Sample code for my Medium article "How to build powerful deep recommender systems using Spotlight".

recommend_next_movies.py

"""
Utility functions for generating movie recommendations using sequence models.
"""
import difflib

def get_movie_id(movie_title, metadata):
    """
    Gets the movie id for a movie title
    """
    
    existing_titles = list(metadata['original_title'].values)
    closest_titles = difflib.get_close_matches(movie_title, existing_titles)
    movie_id = metadata[metadata['original_title'] == closest_titles[0]]['movieId'].values[0]
    return movie_id

def recommend_next_movies(movies, metadata, model, n_movies=5):
    
    """
    Recommends the top n next movies that a user is likely to watch 
    based on a list of previously watched movies.
    """
    
    movie_ids = [get_movie_id(movie, metadata) for movie in movies]
    pred = model.predict(sequences=np.array(movie_ids))
    indices = np.argpartition(pred, -n_movies)[-n_movies:]
    best_movie_ids = indices[np.argsort(pred[indices])]
    return [get_metadata(movie_id + 1, metadata) for movie_id in best_movie_ids]