Yeah, I don't think that's an Arch Linux problem. I had similar problems on Windows, and one version of the project even was supposedly setup to run in Docker. What is the point of setting up Docker if the whole setup and build process is not turnkey?
Seems like all of these projects are broken until you speak shibboleth by guessing at random python incantations. By this point, it's starting to feel intentional, like a way to mark you as part of an in-crowd, not a "L-User".
Unfortunately, I don't remember what I did. I did eventually get SD to work (though not in Docker, just as a normal python project). If I had been sober at the time, I probably would have given up. I know you need no greater than Python 3.9.
Yeah, I don't really get why Python developers tolerate this state of being where minor point releases are so commonly incompatible with each other, or having no standard way to manage building against different versions. I also don't get why ML developers continue with Python, considering these issues.
But, that's the point of the Miniconda dependency. By using Conda, the project can be setup locally with the Python version it expects without clobbering your local, system-level install.
It was still a bit of a pain to learn how to use Conda, but it worked out a little better than figuring it out on my own.
Seems like all of these projects are broken until you speak shibboleth by guessing at random python incantations. By this point, it's starting to feel intentional, like a way to mark you as part of an in-crowd, not a "L-User".
Unfortunately, I don't remember what I did. I did eventually get SD to work (though not in Docker, just as a normal python project). If I had been sober at the time, I probably would have given up. I know you need no greater than Python 3.9.