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