| Description |
1 online resource (xxi, 295 pages) : illustrations |
| Series |
Expert's voice in open source |
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Expert's voice in open source.
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| Contents |
Machine generated contents note: ch. 1 Introduction -- What's All This, Then? -- What the book is about -- What the book covers only briefly or partially -- What the book isn't about -- Why Are You Here? -- Some Prerequisites -- What's in This Book -- Summary -- If You're Curious -- Exercises -- References -- ch. 2 Basics -- Some Core Ideas in Computing -- Asymptotic Notation -- It's Greek to Me! -- Rules of the Road -- Taking the Asymptotics for a Spin -- Three Important Cases -- Empirical Evaluation of Algorithms -- Implementing Graphs and Trees -- Adjacency Lists and the Like -- Adjacency Matrices -- Implementing Trees -- Multitude of Representations -- Beware of Black Boxes -- Hidden Squares -- Trouble with Floats -- Summary -- If You're Curious -- Exercises -- References -- ch. 3 Counting 101 -- Skinny on Sums -- More Greek -- Working with Sums -- Tale of Two Tournaments -- Shaking Hands -- Hare and the Tortoise -- Subsets, Permutations, and Combinations -- Recursion and Recurrences -- Doing It by Hand -- Few Important Examples -- Guessing and Checking -- Master Theorem: A Cookie-Cutter Solution -- So What Was All That About? -- Summary -- If You're Curious -- Exercises -- References -- ch. 4 Induction and Recursion and Reduction -- Oh, That's Easy! -- One, Two, Many -- Mirror, Mirror -- Designing with Induction (and Recursion) -- Finding a Maximum Permutation -- Celebrity Problem -- Topological Sorting -- Stronger Assumptions -- Invariants and Correctness -- Relaxation and Gradual Improvement -- Reduction + Contraposition = Hardness Proof -- Problem Solving Advice -- Summary -- If You're Curious -- Exercises -- References -- ch. 5 Traversal: The Skeleton Key of Algorithmics -- Walk in the Park -- No Cycles Allowed -- How to Stop Walking in Circles -- Go Deep! -- Depth-First Timestamps and Topological Sorting (Again) -- Infinite Mazes and Shortest (Unweighted) Paths -- Strongly Connected Components -- Summary -- If You're Curious -- Exercises -- References -- ch. 6 Divide, Combine, and Conquer -- Tree-Shaped Problems: All About the Balance -- Canonical D & C Algorithm -- Searching by Halves -- Traversing Search Trees with Pruning -- Selection -- Sorting by Halves -- How Fast Can We Sort? -- Three More Examples -- Closest Pair -- Convex Hull -- Greatest Slice -- Tree Balance and Balancing -- Summary -- If You're Curious -- Exercises -- References -- ch. 7 Greed Is Good? Prove It! -- Staying Safe, Step by Step -- Knapsack Problem -- Fractional Knapsack -- Integer Knapsack -- Huffman's Algorithm -- Algorithm -- First Greedy Choice -- Going the Rest of the Way -- Optimal Merging -- Minimum Spanning Trees -- Shortest Edge -- What About the Rest? -- Kruskal's Algorithm -- Prim's Algorithm -- Greed Works. But When? -- Keeping Up with the Best -- No Worse Than Perfect -- Staying Safe -- Summary -- If You're Curious -- Exercises -- References -- ch. 8 Tangled Dependencies and Memoization -- Don't Repeat Yourself -- Shortest Paths in Directed Acyclic Graphs -- Longest Increasing Subsequence -- Sequence Comparison -- Knapsack Strikes Back -- Binary Sequence Partitioning -- Summary -- If You're Curious -- Exercises -- References -- ch. 9 From A to B with Edsger and Friends -- Propagating Knowledge -- Relaxing like Crazy -- Finding the Hidden DAG -- All Against All -- Far-Fetched Subproblems -- Meeting in the Middle -- Knowing Where You're Going -- Summary -- If You're Curious -- Exercises -- References -- ch. 10 Matchings, Cuts, and Flows -- Bipartite Matching -- Disjoint Paths -- Maximum Flow -- Minimum Cut -- Cheapest Flow and the Assignment Problem -- Some Applications -- Summary -- If You're Curious -- Exercises -- References -- ch. 11 Hard Problems and (Limited) Sloppiness -- Reduction Redux -- Not in Kansas Anymore? -- Meanwhile, Back in Kansas -- But Where Do You Start? And Where Do You Go from There? -- Menagerie of Monsters -- Return of the Knapsack -- Cliques and Colorings -- Paths and Circuits -- When the Going Gets Tough, the Smart Get Sloppy -- Desperately Seeking Solutions -- And the Moral of the Story Is -- Summary -- If You're Curious -- Exercises -- References -- Appendix A Pedal to the Metal: Accelerating Python -- Appendix B List of Problems and Algorithms -- Problems -- Algorithms and Data Structures -- Appendix C Graph Terminology -- Appendix D Hints for Exercises -- Chapter 1 -- Chapter 2 -- Chapter 3 -- Chapter 4 -- Chapter 5 -- Chapter 6 -- Chapter 7 -- Chapter 8 -- Chapter 9 -- Chapter 10 -- Chapter 11 |
| Summary |
Python Algorithms, Second Edition 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 in a highly readable manner. It 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 |
| Analysis |
computerwetenschappen |
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computer sciences |
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wiskunde |
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mathematics |
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computer software |
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Information and Communication Technology (General) |
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Informatie- en communicatietechnologie (algemeen) |
| Notes |
Includes index |
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Online resource; title from PDF title page (EBSCO, viewed November 28, 2017) |
| Subject |
Python (Computer program language)
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Computer algorithms.
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Algorithms
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algorithms.
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COMPUTERS -- Programming Languages -- Python.
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Computer algorithms
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Python (Computer program language)
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Python Programmiersprache
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Programmanalyse
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| Form |
Electronic book
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| ISBN |
9781484200551 |
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1484200551 |
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