Bryan Van de Ven
2016-07-28 19:35:52 UTC
Hi all,
On behalf of the Bokeh team, I am pleased to announce the release of version 0.12.1 of Bokeh!
This is a minor, incremental update that adds a few new small features and fixes several bugs.
Please see the announcement post at:
https://bokeh.github.io/blog/2016/6/28/release-0-12-1/
which has much more information as well as live demonstrations. And as always, see the CHANGELOG and Release Notes for full details.
If you are using Anaconda/miniconda, you can install it with conda:
conda install -c bokeh bokeh
Alternatively, you can also install it with pip:
pip install bokeh
Full information including details about how to use and obtain BokehJS are at:
http://bokeh.pydata.org/en/0.12.1/docs/installation.html
Issues, enhancement requests, and pull requests can be made on the Bokeh Github page: https://github.com/bokeh/bokeh
Documentation is available at http://bokeh.pydata.org/en/0.12.1
Questions can be directed to the Bokeh mailing list: ***@continuum.io or the Gitter Chat room: https://gitter.im/bokeh/bokeh
Thanks,
Bryan Van de Ven
Continuum Analytics
-----
Bokeh is a Python interactive visualization library that targets modern web browsers for presentation. Its goal is to provide elegant, concise construction of versatile graphics with high-performance interactivity over very large or streaming datasets. Bokeh can help anyone who would like to quickly and easily create interactive plots, dashboards, and data applications.
On behalf of the Bokeh team, I am pleased to announce the release of version 0.12.1 of Bokeh!
This is a minor, incremental update that adds a few new small features and fixes several bugs.
Please see the announcement post at:
https://bokeh.github.io/blog/2016/6/28/release-0-12-1/
which has much more information as well as live demonstrations. And as always, see the CHANGELOG and Release Notes for full details.
If you are using Anaconda/miniconda, you can install it with conda:
conda install -c bokeh bokeh
Alternatively, you can also install it with pip:
pip install bokeh
Full information including details about how to use and obtain BokehJS are at:
http://bokeh.pydata.org/en/0.12.1/docs/installation.html
Issues, enhancement requests, and pull requests can be made on the Bokeh Github page: https://github.com/bokeh/bokeh
Documentation is available at http://bokeh.pydata.org/en/0.12.1
Questions can be directed to the Bokeh mailing list: ***@continuum.io or the Gitter Chat room: https://gitter.im/bokeh/bokeh
Thanks,
Bryan Van de Ven
Continuum Analytics
-----
Bokeh is a Python interactive visualization library that targets modern web browsers for presentation. Its goal is to provide elegant, concise construction of versatile graphics with high-performance interactivity over very large or streaming datasets. Bokeh can help anyone who would like to quickly and easily create interactive plots, dashboards, and data applications.