"title": "Price",
                                "anyOf": [{"type": "number"}, {"type": "null"}],
                            }
                        )
                        # TODO: remove when deprecating Pydantic v1
                        | IsDict({"title": "Price", "type": "number"}),
                    },
                },
                "ValidationError": {

                    "msg": "Input should be a valid integer, unable to parse string as an integer",
                    "input": "foobar",
                }
            ]
        }
    ) | IsDict(
        # TODO: remove when deprecating Pydantic v1
        {
            "detail": [
                {
                    "loc": ["path", "item_id"],
                    "msg": "value is not a valid integer",

                "User": {
                    "title": "User",
                    "required": IsOneOf(
                        ["username", "email", "full_name", "disabled"],
                        # TODO: remove when deprecating Pydantic v1
                        ["username"],
                    ),
                    "type": "object",
                    "properties": {

# TODO: pv2 should this return strings instead?
def decimal_encoder(dec_value: Decimal) -> Union[int, float]:
    """
    Encodes a Decimal as int of there's no exponent, otherwise float

    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.

                                "anyOf": [{"type": "string"}, {"type": "null"}],
                            }
                        )
                        | IsDict(
                            # TODO: remove when deprecating Pydantic v1
                            {"title": "Description", "type": "string"}
                        ),
                    },
                },
                "Item": {

        # This expects that GenerateJsonSchema was already used to generate the definitions
        json_schema = field_mapping[(field, override_mode or field.mode)]
        if "$ref" not in json_schema:
            # TODO remove when deprecating Pydantic v1
            # Ref: https://github.com/pydantic/pydantic/blob/d61792cc42c80b13b23e3ffa74bc37ec7c77f7d1/pydantic/schema.py#L207
            json_schema["title"] = (