| import sys | |
| from anime_recommender.exception.exception import AnimeRecommendorException | |
| from anime_recommender.loggers.logging import logging | |
| from anime_recommender.utils.main_utils.utils import load_csv_data | |
| from anime_recommender.entity.artifact_entity import DataIngestionArtifact | |
| from anime_recommender.model_trainer.top_anime_filtering import PopularityBasedFiltering | |
| class PopularityBasedRecommendor: | |
| """ | |
| A class that provides anime recommendations based on different popularity criteria. | |
| """ | |
| def __init__(self,data_ingestion_artifact = DataIngestionArtifact): | |
| """ | |
| Initializes the PopularityBasedRecommendor with the ingested anime dataset. | |
| Args: | |
| data_ingestion_artifact (DataIngestionArtifact): An artifact containing the feature store file paths. | |
| """ | |
| try: | |
| self.data_ingestion_artifact = data_ingestion_artifact | |
| except Exception as e: | |
| raise AnimeRecommendorException(e,sys) | |
| def initiate_model_trainer(self,filter_type:str): | |
| """ | |
| Trains the popularity-based recommender model and logs the top anime recommendations | |
| based on the specified filter type. | |
| Args: | |
| filter_type (str): The type of filtering to apply. | |
| Options include: | |
| - 'popular_animes': Most popular anime based on user engagement. | |
| - 'top_ranked_animes': Highest ranked anime. | |
| - 'overall_top_rated_animes': Overall top-rated anime. | |
| - 'favorite_animes': Most favorited anime. | |
| - 'top_animes_members': Anime with the highest number of members. | |
| - 'popular_anime_among_members': Most popular anime among members. | |
| - 'top_avg_rated': Anime with the highest average ratings. | |
| """ | |
| try: | |
| logging.info("Loading transformed data...") | |
| df = load_csv_data(self.data_ingestion_artifact.feature_store_anime_file_path) | |
| recommender = PopularityBasedFiltering(df) | |
| if filter_type == 'popular_animes': | |
| popular_animes = recommender.popular_animes(n =10) | |
| logging.info(f"Popular Anime recommendations: {popular_animes}") | |
| elif filter_type == 'top_ranked_animes': | |
| top_ranked_animes = recommender.top_ranked_animes(n =10) | |
| logging.info(f"top_ranked_animes recommendations: {top_ranked_animes}") | |
| elif filter_type == 'overall_top_rated_animes': | |
| overall_top_rated_animes = recommender.overall_top_rated_animes(n =10) | |
| logging.info(f"overall_top_rated_animes recommendations: {overall_top_rated_animes}") | |
| elif filter_type == 'favorite_animes': | |
| favorite_animes = recommender.favorite_animes(n =10) | |
| logging.info(f"favorite_animes recommendations: {favorite_animes}") | |
| elif filter_type == 'top_animes_members': | |
| top_animes_members = recommender.top_animes_members(n = 10) | |
| logging.info(f"top_animes_members recommendations: {top_animes_members}") | |
| elif filter_type == 'popular_anime_among_members': | |
| popular_anime_among_members = recommender.popular_anime_among_members(n =10) | |
| logging.info(f"popular_anime_among_members recommendations: {popular_anime_among_members}") | |
| elif filter_type == 'top_avg_rated': | |
| top_avg_rated = recommender.top_avg_rated(n =10) | |
| logging.info(f"top_avg_rated recommendations: {top_avg_rated}") | |
| except Exception as e: | |
| raise AnimeRecommendorException(e,sys) |