OBJECT-ORIENTED FEATURES

Python is an object-oriented programming language, which means that it provides features that support object-oriented programming.

It is not easy to define object-oriented programming, but we have already seen some of its characteristics:

• Programs are made up of object definitions and function definitions, and most of the computation is expressed in terms of operations on objects.

• Each object definition corresponds to some object or concept in the real world, and the functions that operate on that object correspond to the ways real-world objects interact.

For example, the Time class defined in Chapter 16 corresponds to the way people record the time of day, and the functions we defined correspond to the kinds of things people do with times. Similarly, the Point and Rectangle classes correspond to the mathematical concepts of a point and a rectangle.

So far, we have not taken advantage of the features Python provides to support object-oriented programming. These features are not strictly necessary; most of them provide alternative syntax for things we have already done. But in many cases, the alternative is more concise and more accurately conveys the structure of the program.

For example, in the Time program, there is no obvious connection between the class definition and the function definitions that follow. With some examination, it is apparent that every function takes at least one Time object as an argument.

THE STRANGE HISTORY OF THIS BOOK

In January 1999, I was preparing to teach an introductory programming class in Java. I had taught it three times and I was getting frustrated. The failure rate in the class was too high, and, even for students who succeeded, the overall level of achievement was too low.

One of the problems I saw was the books. I had tried three different books (and had read a dozen more), and they all had the same problems. They were too big, with too much unnecessary detail about Java and not enough high-level guidance about how to program. And they all suffered from the trap door effect: they would start out easy, proceed gradually, and then somewhere around Chapter 4 the bottom would fall out. The students would get too much new material, too fast, and I would spend the rest of the semester picking up the pieces.

Two weeks before the first day of classes, I decided to write my own book. I wrote one 10-page chapter a day for 13 days. I made some revisions on Day 14 and then sent it out to be photocopied.

My goals were:

• Keep it short. It is better for students to read 10 pages than not read 50 pages.

• Be careful with vocabulary. I tried to minimize the jargon and define each term at first use.

• […]

In this chapter we will develop classes to represent playing cards, decks of cards, and poker hands. If you don't play poker, you can read about it at wikipedia.org/wiki/Poker, but you don't have to; I'll tell you what you need to know for the exercises.

If you are not familiar with Anglo-American playing cards, you can read about them at wikipedia.org/wiki/Playing_cards.

CARD OBJECTS

There are fifty-two cards in a deck, each of which belongs to one of four suits and one of thirteen ranks. The suits are Spades, Hearts, Diamonds, and Clubs (in descending order in bridge). The ranks are Ace, 2, 3, 4, 5, 6, 7, 8, 9, 10, Jack, Queen, and King. Depending on the game that you are playing, an Ace may be higher than King or lower than 2.

If we want to define a new object to represent a playing card, it is obvious what the attributes should be: rank and suit. It is not as obvious what type the attributes should be. One possibility is to use strings containing words like ‘Spade’ for suits and ‘Queen’ for ranks. One problem with this implementation is that it would not be easy to compare cards to see which had a higher rank or suit.

An alternative is to use integers to encode the ranks and suits. In this context, “encode” means that we are going to define a mapping between numbers and suits, or between numbers and ranks.

The goal of this book is to teach you to think like a computer scientist. This way of thinking combines some of the best features of mathematics, engineering, and natural science. Like mathematicians, computer scientists use formal languages to denote ideas (specifically computations). Like engineers, they design things, assembling components into systems and evaluating tradeoffs among alternatives. Like scientists, they observe the behavior of complex systems, form hypotheses, and test predictions.

The single most important skill for a computer scientist is problem solving. Problem solving means the ability to formulate problems, think creatively about solutions, and express a solution clearly and accurately. As it turns out, the process of learning to program is an excellent opportunity to practice problem-solving skills. That's why this chapter is called “The way of the program.”

On one level, you will be learning to program, a useful skill by itself. On another level, you will use programming as a means to an end. As we go along, that end will become clearer.

THE PYTHON PROGRAMMING LANGUAGE

The programming language you will learn is Python. Python is an example of a high-level language; other high-level languages you might have heard of are C, C++, Perl, and Java.

There are also low-level languages, sometimes referred to as “machine languages” or “assembly languages.” Loosely speaking, computers can only execute programs written in low-level languages.