add engine tests

Author: TrevorBergeron

tests/system/small/engines/conftest.py

@@ -90,3 +90,10 @@ def repeated_data_source(
     repeated_pandas_df: pd.DataFrame,
 ) -> local_data.ManagedArrowTable:
     return local_data.ManagedArrowTable.from_pandas(repeated_pandas_df)
+
+
+@pytest.fixture(scope="module")
+def arrays_array_value(
+    repeated_data_source: local_data.ManagedArrowTable, fake_session: bigframes.Session
+):
+    return ArrayValue.from_managed(repeated_data_source, fake_session)

tests/system/small/engines/test_array_ops.py

@@ -0,0 +1,60 @@
+# 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 pytest
+
+from bigframes.core import array_value, expression
+import bigframes.operations as ops
+import bigframes.operations.aggregations as agg_ops
+from bigframes.session import polars_executor
+from bigframes.testing.engine_utils import assert_equivalence_execution
+
+pytest.importorskip("polars")
+
+# Polars used as reference as its fast and local. Generally though, prefer gbq engine where they disagree.
+REFERENCE_ENGINE = polars_executor.PolarsExecutor()
+
+
+@pytest.mark.parametrize("engine", ["polars", "bq"], indirect=True)
+def test_engines_to_array_op(scalars_array_value: array_value.ArrayValue, engine):
+    # Bigquery won't allow you to materialize arrays with null, so use non-nullable
+    int64_non_null = ops.coalesce_op.as_expr("int64_col", expression.const(0))
+    bool_col_non_null = ops.coalesce_op.as_expr("bool_col", expression.const(False))
+    float_col_non_null = ops.coalesce_op.as_expr("float64_col", expression.const(0.0))
+    string_col_non_null = ops.coalesce_op.as_expr("string_col", expression.const(""))
+
+    arr, _ = scalars_array_value.compute_values(
+        [
+            ops.ToArrayOp().as_expr(int64_non_null),
+            ops.ToArrayOp().as_expr(
+                int64_non_null, bool_col_non_null, float_col_non_null
+            ),
+            ops.ToArrayOp().as_expr(string_col_non_null, string_col_non_null),
+        ]
+    )
+    assert_equivalence_execution(arr.node, REFERENCE_ENGINE, engine)
+
+
+@pytest.mark.parametrize("engine", ["polars", "bq"], indirect=True)
+def test_engines_array_reduce_op(arrays_array_value: array_value.ArrayValue, engine):
+    arr, _ = arrays_array_value.compute_values(
+        [
+            ops.ArrayReduceOp(agg_ops.SumOp()).as_expr("float_list_col"),
+            ops.ArrayReduceOp(agg_ops.StdOp()).as_expr("float_list_col"),
+            ops.ArrayReduceOp(agg_ops.MaxOp()).as_expr("date_list_col"),
+            ops.ArrayReduceOp(agg_ops.CountOp()).as_expr("string_list_col"),
+            ops.ArrayReduceOp(agg_ops.AnyOp()).as_expr("bool_list_col"),
+        ]
+    )
+    assert_equivalence_execution(arr.node, REFERENCE_ENGINE, engine)