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Philipp Rudiger Rapidly prototyping and deploying powerful data applications in Jupyter using Pane
Rapidly prototype and deploy powerful data applications in Jupyter with Pane, Panel, and HoloVis. Learn to build interactive data applications and deploy them entirely in the browser without servers.
- Rapid prototyping and deploying powerful data applications in Jupyter is possible with Pane.
- The presentation showcases how to prototype and deploy a portfolio analyzer application in Jupyter.
- The application is created using the Panel library and leverages tools like pandas, Vega, and Plotly.
- The key principles for a powerful exploratory workflow are: 1) reduce friction when iterating, 2) use the tools you already know, 3) iterate quickly, and 4) preview your application before deploying.
- Panel provides a unified set of tools that work well together for building interactive data applications.
- The presentation also highlights the HoloVis platform, which allows users to deploy applications entirely in the browser, eliminating the need for servers.
- Pyodide, a library that runs Python in the browser, is also demonstrated as a tool for deploying Jupyter notebooks.
- The presentation concludes with the statement that “you shouldn’t have to change it, just use it” - emphasizing the ease of use and rapid prototyping capabilities of the tools showcased.