That causes 50 copies of the exact same version of a 1GB library to exist on my system that are all obtained from the same authority (PyPI). I have literally 50 copies of the entire set of CUDA libraries because every conda environment installs PyTorch and PyTorch includes its own CUDA.
I'm not asking the OS to maintain this, but rather the package manager ("npm" or "pip" or similar) should do so on a system-wide basis. "python" and "pip" should allow for 1 copy per officially-released version of each package to live on the system, and multiple officially-released version numbers to coexist in /usr/lib. If a dev version is being used or any version that deviates from what is on PyPI, then that should live within the project.
I basically agree with this. With the caveat that programs should not use any system search paths and packages should be hardlinked into the project directory structure from a centralized cache. This also means that a dev version looks identical to a centralized version - both are just directories within the project.
Also, Windows is my primary dev environment. Any solution must work cross-platform and cross-distro. Telling everyone to use a specific distro is not a solution.
Nix fans are becoming as obnoxious as Rust fans. And I say that as an times annoying Rust fan.
Yes, it would be nice to have that by default.
In fact, it's what uv (https://github.com/astral-sh/uv) does, and one of the reasons it's so fast and became so popular so quickly.
Astral for the win.
> I have to create a new conda environment for almost every ML paper that comes out
That's how it's supposed to work: one env per project.
As for the rest, it's more telling about the C/C++ community building the things bellow the python wrappers.