My team has struggled a lot with how to do python deployment. We know we can isolate the interpreter and modules via venv/docker/etc. and get repeatable and re

My team has struggled a lot with how to do python deployment. We know we can isolate the interpreter and modules via venv/docker/etc. and get repeatable and reliable deployments. However, because we're a utility module, we like to allow users to import our code freely, and that's a lot harder when that code is isolated and bundled with very specific requirements. Seems like the only perfect solution is to just support every conceivable version of python and our required modules. Which is of course very hard. It would probably require greatly reducing our usage of tensorflow and some other packages which change a lot and are trickier to use on Windows. Good old dependency hell.