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I feel that all of these language specific solutions still only solve halve the problem. Your code depends on a lot more than _just_ the python libraries. And often this is exactly what makes projects break on different systems.

Let me make another suggestion: nixpkgs [0] it helps to define exactly that fixed set of dependencies. Not just on published version number, but on the actual source code _and_ all it's dependencies.

[0] - https://nixos.org/nixpkgs/




This. A lot of GPU deep learning libs depend on CUDA, cuDNN, which is not solved by pipenv / virtualenv, BUT is actually handled by conda.




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