- Bokeh Tutorial
- Bokeh - Home
- Bokeh - Introduction
- Bokeh - Environment Setup
- Bokeh - Getting Started
- Bokeh - Jupyter Notebook
- Bokeh - Basic Concepts
- Bokeh - Plots with Glyphs
- Bokeh - Area Plots
- Bokeh - Circle Glyphs
- Bokeh - Rectangle, Oval and Polygon
- Bokeh - Wedges and Arcs
- Bokeh - Specialized Curves
- Bokeh - Setting Ranges
- Bokeh - Axes
- Bokeh - Annotations and Legends
- Bokeh - Pandas
- Bokeh - ColumnDataSource
- Bokeh - Filtering Data
- Bokeh - Layouts
- Bokeh - Plot Tools
- Bokeh - Styling Visual Attributes
- Bokeh - Customising legends
- Bokeh - Adding Widgets
- Bokeh - Server
- Bokeh - Using Bokeh Subcommands
- Bokeh - Exporting Plots
- Bokeh - Embedding Plots and Apps
- Bokeh - Extending Bokeh
- Bokeh - WebGL
- Bokeh - Developing with JavaScript
- Bokeh Useful Resources
- Bokeh - Quick Guide
- Bokeh - Useful Resources
- Bokeh - Discussion
Bokeh - Server
Bokeh architecture has a decouple design in which objects such as plots and glyphs are created using Python and converted in JSON to be consumed by BokehJS client library.
However, it is possible to keep the objects in python and in the browser in sync with one another with the help of Bokeh Server. It enables response to User Interface (UI) events generated in a browser with the full power of python. It also helps automatically push server-side updates to the widgets or plots in a browser.
A Bokeh server uses Application code written in Python to create Bokeh Documents. Every new connection from a client browser results in the Bokeh server creating a new document, just for that session.
First, we have to develop an application code to be served to client browser. Following code renders a sine wave line glyph. Along with the plot, a slider control is also rendered to control the frequency of sine wave. The callback function update_data() updates ColumnDataSource data taking the instantaneous value of slider as current frequency.
import numpy as np from bokeh.io import curdoc from bokeh.layouts import row, column from bokeh.models import ColumnDataSource from bokeh.models.widgets import Slider, TextInput from bokeh.plotting import figure N = 200 x = np.linspace(0, 4*np.pi, N) y = np.sin(x) source = ColumnDataSource(data = dict(x = x, y = y)) plot = figure(plot_height = 400, plot_width = 400, title = "sine wave") plot.line('x', 'y', source = source, line_width = 3, line_alpha = 0.6) freq = Slider(title = "frequency", value = 1.0, start = 0.1, end = 5.1, step = 0.1) def update_data(attrname, old, new): a = 1 b = 0 w = 0 k = freq.value x = np.linspace(0, 4*np.pi, N) y = a*np.sin(k*x + w) + b source.data = dict(x = x, y = y) freq.on_change('value', update_data) curdoc().add_root(row(freq, plot, width = 500)) curdoc().title = "Sliders"
Next, start Bokeh server by following command line −
Bokeh serve –show sliders.py
Bokeh server starts running and serving the application at localhost:5006/sliders. The console log shows the following display −
C:\Users\User>bokeh serve --show scripts\sliders.py 2019-09-29 00:21:35,855 Starting Bokeh server version 1.3.4 (running on Tornado 6.0.3) 2019-09-29 00:21:35,875 Bokeh app running at: http://localhost:5006/sliders 2019-09-29 00:21:35,875 Starting Bokeh server with process id: 3776 2019-09-29 00:21:37,330 200 GET /sliders (::1) 699.99ms 2019-09-29 00:21:38,033 101 GET /sliders/ws?bokeh-protocol-version=1.0&bokeh-session-id=VDxLKOzI5Ppl9kDvEMRzZgDVyqnXzvDWsAO21bRCKRZZ (::1) 4.00ms 2019-09-29 00:21:38,045 WebSocket connection opened 2019-09-29 00:21:38,049 ServerConnection created
Open your favourite browser and enter above address. The Sine wave plot is displayed as follows −
You can try and change the frequency to 2 by rolling the slider.