Bokeh and how to make it into a GUI

Question

I am writing in python and have all my functionalities for analyzing datasets. Now, I would like to turn these functions into a user-ready application that, in a sense, works like an .exe app. In bokeh, I saw that you could create a plot, table...etc; however, is it possible to create a GUI where you can:

1. upload a file for analysis
2. load functions from my written python to analyze the uploaded file
3. graph the results onto a graph
4. click different buttons that can take you to different (so-called) pages so that you can perform different functions.

basically it can go from one page to the other kind of like a webpage where you click one button it links you to the next page for another purpose and home to go back. Could you potentially do this with bokeh?

Answer 1

There are several examples of data web applications created using Bokeh at demo.bokeh.org. Here is one modeled after the "Shiny Movie Explorer", but written in pure Python/Bokeh (instead of R/Shiny).

You can find much more details about creating and deploying Bokeh applications in the Running a Bokeh Server chapter of the docs.

Here is a complete (but simpler) example that demonstrates the basic gist and structure:

import numpy as np

from bokeh.io import curdoc
from bokeh.layouts import column
from bokeh.models import ColumnDataSource, Slider
from bokeh.plotting import figure

# Set up data
x = np.linspace(0, 4*np.pi, 200)
y = np.sin(x)
source = ColumnDataSource(data=dict(x=x, y=y))

# Set up plot
plot = figure(title="my sine wave")
plot.line('x', 'y', source=source, line_width=3, line_alpha=0.6)

# Set up widgets
freq = Slider(title="frequency", value=1.0, start=0.1, end=5.1, step=0.1)


# Set up callbacks
def update_data(attrname, old, new):

    # Get the current slider values and set new data
    k = freq.value
    x = np.linspace(0, 4*np.pi, 200)
    y = np.sin(k*x)
    source.data = dict(x=x, y=y)

freq.on_change('value', update_data)

# Set up layouts and add to document    
curdoc().add_root(column(freq, plot))
curdoc().title = "Sliders"

To run this locally you'd execute:

bokeh serve --show myscript.py

For more sophisticated deployments (i.e. with proxies) or to embed directly in e.g. Flask, see the docs.