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| Started by | Bryan Van de Ven <bryanv@continuum.io> |
|---|---|
| First post | 2016-07-28 14:35 -0500 |
| Last post | 2016-07-28 14:35 -0500 |
| Articles | 1 — 1 participant |
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ANN: Bokeh 0.12.1 released Bryan Van de Ven <bryanv@continuum.io> - 2016-07-28 14:35 -0500
| From | Bryan Van de Ven <bryanv@continuum.io> |
|---|---|
| Date | 2016-07-28 14:35 -0500 |
| Subject | ANN: Bokeh 0.12.1 released |
| Message-ID | <mailman.23.1469793848.6033.python-announce-list@python.org> |
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: bokeh@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.
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