Implementing various data structures and algorithms in Python enhances the maintainability and efficiency of your code and applications. This book provides insights into selecting the right structures and algorithms to optimize performance, ensuring that your programming practices lead to cleaner and more effective solutions. Through practical examples, it guides readers in mastering these concepts for improved coding outcomes.
Learn to implement complex data structures and algorithms using Python. This resource covers the analysis and design of fundamental Python data structures and delves into advanced concepts such as Big O notation and dynamic programming. Data structures are essential for efficiently storing and organizing data, providing complete solutions, and serving as reusable code.
You will explore linked lists, double linked lists, and circular linked lists, as well as create complex structures like graphs, stacks, and queues. The book guides you through binary searches and binary search trees, alongside techniques for preprocessing, modeling, and transforming data. The concluding chapters focus on organizing code in a manageable and extendable manner, while detailing sorting algorithms such as bubble sort, selection sort, insertion sort, and merge sort.
By the end, you will have developed the skills to build components that are easy to understand, debug, and utilize across various applications. Gain insights into Python implementations of key algorithms, understand object representation, attribute binding, and data encapsulation, and study algorithms through illustrative examples. This book is designed for developers eager to learn data structures and algorithms in Python, with a foundational knowledge of Python programming expected.
