Movie Database & Recommender System via Classification Model
BingeMatch is a Python-based movie database and recommender system that leverages a classification model (model selection pending) to provide personalized movie recommendations. Designed for movie enthusiasts, BingeMatch allows users to explore a comprehensive movie database, access detailed movie information, and receive tailored suggestions based on their preferences. The system aims to enhance the movie-watching experience by combining data-driven insights with an intuitive interface.
The primary purpose of BingeMatch is to deliver accurate, user-specific movie recommendations while offering robust tools for browsing and managing movie data.
✅ Movie Database – Store and retrieve detailed movie information (e.g., title, genre, year).
✅ Recommendation Engine – Generate personalized movie suggestions using a classification model.
✅ User Interface – Command-line interface for browsing movies and viewing recommendations.
🚀 Model Optimization – Finalize and optimize the classification model for better accuracy.
🚀 User Profiles – Support for saving user preferences and watch history.
🚀 API Integration – Connect to external movie databases (e.g., IMDb, TMDB) for enriched data.
🚀 Graphical UI – Develop a GUI for a more user-friendly experience.
🔄 Initial release with core movie database and recommendation functionality.
🔄 Basic command-line interface for user interaction.
🔄 Ongoing evaluation of classification models for optimal performance.
📌 Author: dreyyan
📌 Started: 2025-04-07
📌 Finished: 2025-07-20
🛠️ Language: Python
🛠️ Libraries: TBD (pending classification model selection, likely scikit-learn or TensorFlow)
- Python 3.8 or higher
- Create a virtual environment (recommended):
python -m venv venv source venv/bin/activate # On Unix/Mac venv\Scripts\activate # On Windows
Install required packages (update based on final model selection, e.g., scikit-learn):
pip install scikit-learn # Example; adjust based on chosen model
Check Python version:
python --version
Set the command prompt size to 72x30 for optimal display:
- On Windows:
mode con: cols=72 lines=30 - On Unix/Mac: Adjust terminal size to 72 columns by 30 rows.
Start BingeMatch:
python main.py
- Launch the App: Run
python main.pyto start the command-line interface. - Browse Movies: Explore the movie database by searching or filtering by genre, year, etc.
- Get Recommendations: Input preferences to receive personalized movie suggestions.
- View Details: Access detailed information about selected movies.
- Configure the command prompt size to 72x30 for the best experience.
- Adjust settings (e.g., model parameters) via configuration files or the command-line interface (details TBD).
For issues, check console output for error messages related to data loading or model predictions. Run with:
python main.py
Report issues via GitHub Issues for detailed troubleshooting.
main.py: Entry point for the application (assumed; adjust based on actual structure).- Other files may include modules for database management, recommendation logic, and user interface (not specified in provided details).
Contributions are welcome! Fork the repo, make changes, and submit a pull request:
- Create a feature branch:
git checkout -b feature/new-feature - Commit changes:
git commit -m "Add new feature" - Push:
git push origin feature/new-feature - Open a pull request
Report issues or suggest features via GitHub Issues.
This project is licensed under the MIT License. See LICENSE for details.