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1919b7e72b
up the decimal module. Performance gains of the new C implementation are between 12x and 80x, depending on the application.
207 lines
7.3 KiB
Python
207 lines
7.3 KiB
Python
# test interactions between int, float, Decimal and Fraction
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import unittest
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import random
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import math
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import sys
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import operator
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from test.support import run_unittest
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from decimal import Decimal as D
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from fractions import Fraction as F
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# Constants related to the hash implementation; hash(x) is based
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# on the reduction of x modulo the prime _PyHASH_MODULUS.
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_PyHASH_MODULUS = sys.hash_info.modulus
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_PyHASH_INF = sys.hash_info.inf
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class HashTest(unittest.TestCase):
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def check_equal_hash(self, x, y):
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# check both that x and y are equal and that their hashes are equal
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self.assertEqual(hash(x), hash(y),
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"got different hashes for {!r} and {!r}".format(x, y))
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self.assertEqual(x, y)
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def test_bools(self):
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self.check_equal_hash(False, 0)
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self.check_equal_hash(True, 1)
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def test_integers(self):
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# check that equal values hash equal
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# exact integers
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for i in range(-1000, 1000):
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self.check_equal_hash(i, float(i))
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self.check_equal_hash(i, D(i))
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self.check_equal_hash(i, F(i))
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# the current hash is based on reduction modulo 2**n-1 for some
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# n, so pay special attention to numbers of the form 2**n and 2**n-1.
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for i in range(100):
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n = 2**i - 1
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if n == int(float(n)):
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self.check_equal_hash(n, float(n))
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self.check_equal_hash(-n, -float(n))
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self.check_equal_hash(n, D(n))
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self.check_equal_hash(n, F(n))
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self.check_equal_hash(-n, D(-n))
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self.check_equal_hash(-n, F(-n))
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n = 2**i
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self.check_equal_hash(n, float(n))
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self.check_equal_hash(-n, -float(n))
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self.check_equal_hash(n, D(n))
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self.check_equal_hash(n, F(n))
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self.check_equal_hash(-n, D(-n))
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self.check_equal_hash(-n, F(-n))
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# random values of various sizes
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for _ in range(1000):
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e = random.randrange(300)
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n = random.randrange(-10**e, 10**e)
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self.check_equal_hash(n, D(n))
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self.check_equal_hash(n, F(n))
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if n == int(float(n)):
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self.check_equal_hash(n, float(n))
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def test_binary_floats(self):
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# check that floats hash equal to corresponding Fractions and Decimals
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# floats that are distinct but numerically equal should hash the same
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self.check_equal_hash(0.0, -0.0)
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# zeros
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self.check_equal_hash(0.0, D(0))
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self.check_equal_hash(-0.0, D(0))
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self.check_equal_hash(-0.0, D('-0.0'))
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self.check_equal_hash(0.0, F(0))
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# infinities and nans
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self.check_equal_hash(float('inf'), D('inf'))
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self.check_equal_hash(float('-inf'), D('-inf'))
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for _ in range(1000):
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x = random.random() * math.exp(random.random()*200.0 - 100.0)
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self.check_equal_hash(x, D.from_float(x))
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self.check_equal_hash(x, F.from_float(x))
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def test_complex(self):
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# complex numbers with zero imaginary part should hash equal to
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# the corresponding float
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test_values = [0.0, -0.0, 1.0, -1.0, 0.40625, -5136.5,
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float('inf'), float('-inf')]
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for zero in -0.0, 0.0:
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for value in test_values:
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self.check_equal_hash(value, complex(value, zero))
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def test_decimals(self):
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# check that Decimal instances that have different representations
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# but equal values give the same hash
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zeros = ['0', '-0', '0.0', '-0.0e10', '000e-10']
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for zero in zeros:
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self.check_equal_hash(D(zero), D(0))
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self.check_equal_hash(D('1.00'), D(1))
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self.check_equal_hash(D('1.00000'), D(1))
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self.check_equal_hash(D('-1.00'), D(-1))
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self.check_equal_hash(D('-1.00000'), D(-1))
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self.check_equal_hash(D('123e2'), D(12300))
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self.check_equal_hash(D('1230e1'), D(12300))
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self.check_equal_hash(D('12300'), D(12300))
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self.check_equal_hash(D('12300.0'), D(12300))
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self.check_equal_hash(D('12300.00'), D(12300))
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self.check_equal_hash(D('12300.000'), D(12300))
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def test_fractions(self):
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# check special case for fractions where either the numerator
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# or the denominator is a multiple of _PyHASH_MODULUS
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self.assertEqual(hash(F(1, _PyHASH_MODULUS)), _PyHASH_INF)
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self.assertEqual(hash(F(-1, 3*_PyHASH_MODULUS)), -_PyHASH_INF)
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self.assertEqual(hash(F(7*_PyHASH_MODULUS, 1)), 0)
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self.assertEqual(hash(F(-_PyHASH_MODULUS, 1)), 0)
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def test_hash_normalization(self):
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# Test for a bug encountered while changing long_hash.
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#
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# Given objects x and y, it should be possible for y's
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# __hash__ method to return hash(x) in order to ensure that
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# hash(x) == hash(y). But hash(x) is not exactly equal to the
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# result of x.__hash__(): there's some internal normalization
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# to make sure that the result fits in a C long, and is not
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# equal to the invalid hash value -1. This internal
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# normalization must therefore not change the result of
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# hash(x) for any x.
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class HalibutProxy:
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def __hash__(self):
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return hash('halibut')
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def __eq__(self, other):
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return other == 'halibut'
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x = {'halibut', HalibutProxy()}
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self.assertEqual(len(x), 1)
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class ComparisonTest(unittest.TestCase):
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def test_mixed_comparisons(self):
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# ordered list of distinct test values of various types:
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# int, float, Fraction, Decimal
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test_values = [
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float('-inf'),
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D('-1e425000000'),
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-1e308,
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F(-22, 7),
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-3.14,
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-2,
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0.0,
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1e-320,
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True,
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F('1.2'),
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D('1.3'),
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float('1.4'),
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F(275807, 195025),
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D('1.414213562373095048801688724'),
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F(114243, 80782),
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F(473596569, 84615),
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7e200,
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D('infinity'),
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]
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for i, first in enumerate(test_values):
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for second in test_values[i+1:]:
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self.assertLess(first, second)
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self.assertLessEqual(first, second)
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self.assertGreater(second, first)
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self.assertGreaterEqual(second, first)
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def test_complex(self):
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# comparisons with complex are special: equality and inequality
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# comparisons should always succeed, but order comparisons should
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# raise TypeError.
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z = 1.0 + 0j
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w = -3.14 + 2.7j
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for v in 1, 1.0, F(1), D(1), complex(1):
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self.assertEqual(z, v)
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self.assertEqual(v, z)
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for v in 2, 2.0, F(2), D(2), complex(2):
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self.assertNotEqual(z, v)
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self.assertNotEqual(v, z)
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self.assertNotEqual(w, v)
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self.assertNotEqual(v, w)
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for v in (1, 1.0, F(1), D(1), complex(1),
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2, 2.0, F(2), D(2), complex(2), w):
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for op in operator.le, operator.lt, operator.ge, operator.gt:
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self.assertRaises(TypeError, op, z, v)
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self.assertRaises(TypeError, op, v, z)
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def test_main():
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run_unittest(HashTest, ComparisonTest)
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if __name__ == '__main__':
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test_main()
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