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
##言簡意賅,重點是圖論算法,頗有難度,很有啓發。
評分##高大上呀。作者對recursion和induction的關係的描述使人容易理解。
評分 評分 評分##比如第二章習題2-11,證明對於任意無嚮圖,都可以通過調整邊綫方嚮,從中産生有嚮無環圖(DAG),原文答案是這樣的:"Number the nodes (arbitrarily). Orient all edges from lower to higher numbers." ,然後書上翻譯成:“(任何一種)節點編號都可以按照其所有邊的編號從...
評分 評分##比如第二章習題2-11,證明對於任意無嚮圖,都可以通過調整邊綫方嚮,從中産生有嚮無環圖(DAG),原文答案是這樣的:"Number the nodes (arbitrarily). Orient all edges from lower to higher numbers." ,然後書上翻譯成:“(任何一種)節點編號都可以按照其所有邊的編號從...
評分##Python實現的算法書。。好像很有趣的趕腳。。
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