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Edit: summarized_metric_data.py
# coding: utf-8 # Copyright (c) 2016, 2024, 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: 20230515 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 SummarizedMetricData(object): """ The recorded metric value at a specific timestamp. """ def __init__(self, **kwargs): """ Initializes a new SummarizedMetricData object with values from keyword arguments. The following keyword arguments are supported (corresponding to the getters/setters of this class): :param sample_time: The value to assign to the sample_time property of this SummarizedMetricData. :type sample_time: datetime :param resolution: The value to assign to the resolution property of this SummarizedMetricData. :type resolution: str :param dimensions: The value to assign to the dimensions property of this SummarizedMetricData. :type dimensions: dict(str, DimensionValue) :param aggregation_method: The value to assign to the aggregation_method property of this SummarizedMetricData. :type aggregation_method: str :param aggregated_value: The value to assign to the aggregated_value property of this SummarizedMetricData. :type aggregated_value: float """ self.swagger_types = { 'sample_time': 'datetime', 'resolution': 'str', 'dimensions': 'dict(str, DimensionValue)', 'aggregation_method': 'str', 'aggregated_value': 'float' } self.attribute_map = { 'sample_time': 'sampleTime', 'resolution': 'resolution', 'dimensions': 'dimensions', 'aggregation_method': 'aggregationMethod', 'aggregated_value': 'aggregatedValue' } self._sample_time = None self._resolution = None self._dimensions = None self._aggregation_method = None self._aggregated_value = None @property def sample_time(self): """ Gets the sample_time of this SummarizedMetricData. The time at which the metric data was recorded. :return: The sample_time of this SummarizedMetricData. :rtype: datetime """ return self._sample_time @sample_time.setter def sample_time(self, sample_time): """ Sets the sample_time of this SummarizedMetricData. The time at which the metric data was recorded. :param sample_time: The sample_time of this SummarizedMetricData. :type: datetime """ self._sample_time = sample_time @property def resolution(self): """ Gets the resolution of this SummarizedMetricData. The duration over which the metric data is aggregated. Supported values: `1m`-`60m`, `1h`-`24h`, `1d`. :return: The resolution of this SummarizedMetricData. :rtype: str """ return self._resolution @resolution.setter def resolution(self, resolution): """ Sets the resolution of this SummarizedMetricData. The duration over which the metric data is aggregated. Supported values: `1m`-`60m`, `1h`-`24h`, `1d`. :param resolution: The resolution of this SummarizedMetricData. :type: str """ self._resolution = resolution @property def dimensions(self): """ Gets the dimensions of this SummarizedMetricData. Qualifiers provided in the definition of the returned metric. Available dimensions vary by metric namespace. :return: The dimensions of this SummarizedMetricData. :rtype: dict(str, DimensionValue) """ return self._dimensions @dimensions.setter def dimensions(self, dimensions): """ Sets the dimensions of this SummarizedMetricData. Qualifiers provided in the definition of the returned metric. Available dimensions vary by metric namespace. :param dimensions: The dimensions of this SummarizedMetricData. :type: dict(str, DimensionValue) """ self._dimensions = dimensions @property def aggregation_method(self): """ Gets the aggregation_method of this SummarizedMetricData. The aggregation method used for aggregating the metric values. The aggregation method depends on the metric itself. :return: The aggregation_method of this SummarizedMetricData. :rtype: str """ return self._aggregation_method @aggregation_method.setter def aggregation_method(self, aggregation_method): """ Sets the aggregation_method of this SummarizedMetricData. The aggregation method used for aggregating the metric values. The aggregation method depends on the metric itself. :param aggregation_method: The aggregation_method of this SummarizedMetricData. :type: str """ self._aggregation_method = aggregation_method @property def aggregated_value(self): """ Gets the aggregated_value of this SummarizedMetricData. The aggregated metric value for the specified request. :return: The aggregated_value of this SummarizedMetricData. :rtype: float """ return self._aggregated_value @aggregated_value.setter def aggregated_value(self, aggregated_value): """ Sets the aggregated_value of this SummarizedMetricData. The aggregated metric value for the specified request. :param aggregated_value: The aggregated_value of this SummarizedMetricData. :type: float """ self._aggregated_value = aggregated_value 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