human
I am working on the file "Section 2 - Advance Python/Chapter S2.10 Object Serialization and Persistence/1. Object Serialization.ipynb".
The first task is:
Introduction
It 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 reverse operation, whereby a byte stream (from a binary file or bytes-like object from network) is converted back into an object hierarchy. 
Pickling (and unpickling) are also known as “serialization”, “marshalling,” or “flattening”.
Pickle module stores the following data types:

All the native data types that Python maintains: Booleans, integers, floating point numbers, complex numbers, strings, bytes objects, byte arrays, and None.
Lists, tuples, dictionaries, and sets holding any sequence of native data types.
Lists, dictionaries, tuples, and sets with the following variations.
Sets carrying any combination of lists/tuples/dictionaries, and
Sets enclosing any combination of native data types (and so on, to the max nesting level that Python allows).

Functions, classes, and the instances of classes (with limitations).

Benefits of Object Serialization / Pickle
When & Where to use
How To Use Pickle
Pickle has two primary methods. The first one is a dump that drops an object to a file. The second method is the load that loads the object from a file object.
Can you write Python code for it?
 Can you provide a the Python code you requested?
assistant
#Here is the Python code you requested.

# Step-(1) Construct Pickle Data.

# Step-(2) Saving Data As A Pickle File.

# Step-(3) Loading Data From Pickle File.

%%time
import pickle
 
users = [{
    "name": "Vijay",
    "age": 53,
    "section": "R&D",
    "keywords": ["test", "testing", "tested"]
},{
    "name": "Deenanath",
    "age": 29,
    "section": "HR",
    "keywords": ["test", "testing", "tested"]
}]

with open ('users.pickle','wb') as f:
    pickle.dump(users,f)

with open ('users.pickle', 'rb') as f:
    data = pickle.load(f)

print (data)
print(type(data))

%%time

import _pickle as pickle
 
website = {
    "id": "0001",
    "type": "donut",
    "name": "Cake",
    "ppu": 0.55,
    "batters":
        {
            "batter":
                [
                    { "id": "1001", "type": "Regular" },
                    { "id": "1002", "type": "Chocolate" },
                    { "id": "1003", "type": "Blueberry" },
                    { "id": "1004", "type": "Devil's Food" }
                ]
        },
    "topping":
        [
            { "id": "5001", "type": "None" },
            { "id": "5002", "type": "Glazed" },
            { "id": "5005", "type": "Sugar" },
            { "id": "5007", "type": "Powdered Sugar" },
            { "id": "5006", "type": "Chocolate with Sprinkles" },
            { "id": "5003", "type": "Chocolate" },
            { "id": "5004", "type": "Maple" }
        ]
}

with open ('website.pickle','wb') as f:
    pickle.dump(website,f)

with open ('website.pickle', 'rb') as f:
    data = pickle.load(f)
    print (data)
    print(type(data))

import pickle

class
human
def __init__(self, name, passwd, email ):
        self.name = name
        self.passwd = passwd
        self.email = email
        
userlist =  []
userlist.append(User("mayank", "maya@nk", "funmay@yahoo.co.in"))
userlist.append(User("Aalok", "A@10k", "allok@yahoo.co.in"))
userlist.append(User("Roshan Musheer", "R0sh@n", "Roshan@yahoo.co.in"))

with open ('userlist.pickle','wb') as f:
    pickle.dump(userlist, f)
    
users = []
with open...