UpdateDatasetMetadata¶

class openapi_client.models.update_dataset_metadata.UpdateDatasetMetadata(**data)[source]¶

Bases: BaseModel

dataset_description: Optional[StrictStr]¶

display_name: Optional[StrictStr]¶

data_classification: Optional[List[StrictStr]]¶

keywords: Optional[List[StrictStr]]¶

table_update: Optional[StrictStr]¶

skip_file_header: Optional[StrictBool]¶

malware_detection_options: Optional[MalwareDetectionOptions]¶

target_table_prep_mode: Optional[StrictStr]¶

is_data_validation_enabled: Optional[StrictBool]¶

life_cycle_policy_status: Optional[StrictStr]¶

life_cycle_rules: Optional[DatasetLifeCycleRules]¶

data_metrics_collection_options: Optional[DataMetricsCollectionOptions]¶

advanced_config: Optional[AdvancedConfig]¶

is_data_cleanup_enabled: Optional[StrictBool]¶

is_data_profiling_enabled: Optional[StrictBool]¶

skip_lz_process: Optional[StrictBool]¶

update_schema: Optional[StrictStr]¶

dataset_schema: Optional[List[ColumnNameAndType]]¶

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 UpdateDatasetMetadata 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 UpdateDatasetMetadata from a dict

Return type:: Optional[Self]

model_fields: ClassVar[dict[str, FieldInfo]] = {'advanced_config': FieldInfo(annotation=Union[AdvancedConfig, NoneType], required=False, alias='AdvancedConfig', alias_priority=2), 'data_classification': FieldInfo(annotation=Union[List[Annotated[str, Strict(strict=True)]], NoneType], required=False, alias='DataClassification', alias_priority=2), 'data_metrics_collection_options': FieldInfo(annotation=Union[DataMetricsCollectionOptions, NoneType], required=False, alias='DataMetricsCollectionOptions', alias_priority=2), 'dataset_description': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, alias='DatasetDescription', alias_priority=2), 'dataset_schema': FieldInfo(annotation=Union[List[ColumnNameAndType], NoneType], required=False, alias='DatasetSchema', alias_priority=2), 'display_name': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, alias='DisplayName', alias_priority=2), 'is_data_cleanup_enabled': FieldInfo(annotation=Union[Annotated[bool, Strict(strict=True)], NoneType], required=False, alias='IsDataCleanupEnabled', alias_priority=2), 'is_data_profiling_enabled': FieldInfo(annotation=Union[Annotated[bool, Strict(strict=True)], NoneType], required=False, alias='IsDataProfilingEnabled', alias_priority=2), 'is_data_validation_enabled': FieldInfo(annotation=Union[Annotated[bool, Strict(strict=True)], NoneType], required=False, alias='IsDataValidationEnabled', alias_priority=2), 'keywords': FieldInfo(annotation=Union[List[Annotated[str, Strict(strict=True)]], NoneType], required=False, alias='Keywords', alias_priority=2), 'life_cycle_policy_status': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, alias='LifeCyclePolicyStatus', alias_priority=2), 'life_cycle_rules': FieldInfo(annotation=Union[DatasetLifeCycleRules, NoneType], required=False, alias='LifeCycleRules', alias_priority=2), 'malware_detection_options': FieldInfo(annotation=Union[MalwareDetectionOptions, NoneType], required=False, alias='MalwareDetectionOptions', alias_priority=2), 'skip_file_header': FieldInfo(annotation=Union[Annotated[bool, Strict(strict=True)], NoneType], required=False, alias='SkipFileHeader', alias_priority=2), 'skip_lz_process': FieldInfo(annotation=Union[Annotated[bool, Strict(strict=True)], NoneType], required=False, alias='SkipLZProcess', alias_priority=2), 'table_update': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, alias='TableUpdate', alias_priority=2), 'target_table_prep_mode': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, alias='TargetTablePrepMode', alias_priority=2), 'update_schema': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, alias='UpdateSchema', 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