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  • As stated in the documentation:

    The module allows us to store almost any Python object directly to a file or string without the need to perform any conversions.

  • To do that, we can write the following script:

    The above script will output the list items:

    As mentioned in the documentation, the function does the following:

    In the above section, we saw how we can write/load pickles to/from a file.

  • We can thus do the following:

    Notice that we have used the (with an “s” at the end) function, which, according to the documentation:

    In order to restore the pickled data above, we can use the function, as follows:

    According to the documentation, what the function does is that it:

    In the above examples, we have dealt with pickling and restoring (loading) only one object at a time.

  • Say that we have the following objects:

    If you would like to learn more about Python dictionaries and tuples, check the following tutorials:

    We can simply pickle the above objects by running a series of functions, as follows:

    This will pickle all the four objects in the pickle file .

  • Let’s take an example of from the Pandas tutorial:

    In order to pickle our , we can use the function, as follows:

    To restore (load) the pickled , we can use the function, as follows:

    Putting what we have mentioned in this section all together, this is what the script that pickles and loads a pandas object looks like:

    In this tutorial, I have covered an interesting module called .

Pickles in Python are tasty in the sense that they represent a Python object as a string of bytes. Many things can actually be done with those bytes. For instance, you can store them in a file or…

@devstrong: #Python’s Pickles #reactjs #angularjs #vuejs #ionic #javascript #100daysofcode #AppDev #Coding #php #jQuery #Coders

Pickles in Python are tasty in the sense that they represent a Python object as a string of bytes. Many things can actually be done with those bytes. For instance, you can store them in a file or database, or transfer them over a network. 

The pickled representation of a Python object is called a pickle file. The pickled file thus can be used for different purposes, like storing results to be used by another Python program or writing backups. To get the original Python object, you simply unpickle that string of bytes.

module. As stated in the documentation:

The pickle module implements binary protocols for serializing and de-serializing a Python object structure. “Pickling” is the process whereby a Python object hierarchy is converted into a byte stream, and “unpickling” is the inverse operation, whereby a byte stream (from a binary file or bytes-like object) is converted back into an object hierarchy. Pickling (and unpickling) is alternatively known as “serialization”, “marshalling,” or “flattening”; however, to avoid confusion, the terms used here are “pickling” and “unpickling”.

module actually performs is what’s so called object serialization, that is, converting objects to and from strings of bytes. The object to be pickled will be serialized into a stream of bytes that can be written to a file, for instance, and restored at a later point.

list we made in the Python’s lists tutorial.

todo = [‘write blog post’, ‘reply to email’, ‘read in a book’]

), we can do the following:

list. To do that, we can write the following script:

list items:

[‘write blog post’, ‘reply to email’, ‘read in a book’]

function does the following:

In the above section, we saw how we can write/load pickles to/from a file. This is not necessary, however. I mean that if we want to write/load pickles, we don’t always need to deal with files—we can instead work with pickles as strings. We can thus do the following:

(with an “s” at the end) function, which, according to the documentation:

Returns the pickled representation of the object as a string, instead of writing it to a file.

function, as follows:

function does is that it:

In the above examples, we have dealt with pickling and restoring (loading) only one object at a time. In this section, I’m going to show you how we can do that for more than one object. Say that we have the following objects:

name = ‘Abder’ website = ‘http://abder.io’ english_french = {‘paper’:’papier’, ‘pen’:’stylo’, ‘car’:’voiture’} # dictionary tup = (31,’abder’,4.0) # tuple

If you would like to learn more about Python dictionaries and tuples, check the following tutorials:

functions, as follows:

module, as follows:

from pickle import Pickler name = ‘Abder’ website = ‘http://abder.io’ english_french = {‘paper’:’papier’, ‘pen’:’stylo’, ‘car’:’voiture’} # dictionary tup = (31,’abder’,4.0) # tuple pickled_file = open(‘pickled_file.pickle’, ‘w’) p = Pickler(pickled_file) p.dump(name); p.dump(website); p.dump(english_french); p.dump(tup)

function, as follows:

import pickle pickled_file = open(‘pickled_file.pickle’) name = pickle.load(pickled_file) website = pickle.load(pickled_file) english_french = pickle.load(pickled_file) tup = pickle.load(pickled_file) print(‘Name: ‘) print(name) print(‘Website:’) print(website) print(‘Englsh to French:’) print(english_french) print(‘Tuple data:’) print(tup)

The output of the above script is:

Name: Abder Website: http://abder.io Englsh to French: {‘car’: ‘voiture’, ‘pen’: ‘stylo’, ‘paper’: ‘papier’} Tuple data: (31, ‘abder’, 4.0)

module, as follows:

from pickle import Unpickler pickled_file = open(‘pickled_file.pickle’) u = Unpickler(pickled_file) name = u.load(); website = u.load(); english_french = u.load(); tup = u.load() print(‘Name: ‘) print(name) print(‘Website:’) print(website) print(‘English to French:’) print(english_french) print(‘Tuple data:’) print(tup)

Note that the variables have to be written and read in the same order to get the desired output. To avoid any issues here, we can use a dictionary to administer the data, as follows:

To restore (load) the data pickled in the above script, we can do the following:

import pickle pickled_file = open(‘pickled_file.pickle’) data = pickle.load(pickled_file) name = data[‘name’] website = data[‘website’] english_french = data[‘english_french_dictionary’] tup = data[‘tuple’] print(‘Name: ‘) print(name) print(‘Website:’) print(website) print(‘English to French:’) print(english_french) print(‘Tuple data:’) print(tup)

, a tabular data structure composed of ordered columns and rows.

from the Pandas tutorial:

import pandas as pd name_age = {‘Name’ : [‘Ali’, ‘Bill’, ‘David’, ‘Hany’, ‘Ibtisam’], ‘Age’ : [32, 55, 20, 43, 30]} data_frame = pd.DataFrame(name_age)

function, as follows:

function, as follows:

Putting what we have mentioned in this section all together, this is what the script that pickles and loads a pandas object looks like:

import pandas as pd name_age = {‘Name’ : [‘Ali’, ‘Bill’, ‘David’, ‘Hany’, ‘Ibtisam’], ‘Age’ : [32, 55, 20, 43, 30]} data_frame = pd.DataFrame(name_age) data_frame.to_pickle(‘my_panda.pickle’) restore_data_frame = pd.read_pickle(‘my_panda.pickle’) print(restore_data_frame)

. We have seen how easily this module enables us to store Python objects for different purposes, such as using the object with another Python program, transferring the object across a network, saving the object for later use, etc. We can simply pickle the Python object, and unpickle (load) it when we want to restore the original object.

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Python’s Pickles

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