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# 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-1.16
Generated by: https://openapi-generator.tech
"""
import pprint
import re # noqa: F401
import six
from kubernetes.client.configuration import Configuration
class V2beta1HorizontalPodAutoscalerSpec(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',
'metrics': 'list[V2beta1MetricSpec]',
'min_replicas': 'int',
'scale_target_ref': 'V2beta1CrossVersionObjectReference'
}
attribute_map = {
'max_replicas': 'maxReplicas',
'metrics': 'metrics',
'min_replicas': 'minReplicas',
'scale_target_ref': 'scaleTargetRef'
}
def __init__(self, max_replicas=None, metrics=None, min_replicas=None, scale_target_ref=None, local_vars_configuration=None): # noqa: E501
"""V2beta1HorizontalPodAutoscalerSpec - 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._metrics = None
self._min_replicas = None
self._scale_target_ref = None
self.discriminator = None
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 max_replicas(self):
"""Gets the max_replicas of this V2beta1HorizontalPodAutoscalerSpec. # 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 V2beta1HorizontalPodAutoscalerSpec. # noqa: E501
:rtype: int
"""
return self._max_replicas
@max_replicas.setter
def max_replicas(self, max_replicas):
"""Sets the max_replicas of this V2beta1HorizontalPodAutoscalerSpec.
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 V2beta1HorizontalPodAutoscalerSpec. # 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 V2beta1HorizontalPodAutoscalerSpec. # 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. # noqa: E501
:return: The metrics of this V2beta1HorizontalPodAutoscalerSpec. # noqa: E501
:rtype: list[V2beta1MetricSpec]
"""
return self._metrics
@metrics.setter
def metrics(self, metrics):
"""Sets the metrics of this V2beta1HorizontalPodAutoscalerSpec.
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. # noqa: E501
:param metrics: The metrics of this V2beta1HorizontalPodAutoscalerSpec. # noqa: E501
:type: list[V2beta1MetricSpec]
"""
self._metrics = metrics
@property
def min_replicas(self):
"""Gets the min_replicas of this V2beta1HorizontalPodAutoscalerSpec. # 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 V2beta1HorizontalPodAutoscalerSpec. # noqa: E501
:rtype: int
"""
return self._min_replicas
@min_replicas.setter
def min_replicas(self, min_replicas):
"""Sets the min_replicas of this V2beta1HorizontalPodAutoscalerSpec.
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 V2beta1HorizontalPodAutoscalerSpec. # noqa: E501
:type: int
"""
self._min_replicas = min_replicas
@property
def scale_target_ref(self):
"""Gets the scale_target_ref of this V2beta1HorizontalPodAutoscalerSpec. # noqa: E501
:return: The scale_target_ref of this V2beta1HorizontalPodAutoscalerSpec. # noqa: E501
:rtype: V2beta1CrossVersionObjectReference
"""
return self._scale_target_ref
@scale_target_ref.setter
def scale_target_ref(self, scale_target_ref):
"""Sets the scale_target_ref of this V2beta1HorizontalPodAutoscalerSpec.
:param scale_target_ref: The scale_target_ref of this V2beta1HorizontalPodAutoscalerSpec. # noqa: E501
:type: V2beta1CrossVersionObjectReference
"""
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, V2beta1HorizontalPodAutoscalerSpec):
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, V2beta1HorizontalPodAutoscalerSpec):
return True
return self.to_dict() != other.to_dict()
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