Add measures to metrics (temporary) & fix metric deduplication

dbt_semantic_interfaces/transformations/add_input_metric_measures.py

@@ -31,9 +31,7 @@ def _get_measures_for_metric(
     ) -> Set[PydanticMetricInputMeasure]:
         """Returns a unique set of input measures for a given metric."""
         measures: Set = set()
-        matched_metric = next(
-            iter((metric for metric in semantic_manifest.metrics if metric.name == metric_name)), None
-        )
+        matched_metric = next((metric for metric in semantic_manifest.metrics if metric.name == metric_name), None)
         if matched_metric:
             if matched_metric.type is MetricType.SIMPLE or matched_metric.type is MetricType.CUMULATIVE:
                 if matched_metric.type_params.measure is not None:

dbt_semantic_interfaces/transformations/measure_to_metric_transformation_pieces/measure_features_to_metric_name.py

@@ -3,6 +3,7 @@
 from dbt_semantic_interfaces.implementations.elements.measure import PydanticMeasure
 from dbt_semantic_interfaces.implementations.metric import (
     PydanticMetric,
+    PydanticMetricInputMeasure,
     PydanticMetricTypeParams,
 )
 from dbt_semantic_interfaces.implementations.semantic_manifest import (
@@ -65,12 +66,29 @@ def _find_metric_clone_in_manifest(
         but let's not prematurely optimize.
         """
         search_metric = metric.copy(deep=True)
+        original_input_measures = search_metric.type_params.input_measures
+        original_measure = search_metric.type_params.measure
         for existing_metric in manifest.metrics:
             # this allows us to a straight equality comparison, which is safer in the future
             # than implementing a custom comparison function.
             search_metric.name = existing_metric.name
+            search_metric.description = existing_metric.description
+            search_metric.label = existing_metric.label
             search_metric.metadata = existing_metric.metadata
             search_metric.type_params.is_private = existing_metric.type_params.is_private
+            search_metric.config = existing_metric.config
+            # this is used for compatibility between new and old style metrics; we need to
+            # match if the search input measures are empty (new-style) or if they match
+            # the old-style input measures.
+            if len(existing_metric.type_params.input_measures) == 0:
+                search_metric.type_params.input_measures = []
+            else:
+                search_metric.type_params.input_measures = original_input_measures
+            if existing_metric.type_params.measure is None:
+                search_metric.type_params.measure = None
+            else:
+                search_metric.type_params.measure = original_measure
+
             if search_metric == existing_metric:
                 return existing_metric
             print("provided metric", search_metric)
@@ -177,6 +195,10 @@ def get_or_create_metric_for_measure(
             fill_nulls_with=fill_nulls_with,
             join_to_timespine=join_to_timespine,
         )
+        # supporting legacy cases.  Remove when we can remove input measures.
+        built_metric.type_params.measure = PydanticMetricInputMeasure(name=measure.name)
+        built_metric.type_params.input_measures = [PydanticMetricInputMeasure(name=measure.name)]
+
         metric = self._find_metric_clone_in_manifest(
             metric=built_metric,
             manifest=manifest,
@@ -193,6 +215,9 @@ def get_or_create_metric_for_measure(
             )
             metric = built_metric
             metric.name = metric_name
+            # TODO: remove this line when MF can support no-measure metrics
+            metric.type_params.measure = PydanticMetricInputMeasure(name=measure.name)
+            metric.type_params.input_measures.append(metric.type_params.measure)
             manifest.metrics.append(metric)
             existing_metric_names.add(metric_name)
 

dbt_semantic_interfaces/transformations/proxy_measure.py

@@ -62,6 +62,7 @@ def transform_model(semantic_manifest: PydanticSemanticManifest) -> PydanticSema
                     )
                     metric.name = measure.name
                     metric.type_params.measure = PydanticMetricInputMeasure(name=measure.name)
+                    # metric.type_params.input_measures.append(metric.type_params.measure)
                     semantic_manifest.metrics.append(metric)
 
         return semantic_manifest

tests/parsing/test_metric_parsing_with_custom_grain.py

@@ -48,6 +48,7 @@ def test_cumulative_metric_with_custom_grain_to_date() -> None:  # noqa: D
           type_params:
             measure:
               name: bookings
+              fill_nulls_with: 15
             cumulative_type_params:
               grain_to_date: martian_week
         """
@@ -121,9 +122,9 @@ def test_cumulative_metric_with_custom_window() -> None:  # noqa: D
     )
     assert not model.issues.has_blocking_issues
     semantic_manifest = model.semantic_manifest
-    # 2 explicit ones and one that is created for the measure input for the
-    # cumulative metric's params
-    assert len(semantic_manifest.metrics) == 3
+    # 2 explicit metrics.  The cumulative metric's input metric should be deduplicated
+    # so it will match.
+    assert len(semantic_manifest.metrics) == 2
 
     metric = next((m for m in semantic_manifest.metrics if m.name == "test_cumulative_metric_with_custom_window"), None)
     assert metric is not None, "Can't find metric"
@@ -185,9 +186,9 @@ def test_conversion_metric_with_custom_grain_window() -> None:  # noqa: D
     )
     assert not model.issues.has_blocking_issues
     semantic_manifest = model.semantic_manifest
-    # 2 explicit ones and one that is created for the measure input for the
-    # cumulative metric's params
-    assert len(semantic_manifest.metrics) == 3
+    # 2 explicitly created metrics.  The conversion measure -> metric transformation
+    # should not need to create a new metric since the existing one already matches.
+    assert len(semantic_manifest.metrics) == 2
 
     metric = next(
         (m for m in semantic_manifest.metrics if m.name == "test_conversion_metric_with_custom_grain_window"), None