🎬 Movie Recommendation System Backend - Django & Python

This project is a backend API service for a movie recommendation system, built with Django and Python. It provides various endpoints for user authentication, movie data retrieval, and favorite list management. The data is stored in a JSON file containing a list of movies.

🌟 Features

• User Authentication:

  • Register: Create a new user account.
  • Login: Authenticate existing users.

• Movie APIs:

  • All Movies: Retrieve the complete list of movies.
  • Get Movie by ID: Fetch specific movie details by movie ID.

• Favorites:

  • Save Favorite Movie: Users can add movies to their favorites list.
  • Get User Favorites: Retrieve a list of a user's favorite movies.

📂 Project Structure

backend-movie-recommendation/
├── data/
│   └── movies.json         # JSON file containing movie data
├── app/
│   ├── models.py           # Database models
│   ├── views.py            # API endpoints logic
│   ├── serializers.py      # Serializers for data formatting
│   └── urls.py             # URL routing for APIs
└── manage.py               # Django project management script

🚀 Getting Started

Prerequisites

• Python 3.x
• Django

Installation

1. Clone the repository:

   git clone https://github.com/ckkashi/Backend---Movie-recommendation-system---Django---Python.git
   cd Backend---Movie-recommendation-system---Django---Python

2. Install the required packages:

   pip install -r requirements.txt

3. Run database migrations:

   python manage.py migrate

4. Start the development server:

   python manage.py runserver

API Endpoints

Endpoint	Method	Description
/register	POST	Register a new user
/login	POST	User login
/getMovies	GET	Get all movies
/getMovieById?movie_id=1	GET	Get movie by ID
/getFavMovies	GET	Get user favorite movies
/addFavMovie	POST	Add movie to user favorites

💻 Usage

To access the endpoints, use a tool like Postman or curl.

• Register a user to create an account.
• Login with your credentials to receive an authentication token.
• Use the token to access movie data and manage your favorites list.

📈 Future Enhancements

• Implement recommendation algorithms to suggest similar movies.
• Add additional filters and search functionality for movies.
• Enable pagination for large datasets.

🤝 Contributing

Contributions are welcome! Please feel free to submit a pull request or open an issue if you have suggestions or find bugs.

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.