We’re pleased to announced the release of version 0.2 of the Bokeh plotting library. We’ve made lots of progress since our v0.1 release: over 1,500 commits across two repositories. There is a ton of new functionality, improved and refactored architecture, and hopefully a much easier installation process for users. We’ve built Bokeh from the ground-up to be interactive in the browser, with many live examples in the gallery. You can click on the following thumbnails to see some of the interactive examples:

About Bokeh

Bokeh is an interactive web plotting system for visualizing large data. It uses HTML5 Canvas and Python, and has both a high-level interface to allow easy plotting, as well as a powerful low-level interface which is highly configurable.

We are still in the process of building out the “large data” backend pieces, but the frontend components are already useful for a wide variety of applications. One of the core differentiating aspects of Bokeh versus other web plotting technologies is that we have built a first-class Javascript runtime, BokehJS, which is designed from the start to be an interactive engine for “backend” models and state that are potentially controlled by some other language. The primary interface for this backend is currently Python, but we are very open to the idea of additional languages such as R, Ruby, Java, C++, etc. These simply have to generate very straightforward JSON models, which the BokehJS runtime then consumes and uses to produce rich plots.

For more information, visit the Bokeh website.

New Bokeh Website!

We have a new website bokeh.pydata.org, with installation instructions, a Quickstart, a gallery of live Bokeh examples, and more information about the motivations and vision behind Bokeh.

We’re actively working on adding more to the user and developer guides, but we didn’t want to hold up the release just to flesh those out.

More blog posts

Be sure to follow us on Twitter! We’ll be tweeting more tips and examples and blog posts as we produce them. For instance, we have two more blog posts in the pipeline: an end-to-end example of how to build a simple web dashboard with interactive plotting of streaming data from a web service, and an interactive Google Map viewer of geo data, embedded in an IPython Notebook. Stay tuned!

Coming up…

We are excited about the upcoming work in 0.3 and beyond. Besides adding richer interactions, better layout, and more examples showing the capabilities of having a first-class Javascript runtime, we will also be working hard to integrate Abstract Rendering into the server, as well as support for mobile devices and touch events.

See our Roadmap for more details.

Get Involved!

Sign up for our mailing list and follow @BokehPlots on Twitter!