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professionClean.py
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professionClean.py
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# -*- coding: utf-8 -*-
# -*- author: JeremySun -*-
# -*- dating: 19/12/24 -*-
# 模块导入
import os
import re
import time
from tqdm import tqdm
from functools import wraps
from pyltp import SentenceSplitter
# ltp模型目录路径
LTP_DATA_DIR = "D:/PyLTP/ltp_data"
# 数据导入
def batch_file(path, file_list):
for file in os.listdir(path):
fs = os.path.join(path, file)
if os.path.isfile(fs):
file_list.append(fs)
elif os.path.isdir(fs):
batch_file(fs, file_list)
return file_list
# 匹配网页标签
def loss_html(text):
pattern_tag = re.compile('</?\w+[^>]*>') # HTML标签
text_html = re.sub(pattern=pattern_tag, repl='', string=str(text))
return text_html
# 匹配标签
def loss_label(text):
pattern_img = re.compile(r"<(img|IMG)(.*?)(/>|></img>|>)")
text_img = re.sub(pattern=pattern_img, repl='', string=str(text))
pattern_video = re.compile(r'<(video)(.*?)(/>|></video>|>)')
text_video = re.sub(pattern=pattern_video, repl='', string=str(text_img))
pattern_src = re.compile(r"(src|SRC)=(\"|\')(.*?)(\"|\')")
text_src = re.sub(pattern=pattern_src, repl='', string=str(text_video))
pattern_div = re.compile(r'/<div(([\s\S])*?)<\/div>/g')
text_div = re.sub(pattern=pattern_div, repl='', string=str(text_src))
pattern_span = re.compile(r"<(span)(.*?)(/>|></span>|>)")
text_span = re.sub(pattern=pattern_span, repl='', string=str(text_div))
pattern_again = re.compile(r'</span>')
text_span_again = re.sub(pattern=pattern_again, repl='', string=str(text_span))
pattern_p1 = re.compile(r'<(p)(.*?)(/>|></p>|>)')
text_p1 = re.sub(pattern=pattern_p1, repl='', string=str(text_span_again))
pattern_p2 = re.compile(r'(</p>)')
text_p2 = re.sub(pattern=pattern_p2, repl='', string=str(text_p1))
pattern_p3 = re.compile(r'(<p)')
text_p3 = re.sub(pattern=pattern_p3, repl='', string=str(text_p2))
return text_p3
# 匹配邮箱
def loss_mail(text):
pattern_mail = re.compile('[\w]+(\.[\w]+)*@[\w]+(\.[\w])+')
text_mail = re.sub(pattern=pattern_mail, repl='', string=str(text))
return text_mail
# 匹配特殊标点
def loss_other(text):
pattern_other = re.compile(r'[\u4e00-\u9fa5]|[\u0030-\u0039]|[\u0041-\u005a]|[\u0061-\u007a]|[,，。 \.;：/\\:\/!！？?]|[\s]]')
text_other = re.findall(pattern=pattern_other, string=str(text))
text_other = ''.join(text_other)
return text_other
# 匹配网址
def loss_url(text):
pattern_url1 = re.compile(r'(https?|ftp|file|img3):\/\/[a-z0-9_.:]+\/[-a-z0-9_:@&?=+,.!/~*%$]*(\.(html|htm|shtml))?')
pattern_url2 = re.compile(r'^https?:\/\/([^/:]+)(:(\d)+)?(/.*)?$')
pattern_url3 = re.compile(r'^([a-z0-9]\.|[a-z0-9][-a-z0-9]{0,61}[a-z0-9]\.)(com|edu|gov|int|mil|net|org|biz|info|name|museum|coop|aero|[a-z][a-z])$')
pattern_url4 = re.compile(r'(网|网站|网站是|网址|网址是|平台|点击|店|地址|微信公众号|微信号|微信|微信号是|公众号|公众号是)[A-Z.a-z.0-9]{1,100}')
pattern_url5 = re.compile(r'(https?|ftp|file|img3)://[-A-Za-z0-9+&@#/%?=~_|!:,.;]+[-A-Za-z0-9+&@#/%=~_|]')
pattern_url6 = re.compile(r'(www.)[a-zA-Z0-9\-\.]+')
pattern_url7 = re.compile(r'(网：|网站：|网站是：|网址：|网址是：|点击：|店：|微信公众号：|微信号：|微信：|微信号是：|公众号：|公众号是)[A-Z.a-z.0-9]{1,100}')
pattern_url8 = re.compile(r'(网:|网站:|网站是:|网址:|网址是:|点击:|店:|微信公众号:|微信号:|微信:|微信号是:|公众号:|公众号是)[A-Z.a-z.0-9]{1,100}')
text_url1 = re.sub(pattern=pattern_url1, repl='', string=str(text))
text_url2 = re.sub(pattern=pattern_url2, repl='', string=str(text_url1))
text_url3 = re.sub(pattern=pattern_url3, repl='', string=str(text_url2))
text_url4 = re.sub(pattern=pattern_url4, repl='', string=str(text_url3))
text_url5 = re.sub(pattern=pattern_url5, repl='', string=str(text_url4))
text_url6 = re.sub(pattern=pattern_url6, repl='', string=str(text_url5))
text_url7 = re.sub(pattern=pattern_url7, repl='', string=str(text_url6))
text_url = re.sub(pattern=pattern_url8, repl='', string=str(text_url7))
return text_url
# 匹配网址
def clean_url(text):
pattern_in = re.compile(r'（网.*?）')
corpus_in = re.sub(pattern=pattern_in, repl='', string=str(text))
pattern_out = re.compile(r'网（.*?）')
corpus_out = re.sub(pattern=pattern_out, repl='', string=str(corpus_in))
pattern_none = re.compile(r'网站\s.*?）')
corpus_none = re.sub(pattern=pattern_none, repl='', string=str(corpus_out))
pattern_sim = re.compile(r'网址\s.*?）')
corpus_sim = re.sub(pattern=pattern_sim, repl='', string=str(corpus_none))
return corpus_sim
# 匹配连续英文
def loss_continue(text):
pattern_continue = re.compile(r'[A-Za-z ]{13,100}')
text_continue = re.sub(pattern=pattern_continue, repl='', string=str(text))
return text_continue
# 匹配特定单词
def loss_word(text):
pattern_word = re.compile(r'nbsp|video|videobr|epdm|br|alt|img|ref|picType1|imageUrl|divclass|high34|normal34|0datavid|div')
text_word = re.sub(pattern=pattern_word, repl='', string=str(text))
return text_word
# 匹配逗号
def loss_comma(text):
pattern_comma = re.compile(r"[，,：:]") # 加：:
text_comma = re.sub(pattern=pattern_comma, repl='。', string=str(text))
return text_comma
# 去掉空行
def delBlankline(infile, outfile):
infopen = open(infile, 'r', encoding="utf-8")
outfopen = open(outfile, 'w', encoding="utf-8")
lines = infopen.readlines()
for line in lines:
if line.split():
outfopen.writelines(line)
else:
outfopen.writelines("")
infopen.close()
outfopen.close()
# 定义timer
def func_timer(function):
@wraps(function)
def function_timer(*args, **kwargs):
print('[Function: {name} start...]'.format(name=function.__name__))
t0 = time.time()
result = function(*args, **kwargs)
t1 = time.time()
print('[Function: {name} finished, spent time: {time:.2f}s]'.format(name=function.__name__, time=t1 - t0))
return result
return function_timer
# 定义main()函数
@func_timer
def main():
file_list = []
path = r'D:\实习数据备份\备份\professional'
file_path = batch_file(path=path, file_list=file_list)
for path in file_path:
profession_text_connect = open(path, encoding='utf-8').readlines()
assetPath_loss_html = loss_html(text=profession_text_connect)
assetPath_loss_label = loss_label(text=assetPath_loss_html)
assetPath_loss_mail = loss_mail(text=assetPath_loss_label)
assetPath_loss_other = loss_other(text=assetPath_loss_mail)
assetPath_loss_url = loss_url(text=assetPath_loss_other)
assetPath_clean_url = clean_url(text=assetPath_loss_url)
assetPath_loss_continue = loss_continue(text=assetPath_clean_url)
assetPath_loss_word = loss_word(text=assetPath_loss_continue)
assetPath_loss_comma = loss_comma(text=assetPath_loss_word)
# 分句
assetPath_sentence = SentenceSplitter.split(assetPath_loss_comma)
# 去掉其余符号并写入文件
pattern_all = re.compile(r"[。.；;:：？?!！/|]") # 加：:
f = open("profession_pre.txt", 'a', encoding='utf-8')
for i in tqdm(assetPath_sentence):
i = re.sub(pattern=pattern_all, repl='', string=i)
f.write(i + '\n')
f.close()
# delBlankline("assetPath_sentence_pre.txt", "assetPath_sentence.txt")
if __name__ == '__main__':
main()