Python Algorithms explains the Python approach to algorithm analysis and design. Written by Magnus Lie Hetland, author of Beginning Python, this book is sharply focused on classical algorithms, but it also gives a solid understanding of fundamental algorithmic problem-solving techniques. * The book deals with some of the most important and challenging areas of programming and computer science, but in a highly pedagogic and readable manner. * The book covers both algorithmic theory and programming practice, demonstrating how theory is reflected in real Python programs. * Well-known algorithms and data structures that are built into the Python language are explained, and the user is shown how to implement and evaluate others himself. What you'll learn * Transform new problems to well-known algorithmic problems with efficient solutions, or show that the problems belong to classes of problems thought not to be efficiently solvable. * Analyze algorithms and Python programs both using mathematical tools and basic experiments and benchmarks. * Prove correctness, optimality, or bounds on approximation error for Python programs and their underlying algorithms. * Understand several classical algorithms and data structures in depth, and be able to implement these efficiently in Python. * Design and implement new algorithms for new problems, using time-tested design principles and techniques. * Speed up implementations, using a plethora of tools for high-performance computing in Python. Who this book is for The book is intended for Python programmers who need to learn about algorithmic problem-solving, or who need a refresher. Students of computer science, or similar programming-related topics, such as bioinformatics, may also find the book to be quite useful. Table of Contents * Introduction * The Basics * Counting 101 * Induction and Recursion ...and Reduction * Traversal: The Skeleton Key of Algorithmics * Divide, Combine, and Conquer * Greed Is Good? Prove It! * Tangled Dependencies and Memoization * From A to B with Edsger and Friends * Matchings, Cuts, and Flows * Hard Problems and (Limited) Sloppiness
##简单来说就是教你怎么用Python实现算法导论和数据结构课的算法部分,不得不说Python是神器!
评分##中文版翻译成了《python算法教程》,连封面也换了,不过用python的朋友值得花时间好好看看的
评分##试图强行阅读一本自己能力范围之外的书,终以失败结束。
评分 评分##试图强行阅读一本自己能力范围之外的书,终以失败结束。
评分##言简意赅,重点是图论算法,颇有难度,很有启发。
评分 评分 评分##高大上呀。作者对recursion和induction的关系的描述使人容易理解。
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