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43 points robertnishihara | 1 comments | 27 Jun 25 06:14 UTC | HN request time: 0.202s | source

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lz400 ◴[27 Jun 25 08:36 UTC] No.44394984[source]▶

Unfortunately uv is usually insufficient for certain ML deployments in Python. It's a real pain to install pytorch/CUDA with all the necessary drivers and C++ dependencies so people tend to fall back to conda.

Any modern tips / life hacks for this situation?

replies(4): >>44395089 #>>44395516 #>>44395563 #>>44395700 #

1. Kydlaw ◴[27 Jun 25 10:13 UTC] No.44395516[source]▶

>>44394984 #

You should give a try to https://pixi.sh/latest/ (I am not involve in the project).

They are a little more focus on scientific computing than uv, which is more general. They might be a better option in your case.

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Uv and Ray: Pain-Free Python Dependencies in Clusters