Merge branch 'main' into output_schema

Author: ccarpentiere

bigframes/core/compile/polars/compiler.py

@@ -198,6 +198,10 @@ def _(self, op: ops.ScalarOp, l_input: pl.Expr, r_input: pl.Expr) -> pl.Expr:
         def _(self, op: ops.ScalarOp, l_input: pl.Expr, r_input: pl.Expr) -> pl.Expr:
             return l_input | r_input
 
+        @compile_op.register(bool_ops.XorOp)
+        def _(self, op: ops.ScalarOp, l_input: pl.Expr, r_input: pl.Expr) -> pl.Expr:
+            return l_input ^ r_input
+
         @compile_op.register(num_ops.AddOp)
         def _(self, op: ops.ScalarOp, l_input: pl.Expr, r_input: pl.Expr) -> pl.Expr:
             return l_input + r_input

bigframes/display/table_widget.js

@@ -88,7 +88,9 @@ function render({ model, el }) {
 		const totalPages = Math.ceil(rowCount / pageSize);
 
 		rowCountLabel.textContent = `${rowCount.toLocaleString()} total rows`;
-		paginationLabel.textContent = `Page ${currentPage + 1} of ${totalPages || 1}`;
+		paginationLabel.textContent = `Page ${(
+			currentPage + 1
+		).toLocaleString()} of ${(totalPages || 1).toLocaleString()}`;
 		prevPage.disabled = currentPage === 0;
 		nextPage.disabled = currentPage >= totalPages - 1;
 		pageSizeSelect.value = pageSize;

bigframes/session/polars_executor.py

@@ -21,7 +21,7 @@
 from bigframes.core import array_value, bigframe_node, expression, local_data, nodes
 import bigframes.operations
 from bigframes.operations import aggregations as agg_ops
-from bigframes.operations import comparison_ops, generic_ops, numeric_ops
+from bigframes.operations import bool_ops, comparison_ops, generic_ops, numeric_ops
 from bigframes.session import executor, semi_executor
 
 if TYPE_CHECKING:
@@ -44,6 +44,9 @@
 )
 
 _COMPATIBLE_SCALAR_OPS = (
+    bool_ops.AndOp,
+    bool_ops.OrOp,
+    bool_ops.XorOp,
     comparison_ops.EqOp,
     comparison_ops.EqNullsMatchOp,
     comparison_ops.NeOp,
@@ -63,6 +66,8 @@
     generic_ops.FillNaOp,
     generic_ops.CaseWhenOp,
     generic_ops.InvertOp,
+    generic_ops.IsNullOp,
+    generic_ops.NotNullOp,
 )
 _COMPATIBLE_AGG_OPS = (
     agg_ops.SizeOp,

tests/system/small/engines/test_bool_ops.py

@@ -0,0 +1,64 @@
+# 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 itertools
+
+import pytest
+
+from bigframes.core import array_value
+import bigframes.operations as 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()
+
+
+def apply_op_pairwise(
+    array: array_value.ArrayValue, op: ops.BinaryOp, excluded_cols=[]
+) -> array_value.ArrayValue:
+    exprs = []
+    for l_arg, r_arg in itertools.permutations(array.column_ids, 2):
+        if (l_arg in excluded_cols) or (r_arg in excluded_cols):
+            continue
+        try:
+            _ = op.output_type(
+                array.get_column_type(l_arg), array.get_column_type(r_arg)
+            )
+            exprs.append(op.as_expr(l_arg, r_arg))
+        except TypeError:
+            continue
+    assert len(exprs) > 0
+    new_arr, _ = array.compute_values(exprs)
+    return new_arr
+
+
+@pytest.mark.parametrize("engine", ["polars", "bq"], indirect=True)
+@pytest.mark.parametrize(
+    "op",
+    [
+        ops.and_op,
+        ops.or_op,
+        ops.xor_op,
+    ],
+)
+def test_engines_project_boolean_op(
+    scalars_array_value: array_value.ArrayValue, engine, op
+):
+    # exclude string cols as does not contain dates
+    # bool col actually doesn't work properly for bq engine
+    arr = apply_op_pairwise(scalars_array_value, op, excluded_cols=["string_col"])
+    assert_equivalence_execution(arr.node, REFERENCE_ENGINE, engine)