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Choosing the Right Super() in Python’s Multiple Inheritance

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Choosing the Right Super() in Python’s Multiple Inheritance: A Guide for Beginners

Python’s multiple inheritance is a powerful feature that allows developers to incorporate features from multiple parent classes into a single child class. While this can lead to efficient and elegant solutions to complex programming problems, it also brings with it some potential issues – specifically in the use of the super() function.

Super() provides a powerful way to call methods from parent classes in a chain of inheritance, but its behavior can be tricky to understand, especially when dealing with multiple inheritance. Choosing the right super() call is essential to ensure proper ordering of method calls and avoid confusion, bugs or worse.

If you’re just starting out with multiple inheritance in Python or struggling with how to properly use super(), this guide is for you. We’ll cover the basics of super(), best practices, and common pitfalls to watch out for. Whether you’re a beginner or an experienced developer, understanding the right super() call will help you write better code, reduce errors, and ultimately create more effective programs.

By the end of this article, you’ll have a solid grasp on Python’s super() function and feel confident using it in your own projects. So, let’s dive in and explore the finer points of choosing the right super() in Python’s multiple inheritance.

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“Python’S Multiple Inheritance: Picking Which Super() To Call” ~ bbaz


Python supports multiple inheritance- a feature that is missing in many other object-oriented programming languages. Multiple inheritance allows a class to inherit from more than one parent class. As useful as it is, it can also create some confusion and ambiguity- especially when dealing with the super function. The super function is an essential aspect of Python’s multiple inheritance, but it can be tricky to get it right. In this blog post, we are going to take an in-depth look at choosing the right super function in Python’s multiple inheritance, and the different types of super functions that are available to you.

The Basics of super()

The super function is a built-in function in Python that allows you to call a method from a parent class. When you use the super() function, you are calling the method of the superclass.

Understanding the Concept of Inheritance

Inheritance is the process by which a class acquires properties and methods from another class. It is an important mechanism for code reuse and building complex software systems. One of the benefits of inheritance is that it reduces code duplication by allowing you to define common properties and methods in a superclass, which can then be inherited by the subclasses.

The Role of super() in Inheritance

The super() function helps you to achieve method overriding in a clean and organized way. In Python, method overriding happens when a sub-class defines a method that is already defined in the parent class. The method in the subclass is then said to override the method in the parent class. The use of the super function is crucial when it comes to method overriding because it helps you to call the method of the superclass without repeating code.

Types of super()

There are two types of super functions in Python- the bound super function and the unbound super function. The bound super() function is used when you have a specific class and method that you want to call. The unbound super() function, on the other hand, is used when you don’t know the class and method that you want to call.

Bound Super()

The bound super() function takes two arguments: the current class and instance. It returns a temporary object of the superclass that allows you to call its methods. When you call the method on the temporary object, Python automatically passes the self argument for you. This is useful when you have a specific superclass method in mind that you want to call.

Pro Cons
– Targets specific method and class
– Saves you the headache of figuring out which superclass’s method to call in the case of multiple inheritance
– Must know the class and method you want to call
– Can only target specific superclass methods

Unbound Super()

The unbound super() function is used when you want to call a method of a superclass but don’t know the exact class and method to call. It takes two arguments- the current class and an instance of the current class. Unlike the bound super() function, it does not automatically pass the self argument.

Pro Cons
– More flexible compared to bound super()
– Can be used for complex inheritance hierarchies
– Can be confusing and difficult to use
– Time-consuming to figure out exactly which method from which superclass to call


Choosing the right super() function in Python’s multiple inheritance can be a bit tricky, but it is essential to understand because it can have a significant impact on your code. The bound super() function is useful when you have a specific superclass method in mind that you want to call, while the unbound super() function is more flexible, allowing you to call methods of any superclass. Ultimately, the choice of which super() function to use depends on the specifics of your program and the level of flexibility required.

Thank you for taking the time to read about Choosing the Right Super() in Python’s Multiple Inheritance. I hope that this article has provided some valuable insights and helped clarify some of the complexities involved.It is crucial to understand the super() function as it allows you to call a method from a parent class in your child class. However, it is equally important to use it correctly to avoid unexpected behavior in your code. Remember that there are two ways to implement super(), either with or without arguments. Be careful when choosing which one to use and make sure it calls the appropriate method from the right superclass.In summary, the super() function is an essential tool in Python’s multiple inheritance model. Understanding how to use it correctly can help you build robust and scalable applications. Always remember to choose the right super() function for your particular application to ensure the best performance and stability. Thank you for reading and good luck on your Python journey.

When it comes to multiple inheritance in Python, choosing the right super() method can be a bit tricky. Here are some common questions people ask about this topic:

  1. What is the difference between super() and super(ClassName, self)?

    • The super() method without arguments automatically takes the current class and instance as parameters. This is the most common way to use super() in Python.
    • The super(ClassName, self) method explicitly specifies the class and instance to use as parameters. This can be useful when dealing with diamond inheritance or other complex inheritance patterns.
  2. How do I know which class to pass as an argument to super()?

    • You should always pass the immediate parent class of the current class as the argument to super(). This ensures that the method resolution order (MRO) is followed correctly.
    • If you’re not sure which class is the immediate parent, you can use the __mro__ attribute to inspect the MRO of the current class.
  3. What happens if I call super() multiple times in a single method?

    • Each call to super() will return the next class in the MRO, so you’ll need to make sure you’re calling the correct method on the correct class each time.
    • If you’re not careful, you could end up with infinite recursion or other unexpected behavior.

By understanding these common questions about choosing the right super() method in Python’s multiple inheritance, you can avoid common pitfalls and make sure your code behaves as expected.