The keyword super plays a crucial role in object-oriented programming, particularly in languages like Java and Python. Though, its function and potential issues can differ considerably between these languages. This article explores the use of super in both Java and Python, highlighting common use cases and potential pitfalls.

‘super’ in Java: Accessing Parent Class Functionality

In Java, super is primarily used to interact with the parent class (also known as the superclass) of a given class [[1]]. It serves three main purposes:

• Calling Overridden Methods: A subclass can override a method defined in its superclass. The super keyword allows the subclass to call the superclass’s implementation of that method.
• Accessing Hidden Fields: If a subclass declares a field with the same name as a field in its superclass, the subclass’s field hides the superclass’s field. super provides a way to access the hidden field from the superclass.
• Invoking a Superclass’s constructor: The super() call, specifically, is used to invoke a constructor from the superclass [[1]]. This is often necessary to initialize the superclass’s state before the subclass adds its own specific initialization. If a subclass constructor does not explicitly call a superclass constructor, Java will implicitly call the superclass’s no-argument constructor. however, if the superclass only defines constructors with arguments, the subclass *must* explicitly call one of those constructors using super(...) [[2]].

“In general, the super keyword can be used to call overridden methods, access hidden fields or invoke a superclass’s constructor.” [[1]]

‘super’ in Python: Navigating Inheritance hierarchies

In Python, super() is used to access methods of a parent class.Its particularly useful in multiple inheritance scenarios to ensure that methods in different parent classes are called in the correct order, following the method resolution order (MRO). However, issues can arise, as illustrated by a recent problem encountered with Scikit-learn and XGBoost.

Common Issues: the ‘__sklearn_tags__’ Error

One reported issue involves the error message “‘super’ object has no attribute ‘__sklearn_tags__'” when using the fit method on a RandomizedSearchCV object [[3]]. This problem seems to be related to compatibility issues between Scikit-learn and XGBoost, potentially exacerbated by using Python 3.12 with the latest versions of both libraries [[3]]. The root cause likely lies in how super() is being used within the libraries’ inheritance structures and how they interact with each othre.