ModelData

class openapi_client.models.model_data.ModelData(**data)

Bases: BaseModel

artifacts_location: Optional[StrictStr]

description: StrictStr

model_name: StrictStr

output_type: StrictStr

algorithm_used: StrictStr

supported_file_formats: List[StrictStr]

pre_processed_glue_jobs: StrictStr

post_processed_glue_jobs: StrictStr

keywords: Optional[List[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()

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 ModelData 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 ModelData from a dict

Return type:

Optional[Self]

model_fields: ClassVar[dict[str, FieldInfo]] = {'algorithm_used': FieldInfo(annotation=str, required=True, alias='AlgorithmUsed', alias_priority=2, metadata=[Strict(strict=True)]), 'artifacts_location': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, alias='ArtifactsLocation', alias_priority=2), 'description': FieldInfo(annotation=str, required=True, alias='Description', alias_priority=2, metadata=[Strict(strict=True)]), 'keywords': FieldInfo(annotation=Union[List[Annotated[str, Strict(strict=True)]], NoneType], required=False, alias='Keywords', alias_priority=2), 'model_name': FieldInfo(annotation=str, required=True, alias='ModelName', alias_priority=2, metadata=[Strict(strict=True)]), 'output_type': FieldInfo(annotation=str, required=True, alias='OutputType', alias_priority=2, metadata=[Strict(strict=True)]), 'post_processed_glue_jobs': FieldInfo(annotation=str, required=True, alias='PostProcessedGlueJobs', alias_priority=2, metadata=[Strict(strict=True)]), 'pre_processed_glue_jobs': FieldInfo(annotation=str, required=True, alias='PreProcessedGlueJobs', alias_priority=2, metadata=[Strict(strict=True)]), 'supported_file_formats': FieldInfo(annotation=List[Annotated[str, Strict(strict=True)]], required=True, alias='SupportedFileFormats', 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