Computer science deals with people who have problems to solve. Algorithms help find the solutions to those problems. To be a computer scientist means first and foremost that you are a problem solver, capable of constructing algorithms either from scratch or by applying patterns from past experience.
In this text, we use Python as the programming language because it has a clean, simple syntax and an intuitive user environment. The basic collections are powerful yet easy to use. The interactive nature of the language creates a place to test ideas without the need for a lot of coding. Finally, Python provides a textbook-like notation for representing algorithms, alleviating the need for an additional layer of pseudocode. This allows the illustration of many relevant, modern, and interesting problems that make use of algorithms.

Everyday Applications of Computer Science.
Few computer scientists work on problems limited to computers, such as building a better operating system or improving a local area network. Instead, most computer scientists work with people, writing programs that solve problems in areas such as biology, chemistry, business, economics, publishing, automotive design, or entertainment. Look around you and think about the applications you use many times each day — from your browser to an instant messaging program and emails, from word processing to your fitness program, and from your personal calendar to games.
In addition to our laptop computers, tablets, and cell phones, we use computers daily that we may not even realize are computers. For example, the computers in your car check your gas mileage several times every second, examine the wear on your brake pads, monitor your speed and emissions, and update your Global Positioning System (GPS) display to keep track of your exact position and plot it on a map on the dashboard display. More and more appliances have computer-aided functions.
ОГЛАВЛЕНИЕ.
Cover.
Title Page.
Copyright Page.
Dedication Page.
Brief Contents.
Contents.
Preface.
Acknowledgments.
CHAPTER 1 Introduction to Python.
CHAPTER 2 Playing by the Rules.
CHAPTER 3 Codes and Other Secrets.
CHAPTER 4 Introducing the Python Collections.
CHAPTER 5 Bigger Data: File I/O.
CHAPTER 6 Image Processing.
CHAPTER 7 Data Mining: Cluster Analysis.
CHAPTER 8 Cryptanalysis.
CHAPTER 9 Fractals: The Geometry of Nature.
CHAPTER 10 Planet Objects.
CHAPTER 11 Simulation.
CHAPTER 12 A Hierarchy of Shapes.
CHAPTER 13 Interactive Games.
Appendix A: Installing the Required Software.
Appendix B: Python Quick Reference.
Appendix C: turtle Reference.
Appendix D: Answers to Selected Try It Out Exercises.
Glossary.
Index.
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