注意：使用前先要下载搜狗词库

# -*- coding:utf-8 -*-
 
#写了一个简单的支持中文的正向最大匹配的机械分词,其它不用解释了，就几十行代码
#附：搜狗词库下载地址：http://vdisk.weibo.com/s/7RlE5
 
import string
__dict = {}
 
def load_dict(dict_file='words.dic'):
 #加载词库，把词库加载成一个key为首字符，value为相关词的列表的字典
 
 words = [unicode(line, 'utf-8').split() for line in open(dict_file)]
 
 for word_len, word in words:
 first_char = word[0]
 __dict.setdefault(first_char, [])
 __dict[first_char].append(word)
 
 #按词的长度倒序排列
 for first_char, words in __dict.items():
 __dict[first_char] = sorted(words, key=lambda x:len(x), reverse=True)
 
def __match_ascii(i, input):
 #返回连续的英文字母，数字，符号
 result = ''
 for i in range(i, len(input)):
 if not input[i] in string.ascii_letters: break
 result += input[i]
 return result
 
 
def __match_word(first_char, i , input):
 #根据当前位置进行分词，ascii的直接读取连续字符，中文的读取词库
 
 if not __dict.has_key(first_char):
 if first_char in string.ascii_letters:
 return __match_ascii(i, input)
 return first_char
 
 words = __dict[first_char]
 for word in words:
 if input[i:i+len(word)] == word:
 return word
 
 return first_char
 
def tokenize(input):
 #对input进行分词，input必须是uncode编码
 
 if not input: return []
 
 tokens = []
 i = 0
 while i < len(input):
 first_char = input[i]
 matched_word = __match_word(first_char, i, input)
 tokens.append(matched_word)
 i += len(matched_word)
 
 return tokens
 
 
if __name__ == '__main__':
 def get_test_text():
 import urllib2
 url = "http://news.baidu.com/n?cmd=4&class=rolling&pn=1&from=tab&sub=0"
 text = urllib2.urlopen(url).read()
 return unicode(text, 'gbk')
 
 def load_dict_test():
 load_dict()
 for first_char, words in __dict.items():
 print '%s:%s' % (first_char, ' '.join(words))
 
 def tokenize_test(text):
 load_dict()
 tokens = tokenize(text)
 for token in tokens:
 print token
 
 tokenize_test(unicode(u'美丽的花园里有各种各样的小动物'))
 tokenize_test(get_test_text())