UserResources

class openapi_client.models.user_resources.UserResources(**data)

Bases: BaseModel

dataset_access: Optional[DatasetAccess]

schedules: Optional[List[UserResourcesSchedulesInner]]

etl_jobs: Optional[List[UserResourcesEtlJobsInner]]

datalabs: Optional[List[UserResourcesDatalabsInner]]

models: Optional[List[UserResourcesModelsInner]]

dashboards: Optional[List[UserResourcesDashboardsInner]]

roles: Optional[List[UserResourcesRolesInner]]

groups: Optional[UserResourcesGroups]

parameters: Optional[UserResourcesParameters]

shared_libraries: Optional[List[StrictStr]]

data_pipelines: Optional[List[UserResourcesDataPipelinesInner]]

data_quality_checks: Optional[List[UserResourcesDataQualityChecksInner]]

domain_names: Optional[List[UserResourcesDomainNamesInner]]

tenant_names: Optional[List[StrictStr]]

datalab_lifecycle_configurations: Optional[List[UserResourcesDatalabLifecycleConfigurationsInner]]

code_repositories: Optional[List[UserResourcesCodeRepositoriesInner]]

datasources: Optional[List[UserResourcesDatasourcesInner]]

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 UserResources 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 UserResources from a dict

Return type:

Optional[Self]

model_fields: ClassVar[dict[str, FieldInfo]] = {'code_repositories': FieldInfo(annotation=Union[List[UserResourcesCodeRepositoriesInner], NoneType], required=False, alias='CodeRepositories', alias_priority=2), 'dashboards': FieldInfo(annotation=Union[List[UserResourcesDashboardsInner], NoneType], required=False, alias='Dashboards', alias_priority=2), 'data_pipelines': FieldInfo(annotation=Union[List[UserResourcesDataPipelinesInner], NoneType], required=False, alias='DataPipelines', alias_priority=2), 'data_quality_checks': FieldInfo(annotation=Union[List[UserResourcesDataQualityChecksInner], NoneType], required=False, alias='DataQualityChecks', alias_priority=2), 'datalab_lifecycle_configurations': FieldInfo(annotation=Union[List[UserResourcesDatalabLifecycleConfigurationsInner], NoneType], required=False, alias='DatalabLifecycleConfigurations', alias_priority=2), 'datalabs': FieldInfo(annotation=Union[List[UserResourcesDatalabsInner], NoneType], required=False, alias='Datalabs', alias_priority=2), 'dataset_access': FieldInfo(annotation=Union[DatasetAccess, NoneType], required=False, alias='DatasetAccess', alias_priority=2), 'datasources': FieldInfo(annotation=Union[List[UserResourcesDatasourcesInner], NoneType], required=False, alias='Datasources', alias_priority=2), 'domain_names': FieldInfo(annotation=Union[List[UserResourcesDomainNamesInner], NoneType], required=False, alias='DomainNames', alias_priority=2), 'etl_jobs': FieldInfo(annotation=Union[List[UserResourcesEtlJobsInner], NoneType], required=False, alias='EtlJobs', alias_priority=2), 'groups': FieldInfo(annotation=Union[UserResourcesGroups, NoneType], required=False, alias='Groups', alias_priority=2), 'models': FieldInfo(annotation=Union[List[UserResourcesModelsInner], NoneType], required=False, alias='Models', alias_priority=2), 'parameters': FieldInfo(annotation=Union[UserResourcesParameters, NoneType], required=False, alias='Parameters', alias_priority=2), 'roles': FieldInfo(annotation=Union[List[UserResourcesRolesInner], NoneType], required=False, alias='Roles', alias_priority=2), 'schedules': FieldInfo(annotation=Union[List[UserResourcesSchedulesInner], NoneType], required=False, alias='Schedules', alias_priority=2), 'shared_libraries': FieldInfo(annotation=Union[List[Annotated[str, Strict(strict=True)]], NoneType], required=False, alias='SharedLibraries', alias_priority=2), 'tenant_names': FieldInfo(annotation=Union[List[Annotated[str, Strict(strict=True)]], NoneType], required=False, alias='TenantNames', 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