///

{* ../../docs_src/security/tutorial005_an_py310.py hl[157] *}

## Declare scopes in *path operations* and dependencies { #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`.

        val distributionRuntimeOnly = bucket("${prefix}TestDistributionRuntimeOnly", "Declare the distribution that is required to run tests")
        val localRepository = bucket("${prefix}TestLocalRepository", "Declare a local repository required as input data for the tests (e.g. :tooling-api)")

```Python
q: Annotated[str | None, Query(min_length=3)] = None
```

So, when you need to declare a value as required while using `Query`, you can simply not declare a default value:

{* ../../docs_src/query_params_str_validations/tutorial006_an_py39.py hl[9] *}

### Required, can be `None` { #required-can-be-none }

{* ../../docs_src/python_types/tutorial004_py39.py hl[2] *}

## Declaring types { #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 { #simple-types }

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

You can use, for example:

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

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.

/// 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 { #response-model-priority }

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.

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).

vous verrez comme réponse :

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

## Paramètres de chemin typés

Vous pouvez déclarer le type d'un paramètre de chemin dans la fonction, en utilisant les annotations de type Python :


{* ../../docs_src/path_params/tutorial002.py hl[7] *}

Ici, `item_id` est déclaré comme `int`.

/// check | vérifier

Ceci vous permettra d'obtenir des fonctionnalités de l'éditeur dans votre fonction, telles

Se você está se perguntando, "AlexNet", "ResNet" e "LeNet" são apenas nomes de <abbr title="Tecnicamente, arquiteturas de modelos de Deep Learning">modelos</abbr> de Aprendizado de Máquina.
///

### Declare um parâmetro de path { #declare-a-path-parameter }

Em seguida, crie um *parâmetro de path* com anotação de tipo usando a classe enum que você criou (`ModelName`):

{* ../../docs_src/path_params/tutorial005_py39.py hl[16] *}