thealgorithms/go

Analysis updated 2026-06-24

★ 18,032GoAudience · developerComplexity · 2/5Setup · easy

Mindmap

mindmap
  root((thealgorithms/go))
    What it does
      Algorithm examples
      Educational focus
      Tested code
    Topics covered
      Sorting and searching
      Graph algorithms
      Caching strategies
      Encryption ciphers
    Use cases
      Interview prep
      Learning Go
      CS study
    Tech stack
      Go language
      Unit tests
      CI pipeline

mindmap root((thealgorithms/go)) What it does Algorithm examples Educational focus Tested code Topics covered Sorting and searching Graph algorithms Caching strategies Encryption ciphers Use cases Interview prep Learning Go CS study Tech stack Go language Unit tests CI pipeline

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What do people build with it?

USE CASE 1

Study classic computer science algorithms like sorting, searching, and graph traversal with ready-to-run Go code.

USE CASE 2

Prepare for technical coding interviews by reading and running self-contained Go algorithm examples.

USE CASE 3

Learn how LRU and LFU caches work by reading annotated Go implementations with tests.

USE CASE 4

See how encryption ciphers and string matching algorithms are written in idiomatic Go.

What is it built with?

How does it compare?

	thealgorithms/go	matryer/xbar	ginuerzh/gost
Stars	18,032	18,015	17,940
Language	Go	Go	Go
Setup difficulty	easy	moderate	moderate
Complexity	2/5	2/5	3/5
Audience	developer	developer	ops devops

Figures from each repo's GitHub metadata at analysis time.

How do you get it running?

Difficulty · easy Time to first run · 5min

In plain English

This repository is a collection of algorithms and data structures implemented in the Go programming language, intended for educational purposes. It is part of the broader "TheAlgorithms" open-source project, which produces similar collections in many different programming languages. The codebase covers a wide range of topics: string matching algorithms, mathematical operations using binary arithmetic, sorting and searching, graph algorithms, caching strategies (including LRU and LFU caches, which are techniques for deciding what to keep in memory when space is limited), encryption ciphers, and many others. Each implementation is a self-contained Go package with documented functions. The repository includes automated tests and is set up with continuous integration to verify that all implementations pass their tests. It is designed for people learning algorithms, practicing for technical interviews, or studying how classic computer science concepts translate into Go code. Contributions are welcome and the project follows specific contribution guidelines.

Copy-paste prompts

Prompt 1

Using thealgorithms/go as a reference, write me a Go function that implements binary search on a sorted integer slice and explain each step.

Prompt 2

Walk me through how the LRU cache in thealgorithms/go works and show me a simple usage example I can run locally.

Prompt 3

I have a coding interview tomorrow, explain the sorting algorithms in thealgorithms/go and tell me when to use each one.

Prompt 4

Show me how the graph algorithms in thealgorithms/go find shortest paths and give me a real-world example where I would use one.

Prompt 5

Explain the encryption ciphers in thealgorithms/go in plain English and show me how to encrypt and decrypt a string using one of them.

Frequently asked questions

What is go?

A collection of algorithms and data structures implemented in Go for learning, interview prep, and studying computer science fundamentals.

What language is go written in?

Mainly Go. The stack also includes Go.

How hard is go to set up?

Setup difficulty is rated easy, with roughly 5min to a first successful run.

Who is go for?

Mainly developer.

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