COMPAT: 32-bit compat for testing of indexers

xref pandas-dev#16826

pandas/core/indexes/category.py

@@ -497,7 +497,6 @@ def get_indexer(self, target, method=None, limit=None, tolerance=None):
                 codes = self.categories.get_indexer(target)
 
         indexer, _ = self._engine.get_indexer_non_unique(codes)
-
         return _ensure_platform_int(indexer)
 
     @Appender(_index_shared_docs['get_indexer_non_unique'] % _index_doc_kwargs)
@@ -508,7 +507,8 @@ def get_indexer_non_unique(self, target):
             target = target.categories
 
         codes = self.categories.get_indexer(target)
-        return self._engine.get_indexer_non_unique(codes)
+        indexer, missing = self._engine.get_indexer_non_unique(codes)
+        return _ensure_platform_int(indexer), missing
 
     @Appender(_index_shared_docs['_convert_scalar_indexer'])
     def _convert_scalar_indexer(self, key, kind=None):

pandas/tests/indexes/common.py

@@ -132,6 +132,20 @@ def test_reindex_base(self):
         with tm.assert_raises_regex(ValueError, 'Invalid fill method'):
             idx.get_indexer(idx, method='invalid')
 
+    def test_get_indexer_consistency(self):
+        # See GH 16819
+        for name, index in self.indices.items():
+            if isinstance(index, IntervalIndex):
+                continue
+
+            indexer = index.get_indexer(index[0:2])
+            assert isinstance(indexer, np.ndarray)
+            assert indexer.dtype == np.int_
+
+            indexer, _ = index.get_indexer_non_unique(index[0:2])
+            assert isinstance(indexer, np.ndarray)
+            assert indexer.dtype == np.int_
+
     def test_ndarray_compat_properties(self):
         idx = self.create_index()
         assert idx.T.equals(idx)

pandas/tests/indexes/test_base.py

@@ -1131,17 +1131,6 @@ def test_get_indexer_strings(self):
         with pytest.raises(TypeError):
             idx.get_indexer(['a', 'b', 'c', 'd'], method='pad', tolerance=2)
 
-    def test_get_indexer_consistency(self):
-        # See GH 16819
-        for name, index in self.indices.items():
-            indexer = index.get_indexer(index[0:2])
-            assert isinstance(indexer, np.ndarray)
-            assert indexer.dtype == np.intp
-
-            indexer, _ = index.get_indexer_non_unique(index[0:2])
-            assert isinstance(indexer, np.ndarray)
-            assert indexer.dtype == np.intp
-
     def test_get_loc(self):
         idx = pd.Index([0, 1, 2])
         all_methods = [None, 'pad', 'backfill', 'nearest']