Tài liệu Programming for Non-Programmers ppt

Programming for Non-Programmers

Release 2.6.2

Steven F. Lott

January 23, 2012

CONTENTS

I How To Write Your Own Software Using Python 1

1 Preface 5

1.1 Why Read This Book? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

1.2 What Is This Book About? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

1.3 Audience . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6

1.4 Conventions Used in This Book . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8

2 Getting Started 11

2.1 About Python . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

2.2 About Programming . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18

2.3 Let There Be Python: Downloading and Installing . . . . . . . . . . . . . . . . . . . . . . . . 24

2.4 Two Minimally-Geeky Problems : Examples of Things Best Done by Customized Software . 30

2.5 Why Python is So Cool . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35

3 Using Python 39

3.1 Instant Gratification : The Simplest Possible Conversation . . . . . . . . . . . . . . . . . . . 39

3.2 IDLE Time : Using Tools To Be More Productive . . . . . . . . . . . . . . . . . . . . . . . . 48

4 Arithmetic and Expressions 55

4.1 Simple Arithmetic : Numbers and Operators . . . . . . . . . . . . . . . . . . . . . . . . . . . 55

4.2 Better Arithmetic Through Functions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67

4.3 Extra Functions: math and random . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74

4.4 Special Ops : Binary Data and Operators . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79

4.5 More Advanced Expression Topics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 86

5 Programming Essentials 95

5.1 Seeing Results : The print Statement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95

5.2 Turning Python Loose With a Script . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99

5.3 Expressions, Constants and Variables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 102

5.4 Assignment Bonus Features . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 108

5.5 Can We Get Your Input? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 111

6 Some Self-Control 117

6.1 Truth and Logic : Boolean Data and Operators . . . . . . . . . . . . . . . . . . . . . . . . . 117

6.2 Making Decisions : The Comparison Operators . . . . . . . . . . . . . . . . . . . . . . . . . . 123

6.3 Advanced Logic Operators . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 127

6.4 Processing Only When Necessary : The if Statement . . . . . . . . . . . . . . . . . . . . . . 130

6.5 While We Have More To Do : The for Statement . . . . . . . . . . . . . . . . . . . . . . . . 137

6.6 While We Have More To Do : The while Statement . . . . . . . . . . . . . . . . . . . . . . . 144

6.7 Becoming More Controlling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 150

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6.8 Comments and Scripts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 156

7 Organizing Programs with Function Definitions 165

7.1 Adding New Verbs : The def Statement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 165

7.2 Flexibility and Clarity : Optional Parameters, Keyword Arguments . . . . . . . . . . . . . . 177

7.3 A Few More Function Definition Tools . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 187

8 Getting Our Bearings 197

8.1 Where We’ve Been; Where We’re Going . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 197

9 Basic Sequential Collections of Data 201

9.1 Collecting Items in Sequence . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 201

9.2 Sequences of Characters : str and Unicode . . . . . . . . . . . . . . . . . . . . . . . . . . . . 207

9.3 Doubles, Triples, Quadruples : The tuple . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 227

9.4 Flexible Sequences : The list . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 236

9.5 Common List Design Patterns . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 252

10 Additional Processing Control Patterns 263

10.1 The Unexpected : The try and except statements . . . . . . . . . . . . . . . . . . . . . . . 263

10.2 Looping Back : Iterators, the for statement and Generators . . . . . . . . . . . . . . . . . . 277

11 More Data Collections 293

11.1 Collecting Items : The set . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 293

11.2 Mappings : The dict . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 309

11.3 Defining More Flexible Functions with Mappings . . . . . . . . . . . . . . . . . . . . . . . . . 322

11.4 Another Mapping : The defaultdict . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 329

12 Working with Files 335

12.1 External Data and Files . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 335

12.2 Files, Contexts and Patterns of Processing . . . . . . . . . . . . . . . . . . . . . . . . . . . . 346

12.3 File-Related Library Modules . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 352

13 Data + Processing = Objects 365

13.1 Objects: A Retrospective . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 365

13.2 Defining New Objects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 372

14 Modules : The unit of software packaging and assembly 387

14.1 Module Definitions – Adding New Concepts . . . . . . . . . . . . . . . . . . . . . . . . . . . 387

14.2 Fixed-Point Numbers : Doing High Finance with decimal . . . . . . . . . . . . . . . . . . . 402

14.3 Time and Date Processing : The time and datetime Modules . . . . . . . . . . . . . . . . . 407

14.4 Text Processing and Pattern Matching : The re Module . . . . . . . . . . . . . . . . . . . . 422

15 Fit and Finish: Complete Programs 433

15.1 Wrapping and Packaging Our Solution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 433

15.2 Architectural Patterns – A Family Tree . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 441

15.3 Professionalism : Additional Tips and Hints . . . . . . . . . . . . . . . . . . . . . . . . . . . 445

16 Appendices 455

16.1 Debugging Tips . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 455

16.2 Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 473

16.3 Glossary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 473

17 Indices and Tables 479

18 Other Back Matter 481

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Bibliography 483

Python Module Index 485

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Part I

How To Write Your Own Software

Using Python

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For any reuse or distribution, you must make clear to others the license terms of this work.

The Walrus and the Carpenter – Lewis Carroll

“The time has come,” the Walrus said,

“To talk of many things:

Of shoes – and ships – and sealing-wax –

Of cabbages – and kings –

And why the sea is boiling hot –

and whether pigs have wings.”

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CHAPTER

ONE

PREFACE

1.1 Why Read This Book?

You’ll need to read this book when you have the following three things happening at the same time:

• You have a problem to solve that involves data and processing.

• You’ve found that the common desktop tools (word processors, spread sheets, databases, organizers,

graphics) won’t really help. You’ve found that they require too much manual pointing and clicking, or

they don’t do the right kinds of processing on your data.

• You’re ready to invest some of your own time to learn how to write customized software that will solve

your problem.

You’ll want to read this book if you are tinkerer who likes to know how things really work. For many people,

a computer is just an appliance. You may not find this satisfactory, and you want to know more. People

who tinker with computers are called hackers, and you are about to join their ranks.

Python is what you’ve been looking for. It is an easy-to-use tool that can do any kind of processing on any

kind of data. Seriously: any processing, any data. Programming is the term for setting up a computer to

do the processing you define on your data. Once you learn the Python language, you can solve your data

processing problem.

Our objective is to get you, a non-programming newbie, up and running. When you’re done with this book,

you’ll be ready to move on to a more advanced Python book. For example, a book about the Python

libraries. You can use these libraries can help you build high-quality software with a minimum of work.

1.2 What Is This Book About?

This book is about many things. The important topics include Python, programming, languages, data,

processing, and some of the skills that make up the craft of programming. We’ll talk about the core

intellectual tools of abstraction, algorithms and the formality of computer languages. We’ll also touch on

math and logic, statistics, and casino games.

Python. Python is a powerful, flexible toolbox and workbench that can help solve your data processing

problem. If you need to write customized software that does precisely what you want, and you want that

software to be readable, maintainable, adaptable, inexpensive and make best use of your computer, you need

Python.

Programming. When we’ve written a sequence of statements in the Python language, we can then use

that sequence over and over again. We can process different sets of data in a standard, automatic fashion.

We’ve created a program that can automate data processing tasks, replacing tedious or error-prone pointing

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and clicking in other software tools. Also, we can create programs that do things that other desktop tools

can’t do at all.

The big picture is this: the combination of the Python program plus a unique sequence of Python language

statements that we create can have the effect of creating a new application for our computer. This means

that our application uses the existing Python program as its foundation. The Python program, in turn,

depends on many other libraries and programs on your computer. The whole structure forms a kind of

technology stack, with our program on top, controlling the whole assembly.

Languages. We’ll look at three facets of a programming language: how you write it, what it means, and the

additional practical considerations that make a program useful. We’ll use these three concepts to organize

our presentation of the language. We need to separate these concepts to assure that there isn’t a lot of

confusion between the real meaning and the ways we express that meaning.

The sentences “Xander wrote a tone poem for chamber orchestra” and “The chamber orchestra’s tone poem

was written by Xander” have the same meaning, but express it different ways. They have the same semantics,

but different syntax. For example, in one sentence the verb is “wrote”, in the other sentence it is “was written

by” : different forms of the verb to write. The first form is written in active voice, and second form is called

the passive voice. Pragmatically, the first form is slightly clearer and more easily understood.

The syntax of the Python language is covered here, and in the Python Reference Manual [PythonRef]. Python

syntax is simple, and very much like English. We’ll provide many examples of language syntax. We’ll also

provide additional tips and hints focused on the newbies and non-programmers. Also, when you install

Python, you will also install a Python Tutorial [PythonTut] that presents some aspects of the language, so

you’ll have at least three places to learn syntax.

The semantics of the language specify what a statement really means. We’ll define the semantics of each

statement by showing what it makes the Python program do to your data. We’ll also be able to show

where there are alternative syntax choices that have the same meaning. In addition to semantics being

covered in this book, you’ll be able to read about the meaning of Python statements in the Python Reference

Manual [PythonRef], the Python Tutorial [PythonTut], and chapter two of the Python Library Reference

[PythonLib].

In this book, we’ll try to provide you with plenty of practical advice. In addition to breaking the topic

into bite-sized pieces, we’ll also present lots of patterns for using Python that you can apply to real-world

problems.

Extensions. Part of the Python technology stack are the extension libraries. These libraries are added

onto Python, which has the advantage of keeping the language trim and fit. Software components that you

might need for specialized processing are kept separate from the core language. Plus, you can safely ignore

the components you don’t need.

This means that we actually have two things to learn. First, we’ll learn the language. After that, we’ll look

at a few of the essential libraries. Once we’ve seen that, we can see how to make our own libraries, and our

own application programs.

1.3 Audience

Programming and Computer Skills. We’re going to focus on programming skills, which means we have

to presume that you already have general computer skills. You should fit into one of these populations.

• You have good computer skills, but you want to learn to program. You are our target crew. Welcome

aboard.

• You have some programming experience, and you want to learn Python. You’ll find that most of

Getting Started is something you can probably skim through. We’ve provided some advanced material

that you may find interesting.

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What skills will you need? How will we build up your new skills?

Skills You’ll Need. This book assumes an introductory level of skill with any of the commonly-available

computer systems. Python runs on almost any computer; because of this, we call it platform-independent.

We won’t presume a specific computer or operating system. Some basic skills will be required. If these are

a problem, you’ll need to brush up on these before going too far in this book.

• Can you download and install software from the internet? You may need to do this to get the Python

distribution kit from http://www.python.org. If you’ve never downloaded and installed software before,

you may need some help with that skill.

• Do you know how to create text files? We will address doing this using a program called IDLE, the

Python Integrated Development Environment. If you don’t know how to create folders and files, or if

you have trouble finding files you’ve saved on your computer, you’ll need to expand those skills before

trying to do any programming.

• Do you know some basic algebra? Some of the exercises make use of some basic algebra. A few will

compute some statistics. We shouldn’t get past high-school math, and you probably don’t need to

brush up too much on this.

How We Help. Newbie programmers with an interest in Python are our primary audience. We provide

specific help for you in a number of ways.

• Programming is an activity that includes the language skills, but also includes design, debugging and

testing; we’ll help you develop each of these skills.

• We’ll address some of the under-the-hood topics in computers and computing, discussing how things

work and why they work that way. Some things that you’ve probably taken for granted as a user

become more important as you grow to be a programmer.

• We won’t go too far into software engineering and design. We need to provide some hints on how

software gets written, but this is not a book for computer professionals; it’s for computer amateurs

with interesting data or processing needs.

• We cover a few of the most important modules to specifically prevent newbie programmers from

struggling or – worse – reinventing the wheel with each project. We can’t, however, cover too much in

a newbie book. When you’re ready for more information on the various libraries, you’re also ready for

a more advanced Python book.

When you’ve finished with this book you should be able to do the following.

• Use the core language constructs: variables, statements, exceptions, functions and classes. There are

only twenty statements in the language, so this is an easy undertaking.

• Use the Python collection classes to work with more than one piece of data at a time.

• Use a few of the Python extension libraries. We’re only going to look at libraries that help us with

finishing a polished and complete program.

A Note on Clue Absorption. Learning a programming language involves accumulating many new and

closely intertwined concepts. In our experience teaching, coaching and doing programming, there is an upper

limit on the “Clue Absorption Rate”. In order to keep below this limit, we’ve found that it helps to build up

the language as ever-expanding layers. We’ll start with a very tiny, easy to understand subset of statements;

to this we’ll add concepts until we’ve covered the entire Python language and all of the built-in data types.

Our part of the agreement is to do things in small steps. Here’s your part: you learn a language by using it.

In order for each layer to act as a foundation for the following layers, you have to let it solidify by doing small

programming exercises that exemplify the layer’s concepts. Learning Python is no different from learning

Swedish. You can read about Sweden and Swedish, but you must actually use the language to get it off the

page and into your head. We’ve found that doing a number of exercises is the only way to internalize each

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language concept. There is no substitute for hands-on use of Python. You’ll need to follow the examples

and do the exercises. As you can probably tell from this paragraph, we can’t emphasize this enough.

The big difference between learning Python and learning Swedish is that you can immediately interact with

the Python program, doing real work in the Python language. Interacting in Swedish can more difficult.

The point of learning Swedish is to interact with people: for example, buying some kanelbulle (cinnamon

buns) for fika (snack). However, unless you live in Sweden, or have friends or neighbors who speak Swedish,

this interactive part of learning a human language is difficult. Interacting with Python only requires a

working computer, not a trip to Kiruna.

Also, your Swedish phrase-book gives you little useful guidance on how to pronounce words like sked (spoon)

or sju (seven); words which are notoriously tricky for English-speakers to get right. Python, however, is a

purely written language so you don’t have subtleties of pronunciation, you only have spelling and grammar.

1.4 Conventions Used in This Book

Here is how we’ll show Python programs in the rest of the book. The programs will be in separate boxes,

in a different font, often with numbered “callouts” to help explain the program. This example is way too

advanced to read in detail (it’s part of Mappings : The dict) it just shows what examples look like.

Python Example

1 from __future__ import print_function, division

2 combo = { }

3 for i in range(1,7):

4 for j in range(1,7):

5 roll= i+j

6 combo.setdefault( roll, 0 )

7 combo[roll] += 1

8 for n in range(2,13):

9 print("{0:d} {1:.2f}".format(n, combo[n]/36))

Line 1 creates a Python dictionary, a map from key to value. In this case, the key will be a roll, a number

from 2 to 12. The value will be a count of the number of times that roll occurred.

Line 5 assures that the rolled number exists in the dictionary. If it doesn’t exist, it will default, and will be

assigned frequency count of 0.

Line 7 prints each member of the resulting dictionary.

The output from the above program will be shown as follows:

2 0.03%

3 0.06%

4 0.08%

5 0.11%

6 0.14%

7 0.17%

8 0.14%

9 0.11%

10 0.08%

11 0.06%

12 0.03%

Tool completed successfully

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Programming for Non-Programmers, Release 2.6.2

We will use the following type styles for references to a specific Class, method(), attribute, which includes

both class variables or instance variables.

Sidebars

When we do have a digression, it will appear in a sidebar, like this.

Tip: Tips

There will be design tips, and warnings, in the material for each exercise. These reflect considerations and

lessons learned that aren’t typically clear to starting programmers.

1.4. Conventions Used in This Book 9