Python Tutorial



Python Tutorial

Encapsulation in Python


Python is a versatile and popular programming language known for its simplicity and readability. It's also an object-oriented programming (OOP) language and leverages concepts like classes and objects to structure and organize code. One of the fundamental principles of OOP is encapsulation. This article covers what is encapsulation in python, why it's important, how it is implemented, encapsulation real-time examples and more.


Encapsulation is a foundational concept that involves bundling data and methods into classes. The primary goal of encapsulation is to hide the internal details of how a class works and provide a clear, well-defined interface for interacting with it.

What is Encapsulation in Python?

Encapsulation in Python refers to the practice of bundling data (attributes) and methods (functions) that operate on that data into a single unit called a class.  In simpler terms, encapsulation can be compared to packaging items in a box. The box holds various items, protects them and provides a convenient way to access them. Similarly, a class in Python encapsulates data and the functions that manipulate data, creating a self-contained unit within which the data is protected from external interference.

Encapsulation in Python Example

Here is a class called Student that stores their name, age, and grade. With Encapsulation, these data attributes are protected within the class and can only be accessed and modified through well-defined methods. 

class Student:

    def __init__(self, name, age, grade):
        self._name = name  # Protected attribute
        self._age = age    # Protected attribute
        self._grade = grade  # Protected attribute
    # Getter method
    def get_name(self):
        return self._name
    # Setter method
    def set_grade(self, grade):
        if 0 <= grade <= 100:
            self._grade = grade

# Create a Student object
student1 = Student("Alice", 18, 90)

# Accessing attributes through methods
print(student1.get_name())  # Output: "Alice"

# Modifying attributes through methods

Why do we need Encapsulation in Python? 

Encapsulation in Python is essential for several reasons like it protects the internal data of a class from unauthorized access and modification. 

Encapsulation in python real time example:

Consider a class representing a bank account:

class BankAccount:

    def __init__(self, account_number):
        self._account_number = account_number  # Protected attribute
    def __validate_pin(self, pin):
        return len(str(pin)) == 4

In this encapsulation example in Python, the _account_number attribute is protected and prevents direct modification from outside the class.

Access Modifiers in Python encapsulation

Encapsulation is implemented using access modifiers, which determine the visibility and accessibility of a class's members (attributes and methods) in Python. 

The three access modifiers are as follows:

  1. Public (public): Public members are accessible anywhere within and outside the class. By default, all members are public unless explicitly marked as private.

  2. Protected (protected): Protected members can be accessed within the class and its subclasses. You can designate a member as protected by prefixing its name with an underscore (_).

  3. Private (private): Private members are exclusively accessible within the class. To mark a member as private, prefix its name with double underscores (__).

Let's see how these access modifiers work in practice.

Encapsulation in Python using public members

Consider a class "Car" as an example:

class Car:

    def __init__(self, make, model):
        self.make = make  # Public attribute
        self.model = model  # Public attribute
    def start(self):
        print(f"{self.make} {self.model} is starting.")  # Public method

In this case, make and model attributes are public, and the start method is also public. They can be accessed directly from outside the class.

Encapsulation in Python using private members

Now, let's explore how to use private members in Python:

class BankAccount:

    def __init__(self, account_number):
        self.__account_number = account_number  # Private attribute
    def __validate_pin(self, pin):
        # Private method to validate the PIN
        return len(str(pin)) == 4

In this data encapsulation in python example, the __account_number attribute and the __validate_pin method are marked as private using double underscores. They can be accessed within the class.

Name Mangling to access private members

Name mangling is a technique in Python that allows you to access private members (attributes and methods marked with double underscores __) from outside the class by prefixing their names with the class name and an underscore (_ClassName__). It is used to make private members somewhat accessible but is generally discouraged to maintain encapsulation and code clarity. 

Here's how it works:

class BankAccount:

    def __init__(self, account_number):
        self.__account_number = account_number  # Private attribute
    def __validate_pin(self, pin):
        return len(str(pin)) == 4

# Creating an instance of the class
account = BankAccount("12345")

# Accessing private attributes using name mangling
print(account._BankAccount__account_number)  # Output: 12345

# Accessing private method using name mangling
print(account._BankAccount__validate_pin(1234))  # Output: True

Encapsulation in Python using protected members 

Protected members are accessible within the class itself and its subclasses, maintaining data integrity while allowing for some degree of flexibility. You indicate a member as protected by prefixing its name with a single underscore (_). 

Here's an encapsulation in python example:

class Animal:

    def __init__(self, name):
        self._name = name  # Protected attribute
    def _make_sound(self, sound):
        print(f"{self._name} makes a {sound} sound.")  # Protected method

# Subclass of Animal
class Dog(Animal):
    def bark(self):

# Creating instances
animal = Animal("Generic Animal")
dog = Dog("Buddy")

# Accessing protected attribute
print(animal._name)  # Output: Generic Animal

# Accessing protected method
dog.bark()  # Output: Buddy makes a bark sound.

Encapsulation in Python real time example 

Let's explore a real-time example of data encapsulation in python. Consider a scenario where you're developing a class to manage employee data within a company. 

Here's a simple encapsulation in python real time example:

class Employee:

    def __init__(self, emp_id, emp_name, emp_salary):
        self._emp_id = emp_id  # Protected attribute
        self._emp_name = emp_name  # Protected attribute
        self._emp_salary = emp_salary  # Protected attribute
    def get_employee_details(self):
        """Get employee details."""
        return f"ID: {self._emp_id}, Name: {self._emp_name}, Salary: ${self._emp_salary}"
    def increase_salary(self, amount):
        """Increase employee's salary."""
        if amount > 0:
            self._emp_salary = amount
            print("Invalid salary increase amount.")
    def change_name(self, new_name):
        """Change employee's name."""
        self._emp_name = new_name

# Create employee objects
employee1 = Employee(101, "Alice", 50000)
employee2 = Employee(102, "Bob", 60000)

# Access employee details
print(employee1.get_employee_details())  # Output: ID: 101, Name: Alice, Salary: $50000

# Increase employee salary
print(employee1.get_employee_details())  # Output: ID: 101, Name: Alice, Salary: $52000

# Change employee name
print(employee2.get_employee_details())  # Output: ID: 102, Name: Eve, Salary: $60000

In this example, we have an Employee class that encapsulates employee data, including ID, name, and salary, along with methods to interact with this data. Here's how encapsulation benefits us in this scenario:

  1. Data Protection: The attributes _emp_id, _emp_name, and _emp_salary are protected, so they are not directly accessed or modified outside the class.

  2. Modular Design: All employee-related functionality is encapsulated within the Employee class, making the code organized and modular.

  3. Abstraction: External code interacts with the class through well-defined methods like get_employee_details, increase_salary, and change_name, abstracting away the complexity of the internal implementation.

  4. Controlled Access: Access to employee data is controlled through methods. For example, you can't change an employee's salary without using the increase_salary method.

Advantages of Encapsulation 

Following are the advantages of encapsulation in python: 

  1. Data Protection: Encapsulation protects data from unauthorized access and modification. It enforces access controls on class members (attributes and methods) to define who can access the data.

  • Example: Private attributes and methods are only accessible within the class, ensuring data integrity.

  1. Modular Code Design: Encapsulation promotes a modular code design by bundling related data and functionality within a class. This makes the code easier to manage, maintain, and extend.

  • Example: Grouping attributes and methods related to a specific entity, like an employee or a car, within a class.

  1. Abstraction: Encapsulation abstracts complex internal details, providing a simplified and understandable interface for interacting with a class. External code doesn't need to know how things work internally.

  • Example: A Car class offers methods like start and stop to interact with the car's engine without exposing intricate engine details.

  1. Controlled Access: Encapsulation allows controlled access to data and methods through well-defined interfaces. It reduces the risk of unintended changes and errors by enforcing data validation and access control rules.

  • Example: Methods like set_temperature in a TemperatureConverter class ensure that temperature values stay within valid ranges.

  1. Code Reusability: Encapsulation promotes code reusability. Well-encapsulated classes can be easily integrated into different parts of an application, reducing duplication and improving code consistency.

  • Example: Using a Person class to manage user data consistently in various modules of an application.

  1. Improved Security: Encapsulation enhances security by controlling access to sensitive data. Private members are inaccessible from outside the class, reducing the risk of data breaches or misuse.

  • Example: Keeping passwords or encryption keys as private attributes within a class.

  1. Encapsulation Hierarchies: Inheritance and encapsulation can be combined to create encapsulation hierarchies. Subclasses can inherit and extend the encapsulation of their parent classes.

  • Example: A base Shape class encapsulates common attributes and methods, while subclasses like Circle and Rectangle encapsulate shape-specific details.

  1. Code Readability and Maintenance: Encapsulation enhances code readability and maintainability by providing a clear structure and well-defined interfaces. It simplifies troubleshooting and debugging.

  • Example: Well-encapsulated classes are easier to understand and maintain over time.

Disadvantages of Encapsulation in Python

Following are the disadvantages of encapsulation in Python:

1. Complexity: Overusing encapsulation can lead to code complexity and verbosity, making the code harder to understand.
Example: Extremely fine-grained encapsulation with numerous getters and setters can clutter the codebase.

2. Performance Overhead: Accessing data through methods can introduce a slight performance overhead compared to direct attribute access.
Example: In high-performance applications, frequent method calls for simple attribute access can impact speed.

3. Name Mangling: The use of name mangling to access private members can lead to less readable and maintainable code.
Example: Accessing private members using name mangling involves complex naming conventions and may confuse developers.

4. Limited Flexibility: Overly strict encapsulation can limit flexibility and make it challenging to extend or modify a class.
Example: If a class encapsulates data and operations too tightly, making changes in the class requires extensive modifications.

5. Complexity in Testing: Testing encapsulated code can be more complex, as you need to write additional test methods to access encapsulated data.
Example: In unit testing, you have to create extra methods to set encapsulated data for testing purposes.


Encapsulation in Python is a fundamental concept and OOP in general. It helps to create clean, organized, and secure code by encapsulating data and controlling access through different methods. It offers numerous advantages, but it's essential to use encapsulation judiciously to avoid unnecessary complexity.


Q1: What is the purpose of encapsulation in Python?

A1: The primary purpose is to protect data from unauthorized access and modification and provide a clear and controlled interface for interacting with a class.

Q2: Can I access private members of a class from outside using the name mangling?

A2: Yes, you can access private members using name mangling, but it's generally averted as it goes against the principle of encapsulation.

Q3: When should I use public, protected, or private members in Python?

A3: Use public members when the data should be accessible from anywhere, protected members when limited access is required within the class and its subclasses, and private members when data is encapsulated within the class. 

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