Hands-On Data Structures and Algorithms with Python: Store, manipulate, and access data effectively and boost the performance of your applications, 3rd Edition

Hands-On Data Structures and Algorithms with Python: Store, manipulate, and access data effectively and boost the performance of your applications, 3rd Edition

English | 2022 | ISBN: 978-1801073448 | 496 Pages | PDF, EPUB | 29 MB

Understand how implementing different data structures and algorithms intelligently can make your Python code and applications more maintainable and efficient

Key Features

  • Explore functional and reactive implementations of traditional and advanced data structures
  • Apply a diverse range of algorithms in your Python code
  • Implement the skills you have learned to maximize the performance of your applications

Choosing the right data structure is pivotal to optimizing the performance and scalability of applications. This new edition of Hands-On Data Structures and Algorithms with Python will expand your understanding of key structures, including stacks, queues, and lists, and also show you how to apply priority queues and heaps in applications. You’ll learn how to analyze and compare Python algorithms, and understand which algorithms should be used for a problem based on running time and computational complexity. You will also become confident organizing your code in a manageable, consistent, and scalable way, which will boost your productivity as a Python developer.

By the end of this Python book, you’ll be able to manipulate the most important data structures and algorithms to more efficiently store, organize, and access data in your applications.

What you will learn

  • Understand common data structures and algorithms using examples, diagrams, and exercises
  • Explore how more complex structures, such as priority queues and heaps, can benefit your code
  • Implement searching, sorting, and selection algorithms on number and string sequences
  • Become confident with key string-matching algorithms
  • Understand algorithmic paradigms and apply dynamic programming techniques
  • Use asymptotic notation to analyze algorithm performance with regard to time and space complexities
  • Write powerful, robust code using the latest features of Python
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