Bokeh 2.3.3 ❲HOT ✯❳

Bokeh is a popular Python library used for creating interactive and web-based visualizations. The latest version, Bokeh 2.3.3, offers a wide range of tools and features that make it easy to create stunning plots and dashboards. In this write-up, we'll explore the key features and improvements in Bokeh 2.3.3.

Version 2.3.3 is a patch-release, primarily intended to fix several layout and extension-related bugs that were present in previous versions. According to the official release notes, the key bug fixes in this version include resolving issues where a column ignored the CSS class scrollable, bad formatting of y-axis labels with certain themes, and a layout regression in panel. Additional fixes addressed Div model layout differences, ensuring the active tab is in view on render, plots having a height that could not go below 600px, and a dropdown menu being hidden in a multi-choice selection. The release also included updates for extensions to fetch the exact version from the CDN, along with other minor documentation, build, and bugfix updates.

"Unlocking Stunning Visualizations with Bokeh 2.3.3: A Comprehensive Guide" bokeh 2.3.3

p = figure(title="Bokeh 2.3.3 Example", x_axis_label="X", y_axis_label="Y")

If you're starting a new project today, should you use Bokeh 2.3.3 or jump to Bokeh 3.4+? Here’s a decision matrix: Bokeh is a popular Python library used for

or via conda:

The version was a minor patch release in the Bokeh 2.3 series, issued on May 10, 2021 . Version 2

In complex dashboards containing multi-tab panels, switching between tabs programmatically or loading charts fresh often left the targeted view buried outside the browser's visible viewport. The fix ensures that the designated immediately upon initialization. 4. Theme Formatting Override Fix (#11110)