Shiny for Python: Interactive apps and dashboards made easy-ish
summary
Shiny for Python is announced as an Alpha release that brings Shiny’s decade‑old reactive graph/decorators model to Python, trading Streamlit’s simplicity for selective execution so only affected computations rerun instead of reruns entire script on every input. Examples include a matplotlib CPU monitor, a compound‑interest scenario builder, Plotly and ipywidgets integration, and a MediaPipe hand‑tracking demo with a reactive smoother — showing concrete tools, performance gains, and working prototypes.
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chapters (14)
- 0:00Shiny for Python intro
- 6:05Why not Streamlit
- 10:47Interactive dashboard core
- 17:43Shiny reactivity optimizes
- 19:28Demo CPU monitor streaming
- 21:16Demo compound interest calc
- 23:49Demo 3D Brownian motion
- 27:03Call to action
- 28:09Q&A graphing libraries
- 30:12Q&A reactive decorators
- 31:34Q&A reactive programming
- 34:01Q&A Streamlit session state
- 37:37Q&A multi-user deployment
- 42:49Q&A naming and final
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