Allen B. Downey, Ph.D., is an Associate Professor of Computer Science at the Olin College of Engineering in Needham, Massachusetts. He has taught at Wellesley College, Colby College, and UC Berkeley. He has a doctorate in computer science from UC Berkeley and a Master's degree from MIT. Dr Downey is the author of a previous version of this book, titled How to Think Like a Computer Scientist: Learning with Python, which he self-published in 2001.

• 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.

'I liked this book. The presentation is neat and clean, I might even say cheerful. And I learned a lot, not least of all where higher level languages are going, and the terminology used to express that … I liked the pace of presentation. I liked the constant stirring of topics: a new feature, a hint on debugging, a few words on programming style, some thoughts on programming principles, then on to the next new feature. It really is a nice mix.' Scientific Programming

Allen B. Downey, Ph.D., is an Associate Professor of Computer Science at the Olin College of Engineering in Needham, Massachusetts. He has taught at Wellesley College, Colby College, and UC Berkeley. He has a doctorate in computer science from UC Berkeley and a Master's degree from MIT. Dr Downey is the author of a previous version of this book, titled How to Think Like a Computer Scientist: Learning with Python, which he self-published in 2001.

• 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.

'I liked this book. The presentation is neat and clean, I might even say cheerful. And I learned a lot, not least of all where higher level languages are going, and the terminology used to express that … I liked the pace of presentation. I liked the constant stirring of topics: a new feature, a hint on debugging, a few words on programming style, some thoughts on programming principles, then on to the next new feature. It really is a nice mix.' Scientific Programming

Allen B. Downey, Ph.D., is an Associate Professor of Computer Science at the Olin College of Engineering in Needham, Massachusetts. He has taught at Wellesley College, Colby College, and UC Berkeley. He has a doctorate in computer science from UC Berkeley and a Master's degree from MIT. Dr Downey is the author of a previous version of this book, titled How to Think Like a Computer Scientist: Learning with Python, which he self-published in 2001.

• 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.

'I liked this book. The presentation is neat and clean, I might even say cheerful. And I learned a lot, not least of all where higher level languages are going, and the terminology used to express that … I liked the pace of presentation. I liked the constant stirring of topics: a new feature, a hint on debugging, a few words on programming style, some thoughts on programming principles, then on to the next new feature. It really is a nice mix.' Scientific Programming