Data

Data (notebook ops)

When to use

• You need to run, edit, or execute Jupyter notebooks headlessly.
• You want to use jtool for notebook execution/control when a Jupyter server is available.
• You need a clean way to install deps for notebooks without polluting the system (use uv).

Notebook execution (prefer jtool if server exists)

• Start a Jupyter server if needed: uv run jupyter notebook --no-browser --port 8888 --NotebookApp.token=''.
• Add server once: jtool add-server http://127.0.0.1:8888.
• Execute a notebook: jtool execute-cells path/to/notebook.ipynb --max-output-lines 200.
• If no server is available, fall back to uv run ... jupyter nbconvert --execute.

Headless execution via uv (no server)

• uv run --with pandas --with matplotlib --with notebook python -m jupyter nbconvert --to notebook --execute your.ipynb --output your.ipynb --ExecutePreprocessor.timeout=180
• Use --with flags to supply lightweight deps without altering global envs.

Editing notebooks programmatically

• Generate/patch notebooks with small Python scripts that write JSON (nbformat v4).
• Keep cells compact; prefer clear markdown titles and minimal outputs when shipping.

Path & env tips

• Default workspace: ~/github/....
• Ensure ~/.local/bin on PATH so jtool is discoverable (export PATH=\"$HOME/.local/bin:$PATH\").