Skip to main content

Interactive plots and applications in the browser from Python

Project description


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 can help anyone who would like to quickly and easily make interactive plots, dashboards, and data applications.

If you like Bokeh and would like to support our mission, please consider making a donation.

Installation

The easiest way to install Bokeh is using the Anaconda Python distribution and its included Conda package management system. To install Bokeh and its required dependencies, enter the following command at a Bash or Windows command prompt:

conda install bokeh

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

pip install bokeh

For more information, refer to the installation documentation.

Resources

Once Bokeh is installed, check out the Getting Started section of the Quickstart guide.

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 Developer Guide and request an invitation to the Bokeh Dev Slack workspace.

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

Follow us

Follow us on Twitter @bokeh

Sponsors

Fiscal Sponsors

The Bokeh project is grateful for individual contributions as well as sponsorship by the organizations and companies below:

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 Sponsors

The Bokeh project is also grateful for the donation of services from the following companies:

Security

To report a security vulnerability, please use the Tidelift security contact. Tidelift will coordinate the fix and disclosure.

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.

Files for bokeh, version 2.2.2
Filename, size File type Python version Upload date Hashes
Filename, size bokeh-2.2.2.tar.gz (8.8 MB) File type Source Python version None Upload date Hashes View

Supported by

Pingdom Pingdom Monitoring Google Google Object Storage and Download Analytics Sentry Sentry Error logging AWS AWS Cloud computing DataDog DataDog Monitoring Fastly Fastly CDN DigiCert DigiCert EV certificate StatusPage StatusPage Status page