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

The Boyer-Moore algorithm

As we have already discussed, the main objective of the string pattern matching algorithm is to find ways of skipping comparisons as much as possible by avoiding unnecessary comparisons.

The Boyer-Moore pattern matching algorithm is another such algorithm (along with the KMP algorithm) that further improves the performance of pattern matching by skipping comparisons using different methods. We have to understand the following concepts in order to understand the Boyer-Moore algorithm:

1. In this algorithm, we shift the pattern in the direction from left to right, similar to the KMP algorithm.
2. We compare the characters of the pattern and the text string from right to left, which is the opposite of what we do in the case of the KMP algorithm.
3. The algorithm skips the unnecessary comparisons by using the good suffix and bad character shift heuristics. These heuristics themselves find the possible number of comparisons that can be skipped...