DMTF CADF format

Adding support for the DMTF Cloud Audit (CADF) format which will be
used along with a generic notification filter to audit 'core'
component APIs.

initial code drop

blueprint support-standard-audit-formats

Change-Id: I3b27ceae8faa6427e4be1290c1406102e790e2e3

1 files changed, 73 insertions, 0 deletions

diff --git a/pycadf/metric.py b/pycadf/metric.py
new file mode 100644
index 0000000..34376eb
--- /dev/null
+++ b/pycadf/metric.py
@@ -0,0 +1,73 @@
+# -*- encoding: utf-8 -*-
+#
+# Copyright 2013 IBM Corp.
+#
+# Author: Matt Rutkowski <mrutkows@us.ibm.com>
+#
+# 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.
+
+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, str))
+    name = cadftype.ValidatorDescriptor(METRIC_KEYNAME_NAME,
+                                        lambda x: isinstance(x, str))
+
+    def __init__(self, metricId=identifier.generate_uuid(),
+                 unit=None, name=None):
+        # Metric.id
+        setattr(self, METRIC_KEYNAME_METRICID, metricId)
+
+        # 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):
+        # Existence test, id, and unit attributes must both exist
+        return (
+            hasattr(self, METRIC_KEYNAME_METRICID) and
+            hasattr(self, METRIC_KEYNAME_UNIT)
+        )