JSON and pickle of Python serialization

1. JSON INTRODUCTION

JSON (JavaScript Object Notation) is a lightweight data interchange format. Easy for people to read and Write. It is also easy for machine parsing and Generation. It is based on JavaScript programming Language, standard ECMA-262 a subset of 3rd Edition-december 1999. JSON takes a completely language-independent text format, but also uses a similar idiom to the C language family (c, C + +, c #, Java, JavaScript, Perl, python, etc.). These features make JSON an ideal data exchange Language.

The JSON module can be used to encode JSON data in Python3, which contains two functions:

1. Json.dumps (): encode the data
2. Json.loads (): Decoding the data

Json.dumps and Json.loads instances

The following example demonstrates the conversion of a PYTHON data structure to a JSON

1 #!/usr/bin/env python2 #_*_ coding:utf-8 _*_3 #Author:enzhi.wang4 ImportJSON5 #convert the underlying data type of Python into a string6DIC = {"K1":"v1","K2":"v2"}7 Print("python raw Data:", repr (dic), type (dic )8result = Json.dumps (dic)#converting a dictionary type to a string type9 Print("JSON object:", Result,type (result))

Execute the above code to output the Result:

C:\Python3.5\python.exe c:/users/root/pycharmprojects/s14/day4/JSON Serialization. Pypython Raw Data: {'K1':'v1','K2':'v2'} <class 'Dict'>JSON object: {"K1":"v1","K2":"v2"} <class 'Str'>

The result of the output shows that the simple type is very similar by encoding followed by its original repr () Output.

next, we can convert a json-encoded string back to a python data structure:

1 #!/usr/bin/env python2 #_*_ coding:utf-8 _*_3 #Author:enzhi.wang4 ImportJSON5 #convert the underlying data type of Python into a string6DIC = {"K1":"v1","K2":"v2"}7 Print("python raw Data:", repr (dic), type (dic )8result = Json.dumps (dic)#converting a dictionary type to a string type9 Print("JSON object:", Result,type (result))Ten  one #To convert a Python string type to a python base data type aresult =json.loads (result) - Print("result[' K1 ']:", result['K1']) - Print("result[' K2 ']:", result['K2'])

Execute the above code to output the Result:

C:\Python3.5\python.exe c:/users/root/pycharmprojects/s14/day4/JSON Serialization. Pypython Raw Data: {'K1':'v1','K2':'v2'} <class 'Dict'>JSON object: {"K1":"v1","K2":"v2"} <class 'Str'>result['K1']: v1result['K2']: v2

If you are dealing with files instead of strings, you can use json.dump () and json.load () to encode and decode JSON Data. For example:

1data = {2     "name":"Wangenzhi",3     " age": 25,4     "Job":"Ops"5 }6 #Writing JSON data7With open ('Db.json','W') as F:8 json.dump (data,f)9 Ten #Reading JSON data oneWith open ('Db.json','R') as F: ares =json.load (f) -     Print(res,type (RES))

For more information, please refer to: https://docs.python.org/3/library/json.html

2, Pickle Introduction

The data format used by the Pickle module is python-specific and is not backwards compatible with different versions and cannot be recognized by other Languages. To interact with other languages, you can use the built-in JSON package with the Pickle module you can save Python objects directly to a file without having to convert them to a string, or write them into a binary file without the underlying file access Operation. The Pickle module creates a python-language-specific binary format, and you basically don't have to consider any file details, it will help you cleanly complete the read and write exclusive operation, only need a valid file Handle.

The Python3 can be used to encode and decode the data using the pickle Module. It consists of two functions:

1. Pickle.dumps ()
2. Pickle.loads ()

Pickle.dumps and Pickle.loads instances

1 #!/usr/bin/env python2 #_*_ coding:utf-8 _*_3 #Author:enzhi.wang4 ImportPickle5 6data = {7     "name":"Wangenzhi",8     " age": 25,9     "Job":"Ops"Ten } one  a Print("Original Python object:", repr (data)) -R =pickle.dumps (data) - Print("Pickle the converted Object:", R) theres =pickle.loads (r) - Print("res[' name ']:", res['name']) - Print("res[' Age ']:", res[' age']) - Print("res[' Job ']:", res['Job'])

Execute the above code to output the Result:

C:\Python3.5\python.exe c:/users/root/pycharmprojects/s14/day4/Pickle serialization. py original python object: {'name':'Wangenzhi','Job':'Ops',' age': 25}pickle converted Object: B'\x80\x03}q\x00 (x\x04\x00\x00\x00nameq\x01x\t\x00\x00\x00wangenzhiq\x02x\x03\x00\x00\x00jobq\x03x\x03\x00\ X00\x00opsq\x04x\x03\x00\x00\x00ageq\x05k\x19u.'res['name']: wangenzhires[' age']: 25res['Job']: Ops

If you are dealing with files instead of strings, you can use pickle.dump () and pickle.load () to encode and decode JSON Data. For example:

1 ImportPickle2 3data = {4     "name":"Wangenzhi",5     " age": 25,6     "Job":"Ops"7 }8 #write data to be written in WB format9Pickle.dump (data,open ('DB','WB'))Ten #read data, to be read in RB format onef = open ('DB','RB') ares =pickle.load (f) - Print(res)

Execute the above code to output the Result:

C:\Python3.5\python.exe c:/users/root/pycharmprojects/s14/day4/Pickle serialization. py{'job  'ops''name' 'wangenzhi'  'age': 25}

Summary

JSON: for cross-language, python-only for Python basic data types

Pickle: applies only to Python,pickle serialization for all data types in Python

JSON and pickle of Python serialization