An Introduction to Computer Science Using Python 3.6
Paul Gries . Jennifer Campbell . Jason Montojo
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Book Details
Price
|
2.50 |
|---|---|
Pages
| 397 p |
File Size
|
8,428 KB |
File Type
|
PDF format |
ISBN-13
| 978-1-6805026-8-8 |
Copyright©
| 2017 The Pragmatic Programmers, LLC |
Practical Programming
I wish I could go back in time and give this book to my 10-year-old self when I
first learned programming! It’s so much more engaging, practical, and accessible
than the dry introductory programming books that I tried (and often failed) to
comprehend as a kid. I love the authors’ hands-on approach of mixing explanations
with code snippets that students can type into the Python prompt.
➤ Philip Guo
Creator of Online Python Tutor (www.pythontutor.com), Assistant Professor, Department
of Cognitive Science, UCSD
Practical Programming delivers just what it promises: a clear, readable, usable
introduction to programming for beginners. This isn’t just a guide to hacking
together programs. The book provides foundations to lifelong programming skills:
a crisp, consistent, and visual model of memory and execution and a design recipe
that will help readers produce quality software.
➤ Steven Wolfman
Professor of Teaching, Department of Computer Science, University of British Columbia
This excellent text reflects the authors’ many years of experience teaching Python
to beginning students. Topics are presented so that each leads naturally to the
next, and common novice errors and misconceptions are explicitly addressed. The
exercises at the end of each chapter invite interested students to explore computer
science and programming language topics.
➤ Kathleen Freeman
Director of Undergraduate Studies, Department of Computer and Information
Science, University of Oregon
Preface
This book uses the Python programming language to teach introductory
computer science topics and a handful of useful applications. You’ll certainly
learn a fair amount of Python as you work through this book, but along the
way you’ll also learn about issues that every programmer needs to know:
ways to approach a problem and break it down into parts, how and why to
document your code, how to test your code to help ensure your program does
what you want it to, and more.
We chose Python for several reasons:
• It is free and well documented. In fact, Python is one of the largest and
best-organized open source projects going.
• It runs everywhere. The reference implementation, written in C, is used
on everything from cell phones to supercomputers, and it’s supported by
professional-quality installers for Windows, macOS, and Linux.
• It has a clean syntax. Yes, every language makes this claim, but during
the several years that we have been using it at the University of Toronto,
we have found that students make noticeably fewer “punctuation” mistakes
with Python than with C-like languages.
• It is relevant. Thousands of companies use it every day: it is one of the
languages used at Google, Industrial Light & Magic uses it extensively,
and large portions of the game EVE Online are written in Python. It is
also widely used by academic research groups.
• It is well supported by tools. Legacy editors like vi and Emacs all have
Python editing modes, and several professional-quality IDEs are available.
(We use IDLE, the free development environment that comes with a
standard Python installation.)
Table of Contents
Acknowledgments . . . . . . . . . . . xi
Preface . . . . . . . . . . . . . . xiii
1. What’s Programming? . . . . . . . . . . 1
Programs and Programming 2
What’s a Programming Language? 3
What’s a Bug? 4
The Difference Between Brackets, Braces, and Parentheses 5
Installing Python 5
2. Hello, Python . . . . . . . . . . . . . 7
How Does a Computer Run a Python Program? 7
Expressions and Values: Arithmetic in Python 9
What Is a Type? 12
Variables and Computer Memory: Remembering Values 15
How Python Tells You Something Went Wrong 22
A Single Statement That Spans Multiple Lines 23
Describing Code 25
Making Code Readable 26
The Object of This Chapter 27
Exercises 27
3. Designing and Using Functions . . . . . . . . 31
Functions That Python Provides 31
Memory Addresses: How Python Keeps Track of Values 34
Defining Our Own Functions 35
Using Local Variables for Temporary Storage 39
Tracing Function Calls in the Memory Model 40
Designing New Functions: A Recipe 47
Writing and Running a Program 58
Omitting a return Statement: None 60
Dealing with Situations That Your Code Doesn’t Handle 61
What Did You Call That? 62
Exercises 63
4. Working with Text . . . . . . . . . . . 65
Creating Strings of Characters 65
Using Special Characters in Strings 68
Creating a Multiline String 70
Printing Information 70
Getting Information from the Keyboard 73
Quotes About Strings 74
Exercises 75
5. Making Choices . . . . . . . . . . . . 77
A Boolean Type 77
Choosing Which Statements to Execute 86
Nested if Statements 92
Remembering Results of a Boolean Expression Evaluation 92
You Learned About Booleans: True or False? 94
Exercises 94
6. A Modular Approach to Program Organization . . . . 99
Importing Modules 100
Defining Your Own Modules 104
Testing Your Code Semiautomatically 110
Tips for Grouping Your Functions 112
Organizing Our Thoughts 113
Exercises 113
7. Using Methods . . . . . . . . . . . . 115
Modules, Classes, and Methods 115
Calling Methods the Object-Oriented Way 117
Exploring String Methods 119
What Are Those Underscores? 123
A Methodical Review 125
Exercises 126
8. Storing Collections of Data Using Lists . . . . . . 129
Storing and Accessing Data in Lists 129
Type Annotations for Lists 133
Modifying Lists 133
Operations on Lists 135
Slicing Lists 137
Aliasing: What’s in a Name? 139
List Methods 141
Working with a List of Lists 142
A Summary List 145
Exercises 145
9. Repeating Code Using Loops . . . . . . . . 149
Processing Items in a List 149
Processing Characters in Strings 151
Looping Over a Range of Numbers 152
Processing Lists Using Indices 154
Nesting Loops in Loops 156
Looping Until a Condition Is Reached 160
Repetition Based on User Input 162
Controlling Loops Using break and continue 163
Repeating What You’ve Learned 167
Exercises 168
10. Reading and Writing Files . . . . . . . . . 173
What Kinds of Files Are There? 173
Opening a File 175
Techniques for Reading Files 179
Files over the Internet 183
Writing Files 185
Writing Example Calls Using StringIO 186
Writing Algorithms That Use the File-Reading Techniques 188
Multiline Records 195
Looking Ahead 198
Notes to File Away 200
Exercises 201
11. Storing Data Using Other Collection Types . . . . . 203
Storing Data Using Sets 203
Storing Data Using Tuples 209
Storing Data Using Dictionaries 214
Inverting a Dictionary 222
Using the in Operator on Tuples, Sets, and Dictionaries 223
Comparing Collections 224
Creating New Type Annotations 224
A Collection of New Information 226
Exercises 226
12. Designing Algorithms . . . . . . . . . . 229
Searching for the Two Smallest Values 230
Timing the Functions 238
At a Minimum, You Saw This 240
Exercises 240
13. Searching and Sorting . . . . . . . . . . 243
Searching a List 243
Binary Search 250
Sorting 256
More Efficient Sorting Algorithms 265
Merge Sort: A Faster Sorting Algorithm 266
Sorting Out What You Learned 270
Exercises 272
14. Object-Oriented Programming . . . . . . . . 275
Understanding a Problem Domain 276
Function isinstance, Class object, and Class Book 277
Writing a Method in Class Book 280
Plugging into Python Syntax: More Special Methods 285
A Little Bit of OO Theory 288
A Case Study: Molecules, Atoms, and PDB Files 293
Classifying What You’ve Learned 297
Exercises 298
15. Testing and Debugging . . . . . . . . . . 303
Why Do You Need to Test? 303
Case Study: Testing above_freezing 304
Case Study: Testing running_sum 309
Choosing Test Cases 315
Hunting Bugs 316
Bugs We’ve Put in Your Ear 317
Exercises 317
16. Creating Graphical User Interfaces . . . . . . . 321
Using Module tkinter 321
Building a Basic GUI 323
Models, Views, and Controllers, Oh My! 327
Customizing the Visual Style 331
Introducing a Few More Widgets 335
Object-Oriented GUIs 338
Keeping the Concepts from Being a GUI Mess 339
Exercises 340
17. Databases . . . . . . . . . . . . . 343
Overview 343
Creating and Populating 344
Retrieving Data 348
Updating and Deleting 351
Using NULL for Missing Data 352
Using Joins to Combine Tables 353
Keys and Constraints 357
Advanced Features 358
Some Data Based On What You Learned 364
Exercises 365
Bibliography . . . . . . . . . . . . 369
Index . . . . . . . . . . . . . . 371
Bookscreen
Our Approach
We have organized the book into two parts. The first covers fundamental programming
ideas: how to store and manipulate information (numbers, text, lists,
sets, dictionaries, and files), how to control the flow of execution (conditionals
and loops), how to organize code (functions and modules), how to ensure your
code works (testing and debugging), and how to plan your program (algorithms).
The second part of the book consists of more or less independent chapters
on more advanced topics that assume all the basic material has been covered.
The first of these chapters shows how to create and manage your own types
of information. It introduces object-oriented concepts such as encapsulation,
inheritance, and polymorphism. The other chapters cover testing, databases,
and graphical user interface construction.