# 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) )