TwiClipSaver – Twitch Clip Download Platform
Project Overview
TwiClipSaver is a comprehensive web platform that allows users to download, view, and discover Twitch clips. The project combines direct downloading capabilities, content discovery, and video game exploration within a modern, responsive interface.
Technical Architecture
Tech Stack
- Backend: Django with Python
- Database: PostgreSQL in production, SQLite in development
- Cache: Redis for performance and session management
- Frontend: Tailwind CSS with HTMX for dynamic interactions
- Web Server: Gunicorn
- Orchestration: Docker with Docker Swarm
- Async Tasks: Celery with Redis as broker
Infrastructure
- Containerization: Multi-container architecture using Docker Swarm
- CI/CD: GitHub Actions for deployment automation
- Monitoring: Flower for Celery task supervision
- Security: Mandatory HTTPS, HSTS, CSRF protection
Main Features
Clip Downloading
- Simple interface to paste a Twitch clip URL
- Automatic metadata extraction (title, channel, game)
- Video quality selection (HD, 720p, 480p, etc.)
- Direct download via twitch-dl tool
- Temporary storage with auto-cleanup
Content Discovery
- Random Clips: Recommendation system based on popular games
- Trending Clips: Displays most viewed clips with infinite scrolling
- Explore by Game: Full game catalog with IGDB metadata
- Channel Directory: Browse streamers with related clips
API Integration
- Twitch API: OAuth2 authentication, clip and metadata retrieval
- IGDB API: Enrichment of game data with detailed info
- Smart Cache: Redis caching to optimize performance
Data Models
TwitchClip
- Storage of downloaded clips with metadata
- Download statistics tracking
- Linked to channels and games
TwitchGame
- Local database of Twitch games
- Automatic synchronization via Celery tasks
- Linked to IGDB data
IGDBGame
- Game data enrichment
- Detailed info (genres, platforms, developers)
- Slug system for URL rewriting
TwitchStream
- Live stream tracking
- Full metadata (viewers, tags, language)
- Basis for channel directory
Asynchronous Tasks (Celery)
Data Updates
- Weekly synchronization of popular games
- Game data enrichment via IGDB API
- Live stream fetching
Maintenance
- Automatic cleanup of temporary files
- Error handling and automatic retry
- Monitoring via Flower
Technical Optimizations
Performance
- Redis cache for frequent API requests
- Infinite scrolling with HTMX
- Static asset compression
- Database query optimization
SEO and Accessibility
- Dynamic XML sitemap
- Open Graph and Twitter Cards metadata
- Semantic HTML structure
- Configured robots.txt
Security
- CSRF protection on all forms
- Input URL validation
- Secure handling of temporary files
- HTTP security headers
Deployment and Infrastructure
Docker Architecture
- Main container for Django application
- Celery Worker container for async tasks
- Celery Beat container for scheduling
- Redis container for cache and tasks
- Flower container for monitoring
CI/CD
- Automatic Docker image builds
- Push to private registry
- Automatic deployment on Docker Swarm
- Rollback on failure
Monitoring
- Centralized logging
- Celery task monitoring
- Error alerts
- Performance metrics
Advanced Features
User Interface
- Responsive design with Tailwind CSS
- Dynamic interactions using HTMX
- Modal for clip preview
- Search system and filters
REST API
- Endpoints for third-party integration
- Token-based authentication
- API endpoint documentation
- Rate limiting
Analytics
- Download tracking
- Usage statistics
- Google Analytics integration
- Performance monitoring
Resolved Technical Challenges
External API Management
- Rate limit handling for Twitch and IGDB
- Fallback on API unavailability
- Smart caching to reduce calls
- Timeout and error handling
Performance and Scalability
- Optimized database queries
- Caching of expensive results
- Memory management for large files
- Load balancing with Docker Swarm
Security and Reliability
- Strict validation of user input
- Protection against common attacks
- Automatic data backups
- Error monitoring
Results and Metrics
- Scalable architecture supporting thousands of users
- Average response time < 200ms on main pages
- 99.9% availability thanks to containerized architecture
- Fully automated deployment process
- Real-time performance monitoring
