Skip to main content

Interactive plots and applications in the browser from Python

Project description

Bokeh logo -- text is white in dark theme and black in light theme

Bokeh is an interactive visualization library for modern web browsers. It provides elegant, concise construction of versatile graphics and affords high-performance interactivity across large or streaming datasets. Bokeh can help anyone who wants to create interactive plots, dashboards, and data applications quickly and easily.

Package Latest package version Supported Python versions Bokeh license (BSD 3-clause)
Project Github contributors Link to NumFOCUS Link to documentation
Downloads PyPI downloads per month Conda downloads per month NPM downloads per month
Build Current Bokeh-CI github actions build status Current BokehJS-CI github actions build status Codecov coverage percentage
Community Community support on discourse.bokeh.org Bokeh-tagged questions on Stack Overflow Follow Bokeh on Twitter

Consider making a donation if you enjoy using Bokeh and want to support its development.

4x9 image grid of Bokeh plots

Installation

To install Bokeh and its required dependencies using pip, enter the following command at a Bash or Windows command prompt:

pip install bokeh

To install conda, enter the following command at a Bash or Windows command prompt:

conda install bokeh

Refer to the installation documentation for more details.

Resources

Once Bokeh is installed, check out the first steps guides.

Visit the full documentation site to view the User's Guide or launch the Bokeh tutorial to learn about Bokeh in live Jupyter Notebooks.

Community support is available on the Project Discourse.

If you would like to contribute to Bokeh, please review the Contributor Guide and request an invitation to the Bokeh Dev Slack workspace.

Note: Everyone who engages in the Bokeh project's discussion forums, codebases, and issue trackers is expected to follow the Code of Conduct.

Follow us

Follow us on Twitter @bokeh

Support

Fiscal Support

The Bokeh project is grateful for individual contributions, as well as for monetary support from the organizations and companies listed below:

NumFocus Logo CZI Logo Blackstone Logo
TideLift Logo Anaconda Logo NVidia Logo Rapids Logo

If your company uses Bokeh and is able to sponsor the project, please contact info@bokeh.org

Bokeh is a Sponsored Project of NumFOCUS, a 501(c)(3) nonprofit charity in the United States. NumFOCUS provides Bokeh with fiscal, legal, and administrative support to help ensure the health and sustainability of the project. Visit numfocus.org for more information.

Donations to Bokeh are managed by NumFOCUS. For donors in the United States, your gift is tax-deductible to the extent provided by law. As with any donation, you should consult with your tax adviser about your particular tax situation.

In-kind Support

Non-monetary support can help with development, collaboration, infrastructure, security, and vulnerability management. The Bokeh project is grateful to the following companies for their donation of services:

Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

bokeh-3.4.0.tar.gz (6.4 MB view hashes)

Uploaded source

Built Distribution

bokeh-3.4.0-py3-none-any.whl (7.0 MB view hashes)

Uploaded py3

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page