# payments/management/commands/find_users_with_duplicate_wallet_credits.py from __future__ import annotations from datetime import datetime, date, time, timedelta from typing import Optional from django.core.management.base import BaseCommand, CommandError from django.db.models import Count from django.utils import timezone try: from zoneinfo import ZoneInfo # Python 3.9+ except Exception: # pragma: no cover ZoneInfo = None # type: ignore def local_day_window_utc(target_date: date, tz) -> tuple[datetime, datetime]: start_local = datetime.combine(target_date, time.min).replace(tzinfo=tz) end_local = start_local + timedelta(days=1) return (start_local.astimezone(timezone.utc), end_local.astimezone(timezone.utc)) class Command(BaseCommand): help = ( "Find users whose wallet has SAME-DAY duplicate CREDIT usages.\n" "Duplicates = same local DATE + transaction_type='credit' + amount_used + purpose + purpose_note (order_id ignored).\n" "Prints mobile numbers and duplicate groups per day. Use --csv to export." ) def add_arguments(self, parser): parser.add_argument( "--date", dest="on_date", help="Target local date YYYY-MM-DD. (Use either --date OR a range with --from/--to)", ) parser.add_argument("--from", dest="date_from", help="Start local date YYYY-MM-DD (inclusive)") parser.add_argument("--to", dest="date_to", help="End local date YYYY-MM-DD (inclusive)") parser.add_argument( "--tz", dest="tzname", default=None, help="IANA timezone for local day (e.g. Asia/Kolkata). Defaults to Django's current timezone.", ) parser.add_argument( "--min", dest="min_count", type=int, default=2, help="Minimum duplicates threshold per group (default: 2)", ) parser.add_argument( "--csv", dest="csv_path", help="Optional CSV output path", ) def handle(self, *args, **opts): from payments.models import ViralPeWalletUsage # local import from accounts.models import User on_date = opts.get("on_date") date_from = opts.get("date_from") date_to = opts.get("date_to") min_count: int = opts.get("min_count") or 2 csv_path: Optional[str] = opts.get("csv_path") # Resolve timezone tzname: Optional[str] = opts.get("tzname") if tzname: if ZoneInfo is None: raise CommandError("zoneinfo not available; remove --tz or upgrade Python (3.9+).") tz = ZoneInfo(tzname) # type: ignore[arg-type] else: tz = timezone.get_current_timezone() # Parse dates if on_date and (date_from or date_to): raise CommandError("Use either --date OR (--from and --to), not both.") if on_date: try: d = datetime.strptime(on_date, "%Y-%m-%d").date() except ValueError: raise CommandError("Invalid --date. Use YYYY-MM-DD.") days = [d] else: if not date_from or not date_to: raise CommandError("Provide both --from and --to for a range (YYYY-MM-DD).") try: d1 = datetime.strptime(date_from, "%Y-%m-%d").date() d2 = datetime.strptime(date_to, "%Y-%m-%d").date() except ValueError: raise CommandError("Invalid --from/--to. Use YYYY-MM-DD.") if d2 < d1: raise CommandError("--to cannot be earlier than --from.") # build inclusive date list days = [] cur = d1 while cur <= d2: days.append(cur) cur += timedelta(days=1) # CSV init writer = None f = None if csv_path: import csv f = open(csv_path, "w", newline="", encoding="utf-8") writer = csv.writer(f) writer.writerow([ "local_date", "mobile_number", "user_id", "amount_used", "purpose", "purpose_note", "records", "sample_ids", ]) total_groups = 0 users_with_dupes = set() self.stdout.write( f"Scanning {len(days)} day(s) in timezone {tz} with duplicate threshold >= {min_count}\n" ) for target_date in days: start_utc, end_utc = local_day_window_utc(target_date, tz) # Constrain to the local day's UTC window base_qs = ViralPeWalletUsage.objects.filter( transaction_type="credit", used_on__gte=start_utc, used_on__lt=end_utc, ) # Group by user + duplicate keys (order_id intentionally ignored) dup_groups = ( base_qs.values( "user_id", "user__mobile_number", "amount_used", "purpose", "purpose_note", ) .annotate(n=Count("id")) .filter(n__gte=min_count) ) day_groups = dup_groups.count() if day_groups == 0: continue self.stdout.write(f"Date {target_date}: found {day_groups} duplicate group(s)") total_groups += day_groups # For each group, print details + sample IDs for g in dup_groups: uid = g["user_id"] mobile = g["user__mobile_number"] amount = g["amount_used"] purpose = g["purpose"] pnote = g["purpose_note"] n = g["n"] # fetch a few sample IDs for debugging/verification sample_ids = list( base_qs.filter( user_id=uid, amount_used=amount, purpose=purpose, purpose_note=pnote, ) .order_by("used_on", "id") .values_list("id", flat=True)[:10] ) users_with_dupes.add((uid, mobile)) msg = ( f" {mobile} (user_id={uid}) -> x{n} " f"amount={amount} purpose={purpose!r} note={pnote!r} sample_ids={sample_ids}" ) self.stdout.write(msg) if writer: writer.writerow([ target_date, mobile, uid, amount, purpose, pnote, n, " ".join(map(str, sample_ids)), ]) # Summary self.stdout.write("\n=== Summary ===") self.stdout.write(f"Total duplicate groups: {total_groups}") self.stdout.write(f"Unique users with duplicates: {len(users_with_dupes)}") if users_with_dupes: mobiles = sorted({m for (_uid, m) in users_with_dupes}) self.stdout.write("Mobiles: " + ", ".join(mobiles)) if writer: f.close() self.stdout.write(f"\nCSV written to: {csv_path}") # Examples # Single date (Oct 24 IST): # python manage.py find_users_with_duplicate_wallet_credits --date 2025-10-24 --tz Asia/Kolkata # Date range (the last 7 days): # python manage.py find_users_with_duplicate_wallet_credits --from 2025-10-18 --to 2025-10-24 --tz Asia/Kolkata # Require 3+ duplicates per group (stricter): # python manage.py find_users_with_duplicate_wallet_credits --date 2025-10-24 --min 3 --tz Asia/Kolkata # Export to CSV: # python manage.py find_users_with_duplicate_wallet_credits --date 2025-10-24 --tz Asia/Kolkata --csv /tmp/dupe_cred