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>.

    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() {

            # TODO: remove when deprecating Pydantic v1
            custom_encoder=encoders,
            sqlalchemy_safe=sqlalchemy_safe,
        )
    if dataclasses.is_dataclass(obj):
        obj_dict = dataclasses.asdict(obj)
        return jsonable_encoder(
            obj_dict,
            include=include,
            exclude=exclude,
            by_alias=by_alias,

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,
    }

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 collections import deque
from dataclasses import dataclass
from datetime import datetime, timezone
from decimal import Decimal
from enum import Enum
from pathlib import PurePath, PurePosixPath, PureWindowsPath
from typing import Optional

import pytest
from fastapi._compat import PYDANTIC_V2, Undefined
from fastapi.encoders import jsonable_encoder
from pydantic import BaseModel, Field, ValidationError

"docs_src/dependencies/tutorial008.py" = ["F821"]
"docs_src/dependencies/tutorial009.py" = ["F821"]
"docs_src/dependencies/tutorial010.py" = ["F821"]
"docs_src/custom_response/tutorial007.py" = ["B007"]
"docs_src/dataclasses/tutorial003.py" = ["I001"]
"docs_src/path_operation_advanced_configuration/tutorial007.py" = ["B904"]
"docs_src/path_operation_advanced_configuration/tutorial007_pv1.py" = ["B904"]