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What is Bokeh?

Bokeh is an interactive visualization library for modern web browsers. It provides elegant, concise construction of versatile graphics, and affords high-performance interactivity over large or streaming datasets.
Bokeh is a tool in the Charting Libraries category of a tech stack.
Bokeh is an open source tool with 15.7K GitHub stars and 3.8K GitHub forks. Here’s a link to Bokeh's open source repository on GitHub

Who uses Bokeh?

Companies
6 companies reportedly use Bokeh in their tech stacks, including Kinderboerderij het Gouden Gansje, IOTile Cloud, and Data_Analytics.

Developers
75 developers on StackShare have stated that they use Bokeh.

Bokeh Integrations

Python, React, NGINX, Bootstrap, and Django are some of the popular tools that integrate with Bokeh. Here's a list of all 9 tools that integrate with Bokeh.
Pros of Bokeh
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Beautiful Interactive charts in seconds
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Decisions about Bokeh

Here are some stack decisions, common use cases and reviews by companies and developers who chose Bokeh in their tech stack.

Shared insights
on
MatplotlibMatplotlibBokehBokehDjangoDjango

Hi - I am looking to develop an app accessed by a browser that will display interactive networks (including adding or deleting nodes, edges, labels (or changing labels) based on user input. Look to use Django at the backend. Also need to manage graph versions if one person makes a graph change while another person is looking at it. Mainly tree networks for starters anyway. I probably will use the Networkx package. Not sure what the pros and cons are using Bokeh vs Matplotlib. I would be grateful for any comments or suggestions. Thanks.

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Bokeh's Features

  • interactive visualization library
  • versatile graphics
  • open source
  • https://github.com/bokeh/bokeh

Bokeh Alternatives & Comparisons

What are some alternatives to Bokeh?
Plotly.js
It is a standalone Javascript data visualization library, and it also powers the Python and R modules named plotly in those respective ecosystems (referred to as Plotly.py and Plotly.R). It can be used to produce dozens of chart types and visualizations, including statistical charts, 3D graphs, scientific charts, SVG and tile maps, financial charts and more.
Matplotlib
It is a Python 2D plotting library which produces publication quality figures in a variety of hardcopy formats and interactive environments across platforms. It can be used in Python scripts, the Python and IPython shells, the Jupyter notebook, web application servers, and four graphical user interface toolkits.
Dash
Dash is an API Documentation Browser and Code Snippet Manager. Dash stores snippets of code and instantly searches offline documentation sets for 150+ APIs. You can even generate your own docsets or request docsets to be included.
D3.js
It is a JavaScript library for manipulating documents based on data. Emphasises on web standards gives you the full capabilities of modern browsers without tying yourself to a proprietary framework.
Tableau
Tableau can help anyone see and understand their data. Connect to almost any database, drag and drop to create visualizations, and share with a click.
See all alternatives

Bokeh's Followers
142 developers follow Bokeh to keep up with related blogs and decisions.