しかし、ID`bar`のitemのように、デフォルト値が設定されているモデルのフィールドに値が設定されている場合:

```Python hl_lines="3 5"
{
    "name": "Bar",
    "description": "The bartenders",
    "price": 62,
    "tax": 20.2
}
```

それらはレスポンスに含まれます。

#### デフォルト値と同じ値を持つデータ

ID`baz`のitemのようにデフォルト値と同じ値を持つデータの場合:

```Python hl_lines="3 5 6"
{
    "name": "Baz",
    "description": None,
    "price": 50.2,
    "tax": 10.5,
    "tags": []

name: Check closed issue release notes

on:
  issues:
    types: [ closed ]

permissions: {}

jobs:
  check_release_notes:
    permissions:
      issues: write
    runs-on: ubuntu-latest
    steps:
      # Check that release-note-worthy issues have a PR with release notes attached

<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE components PUBLIC "-//DBFLUTE//DTD LastaDi 1.0//EN"
	"http://dbflute.org/meta/lastadi10.dtd">
<components namespace="fessCrawler">
	<include path="crawler/container.xml" />

	<component name="robotsTxtHelper" class="org.codelibs.fess.crawler.helper.RobotsTxtHelper"
		instance="prototype">
	</component>

상기와 같은 방식으로 "호출(실행)" 할 수 있다면 "호출 가능"이 됩니다.

## 의존성으로서의 클래스

파이썬 클래스의 인스턴스를 생성하기 위해 사용하는 것과 동일한 문법을 사용한다는 걸 알 수 있습니다.

예를 들어:

```Python
class Cat:
    def __init__(self, name: str):
        self.name = name


fluffy = Cat(name="Mr Fluffy")
```

이 경우에 `fluffy`는 클래스 `Cat`의 인스턴스입니다. 그리고 우리는 `fluffy`를 만들기 위해서 `Cat`을 "호출"했습니다.

따라서, 파이썬 클래스는 **호출 가능**합니다.

그래서 **FastAPI**에서는 파이썬 클래스를 의존성으로 사용할 수 있습니다.

    return user_id


# Een Pydantic model
class User(BaseModel):
    id: int
    name: str
    joined: date
```

Vervolgens kan je het op deze manier gebruiken:

```Python
my_user: User = User(id=3, name="John Doe", joined="2018-07-19")

second_user_data = {
    "id": 4,
    "name": "Mary",
    "joined": "2018-11-30",
}

my_second_user: User = User(**second_user_data)
```

   * requirement that this data be complete enough to fully reconstitute the object later.
   *
   * @since 12.0 (in Guava 11.0, {@code PrimitiveSink} was named {@code Sink})
   */
  void funnel(@ParametricNullness T from, PrimitiveSink into);

from fastapi import Body, FastAPI
from pydantic import BaseModel

app = FastAPI()


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


@app.put("/items/{item_id}")
async def update_item(item_id: int, item: Item = Body(embed=True)):
    results = {"item_id": item_id, "item": item}

from fastapi import FastAPI
from pydantic import BaseModel

app = FastAPI()


class Item(BaseModel):
    name: str
    description: str | None = None
    price: float
    tax: float | None = None
    tags: list[str] = []


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

from fastapi import FastAPI
from pydantic import BaseModel

app = FastAPI()


class Item(BaseModel):
    name: str
    description: str | None = None
    price: float
    tax: float | None = None
    tags: set[str] = set()


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

```Python hl_lines="48-52"
{!../../docs_src/websockets/tutorial001.py!}
```

You can receive and send binary, text, and JSON data.

## Try it

If your file is named `main.py`, run your application with:

<div class="termy">

```console
$ fastapi dev main.py

<span style="color: green;">INFO</span>:     Uvicorn running on http://127.0.0.1:8000 (Press CTRL+C to quit)
```