added implementation for ConversionMetric properties

dbt_semantic_interfaces/implementations/metric.py

@@ -17,7 +17,11 @@
 )
 from dbt_semantic_interfaces.implementations.metadata import PydanticMetadata
 from dbt_semantic_interfaces.references import MeasureReference, MetricReference
-from dbt_semantic_interfaces.type_enums import MetricType, TimeGranularity
+from dbt_semantic_interfaces.type_enums import (
+    ConversionCalculationType,
+    MetricType,
+    TimeGranularity,
+)
 
 
 class PydanticMetricInputMeasure(PydanticCustomInputParser, HashableBaseModel):
@@ -134,6 +138,26 @@ def post_aggregation_reference(self) -> MetricReference:
         return MetricReference(element_name=self.alias or self.name)
 
 
+class PydanticConversionTypeParams(HashableBaseModel):
+    """Type params to provide context for conversion metrics properties."""
+
+    base_measure: PydanticMetricInputMeasure
+    conversion_measure: PydanticMetricInputMeasure
+    entity: str
+    calculation: ConversionCalculationType = ConversionCalculationType.CONVERSION_RATE
+    window: Optional[PydanticMetricTimeWindow]
+
+    @property
+    def base_measure_reference(self) -> MeasureReference:
+        """Return the measure reference associated with the base measure."""
+        return self.base_measure.measure_reference
+
+    @property
+    def conversion_measure_reference(self) -> MeasureReference:
+        """Return the measure reference associated with the conversion measure."""
+        return self.conversion_measure.measure_reference
+
+
 class PydanticMetricTypeParams(HashableBaseModel):
     """Type params add additional context to certain metric types (the context depends on the metric type)."""
 
@@ -144,6 +168,7 @@ class PydanticMetricTypeParams(HashableBaseModel):
     window: Optional[PydanticMetricTimeWindow]
     grain_to_date: Optional[TimeGranularity]
     metrics: Optional[List[PydanticMetricInput]]
+    conversion_type_params: Optional[PydanticConversionTypeParams]
 
     input_measures: List[PydanticMetricInputMeasure] = Field(default_factory=list)
 
@@ -172,7 +197,7 @@ def measure_references(self) -> List[MeasureReference]:
     @property
     def input_metrics(self) -> Sequence[PydanticMetricInput]:
         """Return the associated input metrics for this metric."""
-        if self.type is MetricType.SIMPLE or self.type is MetricType.CUMULATIVE:
+        if self.type is MetricType.SIMPLE or self.type is MetricType.CUMULATIVE or self.type is MetricType.CONVERSION:
             return ()
         elif self.type is MetricType.DERIVED:
             assert self.type_params.metrics is not None, f"{MetricType.DERIVED} should have type_params.metrics set"
@@ -184,3 +209,11 @@ def input_metrics(self) -> Sequence[PydanticMetricInput]:
             return (self.type_params.numerator, self.type_params.denominator)
         else:
             assert_values_exhausted(self.type)
+
+    @property
+    def conversion_params(self) -> PydanticConversionTypeParams:
+        """Accessor for conversion type params, enforces that it's set."""
+        assert self.type == MetricType.CONVERSION, "Should only access this for a conversion metric."
+        if self.type_params.conversion_type_params is None:
+            raise ValueError("conversion_type_params is not defined.")
+        return self.type_params.conversion_type_params