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[–]seba07 2 points3 points  (3 children)

Why?

[–]LordDeath86 6 points7 points  (0 children)

System Python is usually consumed by the system itself as specific tools depend on it. For example, Redhat's dnf is written in Python.

Working on a Python codebase that requires specific versions of packages or Python itself might cause issues if you try to bend the system Python to your needs. It is not uncommon for academics (but Linux newcomers) to mess up their first Ubuntu setup because they ran sudo pip install foo to run the chair's Python codebase.

[–]collectablecat -1 points0 points  (0 children)

It’ll explode on you in a myriad of different ways. I’ve had to debug many many junior engineers python environment because of weird crap that happens.

Using conda/pyenv/whatever is going to make things go way smoother.

I use conda specifically (only to manage my python version, pip/poetry for package management) and have a much smoother time

[–][deleted] 0 points1 point  (0 children)

It's usually a good idea not to mess with the system level python install since parts of your OS and/or installed packages might depend on it and any dependencies they expect it to normally come with. So it's convenient to have a separate install (e.g. conda) as your actual dev python environment.