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Stephan Sahm - Reactive Notebooks for Python
Discover how to create interactive and reactive Jupyter Notebooks with Stephan Sahm, featuring real-time code updates, client-side triggers, and more, with examples and future plans for the Reactive Notebooks service.
- Reactive Notebooks: a way to make Jupyter Notebooks interactive and reactive, allowing users to write code and see the results in real-time.
- Reactivity: allows cells to update automatically when dependencies change, no need to restart the kernel.
- Client-side and server-side triggers: allows for manual input with UI elements to be integrated with reactive cells.
- Ultimate goal: to make the notebook feel like a website, rather than a traditional notebook.
- Key feature: self-updating cells, which can be integrated with UI elements.
- Examples: shown how to create reactive cells, and how to use them in combination with plots and cameras.
- Future plans: to make the Reactive Notebook service available as a hosted solution, and to integrate it with other tools and services.
- Tools used: Pluto, Plotly, Julia, Python, Jupyter.
- Key concept: reactivity, dependency tracking, self-updating cells.
- Flow: write code, see results in real-time, interactive and reactive.