Python - Mixin Classes

Back to Python

Using Mix-ins with Python

See Article by Chuck Esterbrook

Mix-in programming is a style of software development where units of functionality are created in a class and then mixed in with other classes. This might sound like simple inheritance at first, but a mix-in differs from a traditional class in one or more of the following ways. Often a mix-in is not the “primary” superclass of any given class, does not care what class it is used with, is used with many classes scattered throughout the class hierarchy and is introduced dynamically at runtime.

There are several reasons to use mix-ins: they extend existing classes in new areas without having to edit, maintain or merge with their source code; they keep project components (such as domain frameworks and interface frameworks) separate; they ease the creation of new classes by providing a grab bag of functionalities that can be combined as needed; and they overcome a limitation of subclassing, whereby a new subclass has no effect if objects of the original class are still being created in other parts of the software.

So while mix-ins are not a distinct technical feature of Python, the benefits of this technique are worth studying.

Python provides an ideal language for mix-in development because it supports multiple inheritance, supports full-dynamic binding and allows dynamic changes to classes. Before we dive into Python, let me admit that mix-ins are old hat. The first time I saw mix-in programming by that name was when reviewing the now-defunct Taligent Project, known for its Pink operating system and CommonPoint application framework. However, since C++ does not support language feature #2, full-dynamic binding, or language feature #3, dynamic changes at runtime, I'm not surprised that the approach didn't bring to fruition all its inventors had hoped for.

I have also seen another instance of mix-in programming under a different name. Objective-C has a nifty language feature called categories that allows you to add and replace methods of existing classes, even without access to their source code.

This is great for repairing existing system classes and extending their capabilities. Also, combined with an ability to load libraries dynamically, categories are quite effective in improving the structure of applications and reducing code.

Back to Python