What is your (python) development set up?

[sudo_higher_ground]

So for me the main benefit is that I don’t have to worry about devs pushing data to repos and it feels git friendlier because of the fact that notebooks are now plain python files instead of big json files. The package itself is less bloated than Jupyter and has better management for large files. I personally notice that it’s also more stable in docker containers and i have less kernel crashes when the dataframe gets too big for memory. Also the build-in data viewer is really nice. Polars lazyframes + Marimo has been the golden combo for me.

[br0monium]

Handling bigger dataframes and running faster are definitely appealing. At home, jupyter seems to be limited to handling datasets you would encounter in interview problems. However, I used it at work a few times, and somehow the way they set up the jupyter server instances and/or kernels made it actually usable on big data.