Bokeh 2.3.3 !!link!! Site

# stock_viewer.py from bokeh.plotting import figure, show from bokeh.models import ColumnDataSource, HoverTool, DataTable, TableColumn from bokeh.layouts import column, row from bokeh.io import output_file import pandas as pd import numpy as np

Released in July 2021, this micro-version serves as a crucial lifecycle release within the major 2.x release track, specifically targeting critical regressions, layout alignment discrepancies, and web-component theme handling.

p = figure(title="Simple Line Example", x_axis_label='X-axis', y_axis_label='Y-axis', tools="pan,box_zoom,reset,save") bokeh 2.3.3

Working with categorical axes (e.g., bar charts with string categories) became more intuitive. The factor_cmap and factor_mark functions saw internal fixes, ensuring that color mapping and marker shapes apply correctly even when categories have long names or special characters.

When developing text-based elements in this version, you typically use several core models and properties: # stock_viewer

The 2.3.3 release addressed several crucial issues regarding layout, styling, and interactivity. Key improvements listed in the Bokeh 2.3.3 documentation include:

Bokeh 2.3.3 also includes several enhancements and bug fixes. Some of the notable enhancements include: When developing text-based elements in this version, you

Beyond basic plotting, Bokeh 2.3.3 excels in advanced scenarios that require real-time data handling, custom extensions, and sophisticated layouts.

Bokeh 2.3.3 bridges Python data engineering with scalable, responsive web frontends. By decoupling computational analytical code from browser presentation logic via the ColumnDataSource , developers can generate interactive data apps with minimal overhead. Whether your end goal is an embedded blog visualization, an executive HTML report, or an analytical grid running in a Jupyter space, Bokeh 2.3.3 provides a dependable, field-tested foundation for data communication.

While major iterations introduce sweeping architectural re-designs, version 2.3.3 remains an essential production baseline for enterprise environments, legacy applications, and stable data science pipelines that depend on rigid layout behavior and backward compatibility without the breaking changes found in Bokeh 3.x. Key Technical Layout Fixes in Bokeh 2.3.3