How to Think Like a Computer Scientist - Learning with Python, 2008a

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Appendix C Recommendations for further reading So where do you go from here? There are many directions to pursue, extending your knowledge of Python specifically and computer science in general. The examples in this book have been deliberately simple, but they may not have shown off Python’s most exciting capabilities. Here is a sampling of extensions to Python and suggestions for projects that use them. • GUI (graphical user interface) programming lets your program use a windowing environment to interact with the user and display graphics. The oldest graphics package for Python is Tkinter, which is based on Jon Ousterhout’s Tcl and Tk scripting languages. Tkinter comes bundled with the Python distribution. Another popular platform is wxPython, which is essentially a Python veneer over wxWindows, a C++ package which in turn implements windows using native interfaces on Windows and Unix (including Linux) platforms. The windows and controls under wxPython tend to have a more native look and feel than those of Tkinter and are somewhat simpler to program. Any type of GUI programming will lead you into event-driven programming, where the user and not the programmer determines the flow of execution. This style of programming takes some getting used to, sometimes forcing you to rethink the whole structure of a program. • Web programming integrates Python with the Internet. For example, you can build web client programs that open and read a remote web page (almost) as easily as you can open a file on disk. There are also Python modules
240 Recommendations for further reading that let you access remote files via ftp, and modules to let you send and receive email. Python is also widely used for web server programs to handle input forms. • Databases are a bit like super files where data is stored in predefined schemas, and relationships between data items let you access the data in various ways. Python has several modules to enable users to connect to various database engines, both Open Source and commercial. • Thread programming lets you run several threads of execution within a single program. If you have had the experience of using a web browser to scroll the beginning of a page while the browser continues to load the rest of it, then you have a feel for what threads can do. • When speed is paramount Python extensions may be written in a compiled language like C or C++. Such extensions form the base of many of the modules in the Python library. The mechanics of linking functions and data is somewhat complex. SWIG (Simplified Wrapper and Interface Generator) is a tool to make the process much simpler. C.1 Python-related web sites and books Here are the authors’ recommendations for Python resources on the web: • The Python home page at www.python.org is the place to start your search for any Python related material. You will find help, documentation, links to other sites and SIG (Special Interest Group) mailing lists that you can join. • The Open Book Project www.ibiblio.com/obp contains not only this book online but also similar books for Java and C++ by Allen Downey. In addition there are Lessons in Electric Circuits by Tony R. Kuphaldt, Getting down with ..., a set of tutorials on a range of computer science topics, written andeditedbyhighschoolstudents,Python for Fun, a set of case studies in Python by Chris Meyers, and The Linux Cookbook by Michael Stultz, with 300 pages of tips and techniques. • Finally if you go to Google and use the search string “python -snake -monty” you will get about 750,000 hits.
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How to Think Like a Computer Scient
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How to Think Like a Computer Scient
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Foreword By David Beazley As an edu
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Preface By Jeff Elkner This book ow
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make instant changes whenever someo
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call (type) out its name.” Parame
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Contributor List To paraphrase the
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• Paul Sleigh found an error in C
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xvii • Roger Sperberg pointed out
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Contents Foreword v Preface vii Con
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Contents xxi 4.7 Nested conditional
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Contents xxiii 8.15 Matrices . . .
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Contents xxv 14.4 A more complicate
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Contents xxvii 19.4 Improved Linked
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Chapter 1 The way of the program Th
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1.2 What is a program? 3 $ python P
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1.3 What is debugging? 5 1.3.2 Runt
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1.4 Formal and natural languages 7
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1.6 Glossary 9 source code: A progr
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Chapter 2 Variables, expressions an
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2.3 Variable names and keywords 13
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2.4 Statements 15 >>> 76trombones =
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2.6 Operators and operands 17 2.6 O
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2.9 Composition 19 On one hand, thi
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2.11 Glossary 21 state diagram: A g
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Chapter 3 Functions 3.1 Function ca
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3.4 Math functions 25 >>> minute =
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3.6 Adding new functions 27 problem
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3.7 Definitions and use 29 3.7 Defi
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3.10 Variables and parameters are l
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3.12 Functions with results 33 The
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3.13 Glossary 35 local variable: A
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Chapter 4 Conditionals and recursio
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4.4 Conditional execution 39 In gen
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4.7 Nested conditionals 41 Each con
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4.9 Recursion 43 countdown expects
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4.11 Infinite recursion 45 4.11 Inf
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4.13 Glossary 47 block: A group of
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Chapter 5 Fruitful functions 5.1 Re
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5.2 Program development 51 avoid lo
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5.3 Composition 53 3. Once the prog
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5.5 More recursion 55 But the extra
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5.6 Leap of faith 57 __main__ facto
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5.8 Checking types 59 >>> factorial
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Chapter 6 Iteration 6.1 Multiple as
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6.2 The while statement 63 1. Evalu
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6.3 Tables 65 1.0 0.0 2.0 0.6931471
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6.5 Encapsulation and generalizatio
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6.7 Local variables 69 6.7 Local va
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6.9 Functions 71 the function is ca
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Chapter 7 Strings 7.1 A compound da
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7.3 Traversal and the for loop 75 T
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7.6 Strings are immutable 77 Other
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7.9 The string module 79 As an exer
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7.11 Glossary 81 There are other us
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Chapter 8 Lists A list is an ordere
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8.3 List length 85 If you try to re
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8.6 List operations 87 for VARIABLE
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8.9 List deletion 89 >>> list = [
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8.10 Objects and values 91 8.10 Obj
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8.13 List parameters 93 >>> b[0] =
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8.16 Strings and lists 95 might be
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Chapter 9 Tuples 9.1 Mutability and
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9.3 Tuples as return values 99 9.3
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9.6 Counting 101 >>> randomList(8)
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9.7 Many buckets 103 bucketWidth =
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9.9 Glossary 105 9.9 Glossary Assig
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Chapter 10 Dictionaries The compoun
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10.2 Dictionary methods 109 10.2 Di
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10.5 Hints 111 An alternative is to
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10.6 Long integers 113 Using this v
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10.8 Glossary 115 overflow: A numer
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Chapter 11 Files and exceptions Whi
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11.1 Text files 119 The following f
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11.2 Writing variables 121 the str
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11.3 Directories 123 11.3 Directori
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11.5 Exceptions 125 Or trying to op
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11.6 Glossary 127 format sequence:
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Chapter 12 Classes and objects 12.1
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12.3 Instances as arguments 131 con
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12.5 Rectangles 133 >>> p1 = Point(
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12.8 Copying 135 The variables dwid
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12.9 Glossary 137 12.9 Glossary cla
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Chapter 13 Classes and functions 13
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13.3 Modifiers 141 The output of th
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13.5 Prototype development versus p
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13.8 Glossary 145 Similarly, the te
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Chapter 14 Classes and methods 14.1
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14.3 Another example 149 class Time
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14.5 Optional arguments 151 if done
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14.7 Points revisited 153 >>> curre
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14.9 Polymorphism 155 def __mul__(s
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14.10 Glossary 157 Of course, we in
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Chapter 15 Sets of objects 15.1 Com
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15.3 Class attributes and the str m
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15.5 Decks 163 def __cmp__(self, ot
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15.7 Shuffling the deck 165 >>> dec
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15.9 Glossary 167 class Deck: ... d
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Chapter 16 Inheritance 16.1 Inherit
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16.3 Dealing cards 171 16.3 Dealing
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16.6 OldMaidHand class 173 class Ca
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16.7 OldMaidGame class 175 Hand fra
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16.7 OldMaidGame class 177 class Ol
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16.8 Glossary 179 Hand Allen picked
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Chapter 17 Linked lists 17.1 Embedd
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17.3 Lists as collections 183 node1
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17.5 Infinite lists 185 We invoke t
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17.8 Wrappers and helpers 187 def r
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Page 220 and 221: Chapter 18 Stacks 18.1 Abstract dat
Page 222 and 223: 18.4 Pushing and popping 193 def po
Page 224 and 225: 18.7 Evaluating postfix 195 Python
Page 226 and 227: 18.9 Glossary 197 18.9 Glossary abs
Page 228 and 229: Chapter 19 Queues This chapter pres
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Page 232 and 233: 19.5 Priority queue 203 and it is m
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Page 236 and 237: Chapter 20 Trees Like linked lists,
Page 238 and 239: 20.2 Traversing trees 209 20.2 Trav
Page 240 and 241: 20.4 Tree traversal 211 def printTr
Page 242 and 243: 20.5 Building an expression tree 21
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Page 246 and 247: 20.7 The animal tree 217 Are you th
Page 248 and 249: 20.8 Glossary 219 def yes(ques): fr
Page 250 and 251: Appendix A Debugging Different kind
Page 252 and 253: A.2 Runtime errors 223 A.1.1 I can
Page 254 and 255: A.2 Runtime errors 225 If there is
Page 256 and 257: A.3 Semantic errors 227 A.3 Semanti
Page 258 and 259: A.3 Semantic errors 229 return self
Page 260 and 261: Appendix B Creating a new data type
Page 262 and 263: B.1 Fraction multiplication 233 >>>
Page 264 and 265: B.4 Comparing fractions 235 This re
Page 266 and 267: B.6 Glossary 237 reduce: To change
Page 270 and 271: C.2 Recommended general computer sc
Page 272 and 273: Index Make Way for Ducklings, 75 Py
Page 274 and 275: Index 245 element, 83, 96 embedded
Page 276 and 277: Index 247 well-formed, 189 list del
Page 278 and 279: Index 249 redundancy, 7 reference,
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