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Setting up a python environment for ML work (pytorch + Nvidia) is simpler with Anaconda, it's a pure dependency nightmare doing it with something else.
by myth_drannon 1y ago
Setting up a python environment for ML work (pytorch + Nvidia) is simpler with Anaconda, it's a pure dependency nightmare doing it with something else.
- specproc 1y agoYeah, I remember finding that the case for a while. I can't remember when things clicked and it was fine without. I moved to arch a while back, perhaps then.
- SJC_Hacker 1y agoDocker
- Balinares 1y agoCounterpoint: conda is a constant, neverending source of pure dependency nightmares here, that consistently costs us a two-digit percentage of velocity. I'm glad it's working for you, but I really wouldn't generalize. Or recommend it to anyone getting into Python. Use uv, new people, for real.
- disgruntledphd2 1y agoTo be fair, both you and GP are correct. Conda is really really painful to maintain, and it's also much much better for python stuff that relies on native libraries (i.e. C/Fortran/Cuda). Like, I love uv but GDAL (to use a random recent example) is much easier to install and maintain with conda.