This is incredible to me (not your comment per se, but what you're referencing). I really don't understand how brittle and fragile Python is with all its dependencies. It's crazy to me that a simple bump from 3.10 to 3.11 can break Pytorch. This is like bumping your Ruby version up one level and suddenly Rails doesn't work.
Why on earth is Python like this? It's so frustrating coming from other languages where the dependency management plan isn't just so YOLO and free-for-all.
I have despised Python ever since the 2=>3 transition for the reasons you say. Tools like pyenv help, but it's still a mess. It makes me sad that all the popular ML tooling ends up built in Python.
I wonder how much the space has been encumbered by Python’s relative weaknesses. As a bit of an outsider, I kind of assume there’s some hidden advantage of Python for AI/ML that I just don’t “get.”
Why on earth is Python like this? It's so frustrating coming from other languages where the dependency management plan isn't just so YOLO and free-for-all.