手记实用系列文章：

代码封装类：

#!/usr/bin/env python

# -*- coding:utf-8 -*-

import jieba

import os

import re

import time

from jpype import *

'''

title：利用结巴分词进行文本语料的批量处理

1 首先对文本进行遍历查找

2 创建原始文本的保存结构

3 对原文本进行结巴分词和停用词处理

4 对预处理结果进行标准化格式，并保存原文件结构路径

author：白宁超

myblog：http://www.cnblogs.com/baiboy/

time：2017年4月28日10:03:09

'''

'''

创建文件目录

path:根目录下创建子目录

'''

def mkdir(path):

# 判断路径是否存在

isExists=os.path.exists(path)

# 判断结果

if not isExists:

os.makedirs(path)

print(path+' 创建成功')

return True

else:

pass

print('-->请稍后，文本正在预处理中...')

'''

结巴分词工具进行中文分词处理：

read_folder_path：待处理的原始语料根路径

write_folder_path 中文分词经数据清洗后的语料

'''

def CHSegment(read_folder_path,write_folder_path):

stopwords ={}.fromkeys([line.strip() for line in open('../Database/stopwords/CH_stopWords.txt','r',encoding='utf-8')]) # 停用词表

# 获取待处理根目录下的所有类别

folder_list = os.listdir(read_folder_path)

# 类间循环

# print(folder_list)

for folder in folder_list:

#某类下的路径

new_folder_path = os.path.join(read_folder_path, folder)

# 创建一致的保存文件路径

mkdir(write_folder_path+folder)

#某类下的保存路径

save_folder_path = os.path.join(write_folder_path, folder)

#某类下的全部文件集

# 类内循环

files = os.listdir(new_folder_path)

j = 1

for file in files:

if j > len(files):

break

# 读取原始语料

raw = open(os.path.join(new_folder_path, file),'r',encoding='utf-8').read()

# 只保留汉字

# raw1 = re.sub("[A-Za-z0-9\[\`\~\!\@\#\$\^\&\*\(\)\=\|\{\}\'\:\;\'\,\[\]\.\\/\?\~\！\@\#\\\&\*\%]", "", raw)

# jieba分词

wordslist = jieba.cut(raw, cut_all=False) # 精确模式

# 停用词处理

cutwordlist=''

for word in wordslist:

if word not in stopwords and word=="\n":

cutwordlist+="\n" # 保持原有文本换行格式

elif len(word)>1 :

cutwordlist+=word+"/" #去除空格

#保存清洗后的数据

with open(os.path.join(save_folder_path,file),'w',encoding='utf-8') as f:

f.write(cutwordlist)

j += 1

'''

结巴分词工具进行中文分词处理：

read_folder_path：待处理的原始语料根路径

write_folder_path 中文分词经数据清洗后的语料

'''

def HanLPSeg(read_folder_path,write_folder_path):

startJVM(getDefaultJVMPath(), "-Djava.class.path=C:\hanlp\hanlp-1.3.2.jar;C:\hanlp", "-Xms1g", "-Xmx1g") # 启动JVM，Linux需替换分号;为冒号:

stopwords ={}.fromkeys([line.strip() for line in open('../Database/stopwords/CH_stopWords.txt','r',encoding='utf-8')]) # 停用词表

# 获取待处理根目录下的所有类别

folder_list = os.listdir(read_folder_path)

# 类间循环

# print(folder_list)

for folder in folder_list:

#某类下的路径

new_folder_path = os.path.join(read_folder_path, folder)

# 创建一致的保存文件路径

mkdir(write_folder_path+folder)

#某类下的保存路径

save_folder_path = os.path.join(write_folder_path, folder)

#某类下的全部文件集

# 类内循环

files = os.listdir(new_folder_path)

j = 1

for file in files:

if j > len(files):

break

# 读取原始语料

raw = open(os.path.join(new_folder_path, file),'r',encoding='utf-8').read()

# HanLP分词

HanLP = JClass('com.hankcs.hanlp.HanLP')

wordslist = HanLP.segment(raw)

#保存清洗后的数据

wordslist1=str(wordslist).split(",")

# print(wordslist1[1:len(wordslist1)-1])

flagresult=""

# 去除标签

for v in wordslist1[1:len(wordslist1)-1]:

if "/" in v:

slope=v.index("/")

letter=v[1:slope]

if len(letter)>0 and '\n\u3000\u3000' in letter:

flagresult+="\n"

else:flagresult+=letter +"/" #去除空格

# print(flagresult)

with open(os.path.join(save_folder_path,file),'w',encoding='utf-8') as f:

f.write(flagresult.replace(' /',''))

j += 1

shutdownJVM()

if __name__ == '__main__' :

print('开始进行文本分词操作：\n')

t1 = time.time()

dealpath="../Database/SogouC/FileTest/"

savepath="../Database/SogouCCut/FileTest/"

# 待分词的语料类别集根目录

read_folder_path = '../Database/SogouC/FileNews/'

write_folder_path = '../Database/SogouCCut/'

#jieba中文分词

CHSegment(read_folder_path,write_folder_path) #300个txtq其中结巴分词使用3.31秒

HanLPSeg(read_folder_path,write_folder_path) #300个txt其中hanlp分词使用1.83秒

t2 = time.time()

print('完成中文文本切分: '+str(t2-t1)+"秒。")

运行效果：