bokeh is a library for generating interactive graphics and dashboards in python. Every component offers a myriad of customizing options, and I find it impossible to keep track of them. This tool (very much under development) offers a graphical interface to those options. A user may prepare a plot format that they like, and then obtain yaml code that they can include in whatever bokeh project they are working on.
As you select options, the page will show yaml code to the right of your plot.
You can download this yaml code by clicking the download button (creating the file theme.yaml) or just
copy this yaml into a file to create a bokeh theme. This blog post
explains how to use the theme file to style your plots.
Here is the tool in action:
This valentines theme is an example created by this tool:
You can run this locally as a bokeh server app. You run it like this:
$ bokeh serve .
and navigate in your browser to localhost port 5006.
As a bonus, the utils directory includes the file structure.py where you can find the BokehStructureGraph
class. This can be used to analyze models and determine which attributes are available for customization.
Using this class on the simple figure
yields this interactive display:
These two images were created in a jupyter notebook using this code:
from utils.structure import BokehStructureGraph
from bokeh.plotting import figure, show, output_notebook
output_notebook()
# draw the easy figure
f = figure(height=200,width=200)
f.line(x=[1,2,3],y=[1,2,3])
f.circle(x=[3,2,1],y=[1,2,3],size=10, color='red')
show(f)
# now draw the structure graph with interactive datatable
show(BokehStructureGraph(f).model)