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.
Preface
Free Chapter
Python Data Types and Structures
Introduction to Algorithm Design
Algorithm Design Techniques and Strategies
Stacks and Queues
Trees
Heaps and Priority Queues
Hash Tables
Graphs and Algorithms
Searching
Sorting
Selection Algorithms
String Matching Algorithms
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Index

Timsort algorithm

Timsort is used as the default standard sorting algorithm in all Python versions >=2.3. The Timsort algorithm is an optimal algorithm for real-world long lists that is based on a combination of the merge sort and insertion sort algorithms. The Timsort algorithm utilizes the best of both algorithms; insertion sort works best when the array is sorted partially and its size is small, and the merge method of the merge sort algorithm works fast when we have to combine small, sorted lists.

The main concept of the Timsort algorithm is that it uses the insertion sort algorithm to sort small blocks (also known as chunks) of data elements, and then it uses the merge sort algorithm to merge all the sorted chunks. The main characteristic of the Timsort algorithm is that it takes advantage of already-sorted data elements known as “natural runs,” which occur very frequently in real-world data.

The Timsort algorithm works as follows:

1. Firstly...