Binary wheels for Linux/macOS/Windows

Currently you only provide binary packages via conda. To support pip install wrf-python more generally I created a repository which builds those wheels using Travis CI/Appveyor: https://github.com/letmaik/wrf-python-wheels. It uses https://github.com/matthew-brett/multibuild and follows the concrete adaptation from https://github.com/MacPython/scipy-wheels which had similar requirements, e.g. building Fortran code using numpy distutils.

You can see the build logs for Linux and macOS here:
https://travis-ci.org/letmaik/wrf-python-wheels/builds/322376418
And for Windows including downloadable wheels (see artifacts tab in each job):
https://ci.appveyor.com/project/letmaik/wrf-python-wheels/build/1.0.5

Travis CI doesn't have free artifact storage, but if you guys like the general idea then maybe we can ask whether you can use the Rackspace container that scikit-learn uses as it says in the README of the multibuild repo:

# Contact Matthew Brett, or the
# scikit-learn team, for permission (and the API key) to upload to
# the Rackspace account used here, or use your own account.

The idea is that whenever you release a new version (or for dev builds), you would trigger a build in the wrf-python-wheels repository through a commit. This then builds and uploads wheels to some storage where you download the wheels, do some tests if you like, and then upload them to PyPI.

I'm happy to transfer the repo over to your GitHub org.

Start with the linked wrf-python-wheels repository and its Travis CI/Appveyor build logs, then read the multibuild and scipy-wheels adaptations. The work is complete when cross-platform wheels can be built, tested, stored, and uploaded to PyPI for releases or development builds.