import pickle

# define any Python data structure including lists, sets, tuples, dicts, etc.
l = list(range(10000))

# save it to a file
with open("list.pickle", "wb") as file:
    pickle.dump(l, file)

# load it again
with open("list.pickle", "rb") as file:
    unpickled_l = pickle.load(file)

print("unpickled_l == l: ", unpickled_l == l)
print("unpickled l is l: ", unpickled_l is l)

unpickled_l == l:  True
unpickled l is l:  False

class Person:
    def __init__(self, first_name, last_name, age, gender):
        self.first_name = first_name
        self.last_name = last_name
        self.age = age
        self.gender = gender

    def __str__(self):
        return f"{self.first_name} {self.last_name}, age={self.age}, gender={self.gender}>"

p = Person("John", "Doe", 99, "Male")

# save the object
with open("person.pickle", "wb") as file:
    pickle.dump(p, file)

# load the object
with open("person.pickle", "rb") as file:
    p2 = pickle.load(file)

print(p)
print(p2)

<Person name=John Doe, age=99, gender=Male>
<Person name=John Doe, age=99, gender=Male>

# get the dumped bytes
dumped_p = pickle.dumps(p)
print(dumped_p)

# write them to a file
with open("person.pickle", "wb") as file:
    file.write(dumped_p)

# load it
with open("person.pickle", "rb") as file:
    p2 = pickle.loads(file.read())

b'\x80\x03c__main__\nPerson\nq\x00)\x81q\x01}q\x02(X\n\x00\x00\x00first_nameq\x03X\x04\x00\x00\x00Johnq\x04X\t\x00\x00\x00last_nameq\x05X\x03\x00\x00\x00Doeq\x06X\x03\x00\x00\x00ageq\x07KcX\x06\x00\x00\x00genderq\x08X\x04\x00\x00\x00Maleq\tub.'

• কিছুই না ।
• বুলিয়ান ভেরিয়েবল ( সত্য এবং মিথ্যা )।
• পূর্ণসংখ্যা, ভাসমান পয়েন্ট সংখ্যা এবং জটিল সংখ্যা।
• স্ট্রিং, বাইট, বাইটারি।
• টিপলস, তালিকা, সেট এবং অভিধানে কেবল বাছাইযোগ্য অবজেক্ট রয়েছে objects
• একটি মডিউল শীর্ষ স্তরে সংজ্ঞায়িত ফাংশন ( ডিএফ ব্যবহার করে , ল্যাম্বডা নয় )।
• মডিউলের শীর্ষ স্তরে (যেমন সর্বোচ্চ , মিনিট , বুল ইত্যাদি) সংজ্ঞায়িত অন্তর্নির্মিত ফাংশন ।
• ক্লাসগুলি যা মডিউলের শীর্ষ স্তরে সংজ্ঞায়িত করা হয়।
• None.
• Boolean variables (True and False).
• Integers, floating point numbers and complex numbers.
• Strings, bytes, bytearrays.
• Tuples, lists, sets and dictionaries containing only pickleable 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 (such as max, min, bool, etc.).
• Classes that are defined at the top level of a module.

Code for How to Use Pickle for Object Serialization in Python

import pickle

# define any Python data structure including lists, sets, tuples, dicts, etc.
l = list(range(10000))

# save it to a file
with open("list.pickle", "wb") as file:
    pickle.dump(l, file)

# load it again
with open("list.pickle", "rb") as file:
    unpickled_l = pickle.load(file)


print("unpickled_l == l: ", unpickled_l == l)
print("unpickled l is l: ", unpickled_l is l)

import pickle

class Person:
    def __init__(self, first_name, last_name, age, gender):
        self.first_name = first_name
        self.last_name = last_name
        self.age = age
        self.gender = gender

    def __str__(self):
        return f"{self.first_name} {self.last_name}, age={self.age}, gender={self.gender}>"


p = Person("John", "Doe", 99, "Male")

# save the object
with open("person.pickle", "wb") as file:
    pickle.dump(p, file)

# load the object
with open("person.pickle", "rb") as file:
    p2 = pickle.load(file)

print(p)
print(p2)

import pickle

class Person:
    def __init__(self, first_name, last_name, age, gender):
        self.first_name = first_name
        self.last_name = last_name
        self.age = age
        self.gender = gender

    def __str__(self):
        return f"{self.first_name} {self.last_name}, age={self.age}, gender={self.gender}>"

p = Person("John", "Doe", 99, "Male")

# get the dumped bytes
dumped_p = pickle.dumps(p)
print(dumped_p)

# write them to a file
with open("person.pickle", "wb") as file:
    file.write(dumped_p)

# load it
with open("person.pickle", "rb") as file:
    p2 = pickle.loads(file.read())

print(p)
print(p2)