Add test for synthetic manifest generator.

tests_metricflow/performance/test_manifest_generator.py

@@ -0,0 +1,53 @@
+from __future__ import annotations
+
+import logging
+
+from _pytest.fixtures import FixtureRequest
+from dbt_semantic_interfaces.implementations.semantic_manifest import PydanticSemanticManifest
+from dbt_semantic_interfaces.transformations.semantic_manifest_transformer import PydanticSemanticManifestTransformer
+from dbt_semantic_interfaces.validations.semantic_manifest_validator import SemanticManifestValidator
+from metricflow_semantics.mf_logging.lazy_formattable import LazyFormat
+from metricflow_semantics.test_helpers.config_helpers import MetricFlowTestConfiguration
+from metricflow_semantics.test_helpers.snapshot_helpers import assert_object_snapshot_equal
+
+from tests_metricflow.performance.semantic_manifest_generator import SyntheticManifestGenerator
+from tests_metricflow.performance.synthetic_manifest_parameter_set import SyntheticManifestParameterSet
+
+logger = logging.getLogger(__name__)
+
+
+def test_manifest_generator(  # noqa: D103
+    request: FixtureRequest,
+    mf_test_configuration: MetricFlowTestConfiguration,
+) -> None:
+    parameter_set = SyntheticManifestParameterSet(
+        measure_semantic_model_count=2,
+        measures_per_semantic_model=2,
+        dimension_semantic_model_count=2,
+        categorical_dimensions_per_semantic_model=2,
+        max_metric_depth=2,
+        max_metric_width=2,
+        saved_query_count=2,
+        metrics_per_saved_query=2,
+        categorical_dimensions_per_saved_query=2,
+    )
+    generator = SyntheticManifestGenerator(parameter_set)
+    manifest = generator.generate_manifest()
+    assert_object_snapshot_equal(
+        request=request,
+        mf_test_configuration=mf_test_configuration,
+        obj=manifest,
+    )
+
+    manifest = PydanticSemanticManifestTransformer.transform(manifest)
+    validator = SemanticManifestValidator[PydanticSemanticManifest]()
+    validation_result = validator.validate_semantic_manifest(manifest)
+    logger.debug(LazyFormat("Generated manifest", manifest=manifest))
+
+    assert not validation_result.has_blocking_issues, str(
+        LazyFormat(
+            "Found validation issues with the generated manifest",
+            validation_result=validation_result,
+            manifest=manifest,
+        )
+    )

tests_metricflow/snapshots/test_manifest_generator.py/PydanticSemanticManifest/test_manifest_generator__result.txt

@@ -0,0 +1,155 @@
+PydanticSemanticManifest(
+  semantic_models=[
+    PydanticSemanticModel(
+      name='measure_model_000',
+      node_relation=PydanticNodeRelation(
+        alias='measure_model_000',
+        schema_name='demo',
+        relation_name='demo.measure_model_000',
+      ),
+      entities=[
+        PydanticEntity(name='measure_model_000_primary_entity', type=PRIMARY),
+        PydanticEntity(name='common_entity', type=UNIQUE),
+      ],
+      measures=[
+        PydanticMeasure(name='measure_000', agg=SUM, agg_time_dimension='ds'),
+        PydanticMeasure(name='measure_001', agg=SUM, agg_time_dimension='ds'),
+      ],
+      dimensions=[
+        PydanticDimension(
+          name='ds',
+          type=TIME,
+          is_partition=False,
+          type_params=PydanticDimensionTypeParams(time_granularity=DAY),
+        ),
+      ],
+    ),
+    PydanticSemanticModel(
+      name='measure_model_001',
+      node_relation=PydanticNodeRelation(
+        alias='measure_model_001',
+        schema_name='demo',
+        relation_name='demo.measure_model_001',
+      ),
+      entities=[
+        PydanticEntity(name='measure_model_001_primary_entity', type=PRIMARY),
+        PydanticEntity(name='common_entity', type=UNIQUE),
+      ],
+      measures=[
+        PydanticMeasure(name='measure_002', agg=SUM, agg_time_dimension='ds'),
+        PydanticMeasure(name='measure_003', agg=SUM, agg_time_dimension='ds'),
+      ],
+      dimensions=[
+        PydanticDimension(
+          name='ds',
+          type=TIME,
+          is_partition=False,
+          type_params=PydanticDimensionTypeParams(time_granularity=DAY),
+        ),
+      ],
+    ),
+    PydanticSemanticModel(
+      name='dimension_model_000',
+      node_relation=PydanticNodeRelation(
+        alias='dimension_model_000',
+        schema_name='demo',
+        relation_name='demo.dimension_model_000',
+      ),
+      entities=[
+        PydanticEntity(name='dimension_model_000_primary_entity', type=PRIMARY),
+        PydanticEntity(name='common_entity', type=UNIQUE),
+      ],
+      dimensions=[
+        PydanticDimension(name='dimension_000', type=CATEGORICAL, is_partition=False),
+        PydanticDimension(name='dimension_001', type=CATEGORICAL, is_partition=False),
+      ],
+    ),
+    PydanticSemanticModel(
+      name='dimension_model_001',
+      node_relation=PydanticNodeRelation(
+        alias='dimension_model_001',
+        schema_name='demo',
+        relation_name='demo.dimension_model_001',
+      ),
+      entities=[
+        PydanticEntity(name='dimension_model_001_primary_entity', type=PRIMARY),
+        PydanticEntity(name='common_entity', type=UNIQUE),
+      ],
+      dimensions=[
+        PydanticDimension(name='dimension_002', type=CATEGORICAL, is_partition=False),
+        PydanticDimension(name='dimension_003', type=CATEGORICAL, is_partition=False),
+      ],
+    ),
+  ],
+  metrics=[
+    PydanticMetric(
+      name='metric_0_000',
+      type=SIMPLE,
+      type_params=PydanticMetricTypeParams(
+        measure=PydanticMetricInputMeasure(name='measure_000', join_to_timespine=False),
+      ),
+    ),
+    PydanticMetric(
+      name='metric_0_001',
+      type=SIMPLE,
+      type_params=PydanticMetricTypeParams(
+        measure=PydanticMetricInputMeasure(name='measure_001', join_to_timespine=False),
+      ),
+    ),
+    PydanticMetric(
+      name='metric_1_000',
+      type=DERIVED,
+      type_params=PydanticMetricTypeParams(
+        expr='metric_0_000 + metric_0_001',
+        metrics=[PydanticMetricInput(name='metric_0_000'), PydanticMetricInput(name='metric_0_001')],
+      ),
+    ),
+    PydanticMetric(
+      name='metric_1_001',
+      type=DERIVED,
+      type_params=PydanticMetricTypeParams(
+        expr='metric_0_000 + metric_0_001',
+        metrics=[PydanticMetricInput(name='metric_0_000'), PydanticMetricInput(name='metric_0_001')],
+      ),
+    ),
+  ],
+  project_configuration=PydanticProjectConfiguration(
+    dsi_package_version=PydanticSemanticVersion(
+      major_version='0',
+      minor_version='7',
+      patch_version='2',
+    ),
+    time_spines=[
+      PydanticTimeSpine(
+        node_relation=PydanticNodeRelation(
+          alias='time_spine_source_table',
+          schema_name='demo',
+          relation_name='demo.time_spine_source_table',
+        ),
+        primary_column=PydanticTimeSpinePrimaryColumn(name='ds', time_granularity=DAY),
+      ),
+    ],
+  ),
+  saved_queries=[
+    PydanticSavedQuery(
+      name='saved_query_000',
+      query_params=PydanticSavedQueryQueryParams(
+        metrics=['metric_1_000', 'metric_1_001'],
+        group_by=[
+          "Dimension('common_entity__dimension_000')",
+          "Dimension('common_entity__dimension_001')",
+        ],
+      ),
+    ),
+    PydanticSavedQuery(
+      name='saved_query_001',
+      query_params=PydanticSavedQueryQueryParams(
+        metrics=['metric_1_000', 'metric_1_001'],
+        group_by=[
+          "Dimension('common_entity__dimension_002')",
+          "Dimension('common_entity__dimension_003')",
+        ],
+      ),
+    ),
+  ],
+)