unauthorized_headers = {"WWW-Authenticate": f'Basic realm="{self.realm}"'}
        else:
            unauthorized_headers = {"WWW-Authenticate": "Basic"}
        if not authorization or scheme.lower() != "basic":
            if self.auto_error:
                raise HTTPException(
                    status_code=HTTP_401_UNAUTHORIZED,
                    detail="Not authenticated",

    operation_id = f"{operation_id}_{method.lower()}"
    return operation_id


def generate_unique_id(route: "APIRoute") -> str:
    operation_id = f"{route.name}{route.path_format}"
    operation_id = re.sub(r"\W", "_", operation_id)
    assert route.methods
    operation_id = f"{operation_id}_{list(route.methods)[0].lower()}"
    return operation_id

    Keep in mind that dataclasses can't do everything Pydantic models can do.

    So, you might still need to use Pydantic models.

    But if you have a bunch of dataclasses laying around, this is a nice trick to use them to power a web API using FastAPI. 🤓

## Dataclasses in `response_model`

You can also use `dataclasses` in the `response_model` parameter:

```Python hl_lines="1  7-13  19"
{!../../../docs_src/dataclasses/tutorial002.py!}

    @app.get("/users/me/items/")
    async def read_own_items(
        current_user: Annotated[User, Security(get_current_active_user, scopes=["items"])]
    ):
        return [{"item_id": "Foo", "owner": current_user.username}]
    ```
    """

🖼 🎚 `orion_cat` (👐 `Pet`) 💪 ✔️ 🔢 `orion_cat.type`, 🏓 `type`. & 💲 👈 🔢 💪, ✅ `"cat"`.

👫 🐜 ✔️ 🧰 ⚒ 🔗 ⚖️ 🔗 🖖 🏓 ⚖️ 👨‍💼.

👉 🌌, 👆 💪 ✔️ 🔢 `orion_cat.owner` & 👨‍💼 🔜 🔌 💽 👉 🐶 👨‍💼, ✊ ⚪️➡️ 🏓 *👨‍💼*.

, `orion_cat.owner.name` 💪 📛 (⚪️➡️ `name` 🏓 `owners` 🏓) 👉 🐶 👨‍💼.

⚫️ 💪 ✔️ 💲 💖 `"Arquilian"`.

& 🐜 🔜 🌐 👷 🤚 ℹ ⚪️➡️ 🔗 🏓 *👨‍💼* 🕐❔ 👆 🔄 🔐 ⚫️ ⚪️➡️ 👆 🐶 🎚.

If you are paying for 3 servers but you are using only a little bit of their RAM and CPU, you are probably **wasting money** 💸, and probably **wasting server electric power** 🌎, etc.

In that case, it could be better to have only 2 servers and use a higher percentage of their resources (CPU, memory, disk, network bandwidth, etc).

data = {
    "plumbus": {"description": "Freshly pickled plumbus", "owner": "Morty"},
    "portal-gun": {"description": "Gun to create portals", "owner": "Rick"},
}


class OwnerError(Exception):
    pass


def get_username():
    try:
        yield "Rick"
    except OwnerError as e:
        raise HTTPException(status_code=400, detail=f"Owner error: {e}")


@app.get("/items/{item_id}")

    class ModelC(ModelB):
        password: str

    class ModelA(BaseModel):
        name: str
        description: Optional[str] = None
        foo: ModelB

        @field_validator("name")
        def lower_username(cls, name: str, info: ValidationInfo):
            if not name.endswith("A"):
                raise ValueError("name must end in A")
            return name

    async def get_model_c() -> ModelC:

There you could buy me a coffee ☕️ to say thanks. 😄

And you can also become a Silver or Gold sponsor for FastAPI. 🏅🎉

## Sponsor the tools that power FastAPI

As you have seen in the documentation, FastAPI stands on the shoulders of giants, Starlette and Pydantic.

You can also sponsor:

        "name": "Firulais",
        "owner": {"name": "Foo"},
    }


def test_encode_class():
    person = Person(name="Foo")
    pet = Pet(owner=person, name="Firulais")
    assert jsonable_encoder(pet) == {"name": "Firulais", "owner": {"name": "Foo"}}
    assert jsonable_encoder(pet, include={"name"}) == {"name": "Firulais"}
    assert jsonable_encoder(pet, exclude={"owner"}) == {"name": "Firulais"}