# Bokeh

> Interactive Web Plotting for Python.

- Category: [Python data visualization libraries](https://awesomedataviz.com/categories/python/)
- Website: https://bokeh.org/
- Repository: https://github.com/bokeh/bokeh
- License: BSD-3-Clause
- Language: TypeScript
- Status: Active (commits in the last 90 days)
- GitHub stars: 20,455
- Commits in the last 12 months: 344
- Contributors: 389
- Last commit: Oct 3, 2026
- Install (PyPI): `pip install bokeh`, 1.3M downloads per week
- Topics: Jupyter & notebook visualization

## Overview

Bokeh is an open-source Python visualization library released under the BSD-3-Clause license. Its GitHub repository has 20,455 stars, 4,265 forks, and 389 contributors. It is actively developed with 344 commits in the last 12 months. On PyPI it is downloaded about 1.3M times per week.

## Alternatives

- [Streamlit](https://awesomedataviz.com/tools/streamlit/): Framework for turning Python scripts into interactive data apps. (45.9K stars)
- [Dash](https://awesomedataviz.com/tools/dash/): Framework for building data apps and dashboards in Python, built on Plotly.js and React. (24.4K stars)
- [Matplotlib](https://awesomedataviz.com/tools/matplotlib/): 2D plotting library. (23.3K stars)
- [Taipy](https://awesomedataviz.com/tools/taipy/): Python framework for building data and AI web applications with interactive charts and dashboards. (19.4K stars)
- [Plotly (Python)](https://awesomedataviz.com/tools/plotly-python/): Interactive web based visualization built on top of plotly.js (18.8K stars)
- [PyGWalker](https://awesomedataviz.com/tools/pygwalker/): Turns dataframes into a drag-and-drop visual analysis UI in Jupyter, based on Graphic Walker. (16K stars)

## Comparisons

- [Bokeh vs Streamlit](https://awesomedataviz.com/compare/bokeh-vs-streamlit/)
- [Bokeh vs Dash](https://awesomedataviz.com/compare/bokeh-vs-dash/)
- [Bokeh vs Matplotlib](https://awesomedataviz.com/compare/bokeh-vs-matplotlib/)
- [Bokeh vs Taipy](https://awesomedataviz.com/compare/bokeh-vs-taipy/)

Source: https://awesomedataviz.com/tools/bokeh/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com).