BUG: Series.is_unique has extra output if contains objects with __ne__ defined

doc/source/whatsnew/v0.23.0.txt

@@ -1068,6 +1068,7 @@ Indexing
 - Bug in :meth:`Index.difference` when taking difference of an ``Index`` with itself (:issue:`20040`)
 - Bug in :meth:`DataFrame.first_valid_index` and :meth:`DataFrame.last_valid_index` in presence of entire rows of NaNs in the middle of values (:issue:`20499`).
 - Bug in :class:`IntervalIndex` where some indexing operations were not supported for overlapping or non-monotonic ``uint64`` data (:issue:`20636`)
+- Bug in ``Series.is_unique`` where extraneous output in stderr is shown if Series contains objects with ``__ne__`` defined (:issue:`20661`)
 
 MultiIndex
 ^^^^^^^^^^

pandas/_libs/hashtable.pyx

@@ -39,7 +39,6 @@ from khash cimport (
     kh_put_pymap, kh_resize_pymap)
 
 
-from util cimport _checknan
 cimport util
 
 from missing cimport checknull

pandas/_libs/hashtable_class_helper.pxi.in

@@ -870,7 +870,7 @@ cdef class PyObjectHashTable(HashTable):
         for i in range(n):
             val = values[i]
             hash(val)
-            if not _checknan(val):
+            if not checknull(val):
                 k = kh_get_pymap(self.table, <PyObject*>val)
                 if k == self.table.n_buckets:
                     kh_put_pymap(self.table, <PyObject*>val, &ret)

pandas/_libs/src/util.pxd

@@ -159,8 +159,5 @@ cdef inline bint _checknull(object val):
     except ValueError:
         return False
 
-cdef inline bint _checknan(object val):
-    return not cnp.PyArray_Check(val) and val != val
-
 cdef inline bint is_period_object(object val):
     return getattr(val, '_typ', '_typ') == 'period'

pandas/tests/series/test_analytics.py

@@ -1594,6 +1594,22 @@ def test_is_unique(self):
         s = Series(np.arange(1000))
         assert s.is_unique
 
+    def test_is_unique_class_ne(self, capsys):
+        # GH 20661
+        class Foo(object):
+            def __init__(self, val):
+                self._value = val
+
+            def __ne__(self, other):
+                raise Exception("NEQ not supported")
+
+        li = [Foo(i) for i in range(5)]
+        s = pd.Series(li, index=[i for i in range(5)])
+        _, err = capsys.readouterr()
+        s.is_unique
+        _, err = capsys.readouterr()
+        assert len(err) == 0
+
     def test_is_monotonic(self):
 
         s = Series(np.random.randint(0, 10, size=1000))