"schema": IsDict({"$ref": "#/components/schemas/Item"})
                                | IsDict(
                                    # TODO: remove when deprecating Pydantic v1
                                    {
                                        "allOf": [
                                            {"$ref": "#/components/schemas/Item"}
                                        ],

                                    }
                                )
                                | IsDict(
                                    # TODO: remove when deprecating Pydantic v1
                                    {
                                        "$ref": "#/components/schemas/Body_read_items_items__item_id__put"
                                    }
                                )

                    "msg": "Field required",
                    "input": None,
                },
            ]
        }
    ) | IsDict(
        # TODO: remove when deprecating Pydantic v1
        {
            "detail": [
                {
                    "loc": ["body", "item"],
                    "msg": "field required",
                    "type": "value_error.missing",
                },

        run: uv pip install -r requirements-tests.txt
      - name: Install Pydantic v1
        if: matrix.pydantic-version == 'pydantic-v1'
        run: uv pip install "pydantic>=1.10.0,<2.0.0"
      - name: Install Pydantic v2
        if: matrix.pydantic-version == 'pydantic-v2'
        run: uv pip install --upgrade "pydantic>=2.0.2,<3.0.0"
      - run: mkdir coverage
      - name: Test
        run: bash scripts/test.sh

## Über Pydantic

Pydantic integriert die Tests für **FastAPI** in seine eigenen Tests, sodass neue Versionen von Pydantic (über `1.0.0`) immer mit FastAPI kompatibel sind.

Sie können Pydantic an jede für Sie geeignete Version über `1.0.0` und unter `2.0.0` anpinnen.

Zum Beispiel:
```txt
pydantic>=1.2.0,<2.0.0

```Python hl_lines="10"
{!../../docs_src/security/tutorial001.py!}
```

しかし、それはまだそんなに有用ではありません。

現在のユーザーを取得するようにしてみましょう。

## ユーザーモデルの作成

まずは、Pydanticのユーザーモデルを作成しましょう。

ボディを宣言するのにPydanticを使用するのと同じやり方で、Pydanticを別のどんなところでも使うことができます:

```Python hl_lines="5  12-16"
{!../../docs_src/security/tutorial002.py!}
```

## 依存関係 `get_current_user` を作成

依存関係 `get_current_user` を作ってみましょう。

When using **Pydantic v2**, the generated OpenAPI is a bit more exact and **correct** than before. 😎

In fact, in some cases, it will even have **two JSON Schemas** in OpenAPI for the same Pydantic model, for input and output, depending on if they have **default values**.

Let's see how that works and how to change it if you need to do that.

## Pydantic Models for Input and Output

from datetime import datetime, timezone

from fastapi import FastAPI
from fastapi.testclient import TestClient
from pydantic import BaseModel

from .utils import needs_pydanticv1, needs_pydanticv2


@needs_pydanticv2
def test_pydanticv2():
    from pydantic import field_serializer

    class ModelWithDatetimeField(BaseModel):
        dt_field: datetime

        @field_serializer("dt_field")

    * 생성된 스키마는 이것이 `binary` "형식"의 `str`임을 명시합니다.
* `Decimal`:
    * 표준 파이썬의 `Decimal`.
    * 요청과 응답에서 `float`와 동일하게 다뤄집니다.
* 여기에서 모든 유효한 pydantic 데이터 자료형을 확인할 수 있습니다: <a href="https://docs.pydantic.dev/latest/usage/types/types/" class="external-link" target="_blank">Pydantic 데이터 자료형</a>.

## 예시

위의 몇몇 자료형을 매개변수로 사용하는 *경로 작동* 예시입니다.

//// tab | Python 3.10+

```Python hl_lines="1  3  12-16"

PyGithub>=2.3.0,<3.0.0
pydantic>=2.5.3,<3.0.0
pydantic-settings>=2.1.0,<3.0.0
httpx>=0.27.0,<0.28.0