Jupyter widgets are powerful tools for building user interfaces with graphical controls such as sliders and text boxes inside a Jupyter notebook. Interactive widgets can also be rendered in Sphinx documentation, nbviewer, and static web pages. Jupyter widgets are more than a collection of controls, they also are a framework that makes it easy to build custom GUI controls. Examples of custom widget packages include libraries for interactive 2-D charting (bqplot), 3-D graphics (pythreejs, ipyvolume), mapping (ipyleaflet), and more.
1. This tutorial begins with an overview of the functionalities provided by the base package:
Sylvain Corlay is an applied mathematician specializing in stochastic analysis and optimal control. He holds a PhD in applied mathematics from University Paris VI. As an open source developer, Sylvain contributes to Project Jupyter in the area of interactive widgets for the notebook, and is steering committee member of the Project. Besides Jupyter, Sylvain contributes to a number of scientific computing open-source projects such as bqplot, xtensor and ipyleaflet. Sylvain founded QuantStack in September 2016. Prior to founding QuantStack, Sylvain was a quant researcher at Bloomberg and an adjunct faculty member at the Courant Institute and Columbia University.