In my experience, Anaconda (including Miniconda, Micromamba, IntelPython, et al.) is still the default choice in scientific computing and machine learning.

It's useful because it also packages a lot of other deps like CUDA drivers, DB drivers, git, openssl, etc. When you don't have admin rights, it's really handy to be able to install them and there's no other equivalent in the Python world. That being said, the fact conda (and derivatives) do not follow any of the PEPs about package management is driving me insane. The ergonomics are bad as well with defaults like auto activation of the base env and bad dependency solver for the longest time (fixed now), weird linking of shared libs, etc.

Anaconda was a good idea until it would break apt on Ubuntu and make my job that much harder. That became the reason _not_ to use Anaconda in my book.

venv made these problems start to disappear, and now uv and Nix have closed the loop for me.

How did it manage to do that?

Not saying it didn't, I've just never ran into that after a decade of using the thing on various Nixes

Why don't you use pixi, which has the best from these worlds?

I agree. Pixi solves all of that issues and is fully open source including the packages from conda-forge.

Too bad there is nowadays the confusion with anaconda (the distribution that requires a license) and the FOSS pieces of conda-forge. Explain that to your legacy IT or Procurement -.-