#### 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
Other Books You May Enjoy
Index

# Jump search

The jump search algorithm is an improvement over linear search for searching for a given element from an ordered (or sorted) list of elements. This uses the divide-and-conquer strategy in order to search for the required element. In linear search, we compare the search value with each element of the list, whereas in jump search, we compare the search value at different intervals in the list, which reduces the number of comparisons.

In this algorithm, firstly, we divide the sorted list of data into subsets of data elements called blocks. Within each block, the highest value will lie within the last element, as the array is sorted. Next, in this algorithm, we start comparing the search value with the last element of each block. There can be three conditions:

1. If the search value is less than the last element of the block, we compare it with the next block.
2. If the search value is greater than the last element of the block, it means the desired search value...