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 dataclasses import field  # (1)

from fastapi import FastAPI
from pydantic.dataclasses import dataclass  # (2)


@dataclass
class Item:
    name: str
    description: str | None = None


@dataclass
class Author:
    name: str
    items: list[Item] = field(default_factory=list)  # (3)


app = FastAPI()


@app.post("/authors/{author_id}/items/", response_model=Author)  # (4)

from dataclasses import dataclass

from fastapi import FastAPI


@dataclass
class Item:
    name: str
    price: float
    description: str | None = None
    tax: float | None = None


app = FastAPI()


@app.post("/items/")
async def create_item(item: Item):

from dataclasses import dataclass, field

from fastapi import FastAPI


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


app = FastAPI()


@app.get("/items/next", response_model=Item)
async def read_next_item():
    return {
        "name": "Island In The Moon",
        "price": 12.99,

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 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 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

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`.

6. Здесь мы возвращаем словарь, содержащий `items`, который является списком dataclass.

2. `pydantic.dataclasses` 是 `dataclasses` 的可直接替換版本。
3. `Author` dataclass 內含一個 `Item` dataclass 的清單。
4. `Author` dataclass 被用作 `response_model` 參數。
5. 你可以將其他標準型別註記與 dataclass 一起用作請求本文。

   在此例中，它是 `Item` dataclass 的清單。
6. 這裡我們回傳一個字典，其中的 `items` 是一個 dataclass 清單。

   FastAPI 仍能將資料<dfn title="將資料轉換成可傳輸的格式">序列化</dfn>為 JSON。
7. 這裡 `response_model` 使用的是「`Author` dataclass 的清單」這種型別註記。

   同樣地，你可以把 `dataclasses` 與標準型別註記組合使用。