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

Así que, cuando necesites declarar un valor como requerido mientras usas `Query`, simplemente puedes no declarar un valor por defecto:

{* ../../docs_src/query_params_str_validations/tutorial006_an_py310.py hl[9] *}

### Requerido, puede ser `None` { #required-can-be-none }

It will include all the routes from that router as part of it.

/// note | Technical Details

It will actually internally create a *path operation* for each *path operation* that was declared in the `APIRouter`.

So, behind the scenes, it will actually work as if everything was the same single app.

///

/// check

You don't have to worry about performance when including routers.

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

## Declarar scopes en *path operations* y dependencias { #declare-scopes-in-path-operations-and-dependencies }

Ahora declaramos que la *path operation* para `/users/me/items/` requiere el scope `items`.

Para esto, importamos y usamos `Security` de `fastapi`.

## Crear un modelo de usuario { #create-a-user-model }

Primero, vamos a crear un modelo de usuario con Pydantic.

De la misma manera que usamos Pydantic para declarar cuerpos, podemos usarlo en cualquier otra parte:

{* ../../docs_src/security/tutorial002_an_py310.py hl[5,12:6] *}

## Crear una dependencia `get_current_user` { #create-a-get-current-user-dependency }

Toutes les dépendances que nous avons vues étaient des fonctions ou des classes fixes.

Mais il peut y avoir des cas où vous souhaitez pouvoir définir des paramètres sur la dépendance, sans devoir déclarer de nombreuses fonctions ou classes différentes.

Imaginons que nous voulions avoir une dépendance qui vérifie si le paramètre de requête `q` contient un contenu fixe.

Mais nous voulons pouvoir paramétrer ce contenu fixe.

fastapi dev
```


Run the production server:

```bash
fastapi run
```

### Add an entrypoint in `pyproject.toml`

FastAPI CLI will read the entrypoint in `pyproject.toml` to know where the FastAPI app is declared.

```toml
[tool.fastapi]
entrypoint = "my_app.main:app"
```

### Use `fastapi` with a path

# Body - Fields { #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` { #import-field }

First, you have to import it:

{* ../../docs_src/body_fields/tutorial001_an_py310.py hl[4] *}


/// warning

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 { #list-fields-with-type-parameter }

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

### Declare a `list` with a type parameter { #declare-a-list-with-a-type-parameter }

To declare types that have type parameters (internal types), like `list`, `dict`, `tuple`,

Si tienes chequeo de tipos estricto en tu editor, mypy, etc., puedes declarar el tipo de retorno de la función como `Any`.

De esa manera le dices al editor que intencionalmente estás devolviendo cualquier cosa. Pero FastAPI todavía hará la documentación de datos, validación, filtrado, etc. con `response_model`.

///

### Prioridad del `response_model` { #response-model-priority }

## Import `Header` { #import-header }

First import `Header`:

{* ../../docs_src/header_params/tutorial001_an_py310.py hl[3] *}

## Declare `Header` parameters { #declare-header-parameters }

Then declare the header parameters using the same structure as with `Path`, `Query` and `Cookie`.

You can define the default value as well as all the extra validation or annotation parameters: