{"id":27940779,"url":"https://github.com/cdobratz/nfl-sentiment-analyzer","last_synced_at":"2026-05-01T19:32:30.417Z","repository":{"id":291939248,"uuid":"918036823","full_name":"cdobratz/NFL-Sentiment-Analyzer","owner":"cdobratz","description":"A real-time sentiment analysis tool for NFL games that helps fans and analysts understand the public sentiment around games, teams, and players. 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Built with modern MLOps practices and scalable architecture.\n\n## 🏈 Features\n\n- Real-time sentiment analysis of NFL-related content\n- FastAPI backend with MongoDB Atlas integration\n- Containerized with Docker for easy deployment\n- Scalable architecture ready for high-traffic game days\n\n## ✨ Recent Improvements\n\n- **Enhanced Security**: Replaced dangerous `redis.flushdb()` with safe prefix-based key deletion to prevent accidental data loss in shared Redis instances\n- **Performance Optimization**: Improved MongoDB query efficiency by using direct integer equality instead of `$in` operators for better index utilization\n- **Bug Fixes**: Fixed CORS validator to properly read environment settings from `.env` files using Pydantic's ValidationInfo\n- **CI/CD Improvements**: Resolved NumPy 2.0 compatibility issues in test suite and updated Docker builds to use UV package manager\n- **Code Quality**: Applied Black formatting and improved test reliability with tolerance-based floating-point comparisons\n\n## 🚀 Quick Start\n\n1. Clone the repository:\n\n    ```bash\n    git clone https://github.com/cdobratz/NFL-Sentiment-Analyzer.git\n    cd NFL-Sentiment-Analyzer\n    ```\n\n2. Set up environment variables:\n\n    ```bash\n    cp .env.example .env\n    # Edit .env with your MongoDB Atlas credentials\n    ```\n\n3. Run with Docker:\n\n    ```bash\n    docker-compose up --build\n    ```\n\nThe API will be available at `http://localhost:8000`\n\n## 📚 Documentation\n\nDetailed documentation is available in the [docs](docs) directory:\n\n- [Local Development Setup](docs/setup/local-setup.md)\n- [Production Deployment Guide](docs/setup/deployment.md)\n- [Architecture Overview](docs/architecture/tech-stack.md)\n- [Contributing Guidelines](CONTRIBUTING.md)\n- [Type Checking TODO](docs/type-checking-todo.md) - Plan for re-enabling mypy\n\nVisit our [Documentation Index](docs/README.md) for a complete list of documentation.\n\n## 🔧 Tech Stack\n\n- **Backend**: Python, FastAPI\n- **Database**: MongoDB Atlas\n- **ML**: HuggingFace Transformers\n- **Infrastructure**: Docker, GitHub Actions\n\n## 🛣️ Roadmap\n\n- [ ] User authentication\n- [ ] Real-time Twitter/X data integration\n- [ ] Advanced sentiment analysis models\n- [ ] Interactive dashboard\n- [ ] Automated model retraining\n- [ ] Deployment to Digital Ocean\n\n## 🤝 Contributing\n\nContributions are welcome! Please read our [Contributing Guidelines](CONTRIBUTING.md) before submitting a Pull Request.\n\n## 📝 License\n\nThis project is licensed under the MIT License - see the LICENSE file for details.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcdobratz%2Fnfl-sentiment-analyzer","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fcdobratz%2Fnfl-sentiment-analyzer","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcdobratz%2Fnfl-sentiment-analyzer/lists"}