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A user-friendly, object-oriented language, Python is quickly becoming the favorite introductory programming language among students and instructors. Many find Python to be a more lucid language than Java but with much of the functionality and therefore the ideal first language for those entering the world of Computer Science. Python Programming in Context is a clear, accessible introduction to the fundamental programming and problem solving concepts necessary for students at this level. The authors carefully build upon the many important computer science concepts and problem solving techniques throughout the text and offer relevant, real-world examples and exercises to reinforce key material. Programming skills throughout the text are linked to applied areas such as Image Processing, Cryptography, Astronomy, Music, the Internet, and Bioinformatics, giving students a well rounded look of its capabilities.
A user-friendly, object-oriented language, Python is quickly becoming the favorite introductory programming language among students and instructors. Many find Python to be a more lucid language than Java but with much of the functionality and therefore the ideal first language for those entering the world of Computer Science. Python Programming in Context is a clear, accessible introduction to the fundamental programming and problem solving concepts necessary for students at this level. The authors carefully build upon the many important computer science concepts and problem solving techniques throughout the text and offer relevant, real-world examples and exercises to reinforce key material. Programming skills throughout the text are linked to applied areas such as Image Processing, Cryptography, Astronomy, Music, the Internet, and Bioinformatics, giving students a well rounded look of its capabilities.
A user-friendly, object-oriented language, Python is quickly becoming the favorite introductory programming language among students and instructors. Many find Python to be a more lucid language than Java but with much of the functionality and therefore the ideal first language for those entering the world of Computer Science. Python Programming in Context is a clear, accessible introduction to the fundamental programming and problem solving concepts necessary for students at this level. The authors carefully build upon the many important computer science concepts and problem solving techniques throughout the text and offer relevant, real-world examples and exercises to reinforce key material. Programming skills throughout the text are linked to applied areas such as Image Processing, Cryptography, Astronomy, Music, the Internet, and Bioinformatics, giving students a well rounded look of its capabilities.
This book is suitable for use in a university-level first course in computing (CS1), as well as the increasingly popular course known as CS0. It is difficult for many students to master basic concepts in computer science and programming. A large portion of the confusion can be blamed on the complexity of the tools and materials that are traditionally used to teach CS1 and CS2. This textbook was written with a single overarching goal: to present the core concepts of computer science as simply as possible without being simplistic.
The new edition of an introductory text that teaches students the art of computational problem solving, covering topics ranging from simple algorithms to information visualization.
Practical Python 3 for experienced developers: use the right idioms, techniques, and features to write great code * *Written from a completely 'Python 3' point of view: teaches best practices for making the most of today's newest version of Python. *Designed to help developers get productive fast... then learn how to write any program, use any library, create any library module. *Includes expert guidance on migrating Python 2 code to Python 3. Around the world, programmers appreciate Python for its simplicity, power, expressiveness, and the sheer pleasure of writing Python code. Python 3.1 is the newest and best version of the language yet: more convenient, more consistent, and easier to use. Mark Summerfield demonstrates how to write code that takes full advantage of the latest Python 3 features and idioms. Programming in Python 3, 2/e, brings together all the knowledge needed to write programs, use any library, and even create new library modules. The book teaches every aspect of the Python 3 language. It covers all the built-in functionality, as well as key components of Python's standard library. Structured so readers can write Python programs from chapter 1, each subsequent chapter provides further depth and broader coverage. Two new chapters have been added to this edition increasing the coverage to include parsing, debugging, testing, and profiling. Readers will master Python procedural and object-oriented techniques; creation of custom modules and packages; writing and reading files; multithreading; networking; database programming; GUIs; regular expressions; application debugging, testing, and profiling; and more. Detailed appendices include coverage of migrating applications from Python 2 to Python 3, plus a complete language reference. All sample code has been tested with the final version of Python 3 on Windows, Linux, and Mac OS X.
Discovering Computer Science: Interdisciplinary Problems, Principles, and Python Programming introduces computational problem solving as a vehicle of discovery in a wide variety of disciplines. With a principles-oriented introduction to computational thinking, the text provides a broader and deeper introduction to computer science than typical introductory programming books. Organized around interdisciplinary problem domains, rather than programming language features, each chapter guides students through increasingly sophisticated algorithmic and programming techniques. The author uses a spiral approach to introduce Python language features in increasingly complex contexts as the book progresses. The text places programming in the context of fundamental computer science principles, such as abstraction, efficiency, and algorithmic techniques, and offers overviews of fundamental topics that are traditionally put off until later courses. The book includes thirty well-developed independent projects that encourage students to explore questions across disciplinary boundaries. Each is motivated by a problem that students can investigate by developing algorithms and implementing them as Python programs. The book's accompanying website — http://discoverCS.denison.edu — includes sample code and data files, pointers for further exploration, errata, and links to Python language references. Containing over 600 homework exercises and over 300 integrated reflection questions, this textbook is appropriate for a first computer science course for computer science majors, an introductory scientific computing course or, at a slower pace, any introductory computer science course.

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