Book Image

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

By : Dr. Basant Agarwal, Benjamin Baka
Book Image

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

By: Dr. Basant Agarwal, Benjamin Baka

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)

Binary search

A binary search is a search strategy used to find elements within a sorted array or list; thus, the binary search algorithm finds a given item from the given sorted list of items. It is a very fast and efficient algorithm to search an element, and the only drawback is that we need a sorted list. The worst-case running time complexity of a binary search algorithm is O(log n) whereas the linear search has O(n).

A binary search algorithm works as follows. It starts searching the item by dividing the given list by half. If the search item is smaller than the middle value then it will look for the searched item only in the first half of the list, and if the search item is greater than the middle value it will only look at the second half of the list. We repeat the same process every time until we find the search item or we have checked the whole list.

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