersion task to reference the matrix variable for its Python version
  - task: UsePythonVersion@0
    inputs:
      versionSpec: '$(python.version)'
      architecture: 'x64'

    # Install dependencies and fastai git HEAD or PR
  - script: |
      python -m pip install --upgrade pip && pip3 install --upgrade setuptools
      pip install torch_nightly -f https://download.pytorch.org/whl/nightly/cpu/torch_nightly.html
      # test that we can install fastai package (and torchvision)
      pip install fastai
      pip uninstall -y fastai
      # install editable fastai, which tests the HEAD or PR
      pip install -e .[dev]
    displayName: 'Upgrade pip/setuptools. Install deps, pytorch and fastai'
    continueOnError: false

    # Install Test deps
  - script: |
      pip install pytest pytest-runner
    displayName: 'Install test deps'
    continueOnError: false

    # Run Tests
  - script: |
      py.test tests --cache-clear --junitxml=result.xml
    displayName: 'Run tests'
    continueOnError: false

    # Publish test results to the Azure DevOps server
  - task: PublishTestResults@2
    inputs:
      testResultsFiles: 'result.xml'
      testRunTitle: 'Python $(python.version)'
      condition: succeededOrFailed()

    # Jupyter Test
  - script: |
      # 1. test that we can run jupyter (have all the deps figured out)
      # 2. that we can execute a fastai nb
      jupyter nbconvert --execute --ExecutePreprocessor.timeout=600 --to notebook examples/tabular.ipynb
      # 3. check for expected in the output string and bail if it's not there.
      echo "Testing expected output"
      grep "Total time" examples/tabular.nbconvert.ipynb
      # 4. test that python kernel is available
      echo "Testing jupyter kernelspec list"
      jupyter kernelspec list | grep python3
    displayName: 'Run jupyter notebook tests'
    continueOnError: false



- job: 'Linux_Conda'

  pool:
    vmImage: 'Ubuntu-16.04'

  # Run the pipeline with multiple Python versions
  strategy:
    matrix:
      Python36:
        python.version: '3.6'
      Python37:
        python.version: '3.7'
    # Increase the maxParallel value to simultaneously run the job for all versions in the matrix (max 10 for free open-source)
    maxParallel: 4

  steps:
    # Set the UsePythonVersion task to reference the matrix variable for its Python version
  - task: UsePythonVersion@0
    inputs:
      versionSpec: '$(python.version)'
      architecture: 'x64'

    # XXX: should be fixed in 1.140 release https://github.com/Microsoft/vsts-tasks/issues/8299#issuecomment-427095427
  - script: sudo install -d -m 0777 /usr/envs
    displayName: Fix Conda permissions

    # Conda setup environment.
    # https://docs.microsoft.com/en-us/azure/devops/pipelines/tasks/package/conda-environment?view=vsts
    #
  - task: CondaEnvironment@0
    inputs:
      environmentName: 'fastai-cpu'
      packageSpecs: 'python=$(python.version)'

    # Install dependencies and fastai git HEAD or PR
  - script: |
      conda activate fastai-cpu
      conda install -y conda
      conda install -y pip setuptools
      # pytorch + torchvision
      conda install -y -c pytorch pytorch-nightly-cpu
      conda install -y -c fastai torchvision-nightly-cpu
      # test that we can install fastai package
      conda install -y -c fastai fastai
      conda uninstall -y fastai
      # install editable fastai, which tests the HEAD or PR
      pip install -e .[dev]
    displayName: 'Upgrade pip/conda/setuptools. Install deps, pytorch and fastai'
    continueOnError: false

    # Install Test deps
  - script: |
      conda install -y pytest pytest-runner
    displayName: 'Install test deps'
    continueOnError: false

    # Run Tests
  - script: |
      py.test tests --cache-clear --junitxml=result.xml
    displayName: 'Run tests'
    continueOnError: false

    # Publish test results to the Azure DevOps server
  - task: PublishTestResults@2
    inputs:
      testResultsFiles: 'result.xml'
      testRunTitle: 'Python $(python.version)'
      condition: succeededOrFailed()

    # Jupyter Test
  - script: |
      # 1. test that we can run jupyter (have all the deps figured out)
      # 2. that we can execute a fastai nb
      jupyter nbconvert --execute --ExecutePreprocessor.timeout=600 --to notebook examples/tabular.ipynb
      # 3. check for expected in the output string and bail if it's not there.
      echo "Testing expected output"
      grep "Total time" examples/tabular.nbconvert.ipynb
      # 4. test that python kernel is available
      echo "Testing jupyter kernelspec list"
      jupyter kernelspec list | grep python3
    displayName: 'Run jupyter notebook tests'
    continueOnError: false



################
### MacOS CI ###
################

- job: MacOS_PyPI
  pool:
    vmImage: 'macOS-10.13'

  # Run the pipeline with multiple Python versions
  strategy:
    matrix:
      Python36:
        python.version: '3.6'
      Python37:
        python.version: '3.7'
    maxParallel: 4

  steps:
  - task: UsePythonVersion@0
    inputs:
      versionSpec: '$(python.version)'
      architecture: 'x64'

    # Install dependencies and fastai git HEAD or PR
  - script: |
      python -m pip install --upgrade pip && pip3 install --upgrade setuptools
      pip install torch_nightly -f https://download.pytorch.org/whl/nightly/cpu/torch_nightly.html
      # test that we can install fastai package (and torchvision)
      pip install fastai
      pip uninstall -y fastai
      # install editable fastai, which tests the HEAD or PR
      pip install -e .[dev]
      # workaround for matplotlib bug on macOS: https://stackoverflow.com/questions/21784641/installation-issue-with-matplotlib-python
      mkdir -p ~/.matplotlib
      echo "backend: TkAgg" >> ~/.matplotlib/matplotlibrc
    displayName: 'Upgrade pip and setuptools, install pytorch and fastai deps'
    continueOnError: false

     # Install Test deps
  - script: |
      pip install pytest pytest-runner
    displayName: 'Install test deps'
    continueOnError: false

    # Run Tests
  - script: |
      py.test tests --cache-clear --junitxml=result.xml
    displayName: 'Run tests'
    continueOnError: false

    # Publish test results to the Azure DevOps server
  - task: PublishTestResults@2
    inputs:
      testResultsFiles: 'result.xml'
      testRunTitle: 'Python $(python.version)'
      condition: succeededOrFailed()

    # Jupyter Test
  - script: |
      # 1. test that we can run jupyter (have all the deps figured out)
      # 2. that we can execute a fastai nb
      jupyter nbconvert --execute --ExecutePreprocessor.timeout=600 --to notebook examples/tabular.ipynb
      # 3. check for expected in the output string and bail if it's not there.
      echo "Testing expected output"
      grep "Total time" examples/tabular.nbconvert.ipynb
      # 4. test that python kernel is available
      echo "Testing jupyter kernelspec list"
      jupyter kernelspec list | grep python3
    displayName: 'Run jupyter notebook tests'
    continueOnError: false



- job: 'MacOS_Conda'

  pool:
    vmImage: 'macOS-10.13'

  # Run the pipeline with multiple Python versions
  strategy:
    matrix:
      Python36:
        python.version: '3.6'
      Python37:
        python.version: '3.7'
    # Increase the maxParallel value to simultaneously run the job for all versions in the matrix (max 10 for free open-source)
    maxParallel: 4

  steps:
    # Set the UsePythonVersion task to reference the matrix variable for its Python version
  - task: UsePythonVersion@0
    inputs:
      versionSpec: '$(python.version)'
      architecture: 'x64'

  - script: sudo install -d -m 0777 /usr/local/miniconda/envs/
    displayName: Fix Conda permissions

    # Conda setup environment.
    # https://docs.microsoft.com/en-us/azure/devops/pipelines/tasks/package/conda-environment?view=vsts
    #
  - task: CondaEnvironment@0
    inputs:
      environmentName: 'fastai-cpu'
      packageSpecs: 'python=$(python.version)'

    # Install dependencies and fastai git HEAD or PR
  - script: |
      conda activate fastai-cpu
      conda install -y conda
      conda install -y pip setuptools
      # pytorch + torchvision
      conda install -y -c pytorch pytorch-nightly-cpu
      conda install -y -c fastai torchvision-nightly-cpu
      # test that we can install fastai package
      conda install -y -c fastai fastai
      conda uninstall -y fastai
      # install editable fastai, which tests the HEAD or PR
      pip install -e .[dev]
      # workaround for matplotlib bug on macOS: https://stackoverflow.com/questions/21784641/installation-issue-with-matplotlib-python
      mkdir -p ~/.matplotlib
      echo "backend: TkAgg" >> ~/.matplotlib/matplotlibrc
    displayName: 'Upgrade pip/conda/setuptools. Install deps, pytorch and fastai'
    continueOnError: false

    # Install Test deps
  - script: |
      conda install -y pytest pytest-runner
    displayName: 'Install test deps'
    continueOnError: false

    # Run Tests
  - script: |
      py.test tests --cache-clear --junitxml=result.xml
    displayName: 'Run tests'
    continueOnError: false

    # Publish test results to the Azure DevOps server
  - task: PublishTestResults@2
    inputs:
      testResultsFiles: 'result.xml'
      testRunTitle: 'Python $(python.version)'
      condition: succeededOrFailed()

    # Jupyter Test
  - script: |
      # 1. test that we can run jupyter (have all the deps figured out)
      # 2. that we can execute a fastai nb
      jupyter nbconvert --execute --ExecutePreprocessor.timeout=600 --to notebook examples/tabular.ipynb
      # 3. check for expected in the output string and bail if it's not there.
      echo "Testing expected output"
      grep "Total time" examples/tabular.nbconvert.ipynb
      # 4. test that python kernel is available
      echo "Testing jupyter kernelspec list"
      jupyter kernelspec list | grep python3
    displayName: 'Run jupyter notebook tests'
    continueOnError: false




##################
### nbstripout ###
##################


- job: 'nbstripout_config'

  pool:
    vmImage: 'Ubuntu-16.04'

  steps:
  - task: UsePythonVersion@0
    inputs:
      versionSpec: '3.6'
      architecture: 'x64'

    # check that notebooks are stripped out. if they aren't that means the committer doesn't have the correct configuration for the stripout filter.
  - script: |
      echo "Check we are starting with clean git checkout"
      if [ -n "$(git status -uno -s)" ]; then echo "git status is not clean"; false; fi

      echo "Trying to strip out notebooks"
      tools/fastai-nbstripout -d examples/*ipynb

      echo "Check that strip out was unnecessary"
      git status -s # display the status to see which nbs need cleaning up
      if [ -n "$(git status -uno -s)" ]; then echo -e "!!! Detected unstripped out notebooks\n!!!Remember to run tools/run-after-git-clone"; false; fi
    displayName: 'Detect unstripped out notebook commits'
    continueOnError: false