DataPipelinesPostNodesInner¶

class openapi_client.models.data_pipelines_post_nodes_inner.DataPipelinesPostNodesInner(**data)[source]¶

Bases: BaseModel

module_type: StrictStr¶

source_dataset_id: Optional[StrictStr]¶

source_language_id: Optional[StrictStr]¶

target_language_id: Optional[StrictStr]¶

target_dataset_id: Optional[StrictStr]¶

file_processing_mode: Optional[StrictStr]¶

node_name: StrictStr¶

resource: Optional[DataPipelineNodesInnerResource]¶

concurrency_factor: Optional[Union[StrictFloat, StrictInt]]¶

dataset_domain: Optional[StrictStr]¶

sync_all_datasets: Optional[StrictBool]¶

list_of_input_datasets: Optional[List[StrictStr]]¶

arguments: Optional[Dict[str, Any]]¶

features: Optional[List[StrictStr]]¶

email_body_execution_property_key: Optional[StrictStr]¶

email_subject_execution_property_key: Optional[StrictStr]¶

email_to_execution_property_key: Optional[StrictStr]¶

timeout: Optional[StrictInt]¶

agent_type: Optional[StrictStr]¶

model_id: Optional[StrictStr]¶

dataset_processing_mode: Optional[StrictStr]¶

file_names_list: Optional[List[StrictStr]]¶

columns_to_visualise: Optional[List[StrictStr]]¶

prompt: Optional[StrictStr]¶

ingestion_type: Optional[StrictStr]¶

node_instance: Optional[StrictStr]¶

from_time: Optional[StrictStr]¶

to_time: Optional[StrictStr]¶

configuration: Optional[Dict[str, Any]]¶

resource_identifier: Optional[StrictStr]¶

inputs: Optional[List[DataPipelineNodesInnerInputsInner]]¶

outputs: Optional[List[DataPipelineNodesInnerOutputsInner]]¶

conditions: Optional[List[DataPipelineNodesInnerConditionsInner]]¶

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()[source]¶

Returns the string representation of the model using alias

Return type:: str

to_json()[source]¶

Returns the JSON representation of the model using alias

Return type:: str

classmethod from_json(json_str)[source]¶

Create an instance of DataPipelinesPostNodesInner from a JSON string

Return type:: Optional[Self]

to_dict()[source]¶

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)[source]¶

Create an instance of DataPipelinesPostNodesInner from a dict

Return type:: Optional[Self]

model_fields: ClassVar[dict[str, FieldInfo]] = {'agent_type': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, alias='AgentType', alias_priority=2), 'arguments': FieldInfo(annotation=Union[Dict[str, Any], NoneType], required=False, alias='Arguments', alias_priority=2), 'columns_to_visualise': FieldInfo(annotation=Union[List[Annotated[str, Strict(strict=True)]], NoneType], required=False, alias='ColumnsToVisualise', alias_priority=2), 'concurrency_factor': FieldInfo(annotation=Union[Annotated[float, Strict(strict=True)], Annotated[int, Strict(strict=True)], NoneType], required=False, alias='ConcurrencyFactor', alias_priority=2), 'conditions': FieldInfo(annotation=Union[List[DataPipelineNodesInnerConditionsInner], NoneType], required=False, alias='Conditions', alias_priority=2, description="Condition configurations for Condition nodes. Each condition has Name and optional Expression (default condition doesn't require Expression)."), 'configuration': FieldInfo(annotation=Union[Dict[str, Any], NoneType], required=False, alias='Configuration', alias_priority=2), 'dataset_domain': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, alias='DatasetDomain', alias_priority=2), 'dataset_processing_mode': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, alias='DatasetProcessingMode', alias_priority=2), 'email_body_execution_property_key': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, alias='EmailBodyExecutionPropertyKey', alias_priority=2), 'email_subject_execution_property_key': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, alias='EmailSubjectExecutionPropertyKey', alias_priority=2), 'email_to_execution_property_key': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, alias='EmailToExecutionPropertyKey', alias_priority=2), 'features': FieldInfo(annotation=Union[List[Annotated[str, Strict(strict=True)]], NoneType], required=False, alias='Features', alias_priority=2), 'file_names_list': FieldInfo(annotation=Union[List[Annotated[str, Strict(strict=True)]], NoneType], required=False, alias='FileNamesList', alias_priority=2), 'file_processing_mode': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, alias='FileProcessingMode', alias_priority=2), 'from_time': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, alias='FromTime', alias_priority=2), 'ingestion_type': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, alias='IngestionType', alias_priority=2), 'inputs': FieldInfo(annotation=Union[List[DataPipelineNodesInnerInputsInner], NoneType], required=False, alias='Inputs', alias_priority=2, description='Input configurations for AI Flow nodes. Each input has Name and Type.'), 'list_of_input_datasets': FieldInfo(annotation=Union[List[Annotated[str, Strict(strict=True)]], NoneType], required=False, alias='ListOfInputDatasets', alias_priority=2), 'model_id': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, alias='ModelId', alias_priority=2), 'module_type': FieldInfo(annotation=str, required=True, alias='ModuleType', alias_priority=2, metadata=[Strict(strict=True)]), 'node_instance': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, alias='NodeInstance', alias_priority=2), 'node_name': FieldInfo(annotation=str, required=True, alias='NodeName', alias_priority=2, metadata=[Strict(strict=True)]), 'outputs': FieldInfo(annotation=Union[List[DataPipelineNodesInnerOutputsInner], NoneType], required=False, alias='Outputs', alias_priority=2, description='Output configurations for AI Flow nodes. Each output has Name and Type.'), 'prompt': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, alias='Prompt', alias_priority=2), 'resource': FieldInfo(annotation=Union[DataPipelineNodesInnerResource, NoneType], required=False, alias='Resource', alias_priority=2), 'resource_identifier': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, alias='ResourceIdentifier', alias_priority=2, description='Resource identifier for nodes that require external resources (e.g., KnowledgeBase, LambdaFunction)'), 'source_dataset_id': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, alias='SourceDatasetId', alias_priority=2), 'source_language_id': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, alias='SourceLanguageId', alias_priority=2), 'sync_all_datasets': FieldInfo(annotation=Union[Annotated[bool, Strict(strict=True)], NoneType], required=False, alias='SyncAllDatasets', alias_priority=2), 'target_dataset_id': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, alias='TargetDatasetId', alias_priority=2), 'target_language_id': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, alias='TargetLanguageId', alias_priority=2), 'timeout': FieldInfo(annotation=Union[Annotated[int, Strict(strict=True)], NoneType], required=False, alias='Timeout', alias_priority=2), 'to_time': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, alias='ToTime', alias_priority=2)}¶

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