* Conversión de datos
* Validación de datos
* Documentación automática

## Tipos especiales y validación { #special-types-and-validation }

Además de tipos singulares normales como `str`, `int`, `float`, etc., puedes usar tipos singulares más complejos que heredan de `str`.

	//	}
	MOVB	R1, R2

	//	LMOVB addr ',' rreg
	//	{
	//		outcode(int($1), &$2, 0, &$4);
	//	}
	MOVB	foo<>+3(SB), R2
	MOVB	16(R1), R2
	MOVB	(R1), R2

	//
	// load floats
	//
	//	LFMOV addr ',' freg
	//	{
	//		outcode(int($1), &$2, 0, &$4);
	//	}
	MOVF	foo<>+3(SB), F2
	MOVF	16(R1), F2
	MOVF	(R1), F2

	//	LFMOV fimm ',' freg
	//	{
	//		outcode(int($1), &$2, 0, &$4);

pkg math/big, method (*Int) SetUint64(uint64) *Int
pkg math/big, method (*Int) Uint64() uint64
pkg math/big, method (*Int) UnmarshalJSON([]uint8) error
pkg math/big, method (*Rat) Float64() (float64, bool)
pkg math/big, method (*Rat) SetFloat64(float64) *Rat
pkg mime/multipart, method (*Writer) SetBoundary(string) error
pkg net, const FlagBroadcast = 2
pkg net, const FlagLoopback = 4
pkg net, const FlagMulticast = 16

from fastapi import APIRouter, FastAPI
from pydantic import BaseModel, HttpUrl

app = FastAPI()


class Invoice(BaseModel):
    id: str
    title: Union[str, None] = None
    customer: str
    total: float


class InvoiceEvent(BaseModel):
    description: str
    paid: bool


class InvoiceEventReceived(BaseModel):
    ok: bool


invoices_callback_router = APIRouter()

* `le`: `l`ess than or `e`qual (менше або дорівнює)

{* ../../docs_src/path_params_numeric_validations/tutorial005_an_py39.py hl[10] *}

## Валідація числових даних: float, більше ніж і менше ніж

Валідація чисел також працює для значень типу `float`.

# Introduction aux Types Python

Python supporte des annotations de type (ou *type hints*) optionnelles.

Ces annotations de type constituent une syntaxe spéciale qui permet de déclarer le <abbr title="par exemple : str, int, float, bool">type</abbr> d'une variable.

En déclarant les types de vos variables, cela permet aux différents outils comme les éditeurs de texte d'offrir un meilleur support.

from fastapi.testclient import TestClient
from pydantic import BaseModel, HttpUrl

app = FastAPI()


class Invoice(BaseModel):
    id: str
    title: Optional[str] = None
    customer: str
    total: float


class InvoiceEvent(BaseModel):
    description: str
    paid: bool


class InvoiceEventReceived(BaseModel):
    ok: bool


invoices_callback_router = APIRouter()

from fastapi.testclient import TestClient
from pydantic import BaseModel

app = FastAPI()


class ItemGroup(BaseModel):
    items: list[tuple[str, str]]


class Coordinate(BaseModel):
    x: float
    y: float


@app.post("/model-with-tuple/")
def post_model_with_tuple(item_group: ItemGroup):
    return item_group


@app.post("/tuple-of-models/")

def test_get_timed(client: TestClient):
    response = client.get("/timed")
    assert response.json() == {"message": "It's the time of my life"}
    assert "X-Response-Time" in response.headers

* Datenkonvertierung
* Datenvalidierung
* Automatische Dokumentation

## Spezielle Typen und Validierungen { #special-types-and-validation }

Abgesehen von normalen einfachen Typen wie `str`, `int`, `float`, usw. können Sie komplexere einfache Typen verwenden, die von `str` erben.