ANN: Bokeh 0.5.1 released

On behalf of the Bokeh team, I am very happy to announce the release of Bokeh version 0.5.1! (http://continuum.io/blog/bokeh-0.5.1)

Bokeh is a Python library for visualizing large and realtime datasets on the web.

This release includes many bug fixes and improvements over our last recent 0.5 release:

  • Hover activated by default

  • Boxplot in bokeh.charts

  • Better messages when you forget to start the bokeh-server

  • Fixed some packaging bugs

  • Fixed NBviewer rendering

  • Fixed some Unicodeencodeerror

See the CHANGELOG for full details.

In upcoming releases, you should expect to see dynamic, data-driven layouts (including ggplot-style auto-faceting), as well as R language bindings, more statistical plot types in bokeh.charts, and cloud hosting for Bokeh apps.

Don’t forget to check out the full documentation, interactive gallery, and tutorial at

[http://bokeh.pydata.org](http://bokeh.pydata.org/)

as well as the new Bokeh IPython notebook nbviewer index (including all the tutorials) at:

[http://nbviewer.ipython.org/github/ContinuumIO/bokeh-notebooks/blob/master/index.ipynb](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-0.5.1.min.js](http://cdn.pydata.org/bokeh-0.5.min.js)

[http://cdn.pydata.org/bokeh-0.5.1.min.css](http://cdn.pydata.org/bokeh-0.5.min.css)

Issues, enhancement requests, and pull requests can be made on the Bokeh Github page: https://github.com/continuumio/bokeh

Questions can be directed to the Bokeh mailing list: [email protected]

If you have interest in helping to develop Bokeh, please get involved!

Damián.