class EndpointContext(TypedDict, total=False):
    function: str
    path: str
    file: str
    line: int


class HTTPException(StarletteHTTPException):
    """
    An HTTP exception you can raise in your own code to show errors to the client.

    This is for client errors, invalid authentication, invalid data, etc. Not for server
    errors in your code.

    Read more about it in the

So, even with the code above that doesn't use Pydantic explicitly, FastAPI is using Pydantic to convert those standard dataclasses to Pydantic's own flavor of dataclasses.

And of course, it supports the same:

* data validation
* data serialization
* data documentation, etc.

                            "content": {"application/json": {"schema": {}}},
                        }
                    },
                    "summary": "Read Own Items",
                    "operationId": "read_own_items_users_me_items__get",
                    "security": [{"OAuth2PasswordBearer": []}],
                }
            },
        },
        "components": {

                                "content": {"application/json": {"schema": {}}},
                            }
                        },
                        "summary": "Read Own Items",
                        "operationId": "read_own_items_users_me_items__get",
                        "security": [{"OAuth2PasswordBearer": ["items", "me"]}],
                    }
                },

### List of English terms and their preferred German translations

common:rbe_linux_cpu --copt=-Wno-gnu-offsetof-extensions
# Python config is the same across all containers because the binary is the same
common:rbe_linux_cpu --python_path="/usr/bin/python3"
# These you may need to change for your own GCP project.
common:rbe_linux_cpu --remote_instance_name=projects/tensorflow-testing/instances/default_instance

# Deprecated RBE config with non-hermetic toolchains.
common:rbe_linux_cpu_clang_local --config=rbe_linux_cpu

Additionally, a background task is normally an independent set of logic that should be handled separately, with its own resources (e.g. its own database connection).

async def run_endpoint_function(
    *, dependant: Dependant, values: dict[str, Any], is_coroutine: bool
) -> Any:
    # Only called by get_request_handler. Has been split into its own function to
    # facilitate profiling endpoints, since inner functions are harder to profile.
    assert dependant.call is not None, "dependant.call must be a function"

    if is_coroutine: