5 Types of Inheritance in Python You Must Understand to Level Up!
By Rohit Sharma
Updated on Jul 09, 2025 | 14 min read | 33.35K+ views
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By Rohit Sharma
Updated on Jul 09, 2025 | 14 min read | 33.35K+ views
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Did you know? Inheritance in Python was inspired by the concept invented in 1969 for the Simula programming language, which is considered the first object-oriented language. |
Inheritance in Python simplifies code reuse and allows classes to inherit functionality from parent classes. From single-level to hybrid inheritance, each type offers unique benefits for structuring and organizing code, improving scalability, and reducing redundancy.
While Python’s inheritance types offer flexibility, they can also introduce challenges, like method conflicts and complex hierarchies. This blog will guide you through the 5 types of inheritance in Python, helping you master each one for building efficient and maintainable code.
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Let’s understand inheritance in Python with an example. Imagine you have a parent class called Animal that has a method to speak. A child class Dog can inherit from Animal and use the speak method without having to define it again.
Here's a simple example:
class Animal:
def speak(self):
print("Animal makes a sound")
class Dog(Animal):
pass
dog = Dog()
dog.speak()
Output:
Animal makes a sound
In this example, the Dog class inherits the speak method from the Animal class, so we don't need to rewrite the method. This makes inheritance a powerful tool in Python programming.
Now, let’s explore each of 5 types of inheritance in Python with examples.
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Single-level inheritance is the simplest form where a child class inherits from a single parent class. It’s ideal for scenarios where you want to extend or modify the behavior of one class without complexity. This type of inheritance encourages code reuse, making it easy for beginners to understand and implement.
It’s perfect for small applications with clear relationships between classes. However, it can become limiting if you need to combine behaviors from multiple classes or scale the application. While it simplifies code, it may lead to redundancy if not used carefully as the project grows.
Diagram/Flowchart:
Code Snippet:
class Animal:
def speak(self):
print("Animal makes a sound")
class Dog(Animal):
def bark(self):
print("Dog barks")
dog = Dog()
dog.speak()
dog.bark()
Explanation: In this example, the Dog class inherits the speak() method from the Animal class. The Dog class can also define its own method, like bark(). The child class (Dog) reuses the method from the parent class (Animal) without redefining it, showcasing inheritance.
Output:
Animal makes a sound
Dog barks
Benefits | Limitations |
• Simple and easy to implement • Promotes code reuse without redundancy • Reduces complexity in small projects or simple class structures • Provides clear, straightforward architecture |
• Limited flexibility for complex relationships between classes • Doesn’t allow inheritance from multiple classes • May not be efficient for more complex systems with many behaviors |
Examples:
Parent Class |
Child Class |
Inherited Methods |
Animal |
Dog |
speak() |
Vehicle |
Car |
start() |
Shape |
Circle |
draw() |
Also Read: Essential Skills and a Step-by-Step Guide to Becoming a Python Developer
Building on the idea of inheritance, we can extend functionality even further in more complex structures. Let's explore how multi-level inheritance takes this concept to the next level by creating a chain of inheritance.
Multi-level inheritance occurs when a child class inherits from a parent class, which itself inherits from another parent class, forming a chain of inheritance. This allows for a more structured approach, enabling you to extend behaviors across multiple levels. It's useful when building more specialized classes from a basic parent class.
This type of inheritance works well in larger codebases, where complex hierarchies are required. It helps organize programs logically by separating general functionality in parent classes and more specific behavior in child classes.
However, a potential drawback is that it can tightly couple classes. Changes in a parent class can have unintended consequences on child classes further down the chain, which could introduce bugs or make the code harder to maintain.
Diagram/Flowchart:
Code Snippet:
class Animal:
def speak(self):
print("Animal makes a sound")
class Mammal(Animal):
def breathe(self):
print("Mammal breathes air")
class Dog(Mammal):
def bark(self):
print("Dog barks")
dog = Dog()
dog.speak()
dog.breathe()
dog.bark()
Explanation: Here, the Dog class inherits from the Mammal class, which in turn inherits from the Animal class. This creates a chain where Dog has access to all methods of both Mammal and Animal. The Dog class can directly use speak() from Animal and breathe() from Mammal.
Output:
Animal makes a sound
Mammal breathes air
Dog barks
Benefits | Limitations |
• Code reuse is maximized by building on existing functionality • Helps in creating a clear hierarchy with specialized behaviors • Supports creating more complex structures while avoiding redundancy |
• Increased complexity due to multiple levels • Debugging may become difficult with many inherited levels • The chain of inheritance can become confusing if not well-organized |
Examples:
Grandparent Class |
Parent Class |
Child Class |
Inherited Methods |
Animal |
Mammal |
Dog |
speak(), breathe(), bark() |
Shape |
Circle |
RoundShape |
draw(), area() |
Vehicle |
Car |
ElectricCar |
start(), drive(), charge() |
Also Read: Top 50 Python Project Ideas with Source Code in 2025
While multi-level inheritance builds a chain of functionality, hierarchical inheritance allows multiple child classes to inherit from a single parent class.
Hierarchical inheritance occurs when multiple child classes inherit from a single parent class. It allows several related subclasses to share common functionality or attributes, making it efficient when different classes need to reuse the same behavior.
This structure is ideal when you have multiple specialized classes that all need access to the same core functionality. While it promotes code reuse, hierarchical inheritance can lead to tight coupling between the parent and child classes.
Changes in the parent class can ripple through all child classes, potentially causing issues or breaking functionality. This can make maintenance challenging, especially in large applications where multiple subclasses depend on the same parent class.
Diagram/Flowchart:
Code Snippet:
class Animal:
def speak(self):
print("Animal makes a sound")
class Dog(Animal):
def bark(self):
print("Dog barks")
class Cat(Animal):
def meow(self):
print("Cat meows")
class Wolf(Animal):
def howl(self):
print("Wolf howls")
# Create instances of each class
dog = Dog()
cat = Cat()
wolf = Wolf()
# Call methods from parent and child classes
dog.speak()
dog.bark()
cat.speak()
cat.meow()
wolf.speak()
wolf.howl()
Explanation: In this example, the Dog, Cat, and Wolf classes all inherit from the Animal class. The Animal class provides the shared speak() method, which is inherited by all child classes (Dog, Cat, and Wolf). Each child class also defines its own unique method:
This demonstrates how inheritance allows child classes to reuse methods from the parent class without duplicating code, while still having their own specific behaviors.
Output:
Animal makes a sound
Dog barks
Animal makes a sound
Cat meows
Benefits | Limitations |
• Encourages code reuse across multiple classes • Reduces duplication by inheriting shared methods • Easier maintenance as parent class updates propagate to children |
• Child classes are tightly coupled to the parent • Parent class changes may impact multiple children • Limited flexibility for significant method changes in children |
Examples:
Parent Class |
Child Classes |
Inherited Methods |
Animal |
Dog, Cat |
speak() |
Shape |
Circle, Square |
draw() |
Vehicle |
Car, Truck |
start() |
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Also Read: Data Structures in Python
Moving from one parent to multiple parents, let’s now explore how multiple inheritance allows a class to inherit from more than one class, bringing multiple behaviors into a single child class.
Multiple inheritance occurs when a child class inherits from more than one parent class, allowing it to combine the behaviors and attributes of multiple parent classes. This makes it a powerful tool for reusing code from various sources.
However, multiple inheritance can introduce complexity, especially when two parent classes have methods with the same name. This creates ambiguity, and without a clear method resolution order (MRO), it can be difficult to determine which method should be used.
To manage this, Python uses the Method Resolution Order (MRO), which determines the order in which Python looks for a method in the inheritance hierarchy. When a method is called on an object, Python follows the MRO to search through the parent classes for the method, starting from the leftmost class and moving through the hierarchy.
The "Diamond Problem" arises when two classes inherit from a common ancestor. It may create ambiguity, particularly if two parent classes have methods with the same name or signature, leading to potential conflicts.
Diagram/Flowchart:
Code Snippet:
class Animal:
def speak(self):
print("Animal makes a sound")
class Pet:
def play(self):
print("Pet plays with a ball")
class Dog(Animal, Pet):
pass
dog = Dog()
dog.speak()
dog.play()
Explanation: In this example, the Dog class inherits from both Animal and Pet. This allows the Dog class to use methods from both parent classes: speak() from Animal and play() from Pet. The child class Dog can combine behaviors from both parent classes without needing to redefine them.
Output:
Animal makes a sound
Pet plays with a ball
Benefits | Limitations |
• Combines functionality from multiple classes for flexibility • Avoids code duplication by inheriting methods and properties • Useful for combining behaviors from different domains (e.g., "Animal" and "Pet") |
• Can cause ambiguity if parent classes have methods with the same name • Increases complexity, making code harder to maintain • May lead to method resolution order (MRO) conflicts |
Examples:
Parent Classes |
Child Class |
Inherited Methods |
Animal, Pet |
Dog |
speak(), play() |
Shape, Color |
Circle |
draw(), fill() |
Worker, Engineer |
Manager |
work(), design() |
Also Read: Explore 12 Real-World Applications of Python [2025]
Finally, hybrid inheritance brings together different types of inheritance structures to create highly versatile and flexible class hierarchies. Let's dive into this complex but powerful inheritance model.
Hybrid inheritance is a combination of two or more types of inheritance, often blending multiple inheritance and multi-level inheritance. This allows you to merge different functionalities from multiple parent classes, making it a powerful tool for more complex programs.
In real-world applications, hybrid inheritance is useful when a class needs to combine different behaviors from separate parent classes. For instance, a class representing an "ElectricCar" could inherit from both "Car" (for general vehicle behaviors) and "BatteryPowered" (for electric-specific functionality).
While this provides flexibility, managing the class hierarchy in hybrid inheritance can be challenging. Issues like determining the correct method resolution order (MRO), class order, and debugging become more complex as the inheritance chain grows. Mismanagement of these elements can lead to unintended behavior, making it critical to design hybrid inheritance hierarchies carefully.
Diagram/Flowchart:
Code Snippet:
class Mammal:
def speak(self):
print("Mammal makes a sound")
class MarinaMammal(Mammal):
def swim(self):
print("Marina Mammal swims")
class Pet(Mammal):
def play(self):
print("Pet plays with a toy")
class Dolphin(MarinaMammal):
def jump(self):
print("Dolphin jumps out of water")
class Dog(Pet):
def bark(self):
print("Dog barks")
class Cat(Pet):
def meow(self):
print("Cat meows")
# Create instances of each class
dog = Dog()
cat = Cat()
dolphin = Dolphin()
# Call methods from parent and child classes
dog.speak()
dog.play()
dog.bark()
cat.speak()
cat.play()
cat.meow()
dolphin.speak()
dolphin.swim()
dolphin.jump()
Explanation: In this example, the Dog and Cat classes inherit from the Pet class, which inherits from the Mammal class. The Dolphin class inherits from MarinaMammal, which inherits from Mammal.
This shows a clear multi-level and hierarchical inheritance structure. Each class can access methods from its parent class. For example, both Dog and Cat can use speak() from Mammal and play() from Pet. Similarly, Dolphin can access speak() from Mammal and swim() from MarinaMammal.
Output:
Mammal makes a sound
Pet plays with a toy
Dog barks
Mammal makes a sound
Pet plays with a toy
Cat meows
Mammal makes a sound
Marina Mammal swims
Dolphin jumps out of water
Benefits | Limitations |
• Combines behaviors from different classes, making systems more versatile • Promotes code reuse through multiple inheritance types • Merges diverse functionalities into a single class |
• Increases complexity, making code harder to maintain • Can cause method resolution order (MRO) issues with conflicting methods • Difficult to manage as the inheritance structure grows |
Examples:
Parent Classes |
Child Class |
Inherited Methods |
Animal, Vehicle |
Dog |
speak(), play(), drive() |
Shape, Color, Size |
Square |
draw(), fill(), resize() |
Worker, Engineer |
Manager |
work(), design(), plan() |
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Also Read: Types of Inheritance in C++ What Should You Know?
While all these types of inheritance in Python are powerful, they come with their own challenges. You must learn how to handle common issues you might face when using inheritance, such as method conflicts and complex hierarchies.
Python inheritance can be a powerful tool, but it also comes with certain challenges. Understanding and addressing these challenges ensures that you can effectively use inheritance without facing common pitfalls.
Here are some practical techniques to tackle the most common issues:
Challenge |
Solution |
Diamond Problem (Multiple Inheritance Conflict) | Use Python's Method Resolution Order (MRO) and super() to handle method conflicts. |
Overriding Methods Safely | Call parent class methods using super() to preserve parent functionality. |
Complex Class Hierarchy | Keep inheritance trees shallow and use composition where necessary. |
Inheriting Unrelated Behavior | Use inheritance only for "is-a" relationships; prefer composition for "has-a" relationships. |
Readability with Multiple Inheritance | Use descriptive class and method names; document inheritance structures clearly. |
Losing Functionality in Overridden Methods | Ensure that essential functionality is preserved by explicitly calling parent methods using super(). |
Also Read: Types of Inheritance in Java: Key Concepts, Benefits and Challenges in 2025
Now that you know how to tackle the challenges, let's discuss strategies that will help you leverage inheritance to its fullest potential. These tips will guide you toward writing cleaner, more efficient code.
Learning inheritance in Python is essential for writing efficient, scalable, and maintainable code. Following the right strategies ensures clean, understandable, and extensible code, avoiding common pitfalls like complex hierarchies and method conflicts. This leads to better code reusability, easier debugging, and smoother scaling.
Here are some practical strategies to help you excel in Python inheritance:
1. Understand Inheritance Concepts Thoroughly:
2. Keep Inheritance Hierarchy Simple:
3. Leverage super() to Maintain Functionality:
4. Favor Method Overriding Over Method Overloading:
5. Use Polymorphism to Enhance Flexibility:
6. Embrace Multiple Inheritance Carefully:
7. Document Your Inheritance Design:
8. Write Unit Tests for Your Inherited Methods:
By following these strategies, you can master inheritance in Python and use it effectively in your programming projects.
Also Read: Why Learn to Code Now and How? Top 4 Reasons To Learn
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To master the 5 types of inheritance in Python, start by practicing single-level inheritance for simplicity and gradually explore multi-level and multiple inheritance. Experiment with examples to understand method resolution order and hierarchy. This hands-on approach will solidify your understanding and make you proficient.
Many learners struggle to grasp inheritance complexities on their own. upGrad’s Python courses provide expert-led guidance and practical projects, helping you master inheritance concepts and advance your coding skills.
Here are some relevant courses to enhance your learning journey:
You can also get personalized career counseling with upGrad to guide your career path, or visit your nearest upGrad center and start hands-on training today!
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Reference Link:
https://python-course.eu/oop/inheritance.php
763 articles published
Rohit Sharma is the Head of Revenue & Programs (International), with over 8 years of experience in business analytics, EdTech, and program management. He holds an M.Tech from IIT Delhi and specializes...
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