GuidoandClaude Opus 4.8
14b3e53685
Bisher wurde eine zweite Buchung mit gleichem Tag/Betrag/Text (z. B. zwei Gutschriften à 324 am selben Tag) fälschlich als Duplikat verworfen. Jetzt gilt eine Zeile nur als Duplikat, wenn bereits GENAU SO VIELE identische Buchungen in der DB stehen – ein erneuter Import derselben Datei bleibt weiterhin Duplikat-sicher. - csv_import.detect_rows: existing/seen als Counter (Multiset) statt Set - Tests angepasst + Re-Import-Test ergänzt; an echtem Raiffeisen-Auszug verifiziert (254 Zeilen, 0 fälschliche Duplikate, Saldo == Bank-Endsaldo) Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
540 lines
21 KiB
Python
540 lines
21 KiB
Python
"""CSV-Import: Datei parsen, Vorschau mit Erkennung (Duplikate, interne Transfers,
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Auto-Kategorisierung), und die eigentliche Verbuchung inkl. Batch für Undo.
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"""
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import csv
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import hashlib
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import io
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import json
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from collections import Counter
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from datetime import date, datetime
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from decimal import Decimal, InvalidOperation, ROUND_HALF_UP
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from sqlalchemy.orm import Session
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from ..models import (
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Account,
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AccountIdentifier,
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AmountMode,
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BudgetTreatment,
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CategorizationRule,
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Category,
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CategoryKind,
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IdentifierKind,
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ImportBatch,
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ImportStatus,
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ImportTemplate,
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MatchField,
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RuleSource,
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SAVINGS_ACCOUNT_TYPES,
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Transaction,
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TxnType,
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User,
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)
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from . import currency
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# Vorgefertigte Bank-Vorlagen (aus echten Export-Beispielen). Erscheinen im
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# Import als auswählbare Presets und füllen die Format-/Spalten-Einstellungen.
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PRESETS: list[dict] = [
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{
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"name": "Raiffeisen (CH)",
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"delimiter": ";",
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"decimal_sep": ".",
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"date_format": "%Y-%m-%d %H:%M:%S.%f",
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"encoding": "utf-8",
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"has_header": True,
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"skip_rows": 0,
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"amount_mode": "signed",
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# Spalten: 0=eigene IBAN, 1=Datum, 2=Text, 3=Betrag, 4=Saldo, 5=Valuta.
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"column_map": {"date": 1, "amount": 3, "payee": 2,
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"purpose": None, "counterparty_iban": None},
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},
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{
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"name": "Revolut",
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"delimiter": ",",
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"decimal_sep": ".",
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"date_format": "%Y-%m-%d %H:%M:%S",
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"encoding": "utf-8",
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"has_header": True,
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"skip_rows": 0,
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"amount_mode": "signed",
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# Spalten: 0=Typ, 1=Produkt, 2=Start, 3=Abgeschlossen, 4=Beschreibung,
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# 5=Betrag, 6=Gebühr, 7=Währung, 8=Status, 9=Saldo.
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"column_map": {"date": 3, "amount": 5, "payee": 4,
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"purpose": None, "counterparty_iban": None},
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},
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]
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# --- Kleine Parser-Helfer --------------------------------------------------
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def normalize_text(s: str | None) -> str:
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return (s or "").strip().lower()
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def normalize_iban(s: str | None) -> str:
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return "".join(ch for ch in (s or "").upper() if ch.isalnum())
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def parse_amount(raw: str | None, decimal_sep: str) -> int | None:
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"""Betragstext -> Cent (mit Vorzeichen). Erkennt Tausender-Trenner und Klammern."""
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s = str(raw or "").strip()
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if not s:
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return None
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neg = ("-" in s) or (s.startswith("(") and s.endswith(")"))
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thousands = "." if decimal_sep == "," else ","
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s2 = s.replace(thousands, "").replace(decimal_sep, ".")
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digits = "".join(ch for ch in s2 if ch.isdigit() or ch == ".")
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if digits in ("", "."):
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return None
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try:
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val = Decimal(digits)
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except InvalidOperation:
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return None
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cents = int((val * 100).to_integral_value(rounding=ROUND_HALF_UP))
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return -cents if neg else cents
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def parse_date(raw: str | None, fmt: str) -> date | None:
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s = str(raw or "").strip()
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if not s:
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return None
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try:
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return datetime.strptime(s, fmt).date()
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except ValueError:
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return None
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def decode_bytes(data: bytes, encoding: str) -> str:
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for enc in (encoding, "utf-8-sig", "utf-8", "latin-1"):
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try:
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return data.decode(enc)
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except (UnicodeDecodeError, LookupError):
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continue
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return data.decode("utf-8", errors="replace")
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def read_rows(data: bytes, template: ImportTemplate) -> list[list[str]]:
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text = decode_bytes(data, template.encoding)
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delim = (template.delimiter or ";")[0]
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reader = csv.reader(io.StringIO(text), delimiter=delim)
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rows = [r for r in reader if any((c or "").strip() for c in r)]
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start = template.skip_rows + (1 if template.has_header else 0)
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return rows[start:]
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def preview_raw(data: bytes, template: ImportTemplate, limit: int = 8) -> dict:
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"""Rohe erste Zeilen (zum Spalten-Zuordnen im Template-Editor)."""
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text = decode_bytes(data, template.encoding)
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delim = (template.delimiter or ";")[0]
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reader = csv.reader(io.StringIO(text), delimiter=delim)
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rows = [r for r in reader if any((c or "").strip() for c in r)]
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header = None
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body_start = template.skip_rows
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if template.has_header and len(rows) > body_start:
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header = rows[body_start]
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body_start += 1
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return {"header": header, "rows": rows[body_start: body_start + limit]}
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def import_hash(account_id: int, d: date | None, amount_cents: int | None, payee: str | None) -> str:
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key = f"{account_id}|{d}|{amount_cents}|{normalize_text(payee)}"
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return hashlib.sha256(key.encode("utf-8")).hexdigest()
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# --- Vorschau --------------------------------------------------------------
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def _rule_sort_key(rule: CategorizationRule) -> tuple:
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"""Reihenfolge der Regelanwendung: Betrags-Regeln (spezifischer) zuerst, dann
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längstes Schlagwort, dann manuelle vor gelernten, dann Priorität/Treffer."""
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return (
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1 if rule.amount_cents is not None else 0,
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len(rule.pattern or ""),
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1 if rule.source == RuleSource.manual else 0,
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rule.priority,
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rule.hits,
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)
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def _pattern_hit(rule: CategorizationRule, p: str, z: str) -> bool:
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if rule.match_field == MatchField.payee:
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return rule.pattern in p
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if rule.match_field == MatchField.purpose:
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return rule.pattern in z
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return rule.pattern in p or rule.pattern in z # any: Empfänger ODER Zweck
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def _match_rule(
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rules: list[CategorizationRule],
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payee: str,
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purpose: str,
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amount: int | None,
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allowed_kind: CategoryKind | None,
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cat_kind: dict[int, CategoryKind],
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) -> CategorizationRule | None:
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"""Erste passende Regel (Muster + optionale Betragsbedingung). Kategorie-Regeln
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greifen nur, wenn die Kategorie-Art (Einnahme/Ausgabe) zur Buchung passt;
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Transfer-Regeln kennen keine Art."""
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p = normalize_text(payee)
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z = normalize_text(purpose)
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absamt = abs(amount) if amount is not None else None
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for rule in rules: # bereits sortiert (Betrag/längstes/manuell zuerst)
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if not rule.pattern:
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continue
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if rule.amount_cents is not None and (absamt is None or absamt != rule.amount_cents):
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continue
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if rule.is_transfer:
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if _pattern_hit(rule, p, z):
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return rule
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continue
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if not rule.category_id:
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continue
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if allowed_kind is not None and cat_kind.get(rule.category_id) != allowed_kind:
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continue
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if _pattern_hit(rule, p, z):
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return rule
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return None
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def _guess_target_account(text_idents: list[tuple[str, int]], payee: str, purpose: str, source_id: int) -> int | None:
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"""Zielkonto eines Transfers aus dem Buchungstext raten: längster passender
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Erkennungs-Text je Konto gewinnt."""
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hay = f"{normalize_text(payee)} {normalize_text(purpose)}"
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best: tuple[int, int] | None = None # (Länge, Konto-ID)
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for val, acc_id in text_idents:
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if val and acc_id != source_id and val in hay and (best is None or len(val) > best[0]):
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best = (len(val), acc_id)
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return best[1] if best else None
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# Fenster, in dem eine Buchung als Gegenseite eines bestehenden Transfers gilt
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# (Buchungs-/Valutadatum können ein paar Tage auseinanderliegen).
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COUNTERPART_DAYS = 5
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def _is_counterpart(transfer_index: dict, account_id: int, other_id: int, d: date, amount: int) -> bool:
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"""True, wenn schon ein Transfer zwischen denselben Konten existiert, dessen
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Betrag (Soll- oder Haben-Seite) zu dieser Buchung passt – dann ist es die
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bereits gebuchte Gegenseite und darf nicht erneut zählen."""
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absamt = abs(amount)
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for t_date, amt, to_amt in transfer_index.get(frozenset((account_id, other_id)), []):
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if abs((t_date - d).days) <= COUNTERPART_DAYS and absamt in (amt, to_amt):
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return True
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return False
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def parse_file_to_candidates(data: bytes, template: ImportTemplate) -> list[dict]:
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"""Zerlegt die Datei anhand des Templates in rohe Kandidaten-Zeilen."""
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cmap = json.loads(template.column_map or "{}")
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def col(field: str) -> int | None:
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idx = cmap.get(field)
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return idx if isinstance(idx, int) and idx >= 0 else None
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out: list[dict] = []
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for r in read_rows(data, template):
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def cell(field: str) -> str:
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c = col(field)
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return r[c].strip() if c is not None and c < len(r) else ""
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d = parse_date(cell("date"), template.date_format)
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if template.amount_mode == AmountMode.debit_credit:
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debit = parse_amount(cell("debit"), template.decimal_sep)
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credit = parse_amount(cell("credit"), template.decimal_sep)
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amount = (credit or 0) - (abs(debit) if debit else 0)
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elif template.amount_mode == AmountMode.abs_expense:
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a = parse_amount(cell("amount"), template.decimal_sep)
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amount = -abs(a) if a is not None else None
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else:
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amount = parse_amount(cell("amount"), template.decimal_sep)
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out.append({
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"date": d.isoformat() if d else None,
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"amount_cents": amount,
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"payee": cell("payee") or None,
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"purpose": cell("purpose") or None,
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"counterparty_iban": normalize_iban(cell("counterparty_iban")) or None,
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})
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return out
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def detect_rows(db: Session, user: User, account: Account, candidates: list[dict]) -> list[dict]:
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"""Reichert Kandidaten an: Typ, Auto-Kategorie, interner Transfer, Duplikat.
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Wird von CSV- UND Beleg-Import genutzt (gleiche Prüf-/Buchungslogik)."""
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idents: dict[str, int] = {} # IBAN/Nummer -> Konto (für Transfer via IBAN)
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text_idents: list[tuple[str, int]] = [] # freie Erkennungs-Texte -> Konto
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for value_norm, acc_id, kind in (
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db.query(AccountIdentifier.value_norm, AccountIdentifier.account_id, AccountIdentifier.kind)
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.join(Account, Account.id == AccountIdentifier.account_id)
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.filter(Account.owner_id == user.id)
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):
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if kind == IdentifierKind.text:
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text_idents.append((value_norm, acc_id))
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else:
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idents[value_norm] = acc_id
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rules = db.query(CategorizationRule).filter(CategorizationRule.owner_id == user.id).all()
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rules.sort(key=_rule_sort_key, reverse=True) # längstes/manuell zuerst
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cat_kind: dict[int, CategoryKind] = {
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cid: kind
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for cid, kind in db.query(Category.id, Category.type).filter(Category.owner_id == user.id)
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}
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# Duplikate als Multiset zählen: eine Zeile gilt nur dann als Duplikat, wenn
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# bereits GENAU SO VIELE identische Buchungen in der DB stehen. So werden echte,
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# gleich aussehende Buchungen desselben Tags (z. B. zwei Gutschriften über 324)
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# behalten, ein erneuter Import derselben Datei aber weiter erkannt.
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existing: Counter = Counter(
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h[0]
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for h in db.query(Transaction.import_hash).filter(
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Transaction.owner_id == user.id, Transaction.import_hash.isnot(None)
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)
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)
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# Bestehende Transfers je Konto-Paar: erkennt die Gegenbuchung, wenn beide
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# Auszüge eines Übertrags importiert werden (sonst zählt die Bewegung doppelt).
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transfer_index: dict[frozenset, list[tuple]] = {}
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for t_acc, t_to, t_date, t_amt, t_to_amt in (
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db.query(Transaction.account_id, Transaction.to_account_id, Transaction.date,
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Transaction.amount_cents, Transaction.to_amount_cents)
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.filter(Transaction.owner_id == user.id, Transaction.type == TxnType.transfer,
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Transaction.to_account_id.isnot(None))
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):
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transfer_index.setdefault(frozenset((t_acc, t_to)), []).append(
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(t_date, t_amt, t_to_amt if t_to_amt is not None else t_amt)
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)
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seen: Counter = Counter()
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out: list[dict] = []
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for i, cand in enumerate(candidates):
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d_iso = cand.get("date")
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amount = cand.get("amount_cents")
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payee = cand.get("payee")
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purpose = cand.get("purpose")
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iban = cand.get("counterparty_iban")
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d = date.fromisoformat(d_iso) if d_iso else None
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valid = d is not None and amount is not None and amount != 0
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ttype = "expense" if (amount or 0) < 0 else "income"
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category_id: int | None = None
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matched_rule_id: int | None = None
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to_account_id: int | None = None
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other = idents.get(iban) if iban else None
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if other is None:
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# Symmetrisch: enthält der Text den Erkennungs-Text eines ANDEREN
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# Kontos, ist es ein Transfer von/zu diesem Konto (auch Eingänge).
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other = _guess_target_account(text_idents, payee or "", purpose or "", account.id)
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if other is not None and other != account.id:
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ttype = "transfer"
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to_account_id = other
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else:
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kind = CategoryKind.expense if ttype == "expense" else CategoryKind.income
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rule = _match_rule(rules, payee or "", purpose or "", amount, kind, cat_kind)
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if rule is not None:
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matched_rule_id = rule.id
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if rule.is_transfer:
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ttype = "transfer"
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# Festes Zielkonto der Regel bevorzugen, sonst aus dem Text raten.
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if rule.target_account_id and rule.target_account_id != account.id:
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to_account_id = rule.target_account_id
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else:
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to_account_id = _guess_target_account(text_idents, payee or "", purpose or "", account.id)
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else:
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category_id = rule.category_id
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h = import_hash(account.id, d, amount, payee)
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is_dup = seen[h] < existing[h] # nur so viele Duplikate wie schon in der DB
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seen[h] += 1
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# Gegenbuchung eines bereits gebuchten Transfers? Dann nicht erneut buchen.
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is_counterpart = (
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ttype == "transfer" and to_account_id is not None
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and d is not None and amount is not None
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and _is_counterpart(transfer_index, account.id, to_account_id, d, amount)
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)
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out.append({
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"index": i,
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"date": d.isoformat() if d else None,
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"amount_cents": amount,
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"payee": payee or None,
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"purpose": purpose or None,
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"counterparty_iban": iban or None,
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"valid": valid,
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"type": ttype,
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"category_id": category_id,
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"matched_rule_id": matched_rule_id,
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"to_account_id": to_account_id,
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"import_hash": h,
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"is_duplicate": is_dup,
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"is_counterpart": is_counterpart,
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"include": valid and not is_dup and not is_counterpart,
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})
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return out
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def build_preview(db: Session, user: User, account: Account, template: ImportTemplate, data: bytes) -> list[dict]:
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return detect_rows(db, user, account, parse_file_to_candidates(data, template))
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# --- Verbuchen -------------------------------------------------------------
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def _make_transaction(db: Session, user: User, account: Account, accounts: dict[int, Account], row: dict, batch_id: int) -> Transaction | None:
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d = date.fromisoformat(row["date"]) if row.get("date") else None
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amount = row.get("amount_cents")
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if d is None or not amount:
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return None
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ttype = row.get("type") or ("expense" if amount < 0 else "income")
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payee = row.get("payee")
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purpose = row.get("purpose")
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notes = None
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if ttype == "transfer":
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other_id = row.get("to_account_id")
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other = accounts.get(other_id) if other_id else None
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if other is None:
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ttype = "expense" if amount < 0 else "income" # Fallback ohne Zielkonto
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if ttype == "transfer":
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other = accounts[row["to_account_id"]]
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mag = abs(amount)
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if amount < 0:
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from_acc, to_acc = account, other
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from_amount = mag # in Kontowährung (bekannt aus dem Auszug)
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else:
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from_acc, to_acc = other, account
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# from-Betrag in der Währung des anderen Kontos schätzen.
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conv = currency.convert(db, mag, account.currency, from_acc.currency, d)
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from_amount = conv if conv is not None else mag
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to_amount = mag if amount < 0 else mag
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# Konsistente to_amount-Berechnung:
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if from_acc.currency == to_acc.currency:
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to_amount = from_amount
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else:
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conv = currency.convert(db, from_amount, from_acc.currency, to_acc.currency, d)
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to_amount = conv if conv is not None else from_amount
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# Sparen/Depot-Ziel budgetieren (überschreibbar über row["budget_treatment"]).
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treatment = row.get("budget_treatment")
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budget_cat = row.get("budget_category_id")
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txn = Transaction(
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owner_id=user.id, type=TxnType.transfer, date=d,
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account_id=from_acc.id, to_account_id=to_acc.id,
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amount_cents=from_amount, to_amount_cents=to_amount,
|
||
amount_eur_cents=currency.compute_amount_eur_cents(db, from_amount, from_acc.currency, d),
|
||
budget_treatment=BudgetTreatment(treatment) if treatment in ("budgeted", "neutral") else None,
|
||
budget_category_id=budget_cat,
|
||
description=purpose, payee=payee, notes=notes,
|
||
import_batch_id=batch_id, import_hash=row.get("import_hash"),
|
||
)
|
||
return txn
|
||
|
||
mag = abs(amount)
|
||
txn = Transaction(
|
||
owner_id=user.id,
|
||
type=TxnType.expense if ttype == "expense" else TxnType.income,
|
||
date=d, account_id=account.id, amount_cents=mag,
|
||
amount_eur_cents=currency.compute_amount_eur_cents(db, mag, account.currency, d),
|
||
category_id=row.get("category_id"),
|
||
payee=payee, description=purpose, notes=notes,
|
||
import_batch_id=batch_id, import_hash=row.get("import_hash"),
|
||
)
|
||
return txn
|
||
|
||
|
||
def _learn_rule(db: Session, user: User, row: dict) -> None:
|
||
"""Merkt sich Empfänger -> Kategorie für künftige Importe."""
|
||
cat = row.get("category_id")
|
||
payee = row.get("payee")
|
||
if not cat or not payee or row.get("type") == "transfer":
|
||
return
|
||
pattern = normalize_text(payee)[:255]
|
||
if not pattern:
|
||
return
|
||
# Art der gelernten Regel = Art der Kategorie (Einnahme/Ausgabe). Gehört zur
|
||
# Eindeutigkeit (owner, feld, wort, kind), damit dasselbe Wort je Art zählt.
|
||
ckind = db.query(Category.type).filter(
|
||
Category.id == cat, Category.owner_id == user.id
|
||
).scalar()
|
||
kind = ckind.value if ckind is not None else "expense"
|
||
existing = (
|
||
db.query(CategorizationRule)
|
||
.filter(
|
||
CategorizationRule.owner_id == user.id,
|
||
CategorizationRule.match_field == MatchField.payee,
|
||
CategorizationRule.pattern == pattern,
|
||
CategorizationRule.kind == kind,
|
||
)
|
||
.first()
|
||
)
|
||
if existing is None:
|
||
db.add(CategorizationRule(
|
||
owner_id=user.id, match_field=MatchField.payee, pattern=pattern,
|
||
category_id=cat, kind=kind, source=RuleSource.learned, priority=1, hits=1,
|
||
))
|
||
# Sichtbar machen (Session ist autoflush=False), damit dasselbe Muster ein
|
||
# zweites Mal im selben Import die vorhandene Regel findet statt zu doppeln.
|
||
db.flush()
|
||
else:
|
||
existing.category_id = cat
|
||
existing.hits += 1
|
||
|
||
|
||
def _track_and_learn(db: Session, user: User, row: dict) -> None:
|
||
"""Zählt für die zutreffende Regel Anwendung/Korrektur (Basis fürs Flaggen von
|
||
Schlagwörtern) und lernt anschließend Empfänger -> Kategorie weiter."""
|
||
rid = row.get("matched_rule_id")
|
||
final_cat = row.get("category_id")
|
||
matched_manual_kept = False
|
||
if rid:
|
||
rule = db.get(CategorizationRule, rid)
|
||
if rule is not None and rule.owner_id == user.id:
|
||
rule.applied_count = (rule.applied_count or 0) + 1
|
||
if final_cat != rule.category_id:
|
||
rule.overridden_count = (rule.overridden_count or 0) + 1
|
||
elif rule.source == RuleSource.manual:
|
||
matched_manual_kept = True # Schlagwort greift schon – nicht doppelt lernen
|
||
if not matched_manual_kept:
|
||
_learn_rule(db, user, row)
|
||
|
||
|
||
def commit_import(db: Session, user: User, account: Account, template_id: int | None, filename: str, rows: list[dict]) -> ImportBatch:
|
||
accounts = {a.id: a for a in db.query(Account).filter(Account.owner_id == user.id)}
|
||
batch = ImportBatch(
|
||
owner_id=user.id, account_id=account.id, template_id=template_id,
|
||
filename=(filename or "")[:255], row_count=len(rows),
|
||
imported_count=0, status=ImportStatus.committed,
|
||
)
|
||
db.add(batch)
|
||
db.flush()
|
||
|
||
imported = 0
|
||
for row in rows:
|
||
if not row.get("include", True):
|
||
continue
|
||
txn = _make_transaction(db, user, account, accounts, row, batch.id)
|
||
if txn is None:
|
||
continue
|
||
db.add(txn)
|
||
_track_and_learn(db, user, row)
|
||
imported += 1
|
||
|
||
batch.imported_count = imported
|
||
db.commit()
|
||
db.refresh(batch)
|
||
return batch
|
||
|
||
|
||
def undo_batch(db: Session, user: User, batch: ImportBatch) -> int:
|
||
n = (
|
||
db.query(Transaction)
|
||
.filter(Transaction.owner_id == user.id, Transaction.import_batch_id == batch.id)
|
||
.delete()
|
||
)
|
||
batch.status = ImportStatus.undone
|
||
db.commit()
|
||
return n
|