# coding: utf-8 """ Kubernetes No description provided (generated by Openapi Generator https://github.com/openapitools/openapi-generator) # noqa: E501 The version of the OpenAPI document: release-1.32 Generated by: https://openapi-generator.tech """ import pprint import re # noqa: F401 import six from kubernetes.client.configuration import Configuration class V1HorizontalPodAutoscalerSpec(object): """NOTE: This class is auto generated by OpenAPI Generator. Ref: https://openapi-generator.tech Do not edit the class manually. """ """ Attributes: openapi_types (dict): The key is attribute name and the value is attribute type. attribute_map (dict): The key is attribute name and the value is json key in definition. """ openapi_types = { 'max_replicas': 'int', 'min_replicas': 'int', 'scale_target_ref': 'V1CrossVersionObjectReference', 'target_cpu_utilization_percentage': 'int' } attribute_map = { 'max_replicas': 'maxReplicas', 'min_replicas': 'minReplicas', 'scale_target_ref': 'scaleTargetRef', 'target_cpu_utilization_percentage': 'targetCPUUtilizationPercentage' } def __init__(self, max_replicas=None, min_replicas=None, scale_target_ref=None, target_cpu_utilization_percentage=None, local_vars_configuration=None): # noqa: E501 """V1HorizontalPodAutoscalerSpec - a model defined in OpenAPI""" # noqa: E501 if local_vars_configuration is None: local_vars_configuration = Configuration() self.local_vars_configuration = local_vars_configuration self._max_replicas = None self._min_replicas = None self._scale_target_ref = None self._target_cpu_utilization_percentage = None self.discriminator = None self.max_replicas = max_replicas if min_replicas is not None: self.min_replicas = min_replicas self.scale_target_ref = scale_target_ref if target_cpu_utilization_percentage is not None: self.target_cpu_utilization_percentage = target_cpu_utilization_percentage @property def max_replicas(self): """Gets the max_replicas of this V1HorizontalPodAutoscalerSpec. # noqa: E501 maxReplicas is the upper limit for the number of pods that can be set by the autoscaler; cannot be smaller than MinReplicas. # noqa: E501 :return: The max_replicas of this V1HorizontalPodAutoscalerSpec. # noqa: E501 :rtype: int """ return self._max_replicas @max_replicas.setter def max_replicas(self, max_replicas): """Sets the max_replicas of this V1HorizontalPodAutoscalerSpec. maxReplicas is the upper limit for the number of pods that can be set by the autoscaler; cannot be smaller than MinReplicas. # noqa: E501 :param max_replicas: The max_replicas of this V1HorizontalPodAutoscalerSpec. # noqa: E501 :type: int """ if self.local_vars_configuration.client_side_validation and max_replicas is None: # noqa: E501 raise ValueError("Invalid value for `max_replicas`, must not be `None`") # noqa: E501 self._max_replicas = max_replicas @property def min_replicas(self): """Gets the min_replicas of this V1HorizontalPodAutoscalerSpec. # noqa: E501 minReplicas is the lower limit for the number of replicas to which the autoscaler can scale down. It defaults to 1 pod. minReplicas is allowed to be 0 if the alpha feature gate HPAScaleToZero is enabled and at least one Object or External metric is configured. Scaling is active as long as at least one metric value is available. # noqa: E501 :return: The min_replicas of this V1HorizontalPodAutoscalerSpec. # noqa: E501 :rtype: int """ return self._min_replicas @min_replicas.setter def min_replicas(self, min_replicas): """Sets the min_replicas of this V1HorizontalPodAutoscalerSpec. minReplicas is the lower limit for the number of replicas to which the autoscaler can scale down. It defaults to 1 pod. minReplicas is allowed to be 0 if the alpha feature gate HPAScaleToZero is enabled and at least one Object or External metric is configured. Scaling is active as long as at least one metric value is available. # noqa: E501 :param min_replicas: The min_replicas of this V1HorizontalPodAutoscalerSpec. # noqa: E501 :type: int """ self._min_replicas = min_replicas @property def scale_target_ref(self): """Gets the scale_target_ref of this V1HorizontalPodAutoscalerSpec. # noqa: E501 :return: The scale_target_ref of this V1HorizontalPodAutoscalerSpec. # noqa: E501 :rtype: V1CrossVersionObjectReference """ return self._scale_target_ref @scale_target_ref.setter def scale_target_ref(self, scale_target_ref): """Sets the scale_target_ref of this V1HorizontalPodAutoscalerSpec. :param scale_target_ref: The scale_target_ref of this V1HorizontalPodAutoscalerSpec. # noqa: E501 :type: V1CrossVersionObjectReference """ if self.local_vars_configuration.client_side_validation and scale_target_ref is None: # noqa: E501 raise ValueError("Invalid value for `scale_target_ref`, must not be `None`") # noqa: E501 self._scale_target_ref = scale_target_ref @property def target_cpu_utilization_percentage(self): """Gets the target_cpu_utilization_percentage of this V1HorizontalPodAutoscalerSpec. # noqa: E501 targetCPUUtilizationPercentage is the target average CPU utilization (represented as a percentage of requested CPU) over all the pods; if not specified the default autoscaling policy will be used. # noqa: E501 :return: The target_cpu_utilization_percentage of this V1HorizontalPodAutoscalerSpec. # noqa: E501 :rtype: int """ return self._target_cpu_utilization_percentage @target_cpu_utilization_percentage.setter def target_cpu_utilization_percentage(self, target_cpu_utilization_percentage): """Sets the target_cpu_utilization_percentage of this V1HorizontalPodAutoscalerSpec. targetCPUUtilizationPercentage is the target average CPU utilization (represented as a percentage of requested CPU) over all the pods; if not specified the default autoscaling policy will be used. # noqa: E501 :param target_cpu_utilization_percentage: The target_cpu_utilization_percentage of this V1HorizontalPodAutoscalerSpec. # noqa: E501 :type: int """ self._target_cpu_utilization_percentage = target_cpu_utilization_percentage def to_dict(self): """Returns the model properties as a dict""" result = {} for attr, _ in six.iteritems(self.openapi_types): value = getattr(self, attr) if isinstance(value, list): result[attr] = list(map( lambda x: x.to_dict() if hasattr(x, "to_dict") else x, value )) elif hasattr(value, "to_dict"): result[attr] = value.to_dict() elif isinstance(value, dict): result[attr] = dict(map( lambda item: (item[0], item[1].to_dict()) if hasattr(item[1], "to_dict") else item, value.items() )) else: result[attr] = value return result def to_str(self): """Returns the string representation of the model""" return pprint.pformat(self.to_dict()) def __repr__(self): """For `print` and `pprint`""" return self.to_str() def __eq__(self, other): """Returns true if both objects are equal""" if not isinstance(other, V1HorizontalPodAutoscalerSpec): return False return self.to_dict() == other.to_dict() def __ne__(self, other): """Returns true if both objects are not equal""" if not isinstance(other, V1HorizontalPodAutoscalerSpec): return True return self.to_dict() != other.to_dict()