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From: Bryan Van de Ven <bryanv@continuum.io>
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Subject: ANN: Bokeh 0.6 release
Date: Wed, 10 Sep 2014 08:05:10 -0500
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On behalf of the Bokeh team, I am very happy to announce the release of =
Bokeh version 0.6!

Bokeh is a Python library for visualizing large and realtime datasets on =
the web. Its goal is to provide to developers (and domain experts) with =
capabilities to easily create novel and powerful visualizations that =
extract insight from local or remote (possibly large) data sets, and to =
easily publish those visualization to the web for others to explore and =
interact with.

This release includes many bug fixes and improvements over our most =
recent 0.5.2 release:

  * Abstract Rendering recipes for large data sets: isocontour, heatmap
  * New charts in bokeh.charts: Time Series and Categorical Heatmap
  * Full Python 3 support for bokeh-server
  * Much expanded User and Dev Guides
  * Multiple axes and ranges capability
  * Plot object graph query interface
  * Hit-testing (hover tool support) for patch glyphs

See the CHANGELOG for full details.

I'd also like to announce a new Github Organization for Bokeh: =
https://github.com/bokeh. Currently it is home to Scala and and Julia =
language bindings for Bokeh, but the Bokeh project itself will be moved =
there before the next 0.7 release.  Any implementors of new language =
bindings who are interested in hosting your project under this =
organization are encouraged to contact us.

In upcoming releases, you should expect to see more new layout =
capabilities (colorbar axes, better grid plots and improved =
annotations), additional tools, even more widgets and more charts, R =
language bindings, Blaze integration and cloud hosting for Bokeh apps.

Don't forget to check out the full documentation, interactive gallery, =
and tutorial at

    http://bokeh.pydata.org

as well as the Bokeh IPython notebook nbviewer index (including all the =
tutorials) at:

    =
http://nbviewer.ipython.org/github/ContinuumIO/bokeh-notebooks/blob/master=
/index.ipynb

If you are using Anaconda, you can install with conda:

    conda install bokeh

Alternatively, you can install with pip:

    pip install bokeh

BokehJS is also available by CDN for use in standalone javascript =
applications:

    http://cdn.pydata.org/bokeh-0.6.min.js
    http://cdn.pydata.org/bokeh-0.6.min.css

Issues, enhancement requests, and pull requests can be made on the Bokeh =
Github page:=20

    https://github.com/continuumio/bokeh

Questions can be directed to the Bokeh mailing list: bokeh@continuum.io

If you have interest in helping to develop Bokeh, please get involved!

Thanks,

Bryan Van de Ven
Continuum Analytics
http://continuum.io=