Serialization of Python-pickle

"Python Tour" chapter III (II): Pickle serialization

Python serialization Pickle

Summary: NOTE: The description of Pickle is as follows: 1 2 3 4 5 6 7 The concept of serialization is simple. There is a data structure in memory that you want to save, reuse, or send to others. What would you do? Well, it depends on how you want to save it, how to reuse it, and who to send it to. Many games allow you to save progress when exiting, and then when you start again ...

Description: Description of Pickle

Make the following statement:

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序列化的概念很简单。内存里面有一个数据结构，你希望将它保存下来，重用，或者发送给其他人。你会怎么做？嗯, 这取决于你想要怎么保存，怎么重用，发送给谁。很多游戏允许你在退出的时候保存进度，然后你再次启动的时候回到上次退出的地方。(实际上, 很多非游戏程序也会这么干。) 在这个情况下, 一个捕获了当前进度的数据结构需要在你退出的时候保存到磁盘上，接着在你重新启动的时候从磁盘上加载进来。什么东西能用pickle模块存储?–所有Python支持的 原生类型 : 布尔, 整数, 浮点数, 复数, 字符串, bytes(字节串)对象, 字节数组, 以及 None.–由任何原生类型组成的列表，元组，字典–由任何原生类型组成的列表，元组，字典和集合组成的列表，元组，字典和集合(可以一直嵌套下去，直至Python支持的最大递归层数).–函数，类，和类的实例(带警告)。

Simple introduction and use of 1.Pickle

• A brief description of the following:

A. The data structure of the dictionary is stored in memory, saved as a file is not recognized, if you want to save, and in the next open can also be used, need to do pickle serialization storage;

B. Need to deserialize when reading;

C.pickle can save the progress of the execution of the program;

• Give instance 1:pickle save only one State

A. Storage serialization

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#!/usr/bin/env pythonimportpickleaccount_info = {‘8906143632‘:[‘alex3714‘, 15000, 15000],‘8908223631‘:[‘rachel‘, 9000,9000]}f=file(‘account.pkl‘,‘wb‘)pickle.dump(account_info,f)f.close()

B. Read serialization

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#!/usr/bin/env pythonimport pickle pkl_file = file(‘account.pkl‘,‘rb‘)account_list = pickle.load(pkl_file)pkl_file.close()print account_list

C. The results of the implementation are as follows:

123	[email  protected]:/mnt/hgfs/python/day3$ python pickle_w.py  [email  protected]:/mnt/hgfs/python/day3$ python pickle_r.py  { ' 8908223631 ' : [ ' Rachel ' ,  9000 ,  9000 ],  ' 8906143632 ' :  [ ' alex3714 ' ,  15000 ,  15000

D. The status of the dictionary is saved in the generated ACCOUNT.PKL:

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[email protected]:/mnt/hgfs/Python/day3$ cat account.pkl (dp0S‘8908223631‘p1(lp2S‘rachel‘p3aI9000aI9000asS‘8906143632‘p4(lp5S‘alex3714‘p6aI15000aI15000as.

• Instance 2:pickle save multiple states

A. The storage serialization code is modified to read as follows:

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#!/usr/bin/env pythonimportpickleaccount_info = {‘8906143632‘:[‘alex3714‘, 15000, 15000],‘8908223631‘:[‘rachel‘, 9000,9000]}f=file(‘account.pkl‘,‘wb‘)pickle.dump(account_info,f)    #第一次状态保存account_info[‘8908223631‘][0] = ‘xpleaf‘ #修改字典中的某项内容pickle.dump(account_info,f)    #第二次状态保存f.close()

B. Execute the storage serializer to save two states to the file:

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[email protected]:/mnt/hgfs/Python/day3$ python pickle_w.py [email protected]:/mnt/hgfs/Python/day3$ cat account.pkl (dp0S‘8908223631‘p1(lp2S‘rachel‘p3aI9000aI9000asS‘8906143632‘p4(lp5S‘alex3714‘p6aI15000aI15000as.(dp0S‘8908223631‘p1(lp2S‘xpleaf‘ #对比只保存一次状态的情况，这里多了修改的内容‘xpleaf‘p3aI9000aI9000asS‘8906143632‘p4(lp5S‘alex3714‘p6aI15000aI15000as.

C. Test in the interactive device:

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>>> importpickle>>> f = file(‘account.pkl‘)>>> acc1 = pickle.load(f)    #反序列化读取第一次状态的内容>>> acc2 = pickle.load(f)    #反序列化读取第二次状态的内容>>> acc3 = pickle.load(f)    #无第三次状态内容，读取失败Traceback (most recent call last):  File "<stdin>", line 1, in<module>  File "/usr/lib/python2.7/pickle.py", line 1378, inload    return Unpickler(file).load()  File "/usr/lib/python2.7/pickle.py", line 858, inload    dispatch[key](self)  File "/usr/lib/python2.7/pickle.py", line 880, inload_eof    raise EOFErrorEOFError>>> acc1{‘8908223631‘: [‘rachel‘, 9000, 9000], ‘8906143632‘: [‘alex3714‘, 15000, 15000]}>>> acc2{‘8908223631‘: [‘xpleaf‘, 9000, 9000], ‘8906143632‘: [‘alex3714‘, 15000, 15000]}

• Multiple states (dump) can be saved in one file, but it is not recommended to have one-to-one state (load);

Other instructions and use of 2.Pickle

• Serialization allows the reading of interactive data between different programs;

· Dump () in Pickle can only store the serialization of the data structure on disk, then load () and then deserialize the associated file of the calling disk;

• Use Pickle's dumps () and loads () to operate directly in memory:

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>>> acc1{‘8908223631‘: [‘rachel‘, 9000, 9000], ‘8906143632‘: [‘alex3714‘, 15000, 15000]}>>> pickle.dumps(acc1)"(dp0\nS‘8908223631‘\np1\n(lp2\nS‘rachel‘\np3\naI9000\naI9000\nasS‘8906143632‘\np4\n(lp5\nS‘alex3714‘\np6\naI15000\naI15000\nas.">>> c = pickle.dumps(acc1)>>> pickle.loads(c){‘8908223631‘: [‘rachel‘, 9000, 9000], ‘8906143632‘: [‘alex3714‘, 15000, 15000]}

• The state of the dynamic interactive program can be realized by simply providing the operation interface (example of game progress Switch, P1--P2,P1 the game progress to P2 in real time);

• JSON is just as important as pickle, and usage is similar to pickle;

• The idea of serialization plays an important role in the interaction of data structures between different platforms and different programming languages, and is not described here because it has not been studied in depth.

Serialization of Python-pickle