from net import *
import pandas as pd
c=Client();start=int(pd.Timestamp('2025-01-01',tz='UTC').timestamp());end=int(pd.Timestamp('2026-01-01',tz='UTC').timestamp())
base={'json':1,'language':'all','purchase_type':'steam','review_type':'all','num_per_page':100,'filter_offtopic_activity':1}
for name,params in [('recent_range',base|{'filter':'recent','start_date':start,'end_date':end,'date_range_type':'include'}),('all_range',base|{'filter':'all','start_date':start,'end_date':end,'date_range_type':'include'})]:
    raw=json.loads(c.get('https://store.steampowered.com/appreviews/915310',params,'date_filter_probe'));safe=[{k:x.get(k) for k in ['recommendationid','timestamp_created','timestamp_updated','voted_up','steam_purchase']} for x in raw.get('reviews',[])]
    record={'params':params,'query_summary':raw.get('query_summary'),'cursor':raw.get('cursor'),'reviews':safe};dump(R/'probes'/f'{name}.json',record)
    print(name,'n',len(safe),'summary',raw.get('query_summary'),'all_in_window',all(start<=x['timestamp_created']<end for x in safe),'minmax',min([x['timestamp_created'] for x in safe],default=0),max([x['timestamp_created'] for x in safe],default=0),flush=True)