fix(metrics): warnings when there are default_dimensions

This fixes and reorganizes the code in a few ways:
* Make it clearer that _metrics, _dimensions, _metadata and
  _default_dimensions are class attributes. They don't need to be also
  set as instance attributes when constructing Metrics, as they're only
  meant to be used to construct the provider with shared data.
* Expose metric_set, dimension_set, metadata_set and default_dimensions
  as attributes just to keep backwards compatibility. Don't expose setters
  for these as previously setting them would have no side effect. Now
  users will get an error, which is a small breaking change but arguably
  for something they should never be doing anyway.
* Fix setting the default_dimensions in AmazonCloudWatchEMFProvider, as
  `default_dimensions or {}` was setting a new dict instance when the
  given default_dimensions was empty and we want to share the given dict.

Author: ericbn

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)