diff options
Diffstat (limited to 'git/test/performance/test_utils.py')
| -rw-r--r-- | git/test/performance/test_utils.py | 330 |
1 files changed, 165 insertions, 165 deletions
diff --git a/git/test/performance/test_utils.py b/git/test/performance/test_utils.py index 19c1e84a..8637af48 100644 --- a/git/test/performance/test_utils.py +++ b/git/test/performance/test_utils.py @@ -4,171 +4,171 @@ import sys import stat from lib import ( - TestBigRepoR - ) + TestBigRepoR + ) 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() - st = time() - for i in xrange(ni): - cli.attr - # END for each access - 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 - st = time() - s = cls(range(x)) - for i in xrange(ni): - s[0] - s[1] - s[2] - # END for - elapsed = time() - st - 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 - for mni in range(max_num_items+1): - for cls in (tuple, list): - st = time() - for i in xrange(ni): - if mni == 0: - cls() - elif mni == 1: - cls((1,)) - elif mni == 2: - cls((1,2)) - elif mni == 3: - cls((1,2,3)) - elif mni == 4: - cls((1,2,3,4)) - else: - cls(x for x in xrange(mni)) - # END handle empty cls - # END for each item - elapsed = time() - st - 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): - t = (1,2,3,4) - # 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): - one, two, three, four = sequence - # 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] - # END for eac iteration - 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() - for i in list(xrange(ni)): - i - # 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 - # END for each item - 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): - inst.__class__() - # 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)() - # END for each item - elapsed = time() - st - print >> sys.stderr, "Created %i items using type(inst)() in %f s ( %f items / s)" % (ni, elapsed, ni / elapsed) + + 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() + st = time() + for i in xrange(ni): + cli.attr + # END for each access + 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 + st = time() + s = cls(range(x)) + for i in xrange(ni): + s[0] + s[1] + s[2] + # END for + elapsed = time() - st + 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 + for mni in range(max_num_items+1): + for cls in (tuple, list): + st = time() + for i in xrange(ni): + if mni == 0: + cls() + elif mni == 1: + cls((1,)) + elif mni == 2: + cls((1,2)) + elif mni == 3: + cls((1,2,3)) + elif mni == 4: + cls((1,2,3,4)) + else: + cls(x for x in xrange(mni)) + # END handle empty cls + # END for each item + elapsed = time() - st + 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): + t = (1,2,3,4) + # 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): + one, two, three, four = sequence + # 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] + # END for eac iteration + 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() + for i in list(xrange(ni)): + i + # 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 + # END for each item + 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): + inst.__class__() + # 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)() + # END for each item + elapsed = time() - st + print >> sys.stderr, "Created %i items using type(inst)() in %f s ( %f items / s)" % (ni, elapsed, ni / elapsed) |