### Async Context Manager

If you check, the function is decorated with an `@asynccontextmanager`.

That converts the function into something called an "**async context manager**".

```Python hl_lines="1  13"
{!../../../docs_src/events/tutorial003.py!}
```

This practice is common enough that it has a name, these environment variables are commonly placed in a file `.env`, and the file is called a "dotenv".

!!! tip
    A file starting with a dot (`.`) is a hidden file in Unix-like systems, like Linux and macOS.

    But a dotenv file doesn't really have to have that exact filename.

...Python has a little special syntax for that.

Pass `*`, as the first parameter of the function.

Python won't do anything with that `*`, but it will know that all the following parameters should be called as keyword arguments (key-value pairs), also known as <abbr title="From: K-ey W-ord Arg-uments"><code>kwargs</code></abbr>. Even if they don't have a default value.

```Python hl_lines="7"

# Dependencies with yield

FastAPI supports dependencies that do some <abbr title='sometimes also called "exit code", "cleanup code", "teardown code", "closing code", "context manager exit code", etc.'>extra steps after finishing</abbr>.

To do this, use `yield` instead of `return`, and write the extra steps (code) after.

!!! tip
    Make sure to use `yield` one single time.

!!! note "Technical Details"
    Any function that is valid to use with:

!!! tip
    There's an equivalent article using Peewee here in the docs.

## File structure

For these examples, let's say you have a directory named `my_super_project` that contains a sub-directory called `sql_app` with a structure like this:

```
.
└── sql_app
    ├── __init__.py
    ├── crud.py
    ├── database.py
    ├── main.py
    ├── models.py
    └── schemas.py
```

Wenn Sie eine API haben, die jedes Mal eine vergleichbare Menge an Berechnungen durchführt, und Sie viele Clients haben, dann wird die **CPU-Auslastung** wahrscheinlich *ebenfalls stabil sein* (anstatt ständig schnell zu steigen und zu fallen).

### Beispiele für Replikation-Tools und -Strategien

But by following the steps above, it will be able to do some performance optimizations.

## Technical Details

Modern versions of Python have support for **"asynchronous code"** using something called **"coroutines"**, with **`async` and `await`** syntax.

Let's see that phrase by parts in the sections below:

* **Asynchronous Code**
* **`async` and `await`**
* **Coroutines**

## Asynchronous Code

    return [{"item_id": "Foo"}]


def use_route_names_as_operation_ids(app: FastAPI) -> None:
    """
    Simplify operation IDs so that generated API clients have simpler function
    names.

    Should be called only after all routes have been added.
    """
    for route in app.routes:
        if isinstance(route, APIRoute):
            route.operation_id = route.name  # in this case, 'read_items'

## pytest.mark.anyio

If we want to call asynchronous functions in our tests, our test functions have to be asynchronous. AnyIO provides a neat plugin for this, that allows us to specify that some test functions are to be called asynchronously.

## HTTPX

Even if your **FastAPI** application uses normal `def` functions instead of `async def`, it is still an `async` application underneath.

Most of the code is actually the same.

So, we are going to focus only on the differences.

## File structure

Let's say you have a directory named `my_super_project` that contains a sub-directory called `sql_app` with a structure like this:

```
.
└── sql_app
    ├── __init__.py
    ├── crud.py
    ├── database.py
    ├── main.py
    └── schemas.py
```