notebooks

Notebooks

A single skill for authoring, validating, and delivering reproducible analysis notebooks. Marimo is the default format; Jupyter is supported for existing .ipynb files and when a downstream tool requires JSON. Conversion between the two formats is part of this skill.

A notebook is not "done" until it has been executed end-to-end on a fresh kernel and every figure is embedded in the delivered file.

Instructions

1. Pick the format.

   • New notebook: write a marimo .py notebook. Use the canonical cell layout (one concept per cell, final expression renders, no if guards around outputs, no try/except for control flow).
   • Existing .ipynb to extend or polish: keep it as Jupyter unless the user asks to convert.
   • Conversion: see "Convert between marimo and Jupyter" below.

2. Outline before coding. Write the notebook plan (purpose, data sources, analysis steps, expected outputs/plots) as the first markdown cell, then implement against that plan.

3. Keep marimo cells clean. These are hard rules for every .py notebook:

   • Markdown cells use one plain triple-quoted string: mo.md(r"""...""") or mo.md(f"""...""") only when interpolation is required. Put the prose directly inside the string; never paste quoted string fragments such as " ... " lines inside the markdown body.
   • Do not leave empty generated cells, whitespace-only cells, or @app.cell def _(): return placeholders. Remove them before final verification.
   • Do not accept a marimo "fix" prompt blindly. If one is accepted during interactive editing, inspect the diff immediately and remove unintended PEP 723/header/cell churn.

4. Set up the kernel and dependencies.

   • Marimo. Pin dependencies in the PEP 723 script header at the top of the .py file:

     # /// script
     # requires-python = ">=3.12"
     # dependencies = [
     #     "marimo",
     #     "polars",
     #     "duckdb",
     #     "matplotlib",
     #     # ... add every import used in the notebook
     # ]
     # ///
     

     Run with uvx marimo run --sandbox <notebook.py> or edit interactively with uvx marimo edit --sandbox <notebook.py>. The sandbox reads the header and resolves the notebook environment.
   • Jupyter. Register a named ipykernel for the project's pixi env before the first execution and pin the kernel in the notebook metadata. The kernel name is mandatory: the generic python3 kernel leaks the system interpreter.

     pixi run python -m ipykernel install --user --name <project> --display-name "<project> (pixi)"
     

     Then in <notebook>.ipynb confirm:

     "kernelspec": {"name": "<project>", "display_name": "<project> (pixi)"}
     

     Add every import used in the notebook to pixi.toml so the kernel can resolve it from a clean install.