Introduction

When working with object-oriented programming in Python, inheritance allows you to reuse and extend the functionality of existing classes. However, things get tricky when multiple inheritance enters the picture. Suppose you have class A with a method do_work(), class B inherits from A and overrides do_work(), and then class C inherits from both A and B. Now the question is: when you call do_work() from an object of class C, which version gets executed? That’s where Python’s Method Resolution Order (MRO) comes into play.

Middle: Digging Deeper into MRO

Let’s define the scenario first:

 A:
    def do_work(self):
        print("Work from A")

class B(A):
    def do_work(self):
        print("Work from B")

class C(B, A):
    pass

Now, if you do:

c = C()
c.do_work()

Python will print:

from B

Important Notes:

Always use super() when overriding methods, especially with multiple inheritance, to maintain the expected flow and avoid skipping important method calls.

The order of base classes matters. If you define class C(A, B): instead of class C(B, A):, the MRO and hence the behavior will change.

Conclusion

Python’s MRO is a powerful yet sometimes confusing mechanism that governs how methods are resolved in inheritance chains. In our example, by understanding and using the MRO correctly, we ensure that class C behaves as expected and respects the overridden methods in its parent classes. Always inspect the MRO and use super() where appropriate to avoid surprises in complex hierarchies. Mastering MRO is key to writing clean, maintainable, and bug-free Python code in object-oriented projects.