在列表中使用哈希函数时，为同一字符串获取不同的哈希摘要值

Question

我似乎在程序中为同一个单词获取不同的摘要值。我不确定这是因为我将哈希函数保留在列表中（所以我可以添加到列表中）

当我使用直接散列函数时，对于同一个单词，散列摘要是相同的。当我在列表中使用哈希时，它会有所不同。我究竟做错了什么 ？

什么工作

import hashlib

bloom_len = 100

def bytes_to_int(hash_value):
    return int.from_bytes(hash_value, byteorder='big')  #big-endiang format

def bloom_index(hashint):
    return hashint % bloom_len


def hashIt(word):

    m1 = hashlib.md5()
    m2 = hashlib.sha1()
    m3 = hashlib.sha256()

    m4 = hashlib.sha3_512()
    m5 = hashlib.blake2s()

    m1.update(word)
    m2.update(word)
    m3.update(word)

    m4.update(word)
    m5.update(word)


    hash_values = [m1.digest(), m2.digest(), m3.digest(), m4.digest(), m5.digest()]
    hashints = list(map(bytes_to_int, hash_values))
    indices = list(map(bloom_index, hashints))

    print(indices)


inputWord = 'sent'
word = inputWord.encode('utf-8')
hashIt(word)

inputWord = 'blue'
word = inputWord.encode('utf-8')
hashIt(word)

inputWord = 'sent'
word = inputWord.encode('utf-8')
hashIt(word)

什么是无效的

import hashlib


class BloomFilter():
    def __init__(self, length = 100):

        self.bloomFilterLen = length
        self.bloomFilterArray = [0] * self.bloomFilterLen

        m1 = hashlib.md5()
        m2 = hashlib.sha3_512()
        m3 = hashlib.blake2s()        

        self.hashes = [m1, m2, m3]


    def encode(self, inputWord):
        encoded_word = inputWord.encode('utf-8')
        return encoded_word

    def bytes_to_int(self, hash_value):

        return int.from_bytes(hash_value, byteorder='big')  

    def bloom_index(self, hashint):

        return hashint % self.bloomFilterLen    

    def getIndices(self, inputWord):

        word = self.encode(inputWord)

        print(word)
        hashDigests = []

        for hashFunction in self.hashes:
            hashFunction.update(word)
            print('hashFunction ', hashFunction , '\n')
            print('hashDigest ', hashFunction.digest() , '\n')

            hashDigests.append(hashFunction.digest())


        hashInts = [self.bytes_to_int(h) for h in hashDigests]    
        #print('hashInts ', hashInts)

        bloomFilterIndices = [self.bloom_index(hInt) for hInt in hashInts]
        return bloomFilterIndices

    def insert(self, inputWord):

        bloomFilterIndices = self.getIndices(inputWord)

        for index in bloomFilterIndices:
            self.bloomFilterArray[index] = 1

        print(bloomFilterIndices)


    def lookup(self, inputWord):

        bloomFilterIndices = self.getIndices(inputWord)
        print('Inside lookup')
        print(bloomFilterIndices)

        for idx in bloomFilterIndices:
            print('idx value ', idx)
            print('self.bloomFilterArray[idx] value ', self.bloomFilterArray[idx])
            if self.bloomFilterArray[idx] == 0:
                # Indicates word not present in the bloom filter
                return False

        return True            


if __name__ == '__main__':

     word = 'sent'
     bloomFilter = BloomFilter()
     bloomFilter.insert(word)


     print(bloomFilter.lookup(word))

从第一个程序 - 我一直得到相同的整数索引

• '已发送'指数

[61, 82, 5, 53, 87]

• '蓝色'指数

[95, 25, 24, 69, 85]

• '已发送'指数

[61, 82, 5, 53, 87]

对于非工作程序，整数索引是不同的，当我打印出哈希摘要时是不同的

• '已发送'的指数 - 第一次通过添加

[61, 53, 87]

来自HashDigest的MD5'发送'

hashDigest b'x \ x91 \ x83 \ xb7 \ xe9 \ x86F \ xc1 \ x1d_ \ x05D \ xc8 \ xf3 \ xc4 \ xc9'

• '发送'的指数 - 第二次通过lookup

[70, 89, 8]

来自HashDigest的MD5'发送'

hashDigest b'x95 x17bC x17 x80 xbd 9d] x xca $ xda x89 x06 x16'

Answer 1

散列函数对象无法重用，您可以将这些函数对象移动到getIndices函数中：

import hashlib


class BloomFilter():
    def __init__(self, length = 100):

        self.bloomFilterLen = length
        self.bloomFilterArray = [0] * self.bloomFilterLen

    def encode(self, inputWord):
        encoded_word = inputWord.encode('utf-8')
        return encoded_word

    def bytes_to_int(self, hash_value):

        return int.from_bytes(hash_value, byteorder='big')  

    def bloom_index(self, hashint):

        return hashint % self.bloomFilterLen    

    def getIndices(self, inputWord):
        m1 = hashlib.md5()
        m2 = hashlib.sha3_512()
        m3 = hashlib.blake2s()        
        hashes = [m1, m2, m3]

        word = self.encode(inputWord)

        print(word)
        hashDigests = []

        for hashFunction in hashes:
            hashFunction.update(word)
            print('hashFunction ', hashFunction , '\n')
            print('hashDigest ', hashFunction.digest() , '\n')

            hashDigests.append(hashFunction.digest())


        hashInts = [self.bytes_to_int(h) for h in hashDigests]    
        #print('hashInts ', hashInts)

        bloomFilterIndices = [self.bloom_index(hInt) for hInt in hashInts]
        return bloomFilterIndices

    def insert(self, inputWord):

        bloomFilterIndices = self.getIndices(inputWord)

        for index in bloomFilterIndices:
            self.bloomFilterArray[index] = 1

        print(bloomFilterIndices)
        bloomFilterIndices = self.getIndices(inputWord)
        print(bloomFilterIndices)


    def lookup(self, inputWord):
        print('Inside lookup')
        bloomFilterIndices = self.getIndices(inputWord)
        print(bloomFilterIndices)

        for idx in bloomFilterIndices:
            print('idx value ', idx)
            print('self.bloomFilterArray[idx] value ', self.bloomFilterArray[idx])
            if self.bloomFilterArray[idx] == 0:
                # Indicates word not present in the bloom filter
                return False

        return True            


if __name__ == '__main__':

     word = 'sent'
     bloomFilter = BloomFilter()
     bloomFilter.insert(word)

     print(bloomFilter.lookup(word))

Answer 2

所以我改变了__init __中的代码

从

m1 = hashlib.md5()
m2 = hashlib.sha3_512()
m3 = hashlib.blake2s()        

self.hashes = [m1, m2, m3]

至

self.hashes = ['md5', 'sha3_512', 'blake2s']

然后在方法getIndices（）中的for循环内部

改变了

  for hashFunction in self.hashes:
        hashFunction.update(word)

至

for hashName in self.hashes:
    hashFunction = hashlib.new(hashName)
    hashFunction.update(word)

现在就行！