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OOP: The Big Idea

As is, our code may be small, but it’s fairly functional. And really, it already illustrates the main point behind OOP in general: in OOP, we program by customizing what has already been done, rather than copying or changing existing code. This isn’t always an obvious win to newcomers at first glance, especially given the extra coding requirements of classes. But overall, the programming style implied by classes can cut development time radically compared to other approaches.

For instance, in our example we could theoretically have implemented a custom giveRaise operation without subclassing, but none of the other options yield code as optimal as ours:

 

Although we could have simply coded Manager from scratch as new, independent code, we would have had to reimplement all the behaviors in Person that are the same for Managers.Although we could have simply changed the existing Person class in-place for the requirements of Manager’s giveRaise, doing so would probably break the places where we still need the original Person behavior.Although we could have simply copied the Person class in its entirety, renamed the copy to Manager, and changed its giveRaise, doing so would introduce code redundancy that would double our work in the future—changes made to Person in the future would not be picked up automatically, but would have to be manually propagated to Manager’s code. As usual, the cut-and-paste approach may seem quick now, but it doubles your work in the future.

The customizable hierarchies we can build with classes provide a much better solution for software that will evolve over time. No other tools in Python support this development mode. Because we can tailor and extend our prior work by coding new subclasses, we can leverage what we’ve already done, rather than starting from scratch each time, breaking what already works, or introducing multiple copies of code that may all have to be updated in the future. When done right, OOP is a powerful programmer’s ally.