This section gives more details about the installation process of Bokeh, for those who were unable to complete the process detailed in the Quickstart, or who want more information about the process.
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.
For basic usage, have the following libraries installed:
To use the Bokeh server with python 2.7, you also need to install Futures package.
bokeh.charts interface as well as various examples
depend on the Pandas library, which is recommended to be installed.
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 Continuum Analytics Anaconda repository, along with all dependencies.
Alternatively, it is possible to install from PyPI using
pip install bokeh
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 command prompt:
python -c "import bokeh.sampledata; bokeh.sampledata.download()"
Finally, the location that the sample data is stored can be configured.
By default, data is downloaded and stored to a directory
(The directory is created if it does not already exist.) Bokeh looks for
a YAML configuration file at
$HOME/.bokeh/config. The YAML key
sampledata_dir can be set to the absolute path of a directory where
the data should be stored. For instance adding the following line to the
will cause the sample data to be stored in
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 Getting Set Up section of the Developer Guide for detailed instructions.
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 anaconda.org. If you are using Anaconda, you can install with conda by issuing the command from a Bash or Windows command prompt:
conda install -c bokeh/channel/dev bokeh
Alternatively you can install with pip from a Bash or Windows command prompt:
pip install --pre -i https://pypi.anaconda.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.
First, released versions of BokehJS is available for download from CDN at pydata.org, under the following naming scheme:
for the BokehJS CSS.
As a concrete example, the links for version
Alternatively, BokehJS is available from npmjs through the Node Package Manager. From a Bash or Windows command prompt, execute:
npm install bokehjs