fix: Fix clip int series with float bounds

bigframes/core/compile/scalar_op_compiler.py

@@ -1935,34 +1935,18 @@ def clip_op(
     if isinstance(lower, ibis_types.NullScalar) and (
         not isinstance(upper, ibis_types.NullScalar)
     ):
-        return (
-            ibis_api.case()  # type: ignore
-            .when(upper.isnull() | (original > upper), upper)
-            .else_(original)
-            .end()
-        )
+        return ibis_api.least(original, upper)
     elif (not isinstance(lower, ibis_types.NullScalar)) and isinstance(
         upper, ibis_types.NullScalar
     ):
-        return (
-            ibis_api.case()  # type: ignore
-            .when(lower.isnull() | (original < lower), lower)
-            .else_(original)
-            .end()
-        )
+        return ibis_api.greatest(original, lower)
     elif isinstance(lower, ibis_types.NullScalar) and (
         isinstance(upper, ibis_types.NullScalar)
     ):
         return original
     else:
         # Note: Pandas has unchanged behavior when upper bound and lower bound are flipped. This implementation requires that lower_bound < upper_bound
-        return (
-            ibis_api.case()  # type: ignore
-            .when(lower.isnull() | (original < lower), lower)
-            .when(upper.isnull() | (original > upper), upper)
-            .else_(original)
-            .end()
-        )
+        return ibis_api.greatest(ibis_api.least(original, upper), lower)
 
 
 # N-ary Operations

bigframes/operations/base.py

@@ -245,9 +245,9 @@ def _align(
         )
         return (typing.cast(ex.DerefOp, values[0]), values[1], block)
 
-    def _align3(self, other1: series.Series | scalars.Scalar, other2: series.Series | scalars.Scalar, how="left") -> tuple[ex.DerefOp, AlignedExprT, AlignedExprT, blocks.Block]:  # type: ignore
+    def _align3(self, other1: series.Series | scalars.Scalar, other2: series.Series | scalars.Scalar, how="left", cast_scalars: bool = True) -> tuple[ex.DerefOp, AlignedExprT, AlignedExprT, blocks.Block]:  # type: ignore
         """Aligns the series value with 2 other scalars or series objects. Returns new values and joined tabled expression."""
-        values, index = self._align_n([other1, other2], how)
+        values, index = self._align_n([other1, other2], how, cast_scalars=cast_scalars)
         return (
             typing.cast(ex.DerefOp, values[0]),
             values[1],
@@ -260,7 +260,7 @@ def _align_n(
         others: typing.Sequence[typing.Union[series.Series, scalars.Scalar]],
         how="outer",
         ignore_self=False,
-        cast_scalars: bool = True,
+        cast_scalars: bool = False,
     ) -> tuple[
         typing.Sequence[Union[ex.ScalarConstantExpression, ex.DerefOp]],
         blocks.Block,

bigframes/series.py

@@ -1353,14 +1353,17 @@ def where(self, cond, other=None):
         )
         return Series(block.select_column(result_id).with_column_labels([self.name]))
 
-    def clip(self, lower, upper):
+    def clip(self, lower=None, upper=None):
         if lower is None and upper is None:
             return self
         if lower is None:
             return self._apply_binary_op(upper, ops.minimum_op, alignment="left")
         if upper is None:
             return self._apply_binary_op(lower, ops.maximum_op, alignment="left")
-        value_id, lower_id, upper_id, block = self._align3(lower, upper)
+        # special rule to coerce scalar string args to date
+        value_id, lower_id, upper_id, block = self._align3(
+            lower, upper, cast_scalars=(bigframes.dtypes.is_date_like(self.dtype))
+        )
         block, result_id = block.project_expr(
             ops.clip_op.as_expr(value_id, lower_id, upper_id),
         )

tests/system/small/test_series.py

@@ -3001,6 +3001,17 @@ def test_clip(scalars_df_index, scalars_pandas_df_index, ordered):
     assert_series_equal(bf_result, pd_result, ignore_order=not ordered)
 
 
+def test_clip_int_with_float_bounds(scalars_df_index, scalars_pandas_df_index):
+    col_bf = scalars_df_index["int64_too"]
+    bf_result = col_bf.clip(-100, 3.14151593).to_pandas()
+
+    col_pd = scalars_pandas_df_index["int64_too"]
+    # pandas doesn't work with Int64 and clip with floats
+    pd_result = col_pd.astype("int64").clip(-100, 3.14151593).astype("Float64")
+
+    assert_series_equal(bf_result, pd_result)
+
+
 def test_clip_filtered_two_sided(scalars_df_index, scalars_pandas_df_index):
     col_bf = scalars_df_index["int64_col"].iloc[::2]
     lower_bf = scalars_df_index["int64_too"].iloc[2:] - 1