bpo-33144: random.Random and subclasses: split _randbelow implementation (GH-6291)
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@ -38,7 +38,6 @@ General notes on the underlying Mersenne Twister core generator:
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"""
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from warnings import warn as _warn
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from types import MethodType as _MethodType, BuiltinMethodType as _BuiltinMethodType
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from math import log as _log, exp as _exp, pi as _pi, e as _e, ceil as _ceil
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from math import sqrt as _sqrt, acos as _acos, cos as _cos, sin as _sin
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from os import urandom as _urandom
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@ -94,6 +93,28 @@ class Random(_random.Random):
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self.seed(x)
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self.gauss_next = None
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def __init_subclass__(cls, **kwargs):
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"""Control how subclasses generate random integers.
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The algorithm a subclass can use depends on the random() and/or
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getrandbits() implementation available to it and determines
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whether it can generate random integers from arbitrarily large
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ranges.
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"""
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if (cls.random is _random.Random.random) or (
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cls.getrandbits is not _random.Random.getrandbits):
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# The original random() builtin method has not been overridden
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# or a new getrandbits() was supplied.
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# The subclass can use the getrandbits-dependent implementation
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# of _randbelow().
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cls._randbelow = cls._randbelow_with_getrandbits
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else:
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# There's an overridden random() method but no new getrandbits(),
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# so the subclass can only use the getrandbits-independent
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# implementation of _randbelow().
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cls._randbelow = cls._randbelow_without_getrandbits
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def seed(self, a=None, version=2):
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"""Initialize internal state from hashable object.
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@ -221,22 +242,23 @@ class Random(_random.Random):
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return self.randrange(a, b+1)
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def _randbelow(self, n, int=int, maxsize=1<<BPF, type=type,
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Method=_MethodType, BuiltinMethod=_BuiltinMethodType):
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def _randbelow_with_getrandbits(self, n):
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"Return a random int in the range [0,n). Raises ValueError if n==0."
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random = self.random
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getrandbits = self.getrandbits
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# Only call self.getrandbits if the original random() builtin method
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# has not been overridden or if a new getrandbits() was supplied.
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if type(random) is BuiltinMethod or type(getrandbits) is Method:
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k = n.bit_length() # don't use (n-1) here because n can be 1
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r = getrandbits(k) # 0 <= r < 2**k
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while r >= n:
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r = getrandbits(k)
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return r
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# There's an overridden random() method but no new getrandbits() method,
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# so we can only use random() from here.
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k = n.bit_length() # don't use (n-1) here because n can be 1
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r = getrandbits(k) # 0 <= r < 2**k
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while r >= n:
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r = getrandbits(k)
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return r
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def _randbelow_without_getrandbits(self, n, int=int, maxsize=1<<BPF):
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"""Return a random int in the range [0,n). Raises ValueError if n==0.
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The implementation does not use getrandbits, but only random.
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"""
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random = self.random
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if n >= maxsize:
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_warn("Underlying random() generator does not supply \n"
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"enough bits to choose from a population range this large.\n"
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@ -251,6 +273,8 @@ class Random(_random.Random):
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r = random()
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return int(r*maxsize) % n
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_randbelow = _randbelow_with_getrandbits
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## -------------------- sequence methods -------------------
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def choice(self, seq):
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@ -5,6 +5,7 @@ import os
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import time
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import pickle
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import warnings
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import logging
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from functools import partial
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from math import log, exp, pi, fsum, sin, factorial
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from test import support
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@ -619,6 +620,16 @@ class MersenneTwister_TestBasicOps(TestBasicOps, unittest.TestCase):
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self.assertRaises(ValueError, self.gen.getrandbits, 0)
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self.assertRaises(ValueError, self.gen.getrandbits, -1)
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def test_randrange_uses_getrandbits(self):
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# Verify use of getrandbits by randrange
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# Use same seed as in the cross-platform repeatability test
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# in test_genrandbits above.
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self.gen.seed(1234567)
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# If randrange uses getrandbits, it should pick getrandbits(100)
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# when called with a 100-bits stop argument.
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self.assertEqual(self.gen.randrange(2**99),
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97904845777343510404718956115)
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def test_randbelow_logic(self, _log=log, int=int):
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# check bitcount transition points: 2**i and 2**(i+1)-1
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# show that: k = int(1.001 + _log(n, 2))
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@ -640,21 +651,22 @@ class MersenneTwister_TestBasicOps(TestBasicOps, unittest.TestCase):
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self.assertEqual(k, numbits) # note the stronger assertion
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self.assertTrue(2**k > n > 2**(k-1)) # note the stronger assertion
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@unittest.mock.patch('random.Random.random')
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def test_randbelow_overridden_random(self, random_mock):
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def test_randbelow_without_getrandbits(self):
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# Random._randbelow() can only use random() when the built-in one
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# has been overridden but no new getrandbits() method was supplied.
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random_mock.side_effect = random.SystemRandom().random
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maxsize = 1<<random.BPF
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with warnings.catch_warnings():
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warnings.simplefilter("ignore", UserWarning)
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# Population range too large (n >= maxsize)
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self.gen._randbelow(maxsize+1, maxsize = maxsize)
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self.gen._randbelow(5640, maxsize = maxsize)
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self.gen._randbelow_without_getrandbits(
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maxsize+1, maxsize=maxsize
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)
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self.gen._randbelow_without_getrandbits(5640, maxsize=maxsize)
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# issue 33203: test that _randbelow raises ValueError on
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# n == 0 also in its getrandbits-independent branch.
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with self.assertRaises(ValueError):
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self.gen._randbelow(0, maxsize=maxsize)
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self.gen._randbelow_without_getrandbits(0, maxsize=maxsize)
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# This might be going too far to test a single line, but because of our
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# noble aim of achieving 100% test coverage we need to write a case in
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# which the following line in Random._randbelow() gets executed:
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@ -672,8 +684,10 @@ class MersenneTwister_TestBasicOps(TestBasicOps, unittest.TestCase):
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n = 42
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epsilon = 0.01
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limit = (maxsize - (maxsize % n)) / maxsize
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random_mock.side_effect = [limit + epsilon, limit - epsilon]
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self.gen._randbelow(n, maxsize = maxsize)
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with unittest.mock.patch.object(random.Random, 'random') as random_mock:
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random_mock.side_effect = [limit + epsilon, limit - epsilon]
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self.gen._randbelow_without_getrandbits(n, maxsize=maxsize)
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self.assertEqual(random_mock.call_count, 2)
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def test_randrange_bug_1590891(self):
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start = 1000000000000
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@ -926,6 +940,49 @@ class TestDistributions(unittest.TestCase):
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gammavariate_mock.return_value = 0.0
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self.assertEqual(0.0, random.betavariate(2.71828, 3.14159))
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class TestRandomSubclassing(unittest.TestCase):
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def test_random_subclass_with_kwargs(self):
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# SF bug #1486663 -- this used to erroneously raise a TypeError
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class Subclass(random.Random):
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def __init__(self, newarg=None):
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random.Random.__init__(self)
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Subclass(newarg=1)
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def test_subclasses_overriding_methods(self):
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# Subclasses with an overridden random, but only the original
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# getrandbits method should not rely on getrandbits in for randrange,
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# but should use a getrandbits-independent implementation instead.
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# subclass providing its own random **and** getrandbits methods
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# like random.SystemRandom does => keep relying on getrandbits for
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# randrange
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class SubClass1(random.Random):
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def random(self):
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return super().random()
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def getrandbits(self, n):
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logging.getLogger('getrandbits').info('used getrandbits')
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return super().getrandbits(n)
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with self.assertLogs('getrandbits'):
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SubClass1().randrange(42)
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# subclass providing only random => can only use random for randrange
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class SubClass2(random.Random):
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def random(self):
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logging.getLogger('random').info('used random')
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return super().random()
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with self.assertLogs('random'):
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SubClass2().randrange(42)
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# subclass defining getrandbits to complement its inherited random
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# => can now rely on getrandbits for randrange again
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class SubClass3(SubClass2):
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def getrandbits(self, n):
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logging.getLogger('getrandbits').info('used getrandbits')
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return super().getrandbits(n)
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with self.assertLogs('getrandbits'):
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SubClass3().randrange(42)
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class TestModule(unittest.TestCase):
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def testMagicConstants(self):
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self.assertAlmostEqual(random.NV_MAGICCONST, 1.71552776992141)
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@ -937,13 +994,6 @@ class TestModule(unittest.TestCase):
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# tests validity but not completeness of the __all__ list
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self.assertTrue(set(random.__all__) <= set(dir(random)))
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def test_random_subclass_with_kwargs(self):
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# SF bug #1486663 -- this used to erroneously raise a TypeError
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class Subclass(random.Random):
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def __init__(self, newarg=None):
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random.Random.__init__(self)
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Subclass(newarg=1)
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@unittest.skipUnless(hasattr(os, "fork"), "fork() required")
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def test_after_fork(self):
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# Test the global Random instance gets reseeded in child
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@ -0,0 +1,4 @@
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``random.Random()`` and its subclassing mechanism got optimized to check only
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once at class/subclass instantiation time whether its ``getrandbits()`` method
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can be relied on by other methods, including ``randrange()``, for the
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generation of arbitrarily large random integers. Patch by Wolfgang Maier.
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