# Response Model - Return Type

You can declare the type used for the response by annotating the *path operation function* **return type**.

You can use **type annotations** the same way you would for input data in function **parameters**, you can use Pydantic models, lists, dictionaries, scalar values like integers, booleans, etc.

=== "Python 3.10+"

    ```Python hl_lines="16  21"
    {!> ../../../docs_src/response_model/tutorial001_01_py310.py!}
    ```

It could look like this:

```JSON  hl_lines="7"
{
  "name": "frontend-app",
  "version": "1.0.0",
  "description": "",
  "main": "index.js",
  "scripts": {
    "generate-client": "openapi-ts --input http://localhost:8000/openapi.json --output ./src/client --client axios"
  },
  "author": "",
  "license": "",
  "devDependencies": {
    "@hey-api/openapi-ts": "^0.27.38",
    "typescript": "^4.6.2"
  }
}
```

```JSON
{
  "detail": [
    {
      "type": "int_parsing",
      "loc": [
        "path",
        "item_id"
      ],
      "msg": "Input should be a valid integer, unable to parse string as an integer",
      "input": "foo",
      "url": "https://errors.pydantic.dev/2.1/v/int_parsing"
    }
  ]
}
```

because the path parameter `item_id` had a value of `"foo"`, which is not an `int`.

```JSON
{
  "detail": [
    {
      "type": "int_parsing",
      "loc": [
        "path",
        "item_id"
      ],
      "msg": "Input should be a valid integer, unable to parse string as an integer",
      "input": "foo",
      "url": "https://errors.pydantic.dev/2.1/v/int_parsing"
    }
  ]
}
```

Der Pfad-Parameter `item_id` hatte den Wert `"foo"`, was kein `int` ist.

Ensuite, il 🤖 prendra la première tâche à finir (disons, notre "fichier-lent" 📝) et continuera à faire avec cette dernière ce qu'il était censé.

Ce "attendre quelque chose d'autre" fait généralement référence à des opérations <abbr title="Input/Output ou Entrées et Sorties ">I/O</abbr> qui sont relativement "lentes" (comparées à la vitesse du processeur et de la mémoire RAM) telles qu'attendre que :

* de la donnée soit envoyée par le client à travers le réseau

* Notes to be created (`NoteIn`).
* Notes to be returned (`Note`).

```Python hl_lines="31-33  36-39"
{!../../../docs_src/async_sql_databases/tutorial001.py!}
```

By creating these Pydantic models, the input data will be validated, serialized (converted), and annotated (documented).

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

## Connect and disconnect

* Create your `FastAPI` application.

    * Errori chiari e automatici quando i dati sono invalidi.
    * Validazione anche per gli oggetti JSON più complessi.
* <abbr title="anche noto come: serializzazione, parsing, marshalling">Conversione</abbr> dei dati di input: da risorse esterne a dati e tipi di Python. È possibile leggere da:
    * JSON.
    * Path parameters.
    * Query parameters.
    * Cookies.
    * Headers.
    * Form.
    * File.

!!! tip "Tipp"
    Beachten Sie, dass wir in diesem Fall eine Standard-Python-Funktion `open()` verwenden, die mit einer Datei interagiert.

    Es handelt sich also um I/O (Input/Output), welches „Warten“ erfordert, bis Dinge auf die Festplatte geschrieben werden.

    Aber `open()` verwendet nicht `async` und `await`.

!!! tip "Dica"
    Perceba que nesse caso nós estamos usando a função padrão do Python `open()` que interage com um arquivo.

    Então, isso envolve I/O (input/output), que exige "esperar" que coisas sejam escritas em disco.

    Mas `open()` não usa `async` e `await`.

    Então, nós declaramos uma função de manipulação de evento com o padrão `def` ao invés de `async def`.

Diese könnte so aussehen:

```JSON  hl_lines="7"
{
  "name": "frontend-app",
  "version": "1.0.0",
  "description": "",
  "main": "index.js",
  "scripts": {
    "generate-client": "openapi-ts --input http://localhost:8000/openapi.json --output ./src/client --client axios"
  },
  "author": "",
  "license": "",
  "devDependencies": {
    "@hey-api/openapi-ts": "^0.27.38",
    "typescript": "^4.6.2"
  }
}
```