adler32滚动校验和的计算差异-python

问题描述

在计算运行中的校验和时需要澄清.

Need a clarification while looking at calculating a running checksum.

假设我有这样的数据.

data = 'helloworld'

假设块大小为5，我需要计算运行校验和.

Assuming a blocksize of 5, I need to calculate running checksum.

>>> zlib.adler32('hello')
103547413
>>> zlib.adler32('ellow')
105316900

根据Python文档(Python版本2.7.2)

According to Python documentation (python version 2.7.2)

zlib.adler32(data[, value])

但是当我提供这样的内容时，

But when I provide something like this,

>>> zlib.adler32('ellow', zlib.adler32('hello'))
383190072

输出完全不同.

我尝试创建一个自定义函数来生成rsync算法中定义的滚动校验和.

I tried creating a custom function to generate the rolling checksum as defined in the rsync algorithm.

def weakchecksum(data):
    a = 1
    b = 0

    for char in data:
        a += (ord(char)) % MOD_VALUE
        b += a % MOD_VALUE



    return (b << 16) | a



def rolling(checksum, removed, added, block_size):
    a = checksum
    b = (a >> 16) & 0xffff
    a &= 0xffff

    a = (a - ord(removed) + ord(added)) % MOD_VALUE
    b = (b - (block_size * ord(removed)) + a) % MOD_VALUE

    return (b << 16) | a

这是我通过运行这些功能得到的值

Here is the values that I get from running these functions

Weak for hello: 103547413
Rolling for ellow: 105382436
Weak for ellow: 105316900

正如您所看到的，就价值而言，我的滚动校验和和python的实现存在巨大差异.

As you can see there is some huge difference in my implementation of rolling checksum and python's, in terms of value.

在计算滚动校验和时哪里出错了?我可以正确利用python adler32函数的rolling属性吗?

Where am I going wrong in calculating the rolling checksum?Am I making use of the rolling property of python's adler32 function correctly?

推荐答案

adler32()函数不提供滚动"功能.该文档正确使用了运行"(不是滚动")一词，这意味着它可以按块而不是一次计算adler32.您需要编写自己的代码来计算滚动" adler32值，该值将是数据上滑动窗口的adler32.

The adler32() function does not provide "rolling". The documentation correctly uses the word "running" (not "rolling"), which means simply that it can compute the adler32 in chunks as opposed to all at once. You need to write your own code to do compute a "rolling" adler32 value, which would be the adler32 of a sliding window over the data.

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