说到分词大家肯定一般认为是很高深的技术，但是今天作者用短短几十行代码就搞定了，感叹python很强大啊！作者也很强大。不过这个只是正向最大匹配，没有机器学习能力
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&
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())