Modern data analysis using reactive notebooks and fast package management.

1. Install uv (one-time)

   # macOS/Linux
   curl -LsSf https://astral.sh/uv/install.sh | sh
   
   # Windows  
   powershell -c "irm https://astral.sh/uv/install.ps1 | iex"

2. Setup project

   git clone <repository>
   cd <project>
   uv sync

3. Start exploring

   uv run marimo edit notebooks/explore.py

notebooks/      # Interactive analysis (marimo .py files)
src/            # Reusable functions and classes  
data/           # Raw, processed, results (git-ignored)
tests/          # Unit tests
CLAUDE.md       # Project rules and standards

# Edit notebooks
uv run marimo edit notebooks/explore.py

# Add packages  
uv add pandas plotly

# Run tests
uv run pytest

# Export to app
uv run marimo run notebooks/report.py --mode app

• marimo: Reactive notebooks - no hidden state, pure Python files
• uv: 10-100x faster than pip, reproducible environments
• Type hints: Better code completion and error catching
• Modular: Reusable code in src/, notebooks stay clean

• marimo docs
• uv docs
• Project rules

• Notebooks are .py files (git-friendly!)
• No more "restart kernel and run all"
• mo.ui.slider() instead of ipywidgets
• Convert existing notebooks: uv run marimo convert notebook.ipynb