Python Persistence


  • pickle.dump(obj, file, protocol=None, *, fix_imports=True)

  • pickle.load(file, *, fix_imports=True, encoding="ASCII", errors="strict")


objpickled representation of obj to the open file object file
protocolan integer, tells the pickler to use the given protocol,0-ASCII, 1- old binary format
fileThe file argument must have a write() method wb for dump method and for loading read() method rb

Function utility for save and load

Save data to and from file

import pickle
def save(filename,object):

def load(filename):
    return object

[1, 1, 2, 3, 5, 8, 'a', 'e', 'i', 'o', 'u'

Python Persistence

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,


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

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

The following types can be pickled

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