Python学习之路：json and pickle序列化

序列化实现方法：

#不实用模块
# info ={
#     'name':'alex',
#     'age':22
#
# }
# f = open("test.text","w")
# f.write(str(info))
#
# f.close()

#json 序列化简单数据类型
# import json
#
# info ={
#     'name':'alex',
#     'age':22
#
# }
# f = open("test.text","w")
# f.write(json.dumps(info))
# f.close()

#python会跟JAVA，C语言做交互，其中需要一个中间交互语言---json，能处理的都是简单的数据类型

# import json
# def sayhi(name):
#     print("hello,",name)
#
# info ={
#     'name':'alex',
#     'age':22,
#     'func':sayhi
#
# }
# f = open("test.text","w")
# f.write(json.dumps(info))#报错，函数不可序列化


import pickle#pickle可以序列化Python中所有数据类型
def sayhi(name):
    print("hello,",name)

info ={
    'name':'alex',
    'age':22,
    'func':sayhi

}
f = open("test.text","wb")
f.write(pickle.dumps(info))

 反序列化相应方法：

# f = open("test.text","r")
# data = eval(f.read())
# f.close()
#
# print(data['age'])


# import json
#
# f = open("test.text","r")
# data = json.loads(f.read())
#
# print(data['age'])

#pickle只能在Python语言内部使用
import pickle#f反序列化的整个数据对象
def sayhi(name):
    print("hello,",name)
    print("hello2,",name)

f =open("test.text","rb")
data =pickle.loads(f.read())#data=pickle.load(f)
print(data["func"]('alex'))

 Python3.X可以多次json.dumps,但是只能一次json.loads,建议每个程序只一次json.dumps,一次json.loads

import json


info ={
    'name':'alex',
    'age':22

}
f = open("test.text","w")
f.write(json.dumps(info))

info['age']=21

f.write(json.dumps(info))

f.close()

 pickle.dumps与pickle.dump;pickle.loads与pickle.load

import pickle#pickle可以序列化Python中所有数据类型
def sayhi(name):
    print("hello,",name)

info ={
    'name':'alex',
    'age':22,
    'func':sayhi

}
f = open("test.text","wb")
pickle.dump(info,f)#f.write(pickle.dumps(info))
f.close()

----------------------------------------------------------------

#pickle只能在Python语言内部使用
import pickle#f反序列化的整个数据对象
def sayhi(name):
    print("hello,",name)
    print("hello2,",name)

f =open("test.text","rb")
data =pickle.loads(f.read())#data=pickle.load(f)
print(data["func"]('alex'))