For that, we will create a new dependency with `yield`, as explained before in the section about [Dependencies with `yield`](dependencies/dependencies-with-yield.md){.internal-link target=_blank}.

Our dependency will create a new SQLAlchemy `SessionLocal` that will be used in a single request, and then close it once the request is finished.

=== "Python 3.9+"

    ```Python hl_lines="13-18"

    end

    rect rgba(0, 255, 255, .1)
        code ->> function: say_hi(name="Camila")
        function ->> code: return stored result
    end
```

In the case of our dependency `get_settings()`, the function doesn't even take any arguments, so it always returns the same value.

Then we use the request directly, and extract the body as `bytes`. This means that FastAPI won't even try to parse the request payload as JSON.

And then in our code, we parse that YAML content directly, and then we are again using the same Pydantic model to validate the YAML content:

=== "Pydantic v2"

    ```Python hl_lines="26-33"

    This is useful when we use ConstrainedDecimal to represent Numeric(x,0)
    where a integer (but not int typed) is used. Encoding this as a float
    results in failed round-tripping between encode and parse.
    Our Id type is a prime example of this.

    >>> decimal_encoder(Decimal("1.0"))
    1.0

    >>> decimal_encoder(Decimal("1"))
    1
    """
    if dec_value.as_tuple().exponent >= 0:  # type: ignore[operator]

                exclude_defaults=exclude_defaults,
                exclude_none=exclude_none,
            )

        def __hash__(self) -> int:
            # Each ModelField is unique for our purposes, to allow making a dict from
            # ModelField to its JSON Schema.
            return id(self)

    def get_annotation_from_field_info(
        annotation: Any, field_info: FieldInfo, field_name: str