Computer Science

• Strong fundamentals – Teaches readers how to program in a style that leads them to immediate success, while also gaining a deeper understanding that serves as the foundation for further study.

• Progressive lesson plans – Build upon one another with consistency. EX. A television analogy is introduced as pure design in Ch. 1, then revisited as a tangible class implementation (Ch. 6) and as a base for inheritance (Ch. 9).

• Flexible organization – Allows instructors to reorder or emphasize and deemphasize topics as needed.

• Natural development of object-oriented principles – Familiarizes students with the terminology of object-oriented programming, the concept of an object's underlying state information, and its menu of available behaviors.

• Cases studies with concrete applications – Draw on a wide variety of domains such as animation, puzzles, biology, and math to showcase new techniques and demonstrate the use of computer science in the real world.

• Support for graphics – Includes an exclusive, easy-to-use custom graphics library that helps students grasp basic concepts, while also supporting more advanced explorations into themes such as transformations, double buffering, and event-driven programming.

• Transition to Java or C++ – Lays the groundwork for students’ transition to other languages later in the curriculum, most prominently Java and C++.

• Advanced course material – Provides coverage of more complex topics, including recursion, data structures and algorithms, event-driven programming, and network programming.

• Supportive pedagogy – Displays all source code prominently within boxes, and includes "Word of Warning" features to highlight issues that commonly trip up beginning programmers. "For the Guru" boxes present deeper understanding in context for advanced students.

• Extensive end matter in each chapter – Includes a list of key points from the chapter, glossary of newly introduced terms, clearly marked Practice Problems with solutions, and extensive Exercises and Projects.

	Preface	vii
I	Fundamental Topics	3
1	Cornerstones of Computing	5
1.1	Data and Types	5
1.2	Operations, Functions, and Algorithms	6
1.3	High-Level Programming Languages	10
1.4	The Object-Oriented Paradigm	12
1.5	Design and Modeling	23
1.6	Chapter Review	25
2	Getting Started in Python	31
2.1	The Python Interpreter	31
2.2	Using Objects: the list Class	32
2.3	Other Sequence Classes: str and tuple	49
2.4	Numeric Types: int, long, and float	58
2.5	Type Conversions	60
2.6	Calling Functions	61
2.7	Python Modules	62
2.8	Expressions	64
2.9	Using a File for Source Code	69
2.10	Case Study: Strings and Lists	75
2.11	Chapter Review	76
3	Getting Started with Graphics	89
3.1	The Canvas	90
3.2	Drawable Objects	93
3.3	Rotating, Scaling, and Flipping	103
3.4	Cloning	106
3.5	Case Study: Smiley Face	106
3.6	Layers	108
3.7	Animation	111
3.8	Graphical User Interfaces	113
3.9	Case Study: Flying Arrows	116
3.10	Chapter Review	120
4	Elementary Control Structures	125
4.1	For Loops	125
4.2	Case Study: DNA to RNA Transcription	135
4.3	Case Study: Drawing a Pyramid	136
4.4	Conditional Statements	140
4.5	List Comprehension	148
4.6	Chapter Review	149
5	Additional Control Structures	159
5.1	While Loops	160
5.2	Functions	166
5.3	Avoiding Duplicate Code	172
5.4	Case Study: Computing the Square Root	175
5.5	Error Checking and Exceptions	179
5.6	Case Study: Simulating a Chain under the Force of Gravity	185
5.7	Chapter Review	192
6	Defining Our Own Classes	203
6.1	A Simple Point Class	203
6.2	A Robust Point Class	207
6.3	A Television Class	214
6.4	A Fraction Class	222
6.5	Advanced Lessons	226
6.6	Chapter Review	229
7	Good Software Practices	237
7.1	Overview of Mastermind	237
7.2	Top-Down Design and Bottom-Up Implementation	238
7.3	Our Mastermind Design	239
7.4	Naming Conventions	244
7.5	Formal Documentation: Python Docstrings	246
7.6	Encapsulation of Implementation Details	250
7.7	Modules and Unit Testing	252
7.8	Error Checking	258
7.9	Mastermind: Pulling It Together	260
7.10	Flexibility in Design: Graphical Output	263
7.11	Chapter Review	266
8	Input, Output, and Files	271
8.1	Standard Input and Output	271
8.2	Formatted Strings	273
8.3	Working with Files	275
8.4	Handling Newline Characters	279
8.5	Case Studies	281
8.6	Chapter Review	292
9	Inheritance	299
9.1	Augmentation	300
9.2	Specialization	303
9.3	When Should Inheritance (Not) Be Used	308
9.4	Class Hierarchies and cs1graphics	310
9.5	Multiple Inheritance	318
9.6	Case Study: a Mailbox Class	321
9.7	Chapter Review	326
II	Advanced Topics	331
10	Deeper Understanding of the Management of Objects	333
10.1	Understanding Objects and References	334
10.2	Objects that Reference Other Objects	341
10.3	Objects in the Context of a Function	348
10.4	Case Study: Subtleties in the cs1graphics Module	353
10.5	Chapter Review	356
11	Recursion	361
11.1	A Bullseye Class	362
11.2	Our Own List Implementation	368
11.3	Functional Recursion	374
11.4	Binary Search	376
11.5	Case Study: Solving a Puzzle	383
11.6	Chapter Review	388
12	More Python Containers	397
12.1	Two Familiar Containers: list and tuple	399
12.2	Dictionaries	401
12.3	Containers of Containers	406
12.4	Sets	409
12.5	Arrays	414
12.6	Python's Internal Use of Dictionaries	416
12.7	Case Study: a Simple Search Engine	422
12.8	Chapter Review	430
13	Implementing Data Structures	435
13.1	Measuring Efficiency	436
13.2	Python's list Class	438
13.3	Our Own Dictionary Implementation	441
13.4	Binary Search Trees	451
13.5	Chapter Review	461
14	Sorting Algorithms	467
14.1	Customizing Use of Python's Sort	467
14.2	Selection Sort	471
14.3	Insertion Sort	473
14.4	Merge Sort	475
14.5	Quicksort	482
14.6	Which Algorithm Does Python Use?	487
14.7	Chapter Review	488
15	Event-Driven Programming	493
15.1	Basics of Event-Driven Programming	494
15.2	Event Handling in Our Graphics Module	496
15.3	The Event Class	499
15.4	Programming Using Events	505
15.5	Case Study: a Full GUI for Mastermind	512
15.6	Chapter Review	519
16	Network Programming	521
16.1	A Network Primer	521
16.2	Writing a Basic Client	524
16.3	Basic Network Servers	529
16.4	Case Study: Network Chat Room	532
16.5	Peer-to-Peer: Instant Messenger	540
16.6	Server-Side Scripting and CGI	543
16.7	Case Study: Searching the Web	546
16.8	Chapter Review	553
	Appendices	559
A	Using IDLE	561
A.1	Using the Python Interpreter within IDLE	561
A.2	Working with Files	562
B	Python, Java, and C++: a Transition Guide	565
B.1	The Purpose of This Guide	565
B.2	High-Level Programming Languages	566
B.3	A First Glance at Java and C++	569
B.4	Java Guide	572
B.5	C++ Guide	599
C	Solutions to Practice Exercises	625
D	Glossary	649
	Index	659

Python Programming  (Computer Science)

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Chapter 4 - Elementary Control Structures
Chapter 11 - Recursion

Drs. Goldwasser and Letscher are on the Faculty in the Department of Mathematics and Computer Science at Saint Louis University.  Both are active in teaching the introductory computer science course for which this book was designed.  They have described the development of this material at the premier national and international conferences on Computer Science education. Dr. Goldwasser received his Ph.D. in Computer Science at Stanford University in 1997, and has taught courses at Stanford University, Princeton University, Loyola University of Chicago, and Colorado College before joining Saint Louis University. His research interests center around the design and analysis of algorithms. Dr. Letscher received his Ph.D. in Mathematics from the University of Michigan in 1997, and has taught courses in mathematics and computer science at the University of California San Diego, Oklahoma State University, and the American Institute of Mathematics before joining Saint Louis University. His primary research interests center around computational topology.

Object-Oriented Programming in PYTHON

Goldwasser

Letscher

Python's simple syntax, consistent semantics, and wide popularity make it an exceptionally attractive instructional language for new programmers. This text embraces Python's object-oriented nature, presenting a balanced and flexible approach to mastering object-oriented principles, and building a solid framework for advanced programming in Python and other languages.

Drawing on their highly successful CS1 course at Saint Louis University, the authors begin with core concepts every programmer must master, including data types, objects, control structures, I/O, user-defined classes, inheritance, and good software development practices. Next, students gain far deeper mastery, learning crucial techniques ranging from recursion to data structures. The authors conclude by introducing event-driven and network programming - two "advanced" topics that become surprisingly approachable with Python.

• Strong fundamentals coverage: Helps readers achieve immediate success, while building a strong foundation for further study
• Flexible organization: Enables instructors to reorder, emphasize, or deemphasize topics as needed
• Provides early "object awareness" and helps students master key object-oriented principles naturally and gradually
• Presents real-world case studies from domains such as animation, biology, physics, and the Internet
• Includes an exclusive, simple graphics library that helps students grasp basic concepts and explore more advanced topics such as transformations and layers
• Contains a convenient guide for transitioning from Python to Java™ or C++

About the Authors

Dr. Michael H. Goldwasser is Associate Professor and Dr. David Letscher is Assistant Professor at Saint Louis University. Dr. Goldwasser was previously on the Faculty at Loyola University Chicago where he was Undergraduate Program Director for Computer Science. He has also taught courses at Colorado College, Princeton University, and Stanford University. He holds a Ph.D. in Computer Science from Stanford University. Dr. Letscher served as Assistant Professor at Oklahoma State University, Visting Researcher at American Institute of Mathematics, Assistant Professor at University of California, San Diego, and Visiting Research Fellow at the University of Melbourne. He holds a Ph.D. in Mathematics from the University of Michigan.

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