Using JupyterHub’s REST API

This section will give you information on:

  • what you can do with the API

  • create an API token

  • add API tokens to the config files

  • make an API request programmatically using the requests library

  • learn more about JupyterHub’s API

What you can do with the API

Using the JupyterHub REST API, you can perform actions on the Hub, such as:

  • checking which users are active

  • adding or removing users

  • stopping or starting single user notebook servers

  • authenticating services

A REST API provides a standard way for users to get and send information to the Hub.

Create an API token

To send requests using JupyterHub API, you must pass an API token with the request.

As of version 0.6.0, the preferred way of generating an API token is:

openssl rand -hex 32

This openssl command generates a potential token that can then be added to JupyterHub using .api_tokens configuration setting in jupyterhub_config.py.

Alternatively, use the jupyterhub token command to generate a token for a specific hub user by passing the ‘username’:

jupyterhub token <username>

This command generates a random string to use as a token and registers it for the given user with the Hub’s database.

In version 0.8.0, a TOKEN request page for generating an API token is available from the JupyterHub user interface:

Request API TOKEN page

API TOKEN success page

Add API tokens to the config file

This is deprecated. We are in no rush to remove this feature, but please consider if service tokens are right for you.

You may also add a dictionary of API tokens and usernames to the hub’s configuration file, jupyterhub_config.py (note that the key is the ‘secret-token’ while the value is the ‘username’):

c.JupyterHub.api_tokens = {
    'secret-token': 'username',
}

Updating to admin services

The api_tokens configuration has been softly deprecated since the introduction of services. We have no plans to remove it, but users are encouraged to use service configuration instead.

If you have been using api_tokens to create an admin user and a token for that user to perform some automations, the services mechanism may be a better fit. If you have the following configuration:

c.JupyterHub.admin_users = {"service-admin",}
c.JupyterHub.api_tokens = {
    "secret-token": "service-admin",
}

This can be updated to create an admin service, with the following configuration:

c.JupyterHub.services = [
    {
        "name": "service-token",
        "admin": True,
        "api_token": "secret-token",
    },
]

The token will have the same admin permissions, but there will no longer be a user account created to house it. The main noticeable difference is that there will be no notebook server associated with the account and the service will not show up in the various user list pages and APIs.

Make an API request

To authenticate your requests, pass the API token in the request’s Authorization header.

Use requests

Using the popular Python requests library, here’s example code to make an API request for the users of a JupyterHub deployment. An API GET request is made, and the request sends an API token for authorization. The response contains information about the users:

import requests

api_url = 'http://127.0.0.1:8081/hub/api'

r = requests.get(api_url + '/users',
    headers={
             'Authorization': 'token %s' % token,
            }
    )

r.raise_for_status()
users = r.json()

This example provides a slightly more complicated request, yet the process is very similar:

import requests

api_url = 'http://127.0.0.1:8081/hub/api'

data = {'name': 'mygroup', 'users': ['user1', 'user2']}

r = requests.post(api_url + '/groups/formgrade-data301/users',
    headers={
             'Authorization': 'token %s' % token,
            },
    json=data
)
r.raise_for_status()
r.json()

The same API token can also authorize access to the Jupyter Notebook REST API provided by notebook servers managed by JupyterHub if one of the following is true:

  1. The token is for the same user as the owner of the notebook

  2. The token is tied to an admin user or service and c.JupyterHub.admin_access is set to True

Paginating API requests

Pagination is available through the offset and limit query parameters on certain endpoints, which can be used to return ideally sized windows of results. Here’s example code demonstrating pagination on the GET /users endpoint to fetch the first 20 records.

import requests

api_url = 'http://127.0.0.1:8081/hub/api'

r = requests.get(api_url + '/users?offset=0&limit=20')
r.raise_for_status()
r.json()

By default, pagination limit will be specified by the JupyterHub.api_page_default_limit config variable.

Pagination is enabled on the GET /users, GET /groups, and GET /proxy REST endpoints.

Enabling users to spawn multiple named-servers via the API

With JupyterHub version 0.8, support for multiple servers per user has landed. Prior to that, each user could only launch a single default server via the API like this:

curl -X POST -H "Authorization: token <token>" "http://127.0.0.1:8081/hub/api/users/<user>/server"

With the named-server functionality, it’s now possible to launch more than one specifically named servers against a given user. This could be used, for instance, to launch each server based on a different image.

First you must enable named-servers by including the following setting in the jupyterhub_config.py file.

c.JupyterHub.allow_named_servers = True

If using the zero-to-jupyterhub-k8s set-up to run JupyterHub, then instead of editing the jupyterhub_config.py file directly, you could pass the following as part of the config.yaml file, as per the tutorial:

hub:
  extraConfig: |
    c.JupyterHub.allow_named_servers = True

With that setting in place, a new named-server is activated like this:

curl -X POST -H "Authorization: token <token>" "http://127.0.0.1:8081/hub/api/users/<user>/servers/<serverA>"
curl -X POST -H "Authorization: token <token>" "http://127.0.0.1:8081/hub/api/users/<user>/servers/<serverB>"

The same servers can be stopped by substituting DELETE for POST above.

Some caveats for using named-servers

For named-servers via the API to work, the spawner used to spawn these servers will need to be able to handle the case of multiple servers per user and ensure uniqueness of names, particularly if servers are spawned via docker containers or kubernetes pods.

Learn more about the API

You can see the full JupyterHub REST API for details. This REST API Spec can be viewed in a more interactive style on swagger’s petstore. Both resources contain the same information and differ only in its display. Note: The Swagger specification is being renamed the OpenAPI Initiative.