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:
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:
conda install -c bokeh 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:
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/0.12.1
Questions can be directed to the Bokeh mailing list: email@example.com or the Gitter Chat room: https://gitter.im/bokeh/bokeh
Bryan Van de Ven Continuum Analytics
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.