jupyter-live-kernel

Use the hamelnb script's execute command with a notebook path and code string, for example: uv run "$SCRIPT" execute --path scratch.ipynb --code 'print(x)' --compact. State persists across execute calls, so variables and imports survive between runs.

Use a live kernel when you need state across steps, such as data science exploration, ML experimentation, or inspecting intermediate DataFrames. Use one-shot execution for stateless scripts that do not depend on prior variables.

You need uv installed, JupyterLab installed via uv tool install jupyterlab, and a running Jupyter server. You must also create a kernel session through the Jupyter REST API before executing code.

The kernel needs time to initialize after the server starts, so the first execution may hit the 30-second default timeout. Retry the command, and pass a larger value such as --timeout 120 for heavy computations.

Use the variables subcommand: uv run "$SCRIPT" variables --path notebook.ipynb list --compact to list variables, or add preview --name <varname> to inspect a specific one. Note that --path goes before the list or preview sub-subcommand.