--- viewer: false tags: - uv-script - marimo - tutorial --- # Marimo UV Scripts [Marimo](https://marimo.io/) notebooks that work as both **interactive tutorials** and **batch scripts**. ## What is this? Marimo notebooks are pure Python files that can be: - **Edited interactively** with a reactive notebook interface - **Run as scripts** with `uv run` - same as any UV script This makes them perfect for tutorials and educational content where you want users to explore step-by-step, but also run the whole thing as a batch job. ## Available Scripts | Script | Description | |--------|-------------| | `getting-started.py` | Introduction to UV scripts and HF datasets | | `train-image-classifier.py` | Fine-tune a Vision Transformer on image classification | | `_template.py` | Minimal template for creating your own notebooks | ## Usage ### Run as a script ```bash # Get dataset info uv run https://huggingface.co/datasets/uv-scripts/marimo/raw/main/getting-started.py --dataset squad # Train an image classifier uv run https://huggingface.co/datasets/uv-scripts/marimo/raw/main/train-image-classifier.py \ --dataset beans \ --epochs 3 \ --output-repo your-username/beans-vit ``` ### Run interactively ```bash # Clone and edit locally git clone https://huggingface.co/datasets/uv-scripts/marimo cd marimo # Open in marimo editor (--sandbox auto-installs dependencies) uvx marimo edit --sandbox getting-started.py uvx marimo edit --sandbox train-image-classifier.py ``` ### Run on HF Jobs (GPU) ```bash # Train image classifier with GPU hf jobs uv run --flavor l4x1 --secrets HF_TOKEN \ https://huggingface.co/datasets/uv-scripts/marimo/raw/main/train-image-classifier.py \ -- --dataset beans --output-repo your-username/beans-vit --epochs 5 --push-to-hub ``` ## Why Marimo? - **Reactive**: Cells automatically re-run when dependencies change - **Pure Python**: No JSON, git-friendly, readable as plain code - **Self-contained**: Inline dependencies via PEP 723 metadata - **Dual-mode**: Same file works as notebook and script ## Create Your Own Marimo UV Script Use `_template.py` as a starting point: ```bash # Clone and copy the template git clone https://huggingface.co/datasets/uv-scripts/marimo cp marimo/_template.py my-notebook.py # Edit interactively uvx marimo edit --sandbox my-notebook.py # Test as script uv run my-notebook.py --help ``` ## Recipes ### Add explanation (notebook only) ```python mo.md(""" ## This is a heading This text explains what's happening. Only shows in interactive mode. """) ``` ### Show output in both modes ```python # print() shows in terminal (script) AND cell output (notebook) print(f"Loaded {len(data)} items") ``` ### Interactive control with CLI fallback ```python # Parse CLI args first parser = argparse.ArgumentParser() parser.add_argument("--count", type=int, default=10) args, _ = parser.parse_known_args() # Create UI control with CLI default slider = mo.ui.slider(1, 100, value=args.count, label="Count") # Use it - works in both modes count = slider.value # UI value in notebook, CLI value in script ``` ### Show visuals (notebook only) ```python # mo.md() with images, mo.ui.table(), etc. only display in notebook mo.ui.table(dataframe) # For script mode, also print summary print(f"DataFrame has {len(df)} rows") ``` ### Conditional notebook-only code ```python # Check if running interactively if hasattr(mo, 'running_in_notebook') and mo.running_in_notebook(): # Heavy visualization only in notebook show_complex_plot(data) ``` ## Best Practices 1. **Always include `print()` for important output** - It works in both modes 2. **Use argparse for all configuration** - CLI args work everywhere 3. **Add `mo.md()` explanations between steps** - Makes tutorials readable 4. **Test in script mode first** - Ensure it works without interactivity 5. **Keep dependencies minimal** - Add `marimo` plus only what you need ## Learn More - [Marimo documentation](https://docs.marimo.io/) - [UV scripts guide](https://docs.astral.sh/uv/guides/scripts/) - [uv-scripts organization](https://huggingface.co/uv-scripts)