Setting up a development install#

System requirements#

JupyterHub can only run on macOS or Linux operating systems. If you are using Windows, we recommend using VirtualBox or a similar system to run Ubuntu Linux for development.

Install Python#

JupyterHub is written in the Python programming language and requires you have at least version 3.8 installed locally. If you haven’t installed Python before, the recommended way to install it is to use Miniforge.

Install nodejs#

NodeJS 12+ is required for building some JavaScript components. configurable-http-proxy, the default proxy implementation for JupyterHub, is written in Javascript. If you have not installed NodeJS before, we recommend installing it in the miniconda environment you set up for Python. You can do so with conda install nodejs.

Many in the Jupyter community use nvm to managing node dependencies.

Install git#

JupyterHub uses Git & GitHub for development & collaboration. You need to install git to work on JupyterHub. We also recommend getting a free account on

Setting up a development install#

When developing JupyterHub, you would need to make changes and be able to instantly view the results of the changes. To achieve that, a developer install is required.


This guide does not attempt to dictate how development environments should be isolated since that is a personal preference and can be achieved in many ways, for example, tox, conda, docker, etc. See this forum thread for a more detailed discussion.

  1. Clone the JupyterHub git repository to your computer.

    git clone
    cd jupyterhub
  2. Make sure the python you installed and the npm you installed are available to you on the command line.

    python -V

    This should return a version number greater than or equal to 3.8.

    npm -v

    This should return a version number greater than or equal to 5.0.

  3. Install configurable-http-proxy (required to run and test the default JupyterHub configuration):

    npm install -g configurable-http-proxy

    If you get an error that says Error: EACCES: permission denied, you might need to prefix the command with sudo. sudo may be required to perform a system-wide install. If you do not have access to sudo, you may instead run the following commands:

    npm install configurable-http-proxy
    export PATH=$PATH:$(pwd)/node_modules/.bin

    The second line needs to be run every time you open a new terminal.

    If you are using conda you can instead run:

    conda install configurable-http-proxy
  4. Install an editable version of JupyterHub and its requirements for development and testing. This lets you edit JupyterHub code in a text editor & restart the JupyterHub process to see your code changes immediately.

    python3 -m pip install --editable ".[test]"
  5. You are now ready to start JupyterHub!

  6. You can access JupyterHub from your browser at http://localhost:8000 now.

Happy developing!

Using DummyAuthenticator & SimpleLocalProcessSpawner#

To simplify testing of JupyterHub, it is helpful to use DummyAuthenticator instead of the default JupyterHub authenticator and SimpleLocalProcessSpawner instead of the default spawner.

There is a sample configuration file that does this in testing/ To launch JupyterHub with this configuration:

jupyterhub -f testing/

The test configuration enables a few things to make testing easier:

  • use ‘dummy’ authentication and ‘simple’ spawner

  • named servers are enabled

  • listen only on localhost

  • ‘admin’ is an admin user, if you want to test the admin page

  • disable caching of static files

The default JupyterHub authenticator & spawner require your system to have user accounts for each user you want to log in to JupyterHub as.

DummyAuthenticator allows you to log in with any username & password, while SimpleLocalProcessSpawner allows you to start servers without having to create a Unix user for each JupyterHub user. Together, these make it much easier to test JupyterHub.

Tip: If you are working on parts of JupyterHub that are common to all authenticators & spawners, we recommend using both DummyAuthenticator & SimpleLocalProcessSpawner. If you are working on just authenticator-related parts, use only SimpleLocalProcessSpawner. Similarly, if you are working on just spawner-related parts, use only DummyAuthenticator.

Building frontend components#

The testing configuration file also disables caching of static files, which allows you to edit and rebuild these files without restarting JupyterHub.

If you are working on the admin react page, which is in the jsx directory, you can run:

cd jsx
npm install
npm run build:watch

to continuously rebuild the admin page, requiring only a refresh of the page.

If you are working on the frontend SCSS files, you can run the same build:watch command in the top level directory of the repo:

npm install
npm run build:watch


This section lists common ways setting up your development environment may fail, and how to fix them. Please add to the list if you encounter yet another way it can fail!

lessc not found#

If the python3 -m pip install --editable . command fails and complains about lessc being unavailable, you may need to explicitly install some additional JavaScript dependencies:

npm install

This will fetch client-side JavaScript dependencies necessary to compile CSS.

You may also need to manually update JavaScript and CSS after some development updates, with:

python3 js    # fetch updated client-side js
python3 css   # recompile CSS from LESS sources
python3 jsx   # build React admin app

Failed to bind XXX to<port>/<path>#

This error can happen when there’s already an application or a service using this port.

Use the following command to find out which service is using this port.

lsof -P -i TCP:<port> -sTCP:LISTEN

If nothing shows up, it likely means there’s a system service that uses it but your current user cannot list it. Reuse the same command with sudo.

sudo lsof -P -i TCP:<port> -sTCP:LISTEN

Depending on the result of the above commands, the most simple solution is to configure JupyterHub to use a different port for the service that is failing.

As an example, the following is a frequently seen issue:

Failed to bind hub to

Using the procedure described above, start with:

lsof -P -i TCP:8081 -sTCP:LISTEN

and if nothing shows up:

sudo lsof -P -i TCP:8081 -sTCP:LISTEN

Finally, depending on your findings, you can apply the following change and start JupyterHub again:

c.JupyterHub.hub_port = 9081 # Or any other free port