huaweicloud-sdk-python-v3/huaweicloud-sdk-ces/huaweicloudsdkces/v1/model/batch_metric_data.py

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2020-05-18 07:34:40 +00:00
# coding: utf-8
import pprint
import re
import six
class BatchMetricData(object):
"""
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.
"""
sensitive_list = []
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openapi_types = {
'unit': 'str',
'datapoints': 'list[Datapoint]',
'namespace': 'str',
'metric_name': 'str',
'dimensions': 'list[MetricsDimension]'
}
attribute_map = {
'unit': 'unit',
'datapoints': 'datapoints',
'namespace': 'namespace',
'metric_name': 'metric_name',
'dimensions': 'dimensions'
}
def __init__(self, unit=None, datapoints=None, namespace=None, metric_name=None, dimensions=None): # noqa: E501
"""BatchMetricData - a model defined in huaweicloud sdk"""
self._unit = None
self._datapoints = None
self._namespace = None
self._metric_name = None
self._dimensions = None
self.discriminator = None
if unit is not None:
self.unit = unit
self.datapoints = datapoints
if namespace is not None:
self.namespace = namespace
self.metric_name = metric_name
if dimensions is not None:
self.dimensions = dimensions
@property
def unit(self):
"""Gets the unit of this BatchMetricData.
指标单位
:return: The unit of this BatchMetricData.
:rtype: str
"""
return self._unit
@unit.setter
def unit(self, unit):
"""Sets the unit of this BatchMetricData.
指标单位
:param unit: The unit of this BatchMetricData.
:type: str
"""
self._unit = unit
@property
def datapoints(self):
"""Gets the datapoints of this BatchMetricData.
指标数据列表由于查询数据时云监控会根据所选择的聚合粒度向前取整from参数所以datapoints中包含的数据点有可能会多于预期
:return: The datapoints of this BatchMetricData.
:rtype: list[Datapoint]
"""
return self._datapoints
@datapoints.setter
def datapoints(self, datapoints):
"""Sets the datapoints of this BatchMetricData.
指标数据列表由于查询数据时云监控会根据所选择的聚合粒度向前取整from参数所以datapoints中包含的数据点有可能会多于预期
:param datapoints: The datapoints of this BatchMetricData.
:type: list[Datapoint]
"""
self._datapoints = datapoints
@property
def namespace(self):
"""Gets the namespace of this BatchMetricData.
指标命名空间格式为service.itemservice和item必须是字符串必须以字母开头只能包含0-9/a-z/A-Z/_总长度最短为3最大为32
:return: The namespace of this BatchMetricData.
:rtype: str
"""
return self._namespace
@namespace.setter
def namespace(self, namespace):
"""Sets the namespace of this BatchMetricData.
指标命名空间格式为service.itemservice和item必须是字符串必须以字母开头只能包含0-9/a-z/A-Z/_总长度最短为3最大为32
:param namespace: The namespace of this BatchMetricData.
:type: str
"""
self._namespace = namespace
@property
def metric_name(self):
"""Gets the metric_name of this BatchMetricData.
指标名称例如弹性云服务器监控指标中的cpu_util
:return: The metric_name of this BatchMetricData.
:rtype: str
"""
return self._metric_name
@metric_name.setter
def metric_name(self, metric_name):
"""Sets the metric_name of this BatchMetricData.
指标名称例如弹性云服务器监控指标中的cpu_util
:param metric_name: The metric_name of this BatchMetricData.
:type: str
"""
self._metric_name = metric_name
@property
def dimensions(self):
"""Gets the dimensions of this BatchMetricData.
指标维度列表
:return: The dimensions of this BatchMetricData.
:rtype: list[MetricsDimension]
"""
return self._dimensions
@dimensions.setter
def dimensions(self, dimensions):
"""Sets the dimensions of this BatchMetricData.
指标维度列表
:param dimensions: The dimensions of this BatchMetricData.
:type: list[MetricsDimension]
"""
self._dimensions = dimensions
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:
if attr in self.sensitive_list:
result[attr] = "****"
else:
result[attr] = value
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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, BatchMetricData):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other):
"""Returns true if both objects are not equal"""
return not self == other