Sharing notebooks means solving data access too
marimo’s creators describe exposing a GitHub repository as a filesystem for browser-based Python to simplify sharing code with data.
The takeaway
Reproducible sharing needs code, data, and execution order.
The context
The approach loads the file tree initially and fetches contents on demand, converting some Jupyter notebooks into marimo. The author explicitly notes that conversion assumes top-to-bottom execution and has edge cases. An easy opening mechanism does not eliminate hidden-state or dependency checks.
Steps worth trying
Editorial suggestions, not promises made by the original author.
- 01
Run the notebook from the beginning in a clean environment and check relative paths and missing dependencies.
- 02
Specify data versions and runtime limitations and verify reproducibility in a colleague’s environment.
Where this applies — and where it may not
Not all dependencies run in a browser, and automatic conversion may not preserve a notebook’s implicit execution state.
From the discussion
“Our conversion logic assumes the notebook was meant to be run top-down”
@mscolnick · View source
Show HN: WASM-powered codespaces for Python notebooks on GitHub
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