[fnordlord]

If you don't mind me chiming in, mostly looking for advice if you've got any. I tend to run into a lot of issues when trying to play with projects that use TensorFlow. I have an Apple Silicon laptop and I seem to always get stuck resolving circular, conflicting dependencies. The worst offender is https://github.com/magenta/magenta. It's such a cool project and I got it running once a few years ago but recently lost a few solid weekends trying to get it up and running again.

[haswell]

I will say that the most issues I’ve encountered with Python happened on macOS machines. The default installation was always old, and success using a modern version depended highly on the techniques used to install it.

For anything that involves dependencies, I rely on venv or pyenv to create a clean environment. When on macOS, I tended to use docker/containers as well, but primarily because 99% of my Python work has been in a Linux environment and I wanted like-for-like as much as possible. But a good version manager directly on macOS should help quite a bit.

[antod]

> I will say that the most issues I’ve encountered with Python happened on macOS machines.

Same here. It's probably somewhat to do with my only partial MacOS/Homebrew knowledge, but every time I'd ressurect a Python project on MacOS, Homebrew would end up screwing up / confusing / munging the system Python and it's own ones.

Never ran into problems like that on Linux (except for that one time I tried Linux homebrew). Just something about the way homebrew does stuff seems incompatible with me understanding it. Seems to be a "just me" thing though.

[philote]

I just want to add that using the tool "asdf" for managing python versions on your Mac is very handy. And "direnv" is also great for auto-loading your environment when going into a project directory.