I've been looking at doing something similar in our environment but there's so many options I haven't figured out what the best and most straightforward way might be.
I've been looking at doing something similar in our environment but there's so many options I haven't figured out what the best and most straightforward way might be.
Usage is as simple as
mkwheelhouse mybucket.mycorp.co scipy numpy
which will automatically build and upload those wheels for your current architecture and dump them into mybucket.mycorp.co. It builds a pip-compatible index, too, so you can just tell pip to search your wheelhouse first before falling back to PyPI: pip install --find-links mybucket.mycorp.co scipy numpy
If you need to build for several OSes, you can run mkwheelhouse against the same bucket from each OS.The downside of this approach is you can't host private packages, because you need to enable public website hosting. (Although, VPC endpoints might have changed this!) But the simplicity of this approach plus the massive speedup of not needing to constantly recompile scipy was totally worth it.
I'm using cheeseshop, but some people swear by warehouse, which is supposedly a legacy-free version for running pypi eventually.
If you don't care about the search api, you can also just enable an directory listing index page and use any web server. Pip will do the right thing when given the right incantation of magical arguments and you make a prayer to the pip gods.
You get the benefits and drawbacks of Google Cloud Platform.