* Data conversion
* Data validation
* Automatic documentation

## Special types and validation { #special-types-and-validation }

Apart from normal singular types like `str`, `int`, `float`, etc. you can use more complex singular types that inherit from `str`.

* Преобразование данных
* Валидацию данных
* Автоматическую документацию

## Особые типы и валидация { #special-types-and-validation }

Помимо обычных простых типов, таких как `str`, `int`, `float` и т.д., вы можете использовать более сложные простые типы, которые наследуются от `str`.

def process_items(prices: dict[str, float]):
    for item_name, item_price in prices.items():
        print(item_name)

from fastapi.testclient import TestClient
from pydantic.dataclasses import dataclass

app = FastAPI()


@dataclass
class Item:
    name: str
    price: Optional[float] = None
    owner_ids: Optional[list[int]] = None


@app.get("/items/invalid", response_model=Item)
def get_invalid():
    return {"name": "invalid", "price": "foo"}

  @Override
  void writeShort(int v);

  @Override
  void writeChar(int v);

  @Override
  void writeInt(int v);

  @Override
  void writeLong(long v);

  @Override
  void writeFloat(float v);

  @Override
  void writeDouble(double v);

  @Override
  void writeChars(String s);

  @Override
  void writeUTF(String s);

  /**

from fastapi import FastAPI, Path, Query

app = FastAPI()


@app.get("/items/{item_id}")
async def read_items(
    *,
    item_id: int = Path(title="The ID of the item to get", ge=0, le=1000),
    q: str,
    size: float = Query(gt=0, lt=10.5),
):
    results = {"item_id": item_id}
    if q:
        results.update({"q": q})
    if size:
        results.update({"size": size})

# Python Veri Tiplerine Giriş

Python isteğe bağlı olarak "tip belirteçlerini" destekler.

 **"Tip belirteçleri"** bir değişkenin <abbr title="örneğin: str, int, float, bool">tipinin</abbr> belirtilmesine olanak sağlayan özel bir sözdizimidir.

Değişkenlerin tiplerini belirterek editör ve araçlardan daha fazla destek alabilirsiniz.

    out.writeChar('a');
    out.writeShort((short) -30000);
    out.writeShort((short) 50000);
    out.writeInt(0xCAFEBABE);
    out.writeLong(0xDEADBEEFCAFEBABEL);
    out.writeUTF("Herby Derby");
    out.writeFloat(Float.intBitsToFloat(0xCAFEBABE));
    out.writeDouble(Double.longBitsToDouble(0xDEADBEEFCAFEBABEL));
  }

  public void testReadFully() throws IOException {

func (d *Decoder) number() (float64, error) {
	d.scratch.reset()

	var (
		c       = d.cur()
		n       float64
		isFloat bool
	)

	// digits first
	switch {
	case c == '0':
		d.scratch.add(c)
		c = d.next()
	case '1' <= c && c <= '9':
		for ; c >= '0' && c <= '9'; c = d.next() {
			n = 10*n + float64(c-'0')
			d.scratch.add(c)
		}
	}

from fastapi import FastAPI
from fastapi.temp_pydantic_v1_params import Body
from pydantic.v1 import BaseModel


class Item(BaseModel):
    name: str
    description: str | None = None
    size: float


app = FastAPI()


@app.post("/items/")
async def create_item(item: Annotated[Item, Body(embed=True)]) -> Item: