# bokeh
**Repository Path**: mirrors/bokeh
## Basic Information
- **Project Name**: bokeh
- **Description**: Interactive Data Visualization in the browser, from Python
- **Primary Language**: Unknown
- **License**: BSD-3-Clause
- **Default Branch**: branch-3.9
- **Homepage**: None
- **GVP Project**: No
## Statistics
- **Stars**: 15
- **Forks**: 0
- **Created**: 2017-04-02
- **Last Updated**: 2026-02-14
## Categories & Tags
**Categories**: Uncategorized
**Tags**: None
## README
----
[Bokeh](https://bokeh.org) 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
Project
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Community
*Consider [making a donation](https://opencollective.com/bokeh) if you enjoy using Bokeh and want to support its development.*

## 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](https://docs.bokeh.org/en/latest/docs/first_steps/installation.html) for more details.
## Resources
Once Bokeh is installed, check out the [first steps guides](https://docs.bokeh.org/en/latest/docs/first_steps.html#first-steps-guides).
Visit the [full documentation site](https://docs.bokeh.org) to view the [User's Guide](https://docs.bokeh.org/en/latest/docs/user_guide.html) or [checkout the Bokeh tutorial repository](https://github.com/bokeh/tutorial/) to learn about Bokeh in live Jupyter Notebooks.
Community support is available on the [Project Discourse](https://discourse.bokeh.org).
If you would like to contribute to Bokeh, please review the [Contributor Guide](https://docs.bokeh.org/en/latest/docs/dev_guide.html) and [request an invitation to the Bokeh Dev Slack workspace](https://slack-invite.bokeh.org/).
*Note: Everyone who engages in the Bokeh project's discussion forums, codebases, and issue trackers is expected to follow the [Code of Conduct](https://github.com/bokeh/bokeh/blob/HEAD/docs/CODE_OF_CONDUCT.md).*
## Support
### Fiscal Support
The Bokeh project is grateful for [individual contributions](https://opencollective.com/bokeh), as well as for present and past monetary support from the organizations and companies listed 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](https://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:
* [Amazon Web Services](https://aws.amazon.com/)
* [GitGuardian](https://gitguardian.com/)
* [GitHub](https://github.com/)
* [makepath](https://makepath.com/)
* [Pingdom](https://www.pingdom.com/website-monitoring)
* [Slack](https://slack.com)
* [QuestionScout](https://www.questionscout.com/)
* [1Password](https://1password.com/)
* [Digital Ocean](https://www.digitalocean.com)