Bokeh
Python library for interactive plots and data applications that render in web browsers.
Bokeh is a Python library for interactive plots and data applications. Its output is HTML that a web browser runs, whether as static files, as embedded pages or in Jupyter notebooks, and the Bokeh server runs Python code in a server process that serves interactive applications to browsers. The library is installed with pip or conda.
The project’s homepage describes it as a Python library for plots and data applications in modern web browsers. The project is fiscally sponsored by NumFOCUS.
Worth knowing
A static Bokeh page needs only a web server that serves files. An application built on the Bokeh server needs a Python process that stays running, and the deployment guide describes running several server processes.
Identity
Rendering and deploy
- Runs as
- Always on7
- Rendering
- Static output6
- Install with
- pip3
Releases
Adoption
Sources
- 2026-11-04: links, Categories
bokeh.org/ - 2026-11-04: links, Written in, GitHub stars
api.github.com/repos/bokeh/bokeh - 2026-11-04: links, Install with
raw.githubusercontent.com/bokeh/bokeh/branch-4.0/README.md - 2026-11-04: Maintainer, License, License model
raw.githubusercontent.com/bokeh/bokeh/branch-4.0/LICENSE.txt - 2026-11-04: Runtime, Minimum runtime
docs.bokeh.org/en/latest/docs/first_steps/installation.html - 2026-11-04: Rendering
docs.bokeh.org/en/latest/docs/user_guide/output.html - 2026-11-04: Runs as
docs.bokeh.org/en/latest/docs/user_guide/server/deploy.html - 2026-11-04: First release
api.github.com/repos/bokeh/bokeh/commits/0.0.1 - 2026-11-04: Current major version, Last release
pypi.org/pypi/bokeh/json - 2026-11-04: Contributors
api.github.com/repos/bokeh/bokeh/contributors?per_page=1