On behalf of the Bokeh team, I am very happy to announce the release of Bokeh version 0.6.1! 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 point release includes several bug fixes and improvements over our most recent 0.6.0 release: * Toolbar enhancements * bokeh-server fixes * Improved documentation * Button widgets * Google map support in the Python side * Code cleanup in the JS side and examples * New examples See the CHANGELOG for full details. In upcoming releases, you should expect to see more new layout capabilities (colorbar axes, better grid plots and improved annotations), additional tools, even more widgets and more charts, R language bindings, Blaze integration and cloud hosting for Bokeh apps. 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/ContinuumIO/bokeh-notebooks/blob/master/i... If you are using Anaconda or miniconda, you can install with conda: conda install bokeh Alternatively, you can install with pip: pip install bokeh BokehJS is also available by CDN for use in standalone javascript applications: http://cdn.pydata.org/bokeh-0.6.1.min.js http://cdn.pydata.org/bokeh-0.6.1.min.css 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: bokeh@continuum.io If you have interest in helping to develop Bokeh, please get involved! Cheers, Damián Avila damian.avila@continuum.io
Congrats on the release. I've been playing with Bokeh the last couple weeks and it's really good. There was some talk about expanding the ecosystem page http://pandas.pydata.org/pandas-docs/stable/ecosystem.html in the pandas docs to show off brief examples for the various projects (btw I think we should rename that to **pydata** ecosystem, instead of pandas ecosystem). Would you say the API for something like a ColumnDataSource example (like the car example http://bokeh.pydata.org/tutorial/solutions/gallery/brushing.html) is stable enough to include in our docs?
Hi Tom,
I would wait for 0.7, where we are going to make a few changes to the plotting.py interface. That API started out as a "stateful, implicit current plot" style interface, and experience has shown that this does not always work well, especially in the IPython notebook where you can have any order of execution of the cells. It basically not possible to reason about which plot is the "current plot" and we got lots of support issues around this. The interface is not changing drastically, but it is changing some. Basically instead of "line(...)" acting on some implicit plot, you will have "p.line(...)" acting on some explicitly specified plot "p". Currently 0.7 looks to be release late October/early November, all the examples will be updated at that time, and I would not expect that API to change any time soon after.
Bryan
On Sep 26, 2014, at 9:22 AM, Tom Augspurger
Congrats on the release. I've been playing with Bokeh the last couple weeks and it's really good.
There was some talk about expanding the ecosystem page in the pandas docs to show off brief examples for the various projects (btw I think we should rename that to **pydata** ecosystem, instead of pandas ecosystem).
Would you say the API for something like a ColumnDataSource example (like the car example) is stable enough to include in our docs? _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Hi Damian, how you doing? The IPy nb Link is broken... =/ Cheers, Arnaldo. Em sexta-feira, 26 de setembro de 2014 00h34min39s UTC-3, Damian Avila escreveu:
On behalf of the Bokeh team, I am very happy to announce the release of Bokeh version 0.6.1!
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 point release includes several bug fixes and improvements over our most recent 0.6.0 release:
* Toolbar enhancements * bokeh-server fixes * Improved documentation * Button widgets * Google map support in the Python side * Code cleanup in the JS side and examples * New examples
See the CHANGELOG for full details.
In upcoming releases, you should expect to see more new layout capabilities (colorbar axes, better grid plots and improved annotations), additional tools, even more widgets and more charts, R language bindings, Blaze integration and cloud hosting for Bokeh apps.
Don't forget to check out the full documentation, interactive gallery, and tutorial at
as well as the Bokeh IPython notebook nbviewer index (including all the tutorials) at:
http://nbviewer.ipython.org/github/ContinuumIO/bokeh-notebooks/blob/master/i...
If you are using Anaconda or miniconda, you can install with conda:
conda install bokeh
Alternatively, you can install with pip:
pip install bokeh
BokehJS is also available by CDN for use in standalone javascript applications:
http://cdn.pydata.org/bokeh-0.6.1.min.js http://cdn.pydata.org/bokeh-0.6.1.min.css
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: bo...@continuum.io javascript:
If you have interest in helping to develop Bokeh, please get involved!
Cheers,
Damián Avila damian...@continuum.io javascript:
On 26.09.2014 05:34, Damian Avila wrote:
On behalf of the Bokeh team, I am very happy to announce the release of Bokeh version 0.6.1!
Hi, this looks awesome! Just out of curiosity: is Bokeh also able to provide interactive charts as Brython does? Example: http://www.brython.info/gallery/highcharts/examples/area-stacked/index_py.ht... thanks, Fabien
On Mon, Dec 1, 2014 at 6:17 AM, Fabien
Just out of curiosity: is Bokeh also able to provide interactive charts as Brython does?
Example:
http://www.brython.info/gallery/highcharts/examples/area-stacked/index_py.ht...
not really your question, but that example is using Brython to call HighCharts: http://www.highcharts.com/ Brython is doing very little there. -CHB -- Christopher Barker, Ph.D. Oceanographer Emergency Response Division NOAA/NOS/OR&R (206) 526-6959 voice 7600 Sand Point Way NE (206) 526-6329 fax Seattle, WA 98115 (206) 526-6317 main reception Chris.Barker@noaa.gov
On 01.12.2014 18:52, Chris Barker wrote:
not really your question, but that example is using Brython to call HighCharts:
Brython is doing very little there.
thanks for the hint! I am trying to gather information about how to make to make an interactive website with a python model running on a webserver and making plots. There's a bunch of tools out there, it's hard to get things sorted out. Fabien
Getting a bit OT here, but...
On Mon, Dec 1, 2014 at 10:46 AM, Fabien
thanks for the hint! I am trying to gather information about how to make to make an interactive website with a python model running on a webserver and making plots. There's a bunch of tools out there, it's hard to get things sorted out.
Broadly, you have two opitons: 1) use a nifty JS interactive plotting lib, and have python as a web service that it accesses to get the data to plot. This will require a fair bi tof javascript work (or _maybe_ Brython, but I don't know how complete or robust that is) 2) Use a python lib on the server side that essentially generates the HTML/CSS/Javascript for you. - Bokeh looks really grat for this -- I haven't tried o\it for real yet, but the demos are pretty darn cool! - Matplotlib has the WebAgg back-end. not sure how robust it is either, but worth checking out. -Chris -- Christopher Barker, Ph.D. Oceanographer Emergency Response Division NOAA/NOS/OR&R (206) 526-6959 voice 7600 Sand Point Way NE (206) 526-6329 fax Seattle, WA 98115 (206) 526-6317 main reception Chris.Barker@noaa.gov
participants (6)
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Arnaldo Russo -
Bryan Van de Ven -
Chris Barker -
Damian Avila -
Fabien -
Tom Augspurger