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appveyor.yml
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appveyor.yml
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# 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 .\\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%"
- "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 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 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"
- "python -c \"import nose; nose.main()\" --with-timer --timer-top-n 20 -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'