Source code for beta_rec.datasets.gowalla

import os
import time

import pandas as pd

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

# Download URL

# processed data url
GOWALLA_RANDOM_SPLIT_URL = "!AjMahLyQeZqughJgziqB9ORAzcs5?e=wdHaxf"

[docs]def process_time(standard_time=None): """Transform time format "xxxx-xx-xxTxx-xx-xxZ" into format "xxxx-xx-xx xx-xx-xx". Args: standard_time: str with format "xxxx-xx-xxTxx-xx-xxZ". Returns: timestamp: timestamp data. """ standard_time_list = list(standard_time) standard_time_list[10] = " " standard_time_list.pop() standard_time = "".join(standard_time_list) date_arr = time.strptime(standard_time, "%Y-%m-%d %H:%M:%S") timestamp = int(time.mktime(date_arr)) return timestamp
[docs]class Gowalla(DatasetBase): """Gowalla Dataset. Gowalla is a location-based social networking website where users share their locations by checking-in. The friendship network is undirected and was collected using their public API, and consists of 196,591 nodes and 950,327 edges. We have collected a total of 6,442,890 check-ins of these users over the period of Feb. 2009 - Oct. 2010. If the dataset can not be download by the url, you need to down the dataset by the link: then put it into the directory `gowalla/raw` and unzip it. """ def __init__(self, dataset_name="gowalla", min_u_c=0, min_i_c=3, root_dir=None): """Init Gowalla Class.""" super().__init__( dataset_name=dataset_name, min_u_c=min_u_c, min_i_c=min_i_c, root_dir=root_dir, url=GOWALLA_CHECKIN_URL, processed_random_split_url=GOWALLA_RANDOM_SPLIT_URL, processed_temporal_split_url=GOWALLA_TEMPORAL_SPLIT_UTL, )
[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 Download datasets if not existed. Gowalla_checkin_name: Gowalla_totalCheckins.txt Gowalla_edges_name : Gowalla_edges.txt 1. Download gowalla dataset if this dataset is not existed. 2. Load gowalla <Gowalla_checkin> table from 'Gowalla_totalCheckins.txt'. 3. Process time columns and transform it into timestamp. 4. Rename and save dataset model. """ # Step 1: Download gowalla dataset if this dataset is not existed. gowalla_path_checkin = os.path.join(self.raw_path, "Gowalla_totalCheckins.txt") gowalla_path_edges = os.path.join(self.raw_path, "Gowalla_edges.txt") if not os.path.exists(gowalla_path_checkin): self.url = GOWALLA_EDGES_URL if not os.path.exists(gowalla_path_edges): # Step 2: Load gowalla <Gowalla_checkin> table from 'Gowalla_totalCheckins.txt' prior_transactions = pd.read_table( gowalla_path_checkin, header=None, sep="\t", usecols=[0, 1, 4], names=[DEFAULT_USER_COL, DEFAULT_TIMESTAMP_COL, DEFAULT_ITEM_COL], ) # Add rating column into the table. prior_transactions.insert(2, "rating", 1.0) # Step 3: Process time columns and transform it into timestamp. prior_transactions[DEFAULT_TIMESTAMP_COL] = prior_transactions[ DEFAULT_TIMESTAMP_COL ].apply(lambda t: process_time(t)) # Step 4: Rename and save dataset model. prior_transactions.rename( columns={ DEFAULT_USER_COL: DEFAULT_USER_COL, DEFAULT_ITEM_COL: DEFAULT_ITEM_COL, "rating": DEFAULT_RATING_COL, DEFAULT_TIMESTAMP_COL: DEFAULT_TIMESTAMP_COL, }, inplace=True, ) # Check the validation of this table. print(prior_transactions.head()) # Save data model. self.save_dataframe_as_npz( prior_transactions, os.path.join(self.processed_path, f"{self.dataset_name}_interaction.npz"), ) print("Done.")