```Python hl_lines="9"
    {!> ../../../docs_src/path_params_numeric_validations/tutorial005.py!}
    ```

## Validierung von Zahlen: Floats, größer und kleiner

Zahlenvalidierung funktioniert auch für <abbr title="Kommazahl">`float`</abbr>-Werte.

    ```Python hl_lines="9"
    {!> ../../../docs_src/path_params_numeric_validations/tutorial005.py!}
    ```

## Number validations: floats, greater than and less than

Number validations also work for `float` values.

        "short" to "Short",
        "java.lang.Integer" to "Int",
        "int" to "Int",
        "java.lang.Long" to "Long",
        "long" to "Long",
        "java.lang.Float" to "Float",
        "float" to "Float",
        "java.lang.Double" to "Double",
        "double" to "Double"

# Extra Data Types

Up to now, you have been using common data types, like:

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

But you can also use more complex data types.

And you will still have the same features as seen up to now:

* Great editor support.
* Data conversion from incoming requests.
* Data conversion for response data.
* Data validation.
* Automatic annotation and documentation.

## Other data types

    override val LONG: KtType by cachedBuiltin(builtinTypes.longType)
    override val SHORT: KtType by cachedBuiltin(builtinTypes.shortType)
    override val BYTE: KtType by cachedBuiltin(builtinTypes.byteType)

    override val FLOAT: KtType by cachedBuiltin(builtinTypes.floatType)
    override val DOUBLE: KtType by cachedBuiltin(builtinTypes.doubleType)

    override val CHAR: KtType by cachedBuiltin(builtinTypes.charType)

    }
}
```

繰り返しになりますが、**FastAPI** を使用して、その宣言を行うだけで以下のような恩恵を受けられます:

* ネストされたモデルでも対応可能なエディタのサポート（補完など）
* データ変換
* データの検証
* 自動文書化

## 特殊な型とバリデーション

`str`や`int`、`float`のような通常の単数型の他にも、`str`を継承したより複雑な単数型を使うこともできます。

すべてのオプションをみるには、<a href="https://docs.pydantic.dev/latest/concepts/types/" class="external-link" target="_blank">Pydanticのエキゾチック な型</a>のドキュメントを確認してください。次の章でいくつかの例をみることができます。

        "name": "The Foo live"
    }
}
```

再一次，仅仅进行这样的声明，你将通过 **FastAPI** 获得：

* 对被嵌入的模型也适用的编辑器支持（自动补全等）
* 数据转换
* 数据校验
* 自动生成文档

## 特殊的类型和校验

除了普通的单一值类型（如 `str`、`int`、`float` 等）外，你还可以使用从 `str` 继承的更复杂的单一值类型。

要了解所有的可用选项，请查看关于 <a href="https://docs.pydantic.dev/latest/concepts/types/" class="external-link" target="_blank">来自 Pydantic 的外部类型</a> 的文档。你将在下一章节中看到一些示例。

    }
}
```

🔄, 🤸 👈 📄, ⏮️ **FastAPI** 👆 🤚:

* 👨‍🎨 🐕‍🦺 (🛠️, ♒️), 🐦 🏷
* 💽 🛠️
* 💽 🔬
* 🏧 🧾

## 🎁 🆎 & 🔬

↖️ ⚪️➡️ 😐 ⭐ 🆎 💖 `str`, `int`, `float`, ♒️. 👆 💪 ⚙️ 🌅 🏗 ⭐ 🆎 👈 😖 ⚪️➡️ `str`.

👀 🌐 🎛 👆 ✔️, 🛒 🩺 <a href="https://docs.pydantic.dev/latest/concepts/types/" class="external-link" target="_blank">Pydantic 😍 🆎</a>. 👆 🔜 👀 🖼 ⏭ 📃.

pkg p1, const ConstChase2 = 11
pkg p1, const ConstChase2 ideal-int
pkg p1, const ConversionConst = 5
pkg p1, const ConversionConst MyInt
pkg p1, const FloatConst = 1.5  // 3/2
pkg p1, const FloatConst ideal-float
pkg p1, const StrConst = "foo"
pkg p1, const StrConst ideal-string
pkg p1, func Bar(int8, int16, int64)
pkg p1, func Bar1(int8, int16, int64) uint64
pkg p1, func Bar2(int8, int16, int64) (uint8, uint64)

    * `price` adında zorunlu bir parametre olup olmadığını ve varsa tipinin `float` olup olmadığını kontol edecek.
    * `is_offer` adında opsiyonel bir parametre olup olmadığını ve varsa tipinin `float` olup olmadığını kontol edecek.
    * Bunların hepsi en derin JSON nesnelerinde bile çalışacak.