feat(import): RPRO3-Dubletten-Entscheidungen der Züchterin als Override
Manuelle "gleich/verschieden?"-Entscheidungen aus den rpro3-import-Tickets fließen jetzt in den RennmausPro-III-Import ein: - Rpro3Decisions (Modell + JSON-Loader): same (Force-Merge), different (Force-Split), fields (Farbe/DOB/Herkunft/resident/Notiz). Schlüssel = rid. - Rpro3Dedup.Run(animals, decisions): honoriert die Overrides nach dem automatischen Dedup (eine rid zieht ihren Cluster mit). - Rpro3ImportService: lädt Import/Rpro3/rpro3-decisions.json, wendet Feld-Overrides im Plan-Builder an. - rpro3-decisions.json: 14 bestätigte Entscheidungen (Eiji, Momo, Samuel, Female, Kennedy, Fegur, Tuli, Bura, Mister X, Zoey, Max, Akiro, Merlin, Snickers). - tools/import/rpro3_lookup.py: Triage-Helfer (Farbe/Gencode/Eltern/ Nachzucht+Partner aus _rpro3.db) für die Rückfragen an die Züchterin. - 4 neue Tests (Force-Merge/Force-Split/Loader); Suite 268 grün. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
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tools/import/rpro3_lookup.py
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tools/import/rpro3_lookup.py
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#!/usr/bin/env python3
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# -*- coding: utf-8 -*-
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"""
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Triage-Helfer: Beantwortet die Gegenfragen der Züchterin zu RPRO3-Namensdubletten.
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Liefert pro Variante (A/B/C … exakt wie im Rückfrage-Ticket) die Daten, die die
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Züchterin typischerweise sehen will: Geburtsdatum, Farbe, **Gencode (Fcode)**,
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Herkunft, Eltern (Vater/Mutter) sowie Nachzucht inkl. Co-Elternteil (Partner).
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Die Variantenbildung/Label-Vergabe spiegelt rpro3_tickets.py + compare_rpro3.dedup
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exakt (Union-Find über gleiche Namen; Filter „informativ"; Sortierung
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(not is_own, -count) → A,B,C…). Im Gegensatz zum Ticket wird hier über den GESAMTEN
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Cluster aggregiert (rpro3_tickets kappt rids auf 4 – Nachzucht wäre sonst unvollständig).
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Aufruf:
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python rpro3_lookup.py <_rpro3.db> "<Name>" [LETTERS]
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LETTERS optional, z. B. "B,C" → nur diese Varianten. Default: alle.
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python rpro3_lookup.py <_rpro3.db> "<Name>" --json → strukturiert (für Agenten)
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"""
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from __future__ import annotations
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import sys, json
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from collections import defaultdict
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import compare_rpro3 as C
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LETTERS = "ABCDEFGHIJKLMNOPQRSTUVWXYZ"
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def informative(recs):
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return any(r["dob"] or r["farbe"] or r["origin"] for r in recs)
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def build_clusters(animals):
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"""Spiegelt compare_rpro3.dedup: Union-Find je Name, gibt {name: [cluster_recs,...]}."""
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def compat(x, y):
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return (not x) or (not y) or (x == y)
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for a in animals:
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a["namek"] = C.norm_name(a["name"])
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a["dobk"] = a["dob"]
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a["farbek"] = C.norm_farbe(a["farbe"])
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a["origink"] = C.norm_origin(a["origin"])
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by_name = defaultdict(list)
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for a in animals:
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if a["namek"] in C.PLACEHOLDER_NAMES:
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continue
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by_name[a["namek"]].append(a)
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parent = {}
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def find(x):
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while parent[x] != x:
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parent[x] = parent[parent[x]]
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x = parent[x]
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return x
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def union(x, y):
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parent.setdefault(x, x); parent.setdefault(y, y)
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parent[find(x)] = find(y)
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def positive(a, b):
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agree = 0
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if a["dobk"] and b["dobk"] and a["dobk"] == b["dobk"]:
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agree += 1
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if a["farbek"] and b["farbek"] and a["farbek"] == b["farbek"]:
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agree += 1
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if a["origink"] and b["origink"] and a["origink"] == b["origink"]:
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agree += 1
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return agree
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def conflict(a, b):
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c = 0
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if a["dobk"] and b["dobk"] and a["dobk"] != b["dobk"]:
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c += 1
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if a["farbek"] and b["farbek"] and a["farbek"] != b["farbek"]:
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c += 1
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if a["origink"] and b["origink"] and a["origink"] != b["origink"]:
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c += 1
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return c
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for name, group in by_name.items():
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for a in group:
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parent.setdefault(a["rid"], a["rid"])
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n = len(group)
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for i in range(n):
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for j in range(i + 1, n):
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a, b = group[i], group[j]
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comp = (compat(a["dobk"], b["dobk"]) and compat(a["farbek"], b["farbek"])
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and compat(a["origink"], b["origink"]))
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if comp and positive(a, b) >= 1 and conflict(a, b) == 0:
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union(a["rid"], b["rid"])
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# Cluster je Name sammeln
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name_clusters = {}
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by_rid = {a["rid"]: a for a in animals}
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for name, group in by_name.items():
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roots = defaultdict(list)
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for a in group:
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roots[find(a["rid"])].append(a)
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name_clusters[name] = list(roots.values())
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return name_clusters
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def variants_for(animals, display_name):
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"""Liefert [(letter, recs)] für einen Namen – Reihenfolge wie im Ticket."""
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namek = C.norm_name(display_name)
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clusters = build_clusters(animals).get(namek, [])
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info = [recs for recs in clusters if informative(recs)]
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# Sortierung exakt wie rpro3_tickets.py: eigene Tiere zuerst, dann größere Cluster
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info.sort(key=lambda recs: (not any(r["src"] == "stamm" for r in recs), -len(recs)))
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return [(LETTERS[i], recs) for i, recs in enumerate(info)]
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def aggregate(recs, animals):
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"""Aggregiert Daten + Nachzucht über alle recs eines Clusters."""
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names = {r["name"] for r in recs}
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dob = sorted({C.iso(r["dob"]) for r in recs if r["dob"]})
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farbe = sorted({r["farbe"] for r in recs if r["farbe"]})
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fcode = sorted({r["fcode"] for r in recs if r["fcode"]})
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origin = sorted({r["origin"] for r in recs if r["origin"]})
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fathers = sorted({r["father"] for r in recs if r["father"]})
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mothers = sorted({r["mother"] for r in recs if r["mother"]})
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is_own = any(r["src"] == "stamm" for r in recs)
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rids = [r["rid"] for r in recs]
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# Nachzucht: alle Tiere, deren Eltern-rid auf eine rid dieses Clusters zeigt
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rid_set = set(rids)
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kids = []
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seen = set()
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for a in animals:
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if str(a.get("mid_raw")) in rid_set or str(a.get("pid_raw")) in rid_set:
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co = a["father"] if a["mother"] in names else a["mother"]
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key = (C.norm_name(a["name"]), C.iso(a["dob"]) if a["dob"] else "")
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if key in seen:
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continue
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seen.add(key)
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kids.append({"name": a["name"], "dob": C.iso(a["dob"]) if a["dob"] else None,
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"farbe": a["farbe"], "fcode": a["fcode"], "partner": co})
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return {"names": sorted(names), "rids": rids, "count": len(recs),
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"is_own": is_own, "dob": dob, "farbe": farbe, "fcode": fcode,
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"origin": origin, "fathers": fathers, "mothers": mothers, "kids": kids}
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def fmt_block(letter, agg):
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src = "eigenes Tier" if agg["is_own"] else "externer Ahn"
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L = []
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L.append(f"**{letter}** ({src}, {agg['count']}× in RennmausPro):")
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L.append(f"• Geburtsdatum: {', '.join(agg['dob']) or 'unbekannt'}")
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L.append(f"• Farbe: {', '.join(agg['farbe']) or 'unbekannt'}")
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L.append(f"• Gencode: {', '.join(agg['fcode']) or 'unbekannt'}")
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L.append(f"• Herkunft: {', '.join(agg['origin']) or 'unbekannt'}")
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vat = ', '.join(agg['fathers']) or 'unbekannt'
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mut = ', '.join(agg['mothers']) or 'unbekannt'
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L.append(f"• Eltern: Vater {vat} · Mutter {mut}")
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if agg["kids"]:
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L.append("• Nachzucht:")
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for k in agg["kids"]:
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d = k["dob"] or "?"
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f = k["farbe"] or "?"
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gc = f" [{k['fcode']}]" if k["fcode"] else ""
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p = f" — Partner: {k['partner']}" if k["partner"] else ""
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L.append(f" – {k['name']} (geb. {d}, {f}{gc}){p}")
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else:
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L.append("• Nachzucht: keine in RennmausPro hinterlegt")
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return "\n".join(L)
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def variants_by_rids(animals, rid_groups):
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"""rid_groups: Liste von rid-Listen (eine je Variante/Buchstabe). Aggregiert pro Gruppe
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über den GANZEN Auto-Cluster (eine rid zieht ihren Cluster mit). Für Platzhalter-Namen
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(„...") und Freitext-Tickets, wo der Name nicht greift, aber rids bekannt sind."""
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from collections import defaultdict
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# Auto-Cluster wie build_clusters, aber global über rids indizieren
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clusters = build_clusters(animals)
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rid_to_recs = {}
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for recs_list in clusters.values():
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for recs in recs_list:
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for r in recs:
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rid_to_recs[r["rid"]] = recs
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out = []
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for i, grp in enumerate(rid_groups):
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merged, seen = [], set()
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for rid in grp:
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for r in rid_to_recs.get(rid, []):
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if r["rid"] not in seen:
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seen.add(r["rid"]); merged.append(r)
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if merged:
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out.append((LETTERS[i], merged))
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return out
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def main():
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db = sys.argv[1]
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name = sys.argv[2]
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# --rids "u84,u83;u1" → Variante A=u84,u83 Variante B=u1 (per Semikolon getrennt)
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if name == "--rids":
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rid_spec = sys.argv[3]
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R = C.load_rpro3(db)
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groups = [[x.strip() for x in g.split(",") if x.strip()] for g in rid_spec.split(";") if g.strip()]
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vs = variants_by_rids(R["animals"], groups)
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print("=== (per rids) ===")
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for letter, recs in vs:
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print(fmt_block(letter, aggregate(recs, R["animals"])))
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print()
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return
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as_json = "--json" in sys.argv[3:]
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letters = None
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for a in sys.argv[3:]:
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if a != "--json":
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letters = {x.strip().upper() for x in a.split(",") if x.strip()}
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R = C.load_rpro3(db)
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animals = R["animals"]
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vs = variants_for(animals, name)
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if not vs:
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print(f"(keine Varianten für „{name}“ gefunden)")
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return
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out = []
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for letter, recs in vs:
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if letters and letter not in letters:
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continue
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agg = aggregate(recs, animals)
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out.append((letter, agg))
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if as_json:
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print(json.dumps({"name": name, "variants": {l: a for l, a in out}},
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ensure_ascii=False, indent=1))
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else:
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print(f"=== {name} ===")
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for letter, agg in out:
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print(fmt_block(letter, agg))
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print()
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if __name__ == "__main__":
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main()
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