}

	// object size is larger than supported maximum.
	if objectSize > maxMultipartPutObjectSize {
		err = errors.New("entity too large")
		return
	}

	configuredPartSize := minPartSize
	// Use floats for part size for all calculations to avoid
	// overflows during float64 to int64 conversions.
	partSizeFlt := float64(objectSize / maxPartsCount)

    writeLong(Double.doubleToLongBits(v));
  }

  /**
   * Writes a {@code float} as specified by {@link DataOutputStream#writeFloat(float)}, except using
   * little-endian byte order.
   *
   * @throws IOException if an I/O error occurs
   */
  @Override
  public void writeFloat(float v) throws IOException {
    writeInt(Float.floatToIntBits(v));
  }

  /**

    void setDepth(Integer depth);

    Long getLastModified();

    void setLastModified(Long lastModified);

    Long getCreateTime();

    void setCreateTime(Long createTime);

    float getWeight();

    void setWeight(float weight);

     */
    @Override
    public void setLastModified(final Long lastModified) {
        this.lastModified = lastModified;
    }

    @Override
    public float getWeight() {
        return weight;
    }

    @Override
    public void setWeight(float weight) {
        this.weight = weight;
    }

    @Override
    public String toString() {

    padding-right: 8px;
  }

  .daterangepicker .ranges, .daterangepicker .drp-calendar {
    float: left;
  }
}

@media (min-width: 730px) {
  .daterangepicker .ranges {
    width: auto;
  }

  .daterangepicker .ranges {
    float: left;
  }

  .daterangepicker.rtl .ranges {
    float: right;
  }

  .daterangepicker .drp-calendar.left {
    clear: none !important;
  }

```Python hl_lines="4  9-12  25-27"
from typing import Union

from fastapi import FastAPI
from pydantic import BaseModel

app = FastAPI()


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


@app.get("/")
def read_root():
    return {"Hello": "World"}


@app.get("/items/{item_id}")
def read_item(item_id: int, q: Union[str, None] = None):

      "depth": {
        "type": "integer"
      },
      "parentUrl": {
        "type": "keyword"
      },
      "method": {
        "type": "keyword"
      },
      "weight": {
        "type": "float"
      },
      "createTime": {
        "type": "long"
      },
      "lastModified": {
        "type": "long"
      },
      "sessionId": {
        "type": "keyword"
      },
      "url": {

# 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.

# Python Types Intro

Python has support for optional "type hints" (also called "type annotations").

These **"type hints"** or annotations are a special syntax that allow declaring the <abbr title="for example: str, int, float, bool">type</abbr> of a variable.

By declaring types for your variables, editors and tools can give you better support.

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

## Validations numériques : flottants, supérieur et inférieur

Les validations numériques fonctionnent également pour les valeurs `float`.