[plipt]

I haven’t used Jupyter in a few years. Wondering what is the current standard practice of starting a new Jupyter project.

Do users typically have one system-wide Jupyter install that gets reused for each data analysis project that then have their own dependencies in a virtual environment that Jupyter activates?

Or is Jupyter installed inside each project’s virtual environment?

[epistasis]

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

[heisenzombie]

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

[epistasis]

Very nice, thanks for sharing!

[morkalork]

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.

[porridgeraisin]

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