Follow Techotopia on Twitter

On-line Guides
All Guides
eBook Store
iOS / Android
Linux for Beginners
Office Productivity
Linux Installation
Linux Security
Linux Utilities
Linux Virtualization
Linux Kernel
System/Network Admin
Programming
Scripting Languages
Development Tools
Web Development
GUI Toolkits/Desktop
Databases
Mail Systems
openSolaris
Eclipse Documentation
Techotopia.com
Virtuatopia.com
Answertopia.com

How To Guides
Virtualization
General System Admin
Linux Security
Linux Filesystems
Web Servers
Graphics & Desktop
PC Hardware
Windows
Problem Solutions
Privacy Policy

  




 

 

Chapter 26. Decorators

In addition to object-oriented programming, Python also supports an approach called Aspect-Oriented Programming. Object-oriented programming focuses on structure and behavior of individual objects. Aspect-oriented programming refines object design techniques by defining aspects which are common across a number of classes or methods.

The focus of aspect-oriented programming is consistency. Toward this end Python allows us to define "decorators" which we can apply to class definitions and method definitions and create consistency.

We have to note that decorators can easily be overused. The issue is to strike a balance between the obvious programming in the class definition and the not-obvious programming in the decorator. Generally, decorators should be transparently simple and so obvious that they hardly bear explanation.

Semantics of Decorators

Essentially, a decorator is a function. The purpose of a decorator function is to transform one function definition (the argument function) into another function definition. When you apply a decorator to a function definition, Python creates the argument function, then applies the decorator function to the argument function. The object returned by the decorator is the net effect of a decorated definition. It should be a function or object that behaves like a function.

When we say

@theDecorator
def someFunction( anArg ):
    pass # some function body

We are doing the following:

  1. We define an argument function, someFunction.

  2. We modify the argument function with the decorator. Python will apply the decorator function, theDecorator, to the argument function. The decorator returns a value; this should be some kind of callable object, either a class with a __call__ method or a function.

  3. Python binds the result of the decorator to the original function name, someFunction.

Generally, decorators fall into a number of common categories.

  • Simplifying Class Definitions. In some cases, we want to create a method function which applies to the class-level attributes, not the instance variables. We described class-level variables in the section called “Class Variables”. We introduced the built-in @staticmethod decorator in the section called “Static Methods and Class Method”.

    Additionally, we may want to create a class function which applies to the class as a whole. To declare this kind of method function, the built-in @classmethod decorator can be used.

    If you look at the Python Wiki page for decorators (https://wiki.python.org/moin/PythonDecoratorLibrary), you can find several examples of decorators that help define properties for managing attributes.

  • Debugging. There are several popular decorators to help with debugging. Decorators can be used to automatically log function arguments, function entrance and exit. The idea is that the decorator "wraps" your method function with additional statements to record details of the method function.

    One of the more interesting uses for decorators is to introduce some elements of type safety into Python. The Python Wiki page shows decorators which can provide some type checking for method functions where this is essential.

    Additionally, Python borrows the concept of deprecation from Java. A deprecated function is one that will be removed in a future version of the module, class or framework. We can define a decorator that uses the Python warnings module to create warning messages when the deprecated function is used.

  • Handling Database Transactions. In some frameworks, like Django (https://www.djangoproject.org), decorators are used to simplify definition of database transactions. Rather than write explicit statements to begin and end a transaction, you can provide a decorator which wraps your method function with the necessary additional processing.

  • Authorization. Web Security stands on several legs; two of those legs are authentication and authorization. Authentication is a serious problem involving transmission and validation of usernames and passwords or other credentials. It's beyond the scope of this book. Once we know who the user is, the next question is what are they authorized to do? Decorators are commonly used web frameworks to specify the authorization required for each function.


 
 
  Published under the terms of the Open Publication License Design by Interspire