feat: Add bigframes.pandas.col with basic operators

bigframes/core/agg_expressions.py

@@ -19,7 +19,7 @@
 import functools
 import itertools
 import typing
-from typing import Callable, Mapping, Tuple, TypeVar
+from typing import Callable, Hashable, Mapping, Tuple, TypeVar
 
 from bigframes import dtypes
 from bigframes.core import expression, window_spec
@@ -68,7 +68,7 @@ def children(self) -> Tuple[expression.Expression, ...]:
         return self.inputs
 
     @property
-    def free_variables(self) -> typing.Tuple[str, ...]:
+    def free_variables(self) -> typing.Tuple[Hashable, ...]:
         return tuple(
             itertools.chain.from_iterable(map(lambda x: x.free_variables, self.inputs))
         )
@@ -92,7 +92,7 @@ def transform_children(
 
     def bind_variables(
         self: TExpression,
-        bindings: Mapping[str, expression.Expression],
+        bindings: Mapping[Hashable, expression.Expression],
         allow_partial_bindings: bool = False,
     ) -> TExpression:
         return self.transform_children(
@@ -192,7 +192,7 @@ def children(self) -> Tuple[expression.Expression, ...]:
         return self.inputs
 
     @property
-    def free_variables(self) -> typing.Tuple[str, ...]:
+    def free_variables(self) -> typing.Tuple[Hashable, ...]:
         return tuple(
             itertools.chain.from_iterable(map(lambda x: x.free_variables, self.inputs))
         )
@@ -216,7 +216,7 @@ def transform_children(
 
     def bind_variables(
         self: WindowExpression,
-        bindings: Mapping[str, expression.Expression],
+        bindings: Mapping[Hashable, expression.Expression],
         allow_partial_bindings: bool = False,
     ) -> WindowExpression:
         return self.transform_children(

bigframes/core/col.py

@@ -0,0 +1,126 @@
+# Copyright 2026 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.
+from __future__ import annotations
+
+import dataclasses
+from typing import Any, Hashable
+
+import bigframes_vendored.pandas.core.col as pd_col
+
+import bigframes.core.expression as bf_expression
+import bigframes.operations as bf_ops
+
+
+# Not to be confused with internal Expressions class
+# Name collision unintended
+@dataclasses.dataclass(frozen=True)
+class Expression:
+    __doc__ = pd_col.Expression.__doc__
+
+    _value: bf_expression.Expression
+
+    def _apply_unary(self, op: bf_ops.UnaryOp) -> Expression:
+        return Expression(op.as_expr(self._value))
+
+    def _apply_binary(self, other: Any, op: bf_ops.BinaryOp, reverse: bool = False):
+        if isinstance(other, Expression):
+            other_value = other._value
+        else:
+            other_value = bf_expression.const(other)
+        if reverse:
+            return Expression(op.as_expr(other_value, self._value))
+        else:
+            return Expression(op.as_expr(self._value, other_value))
+
+    def __add__(self, other: Any) -> Expression:
+        return self._apply_binary(other, bf_ops.add_op)
+
+    def __radd__(self, other: Any) -> Expression:
+        return self._apply_binary(other, bf_ops.add_op, reverse=True)
+
+    def __sub__(self, other: Any) -> Expression:
+        return self._apply_binary(other, bf_ops.sub_op)
+
+    def __rsub__(self, other: Any) -> Expression:
+        return self._apply_binary(other, bf_ops.sub_op, reverse=True)
+
+    def __mul__(self, other: Any) -> Expression:
+        return self._apply_binary(other, bf_ops.mul_op)
+
+    def __rmul__(self, other: Any) -> Expression:
+        return self._apply_binary(other, bf_ops.mul_op, reverse=True)
+
+    def __truediv__(self, other: Any) -> Expression:
+        return self._apply_binary(other, bf_ops.div_op)
+
+    def __rtruediv__(self, other: Any) -> Expression:
+        return self._apply_binary(other, bf_ops.div_op, reverse=True)
+
+    def __floordiv__(self, other: Any) -> Expression:
+        return self._apply_binary(other, bf_ops.floordiv_op)
+
+    def __rfloordiv__(self, other: Any) -> Expression:
+        return self._apply_binary(other, bf_ops.floordiv_op, reverse=True)
+
+    def __ge__(self, other: Any) -> Expression:
+        return self._apply_binary(other, bf_ops.ge_op)
+
+    def __gt__(self, other: Any) -> Expression:
+        return self._apply_binary(other, bf_ops.gt_op)
+
+    def __le__(self, other: Any) -> Expression:
+        return self._apply_binary(other, bf_ops.le_op)
+
+    def __lt__(self, other: Any) -> Expression:
+        return self._apply_binary(other, bf_ops.lt_op)
+
+    def __eq__(self, other: object) -> Expression:  # type: ignore
+        return self._apply_binary(other, bf_ops.eq_op)
+
+    def __ne__(self, other: object) -> Expression:  # type: ignore
+        return self._apply_binary(other, bf_ops.ne_op)
+
+    def __mod__(self, other: Any) -> Expression:
+        return self._apply_binary(other, bf_ops.mod_op)
+
+    def __rmod__(self, other: Any) -> Expression:
+        return self._apply_binary(other, bf_ops.mod_op, reverse=True)
+
+    def __and__(self, other: Any) -> Expression:
+        return self._apply_binary(other, bf_ops.and_op)
+
+    def __rand__(self, other: Any) -> Expression:
+        return self._apply_binary(other, bf_ops.and_op, reverse=True)
+
+    def __or__(self, other: Any) -> Expression:
+        return self._apply_binary(other, bf_ops.or_op)
+
+    def __ror__(self, other: Any) -> Expression:
+        return self._apply_binary(other, bf_ops.or_op, reverse=True)
+
+    def __xor__(self, other: Any) -> Expression:
+        return self._apply_binary(other, bf_ops.xor_op)
+
+    def __rxor__(self, other: Any) -> Expression:
+        return self._apply_binary(other, bf_ops.xor_op, reverse=True)
+
+    def __invert__(self) -> Expression:
+        return self._apply_unary(bf_ops.invert_op)
+
+
+def col(col_name: Hashable) -> Expression:
+    return Expression(bf_expression.free_var(col_name))
+
+
+col.__doc__ = pd_col.col.__doc__

bigframes/core/expression.py

@@ -19,7 +19,7 @@
 import functools
 import itertools
 import typing
-from typing import Callable, Generator, Mapping, TypeVar, Union
+from typing import Callable, Generator, Hashable, Mapping, TypeVar, Union
 
 import pandas as pd
 
@@ -39,7 +39,7 @@ def deref(name: str) -> DerefOp:
     return DerefOp(ids.ColumnId(name))
 
 
-def free_var(id: str) -> UnboundVariableExpression:
+def free_var(id: Hashable) -> UnboundVariableExpression:
     return UnboundVariableExpression(id)
 
 
@@ -52,7 +52,7 @@ class Expression(abc.ABC):
     """An expression represents a computation taking N scalar inputs and producing a single output scalar."""
 
     @property
-    def free_variables(self) -> typing.Tuple[str, ...]:
+    def free_variables(self) -> typing.Tuple[Hashable, ...]:
         return ()
 
     @property
@@ -116,7 +116,9 @@ def bind_refs(
 
     @abc.abstractmethod
     def bind_variables(
-        self, bindings: Mapping[str, Expression], allow_partial_bindings: bool = False
+        self,
+        bindings: Mapping[Hashable, Expression],
+        allow_partial_bindings: bool = False,
     ) -> Expression:
         """Replace variables with expression given in `bindings`.
 
@@ -191,7 +193,9 @@ def output_type(self) -> dtypes.ExpressionType:
         return self.dtype
 
     def bind_variables(
-        self, bindings: Mapping[str, Expression], allow_partial_bindings: bool = False
+        self,
+        bindings: Mapping[Hashable, Expression],
+        allow_partial_bindings: bool = False,
     ) -> Expression:
         return self
 
@@ -226,10 +230,10 @@ def transform_children(self, t: Callable[[Expression], Expression]) -> Expressio
 class UnboundVariableExpression(Expression):
     """A variable expression representing an unbound variable."""
 
-    id: str
+    id: Hashable
 
     @property
-    def free_variables(self) -> typing.Tuple[str, ...]:
+    def free_variables(self) -> typing.Tuple[Hashable, ...]:
         return (self.id,)
 
     @property
@@ -256,7 +260,9 @@ def bind_refs(
         return self
 
     def bind_variables(
-        self, bindings: Mapping[str, Expression], allow_partial_bindings: bool = False
+        self,
+        bindings: Mapping[Hashable, Expression],
+        allow_partial_bindings: bool = False,
     ) -> Expression:
         if self.id in bindings.keys():
             return bindings[self.id]
@@ -304,7 +310,9 @@ def output_type(self) -> dtypes.ExpressionType:
         raise ValueError(f"Type of variable {self.id} has not been fixed.")
 
     def bind_variables(
-        self, bindings: Mapping[str, Expression], allow_partial_bindings: bool = False
+        self,
+        bindings: Mapping[Hashable, Expression],
+        allow_partial_bindings: bool = False,
     ) -> Expression:
         return self
 
@@ -373,7 +381,7 @@ def column_references(
         )
 
     @property
-    def free_variables(self) -> typing.Tuple[str, ...]:
+    def free_variables(self) -> typing.Tuple[Hashable, ...]:
         return tuple(
             itertools.chain.from_iterable(map(lambda x: x.free_variables, self.inputs))
         )
@@ -408,7 +416,9 @@ def output_type(self) -> dtypes.ExpressionType:
         return self.op.output_type(*input_types)
 
     def bind_variables(
-        self, bindings: Mapping[str, Expression], allow_partial_bindings: bool = False
+        self,
+        bindings: Mapping[Hashable, Expression],
+        allow_partial_bindings: bool = False,
     ) -> OpExpression:
         return OpExpression(
             self.op,

bigframes/dataframe.py

@@ -58,6 +58,7 @@
 from bigframes.core import agg_expressions
 import bigframes.core.block_transforms as block_ops
 import bigframes.core.blocks as blocks
+import bigframes.core.col
 import bigframes.core.convert
 import bigframes.core.explode
 import bigframes.core.expression as ex
@@ -94,7 +95,13 @@
     import bigframes.session
 
     SingleItemValue = Union[
-        bigframes.series.Series, int, float, str, pandas.Timedelta, Callable
+        bigframes.series.Series,
+        int,
+        float,
+        str,
+        pandas.Timedelta,
+        Callable,
+        bigframes.core.col.Expression,
     ]
     MultiItemValue = Union[
         "DataFrame", Sequence[int | float | str | pandas.Timedelta | Callable]
@@ -2236,6 +2243,13 @@ def _assign_single_item(
     ) -> DataFrame:
         if isinstance(v, bigframes.series.Series):
             return self._assign_series_join_on_index(k, v)
+        elif isinstance(v, bigframes.core.col.Expression):
+            label_to_col_ref = {
+                label: ex.deref(id) for id, label in self._block.col_id_to_label.items()
+            }
+            resolved_expr = v._value.bind_variables(label_to_col_ref)
+            block = self._block.project_block_exprs([resolved_expr], labels=[k])
+            return DataFrame(block)
         elif isinstance(v, bigframes.dataframe.DataFrame):
             v_df_col_count = len(v._block.value_columns)
             if v_df_col_count != 1:

bigframes/operations/aggregations.py

@@ -205,7 +205,7 @@ def output_type(self, *input_types: dtypes.ExpressionType) -> dtypes.ExpressionT
             return dtypes.TIMEDELTA_DTYPE
 
         if dtypes.is_numeric(input_types[0]):
-            if pd.api.types.is_bool_dtype(input_types[0]):
+            if pd.api.types.is_bool_dtype(input_types[0]):  # type: ignore
                 return dtypes.INT_DTYPE
             return input_types[0]
 
@@ -224,7 +224,7 @@ def output_type(self, *input_types: dtypes.ExpressionType) -> dtypes.ExpressionT
         # These will change if median is changed to exact implementation.
         if not dtypes.is_orderable(input_types[0]):
             raise TypeError(f"Type {input_types[0]} is not orderable")
-        if pd.api.types.is_bool_dtype(input_types[0]):
+        if pd.api.types.is_bool_dtype(input_types[0]):  # type: ignore
             return dtypes.INT_DTYPE
         else:
             return input_types[0]

bigframes/pandas/__init__.py

@@ -27,6 +27,7 @@
 import pandas
 
 import bigframes._config as config
+from bigframes.core.col import col
 import bigframes.core.global_session as global_session
 import bigframes.core.indexes
 from bigframes.core.logging import log_adapter
@@ -415,6 +416,7 @@ def reset_session():
     "clean_up_by_session_id",
     "concat",
     "crosstab",
+    "col",
     "cut",
     "deploy_remote_function",
     "deploy_udf",

tests/unit/test_dataframe_polars.py

@@ -828,6 +828,25 @@ def test_assign_new_column(scalars_dfs):
     assert_frame_equal(bf_result, pd_result)
 
 
+def test_assign_using_pd_col(scalars_dfs):
+    if pd.__version__.startswith("1.") or pd.__version__.startswith("2."):
+        pytest.skip("col expression interface only supported for pandas 3+")
+    scalars_df, scalars_pandas_df = scalars_dfs
+    bf_kwargs = {
+        "new_col_1": 4 - bpd.col("int64_col"),
+        "new_col_2": bpd.col("int64_col") / (bpd.col("float64_col") * 0.5),
+    }
+    pd_kwargs = {
+        "new_col_1": 4 - pd.col("int64_col"),  # type: ignore
+        "new_col_2": pd.col("int64_col") / (pd.col("float64_col") * 0.5),  # type: ignore
+    }
+    df = scalars_df.assign(**bf_kwargs)
+    bf_result = df.to_pandas()
+    pd_result = scalars_pandas_df.assign(**pd_kwargs)
+
+    assert_frame_equal(bf_result, pd_result)
+
+
 def test_assign_new_column_w_loc(scalars_dfs):
     scalars_df, scalars_pandas_df = scalars_dfs
     bf_df = scalars_df.copy()