BUG: avoid unnecessary casting in CategoricalIndex.reindex

pandas/core/indexes/category.py

@@ -399,9 +399,9 @@ def reindex(
             indexer = None
             missing = np.array([], dtype=np.intp)
         else:
-            indexer, missing = self.get_indexer_non_unique(np.array(target))
+            indexer, missing = self.get_indexer_non_unique(target)
 
-        if len(self.codes) and indexer is not None:
+        if len(self) and indexer is not None:
             new_target = self.take(indexer)
         else:
             new_target = target
@@ -410,10 +410,8 @@ def reindex(
         if len(missing):
             cats = self.categories.get_indexer(target)
 
-            if not isinstance(cats, CategoricalIndex) or (cats == -1).any():
-                # coerce to a regular index here!
-                result = Index(np.array(self), name=self.name)
-                new_target, indexer, _ = result._reindex_non_unique(target)
+            if not isinstance(target, CategoricalIndex) or (cats == -1).any():
+                new_target, indexer, _ = super()._reindex_non_unique(target)
             else:
 
                 codes = new_target.codes.copy()
@@ -426,11 +424,12 @@ def reindex(
         # coerce based on the actual values, only on the dtype)
         # unless we had an initial Categorical to begin with
         # in which case we are going to conform to the passed Categorical
-        new_target = np.asarray(new_target)
         if is_categorical_dtype(target):
             cat = Categorical(new_target, dtype=target.dtype)
             new_target = type(self)._simple_new(cat, name=self.name)
         else:
+            # e.g. test_reindex_with_categoricalindex, test_reindex_duplicate_target
+            new_target = np.asarray(new_target)
             new_target = Index(new_target, name=self.name)
 
         return new_target, indexer