1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
|
from test import support, seq_tests
import gc
class TupleTest(seq_tests.CommonTest):
type2test = tuple
def test_constructors(self):
super().test_len()
# 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.assert_(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'))
def test_truth(self):
super().test_truth()
self.assert_(not ())
self.assert_((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.assert_(u is not u2)
def test_imul(self):
super().test_imul()
u = (0, 1)
u2 = u
u *= 3
self.assert_(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.assert_(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)
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]))
def test_track_dynamic(self):
# Test GC-optimization of dynamically constructed tuples.
self.check_track_dynamic(tuple, False)
def test_track_subtypes(self):
# Tuple subtypes must always be tracked
class MyTuple(tuple):
pass
self.check_track_dynamic(MyTuple, True)
def test_main():
support.run_unittest(TupleTest)
if __name__=="__main__":
test_main()
|
