Notes for marimo Notebooks

Running Marimo Notebooks

# Run as script (non-interactive, for testing)
uv run <notebook.py>

# Run interactively in browser
uv run marimo run <notebook.py>

# Edit interactively
uv run marimo edit <notebook.py>

Script Mode Detection

Use mo.app_meta().mode == "script" to detect CLI vs interactive:

@app.cell
def _(mo):
    is_script_mode = mo.app_meta().mode == "script"
    return (is_script_mode,)

Key Principle: Keep It Simple

Show all UI elements always. Only change the data source in script mode.

Sliders, buttons, widgets should always be created and displayed
In script mode, just use synthetic/default data instead of waiting for user input
Don't wrap everything in if not is_script_mode conditionals
Don't use try/except for normal control flow

Good Pattern

# Always show the widget
@app.cell
def _(ScatterWidget, mo):
    scatter_widget = mo.ui.anywidget(ScatterWidget())
    scatter_widget
    return (scatter_widget,)

# Only change data source based on mode
@app.cell
def _(is_script_mode, make_moons, scatter_widget, np, torch):
    if is_script_mode:
        # Use synthetic data for testing
        X, y = make_moons(n_samples=200, noise=0.2)
        X_data = torch.tensor(X, dtype=torch.float32)
        y_data = torch.tensor(y)
        data_error = None
    else:
        # Use widget data in interactive mode
        X, y = scatter_widget.widget.data_as_X_y
        # ... process data ...
    return X_data, y_data, data_error

# Always show sliders - use their .value in both modes
@app.cell
def _(mo):
    lr_slider = mo.ui.slider(start=0.001, stop=0.1, value=0.01)
    lr_slider
    return (lr_slider,)

# Auto-run in script mode, wait for button in interactive
@app.cell
def _(is_script_mode, train_button, lr_slider, run_training, X_data, y_data):
    if is_script_mode:
        # Auto-run with slider defaults
        results = run_training(X_data, y_data, lr=lr_slider.value)
    else:
        # Wait for button click
        if train_button.value:
            results = run_training(X_data, y_data, lr=lr_slider.value)
    return (results,)

Don't Guard Cells with `if` Statements

Marimo's reactivity means cells only run when their dependencies are ready. Don't add unnecessary guards:

# BAD - the if statement prevents the chart from showing
@app.cell
def _(plt, training_results):
    if training_results:  # WRONG - don't do this
        fig, ax = plt.subplots()
        ax.plot(training_results['losses'])
        fig
    return

# GOOD - let marimo handle the dependency
@app.cell
def _(plt, training_results):
    fig, ax = plt.subplots()
    ax.plot(training_results['losses'])
    fig
    return

The cell won't run until training_results has a value anyway.

Don't Use try/except for Control Flow

Don't wrap code in try/except blocks unless you're handling a specific, expected exception. Let errors surface naturally.

# BAD - hiding errors behind try/except
@app.cell
def _(scatter_widget, np, torch):
    try:
        X, y = scatter_widget.widget.data_as_X_y
        X = np.array(X, dtype=np.float32)
        # ...
    except Exception as e:
        return None, None, f"Error: {e}"

# GOOD - let it fail if something is wrong
@app.cell
def _(scatter_widget, np, torch):
    X, y = scatter_widget.widget.data_as_X_y
    X = np.array(X, dtype=np.float32)
    # ...

Only use try/except when:

You're handling a specific, known exception type
The exception is expected in normal operation (e.g., file not found)
You have a meaningful recovery action

Cell Output Rendering

Marimo only renders the final expression of a cell. Indented or conditional expressions won't render:

# BAD - indented expression won't render
@app.cell
def _(mo, condition):
    if condition:
        mo.md("This won't show!")  # WRONG - indented
    return

# GOOD - final expression renders
@app.cell
def _(mo, condition):
    result = mo.md("Shown!") if condition else mo.md("Also shown!")
    result  # This renders because it's the final expression
    return

Marimo Variable Naming

Variables in for loops that would conflict across cells need underscore prefix:

# Use _name, _model to make them cell-private
for _name, _model in items:
    ...

PEP 723 Dependencies

# /// script
# requires-python = ">=3.12"
# dependencies = [
#     "marimo",
#     "torch>=2.0.0",
# ]
# ///

Prefer pathlib over os.path

Use pathlib.Path for file path operations instead of os.path:

# GOOD - use pathlib
from pathlib import Path
data_dir = Path(tempfile.mkdtemp())
parquet_file = data_dir / "data.parquet"

# BAD - avoid os.path
import os
parquet_file = os.path.join(temp_dir, "data.parquet")

marimo check

When working on a notebook it is important to check if the notebook can run. That's why marimo provides a check command that acts as a linter to find common mistakes.

uvx marimo check <notebook.py>

Make sure these are checked before handing a notebook back to the user.

api docs

If the user specifically wants you to use a marimo function, you can locally check the docs via:

uv --with marimo run python -c "import marimo as mo; help(mo.ui.form)"

Additional resources

For SQL use in marimo see SQL.md
For UI elements in marimo UI.md
For exposing functions/classes as top level imports TOP-LEVEL-IMPORTS.md

marimo-notebook