ai-content-maker/.venv/Lib/site-packages/preshed/bloom.pyx

137 lines
4.4 KiB
Cython

# cython: infer_types=True
# cython: cdivision=True
#
from murmurhash.mrmr cimport hash128_x86
import math
from array import array
try:
import copy_reg
except ImportError:
import copyreg as copy_reg
def calculate_size_and_hash_count(members, error_rate):
"""Calculate the optimal size in bits and number of hash functions for a
given number of members and error rate.
"""
base = math.log(1 / (2 ** math.log(2)))
bit_count = math.ceil((members * math.log(error_rate)) / base)
hash_count = math.floor((bit_count / members) * math.log(2))
return (bit_count, hash_count)
cdef class BloomFilter:
"""Bloom filter that allows for basic membership tests.
Only integers are supported as keys.
"""
def __init__(self, key_t size=(2 ** 10), key_t hash_funcs=23, uint32_t seed=0):
self.mem = Pool()
self.c_bloom = <BloomStruct*>self.mem.alloc(1, sizeof(BloomStruct))
bloom_init(self.mem, self.c_bloom, hash_funcs, size, seed)
@classmethod
def from_error_rate(cls, members, error_rate=1E-4):
params = calculate_size_and_hash_count(members, error_rate)
return cls(*params)
def add(self, key_t item):
bloom_add(self.c_bloom, item)
def __contains__(self, item):
return bloom_contains(self.c_bloom, item)
cdef inline bint contains(self, key_t item) nogil:
return bloom_contains(self.c_bloom, item)
def to_bytes(self):
return bloom_to_bytes(self.c_bloom)
def from_bytes(self, bytes byte_string):
bloom_from_bytes(self.mem, self.c_bloom, byte_string)
return self
cdef bytes bloom_to_bytes(const BloomStruct* bloom):
py = array("L")
py.append(bloom.hcount)
py.append(bloom.length)
py.append(bloom.seed)
for i in range(bloom.length // sizeof(key_t)):
py.append(bloom.bitfield[i])
if hasattr(py, "tobytes"):
return py.tobytes()
else:
# Python 2 :(
return py.tostring()
cdef void bloom_from_bytes(Pool mem, BloomStruct* bloom, bytes data):
py = array("L")
if hasattr(py, "frombytes"):
py.frombytes(data)
else:
py.fromstring(data)
bloom.hcount = py[0]
bloom.length = py[1]
bloom.seed = py[2]
bloom.bitfield = <key_t*>mem.alloc(bloom.length // sizeof(key_t), sizeof(key_t))
for i in range(bloom.length // sizeof(key_t)):
bloom.bitfield[i] = py[3+i]
cdef void bloom_init(Pool mem, BloomStruct* bloom, key_t hcount, key_t length, uint32_t seed) except *:
# size should be a multiple of the container size - round up
if length % sizeof(key_t):
length = math.ceil(length / sizeof(key_t)) * sizeof(key_t)
bloom.length = length
bloom.hcount = hcount
bloom.bitfield = <key_t*>mem.alloc(length // sizeof(key_t), sizeof(key_t))
bloom.seed = seed
# Instead of calling MurmurHash with a different seed for each hash function, this
# generates two initial hash values and then combines them to create the correct
# number of hashes. This technique is faster than just doing MurmurhHash
# repeatedly and has been shown to work as well as full hashing.
# For details see "Less Hashing, Same Performance: Building a Better Bloom
# Filter", Kirsch & Mitzenmacher.
# https://www.semanticscholar.org/paper/Less-hashing%2C-same-performance%3A-Building-a-better-Kirsch-Mitzenmacher/65c43afbfc064705bdc40d3473f32518e9306429
# The choice of seeds is arbitrary.
cdef void bloom_add(BloomStruct* bloom, key_t item) nogil:
cdef key_t hv
cdef key_t[2] keys
cdef key_t one = 1 # We want this explicitly typed, because bits
hash128_x86(&item, sizeof(key_t), 0, &keys)
for hiter in range(bloom.hcount):
hv = (keys[0] + (hiter * keys[1])) % bloom.length
bloom.bitfield[hv // sizeof(key_t)] |= one << (hv % sizeof(key_t))
cdef bint bloom_contains(const BloomStruct* bloom, key_t item) nogil:
cdef key_t hv
cdef key_t[2] keys
cdef key_t one = 1 # We want this explicitly typed, because bits
hash128_x86(&item, sizeof(key_t), 0, &keys)
for hiter in range(bloom.hcount):
hv = (keys[0] + (hiter * keys[1])) % bloom.length
if not (bloom.bitfield[hv // sizeof(key_t)] & one << (hv % sizeof(key_t))):
return False
return True
def pickle_bloom(BloomFilter bloom):
return unpickle_bloom, (bloom.to_bytes(),)
def unpickle_bloom(byte_string):
return BloomFilter().from_bytes(byte_string)
copy_reg.pickle(BloomFilter, pickle_bloom, unpickle_bloom)