python-fullstack-s13-day24-python模块部分

Json模块提供了四个功能：dumps、dump、loads、load
1 import json
2 # dumps loads一般用于网络传输数据使用，可在多语言环境中使用，但是只支持str,dict,list,bool
3 dic = {"alex": ["woman", "man", "lady_boy"], "age": 13, "hobby": "老女人"}
4 ret = json.dumps(dic)
5 ret2 = json.dumps(dic, ensure_ascii=False)  # dumps()括号内可加参数，indent缩进量等参数
6 print(ret)      # {"alex": ["woman", "man", "lady_boy"], "age": 13, "hobby": "\u8001\u5973\u4eba"}
7 print(ret2)     # {"alex": ["woman", "man", "lady_boy"], "age": 13, "hobby": "老女人"}
8 dic_ret = json.loads(ret)
9 print(dic_ret)  # {‘alex‘: [‘woman‘, ‘man‘, ‘lady_boy‘], ‘age‘: 13, ‘hobby‘: ‘老女人‘}

 1 import json
 2 # 利用json的dumps loads向文件中写多条数据读取多行数据
 3 dic = {"alex": ["woman", "man", "lady_boy"], "age": 13, "hobby": "老女人"}
 4 dic1 = {"alex1": ["woman", "man", "lady_boy"], "age": 13, "hobby": "老女人"}
 5 dic2 = {"alex2": ["woman", "man", "lady_boy"], "age": 13, "hobby": "老女人"}
 6 with open("dumps", mode="w", encoding="utf-8") as f:
 7     f.write(json.dumps(dic) + "\n")
 8     f.write(json.dumps(dic1) + "\n")
 9     f.write(json.dumps(dic2) + "\n")
10 
11 with open("dumps", encoding="utf-8") as f1:
12     for line in f1:
13         print(json.loads(line))

 1 import json
 2 
 3 dic = {"alex": ["woman", "man", "lady_boy"], "age": 13, "hobby": "老女人"}
 4 dic1 = {"alex1": ["woman", "man", "lady_boy"], "age": 13, "hobby": "老女人"}
 5 dic2 = {"alex2": ["woman", "man", "lady_boy"], "age": 13, "hobby": "老女人"}
 6 with open("file", mode="w", encoding="utf-8") as f:
 7     json.dump(dic, f)
 8     # json.dump(dic1, f)
 9     # json.dump(dic2, f)
10 # 能够成功向文件中写入多条数据，但都是写到一行上，而外读取的时候会发生错误。只有写入时是一条数据的时候不会发生错误。
11 with open("file", encoding="utf-8") as f2:
12     print(json.load(f2))

Serialize obj to a JSON formatted str.(字符串表示的json对象)
Skipkeys：默认值是False，如果dict的keys内的数据不是python的基本类型(str,unicode,int,long,float,bool,None)，设置为False时，就会报TypeError的错误。此时设置成True，则会跳过这类key
ensure_ascii:，当它为True的时候，所有非ASCII码字符显示为\uXXXX序列，只需在dump时将ensure_ascii设置为False即可，此时存入json的中文即可正常显示。)
If check_circular is false, then the circular reference check for container types will be skipped and a circular reference will result in an OverflowError (or worse).
If allow_nan is false, then it will be a ValueError to serialize out of range float values (nan, inf, -inf) in strict compliance of the JSON specification, instead of using the JavaScript equivalents (NaN, Infinity, -Infinity).
indent：应该是一个非负的整型，如果是0就是顶格分行显示，如果为空就是一行最紧凑显示，否则会换行且按照indent的数值显示前面的空白分行显示，这样打印出来的json数据也叫pretty-printed json
separators：分隔符，实际上是(item_separator, dict_separator)的一个元组，默认的就是(‘,’,’:’)；这表示dictionary内keys之间用“,”隔开，而KEY和value之间用“：”隔开。
default(obj) is a function that should return a serializable version of obj or raise TypeError. The default simply raises TypeError.
sort_keys：将数据根据keys的值进行排序。
To use a custom JSONEncoder subclass (e.g. one that overrides the .default() method to serialize additional types), specify it with the cls kwarg; otherwise JSONEncoder is used.

其他参数说明

用于序列化的两个模块

• json，用于字符串 和 python数据类型间进行转换
• pickle，用于python特有的类型 和 python的数据类型间进行转换

pickle模块提供了四个功能：dumps、dump(序列化，存）、loads（反序列化，读）、load  （不仅可以序列化字典，列表...可以把python中任意的数据类型序列化）

1 import pickle
2 # 用于网络传输的时候会将数据转化为bytes类型
3 dic = {"alex": ["woman", "man", "lady_boy"], "age": 13, "hobby": "老女人"}
4 print(pickle.dumps(dic))    # b‘\x80\x03}q\x00(X\x04\x00\x00\x00alexq\x01]q\    bytes字节类型数据
5 print(pickle.loads(pickle.dumps(dic)))  # {‘alex‘: [‘woman‘, ‘man‘, ‘lady_boy‘], ‘age‘: 13, ‘hobby‘: ‘老女人‘}

import pickle
dic = {"alex": ["woman", "man", "lady_boy"], "age": 13, "hobby": "老女人"}
dic1 = {"alex1": ["woman", "man", "lady_boy"], "age": 13, "hobby": "老女人"}
dic2 = {"alex2": ["woman", "man", "lady_boy"], "age": 13, "hobby": "老女人"}
with open("files", mode="wb") as f1:    # 因为dump出来的是bytes类型的数据，所以向文件中写入到时候要选择b类型操作
    pickle.dump(dic, f1)        # dump()可多次向一个文件中写入多条数据
    pickle.dump(dic1, f1)
    pickle.dump(dic2, f1)
    pickle.dump(dic2, f1)
    pickle.dump(dic2, f1)
    pickle.dump(dic2, f1)


with open("files", mode="rb") as f2:
    while True:     # 读取的时候当文件句柄为生成器
        try:
            print(pickle.load(f2))
        except EOFError:
            break

 1 import shelve
 2 f = shelve.open(‘shelve_file‘)
 3 f[‘key‘] = {‘int‘:10, ‘float‘:9.5, ‘string‘:‘Sample data‘}  #直接对文件句柄操作，就可以存入数据
 4 f.close()
 5 
 6 import shelve
 7 f1 = shelve.open(‘shelve_file‘)
 8 existing = f1[‘key‘]  #取出数据的时候也只需要直接用key获取即可，但是如果key不存在会报错
 9 f1.close()
10 print(existing)

1 import shelve
2 f = shelve.open(‘shelve_file‘, flag=‘r‘)
3 existing = f[‘key‘]
4 f.close()
5 print(existing)

import shelve
f1 = shelve.open(‘shelve_file‘)
print(f1[‘key‘])
f1[‘key‘][‘new_value‘] = ‘this was not here before‘
f1.close()

f2 = shelve.open(‘shelve_file‘, writeback=True)
print(f2[‘key‘])
f2[‘key‘][‘new_value‘] = ‘this was not here before‘
f2.close()