Diese Typen mit inneren Typen werden „**generische**“ Typen genannt. Es ist möglich, sie mit ihren inneren Typen zu deklarieren.

Um diese Typen und die inneren Typen zu deklarieren, können Sie Pythons Standardmodul `typing` verwenden. Es existiert speziell für die Unterstützung dieser Typhinweise.

#### Neuere Python-Versionen { #newer-versions-of-python }

# Introdução aos tipos Python { #python-types-intro }

O Python possui suporte para "dicas de tipo" ou "type hints" (também chamado de "anotações de tipo" ou "type annotations")

Esses **"type hints"** são uma sintaxe especial que permite declarar o <abbr title = "por exemplo: str, int, float, bool">tipo</abbr> de uma variável.

Ao declarar tipos para suas variáveis, editores e ferramentas podem oferecer um melhor suporte.

These types that have internal types are called "**generic**" types. And it's possible to declare them, even with their internal types.

To declare those types and the internal types, you can use the standard Python module `typing`. It exists specifically to support these type hints.

#### Newer versions of Python { #newer-versions-of-python }

### Tipos simples { #simple-types }

Puedes declarar todos los tipos estándar de Python, no solo `str`.

Puedes usar, por ejemplo:

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

{* ../../docs_src/python_types/tutorial005_py39.py hl[1] *}

### Tipos genéricos con parámetros de tipo { #generic-types-with-type-parameters }

### Простые типы { #simple-types }

Вы можете объявлять все стандартные типы Python, не только `str`.

Можно использовать, например:

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

{* ../../docs_src/python_types/tutorial005_py39.py hl[1] *}

### Generic-типы с параметрами типов { #generic-types-with-type-parameters }

import types
from enum import Enum
from typing import Any, Callable, Optional, TypeVar, Union

from pydantic import BaseModel

DecoratedCallable = TypeVar("DecoratedCallable", bound=Callable[..., Any])
UnionType = getattr(types, "UnionType", Union)
ModelNameMap = dict[Union[type[BaseModel], type[Enum]], str]
IncEx = Union[set[int], set[str], dict[int, Any], dict[str, Any]]

## **Typer**, das FastAPI der CLIs { #typer-the-fastapi-of-clis }

<a href="https://typer.tiangolo.com" target="_blank"><img src="https://typer.tiangolo.com/img/logo-margin/logo-margin-vector.svg" style="width: 20%;"></a>

* `Decimal`:
    * `Decimal` estándar de Python.
    * En requests y responses, manejado igual que un `float`.
* Puedes revisar todos los tipos de datos válidos de Pydantic aquí: <a href="https://docs.pydantic.dev/latest/usage/types/types/" class="external-link" target="_blank">Tipos de datos de Pydantic</a>.

## Ejemplo { #example }

Aquí tienes un ejemplo de una *path operation* con parámetros usando algunos de los tipos anteriores.

from docs_src.custom_response.tutorial006_py39 import app

client = TestClient(app)


def test_get():
    response = client.get("/typer", follow_redirects=False)
    assert response.status_code == 307, response.text
    assert response.headers["location"] == "https://typer.tiangolo.com"


def test_openapi_schema():
    response = client.get("/openapi.json")
    assert response.status_code == 200, response.text

    return BodyModel


def get_model_fields(model: type[BaseModel]) -> list[ModelField]:
    model_fields: list[ModelField] = []
    for name, field_info in model.model_fields.items():
        type_ = field_info.annotation
        if lenient_issubclass(type_, (BaseModel, dict)) or is_dataclass(type_):
            model_config = None
        else: