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JupyterHub

JupyterHub is the best way to serve Jupyter notebook for multiple users. It can be used in a classes 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 have 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.

Upgrading JupyterHub

We try to make upgrades between minor versions as painless as possible.

API Reference

Troubleshooting

Indices and tables

Questions? Suggestions?

Installation Guide