python实现BM和KMP算法

1.KMP算法

 

def compute_prefix_function(p):
    m = len(p)
    pi = [0] * m
    k = 0
    for q in range(1, m):
        while k > 0 and p[k] != p[q]:
            k = pi[k - 1]
        if p[k] == p[q]:
            k = k + 1
        pi[q] = k
    return pi

def kmp_matcher(t, p):
    n = len(t)
    m = len(p)
    pi = compute_prefix_function(p)
    q = 0
    for i in range(n):
        while q > 0 and p[q] != t[i]:
            q = pi[q - 1]
        if p[q] == t[i]:
            q = q + 1
        if q == m:
            return i - m + 1
    return -1

 

2.BM算法例子

 

def BoyerMooreHorspool(pattern, text):
    m = len(pattern)
    n = len(text)
    if m > n: return -1
    skip = []
    for k in range(256): skip.append(m)
    for k in range(m - 1): skip[ord(pattern[k])] = m - k - 1
    skip = tuple(skip)
    k = m - 1
    while k < n:
        j = m - 1; i = k
        while j >= 0 and text[i] == pattern[j]:
            j -= 1; i -= 1
        if j == -1: return i + 1
        k += skip[ord(text[k])]
    return -1

if __name__ == '__main__':
    text = "this is the string to search in"
    pattern = "the"
    s = BoyerMooreHorspool(pattern, text)
    print 'Text:',text
    print 'Pattern:',pattern
    if s > -1:
        print 'Pattern \"' + pattern + '\" found at position',s

 

 

这两个算法主要应用于字符串匹配。网上评论说BM性能优于KMP，我没验证过。改天可以用cProfile测试一下。

 

ps：今天分别用这两个算法，查找了69K文档的最后一行字符串，KMP用了0.053个CPU时间，BM仅用了0.025个CPU时间。

其实我非常想看一下sunday算法，据说是BM的改进，提升不少性能。研究了一下算法，是人性多了。但是现在网上没有它的python实现，改天尝试搞一个出来。