While the SALT data quality site framework tries to make adding plots as simple as possible, getting a plot up-and-running on the server can have its intricacies. But there are two alternative options.
In case you have no time to create a plot, you should speak to Nhlavutelo and Christian about your needs, and they'll create the plot for you.
In case you have the time to create a plot, you can come up with your (static) plot on your own machine. You don't need a web server for this, and brief instructions are given in the next section.
Once finished, you should send your shiny new plot file to Nhlavutelo and Christian.
Please make sure you are using Python 3 before you start creating your plot. Bokeh might require the latest version, 3.5 at the time of writing. An easy way to get Python 3 with all the necessary libraries is to install Anaconda.
If you are using Anaconda, you can install Bokeh by means of its conda command.
conda install bokeh
Otherwise you can use pip (preferably in a virtual environment).
pip install numpy
pip install bokeh
To test the Bokeh installation, create and run a Python file with the following content.
import math
import numpy as np
from bokeh.plotting import figure, output_file, show
output_file('output.html')
x = np.linspace(0, 2 * math.pi)
y = np.sin(x)
p = figure(title='Sine')
p.line(x, y)
show(p)
In case you are running your code in a Jupyter notebook, you should use the function output_notebook
instead of output_file
.
A good introduction to Bokeh is provided by the user guide on the Bokeh website.