add whole new app for balance prediction, replace uwsgi, update everything

core/management/commands/predict_balance.py

@@ -0,0 +1,74 @@
+from datetime import datetime
+from decimal import Decimal
+
+from dateutil.relativedelta import relativedelta
+from django.core.management import BaseCommand
+
+from core.models import Subject
+from core.prediction import predict_transactions
+
+past_lookup_delta = relativedelta(weeks=2)
+future_lookup_delta = relativedelta(months=2)
+
+
+class Command(BaseCommand):
+
+    def add_arguments(self, parser):
+        parser.add_argument(
+            "--start", default="0", help="the current balance to use as a starting point for prediction",
+        )
+
+    def handle(self, *args, **options):
+        start_balance = Decimal(options["start"])
+
+        today = datetime.now().date()
+        past_lookup_bound = today - past_lookup_delta
+        future_lookup_bound = today + future_lookup_delta
+
+        transaction_dict = {}
+        for subject in Subject.objects.all():
+            transactions = []
+            for tr in subject.transactions.order_by("booking_date"):
+                if past_lookup_bound <= tr.booking_date <= future_lookup_bound:
+                    transactions.append(tr)
+            predicted_transaction, prediction_info = predict_transactions(subject)
+            if predicted_transaction:
+                first_predicted_date = predicted_transaction[0].booking_date
+                if first_predicted_date >= past_lookup_bound:
+                    # if two weeks after the first predicted transaction have passed, the subject is considered done
+                    for tr in predicted_transaction:
+                        if past_lookup_bound <= tr.booking_date <= future_lookup_bound:
+                            transactions.append(tr)
+            transaction_dict[subject] = (transactions, prediction_info)
+
+        future_transactions = []
+        for subject, prediction in transaction_dict.items():
+            transactions, info = prediction[0], prediction[1]
+            print(f">>> {subject}")
+            if info:
+                rec_days, rec_months, day_of_month = \
+                    info["recurring_days"], info["recurring_months"], info["day_of_month"]
+                if rec_months and day_of_month:
+                    print(f"~~~ predicted transaction on day-of-month {day_of_month} every {rec_months} month(s)")
+                elif rec_months:
+                    print(f"~~~ predicted transaction every {rec_months} month(s)")
+                elif rec_days:
+                    print(f"~~~ predicted transaction every {rec_days} day(s)")
+            else:
+                print("~~~ no prediction possible")
+            for tr in transactions:
+                print(f"  {tr.booking_date:%d.%m.%Y} | {tr.amount} € | {'stored' if tr.pk else 'predicted'}")
+                if tr.booking_date > today:
+                    future_transactions.append(tr)
+            print()
+
+        current_balance = start_balance
+        print(f"starting calculation with amount {current_balance} €")
+        for tr in sorted(future_transactions, key=lambda t: t.booking_date):
+            current_balance += tr.amount
+            print(
+                f"{tr.booking_date:%d.%m.%Y} | "
+                f"{tr.subject.name:<18} | "
+                f"{tr.amount:>8} €  ==> "
+                f"{current_balance:>8} €"
+            )