Json可以在不同语言之间使用,而pickle只能在Python使用

Json不能序列化函数,而pickle可以。但是程序使用pickle.dump序列化函数后,执行该函数的内存就会释放,在另一个程序用pickle.load重新打开读取到的内存地址对应的空间已被释放,所以无法执行该函数:

 1 #_*_coding:utf-8_*_
 2 #__author__ = "csy"
 3 import pickle
 4 def sayhi(name):
 5     print("hello,",name)
 6 
 7 info = {
 8     'name':'csy',
 9     'age':'31',
10     'job':'工人',
11     'func':sayhi
12 }
13 f = open("test.text","wb")
14 pickle.dump(info,f)   #相当于f.write(pickle.dumps(info))
15 f.close()

为了演示不报错,于是将被序列化的函数sayhi复制到调用pickle.load的Python文件:

 1 #_*_coding:utf-8_*_
 2 #__author__ = "csy"
 3 import pickle
 4 def sayhi(name):
 5     print("hello,",name)
 6 
 7 f = open("test.text","rb")
 8 data = pickle.load(f)   #相当于data = pickle.loads(f.read())
 9 f.close()
10 
11 print(data)
12 print(data['func']('csy'))

输出:

{'func': <function sayhi at 0x000000000111FEA0>, 'job': '工人', 'name': 'csy', 'age': '31'}
hello, csy
None

posted on 2017-10-07 12:54  csy113  阅读(500)  评论(0)    收藏  举报