DatasourceFlowsDetailsDatasetDetailsInner

class openapi_client.models.datasource_flows_details_dataset_details_inner.DatasourceFlowsDetailsDatasetDetailsInner(**data)[source]

Bases: BaseModel

schema_name: Optional[StrictStr]
size: Optional[StrictInt]
table_name: Optional[StrictStr]
dataset_name: Optional[StrictStr]
description: Optional[StrictStr]
domain: Optional[StrictStr]
keywords: Optional[List[Any]]
skip_lz_process: Optional[StrictBool]
skip_file_header: Optional[StrictBool]
file_type: Optional[StrictStr]
file_delimiter: Optional[StrictStr]
data_classification: Optional[List[Any]]
data_schema: Optional[List[Any]]
dataset_id: Optional[StrictStr]
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 DatasourceFlowsDetailsDatasetDetailsInner 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 DatasourceFlowsDetailsDatasetDetailsInner from a dict

Return type:

Optional[Self]

model_fields: ClassVar[dict[str, FieldInfo]] = {'data_classification': FieldInfo(annotation=Union[List[Any], NoneType], required=False, alias='DataClassification', alias_priority=2), 'data_schema': FieldInfo(annotation=Union[List[Any], NoneType], required=False, alias='DataSchema', alias_priority=2), 'dataset_id': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, alias='DatasetId', alias_priority=2), 'dataset_name': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, alias='DatasetName', alias_priority=2), 'description': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, alias='Description', alias_priority=2), 'domain': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, alias='Domain', alias_priority=2), 'file_delimiter': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, alias='FileDelimiter', alias_priority=2), 'file_type': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, alias='FileType', alias_priority=2), 'keywords': FieldInfo(annotation=Union[List[Any], NoneType], required=False, alias='Keywords', alias_priority=2), 'schema_name': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, alias='SchemaName', alias_priority=2), 'size': FieldInfo(annotation=Union[Annotated[int, Strict(strict=True)], NoneType], required=False, alias='Size', 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_name': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, alias='TableName', 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