Go: Learning Journey Through Algorithms

I've been working with Node.js and its ecosystem. Now I'm diving deep into Go and I'm getting huge enjoyment from its approach — on one hand, simplicity and no syntactic sugar (you can get diabetes from all the sugar in JS, it's too sweet🙃), on the other hand, incredible capabilities and a greater sense of being "close to hardware."

I decided to document my learning notes in an open repo dsa-golang — specifically, implementations of classic algorithms in Go. This isn't production code, but educational examples with comments and Big O complexity analysis.

Sure, there are hundreds of similar repos... so what's the value in opening another one? 👇

• Classic solutions to classic CS problems, without over-engineering or language-specific optimizations, for clear understanding of the algorithm.

• Meaningful semantic naming

• Aiming for simple and idiomatic Go code

• Breakdowns and diagrams right in the comments

What's included:

algorithms/
├── search/
│   ├── Binary
│   ├── Linear
│   ├── Jump
│   ├── BFS Filesystem · BFS Graph Queue
│   └── DFS Filesystem · DFS Graph Recursive · DFS Graph Stack
├── selection/
│   └── Quickselect
└── sort/
    ├── Bubble
    ├── Selection
    ├── Insertion
    ├── Merge
    ├── Quick
    ├── Quick In-Place
    └── Heap

datastructures/
└── graph/
    └── Adjacency List

leetcode/
├── Two Sum #1
├── Merge Sorted Array #88
└── Valid Palindrome #125

interview_exercises/
├── Reverse
├── Duplicates
├── Whitespaces
└── Longest

informatica/
├── Factorial
├── Fibonacci
├── Prime
└── Table

I'm planning to expand it by adding data structures and more LeetCode problems.
If you're also learning Go or algorithms — I'd be happy if this helps you and to hear your feedback!

Repository: github.com/AshBuk/dsa-golang