Declara los **parámetros query** que necesitas en un **modelo de Pydantic**, y luego declara el parámetro como `Query`:

{* ../../docs_src/query_param_models/tutorial001_an_py310.py hl[9:13,17] *}

**FastAPI** **extraerá** los datos para **cada campo** de los **parámetros query** en el request y te proporcionará el modelo de Pydantic que definiste.

## Revisa la Documentación { #check-the-docs }

## A `dict` from the previous example { #a-dict-from-the-previous-example }

In the previous example, we were returning a `dict` from our dependency ("dependable"):

{* ../../docs_src/dependencies/tutorial001_an_py310.py hl[9] *}

But then we get a `dict` in the parameter `commons` of the *path operation function*.

## `dict` do exemplo anterior { #a-dict-from-the-previous-example }

No exemplo anterior, nós retornávamos um `dict` da nossa dependência ("injetável"):

{* ../../docs_src/dependencies/tutorial001_an_py310.py hl[9] *}

Mas assim obtemos um `dict` como valor do parâmetro `commons` na *função de operação de rota*.

Deklarieren Sie die benötigten **Query-Parameter** in einem **Pydantic-Modell** und dann den Parameter als `Query`:

{* ../../docs_src/query_param_models/tutorial001_an_py310.py hl[9:13,17] *}

Declare the **query parameters** that you need in a **Pydantic model**, and then declare the parameter as `Query`:

{* ../../docs_src/query_param_models/tutorial001_an_py310.py hl[9:13,17] *}

**FastAPI** will **extract** the data for **each field** from the **query parameters** in the request and give you the Pydantic model you defined.

## Check the Docs { #check-the-docs }

@pytest.fixture(
    name="client",
    params=[
        "tutorial001_py39",
        pytest.param("tutorial001_py310", marks=needs_py310),
        "tutorial001_an_py39",
        pytest.param("tutorial001_an_py310", marks=needs_py310),
    ],
)
def get_client(request: pytest.FixtureRequest):
    mod = importlib.import_module(f"docs_src.additional_status_codes.{request.param}")

    client = TestClient(mod.app)

/// note

自 FastAPI 版本 `0.115.0` 起支持此功能。🤓

///

## 使用 Pydantic 模型的 Header 参数

在 **Pydantic 模型**中声明所需的 **header 参数**，然后将参数声明为 `Header` :

{* ../../docs_src/header_param_models/tutorial001_an_py310.py hl[9:14,18] *}

**FastAPI** 将从请求中接收到的 **headers** 中**提取**出**每个字段**的数据，并提供您定义的 Pydantic 模型。

## 查看文档

您可以在文档 UI 的 `/docs` 中查看所需的 headers：

<div class="screenshot">

## Importer Path

Tout d'abord, importez `Path` de `fastapi`, et importez `Annotated` :

{* ../../docs_src/path_params_numeric_validations/tutorial001_an_py310.py hl[1,3] *}

/// info

FastAPI a ajouté le support pour `Annotated` (et a commencé à le recommander) dans la version 0.95.0.

## Importe `Path` { #import-path }

Primeiro, importe `Path` de `fastapi`, e importe `Annotated`:

{* ../../docs_src/path_params_numeric_validations/tutorial001_an_py310.py hl[1,3] *}

/// info | Informação

O FastAPI adicionou suporte a `Annotated` (e passou a recomendá-lo) na versão 0.95.0.

Se você tiver uma versão mais antiga, verá erros ao tentar usar `Annotated`.

@pytest.fixture(
    name="client",
    params=[
        "tutorial001_py39",
        pytest.param("tutorial001_py310", marks=needs_py310),
        "tutorial001_an_py39",
        pytest.param("tutorial001_an_py310", marks=needs_py310),
    ],
)
def get_client(request: pytest.FixtureRequest):
    mod = importlib.import_module(f"docs_src.body_multiple_params.{request.param}")

    client = TestClient(mod.app)