We are excited to announce the release of version 0.5.1 of Bokeh, an interactive web plotting library for Python!
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
Get It Now!
If you are using Anaconda, you can install with conda:
conda install bokeh
Alternatively, you can install with pip:
pip install bokeh
In order to push features to users even faster there are also now periodic dev builds made available. See the Developer’s Guide for more details.
Additionally, BokehJS is also now installable with the Node Package Manager.
The release of Bokeh 0.6 is planned for August. Some notable features we intend to work on are:
- Dynamic and data-driven layout using the Kiwi.js constraint solver (work underway)
- More chart types (boxplot, violin, contour, etc.) and auto-faceting for bokeh.charts
- R and/or Matlab language bindings
- Polar coordinate systems
How to get involved
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]
- check out the script gallery
- and the nbviewer gallery
- go through the tutorial
- play with the source
- follow us on Twitter @bokehplots!
If you would like some help incorporating Bokeh into your Notebooks, apps, or dashboards, please send an email to [email protected] to inquire about Continuum’s training and consulting services – not just for Bokeh, but for anything in the full NumPy/SciPy/PyData stack.