Python for software design : how to think like a computer scientist / Allen B. Downey.
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TextPublication details: Cambridge ; New York : Cambridge University Press, 2009.Description: xvi, 251 p. : ill. ; 27 cmISBN: - 9780521898119 (hardback)
- 0521898110 (hardback)
- 9780521725965 (pbk.)
- 0521725968 (pbk.)
- 005.133 22
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Main library General Stacks | 005.133 / DO.P 2009 (Browse shelf(Opens below)) | 1 | Available | 006319 |
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| 005.133 / DE.V 2008 Visual C++ 2008 : | 005.133 / DE.V 2008 Visual C# 2008 : | 005.133 / DO.P 2004 Programming in C++ : | 005.133 / DO.P 2009 Python for software design : | 005.133 / FA.O 2009 Object-oriented programming using C++ / | 005.133 / GO. S 1996 Schaum's outline of theory and problems of programming with C / | 005.133 / GO. S 1996 Schaum's outline of theory and problems of programming with C / |
Includes bibliographical references and index.
1. Preface -- 2. The way of the program -- 3. Variables, expressions and statements -- 4. Functions -- 5. Case study: interface design -- 6. Conditionals and recursion -- 7. Fruitful functions -- 8. Iteration -- 9. Strings -- 10. Case study: word play -- 11. Lists -- 12. Dictionaries -- 13. Tuples -- 14. Case study: data structure selection -- 15. Files -- 16. Classes and objects -- 17. Classes and functions -- 18. Classes and methods -- 19. Inheritance -- 20. Case study: Tkinter.
A no-nonsense introduction to software design using the Python programming language. Written for people with no programming experience, this book starts with the most basic concepts and gradually adds new material. Some of the ideas students find most challenging, like recursion and object-oriented programming, are divided into a sequence of smaller steps and introduced over the course of several chapters. The focus is on the programming process, with special emphasis on debugging. The book includes a wide range of exercises, from short examples to substantial projects, so that students have ample opportunity to practise each new concept. Exercise solutions and code examples are available from thinkpython.com, along with Swampy, a suite of Python programs that is used in some of the exercises.
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