# Дополнительные типы данных

До сих пор вы использовали простые типы данных, такие как:

* `int`
* `float`
* `str`
* `bool`

Но вы также можете использовать и более сложные типы.

При этом у вас останутся те же возможности , что и до сих пор:

* Отличная поддержка редактора.
* Преобразование данных из входящих запросов.
* Преобразование данных для ответа.
* Валидация данных.
* Автоматическая аннотация и документация.

  }

  /**
   * Returns the value of this {@code UnsignedLong} as a {@code float}, analogous to a widening
   * primitive conversion from {@code long} to {@code float}, and correctly rounded.
   */
  @Override
  public float floatValue() {
    if (value >= 0) {
      return (float) value;
    }
    // The top bit is set, which means that the float value is going to come from the top 24 bits.

  }

  /**
   * Returns the value of this {@code UnsignedLong} as a {@code float}, analogous to a widening
   * primitive conversion from {@code long} to {@code float}, and correctly rounded.
   */
  @Override
  public float floatValue() {
    if (value >= 0) {
      return (float) value;
    }
    // The top bit is set, which means that the float value is going to come from the top 24 bits.

)

// ISO8601Format converts time 't' into ISO8601 time format expected in AWS S3 spec.
//
// This function is needed to avoid a Go's float64 precision bug, where Go avoids
// padding the extra '0' before the timezone.
func ISO8601Format(t time.Time) string {
	value := t.Format(iso8601TimeFormat)
	if len(value) < len(iso8601TimeFormat) {

				return true
			}
		}
		return false
	}
}

// Details for the measured bandwidth
type Details struct {
	LimitInBytesPerSecond            int64   `json:"limitInBits"`
	CurrentBandwidthInBytesPerSecond float64 `json:"currentBandwidth"`
}

// BucketBandwidthReport captures the details for all buckets.
type BucketBandwidthReport struct {
	BucketStats map[BucketOptions]Details `json:"bucketStats,omitempty"`
}

                pageSize, offset);
    }

    protected float toFloat(final Object value) {
        if (value instanceof final Float f) {
            return f;
        }
        if (value instanceof final String s) {
            return Float.parseFloat(s);
        }
        return 0.0f;
    }

from typing import Union

from fastapi import Body, FastAPI
from pydantic import BaseModel

app = FastAPI()


class Item(BaseModel):
    name: str
    description: Union[str, None] = None
    price: float
    tax: Union[float, None] = None


@app.put("/items/{item_id}")
async def update_item(
    *,
    item_id: int,
    item: Item = Body(
        openapi_examples={
            "normal": {

  @Override
  public int intValue() {
    return (int) sum();
  }

  /** Returns the {@link #sum} as a {@code float} after a widening primitive conversion. */
  @Override
  public float floatValue() {
    return (float) sum();
  }

  /** Returns the {@link #sum} as a {@code double} after a widening primitive conversion. */
  @Override
  public double doubleValue() {

    return Longs.fromBytes(b8, b7, b6, b5, b4, b3, b2, b1);
  }

  /**
   * Reads a {@code float} as specified by {@link DataInputStream#readFloat()}, except using
   * little-endian byte order.
   *
   * @return the next four bytes of the input stream, interpreted as a {@code float} in
   *     little-endian byte order
   * @throws IOException if an I/O error occurs
   */

# Tipos de dados extras

Até agora, você tem usado tipos de dados comuns, tais como:

* `int`
* `float`
* `str`
* `bool`

Mas você também pode usar tipos de dados mais complexos.

E você ainda terá os mesmos recursos que viu até agora:

* Ótimo suporte do editor.
* Conversão de dados das requisições recebidas.
* Conversão de dados para os dados da resposta.
* Validação de dados.
* Anotação e documentação automáticas.