# coding: utf-8 """ Kubernetes No description provided (generated by Swagger Codegen https://github.com/swagger-api/swagger-codegen) OpenAPI spec version: v1.7.4 Generated by: https://github.com/swagger-api/swagger-codegen.git """ from pprint import pformat from six import iteritems import re class V2alpha1HorizontalPodAutoscalerSpec(object): """ NOTE: This class is auto generated by the swagger code generator program. Do not edit the class manually. """ def __init__(self, max_replicas=None, metrics=None, min_replicas=None, scale_target_ref=None): """ V2alpha1HorizontalPodAutoscalerSpec - a model defined in Swagger :param dict swaggerTypes: The key is attribute name and the value is attribute type. :param dict attributeMap: The key is attribute name and the value is json key in definition. """ self.swagger_types = { 'max_replicas': 'int', 'metrics': 'list[V2alpha1MetricSpec]', 'min_replicas': 'int', 'scale_target_ref': 'V2alpha1CrossVersionObjectReference' } self.attribute_map = { 'max_replicas': 'maxReplicas', 'metrics': 'metrics', 'min_replicas': 'minReplicas', 'scale_target_ref': 'scaleTargetRef' } self._max_replicas = max_replicas self._metrics = metrics self._min_replicas = min_replicas self._scale_target_ref = scale_target_ref @property def max_replicas(self): """ Gets the max_replicas of this V2alpha1HorizontalPodAutoscalerSpec. maxReplicas is the upper limit for the number of replicas to which the autoscaler can scale up. It cannot be less that minReplicas. :return: The max_replicas of this V2alpha1HorizontalPodAutoscalerSpec. :rtype: int """ return self._max_replicas @max_replicas.setter def max_replicas(self, max_replicas): """ Sets the max_replicas of this V2alpha1HorizontalPodAutoscalerSpec. maxReplicas is the upper limit for the number of replicas to which the autoscaler can scale up. It cannot be less that minReplicas. :param max_replicas: The max_replicas of this V2alpha1HorizontalPodAutoscalerSpec. :type: int """ if max_replicas is None: raise ValueError("Invalid value for `max_replicas`, must not be `None`") self._max_replicas = max_replicas @property def metrics(self): """ Gets the metrics of this V2alpha1HorizontalPodAutoscalerSpec. 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. :return: The metrics of this V2alpha1HorizontalPodAutoscalerSpec. :rtype: list[V2alpha1MetricSpec] """ return self._metrics @metrics.setter def metrics(self, metrics): """ Sets the metrics of this V2alpha1HorizontalPodAutoscalerSpec. 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. :param metrics: The metrics of this V2alpha1HorizontalPodAutoscalerSpec. :type: list[V2alpha1MetricSpec] """ self._metrics = metrics @property def min_replicas(self): """ Gets the min_replicas of this V2alpha1HorizontalPodAutoscalerSpec. minReplicas is the lower limit for the number of replicas to which the autoscaler can scale down. It defaults to 1 pod. :return: The min_replicas of this V2alpha1HorizontalPodAutoscalerSpec. :rtype: int """ return self._min_replicas @min_replicas.setter def min_replicas(self, min_replicas): """ Sets the min_replicas of this V2alpha1HorizontalPodAutoscalerSpec. minReplicas is the lower limit for the number of replicas to which the autoscaler can scale down. It defaults to 1 pod. :param min_replicas: The min_replicas of this V2alpha1HorizontalPodAutoscalerSpec. :type: int """ self._min_replicas = min_replicas @property def scale_target_ref(self): """ Gets the scale_target_ref of this V2alpha1HorizontalPodAutoscalerSpec. scaleTargetRef points to the target resource to scale, and is used to the pods for which metrics should be collected, as well as to actually change the replica count. :return: The scale_target_ref of this V2alpha1HorizontalPodAutoscalerSpec. :rtype: V2alpha1CrossVersionObjectReference """ return self._scale_target_ref @scale_target_ref.setter def scale_target_ref(self, scale_target_ref): """ Sets the scale_target_ref of this V2alpha1HorizontalPodAutoscalerSpec. scaleTargetRef points to the target resource to scale, and is used to the pods for which metrics should be collected, as well as to actually change the replica count. :param scale_target_ref: The scale_target_ref of this V2alpha1HorizontalPodAutoscalerSpec. :type: V2alpha1CrossVersionObjectReference """ if scale_target_ref is None: raise ValueError("Invalid value for `scale_target_ref`, must not be `None`") self._scale_target_ref = scale_target_ref def to_dict(self): """ Returns the model properties as a dict """ result = {} for attr, _ in iteritems(self.swagger_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 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, V2alpha1HorizontalPodAutoscalerSpec): return False return self.__dict__ == other.__dict__ def __ne__(self, other): """ Returns true if both objects are not equal """ return not self == other