feat: Phase 5 – PDF/Bild-Beleg-Import (lokal, Tesseract-OCR)
Backend: - services/ocr: PDF-Text via PyMuPDF, OCR (Tesseract) für Scans/Bilder, heuristischer Parser (Datum + Betrag je Zeile, CH/DE/US-Beträge). - routers/documents: /documents/preview (Upload -> Text -> Kandidaten -> gemeinsame Prüf-/Buchungslogik des CSV-Imports). csv_import refaktoriert: detect_rows() von CSV und Beleg gemeinsam genutzt. - requirements: PyMuPDF, pytesseract, pillow; install.sh installiert tesseract-ocr (+ deu). pytest: Heuristik-Parser und PDF-Vorschau. Frontend: - Import-Seite: CSV/PDF-Umschalter; PDF-Modus mit Beleg-Auslesen, extrahiertem Text zur Kontrolle und Best-Effort-Hinweis; gleiche Prüfansicht + Buchen. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
This commit is contained in:
Guido
Claude Opus 4.8
@@ -24,6 +24,7 @@ from .routers import (
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budgets,
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categories,
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dashboard,
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documents,
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imports,
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rates,
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settings as settings_router,
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@@ -105,6 +106,7 @@ api.include_router(transactions.router)
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api.include_router(budgets.router)
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api.include_router(dashboard.router)
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api.include_router(imports.router)
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api.include_router(documents.router)
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api.include_router(rates.router)
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app.include_router(api)
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@@ -0,0 +1,34 @@
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"""PDF-/Bild-Beleg-Import (Phase 5, lokal). Nutzt die Prüf-/Buchungslogik des CSV-Imports."""
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from fastapi import APIRouter, Depends, File, Form, HTTPException, UploadFile
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from sqlalchemy.orm import Session
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from ..database import get_db
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from ..deps import get_current_user, get_owned
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from ..models import Account, User
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from ..services import csv_import, ocr
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router = APIRouter(prefix="/documents", tags=["documents"])
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@router.post("/preview")
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async def preview(
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file: UploadFile = File(...),
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account_id: int = Form(...),
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db: Session = Depends(get_db),
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user: User = Depends(get_current_user),
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) -> dict:
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account = get_owned(db, Account, account_id, user)
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data = await file.read()
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try:
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text = ocr.extract_text(data, file.filename or "", file.content_type or "")
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except ocr.ExtractionError as exc:
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raise HTTPException(status_code=400, detail=str(exc))
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candidates = ocr.parse_transactions(text)
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rows = csv_import.detect_rows(db, user, account, candidates)
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return {
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"rows": rows,
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"text": text[:8000],
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"count": len(rows),
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"filename": file.filename or "",
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}
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@@ -153,16 +153,45 @@ def _apply_rules(rules: list[CategorizationRule], payee: str, purpose: str) -> i
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return None
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def build_preview(db: Session, user: User, account: Account, template: ImportTemplate, data: bytes) -> list[dict]:
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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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rows = read_rows(data, template)
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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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# Identifikatoren aller Konten des Nutzers -> Konto-ID (für Transfer-Erkennung).
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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] = {}
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for value_norm, acc_id in (
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db.query(AccountIdentifier.value_norm, AccountIdentifier.account_id)
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@@ -177,39 +206,25 @@ def build_preview(db: Session, user: User, account: Account, template: ImportTem
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.order_by(CategorizationRule.priority.desc(), CategorizationRule.hits.desc())
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.all()
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)
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existing = {
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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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seen_in_file: set[str] = set()
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seen: set[str] = set()
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out: list[dict] = []
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for i, r in enumerate(rows):
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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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payee = cell("payee")
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purpose = cell("purpose")
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iban = normalize_iban(cell("counterparty_iban"))
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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 = "transfer" if False else ("expense" if (amount or 0) < 0 else "income")
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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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to_account_id: int | None = None
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@@ -218,11 +233,11 @@ def build_preview(db: Session, user: User, account: Account, template: ImportTem
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ttype = "transfer"
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to_account_id = other
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else:
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category_id = _apply_rules(rules, payee, purpose)
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category_id = _apply_rules(rules, payee or "", purpose or "")
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h = import_hash(account.id, d, amount, payee)
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is_dup = h in existing or h in seen_in_file
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seen_in_file.add(h)
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is_dup = h in existing or h in seen
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seen.add(h)
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out.append({
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"index": i,
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@@ -242,6 +257,10 @@ def build_preview(db: Session, user: User, account: Account, template: ImportTem
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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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@@ -0,0 +1,127 @@
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"""PDF-/Bild-Belege lokal auslesen (kein Cloud-Dienst).
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- Digitale PDFs: Text direkt via PyMuPDF.
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- Gescannte PDFs / Bilder: OCR via Tesseract (pytesseract).
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Danach ein heuristischer Parser, der Zeilen mit Datum + Betrag findet. Das ist
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bewusst Best-Effort – das Ergebnis landet in derselben Prüfansicht wie der
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CSV-Import und wird dort korrigiert.
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"""
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import io
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import re
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from datetime import datetime
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from decimal import Decimal, InvalidOperation
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try: # PyMuPDF (Text + Rendern)
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import fitz # type: ignore
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except Exception: # noqa: BLE001
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fitz = None
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try: # OCR
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import pytesseract # type: ignore
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from PIL import Image # type: ignore
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except Exception: # noqa: BLE001
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pytesseract = None
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Image = None
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class ExtractionError(RuntimeError):
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pass
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def _image_to_text(data: bytes) -> str:
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if pytesseract is None or Image is None:
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raise ExtractionError("OCR nicht verfügbar (pytesseract/Pillow/Tesseract fehlen).")
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img = Image.open(io.BytesIO(data))
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return pytesseract.image_to_string(img, lang="deu+eng")
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def _pdf_to_text(data: bytes) -> str:
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if fitz is None:
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raise ExtractionError("PDF-Verarbeitung nicht verfügbar (PyMuPDF fehlt).")
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parts: list[str] = []
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with fitz.open(stream=data, filetype="pdf") as doc:
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for page in doc:
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txt = page.get_text()
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if txt and txt.strip():
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parts.append(txt)
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elif pytesseract is not None and Image is not None:
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pix = page.get_pixmap(dpi=200)
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img = Image.open(io.BytesIO(pix.tobytes("png")))
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parts.append(pytesseract.image_to_string(img, lang="deu+eng"))
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return "\n".join(parts)
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def extract_text(data: bytes, filename: str, content_type: str) -> str:
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name = (filename or "").lower()
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if name.endswith(".pdf") or content_type == "application/pdf":
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return _pdf_to_text(data)
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return _image_to_text(data)
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# --- Heuristischer Zeilen-Parser -------------------------------------------
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DATE_RE = re.compile(r"\b(\d{4}-\d{2}-\d{2}|\d{1,2}[./]\d{1,2}[./]\d{2,4})\b")
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# Betrag: entweder mit Tausender-Gruppen (1'234.56 / 1.234,56) oder schlicht (3000.00).
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AMOUNT_RE = re.compile(r"[-+]?(?:\d{1,3}(?:['.,\s]\d{3})+|\d+)[.,]\d{2}(?!\d)")
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_DATE_FORMATS = ["%Y-%m-%d", "%d.%m.%Y", "%d.%m.%y", "%d/%m/%Y", "%d/%m/%y"]
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def _norm_date(token: str):
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for fmt in _DATE_FORMATS:
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try:
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return datetime.strptime(token, fmt).date()
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except ValueError:
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continue
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return None
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def _parse_amount_auto(s: str) -> int | None:
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"""Betrag mit automatisch erkanntem Dezimaltrenner (CH/DE/US) -> Cent."""
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s = s.strip()
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neg = s.startswith("-") or (s.startswith("(") and s.endswith(")"))
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m = re.search(r"[.,](\d{2})$", s)
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if not m:
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return None
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int_digits = re.sub(r"\D", "", s[: m.start()])
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frac = m.group(1)
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try:
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val = Decimal(f"{int_digits or '0'}.{frac}")
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except InvalidOperation:
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return None
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cents = int(val * 100)
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return -cents if neg else cents
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def parse_transactions(text: str) -> list[dict]:
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"""Findet Zeilen mit Datum + Betrag und macht daraus Kandidaten-Buchungen."""
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rows: list[dict] = []
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for line in text.splitlines():
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line = line.strip()
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if len(line) < 6:
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continue
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dm = DATE_RE.search(line)
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if not dm:
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continue
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d = _norm_date(dm.group(0))
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if d is None:
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continue
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rest = f"{line[: dm.start()]} {line[dm.end():]}"
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amounts = AMOUNT_RE.findall(rest)
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if not amounts:
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continue
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amount = _parse_amount_auto(amounts[0])
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if amount is None or amount == 0:
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continue
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desc = rest
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for a in amounts:
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desc = desc.replace(a, " ")
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desc = re.sub(r"\s+", " ", desc).strip(" -–|;,.")
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rows.append({
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"date": d.isoformat(),
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"amount_cents": amount,
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"payee": desc[:120] or None,
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"purpose": None,
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"counterparty_iban": None,
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})
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return rows
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