controller.utilities.configuration.CustomVariablesModel.model_dump
- CustomVariablesModel.model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)
Usage docs: https://docs.pydantic.dev/2.7/concepts/serialization/#modelmodel_dump
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
- Parameters:
mode (
Union[Literal['json','python'],str], default:'python') – The mode in which to_python should run. If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.include (
Union[Set[int],Set[str],Dict[int,Any],Dict[str,Any],None], default:None) – A set of fields to include in the output.exclude (
Union[Set[int],Set[str],Dict[int,Any],Dict[str,Any],None], default:None) – A set of fields to exclude from the output.context (
dict[str,Any] |None, default:None) – Additional context to pass to the serializer.by_alias (
bool, default:False) – Whether to use the field’s alias in the dictionary key if defined.exclude_unset (
bool, default:False) – Whether to exclude fields that have not been explicitly set.exclude_defaults (
bool, default:False) – Whether to exclude fields that are set to their default value.exclude_none (
bool, default:False) – Whether to exclude fields that have a value of None.round_trip (
bool, default:False) – If True, dumped values should be valid as input for non-idempotent types such as Json[T].warnings (
Union[bool,Literal['none','warn','error']], default:True) – How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors, “error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].serialize_as_any (
bool, default:False) – Whether to serialize fields with duck-typing serialization behavior.
- Return type:
dict[str,Any]- Returns:
A dictionary representation of the model.