How to Dynamically Change an Object’s Base Class in Python


In the realm of Python programming, there are instances where the need for objects to be dynamic and adaptable arises. This calls for the ability to alter an object’s base class on-the-fly, allowing it to inherit different behaviors or properties based on changing conditions at runtime. The question then emerges: Can we dynamically change an object’s base class in Python? This guide delves into this intriguing concept, exploring the techniques and possibilities it offers.

What You Will Learn

In this tutorial, you will delve into the realm of dynamic inheritance in Python. By the end of this guide, you will have a solid understanding of how to implement dynamic inheritance in your codebase, enabling your objects to adjust their behavior dynamically.

Understanding Dynamic Inheritance

At first glance, the idea of changing an object’s base class dynamically may seem unconventional or even unattainable. However, with Python’s dynamic nature, manipulating an object’s inheritance tree post-creation is indeed possible. This process involves techniques such as modifying the __class__ attribute of an instance or leveraging metaprogramming concepts. While these methods offer flexibility and power, they should be wielded cautiously due to their potential impact on code clarity and maintenance.

Code Solution

# Define two classes for demonstration purposes.
class BaseClassOne:
    def greet(self):
        print("Hello from BaseClassOne")

class BaseClassTwo:
    def greet(self):
        print("Hello from BaseClassTwo")

# Creating an instance of BaseClassOne.
obj = BaseClassOne()
obj.greet()  # Output: Hello from BaseClassOne

# Dynamically changing the base class of obj.
obj.__class__ = BaseClassTwo
obj.greet()  # Output: Hello from BaseClassTwo

# Copyright PHD


The provided solution showcases a simple way to dynamically alter an object’s base class by directly assigning a new class to its __class__ attribute. Initially instantiated as BaseClassOne, obj transforms into behaving like an instance of BaseClassTwo after reassigning its __class__ attribute. While this method grants significant flexibility, understanding its implications on your application’s logic and structure is crucial.

Deep Dive into __class__

  • Changing Behavior: Modifying __class__ alters how instances respond to method invocations.
  • Compatibility Considerations: The new base class should align with the original one in terms of expected methods and attributes to avoid unexpected errors.
  • Use Cases: Dynamic inheritance proves beneficial in scenarios necessitating quick adaptation without extensive subclassing or convoluted conditional statements throughout your codebase.
  1. Can I use this technique with built-in types?

  2. No, attempting this with built-in types (e.g., lists or dicts) raises a TypeError since their type cannot be changed post-creation.

  3. Is altering __class__ considered good practice?

  4. Its appropriateness varies based on context; while potent for specific dynamic behaviors or mock testing, excessive usage can obfuscate code comprehension and maintenance.

  5. What happens if methods called don’t exist in the new base class?

  6. Python raises AttributeError when methods/attributes expected within the current class definition are absent post-switching.

  7. Are there any performance considerations?

  8. Dynamic class modifications may incur slight overhead due to additional lookups but typically remain insignificant unless extensively utilized in performance-critical paths.

  9. How does dynamic inheritance impact code readability?

  10. While offering enhanced functionality and adaptability, judicious application is key to maintaining code readability amidst increased complexity.


Dynamic inheritance exemplifies Python’s versatility but necessitates thoughtful implementation considering potential complexities introduced into your codebase. When employed prudently�such as designing adaptable systems or simplifying mocking�it emerges as a potent tool enhancing functionality and flexibility while prioritizing readability wherever feasible.

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