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Not a datascientist myself but I see a huge potential in PyO3, so you keep the python tooling and whenever you need to optimize you can write your own native library. The build process is really smooth and it integrates nicely, you have access to python types, you can do heavywork without blocking the GIL but you can take the GIL if needed ( such as having to mutate a python variable ). That also means companies don't have to drop everything they have, they can experiment with hybrid teams.
NOTE:
The number of mentions on this list indicates mentions on common posts plus user suggested alternatives.
Hence, a higher number means a more popular project.