azure-pipelines.yml

# Azure Pipelines configuration file for Continuous Integration
# for building the package and running the tests under Windows.
variables:
  PIP_CACHE_DIR: $(Pipeline.Workspace)/.pip
  # data cache dir determined via: print(pooch.os_cache('scikit-image'))
  SKIMAGE_DATA_CACHE_FOLDER: C:\Users\VssAdministrator\AppData\Local\scikit-image\scikit-image\Cache

jobs:
- job: 'Default'
  pool:
    vmImage: 'vs2017-win2016'
  strategy:
    maxParallel: 10
    matrix:
      Python37:
        PYTHON_VERSION: '3.7'
        ARCH: 'x86'
        PIP_FLAGS: ''
      Python37-x64:
        PYTHON_VERSION: '3.7'
        ARCH: 'x64'
        PIP_FLAGS: ''
        TEST_EXAMPLES: 'true'
      Python38:
        PYTHON_VERSION: '3.8'
        ARCH: 'x86'
        PIP_FLAGS: ''
      Python38-x64:
        PYTHON_VERSION: '3.8'
        ARCH: 'x64'
        PIP_FLAGS: ''
        BUILD_DOCS: 'true'
      # build pre release packages on Python 3.8 since it has been out long
      # enough for wheels to be built for packages that need to be compiled.
      Python38-x64-pre:
        PYTHON_VERSION: '3.8'
        ARCH: 'x64'
        PIP_FLAGS: '--pre'
      Python39:
        PYTHON_VERSION: '3.9'
        ARCH: 'x86'
        PIP_FLAGS: ''
      Python39-x64:
        PYTHON_VERSION: '3.9'
        ARCH: 'x64'
        PIP_FLAGS: ''
        # NOTE(honles): winpty is required by one of the doc dependencies,
        #               but does not provide a wheel for Python 3.9
        # TEST_EXAMPLES: 'true'
  continueOnError: false
  timeoutInMinutes: 60

  steps:
  - task: UsePythonVersion@0
    inputs:
      versionSpec: '$(PYTHON_VERSION)'
      architecture: '$(ARCH)'
    name: python

  # https://docs.microsoft.com/en-us/azure/devops/pipelines/release/caching?view=azure-devops
  - task: Cache@2
    inputs:
      key: '"skimage_data" | skimage/data/_registry.py'
      path: $(SKIMAGE_DATA_CACHE_FOLDER)
    displayName: Cache scikit-image data files

  # https://docs.microsoft.com/en-us/azure/devops/pipelines/release/caching?view=azure-devops#pythonpip
  - task: Cache@2
    inputs:
      key: '"Python$(PYTHON_VERSION)-$(ARCH)" | "$(Agent.OS)" | requirements/build.txt | requirements/default.txt | requirements/test.txt | requirements/docs.txt'
      restoreKeys: |
        "Python$(PYTHON_VERSION)-$(ARCH)" | "$(Agent.OS)"
        "Python$(PYTHON_VERSION)-$(ARCH)"
      path: $(PIP_CACHE_DIR)
    displayName: Cache pip packages

  - bash: |
      set -ex
      PYTHON="$(python.pythonLocation)\\python.exe"

      # Update pip
      $PYTHON -m pip install -U pip setuptools wheel

      # print out the pip cache dir followed by the variable defined above
      # to confirm that they match
      $PYTHON -m pip cache dir
      echo "PIP_CACHE_DIR: $PIP_CACHE_DIR"

      # Check that we have the expected version and architecture for Python
      $PYTHON --version
      $PYTHON -m pip --version
      $PYTHON -c "import struct; print('Void pointer width is', struct.calcsize('P') * 8)"
      $PYTHON -m pip list

      # Install the build and runtime dependencies of the project
      $PYTHON -m pip install ${PIP_FLAGS} -r requirements/build.txt

      # Disable C99 complex if PyWavelets needs to be built from source.
      # The compiler used will be MSVC, but C99 may be detected improperly
      USE_C99_COMPLEX=0 $PYTHON -m pip install ${PIP_FLAGS} -r requirements/default.txt

      $PYTHON -m pip list
    displayName: 'Pre-installation'

  - bash: |
      set -ex
      PYTHON="$(python.pythonLocation)\\python.exe"

      # Compile the package and build the wheel
      $PYTHON setup.py bdist_wheel

      # Install the generated wheel package
      ls dist
      $PYTHON -m pip install ${PIP_FLAGS} --no-index --find-links dist/ scikit-image
    displayName: 'Installation'

  - bash: |
      set -ex
      PYTHON="$(python.pythonLocation)\\python.exe"

      # Install the test dependencies
      $PYTHON -m pip install ${PIP_FLAGS} -r requirements/test.txt
      $PYTHON -m pip list

      # Set non-UI Matplotlib backend
      cd ${AGENT_BUILDDIRECTORY}  # D:\a\1
      echo "backend : Agg" > matplotlibrc
    displayName: 'Pre-testing'

  - bash: |
      set -ex
      PYTHON="$(python.pythonLocation)\\python.exe"

      # Change the working directory in order to run the tests
      # on the installed version of skimage
      cd ${AGENT_BUILDDIRECTORY}  # D:\a\1

      # Show the info about the installed scikit-image
      $PYTHON -c "import skimage; print(skimage.__path__)"

      # Show the path pooch is using for the data cache
      # (this should match the SKIMAGE_DATA_CACHE_FOLDER variable above)
      $PYTHON -c "import pooch; print(pooch.os_cache('scikit-image'))"
      echo "SKIMAGE_DATA_CACHE_FOLDER: $SKIMAGE_DATA_CACHE_FOLDER"

      # Force matplotlib to use the prepared config
      export MATPLOTLIBRC=${AGENT_BUILDDIRECTORY}

      # Run unit tests with pytest
      # We don't test docstring examples (--doctest-modules) on
      # Windows due to inconsistent ndarray formatting in `numpy`.
      # For more details, see https://github.com/numpy/numpy/issues/13468
      export TEST_ARGS="-v --cov=skimage"
      $PYTHON -m pytest ${TEST_ARGS} --pyargs skimage
    displayName: 'Package testing'

  - bash: |
      set -ex
      PYTHON="$(python.pythonLocation)\\python.exe"
      $PYTHON -m asv check -v -E existing
    displayName: Check benchmarks

  - bash: |
      set -ex
      export PYTHON="$(python.pythonLocation)\\python.exe"

      # Install the doc dependencies
      $PYTHON -m pip install ${PIP_FLAGS} -r requirements/docs.txt
      $PYTHON -m pip list

      # Build the documentation
      choco install optipng
      export SPHINXCACHE=${AGENT_BUILDDIRECTORY}/.cache/sphinx
      export SPHINXOPTS=-W
      make -C doc html
    condition: eq(variables['BUILD_DOCS'], 'true')
    displayName: 'Documentation testing'

  - bash: |
      set -ex
      PYTHON="$(python.pythonLocation)\\python.exe"

      # Install the doc dependencies
      $PYTHON -m pip install ${PIP_FLAGS} -r requirements/docs.txt
      $PYTHON -m pip list

      # Force matplotlib to use the prepared config
      export MATPLOTLIBRC=${AGENT_BUILDDIRECTORY}

      # Run example applications
      for f in doc/examples/*/*.py; do
        # Comment out any plotly.io.show() calls before running the example.
        # Plotly opens a web browser, which often seemed to cause the CI to
        # hang and timeout.
        sed -i 's/plotly.io.show/# plotly.io.show/g' ${f}

        $PYTHON -W ignore:Matplotlib:UserWarning "${f}"
        if [ $? -ne 0 ]; then
          exit 1
        fi
      done
    condition: eq(variables['TEST_EXAMPLES'], 'true')
    displayName: 'Gallery testing'

#  - bash: |
#      # -- Publish the .whl artifacts
#      # -- Upload the content of dist/*.whl to a public wheelhouse
#    displayName: 'Further consideration'