* <ul>
   *   <li>If {@code exceptions} has a single exception and that exception is a {@link
   *       RuntimeException}, return it
   *   <li>If {@code exceptions} has a single exceptions and that exceptions is not a
   *       {@link RuntimeException}, return a simple {@code RuntimeException} that wraps it
   *   <li>Otherwise, return an instance of {@link ClusterException} that wraps the first exception

## Containers and Processes

A **container image** normally includes in its metadata the default program or command that should be run when the **container** is started and the parameters to be passed to that program. Very similar to what would be if it was in the command line.

When a **container** is started, it will run that command/program (although you can override it and make it run a different command/program).

The important thing to remember is that **the first *type parameter*** you pass to `Annotated` is the **actual type**. The rest, is just metadata for other tools.

For now, you just need to know that `Annotated` exists, and that it's standard Python. 😎

Later you will see how **powerful** it can be.

/// tip

It will use the default status code or the one you set in your *path operation*.

## Additional status codes

If you want to return additional status codes apart from the main one, you can do that by returning a `Response` directly, like a `JSONResponse`, and set the additional status code directly.

`secrets.compare_digest()` needs to take `bytes` or a `str` that only contains ASCII characters (the ones in English), this means it wouldn't work with characters like `á`, as in `Sebastián`.

To handle that, we first convert the `username` and `password` to `bytes` encoding them with UTF-8.

Then we can use `secrets.compare_digest()` to ensure that `credentials.username` is `"stanleyjobson"`, and that `credentials.password` is `"swordfish"`.

This can be very useful for setting up **resources** that you need to use for the whole app, and that are **shared** among requests, and/or that you need to **clean up** afterwards. For example, a database connection pool, or loading a shared machine learning model.

## Use Case

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. 🤖

OAuth2 was designed so that the backend or API could be independent of the server that authenticates the user.

But in this case, the same **FastAPI** application will handle the API and the authentication.

So, let's review it from that simplified point of view:

* The user types the `username` and `password` in the frontend, and hits `Enter`.

This way, you don't have to know beforehand what the valid field/attribute names are (as would be the case with Pydantic models).

This would be useful if you want to receive keys that you don't already know.

---

Another useful case is when you want to have keys of another type (e.g., `int`).

That's what we are going to see here.

new properties on a task, extension or domain object that use plain getters and setters.  It is also not acceptable to add setters that take a Provider.

Note that when adding a lazy property to an existing class, you need to check if instances of the class are instantiated via ObjectFactory. Most classes are instantiated this way, but it's possible that a class without any lazy properties was never updated to use it. A tell-tale sign that an object is not instantiated via the ObjectFactory...

   * of the function, thus time. Thus, the RateLimiter becomes /faster/ after a period of
   * underutilization. If, on the other hand, we pick a function that goes /above/ that horizontal
   * line, then it means that the area (time) is increased, thus storedPermits are more costly than
   * fresh permits, thus the RateLimiter becomes /slower/ after a period of underutilization.
   *