Python pickle and unpickle

Pickle is a built-in module in Python that allows you to serialize (convert a Python object into a byte stream) and deserialize (convert a byte stream back into a Python object) objects. This is particularly useful for saving complex data structures, such as lists, dictionaries, and class instances, to a file or transmitting them over a network.

1. What is Serialization and Deserialization?

2. Basic Usage of Pickle

import pickle

data = {'name': 'Alice', 'age': 30, 'city': 'New York'}

# Serializing and saving the dictionary to a file
with open('data.pkl', 'wb') as file:
    pickle.dump(data, file)

Output:
(No output, but a file named data.pkl is created)

# Loading the dictionary back from the file
with open('data.pkl', 'rb') as file:
    loaded_data = pickle.load(file)

print(loaded_data)

Output:
{'name': 'Alice', 'age': 30, 'city': 'New York'}

3. Pickle Protocols

with open('data_v2.pkl', 'wb') as file:
    pickle.dump(data, file, protocol=pickle.HIGHEST_PROTOCOL)

Output:
(No output, but a file named data_v2.pkl is created using the highest protocol)

4. Handling Custom Classes

class Person:
    def __init__(self, name, age):
        self.name = name
        self.age = age

# Create an instance of Person
alice = Person("Alice", 30)

# Serialize the object
with open('person.pkl', 'wb') as file:
    pickle.dump(alice, file)

# Deserialize the object
with open('person.pkl', 'rb') as file:
    loaded_person = pickle.load(file)

print(f'Name: {loaded_person.name}, Age: {loaded_person.age}')

Output:
Name: Alice, Age: 30

5. Security Considerations

# Avoid loading pickled data from untrusted sources
# with open('malicious.pkl', 'rb') as file:
#     data = pickle.load(file)  # This could execute malicious code

Output:
(No output, but be cautious)

6. Alternatives to Pickle

import json

# Serialize to JSON
with open('data.json', 'w') as json_file:
    json.dump(data, json_file)

# Deserialize from JSON
with open('data.json', 'r') as json_file:
    json_data = json.load(json_file)

print(json_data)

Output:
{'name': 'Alice', 'age': 30, 'city': 'New York'}

7. Advanced Pickle Usage

def greet(name):
    return f"Hello, {name}!"

# Pickle the function
with open('greet.pkl', 'wb') as file:
    pickle.dump(greet, file)

# Unpickle the function
with open('greet.pkl', 'rb') as file:
    loaded_greet = pickle.load(file)

print(loaded_greet("Alice"))

Output:
Hello, Alice!

class Employee(Person):
    def __init__(self, name, age, position):
        super().__init__(name, age)
        self.position = position

# Create an instance of Employee
bob = Employee("Bob", 25, "Developer")

# Serialize the object
with open('employee.pkl', 'wb') as file:
    pickle.dump(bob, file)

# Deserialize the object
with open('employee.pkl', 'rb') as file:
    loaded_employee = pickle.load(file)

print(f'Name: {loaded_employee.name}, Age: {loaded_employee.age}, Position: {loaded_employee.position}')

Output:
Name: Bob, Age: 25, Position: Developer

8. Conclusion