206 lines
8.1 KiB
Python
206 lines
8.1 KiB
Python
# coding: utf-8
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"""
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Kubernetes
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No description provided (generated by Openapi Generator https://github.com/openapitools/openapi-generator) # noqa: E501
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The version of the OpenAPI document: release-1.32
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Generated by: https://openapi-generator.tech
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"""
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import pprint
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import re # noqa: F401
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import six
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from kubernetes.client.configuration import Configuration
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class V1HorizontalPodAutoscalerSpec(object):
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"""NOTE: This class is auto generated by OpenAPI Generator.
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Ref: https://openapi-generator.tech
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Do not edit the class manually.
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"""
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"""
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Attributes:
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openapi_types (dict): The key is attribute name
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and the value is attribute type.
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attribute_map (dict): The key is attribute name
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and the value is json key in definition.
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"""
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openapi_types = {
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'max_replicas': 'int',
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'min_replicas': 'int',
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'scale_target_ref': 'V1CrossVersionObjectReference',
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'target_cpu_utilization_percentage': 'int'
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}
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attribute_map = {
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'max_replicas': 'maxReplicas',
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'min_replicas': 'minReplicas',
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'scale_target_ref': 'scaleTargetRef',
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'target_cpu_utilization_percentage': 'targetCPUUtilizationPercentage'
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}
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def __init__(self, max_replicas=None, min_replicas=None, scale_target_ref=None, target_cpu_utilization_percentage=None, local_vars_configuration=None): # noqa: E501
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"""V1HorizontalPodAutoscalerSpec - a model defined in OpenAPI""" # noqa: E501
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if local_vars_configuration is None:
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local_vars_configuration = Configuration()
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self.local_vars_configuration = local_vars_configuration
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self._max_replicas = None
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self._min_replicas = None
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self._scale_target_ref = None
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self._target_cpu_utilization_percentage = None
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self.discriminator = None
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self.max_replicas = max_replicas
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if min_replicas is not None:
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self.min_replicas = min_replicas
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self.scale_target_ref = scale_target_ref
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if target_cpu_utilization_percentage is not None:
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self.target_cpu_utilization_percentage = target_cpu_utilization_percentage
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@property
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def max_replicas(self):
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"""Gets the max_replicas of this V1HorizontalPodAutoscalerSpec. # noqa: E501
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maxReplicas is the upper limit for the number of pods that can be set by the autoscaler; cannot be smaller than MinReplicas. # noqa: E501
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:return: The max_replicas of this V1HorizontalPodAutoscalerSpec. # noqa: E501
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:rtype: int
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"""
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return self._max_replicas
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@max_replicas.setter
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def max_replicas(self, max_replicas):
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"""Sets the max_replicas of this V1HorizontalPodAutoscalerSpec.
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maxReplicas is the upper limit for the number of pods that can be set by the autoscaler; cannot be smaller than MinReplicas. # noqa: E501
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:param max_replicas: The max_replicas of this V1HorizontalPodAutoscalerSpec. # noqa: E501
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:type: int
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"""
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if self.local_vars_configuration.client_side_validation and max_replicas is None: # noqa: E501
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raise ValueError("Invalid value for `max_replicas`, must not be `None`") # noqa: E501
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self._max_replicas = max_replicas
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@property
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def min_replicas(self):
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"""Gets the min_replicas of this V1HorizontalPodAutoscalerSpec. # noqa: E501
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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
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:return: The min_replicas of this V1HorizontalPodAutoscalerSpec. # noqa: E501
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:rtype: int
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"""
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return self._min_replicas
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@min_replicas.setter
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def min_replicas(self, min_replicas):
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"""Sets the min_replicas of this V1HorizontalPodAutoscalerSpec.
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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
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:param min_replicas: The min_replicas of this V1HorizontalPodAutoscalerSpec. # noqa: E501
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:type: int
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"""
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self._min_replicas = min_replicas
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@property
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def scale_target_ref(self):
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"""Gets the scale_target_ref of this V1HorizontalPodAutoscalerSpec. # noqa: E501
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:return: The scale_target_ref of this V1HorizontalPodAutoscalerSpec. # noqa: E501
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:rtype: V1CrossVersionObjectReference
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"""
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return self._scale_target_ref
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@scale_target_ref.setter
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def scale_target_ref(self, scale_target_ref):
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"""Sets the scale_target_ref of this V1HorizontalPodAutoscalerSpec.
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:param scale_target_ref: The scale_target_ref of this V1HorizontalPodAutoscalerSpec. # noqa: E501
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:type: V1CrossVersionObjectReference
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"""
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if self.local_vars_configuration.client_side_validation and scale_target_ref is None: # noqa: E501
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raise ValueError("Invalid value for `scale_target_ref`, must not be `None`") # noqa: E501
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self._scale_target_ref = scale_target_ref
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@property
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def target_cpu_utilization_percentage(self):
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"""Gets the target_cpu_utilization_percentage of this V1HorizontalPodAutoscalerSpec. # noqa: E501
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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
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:return: The target_cpu_utilization_percentage of this V1HorizontalPodAutoscalerSpec. # noqa: E501
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:rtype: int
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"""
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return self._target_cpu_utilization_percentage
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@target_cpu_utilization_percentage.setter
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def target_cpu_utilization_percentage(self, target_cpu_utilization_percentage):
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"""Sets the target_cpu_utilization_percentage of this V1HorizontalPodAutoscalerSpec.
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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
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:param target_cpu_utilization_percentage: The target_cpu_utilization_percentage of this V1HorizontalPodAutoscalerSpec. # noqa: E501
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:type: int
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"""
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self._target_cpu_utilization_percentage = target_cpu_utilization_percentage
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def to_dict(self):
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"""Returns the model properties as a dict"""
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result = {}
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for attr, _ in six.iteritems(self.openapi_types):
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value = getattr(self, attr)
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if isinstance(value, list):
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result[attr] = list(map(
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lambda x: x.to_dict() if hasattr(x, "to_dict") else x,
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value
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))
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elif hasattr(value, "to_dict"):
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result[attr] = value.to_dict()
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elif isinstance(value, dict):
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result[attr] = dict(map(
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lambda item: (item[0], item[1].to_dict())
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if hasattr(item[1], "to_dict") else item,
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value.items()
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))
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else:
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result[attr] = value
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return result
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def to_str(self):
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"""Returns the string representation of the model"""
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return pprint.pformat(self.to_dict())
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def __repr__(self):
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"""For `print` and `pprint`"""
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return self.to_str()
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def __eq__(self, other):
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"""Returns true if both objects are equal"""
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if not isinstance(other, V1HorizontalPodAutoscalerSpec):
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return False
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return self.to_dict() == other.to_dict()
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def __ne__(self, other):
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"""Returns true if both objects are not equal"""
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if not isinstance(other, V1HorizontalPodAutoscalerSpec):
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return True
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return self.to_dict() != other.to_dict()
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