# Body - Fields

The same way you can declare additional validation and metadata in *path operation function* parameters with `Query`, `Path` and `Body`, you can declare validation and metadata inside of Pydantic models using Pydantic's `Field`.

## Import `Field`

First, you have to import it:

=== "Python 3.10+"

    ```Python hl_lines="4"
    {!> ../../../docs_src/body_fields/tutorial001_an_py310.py!}
    ```

=== "Python 3.9+"

```JSON
{"item_id":"foo"}
```

## Path parameters with types

You can declare the type of a path parameter in the function, using standard Python type annotations:

```Python hl_lines="7"
{!../../../docs_src/path_params/tutorial002.py!}
```

In this case, `item_id` is declared to be an `int`.

!!! check
    This will give you editor support inside of your function, with error checks, completion, etc.

!!! tip
    If you have strict type checks in your editor, mypy, etc, you can declare the function return type as `Any`.

    That way you tell the editor that you are intentionally returning anything. But FastAPI will still do the data documentation, validation, filtering, etc. with the `response_model`.

### `response_model` Priority

    ] = True,
) -> Any:
    """
    Declare a FastAPI Security dependency.

    The only difference with a regular dependency is that it can declare OAuth2
    scopes that will be integrated with OpenAPI and the automatic UI docs (by default
    at `/docs`).

    It takes a single "dependable" callable (like a function).

    Don't call it directly, FastAPI will call it for you.

    Read more about it in the

The dependency injection system requires pre-registration of the dependencies and the dependencies are solved based on the declared types. So, it's not possible to declare more than one "component" that provides a certain type.

# Background Tasks - `BackgroundTasks`

You can declare a parameter in a *path operation function* or dependency function with the type `BackgroundTasks`, and then you can use it to schedule the execution of background tasks after the response is sent.

You can import it directly from `fastapi`:

```python
from fastapi import BackgroundTasks
```

# `Request` class

You can declare a parameter in a *path operation function* or dependency to be of type `Request` and then you can access the raw request object directly, without any validation, etc.

You can import it directly from `fastapi`:

```python
from fastapi import Request
```

!!! tip

## Adicione informações extras

Você pode declarar informação extra em `Field`, `Query`, `Body`, etc. E isso será incluído no JSON Schema gerado.

Você irá aprender mais sobre adicionar informações extras posteriormente nessa documentação, quando estiver aprendendo a declarar exemplos.

## Recapitulando

Você pode usar `Field` do Pydantic para declarar validações extras e metadados para atributos do modelo.

## Importe `Cookie`

Primeiro importe `Cookie`:

```Python hl_lines="3"
{!../../../docs_src/cookie_params/tutorial001.py!}
```

## Declare parâmetros de `Cookie`

Então declare os paramêtros de cookie usando a mesma estrutura que em `Path` e `Query`.

O primeiro valor é o valor padrão, você pode passar todas as validações adicionais ou parâmetros de anotação:

    ```Python hl_lines="31"
    {!> ../../../docs_src/security/tutorial002.py!}
    ```

Notice that we declare the type of `current_user` as the Pydantic model `User`.

This will help us inside of the function with all the completion and type checks.

!!! tip
    You might remember that request bodies are also declared with Pydantic models.

    Here **FastAPI** won't get confused because you are using `Depends`.

!!! check