Installation¶

Dependencies¶

Because the Bokeh client library is mostly concerned with providing a nice Python interface for generating JSON objects which are then consumed by the BokehJS library running in the browser, there shouldn’t be a hard dependency on any of the standard NumPy/SciPy stack. It is entirely possible to use Bokeh with plain Python lists of values.

The Bokeh plot server does take advantage of NumPy, and may have a hard dependency on several compiled libraries.

Ideally, you should have the following libraries installed:

Package Installs¶

These Bokeh dependencies are best obtained via the Anaconda Python Distribution, which was designed to include robust versions of popular libraries for the Python scientific and data analysis stacks.

If you are already an Anaconda user, you can simply run the command:

$ conda install bokeh

This will install the most recent published Bokeh release from the Anaconda Anaconda repository, along with all dependencies.

Alternatively, it is possible to install from PyPI using pip:

$ pip install bokeh

Sample Data¶

Some of the Bokeh examples rely on sample data that is not included in the Bokeh GitHub repository or released packages, due to their size. Once Bokeh is installed, the sample data can be obtained by executing the following commands at a python prompt:

>>> import bokeh.sampledata
>>> bokeh.sampledata.download()

Or directly from a Bash or Windows comand prompt:

python -c "import bokeh.sampledata; bokeh.sampledata.download()"

Notes for Windows Users¶

If you are using Windows then installing redis may be challenging. On Windows the Bokeh plot server defaults to an in-memory (non-persistent) storage backend.

If you would like to try using the Redis backend, we recommend grabbing the binaries from one of these locations:

• https://github.com/dmajkic/redis/downloads
• http://cloud.github.com/downloads/rgl/redis/redis-2.4.6-setup-64-bit.exe

Once installed, you should add C:\Program Files\Redis to your PATH variable, and execute run the Bokeh server as follows:

$ bokeh-server --backend=redis

Installing from Source¶

Installing Bokeh from source requires rebuilding the BokehJS library from its CoffeeScript sources. Some additional toolchain support is required. Please consult the Building and Installing section of the Developer Guide for more detailed instructions.

Developer Builds¶

And easier way to obtain the most recent Bokeh updates without having to worry about building Bokeh yourself is to install a developer build. We typically try to make a new developer build available at least once a week, and sometimes more often.

These builds are being made available on binstar.org. If you are using Anaconda, you can install with conda by issuing the command:

conda install -c bokeh/channel/dev bokeh

Alternatively you can install with pip:

pip install --pre -i https://pypi.binstar.org/bokeh/channel/dev/simple bokeh --extra-index-url https://pypi.python.org/simple/

We attempt to make sure the developer builds are relatively stable, however please be aware they they are not tested as rigorously as standard releases. Any problems or issues reported on the GitHub issue tracker are appreciated.

BokehJS Standalone¶

If you would like to use BokehJS as a standalone JavaScript library, there are two easy ways to get any published release.

First, released versions of BokehJS is available for download from CDN at pydata.org, under the following naming scheme:

https://cdn.bokeh.org/bokeh/release/bokeh-x.y.z.min.js

for the BokehJS JavaScript, and:

https://cdn.bokeh.org/bokeh/release/bokeh-x.y.z.min.css

for the BokehJS CSS.

As a concrete example, the links for version 0.8.1 are:

• https://cdn.bokeh.org/bokeh/release/bokeh-0.8.1.min.css
• https://cdn.bokeh.org/bokeh/release/bokeh-0.8.1.min.css

Alternatively, BokehJS is available from npmjs through the Node Package Manager:

$ npm install bokehjs