__pydantic_config__ = {"extra": "allow"}  # type: ignore[misc]


class ParameterInType(Enum):
    query = "query"
    header = "header"
    path = "path"
    cookie = "cookie"


class Encoding(BaseModelWithConfig):
    contentType: str | None = None
    headers: dict[str, Union["Header", Reference]] | None = None
    style: str | None = None
    explode: bool | None = None
    allowReserved: bool | None = None

async def read_admin():
    return {"message": "Admin Access"}


client = TestClient(app)


def test_read_admin():
    response = client.get("/admin", headers={"Authorization": "Bearer faketoken"})
    assert response.status_code == 200, response.text
    assert response.json() == {"message": "Admin Access"}


def test_openapi_schema():

        File file = new File(path);
        if (!file.exists()) {
            return Collections.emptyList();
        }
        try (FileReader reader = new FileReader(file)) {
            List<UpgradedProperty> upgradedProperties = new Gson().fromJson(reader, new TypeToken<List<UpgradedProperty>>() {}.getType());
            // FIXME There should be no duplicates, yet there are some
            return upgradedProperties.stream()

If you are running your container behind a TLS Termination Proxy (load balancer) like Nginx or Traefik, add the option `--proxy-headers`, this will tell Uvicorn (through the FastAPI CLI) to trust the headers sent by that proxy telling it that the application is running behind HTTPS, etc.

```Dockerfile
CMD ["fastapi", "run", "app/main.py", "--proxy-headers", "--port", "80"]
```

#### Docker Cache { #docker-cache }

* `path` - La path del archivo para el archivo a transmitir.
* `headers` - Cualquier header personalizado para incluir, como un diccionario.
* `media_type` - Un string que da el media type. Si no se establece, se usará el nombre de archivo o la path para inferir un media type.
* `filename` - Si se establece, se incluirá en el response `Content-Disposition`.

Los responses de archivos incluirán los headers apropiados `Content-Length`, `Last-Modified` y `ETag`.

func (z BucketBandwidthReport) EncodeMsg(en *msgp.Writer) (err error) {
	// map header, size 0
	_ = z
	err = en.Append(0x80)
	if err != nil {
		return
	}
	return
}

// MarshalMsg implements msgp.Marshaler
func (z BucketBandwidthReport) MarshalMsg(b []byte) (o []byte, err error) {
	o = msgp.Require(b, z.Msgsize())
	// map header, size 0
	_ = z
	o = append(o, 0x80)
	return
}

* To pass a JSON body, pass a Python object (e.g. a `dict`) to the parameter `json`.
* If you need to send *Form Data* instead of JSON, use the `data` parameter instead.
* To pass *headers*, use a `dict` in the `headers` parameter.
* For *cookies*, a `dict` in the `cookies` parameter.

mvn test                       # Run tests
mvn formatter:format           # Format code
mvn license:format             # Update license headers
```

### Code Style

- 4 spaces (no tabs), opening brace on same line, max line length 120
- JavaDoc required for public APIs
- License headers required (Apache 2.0)

### Testing

- **Structure**: `src/test/java/org/codelibs/fess/crawler/`

    ]
}
```

## Summary { #summary }

You can use **Pydantic models** to declare **query parameters** in **FastAPI**. 😎

/// tip

Spoiler alert: you can also use Pydantic models to declare cookies and headers, but you will read about that later in the tutorial. 🤫

# Usar el Request Directamente { #using-the-request-directly }

Hasta ahora, has estado declarando las partes del request que necesitas con sus tipos.

Tomando datos de:

* El path como parámetros.
* Headers.
* Cookies.
* etc.

Y al hacerlo, **FastAPI** está validando esos datos, convirtiéndolos y generando documentación para tu API automáticamente.

Pero hay situaciones donde podrías necesitar acceder al objeto `Request` directamente.