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Hands-On Data Structures and Algorithms with Python

Hands-On Data Structures and Algorithms with Python

By : Dr. Basant Agarwal, Benjamin Baka
3 (13)
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Hands-On Data Structures and Algorithms with Python

Hands-On Data Structures and Algorithms with Python

3 (13)
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)
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Modules for data structures and algorithms

In addition to the built-in types, there are several Python modules that we can use to extend the built-in types and functions. In many cases, these Python modules may offer efficiency and programming advantages that allow us to simplify our code.

So far, we have looked at the built-in datatypes of strings, lists, sets, and dictionaries as well as the decimal and fraction modules. They are often described by the term Abstract Data Types (ADTs). ADTs can be considered mathematical specifications for the set of operations that can be performed on data. They are defined by their behavior rather than their implementation. In addition to the ADTs that we have looked at, there are several Python libraries that provide extensions to the built-in datatypes. These will be discussed in the following section.

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