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Radius is a movie streaming website built with Python, Django, and MySQL.

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Radius

Radius is a movie streaming website built with Python, Django, and MySQL. It's an OTT platform that allows users to stream movies and TV shows, and includes a payment gateway integrated with Stripe for secure and easy payment processing. Additionally, the website includes a small recommendation system that uses collaborative filtering to recommend movies to users based on their viewing history.

Usage

To use the website, navigate to the live demo by clicking on the following link:

LIVE DEMO

The live demo allows users to create an account, browse the available movies and TV shows, and stream content. The payment gateway is also active, allowing users to securely purchase access to premium content.

Homepage

Radius Homepage

The homepage displays a selection of popular movies and TV shows, as well as featured content. Users can browse the available content and search for specific movies or TV shows.

Movie Details Page

Radius Movie Details

The movie details page displays information about the selected movie or TV show, including a synopsis, cast and crew information, and user ratings. Users can also see related movies and TV shows, as well as add the selected movie to their watchlist.

Watchlist

Radius Watchlist

The watchlist page displays all of the movies and TV shows that a user has added to their watchlist. Users can access their watchlist from the navigation menu, and remove items from the list as they watch them.

Payment Gateway

Radius Payment Gateway

The payment gateway is integrated with Stripe for secure and easy payment processing. Users can purchase access to premium content using a credit card.

Recommendations

Radius Recommendations

The recommendations page displays movies and TV shows that are recommended to the user based on their viewing history. The recommendation system uses collaborative filtering to identify similar users and suggest movies and TV shows that they have enjoyed. Users can add recommended content to their watchlist and rate the content that they have already watched.

Collaborative Filtering

The recommendation system on this website uses collaborative filtering to recommend movies to users based on their viewing history. The system analyzes the viewing patterns of all users on the website and identifies movies that are commonly watched together. It then recommends movies to users based on their viewing history and the viewing history of users with similar interests.

Thanks

Thanks to CHATGPT for generating this README.md file! If you have any questions or feedback about this website, please feel free to contact us. We welcome all feedback and suggestions!

Contributing

If you would like to contribute to this project, please fork the repository and submit a pull request with your changes. We welcome all contributions, big and small!

License

This website is licensed under the MIT License. See LICENSE for more information.