# 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 V2HorizontalPodAutoscalerSpec(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 = { 'behavior': 'V2HorizontalPodAutoscalerBehavior', 'max_replicas': 'int', 'metrics': 'list[V2MetricSpec]', 'min_replicas': 'int', 'scale_target_ref': 'V2CrossVersionObjectReference' } attribute_map = { 'behavior': 'behavior', 'max_replicas': 'maxReplicas', 'metrics': 'metrics', 'min_replicas': 'minReplicas', 'scale_target_ref': 'scaleTargetRef' } def __init__(self, behavior=None, max_replicas=None, metrics=None, min_replicas=None, scale_target_ref=None, local_vars_configuration=None): # noqa: E501 """V2HorizontalPodAutoscalerSpec - 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._behavior = None self._max_replicas = None self._metrics = None self._min_replicas = None self._scale_target_ref = None self.discriminator = None if behavior is not None: self.behavior = behavior self.max_replicas = max_replicas if metrics is not None: self.metrics = metrics if min_replicas is not None: self.min_replicas = min_replicas self.scale_target_ref = scale_target_ref @property def behavior(self): """Gets the behavior of this V2HorizontalPodAutoscalerSpec. # noqa: E501 :return: The behavior of this V2HorizontalPodAutoscalerSpec. # noqa: E501 :rtype: V2HorizontalPodAutoscalerBehavior """ return self._behavior @behavior.setter def behavior(self, behavior): """Sets the behavior of this V2HorizontalPodAutoscalerSpec. :param behavior: The behavior of this V2HorizontalPodAutoscalerSpec. # noqa: E501 :type: V2HorizontalPodAutoscalerBehavior """ self._behavior = behavior @property def max_replicas(self): """Gets the max_replicas of this V2HorizontalPodAutoscalerSpec. # noqa: E501 maxReplicas is the upper limit for the number of replicas to which the autoscaler can scale up. It cannot be less that minReplicas. # noqa: E501 :return: The max_replicas of this V2HorizontalPodAutoscalerSpec. # noqa: E501 :rtype: int """ return self._max_replicas @max_replicas.setter def max_replicas(self, max_replicas): """Sets the max_replicas of this V2HorizontalPodAutoscalerSpec. maxReplicas is the upper limit for the number of replicas to which the autoscaler can scale up. It cannot be less that minReplicas. # noqa: E501 :param max_replicas: The max_replicas of this V2HorizontalPodAutoscalerSpec. # 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 metrics(self): """Gets the metrics of this V2HorizontalPodAutoscalerSpec. # noqa: E501 metrics contains the specifications for which to use to calculate the desired replica count (the maximum replica count across all metrics will be used). The desired replica count is calculated multiplying the ratio between the target value and the current value by the current number of pods. Ergo, metrics used must decrease as the pod count is increased, and vice-versa. See the individual metric source types for more information about how each type of metric must respond. If not set, the default metric will be set to 80% average CPU utilization. # noqa: E501 :return: The metrics of this V2HorizontalPodAutoscalerSpec. # noqa: E501 :rtype: list[V2MetricSpec] """ return self._metrics @metrics.setter def metrics(self, metrics): """Sets the metrics of this V2HorizontalPodAutoscalerSpec. metrics contains the specifications for which to use to calculate the desired replica count (the maximum replica count across all metrics will be used). The desired replica count is calculated multiplying the ratio between the target value and the current value by the current number of pods. Ergo, metrics used must decrease as the pod count is increased, and vice-versa. See the individual metric source types for more information about how each type of metric must respond. If not set, the default metric will be set to 80% average CPU utilization. # noqa: E501 :param metrics: The metrics of this V2HorizontalPodAutoscalerSpec. # noqa: E501 :type: list[V2MetricSpec] """ self._metrics = metrics @property def min_replicas(self): """Gets the min_replicas of this V2HorizontalPodAutoscalerSpec. # 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 V2HorizontalPodAutoscalerSpec. # noqa: E501 :rtype: int """ return self._min_replicas @min_replicas.setter def min_replicas(self, min_replicas): """Sets the min_replicas of this V2HorizontalPodAutoscalerSpec. 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 V2HorizontalPodAutoscalerSpec. # noqa: E501 :type: int """ self._min_replicas = min_replicas @property def scale_target_ref(self): """Gets the scale_target_ref of this V2HorizontalPodAutoscalerSpec. # noqa: E501 :return: The scale_target_ref of this V2HorizontalPodAutoscalerSpec. # noqa: E501 :rtype: V2CrossVersionObjectReference """ return self._scale_target_ref @scale_target_ref.setter def scale_target_ref(self, scale_target_ref): """Sets the scale_target_ref of this V2HorizontalPodAutoscalerSpec. :param scale_target_ref: The scale_target_ref of this V2HorizontalPodAutoscalerSpec. # noqa: E501 :type: V2CrossVersionObjectReference """ 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 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, V2HorizontalPodAutoscalerSpec): 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, V2HorizontalPodAutoscalerSpec): return True return self.to_dict() != other.to_dict()