|  | from test import support, seq_tests | 
|  | import unittest | 
|  |  | 
|  | import gc | 
|  | import pickle | 
|  |  | 
|  | class TupleTest(seq_tests.CommonTest): | 
|  | type2test = tuple | 
|  |  | 
|  | def test_getitem_error(self): | 
|  | msg = "tuple indices must be integers or slices" | 
|  | with self.assertRaisesRegex(TypeError, msg): | 
|  | ()['a'] | 
|  |  | 
|  | def test_constructors(self): | 
|  | super().test_constructors() | 
|  | # calling built-in types without argument must return empty | 
|  | self.assertEqual(tuple(), ()) | 
|  | t0_3 = (0, 1, 2, 3) | 
|  | t0_3_bis = tuple(t0_3) | 
|  | self.assertTrue(t0_3 is t0_3_bis) | 
|  | self.assertEqual(tuple([]), ()) | 
|  | self.assertEqual(tuple([0, 1, 2, 3]), (0, 1, 2, 3)) | 
|  | self.assertEqual(tuple(''), ()) | 
|  | self.assertEqual(tuple('spam'), ('s', 'p', 'a', 'm')) | 
|  | self.assertEqual(tuple(x for x in range(10) if x % 2), | 
|  | (1, 3, 5, 7, 9)) | 
|  |  | 
|  | def test_keyword_args(self): | 
|  | with self.assertRaisesRegex(TypeError, 'keyword argument'): | 
|  | tuple(sequence=()) | 
|  |  | 
|  | def test_truth(self): | 
|  | super().test_truth() | 
|  | self.assertTrue(not ()) | 
|  | self.assertTrue((42, )) | 
|  |  | 
|  | def test_len(self): | 
|  | super().test_len() | 
|  | self.assertEqual(len(()), 0) | 
|  | self.assertEqual(len((0,)), 1) | 
|  | self.assertEqual(len((0, 1, 2)), 3) | 
|  |  | 
|  | def test_iadd(self): | 
|  | super().test_iadd() | 
|  | u = (0, 1) | 
|  | u2 = u | 
|  | u += (2, 3) | 
|  | self.assertTrue(u is not u2) | 
|  |  | 
|  | def test_imul(self): | 
|  | super().test_imul() | 
|  | u = (0, 1) | 
|  | u2 = u | 
|  | u *= 3 | 
|  | self.assertTrue(u is not u2) | 
|  |  | 
|  | def test_tupleresizebug(self): | 
|  | # Check that a specific bug in _PyTuple_Resize() is squashed. | 
|  | def f(): | 
|  | for i in range(1000): | 
|  | yield i | 
|  | self.assertEqual(list(tuple(f())), list(range(1000))) | 
|  |  | 
|  | def test_hash(self): | 
|  | # See SF bug 942952:  Weakness in tuple hash | 
|  | # The hash should: | 
|  | #      be non-commutative | 
|  | #      should spread-out closely spaced values | 
|  | #      should not exhibit cancellation in tuples like (x,(x,y)) | 
|  | #      should be distinct from element hashes:  hash(x)!=hash((x,)) | 
|  | # This test exercises those cases. | 
|  | # For a pure random hash and N=50, the expected number of occupied | 
|  | #      buckets when tossing 252,600 balls into 2**32 buckets | 
|  | #      is 252,592.6, or about 7.4 expected collisions.  The | 
|  | #      standard deviation is 2.73.  On a box with 64-bit hash | 
|  | #      codes, no collisions are expected.  Here we accept no | 
|  | #      more than 15 collisions.  Any worse and the hash function | 
|  | #      is sorely suspect. | 
|  |  | 
|  | N=50 | 
|  | base = list(range(N)) | 
|  | xp = [(i, j) for i in base for j in base] | 
|  | inps = base + [(i, j) for i in base for j in xp] + \ | 
|  | [(i, j) for i in xp for j in base] + xp + list(zip(base)) | 
|  | collisions = len(inps) - len(set(map(hash, inps))) | 
|  | self.assertTrue(collisions <= 15) | 
|  |  | 
|  | def test_repr(self): | 
|  | l0 = tuple() | 
|  | l2 = (0, 1, 2) | 
|  | a0 = self.type2test(l0) | 
|  | a2 = self.type2test(l2) | 
|  |  | 
|  | self.assertEqual(str(a0), repr(l0)) | 
|  | self.assertEqual(str(a2), repr(l2)) | 
|  | self.assertEqual(repr(a0), "()") | 
|  | self.assertEqual(repr(a2), "(0, 1, 2)") | 
|  |  | 
|  | def _not_tracked(self, t): | 
|  | # Nested tuples can take several collections to untrack | 
|  | gc.collect() | 
|  | gc.collect() | 
|  | self.assertFalse(gc.is_tracked(t), t) | 
|  |  | 
|  | def _tracked(self, t): | 
|  | self.assertTrue(gc.is_tracked(t), t) | 
|  | gc.collect() | 
|  | gc.collect() | 
|  | self.assertTrue(gc.is_tracked(t), t) | 
|  |  | 
|  | @support.cpython_only | 
|  | def test_track_literals(self): | 
|  | # Test GC-optimization of tuple literals | 
|  | x, y, z = 1.5, "a", [] | 
|  |  | 
|  | self._not_tracked(()) | 
|  | self._not_tracked((1,)) | 
|  | self._not_tracked((1, 2)) | 
|  | self._not_tracked((1, 2, "a")) | 
|  | self._not_tracked((1, 2, (None, True, False, ()), int)) | 
|  | self._not_tracked((object(),)) | 
|  | self._not_tracked(((1, x), y, (2, 3))) | 
|  |  | 
|  | # Tuples with mutable elements are always tracked, even if those | 
|  | # elements are not tracked right now. | 
|  | self._tracked(([],)) | 
|  | self._tracked(([1],)) | 
|  | self._tracked(({},)) | 
|  | self._tracked((set(),)) | 
|  | self._tracked((x, y, z)) | 
|  |  | 
|  | def check_track_dynamic(self, tp, always_track): | 
|  | x, y, z = 1.5, "a", [] | 
|  |  | 
|  | check = self._tracked if always_track else self._not_tracked | 
|  | check(tp()) | 
|  | check(tp([])) | 
|  | check(tp(set())) | 
|  | check(tp([1, x, y])) | 
|  | check(tp(obj for obj in [1, x, y])) | 
|  | check(tp(set([1, x, y]))) | 
|  | check(tp(tuple([obj]) for obj in [1, x, y])) | 
|  | check(tuple(tp([obj]) for obj in [1, x, y])) | 
|  |  | 
|  | self._tracked(tp([z])) | 
|  | self._tracked(tp([[x, y]])) | 
|  | self._tracked(tp([{x: y}])) | 
|  | self._tracked(tp(obj for obj in [x, y, z])) | 
|  | self._tracked(tp(tuple([obj]) for obj in [x, y, z])) | 
|  | self._tracked(tuple(tp([obj]) for obj in [x, y, z])) | 
|  |  | 
|  | @support.cpython_only | 
|  | def test_track_dynamic(self): | 
|  | # Test GC-optimization of dynamically constructed tuples. | 
|  | self.check_track_dynamic(tuple, False) | 
|  |  | 
|  | @support.cpython_only | 
|  | def test_track_subtypes(self): | 
|  | # Tuple subtypes must always be tracked | 
|  | class MyTuple(tuple): | 
|  | pass | 
|  | self.check_track_dynamic(MyTuple, True) | 
|  |  | 
|  | @support.cpython_only | 
|  | def test_bug7466(self): | 
|  | # Trying to untrack an unfinished tuple could crash Python | 
|  | self._not_tracked(tuple(gc.collect() for i in range(101))) | 
|  |  | 
|  | def test_repr_large(self): | 
|  | # Check the repr of large list objects | 
|  | def check(n): | 
|  | l = (0,) * n | 
|  | s = repr(l) | 
|  | self.assertEqual(s, | 
|  | '(' + ', '.join(['0'] * n) + ')') | 
|  | check(10)       # check our checking code | 
|  | check(1000000) | 
|  |  | 
|  | def test_iterator_pickle(self): | 
|  | # Userlist iterators don't support pickling yet since | 
|  | # they are based on generators. | 
|  | data = self.type2test([4, 5, 6, 7]) | 
|  | for proto in range(pickle.HIGHEST_PROTOCOL + 1): | 
|  | itorg = iter(data) | 
|  | d = pickle.dumps(itorg, proto) | 
|  | it = pickle.loads(d) | 
|  | self.assertEqual(type(itorg), type(it)) | 
|  | self.assertEqual(self.type2test(it), self.type2test(data)) | 
|  |  | 
|  | it = pickle.loads(d) | 
|  | next(it) | 
|  | d = pickle.dumps(it, proto) | 
|  | self.assertEqual(self.type2test(it), self.type2test(data)[1:]) | 
|  |  | 
|  | def test_reversed_pickle(self): | 
|  | data = self.type2test([4, 5, 6, 7]) | 
|  | for proto in range(pickle.HIGHEST_PROTOCOL + 1): | 
|  | itorg = reversed(data) | 
|  | d = pickle.dumps(itorg, proto) | 
|  | it = pickle.loads(d) | 
|  | self.assertEqual(type(itorg), type(it)) | 
|  | self.assertEqual(self.type2test(it), self.type2test(reversed(data))) | 
|  |  | 
|  | it = pickle.loads(d) | 
|  | next(it) | 
|  | d = pickle.dumps(it, proto) | 
|  | self.assertEqual(self.type2test(it), self.type2test(reversed(data))[1:]) | 
|  |  | 
|  | def test_no_comdat_folding(self): | 
|  | # Issue 8847: In the PGO build, the MSVC linker's COMDAT folding | 
|  | # optimization causes failures in code that relies on distinct | 
|  | # function addresses. | 
|  | class T(tuple): pass | 
|  | with self.assertRaises(TypeError): | 
|  | [3,] + T((1,2)) | 
|  |  | 
|  | def test_lexicographic_ordering(self): | 
|  | # Issue 21100 | 
|  | a = self.type2test([1, 2]) | 
|  | b = self.type2test([1, 2, 0]) | 
|  | c = self.type2test([1, 3]) | 
|  | self.assertLess(a, b) | 
|  | self.assertLess(b, c) | 
|  |  | 
|  | if __name__ == "__main__": | 
|  | unittest.main() |