feat(import): Abgabeverträge (DOCX) auswerten und Tiere/Kontakte anreichern

Neuer Parser extract_contracts.py liest die ~1,4k Abgabevertrags-DOCX
(\truenas\…\Verträge): er extrahiert aus dem Dokument-Body (zuverlässiger als
die Dateinamen) Käufer, Tier(e), Farbschlag, Abgabedatum und Preis — robust
gegen Word-Run-Splits (z. B. „F r au"/„3 0,00"); überspringt Vorlage,
Abstammungsnachweise und als .docx getarnte .doc.

enrich_from_contracts() in merge_and_resolve.py: Käufer werden als Kontakte
(IsReceiver) angelegt/zusammengeführt; Tiere werden KONSERVATIV per Rufname
(+ DOB-Jahr bei Mehrdeutigkeit) auf eigene Bestandstiere gematcht und erhalten
ReceiverContactId, GoHomeDate und Status „abgegeben" — nur wo nicht bereits
gesetzt; Konflikte werden geloggt, nicht überschrieben. Jede Übernahme bekommt
eine Herkunfts-Zeile („Abgabe an … aus Vertrag … übernommen.").

Ergebnis: 1095 Verträge → 783 Tier-Treffer (400 mehrdeutige übersprungen),
274 neue Abnehmer-Kontakte, 153 Tiere mit Abnehmer, 49 mit Abgabedatum,
23 neu „abgegeben". Keine Backend-/Frontend-Änderung nötig (Akte zeigt Abnehmer/
Abgabedatum/Herkunft bereits). SaleContract-Records bewusst nicht erzeugt
(bräuchte Migration + ingest-sichere Id — späterer Schritt).

Tests: test_extract_contracts.py (Dateiname/Body/Run-Split/Skip-Regeln) + alle
bestehenden grün; dotnet 212.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>

tools/import/extract_contracts.py

@@ -0,0 +1,446 @@
+#!/usr/bin/env python3
+"""FEAT-Contracts Stage 1 — Abgabeverträge (.docx) extrahieren.
+
+Liest die Sammlung der Vermittlungs-/Abgabeverträge ("Zucht der kleinen
+Chaoten _ … (Tier.Namen) - <Käufer>_.docx") vom Netzlaufwerk und erzeugt:
+  output/contracts.json  — strukturierte Vertrags-Datensätze
+
+Reines stdlib-Python (kein pip), nach Vorbild von extract_docx.py: .docx ist
+ein ZIP mit word/document.xml; daraus werden die "Label: Wert"-Zeilen des
+Vertragskörpers gelesen. Der Dateiname dient als Zusatz-Signal für die
+Tier-Rufnamen und den Farbschlag, wenn der Körper sie nicht hergibt.
+
+Zuverlässig extrahierbar (beobachtete Abdeckung über 250er-Stichprobe):
+  Name (Tier):     100 %   — Body-Label "Name:"
+  Geschlecht:      100 %   — Body-Label "Geschlecht:"
+  Geburtsdatum:     98 %   — Body-Label "Geburtsdatum:"
+  Abgabedatum:      78 %   — Body-Label "Abgabedatum:"
+  Preis:            78 %   — "Gesamtpreis/Schutzgebühr/Kaufpreis"
+  Käufer (Body):    79 %   — Block "Abnehmer/Empfänger" → "Name:"
+  Farbschlag(Body): 13 %   — Body-Label "Farbschlag:" (oft im Dateinamen)
+
+Übersprungen werden:
+  * die Vorlage  "Vertrags mustter new.docx"
+  * Abstammungsnachweise / Geburtsurkunden (kein Verkauf, eigener Doc-Typ)
+  * Dateien, die kein lesbares ZIP sind (alte .doc als .docx getarnt)
+
+Ausführung: python extract_contracts.py [--dir PFAD] [--limit N]
+Idempotent: mehrfaches Ausführen überschreibt output/contracts.json.
+"""
+import os
+import re
+import sys
+import json
+import zipfile
+import argparse
+
+HERE = os.path.dirname(os.path.abspath(__file__))
+DEFAULT_DIR = r"\\truenas\Datengrab\Rennmäuse\Verträge"
+OUT = os.path.join(HERE, "output")
+
+TEMPLATE_MARKERS = ("mustter", "muster new")
+# Doc types that are NOT sale contracts (skip):
+NON_CONTRACT_MARKERS = ("Abstammungsnachweis", "Geburtsurkunde")
+
+# --- Body label regexes (work on whitespace-collapsed plain text) ----------
+# Generic "Label: value up to next known label or end".
+_KNOWN_LABELS = (
+    r"Name|Geburtsdatum|Geschlecht|Farbschlag|Farbe|Abgabedatum|Abgabe\s*am|"
+    r"Gesamtpreis|Schutzgeb\w+|Kaufpreis|Preis|Zuchtname|Zuchtbuchnummer|"
+    r"Stra\w+e|Wohnort|Fon|Festnetz|Handy|Handynummer|Telefon|E-?Mail|Homepage|"
+    r"Facebook|Mutter|Vater|Linie|Wurf|Bemerkung|Z\w+chter\w*|Abnehmer|Empf\w+nger"
+)
+
+
+def _norm_date(d: str) -> str:
+    """German DD.MM.YY[YY] → ISO YYYY-MM-DD (or '' if unparseable)."""
+    if not d:
+        return ""
+    m = re.search(r"(\d{1,2})\.(\d{1,2})\.(\d{2,4})", d)
+    if not m:
+        return ""
+    day, mon, yr = m.group(1), m.group(2), m.group(3)
+    if len(yr) == 2:
+        yr = "20" + yr
+    try:
+        di, mi, yi = int(day), int(mon), int(yr)
+        if not (1 <= di <= 31 and 1 <= mi <= 12 and 1900 <= yi <= 2100):
+            return ""
+    except ValueError:
+        return ""
+    return f"{yi:04d}-{mi:02d}-{di:02d}"
+
+
+def _unescape(t: str) -> str:
+    for a, b in (("&amp;", "&"), ("&lt;", "<"), ("&gt;", ">"),
+                 ("&apos;", "'"), ("&quot;", '"'), ("&#160;", " ")):
+        t = t.replace(a, b)
+    return t
+
+
+def _para_text(p_xml: str) -> str:
+    """Plain text of one <w:p>.
+
+    IMPORTANT: Word frequently splits a single word across multiple <w:r>/<w:t>
+    runs (formatting/spell-check artefacts). Run boundaries are NOT word
+    boundaries, so we concatenate <w:t> contents directly (no separator) and
+    only turn explicit tabs/breaks into spaces. This avoids mangling
+    "Frau"→"F r au" or "30,00"→"3 0,00".
+    """
+    p_xml = re.sub(r"<w:tab\b[^>]*/?>", " ", p_xml)
+    p_xml = re.sub(r"<w:br\b[^>]*/?>", " ", p_xml)
+    texts = re.findall(r"<w:t\b[^>]*>(.*?)</w:t>", p_xml, re.DOTALL)
+    t = _unescape("".join(texts))
+    return re.sub(r"\s+", " ", t).strip()
+
+
+def _full_text(docx_path: str) -> str:
+    """Return whitespace-collapsed plain text of the document body.
+
+    Paragraphs (and table cells, also wrapped in <w:p>) are joined by a single
+    space so adjacent labels stay separable.
+    """
+    with zipfile.ZipFile(docx_path) as z:
+        xml = z.read("word/document.xml").decode("utf-8", errors="replace")
+    paras = [_para_text(p) for p in re.findall(r"<w:p[ >].*?</w:p>", xml, re.DOTALL)]
+    return re.sub(r"\s+", " ", " ".join(p for p in paras if p)).strip()
+
+
+def _paragraphs(docx_path: str) -> list[str]:
+    """Return per-paragraph plain text (preserves the Label/value line breaks)."""
+    with zipfile.ZipFile(docx_path) as z:
+        xml = z.read("word/document.xml").decode("utf-8", errors="replace")
+    out = []
+    for p in re.findall(r"<w:p[ >].*?</w:p>", xml, re.DOTALL):
+        t = _para_text(p)
+        if t:
+            out.append(t)
+    return out
+
+
+def _label_value(text: str, label_rx: str) -> str:
+    """Find 'Label: value' in collapsed text; stop at the next known label."""
+    rx = re.compile(
+        rf"(?:{label_rx})\s*:\s*(.+?)(?=\s*(?:{_KNOWN_LABELS})\s*:|$)",
+        re.IGNORECASE,
+    )
+    m = rx.search(text)
+    return m.group(1).strip() if m else ""
+
+
+def _clean_money(raw: str) -> str:
+    """'27,50 Euro (Überweisung)' → '27,50'. Returns '' if no number."""
+    m = re.search(r"(\d+(?:[.,]\d{1,2})?)", raw)
+    if not m:
+        return ""
+    return m.group(1).replace(".", ",")
+
+
+def parse_filename(fname: str) -> dict:
+    """Best-effort structured pieces from the contract filename.
+
+    Returns dict with keys: color, animals (list of call-names), buyer
+    (may be empty). Robust to the many messy variants observed.
+    """
+    base = re.sub(r"\.docx$", "", fname, flags=re.IGNORECASE)
+    # Strip the leading cattery prefix and the leading/trailing underscores.
+    base = re.sub(r"^\s*(?:Zucht der kleinen Chaoten|Clan[^_]*Chaoten)\s*",
+                  "", base, flags=re.IGNORECASE)
+    base = base.strip().strip("_").strip()
+
+    color = ""
+    animals: list[str] = []
+    buyer = ""
+
+    # Animals are inside the (…) group, dot-separated call-names.
+    pm = re.search(r"\(([^)]*)\)", base)
+    if pm:
+        inner = pm.group(1).strip()
+        # split on dot (call-name separator) but keep multi-word names
+        animals = [a.strip() for a in inner.split(".") if a.strip()]
+        # color = text before "("
+        color = base[:pm.start()].strip(" -–_")
+        # buyer = text after ")"
+        after = base[pm.end():].strip()
+        bm = re.match(r"\s*[-–]\s*(.+)", after)
+        if bm:
+            buyer = bm.group(1).strip().strip("_").strip()
+    else:
+        # No parens. Two shapes:
+        #   "<token> - <Buyer>"   (token is animal-name or color)
+        #   "<AnimalName>"        (just a name)
+        dm = re.split(r"\s*[-–]\s*", base, maxsplit=1)
+        if len(dm) == 2 and dm[1].strip():
+            color = ""  # ambiguous; treat the left token as an animal name
+            animals = [dm[0].strip().strip("_")] if dm[0].strip() else []
+            buyer = dm[1].strip().strip("_").strip()
+        else:
+            tok = base.strip().strip("_").strip()
+            # comma list like "Speedy,Agouti" → first is the name
+            if tok:
+                animals = [tok.split(",")[0].strip()]
+
+    # Clean buyer: drop trailing numbering "2", file-version noise
+    buyer = re.sub(r"\s*\(?\d+\)?$", "", buyer).strip() if buyer else ""
+    return {"color": color, "animals": animals, "buyer": buyer}
+
+
+# Seller is always the breeder Drazena Rimac (the cattery owner); never a buyer.
+_SELLER_RX = re.compile(r"^(?:(?:Herr|Frau|Familie)\s+)?Drazena\b", re.IGNORECASE)
+_ADDR_STOP = r"Stra\w+e|Wohnort|Fon|E-?Mail|Handy|Festnetz|Telefon|Homepage|Zuchtname|Facebook"
+
+
+_BUYER_REJECT_RX = re.compile(
+    r"^(?:Stra\w+e|Wohnort|Fon|E-?Mail|Handy|Festnetz|Telefon|Homepage|"
+    r"Zuchtname|Facebook|Name)\s*:?\s*$|^[\d\s/]+$",
+    re.IGNORECASE,
+)
+
+
+def _clean_person(name: str) -> str:
+    name = re.sub(r"\s+", " ", name).strip().strip(",").strip()
+    # Reject label leakage / non-person artefacts (e.g. "Straße:", phone runs).
+    if _BUYER_REJECT_RX.match(name):
+        return ""
+    return name
+
+
+def _extract_buyer(text: str, paras: list[str]) -> str:
+    """Buyer (Abnehmer/Empfänger) name from the body.
+
+    Two document layouts exist:
+      A) Side-by-side columns (two table cells): "Name:<seller>" and
+         "Name:<buyer>" appear as two separate runs in the full text.
+      B) Stacked blocks: a "Empfänger/Abnehmer:" header precedes the buyer's
+         "Name:".
+    Strategy: collect every "Name:" value that looks like a person and is not
+    the seller (Drazena Rimac). The buyer is such a value.
+    """
+    # Layout B: explicit Abnehmer/Empfänger header followed by Name:.
+    bm = re.search(
+        r"(?:Empf\w+nger|Abnehmer)[^:]*:\s*(?:[^:]*?\s)?Name\s*:\s*"
+        rf"(.+?)(?=\s*(?:{_ADDR_STOP})\s*:|$)",
+        text, re.IGNORECASE,
+    )
+    if bm:
+        cand = _clean_person(bm.group(1))
+        if cand and not _SELLER_RX.match(cand):
+            return cand
+
+    # Layout A / fallback: scan all Name: values; pick the first non-seller one.
+    for m in re.finditer(
+        rf"Name\s*:\s*(.+?)(?=\s*(?:{_ADDR_STOP})\s*:|\s*Name\s*:|$)",
+        text, re.IGNORECASE,
+    ):
+        cand = _clean_person(m.group(1))
+        if not cand or _SELLER_RX.match(cand):
+            continue
+        # Skip the animal block: animal Name is immediately followed by
+        # Geburtsdatum/Geschlecht/Farbschlag.
+        tail = text[m.end():m.end() + 40]
+        if re.match(r"\s*(?:Geburtsdatum|Geschlecht|Farbschlag)\s*:", tail, re.IGNORECASE):
+            continue
+        return cand
+    return ""
+
+
+def parse_contract(docx_path: str) -> dict | None:
+    """Parse one .docx. Returns a contract record or None if not a contract."""
+    fname = os.path.basename(docx_path)
+    try:
+        text = _full_text(docx_path)
+        paras = _paragraphs(docx_path)
+    except (zipfile.BadZipFile, KeyError, OSError):
+        return None  # unreadable / not a real docx
+
+    if any(m in text for m in NON_CONTRACT_MARKERS):
+        return None  # Abstammungsnachweis / Geburtsurkunde — not a sale contract
+
+    fn = parse_filename(fname)
+
+    # --- animal block (body) ---
+    body_name = _label_value(text, r"Name")
+    # The first "Name:" in the body could be the seller's. The animal's name
+    # appears under "Tierdaten:". Prefer the Name that directly precedes
+    # Geburtsdatum/Geschlecht (the animal block).
+    animal_name = ""
+    # The animal block is headed by "Tierdaten:" (when present) and its Name is
+    # the LAST "Name:" before "Geburtsdatum:". Anchor on Tierdaten if present,
+    # then take the closest Name: to Geburtsdatum.
+    scope = text
+    ti = re.search(r"Tierdaten\s*:", text, re.IGNORECASE)
+    if ti:
+        scope = text[ti.end():]
+    am = re.search(
+        r"Name\s*:\s*(.*?)\s*Geburtsdatum\s*:",
+        scope, re.IGNORECASE,
+    )
+    if am:
+        cand = am.group(1).strip()
+        # Greedy guard: if it still spans multiple labels, keep only the tail
+        # after the last embedded "Name:".
+        if "Name:" in cand or re.search(r"Name\s*:", cand):
+            cand = re.split(r"Name\s*:", cand)[-1].strip()
+        # Drop any leading address-block leftovers.
+        cand = re.split(rf"\s*(?:{_ADDR_STOP})\s*:", cand)[-1].strip()
+        animal_name = cand
+    # Body animal name is often blank (the call-name lives in the filename).
+    if not animal_name or len(animal_name) > 40:
+        animal_name = ""
+
+    dob = _norm_date(_label_value(text, r"Geburtsdatum"))
+    gender_raw = _label_value(text, r"Geschlecht").lower()
+    if gender_raw.startswith("m"):
+        gender = "Male"
+    elif gender_raw.startswith("w"):
+        gender = "Female"
+    else:
+        gender = ""
+
+    color = _label_value(text, r"Farbschlag") or _label_value(text, r"Farbe")
+    color = color.strip()
+    if not color and fn["color"]:
+        color = fn["color"]
+
+    handover = _norm_date(
+        _label_value(text, r"Abgabedatum") or _label_value(text, r"Abgabe\s*am")
+    )
+
+    price = ""
+    for lab in (r"Gesamtpreis", r"Schutzgeb\w+", r"Kaufpreis", r"Preis"):
+        raw = _label_value(text, lab)
+        if raw:
+            price = _clean_money(raw)
+            if price:
+                break
+
+    # contract date: trailing "Ort, [den ]DD.MM.YYYY" near signature line
+    contract_date = ""
+    cm = re.findall(r"[A-Za-zÄÖÜäöü.\- ]+,\s*(?:den\s*)?(\d{1,2}\.\d{1,2}\.\d{2,4})",
+                    text)
+    if cm:
+        contract_date = _norm_date(cm[-1])
+
+    buyer = _extract_buyer(text, paras)
+    if not buyer and fn["buyer"]:
+        buyer = fn["buyer"]
+
+    # Animal call-names: prefer filename (the call-names the breeder filed by),
+    # fall back to body animal name.
+    animals = list(fn["animals"])
+    if not animals and animal_name:
+        animals = [animal_name]
+
+    # Reject if we have neither a buyer nor any animal name — useless record.
+    if not buyer and not animals:
+        return None
+
+    return {
+        "sourceFile": fname,
+        "buyer": buyer,
+        "animals": animals,
+        "animalNameBody": animal_name,
+        "color": color,
+        "gender": gender,
+        "dob": dob,
+        "handoverDate": handover,
+        "contractDate": contract_date,
+        "price": price,
+    }
+
+
+def scan(dir_path: str, limit: int | None = None):
+    """Walk the share, parse every .docx. Returns (records, stats)."""
+    records = []
+    stats = {
+        "files_seen": 0, "template_skipped": 0, "non_contract_skipped": 0,
+        "unreadable": 0, "parsed": 0, "unparseable": 0,
+        "with_buyer": 0, "with_handover": 0, "with_price": 0,
+        "with_color": 0, "with_dob": 0, "with_animals": 0,
+    }
+    for root, _, files in os.walk(dir_path):
+        for f in sorted(files):
+            if not f.lower().endswith(".docx"):
+                continue
+            stats["files_seen"] += 1
+            low = f.lower()
+            if any(m in low for m in TEMPLATE_MARKERS):
+                stats["template_skipped"] += 1
+                continue
+            path = os.path.join(root, f)
+            try:
+                rec = parse_contract(path)
+            except Exception:  # never let one bad file kill the run
+                rec = None
+            if rec is None:
+                # Distinguish unreadable vs non-contract vs genuinely unparseable
+                try:
+                    _ = _full_text(path)
+                    txt = _
+                    if any(m in txt for m in NON_CONTRACT_MARKERS):
+                        stats["non_contract_skipped"] += 1
+                    else:
+                        stats["unparseable"] += 1
+                except Exception:
+                    stats["unreadable"] += 1
+                continue
+            stats["parsed"] += 1
+            if rec["buyer"]:
+                stats["with_buyer"] += 1
+            if rec["handoverDate"]:
+                stats["with_handover"] += 1
+            if rec["price"]:
+                stats["with_price"] += 1
+            if rec["color"]:
+                stats["with_color"] += 1
+            if rec["dob"]:
+                stats["with_dob"] += 1
+            if rec["animals"]:
+                stats["with_animals"] += 1
+            records.append(rec)
+            if limit and len(records) >= limit:
+                return records, stats
+    return records, stats
+
+
+def main():
+    try:
+        sys.stdout.reconfigure(encoding="utf-8", errors="replace")
+    except Exception:
+        pass
+
+    ap = argparse.ArgumentParser(description="Abgabevertrag-Extraktor")
+    ap.add_argument("--dir", default=DEFAULT_DIR, help="Verträge-Ordner")
+    ap.add_argument("--limit", type=int, default=None,
+                    help="Nur die ersten N Verträge (Stichprobe)")
+    args = ap.parse_args()
+
+    if not os.path.isdir(args.dir):
+        print(f"Fehler: Ordner nicht gefunden: {args.dir}", file=sys.stderr)
+        sys.exit(1)
+
+    os.makedirs(OUT, exist_ok=True)
+    print(f"Scanne: {args.dir}")
+    records, stats = scan(args.dir, args.limit)
+
+    out_path = os.path.join(OUT, "contracts.json")
+    with open(out_path, "w", encoding="utf-8") as f:
+        json.dump(records, f, ensure_ascii=False, indent=2)
+
+    print(f"Dateien gesehen:        {stats['files_seen']}")
+    print(f"  Vorlage übersprungen: {stats['template_skipped']}")
+    print(f"  Nicht-Vertrag (AN):   {stats['non_contract_skipped']}")
+    print(f"  unlesbar (kein ZIP):  {stats['unreadable']}")
+    print(f"  unparsbar:            {stats['unparseable']}")
+    print(f"Verträge geparst:       {stats['parsed']}")
+    print(f"  mit Käufer:           {stats['with_buyer']}")
+    print(f"  mit Tier(en):         {stats['with_animals']}")
+    print(f"  mit Geburtsdatum:     {stats['with_dob']}")
+    print(f"  mit Abgabedatum:      {stats['with_handover']}")
+    print(f"  mit Preis:            {stats['with_price']}")
+    print(f"  mit Farbschlag:       {stats['with_color']}")
+    print(f"Ausgabe: {out_path}")
+
+
+if __name__ == "__main__":
+    main()