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.

    ```

The files and form fields will be uploaded as form data and you will receive the files and form fields.

And you can declare some of the files as `bytes` and some as `UploadFile`.

!!! warning
    You can declare multiple `File` and `Form` parameters in a *path operation*, but you can't also declare `Body` fields that you expect to receive as JSON, as the request will have the body encoded using `multipart/form-data` instead of `application/json`.

    Então, você deve declará-lo com `...` para marcá-lo como obrigatório.

    Mesmo que você declare-o como `None` ou defina um valor padrão, isso não teria efeito algum, o parâmetro ainda seria obrigatório.

## Ordene os parâmetros de acordo com sua necessidade

Suponha que você queira declarar o parâmetro de consulta `q` como uma `str` obrigatória.

# 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
```

    ```

This will make `tags` be a list, although it doesn't declare the type of the elements of the list.

## List fields with type parameter

But Python has a specific way to declare lists with internal types, or "type parameters":

### Import typing's `List`

In Python 3.9 and above you can use the standard `list` to declare these type annotations as we'll see below. 💡

# Declare Request Example Data

You can declare examples of the data your app can receive.

Here are several ways to do it.

## Extra JSON Schema data in Pydantic models

You can declare `examples` for a Pydantic model that will be added to the generated JSON Schema.

=== "Python 3.10+ Pydantic v2"

    ```Python hl_lines="13-24"
    {!> ../../../docs_src/schema_extra_example/tutorial001_py310.py!}
    ```

# `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

## 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).

    It is used by Pydantic and FastAPI to explicitly declare that a value is required.

This will let **FastAPI** know that this parameter is required.

### Required with `None`

You can declare that a parameter can accept `None`, but that it's still required. This would force clients to send a value, even if the value is `None`.

To do that, you can declare that `None` is a valid type but still use `...` as the default:

!!! tip
    To declare File bodies, you need to use `File`, because otherwise the parameters would be interpreted as query parameters or body (JSON) parameters.

The files will be uploaded as "form data".