fix: Remove itertools.pairwise usage (#1638)

Author: TrevorBergeron

bigframes/core/local_data.py

@@ -212,7 +212,7 @@ def _(
         value_generator = iter_array(
             array.flatten(), bigframes.dtypes.get_array_inner_type(dtype)
         )
-        for (start, end) in itertools.pairwise(array.offsets):
+        for (start, end) in _pairwise(array.offsets):
             arr_size = end.as_py() - start.as_py()
             yield list(itertools.islice(value_generator, arr_size))
 
@@ -389,3 +389,16 @@ def _physical_type_replacements(dtype: pa.DataType) -> pa.DataType:
     if dtype in _ARROW_MANAGED_STORAGE_OVERRIDES:
         return _ARROW_MANAGED_STORAGE_OVERRIDES[dtype]
     return dtype
+
+
+def _pairwise(iterable):
+    do_yield = False
+    a = None
+    b = None
+    for item in iterable:
+        a = b
+        b = item
+        if do_yield:
+            yield (a, b)
+        else:
+            do_yield = True

tests/unit/test_local_data.py

@@ -0,0 +1,46 @@
+# Copyright 2025 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+import pandas as pd
+import pandas.testing
+import pyarrow as pa
+
+from bigframes import dtypes
+from bigframes.core import local_data
+
+pd_data = pd.DataFrame(
+    {
+        "ints": [10, 20, 30, 40],
+        "nested_ints": [[1, 2], [3, 4, 5], [], [20, 30]],
+        "structs": [{"a": 100}, {}, {"b": 200}, {"b": 300}],
+    }
+)
+
+pd_data_normalized = pd.DataFrame(
+    {
+        "ints": pd.Series([10, 20, 30, 40], dtype=dtypes.INT_DTYPE),
+        "nested_ints": pd.Series(
+            [[1, 2], [3, 4, 5], [], [20, 30]], dtype=pd.ArrowDtype(pa.list_(pa.int64()))
+        ),
+        "structs": pd.Series(
+            [{"a": 100}, {}, {"b": 200}, {"b": 300}],
+            dtype=pd.ArrowDtype(pa.struct({"a": pa.int64(), "b": pa.int64()})),
+        ),
+    }
+)
+
+
+def test_local_data_well_formed_round_trip():
+    local_entry = local_data.ManagedArrowTable.from_pandas(pd_data)
+    result = pd.DataFrame(local_entry.itertuples(), columns=pd_data.columns)
+    pandas.testing.assert_frame_equal(pd_data_normalized, result, check_dtype=False)