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Using uv with PyTorch

(docs.astral.sh)
167 points charliermarsh | 2 comments | 19 Nov 24 21:59 UTC | HN request time: 0.001s | source
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alex_suzuki ◴[20 Nov 24 10:11 UTC] No.42192428[source]▶
In a nutshell, what do I gain from switching to uv from my current workflow, which is: 1) create a venv (`python3.xx -m venv venv`) 2) install packages from a requirements.txt into that venv?

One limitation I know of are the inability to detect stale packages.

Apart from „blazing fast“, which I‘m not convinced it really matters to me as I rarely touch the dependencies, what are the main reasons why uv is gaining traction?

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alex_suzuki ◴[20 Nov 24 10:13 UTC] No.42192436[source]▶
PS: one thing I like about my current workflow is no extra tools needed, base python install is all that‘s required.
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1. JimDabell ◴[20 Nov 24 12:26 UTC] No.42193311[source]▶
It’s similar with uv. You have exactly one dependency on the host system – it’s just uv instead of Python. uv will then obtain the correct version of Python for your project. And uv is easier to install than Python – it’s literally just one binary.
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2. alex_suzuki ◴[20 Nov 24 18:01 UTC] No.42196535[source]▶
Interesting, thanks for pointing that out. Will give it a try.