Appveyor first attempt

Author: Guillaume Lemaitre

appveyor.yml

@@ -0,0 +1,51 @@
+environment:
+  # There is no need to run the build for all the Python version /
+  # architectures combo as the generated nilearn wheel is the same on all
+  # platforms (universal wheel).
+  # We run the tests on 2 different target platforms for testing purpose only.
+  # We use miniconda versions of Python provided by appveyor windows images
+  matrix:
+    - PYTHON: "C:\\Miniconda-x64"
+      PYTHON_VERSION: "2.7.x"
+      PYTHON_ARCH: "64"
+
+    - PYTHON: "C:\\Miniconda3-x64"
+      PYTHON_VERSION: "3.5.x"
+      PYTHON_ARCH: "64"
+
+install:
+  # Prepend miniconda installed Python to the PATH of this build
+  # Add Library/bin directory to fix issue
+  # https://github.com/conda/conda/issues/1753
+  - "SET PATH=%PYTHON%;%PYTHON%\\Scripts;%PYTHON%\\Library\\bin;%PATH%"
+
+  # Check that we have the expected version and architecture for Python
+  - "python --version"
+  - "python -c \"import struct; print(struct.calcsize('P') * 8)\""
+
+  # Installed prebuilt dependencies from conda
+  - "conda install pip numpy scipy scikit-learn nose wheel matplotlib -y -q"
+
+  # Install other nilearn dependencies
+  - "pip install coverage nose-timer"
+  - "python setup.py bdist_wheel"
+  - ps: "ls dist"
+
+  # Install the generated wheel package to test it
+  - "pip install --pre --no-index --find-links dist/ imbalanced-learn"
+
+# Not a .NET project, we build 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.
+  - "cd C:\\"
+  - "python -c \"import nose; nose.main()\" -v -s imbalanced-learn --with-timer --timer-top-n 50"
+
+artifacts:
+  # Archive the generated packages in the ci.appveyor.com build report.
+  - path: dist\*
+
+#on_success:
+#  - TODO: upload the content of dist/*.whl to a public wheelhouse