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Issue #8188: Introduce a new scheme for computing hashes of numbers 

(instances of int, float, complex, decimal.Decimal and
fractions.Fraction) that makes it easy to maintain the invariant that
hash(x) == hash(y) whenever x and y have equal value.
This commit is contained in:
Mark Dickinson 2010-05-23 13:33:13 +00:00
parent 03721133a6
commit dc787d2055
14 changed files with 566 additions and 137 deletions
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103
Doc/library/stdtypes.rst
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@ -595,6 +595,109 @@ hexadecimal string representing the same number::
'0x1.d380000000000p+11'
.. _numeric-hash:
Hashing of numeric types
------------------------
For numbers ``x`` and ``y``, possibly of different types, it's a requirement
that ``hash(x) == hash(y)`` whenever ``x == y`` (see the :meth:`__hash__`
method documentation for more details). For ease of implementation and
efficiency across a variety of numeric types (including :class:`int`,
:class:`float`, :class:`decimal.Decimal` and :class:`fractions.Fraction`)
Python's hash for numeric types is based on a single mathematical function
that's defined for any rational number, and hence applies to all instances of
:class:`int` and :class:`fraction.Fraction`, and all finite instances of
:class:`float` and :class:`decimal.Decimal`. Essentially, this function is
given by reduction modulo ``P`` for a fixed prime ``P``. The value of ``P`` is
made available to Python as the :attr:`modulus` attribute of
:data:`sys.hash_info`.
.. impl-detail::
Currently, the prime used is ``P = 2**31 - 1`` on machines with 32-bit C
longs and ``P = 2**61 - 1`` on machines with 64-bit C longs.
Here are the rules in detail:
- If ``x = m / n`` is a nonnegative rational number and ``n`` is not divisible
by ``P``, define ``hash(x)`` as ``m * invmod(n, P) % P``, where ``invmod(n,
P)`` gives the inverse of ``n`` modulo ``P``.
- If ``x = m / n`` is a nonnegative rational number and ``n`` is
divisible by ``P`` (but ``m`` is not) then ``n`` has no inverse
modulo ``P`` and the rule above doesn't apply; in this case define
``hash(x)`` to be the constant value ``sys.hash_info.inf``.
- If ``x = m / n`` is a negative rational number define ``hash(x)``
as ``-hash(-x)``. If the resulting hash is ``-1``, replace it with
``-2``.
- The particular values ``sys.hash_info.inf``, ``-sys.hash_info.inf``
and ``sys.hash_info.nan`` are used as hash values for positive
infinity, negative infinity, or nans (respectively). (All hashable
nans have the same hash value.)
- For a :class:`complex` number ``z``, the hash values of the real
and imaginary parts are combined by computing ``hash(z.real) +
sys.hash_info.imag * hash(z.imag)``, reduced modulo
``2**sys.hash_info.width`` so that it lies in
``range(-2**(sys.hash_info.width - 1), 2**(sys.hash_info.width -
1))``. Again, if the result is ``-1``, it's replaced with ``-2``.
To clarify the above rules, here's some example Python code,
equivalent to the builtin hash, for computing the hash of a rational
number, :class:`float`, or :class:`complex`::
import sys, math
def hash_fraction(m, n):
"""Compute the hash of a rational number m / n.
Assumes m and n are integers, with n positive.
Equivalent to hash(fractions.Fraction(m, n)).
"""
P = sys.hash_info.modulus
# Remove common factors of P. (Unnecessary if m and n already coprime.)
while m % P == n % P == 0:
m, n = m // P, n // P
if n % P == 0:
hash_ = sys.hash_info.inf
else:
# Fermat's Little Theorem: pow(n, P-1, P) is 1, so
# pow(n, P-2, P) gives the inverse of n modulo P.
hash_ = (abs(m) % P) * pow(n, P - 2, P) % P
if m < 0:
hash_ = -hash_
if hash_ == -1:
hash_ = -2
return hash_
def hash_float(x):
"""Compute the hash of a float x."""
if math.isnan(x):
return sys.hash_info.nan
elif math.isinf(x):
return sys.hash_info.inf if x > 0 else -sys.hash_info.inf
else:
return hash_fraction(*x.as_integer_ratio())
def hash_complex(z):
"""Compute the hash of a complex number z."""
hash_ = hash_float(z.real) + sys.hash_info.imag * hash_float(z.imag)
# do a signed reduction modulo 2**sys.hash_info.width
M = 2**(sys.hash_info.width - 1)
hash_ = (hash_ & (M - 1)) - (hash & M)
if hash_ == -1:
hash_ == -2
return hash_
.. _typeiter:
Iterator Types

24
Doc/library/sys.rst
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@ -446,6 +446,30 @@ always available.
Changed to a named tuple and added *service_pack_minor*,
*service_pack_major*, *suite_mask*, and *product_type*.
.. data:: hash_info
A structseq giving parameters of the numeric hash implementation. For
more details about hashing of numeric types, see :ref:`numeric-hash`.
+---------------------+--------------------------------------------------+
| attribute | explanation |
+=====================+==================================================+
| :const:`width` | width in bits used for hash values |
+---------------------+--------------------------------------------------+
| :const:`modulus` | prime modulus P used for numeric hash scheme |
+---------------------+--------------------------------------------------+
| :const:`inf` | hash value returned for a positive infinity |
+---------------------+--------------------------------------------------+
| :const:`nan` | hash value returned for a nan |
+---------------------+--------------------------------------------------+
| :const:`imag` | multiplier used for the imaginary part of a |
| | complex number |
+---------------------+--------------------------------------------------+
.. versionadded:: 3.2
.. data:: hexversion
The version number encoded as a single integer. This is guaranteed to increase

14
Include/pyport.h
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@ -126,6 +126,20 @@ Used in: PY_LONG_LONG
#endif
#endif
/* Parameters used for the numeric hash implementation. See notes for
_PyHash_Double in Objects/object.c. Numeric hashes are based on
reduction modulo the prime 2**_PyHASH_BITS - 1. */
#if SIZEOF_LONG >= 8
#define _PyHASH_BITS 61
#else
#define _PyHASH_BITS 31
#endif
#define _PyHASH_MODULUS ((1UL << _PyHASH_BITS) - 1)
#define _PyHASH_INF 314159
#define _PyHASH_NAN 0
#define _PyHASH_IMAG 1000003UL
/* uintptr_t is the C9X name for an unsigned integral type such that a
* legitimate void* can be cast to uintptr_t and then back to void* again
* without loss of information. Similarly for intptr_t, wrt a signed

64
Lib/decimal.py
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@ -935,55 +935,28 @@ class Decimal(object):
def __hash__(self):
"""x.__hash__() <==> hash(x)"""
# Decimal integers must hash the same as the ints
#
# The hash of a nonspecial noninteger Decimal must depend only
# on the value of that Decimal, and not on its representation.
# For example: hash(Decimal('100E-1')) == hash(Decimal('10')).
# Equality comparisons involving signaling nans can raise an
# exception; since equality checks are implicitly and
# unpredictably used when checking set and dict membership, we
# prevent signaling nans from being used as set elements or
# dict keys by making __hash__ raise an exception.
# In order to make sure that the hash of a Decimal instance
# agrees with the hash of a numerically equal integer, float
# or Fraction, we follow the rules for numeric hashes outlined
# in the documentation. (See library docs, 'Built-in Types').
if self._is_special:
if self.is_snan():
raise TypeError('Cannot hash a signaling NaN value.')
elif self.is_nan():
# 0 to match hash(float('nan'))
return 0
return _PyHASH_NAN
else:
# values chosen to match hash(float('inf')) and
# hash(float('-inf')).
if self._sign:
return -271828
return -_PyHASH_INF
else:
return 314159
return _PyHASH_INF
# In Python 2.7, we're allowing comparisons (but not
# arithmetic operations) between floats and Decimals; so if
# a Decimal instance is exactly representable as a float then
# its hash should match that of the float.
self_as_float = float(self)
if Decimal.from_float(self_as_float) == self:
return hash(self_as_float)
if self._isinteger():
op = _WorkRep(self.to_integral_value())
# to make computation feasible for Decimals with large
# exponent, we use the fact that hash(n) == hash(m) for
# any two nonzero integers n and m such that (i) n and m
# have the same sign, and (ii) n is congruent to m modulo
# 2**64-1. So we can replace hash((-1)**s*c*10**e) with
# hash((-1)**s*c*pow(10, e, 2**64-1).
return hash((-1)**op.sign*op.int*pow(10, op.exp, 2**64-1))
# The value of a nonzero nonspecial Decimal instance is
# faithfully represented by the triple consisting of its sign,
# its adjusted exponent, and its coefficient with trailing
# zeros removed.
return hash((self._sign,
self._exp+len(self._int),
self._int.rstrip('0')))
if self._exp >= 0:
exp_hash = pow(10, self._exp, _PyHASH_MODULUS)
else:
exp_hash = pow(_PyHASH_10INV, -self._exp, _PyHASH_MODULUS)
hash_ = int(self._int) * exp_hash % _PyHASH_MODULUS
return hash_ if self >= 0 else -hash_
def as_tuple(self):
"""Represents the number as a triple tuple.
@ -6218,6 +6191,17 @@ _NegativeOne = Decimal(-1)
# _SignedInfinity[sign] is infinity w/ that sign
_SignedInfinity = (_Infinity, _NegativeInfinity)
# Constants related to the hash implementation; hash(x) is based
# on the reduction of x modulo _PyHASH_MODULUS
import sys
_PyHASH_MODULUS = sys.hash_info.modulus
# hash values to use for positive and negative infinities, and nans
_PyHASH_INF = sys.hash_info.inf
_PyHASH_NAN = sys.hash_info.nan
del sys
# _PyHASH_10INV is the inverse of 10 modulo the prime _PyHASH_MODULUS
_PyHASH_10INV = pow(10, _PyHASH_MODULUS - 2, _PyHASH_MODULUS)
if __name__ == '__main__':

31
Lib/fractions.py
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@ -8,6 +8,7 @@ import math
import numbers
import operator
import re
import sys
__all__ = ['Fraction', 'gcd']
@ -23,6 +24,12 @@ def gcd(a, b):
a, b = b, a%b
return a
# Constants related to the hash implementation; hash(x) is based
# on the reduction of x modulo the prime _PyHASH_MODULUS.
_PyHASH_MODULUS = sys.hash_info.modulus
# Value to be used for rationals that reduce to infinity modulo
# _PyHASH_MODULUS.
_PyHASH_INF = sys.hash_info.inf
_RATIONAL_FORMAT = re.compile(r"""
\A\s* # optional whitespace at the start, then
@ -528,16 +535,22 @@ class Fraction(numbers.Rational):
"""
# XXX since this method is expensive, consider caching the result
if self._denominator == 1:
# Get integers right.
return hash(self._numerator)
# Expensive check, but definitely correct.
if self == float(self):
return hash(float(self))
# In order to make sure that the hash of a Fraction agrees
# with the hash of a numerically equal integer, float or
# Decimal instance, we follow the rules for numeric hashes
# outlined in the documentation. (See library docs, 'Built-in
# Types').
# dinv is the inverse of self._denominator modulo the prime
# _PyHASH_MODULUS, or 0 if self._denominator is divisible by
# _PyHASH_MODULUS.
dinv = pow(self._denominator, _PyHASH_MODULUS - 2, _PyHASH_MODULUS)
if not dinv:
hash_ = _PyHASH_INF
else:
# Use tuple's hash to avoid a high collision rate on
# simple fractions.
return hash((self._numerator, self._denominator))
hash_ = abs(self._numerator) * dinv % _PyHASH_MODULUS
return hash_ if self >= 0 else -hash_
def __eq__(a, b):
"""a == b"""

9
Lib/test/test_float.py
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@ -914,15 +914,6 @@ class InfNanTest(unittest.TestCase):
self.assertFalse(NAN.is_inf())
self.assertFalse((0.).is_inf())
def test_hash_inf(self):
# the actual values here should be regarded as an
# implementation detail, but they need to be
# identical to those used in the Decimal module.
self.assertEqual(hash(float('inf')), 314159)
self.assertEqual(hash(float('-inf')), -271828)
self.assertEqual(hash(float('nan')), 0)
fromHex = float.fromhex
toHex = float.hex
class HexFloatTestCase(unittest.TestCase):

151
Lib/test/test_numeric_tower.py Normal file
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@ -0,0 +1,151 @@
# test interactions betwen int, float, Decimal and Fraction
import unittest
import random
import math
import sys
import operator
from test.support import run_unittest
from decimal import Decimal as D
from fractions import Fraction as F
# Constants related to the hash implementation; hash(x) is based
# on the reduction of x modulo the prime _PyHASH_MODULUS.
_PyHASH_MODULUS = sys.hash_info.modulus
_PyHASH_INF = sys.hash_info.inf
class HashTest(unittest.TestCase):
def check_equal_hash(self, x, y):
# check both that x and y are equal and that their hashes are equal
self.assertEqual(hash(x), hash(y),
"got different hashes for {!r} and {!r}".format(x, y))
self.assertEqual(x, y)
def test_bools(self):
self.check_equal_hash(False, 0)
self.check_equal_hash(True, 1)
def test_integers(self):
# check that equal values hash equal
# exact integers
for i in range(-1000, 1000):
self.check_equal_hash(i, float(i))
self.check_equal_hash(i, D(i))
self.check_equal_hash(i, F(i))
# the current hash is based on reduction modulo 2**n-1 for some
# n, so pay special attention to numbers of the form 2**n and 2**n-1.
for i in range(100):
n = 2**i - 1
if n == int(float(n)):
self.check_equal_hash(n, float(n))
self.check_equal_hash(-n, -float(n))
self.check_equal_hash(n, D(n))
self.check_equal_hash(n, F(n))
self.check_equal_hash(-n, D(-n))
self.check_equal_hash(-n, F(-n))
n = 2**i
self.check_equal_hash(n, float(n))
self.check_equal_hash(-n, -float(n))
self.check_equal_hash(n, D(n))
self.check_equal_hash(n, F(n))
self.check_equal_hash(-n, D(-n))
self.check_equal_hash(-n, F(-n))
# random values of various sizes
for _ in range(1000):
e = random.randrange(300)
n = random.randrange(-10**e, 10**e)
self.check_equal_hash(n, D(n))
self.check_equal_hash(n, F(n))
if n == int(float(n)):
self.check_equal_hash(n, float(n))
def test_binary_floats(self):
# check that floats hash equal to corresponding Fractions and Decimals
# floats that are distinct but numerically equal should hash the same
self.check_equal_hash(0.0, -0.0)
# zeros
self.check_equal_hash(0.0, D(0))
self.check_equal_hash(-0.0, D(0))
self.check_equal_hash(-0.0, D('-0.0'))
self.check_equal_hash(0.0, F(0))
# infinities and nans
self.check_equal_hash(float('inf'), D('inf'))
self.check_equal_hash(float('-inf'), D('-inf'))
for _ in range(1000):
x = random.random() * math.exp(random.random()*200.0 - 100.0)
self.check_equal_hash(x, D.from_float(x))
self.check_equal_hash(x, F.from_float(x))
def test_complex(self):
# complex numbers with zero imaginary part should hash equal to
# the corresponding float
test_values = [0.0, -0.0, 1.0, -1.0, 0.40625, -5136.5,
float('inf'), float('-inf')]
for zero in -0.0, 0.0:
for value in test_values:
self.check_equal_hash(value, complex(value, zero))
def test_decimals(self):
# check that Decimal instances that have different representations
# but equal values give the same hash
zeros = ['0', '-0', '0.0', '-0.0e10', '000e-10']
for zero in zeros:
self.check_equal_hash(D(zero), D(0))
self.check_equal_hash(D('1.00'), D(1))
self.check_equal_hash(D('1.00000'), D(1))
self.check_equal_hash(D('-1.00'), D(-1))
self.check_equal_hash(D('-1.00000'), D(-1))
self.check_equal_hash(D('123e2'), D(12300))
self.check_equal_hash(D('1230e1'), D(12300))
self.check_equal_hash(D('12300'), D(12300))
self.check_equal_hash(D('12300.0'), D(12300))
self.check_equal_hash(D('12300.00'), D(12300))
self.check_equal_hash(D('12300.000'), D(12300))
def test_fractions(self):
# check special case for fractions where either the numerator
# or the denominator is a multiple of _PyHASH_MODULUS
self.assertEqual(hash(F(1, _PyHASH_MODULUS)), _PyHASH_INF)
self.assertEqual(hash(F(-1, 3*_PyHASH_MODULUS)), -_PyHASH_INF)
self.assertEqual(hash(F(7*_PyHASH_MODULUS, 1)), 0)
self.assertEqual(hash(F(-_PyHASH_MODULUS, 1)), 0)
def test_hash_normalization(self):
# Test for a bug encountered while changing long_hash.
#
# Given objects x and y, it should be possible for y's
# __hash__ method to return hash(x) in order to ensure that
# hash(x) == hash(y). But hash(x) is not exactly equal to the
# result of x.__hash__(): there's some internal normalization
# to make sure that the result fits in a C long, and is not
# equal to the invalid hash value -1. This internal
# normalization must therefore not change the result of
# hash(x) for any x.
class HalibutProxy:
def __hash__(self):
return hash('halibut')
def __eq__(self, other):
return other == 'halibut'
x = {'halibut', HalibutProxy()}
self.assertEqual(len(x), 1)
def test_main():
run_unittest(HashTest)
if __name__ == '__main__':
test_main()

17
Lib/test/test_sys.py
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@ -426,6 +426,23 @@ class SysModuleTest(unittest.TestCase):
self.assertEqual(type(sys.int_info.bits_per_digit), int)
self.assertEqual(type(sys.int_info.sizeof_digit), int)
self.assertIsInstance(sys.hexversion, int)
self.assertEqual(len(sys.hash_info), 5)
self.assertLess(sys.hash_info.modulus, 2**sys.hash_info.width)
# sys.hash_info.modulus should be a prime; we do a quick
# probable primality test (doesn't exclude the possibility of
# a Carmichael number)
for x in range(1, 100):
self.assertEqual(
pow(x, sys.hash_info.modulus-1, sys.hash_info.modulus),
1,
"sys.hash_info.modulus {} is a non-prime".format(
sys.hash_info.modulus)
)
self.assertIsInstance(sys.hash_info.inf, int)
self.assertIsInstance(sys.hash_info.nan, int)
self.assertIsInstance(sys.hash_info.imag, int)
self.assertIsInstance(sys.maxsize, int)
self.assertIsInstance(sys.maxunicode, int)
self.assertIsInstance(sys.platform, str)

5
Misc/NEWS
View File

@ -12,6 +12,11 @@ What's New in Python 3.2 Alpha 1?
Core and Builtins
-----------------
- Issue #8188: Introduce a new scheme for computing hashes of numbers
(instances of int, float, complex, decimal.Decimal and
fractions.Fraction) that makes it easy to maintain the invariant
that hash(x) == hash(y) whenever x and y have equal value.
- Issue #8748: Fix two issues with comparisons between complex and integer
objects. (1) The comparison could incorrectly return True in some cases
(2**53+1 == complex(2**53) == 2**53), breaking transivity of equality.

18
Objects/complexobject.c
View File

@ -403,12 +403,12 @@ complex_str(PyComplexObject *v)
static long
complex_hash(PyComplexObject *v)
{
long hashreal, hashimag, combined;
hashreal = _Py_HashDouble(v->cval.real);
if (hashreal == -1)
unsigned long hashreal, hashimag, combined;
hashreal = (unsigned long)_Py_HashDouble(v->cval.real);
if (hashreal == (unsigned long)-1)
return -1;
hashimag = _Py_HashDouble(v->cval.imag);
if (hashimag == -1)
hashimag = (unsigned long)_Py_HashDouble(v->cval.imag);
if (hashimag == (unsigned long)-1)
return -1;
/* Note: if the imaginary part is 0, hashimag is 0 now,
* so the following returns hashreal unchanged. This is
@ -416,10 +416,10 @@ complex_hash(PyComplexObject *v)
* compare equal must have the same hash value, so that
* hash(x + 0*j) must equal hash(x).
*/
combined = hashreal + 1000003 * hashimag;
if (combined == -1)
combined = -2;
return combined;
combined = hashreal + _PyHASH_IMAG * hashimag;
if (combined == (unsigned long)-1)
combined = (unsigned long)-2;
return (long)combined;
}
/* This macro may return! */

39
Objects/longobject.c
View File

@ -2571,18 +2571,37 @@ long_hash(PyLongObject *v)
sign = -1;
i = -(i);
}
/* The following loop produces a C unsigned long x such that x is
congruent to the absolute value of v modulo ULONG_MAX. The
resulting x is nonzero if and only if v is. */
while (--i >= 0) {
/* Force a native long #-bits (32 or 64) circular shift */
x = (x >> (8*SIZEOF_LONG-PyLong_SHIFT)) | (x << PyLong_SHIFT);
/* Here x is a quantity in the range [0, _PyHASH_MODULUS); we
want to compute x * 2**PyLong_SHIFT + v->ob_digit[i] modulo
_PyHASH_MODULUS.
The computation of x * 2**PyLong_SHIFT % _PyHASH_MODULUS
amounts to a rotation of the bits of x. To see this, write
x * 2**PyLong_SHIFT = y * 2**_PyHASH_BITS + z
where y = x >> (_PyHASH_BITS - PyLong_SHIFT) gives the top
PyLong_SHIFT bits of x (those that are shifted out of the
original _PyHASH_BITS bits, and z = (x << PyLong_SHIFT) &
_PyHASH_MODULUS gives the bottom _PyHASH_BITS - PyLong_SHIFT
bits of x, shifted up. Then since 2**_PyHASH_BITS is
congruent to 1 modulo _PyHASH_MODULUS, y*2**_PyHASH_BITS is
congruent to y modulo _PyHASH_MODULUS. So
x * 2**PyLong_SHIFT = y + z (mod _PyHASH_MODULUS).
The right-hand side is just the result of rotating the
_PyHASH_BITS bits of x left by PyLong_SHIFT places; since
not all _PyHASH_BITS bits of x are 1s, the same is true
after rotation, so 0 <= y+z < _PyHASH_MODULUS and y + z is
the reduction of x*2**PyLong_SHIFT modulo
_PyHASH_MODULUS. */
x = ((x << PyLong_SHIFT) & _PyHASH_MODULUS) |
(x >> (_PyHASH_BITS - PyLong_SHIFT));
x += v->ob_digit[i];
/* If the addition above overflowed we compensate by
incrementing. This preserves the value modulo
ULONG_MAX. */
if (x < v->ob_digit[i])
x++;
if (x >= _PyHASH_MODULUS)
x -= _PyHASH_MODULUS;
}
x = x * sign;
if (x == (unsigned long)-1)

132
Objects/object.c
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@ -647,63 +647,101 @@ PyObject_RichCompareBool(PyObject *v, PyObject *w, int op)
All the utility functions (_Py_Hash*()) return "-1" to signify an error.
*/
/* For numeric types, the hash of a number x is based on the reduction
of x modulo the prime P = 2**_PyHASH_BITS - 1. It's designed so that
hash(x) == hash(y) whenever x and y are numerically equal, even if
x and y have different types.
A quick summary of the hashing strategy:
(1) First define the 'reduction of x modulo P' for any rational
number x; this is a standard extension of the usual notion of
reduction modulo P for integers. If x == p/q (written in lowest
terms), the reduction is interpreted as the reduction of p times
the inverse of the reduction of q, all modulo P; if q is exactly
divisible by P then define the reduction to be infinity. So we've
got a well-defined map
reduce : { rational numbers } -> { 0, 1, 2, ..., P-1, infinity }.
(2) Now for a rational number x, define hash(x) by:
reduce(x) if x >= 0
-reduce(-x) if x < 0
If the result of the reduction is infinity (this is impossible for
integers, floats and Decimals) then use the predefined hash value
_PyHASH_INF for x >= 0, or -_PyHASH_INF for x < 0, instead.
_PyHASH_INF, -_PyHASH_INF and _PyHASH_NAN are also used for the
hashes of float and Decimal infinities and nans.
A selling point for the above strategy is that it makes it possible
to compute hashes of decimal and binary floating-point numbers
efficiently, even if the exponent of the binary or decimal number
is large. The key point is that
reduce(x * y) == reduce(x) * reduce(y) (modulo _PyHASH_MODULUS)
provided that {reduce(x), reduce(y)} != {0, infinity}. The reduction of a
binary or decimal float is never infinity, since the denominator is a power
of 2 (for binary) or a divisor of a power of 10 (for decimal). So we have,
for nonnegative x,
reduce(x * 2**e) == reduce(x) * reduce(2**e) % _PyHASH_MODULUS
reduce(x * 10**e) == reduce(x) * reduce(10**e) % _PyHASH_MODULUS
and reduce(10**e) can be computed efficiently by the usual modular
exponentiation algorithm. For reduce(2**e) it's even better: since
P is of the form 2**n-1, reduce(2**e) is 2**(e mod n), and multiplication
by 2**(e mod n) modulo 2**n-1 just amounts to a rotation of bits.
*/
long
_Py_HashDouble(double v)
{
double intpart, fractpart;
int expo;
long hipart;
long x; /* the final hash value */
/* This is designed so that Python numbers of different types
* that compare equal hash to the same value; otherwise comparisons
* of mapping keys will turn out weird.
*/
int e, sign;
double m;
unsigned long x, y;
if (!Py_IS_FINITE(v)) {
if (Py_IS_INFINITY(v))
return v < 0 ? -271828 : 314159;
return v > 0 ? _PyHASH_INF : -_PyHASH_INF;
else
return 0;
return _PyHASH_NAN;
}
fractpart = modf(v, &intpart);
if (fractpart == 0.0) {
/* This must return the same hash as an equal int or long. */
if (intpart > LONG_MAX/2 || -intpart > LONG_MAX/2) {
/* Convert to long and use its hash. */
PyObject *plong; /* converted to Python long */
plong = PyLong_FromDouble(v);
if (plong == NULL)
return -1;
x = PyObject_Hash(plong);
Py_DECREF(plong);
return x;
m = frexp(v, &e);
sign = 1;
if (m < 0) {
sign = -1;
m = -m;
}
/* Fits in a C long == a Python int, so is its own hash. */
x = (long)intpart;
if (x == -1)
x = -2;
return x;
/* process 28 bits at a time; this should work well both for binary
and hexadecimal floating point. */
x = 0;
while (m) {
x = ((x << 28) & _PyHASH_MODULUS) | x >> (_PyHASH_BITS - 28);
m *= 268435456.0; /* 2**28 */
e -= 28;
y = (unsigned long)m; /* pull out integer part */
m -= y;
x += y;
if (x >= _PyHASH_MODULUS)
x -= _PyHASH_MODULUS;
}
/* The fractional part is non-zero, so we don't have to worry about
* making this match the hash of some other type.
* Use frexp to get at the bits in the double.
* Since the VAX D double format has 56 mantissa bits, which is the
* most of any double format in use, each of these parts may have as
* many as (but no more than) 56 significant bits.
* So, assuming sizeof(long) >= 4, each part can be broken into two
* longs; frexp and multiplication are used to do that.
* Also, since the Cray double format has 15 exponent bits, which is
* the most of any double format in use, shifting the exponent field
* left by 15 won't overflow a long (again assuming sizeof(long) >= 4).
*/
v = frexp(v, &expo);
v *= 2147483648.0; /* 2**31 */
hipart = (long)v; /* take the top 32 bits */
v = (v - (double)hipart) * 2147483648.0; /* get the next 32 bits */
x = hipart + (long)v + (expo << 15);
if (x == -1)
x = -2;
return x;
/* adjust for the exponent; first reduce it modulo _PyHASH_BITS */
e = e >= 0 ? e % _PyHASH_BITS : _PyHASH_BITS-1-((-1-e) % _PyHASH_BITS);
x = ((x << e) & _PyHASH_MODULUS) | x >> (_PyHASH_BITS - e);
x = x * sign;
if (x == (unsigned long)-1)
x = (unsigned long)-2;
return (long)x;
}
long

20
Objects/typeobject.c
View File

@ -4921,6 +4921,7 @@ slot_tp_hash(PyObject *self)
PyObject *func, *res;
static PyObject *hash_str;
long h;
int overflow;
func = lookup_method(self, "__hash__", &hash_str);
@ -4937,10 +4938,23 @@ slot_tp_hash(PyObject *self)
Py_DECREF(func);
if (res == NULL)
return -1;
if (PyLong_Check(res))
if (!PyLong_Check(res)) {
PyErr_SetString(PyExc_TypeError,
"__hash__ method should return an integer");
return -1;
}
/* Transform the PyLong `res` to a C long `h`. For an existing
hashable Python object x, hash(x) will always lie within the range
of a C long. Therefore our transformation must preserve values
that already lie within this range, to ensure that if x.__hash__()
returns hash(y) then hash(x) == hash(y). */
h = PyLong_AsLongAndOverflow(res, &overflow);
if (overflow)
/* res was not within the range of a C long, so we're free to
use any sufficiently bit-mixing transformation;
long.__hash__ will do nicely. */
h = PyLong_Type.tp_hash(res);
else
h = PyLong_AsLong(res);
Py_DECREF(res);
if (h == -1 && !PyErr_Occurred())
h = -2;

56
Python/sysmodule.c
View File

@ -570,6 +570,57 @@ sys_setrecursionlimit(PyObject *self, PyObject *args)
return Py_None;
}
static PyTypeObject Hash_InfoType;
PyDoc_STRVAR(hash_info_doc,
"hash_info\n\
\n\
A struct sequence providing parameters used for computing\n\
numeric hashes. The attributes are read only.");
static PyStructSequence_Field hash_info_fields[] = {
{"width", "width of the type used for hashing, in bits"},
{"modulus", "prime number giving the modulus on which the hash "
"function is based"},
{"inf", "value to be used for hash of a positive infinity"},
{"nan", "value to be used for hash of a nan"},
{"imag", "multiplier used for the imaginary part of a complex number"},
{NULL, NULL}
};
static PyStructSequence_Desc hash_info_desc = {
"sys.hash_info",
hash_info_doc,
hash_info_fields,
5,
};
PyObject *
get_hash_info(void)
{
PyObject *hash_info;
int field = 0;
hash_info = PyStructSequence_New(&Hash_InfoType);
if (hash_info == NULL)
return NULL;
PyStructSequence_SET_ITEM(hash_info, field++,
PyLong_FromLong(8*sizeof(long)));
PyStructSequence_SET_ITEM(hash_info, field++,
PyLong_FromLong(_PyHASH_MODULUS));
PyStructSequence_SET_ITEM(hash_info, field++,
PyLong_FromLong(_PyHASH_INF));
PyStructSequence_SET_ITEM(hash_info, field++,
PyLong_FromLong(_PyHASH_NAN));
PyStructSequence_SET_ITEM(hash_info, field++,
PyLong_FromLong(_PyHASH_IMAG));
if (PyErr_Occurred()) {
Py_CLEAR(hash_info);
return NULL;
}
return hash_info;
}
PyDoc_STRVAR(setrecursionlimit_doc,
"setrecursionlimit(n)\n\
\n\
@ -1482,6 +1533,11 @@ _PySys_Init(void)
PyFloat_GetInfo());
SET_SYS_FROM_STRING("int_info",
PyLong_GetInfo());
/* initialize hash_info */
if (Hash_InfoType.tp_name == 0)
PyStructSequence_InitType(&Hash_InfoType, &hash_info_desc);
SET_SYS_FROM_STRING("hash_info",
get_hash_info());
SET_SYS_FROM_STRING("maxunicode",
PyLong_FromLong(PyUnicode_GetMax()));
SET_SYS_FROM_STRING("builtin_module_names",