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020 _a9783031422096
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024 7 _a10.1007/978-3-031-42209-6
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050 4 _aQA76.9.D35
050 4 _aQ350-390
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100 1 _aLee, Kent D.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_996798
245 1 0 _aData Structures and Algorithms with Python
_h[electronic resource] :
_bWith an Introduction to Multiprocessing /
_cby Kent D. Lee, Steve Hubbard.
250 _a2nd ed. 2024.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2024.
300 _aXVI, 398 p. 156 illus., 144 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
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347 _atext file
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490 1 _aUndergraduate Topics in Computer Science,
_x2197-1781
505 0 _a1. Python Programming 101 -- 2. Computational Complexity -- 3. Recursion -- 4. Sequences -- 5. Sets and Maps -- 6. Trees -- 7. Graphs -- 8. Membership Structures -- 9. Heaps -- 10. Balanced Binary Search Trees -- 11. B-Trees -- 12. Heuristic Search.
520 _aThis 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 maps, and examines binary search trees, tree traversals, and select graph algorithms Offers downloadable programs and supplementary files at an associated website to help students Students of computer science will find this clear and concise textbook invaluable for undergraduate courses on data structures and algorithms, at both introductory and advanced levels. The book is also suitable as a refresher guide for computer programmers starting new jobs working with Python. Dr. Kent D. Lee is a Professor Emeritus of Computer Science at Luther College, Decorah, Iowa, USA. He is the author of the successful Springer books, Python Programming Fundamentals, and Foundations of Programming Languages. Dr. Steve Hubbard is a Professor Emeritus of Mathematics and Computer Science at Luther College.
650 0 _aData structures (Computer science).
_98188
650 0 _aInformation theory.
_914256
650 0 _aAlgorithms.
_93390
650 0 _aPython (Computer program language).
_96666
650 0 _aComputer programming.
_94169
650 1 4 _aData Structures and Information Theory.
_931923
650 2 4 _aAlgorithms.
_93390
650 2 4 _aPython.
_934340
650 2 4 _aProgramming Techniques.
_996802
700 1 _aHubbard, Steve.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_996804
710 2 _aSpringerLink (Online service)
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773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783031422089
776 0 8 _iPrinted edition:
_z9783031422102
830 0 _aUndergraduate Topics in Computer Science,
_x2197-1781
_996808
856 4 0 _uhttps://doi.org/10.1007/978-3-031-42209-6
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