Run format

Author: midhun-pm

libs/labelbox/src/labelbox/data/metrics/confusion_matrix/confusion_matrix.py

@@ -96,7 +96,7 @@ def _get_metric_name(
     if _is_classification(ground_truths, predictions):
         return "classification"
 
-    return f"{int(iou*100)}pct_iou"
+    return f"{int(iou * 100)}pct_iou"
 
 
 def _is_classification(

libs/labelbox/src/labelbox/orm/db_object.py

@@ -76,8 +76,7 @@ def _set_field_values(self, field_values):
                     value = value.replace(tzinfo=timezone.utc)
                 except ValueError:
                     logger.warning(
-                        "Failed to convert value '%s' to datetime for "
-                        "field %s",
+                        "Failed to convert value '%s' to datetime for field %s",
                         value,
                         field,
                     )

libs/labelbox/src/labelbox/schema/workflow/filter_converters.py

@@ -358,7 +358,7 @@ def _handle_feature_consensus_average(
             if isinstance(annotations[0], str):
                 # Simple ID list - convert to full format (placeholder names)
                 annotation_objects = [
-                    {"name": f"Feature {i+1}", "schemaNodeId": ann_id}
+                    {"name": f"Feature {i + 1}", "schemaNodeId": ann_id}
                     for i, ann_id in enumerate(annotations)
                 ]
             else:

libs/labelbox/src/labelbox/schema/workflow/filter_utils.py

@@ -84,27 +84,27 @@ def build_metadata_items(
     """
     if item_type == "user":
         return [
-            {key_field: item_id, "email": f"user{i+1}@example.com"}
+            {key_field: item_id, "email": f"user{i + 1}@example.com"}
             for i, item_id in enumerate(ids)
         ]
     elif item_type == "dataset":
         return [
-            {key_field: item_id, "name": f"Dataset {i+1}"}
+            {key_field: item_id, "name": f"Dataset {i + 1}"}
             for i, item_id in enumerate(ids)
         ]
     elif item_type == "annotation":
         return [
-            {"name": f"Annotation {i+1}", "schemaNodeId": item_id}
+            {"name": f"Annotation {i + 1}", "schemaNodeId": item_id}
             for i, item_id in enumerate(ids)
         ]
     elif item_type == "issue":
         return [
-            {key_field: item_id, "name": f"Issue Category {i+1}"}
+            {key_field: item_id, "name": f"Issue Category {i + 1}"}
             for i, item_id in enumerate(ids)
         ]
     else:
         return [
-            {key_field: item_id, "name": f"{item_type.title()} {i+1}"}
+            {key_field: item_id, "name": f"{item_type.title()} {i + 1}"}
             for i, item_id in enumerate(ids)
         ]
 

libs/labelbox/src/labelbox/schema/workflow/workflow_utils.py

@@ -402,5 +402,5 @@ def print_filters(workflow: "ProjectWorkflow") -> None:
             if isinstance(node, LogicNode):
                 logger.info(f"Filters for node {node.id} ({node.name}):")
                 for i, f in enumerate(node.get_parsed_filters()):
-                    logger.info(f"  Filter {i+1}:")
+                    logger.info(f"  Filter {i + 1}:")
                     logger.info(f"  {json.dumps(f, indent=2)}")

libs/labelbox/tests/conftest.py

@@ -688,12 +688,12 @@ def create_label():
             predictions,
         )
         upload_task.wait_until_done(sleep_time_seconds=5)
-        assert (
-            upload_task.state == AnnotationImportState.FINISHED
-        ), "Label Import did not finish"
-        assert (
-            len(upload_task.errors) == 0
-        ), f"Label Import {upload_task.name} failed with errors {upload_task.errors}"
+        assert upload_task.state == AnnotationImportState.FINISHED, (
+            "Label Import did not finish"
+        )
+        assert len(upload_task.errors) == 0, (
+            f"Label Import {upload_task.name} failed with errors {upload_task.errors}"
+        )
 
     project.create_label = create_label
     project.create_label()

libs/labelbox/tests/data/annotation_import/conftest.py

@@ -1929,12 +1929,12 @@ def model_run_with_data_rows(
         model_run_predictions,
     )
     upload_task.wait_until_done()
-    assert (
-        upload_task.state == AnnotationImportState.FINISHED
-    ), "Label Import did not finish"
-    assert (
-        len(upload_task.errors) == 0
-    ), f"Label Import {upload_task.name} failed with errors {upload_task.errors}"
+    assert upload_task.state == AnnotationImportState.FINISHED, (
+        "Label Import did not finish"
+    )
+    assert len(upload_task.errors) == 0, (
+        f"Label Import {upload_task.name} failed with errors {upload_task.errors}"
+    )
     labels = wait_for_label_processing(configured_project)
     label_ids = [label.uid for label in labels]
     model_run.upsert_labels(label_ids)
@@ -1963,12 +1963,12 @@ def model_run_with_all_project_labels(
         model_run_predictions,
     )
     upload_task.wait_until_done()
-    assert (
-        upload_task.state == AnnotationImportState.FINISHED
-    ), "Label Import did not finish"
-    assert (
-        len(upload_task.errors) == 0
-    ), f"Label Import {upload_task.name} failed with errors {upload_task.errors}"
+    assert upload_task.state == AnnotationImportState.FINISHED, (
+        "Label Import did not finish"
+    )
+    assert len(upload_task.errors) == 0, (
+        f"Label Import {upload_task.name} failed with errors {upload_task.errors}"
+    )
     labels = wait_for_label_processing(configured_project)
     label_ids = [label.uid for label in labels]
     model_run.upsert_labels(label_ids)

libs/labelbox/tests/data/export/conftest.py

@@ -462,12 +462,12 @@ def model_run_with_data_rows(
         model_run_predictions,
     )
     upload_task.wait_until_done()
-    assert (
-        upload_task.state == AnnotationImportState.FINISHED
-    ), "Label Import did not finish"
-    assert (
-        len(upload_task.errors) == 0
-    ), f"Label Import {upload_task.name} failed with errors {upload_task.errors}"
+    assert upload_task.state == AnnotationImportState.FINISHED, (
+        "Label Import did not finish"
+    )
+    assert len(upload_task.errors) == 0, (
+        f"Label Import {upload_task.name} failed with errors {upload_task.errors}"
+    )
     labels = wait_for_label_processing(configured_project_with_ontology)
     label_ids = [label.uid for label in labels]
     model_run.upsert_labels(label_ids)

libs/labelbox/tests/data/export/streamable/test_export_data_rows_streamable.py

@@ -138,7 +138,9 @@ def test_cancel_export_task(
         cancelled_task = client.get_task_by_id(export_task.uid)
         assert cancelled_task.status in ["CANCELING", "CANCELED"]
 
-    @pytest.mark.skip(reason="Test times out in environments with high task volume - querying all org tasks is too slow")
+    @pytest.mark.skip(
+        reason="Test times out in environments with high task volume - querying all org tasks is too slow"
+    )
     def test_task_filter(self, client, data_row, wait_for_data_row_processing):
         organization = client.get_organization()
         user = client.get_user()

libs/labelbox/tests/data/metrics/confusion_matrix/test_confusion_matrix_data_row.py

@@ -38,9 +38,9 @@ def test_overlapping_objects(tool_examples):
                 ).values():
                     for idx in range(4):
                         expected[idx] += expected_values[idx]
-                assert score[0].value == tuple(
-                    expected
-                ), f"{example.predictions},{example.ground_truths}"
+                assert score[0].value == tuple(expected), (
+                    f"{example.predictions},{example.ground_truths}"
+                )
 
 
 @parametrize(
@@ -59,9 +59,9 @@ def test_overlapping_classifications(tool_examples):
             for expected_values in example.expected.values():
                 for idx in range(4):
                     expected[idx] += expected_values[idx]
-            assert score[0].value == tuple(
-                expected
-            ), f"{example.predictions},{example.ground_truths}"
+            assert score[0].value == tuple(expected), (
+                f"{example.predictions},{example.ground_truths}"
+            )
 
 
 def test_partial_overlap(pair_iou_thresholds):
@@ -70,6 +70,6 @@ def test_partial_overlap(pair_iou_thresholds):
             score = confusion_matrix_metric(
                 example.predictions, example.ground_truths, iou=iou
             )
-            assert score[0].value == tuple(
-                example.expected[iou]
-            ), f"{example.predictions},{example.ground_truths}"
+            assert score[0].value == tuple(example.expected[iou]), (
+                f"{example.predictions},{example.ground_truths}"
+            )