Melu_L2L_hyperTunning/dataset.py

import datetime
import pandas as pd


class movielens_1m(object):
    def __init__(self):
        self.user_data, self.item_data, self.score_data = self.load()

    def load(self):
        path = "movielens/ml-1m"
        profile_data_path = "{}/users.dat".format(path)
        score_data_path = "{}/ratings.dat".format(path)
        item_data_path = "{}/movies_extrainfos.dat".format(path)

        profile_data = pd.read_csv(
            profile_data_path, names=['user_id', 'gender', 'age', 'occupation_code', 'zip'], 
            sep="::", engine='python'
        )
        item_data = pd.read_csv(
            item_data_path, names=['movie_id', 'title', 'year', 'rate', 'released', 'genre', 'director', 'writer', 'actors', 'plot', 'poster'], 
            sep="::", engine='python', encoding="utf-8"
        )
        score_data = pd.read_csv(
            score_data_path, names=['user_id', 'movie_id', 'rating', 'timestamp'],
            sep="::", engine='python'
        )

        score_data['time'] = score_data["timestamp"].map(lambda x: datetime.datetime.fromtimestamp(x))
        score_data = score_data.drop(["timestamp"], axis=1)
        return profile_data, item_data, score_data