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Good Habits for Great Coding : improving programming skills with examples in python / by Michael Stueben.

By: Material type: TextTextPublisher: Berkeley, CA : Apress : Imprint: Apress, 2018Edition: 1st ed. 2018Description: xxix,314p. ; PB 23.5 cmContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9781484234594
Subject(s): Additional physical formats: Print version:: Good habits for great coding : improving programming skills with examples in Python; Printed edition:: No title; Printed edition:: No title; Printed edition:: No titleDDC classification:
  • 005.1372 1 STUM
Contents:
Part 1: Not Learned in School -- 1. A Coding Fantasy -- 2. Coding Tricks -- 3. Style -- 4. More Coding Tricks -- Part 2: Coding Advice -- 5. Function Design -- 6. Self-Documenting Code -- 7. Step-Wise Refinement -- 8. Comments -- 9. Stop Coding -- 10. Testing -- 11. Defensive Programming -- 12. Refactoring -- 13. Write The Tests First (Sometimes) -- 14. Expert Advice -- Part 3: Perspective -- 15. A Lesson In Design -- 16. Beware Of OOP -- 17. The Evolution Of A Function -- 18. Do Not Snub Inefficient Algorithms -- Part 4: Walk the Walk -- 19.Problems Worth Solving -- 20. Problem Solving -- 21. Dynamic Programming.
Summary: Improve your coding skills and learn how to write readable code. Rather than teach basic programming, this book presumes that readers understand the fundamentals, and offers time-honed best practices for style, design, documenting, testing, refactoring, and more. Taking an informal, conversational tone, author Michael Stueben offers programming stories, anecdotes, observations, advice, tricks, examples, and challenges based on his 38 years experience writing code and teaching programming classes. Trying to teach style to beginners is notoriously difficult and can easily appear pedantic. Instead, this book offers solutions and many examples to back up his ideas. Good Habits for Great Coding distills Stueben's three decades of analyzing his own mistakes, analyzing student mistakes, searching for problems that teach lessons, and searching for simple examples to illustrate complex ideas. Having found that most learn by trying out challenging problems, and reflecting on them, each chapter includes quizzes and problems in each chapter. The final chapter introduces dynamic programming to reduce complex problems to subcases, and illustrates many concepts discussed in the book. Code samples are provided in Python and designed to be understandable by readers familiar with any modern programming language. At the end of this book, you will have acquired a lifetime of good coding advice; the lessons the author wishes he had learned when he was a novice.
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Part 1: Not Learned in School -- 1. A Coding Fantasy -- 2. Coding Tricks -- 3. Style -- 4. More Coding Tricks -- Part 2: Coding Advice -- 5. Function Design -- 6. Self-Documenting Code -- 7. Step-Wise Refinement -- 8. Comments -- 9. Stop Coding -- 10. Testing -- 11. Defensive Programming -- 12. Refactoring -- 13. Write The Tests First (Sometimes) -- 14. Expert Advice -- Part 3: Perspective -- 15. A Lesson In Design -- 16. Beware Of OOP -- 17. The Evolution Of A Function -- 18. Do Not Snub Inefficient Algorithms -- Part 4: Walk the Walk -- 19.Problems Worth Solving -- 20. Problem Solving -- 21. Dynamic Programming.

Improve your coding skills and learn how to write readable code. Rather than teach basic programming, this book presumes that readers understand the fundamentals, and offers time-honed best practices for style, design, documenting, testing, refactoring, and more. Taking an informal, conversational tone, author Michael Stueben offers programming stories, anecdotes, observations, advice, tricks, examples, and challenges based on his 38 years experience writing code and teaching programming classes. Trying to teach style to beginners is notoriously difficult and can easily appear pedantic. Instead, this book offers solutions and many examples to back up his ideas. Good Habits for Great Coding distills Stueben's three decades of analyzing his own mistakes, analyzing student mistakes, searching for problems that teach lessons, and searching for simple examples to illustrate complex ideas. Having found that most learn by trying out challenging problems, and reflecting on them, each chapter includes quizzes and problems in each chapter. The final chapter introduces dynamic programming to reduce complex problems to subcases, and illustrates many concepts discussed in the book. Code samples are provided in Python and designed to be understandable by readers familiar with any modern programming language. At the end of this book, you will have acquired a lifetime of good coding advice; the lessons the author wishes he had learned when he was a novice.

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