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020			_a9798888650356
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040			_cNULRC
100			_aWengrow, Jay _eauthor
245			_aA Common-Sense guide to data structures and algorithms in python, volume 1 / _cJay Wengrow
260			_aDallas, Texas : _bPragmatic Bookshelf, _c2023.
300			_a482 pages.
365			_bUSD50.00
490			_vVolume 1.
504			_aIncludes index.
505			_aPreface -- Acknowledgments -- 1. Why Data Structures Matter -- 2. Why Algorithms Matter -- 3. O Yes! Big O Notation -- 4. Speeding Up Your Code with Big O -- 5. Optimizing Code With and Without Big O -- 6. Optimizing for Optimistic Scenarios -- 7. Big O in Everyday Code -- 8. Blazing Fast Lookup with Hash Tables -- 9. Crafting Elegant Code with Stacks and Queues -- 10. Recursively Recurse with Recursion -- 11. Learning to Write in Recursive -- 12. Dynamic Programming -- 13. Recursive Algorithms for Speed -- 14. Node-Based Data Structures -- 15. Speeding Up All the Things with Binary Search Trees -- 16. Keeping Your Priorities Straight with Heaps -- 17. It Doesn't Hurt to Trie -- 18. Connecting Everything with Graphs -- 19. Dealing with Space Constraints -- 20. Techniques for Code Optimization -- A1. Exercise Solutions -- Index.
520			_aIf you thought data structures and algorithms were all just theory, you're missing out on what they can do for your Python code. Learn to use Big O notation to make your code run faster by orders of magnitude. Choose from data structures such as hash tables, trees, and graphs to increase your code's efficiency exponentially. With simple language and clear diagrams, this book makes this complex topic accessible, no matter your background. Every chapter features practice exercises to give you the hands-on information you need to master data structures and algorithms for your day-to-day work. Algorithms and data structures are much more than abstract concepts. Mastering them enables you to write code that runs faster and more efficiently, which is particularly important for today's web and mobile apps. Take a practical approach to data structures and algorithms, with techniques and real-world scenarios that you can use in your daily production code. The Python edition uses Python exclusively for all code examples, exercise, and solutions. Use Big O notation to measure and articulate the efficiency of your code, and modify your algorithm to make it faster. Find out how your choice of arrays, linked lists, and hash tables can dramatically affect the code you write. Use recursion to solve tricky problems and create algorithms that run exponentially faster than the alternatives.
650			_aCOMPUTER ALGORITHMS
650			_aDATA STRUCTURES (COMPUTER SCIENCE)
856			_uhttps://research.ebsco.com/c/nahjoz/search/details/7ktquxtvaf?db=nlebk&db=nlabk
942			_2lcc _cEL _n0
999			_c1960 _d1960