ANN: Bokeh 0.12 Released

[Bryan Van de Ven]

Apologies, I neglected to include a project description:

"""
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.
"""

> On Jun 28, 2016, at 1:32 PM, Bryan Van de Ven <bryanv at continuum.io> wrote:
> 
> 
> Hi all,
> 
> On behalf of the Bokeh team, I am pleased to announce the release of version 0.12.0 of Bokeh!
> 
> This release was a major update, and was focused on areas of layout and styling, new JavaScript APIs for BokehJS, and improvements to the Bokeh Server. But there were many additional improvements in other areas as well. Rather than try to describe all the changes here, I encourage every one to check out the new project blog:
> 
> 	https://bokeh.github.io/blog/2016/6/28/release-0-12/
> 
> which has details 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:
> 
> 	conda install bokeh
> 
> Alternatively, you can also install it with pip:
> 
> 	pip install bokeh
> 
> Full information including details about how to use and obtain BokehJS are at:
> 
> 	http://bokeh.pydata.org/en/0.12.0/docs/installation.html
> 
> Issues, enhancement requests, and pull requests can be made on the Bokeh Github page: https://github.com/bokeh/bokeh
> 
> Documentation is available at http://bokeh.pydata.org/en/0.12.0
> 
> Questions can be directed to the Bokeh mailing list: bokeh at continuum.io or the Gitter Chat room: https://gitter.im/bokeh/bokeh
> 
> Thanks,
> 
> Bryan Van de Ven
> Continuum Analytics