Run code interactively with Jupyter kernels.
Supports Python, R, JavaScript, and other languages with rich output including plots, images, HTML, and LaTeX.
- Interactive execution: run lines, selections, or automatically detected code blocks with inline results, multiple cursors, and smart Python/bracket/fold detection.
- Rich media output: renders plots, images, video, HTML, LaTeX, and interactive Plotly and Vega charts inline.
- Jupyter widgets: renders the core
ipywidgetscontrols live against the kernel, includinginteractand the output widget. - Kernel intelligence: autocomplete, object introspection, and a shared namespace with one kernel per language across files.
- Kernel management: starts local kernels, connects to remote gateways, and interrupts, restarts or shuts them down.
- Notebook adapters: drives external notebook cells, such as jupyter-view's, through the
jupyter.adapterservice. - Jupyter console: attaches a console to the active kernel in an embedded terminal, a system terminal, or via a copied command.
- Extensible services: provides and consumes services for autocomplete, kernels, execution, and third-party integrations.
To install jupyter-repl search for it in the Install pane of the Lumine settings, or run the command lumine --install lumine-code/jupyter-repl.
Commands available in lumine-workspace:
jupyter-repl:run: run code at cursor,jupyter-repl:run-and-move-down: run and move to next block,jupyter-repl:run-all-inline: run all code inline, one statement at a time,jupyter-repl:run-all-above-inline: run all code above cursor inline,jupyter-repl:run-all-below-inline: run all code below cursor inline,jupyter-repl:recalculate-all-inline: clear results, restart kernel, run all inline,jupyter-repl:recalculate-all-above-inline: clear results, restart kernel, run all above inline,jupyter-repl:clear-results: clear output results,jupyter-repl:clear-and-restart: clear results and restart kernel,jupyter-repl:toggle-output-area: toggle output area mode,jupyter-repl:toggle-kernel-commands: toggle the active kernel's command picker,jupyter-repl:start-local-kernel: start a local kernel,jupyter-repl:connect-to-remote-kernel: connect to a remote kernel via gateway,jupyter-repl:connect-to-existing-kernel: connect to an existing kernel,jupyter-repl:interrupt-kernel: interrupt running execution,jupyter-repl:restart-kernel: restart the kernel,jupyter-repl:shutdown-kernel: shutdown the kernel,jupyter-repl:rename-remote-session: rename remote session,jupyter-repl:disconnect-remote-session: disconnect remote session,jupyter-repl:update-kernels: refresh available kernels list,jupyter-repl:open-examples: open example files,jupyter-repl:edit-gateways: opengateways.json,jupyter-repl:shutdown-all-kernels: shutdown all running kernels,jupyter-repl:debug-toggle: toggle debug logging,jupyter-repl:open-terminal: open Jupyter console attached to active kernel in an embedded terminal pane,jupyter-repl:spawn-terminal: spawn Jupyter console attached to active kernel in a system terminal,jupyter-repl:copy-console-command: copy the Jupyter console command to clipboard,jupyter-repl:copy-result: copy a result's text or image to clipboard,jupyter-repl:open-result-in-editor: open a result's contents in a new editor,jupyter-repl:save-result-image: save a result's image to a file,jupyter-repl:toggle-result-expansion: expand or collapse a scrolling result,jupyter-repl:reset-result-size: return a dragged result to its natural size,jupyter-repl:close-result: remove a result.
The last six act on the result the command was dispatched from — its own context menu or its chrome — and otherwise on the result at the cursor's line.
Commands available in .jupyter-repl.kernel-picker, all listed with their keybindings in the item-actions list (F12):
jupyter-repl:insert-kernel-comment: insert or update the kernel magic comment on the first line,jupyter-repl:refresh-kernel-list: rescan kernel specs and reload the list.
Rendered in the editor under Settings, and readable here:
- Kernels — installing kernels, choosing between them, and remote gateways.
- Running code — what a run sends, what the results do, and the console launcher.
- Integration — the notebook adapter and the kernel object a service hands over.
- Widgets — which
ipywidgetscontrols render, and what happens to them when the kernel restarts. - jupyter.kernel, jupyter.output, jupyter.execution — the service contracts.
jupyter.kernel: provided to let other packages execute code, request completions and introspection, and follow kernel state.jupyter.output: provided to let other packages render Jupyter output bundles with this package's renderers.autocomplete.provider: provided to feed kernel-backed completions to autocomplete consumers while a kernel is active for the editor.jupyter.execution: provided to run pre-computed code blocks through this package's kernels and result bubbles.mcp.tools: provided to let an AI assistant list the running kernels, run code in one, inspect an expression, interrupt a run, and restart a kernel.jupyter.adapter: consumed to run cells of external pane items, such as jupyter-view notebooks, through the normal run commands.jupyter.cells: consumed to read cell boundaries and markdown-cell metadata where the run paths meet# %%markers.status-bar: consumed to display the kernel of the active editor and its execution state.terminal: consumed to run the Jupyter console in an embedded terminal pane.terminal-spawn: consumed to run the Jupyter console in a system terminal.image-editor: consumed to open image outputs in a full image editor.
Got ideas to make this package better, found a bug, or want to help add new features? Just drop your thoughts on GitHub. Any feedback is welcome!