Installation¶
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.
Dependencies¶
Bokeh is officially supported (and continuously tested) on CPython versions 2.7 and 3.4+ only. Other Python versions may function, possibly in limited capacity. In particular, converting NumPy arrays to lists may be useful with other versions. However, this guidance is only provided as-is, in case it happens to be useful, and does not imply any level of official support for other Python versions. All issues opened related to unsupported Python versions will be closed as invalid.
For basic usage, have the following libraries installed:
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To use the Bokeh server with python 2.7, you also need to install Futures package.
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. However, the Bokeh plot server does make direct use of NumPy, and it is required to be installed for Bokeh apps to function.
Additionally the bokeh.charts
interface and various examples
depend on the Pandas library; it is recommended to install Pandas version 0.16.1
or later.
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 command at a Bash or Windows prompt:
bokeh sampledata
Alternatively, the following statements can be executed in a Python interpreter:
>>> 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 $HOME/.bokeh/data
.
(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
config file:
sampledata_dir: /tmp/bokeh_data
will cause the sample data to be stored in /tmp/bokeh_data
.
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.
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 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.
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:
http://cdn.pydata.org/bokeh/release/bokeh-x.y.z.min.js
http://cdn.pydata.org/bokeh/release/bokeh-widgets-x.y.z.min.js
for the BokehJS JavaScript files, and:
http://cdn.pydata.org/bokeh/release/bokeh-x.y.z.min.css
http://cdn.pydata.org/bokeh/release/bokeh-widgets-x.y.z.min.css
for the BokehJS CSS files.
The "-widgets"
files are only necessary if you are using any of the widgets
built into Bokeh in bokeh.models.widgets
in your documents.
As a concrete example, the links for version 0.12
are:
- https://cdn.bokeh.org/bokeh/release/bokeh-0.12.0.min.js
- https://cdn.bokeh.org/bokeh/release/bokeh-widgets-0.12.0.min.js
and
- https://cdn.bokeh.org/bokeh/release/bokeh-0.12.0.min.css
- https://cdn.bokeh.org/bokeh/release/bokeh-widgets-0.12.0.min.css
Note
For releases 0.12.2
and after, the BokehJS API has been branched to a separate file.
It is also available for download from CDN at pydata.org under the name bokeh-api using
the above naming scheme.