utf8Valid1, utf8Require1 := detectUTF8(fh.Name)
	utf8Valid2, utf8Require2 := detectUTF8(fh.Comment)
	switch {
	case fh.NonUTF8:
		fh.Flags &^= 0x800
	case (utf8Require1 || utf8Require2) && (utf8Valid1 && utf8Valid2):
		fh.Flags |= 0x800
	}

	fh.CreatorVersion = fh.CreatorVersion&0xff00 | zipVersion20 // preserve compatibility byte
	fh.ReaderVersion = zipVersion20

    }
}
```

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。

				}
				sendResult()
				break
			}

			// We break if we did not see 2.5% growth rate in total GET
			// requests, we have reached our peak at this point.
			doBreak := float64(totalGet-throughputHighestGet)/float64(totalGet) < 0.025

			throughputHighestGet = totalGet
			throughputHighestResults = results
			throughputHighestPut = totalPut

			if doBreak {
				sendResult()
				break
			}

                            <la:message key="labels.dict_stemmeroverride_title"/>
                        </h1>
                    </div>
                    <div class="col-sm-6">
                        <ol class="breadcrumb float-sm-right">
                            <li class="breadcrumb-item"><la:link href="/admin/dict">
                                <la:message key="labels.dict_list_link"/>
                            </la:link></li>

                            <la:message key="labels.elevate_word_configuration"/>
                        </h1>
                    </div>
                    <div class="col-sm-6">
                        <ol class="breadcrumb float-sm-right">
                            <li class="breadcrumb-item active"><la:link href="/admin/elevateword">
                                <la:message key="labels.elevate_word_link_list"/>

        settings.set(key, value);
        assertEquals(value, settings.getAsLong(key, -1));
    }

    @Test
    public void test_setAndGetAsFloat() {
        String key = "key";
        float value = 0.01F;
        settings.set(key, value);
        assertEquals(value, settings.getAsFloat(key, -1), 0);
    }

    @Test
    public void test_setAndGetAsBoolean() {
        String key = "key";

                } else if (parameterType.equals(Double.TYPE)) {
                    methodKey.append("java.lang.Double");
                } else if (parameterType.equals(Float.TYPE)) {
                    methodKey.append("java.lang.Float");
                } else if (parameterType.equals(Integer.TYPE)) {
                    methodKey.append("java.lang.Integer");
                } else if (parameterType.equals(Long.TYPE)) {

```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):

```Python hl_lines="2  7-10  23-25"
from fastapi import FastAPI
from pydantic import BaseModel
from typing import Optional

app = FastAPI()


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


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


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

# 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.