# 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 intepreter # See: http://stackoverflow.com/a/13751649/163740 CMD_IN_ENV: "cmd /E:ON /V:ON /C .\\continuous_integration\\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:\\Python27" PYTHON_VERSION: "2.7.8" PYTHON_ARCH: "32" - PYTHON: "C:\\Python27-x64" PYTHON_VERSION: "2.7.8" PYTHON_ARCH: "64" - PYTHON: "C:\\Python35" PYTHON_VERSION: "3.5.0" PYTHON_ARCH: "32" - PYTHON: "C:\\Python35-x64" PYTHON_VERSION: "3.5.0" PYTHON_ARCH: "64" install: # Install Python (from the official .msi of http://python.org) and pip when # not already installed. - "powershell ./continuous_integration/appveyor/install.ps1" - "SET PATH=%PYTHON%;%PYTHON%\\Scripts;%PATH%" # Check that we have the expected version and architecture for Python - "python --version" - "python -c \"import struct; print(struct.calcsize('P') * 8)\"" # 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 continuous_integration/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 genreated 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" - "python -c \"import nose; nose.main()\" -s -v sklearn" # Move back to the project folder - "cd .." 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 --no-ssl-check --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'