python文本处理的方案(结巴分词并去除符号)

看代码吧~

import re
import jieba.analyse
import codecs
import pandas as pd
def simplification_text(xianbingshi):
    """提取文本"""
    xianbingshi_simplification = []
    with codecs.open(xianbingshi,'r','utf8') as f:
        for line in f :
            line = line.strip()
            line_write = re.findall('(?<=\<b\>).*?(?=\<e\>)',line)
            for line in line_write:
                xianbingshi_simplification.append(line)
    with codecs.open(r'C:\Users\Administrator.SC-201812211013\PycharmProjects\untitled29\yiwoqu\code\xianbingshi_write.txt','w','utf8') as f:
        for line in xianbingshi_simplification:
            f.write(line + '\n')
def jieba_text():
    """"""
    word_list = []
    data = open(r"C:\Users\Administrator.SC-201812211013\PycharmProjects\untitled29\xianbingshi_write.txt", encoding='utf-8').read()
    seg_list = jieba.cut(data, cut_all=False)  # 精确模式
    for i in seg_list:
        word_list.append(i.strip())
    data_quchong = pd.DataFrame({'a':word_list})
    data_quchong.drop_duplicates(subset=['a'],keep='first',inplace=True)
    word_list = data_quchong['a'].tolist()
    with codecs.open('word.txt','w','utf8')as w:
        for line in word_list:
            w.write(line + '\n')
def word_messy(word):
    """词语提炼"""
    word_sub_list = []
    with codecs.open(word,'r','utf8') as f:
        for line in f:
            line_sub = re.sub("^[1-9]\d*\.\d*|^[A-Za-z0-9]+$|^[0-9]*$|^(-?\d+)(\.\d+)?$|^[A-Za-z0-9]{4,40}.*?",'',line)
            word_sub_list.append(line_sub)
    word_sub_list.sort()
    with codecs.open('word.txt','w','utf8')as w:
        for line in word_sub_list:
            w.write(line.strip("\n") + '\n')
if __name__ == '__main__':
    xianbingshi = r'C:\Users\Administrator.SC-201812211013\PycharmProjects\untitled29\yiwoqu\xianbingshi_sub_sen_all(1).txt'
    # simplification_text(xianbingshi)
    # word = r'C:\Users\Administrator.SC-201812211013\PycharmProjects\untitled29\word.txt'
    simplification_text(xianbingshi)

补充：python 进行结巴分词 并且用re去掉符号

看代码吧~

# 把停用词做成字典
stopwords = {}
fstop = open('stop_words.txt', 'r',encoding='utf-8',errors='ingnore')
for eachWord in fstop:
    stopwords[eachWord.strip()] = eachWord.strip()  #停用词典
fstop.close()
f1=open('all.txt','r',encoding='utf-8',errors='ignore')
f2=open('allutf11.txt','w',encoding='utf-8')
line=f1.readline()
while line:
    line = line.strip()  #去前后的空格
    line = re.sub(r"[0-9\s+\.\!\/_,$%^*()?;；:-【】+\"\']+|[+——！，;:。？、~@#￥%……&*（）]+", " ", line) #去标点符号
    seg_list=jieba.cut(line,cut_all=False)  #结巴分词
    outStr=""
    for word in seg_list:
        if word not in stopwords:
            outStr+=word
            outStr+=" "
    f2.write(outStr)
    line=f1.readline()
f1.close()
f2.close()

以上为个人经验，希望能给大家一个参考，也希望大家多多支持编程网。