• NLP 文本处理 工具


     


    1.中文语料常常遇到编码问题,将任意字符集文件转为utf-8编码

    复制代码
     1 import chardet 
     2 import codecs
     3 from django.utils.encoding import smart_text
     4  
     5 def check_file_charset(file):                 #查看file文件的编码 
     6     with open(file, 'rb') as f:
     7         return chardet.detect(f.read())
     8 
     9 def Convert_file_character(File_path):
    10     f_type = check_file_charset(File_path)
    11     print (File_path,"字符集为:",f_type['encoding'])       
    12     try:
    13         if f_type and 'encoding' in f_type.keys() and f_type['encoding'] != 'utf-8':
    14             with codecs.open(File_path, 'rb', f_type['encoding'],errors='ignore') as f:
    15                 content = smart_text(f.read())
    16             with codecs.open(File_path, 'wb', 'utf-8') as f:
    17                 f.write(content)
    18             print ("字符集转换成功")
    19         else:
    20             print("字符集为 utf-8,不需要进行转换")
    21     except Exception as ERR:
    22         print("字符集转换失败")
    23         print (ERR)
    24 
    25 corpus_path = './unlabel'
    26 raw_train_files = [corpus_path + os.sep + file_name for file_name in os.listdir(corpus_path)]
    27 for raw_train_file in raw_train_files:
    28     Convert_file_character(raw_train_file)
    复制代码

    参考:https://blog.csdn.net/qq_35751770/article/details/103664496

    2.将unlabel文件夹中的所有.txt文件合并,每个文件之间空一行 

    先调用上面的代码转换编码

    复制代码
     1 def combine(corpus_path, outpath):
     2     output = open(outpath, 'a', encoding='utf-8')
     3     
     4     raw_train_files = [corpus_path + os.sep + file_name for file_name in os.listdir(corpus_path)]
     5     for raw_train_file in raw_train_files:
     6         
     7         f_type = check_file_charset(raw_train_file)                    #查看文件的编码 
     8         print (raw_train_file,"字符集为:",f_type['encoding'])
     9         with open(raw_train_file, 'r+', encoding='utf-8') as f:
    10             context = f.readlines()
    11     
    12         for x in context:
    13             output.write(x)
    14         output.write('
    ')
    15 
    16 combine('./unlabel', 'all_unlabel.txt')
    复制代码

    3.随机抽取.txt文件中的60%,20%,5%

    复制代码
     1 def part(filename, outpath, ratio): 
     2     output = open(outpath, 'w+', encoding='utf-8')
     3     context = []
     4     with open(filename, 'r+', encoding='utf-8') as f:
     5         context.extend(f.readlines())
     6     
     7     length = len(context)
     8     random_order = list(range(length))
     9     np.random.shuffle(random_order)
    10     
    11     batch_size = int(length*ratio)
    12     print(batch_size)
    13     for x in context[:batch_size]:
    14         output.write(x)
    15         
    16 ratio1, ratio2, ratio3 = 0.6, 0.2, 0.05
    17 part('training/law_train.txt', 'training/law_train1.txt', ratio1)    
    18 part('training/law_train.txt', 'training/law_train2.txt', ratio2)           
    19 part('training/law_train.txt', 'training/law_train3.txt', ratio3) 
    复制代码

    4.将已经分好词的文件去掉空格(正则),恢复成文件原来的样子

    复制代码
     1 def deal_data(filename, outpath): 
     2     output = open(outpath, 'w+', encoding='utf-8')
     3     
     4     with open(filename, 'r+', encoding='utf-8') as f:
     5         context = f.readlines()
     6         for data in context:                 #data为某一行数据             
     7             x = re.sub('s+', '', data).strip()
     8             output.write(x)
     9             
    10 
    11 deal_data('evaluate/law/Law_contract_test.txt', 'evaluate/gold/Law_contract_test.txt')
    12 deal_data('evaluate/law/Law_marriage_test.txt', 'evaluate/gold/Law_marriage_test.txt')            
    13 deal_data('evaluate/law/Law_mixed_test.txt', 'evaluate/gold/Law_mixed_test.txt')
    复制代码

    5.读取excel文件转换成.json文件

    复制代码
     1 #coding=utf-8
     2 import xlrd        #对excel文件内容读取
     3 import xlwt        #对excel文件内容写入 
     4 import json
     5 """
     6 打开excel文件 处理成json文件 {text:,label:}
     7 data.xls变成train.json、val.json、test.json
     8 """
     9 
    10 def deal_data(filename,outpath):              #filename为xlsx文件路径 outputfile为json文件路径
    11     wb = xlrd.open_workbook(filename)         #打开excel文件读取数据 
    12     data_file=["train","test","val"]
    13 
    14     for excel_name in data_file:
    15         output_file = outpath + excel_name+".json"              #命名处理之后的json文件名 
    16         output = open(output_file, "w", encoding="utf-8")       #写入 
    17 
    18         excel = wb.sheet_by_name(excel_name)    #根据sheet名称获取sheet内容
    19         rows_n = excel.nrows                    #同时获取sheet总行数
    20         for i in range(rows_n):                                 #分别获取每行的第0、1、2列 
    21             data_dic = {}
    22             data_dic["filepath"] = excel.cell_value(i , 0)            
    23             data_dic["text"] = excel.cell_value(i , 1).strip()
    24             data_dic["label"] = tuple(excel.cell_value(i , 2).split())
    25 
    26             output.write(json.dumps(data_dic) + "
    ")           #写入json文件 
    27         output.close()
    28 
    29 deal_data("data01.xls","corpus/class/origin_corpus/")
    复制代码
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  • 原文地址:https://www.cnblogs.com/wszme/p/14846058.html
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