Streamlit Data Apps
Build interactive data apps in pure Python with Streamlit. Turns scripts into dashboards with widgets, charts, and caching — no frontend code needed for internal tools, ML demos, and analytics apps.
This skill makes Claude a Streamlit expert. It builds data apps from plain Python scripts using widgets, layout containers, and native charts, with session state for interactivity and caching for performance. Covers multipage apps, custom components, file uploads, connecting to warehouses and dataframes, and deploying to Streamlit Community Cloud or a container.
When to use
Use when building an internal dashboard, an ML demo, or an analytics tool in Python with Streamlit, adding widgets and caching, or deploying a Streamlit app.
Examples
Build a dashboard
Interactive charts
Build a Streamlit dashboard that loads a CSV, filters by date with a slider, and plots revenue over time
Cache expensive work
Speed it up
Add st.cache_data to my Streamlit app so the warehouse query only reruns when inputs change
Multipage app
Organize views
Convert my single-file Streamlit app into a multipage app with an overview and a details page