Supercharge Your Shiny (for Python) App: Unleashing Interactive Jupyter Widgets
summary
shinywidgets brings the Jupyter ipywidgets standard into Shiny for Python, letting hundreds of notebook widgets render as Shiny outputs and turning common one‑way renders (Altair, Plotly, etc.) into two‑way bindings automatically. code uses the render_widget decorator and reactive_read to access front‑end state (for example quak exposes a SQL attribute that updates as the table is filtered), enabling linked views like an Altair bin scatter that updates from table filters; implementation uses the ipywidgets comm layer and it works.
AI-written summary · about
chapters (6)
- 0:00Introduction to widgets
- 2:48One-way vs. two-way binding
- 7:35Integrating into Shiny
- 11:19Creating reactive interfaces
- 13:43Advanced linked views
- 16:13Architecture and summary
related talks
29mUsing Jupyter notebooks to develop and share interactive data displays
44mShiny: Data-centric web applications in Python
41mInteractive Visualization in Jupyter with Bqplot and Interactive Widgets
01h 16mMake your research interactive with Jupyter Dashboards
18mDiversify Your Career with Shiny for Python
35mBuild Simple and Scalable Apps with Shiny
25mUnderstanding reactive execution in Shiny
31mTips to Level-Up Your Shiny for Python Applications