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  Bot making the reservation, sent to my email

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Reservation Sniper

Inspiration

• The frustration of missing premium restaurant reservations
• The manual effort required to constantly check multiple platforms
• The speed advantage needed to secure high-demand reservations
• Real-world problem: valuable reservation opportunities slipping away

What it does

• Intelligent Monitoring: Continuously scans AppointmentTrader for active bids
• Cross-Platform Integration: Maps AppointmentTrader venues to OpenTable restaurant IDs
• Automated Booking: Attempts real-time slot locking and reservation creation
• Speed Optimization: Uses proxy rotation, parallel processing, and direct API calls
• Comprehensive Logging: Tracks every attempt with detailed timing and success metrics

How we built it

• Go Backend: 8,100+ lines of high-performance Go code
• CLI Architecture: Three main commands (monitor, book, autobook)
• Advanced Web Scraping: Chrome fingerprinting, CSRF token management, azuretls client
• Concurrent Processing: Worker pool pattern with configurable parallelism
• API Integration: OpenTable GraphQL API and REST endpoints
• Session Management: Proxy rotation with 1000+ proxy support

Challenges we ran into

• Anti-Bot Detection: Implementing sophisticated browser fingerprinting
• CSRF Token Management: Building a robust caching and refresh system
• Rate Limiting: Balancing speed with server protection
• API Reverse Engineering: Understanding OpenTable's internal GraphQL structure
• Concurrent Safety: Thread-safe operations across multiple workers

Accomplishments that we're proud of

• Full End-to-End Automation: From bid detection to successful reservations
• Real API Integration: Successfully connecting to production OpenTable systems
• Performance Engineering: Sub-second response times with parallel processing
• Comprehensive Testing: Unit tests, integration tests, and edge case coverage
• Production Ready: Error handling, logging, and retry mechanisms

What we learned

• Advanced Web Scraping Techniques: Browser fingerprinting and anti-detection
• Go Concurrency Patterns: Worker pools, channels, and goroutine management
• API Security: CSRF tokens, session management, and authentication flows
• System Architecture: Building scalable, maintainable CLI applications
• Performance Optimization: Speed-critical system design principles

What's next for Reservation Sniper

• Machine Learning: Predict optimal booking times based on historical data
• Multi-Platform Support: Expand to Resy, Yelp Reservations, and other platforms
• Mobile App: Real-time notifications and manual booking interface
• Success Analytics: Track booking success rates and optimization opportunities
• Restaurant Partnerships: Direct API integrations for better availability data

Built With

• docker
• go
• graphql