Bhagvan Kommadi's guide to learning data structures and algorithms using Go, covering everything from basic arrays to garbage collection.
“Learn Data Structures and Algorithms with Golang” teaches the core building blocks of computer science using Go as the implementation language. Instead of the usual Java or Python examples, every data structure and algorithm is shown with actual Go code you can run and experiment with.
The book is split into three sections. Section one covers the basics, including what data structures are, how to classify them, and how to set up your Go environment. Section two gets into the core structures like lists, stacks, trees, hash tables, arrays, linked lists, dictionaries, and classic sorting and searching algorithms. Section three tackles advanced topics like graphs, sparse matrices, memory management, and garbage collection.
This is for Go developers who want to fill in their CS fundamentals, people prepping for technical interviews, or anyone who learned data structures in another language and wants to see how they work in Go. The book assumes you can already write basic code, so complete beginners should start elsewhere.
So I picked up this book called “Learn Data Structures and Algorithms with Golang” by Bhagvan Kommadi (Packt Publishing, 2019, ISBN: 978-1-78961-850-1). And I’m going to retell the whole thing here on the blog, chapter by chapter.
Chapter 1 of the book jumps right into classifying data structures and showing some structural design patterns in Go. There’s a lot packed in here, so I’m splitting it into two parts. This first part covers what data structures are, how they’re classified, and a bunch of design patterns with Go code.
In Part 1 we covered what data structures are, how they get classified, and a bunch of structural design patterns. Now we’re getting to the fun stuff: algorithms, how to measure their performance, and a few classic algorithm types.
Welcome to Chapter 2 of our walkthrough of “Learn Data Structures and Algorithms with Golang” by Bhagvan Kommadi. This is Part 1, where we cover the Go-specific building blocks you need before getting into the heavier data structure topics. Think of this as your toolkit chapter.
Welcome back. In Part 1 we covered arrays, basic slices, two-dimensional slices, and maps. That was the foundation. Now Kommadi moves into the more interesting Go patterns: variadic functions, defer and panic, and a full CRUD web application that ties it all together. He also shows more advanced slice operations along the way.