OOP Is Simpler Than You May Think

In this complete form, despite their sizes, our classes capture nearly all the important concepts in Python’s OOP machinery:

 

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  • Instance creation—filling out instance attributes
  • Behavior methods—encapsulating logic in class methods
  • Operator overloading—providing behavior for built-in operations like printing
  • Customizing behavior—redefining methods in subclasses to specialize them
  • Customizing constructors—adding initialization logic to superclass steps

Most of these concepts are based upon just three simple ideas: the inheritance search for attributes in object trees, the special self argument in methods, and operator overloading’s automatic dispatch to methods.

Along the way, we’ve also made our code easy to change in the future, by harnessing the class’s propensity for factoring code to reduce redundancy. For example, we wrapped up logic in methods and called back to superclass methods from extensions to avoid having multiple copies of the same code. Most of these steps were a natural outgrowth of the structuring power of classes.

By and large, that’s all there is to OOP in Python. Classes certainly can become larger than this, and there are some more advanced class concepts, such as decorators and metaclasses, which we will meet in later chapters. In terms of the basics, though, our classes already do it all. In fact, if you’ve grasped the workings of the classes we’ve written, most OOP Python code should now be within your reach.