On behalf of the Bokeh team, I am very happy to announce the release of Bokeh version 0.7!
Bokeh is a Python library for visualizing large and realtime datasets on the web. Its goal is to provide to developers (and domain experts) with capabilities to easily create novel and powerful visualizations that extract insight from local or remote (possibly large) data sets, and to easily publish those visualization to the web for others to explore and interact with. This release includes many major new features: * IPython widgets and animations without a Bokeh server * Touch UI working for tools on mobile devices * Vastly improved linked data table * More new (and improving) bokeh.charts (high level charting interface) * Color mappers on the python side * Improved toolbar * Many new tools: lasso, poly, and point selection, crosshair inspector Check our blog post: http://continuum.io/blog/bokeh-0.7, to watch some of these tools in action! And you can also see the CHANGELOG for full details. We would like to mention that the Github Organization for Bokeh is growing! This organization was already home to bokeh-scala and bokeh.jl, and now the Bokeh project itself has a new home there as well, located at https://github.com/bokeh/bokeh. Anyone interested in developing new language bindings for Bokeh is encouraged to contact us about hosting your project under this organization. Also, the release of Bokeh 0.8 should happen in early 2015. Some notable features we intend to work on are: * Simplifying production and multi-user Bokeh server deployments * Colorbar axis and axis location inspectors * Better support for maps and projections As usual, don't forget to check out the full documentation, interactive gallery, and tutorial at http://bokeh.pydata.org as well as the Bokeh IPython notebook nbviewer index (including all the tutorials) at: http://nbviewer.ipython.org/github/bokeh/bokeh-notebooks/blob/master/index.ipynb To install the latest release, if you are using Anaconda, you can install it with conda: conda install bokeh Alternatively, you can install it with pip: pip install bokeh BokehJS is also available by CDN for use in standalone Javascript applications: http://cdn.pydata.org/bokeh-0.7.0.min.js http://cdn.pydata.org/bokeh-0.7.0.min.css Finally, BokehJS is also installable with the Node Package Manager. 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: bo...@continuum.io Thank you for your attention! Damián -- https://mail.python.org/mailman/listinfo/python-announce-list Support the Python Software Foundation: http://www.python.org/psf/donations/
