Bokeh 2.3.3 Updated Review

This occurs when you reuse the same figure or ColumnDataSource in two different layouts. : Create a new source for each independent document, or use bokeh.io.curdoc() to manage ownership properly (for server apps).

Released as a patch update to the popular 2.3 series, Bokeh 2.3.3 consolidates months of bug fixes and minor enhancements without introducing the architectural shifts found in later versions (like the Bokeh 3.0 line). For teams maintaining legacy dashboards, educational platforms, or large-scale data applications, this version is the unsung hero. This article explores everything you need to know about Bokeh 2.3.3: its key features, why you might choose it over newer releases, how to install it, and practical examples to get you started. bokeh 2.3.3

# 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 This occurs when you reuse the same figure