///

{* ../../docs_src/security/tutorial005_an_py310.py hl[156] *}

## Declare scopes in *path operations* and dependencies

Now we declare that the *path operation* for `/users/me/items/` requires the scope `items`.

For this, we import and use `Security` from `fastapi`.

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, can be `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

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

///

/// 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".

{* ../../docs_src/python_types/tutorial004.py hl[2] *}

## Declaring types

You just saw the main place to declare type hints. As function parameters.

This is also the main place you would use them with **FastAPI**.

### Simple types

You can declare all the standard Python types, not only `str`.

You can use, for example:

* `int`
* `float`
* `bool`
* `bytes`

# 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.

//// tab | Python 3.10+ Pydantic v2

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

////

Because each SQLModel model is also a Pydantic model, you can use it in the same **type annotations** that you could use Pydantic models.

For example, if you declare a parameter of type `Hero`, it will be read from the **JSON body**.

The same way, you can declare it as the function's **return type**, and then the shape of the data will show up in the automatic API docs UI.

   *
   * @return this method does not return; it always throws
   * @throws IOException when the given throwable is an IOException
   * @throws X1 when the given throwable is of the declared type X1
   * @throws X2 when the given throwable is of the declared type X2
   */
  public <X1 extends Exception, X2 extends Exception> RuntimeException rethrow(
      Throwable e, Class<X1> declaredType1, Class<X2> declaredType2) throws IOException, X1, X2 {

But if you return a `Response` directly (or any subclass, like `JSONResponse`), the data won't be automatically converted (even if you declare a `response_model`), and the documentation won't be automatically generated (for example, including the specific "media type", in the HTTP header `Content-Type` as part of the generated OpenAPI).

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.