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# Copyright 2013 IBM Corp.
#
# Licensed under the Apache License, Version 2.0 (the "License"); you may not
# use this file except in compliance with the License. You may obtain a copy of
# the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
# WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
# License for the specific language governing permissions and limitations under
# the License.
import six
from pycadf import cadftype
from pycadf import identifier
# Metric types can appear outside a cadf:Event record context, in these cases
# a typeURI may be used to identify the cadf:Metric data type.
TYPE_URI_METRIC = cadftype.CADF_VERSION_1_0_0 + 'metric'
METRIC_KEYNAME_METRICID = "metricId"
METRIC_KEYNAME_UNIT = "unit"
METRIC_KEYNAME_NAME = "name"
# METRIC_KEYNAME_ANNOTATIONS = "annotations"
METRIC_KEYNAMES = [METRIC_KEYNAME_METRICID,
METRIC_KEYNAME_UNIT,
METRIC_KEYNAME_NAME
# METRIC_KEYNAME_ANNOTATIONS
]
class Metric(cadftype.CADFAbstractType):
metricId = cadftype.ValidatorDescriptor(METRIC_KEYNAME_METRICID,
lambda x: identifier.is_valid(x))
unit = cadftype.ValidatorDescriptor(METRIC_KEYNAME_UNIT,
lambda x: isinstance(x,
six.string_types))
name = cadftype.ValidatorDescriptor(METRIC_KEYNAME_NAME,
lambda x: isinstance(x,
six.string_types))
def __init__(self, metricId=None, unit=None, name=None):
"""Create metric data type
:param metricId: id of metric. uuid generated if not provided
:param unit: unit of metric
:param name: name of metric
"""
# Metric.id
setattr(self, METRIC_KEYNAME_METRICID,
metricId or identifier.generate_uuid())
# Metric.unit
if unit is not None:
setattr(self, METRIC_KEYNAME_UNIT, unit)
# Metric.name
if name is not None:
setattr(self, METRIC_KEYNAME_NAME, name)
# TODO(mrutkows): add mechanism for annotations, OpenStack may choose
# not to support this "extension mechanism" and is not required (and not
# critical in many audit contexts)
def set_annotations(self, value):
raise NotImplementedError()
# setattr(self, METRIC_KEYNAME_ANNOTATIONS, value)
# self validate cadf:Metric type against schema
def is_valid(self):
"""Validation to ensure Metric required attributes are set.
"""
# Existence test, id, and unit attributes must both exist
return (
self._isset(METRIC_KEYNAME_METRICID) and
self._isset(METRIC_KEYNAME_UNIT)
)
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