feat: Support callable for series mask method

bigframes/series.py

@@ -2113,13 +2113,8 @@ def duplicated(self, keep: str = "first") -> Series:
         )
 
     def mask(self, cond, other=None) -> Series:
-        if callable(cond):
-            if hasattr(cond, "bigframes_bigquery_function"):
-                cond = self.apply(cond)
-            else:
-                # For non-BigQuery function assume that it is applicable on Series
-                cond = self.apply(cond, by_row=False)
-
+        cond = self._apply_callable(cond)
+        other = self._apply_callable(other)
         if not isinstance(cond, Series):
             raise TypeError(
                 f"Only bigframes series condition is supported, received {type(cond).__name__}. "

tests/system/large/functions/test_managed_function.py

@@ -1077,7 +1077,7 @@ def func_for_other(x):
         )
 
 
-def test_managed_function_series_where(session, dataset_id, scalars_dfs):
+def test_managed_function_series_where_mask(session, dataset_id, scalars_dfs):
     try:
 
         # The return type has to be bool type for callable where condition.
@@ -1098,8 +1098,8 @@ def _is_positive(s):
         pd_int64 = scalars_pandas["int64_col"]
         pd_int64_filtered = pd_int64.dropna()
 
-        # The cond is a callable (managed function) and the other is not a
-        # callable in series.where method.
+        # Test series.where method: the cond is a callable (managed function)
+        # and the other is not a callable.
         bf_result = bf_int64_filtered.where(
             cond=is_positive_mf, other=-bf_int64_filtered
         ).to_pandas()
@@ -1108,6 +1108,16 @@ def _is_positive(s):
         # Ignore any dtype difference.
         pandas.testing.assert_series_equal(bf_result, pd_result, check_dtype=False)
 
+        # Test series.mask method: the cond is a callable (managed function)
+        # and the other is not a callable.
+        bf_result = bf_int64_filtered.mask(
+            cond=is_positive_mf, other=-bf_int64_filtered
+        ).to_pandas()
+        pd_result = pd_int64_filtered.mask(cond=_is_positive, other=-pd_int64_filtered)
+
+        # Ignore any dtype difference.
+        pandas.testing.assert_series_equal(bf_result, pd_result, check_dtype=False)
+
     finally:
         # Clean up the gcp assets created for the managed function.
         cleanup_function_assets(is_positive_mf, session.bqclient, ignore_failures=False)

tests/system/large/functions/test_remote_function.py

@@ -2933,7 +2933,7 @@ def func_for_other(x):
 
 
 @pytest.mark.flaky(retries=2, delay=120)
-def test_remote_function_series_where(session, dataset_id, scalars_dfs):
+def test_remote_function_series_where_mask(session, dataset_id, scalars_dfs):
     try:
 
         def _ten_times(x):
@@ -2954,8 +2954,8 @@ def _ten_times(x):
         pd_int64 = scalars_pandas["float64_col"]
         pd_int64_filtered = pd_int64.dropna()
 
-        # The cond is not a callable and the other is a callable (remote
-        # function) in series.where method.
+        # Test series.where method: the cond is not a callable and the other is
+        # a callable (remote function).
         bf_result = bf_int64_filtered.where(
             cond=bf_int64_filtered < 0, other=ten_times_mf
         ).to_pandas()
@@ -2966,6 +2966,16 @@ def _ten_times(x):
         # Ignore any dtype difference.
         pandas.testing.assert_series_equal(bf_result, pd_result, check_dtype=False)
 
+        # Test series.mask method: the cond is not a callable and the other is
+        # a callable (remote function).
+        bf_result = bf_int64_filtered.mask(
+            cond=bf_int64_filtered < 0, other=ten_times_mf
+        ).to_pandas()
+        pd_result = pd_int64_filtered.mask(cond=pd_int64_filtered < 0, other=_ten_times)
+
+        # Ignore any dtype difference.
+        pandas.testing.assert_series_equal(bf_result, pd_result, check_dtype=False)
+
     finally:
         # Clean up the gcp assets created for the remote function.
         cleanup_function_assets(ten_times_mf, session.bqclient, ignore_failures=False)

tests/system/small/test_series.py

@@ -3603,6 +3603,26 @@ def test_mask_custom_value(scalars_dfs):
     assert_pandas_df_equal(bf_result, pd_result)
 
 
+def test_mask_with_callable(scalars_df_index, scalars_pandas_df_index):
+    def _ten_times(x):
+        return x * 10
+
+    # Both cond and other are callable.
+    bf_result = (
+        scalars_df_index["int64_col"]
+        .mask(cond=lambda x: x > 0, other=_ten_times)
+        .to_pandas()
+    )
+    pd_result = scalars_pandas_df_index["int64_col"].mask(
+        cond=lambda x: x > 0, other=_ten_times
+    )
+
+    pd.testing.assert_series_equal(
+        bf_result,
+        pd_result,
+    )
+
+
 @pytest.mark.parametrize(
     ("lambda_",),
     [