* Como as estruturas de dados do Pydantic são apenas instâncias de classes que você define, a auto completação, _linting_, _mypy_ e a sua intuição devem funcionar corretamente com seus dados validados.
* Valida **estruturas complexas**:
    * Use modelos hierárquicos do Pydantic, `List` e `Dict` do `typing` do Python, etc.

* Valida **estructuras complejas**:
    * Usa modelos jerárquicos de modelos de Pydantic, `typing` de Python,  `List` y `Dict`, etc.

    with pytest.raises(ResponseValidationError):
        client.get("/items/invalidnone")


def test_valid_none_data():
    response = client.get("/items/validnone")
    data = response.json()
    assert response.status_code == 200
    assert data == {"name": "invalid", "price": 3.2, "owner_ids": None}


def test_valid_none_none():
    response = client.get("/items/validnone", params={"send_none": "true"})
    data = response.json()

        raise fastapi.exceptions.FastAPIError(
            "Invalid args for response field! Hint: "
            f"check that {type_} is a valid Pydantic field type. "
            "If you are using a return type annotation that is not a valid Pydantic "
            "field (e.g. Union[Response, dict, None]) you can disable generating the "

```Python
q: Union[str, None] = Query(default=None, max_length=50)
```

Cela va valider les données, montrer une erreur claire si ces dernières ne sont pas valides, et documenter le paramètre dans le schéma `OpenAPI` de cette *path operation*.

## Rajouter plus de validation

Vous pouvez aussi rajouter un second paramètre `min_length` :

The same would happen if you had something like a <abbr title='A union between multiple types means "any of these types".'>union</abbr> between different types where one or more of them are not valid Pydantic types, for example this would fail 💥:

        {
            "detail": [
                {
                    "type": "int_parsing",
                    "loc": ["query", "query"],
                    "msg": "Input should be a valid integer, unable to parse string as an integer",
                    "input": "42.5",
                }
            ]
        }
    ) | IsDict(
        # TODO: remove when deprecating Pydantic v1
        {

        {
            "detail": [
                {
                    "type": "float_parsing",
                    "loc": ["body", "price"],
                    "msg": "Input should be a valid number, unable to parse string as a number",
                    "input": "twenty",
                }
            ]
        }
    ) | IsDict(
        # TODO: remove when deprecating Pydantic v1
        {

        {
            "detail": [
                {
                    "type": "float_parsing",
                    "loc": ["body", "price"],
                    "msg": "Input should be a valid number, unable to parse string as a number",
                    "input": "twenty",
                }
            ]
        }
    ) | IsDict(
        # TODO: remove when deprecating Pydantic v1
        {

                    "loc": ["query", "skip"],
                    "msg": "Input should be a valid integer, unable to parse string as an integer",
                    "input": "a",
                },
                {
                    "type": "int_parsing",
                    "loc": ["query", "limit"],
                    "msg": "Input should be a valid integer, unable to parse string as an integer",
                    "input": "b",