Reactive Notebooks for Python
summary
Reactive Python notebooks implement automatic dependency tracking so cells re-run only when needed and claim impossible to reach an invalid state by design. The implementation reuses Pluto UI widgets (sliders, scrubbables, file picker, webcam), binds UI inputs to variables, and supports self-updates via queues and threads for real‑time streams. Demos show Matplotlib→Plotly plots updating, outputs movable (default top), and deployment on Jolan IO / cloud.jolan.io with Conda-based package installs that auto-run and work as shown.
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chapters (13)
- 0:00Introduction
- 1:57What are reactive notebooks
- 3:23Reactive cells basics
- 8:19Graphical user input
- 12:13Interactive elements overview
- 13:59Key features
- 16:08Self-updating notebooks
- 19:17Real-time data stream
- 24:37Long-running updates
- 27:50Dashboards with plots
- 29:35Package installation
- 30:19Future plans
- 31:43Summary
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