ANN: Bokeh 0.9.1 released

[Damian Avila]

Hi all,

On behalf of the Bokeh team, I am excited to announce the release of
version 0.9.1 of Bokeh, an interactive web plotting library for Python...
and other languages!

This release focused on extending Bokeh’s new callback system by adding
more places where callbacks can be used, expanding and improving the new
User’s Guide, exposing better ways to embed Bokeh plots and widgets into
your own layouts, and providing validation error and warning feedback to
diagnose problems.

Some of the highlights are:

* New callbacks options for hover, selection, and range updates
* Documentation for widgets and new callbacks in the User’s Guide
* Much more flexible embed.components that can embed multiple objects
* Implemented a validation framework to provide errors and warnings
* More than 30 smaller bugfixes

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 Binstar 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-0.9.1.min.js
* http://cdn.pydata.org/bokeh/release/bokeh-0.9.1.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

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

Cheers.

-- 
*Damián Avila*
*Continuum Analytics*
*damian.avila at continuum.io <damian.avila at continuum.io>*