ClusterMetricsClustersMetrics

class openapi_client.models.cluster_metrics_clusters_metrics.ClusterMetricsClustersMetrics(**data)

Bases: BaseModel

start_time: Optional[StrictStr]

end_time: Optional[StrictStr]

cpu_utilization: Optional[LabelAndDatapoints]

db_connection_count: Optional[LabelAndDatapoints]

health_status: Optional[LabelAndDatapoints]

percentage_disk_space_used: Optional[LabelAndDatapoints]

network_receive_throughput: Optional[LabelAndDatapoints]

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 ClusterMetricsClustersMetrics 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 ClusterMetricsClustersMetrics from a dict

Return type:

Optional[Self]

model_fields: ClassVar[dict[str, FieldInfo]] = {'cpu_utilization': FieldInfo(annotation=Union[LabelAndDatapoints, NoneType], required=False, alias='CPUUtilization', alias_priority=2), 'db_connection_count': FieldInfo(annotation=Union[LabelAndDatapoints, NoneType], required=False, alias='DBConnectionCount', alias_priority=2), 'end_time': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, alias='EndTime', alias_priority=2), 'health_status': FieldInfo(annotation=Union[LabelAndDatapoints, NoneType], required=False, alias='HealthStatus', alias_priority=2), 'network_receive_throughput': FieldInfo(annotation=Union[LabelAndDatapoints, NoneType], required=False, alias='NetworkReceiveThroughput', alias_priority=2), 'percentage_disk_space_used': FieldInfo(annotation=Union[LabelAndDatapoints, NoneType], required=False, alias='PercentageDiskSpaceUsed', alias_priority=2), 'start_time': FieldInfo(annotation=Union[Annotated[str, Strict(strict=True)], NoneType], required=False, alias='StartTime', 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