《Good Habits for Great Coding Improving Programming Skills with Examples in Python》读书笔记四

• Overview

  Page 181 - 314

  The art of formulating and solving problems using dynamic programming can be learned only through active participation by the student.
  — Stuart E. Dreyfus; The Art and Theory of Dynamic Programming

• A Lesson in Design

• Beware of OOP

• The Evolution of a Function

• Do Not Snub Inefficient Algorithms

• Problems Worth Solving

• Problem Solving

  The goal of this book is to inform you that professional programmers (and chess player and pianists) believe that certain habis have increased their productivity and reduced their frustrations.

• Dynamic Programming

  Why introducing dynamic programming in a book for still-developing programmers?

  The answer is that we build skills for deriving and coding difficult algorithms by trying to derive and code difficult algorithms. That is the only way.

  The term dynamic programming in operations research refers to the mathematical theory of multi-stage decision making – i.e., making the best decisions at different stages of a process, usually by creating an optimal policy function.

  The word “programming” in “dynamic programming” means scheduling, or planning.

  It has been said that teaching by example is not just one way of teaching – it is the only way of teaching.

• References

1. Stueben, M. Good Habits for Great Coding. (Apress, 2018). doi:10.1007/978-1-4842-3459-4.