#### 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

# String Matching Algorithms

There are many popular string matching algorithms. String matching algorithms have very important applications, such as searching for an element in a text document, plagiarism detection, text editing programs, and so on. In this chapter, we will study the pattern matching algorithms that find the locations of a given pattern or substring in any given text. We will discuss the brute force algorithm, along with the Rabin-Karp, Knuth-Morris-Pratt (KMP), and Boyer-Moore pattern matching algorithms. This chapter aims to discuss algorithms that are related to strings. The following topics will be covered in this chapter:

• Learning pattern matching algorithms and their implementation
• Understanding and implementing the Rabin-Karp pattern matching algorithm
• Understanding and implementing the Knuth-Morris-Pratt (KMP) algorithm
• Understanding and implementing the Boyer-Moore pattern matching algorithm