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302 lines
11 KiB
Python
302 lines
11 KiB
Python
from test import support, seq_tests
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import unittest
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import gc
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import pickle
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class TupleTest(seq_tests.CommonTest):
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type2test = tuple
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def test_getitem_error(self):
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msg = "tuple indices must be integers or slices"
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with self.assertRaisesRegex(TypeError, msg):
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()['a']
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def test_constructors(self):
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super().test_constructors()
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# calling built-in types without argument must return empty
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self.assertEqual(tuple(), ())
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t0_3 = (0, 1, 2, 3)
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t0_3_bis = tuple(t0_3)
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self.assertTrue(t0_3 is t0_3_bis)
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self.assertEqual(tuple([]), ())
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self.assertEqual(tuple([0, 1, 2, 3]), (0, 1, 2, 3))
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self.assertEqual(tuple(''), ())
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self.assertEqual(tuple('spam'), ('s', 'p', 'a', 'm'))
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self.assertEqual(tuple(x for x in range(10) if x % 2),
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(1, 3, 5, 7, 9))
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def test_keyword_args(self):
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with self.assertRaisesRegex(TypeError, 'keyword argument'):
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tuple(sequence=())
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def test_truth(self):
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super().test_truth()
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self.assertTrue(not ())
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self.assertTrue((42, ))
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def test_len(self):
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super().test_len()
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self.assertEqual(len(()), 0)
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self.assertEqual(len((0,)), 1)
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self.assertEqual(len((0, 1, 2)), 3)
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def test_iadd(self):
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super().test_iadd()
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u = (0, 1)
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u2 = u
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u += (2, 3)
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self.assertTrue(u is not u2)
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def test_imul(self):
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super().test_imul()
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u = (0, 1)
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u2 = u
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u *= 3
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self.assertTrue(u is not u2)
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def test_tupleresizebug(self):
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# Check that a specific bug in _PyTuple_Resize() is squashed.
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def f():
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for i in range(1000):
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yield i
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self.assertEqual(list(tuple(f())), list(range(1000)))
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# Various tests for hashing of tuples to check that we get few collisions.
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#
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# Earlier versions of the tuple hash algorithm had collisions
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# reported at:
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# - https://bugs.python.org/issue942952
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# - https://bugs.python.org/issue34751
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#
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# Notes:
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# - The hash of tuples is deterministic: if the test passes once on a given
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# system, it will always pass. So the probabilities mentioned in the
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# test_hash functions below should be interpreted assuming that the
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# hashes are random.
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# - Due to the structure in the testsuite inputs, collisions are not
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# independent. For example, if hash((a,b)) == hash((c,d)), then also
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# hash((a,b,x)) == hash((c,d,x)). But the quoted probabilities assume
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# independence anyway.
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# - We limit the hash to 32 bits in the tests to have a good test on
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# 64-bit systems too. Furthermore, this is also a sanity check that the
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# lower 32 bits of a 64-bit hash are sufficiently random too.
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def test_hash1(self):
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# Check for hash collisions between small integers in range(50) and
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# certain tuples and nested tuples of such integers.
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N=50
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base = list(range(N))
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xp = [(i, j) for i in base for j in base]
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inps = base + [(i, j) for i in base for j in xp] + \
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[(i, j) for i in xp for j in base] + xp + list(zip(base))
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self.assertEqual(len(inps), 252600)
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hashes = set(hash(x) % 2**32 for x in inps)
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collisions = len(inps) - len(hashes)
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# For a pure random 32-bit hash and N = 252,600 test items, the
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# expected number of collisions equals
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#
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# 2**(-32) * N(N-1)/2 = 7.4
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#
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# We allow up to 15 collisions, which suffices to make the test
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# pass with 99.5% confidence.
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self.assertLessEqual(collisions, 15)
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def test_hash2(self):
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# Check for hash collisions between small integers (positive and
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# negative), tuples and nested tuples of such integers.
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# All numbers in the interval [-n, ..., n] except -1 because
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# hash(-1) == hash(-2).
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n = 5
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A = [x for x in range(-n, n+1) if x != -1]
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B = A + [(a,) for a in A]
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L2 = [(a,b) for a in A for b in A]
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L3 = L2 + [(a,b,c) for a in A for b in A for c in A]
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L4 = L3 + [(a,b,c,d) for a in A for b in A for c in A for d in A]
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# T = list of testcases. These consist of all (possibly nested
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# at most 2 levels deep) tuples containing at most 4 items from
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# the set A.
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T = A
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T += [(a,) for a in B + L4]
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T += [(a,b) for a in L3 for b in B]
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T += [(a,b) for a in L2 for b in L2]
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T += [(a,b) for a in B for b in L3]
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T += [(a,b,c) for a in B for b in B for c in L2]
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T += [(a,b,c) for a in B for b in L2 for c in B]
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T += [(a,b,c) for a in L2 for b in B for c in B]
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T += [(a,b,c,d) for a in B for b in B for c in B for d in B]
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self.assertEqual(len(T), 345130)
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hashes = set(hash(x) % 2**32 for x in T)
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collisions = len(T) - len(hashes)
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# For a pure random 32-bit hash and N = 345,130 test items, the
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# expected number of collisions equals
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#
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# 2**(-32) * N(N-1)/2 = 13.9
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#
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# We allow up to 20 collisions, which suffices to make the test
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# pass with 95.5% confidence.
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self.assertLessEqual(collisions, 20)
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def test_hash3(self):
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# Check for hash collisions between tuples containing 0.0 and 0.5.
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# The hashes of 0.0 and 0.5 itself differ only in one high bit.
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# So this implicitly tests propagation of high bits to low bits.
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from itertools import product
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T = list(product([0.0, 0.5], repeat=18))
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self.assertEqual(len(T), 262144)
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hashes = set(hash(x) % 2**32 for x in T)
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collisions = len(T) - len(hashes)
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# For a pure random 32-bit hash and N = 262,144 test items, the
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# expected number of collisions equals
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#
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# 2**(-32) * N(N-1)/2 = 8.0
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#
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# We allow up to 15 collisions, which suffices to make the test
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# pass with 99.1% confidence.
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self.assertLessEqual(collisions, 15)
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def test_repr(self):
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l0 = tuple()
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l2 = (0, 1, 2)
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a0 = self.type2test(l0)
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a2 = self.type2test(l2)
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self.assertEqual(str(a0), repr(l0))
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self.assertEqual(str(a2), repr(l2))
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self.assertEqual(repr(a0), "()")
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self.assertEqual(repr(a2), "(0, 1, 2)")
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def _not_tracked(self, t):
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# Nested tuples can take several collections to untrack
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gc.collect()
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gc.collect()
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self.assertFalse(gc.is_tracked(t), t)
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def _tracked(self, t):
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self.assertTrue(gc.is_tracked(t), t)
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gc.collect()
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gc.collect()
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self.assertTrue(gc.is_tracked(t), t)
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@support.cpython_only
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def test_track_literals(self):
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# Test GC-optimization of tuple literals
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x, y, z = 1.5, "a", []
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self._not_tracked(())
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self._not_tracked((1,))
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self._not_tracked((1, 2))
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self._not_tracked((1, 2, "a"))
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self._not_tracked((1, 2, (None, True, False, ()), int))
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self._not_tracked((object(),))
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self._not_tracked(((1, x), y, (2, 3)))
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# Tuples with mutable elements are always tracked, even if those
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# elements are not tracked right now.
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self._tracked(([],))
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self._tracked(([1],))
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self._tracked(({},))
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self._tracked((set(),))
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self._tracked((x, y, z))
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def check_track_dynamic(self, tp, always_track):
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x, y, z = 1.5, "a", []
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check = self._tracked if always_track else self._not_tracked
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check(tp())
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check(tp([]))
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check(tp(set()))
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check(tp([1, x, y]))
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check(tp(obj for obj in [1, x, y]))
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check(tp(set([1, x, y])))
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check(tp(tuple([obj]) for obj in [1, x, y]))
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check(tuple(tp([obj]) for obj in [1, x, y]))
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self._tracked(tp([z]))
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self._tracked(tp([[x, y]]))
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self._tracked(tp([{x: y}]))
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self._tracked(tp(obj for obj in [x, y, z]))
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self._tracked(tp(tuple([obj]) for obj in [x, y, z]))
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self._tracked(tuple(tp([obj]) for obj in [x, y, z]))
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@support.cpython_only
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def test_track_dynamic(self):
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# Test GC-optimization of dynamically constructed tuples.
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self.check_track_dynamic(tuple, False)
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@support.cpython_only
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def test_track_subtypes(self):
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# Tuple subtypes must always be tracked
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class MyTuple(tuple):
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pass
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self.check_track_dynamic(MyTuple, True)
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@support.cpython_only
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def test_bug7466(self):
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# Trying to untrack an unfinished tuple could crash Python
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self._not_tracked(tuple(gc.collect() for i in range(101)))
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def test_repr_large(self):
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# Check the repr of large list objects
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def check(n):
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l = (0,) * n
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s = repr(l)
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self.assertEqual(s,
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'(' + ', '.join(['0'] * n) + ')')
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check(10) # check our checking code
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check(1000000)
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def test_iterator_pickle(self):
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# Userlist iterators don't support pickling yet since
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# they are based on generators.
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data = self.type2test([4, 5, 6, 7])
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for proto in range(pickle.HIGHEST_PROTOCOL + 1):
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itorg = iter(data)
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d = pickle.dumps(itorg, proto)
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it = pickle.loads(d)
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self.assertEqual(type(itorg), type(it))
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self.assertEqual(self.type2test(it), self.type2test(data))
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it = pickle.loads(d)
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next(it)
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d = pickle.dumps(it, proto)
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self.assertEqual(self.type2test(it), self.type2test(data)[1:])
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def test_reversed_pickle(self):
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data = self.type2test([4, 5, 6, 7])
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for proto in range(pickle.HIGHEST_PROTOCOL + 1):
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itorg = reversed(data)
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d = pickle.dumps(itorg, proto)
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it = pickle.loads(d)
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self.assertEqual(type(itorg), type(it))
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self.assertEqual(self.type2test(it), self.type2test(reversed(data)))
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it = pickle.loads(d)
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next(it)
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d = pickle.dumps(it, proto)
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self.assertEqual(self.type2test(it), self.type2test(reversed(data))[1:])
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def test_no_comdat_folding(self):
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# Issue 8847: In the PGO build, the MSVC linker's COMDAT folding
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# optimization causes failures in code that relies on distinct
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# function addresses.
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class T(tuple): pass
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with self.assertRaises(TypeError):
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[3,] + T((1,2))
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def test_lexicographic_ordering(self):
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# Issue 21100
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a = self.type2test([1, 2])
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b = self.type2test([1, 2, 0])
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c = self.type2test([1, 3])
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self.assertLess(a, b)
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self.assertLess(b, c)
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if __name__ == "__main__":
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unittest.main()
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