Technical overview | Prerequisites | Installation | Running the Hub Server | Configuration | Docker | Contributing | License | Getting help
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With JupyterHub you can create a multi-user Hub which spawns, manages, and proxies multiple instances of the single-user Jupyter notebook (IPython notebook) server.
JupyterHub provides single-user notebook servers to many users. For example, JupyterHub could serve notebooks to a class of students, a corporate workgroup, or a science research group.
Three main actors make up JupyterHub:
- multi-user Hub (tornado process)
- configurable http proxy (node-http-proxy)
- multiple single-user Jupyter notebook servers (Python/IPython/tornado)
JupyterHub's basic principles for operation are:
- Hub spawns a proxy
- Proxy forwards all requests to Hub by default
- Hub handles login, and spawns single-user servers on demand
- Hub configures proxy to forward url prefixes to the single-user servers
JupyterHub also provides a REST API for administration of the Hub and users.
Before installing JupyterHub, you need:
-
Python 3.3 or greater
An understanding of using
pipfor installing Python packages is recommended. -
Install nodejs/npm, which is available from your package manager. For example, install on Linux (Debian/Ubuntu) using:
sudo apt-get install npm nodejs-legacy(The
nodejs-legacypackage installs thenodeexecutable and is currently required for npm to work on Debian/Ubuntu.) -
TLS certificate and key for HTTPS communication
-
Domain name
Before running the single-user notebook servers (which may be on the same system as the Hub or not):
- Jupyter Notebook version 4 or greater
JupyterHub can be installed with pip, and the proxy with npm:
npm install -g configurable-http-proxy
pip3 install jupyterhub If you plan to run notebook servers locally, you will need to install the Jupyter notebook:
pip3 install --upgrade notebook
To start the Hub server, run the command:
jupyterhub
Visit https://localhost:8000 in your browser, and sign in with your unix credentials.
To allow multiple users to sign into the server, you will need to
run the jupyterhub command as a privileged user, such as root.
The wiki
describes how to run the server as a less privileged user, which requires more
configuration of the system.
The getting started document contains the basics of configuring a JupyterHub deployment.
The JupyterHub tutorial provides a video and documentation that explains and illustrates the fundamental steps for installation and configuration. Repo | Tutorial documentation
Generate a default config file:
jupyterhub --generate-config
Spawn the server on 10.0.1.2:443 with https:
jupyterhub --ip 10.0.1.2 --port 443 --ssl-key my_ssl.key --ssl-cert my_ssl.cert
The authentication and process spawning mechanisms can be replaced, which should allow plugging into a variety of authentication or process control environments. Some examples, meant as illustration and testing of this concept:
- Using GitHub OAuth instead of PAM with OAuthenticator
- Spawning single-user servers with Docker, using the DockerSpawner
A starter docker image for JupyterHub gives a baseline deployment of JupyterHub.
Important: This jupyterhub/jupyterhub image contains only the Hub itself, with no configuration. In general, one needs
to make a derivative image, with at least a jupyterhub_config.py setting up an Authenticator and/or a Spawner. To run the
single-user servers, which may be on the same system as the Hub or not, Jupyter Notebook version 4 or greater must be installed.
The JupyterHub docker image can be started with the following command:
docker run -d --name jupyterhub jupyterhub/jupyterhub jupyterhub
This command will create a container named jupyterhub that you can stop and resume with docker stop/start.
The Hub service will be listening on all interfaces at port 8000, which makes this a good choice for testing JupyterHub on your desktop or laptop.
If you want to run docker on a computer that has a public IP then you should (as in MUST) secure it with ssl by adding ssl options to your docker configuration or using a ssl enabled proxy.
Mounting volumes will allow you to store data outside the docker image (host system) so it will be persistent, even when you start a new image.
The command docker exec -it jupyterhub bash will spawn a root shell in your docker
container. You can use the root shell to create system users in the container. These accounts will be used for authentication
in JupyterHub's default configuration.
If you would like to contribute to the project, please read our contributor documentation and the CONTRIBUTING.md.
For a development install, clone the repository and then install from source:
git clone https://github.com/jupyterhub/jupyterhub
cd jupyterhub
pip3 install -r dev-requirements.txt -e .If the pip3 install 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 setup.py js # fetch updated client-side js
python3 setup.py css # recompile CSS from LESS sourcesWe use pytest for testing. To run tests:
pytest jupyterhub/testsWe use a shared copyright model that enables all contributors to maintain the copyright on their contributions.
All code is licensed under the terms of the revised BSD license.
We encourage you to ask questions on the mailing list, and you may participate in development discussions or get live help on Gitter.