Thanks Simon for the kind words!

For those new to marimo, we have affordances for working with expensive (ML/AI/pyspark) notebooks too, including lazy execution that gives you guarantees on state without running automatically.

One small note: marimo was actually first launched publicly (on HN) in January 2024 [1]. Our first open-source release was in 2023 (a quiet soft launch). And we've been in development since 2022, in close consultation with Stanford scientists. We're used pretty broadly today :)

[1] https://news.ycombinator.com/item?id=38971966

I think it’s safe to say Observable’s inability to properly price their services made people look elsewhere. Their new offering is interesting but also ridiculously priced.

I was also wondering their pricing because Canvas seemed so cool at first. Now that I've seen your comment I checked and $900/month (includes 10 users) is indeed very high. I guess they are primarily targeting big enterprises.

> it adds "reactivity", which solves the issue where Jupyter cells can be run in any order

This is one of the key features of Jupyter to me; it encourages quick experimentation.

Once you get to a certain complexity of notebooks, I find it only serves to complicate my mental model to “experiment” out of order. It makes me far more likely to forget to “commit” an ordering change.

Jupyter notebooks do store the execution order of the cells. Just enforce a pre-commit or pre-merge hook that doesn't allow adding notebooks that have out-of-order cells.

marimo still allows you to run cells one at a time (and has many built-in UI elements for very rapid experimentation). But the distinction is that in marimo, running a cell runs the subtree rooted at it (or if you have enabled lazy execution, marks its descendants as stale), keeping code and outputs consistent while also facilitating very rapid experimentation. The subtree is determined by statically parsing code into a dependency graph on cells.