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Hands-On Data Structures and Algorithms with Python – Third Edition

Hands-On Data Structures and Algorithms with Python – Third Edition - Third Edition

By : Dr. Basant Agarwal
4.8 (26)
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Hands-On Data Structures and Algorithms with Python – Third Edition

Hands-On Data Structures and Algorithms with Python – Third Edition

4.8 (26)
By: Dr. Basant Agarwal

Overview of this book

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.
Table of Contents (17 chapters)
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14
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Index

Priority queues

A priority queue is a data structure that is similar to a queue in which data is retrieved based on the First In, First Out (FIFO) policy, but in the priority queue, priority is attached with the data. In the priority queue, the data is retrieved based on the priority associated with the data elements, the data elements with the highest priority are retrieved before the lower priority data elements, and if two data elements have the same priority, they are retrieved according to the FIFO policy.

We can assign the priority of the data depending upon the application. It is used in many applications, such as CPU scheduling, and many algorithms also rely on priority queues, such as Dijkstra’s shortest-path, A* search, and Huffman codes for data compression.

So, in the priority queue, the item with the highest priority is served first. The priority queue stores the data according to the priority associated with the data, so insertion of an element will be...

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Hands-On Data Structures and Algorithms with Python – Third Edition
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