# ANN: Bokeh 0.12.1 released

**URL:** <https://discourse.bokeh.org/t/ann-bokeh-0-12-1-released/1421>\
**Category:** Community Support\
**Created:** [July 28, 2016, 7:35pm UTC](https://discourse.bokeh.org/t/ann-bokeh-0-12-1-released/1421 "2016-07-28T19:35:47Z")\
**Posts on this page:** 2\
**Page:** 1

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**Author:** ![Bryan](https://discourse.bokeh.org/user_avatar/discourse.bokeh.org/bryan/32/3625_2.png) [@Bryan](https://discourse.bokeh.org/u/Bryan)\
**Post date:** [July 28, 2016, 7:35pm UTC](https://discourse.bokeh.org/t/ann-bokeh-0-12-1-released/1421/1 "2016-07-28T19:35:47Z")

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Hi all,

On behalf of the Bokeh team, I am pleased to announce the release of version 0.12.1 of Bokeh!  
This is a minor, incremental update that adds a few new small features and fixes several bugs.  
Please see the announcement post at:

&nbsp;&nbsp;[https://bokeh.github.io/blog/2016/6/28/release-0-12-1/](https://bokeh.github.io/blog/2016/6/28/release-0-12-1/)

which has much more information as well as live demonstrations. And as always, see the CHANGELOG and Release Notes for full details.

If you are using Anaconda/miniconda, you can install it with conda:

&nbsp;&nbsp;conda install -c bokeh bokeh

Alternatively, you can also install it with pip:

&nbsp;&nbsp;pip install bokeh

Full information including details about how to use and obtain BokehJS are at:

&nbsp;&nbsp;[Installation — Bokeh 0.12.1 documentation](http://bokeh.pydata.org/en/0.12.1/docs/installation.html)

Issues, enhancement requests, and pull requests can be made on the Bokeh Github page: [GitHub - bokeh/bokeh: Interactive Data Visualization in the browser, from Python](https://github.com/bokeh/bokeh)

Documentation is available at [Welcome to Bokeh — Bokeh 0.12.1 documentation](http://bokeh.pydata.org/en/0.12.1)

Questions can be directed to the Bokeh mailing list: [bokeh@continuum.io](mailto:bokeh@continuum.io) or the Gitter Chat room: [https://gitter.im/bokeh/bokeh](https://gitter.im/bokeh/bokeh)

Thanks,

Bryan Van de Ven  
Continuum Analytics

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> Bokeh is a Python interactive visualization library that targets modern web browsers for presentation. Its goal is to provide elegant, concise construction of versatile graphics with high-performance interactivity over very large or streaming datasets. Bokeh can help anyone who would like to quickly and easily create interactive plots, dashboards, and data applications.

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**Author:** ![system](https://discourse-uploads.bokeh.org/original/2X/1/14eb24f9e10e4e9b78e3f10f66c04ffa96446e5a.svg) [@system](https://discourse.bokeh.org/u/system)\
**Post date:** [July 21, 2021, 9:09pm UTC](https://discourse.bokeh.org/t/ann-bokeh-0-12-1-released/1421/2 "2021-07-21T21:09:02Z")

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