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It... depends. There is some great tooling for Python -- this was less true only a few years ago, mind you -- but the landscape is very much in flux, and usage of the modern stuff is not yet widespread. And a lot of the legacy stuff has a whole host of pitfalls.
Things are broadly progressing in the right direction, and I'd say I'm cautiously optimistic, although if you have to deal with anything related to conda then for the time being: good luck, and sorry.
Docker might be solution here.
But from my experience most python scripts are absolute junk. The barrier for entry is low so there's a massive disparity in quality.
I'm no Python expert either and yeah, from an outsider's perspective it seems needlessly confusing. easy_install that's never been easy, pip that should absolutely be put on a Performance Improvement Plan, and now this venv nonsense.
You can criticize javascript's ridiculous dependencies all you want (left-pad?), but one thing that they absolutely got right is how to manage them. Everything's in node_modules and that's it. Yeah, you might get eleven copies of left-pad on your system, but you know what you NEVER get? Version conflicts between projects you're working on.
Seriously. Those are EXACTLY the thoughts I had after I was forced to deal with Python after a ton of time writing projects in JS.
Tried to install Automatic1111 for Stable Diffusion in an Arch distrobox, and despite editing the .sh file to point to the older tarballed Python version as advised on Github, it still tells me it uses the most up to date one that's installed system wide and thus can't install pytorch. And that's pretty much where my personal knowledge ends, and apparently that of those (i.e. that one person) on Github. ¯\_(ツ)_/¯
Always funny when people urge you to ask for help but no one ends up actually helping.
Lol this is exactly why I made this post. I ended up using ComfyUI instead which has other, different python issues, but I got it working (kinda, no GPU but it's fine it works)
I definitely want gpu support. Although I struggle with that somewhat on Koboldcpp as well where I can't use ROCm, only Vulkan. Unsure where the difference is performance wise.
I'd like to try the other UIs too, but the problem is that Automatic1111 is where the majority of additional plugins can be found.
Yep, they are not portable, every app should come bundled with its own interpreter. As to why, I think historically it didn't target production grade application development.
I'm not sure this can be really fixed with Python 3, maybe we just have to hope for Python 4
