Python Bokeh save(): Export Plots to Static Files Guide

The Bokeh library in Python offers powerful visualization capabilities, and one essential feature is the ability to save plots as static files using the save() function. This guide will show you how to effectively use this functionality.

Understanding Bokeh save() Function

The save() function allows you to export your Bokeh visualizations to various file formats, making them suitable for documentation, presentations, or sharing with others who don't have Bokeh installed.

Basic Usage of save()

Here's a simple example demonstrating how to create a basic plot and save it:

from bokeh.plotting import figure, save
from bokeh.io import output_file

# Create a simple plot
p = figure(width=400, height=300, title="Basic Example")
p.line([1, 2, 3, 4, 5], [2, 5, 8, 2, 7])

# Save the plot
output_file("basic_plot.html")
save(p)

This example creates a simple line plot and saves it as an HTML file. Similar to how you might create interactive visualizations in Bokeh line plots.

Saving Different File Formats

While HTML is the default format, Bokeh supports multiple export formats through the export_png() and export_svg() functions:

from bokeh.io import export_png, export_svg

# Create your plot
p = figure(width=400, height=300)
p.circle([1, 2, 3], [4, 5, 6])

# Export as PNG
export_png(p, filename="plot.png")

# Export as SVG
export_svg(p, filename="plot.svg")

Adding Interactive Features Before Saving

You can add interactive features to your plot before saving it. This is particularly useful when saving to HTML format, as these features will be preserved:

from bokeh.models import HoverTool
from bokeh.plotting import figure, save
from bokeh.io import output_file

# Create plot with hover tool
p = figure(width=400, height=300)
p.add_tools(HoverTool(tooltips=[("x", "@x"), ("y", "@y")]))
p.circle([1, 2, 3], [4, 5, 6])

# Save interactive plot
output_file("interactive_plot.html")
save(p)

This example incorporates hover tooltips, similar to what you might learn in the Bokeh HoverTool guide.

Best Practices for Saving Plots

File Naming: Use clear, descriptive filenames that indicate the plot's content.

Resolution Settings: When exporting to PNG, consider setting appropriate DPI (dots per inch) for quality:

from bokeh.io import export_png

# Export with custom DPI
export_png(p, filename="high_res_plot.png", height=600, width=800)

Saving Multiple Plots

When working with multiple plots, you can save them together using layouts:

from bokeh.layouts import column
from bokeh.plotting import figure, save
from bokeh.io import output_file

# Create two plots
p1 = figure(width=300, height=200)
p1.line([1, 2, 3], [4, 5, 6])

p2 = figure(width=300, height=200)
p2.circle([1, 2, 3], [4, 5, 6])

# Combine and save
layout = column(p1, p2)
output_file("multiple_plots.html")
save(layout)

For more complex layouts, you might want to explore the Bokeh gridplot functionality.

Common Issues and Solutions

Missing Dependencies: When exporting to PNG or SVG, ensure you have selenium and chrome/chromium installed:

pip install selenium
pip install chromedriver-binary

File Permissions: Ensure you have write permissions in the target directory.

Conclusion

The Bokeh save() function is a versatile tool for exporting your visualizations. Whether you need static images or interactive HTML files, proper understanding of this function is essential for sharing your data visualizations effectively.