appveyor.yml

# AppVeyor.com is a Continuous Integration service to build and run tests under
# Windows


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 .\\ci_scripts\\appveyor\\run_with_env.cmd"
    WHEELHOUSE_UPLOADER_USERNAME: sklearn
    WHEELHOUSE_UPLOADER_SECRET:
      secure: XzK+Mi6Ba5frV2B/jHq7h4aD8/nox9SsI3T8Kub1L2XNevRSIurUEry3PdWESzRY
    MODULE: skltemplate
    PROJECT_NAME: sklearn-template
    CLOUD_STORAGE: CLOUDFILES
    CLOUD_CONTATINER: sklearn-template-trial

  matrix:
    - PYTHON: "C:\\Python27"
      PYTHON_VERSION: "2.7.8"
      PYTHON_ARCH: "32"
      MINICONDA: "C:\\Miniconda"

    - PYTHON: "C:\\Python27-x64"
      PYTHON_VERSION: "2.7.8"
      PYTHON_ARCH: "64"
      MINICONDA: "C:\\Miniconda-x64"

    - PYTHON: "C:\\Python35"
      PYTHON_VERSION: "3.5.0"
      PYTHON_ARCH: "32"
      MINICONDA: "C:\\Miniconda35"

    - PYTHON: "C:\\Python35-x64"
      PYTHON_VERSION: "3.5.0"
      PYTHON_ARCH: "64"
      MINICONDA: "C:\\Miniconda35-x64"

install:
  # Miniconda is pre-installed in the worker build
  - "SET PATH=%MINICONDA%;%MINICONDA%\\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"

  # Remove cygwin because it clashes with conda
  # see http://help.appveyor.com/discussions/problems/3712-git-remote-https-seems-to-be-broken
  - rmdir C:\\cygwin /s /q

  # Install the build and runtime dependencies of the project.
  - conda install --quiet --yes numpy scipy cython nose scikit-learn wheel
  - pip install wheelhouse_uploader nose-timer
  - "%CMD_IN_ENV% python setup.py bdist_wheel bdist_wininst"
  - ps: "ls dist"

  # Install the generated wheel package to test it
  - "pip install --pre --no-index --find-links dist %PROJECT_NAME%"


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


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


on_success:
  # Upload the generated wheel package to Rackspace
  # On Windows, Apache Libcloud cannot find a standard CA cert bundle so we
  # disable the ssl checks.
  - "python -m wheelhouse_uploader upload provider=%CLOUD_STORAGE% --no-ssl-check --local-folder=dist %CLOUD_CONTAINER%"


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"

  - "python -c \"import nose; nose.main()\" --with-timer --timer-top-n 20 -s -v %MODULE%"

  # Move back to the project folder
  - "cd .."


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'