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,