Source code for openapi_client.models.cluster_metrics_clusters_metrics

# coding: utf-8

"""
    Amorphic Data Platform

    Amorphic Data Platform - API Definition documentation

    The version of the OpenAPI document: 0.3.0
    Generated by OpenAPI Generator (https://openapi-generator.tech)

    Do not edit the class manually.
"""  # noqa: E501


from __future__ import annotations
import pprint
import re  # noqa: F401
import json

from pydantic import BaseModel, ConfigDict, Field, StrictStr
from typing import Any, ClassVar, Dict, List, Optional
from openapi_client.models.label_and_datapoints import LabelAndDatapoints
from typing import Optional, Set
from typing_extensions import Self



class ClusterMetricsClustersMetrics(BaseModel):
    """
    ClusterMetricsClustersMetrics
    """ # noqa: E501
    start_time: Optional[StrictStr] = Field(default=None, alias="StartTime")
    end_time: Optional[StrictStr] = Field(default=None, alias="EndTime")
    cpu_utilization: Optional[LabelAndDatapoints] = Field(default=None, alias="CPUUtilization")
    db_connection_count: Optional[LabelAndDatapoints] = Field(default=None, alias="DBConnectionCount")
    health_status: Optional[LabelAndDatapoints] = Field(default=None, alias="HealthStatus")
    percentage_disk_space_used: Optional[LabelAndDatapoints] = Field(default=None, alias="PercentageDiskSpaceUsed")
    network_receive_throughput: Optional[LabelAndDatapoints] = Field(default=None, alias="NetworkReceiveThroughput")
    __properties: ClassVar[List[str]] = ["StartTime", "EndTime", "CPUUtilization", "DBConnectionCount", "HealthStatus", "PercentageDiskSpaceUsed", "NetworkReceiveThroughput"]

    model_config = ConfigDict(
        populate_by_name=True,
        validate_assignment=True,
        protected_namespaces=(),
    )




    def to_str(self) -> str:
        """Returns the string representation of the model using alias"""
        return pprint.pformat(self.model_dump(by_alias=True))




    def to_json(self) -> str:
        """Returns the JSON representation of the model using alias"""
        # TODO: pydantic v2: use .model_dump_json(by_alias=True, exclude_unset=True) instead
        return json.dumps(self.to_dict())




    @classmethod
    def from_json(cls, json_str: str) -> Optional[Self]:
        """Create an instance of ClusterMetricsClustersMetrics from a JSON string"""
        return cls.from_dict(json.loads(json_str))




    def to_dict(self) -> Dict[str, Any]:
        """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.
        """
        excluded_fields: Set[str] = set([
        ])

        _dict = self.model_dump(
            by_alias=True,
            exclude=excluded_fields,
            exclude_none=True,
        )
        # override the default output from pydantic by calling `to_dict()` of cpu_utilization
        if self.cpu_utilization:
            _dict['CPUUtilization'] = self.cpu_utilization.to_dict()
        # override the default output from pydantic by calling `to_dict()` of db_connection_count
        if self.db_connection_count:
            _dict['DBConnectionCount'] = self.db_connection_count.to_dict()
        # override the default output from pydantic by calling `to_dict()` of health_status
        if self.health_status:
            _dict['HealthStatus'] = self.health_status.to_dict()
        # override the default output from pydantic by calling `to_dict()` of percentage_disk_space_used
        if self.percentage_disk_space_used:
            _dict['PercentageDiskSpaceUsed'] = self.percentage_disk_space_used.to_dict()
        # override the default output from pydantic by calling `to_dict()` of network_receive_throughput
        if self.network_receive_throughput:
            _dict['NetworkReceiveThroughput'] = self.network_receive_throughput.to_dict()
        return _dict




    @classmethod
    def from_dict(cls, obj: Optional[Dict[str, Any]]) -> Optional[Self]:
        """Create an instance of ClusterMetricsClustersMetrics from a dict"""
        if obj is None:
            return None

        if not isinstance(obj, dict):
            return cls.model_validate(obj)

        _obj = cls.model_validate({
            "StartTime": obj.get("StartTime"),
            "EndTime": obj.get("EndTime"),
            "CPUUtilization": LabelAndDatapoints.from_dict(obj["CPUUtilization"]) if obj.get("CPUUtilization") is not None else None,
            "DBConnectionCount": LabelAndDatapoints.from_dict(obj["DBConnectionCount"]) if obj.get("DBConnectionCount") is not None else None,
            "HealthStatus": LabelAndDatapoints.from_dict(obj["HealthStatus"]) if obj.get("HealthStatus") is not None else None,
            "PercentageDiskSpaceUsed": LabelAndDatapoints.from_dict(obj["PercentageDiskSpaceUsed"]) if obj.get("PercentageDiskSpaceUsed") is not None else None,
            "NetworkReceiveThroughput": LabelAndDatapoints.from_dict(obj["NetworkReceiveThroughput"]) if obj.get("NetworkReceiveThroughput") is not None else None
        })
        return _obj