The dataclass will be automatically converted to a Pydantic dataclass.

This way, its schema will show up in the API docs user interface:

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

## Dataclasses in Nested Data Structures { #dataclasses-in-nested-data-structures }

You can also combine `dataclasses` with other type annotations to make nested data structures.

If a class is needed, instead create a regular function dependency that returns a class instance.

Do this:

```python
from dataclasses import dataclass
from typing import Annotated

from fastapi import Depends, FastAPI

app = FastAPI()


@dataclass
class DatabasePaginator:
    offset: int = 0
    limit: int = 100
    q: str | None = None

    def get_page(self) -> dict:

from __future__ import annotations

import uuid
from dataclasses import dataclass, field

from dirty_equals import IsUUID
from fastapi import FastAPI
from fastapi.testclient import TestClient
from inline_snapshot import snapshot


@dataclass
class Item:
    id: uuid.UUID
    name: str
    price: float
    tags: list[str] = field(default_factory=list)
    description: str | None = None
    tax: float | None = None

import inspect
import sys
from collections.abc import Callable
from dataclasses import dataclass, field
from functools import cached_property, partial
from typing import Any, Literal

from fastapi._compat import ModelField
from fastapi.security.base import SecurityBase
from fastapi.types import DependencyCacheKey

if sys.version_info >= (3, 13):  # pragma: no cover
    from inspect import iscoroutinefunction
else:  # pragma: no cover

import warnings
from collections import deque
from dataclasses import dataclass
from datetime import datetime, timezone
from decimal import Decimal
from enum import Enum
from math import isinf, isnan
from pathlib import PurePath, PurePosixPath, PureWindowsPath
from typing import TypedDict

import pytest
from fastapi._compat import Undefined
from fastapi.encoders import jsonable_encoder
from fastapi.exceptions import PydanticV1NotSupportedError

            json_schema_extra=json_schema_extra,
            **extra,
        )


@dataclass(frozen=True)
class Depends:
    dependency: Callable[..., Any] | None = None
    use_cache: bool = True
    scope: Literal["function", "request"] | None = None


@dataclass(frozen=True)
class Security(Depends):

import dataclasses
import inspect
import sys
from collections.abc import (
    AsyncGenerator,
    AsyncIterable,
    AsyncIterator,
    Callable,
    Generator,
    Iterable,
    Iterator,
    Mapping,
    Sequence,
)
from contextlib import AsyncExitStack, contextmanager
from copy import copy, deepcopy
from dataclasses import dataclass
from typing import (
    Annotated,
    Any,
    ForwardRef,
    Literal,

import re
import warnings
from collections.abc import Sequence
from copy import copy
from dataclasses import dataclass, is_dataclass
from enum import Enum
from functools import lru_cache
from typing import (
    Annotated,
    Any,
    Literal,
    Union,
    cast,
    get_args,
    get_origin,
)

from fastapi._compat import lenient_issubclass, shared
from fastapi.openapi.constants import REF_TEMPLATE

2. `pydantic.dataclasses` — полностью совместимая замена (drop-in replacement) для `dataclasses`.

3. Dataclass `Author` содержит список dataclass `Item`.

4. Dataclass `Author` используется в параметре `response_model`.

5. Вы можете использовать и другие стандартные аннотации типов вместе с dataclasses в качестве тела запроса.

    В этом случае это список dataclass `Item`.

その場合は、標準の `dataclasses` を `pydantic.dataclasses` に置き換えるだけで済みます。これはドロップイン置換です:

{* ../../docs_src/dataclasses_/tutorial003_py310.py hl[1,4,7:10,13:16,22:24,27] *}

1. 依然として標準の `dataclasses` から `field` をインポートします。

2. `pydantic.dataclasses` は `dataclasses` のドロップイン置換です。

3. `Author` dataclass は `Item` dataclass のリストを含みます。

4. `Author` dataclass を `response_model` パラメータとして使用しています。