The Panel ecosystem relies entirely on Bokeh models to render high-level analytic dashboards. Changes in previous minor patches caused nested components inside Panel templates to collapse or span beyond container frames. Version 2.3.3 fixed these sizing conflicts, assuring data scientists that complex multi-plot arrays wouldn't break upon UI resizing. 2. Scrollable CSS Class Compliance (#11083)
This patch-release also included several other minor documentation, build, and bugfix updates, solidifying Bokeh 2.3.3 as a stable and reliable version for production use.
Let’s create a small interactive dashboard that demonstrates the power of Bokeh 2.3.3. This example combines a line plot, a scatter plot, and a slider widget to filter data dynamically. bokeh 2.3.3
Configured custom extensions to fetch the exact matching version directly from the Bokeh CDN. This prevents major security and compatibility issues resulting from mismatched server and client environments. 💻 Sample Code: Creating a Basic Plot in Bokeh 2.3.3
The Bokeh community is active and welcoming. For users of Bokeh 2.3.3, the following resources are available: The Panel ecosystem relies entirely on Bokeh models
Bokeh is an open-source Python library designed to help data scientists and developers create interactive visualizations and dashboards. It provides a high-level interface for drawing plots, charts, and other graphical elements, making it easy to create web-based interactive plots. Bokeh's primary goal is to provide a simple and elegant way to create interactive visualizations that can be easily shared and deployed.
Even as a patch release, Bokeh 2.3.3 inherits the full feature set of the 2.3 series. Some of the most notable features include: This example combines a line plot, a scatter
or via conda: