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Python学习 —— 阶段综合练习三

时间:2015-05-12 编辑:feesland 来源:本站整理

Python学习 —— 阶段综合练习三

  综合之前的类的学习,做以下实例练习:包含 文件夹及文件的操作(建议先不要看代码,自己先试着写;代码仅供参考,有多种实现方法)

  1. 目录文件遍历(二层目录结构)

    1).  使用之前学习示例的文件夹模拟;print 出对应目录的目录结构,需缩进;a. 第一行print目标目录  b.具体的二层目录结构(一层文件夹后加\),文件加文件名后缀

    2).  不仅print出结果,将上述print的内容保存至当前工作目录下的 dir_demo.txt 文件中,

      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" border="0" onload="return imgzoom(this,600);"/>  可下载后解压至D盘: http://files.cnblogs.com/files/feeland/Python_shutil.rar

        示例的要求结果如下:

           

 # !/usr/bin/config python
 # -*- coding:utf-8 -*-
 
 import os
 def listdir(d,f):
     d_list = os.listdir(d)              # 列出目录下的所有文件和目录
     print (d)
     f.write(d + '\n')
     
     for i in d_list:
         filepath = os.path.join(d,i)
         if os.path.isdir(filepath):     # 如果filepath 是目录,则再列出该目录下的所有文件
             print ('\t' + i + '\\')
             f.write('\t' + i + '\\'+'\n')
             for li in os.listdir(filepath):
                 print ('\t\t'+li)
                 f.write('\t\t'+li+'\n')
         elif os.path:                   # 如果filepath是文件,直接列出文件名
             print ('\t'+i)
             f.write('\t'+i+'\n')
     
     
 demo_dir = u"D:\Python_shutil"
 
 with open('dir_demo.txt','w') as f:
     listdir(demo_dir,f)
listdir

  示例使用 "\t" 表示缩进;注意 file.write() 函数不会自动换行,print会打印换行。

  2. 在 D:\\demo2 文件夹下,创建5个txt文件,名称及txt的内容分别为 test1、test2 ... test5

    1).  判断 D:\\demo2 文件夹是否存在,若存在,清空该文件夹里所有文件 (请务必确保无你需要的文件);若不存在,创建该文件夹

    2).  创建txt文件,示例的要求结果如下:

 import os,shutil,time
 
 os.chdir("d:\\")
 dir_name = u"demo2"
 dir_abs = os.path.join(os.getcwd(),dir_name)
 if os.path.exists(dir_abs):
     shutil.rmtree(dir_abs)
     time.sleep(1)           # 删除操作之后最好加个等待时间,不然后续 mkdir 操作可能报错
 os.mkdir(dir_name)
 os.chdir(dir_abs)
  
 for i in range(1,6):
     txt_name = "test{0}.txt".format(i)
     with open(txt_name,"w") as f:
         f.write("test{0}".format(i))
folder&txt
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