README.md

Repository Overview

This is a comprehensive Go training repository organized into structured learning modules, from basic concepts to expert-level implementations. The codebase uses Go 1.24.0 and includes practical examples, advanced projects, and performance optimization studies.

Architecture

The repository follows a hierarchical learning structure:

• A.Basic/: Foundational Go concepts organized into 9 training modules

  • training1: Syntax basics (variables, data types, operators)
  • training2: Control structures (arrays, slices, maps, loops, branching)
  • training3: Object-oriented concepts (functions, methods, interfaces, pointers, reflection)
  • training4: Concurrency (goroutines, channels, contexts)
  • training5: Standard library utilities (strings, time, random)
  • training6: System programming (files, CLI, regex, hashing)
  • training7: Web development (HTTP, JSON, APIs)
  • training8: Data persistence (SQL, MongoDB, unit testing)
  • training9: Advanced patterns (concurrency pipelines, generics, mutexes)

• B.Intermediate/: Currently empty, planned for intermediate concepts

• C.Advanced/: Currently empty, planned for advanced topics

• D.Expert/: Advanced implementations

  • AI/ML integrations (Model Context Protocol, LangChain)
  • Blockchain (P2P networks)
  • Machine learning and data science modules

• E.Other/: Specialized topics and examples

  • Performance benchmarking and optimization
  • One Billion Row Challenge implementations
  • Health check patterns
  • Error handling patterns
  • Profile-guided optimization

Common Development Tasks

Running Individual Examples

Most files in the Basic training modules are standalone examples with main() functions:

go run A.Basic/training1/introduction/main.go
go run A.Basic/training3/function/basic-func/implement-func.go

Running Benchmarks

Execute performance benchmarks to study optimization techniques:

go test -bench=. ./E.Other/benchmark/
go test -bench=BenchmarkAdd ./E.Other/benchmark/

Running Specific Applications

For complex projects in D.Expert and E.Other:

# Run LangChain Gin application
go run D.Expert/large-language-models/gin-langchain/main.go

# Run One Billion Row Challenge implementations
go run E.Other/one_brc/brc2/main.go -revision=1 measurements.txt

Testing

Run tests for specific modules:

go test ./E.Other/one_brc/brc4/
go test -v ./E.Other/one_brc/brc4/

Building

The module can be tidied and dependencies managed:

go mod tidy
go mod download

Key Architectural Patterns

Learning Structure

Each training module contains focused examples that build upon previous concepts. Examples are self-contained with descriptive filenames that indicate their purpose.

Performance Focus

The repository emphasizes performance optimization:

• Benchmark suites in E.Other/benchmark/
• One Billion Row Challenge implementations demonstrating various optimization techniques
• Profile-guided optimization examples

Practical Applications

Expert-level modules demonstrate real-world integrations:

• Model Context Protocol: AI tool integration patterns
• LangChain Integration: LLM application development
• P2P Blockchain: Distributed systems implementation
• Health Check Patterns: Multiple health checking library implementations

Error Handling

Comprehensive error handling patterns demonstrated across modules, with dedicated examples in E.Other/error-handling/.

Module-Specific Notes

Basic Training Modules

• Each subdirectory typically contains multiple .go files with main functions
• Files cannot be tested together as packages due to multiple main() functions
• Run individual files to see specific concept demonstrations

Expert Modules

• Complete applications with proper package structure
• May require external dependencies (defined in go.mod)
• Include more complex architectural patterns

Benchmark Modules

• Use Go's built-in benchmark framework
• Focus on performance optimization techniques
• Include memory allocation profiling

Dependencies

The project uses numerous external libraries for different training scenarios:

• Web frameworks: Gin, Chi
• AI/ML: LangChain Go, MCP Golang
• Testing: Testify, SQL Mock
• Health checks: Multiple health check libraries for comparison
• Databases: SQLite, MongoDB drivers
• System: SSH server, Discord bot integration

Development Environment

• Go 1.24.0 required
• No special build tools or Makefiles needed
• Standard Go toolchain sufficient for all operations
• Uses standard Go module structure with comprehensive dependency management