Python Programming 101

Abstract

This text serves well as a follow-on text to Python Programming Fundamentals by Kent D. Lee and published by Springer, but does not require you to have read that text. In this text the next steps are taken to teach you how to handle large amounts of data efficiently. A number of algorithms are introduced and the need for them is motivated through examples that bring meaning to the problems we face as computer programmers. An algorithm is a well-defined procedure for accom- plishing a task. Algorithms are an important part of Computer Science and this text explores many algorithms to give you the background you need when writing programs of your own. The goal is that having seen some of the sorts of algorithms presented in this text, you will be able to apply these techniques to other programs you write in the future. Another goal of this text is to introduce you to the idea of computational complexity. While there are many unique and interesting algorithms that we could explore, it is important to understand that some algorithms are more efficient than others. While computers are very good at doing calculations quickly, an inefficient algorithm can make the fastest computer seem very slow or even make it appear to come to a halt. This text will show you what can and cannot be computed effi- ciently. The text builds this idea of efficiency from the most basic of facts giving you the tools you will need to determine just how efficient any algorithm is so you can make informed judgements about the programs you write. v