Bokeh 2.3.3 -

For real-time dashboards, this version fixed a critical bug where stream() and patch() methods on ColumnDataSource would sometimes update the wrong indices, leading to visual artifacts.

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

pip install bokeh==2.3.3

or via conda:

conda install bokeh=2.3.3 -c conda-forge

Installing this specific version is straightforward. It is strongly recommended to use a virtual environment. bokeh 2.3.3

When the HTML file generated by the script was opened in the boardroom, the story was clear.

The lead analyst pointed to the screen. "In 2019, the crowd was a background noise. In 2021, the data shows they became a physical force."

Thanks to the stability and layout features of Bokeh 2.3.3, the visualization wasn't just a chart; it was a testament to the human need to cheer. The board approved the budget for improved soundproofing the very next day. For real-time dashboards, this version fixed a critical

⚠️ Later Bokeh versions (3.x) have breaking changes in API and default themes.

from bokeh.plotting import figure, show
from bokeh.io import output_notebook
output_notebook()  # or output_file("plot.html")
p = figure(title="Bokeh 2.3.3 Example",
x_axis_label="X", y_axis_label="Y") or via conda: 
  conda install bokeh=2
p.circle([1,2,3,4,5], [6,7,2,4,5],
size=15, color="navy", alpha=0.6)
show(p)