Expose measures for metrics on MFEngine (#735)

.changes/unreleased/Features-20230823-131738.yaml

@@ -0,0 +1,6 @@
+kind: Features
+body: Expose measures for metrics on MFEngine with agg_time_dimension
+time: 2023-08-23T13:17:38.517068-07:00
+custom:
+  Author: courtneyholcomb
+  Issue: "735"

metricflow/engine/metricflow_engine.py

@@ -10,7 +10,7 @@
 import pandas as pd
 from dbt_semantic_interfaces.implementations.elements.dimension import PydanticDimensionTypeParams
 from dbt_semantic_interfaces.pretty_print import pformat_big_objects
-from dbt_semantic_interfaces.references import EntityReference, MetricReference
+from dbt_semantic_interfaces.references import EntityReference, MeasureReference, MetricReference
 from dbt_semantic_interfaces.type_enums import DimensionType
 
 from metricflow.assert_one_arg import assert_exactly_one_arg_set
@@ -27,7 +27,7 @@
 from metricflow.dataset.convert_semantic_model import SemanticModelToDataSetConverter
 from metricflow.dataset.dataset import DataSet
 from metricflow.dataset.semantic_model_adapter import SemanticModelDataSet
-from metricflow.engine.models import Dimension, Entity, Metric
+from metricflow.engine.models import Dimension, Entity, Measure, Metric
 from metricflow.engine.time_source import ServerTimeSource
 from metricflow.errors.errors import ExecutionException
 from metricflow.execution.execution_plan import ExecutionPlan, SqlQuery
@@ -494,6 +494,32 @@ def _create_execution_plan(self, mf_query_request: MetricFlowQueryRequest) -> Me
     def explain(self, mf_request: MetricFlowQueryRequest) -> MetricFlowExplainResult:  # noqa: D
         return self._create_execution_plan(mf_request)
 
+    def get_measures_for_metrics(self, metric_names: List[str]) -> List[Measure]:  # noqa: D
+        metrics = self._semantic_manifest_lookup.metric_lookup.get_metrics(
+            metric_references=[MetricReference(element_name=metric_name) for metric_name in metric_names]
+        )
+        semantic_model_lookup = self._semantic_manifest_lookup.semantic_model_lookup
+
+        measures = set()
+        for metric in metrics:
+            for input_measure in metric.input_measures:
+                measure_reference = MeasureReference(element_name=input_measure.name)
+                # populate new obj
+                measure = semantic_model_lookup.get_measure(measure_reference=measure_reference)
+                measures.add(
+                    Measure(
+                        name=measure.name,
+                        agg=measure.agg,
+                        agg_time_dimension=semantic_model_lookup.get_agg_time_dimension_for_measure(
+                            measure_reference=measure_reference
+                        ).element_name,
+                        description=measure.description,
+                        expr=measure.expr,
+                        agg_params=measure.agg_params,
+                    )
+                )
+        return list(measures)
+
     def simple_dimensions_for_metrics(  # noqa: D
         self,
         metric_names: List[str],

metricflow/engine/models.py

@@ -12,11 +12,13 @@
     DimensionTypeParams,
 )
 from dbt_semantic_interfaces.protocols.entity import Entity as SemanticManifestEntity
+from dbt_semantic_interfaces.protocols.measure import MeasureAggregationParameters
 from dbt_semantic_interfaces.protocols.metadata import Metadata
 from dbt_semantic_interfaces.protocols.metric import Metric as SemanticManifestMetric
 from dbt_semantic_interfaces.protocols.metric import MetricInputMeasure, MetricType, MetricTypeParams
 from dbt_semantic_interfaces.protocols.where_filter import WhereFilter
 from dbt_semantic_interfaces.transformations.add_input_metric_measures import AddInputMetricMeasuresRule
+from dbt_semantic_interfaces.type_enums.aggregation_type import AggregationType
 from dbt_semantic_interfaces.type_enums.entity_type import EntityType
 
 from metricflow.model.semantics.linkable_spec_resolver import ElementPathKey
@@ -133,3 +135,15 @@ def from_pydantic(cls, pydantic_entity: SemanticManifestEntity) -> Entity:
             role=pydantic_entity.role,
             expr=pydantic_entity.expr,
         )
+
+
+@dataclass(frozen=True)
+class Measure:
+    """Dataclass representation of a Measure."""
+
+    name: str
+    agg: AggregationType
+    agg_time_dimension: str
+    description: Optional[str] = None
+    expr: Optional[str] = None
+    agg_params: Optional[MeasureAggregationParameters] = None

metricflow/test/api/test_metricflow_client.py

@@ -93,6 +93,32 @@ def test_list_dimensions(mf_client: MetricFlowClient) -> None:  # noqa: D
     assert tuple(dim.name for dim in dimensions) == ("metric_time", "metric_time")
 
 
+def test_get_measures_for_metrics(mf_client: MetricFlowClient) -> None:  # noqa: D
+    measures = mf_client.engine.get_measures_for_metrics(["bookings"])
+    assert len(measures) == 1
+    measure = measures[0]
+    assert measure.name == "bookings"
+    assert measure.agg_time_dimension == "ds"
+
+    # Multiple metrics
+    measures = mf_client.engine.get_measures_for_metrics(["bookings", "revenue"])
+    assert len(measures) == 2
+    assert {measure.name for measure in measures} == {"bookings", "txn_revenue"}
+    assert {measure.agg_time_dimension for measure in measures} == {"ds"}
+
+    # Derived metric with multiple metric inputs
+    measures = mf_client.engine.get_measures_for_metrics(["views_times_booking_value"])
+    assert len(measures) == 2
+    assert {measure.name for measure in measures} == {"views", "booking_value"}
+    assert {measure.agg_time_dimension for measure in measures} == {"ds"}
+
+    # Ratio metric with multiple measure inputs
+    measures = mf_client.engine.get_measures_for_metrics(["bookings_per_booker"])
+    assert len(measures) == 2
+    assert {measure.name for measure in measures} == {"bookings", "bookers"}
+    assert {measure.agg_time_dimension for measure in measures} == {"ds"}
+
+
 def test_get_dimension_values(mf_client: MetricFlowClient) -> None:  # noqa: D
     dim_vals = mf_client.get_dimension_values(
         ["bookings"], "metric_time", start_time="2020-01-01", end_time="2024-01-01"