Source code for beta_rec.datasets.yelp

import json
import os
import time

import pandas as pd

from ..datasets.dataset_base import DatasetBase
from ..utils.constants import (

# Download URL.

# Yelp
    Yelp dataset can not be downloaded by this url automatically, and you need to do:
    1. Download this dataset via '',
    2. Put '' into the directory `yelp/raw/yelp`,
    3. Unzip '',
    4. Rerun this program.

[docs]class Yelp(DatasetBase): """Yelp Dataset. The dataset can not be download by the url, you need to down the dataset by '' then put it into the directory `yelp/raw/yelp`. """ def __init__(self, dataset_name="yelp", min_u_c=0, min_i_c=3, root_dir=None): """Init Yelp Class.""" super().__init__( dataset_name=dataset_name, min_u_c=min_u_c, min_i_c=min_i_c, root_dir=root_dir, manual_download_url=YELP_URL, processed_leave_one_out_url="", processed_random_split_url="", processed_temporal_split_url="", tips=YELP_TIPS, )
[docs] def preprocess(self): """Preprocess the raw file. Preprocess the file downloaded via the url, convert it to a dataframe consist of the user-item interaction and save in the processed directory. """ file_name = os.path.join( self.raw_path, self.dataset_name, "yelp_academic_dataset_review.json" ) if not os.path.exists(file_name): """Load yelp json-format dataset into yelp dataframe. 1. Load json data in lists, we only use userID, businessID, stars, date in this file. 2. Add lists into dataframe. 3. Map fix-length string ID into int format. """ userList, itemList, starList, dateList = [], [], [], [] userMap, itemMap = {}, {} userCnt, itemCnt = 0, 0 with open(file_name, "r", encoding="utf-8") as fin: for line in fin: line = json.loads(line) user = str(line["user_id"]) item = str(line["business_id"]) star = line["stars"] # Create timestamp. date_str = str(line["date"]) date_arr = time.strptime(date_str, "%Y-%m-%d %H:%M:%S") timestamp = int(time.mktime(date_arr)) # Construct HashMap. if user not in userMap: userMap[user] = userCnt userCnt += 1 if item not in itemMap: itemMap[item] = itemCnt itemCnt += 1 # Add pairs into dataframe. userList.append(user) itemList.append(item) starList.append(star) dateList.append(timestamp) prior_transactions = pd.DataFrame( { DEFAULT_USER_COL: userList, DEFAULT_ITEM_COL: itemList, DEFAULT_RATING_COL: starList, DEFAULT_TIMESTAMP_COL: dateList, } ) # Transfer fix-length string into num. prior_transactions[DEFAULT_USER_COL] = prior_transactions[ DEFAULT_USER_COL ].apply(lambda u: userMap[u]) prior_transactions[DEFAULT_ITEM_COL] = prior_transactions[ DEFAULT_ITEM_COL ].apply(lambda i: itemMap[i]) # Check the validation of this table. print(prior_transactions.head()) # Save this table. self.save_dataframe_as_npz( prior_transactions, os.path.join(self.processed_path, f"{self.dataset_name}_interaction.npz"), ) print("Done.")