think python（PDF download）

Preface

The strange history of this book

In January 1999 I was preparing to teach an introductory programming class in Java.Ihad 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.

Oneof the problems I saw was the books. They were toobig, with toomuchunnecessary detail about Java,and not enough high-levelguidance 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 5 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. My goals were:

·Keep it short. It is betterfor students to read 10 pages than not read 50 pages.

·Be careful with vocabulary. I tried to minimize the jargon and define each term a fist use.·Build gradually.To avoid trap doors, I took the most difficult topics and split them into a series of small steps.

·Focus on programming.not the programming language.Iincluded the minimumuseful subset of Java and left out the rest.

I needed a title, so on a whim I chose How to Think Like a Computer Scientist.

My first version was rough, but it worked. Students did the reading, and they understood enough that I could spend class time on the hard topics, the interesting topics and (most important)letting the students practice.

Ireleased the book under the GNU FreeDocumentation License,which allows users to copy,modify, and distribute the book.

What happened nextis thecoolpart. Jeff Elkner, a high school teacherin Virginia,adopted my book and translated it into Python.He sent me acopy of his translation,and Ihad the unusual experience of learning Python by reading my own book.

Jeff and I revised the book, incorporated a case study by Chris Meyers, and in 2001 we released HowtoThink Like a Computer Sdentist:Learning with Python, also under the GNU Free Doc- umentation License. As Green Tea Press, I published the book and started selling hard copies through Amazon.com and college book stores. Other books from Green Tea Press are available at greenteapress. com.

In 2003 I started teaching at Olin College andI got to teach Python for the first time. The contrast with Java was striking. Students struggled less,learmed more, worked on more interesting projects, and generally had a lot more fun.

Over the last five years I have continued to develop the book,correcting errors,improving some of the examples and adding material, especially exercises.In2008 Istarted workona majorrevision— at the same time,I was contacted by an editor at Cambridge University Press who was interested in publishing the next edition. Good timing!

The result is this book,now with the less grandiose title Think Python. Some of the changes are:

·I added a section about debugging at the end of each chapter. These sections present general techniques for finding and avoiding bugs.and warnings about Python pifalls.

·I removed the material in the last few chapters about the implementation of lists and trees.I still love those topics, but I thought they were incongruent with the rest of the book.

·I added more exercises,ranging from short tests of understanding to afew substantialprojects.

·I added a series of case studies—longer examples with exercises, solutions, and discussion. Some of them are based on Swampy.a suite of Pythonprograms I wrote for use in my classes. Swampy,code examples, and some solutions are available from thinkpython.cam.

·I expanded the discussion of program development plans and basic design patterns.· The use of Python is more idiomatic. The book is still about programming, not Python, but now I think the book gets more leverage from the language.

I hope you enjoy working with this book,and that it helps you learn to program and think,at least a little bit, like a computer scientist.

Allen B. Downey

Needham MA

Allen Downey is an Associate Professor of Computer Science at the Franklin W.Olin College of Engineering.

Chapter 1

The way of the program

The goal of this book is to teach you to think like a computer scientist. This way of thinking com- bines some of the best features of mathematics, engineering, and natural science. Like mathemati- cians, 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,andexpress asolution clearly and accurately. As it turns out, the process of leaming 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.

1.1 The Python programming language

The programming language you will learn is Python. Python is an example of ahigh-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. So programs written in a high-level language have to be processed before they can run. This extra processing takes some time, which is a small disadvantage of high-level languages.

The advantages are enormous. First, it is much easierto program in a high-levellanguage. Programs written in a high-level language take less time to write,they are shorter and easier to read,and they are more likely to be correct. Second, high-level languages are portable, meaning that they can run on different kinds of computers with few or no modifications. Low-level programs can run on only one kind of computer and have to be rewritten to run on another.

Due to these advantages,almost all programs are written in high-level languages. Low-level lan- guages are used only for a few specialized applications.

Two kinds of programs process high-level languages into low-levellanguages: interpreters and compilers. An interpreter reads a high-level program and executesit.meaning that it does what the program says. It processes the program a little at a time,alternately reading lines and performing Computations.

Acompiler reads the program and translates it completely before the program starts running.In this context. the high-level program is called the source code.and the translated program is called the object code or the executable. Once a program is compiled,you can execute it repeatedly without further translation.

Python is considered an interpreted language because Python programs are executed by an inter- preter. There are two ways to use the interpreter: interactive mode and script mode.In interactive mode, you type Python programs and the interpreter prints the result:

>>> 1 ＋1
2

The chevron,>>>,is the prompt the interpreteruses to indicate that it is ready.If you type 1 + i, the interpreter replies 2.

Altematively, you can store code in a file and use the interpreter to execute the contents of the file, which is called a script. By convention, Python scripts have names that end with .py.

To execute the script,you have to tell the interpreter the name of the file. In a UNIX command window, you would type python dinsdale.py. In other development environments, the details of executing scripts are different. You can find instructions for yourenvironment at the Python Website python.org.

Working ininteractive mode is convenient for testing small pieces ofcode because you can type and execute them immediately. But for anything more than a few lines,you should save your code as a script so you can modify and execute it in the future.

1.2 What is a program?

A program is a sequence of instructions that specifies how to perform a computation. The compu- tation might be something mathematical,such as solving a system of equations or finding the roots of a polynomial, but it can also be a symbolic computation,such as searching and replacing text in a document or (strangely enough)compiling a program.

The details look different in different languages, but a few basic instructions appear in just about every language:

input: Get data from the keyboard, a file,or some other device.

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