Bokeh 2.3.3 Exclusive -

Overview of Bokeh

Bokeh remains a premier choice for Python developers needing web-ready interactivity without writing JavaScript.

• Improved Performance: Bokeh 2.3.3 includes several performance improvements, making it faster and more efficient.
• Enhanced Hover Tool: The hover tool has been enhanced to support additional features, such as displaying multiple lines of text and showing images.
• New Glyphs: Bokeh 2.3.3 includes several new glyphs, including a text glyph for displaying text on a plot.

: While PNG was standard, 2.3.3 documentation provides specific paths for exporting layouts as SVGs Bokeh documentation 🏗️ Building a Basic Plot In Bokeh 2.3.3, the bokeh.plotting interface is the most common entry point: # Create a figure with specific tools = figure(title= Basic Line Plot , x_axis_label= , y_axis_label= pan,wheel_zoom,box_zoom,reset # Add a renderer ], line_width= # Display the result Use code with caution. Copied to clipboard 🚀 Advanced Usage Bokeh Server bokeh 2.3.3

from bokeh.models import ColumnDataSource from bokeh.plotting import figure, show Overview of Bokeh Bokeh remains a premier choice

Key Features in Bokeh 2.3.3

save(p, "plot.html") # interactive HTML export_png(p, "plot.png") # requires selenium + phantomjs (older) Improved Performance : Bokeh 2

Here's an example of how to create a simple line plot using Bokeh 2.3.3: