The pickle of Python

The

pickle module can serialize objects and save them to disk and read them when needed, and any object can perform serialization operations. In machine learning, we often need to store a well-trained model so that we can make decisions by simply putting the model alone, without having to retrain the model, which saves time.

Pickle Module Common functions

Dump (Obj,file,[,protocol])	Serializes an Obj object into a file that is already open
Load (file)	Serializing an object in file to read
Dumps (Obj,[,protocol])	Serializes an Obj object into a string, rather than depositing it in a file
Loads (String)	Reads the Obj object before serialization from a string

Example

#Coding=utf-8Importpickledatalist= [[1, 1,'Yes'],             [1, 1,'Yes'],             [1, 0,'No'], [0,1,'No'], [0,1,'No']] Datadict= {0: [1, 2, 3, 4],              1: ('a','b'),              2: {'C':'Yes','D':'No'}} with open ("Pickle_test.txt","WB"as Writefp:pickle.dump (DataList, WRITEFP) Pickle.dump (Datadict, WRITEFP) with open ("Pickle_test.txt","RB") as Readfp:data1=pickle.load (READFP) data2=pickle.load (READFP)Print(data1)Print(DATA2) p=Pickle.dumps (DataList)Print(Pickle.loads (P)) p=pickle.dumps (datadict)Print(Pickle.loads (P))

>>> [[1, 1, ' yes '], [1, 1, ' yes '], [1, 0, ' no '], [0, 1, ' no '], [0, 1, ' no ']
>>> {0: [1, 2, 3, 4], 1: (' A ', ' B '), 2: {' c ': ' Yes ', ' d ': ' No '}}
>>> [[1, 1, ' yes '], [1, 1, ' yes '], [1, 0, ' no '], [0, 1, ' no '], [0, 1, ' no ']
>>> {0: [1, 2, 3, 4], 1: (' A ', ' B '), 2: {' c ': ' Yes ', ' d ': ' No '}}

dump and load have another ability compared to dumps and loads: the dump () function can sequentially store several objects in the same file, and then call Load () to deserialize the objects in the same order

The pickle of Python