serverless-python-requirements

> You'd need to pin all transitive dependencies as well and cache the venv. I think to do this stuff, you need hooks in Jupyter to setup and teardown the venv before it runs the kernel. (And generally Jupyter would want to clean up unused venvs to mitigate the teardown hook not firing.) > Only issue is that it'd be really space inefficient A venv is overkill. You can just run the kernel in a regular directory, and `pip install --target kernel_dir foo-bar-pkg` to put packages directly in it. As long as the linker sees it, third-party libraries will work. This technique is used in the serverless project[1] to bundle dependencies for use on AWS Lambda. > Not sure if you'd need to find older versions of new direct dependencies to avoid conflicts. Curation is a solution to this. Stackage[1] is popular in the Haskell community; they build a con

I'm using serverless-python-requirements (see the specific example https://github.com/UnitedIncome/serverless-python-requiremen...) - it uploads the libs zipped and unzips them on first invocation in the handler.

Personally, I do it with docker. I don't bother with venvs, because python is just not designed to be self-contained (or maybe it's a failed implementation of such design). As to lambda - using serverless and this https://github.com/UnitedIncome/serverless-python-requiremen... may help you.

Serverless Framework is also great for Python if you're not porting a WSGI application. Plug/Disclaimer: I'm the creator/maintainer of the defacto python dependency packaging plugin for serverless[0] [0] https://github.com/UnitedIncome/serverless-python-requiremen...