JupyterHub

JupyterHub is the best way to serve Jupyter notebook for multiple users. It can be used in a class of students, a corporate data science group or scientific research group. It is a multi-user Hub that spawns, manages, and proxies multiple instances of the single-user Jupyter notebook server.

To make life easier, JupyterHub has distributions. Be sure to take a look at them before continuing with the configuration of the broad original system of JupyterHub. Today, you can find two main cases:

  1. If you need a simple case for a small amount of users (0-100) and single server take a look at The Littlest JupyterHub distribution.

  2. If you need to allow for even more users, a dynamic amount of servers can be used on a cloud, take a look at the Zero to JupyterHub with Kubernetes .

Four subsystems make up JupyterHub:

  • a Hub (tornado process) that is the heart of JupyterHub

  • a configurable http proxy (node-http-proxy) that receives the requests from the client’s browser

  • multiple single-user Jupyter notebook servers (Python/IPython/tornado) that are monitored by Spawners

  • an authentication class that manages how users can access the system

Besides these central pieces, you can add optional configurations through a config.py file and manage users kernels on an admin panel. A simplification of the whole system can be seen in the figure below:

JupyterHub subsystems

JupyterHub performs the following functions:

  • The Hub launches a proxy

  • The proxy forwards all requests to the Hub by default

  • The Hub handles user login and spawns single-user servers on demand

  • The Hub configures the proxy to forward URL prefixes to the single-user notebook servers

For convenient administration of the Hub, its users, and services, JupyterHub also provides a REST API.

The JupyterHub team and Project Jupyter value our community, and JupyterHub follows the Jupyter Community Guides.

Contents

Distributions

A JupyterHub distribution is tailored towards a particular set of use cases. These are generally easier to set up than setting up JupyterHub from scratch, assuming they fit your use case.

The two popular ones are:

Contributing

We want you to contribute to JupyterHub in ways that are most exciting & useful to you. We value documentation, testing, bug reporting & code equally, and are glad to have your contributions in whatever form you wish :)

Our Code of Conduct (reporting guidelines) helps keep our community welcoming to as many people as possible.

Indices and tables

Questions? Suggestions?

Installation