Python for software design : how to think like a computer scientist / Allen B. Downey.
Material type:
- 9780521725965
- QA 76.73.P98 .D69 2009

Item type | Current library | Home library | Collection | Call number | Copy number | Status | Date due | Barcode | |
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National University - Manila | LRC - Main General Circulation | Computer Engineering | GC QA 76.73.P98 .D69 2009 (Browse shelf(Opens below)) | c.1 | Available | NULIB000006399 |
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GC QA 76.73.F25 .N94 1996 Fortran 77 for engineers and scientist with an introduction to Fortran 90 / | GC QA 76.73.J38 .F377 2012 Java programming : concepts and applications / | GC QA 76.73.P98 .D39 2010 Python programming for the absolute beginner / | GC QA 76.73.P98 .D69 2009 Python for software design : how to think like a computer scientist / | GC QA 76.73.P98 .M36 2013 Raspberry pi for dummies / | GC QA 76.73.P224 .G677 2011 Php programming with MySQL / | GC QA 76.73.P224 .P69 2008 Php object-oriented solutions / |
Includes 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 -- Appendix 1: debugging.
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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