Upgrade black

.pre-commit-config.yaml

@@ -19,7 +19,7 @@ repos:
       args: [--fix, --exit-non-zero-on-fix]
 
   - repo: https://github.com/psf/black
-    rev: 23.3.0
+    rev: 24.3.0
     hooks:
     - id: black
       verbose: true

dbt-metricflow/dbt_metricflow/cli/main.py

@@ -645,7 +645,9 @@ def validate_configs(
     ).validate_semantic_manifest(semantic_manifest)
 
     if not model_issues.has_blocking_issues:
-        semantic_spinner.succeed(f"🎉 Successfully validated the semantics of built manifest ({model_issues.summary()})")
+        semantic_spinner.succeed(
+            f"🎉 Successfully validated the semantics of built manifest ({model_issues.summary()})"
+        )
     else:
         semantic_spinner.fail(
             f"Breaking issues found when checking semantics of built manifest ({model_issues.summary()})"

metricflow-semantics/metricflow_semantics/model/spec_converters.py

@@ -8,6 +8,7 @@
 classes, rather than the perhaps more natural approach of adding a to_spec() method on the model objects. These
 shims likely point to the need for a bit of an internal refactor, but that's a concern for another time.
 """
+
 from __future__ import annotations
 
 from dbt_semantic_interfaces.protocols.measure import Measure

metricflow-semantics/metricflow_semantics/query/resolver_inputs/query_resolver_inputs.py

@@ -3,6 +3,7 @@
 The naming of these classes is a little odd as they have the "For.." suffix. But using the "*ResolverInput" leads to
 some confusing names like "ResolverInputForQuery" -> "QueryResolverInput". Improved naming for these classes is TBD.
 """
+
 from __future__ import annotations
 
 from dataclasses import dataclass

metricflow/dataflow/builder/dataflow_plan_builder.py

@@ -1613,12 +1613,12 @@ def _build_aggregated_measure_from_measure_source_node(
             non_additive_dimension_grain = self._semantic_model_lookup.get_defined_time_granularity(
                 TimeDimensionReference(non_additive_dimension_spec.name)
             )
-            queried_time_dimension_spec: Optional[
-                TimeDimensionSpec
-            ] = self._find_non_additive_dimension_in_linkable_specs(
-                agg_time_dimension=agg_time_dimension,
-                linkable_specs=queried_linkable_specs.as_tuple,
-                non_additive_dimension_spec=non_additive_dimension_spec,
+            queried_time_dimension_spec: Optional[TimeDimensionSpec] = (
+                self._find_non_additive_dimension_in_linkable_specs(
+                    agg_time_dimension=agg_time_dimension,
+                    linkable_specs=queried_linkable_specs.as_tuple,
+                    non_additive_dimension_spec=non_additive_dimension_spec,
+                )
             )
             time_dimension_spec = TimeDimensionSpec(
                 # The NonAdditiveDimensionSpec name property is a plain element name

metricflow/plan_conversion/sql_expression_builders.py

@@ -1,4 +1,5 @@
 """Utility module for building sql expressions from inputs derived from dataflow plan or other nodes."""
+
 from __future__ import annotations
 
 from typing import List, Sequence

metricflow/validation/data_warehouse_model_validator.py

@@ -389,9 +389,9 @@ def gen_measure_tasks(
                 source_node_by_measure_spec.update({measure_spec: source_node for measure_spec in measure_specs})
                 measure_specs_source_node_pair.append((measure_specs, source_node))
 
-            source_node_to_sub_task: DefaultDict[
-                DataflowPlanNode, List[DataWarehouseValidationTask]
-            ] = collections.defaultdict(list)
+            source_node_to_sub_task: DefaultDict[DataflowPlanNode, List[DataWarehouseValidationTask]] = (
+                collections.defaultdict(list)
+            )
             for spec in semantic_model_specs:
                 obtained_source_node = source_node_by_measure_spec.get(spec)
                 assert obtained_source_node, f"Unable to find generated source node for measure: {spec.element_name}"