We could do better.

We can declare a `UserBase` model that serves as a base for our other models. And then we can make subclasses of that model that inherit its attributes (type declarations, validation, etc).

All the data conversion, validation, documentation, etc. will still work as normally.

```

////

//// tab | Python 3.8+

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

////

## Declare parâmetros de `Header`

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

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

# Response Headers

## Use a `Response` parameter

You can declare a parameter of type `Response` in your *path operation function* (as you can do for cookies).

And then you can set headers in that *temporal* response object.

```Python hl_lines="1  7-8"
{!../../docs_src/response_headers/tutorial002.py!}
```

And then you can return any object you need, as you normally would (a `dict`, a database model, etc).

/// note | Nota

Isso é possível desde a versão `0.115.0` do FastAPI. 🤓

///

## Parâmetros do Cabeçalho com um Modelo Pydantic

Declare os **parâmetros de cabeçalho** que você precisa em um **modelo do Pydantic**, e então declare o parâmetro como `Header`:

//// tab | Python 3.10+

```Python hl_lines="9-14  18"
{!> ../../docs_src/header_param_models/tutorial001_an_py310.py!}
```

////

## What is "Dependency Injection"

**"Dependency Injection"** means, in programming, that there is a way for your code (in this case, your *path operation functions*) to declare things that it requires to work and use: "dependencies".

And then, that system (in this case **FastAPI**) will take care of doing whatever is needed to provide your code with those needed dependencies ("inject" the dependencies).

# you may need to define a router file `my.application.routes`.
# Default to Routes in the root package (and `conf/routes`)
# application.router=my.application.Routes

# Database configuration
# ~~~~~
# You can declare as many datasources as you want.
# By convention, the default datasource is named `default`
#
# db.default.driver=org.h2.Driver
# db.default.url="jdbc:h2:mem:play"
# db.default.user=sa
# db.default.password=""
#

# 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
```

///

/// tip | Dica

Essa mesma técnica se aplica para `Query`, `Cookie`, e `Header`. 😎

///

## Cookies com Modelos Pydantic

Declare o parâmetro de **cookie** que você precisa em um **modelo Pydantic**, e depois declare o parâmetro como um `Cookie`:

//// tab | Python 3.10+

```Python hl_lines="9-12  16"
{!> ../../docs_src/cookie_param_models/tutorial001_an_py310.py!}
```

////

# Response Cookies

## Use a `Response` parameter

You can declare a parameter of type `Response` in your *path operation function*.

And then you can set cookies in that *temporal* response object.

```Python hl_lines="1  8-9"
{!../../docs_src/response_cookies/tutorial002.py!}
```

And then you can return any object you need, as you normally would (a `dict`, a database model, etc).

            dependency is called again (if declared more than once) in the same request.
            """
        ),
    ] = 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`).