jupyter-live-kernel

A stateful Python REPL via a live Jupyter kernel preserves variables across executions, enabling iterative data exploration and rapid API prototyping. Session state is maintained in the kernel, allowing subsequent commands to access previously defined variables.

A stateful Python REPL is an interactive environment that retains variables and objects between sequential code executions. It is needed for data science exploration, API prototyping, and debugging workflows that require building up session state across multiple iterative steps.

Yes, you need JupyterLab and uv installed to run this stateful Python kernel. You must also ensure a running Jupyter server managed by the hamelnb tool located under ~/.agent-skills/hamelnb to execute commands and inspect results in the interactive session.

The best way to debug Python code with persistent session state is using a live Jupyter kernel. It allows you to execute code iteratively via script-driven interaction, preserving variables so you can inspect and troubleshoot results across multiple sequential steps without restarting.

Using a live Jupyter kernel for interactive Python requires a continuously running Jupyter server managed by the hamelnb tool. If the server stops or restarts, the persistent variables and session state are lost, requiring you to reinitialize your environment.