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by data-ottawa
315 days ago
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I've been using marimo since January pretty heavily, I absolutely love it and would recommend it to anyone. I run it with uv and --sandboxed which makes it much easy to share notebooks with teammates and not have to worry about limiting dependencies. Any issues I've had were were Python libraries themselves (specifically graphviz). I really like how much easier it is to reason about interactive components vs Jupyter. The mo.ui.altair_chart method has got me to migrate off of matplotlib because charts can be fully integrated – as you can see in the demo being able to lasso data points or scrub a chart and analyze specific time periods is awesome. One thing which I don't like about reactive notebooks is that you have to be much more mindful of expensive and long running calculations. There are feature to help, like adding a run button, but often I end up just disabling auto-run which does reduce the value of the reactive flow. For those use cases I don't find myself using marimo over Jupyter. I think the entire marimo team deserves a shoutout, the quality of the software is excellent, they've moved very quickly, and they have been very receptive to issues and feature suggestions. |
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We're committed to having an excellent experience for working with expensive notebooks [1]. At least for my own personal work, I find that there are many reasons to use marimo even when autorun is disabled — you still get guarantees on state, rich dataframe views, reusable functions [2], the Python file format, and more. If you have feedback on how we might improve the experience, we'd love to hear it.
[1] https://docs.marimo.io/guides/expensive_notebooks/
[2] https://docs.marimo.io/guides/reusing_functions/