Python Language Tutorial => Python Persistence

Example

Objects like numbers, lists, dictionaries,nested structures and class instance objects live in your computer’s memory and are lost as soon as the script ends.

pickle stores data persistently in separate file.

pickled representation of an object is always a bytes object in all cases so one must open files in wb to store data and rb to load data from pickle.

the data may may be off any kind , for example,

data={'a':'some_value',
     'b':[9,4,7],
     'c':['some_str','another_str','spam','ham'],
     'd':{'key':'nested_dictionary'},
     }

Store data

import pickle
file=open('filename','wb')  #file object in binary write mode
pickle.dump(data,file)      #dump the data in the file object
file.close()                #close the file to write into the file

Load data

import pickle
file=open('filename','rb')  #file object in binary read mode
data=pickle.load(file)      #load the data back
file.close()

>>>data
{'b': [9, 4, 7], 'a': 'some_value', 'd': {'key': 'nested_dictionary'},
 'c': ['some_str', 'another_str', 'spam', 'ham']}

The following types can be pickled

None, True, and False
integers, floating point numbers, complex numbers
strings, bytes, bytearrays
tuples, lists, sets, and dictionaries containing only picklable objects
functions defined at the top level of a module (using def, not lambda)
built-in functions defined at the top level of a module
classes that are defined at the top level of a module
instances of such classes whose dict or the result of calling getstate()

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