Hands-On Data Structures and Algorithms with Python Second Edition

Key Features

• Understand the analysis and design of fundamental Python data structures
• Explore advanced Python concepts such as Big O notation and dynamic programming
• Learn functional and reactive implementations of traditional data structures

Book Description

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.

What you will learn

• Understand object representation, attribute binding, and data encapsulation
• Gain a solid understanding of Python data structures using algorithms
• Study algorithms using examples with pictorial representation
• Learn complex algorithms through easy explanation, implementing Python
• Build sophisticated and efficient data applications in Python
• Understand common programming algorithms used in Python data science
• Write efficient and robust code in Python 3.7