Just like any tool, the use case varies. If you are playing around locally, and or uploading to open source like github or pypi, then its fine to use. For pro

Just like any tool, the use case varies. If you are playing around locally, and or uploading to open source like github or pypi, then its fine to use. For production code that is critical, the entire "build" process needs to be pure local processing/copy - i.e nothing downloaded from the internet, anything that is compiled needs to be done with local tools that are already installed. I.e for python project deployments, the right way of doing this with containers for is to build a core image where you do run all the install commands that download stuff from the internet, and the actual production build dockerfile involves only copying files to the library locations, and the final run command. You don't need to "build" packages with anything (unless of course your package contains C dependencies, which is a whole nother can of worms). I think the desire for something like UV comes from the fact that people just don't think about what is going under the hood. Its somewhat understandable if you are a data scientist that just uses python for math, but for people in computer science/engineering, they really should be able to use python as is without any external tools.