DatasourceDetailsDatasourceConfigClusterConfig¶
- pydantic model openapi_client.models.datasource_details_datasource_config_cluster_config.DatasourceDetailsDatasourceConfigClusterConfig¶
DatasourceDetailsDatasourceConfigClusterConfig
- Fields:
- field cluster_size: Optional[StrictStr] = None (alias 'ClusterSize')¶
- field cluster_storage: Optional[StrictStr] = None (alias 'ClusterStorage')¶
- field number_of_brokers: Optional[StrictStr] = None (alias 'NumberOfBrokers')¶
- field kafka_version: Optional[StrictStr] = None (alias 'KafkaVersion')¶
- field data_retention_in_hours: Optional[StrictStr] = None (alias 'DataRetentionInHours')¶
- field is_auto_scaling_enabled: Optional[StrictBool] = None (alias 'IsAutoScalingEnabled')¶
- field auto_scaling_config: Optional[DatasourceDetailsDatasourceConfigClusterConfigAutoScalingConfig] = None (alias 'AutoScalingConfig')¶
- 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 DatasourceDetailsDatasourceConfigClusterConfig 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 DatasourceDetailsDatasourceConfigClusterConfig from a dict
- Return type:
Optional[Self]