fix(metrics): warnings when there are default_dimensions

aws_lambda_powertools/metrics/metrics.py

@@ -91,21 +91,14 @@ def __init__(
         provider: AmazonCloudWatchEMFProvider | None = None,
         function_name: str | None = None,
     ):
-        self.metric_set = self._metrics
-        self.metadata_set = self._metadata
-        self.default_dimensions = self._default_dimensions
-        self.dimension_set = self._dimensions
-
-        self.dimension_set.update(**self._default_dimensions)
-
         if provider is None:
             self.provider = AmazonCloudWatchEMFProvider(
                 namespace=namespace,
                 service=service,
-                metric_set=self.metric_set,
-                dimension_set=self.dimension_set,
-                metadata_set=self.metadata_set,
-                default_dimensions=self._default_dimensions,
+                metric_set=Metrics._metrics,
+                dimension_set=Metrics._dimensions,
+                metadata_set=Metrics._metadata,
+                default_dimensions=Metrics._default_dimensions,
                 function_name=function_name,
             )
         else:
@@ -174,7 +167,6 @@ def log_metrics(
         )
 
     def set_default_dimensions(self, **dimensions) -> None:
-        self.provider.set_default_dimensions(**dimensions)
         """Persist dimensions across Lambda invocations
 
         Parameters
@@ -195,14 +187,10 @@ def set_default_dimensions(self, **dimensions) -> None:
             def lambda_handler():
                 return True
         """
-        for name, value in dimensions.items():
-            self.add_dimension(name, value)
-
-        self.default_dimensions.update(**dimensions)
+        self.provider.set_default_dimensions(**dimensions)
 
     def clear_default_dimensions(self) -> None:
         self.provider.default_dimensions.clear()
-        self.default_dimensions.clear()
 
     def clear_metrics(self) -> None:
         self.provider.clear_metrics()
@@ -227,6 +215,22 @@ def service(self):
     def service(self, service):
         self.provider.service = service
 
+    @property
+    def metric_set(self):
+        return self.provider.metric_set
+
+    @property
+    def dimension_set(self):
+        return self.provider.dimension_set
+
+    @property
+    def metadata_set(self):
+        return self.provider.metadata_set
+
+    @property
+    def default_dimensions(self):
+        return self.provider.default_dimensions
+
 
 # Maintenance: until v3, we can't afford to break customers.
 # AmazonCloudWatchEMFProvider has the exact same functionality (non-singleton)

aws_lambda_powertools/metrics/provider/cloudwatch_emf/cloudwatch.py

@@ -87,7 +87,7 @@ def __init__(
     ):
         self.metric_set = metric_set if metric_set is not None else {}
         self.dimension_set = dimension_set if dimension_set is not None else {}
-        self.default_dimensions = default_dimensions or {}
+        self.default_dimensions = default_dimensions if default_dimensions is not None else {}
         self.namespace = resolve_env_var_choice(choice=namespace, env=os.getenv(constants.METRICS_NAMESPACE_ENV))
         self.service = resolve_env_var_choice(choice=service, env=os.getenv(constants.SERVICE_NAME_ENV))
         self.function_name = function_name
@@ -453,7 +453,8 @@ def clear_metrics(self) -> None:
         self.dimension_set.clear()
         self.dimension_sets.clear()
         self.metadata_set.clear()
-        self.set_default_dimensions(**self.default_dimensions)
+        # Initialize dimension_set as in __init__
+        self.dimension_set.update(**self.default_dimensions)
 
     def flush_metrics(self, raise_on_empty_metrics: bool = False) -> None:
         """Manually flushes the metrics. This is normally not necessary,

tests/functional/metrics/required_dependencies/test_metrics_cloudwatch_emf.py

@@ -1221,6 +1221,28 @@ def lambda_handler(evt, ctx):
     assert "environment" in second_invocation
 
 
+def test_flush_metrics_with_default_dimensions(capsys, metrics, dimensions, namespace):
+    # GIVEN a Metrics is initialized
+    my_metrics = Metrics(namespace=namespace)
+    my_metrics.set_default_dimensions(environment="test", log_group="/lambda/test")
+
+    # WHEN we add_metric and flush_metrics
+    # THEN we should have no warnings
+    with warnings.catch_warnings(record=True) as w:
+        for metric in metrics:
+            my_metrics.add_metric(**metric)
+        assert not w
+
+    with warnings.catch_warnings(record=True) as w:
+        my_metrics.flush_metrics()
+        assert not w
+
+    # THEN we should have default dimensions in output
+    output = capture_metrics_output(capsys)
+    assert "environment" in output
+    assert "log_group" in output
+
+
 def test_metrics_reuse_dimension_set(metric, dimension, namespace):
     # GIVEN Metrics is initialized with a metric and dimension
     my_metrics = Metrics(namespace=namespace)