c54c569f30
Completed clean root directory structure: - Root now contains only: .git, .env, docs/, orig/ - Moved all remaining files and directories to orig/: - Config files (.claude, .dockerignore, .drone.yml, etc.) - All .env variants (except active .env) - Git config (.gitconfig, .github, .gitignore, etc.) - Tool configs (.golangci.yml, .revive.toml, etc.) - Documentation (*.md files, @prompts) - Build files (Dockerfiles, Makefile, go.mod, go.sum) - Docker compose files - All source directories (scripts, tests, tools, etc.) - Runtime directories (logs, monitoring, reports) - Dependency files (node_modules, lib, cache) - Special files (--delete) - Removed empty runtime directories (bin/, data/) V2 structure is now clean: - docs/planning/ - V2 planning documents - orig/ - Complete V1 codebase preserved - .env - Active environment config (not in git) 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
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You are an expert in Go concurrency patterns and high-performance systems. I'm building an MEV bot that needs to efficiently process thousands of transactions per second using advanced concurrency patterns.
I need help with:
- Implementing efficient worker pools for transaction processing
- Creating pipeline patterns for multi-stage processing
- Implementing fan-in and fan-out patterns for data distribution
- Using channels effectively for communication between goroutines
- Managing rate limiting across multiple RPC endpoints
- Implementing backpressure handling to prevent resource exhaustion
- Optimizing memory usage and garbage collection
- Using context for cancellation and timeouts
Please provide production-ready Go code that:
- Implements efficient concurrency patterns
- Handles errors gracefully without leaking goroutines
- Uses appropriate buffering for channels
- Follows Go best practices for concurrent programming
- Includes comprehensive comments explaining the patterns used
- Provides metrics for monitoring performance
The code should:
- Process transactions with minimal latency
- Scale efficiently across multiple CPU cores
- Handle backpressure gracefully
- Provide clear error handling and recovery
- Include benchmarks for critical functions