Marimo is very impressive. It's effectively a cross between Jupyter and https://observablehq.com/ - it adds "reactivity", which solves the issue where Jupyter cells can be run in any order which can make the behavior of a notebook unpredictable, whereas in Marimo (and Observable) updating a cell automatically triggers other dependent cells to re-execute, similar to a spreadsheet.

Marimo is pretty new (first release January 2025) but has a high rate of improvement. It's particularly good for WebAssembly stuff - that's been one of their key features almost from the start.

My notes on it so far are here: https://simonwillison.net/tags/marimo/

I personally really like marimo. It's very easy to use and for data analysis type tasks it seems to work a lot better than jupyter in most cases.

marimo is open source and uses a reactive model which makes it fun to mix/match widgets with Python code. It even supports gamepads if you wanted to go nuts!

https://youtu.be/4fXLB5_F2rg?si=jeUj77Cte3TkQ1j-

disclaimer: I work for marimo and I made that video, but the gamepad support is awesome and really shows the flexibility

Thanks for the feedback. Bauplan actually features a few innovative points in this area, and full Pythonic at that: Git for Data (https://docs.bauplanlabs.com/en/latest/concepts/git_for_data...) to sandbox any data change, tag it for compliance and make it querable; full code and data auditability in one command (AFAIK, the only platform offering this), as every change is automatically versioned and tagged with the exact run and code that produced it (https://docs.bauplanlabs.com/en/latest/concepts/git_for_data...).

Our sandbox with public data is free for you to try, or just reach out and ask any question!

You mean on the data side? Data access in the example (and in real-world) is mediated by production-grade Iceberg compatible catalog, sandboxed changes, and full auditability trail (https://docs.bauplanlabs.com/en/latest/concepts/git_for_data...). Or do you mean something else?

I find Marimo best for when you're trying to build something "app-like"; an interactive tool to perform a specific task. I find Jupyter lab more appropriate for random experimentation and exploration, and documenting your learnings. Each absolutely has it's place in the toolbox, and does it's thing well, but for me at least, there's not much overlap between the two other than the cell-based notebook-like similarity. That similarity works well for me when migrating from exploration mode to app design mode. The familiar interface makes it easy for me to take ideas from Jupyter into Marimo to build out a proper application.