[MAINTENANCE] Column Descriptive Metrics: Remove compute_metrics_with_aborted_metrics

great_expectations/expectations/core/expect_column_kl_divergence_to_be_less_than.py

@@ -1,5 +1,5 @@
 import logging
-from typing import TYPE_CHECKING, Dict, Optional, Tuple
+from typing import TYPE_CHECKING, Dict, Optional
 
 import altair as alt
 import numpy as np
@@ -44,9 +44,11 @@
     parse_row_condition_string_pandas_engine,
     substitute_none_for_missing,
 )
-from great_expectations.validator.computed_metric import MetricValue  # noqa: TCH001
 from great_expectations.validator.metric_configuration import MetricConfiguration
-from great_expectations.validator.metrics_calculator import MetricsCalculator
+from great_expectations.validator.metrics_calculator import (
+    MetricsCalculator,
+    _MetricsDict,
+)
 from great_expectations.validator.validator import (
     ValidationDependencies,
 )
@@ -248,9 +250,8 @@ def get_validation_dependencies(
                     execution_engine=execution_engine,
                     show_progress_bars=True,
                 )
-                resolved_metrics: Dict[
-                    Tuple[str, str, str], MetricValue
-                ] = metrics_calculator.compute_metrics(
+                resolved_metrics: _MetricsDict
+                resolved_metrics, _ = metrics_calculator.compute_metrics(
                     metric_configurations=[partition_metric_configuration],
                     runtime_configuration=None,
                     min_graph_edges_pbar_enable=0,

great_expectations/experimental/metric_repository/column_descriptive_metrics_metric_retriever.py

@@ -317,7 +317,7 @@ def _compute_metrics(
         (
             computed_metrics,
             aborted_metrics,
-        ) = validator.compute_metrics_with_aborted_metrics(
+        ) = validator.compute_metrics(
             metric_configurations=metric_configs,
             runtime_configuration={"catch_exceptions": True},
         )

great_expectations/rule_based_profiler/helpers/util.py

@@ -72,6 +72,9 @@
     from great_expectations.data_context.data_context.abstract_data_context import (
         AbstractDataContext,
     )
+    from great_expectations.validator.metrics_calculator import (
+        _MetricsDict,
+    )
     from great_expectations.validator.validator import Validator
 
 logger = logging.getLogger(__name__)
@@ -360,9 +363,8 @@ def get_resolved_metrics_by_key(
 
     # Step 1: Gather "MetricConfiguration" objects corresponding to all possible key values/combinations.
     # and compute all metric values (resolve "MetricConfiguration" objects ) using a single method call.
-    resolved_metrics: Dict[
-        Tuple[str, str, str], MetricValue
-    ] = validator.compute_metrics(
+    resolved_metrics: _MetricsDict
+    resolved_metrics, _ = validator.compute_metrics(
         metric_configurations=[
             metric_configuration
             for key, metric_configurations_for_key in metric_configurations_by_key.items()

great_expectations/validator/metrics_calculator.py

@@ -138,7 +138,8 @@ def get_metrics(
         Returns:
             Return Dictionary with requested metrics resolved, with metric_name as key and computed metric as value.
         """
-        resolved_metrics: _MetricsDict = self.compute_metrics(
+        resolved_metrics: _MetricsDict
+        resolved_metrics, _ = self.compute_metrics(
             metric_configurations=list(metrics.values()),
             runtime_configuration=None,
             min_graph_edges_pbar_enable=0,
@@ -148,7 +149,7 @@ def get_metrics(
             for metric_configuration in metrics.values()
         }
 
-    def compute_metrics_with_aborted_metrics(
+    def compute_metrics(
         self,
         metric_configurations: List[MetricConfiguration],
         runtime_configuration: Optional[dict] = None,
@@ -162,7 +163,9 @@ def compute_metrics_with_aborted_metrics(
             min_graph_edges_pbar_enable: Minumum number of graph edges to warrant showing progress bars.
 
         Returns:
-            Dictionary with requested metrics resolved, with unique metric ID as key and computed metric as value.
+            Tuple of two elements, the first is a dictionary with requested metrics resolved,
+            with unique metric ID as key and computed metric as value. The second is a dictionary of the
+            aborted metrics information, with metric ID as key if any metrics were aborted.
         """
         graph: ValidationGraph = self.build_metric_dependency_graph(
             metric_configurations=metric_configurations,
@@ -172,39 +175,13 @@ def compute_metrics_with_aborted_metrics(
         aborted_metrics_info: _AbortedMetricsInfoDict
         (
             resolved_metrics,
-            aborted_metrics_info,
+            aborted_metrics,
         ) = self.resolve_validation_graph_and_handle_aborted_metrics_info(
             graph=graph,
             runtime_configuration=runtime_configuration,
             min_graph_edges_pbar_enable=min_graph_edges_pbar_enable,
         )
-        return resolved_metrics, aborted_metrics_info
-
-    def compute_metrics(
-        self,
-        metric_configurations: List[MetricConfiguration],
-        runtime_configuration: Optional[dict] = None,
-        min_graph_edges_pbar_enable: int = 0,
-        # Set to low number (e.g., 3) to suppress progress bar for small graphs.
-    ) -> _MetricsDict:
-        """
-        Args:
-            metric_configurations: List of desired MetricConfiguration objects to be resolved.
-            runtime_configuration: Additional run-time settings (see "Validator.DEFAULT_RUNTIME_CONFIGURATION").
-            min_graph_edges_pbar_enable: Minumum number of graph edges to warrant showing progress bars.
-
-        Returns:
-            Dictionary with requested metrics resolved, with unique metric ID as key and computed metric as value.
-        """
-
-        # Note: Dropping aborted metrics for backward compatibility.
-        # This is a temporary solution until we can change all the callers to handle aborted metrics.
-        resolved_metrics, _ = self.compute_metrics_with_aborted_metrics(
-            metric_configurations=metric_configurations,
-            runtime_configuration=runtime_configuration,
-            min_graph_edges_pbar_enable=min_graph_edges_pbar_enable,
-        )
-        return resolved_metrics
+        return resolved_metrics, aborted_metrics
 
     def build_metric_dependency_graph(
         self,

great_expectations/validator/validator.py

@@ -357,30 +357,6 @@ def compute_metrics(
         runtime_configuration: Optional[dict] = None,
         min_graph_edges_pbar_enable: int = 0,
         # Set to low number (e.g., 3) to suppress progress bar for small graphs.
-    ) -> _MetricsDict:
-        """
-        Convenience method that computes requested metrics (specified as elements of "MetricConfiguration" list).
-
-        Args:
-            metric_configurations: List of desired MetricConfiguration objects to be resolved.
-            runtime_configuration: Additional run-time settings (see "Validator.DEFAULT_RUNTIME_CONFIGURATION").
-            min_graph_edges_pbar_enable: Minumum number of graph edges to warrant showing progress bars.
-
-        Returns:
-            Dictionary with requested metrics resolved, with unique metric ID as key and computed metric as value.
-        """
-        return self._metrics_calculator.compute_metrics(
-            metric_configurations=metric_configurations,
-            runtime_configuration=runtime_configuration,
-            min_graph_edges_pbar_enable=min_graph_edges_pbar_enable,
-        )
-
-    def compute_metrics_with_aborted_metrics(
-        self,
-        metric_configurations: List[MetricConfiguration],
-        runtime_configuration: Optional[dict] = None,
-        min_graph_edges_pbar_enable: int = 0,
-        # Set to low number (e.g., 3) to suppress progress bar for small graphs.
     ) -> tuple[_MetricsDict, _AbortedMetricsInfoDict]:
         """
         Convenience method that computes requested metrics (specified as elements of "MetricConfiguration" list).
@@ -391,11 +367,11 @@ def compute_metrics_with_aborted_metrics(
             min_graph_edges_pbar_enable: Minumum number of graph edges to warrant showing progress bars.
 
         Returns:
-            Tuple with two elements. The first is a dictionary with requested metrics resolved, with unique metric
-            ID as key and computed metric as value. The second is a dictionary with information about any metrics
-            that were aborted during computation, using the unique metric ID as key.
+            Tuple of two elements, the first is a dictionary with requested metrics resolved,
+            with unique metric ID as key and computed metric as value. The second is a dictionary of the
+            aborted metrics information, with metric ID as key if any metrics were aborted.
         """
-        return self._metrics_calculator.compute_metrics_with_aborted_metrics(
+        return self._metrics_calculator.compute_metrics(
             metric_configurations=metric_configurations,
             runtime_configuration=runtime_configuration,
             min_graph_edges_pbar_enable=min_graph_edges_pbar_enable,

tests/experimental/metric_repository/test_column_descriptive_metrics_metric_retriever.py

@@ -45,7 +45,7 @@ def test_get_metrics():
         ("column_values.null.count", "column=col2", ()): 1,
     }
     aborted_metrics = {}
-    mock_validator.compute_metrics_with_aborted_metrics.return_value = (
+    mock_validator.compute_metrics.return_value = (
         computed_metrics,
         aborted_metrics,
     )
@@ -182,7 +182,7 @@ def test_get_metrics_metrics_missing():
         ("column_values.null.count", "column=col2", ()): 1,
     }
     mock_aborted_metrics = {}
-    mock_validator.compute_metrics_with_aborted_metrics.return_value = (
+    mock_validator.compute_metrics.return_value = (
         mock_computed_metrics,
         mock_aborted_metrics,
     )
@@ -344,7 +344,7 @@ def test_get_metrics_with_exception():
         ("column_values.null.count", "column=col1", ()): 1,
         ("column_values.null.count", "column=col2", ()): 1,
     }
-    mock_validator.compute_metrics_with_aborted_metrics.return_value = (
+    mock_validator.compute_metrics.return_value = (
         computed_metrics,
         aborted_metrics,
     )
@@ -502,7 +502,7 @@ def test_get_metrics_with_column_type_missing():
         ("column_values.null.count", "column=col1", ()): 1,
         ("column_values.null.count", "column=col2", ()): 1,
     }
-    mock_validator.compute_metrics_with_aborted_metrics.return_value = (
+    mock_validator.compute_metrics.return_value = (
         computed_metrics,
         aborted_metrics,
     )
@@ -642,7 +642,7 @@ def test_get_metrics_only_gets_a_validator_once():
         ("column_values.null.count", "column=col1", ()): 1,
         ("column_values.null.count", "column=col2", ()): 1,
     }
-    mock_validator.compute_metrics_with_aborted_metrics.return_value = (
+    mock_validator.compute_metrics.return_value = (
         computed_metrics,
         aborted_metrics,
     )

tests/validator/test_metrics_calculator.py

@@ -93,7 +93,9 @@ def test_column_partition_metric(
             "allow_relative_error": False,
         },
     )
-    results = metrics_calculator.compute_metrics(metric_configurations=[desired_metric])
+    results, _ = metrics_calculator.compute_metrics(
+        metric_configurations=[desired_metric]
+    )
 
     increment = float(n_bins + 1) / n_bins
     assert all(
@@ -112,7 +114,9 @@ def test_column_partition_metric(
             "allow_relative_error": False,
         },
     )
-    results = metrics_calculator.compute_metrics(metric_configurations=[desired_metric])
+    results, _ = metrics_calculator.compute_metrics(
+        metric_configurations=[desired_metric]
+    )
 
     increment = datetime.timedelta(
         seconds=(seconds_in_week * float(n_bins + 1) / n_bins)