Algorithms and data structures are much more than abstract concepts. Mastering them enables you to write code that runs faster and more efficiently, which is particularly important for today’s web and mobile apps. Take a practical approach to data structures and algorithms, with techniques and real-world scenarios that you can use in your daily production code, with examples in JavaScript, Python, and Ruby. This new and revised second edition features new chapters on recursion, dynamic programming, and using Big O in your daily work. Use Big O notation to measure and articulate the efficiency of your code, and modify your algorithm to make it faster. Find out how your choice of arrays, linked lists, and hash tables can dramatically affect the code you write. Use recursion to solve tricky problems and create algorithms that run exponentially faster than the alternatives. Dig into advanced data structures such as binary trees and graphs to help scale specialized applications such as social networks and mapping software. You’ll even encounter a single keyword that can give your code a turbo boost. Practice your new skills with exercises in every chapter, along with detailed solutions. Use these techniques today to make your code faster and more scalable
Jay Wengrow Livres


Common-Sense Guide to Data Structure and Algorithms in Python, Volume 1
Level Up Your Core Programming Skills
Focusing on the practical application of data structures and algorithms, this book teaches how to enhance Python code efficiency using Big O notation. It covers essential structures like hash tables, trees, and graphs, making complex concepts accessible through simple language and clear diagrams. Each chapter includes practice exercises to reinforce learning, emphasizing real-world scenarios relevant to web and mobile app development. Exclusively using Python for examples, it equips readers with the hands-on skills needed for everyday coding challenges.