# AppVeyor.com is a Continuous Integration service to build and run tests under
# Windows
# https://ci.appveyor.com/project/sklearn-ci/scikit-learn

environment:
  global:
    # SDK v7.0 MSVC Express 2008's SetEnv.cmd script will fail if the
    # /E:ON and /V:ON options are not enabled in the batch script interpreter
    # See: http://stackoverflow.com/a/13751649/163740
    CMD_IN_ENV: "cmd /E:ON /V:ON /C .\\build_tools\\appveyor\\run_with_env.cmd"
    WHEELHOUSE_UPLOADER_USERNAME: sklearn-appveyor
    WHEELHOUSE_UPLOADER_SECRET:
      secure: BQm8KfEj6v2Y+dQxb2syQvTFxDnHXvaNktkLcYSq7jfbTOO6eH9n09tfQzFUVcWZ

    # Make sure we don't download large datasets when running the test on
    # continuous integration platform
    SKLEARN_SKIP_NETWORK_TESTS: 1

  matrix:
    - PYTHON: "C:\\Python37-x64"
      PYTHON_VERSION: "3.7.0"
      PYTHON_ARCH: "64"

    - PYTHON: "C:\\Python27"
      PYTHON_VERSION: "2.7.8"
      PYTHON_ARCH: "32"


# Because we only have a single worker, we don't want to waste precious
# appveyor CI time and make other PRs wait for repeated failures in a failing
# PR. The following option cancels pending jobs in a given PR after the first
# job failure in that specific PR.
matrix:
    fast_finish: true


install:
  # If there is a newer build queued for the same PR, cancel this one.
  # The AppVeyor 'rollout builds' option is supposed to serve the same
  # purpose but is problematic because it tends to cancel builds pushed
  # directly to master instead of just PR builds.
  # credits: JuliaLang developers.
  - ps: if ($env:APPVEYOR_PULL_REQUEST_NUMBER -and $env:APPVEYOR_BUILD_NUMBER -ne ((Invoke-RestMethod `
        https://ci.appveyor.com/api/projects/$env:APPVEYOR_ACCOUNT_NAME/$env:APPVEYOR_PROJECT_SLUG/history?recordsNumber=500).builds | `
        Where-Object pullRequestId -eq $env:APPVEYOR_PULL_REQUEST_NUMBER)[0].buildNumber) { `
        throw "There are newer queued builds for this pull request, failing early." }

  # Install Python (from the official .msi of http://python.org) and pip when
  # not already installed.
  - "powershell ./build_tools/appveyor/install.ps1"
  - "SET PATH=%PYTHON%;%PYTHON%\\Scripts;%PATH%"
  - "python -m pip install -U pip"

  # Check that we have the expected version and architecture for Python
  - "python --version"
  - "python -c \"import struct; print(struct.calcsize('P') * 8)\""
  - "pip --version"

  # Install the build and runtime dependencies of the project.
  - "%CMD_IN_ENV% pip install --timeout=60 --trusted-host 28daf2247a33ed269873-7b1aad3fab3cc330e1fd9d109892382a.r6.cf2.rackcdn.com -r build_tools/appveyor/requirements.txt"
  - "%CMD_IN_ENV% python setup.py bdist_wheel bdist_wininst -b doc/logos/scikit-learn-logo.bmp"
  - ps: "ls dist"

  # Install the generated wheel package to test it
  - "pip install --pre --no-index --find-links dist/ scikit-learn"

# Not a .NET project, we build scikit-learn in the install step instead
build: false

test_script:
  # Change to a non-source folder to make sure we run the tests on the
  # installed library.
  - mkdir "../empty_folder"
  - cd "../empty_folder"
  - pytest --showlocals --durations=20 --pyargs sklearn
  # Move back to the project folder
  - cd "../scikit-learn"

artifacts:
  # Archive the generated wheel package in the ci.appveyor.com build report.
  - path: dist\*

on_success:
  # Upload the generated wheel package to Rackspace
  - "python -m wheelhouse_uploader upload --local-folder=dist sklearn-windows-wheels"

notifications:
  - provider: Webhook
    url: https://webhooks.gitter.im/e/0dc8e57cd38105aeb1b4
    on_build_success: false
    on_build_failure: True

cache:
  # Use the appveyor cache to avoid re-downloading large archives such
  # the MKL numpy and scipy wheels mirrored on a rackspace cloud
  # container, speed up the appveyor jobs and reduce bandwidth
  # usage on our rackspace account.
  - '%APPDATA%\pip\Cache'