## Simple HTTP Basic Auth { #simple-http-basic-auth }

* Import `HTTPBasic` and `HTTPBasicCredentials`.
* Create a "`security` scheme" using `HTTPBasic`.
* Use that `security` with a dependency in your *path operation*.
* It returns an object of type `HTTPBasicCredentials`:
    * It contains the `username` and `password` sent.

from fastapi import FastAPI
from pydantic import BaseModel, Field

app = FastAPI()


class Item(BaseModel):
    name: str = Field(examples=["Foo"])
    description: str | None = Field(default=None, examples=["A very nice Item"])
    price: float = Field(examples=[35.4])
    tax: float | None = Field(default=None, examples=[3.2])


@app.put("/items/{item_id}")
async def update_item(item_id: int, item: Item):

    example: Optional[Any] = None
    examples: Optional[dict[str, Union[Example, Reference]]] = None
    encoding: Optional[dict[str, Encoding]] = None


class ParameterBase(BaseModelWithConfig):
    description: Optional[str] = None
    required: Optional[bool] = None
    deprecated: Optional[bool] = None
    # Serialization rules for simple scenarios
    style: Optional[str] = None

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

/// tip

Having the return model ensure that a value is always available and always `int` (not `None`) is very useful for the API clients, they can write much simpler code having this certainty.

Also, **automatically generated clients** will have simpler interfaces, so that the developers communicating with your API can have a much better time working with your API. 😎

///

---

Mas para este exemplo, usaremos um documento HTML muito simples com algum JavaScript, tudo dentro de uma string longa.

Esse, é claro, não é o ideal e você não o usaria para produção.

Na produção, você teria uma das opções acima.

Mas é a maneira mais simples de focar no lado do servidor de WebSockets e ter um exemplo funcional:

```Python
from unicorn import UnicornMiddleware

app = SomeASGIApp()

new_app = UnicornMiddleware(app, some_config="rainbow")
```

But FastAPI (actually Starlette) provides a simpler way to do it that makes sure that the internal middlewares handle server errors and custom exception handlers work properly.

For that, you use `app.add_middleware()` (as in the example for CORS).

```Python

            allow_inf_nan=allow_inf_nan,
            max_digits=max_digits,
            decimal_places=decimal_places,
            **extra,
        )
        if examples is not None:
            kwargs["examples"] = examples
        if regex is not None:
            warnings.warn(
                "`regex` has been deprecated, please use `pattern` instead",
                category=FastAPIDeprecationWarning,

   * original interned instance was garbage-collected.
   *
   * <p><b>Warning:</b> do not use with mutable objects.
   *
   * @throws NullPointerException if {@code sample} is null
   */
  E intern(E sample);

            "Deprecated in OpenAPI 3.1.0 that now uses JSON Schema 2020-12, "
            "although still supported. Use examples instead."
        ),
    ] = _Unset,
    openapi_examples: Annotated[
        Optional[dict[str, Example]],
        Doc(
            """
            OpenAPI-specific examples.

            It will be added to the generated OpenAPI (e.g. visible at `/docs`).