精通Python算法:基础算法指南

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"Python算法:精通Python语言中的基础算法" 本书《Python Algorithms: Mastering Basic Algorithms in the Python Language》由Magnus Lie Hetland撰写,旨在帮助读者掌握如何在Python编程环境中实现经典的算法,并学习设计新的问题解决算法。这本书是Python开发者深入理解和应用算法的重要资源。 在Python编程中,算法是解决问题的关键工具,它涉及到计算机科学的核心概念,如排序、搜索、图论和动态规划。通过阅读此书,读者将能够: 1. 学习基础算法:包括排序算法(如冒泡排序、选择排序、插入排序、快速排序、归并排序)和搜索算法(如线性搜索、二分查找)等,这些都是解决日常编程问题的基础。 2. 理解数据结构:了解如何在Python中实现和使用各种数据结构,如链表、栈、队列、堆和树等,这些数据结构是高效算法设计的基础。 3. 探索高级主题:深入到更复杂的算法,如图的遍历(深度优先搜索和广度优先搜索)、最短路径算法(Dijkstra算法或Floyd-Warshall算法)以及字符串匹配算法(如KMP算法)。 4. 设计和分析算法:学习如何分析算法的时间复杂度和空间复杂度,以评估其效率,并能根据具体问题选择合适的算法。 5. 实践编程技巧:通过实际的Python代码示例来理解算法,提升编程技能,书中提供的代码可以帮助读者在实践中巩固所学知识。 6. 深入理解面向对象编程:结合Python的面向对象特性,学习如何构建可维护和可扩展的算法实现。 7. 学习动态规划:这是一种用于解决复杂问题的强大技术,通过将大问题分解为小问题来求解,书中会介绍如何在Python中应用动态规划。 8. 掌握递归:递归是许多算法的核心,理解其工作原理和如何避免常见的陷阱是编程者必备的技能。 通过《Python Algorithms》这本书,读者不仅能学习到Python编程语言的基本算法,还能了解到如何将这些算法应用于实际项目,提升自己的编程能力和问题解决能力。无论你是初学者还是经验丰富的开发者,这本书都将是你提升算法知识的宝贵资源。
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副标题: Mastering Basic Algorithms in the Python Language 作者: Magnus Lie Hetland 出版社: Apress 出版年: 2010-11-24 页数: 336 定价: USD 49.99 装帧: Paperback ISBN: 9781430232377 内容简介 · · · · · ·   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