{!../../../docs_src/extending_openapi/tutorial001.py!}
```

### Cache the OpenAPI schema

You can use the property `.openapi_schema` as a "cache", to store your generated schema.

That way, your application won't have to generate the schema every time a user opens your API docs.

It will be generated only once, and then the same cached schema will be used for the next requests.

```Python hl_lines="13-14  25-26"

        }
    }
}
```

### Custom OpenAPI *path operation* schema

The dictionary in `openapi_extra` will be deeply merged with the automatically generated OpenAPI schema for the *path operation*.

So, you could add additional data to the automatically generated schema.

You can add code to be run with the `request`,  before any *path operation* receives it.

And also after the `response` is generated, before returning it.

For example, you could add a custom header `X-Process-Time` containing the time in seconds that it took to process the request and generate a response:

```Python hl_lines="10  12-13"
{!../../../docs_src/middleware/tutorial001.py!}
```

## Other middlewares

    new_field.populate_validators()  # type: ignore[attr-defined]
    return new_field


def generate_operation_id_for_path(
    *, name: str, path: str, method: str
) -> str:  # pragma: nocover
    warnings.warn(
        "fastapi.utils.generate_operation_id_for_path() was deprecated, "
        "it is not used internally, and will be removed soon",
        DeprecationWarning,

## Add extra information

You can declare extra information in `Field`, `Query`, `Body`, etc. And it will be included in the generated JSON Schema.

You will learn more about adding extra information later in the docs, when learning to declare examples.

!!! warning

from typing import AsyncGenerator, Generator

import pytest
from fastapi import Depends, FastAPI
from fastapi.testclient import TestClient

app = FastAPI()


class CallableDependency:
    def __call__(self, value: str) -> str:
        return value


class CallableGenDependency:
    def __call__(self, value: str) -> Generator[str, None, None]:
        yield value


class AsyncCallableDependency:

    * Si no usaras FastAPI y usaras Starlette directamente (u otra herramienta, como Sanic, Flask, Responder, etc.), tendrías que implementar toda la validación y serialización de datos...

    * If you didn't use FastAPI and used Starlette directly (or another tool, like Sanic, Flask, Responder, etc) you would have to implement all the data validation and serialization yourself. So, your final application would still...

You can also combine `dataclasses` with other type annotations to make nested data structures.

In some cases, you might still have to use Pydantic's version of `dataclasses`. For example, if you have errors with the automatically generated API documentation.

In that case, you can simply swap the standard `dataclasses` with `pydantic.dataclasses`, which is a drop-in replacement:

```{ .python .annotate hl_lines="1  5  8-11  14-17  23-25  28" }

Es steht Ihnen weiterhin frei, den Couchbase-basierten Generator zu verwenden, wenn Sie möchten. Er sollte wahrscheinlich immer noch gut funktionieren, und wenn Sie bereits ein Projekt damit erstellt haben, ist das auch in Ordnung (und Sie haben es wahrscheinlich bereits an Ihre Bedürfnisse angepasst).