Using your own editor

While we recommend using the marimo editor, we understand that you may prefer to use your own. marimo provides a --watch flag that watches your notebook file for changes, syncing them to the marimo editor or running application. This lets you edit your notebook using an editor of your choice, like neovim, VSCode, Cursor, or PyCharm, and have the changes automatically reflected in your browser.

Install watchdog for better file watching

For better performance, install watchdog. Without watchdog, marimo resorts to polling.

marimo's file format

File format tutorial

Run marimo tutorial fileformat at the command line for a full guide.

marimo stores notebooks as Python cells. Cells are stored as functions, decorated with@app.cell; you can optionally give cells names in the editor UI or by editing the notebook file.

@app.cell
def memorable_cell_name(auto, determined, references):  # signature denotes cell inputs
    computed_value = auto + determined + references
    "hello!"                                            # final statement are outputted
    return computed_value                               # return denotes cell outputs

Cell signature and returns

Don't worry about maintaining the signatures of cells and their return values; marimo will handle this for you.

You may also expose imports, and top-level functions and classes in your notebook. Functions must be decorated with @app.function, and classes with app.class_definition. These functions and classes must be pure, closing over only other pure functions and classes or imports and constants defined in an app.setup with block:

For more details see the library guide.

with app.setup:
    CONSTANT: int = 1
    import marimo as mo

@app.function
def my_function(x): ...

@app.class_definition
class MyClass: ...

marimo edit --watch

When you run marimo edit with the --watch flag, the marimo server will open your notebook in the browser and watch the underlying notebook file for changes. When you make changes to the notebook file, they will be streamed to the marimo editor in the browser.

By default, synced code will not be executed automatically, with cells marked as stale instead. Run all stale cells with the marimo editor's "Run" button, or the runStale hotkey, to see the new outputs.

If you want to run all affected cells automatically when you save, change the runtime config in your pyproject.toml file.

[tool.marimo.runtime]
watcher_on_save = "autorun"

marimo run --watch

When you run a notebook with the --watch flag, whenever the file watcher detects a change to the notebook file, the application will be refreshed. The browser will trigger a page refresh to ensure your notebook starts from a fresh state.

Watching for changes to other modules

marimo can also watch for changes to Python modules that your notebook imports, letting you edit auxiliary Python files in your own editor as well. Learn how to enable this feature in our Module Autoreloading Guide

Watching for data changes

Note

Support for watching data files and automatically refreshing cells that depend on them is coming soon. Follow along at https://github.com/marimo-team/marimo/issues/3258

Hot-reloading WebAssembly notebooks

Follow these steps to develop a notebook using your own editor while previewing it as a WebAssembly notebook in the browser. This lets you take advantage of local development tools while seeing the notebook as it appears when deployed as a WebAssembly notebook.

# in one terminal, start a watched edit (or run) session
marimo edit notebook.py --watch

# in another terminal
marimo export html-wasm notebook.py -o output_dir --watch

# in a third terminal, serve the WASM application
cd path/to/output_dir
python -m http.server  # or a server that watches for changes