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