Metadata-Version: 2.1 Name: bokeh Version: 2.4.2 Summary: Interactive plots and applications in the browser from Python Home-page: https://github.com/bokeh/bokeh Author: Bokeh Team Author-email: info@bokeh.org License: BSD-3-Clause Platform: UNKNOWN Classifier: Development Status :: 5 - Production/Stable Classifier: Environment :: Console Classifier: Environment :: Web Environment Classifier: Intended Audience :: Developers Classifier: Intended Audience :: Education Classifier: Intended Audience :: End Users/Desktop Classifier: Intended Audience :: Financial and Insurance Industry Classifier: Intended Audience :: Healthcare Industry Classifier: Intended Audience :: Information Technology Classifier: Intended Audience :: Legal Industry Classifier: Intended Audience :: Other Audience Classifier: Intended Audience :: Science/Research Classifier: License :: OSI Approved :: BSD License Classifier: Programming Language :: Python Classifier: Programming Language :: Python :: 3 Classifier: Programming Language :: Python :: 3 :: Only Classifier: Programming Language :: Python :: 3.7 Classifier: Programming Language :: Python :: 3.8 Classifier: Programming Language :: Python :: 3.9 Classifier: Programming Language :: JavaScript Classifier: Topic :: Office/Business Classifier: Topic :: Office/Business :: Financial Classifier: Topic :: Scientific/Engineering Classifier: Topic :: Scientific/Engineering :: Visualization Classifier: Topic :: Scientific/Engineering :: Mathematics Classifier: Topic :: Scientific/Engineering :: Information Analysis Classifier: Topic :: Utilities Requires-Python: >=3.7 Description-Content-Type: text/markdown License-File: LICENSE.txt Requires-Dist: Jinja2 (>=2.9) Requires-Dist: numpy (>=1.11.3) Requires-Dist: packaging (>=16.8) Requires-Dist: pillow (>=7.1.0) Requires-Dist: PyYAML (>=3.10) Requires-Dist: tornado (>=5.1) Requires-Dist: typing-extensions (>=3.10.0) Bokeh logotype ---- [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 over large or streaming datasets. Bokeh can help anyone who would like to quickly and easily make interactive plots, dashboards, and data applications.
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Language grade: Python
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*If you like Bokeh and would like to support our mission, please consider [making a donation](https://numfocus.org/donate-to-bokeh).*

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stacked bars plot thumbnail quiver plot thumbnail elements data plot thumbnail boxplot thumbnail categorical plot thumbnail unemployment data plot thumbnail Les Mis co-occurrence plot thumbnail

## Installation The easiest way to install Bokeh is using the [Anaconda Python distribution](https://www.anaconda.com/what-is-anaconda/) 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](https://docs.bokeh.org/en/latest/docs/first_steps/installation.html). ## 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/dev/docs/user_guide.html) or [launch the Bokeh tutorial](https://mybinder.org/v2/gh/bokeh/bokeh-notebooks/master?filepath=tutorial%2F00%20-%20Introduction%20and%20Setup.ipynb) 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 interacting in the Bokeh project's codebases, issue trackers and discussion forums is expected to follow the [Code of Conduct](https://github.com/bokeh/bokeh/blob/master/CODE_OF_CONDUCT.md).* ## Follow us Follow us on Twitter [@bokeh](https://twitter.com/bokeh) ## Support ### Fiscal Support The Bokeh project is grateful for [individual contributions](https://numfocus.org/donate-to-bokeh) sponsorship as well as support by the organizations and companies below:
NumFocus Logo CZI Logo Quansight 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](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 The Bokeh project is also grateful for the donation of services from the following companies: * [Amazon Web Services](https://aws.amazon.com/) * [GitGuardian](https://gitguardian.com/) * [GitHub](https://github.com/) * [Pingdom](https://www.pingdom.com/website-monitoring) * [Slack](https://slack.com) * [QuestionScout](https://www.questionscout.com/) * [1Password](https://1password.com/) ## Security To report a security vulnerability, please use the [Tidelift security contact](https://tidelift.com/security). Tidelift will coordinate the fix and disclosure.