How to Bundle Attributes and Methods with Encapsulation

Encapsulation is the practice of combining an object's data (attributes) and the methods that operate on that data into a single unit.

This allows us to hide the object's internal implementation and protect the data from improper external access.

In Python, encapsulation is implemented by prefixing attribute names with double underscores (__), making them private attributes.

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class ClassName:
    # Constructor
    def __init__(self):
        # Private attribute
        self.__private_attr = 0

In the code above, __private_attr is a private attribute that cannot be accessed directly from outside the class.

It is customary to use two underscores (_) to indicate that an attribute is private in Python.

Encapsulation serves the following key purposes in object-oriented programming:

• Providing an Interface: An interface is a point of interaction for different systems or objects. Through encapsulation, you can interact with objects using provided methods without needing to know how the object works internally.

• Data Protection: It safeguards important data of the object from unauthorized access.

The following code example defines an Account class representing a bank account and safely manages the account balance through encapsulation.

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class Account:
    def __init__(self, balance):
        # Private attribute
        self.__balance = balance

    # Deposit method
    def deposit(self, amount):
        if amount > 0:
            self.__balance += amount
        return "Invalid deposit amount."

    # Balance inquiry method
    def get_balance(self):
        return f"Current balance: ${self.__balance}"

# Create account with initial balance of $10000
account = Account(10000)
# Deposit $5000
account.deposit(5000)
# Check balance
print(account.get_balance())

In this example, __balance is set as a private variable, making it inaccessible directly from outside the class.

Instead, you can safely manipulate or verify this variable through the deposit and get_balance methods.