return q


def query_or_cookie_extractor(
    q: Annotated[str, Depends(query_extractor)],
    last_query: Annotated[Union[str, None], Cookie()] = None,
):
    if not q:
        return last_query
    return q


@app.get("/items/")
async def read_query(
    query_or_default: Annotated[str, Depends(query_or_cookie_extractor)],
):

### Always `raise` in Dependencies with `yield` and `except`

If you catch an exception in a dependency with `yield`, unless you are raising another `HTTPException` or similar, you should re-raise the original exception.

    You can probably skip this part.

There's an alternative way to define this logic to be executed during *startup* and during *shutdown*.

You can define event handlers (functions) that need to be executed before the application starts up, or when the application is shutting down.

These functions can be declared with `async def` or normal `def`.

### `startup` event

    So, you should declare it with `...` to mark it as required.

    Nevertheless, even if you declared it with `None` or set a default value, it would not affect anything, it would still be always required.

## Order the parameters as you need

!!! tip
    This is probably not as important or necessary if you use `Annotated`.

Let's say that you want to declare the query parameter `q` as a required `str`.

                parameter or in an HTTP Bearer token).
                """
            ),
        ] = True,
    ):
        self.model: APIKey = APIKey(
            **{"in": APIKeyIn.query},  # type: ignore[arg-type]
            name=name,
            description=description,
        )
        self.scheme_name = scheme_name or self.__class__.__name__
        self.auto_error = auto_error

# `Response` class

You can declare a parameter in a *path operation function* or dependency to be of type `Response` and then you can set data for the response like headers or cookies.

You can also use it directly to create an instance of it and return it from your *path operations*.

You can import it directly from `fastapi`:

```python
from fastapi import Response
```

                        str(additional_status_code).upper()
                    ) or http.client.responses.get(int(additional_status_code))
                    description = (
                        process_response.get("description")
                        or openapi_response.get("description")
                        or status_text
                        or "Additional Response"
                    )

            {
              "answered": {
                "delay": 864000,
                "message": "Assuming the original need was handled, this will be automatically closed now. But feel free to add more comments or create new issues or PRs."
              },
              "changes-requested": {
                "delay": 2628000,

For a **web API**, it normally involves putting it in a **remote machine**, with a **server program** that provides good performance, stability, etc, so that your **users** can **access** the application efficiently and without interruptions or problems.

This is in contrast to the **development** stages, where you are constantly changing the code, breaking it and fixing it, stopping and restarting the development server, etc.

## Deployment Strategies

            # `tests/test_infer_param_optionality.py` for an example.
            field_info = params.Path(annotation=use_annotation)
        elif is_uploadfile_or_nonable_uploadfile_annotation(
            type_annotation
        ) or is_uploadfile_sequence_annotation(type_annotation):
            field_info = params.File(annotation=use_annotation, default=default_value)