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Ideally all reuse can be achieved by assembling existing components, but in practice inheritance is often needed to make new ones. Therefore inheritance and object composition typically work hand-in-hand, as discussed in the book Design Patterns (1994). [3]
For example, a container defined as std::vector<Shape*> does not work because Shape is not a class, but a template needing specialization. A container defined as std::vector<Shape<Circle>*> can only store Circles, not Squares. This is because each of the classes derived from the CRTP base class Shape is a unique type.
Polymorphism can be distinguished by when the implementation is selected: statically (at compile time) or dynamically (at run time, typically via a virtual function). This is known respectively as static dispatch and dynamic dispatch, and the corresponding forms of polymorphism are accordingly called static polymorphism and dynamic polymorphism.
The defining feature of inheritance is that both interface and implementation are inherited; if only interface is inherited, this is known as interface inheritance or subtyping. Inheritance can also be done without classes, as in prototype-based programming .
The concept of the virtual function solves the following problem: In object-oriented programming, when a derived class inherits from a base class, an object of the derived class may be referred to via a pointer or reference of the base class type instead of the derived class type.
Polymorphism is the phenomenon wherein somewhat interchangeable objects each expose an operation of the same name but possibly differing in behavior. As an example, a File object and a Database object both have a StoreRecord method that can be used to write a personnel record to storage. Their implementations differ.
Python supports most object oriented programming (OOP) techniques. It allows polymorphism, not only within a class hierarchy but also by duck typing. Any object can be used for any type, and it will work so long as it has the proper methods and attributes. And everything in Python is an object, including classes, functions, numbers and modules.
Multiple dispatch can be added to Python using a library extension. For example, using the module multimethod.py [ 13 ] and also with the module multimethods.py [ 14 ] which provides CLOS-style multimethods for Python without changing the underlying syntax or keywords of the language.