go-interview-practice
Interactive Go Interview Platform - 30+ coding challenges with instant feedback, AI interview simulation, competitive leaderboards, and automated testing. From beginner to advanced levels with real-world scenarios.
Stars: 1262
The Go Interview Practice repository is a comprehensive platform designed to help users practice and master Go programming through interactive coding challenges. It offers an interactive web interface with a code editor, testing experience, and competitive leaderboard. Users can practice with challenges categorized by difficulty levels, contribute solutions, and track their progress. The repository also features AI-powered interview simulation, real-time code review, dynamic interview questions, and progressive hints. Users can showcase their achievements with auto-updating profile badges and contribute to the project by submitting solutions or adding new challenges.
README:
Welcome to the Go Interview Practice repository! Master Go programming and ace your technical interviews with our interactive coding challenges.
Our interactive platform is now live at gointerview.dev π Explore challenges, track your progress, and elevate your Go skills with AI-powered mentorship.
Our comprehensive web interface provides everything you need to practice and master Go programming:
A brief introduction to the project
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Interactive Code Editor Write, edit, and test your Go solutions with syntax highlighting and real-time feedback |
Instant Results & Analytics Get immediate test results, performance metrics, and detailed execution analysis |
Beautiful leaderboard showcasing top developers with challenge completion indicators, rankings, and achievements
Our most accomplished Go developers, ranked by number of challenges completed:
Note: The data below is automatically updated by GitHub Actions when challenge scoreboards change.
| π | Developer | Solved | Rate | Achievement | Progress |
|---|---|---|---|---|---|
| π₯ |
PolinaSvet |
30/30 | 100.0% | Master | β
β
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β β β β β β β β β β β β β β β |
| π₯ |
odelbos |
30/30 | 100.0% | Master | β
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β
β
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β
β
β
β
β
β
β
β
β
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β β β β β β β β β β β β β β β |
| π₯ |
mick4711 |
23/30 | 76.7% | Master | β
β
β
β
β
β
β
β
β
β
β¬β¬β
β
β¬ β β β β β β β β β¬β¬β β β¬β¬β |
| 4 |
Gandook |
22/30 | 73.3% | Master | β
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β
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β¬β¬ β¬β β β β¬β β β β β β β β¬β¬β |
| 5 |
y1hao |
21/30 | 70.0% | Master | β
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β
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β¬ β β β β β β β β β¬β¬β¬β β¬β¬β |
| 6 |
JackDalberg |
20/30 | 66.7% | Master | β
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β
β
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β¬ β¬β β β β β β β β¬β¬β¬β β¬β¬β |
| 7 |
Cpoing |
17/30 | 56.7% | Expert | β
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β¬β β β¬β¬β β¬β¬β¬β¬β¬β¬β¬β¬β¬ |
| 8 |
ashwinipatankar β€οΈ |
17/30 | 56.7% | Expert | β
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| 9 |
t4e1 |
15/30 | 50.0% | Expert | β
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β¬β¬β
β¬β¬ β¬β β β β¬β β β¬β¬β¬β¬β β¬β¬β¬ |
| 10 |
KhaledMosaad |
14/30 | 46.7% | Advanced | β
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β¬β¬ β¬β β β β¬β β β β¬β¬β β β¬β¬β |
β Completed β’ β¬ Not Completed
All 30 challenges shown in two rows
Updated automatically based on 30 available challenges
- Total Challenges Available: 30
- Active Developers: 138
- Most Challenges Solved: 30 by PolinaSvet
Master Go packages through hands-on challenges! Each package offers a structured learning path with real-world scenarios.
Note: The data below is automatically updated by GitHub Actions when package challenge scoreboards change.
| π | Developer | Total Solved | Packages | Achievement | Challenge Distribution |
|---|---|---|---|---|---|
| π₯ |
odelbos |
17 | 4 pkgs | π₯ Package Master | cobra: 4 β’ fiber: 4 β’ gin: 4 β’ gorm: 5 |
| π₯ |
PolinaSvet |
8 | 2 pkgs | πͺ Package Advanced | cobra: 4 β’ gin: 4 |
| π₯ |
RezaSi |
7 | 6 pkgs | πͺ Package Advanced | cobra: 1 β’ echo: 1 β’ fiber: 1 β’ gin: 1 β’ gorm: 1 β’ mongodb: 2 |
| 4 |
ashwinipatankar β€οΈ |
3 | 1 pkg | π Package Intermediate | cobra: 3 |
| 5 |
GleeN987 |
1 | 1 pkg | π± Package Beginner | gin: 1 |
| 6 |
MarioPaez |
1 | 1 pkg | π± Package Beginner | gin: 1 |
| 7 |
kelvin-yong |
1 | 1 pkg | π± Package Beginner | gin: 1 |
π Package Challenges - Learn Go packages through practical, real-world scenarios
| Rank | Developer | Completed | Progress |
|---|---|---|---|
| π₯ | PolinaSvet | 4/4 | π©π©π©π©π©π©π©π©π©π© 100% |
| π₯ | odelbos | 4/4 | π©π©π©π©π©π©π©π©π©π© 100% |
| π₯ | ashwinipatankar | 3/4 | π©π©π©π©π©π©π©β¬β¬β¬ 75% |
| 4 | RezaSi | 1/4 | π©π©β¬β¬β¬β¬β¬β¬β¬β¬ 25% |
| Rank | Developer | Completed | Progress |
|---|---|---|---|
| π₯ | RezaSi | 1/4 | π©π©β¬β¬β¬β¬β¬β¬β¬β¬ 25% |
| Rank | Developer | Completed | Progress |
|---|---|---|---|
| π₯ | odelbos | 4/4 | π©π©π©π©π©π©π©π©π©π© 100% |
| π₯ | RezaSi | 1/4 | π©π©β¬β¬β¬β¬β¬β¬β¬β¬ 25% |
| Rank | Developer | Completed | Progress |
|---|---|---|---|
| π₯ | PolinaSvet | 4/4 | π©π©π©π©π©π©π©π©π©π© 100% |
| π₯ | odelbos | 4/4 | π©π©π©π©π©π©π©π©π©π© 100% |
| π₯ | GleeN987 | 1/4 | π©π©β¬β¬β¬β¬β¬β¬β¬β¬ 25% |
| 4 | MarioPaez | 1/4 | π©π©β¬β¬β¬β¬β¬β¬β¬β¬ 25% |
| 5 | RezaSi | 1/4 | π©π©β¬β¬β¬β¬β¬β¬β¬β¬ 25% |
| Rank | Developer | Completed | Progress |
|---|---|---|---|
| π₯ | odelbos | 5/5 | π©π©π©π©π©π©π©π©π©π© 100% |
| π₯ | RezaSi | 1/5 | π©π©β¬β¬β¬β¬β¬β¬β¬β¬ 20% |
| Rank | Developer | Completed | Progress |
|---|---|---|---|
| π₯ | RezaSi | 2/5 | π©π©π©π©β¬β¬β¬β¬β¬β¬ 40% |
-
Total Package Challenges Available: 26
-
Active Package Learners: 7
-
Available Packages: 6 (cobra, echo, fiber, gin, gorm, mongodb)
-
Most Package Challenges Solved: 17 by odelbos
- Interactive Web UI - Code, test, and submit solutions in your browser
- Automated Testing - Get immediate feedback on your solutions
- Automated Scoreboards - Solutions are automatically scored and ranked
- Profile Badges - Beautiful auto-updating badges for GitHub profiles, LinkedIn, and portfolios
- Performance Analytics - Track execution time and memory usage for your solutions
- Comprehensive Learning - Each challenge includes detailed explanations and resources
- Progressive Difficulty - From beginner to advanced Go concepts
- AI Interview Simulation - Practice with AI-powered code review and interviewer questions
Transform your coding practice into realistic interview scenarios with our AI-powered features:
Real-Time Code Review - Get instant feedback on code quality, complexity analysis, and improvement suggestions
Dynamic Interview Questions - AI generates follow-up questions based on your solution approach
Progressive Hints - 4-level hint system from subtle nudges to detailed explanations
Multi-LLM Support - Works with Gemini (recommended), OpenAI, or Claude
Simply add your API key to experience interview-style feedback that adapts to your code and challenges you with realistic technical questions.
|
AI Code Review Get instant feedback on code quality, complexity analysis, and improvement suggestions from AI |
Dynamic Interview Questions AI generates follow-up questions based on your solution approach and coding patterns |
Important: You must fork this repository first before cloning, otherwise you won't be able to push your solutions or create pull requests!
# 1. First, fork this repository on GitHub
# Go to https://github.com/RezaSi/go-interview-practice
# Click the "Fork" button in the top-right corner
# 2. Clone your forked repository (replace 'yourusername' with your GitHub username)
git clone https://github.com/yourusername/go-interview-practice.git
cd go-interview-practice
# 3. Start the web interface
cd web-ui
go run main.go
# 4. Open http://localhost:8080 in your browser
# 5. Optional: Enable AI Features (Recommended) π€
# Add your free Gemini API key to enable AI interview simulation
echo "AI_PROVIDER=gemini" > web-ui/.env
echo "GEMINI_API_KEY=your_actual_api_key_here" >> web-ui/.env
# Get your free API key: https://makersuite.google.com/app/apikey
# Note: .env files are automatically ignored by git for securityAfter solving challenges and submitting solutions:
- Your solutions will be automatically saved to your local repository
- Follow the provided Git commands to commit and push your changes
- Create a pull request to contribute your solutions back to the main project
Want to get started instantly without setting up anything locally? Use GitHub Codespaces!
- Fork this repository (if you haven't already)
- Open in Codespaces: Click the green "Code" button on your forked repository, then select "Codespaces" tab
- Create Codespace: Click "Create codespace on main"
-
Start the Web UI: Once the codespace loads, open a terminal and run:
cd web-ui go run main.go -
Optional: Enable AI Features: Add your Gemini API key:
echo "AI_PROVIDER=gemini" > .env echo "GEMINI_API_KEY=your_actual_api_key_here" >> .env
- Access the Web UI: Click on the "Ports" tab in the bottom panel, then click the "Open in Browser" button next to port 8080
Benefits of using Codespaces:
- No local setup required
- Pre-configured Go environment
- Full VS Code experience in the browser
- Automatic port forwarding for the web UI
- All dependencies pre-installed
- Works on any device with a browser
Deploy your own instance of the platform to the cloud with Railway!
Perfect for:
- Teams & Organizations: Private instance for internal use
- Educators: Custom environment for students
- Customization: Fork and modify for specific needs
- Always Available: 24/7 cloud hosting with automatic scaling
Setup Steps:
- Click Deploy Button above
-
Configure AI Features (optional but recommended):
- Choose AI provider:
gemini(recommended - free tier) - Add API key: Get free Gemini key
- Choose AI provider:
- Access Your Platform: Railway provides instant public URL
- Start Using: Full platform with all challenges immediately available
# 1. Fork the repository first (see step 1 above)
# 2. Clone your fork and set up a challenge workspace
git clone https://github.com/yourusername/go-interview-practice.git
cd go-interview-practice
./create_submission.sh 1 # For challenge #1
# 3. Implement your solution in the editor of your choice
# 4. Run tests
cd challenge-1
./run_tests.shShowcase your Go programming achievements with auto-updating profile badges for GitHub profiles, portfolios, and personal websites.
[](https://github.com/RezaSi/go-interview-practice)After contributing solutions, your badges are automatically generated in badges/YOUR_USERNAME_badges.md with multiple formats ready to use.
Complete Badge Guide & Examples β
Perfect for those new to Go or brushing up on fundamentals
- Challenge 1: Sum of Two Numbers
- Challenge 2: Reverse a String
- Challenge 3: Employee Data Management
- Challenge 6: Word Frequency Counter
- Challenge 18: Temperature Converter
- Challenge 21: Binary Search Implementation
- Challenge 22: Greedy Coin Change
For developers familiar with Go who want to deepen their knowledge
- Challenge 4: Concurrent Graph BFS Queries
- Challenge 5: HTTP Authentication Middleware
- Challenge 7: Bank Account with Error Handling
- Challenge 10: Polymorphic Shape Calculator
- Challenge 13: SQL Database Operations
- Challenge 14: Microservices with gRPC
- Challenge 16: Performance Optimization
- Challenge 17: Interactive Debugging Tutorial
- Challenge 19: Slice Operations
- Challenge 20: Circuit Breaker Pattern
- Challenge 23: String Pattern Matching
- Challenge 27: Go Generics Data Structures
- Challenge 30: Context Management Implementation
Challenging problems that test mastery of Go and computer science concepts
- Challenge 8: Chat Server with Channels
- Challenge 9: RESTful Book Management API
- Challenge 11: Concurrent Web Content Aggregator
- Challenge 12: File Processing Pipeline
- Challenge 15: OAuth2 Authentication
- Challenge 24: Dynamic Programming - Longest Increasing Subsequence
- Challenge 25: Graph Algorithms - Shortest Path
- Challenge 26: Regular Expression Text Processor
- Challenge 28: Cache Implementation with Multiple Eviction Policies
- Challenge 29: Rate Limiter Implementation
Browse challenges through the web UI or in the code repository. Each challenge includes:
- Detailed problem statement
- Function signature to implement
- Comprehensive test cases
- Learning resources
Write code that solves the challenge requirements and passes all test cases.
Use the built-in testing tools to validate your solution, then refine it for:
- Correctness
- Efficiency
- Code quality
Submit your passing solution to be added to the scoreboard:
- Your solution is automatically tested and scored
- Execution time and resource usage are recorded
- Your solution is ranked among other submissions
- Access detailed performance metrics to optimize further
Review the learning materials to deepen your understanding of the concepts used.
We welcome contributions! You can contribute in several ways:
Submit Solutions:
- Solve existing classic or package challenges
- Submit your solutions via pull request
Add New Challenges:
- Package Challenges: Framework-specific practical applications (Gin, Cobra, GORM, etc.)
Quick Steps:
- Fork the repository
- Choose challenge type (classic or package-based)
- Follow our template structure
- Submit a pull request
See CONTRIBUTING.md for detailed guidelines on both challenge types.
Thank you to our premium sponsors who make this project possible!
Interested in premium sponsorship? Contact us to feature your company logo here and on our platform!
This project is licensed under the MIT License - see the LICENSE file for details.
Happy Coding! π»
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Sweep is an AI junior developer that turns bugs and feature requests into code changes. It automatically handles developer experience improvements like adding type hints and improving test coverage.
teams-ai
The Teams AI Library is a software development kit (SDK) that helps developers create bots that can interact with Teams and Microsoft 365 applications. It is built on top of the Bot Framework SDK and simplifies the process of developing bots that interact with Teams' artificial intelligence capabilities. The SDK is available for JavaScript/TypeScript, .NET, and Python.
ai-guide
This guide is dedicated to Large Language Models (LLMs) that you can run on your home computer. It assumes your PC is a lower-end, non-gaming setup.
classifai
Supercharge WordPress Content Workflows and Engagement with Artificial Intelligence. Tap into leading cloud-based services like OpenAI, Microsoft Azure AI, Google Gemini and IBM Watson to augment your WordPress-powered websites. Publish content faster while improving SEO performance and increasing audience engagement. ClassifAI integrates Artificial Intelligence and Machine Learning technologies to lighten your workload and eliminate tedious tasks, giving you more time to create original content that matters.
chatbot-ui
Chatbot UI is an open-source AI chat app that allows users to create and deploy their own AI chatbots. It is easy to use and can be customized to fit any need. Chatbot UI is perfect for businesses, developers, and anyone who wants to create a chatbot.
BricksLLM
BricksLLM is a cloud native AI gateway written in Go. Currently, it provides native support for OpenAI, Anthropic, Azure OpenAI and vLLM. BricksLLM aims to provide enterprise level infrastructure that can power any LLM production use cases. Here are some use cases for BricksLLM: * Set LLM usage limits for users on different pricing tiers * Track LLM usage on a per user and per organization basis * Block or redact requests containing PIIs * Improve LLM reliability with failovers, retries and caching * Distribute API keys with rate limits and cost limits for internal development/production use cases * Distribute API keys with rate limits and cost limits for students
uAgents
uAgents is a Python library developed by Fetch.ai that allows for the creation of autonomous AI agents. These agents can perform various tasks on a schedule or take action on various events. uAgents are easy to create and manage, and they are connected to a fast-growing network of other uAgents. They are also secure, with cryptographically secured messages and wallets.
griptape
Griptape is a modular Python framework for building AI-powered applications that securely connect to your enterprise data and APIs. It offers developers the ability to maintain control and flexibility at every step. Griptape's core components include Structures (Agents, Pipelines, and Workflows), Tasks, Tools, Memory (Conversation Memory, Task Memory, and Meta Memory), Drivers (Prompt and Embedding Drivers, Vector Store Drivers, Image Generation Drivers, Image Query Drivers, SQL Drivers, Web Scraper Drivers, and Conversation Memory Drivers), Engines (Query Engines, Extraction Engines, Summary Engines, Image Generation Engines, and Image Query Engines), and additional components (Rulesets, Loaders, Artifacts, Chunkers, and Tokenizers). Griptape enables developers to create AI-powered applications with ease and efficiency.



