DatasourceFlowsDetailsDataflowConfigTableMappingsRulesInner

class openapi_client.models.datasource_flows_details_dataflow_config_table_mappings_rules_inner.DatasourceFlowsDetailsDataflowConfigTableMappingsRulesInner(**data)

Bases: BaseModel

old_value: Optional[StrictStr]

rule_action: Optional[StrictStr]

rule_id: Optional[StrictStr]

rule_name: Optional[StrictStr]

rule_target: Optional[StrictStr]

rule_type: Optional[StrictStr]

value: Optional[StrictStr]

object_locator: Optional[DatasetLineageTaskFiltersInfoSourceTableInfo]

data_type: Optional[DatasourceFlowsDetailsDataflowConfigTableMappingsRulesInnerDataType]

filters: Optional[List[DatasetLineageTaskFiltersInfoFilterRulesInner]]

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'validate_assignment': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

to_str()

Returns the string representation of the model using alias

Return type:

str

to_json()

Returns the JSON representation of the model using alias

Return type:

str

classmethod from_json(json_str)

Create an instance of DatasourceFlowsDetailsDataflowConfigTableMappingsRulesInner from a JSON string

Return type:

Optional[Self]

to_dict()

Return the dictionary representation of the model using alias.

This has the following differences from calling pydantic’s self.model_dump(by_alias=True):

• None is only added to the output dict for nullable fields that were set at model initialization. Other fields with value None are ignored.

Return type:

Dict[str, Any]

classmethod from_dict(obj)

Create an instance of DatasourceFlowsDetailsDataflowConfigTableMappingsRulesInner from a dict

Return type:

Optional[Self]

model_fields: ClassVar[dict[str, FieldInfo]] = {'data_type': FieldInfo(annotation=Union[DatasourceFlowsDetailsDataflowConfigTableMappingsRulesInnerDataType, NoneType], required=False, alias='data-type', alias_priority=2), 'filters': FieldInfo(annotation=Union[List[DatasetLineageTaskFiltersInfoFilterRulesInner], NoneType], required=False), 'object_locator': FieldInfo(annotation=Union[DatasetLineageTaskFiltersInfoSourceTableInfo, NoneType], required=False, alias='object-locator', alias_priority=2), 'old_value': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, alias='old-value', alias_priority=2), 'rule_action': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, alias='rule-action', alias_priority=2), 'rule_id': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, alias='rule-id', alias_priority=2), 'rule_name': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, alias='rule-name', alias_priority=2), 'rule_target': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, alias='rule-target', alias_priority=2), 'rule_type': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, alias='rule-type', alias_priority=2), 'value': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

model_post_init(__context)

This function is meant to behave like a BaseModel method to initialise private attributes.

It takes context as an argument since that’s what pydantic-core passes when calling it.

Parameters:

• self (BaseModel) – The BaseModel instance.

• __context (Any) – The context.

Return type:

None