indicate when similarity matrix computation is done

surprise/prediction_algorithms/algo_base.py

@@ -239,9 +239,11 @@ def compute_similarities(self):
 
             args += [self.trainset.global_mean, bx, by, shrinkage]
 
-        print('Computing the {0} similarity matrix...'.format(name))
         try:
-            return construction_func[name](*args)
+            print('Computing the {0} similarity matrix...'.format(name))
+            sim = construction_func[name](*args)
+            print('Done computing similarity matrix.')
+            return sim
         except KeyError:
             raise NameError('Wrong sim name ' + name + '. Allowed values ' +
                             'are ' + ', '.join(construction_func.keys()) + '.')

surprise/prediction_algorithms/knns.py

@@ -20,7 +20,7 @@ class SymmetricAlgo(AlgoBase):
     """This is an abstract class aimed to ease the use of symmetric algorithms.
 
     A symmetric algorithm is an algorithm that can can be based on users or on
-    items indiferently, e.g. all the algorithms in this module.
+    items indifferently, e.g. all the algorithms in this module.
 
     When the algo is user-based x denotes a user and y an item. Else, it's
     reversed.