KMP演算法（Python實現）

關於kmp演算法的原理等請參閱這篇文章：kmp演算法**（c++實現）

本篇文章只是對kmp用python進行了實現。

1.時間複雜度分析

bf演算法的時間複雜度：在最壞的情況下，bf演算法要將目標串的每乙個字元同模式串進行比較一遍，假定目標串長度為m，模式串長度為n，總的時間複雜度為o（m*n）。而對於kmp演算法，進行比較的時間複雜度為o（m+n），求next陣列的時間複雜度為n，總體時間複雜度為o（m+2n）。

2.源**

源**介紹：bf_match為常規的模式匹配演算法，kmp_match_1和kmp_match_2為kmp演算法，二者是一樣的，不同之處在於二者呼叫了不同的求next陣列的函式。求next陣列有兩種方法：一種是遞推法getnext_1()，一種是直接求取的方法getnext_2()。詳情請參閱下面的源**：

import random
import datetime
def bf_match(s, t):
slen = len(s)
tlen = len(t)
if slen >= tlen:
for k in range(slen - tlen + 1):
i = k
j = 0
while i < slen and j < tlen and s[i] == t[j]:
i = i + 1
j = j + 1
if j == tlen:
return k
else:
continue
return -1
def kmp_match_1(s, t):
slen = len(s)
tlen = len(t)
if slen >= tlen:
i = 0
j = 0
next_list = [-2 for i in range(len(t))]
getnext_1(t, next_list)
#print next_list
while i < slen:
if j == -1 or s[i] == t[j]:
i = i + 1
j = j + 1
else:
j = next_list[j]
if(j == tlen):
return i - tlen
return -1
def kmp_match_2(s, t):
slen = len(s)
tlen = len(t)
if slen >= tlen:
i = 0
j = 0
next_list = [-2 for i in range(len(t))]
getnext_2(t, next_list)
#print next_list
while i < slen:
if j == -1 or s[i] == t[j]:
i = i + 1
j = j + 1
else:
j = next_list[j]
if j == tlen:
return i - tlen
return -1
def getnext_1(t, next_list):
next_list[0] = -1
j = 0
k = -1
while j < len(t) - 1:
if k == -1 or t[j] == t[k]:
j = j + 1
k = k + 1
next_list[j] = k
else:
k = next_list[k]
def getnext_2(t, next_list):
next_list[0] = -1
next_list[1] = 0
for i in range(2, len(t)):
tmp = i -1
for j in range(tmp, 0, -1):
if equals(t, i, j):
next_list[i] = j
break
next_list[i] = 0
def equals(s, i, j):
k = 0
m = i - j
while k <= j - 1 and m <= i - 1:
if s[k] == s[m]:
k = k + 1
m = m + 1
else:
return false
return true
def rand_str(length):
str_0 = 
for i in range(length):
return str_0
def main():
x = rand_str(20000)
y = rand_str(5)
print "the string x length is : ", len(x), " string is :",
for i in range(len(x)):
print x[i],
print ""    
print "the string y length is : ", len(y), " string is :",
for i in range(len(y)):
print y[i],
print ""    
time_1 = datetime.datetime.now()
pos_1 = bf_match(x, y)
time_2 = datetime.datetime.now()
print "pos_1 = ", pos_1
time_3 = datetime.datetime.now()
pos_2 = kmp_match_1(x, y)
time_4 = datetime.datetime.now()
print "pos_2 = ", pos_2
time_5 = datetime.datetime.now()
pos_3 = kmp_match_2(x, y)
time_6 = datetime.datetime.now()
print "pos_3 = ", pos_3
print "function 1 spend ", time_2 - time_1
print "function 2 spend ", time_4 - time_3
print "function 3 spend ", time_6 - time_5
main()

KMP演算法（Python實現）

KMP演算法python實現

KMP演算法 python實現

python實現演算法 kmp演算法python實現

KMP演算法（Python實現）

KMP演算法python實現

KMP演算法 python實現

python實現演算法 kmp演算法python實現

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