Validate metrics using metadata.csv

datadog_checks_base/datadog_checks/base/stubs/aggregator.py

@@ -7,10 +7,9 @@
 
 from six import iteritems
 
-from datadog_checks.base.stubs.common import HistogramBucketStub, MetricStub, ServiceCheckStub
-from datadog_checks.base.stubs.similar import build_similar_elements_msg
-
 from ..utils.common import ensure_unicode, to_native_string
+from .common import HistogramBucketStub, MetricStub, ServiceCheckStub
+from .similar import build_similar_elements_msg
 
 
 def normalize_tags(tags, sort=False):
@@ -42,6 +41,7 @@ class AggregatorStub(object):
             ('historate', 6),
         )
     )
+    METRIC_ENUM_MAP_REV = {v: k for k, v in iteritems(METRIC_ENUM_MAP)}
     GAUGE, RATE, COUNT, MONOTONIC_COUNT, COUNTER, HISTOGRAM, HISTORATE = list(METRIC_ENUM_MAP.values())
     AGGREGATE_TYPES = {COUNT, COUNTER}
     IGNORED_METRICS = {'datadog.agent.profile.memory.check_run_alloc'}
@@ -301,6 +301,45 @@ def assert_all_metrics_covered(self):
             msg += '\nMissing Metrics:{}{}'.format(prefix, prefix.join(sorted(self.not_asserted())))
         assert condition, msg
 
+    def assert_metrics_using_metadata(self, metadata_metrics, check_metric_type=True, exclude=None):
+        """
+        Assert metrics using metadata.csv
+
+        Checking type: Since we are asserting the in-app metric type (NOT submission type),
+        asserting the type make sense only for e2e (metrics collected from agent).
+        For integration tests, set kwarg `check_metric_type=False`.
+
+        Usage:
+
+            from datadog_checks.dev.utils import get_metadata_metrics
+            aggregator.assert_metrics_using_metadata(get_metadata_metrics())
+
+        """
+
+        exclude = exclude or []
+        errors = set()
+        for metric_name, metric_stubs in iteritems(self._metrics):
+            if metric_name in exclude:
+                continue
+            for metric_stub in metric_stubs:
+
+                if metric_stub.name not in metadata_metrics:
+                    errors.add("Expect `{}` to be in metadata.csv.".format(metric_stub.name))
+                    continue
+
+                if check_metric_type:
+                    expected_metric_type = metadata_metrics[metric_stub.name]['metric_type']
+                    actual_metric_type = AggregatorStub.METRIC_ENUM_MAP_REV[metric_stub.type]
+
+                    if expected_metric_type != actual_metric_type:
+                        errors.add(
+                            "Expect `{}` to have type `{}` but got `{}`.".format(
+                                metric_stub.name, expected_metric_type, actual_metric_type
+                            )
+                        )
+
+        assert not errors, "Metadata assertion errors using metadata.csv: " + "\n\t- ".join([""] + sorted(list(errors)))
+
     def assert_no_duplicate_all(self):
         """
         Assert no duplicate metrics and service checks have been submitted.

datadog_checks_dev/datadog_checks/dev/utils.py

@@ -5,6 +5,7 @@
 Utilities functions abstracting common operations, specially designed to be used
 by Integrations within tests.
 """
+import csv
 import inspect
 import os
 import platform
@@ -315,3 +316,14 @@ def get_ip():
         # doesn't even have to be reachable
         s.connect(('10.255.255.255', 1))
         return s.getsockname()[0]
+
+
+def get_metadata_metrics():
+    # Only called in tests of a check, so just go back one frame
+    root = find_check_root(depth=1)
+    metadata_path = os.path.join(root, 'metadata.csv')
+    metrics = {}
+    with open(metadata_path) as f:
+        for row in csv.DictReader(f):
+            metrics[row['metric_name']] = row
+    return metrics