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Closer to production quality Python notebooks with `marimo check`

Closer to production quality Python notebooks with `marimo check`

4 comments

·October 7, 2025
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wodenokoto

I’m very interested in moving beyond Jupyter notebooks so I have my eye on marimo.

My understanding is it’s just python code with a bit of notebook hints and an idea that gives the notebook experience.

So I didn’t quite catch from the article why ruff and pylons aren’t enough.

loveparade

I wish this didn't have AI in it. I've been looking for a Jupyter alternative that is pure python and can be modified from a regular text editor. Jupytext works okay, but I miss the advanced Jupyter features. But I really don't want to deal with yet another AI assistant, especially not a custom one when I'm already using Claude/etc from the CLI and I want those agents to help me edit the notebooks.

Take out all the AI stuff and I'd give it a try. I use AI coding agents as my daily driver, but I really don't need this AI enshittification in every tool/library I'm using.

3eb7988a1663

I hate how much I lean into VSCode, but the Python interactive mode gets you a really good live coding environment. Instead of Jupyter cells, you have a regular .py file with chunks of code prefixed with a `# %%`. VSCode gives you a similar experience to a notebook, with the same controls (Run Above Cells, Restart and Run All, etc). So something like

  # %%
  import polars as pl

  # %%
  df = pl.DataFrame()
  df.shape

  # %%
  def foobar():
    return 1
Since it is a regular .py file all of your existing tooling will work with it. The one thing you lose vs a Jupyter notebook is saved output. I mostly use these .py files, but have a few .ipynb notebook files for when I want to commit the output from some important task.

dmadisetti

marimo notebooks double as python Python programs, which means they can be lint-ed like any other code. `marimo check` catches notebook-specific issues (variable redefinition across cells, circular dependencies) with Rust-inspired (and uv; uv is amazing) error messages. It outputs JSON for AI agents to self-correct, integrates into CI pipelines, and includes `--fix` flags for automatic repairs. The team is already using it in their own CI and seeing Claude Code iterate on notebooks without human intervention.