Actually set default_granularity during transformation

dbt_semantic_interfaces/transformations/default_granularity.py

@@ -45,4 +45,6 @@ def transform_model(semantic_manifest: PydanticSemanticManifest) -> PydanticSema
                     ):
                         default_granularity = dimension.type_params.time_granularity
 
+            metric.default_granularity = default_granularity
+
         return semantic_manifest

tests/transformations/test_configurable_transform_rules.py

@@ -1,12 +1,18 @@
+from typing import Dict
+
 from dbt_semantic_interfaces.implementations.semantic_manifest import (
     PydanticSemanticManifest,
 )
+from dbt_semantic_interfaces.transformations.default_granularity import (
+    SetDefaultGranularityRule,
+)
 from dbt_semantic_interfaces.transformations.semantic_manifest_transformer import (
     PydanticSemanticManifestTransformer,
 )
 from dbt_semantic_interfaces.transformations.transform_rule import (
     SemanticManifestTransformRule,
 )
+from dbt_semantic_interfaces.type_enums import TimeGranularity
 
 
 class SliceNamesRule(SemanticManifestTransformRule):
@@ -32,3 +38,30 @@ def test_can_configure_model_transform_rules(  # noqa: D
     rules = [SliceNamesRule()]
     transformed_model = PydanticSemanticManifestTransformer.transform(pre_model, ordered_rule_sequences=(rules,))
     assert all(len(x.name) == 3 for x in transformed_model.semantic_models)
+
+
+def test_set_default_granularity_rule(  # noqa: D
+    simple_semantic_manifest__with_primary_transforms: PydanticSemanticManifest,
+) -> None:
+    pre_model = simple_semantic_manifest__with_primary_transforms
+
+    metric_exists_without_default_granularity = False
+    configured_default_granularities: Dict[str, TimeGranularity] = {}
+    for metric in pre_model.metrics:
+        if metric.default_granularity:
+            configured_default_granularities[metric.name] = metric.default_granularity
+            metric_exists_without_default_granularity = True
+
+    assert (
+        pre_model.metrics and metric_exists_without_default_granularity
+    ), "If there are no metrics without a configured default_granularity, this tests nothing."
+
+    rules = [SetDefaultGranularityRule()]
+    transformed_model = PydanticSemanticManifestTransformer.transform(pre_model, ordered_rule_sequences=(rules,))
+
+    for metric in transformed_model.metrics:
+        assert metric.default_granularity, f"No default_granularity set in transformation for metric '{metric.name}'"
+        if metric.name in configured_default_granularities:
+            assert (
+                metric.default_granularity == configured_default_granularities[metric.name]
+            ), f"Default granularity was unexpected changed during transformation for metric '{metric.name}"