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Typically one Jupyter install system wide, and then multiple kernels with each environment.

Personally, I really like the juv model where dependencies are taken from the first cell of the notebook and a new kernel is created to launch the interface, but I haven't seen others using it much yet:

https://github.com/manzt/juv

The idea is good, but juv is a one-jupyter-per-notebook model which isn't very practical for how my team uses jupyter. My attempt at "juv, but systemwide-jupyter-plus-one-kernel-per-notebook model" is this: https://github.com/tobinjones/uvkernel

Very nice, thanks for sharing!

I'm definitely guilty of This system-wide install but I've noticed people doing per-project installs more often now and I'm trying to get in the habit.

ipykernel (jupyter basically) is installed in the virtual environment itself, especially since sometimes different envs are different python versions.