getLockers func() ([]dsync.NetLocker, string)

	// getEndpoints returns list of endpoint belonging this set.
	// some may be local and some remote.
	getEndpoints func() []Endpoint

	// getEndpoints returns list of endpoint strings belonging this set.
	// some may be local and some remote.
	getEndpointStrings func() []string

	// Locker mutex map.
	nsMutex *nsLockMap
}

I will show you some of the main concepts you should probably keep in mind when deploying a **FastAPI** application (although most of it applies to any other type of web application).

   * {@code node}'s outgoing edges in the direction (if any) of the edge.
   *
   * <p>This is <i>not</i> the same as "all nodes reachable from {@code node} by following outgoing
   * edges". For that functionality, see {@link Graphs#reachableNodes(Graph, Object)}.
   *
   * <p>Some algorithms that operate on a {@code SuccessorsFunction} may produce undesired results

They have different levels of permissions and [specific instructions](./management-tasks.md){.internal-link target=_blank}.

Some of the tasks they can perform include:

* Adding labels to PRs.
* Editing PR titles.
* Adding commits on top of PRs to tweak them.
* Mark answers in GitHub Discussions questions, etc.
* Merge some specific types of PRs.

They are just a convenience, they hold the same number, but that way you can use the editor's autocomplete to find them:

<img src="/img/tutorial/response-status-code/image02.png">

/// note | Technical Details

You could also use `from starlette import status`.

The same as when using a custom CDN, the first step is to disable the automatic docs, as those use the CDN by default.

To disable them, set their URLs to `None` when creating your `FastAPI` app:

{* ../../docs_src/custom_docs_ui/tutorial002.py hl[9] *}

### Include the custom docs for static files { #include-the-custom-docs-for-static-files }

Let's start with an example **use case** and then see how to solve it with this.

Let's imagine that you have some **machine learning models** that you want to use to handle requests. 🤖

The same models are shared among requests, so, it's not one model per request, or one per user or something similar.

Let's imagine that loading the model can **take quite some time**, because it has to read a lot of **data from disk**. So you don't want to do it for every request.

   * {@code node}'s outgoing edges in the direction (if any) of the edge.
   *
   * <p>This is <i>not</i> the same as "all nodes reachable from {@code node} by following outgoing
   * edges". For that functionality, see {@link Graphs#reachableNodes(Graph, Object)}.
   *
   * <p>Some algorithms that operate on a {@code SuccessorsFunction} may produce undesired results

* It can then do something to that **request** or run any needed code.
* Then it passes the **request** to be processed by the rest of the application (by some *path operation*).
* It then takes the **response** generated by the application (by some *path operation*).
* It can do something to that **response** or run any needed code.
* Then it returns the **response**.

/// note | Technical Details

When using containers, you would normally have some component **listening on the main port**. It could possibly be another container that is also a **TLS Termination Proxy** to handle **HTTPS** or some similar tool.

As this component would take the **load** of requests and distribute that among the workers in a (hopefully) **balanced** way, it is also commonly called a **Load Balancer**.

/// tip