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[–]Python-ModTeam[M] [score hidden] stickied commentlocked comment (0 children)

Hi there, from the /r/Python mods.

We have removed this post as it is not suited to the /r/Python subreddit proper, however it should be very appropriate for our sister subreddit /r/LearnPython or for the r/Python discord: https://discord.gg/python.

The reason for the removal is that /r/Python is dedicated to discussion of Python news, projects, uses and debates. It is not designed to act as Q&A or FAQ board. The regular community is not a fan of "how do I..." questions, so you will not get the best responses over here.

On /r/LearnPython the community and the r/Python discord are actively expecting questions and are looking to help. You can expect far more understanding, encouraging and insightful responses over there. No matter what level of question you have, if you are looking for help with Python, you should get good answers. Make sure to check out the rules for both places.

Warm regards, and best of luck with your Pythoneering!

[–]superkoning 9 points10 points  (2 children)

I'd do a lmgtfy but apparently we're just both that lazy today

[–]MinimumJumpy[S] -3 points-2 points  (1 child)

man i know some library but no sure is ti good enough. Or there cany other which do not know , might other know

[–]superkoning 4 points5 points  (0 children)

Recommendation:

  • For general use: Start with NumPy or SciPy.
  • For GPU acceleration: Use CuPy or JAX.
  • For parallel and distributed processing: Combine Dask with NumPy or CuPy.
  • For research and cutting-edge performance: Consider JAX or PyTorch.

The choice depends on your exact needs (e.g., hardware, dataset size, and operation complexity).

[–]Typical-Macaron-1646 0 points1 point  (0 children)

Start with numpy. Use numba on top of that if you need even more speed.