BUG: generate proper code for custom aggregation func (#428)

python/xorbits/_mars/dataframe/groupby/tests/test_groupby_execution.py

@@ -1674,8 +1674,7 @@ def test_gpu_groupby_size(data_type, chunked, as_index, sort, setup_gpu):
         pd.testing.assert_series_equal(expected, actual)
 
 
-# TODO: support cuda
-# @support_cuda
+@support_cuda
 @pytest.mark.parametrize(
     "as_index",
     [True, False],
@@ -1706,16 +1705,78 @@ def g3(x):
         df.groupby("a", as_index=False).agg((g1, g2, g3)),
         mdf.groupby("a", as_index=False).agg((g1, g2, g3)).execute().fetch(),
     )
-    pd.testing.assert_frame_equal(
-        df.groupby("a", as_index=as_index).agg((g1, g1)),
-        mdf.groupby("a", as_index=as_index).agg((g1, g1)).execute().fetch(),
-    )
+    if not gpu:
+        # cuDF doesn't support having multiple columns with same names yet.
+        pd.testing.assert_frame_equal(
+            df.groupby("a", as_index=as_index).agg((g1, g1)),
+            mdf.groupby("a", as_index=as_index).agg((g1, g1)).execute().fetch(),
+        )
 
     pd.testing.assert_frame_equal(
         df.groupby("a", as_index=as_index)["b"].agg((g1, g2, g3)),
         mdf.groupby("a", as_index=as_index)["b"].agg((g1, g2, g3)).execute().fetch(),
     )
+    if not gpu:
+        # cuDF doesn't support having multiple columns with same names yet.
+        pd.testing.assert_frame_equal(
+            df.groupby("a", as_index=as_index)["b"].agg((g1, g1)),
+            mdf.groupby("a", as_index=as_index)["b"].agg((g1, g1)).execute().fetch(),
+        )
+
+
+@support_cuda
+def test_groupby_agg_on_custom_funcs(setup_gpu, gpu):
+    rs = np.random.RandomState(0)
+    df = pd.DataFrame(
+        {
+            "a": rs.choice(["foo", "bar", "baz"], size=100),
+            "b": rs.choice(["foo", "bar", "baz"], size=100),
+            "c": rs.choice(["foo", "bar", "baz"], size=100),
+        },
+    )
+
+    mdf = md.DataFrame(df, chunk_size=34, gpu=gpu)
+
+    def g1(x):
+        return ("foo" == x).sum()
+
+    def g2(x):
+        return ("foo" != x).sum()
+
+    def g3(x):
+        return (x > "bar").sum()
+
+    def g4(x):
+        return (x >= "bar").sum()
+
+    def g5(x):
+        return (x < "baz").sum()
+
+    def g6(x):
+        return (x <= "baz").sum()
+
     pd.testing.assert_frame_equal(
-        df.groupby("a", as_index=as_index)["b"].agg((g1, g1)),
-        mdf.groupby("a", as_index=as_index)["b"].agg((g1, g1)).execute().fetch(),
+        df.groupby("a", as_index=False).agg(
+            (
+                g1,
+                g2,
+                g3,
+                g4,
+                g5,
+                g6,
+            )
+        ),
+        mdf.groupby("a", as_index=False)
+        .agg(
+            (
+                g1,
+                g2,
+                g3,
+                g4,
+                g5,
+                g6,
+            )
+        )
+        .execute()
+        .fetch(),
     )

python/xorbits/_mars/dataframe/reduction/core.py

@@ -1164,6 +1164,24 @@ def _interpret_var(v):
                     axis_expr = f"axis={op_axis!r}, " if op_axis is not None else ""
                     op_str = _func_name_to_op[func_name]
                     if t.op.lhs is t.inputs[0]:
+                        if (
+                            (
+                                func_name
+                                in (
+                                    "gt",
+                                    "ge",
+                                    "lt",
+                                    "le",
+                                    "eq",
+                                    "ne",
+                                )
+                            )
+                            and isinstance(t.op.lhs, DATAFRAME_TYPE)
+                            and isinstance(t.op.rhs, str)
+                        ):
+                            # for a cudf dataframe, df == 'foo' doesn't work, so we convert the rhs
+                            # to a tuple.
+                            rhs = f"({rhs},) * len({lhs}.columns)"
                         statements = [
                             f"try:",
                             f"    {var_name} = {lhs}.{func_name}({rhs}, {axis_expr})",