ANN: Bokeh 0.10.0 released!

[Damian Avila]

Hi all,

On behalf of the *Bokeh team*, I am excited to announce the release of
version *0.10.0* of *Bokeh*, an interactive web plotting library for
Python... and other languages!

This release was focused into provide several new features such as webgl
support, a new refactored and more powerful chart interface and responsive
plots. But we are also shipping a lot of bug-fixes and enhancements in our
documentation, testing and build machineries and examples.

Some of the highlights from this release are:

* Initial webgl support (check our new examples: maps city, iris blend,
scatter 10K, clustering.py)
* New charts interface supporting aggregation (see our new Bars, BoxPlot,
Histogram and Scatter examples)
* Responsive plots
* Lower-level jsresources & cssresources (allow more subtle uses of
resources)
* Several test machinery fixes
* Several build machinery enhancements
* More pytest-related fixes and enhancements
* More docs fixes and enhancements
* Now the glyph methods return the glyph renderer (not the plot)
* Gmap points moves consistently
* Added alpha control for imageurl objects
* Removed python33 testing and packaging
* Removed multiuserblazeserver

See the CHANGELOG <https://github.com/bokeh/bokeh/blob/master/CHANGELOG>
for full details.

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

    *conda install bokeh*

or directly from our Anaconda Cloud main channel with:

    *conda install -c bokeh bokeh*

Alternatively, you can also install it with pip:

    *pip install bokeh*

If you want to use *Bokeh* in standalone Javascript applications, *BokehJS*
is available by CDN at:

* http://cdn.pydata.org/bokeh/release/bokeh-0.10.0.min.js
* http://cdn.pydata.org/bokeh/release/bokeh-0.10.0.min.css

Additionally, *BokehJS* is also installable with the Node Package Manager
at https://www.npmjs.com/package/bokehjs

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/0.10.0

Questions can be directed to the *Bokeh* mailing list: bokeh at continuum.io

We also have a new "*general*" channel available at Slack:
https://bokehplots.slack.com/
*Note*: This is an *unsupported* place where users can congregate and
self-support or share experiences.
The *supported* place by default is the Bokeh mailing list.

Cheers.

-- 

*Damián Avila*
*Software Developer*



*@damian_avila*
*davila at continuum.io <davila at continuum.io>*

*+5492215345134 | cell (ARG)*