DatasourceEntityDetailsEntityConfig¶
- class openapi_client.models.datasource_entity_details_entity_config.DatasourceEntityDetailsEntityConfig(**data)[source]¶
Bases:
BaseModel- instance_multi_az: Optional[StrictBool]¶
- auto_minor_version_upgrade: Optional[StrictBool]¶
- preferred_maintenance_window: Optional[StrictStr]¶
- instance_class: Optional[StrictStr]¶
- allocated_storage: Optional[StrictInt]¶
- instance_az: Optional[StrictStr]¶
- dms_version: Optional[StrictStr]¶
- publicly_accessible_instance: Optional[StrictBool]¶
- lambda_handler: Optional[StrictStr]¶
- memory_size: Optional[StrictInt]¶
- cluster_size: Optional[StrictStr]¶
- cluster_storage: Optional[StrictStr]¶
- number_of_brokers: Optional[StrictStr]¶
- list_of_consumers: Optional[List[Any]]¶
- kafka_version: Optional[StrictStr]¶
- is_auto_scaling_enabled: Optional[StrictBool]¶
- is_auto_terminate_enabled: Optional[StrictBool]¶
- data_retention_in_hours: Optional[StrictStr]¶
- auto_scaling_config: Optional[DatasourceDetailsDatasourceConfigClusterConfigAutoScalingConfig]¶
- schedule_config: Optional[DatasourceEntityDetailsEntityConfigScheduleConfig]¶
- 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].
- classmethod from_json(json_str)[source]¶
Create an instance of DatasourceEntityDetailsEntityConfig 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 DatasourceEntityDetailsEntityConfig from a dict
- Return type:
Optional[Self]
- model_fields: ClassVar[dict[str, FieldInfo]] = {'allocated_storage': FieldInfo(annotation=Union[Annotated[int, Strict(strict=True)], NoneType], required=False, alias='AllocatedStorage', alias_priority=2), 'auto_minor_version_upgrade': FieldInfo(annotation=Union[Annotated[bool, Strict(strict=True)], NoneType], required=False, alias='AutoMinorVersionUpgrade', alias_priority=2), 'auto_scaling_config': FieldInfo(annotation=Union[DatasourceDetailsDatasourceConfigClusterConfigAutoScalingConfig, NoneType], required=False, alias='AutoScalingConfig', alias_priority=2), 'cluster_size': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, alias='ClusterSize', alias_priority=2), 'cluster_storage': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, alias='ClusterStorage', alias_priority=2), 'data_retention_in_hours': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, alias='DataRetentionInHours', alias_priority=2), 'dms_version': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, alias='DmsVersion', alias_priority=2), 'instance_az': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, alias='InstanceAZ', alias_priority=2), 'instance_class': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, alias='InstanceClass', alias_priority=2), 'instance_multi_az': FieldInfo(annotation=Union[Annotated[bool, Strict(strict=True)], NoneType], required=False, alias='InstanceMultiAZ', alias_priority=2), 'is_auto_scaling_enabled': FieldInfo(annotation=Union[Annotated[bool, Strict(strict=True)], NoneType], required=False, alias='IsAutoScalingEnabled', alias_priority=2), 'is_auto_terminate_enabled': FieldInfo(annotation=Union[Annotated[bool, Strict(strict=True)], NoneType], required=False, alias='IsAutoTerminateEnabled', alias_priority=2), 'kafka_version': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, alias='KafkaVersion', alias_priority=2), 'lambda_handler': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, alias='LambdaHandler', alias_priority=2), 'list_of_consumers': FieldInfo(annotation=Union[List[Any], NoneType], required=False, alias='ListOfConsumers', alias_priority=2), 'memory_size': FieldInfo(annotation=Union[Annotated[int, Strict(strict=True)], NoneType], required=False, alias='MemorySize', alias_priority=2), 'number_of_brokers': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, alias='NumberOfBrokers', alias_priority=2), 'preferred_maintenance_window': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, alias='PreferredMaintenanceWindow', alias_priority=2), 'publicly_accessible_instance': FieldInfo(annotation=Union[Annotated[bool, Strict(strict=True)], NoneType], required=False, alias='PubliclyAccessibleInstance', alias_priority=2), 'schedule_config': FieldInfo(annotation=Union[DatasourceEntityDetailsEntityConfigScheduleConfig, NoneType], required=False, alias='ScheduleConfig', alias_priority=2), 'shared_cluster': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, alias='SharedCluster', alias_priority=2), 'shared_instance': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, alias='SharedInstance', 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