kylebarron opened a new issue, #977:
URL: https://github.com/apache/datafusion-python/issues/977

   **Is your feature request related to a problem or challenge? Please describe 
what you are trying to do.**
   
   Right now this project uses a strange mix of pip, pip-compile, and conda. 
This means dependencies have to be declared in several places, and pip-compile 
gives hard-coded environment files per Python version, which makes it hard to 
understand where those lockfiles came from and how to update them.
   
   I'd like to suggest that this project considers 
[uv](https://docs.astral.sh/uv/) for Python package management. I'd argue it's 
the modern standard for package management. It's fast and widely used.
   
   The only reason I can think of to use conda instead for developing would be 
if we needed GPU support in development. But aside from having a `cuda`-enabled 
environment.yml file, there's no mention of CUDA in the repo. This linked 
example seems to be missing from the repo:
   
https://github.com/apache/datafusion-python/blob/79c22d6d6c0809e7e93a0a23249baa516dbd8d6f/examples/README.md?plain=1#L54
   
   If we did need to stay in the Conda ecosystem, I'd highly recommend 
[pixi](https://github.com/prefix-dev/pixi), which manages native dependencies 
but provides a full platform-independent lockfile across multiple Python 
versions.
   
   **Describe the solution you'd like**
   
   Use uv.
   
   **Describe alternatives you've considered**
   
   Status quo.
   
   **Additional context**
   Add any other context or screenshots about the feature request here.
   


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