Use monkeypatch.setattr to unpatch

python/cudf/cudf/pandas/fast_slow_proxy.py

@@ -26,9 +26,8 @@
 
 import numpy as np
 
-from cudf.testing._utils import assert_eq
-
 from ..options import _env_get_bool
+from ..testing._utils import assert_eq
 from .annotation import nvtx
 
 
@@ -890,7 +889,7 @@ def __name__(self, value):
 
 def _assert_fast_slow_eq(left, right, **kwargs):
     assert_func = kwargs.get("assert_func", assert_eq)
-    if _is_final_type(type(left)) or (type(left) in NUMPY_TYPES):
+    if _is_final_type(type(left)) or type(left) in NUMPY_TYPES:
         assert_func(left, right)
 
 

python/cudf/cudf_pandas_tests/test_cudf_pandas.py

@@ -40,7 +40,7 @@
     get_calendar,
 )
 
-# Accelerated pandas has the real pandas and cudf modules as an attributes
+# Accelerated pandas has the real pandas and cudf modules as attributes
 pd = xpd._fsproxy_slow
 cudf = xpd._fsproxy_fast
 
@@ -1425,45 +1425,56 @@ def test_holidays_within_dates(holiday, start, expected):
 
 
 def test_cudf_pandas_debugging_different_results(monkeypatch):
-    def mock_mean(self, *args, **kwargs):
+    cudf_mean = cudf.Series.mean
+
+    def mock_mean_one(self, *args, **kwargs):
         return np.float64(1.0)
 
     with monkeypatch.context() as monkeycontext:
-        monkeycontext.setattr(cudf.Series, "mean", mock_mean)
+        monkeypatch.setattr(xpd.Series.mean, "_fsproxy_fast", mock_mean_one)
         monkeycontext.setenv("CUDF_PANDAS_DEBUGGING", "True")
         s = xpd.Series([1, 2])
         with pytest.warns(
             UserWarning,
             match="The results from cudf and pandas were different.",
         ):
-            assert s.mean() == np.float64(1.0)
+            assert s.mean() == 1.0
+    monkeypatch.setattr(xpd.Series.mean, "_fsproxy_fast", cudf_mean)
 
 
 def test_cudf_pandas_debugging_pandas_error(monkeypatch):
-    def mock_median(self, *args, **kwargs):
+    pd_mean = pd.Series.mean
+
+    def mock_mean_exception(self, *args, **kwargs):
         raise Exception()
 
     with monkeypatch.context() as monkeycontext:
-        monkeycontext.setattr(pd.Series, "median", mock_median)
+        monkeycontext.setattr(
+            xpd.Series.mean, "_fsproxy_slow", mock_mean_exception
+        )
         monkeycontext.setenv("CUDF_PANDAS_DEBUGGING", "True")
         s = xpd.Series([1, 2])
         with pytest.warns(
             UserWarning,
             match="The result from pandas could not be computed.",
         ):
-            assert s.median() == 1.5
+            assert s.mean() == 1.5
+    monkeypatch.setattr(xpd.Series.mean, "_fsproxy_slow", pd_mean)
 
 
 def test_cudf_pandas_debugging_failed(monkeypatch):
-    def mock_std(self, *args, **kwargs):
+    pd_mean = pd.Series.mean
+
+    def mock_mean_none(self, *args, **kwargs):
         return None
 
     with monkeypatch.context() as monkeycontext:
-        monkeycontext.setattr(pd.Series, "std", mock_std)
+        monkeycontext.setattr(xpd.Series.mean, "_fsproxy_slow", mock_mean_none)
         monkeycontext.setenv("CUDF_PANDAS_DEBUGGING", "True")
         s = xpd.Series([1, 2])
         with pytest.warns(
             UserWarning,
             match="Pandas debugging mode failed.",
         ):
-            assert s.std() == 0.7071067811865476
+            assert s.mean() == 1.5
+    monkeypatch.setattr(xpd.Series.mean, "_fsproxy_slow", pd_mean)