pep8 linting (whitespaces)

W191 indentation contains tabs
E221 multiple spaces before operator
E222 multiple spaces after operator
E225 missing whitespace around operator
E271 multiple spaces after keyword
W292 no newline at end of file
W293 blank line contains whitespace
W391 blank line at end of file

1 files changed, 20 insertions, 20 deletions

diff --git a/git/test/performance/test_utils.py b/git/test/performance/test_utils.py
index 8637af48..7de77970 100644
--- a/git/test/performance/test_utils.py
+++ b/git/test/performance/test_utils.py
@@ -9,29 +9,29 @@ from lib import (
 
 
 class TestUtilPerformance(TestBigRepoR):
-    
+
     def test_access(self):
         # compare dict vs. slot access
         class Slotty(object):
             __slots__ = "attr"
             def __init__(self):
                 self.attr = 1
-                
+
         class Dicty(object):
             def __init__(self):
                 self.attr = 1
-                
+
         class BigSlotty(object):
             __slots__ = ('attr', ) + tuple('abcdefghijk')
             def __init__(self):
                 for attr in self.__slots__:
                     setattr(self, attr, 1)
-                    
+
         class BigDicty(object):
             def __init__(self):
                 for attr in BigSlotty.__slots__:
                     setattr(self, attr, 1)
-        
+
         ni = 1000000
         for cls in (Slotty, Dicty, BigSlotty, BigDicty):
             cli = cls()
@@ -42,7 +42,7 @@ class TestUtilPerformance(TestBigRepoR):
             elapsed = time() - st
             print >> sys.stderr, "Accessed %s.attr %i times in %s s ( %f acc / s)" % (cls.__name__, ni, elapsed, ni / elapsed)
         # END for each class type
-        
+
         # check num of sequence-acceses
         for cls in (list, tuple):
             x = 10
@@ -57,7 +57,7 @@ class TestUtilPerformance(TestBigRepoR):
             na = ni * 3
             print >> sys.stderr, "Accessed %s[x] %i times in %s s ( %f acc / s)" % (cls.__name__, na, elapsed, na / elapsed)
         # END for each sequence 
-        
+
     def test_instantiation(self):
         ni = 100000
         max_num_items = 4
@@ -83,7 +83,7 @@ class TestUtilPerformance(TestBigRepoR):
                 print >> sys.stderr, "Created %i %ss of size %i in %f s ( %f inst / s)" % (ni, cls.__name__, mni, elapsed, ni / elapsed)
             # END for each type
         # END for each item count
-        
+
         # tuple and tuple direct
         st = time()
         for i in xrange(ni):
@@ -91,19 +91,19 @@ class TestUtilPerformance(TestBigRepoR):
         # END for each item
         elapsed = time() - st
         print >> sys.stderr, "Created %i tuples (1,2,3,4) in %f s ( %f tuples / s)" % (ni, elapsed, ni / elapsed)
-        
+
         st = time()
         for i in xrange(ni):
             t = tuple((1,2,3,4))
         # END for each item
         elapsed = time() - st
         print >> sys.stderr, "Created %i tuples tuple((1,2,3,4)) in %f s ( %f tuples / s)" % (ni, elapsed, ni / elapsed)
-        
+
     def test_unpacking_vs_indexing(self):
         ni = 1000000
         list_items = [1,2,3,4]
         tuple_items = (1,2,3,4)
-        
+
         for sequence in (list_items, tuple_items):
             st = time()
             for i in xrange(ni):
@@ -111,14 +111,14 @@ class TestUtilPerformance(TestBigRepoR):
             # END for eac iteration
             elapsed = time() - st
             print >> sys.stderr, "Unpacked %i %ss of size %i in %f s ( %f acc / s)" % (ni, type(sequence).__name__, len(sequence), elapsed, ni / elapsed)
-            
+
             st = time()
             for i in xrange(ni):
                 one, two, three, four = sequence[0], sequence[1], sequence[2], sequence[3]
             # END for eac iteration
             elapsed = time() - st
             print >> sys.stderr, "Unpacked %i %ss of size %i individually in %f s ( %f acc / s)" % (ni, type(sequence).__name__, len(sequence), elapsed, ni / elapsed)
-            
+
             st = time()
             for i in xrange(ni):
                 one, two = sequence[0], sequence[1]
@@ -126,14 +126,14 @@ class TestUtilPerformance(TestBigRepoR):
             elapsed = time() - st
             print >> sys.stderr, "Unpacked %i %ss of size %i individually (2 of 4) in %f s ( %f acc / s)" % (ni, type(sequence).__name__, len(sequence), elapsed, ni / elapsed)
         # END for each sequence
-        
+
     def test_large_list_vs_iteration(self):
         # what costs more: alloc/realloc of lists, or the cpu strain of iterators ?
         def slow_iter(ni):
             for i in xrange(ni):
                 yield i
         # END slow iter - be closer to the real world
-        
+
         # alloc doesn't play a role here it seems 
         for ni in (500, 1000, 10000, 20000, 40000):
             st = time()
@@ -142,7 +142,7 @@ class TestUtilPerformance(TestBigRepoR):
             # END for each item
             elapsed = time() - st
             print >> sys.stderr, "Iterated %i items from list in %f s ( %f acc / s)" % (ni, elapsed, ni / elapsed)
-            
+
             st = time()
             for i in slow_iter(ni):
                 i
@@ -150,14 +150,14 @@ class TestUtilPerformance(TestBigRepoR):
             elapsed = time() - st
             print >> sys.stderr, "Iterated %i items from iterator in %f s ( %f acc / s)" % (ni, elapsed, ni / elapsed)
         # END for each number of iterations
-        
+
     def test_type_vs_inst_class(self):
         class NewType(object):
             pass
-        
+
         # lets see which way is faster
         inst = NewType()
-        
+
         ni = 1000000
         st = time()
         for i in xrange(ni):
@@ -165,7 +165,7 @@ class TestUtilPerformance(TestBigRepoR):
         # END for each item
         elapsed = time() - st
         print >> sys.stderr, "Created %i items using inst.__class__ in %f s ( %f items / s)" % (ni, elapsed, ni / elapsed)
-        
+
         st = time()
         for i in xrange(ni):
             type(inst)()