text: Title: 如何高速处理5万多行的分词数据
  Body: 为了处理5万多行的分词数据，改写了脚本案例
  import sys,os,time
  sys.path.append(os.path.abspath(os.path.dirname(__file__) + '/' + '..'))
  from ltp import LTP
  root_path=os.path.abspath(os.path.dirname(__file__) + '/' + '..')
  ltp = LTP(path = "base")
  url = "tests/zrbzdz.txt"
  t1 = time.time()
  
  url = "tests/zrbzdz.txt"
  t1 = time.time()
  
  output=''
  with open(url,"r",encoding='utf-8-sig') as f:
      lines=f.readlines()
      for line in lines:
          segment, _ = ltp.seg([line])
          output+="/ ".join(segment[0])+'\n'
  
  tt =  time.time()-t1
  
  # 输出分词后的文件路径
  LTP_f = open("tests/output/1_LTP.txt","wb")
  LTP_f.write(output.encode('utf-8'))
  LTP_f.close()
  
  print('time ' + str(tt))
  
  执行这个脚本，数据5万多条，执行时间43分钟，怎么解决这个时间长的问题