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Titlebook: Data Structures and Algorithms with Python; With an Introduction Kent D. Lee,Steve Hubbard Textbook 2024Latest edition The Editor(s) (if ap

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书目名称Data Structures and Algorithms with Python
副标题With an Introduction
编辑Kent D. Lee,Steve Hubbard
视频video
概述Includes broad coverage of both introductory and advanced data structures topics, supported by examples.Makes learning fun, using the development of graphical user interface programs to illustrate con
丛书名称Undergraduate Topics in Computer Science
图书封面Titlebook: Data Structures and Algorithms with Python; With an Introduction Kent D. Lee,Steve Hubbard Textbook 2024Latest edition The Editor(s) (if ap
描述.This textbook explains the concepts and techniques required to write programs that can handle large amounts of data efficiently. Project-oriented and classroom-tested, the book presents a number of important algorithms—supported by motivating examples—that bring meaning to the problems faced by computer programmers. The idea of computational complexity is introduced, demonstrating what can and cannot be computed efficiently at scale, helping programmers make informed judgements about the algorithms they use. The easy-to-read text assumes some basic experience in computer programming and familiarity in an object-oriented language, but not necessarily with Python..Topics and features:.Includes introductory and advanced data structures and algorithms topics, with suggested chapter sequences for those respective courses.Provides learning goals, review questions, and programming exercises in each chapter, as well as numerous examples.Presents a primer on Python for those coming from a different language background.Adds a new chapter on multiprocessing with Python using the DragonHPC multinode implementation of multiprocessing (includes a tutorial).Reviews the use of hashing in sets and
出版日期Textbook 2024Latest edition
关键词Algorithms; Computational Complexity; Data Structures; Programming; Python; Algorithm Analysis and Proble
版次2
doihttps://doi.org/10.1007/978-3-031-42209-6
isbn_softcover978-3-031-42208-9
isbn_ebook978-3-031-42209-6Series ISSN 1863-7310 Series E-ISSN 2197-1781
issn_series 1863-7310
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
The information of publication is updating

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Recursion,his is one time when it is appropriate. You need to read this chapter if you have not written recursive functions before. Most computer science students start by learning to program in a style called . programming. This simply means that you are likely used to thinking about creating variables, stor
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Graphs,atical representation of problems like these. In the last chapter we saw that trees serve a variety of purposes in Computer Science. Trees are graphs. However, graphs are more general than trees. Abstracting away the details of a problem and studying it in its simplest form often leads to new insigh
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Heaps,) memory allocation. Another meaning, and the topic of this chapter, is a data structure that is conceptually a complete binary tree. Heaps are used in implementing priority queues, the heapsort algorithm, and some graph algorithms. Heaps are somewhat like binary search trees in that they maintain a
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Parallel Applications,doubled. In doubling the number of transistors, the sizes of memory doubled as well. And in conjunction with this doubling of capacity, the performance of processors roughly doubled every two years as well.
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Graphs,t. As a result, many algorithms have come out of the research in graph theory. Graph theory was first studied by mathematicians. Many of the algorithms in graph theory are named for the mathematician that developed or discovered them. Dijkstra and Kruskal are two such mathematicians and this chapter covers algorithms developed by them.
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1863-7310 pment of graphical user interface programs to illustrate con.This textbook explains the concepts and techniques required to write programs that can handle large amounts of data efficiently. Project-oriented and classroom-tested, the book presents a number of important algorithms—supported by motivat
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