Using and Defining Decorators

Depending on your job description, you might encounter decorators as a user or a provider. As we’ve seen, Python itself comes with built-in decorators that have specialized roles—static method declaration, property creation, and more. In addition, many popular Python toolkits include decorators to perform tasks such as managing database or user-interface logic. In such cases, we can get by without knowing how the decorators are coded.

For more general tasks, programmers can code arbitrary decorators of their own. For example, function decorators may be used to augment functions with code that adds call tracing, performs argument validity testing during debugging, automatically acquires and releases thread locks, times calls made to function for optimization, and so on. Any behavior you can imagine adding to a function call is a candidate for custom function decorators.

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On the other hand, function decorators are designed to augment only a specific function or method call, not an entire object interface. Class decorators fill the latter role better—because they can intercept instance creation calls, they can be used to implement arbitrary object interface augmentation or management tasks. For example, custom class decorators can trace or validate every attribute reference made for an object. They can also be used to implement proxy objects, singleton classes, and other common coding patterns. In fact, we’ll find that many class decorators bear a strong resemblance to the delegation coding pattern we met in Chapter 30.