Diese Funktionen können mit `async def` oder normalem `def` deklariert werden.

### `startup`-Event

Um eine Funktion hinzuzufügen, die vor dem Start der Anwendung ausgeführt werden soll, deklarieren Sie diese mit dem Event `startup`:

```Python hl_lines="8"
{!../../../docs_src/events/tutorial001.py!}
```

</p>
<p align="center">
<a href="https://github.com/tiangolo/fastapi/actions?query=workflow%3ATest+event%3Apush+branch%3Amaster" target="_blank">
    <img src="https://github.com/tiangolo/fastapi/workflows/Test/badge.svg?event=push&branch=master" alt="Test">
</a>
<a href="https://codecov.io/gh/tiangolo/fastapi" target="_blank">

href="https://stackoverflow.com/questions/41584243/runtimeerror-task-attached-to-a-different-loop" class="external-link" target="_blank">MongoDBs MotorClient</a>), dann denken Sie daran, Objekte zu instanziieren, die einen Event Loop nur innerhalb asynchroner Funktionen benötigen, z. B. einen `@app.on_event("startup")`-Callback....

So, you will be able to see it all in the interactive API docs.

## Connect and disconnect

* Create your `FastAPI` application.
* Create event handlers to connect and disconnect from the database.

```Python hl_lines="42  45-47  50-52"
{!../../../docs_src/async_sql_databases/tutorial001.py!}
```

## Read notes

https://yourapi.com/invoices/?callback_url=https://www.external.org/events
```

mit einem JSON-Körper:

```JSON
{
    "id": "2expen51ve",
    "customer": "Mr. Richie Rich",
    "total": "9999"
}
```

dann verarbeitet *Ihre API* die Rechnung und sendet irgendwann später einen Callback-Request an die `callback_url` (die *externe API*):

```
https://www.external.org/events/invoices/2expen51ve
```

```
https://yourapi.com/invoices/?callback_url=https://www.external.org/events
```

⏮️ 🎻 💪:

```JSON
{
    "id": "2expen51ve",
    "customer": "Mr. Richie Rich",
    "total": "9999"
}
```

⤴️ *👆 🛠️* 🔜 🛠️ 🧾, & ☝ ⏪, 📨 ⏲ 📨 `callback_url` ( *🔢 🛠️*):

```
https://www.external.org/events/invoices/2expen51ve
```

⏮️ 🎻 💪 ⚗ 🕳 💖:

```JSON
{

It has:

* Seriously impressive performance.
* WebSocket support.
* In-process background tasks.
* Startup and shutdown events.
* Test client built on HTTPX.
* CORS, GZip, Static Files, Streaming responses.
* Session and Cookie support.
* 100% test coverage.
* 100% type annotated codebase.
* Few hard dependencies.

### `response_model` Priority

If you declare both a return type and a `response_model`, the `response_model` will take priority and be used by FastAPI.

This way you can add correct type annotations to your functions even when you are returning a type different than the response model, to be used by the editor and tools like mypy. And still you can have FastAPI do the data validation, documentation, etc. using the `response_model`.

    * If you didn't use FastAPI and used Starlette directly (or another tool, like Sanic, Flask, Responder, etc) you would have to implement all the data validation and serialization...

So, even with the code above that doesn't use Pydantic explicitly, FastAPI is using Pydantic to convert those standard dataclasses to Pydantic's own flavor of dataclasses.

And of course, it supports the same:

* data validation