cpython/Lib/test/test_tuple.py

303 lines
11 KiB
Python

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)))
# Various tests for hashing of tuples to check that we get few collisions.
#
# Earlier versions of the tuple hash algorithm had collisions
# reported at:
# - https://bugs.python.org/issue942952
# - https://bugs.python.org/issue34751
#
# Notes:
# - The hash of tuples is deterministic: if the test passes once on a given
# system, it will always pass. So the probabilities mentioned in the
# test_hash functions below should be interpreted assuming that the
# hashes are random.
# - Due to the structure in the testsuite inputs, collisions are not
# independent. For example, if hash((a,b)) == hash((c,d)), then also
# hash((a,b,x)) == hash((c,d,x)). But the quoted probabilities assume
# independence anyway.
# - We limit the hash to 32 bits in the tests to have a good test on
# 64-bit systems too. Furthermore, this is also a sanity check that the
# lower 32 bits of a 64-bit hash are sufficiently random too.
def test_hash1(self):
# Check for hash collisions between small integers in range(50) and
# certain tuples and nested tuples of such integers.
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))
self.assertEqual(len(inps), 252600)
hashes = set(hash(x) % 2**32 for x in inps)
collisions = len(inps) - len(hashes)
# For a pure random 32-bit hash and N = 252,600 test items, the
# expected number of collisions equals
#
# 2**(-32) * N(N-1)/2 = 7.4
#
# We allow up to 15 collisions, which suffices to make the test
# pass with 99.5% confidence.
self.assertLessEqual(collisions, 15)
def test_hash2(self):
# Check for hash collisions between small integers (positive and
# negative), tuples and nested tuples of such integers.
# All numbers in the interval [-n, ..., n] except -1 because
# hash(-1) == hash(-2).
n = 5
A = [x for x in range(-n, n+1) if x != -1]
B = A + [(a,) for a in A]
L2 = [(a,b) for a in A for b in A]
L3 = L2 + [(a,b,c) for a in A for b in A for c in A]
L4 = L3 + [(a,b,c,d) for a in A for b in A for c in A for d in A]
# T = list of testcases. These consist of all (possibly nested
# at most 2 levels deep) tuples containing at most 4 items from
# the set A.
T = A
T += [(a,) for a in B + L4]
T += [(a,b) for a in L3 for b in B]
T += [(a,b) for a in L2 for b in L2]
T += [(a,b) for a in B for b in L3]
T += [(a,b,c) for a in B for b in B for c in L2]
T += [(a,b,c) for a in B for b in L2 for c in B]
T += [(a,b,c) for a in L2 for b in B for c in B]
T += [(a,b,c,d) for a in B for b in B for c in B for d in B]
self.assertEqual(len(T), 345130)
hashes = set(hash(x) % 2**32 for x in T)
collisions = len(T) - len(hashes)
# For a pure random 32-bit hash and N = 345,130 test items, the
# expected number of collisions equals
#
# 2**(-32) * N(N-1)/2 = 13.9
#
# We allow up to 20 collisions, which suffices to make the test
# pass with 95.5% confidence.
self.assertLessEqual(collisions, 20)
def test_hash3(self):
# Check for hash collisions between tuples containing 0.0 and 0.5.
# The hashes of 0.0 and 0.5 itself differ only in one high bit.
# So this implicitly tests propagation of high bits to low bits.
from itertools import product
T = list(product([0.0, 0.5], repeat=18))
self.assertEqual(len(T), 262144)
hashes = set(hash(x) % 2**32 for x in T)
collisions = len(T) - len(hashes)
# For a pure random 32-bit hash and N = 262,144 test items, the
# expected number of collisions equals
#
# 2**(-32) * N(N-1)/2 = 8.0
#
# We allow up to 15 collisions, which suffices to make the test
# pass with 99.1% confidence.
self.assertLessEqual(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()