Setting up a development environment#
The Bokeh project consists of two major components: the Bokeh package source code, written in Python, and the BokehJS client-side library, written in TypeScript.
Therefore, you need to set up two environments to contribute to Bokeh: A Python environment and a TypeScript environment. This chapter walks you through all the necessary steps to set up a full development environment.
1. Check basic requirements#
Install or update Git#
The Bokeh source code is stored in a Git source control repository. The first step to working on Bokeh is to install or update Git on your system.
There are different ways to do this, depending on whether you are using Windows, OSX, or Linux. To install Git on any platform, refer to the Installing Git section of the Pro Git Book.
If you have never used Git before, you can find links to several beginner tutorials and resources in the Git documentation.
Install or update conda#
Working on the Bokeh codebase requires installing several software packages that are not Python packages. For example, Node.js for TypeScript development or Selenium for testing and exporting.
To be able to manage Python and non-Python dependencies in one place, Bokeh uses
the conda package manager.
conda is part of the free Anaconda Python
distribution available for Windows, macOS, and Linux. Conda creates and manages
virtual environments for you. Therefore, you don’t need tools like
pipenv. While it is technically possible to install all
dependencies manually without
conda, this guide will assume that you have
To install or update Conda on your system, see Installation in the Conda documentation.
conda is already installed on your system, make sure it is up to date
by running the following command:
conda update -n base -c defaults conda
2. Fork and clone the repository#
The source code for the Bokeh project is hosted on GitHub, at https://github.com/bokeh/bokeh.
Unless you are a @bokeh/dev team member, you first need to create a fork of Bokeh’s main repository. For more information on creating a fork, see Fork a repo in GitHub Help.
Next, clone the version of the Bokeh repository you want to work on to a local
folder on your hard drive. Use
git clone or follow the instructions for
cloning a forked repository in GitHub Help.
Cloning the repository creates a
bokeh directory at your file system
location. This local
bokeh directory is referred to as the source checkout
for the remainder of this document.
3. Create a conda environment#
The Bokeh repository you just cloned to your local hard drive contains test environment files in the conda folder. In these files is all the necessary information to automatically create a basic development environment.
conda env create at the root level of your source checkout directory
to set up the environment and install all necessary packages. The “test”
environment files are versioned by Python version.
For example, to install an environment for Python 3.10, invoke:
conda env create -n bkdev -f conda/environment-test-3.10.yml
conda -n bkdev option to make
bkdev the name of your
environment. The remainder of this chapter and all other chapters in this
guide assume that this is the name of your environment.
Then, activate the environment:
conda activate bkdev
To update your local environment, use
conda env update --name bkdev -f <environment file>. Updating your local
environment is necessary whenever the dependencies in the test environments
change. This can happen when the environment files are updated in the main
Bokeh repository or when you switch branches to work on different issues,
To learn more about creating and managing conda environments, see Managing environments in the Conda documentation.
4. Install Node packages#
the Node Package Manager (npm). If you have followed the
conda has already installed the necessary
packages to your system.
Bokeh usually requires the latest major revision of
npm. To install the
newest version globally, start from the top level of the source checkout
directory, and run the following commands:
cd bokehjs npm install --location=global npm@8
If you do not want to install npm globally, leave out the
flag. In this case, you need to adjust all subsequent
npm commands to use
the local version installed under
Next, still in the
bokehjs subdirectory, run the following command
This command installs the necessary packages into the
Typically, you only need to do this once when you first set up your local environment. However, if dependencies are added or changed, you need to repeat these steps to install and update the respective packages.
5. Set up pre-commit#
Bokeh uses pre-commit to help you prevent some common mistakes in your commits.
To set up pre-commit locally, run the following command from the top level of your source checkout directory:
This configures pre-commit to use two Git hooks that will check your code whenever you push a commit to Bokeh’s GitHub repository:
- Codebase tests
git-commit will run Bokeh’s codebase tests to check for codebase quality issues such as whitespaces and imports. This includes testing with Flake8, ESLint, and isort.
- Protected branches
git-commit will make sure you don’t accidentally push a commit to Bokeh’s protected branches
Depending on your system, running those tests may take several dozen seconds. If any of the tests fail, check the output of your console. In most cases, this is where you will find the necessary information about what you need to change to pass the tests.
To uninstall the Git hooks, run the following command from the top level of your source checkout directory:
6. Build and install locally#
Once you have all the required dependencies installed, the simplest way to
build and install Bokeh and BokehJS is to use pip.
pip is the package
installer for Python and is automatically installed when you
set up the conda environment.
Make sure you have activated the
bkdev environment before running
There are two ways to install a local development version of Bokeh with
pip install -e .
Bokeh will be installed to refer to your local source directory. Any changes you make to the Python source code will be available immediately without any additional steps. This is the recommended mode when working on the Bokeh codebase.
pip install .
Bokeh will be installed in your local Python
site-packagesdirectory. In this mode, any changes to the Python source code will have no effect until you run
pip install .again.
Running either of those two commands also builds and installs a local version of
BokehJS. If you want to skip building a new version of BokehJS and use a
different local version instead, set the
BOKEHJS_ACTION environment variable:
BOKEHJS_ACTION="install" pip install -e .
You need to rebuild BokehJS each time the BokehJS source code changes.
This can be necessary because you made changes yourself or because you
pulled updated code from GitHub. Re-run
pip install -e . to build
and install BokehJS.
In case you update from a development environment based on Bokeh 2.3 or
older, you most likely also need to delete the
bokehjs/build folder in
your local environment before building and installing a fresh BokehJS.
7. Download sample data#
Several tests and examples require Bokeh’s sample data to be available on your hard drive. After installing Bokeh, use the following command to download and install the data:
You also have the opportunity to configure the download location or to start the download programmatically. See the Installing sample data section of the first steps guides for more details.
8. Set environment variables#
Bokeh uses environment variables to control several aspects of how the different parts of the library operate and interact.
To learn about all environment variables available in Bokeh, see bokeh.settings in the reference guide.
When working on Bokeh’s codebase, the most important environment variable to be
aware of is
BOKEH_RESOURCES. This variable controls which version of
BokehJS to use.
You have the following three options to use your local version of BokehJS:
$Env:BOKEH_RESOURCES = "absolute-dev"
$Env:BOKEH_RESOURCES = "inline"
server-devto load your local BokehJS through a Bokeh server.
First, start a local server.
BOKEH_DEV=true bokeh static
$Env:BOKEH_DEV = "true" bokeh.exe static
set BOKEH_DEV=true bokeh static
Next, open a new terminal window and set
$Env:BOKEH_RESOURCES = "server-dev"
Resources for more details.
There are several other environment variables that are helpful when working on
Bokeh’s codebase. The most common settings for local development are combined in
To enable development settings, set
$Env:BOKEH_DEV = "true"
true is equivalent to setting all of the following
This way, Bokeh will use local and unminified BokehJS resources, the default log
levels are increased, the generated HTML and JSON code will be more
human-readable, and Bokeh will not open a new browser window each time
causes rendering problems when used with Bokeh server or in
Jupyter notebooks. To avoid those problems,
use the following settings instead:
9. Test your local setup#
Run the following tests to check that everything is installed and set up correctly:
Test Bokeh core#
First, use the following command to test the Bokeh installation:
python -m bokeh info
You should see output similar to:
Python version : 3.9.7 | packaged by conda-forge | (default, Sep 29 2021, 19:20:46) IPython version : 7.20.0 Tornado version : 6.1 Bokeh version : 3.0.0dev1+20.g6c394d579 BokehJS static path : /opt/anaconda/envs/test/lib/python3.9/site-packages/bokeh/server/static node.js version : v16.12.0 npm version : 7.24.2 Operating system : Linux-5.11.0-40-generic-x86_64-with-glibc2.31
Next, run some of the standalone examples included with Bokeh.
Make sure the environment variable
BOKEH_RESOURCES is set to
inline in order to use
your local version of BokehJS. In the source checkout directory, run the
BOKEH_RESOURCES=inline python examples/plotting/marker_map.py
$Env:BOKEH_RESOURCES = "inline" python.exe .\examples\plotting\file\marker_map.py
set BOKEH_RESOURCES=inline python examples\plotting\file\marker_map.py
This creates a file
marker_map.html locally. When you open this file in a web
browser, it should display this visualization:
Run Bokeh Server#
Another way to use Bokeh is as a server. Set the
BOKEH_DEV=false and run the
bokeh serve command in the source
BOKEH_DEV=false python -m bokeh serve --show examples/app/sliders.py
$Env:BOKEH_DEV = "False" python.exe -m bokeh serve --show .\examples\app\sliders.py
set BOKEH_DEV=false python -m bokeh serve --show examples\app\sliders.py
This should open up a browser with an interactive figure:
All the sliders allow interactive control of the sine wave, with each update
redrawing the line with the new parameters. The
--show option opens a
web browser. The default URL for the Bokeh server is
Updating an existing development environment does not always work as expected. Make sure your conda environment, Node packages, and local build are up to date.
If you keep getting errors after updating an older environment, use
conda remove --name bkdev --all, delete your local
and reinstall your development environment, following the steps in this guide
from the beginning.
For more information on running and installing Bokeh, check the additional resources available to contributors. Please feel free to ask at the Bokeh Discourse or Bokeh’s contributor Slack.