Fix black formatting for CI

Author: Saurabh Badenkal

src/PowerPlatform/Dataverse/operations/batch.py

@@ -707,9 +707,7 @@ def delete(
             return
         invalid = [ids.index[i] for i, v in enumerate(raw_list) if not isinstance(v, str) or not v.strip()]
         if invalid:
-            raise ValueError(
-                f"ids contains invalid values at index(es) {invalid}. All IDs must be non-empty strings."
-            )
+            raise ValueError(f"ids contains invalid values at index(es) {invalid}. All IDs must be non-empty strings.")
         id_list = [v.strip() for v in raw_list]
         self._batch.records.delete(table, id_list, use_bulk_delete=use_bulk_delete)
 

tests/unit/data/test_batch_edge_cases.py

@@ -335,9 +335,7 @@ def test_changeset_ops_counted_toward_limit(self):
         items.append(cs)
 
         od._build_get.return_value = _RawRequest(method="GET", url="https://org/api/data/v9.2/accounts(x)")
-        od._build_create.return_value = _RawRequest(
-            method="POST", url="https://org/api/data/v9.2/accounts", body="{}"
-        )
+        od._build_create.return_value = _RawRequest(method="POST", url="https://org/api/data/v9.2/accounts", body="{}")
 
         with self.assertRaises(ValidationError) as ctx:
             client.execute(items)

tests/unit/test_batch_dataframe.py

@@ -36,10 +36,12 @@ class TestBatchDataFrameCreate(unittest.TestCase):
 
     def test_create_from_dataframe(self):
         batch = _make_batch()
-        df = pd.DataFrame([
-            {"name": "Contoso", "telephone1": "555-0100"},
-            {"name": "Fabrikam", "telephone1": "555-0200"},
-        ])
+        df = pd.DataFrame(
+            [
+                {"name": "Contoso", "telephone1": "555-0100"},
+                {"name": "Fabrikam", "telephone1": "555-0200"},
+            ]
+        )
         batch.dataframe.create("account", df)
         # Should have enqueued a _RecordCreate with a list of dicts
         self.assertEqual(len(batch._items), 1)
@@ -82,10 +84,12 @@ def test_create_rejects_rows_with_all_nan(self):
     def test_create_handles_nan_values(self):
         """NaN values are dropped from individual records by default."""
         batch = _make_batch()
-        df = pd.DataFrame([
-            {"name": "Contoso", "telephone1": "555-0100"},
-            {"name": "Fabrikam", "telephone1": None},
-        ])
+        df = pd.DataFrame(
+            [
+                {"name": "Contoso", "telephone1": "555-0100"},
+                {"name": "Fabrikam", "telephone1": None},
+            ]
+        )
         batch.dataframe.create("account", df)
         item = batch._items[0]
         # Second record should not have telephone1
@@ -98,10 +102,12 @@ class TestBatchDataFrameUpdate(unittest.TestCase):
 
     def test_update_enqueues_record_update(self):
         batch = _make_batch()
-        df = pd.DataFrame([
-            {"accountid": "guid-1", "telephone1": "555-0100"},
-            {"accountid": "guid-2", "telephone1": "555-0200"},
-        ])
+        df = pd.DataFrame(
+            [
+                {"accountid": "guid-1", "telephone1": "555-0100"},
+                {"accountid": "guid-2", "telephone1": "555-0200"},
+            ]
+        )
         batch.dataframe.update("account", df, id_column="accountid")
         self.assertEqual(len(batch._items), 1)
         item = batch._items[0]
@@ -139,9 +145,11 @@ def test_update_rejects_invalid_ids(self):
     def test_update_skips_all_nan_rows(self):
         """Rows where all change values are NaN are silently skipped."""
         batch = _make_batch()
-        df = pd.DataFrame([
-            {"accountid": "guid-1", "name": None},
-        ])
+        df = pd.DataFrame(
+            [
+                {"accountid": "guid-1", "name": None},
+            ]
+        )
         batch.dataframe.update("account", df, id_column="accountid")
         # Nothing enqueued because all change values were NaN
         self.assertEqual(len(batch._items), 0)