fix(kubernetes): temporary solution for updated k8s python client

kubernetes/client/models/v1_weighted_pod_affinity_term.py

@@ -0,0 +1,150 @@
+# 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 V1WeightedPodAffinityTerm(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 = {
+        'pod_affinity_term': 'V1PodAffinityTerm',
+        'weight': 'int'
+    }
+
+    attribute_map = {
+        'pod_affinity_term': 'podAffinityTerm',
+        'weight': 'weight'
+    }
+
+    def __init__(self, pod_affinity_term=None, weight=None, local_vars_configuration=None):  # noqa: E501
+        """V1WeightedPodAffinityTerm - 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._pod_affinity_term = None
+        self._weight = None
+        self.discriminator = None
+
+        self.pod_affinity_term = pod_affinity_term
+        self.weight = weight
+
+    @property
+    def pod_affinity_term(self):
+        """Gets the pod_affinity_term of this V1WeightedPodAffinityTerm.  # noqa: E501
+
+
+        :return: The pod_affinity_term of this V1WeightedPodAffinityTerm.  # noqa: E501
+        :rtype: V1PodAffinityTerm
+        """
+        return self._pod_affinity_term
+
+    @pod_affinity_term.setter
+    def pod_affinity_term(self, pod_affinity_term):
+        """Sets the pod_affinity_term of this V1WeightedPodAffinityTerm.
+
+
+        :param pod_affinity_term: The pod_affinity_term of this V1WeightedPodAffinityTerm.  # noqa: E501
+        :type: V1PodAffinityTerm
+        """
+        if self.local_vars_configuration.client_side_validation and pod_affinity_term is None:  # noqa: E501
+            raise ValueError("Invalid value for `pod_affinity_term`, must not be `None`")  # noqa: E501
+
+        self._pod_affinity_term = pod_affinity_term
+
+    @property
+    def weight(self):
+        """Gets the weight of this V1WeightedPodAffinityTerm.  # noqa: E501
+
+        weight associated with matching the corresponding podAffinityTerm, in the range 1-100.  # noqa: E501
+
+        :return: The weight of this V1WeightedPodAffinityTerm.  # noqa: E501
+        :rtype: int
+        """
+        return self._weight
+
+    @weight.setter
+    def weight(self, weight):
+        """Sets the weight of this V1WeightedPodAffinityTerm.
+
+        weight associated with matching the corresponding podAffinityTerm, in the range 1-100.  # noqa: E501
+
+        :param weight: The weight of this V1WeightedPodAffinityTerm.  # noqa: E501
+        :type: int
+        """
+        if self.local_vars_configuration.client_side_validation and weight is None:  # noqa: E501
+            raise ValueError("Invalid value for `weight`, must not be `None`")  # noqa: E501
+
+        self._weight = weight
+
+    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, V1WeightedPodAffinityTerm):
+            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, V1WeightedPodAffinityTerm):
+            return True
+
+        return self.to_dict() != other.to_dict()