# External services When working with JupyterHub, a **Service** is defined as a process that interacts with the Hub's REST API. A Service may perform a specific or action or task. For example, shutting down individuals' single user notebook servers that have been is a good example of a task that could be automated by a Service. Let's look at how the [cull_idle_servers][] script can be used as a Service. ## Real-world example to cull idle servers JupyterHub has a REST API that can be used by external services. This document will: - explain some basic information about API tokens - clarify that API tokens can be used to authenticate to single-user servers as of [version 0.8.0](../changelog.html) - show how the [cull_idle_servers][] script can be: - used in a Hub-managed service - run as a standalone script Both examples for `cull_idle_servers` will communicate tasks to the Hub via the REST API. ## API Token basics ### Create an API token To run such an external service, an API token must be created and provided to the service. As of [version 0.6.0](../changelog.html), the preferred way of doing this is to first generate an API token: ```bash openssl rand -hex 32 ``` In [version 0.8.0](../changelog.html), a TOKEN request page for generating an API token is available from the JupyterHub user interface: ![Request API TOKEN page](../images/token-request.png) ![API TOKEN success page](../images/token-request-success.png) ### Pass environment variable with token to the Hub In the case of `cull_idle_servers`, it is passed as the environment variable called `JUPYTERHUB_API_TOKEN`. ### Use API tokens for services and tasks that require external access While API tokens are often associated with a specific user, API tokens can be used by services that require external access for activities that may not correspond to a specific human, e.g. adding users during setup for a tutorial or workshop. Add a service and its API token to the JupyterHub configuration file, `jupyterhub_config.py`: ```python c.JupyterHub.services = [ {'name': 'adding-users', 'api_token': 'super-secret-token'}, ] ``` ### Restart JupyterHub Upon restarting JupyterHub, you should see a message like below in the logs: ``` Adding API token for ``` ## Authenticating to single-user servers using API token In JupyterHub 0.7, there is no mechanism for token authentication to single-user servers, and only cookies can be used for authentication. 0.8 supports using JupyterHub API tokens to authenticate to single-user servers. ## Configure `cull-idle` to run as a Hub-Managed Service In `jupyterhub_config.py`, add the following dictionary for the `cull-idle` Service to the `c.JupyterHub.services` list: ```python c.JupyterHub.services = [ { 'name': 'cull-idle', 'admin': True, 'command': 'python3 cull_idle_servers.py --timeout=3600'.split(), } ] ``` where: - `'admin': True` indicates that the Service has 'admin' permissions, and - `'command'` indicates that the Service will be launched as a subprocess, managed by the Hub. ## Run `cull-idle` manually as a standalone script Now you can run your script, i.e. `cull_idle_servers`, by providing it the API token and it will authenticate through the REST API to interact with it. This will run `cull-idle` manually. `cull-idle` can be run as a standalone script anywhere with access to the Hub, and will periodically check for idle servers and shut them down via the Hub's REST API. In order to shutdown the servers, the token given to cull-idle must have admin privileges. Generate an API token and store it in the `JUPYTERHUB_API_TOKEN` environment variable. Run `cull_idle_servers.py` manually. ```bash export JUPYTERHUB_API_TOKEN='token' python3 cull_idle_servers.py [--timeout=900] [--url=http://127.0.0.1:8081/hub/api] ``` [cull_idle_servers]: https://github.com/jupyterhub/jupyterhub/blob/master/examples/cull-idle/cull_idle_servers.py