jupyter-live-kernel

Use the hamelnb jupyter_live_kernel.py script with the execute subcommand, passing --path to a notebook and --code with your Python code. State persists across calls because all executions share the same live kernel session.

Use a live kernel when you need state to persist across steps, such as iterative data exploration, DataFrame inspection, or building up complex objects. Use one-shot execution for stateless scripts that need tool access like web search or file operations.

Run the variables subcommand with list to see all live variables, or preview with --name to inspect a specific variable's value. Note that --path goes before the list or preview sub-subcommand.

The kernel needs a moment to initialize after the server starts, so the first execution may hit the 30-second default timeout. Retry the call, or pass a larger value such as --timeout 120 for heavy computation.

The kernel uses JupyterLab's Python environment, so packages must be installed into that environment before use. Install them with uv into the JupyterLab tool environment, then they are importable in executed code.