Advanced Streamlit for Python Developers
summary
A multi‑page Streamlit app gets built live: a GitHub activity dashboard with sliders, area/scatter/bar charts, st.cache_data for performance and session state for interactivity, plus a RAG chatbot using llama_index and GPT‑3.5 over repo markdown. Code shows csv loaders, pandas datetime conversion, grouped contributor totals, three metrics and a week‑range slider; experimental_fragment reduces reruns. The example runs locally and the slides link includes ready‑to‑paste step files.
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chapters (12)
- 0:00Introduction
- 5:30Setup and project structure
- 7:57Loading and caching data
- 15:44App layout and tabs
- 20:26Code frequency visualization
- 24:58Date range filters
- 30:14Area and scatter charts
- 32:17Commit activity tab
- 34:02Commit metrics and charts
- 36:03Contributor data analysis
- 37:48Grouping contributor activity
- 38:51Summary and resources
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