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Hands-On Data Structures and Algorithms with Python

Hands-On Data Structures and Algorithms with Python - Second Edition

By : Dr. Basant Agarwal, Benjamin Baka, David Julian
3 (13)
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Hands-On Data Structures and Algorithms with Python

Hands-On Data Structures and Algorithms with Python

3 (13)
By: Dr. Basant Agarwal, Benjamin Baka, David Julian

Overview of this book

Data structures allow you to store and organize data efficiently. They are critical to any problem, provide a complete solution, and act like reusable code. Hands-On Data Structures and Algorithms with Python teaches you the essential Python data structures and the most common algorithms for building easy and maintainable applications. This book helps you to understand the power of linked lists, double linked lists, and circular linked lists. You will learn to create complex data structures, such as graphs, stacks, and queues. As you make your way through the chapters, you will explore the application of binary searches and binary search trees, along with learning common techniques and structures used in tasks such as preprocessing, modeling, and transforming data. In the concluding chapters, you will get to grips with organizing your code in a manageable, consistent, and extendable way. You will also study how to bubble sort, selection sort, insertion sort, and merge sort algorithms in detail. By the end of the book, you will have learned how to build components that are easy to understand, debug, and use in different applications. You will get insights into Python implementation of all the important and relevant algorithms.
Table of Contents (16 chapters)
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Heap sort algorithms

In Chapter 8, Graphs and Other Algorithms, we implemented a binary heap data structure. Our implementation always made sure that, after an element had been removed or added to a heap, the heap order property was maintained, by using the sink() and arrange() helper methods.

The heap data structure can be used to implement a sorting algorithm called the heap sort. As a recap, let's create a simple heap with the following items:

    h = Heap() 
unsorted_list = [4, 8, 7, 2, 9, 10, 5, 1, 3, 6]
for i in unsorted_list:
h.insert(i)
print("Unsorted list: {}".format(unsorted_list))

The heap, h, is created and the elements in the unsorted_list are inserted. After each method call to insert, the heap order property is restored by the subsequent call to the float method. After the loop is terminated, element 4 will be at the top of...

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