On behalf of the Bokeh team, I am excited to announce the release of version 0.11 of Bokeh.
Bokeh Version 0.11 is a large release with *many* new improvements. The major focus of this release was to introduce a new Bokeh server, based on Tornado and websockets that is more stable, has higher performance, and simpler to use and deploy. You can already see a small sample of hosted Bokeh application examples at a new site located here:
We will be adding many new examples here over the coming weeks.
There is so much exciting in this release, that we will need a few blog posts to talk about everything. Keep an eye on our Twitter @BokehPlots or the mailing list for upcoming blog announcements. Some of the highlights from this release are:
* New Bokeh Server based on Tornado and websockets - highly expanded documentation, with examples and guidance for usage * User-Defined Models allowing anyone to extend Bokeh * Significant GIS features and improvements - Support for Stamen, OpenStreetMap, and other tile sources - GeoJSON data source - Patches with holes * WebGL support for rendering lines * Python -> JS compilation for CustomJS callbacks (Py3 only for now) * New general push_notebook() based on Jupyter comms * Updates to charts, charts examples, and charts docs * UX improvements - configurable and "auto" range bounds - wheel zoom scroll capture turned off by default - easily set visual styling for highlighting hovered points - responsive improvements, maintain plot aspect and auto-resize
Nearly 400 issues and PRs were closed for the release! See the CHANGELOG for full details, and the release notes for known issues and any migration notes.
The next big feature we plan is to dramatically improve our layout options using PhosporJS, which is also the foundation of the new Jupyter Workbench project. We also plan to have several, more frequent point releases with smaller incremental improvements and fixes.
I'd also like to take the opportunity to thank all the Bokeh contributors, and especially new people who have helped greatly with this release: Havoc Pennington, Greg Nordin, and Christian Tremblay.
If you are using Anaconda/miniconda, you can install it with conda:
conda install bokeh
Alternatively, you can also install it with pip:
pip install bokeh
Issues, enhancement requests, and pull requests can be made on the Bokeh Github page: https://github.com/bokeh/bokeh
Full documentation is available at http://bokeh.pydata.org/en/0.11.0
Questions can be directed to the Bokeh mailing list: firstname.lastname@example.org
The Bokeh Team