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

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 using 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 checkout the Bokeh tutorial repository 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.

Support

Fiscal Support

The Bokeh project is grateful for individual contributions, as well as for present and past 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-3.8.0rc1.tar.gz (6.5 MB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

bokeh-3.8.0rc1-py3-none-any.whl (7.2 MB view details)

Uploaded Python 3

File details

Details for the file bokeh-3.8.0rc1.tar.gz.

File metadata

  • Download URL: bokeh-3.8.0rc1.tar.gz
  • Upload date:
  • Size: 6.5 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.10.18

File hashes

Hashes for bokeh-3.8.0rc1.tar.gz
Algorithm Hash digest
SHA256 9bb733839f15b0c142139f9b6cbafcd21c30b348700c0f6d7c891f880fee6629
MD5 fd9df07ce550562033f60abd6a5ca842
BLAKE2b-256 55c34b70852afe9671ba9b396a10b6112508816022baeeb6fb9c598479bc482d

See more details on using hashes here.

File details

Details for the file bokeh-3.8.0rc1-py3-none-any.whl.

File metadata

  • Download URL: bokeh-3.8.0rc1-py3-none-any.whl
  • Upload date:
  • Size: 7.2 MB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.10.18

File hashes

Hashes for bokeh-3.8.0rc1-py3-none-any.whl
Algorithm Hash digest
SHA256 fe398362b14147d54c459c869ed7e7ceab5e1b94a34e4ed55f0b2536dab5be4e
MD5 5f9cd036944133ca72c1bc513315cf8f
BLAKE2b-256 0cf739c31a7e2ae9ade769107b9e213c3553e7b16487671a6e3742f09238f5ab

See more details on using hashes here.

Supported by

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