def download_steam_reviews(): from appids import appid_hidden_gems_reference_set # All the reference hidden-gems steamreviews.download_reviews_for_app_id_batch( appid_hidden_gems_reference_set) # All the remaining hidden-gem candidates, which app_ids are stored in idlist.txt steamreviews.download_reviews_for_app_id_batch()
def main(download_reference_hidden_gems_as_well=False): if download_reference_hidden_gems_as_well: from appids import appid_hidden_gems_reference_set # All the reference hidden-gems steamreviews.download_reviews_for_app_id_batch(appid_hidden_gems_reference_set) # All the remaining hidden-gem candidates, which app_ids are stored in idlist.txt steamreviews.download_reviews_for_app_id_batch() return True
def main(): from appids import appids # All the references request_params = dict() # Reference: https://partner.steamgames.com/doc/store/getreviews request_params[ 'filter'] = 'all' # reviews are sorted by helpfulness instead of chronology request_params[ 'day_range'] = '28' # focus on reviews which were published during the past four weeks steamreviews.download_reviews_for_app_id_batch( appids, chosen_request_params=request_params) return True
def download_reviews_for_top_100(): # For each of the top 100 most played games, download English reviews, sorted by helpfulness, for the past 4 weeks data_request = dict() data_request['request'] = 'top100in2weeks' data = steamspypi.download(data_request) app_ids = list(data.keys()) request_params = dict() request_params['language'] = 'english' request_params['filter'] = 'recent' request_params['day_range'] = '28' # focus on reviews which were published during the past four weeks steamreviews.download_reviews_for_app_id_batch(app_ids, chosen_request_params=request_params) return
def test_download_reviews(self): app_ids = [329070, 573170] steamreviews.download_reviews_for_app_id_batch(app_ids, verbose=True) review_dict = steamreviews.load_review_dict(329070) self.assertGreater(len(review_dict["reviews"]), 1)
import steamreviews import json import csv request_params = dict() request_params['language'] = 'english' steamreviews.download_reviews_for_app_id_batch( chosen_request_params=request_params)
import steamreviews #port royale 4 (mixed) gameID1 = 1024650 #port royale 3 (mostly positive) gameID2 = 205610 #port royale 2 (mixed) gameID3 = 12470 gameIDs = [gameID1, gameID2, gameID3] steamreviews.download_reviews_for_app_id_batch(gameIDs) import json import pandas as pd import os from io import StringIO def extract_reviews_to_csv(gameID): json_path = 'data/review_' + str(gameID) +'.json' json_abspath = os.path.abspath(json_path) f = open(json_abspath, 'r') data = json.load(f) review_list = [] #Below, we make use of the fact that #each review stored in 'data['reviews']' is stored as a tuple {user ID, details of the review}, #and each 'details of the review' is itself a dictationary. #This can be converted into a nested dictinoary using data['reviews'].items(), so that user ID #become the key and the details of the review becomes the corresponding value. for user_id, review_info in data['reviews'].items(): #For each item, we build our own disctionary, selecting info we care at the moment review_select = {'Steam ID': user_id,