I’m curious what Julia/Linux users have found the best approach to dividing package responsibilities between their distro and Conda.
Conda is pretty great in some ways, but it can be painfully slow, and can be a little weird about downgrading packages with no explanation.
If I were just using Julia, I would probably have my distro (“Arch-like” Manjaro) do what it can, then Pkg, and (mini)conda for anything missing. In this case I’d see no reason to let Conda near Jupyter, for example. But I do need to use Python a lot for work, and Conda doesn’t seem too great about finding things that are already installed. And there are a few Julia packages that seem to need (or at least strongly encourage) using Conda.
I’d love to find a strategy for what-to-install-from-where that’s relatively simple, without excessive Conda bloat. What have you found to work well?