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<p>在我的程序中,对于同一个单词,我似乎得到了不同的摘要值。我不确定这是因为我把散列函数保存在一个列表中(这样我就可以添加到列表中)</p>
<p>当我使用直接哈希函数时,哈希摘要对于同一个单词是相同的。当我使用列表中的哈希时,情况就不同了。我做错什么了?你知道吗</p>
<p>什么在起作用</p>
<pre class="lang-py prettyprint-override"><code>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)
</code></pre>
<p>什么不起作用</p>
<pre class="lang-py prettyprint-override"><code>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))
</code></pre>
<p>从第一个程序-我总是得到相同的整数索引</p>
<ul>
<li>“<strong>发送的索引”</li>
</ul>
<p><code>[61, 82, 5, 53, 87]</code></p>
<ul>
<li>“<strong>蓝色</strong>”的索引</li>
</ul>
<p><code>[95, 25, 24, 69, 85]</code></p>
<ul>
<li>“<strong>发送的索引”</li>
</ul>
<p><code>[61, 82, 5, 53, 87]</code></p>
<p>对于非工作程序,整数索引是不同的,当我打印出散列摘要时是不同的</p>
<ul>
<li>“<strong>已发送</strong>”的索引-首次通过add</li>
</ul>
<p><code>[61, 53, 87]</code></p>
<p><code>HashDigest</code>来自<code>MD5</code>的^{<strong>已发送</strong>'</p>
<blockquote>
<p>hashDigest b'x\x91\x83\xb7\xe9\x86F\xc1\x1d_\x05D\xc8\xf3\xc4\xc9'</p>
</blockquote>
<ul>
<li>“<strong>的索引已发送</strong>”—第二次通过<code>lookup</code></li>
</ul>
<p><code>[70, 89, 8]</code></p>
<p><code>HashDigest</code>来自<code>MD5</code>的^{<strong>已发送</strong>'</p>
<blockquote>
<p>hashDigest b'\x95\x17bC\x17\x80\xb5\x9d]x\xca$\xda\x89\x06\x16'</p>
</blockquote>