File: //lib/mysqlsh/lib/python3.8/site-packages/oci/cloud_guard/models/problem_trend_aggregation.py
# coding: utf-8
# Copyright (c) 2016, 2025, Oracle and/or its affiliates. All rights reserved.
# This software is dual-licensed to you under the Universal Permissive License (UPL) 1.0 as shown at https://oss.oracle.com/licenses/upl or Apache License 2.0 as shown at http://www.apache.org/licenses/LICENSE-2.0. You may choose either license.
# NOTE: This class is auto generated by OracleSDKGenerator. DO NOT EDIT. API Version: 20200131
from oci.util import formatted_flat_dict, NONE_SENTINEL, value_allowed_none_or_none_sentinel # noqa: F401
from oci.decorators import init_model_state_from_kwargs
@init_model_state_from_kwargs
class ProblemTrendAggregation(object):
"""
Provides aggregated information on trends for counts of problems by specified parameters.
"""
def __init__(self, **kwargs):
"""
Initializes a new ProblemTrendAggregation 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 ProblemTrendAggregation.
:type dimensions_map: dict(str, str)
:param start_timestamp:
The value to assign to the start_timestamp property of this ProblemTrendAggregation.
:type start_timestamp: float
:param duration_in_seconds:
The value to assign to the duration_in_seconds property of this ProblemTrendAggregation.
:type duration_in_seconds: int
:param count:
The value to assign to the count property of this ProblemTrendAggregation.
:type count: int
"""
self.swagger_types = {
'dimensions_map': 'dict(str, str)',
'start_timestamp': 'float',
'duration_in_seconds': 'int',
'count': 'int'
}
self.attribute_map = {
'dimensions_map': 'dimensionsMap',
'start_timestamp': 'startTimestamp',
'duration_in_seconds': 'durationInSeconds',
'count': 'count'
}
self._dimensions_map = None
self._start_timestamp = None
self._duration_in_seconds = None
self._count = None
@property
def dimensions_map(self):
"""
**[Required]** Gets the dimensions_map of this ProblemTrendAggregation.
The key-value pairs of dimensions and their names
:return: The dimensions_map of this ProblemTrendAggregation.
:rtype: dict(str, str)
"""
return self._dimensions_map
@dimensions_map.setter
def dimensions_map(self, dimensions_map):
"""
Sets the dimensions_map of this ProblemTrendAggregation.
The key-value pairs of dimensions and their names
:param dimensions_map: The dimensions_map of this ProblemTrendAggregation.
:type: dict(str, str)
"""
self._dimensions_map = dimensions_map
@property
def start_timestamp(self):
"""
**[Required]** Gets the start_timestamp of this ProblemTrendAggregation.
Start time in epoch seconds
:return: The start_timestamp of this ProblemTrendAggregation.
:rtype: float
"""
return self._start_timestamp
@start_timestamp.setter
def start_timestamp(self, start_timestamp):
"""
Sets the start_timestamp of this ProblemTrendAggregation.
Start time in epoch seconds
:param start_timestamp: The start_timestamp of this ProblemTrendAggregation.
:type: float
"""
self._start_timestamp = start_timestamp
@property
def duration_in_seconds(self):
"""
**[Required]** Gets the duration_in_seconds of this ProblemTrendAggregation.
Duration
:return: The duration_in_seconds of this ProblemTrendAggregation.
:rtype: int
"""
return self._duration_in_seconds
@duration_in_seconds.setter
def duration_in_seconds(self, duration_in_seconds):
"""
Sets the duration_in_seconds of this ProblemTrendAggregation.
Duration
:param duration_in_seconds: The duration_in_seconds of this ProblemTrendAggregation.
:type: int
"""
self._duration_in_seconds = duration_in_seconds
@property
def count(self):
"""
**[Required]** Gets the count of this ProblemTrendAggregation.
The number of occurrences for the corresponding time range and dimensions.
:return: The count of this ProblemTrendAggregation.
:rtype: int
"""
return self._count
@count.setter
def count(self, count):
"""
Sets the count of this ProblemTrendAggregation.
The number of occurrences for the corresponding time range and dimensions.
:param count: The count of this ProblemTrendAggregation.
:type: int
"""
self._count = count
def __repr__(self):
return formatted_flat_dict(self)
def __eq__(self, other):
if other is None:
return False
return self.__dict__ == other.__dict__
def __ne__(self, other):
return not self == other