# 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'