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Þ'¯°ÌME[YéïĵÂCå½ Ué©Áû'Ê9%eÔðNU”ë‘ÌsD3/®+UI˜9h.WC”빓$#:pz:YÓ ¿xž* ³$Í +$kñAŠ‹†¢ Uê>¸)_š¬÷©ßAÂÔb9ÇU ¯¾á•9¯ÏÏ÷O÷¼¼Fähal1‰3Ì[Ïr•´UCksNÐ] R‘¸¥H+§Šé†c©vÖÞ0iÓ76s†î!§=ß ¼~Ô'°Ãmäoäš³ªøi1úÉ)³yV8 CLÄØÁ‘WYïi€H6ÖÑiámø^ÈY´°Ñ7¥Û*—Ñ©L«Qƒï—Ùrÿ ›£Ð*š¸ˆL©ˆ$ˆ ÷¾D§9È®«qbqC)–ˆïv´çñsÑVT­Ø, <àïºÀO«Jý·õ àfPìð .wFšir´þ’2_Y *Æ€x\« ì€9š@ Ž|F⇥ˆkZ@hÖÄ0t¿-<“‹qµ¾*ZL¤Ú)&BJpÓF5=$„at*Zš$’ÑtdûÝRI1 2Ž‰$€$I$#‰SÞ’Hë¬ï;Á$¡t$’`<(ñÇt)$‡Ð.Êf¢X’Kt=Éé$‚ˆªè¢oÝëòI%Rgcª÷ŠyI%¡‰ÿ !ñ)´õ $¤ Ô’IIGÿÙfrom test import support import random import unittest from functools import cmp_to_key verbose = support.verbose nerrors = 0 def check(tag, expected, raw, compare=None): global nerrors if verbose: print(" checking", tag) orig = raw[:] # save input in case of error if compare: raw.sort(key=cmp_to_key(compare)) else: raw.sort() if len(expected) != len(raw): print("error in", tag) print("length mismatch;", len(expected), len(raw)) print(expected) print(orig) print(raw) nerrors += 1 return for i, good in enumerate(expected): maybe = raw[i] if good is not maybe: print("error in", tag) print("out of order at index", i, good, maybe) print(expected) print(orig) print(raw) nerrors += 1 return class TestBase(unittest.TestCase): def testStressfully(self): # Try a variety of sizes at and around powers of 2, and at powers of 10. sizes = [0] for power in range(1, 10): n = 2 ** power sizes.extend(range(n-1, n+2)) sizes.extend([10, 100, 1000]) class Complains(object): maybe_complain = True def __init__(self, i): self.i = i def __lt__(self, other): if Complains.maybe_complain and random.random() < 0.001: if verbose: print(" complaining at", self, other) raise RuntimeError return self.i < other.i def __repr__(self): return "Complains(%d)" % self.i class Stable(object): def __init__(self, key, i): self.key = key self.index = i def __lt__(self, other): return self.key < other.key def __repr__(self): return "Stable(%d, %d)" % (self.key, self.index) for n in sizes: x = list(range(n)) if verbose: print("Testing size", n) s = x[:] check("identity", x, s) s = x[:] s.reverse() check("reversed", x, s) s = x[:] random.shuffle(s) check("random permutation", x, s) y = x[:] y.reverse() s = x[:] check("reversed via function", y, s, lambda a, b: (b>a)-(b= 2: def bad_key(x): raise RuntimeError s = x[:] self.assertRaises(RuntimeError, s.sort, key=bad_key) x = [Complains(i) for i in x] s = x[:] random.shuffle(s) Complains.maybe_complain = True it_complained = False try: s.sort() except RuntimeError: it_complained = True if it_complained: Complains.maybe_complain = False check("exception during sort left some permutation", x, s) s = [Stable(random.randrange(10), i) for i in range(n)] augmented = [(e, e.index) for e in s] augmented.sort() # forced stable because ties broken by index x = [e for e, i in augmented] # a stable sort of s check("stability", x, s) #============================================================================== class TestBugs(unittest.TestCase): def test_bug453523(self): # bug 453523 -- list.sort() crasher. # If this fails, the most likely outcome is a core dump. # Mutations during a list sort should raise a ValueError. class C: def __lt__(self, other): if L and random.random() < 0.75: L.pop() else: L.append(3) return random.random() < 0.5 L = [C() for i in range(50)] self.assertRaises(ValueError, L.sort) def test_undetected_mutation(self): # Python 2.4a1 did not always detect mutation memorywaster = [] for i in range(20): def mutating_cmp(x, y): L.append(3) L.pop() return (x > y) - (x < y) L = [1,2] self.assertRaises(ValueError, L.sort, key=cmp_to_key(mutating_cmp)) def mutating_cmp(x, y): L.append(3) del L[:] return (x > y) - (x < y) self.assertRaises(ValueError, L.sort, key=cmp_to_key(mutating_cmp)) memorywaster = [memorywaster] #============================================================================== class TestDecorateSortUndecorate(unittest.TestCase): def test_decorated(self): data = 'The quick Brown fox Jumped over The lazy Dog'.split() copy = data[:] random.shuffle(data) data.sort(key=str.lower) def my_cmp(x, y): xlower, ylower = x.lower(), y.lower() return (xlower > ylower) - (xlower < ylower) copy.sort(key=cmp_to_key(my_cmp)) def test_baddecorator(self): data = 'The quick Brown fox Jumped over The lazy Dog'.split() self.assertRaises(TypeError, data.sort, key=lambda x,y: 0) def test_stability(self): data = [(random.randrange(100), i) for i in range(200)] copy = data[:] data.sort(key=lambda t: t[0]) # sort on the random first field copy.sort() # sort using both fields self.assertEqual(data, copy) # should get the same result def test_key_with_exception(self): # Verify that the wrapper has been removed data = list(range(-2, 2)) dup = data[:] self.assertRaises(ZeroDivisionError, data.sort, key=lambda x: 1/x) self.assertEqual(data, dup) def test_key_with_mutation(self): data = list(range(10)) def k(x): del data[:] data[:] = range(20) return x self.assertRaises(ValueError, data.sort, key=k) def test_key_with_mutating_del(self): data = list(range(10)) class SortKiller(object): def __init__(self, x): pass def __del__(self): del data[:] data[:] = range(20) def __lt__(self, other): return id(self) < id(other) self.assertRaises(ValueError, data.sort, key=SortKiller) def test_key_with_mutating_del_and_exception(self): data = list(range(10)) ## dup = data[:] class SortKiller(object): def __init__(self, x): if x > 2: raise RuntimeError def __del__(self): del data[:] data[:] = list(range(20)) self.assertRaises(RuntimeError, data.sort, key=SortKiller) ## major honking subtlety: we *can't* do: ## ## self.assertEqual(data, dup) ## ## because there is a reference to a SortKiller in the ## traceback and by the time it dies we're outside the call to ## .sort() and so the list protection gimmicks are out of ## date (this cost some brain cells to figure out...). def test_reverse(self): data = list(range(100)) random.shuffle(data) data.sort(reverse=True) self.assertEqual(data, list(range(99,-1,-1))) def test_reverse_stability(self): data = [(random.randrange(100), i) for i in range(200)] copy1 = data[:] copy2 = data[:] def my_cmp(x, y): x0, y0 = x[0], y[0] return (x0 > y0) - (x0 < y0) def my_cmp_reversed(x, y): x0, y0 = x[0], y[0] return (y0 > x0) - (y0 < x0) data.sort(key=cmp_to_key(my_cmp), reverse=True) copy1.sort(key=cmp_to_key(my_cmp_reversed)) self.assertEqual(data, copy1) copy2.sort(key=lambda x: x[0], reverse=True) self.assertEqual(data, copy2) #============================================================================== def check_against_PyObject_RichCompareBool(self, L): ## The idea here is to exploit the fact that unsafe_tuple_compare uses ## PyObject_RichCompareBool for the second elements of tuples. So we have, ## for (most) L, sorted(L) == [y[1] for y in sorted([(0,x) for x in L])] ## This will work as long as __eq__ => not __lt__ for all the objects in L, ## which holds for all the types used below. ## ## Testing this way ensures that the optimized implementation remains consistent ## with the naive implementation, even if changes are made to any of the ## richcompares. ## ## This function tests sorting for three lists (it randomly shuffles each one): ## 1. L ## 2. [(x,) for x in L] ## 3. [((x,),) for x in L] random.seed(0) random.shuffle(L) L_1 = L[:] L_2 = [(x,) for x in L] L_3 = [((x,),) for x in L] for L in [L_1, L_2, L_3]: optimized = sorted(L) reference = [y[1] for y in sorted([(0,x) for x in L])] for (opt, ref) in zip(optimized, reference): self.assertIs(opt, ref) #note: not assertEqual! We want to ensure *identical* behavior. class TestOptimizedCompares(unittest.TestCase): def test_safe_object_compare(self): heterogeneous_lists = [[0, 'foo'], [0.0, 'foo'], [('foo',), 'foo']] for L in heterogeneous_lists: self.assertRaises(TypeError, L.sort) self.assertRaises(TypeError, [(x,) for x in L].sort) self.assertRaises(TypeError, [((x,),) for x in L].sort) float_int_lists = [[1,1.1], [1<<70,1.1], [1.1,1], [1.1,1<<70]] for L in float_int_lists: check_against_PyObject_RichCompareBool(self, L) def test_unsafe_object_compare(self): # This test is by ppperry. It ensures that unsafe_object_compare is # verifying ms->key_richcompare == tp->richcompare before comparing. class WackyComparator(int): def __lt__(self, other): elem.__class__ = WackyList2 return int.__lt__(self, other) class WackyList1(list): pass class WackyList2(list): def __lt__(self, other): raise ValueError L = [WackyList1([WackyComparator(i), i]) for i in range(10)] elem = L[-1] with self.assertRaises(ValueError): L.sort() L = [WackyList1([WackyComparator(i), i]) for i in range(10)] elem = L[-1] with self.assertRaises(ValueError): [(x,) for x in L].sort() # The following test is also by ppperry. It ensures that # unsafe_object_compare handles Py_NotImplemented appropriately. class PointlessComparator: def __lt__(self, other): return NotImplemented L = [PointlessComparator(), PointlessComparator()] self.assertRaises(TypeError, L.sort) self.assertRaises(TypeError, [(x,) for x in L].sort) # The following tests go through various types that would trigger # ms->key_compare = unsafe_object_compare lists = [list(range(100)) + [(1<<70)], [str(x) for x in range(100)] + ['\uffff'], [bytes(x) for x in range(100)], [cmp_to_key(lambda x,y: x (x,) < (x,) # # Note that we don't have to put anything in tuples here, because # the check function does a tuple test automatically. check_against_PyObject_RichCompareBool(self, [float('nan')]*100) check_against_PyObject_RichCompareBool(self, [float('nan') for _ in range(100)]) def test_not_all_tuples(self): self.assertRaises(TypeError, [(1.0, 1.0), (False, "A"), 6].sort) self.assertRaises(TypeError, [('a', 1), (1, 'a')].sort) self.assertRaises(TypeError, [(1, 'a'), ('a', 1)].sort) #============================================================================== if __name__ == "__main__": unittest.main()