API 文档中也会显示相关概图：

<img src="/img/tutorial/dataclasses/image01.png">

## 在嵌套数据结构中使用数据类

您还可以把 `dataclasses` 与其它类型注解组合在一起，创建嵌套数据结构。

还有一些情况也可以使用 Pydantic 的 `dataclasses`。例如，在 API 文档中显示错误。

本例把标准的 `dataclasses` 直接替换为 `pydantic.dataclasses`：

```{ .python .annotate hl_lines="1  5  8-11  14-17  23-25  28" }
{!../../../docs_src/dataclasses/tutorial003.py!}
```

1. 本例依然要从标准的 `dataclasses` 中导入 `field`；

In that case, you can simply swap the standard `dataclasses` with `pydantic.dataclasses`, which is a drop-in replacement:

```{ .python .annotate hl_lines="1  5  8-11  14-17  23-25  28" }
{!../../../docs_src/dataclasses/tutorial003.py!}
```

1. We still import `field` from standard `dataclasses`.

```Python hl_lines="1  7-12  19-20"
{!../../../docs_src/dataclasses/tutorial001.py!}
```

👉 🐕‍🦺 👏 **Pydantic**, ⚫️ ✔️ <a href="https://docs.pydantic.dev/latest/concepts/dataclasses/#use-of-stdlib-dataclasses-with-basemodel" class="external-link" target="_blank">🔗 🐕‍🦺 `dataclasses`</a>.

```Python hl_lines="1  7-12  19-20"
{!../../../docs_src/dataclasses/tutorial001.py!}
```

Das ist dank **Pydantic** ebenfalls möglich, da es <a href="https://pydantic-docs.helpmanual.io/usage/dataclasses/#use-of-stdlib-dataclasses-with-basemodel" class="external-link" target="_blank">`dataclasses` intern unterstützt</a>.

from typing import List, Optional

import pytest
from fastapi import FastAPI
from fastapi.exceptions import ResponseValidationError
from fastapi.testclient import TestClient
from pydantic.dataclasses import dataclass

app = FastAPI()


@dataclass
class Item:
    name: str
    price: Optional[float] = None
    owner_ids: Optional[List[int]] = None


@app.get("/items/invalid", response_model=Item)
def get_invalid():

    runTest("analysis/analysis-api/testData/components/typeProvider/haveCommonSubtype/collections.kt");
  }

  @Test
  @TestMetadata("dataClasses.kt")
  public void testDataClasses() {
    runTest("analysis/analysis-api/testData/components/typeProvider/haveCommonSubtype/dataClasses.kt");
  }

  @Test
  @TestMetadata("enums.kt")
  public void testEnums() {

from dataclasses import dataclass
from datetime import datetime
from typing import List, Optional

from fastapi import FastAPI
from fastapi.testclient import TestClient

app = FastAPI()


@dataclass
class Item:
    name: str
    date: datetime
    price: Optional[float] = None
    owner_ids: Optional[List[int]] = None


@app.get("/items/valid", response_model=Item)
def get_valid():

from dirty_equals import IsDict, IsOneOf
from fastapi.testclient import TestClient

from docs_src.dataclasses.tutorial002 import app

client = TestClient(app)


def test_get_item():
    response = client.get("/items/next")
    assert response.status_code == 200
    assert response.json() == {
        "name": "Island In The Moon",
        "price": 12.99,
        "description": "A place to be be playin' and havin' fun",

import re
import warnings
from dataclasses import is_dataclass
from typing import (
    TYPE_CHECKING,
    Any,
    Dict,
    MutableMapping,
    Optional,
    Set,
    Type,
    Union,
    cast,
)
from weakref import WeakKeyDictionary

import fastapi
from fastapi._compat import (
    PYDANTIC_V2,
    BaseConfig,
    ModelField,
    PydanticSchemaGenerationError,
    Undefined,
    UndefinedType,

from dirty_equals import IsDict
from fastapi.testclient import TestClient

from docs_src.dataclasses.tutorial001 import app

client = TestClient(app)


def test_post_item():
    response = client.post("/items/", json={"name": "Foo", "price": 3})
    assert response.status_code == 200
    assert response.json() == {
        "name": "Foo",
        "price": 3,
        "description": None,
        "tax": None,
    }