**FastAPI** prendra le modèle Pydantic à partir de là, générera le `JSON Schema` et le placera au bon endroit.

Le bon endroit est :

* Dans la clé `content`, qui a pour valeur un autre objet JSON (`dict`) qui contient :
    * Une clé avec le type de support, par ex. `application/json`, qui contient comme valeur un autre objet JSON, qui contient :
        * Une clé `schema`, qui a pour valeur le schéma JSON du modèle, voici le bon endroit.

    url: AnyUrl


# Ref JSON Schema 2020-12: https://json-schema.org/draft/2020-12/json-schema-validation#name-type
SchemaType = Literal[
    "array", "boolean", "integer", "null", "number", "object", "string"
]


class Schema(BaseModelWithConfig):
    # Ref: JSON Schema 2020-12: https://json-schema.org/draft/2020-12/json-schema-core.html#name-the-json-schema-core-vocabu
    # Core Vocabulary

// Identity represents access key who caused the event.
type Identity struct {
	Type        string `json:"type"`
	PrincipalID string `json:"principalId"`
	AccessKeyID string `json:"accessKeyId"`
}

// UserRequest user request headers
type UserRequest struct {
	URL     string      `json:"url"`
	Headers http.Header `json:"headers"`
}

// GetObjectContext provides the necessary details to perform

    response = client.get(path)
    assert response.status_code == expected_status
    assert response.json() == expected_response


def test_openapi_schema():
    client = TestClient(app)
    response = client.get("/openapi.json")
    assert response.status_code == 200
    assert response.json() == snapshot(
        {
            "openapi": "3.1.0",
            "info": {"title": "FastAPI", "version": "0.1.0"},

                    // Filtering an array is NOT in place
                    result.acceptedApiChanges = result.acceptedApiChanges.filter((item, pos, ary) => (!pos || (JSON.stringify(item) != JSON.stringify(ary[pos - 1]))));
                    return result;
                }

///

## Mehrere Body-Parameter { #multiple-body-parameters }

Im vorherigen Beispiel erwarteten die *Pfadoperationen* einen JSON-Body mit den Attributen eines `Item`s, etwa:

```JSON
{
    "name": "Foo",
    "description": "The pretender",
    "price": 42.0,
    "tax": 3.2
}
```

Aber Sie können auch mehrere Body-Parameter deklarieren, z. B. `item` und `user`:

///

## Multiple body parameters { #multiple-body-parameters }

In the previous example, the *path operations* would expect a JSON body with the attributes of an `Item`, like:

```JSON
{
    "name": "Foo",
    "description": "The pretender",
    "price": 42.0,
    "tax": 3.2
}
```

But you can also declare multiple body parameters, e.g. `item` and `user`:

## Atributos con listas de submodelos { #attributes-with-lists-of-submodels }

También puedes usar modelos Pydantic como subtipos de `list`, `set`, etc.:

{* ../../docs_src/body_nested_models/tutorial006_py310.py hl[18] *}

Esto esperará (convertirá, validará, documentará, etc.) un cuerpo JSON como:

```JSON hl_lines="11"
{
    "name": "Foo",

*경로 처리*를 지원 중단(deprecate)으로 표시하고, 문서 UI에 보여주려면 [튜토리얼 - 경로 처리 구성 - 지원 중단](../tutorial/path-operation-configuration.md#deprecate-a-path-operation) 문서를 읽어보세요.

## 어떤 데이터든 JSON 호환으로 변환하기 { #convert-any-data-to-json-compatible }

어떤 데이터든 JSON 호환 형식으로 변환하려면 [튜토리얼 - JSON 호환 인코더](../tutorial/encoder.md) 문서를 읽어보세요.

## OpenAPI 메타데이터 - 문서 { #openapi-metadata-docs }

    """When no response_class is set, the fast path serializes directly to
    JSON bytes via Pydantic's dump_json and never calls json.dumps."""
    with patch(
        "starlette.responses.json.dumps", wraps=__import__("json").dumps
    ) as mock_dumps:
        response = client.get("/default")
    assert response.status_code == 200
    assert response.json() == {"name": "widget", "price": 9.99}
    mock_dumps.assert_not_called()