# 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>

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

# 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,)

# 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

# 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)
    # ...

# 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

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

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

# 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")

uvx marimo check <notebook.py>