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In languages supporting multiple inheritance, such as C++, interfaces are implemented as abstract classes. In languages without explicit support, protocols are often still present as conventions. This is known as duck typing. For example, in Python, any class can implement an __iter__ method and be used as a collection. [3]
A class defines an implementation of an interface, and instantiating the class results in an object that exposes the implementation via the interface. [3] In the terms of type theory, a class is an implementation—a concrete data structure and collection of subroutines—while a type is an interface .
They can be defined on classes, member variables, methods, and method parameters and may be accessed using reflection. In Python, the term "marker interface" is common in Zope and Plone. Interfaces are declared as metadata and subclasses can use implementsOnly to declare they do not implement everything from their super classes.
Python is a high-level, general-purpose programming language. Its design philosophy emphasizes code readability with the use of significant indentation. [33] Python is dynamically type-checked and garbage-collected. It supports multiple programming paradigms, including structured (particularly procedural), object-oriented and functional ...
Protocols and interfaces provide a way to explicitly declare that some methods, operators or behaviors must be defined. If a third-party library implements a class that cannot be modified, a client cannot use an instance of it with an interface unknown to that library even if the class satisfies the interface requirements.
class name definition «inheriting from parentclass». «interfaces: interfaces.» method_and_field_declarations endclass. class name implementation. method_implementations endclass. interface name . members endinterface.
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.
This is the real-world definition for an adapter. Interfaces may be incompatible, but the inner functionality should suit the need. The adapter design pattern allows otherwise incompatible classes to work together by converting the interface of one class into an interface expected by the clients.