4. The `Author` dataclass is used as the `response_model` parameter.

5. You can use other standard type annotations with dataclasses as the request body.

    In this case, it's a list of `Item` dataclasses.

6. Here we are returning a dictionary that contains `items` which is a list of dataclasses.

    FastAPI is still capable of <abbr title="converting the data to a format that can be transmitted">serializing</abbr> the data to JSON.

# Cache for `create_cloned_field`
_CLONED_TYPES_CACHE: MutableMapping[
    Type[BaseModel], Type[BaseModel]
] = WeakKeyDictionary()


def is_body_allowed_for_status_code(status_code: Union[int, str, None]) -> bool:
    if status_code is None:
        return True
    # Ref: https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.1.0.md#patterned-fields-1
    if status_code in {
        "default",

    is_correct_username = secrets.compare_digest(
        current_username_bytes, correct_username_bytes
    )
    current_password_bytes = credentials.password.encode("utf8")
    correct_password_bytes = b"swordfish"
    is_correct_password = secrets.compare_digest(
        current_password_bytes, correct_password_bytes
    )
    if not (is_correct_username and is_correct_password):
        raise HTTPException(

FastAPI uses a standard for building Python web frameworks and servers called <abbr title="Asynchronous Server Gateway Interface">ASGI</abbr>. FastAPI is an ASGI web framework.

The main thing you need to run a **FastAPI** application (or any other ASGI application) in a remote server machine is an ASGI server program like **Uvicorn**, this is the one that comes by default in the `fastapi` command.

There are several alternatives, including:

    Notice that the path parameter is declared to be an integer.

## Standards-based benefits, alternative documentation

When you check the benchmarks, it is common to see several tools of different types compared as equivalent.

Specifically, to see Uvicorn, Starlette and FastAPI compared together (among many other tools).

The simpler the problem solved by the tool, the better performance it will get. And most of the benchmarks don't test the additional features provided by the tool.

The hierarchy is like:

* **Uvicorn**: an ASGI server

# Testing

Thanks to <a href="https://www.starlette.io/testclient/" class="external-link" target="_blank">Starlette</a>, testing **FastAPI** applications is easy and enjoyable.

It is based on <a href="https://www.python-httpx.org" class="external-link" target="_blank">HTTPX</a>, which in turn is designed based on Requests, so it's very familiar and intuitive.

        username: str = payload.get("sub")
        if username is None:
            raise credentials_exception
        token_data = TokenData(username=username)
    except JWTError:
        raise credentials_exception
    user = get_user(fake_users_db, username=token_data.username)
    if user is None:
        raise credentials_exception
    return user

        username: str = payload.get("sub")
        if username is None:
            raise credentials_exception
        token_data = TokenData(username=username)
    except JWTError:
        raise credentials_exception
    user = get_user(fake_users_db, username=token_data.username)
    if user is None:
        raise credentials_exception
    return user

                },
                {
                    "loc": ["query", "skip"],
                    "msg": "value is not a valid integer",
                    "type": "type_error.integer",
                },
                {
                    "loc": ["query", "limit"],
                    "msg": "value is not a valid integer",
                    "type": "type_error.integer",
                },
            ]
        }
    )