Recommender systems are effective tools to offer personalized referrals to the Internet users who seek and/or surf for books, movies, restaurants, etc. In this study, we propose and implement a novel hybrid recommender system over Python for online movie platforms. We empirically analyze our system in terms of prediction quality on real movie content and ratings dataset. Our hybrid recommender system gives promising accurate results and is efficient at the same time. We uploaded the entire Python project into GitHub repository.