pickle文件序列化

1.使用pickle将list序列化

# -*- coding: cp936 -*-
'''
pickle一个list,将数据写入文件
'''
import pickle
d = range(0,200,5)
f = file("c:\\pickleList.dat","w")
p = pickle.dump(d,f)
f.close()
2.将序列化的数据读入
# -*- coding: cp936 -*-
'''
pickle一个list,将数据从文件中读取出来
'''
import pickle
f = file("c:\\pickleList.dat","r")
p = pickle.load(f)
f.close()
print p
与list相同的还有：

None, True, and False

• integers, long integers, floating point numbers, complex numbers
  
• normal and Unicode strings
  
• tuples, lists, sets, and dictionaries containing only picklable objects
  3.将函数序列化
  # -*- coding: cp936 -*-
  '''使用pickle序列化对象
  1.将pickleTest写入文件
  2.函数、类pickle的是refence不是value
  '''
  import pickle
  def pickleTest(val = None):
      print val
  l = [pickleTest,pickleTest]
  f = file("c:\\pickleTest.dat","wb")
  p = pickle.dump(pickleTest,f)
  f.close()
  4.将函数从文件中读取出来
  # -*- coding: cp936 -*-
  '''使用pickle序列化对象
  1.使用load从文件中载入对象，并执行代码
  2.必须使用import，pickle不会对函数的代码进行处理
  '''
  import pickle
  import test
  f = file("c:\\pickleTest.dat","rb")
  p = pickle.load(f)
  f.close()
  p("jcodeer")
  与函数相同的还有如下：
  
• functions defined at the top level of a module
  
• built-in functions defined at the top level of a module
  
• classes that are defined at the top level of a module
  
• instances of such classes whose __dict__ or __setstate__() is picklable