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a N��f� � @ s8 d dl mZmZmZ d dlmZ eG dd� de��ZdS )� )�formatted_flat_dict� NONE_SENTINEL�#value_allowed_none_or_none_sentinel)� init_model_state_from_kwargsc @ sd e Zd ZdZdd� Zedd� �Zejdd� �Zedd� �Zejd d� �Zd d � Z d d � Z dd� Z dS )� ResponderExecutionAggregationzF Provides the dimensions and their corresponding count value. c K s( ddd�| _ ddd�| _d| _d| _dS )a Initializes a new ResponderExecutionAggregation object with values from keyword arguments. The following keyword arguments are supported (corresponding to the getters/setters of this class): :param dimensions_map: The value to assign to the dimensions_map property of this ResponderExecutionAggregation. :type dimensions_map: dict(str, str) :param count: The value to assign to the count property of this ResponderExecutionAggregation. :type count: int zdict(str, str)�int)�dimensions_map�count� dimensionsMapr N)� swagger_types� attribute_map�_dimensions_map�_count)�self�kwargs� r ��/sparta/input/_build_configuration/image_build+validate/lib/bmcenv/lib64/python3.9/site-packages/oci/cloud_guard/models/responder_execution_aggregation.py�__init__ s ��z&ResponderExecutionAggregation.__init__c C s | j S )a� **[Required]** Gets the dimensions_map of this ResponderExecutionAggregation. The key-value pairs of dimensions and their names. The key corresponds to the Analytic Dimension(s) chosen, and the value corresponds to the value of the dimension from the data. E.g. if the Analytic Dimension chosen is "RISK_LEVEL", then the value will be like "CRITICAL". If the Analytic Dimensions chosen are "RISK_LEVEL" and "RESOURCE_TYPE", then the map will have two key-value pairs of form {"RISK_LEVEL" : "CRITICAL, "RESOURCE_TYPE" : "LOAD_BALANCER"} :return: The dimensions_map of this ResponderExecutionAggregation. :rtype: dict(str, str) �r �r r r r r + s z,ResponderExecutionAggregation.dimensions_mapc C s || _ dS )a� Sets the dimensions_map of this ResponderExecutionAggregation. The key-value pairs of dimensions and their names. The key corresponds to the Analytic Dimension(s) chosen, and the value corresponds to the value of the dimension from the data. E.g. if the Analytic Dimension chosen is "RISK_LEVEL", then the value will be like "CRITICAL". If the Analytic Dimensions chosen are "RISK_LEVEL" and "RESOURCE_TYPE", then the map will have two key-value pairs of form {"RISK_LEVEL" : "CRITICAL, "RESOURCE_TYPE" : "LOAD_BALANCER"} :param dimensions_map: The dimensions_map of this ResponderExecutionAggregation. :type: dict(str, str) Nr )r r r r r r 7 s c C s | j S )z� **[Required]** Gets the count of this ResponderExecutionAggregation. The number of occurences with given dimension(s) :return: The count of this ResponderExecutionAggregation. :rtype: int �r r r r r r C s z#ResponderExecutionAggregation.countc C s || _ dS )z� Sets the count of this ResponderExecutionAggregation. The number of occurences with given dimension(s) :param count: The count of this ResponderExecutionAggregation. :type: int Nr )r r r r r r O s c C s t | �S �N)r r r r r �__repr__[ s z&ResponderExecutionAggregation.__repr__c C s |d u r dS | j |j kS )NF)�__dict__�r �otherr r r �__eq__^ s z$ResponderExecutionAggregation.__eq__c C s | |k S r r r r r r �__ne__d s z$ResponderExecutionAggregation.__ne__N) �__name__� __module__� __qualname__�__doc__r �propertyr �setterr r r r r r r r r s r N)�oci.utilr r r �oci.decoratorsr �objectr r r r r �<module> s
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