Gulum
5a6d1c2541
Genetik-Engine (bde4ec70, f89e95ad, 2322c2a8):
- Saphir/Platin/Platin-Hell unterscheiden sich NUR in der C-Zygotie und waren im
Katalog identisch (locusToken reduziert auf das dominante Allel) → Saphir war
unerreichbar. Token darf jetzt ein exaktes, ungeordnetes Allelpaar "x/y"
verlangen: Platin C/C, Saphir C/cchm, Platin-Hell C/ch. TS- und Python-Mirror
identisch, Seeds regeneriert, Migration ReseedColorVarietiesGen6Saphir.
- c[hm] wird als Alias auf c[chm] normalisiert (Tippfehler in zwei Charts) —
vorher war Jays Gencode unparsebar und ergab "Zobel-Hell".
- 6 Tiere wechseln den errechneten Farbschlag (5x Platin→Saphir, Jay→Zobel).
Importer-Logik:
- renameTo-Notiz-Sweep: der alte Name blieb in Wurf-Notizen stehen ("Blacky +
Kruke") — jetzt wortgenau ersetzt, mit vier Guards gegen Kollateralschaden.
- Neuer Resolution-Schlüssel goHomeDate (autoritativ, zieht GivenAway nach) und
spottingType; Gencode-Overrides gewinnen jetzt bei präzisem Match (vorher
wurden Entscheidungen stumm verschluckt, z. B. Eliza und Chris).
- parse_date verwirft implausible Jahre (JackJack hatte 1310-05-13).
- extract.py erkennt Stammbaum-Blöcke auch ohne Stern vor dem Geburtsdatum
(Bijou bekam dadurch den Nachbar-Ast als Mutter).
- Backend-Ingest überträgt SpottingType (nur bei Payload-Wert).
Daten (conflict-decisions.json, re-ingest-stabil): Kuke-Merge + Zuchtname,
Jamie- und Sakura-Dubletten, Phantom-Tier "Unbekannt", Eltern von Kathlin,
Fast Boy/Ziwa und dem Q4-/TS-Wurf, Eliza-Gencode, Merle-Abgabe, JackJack.
Frontend (24522f5f): Abgabedatum steht in der Tier-Akte jetzt direkt unter dem
Abnehmer und hängt nicht mehr am Status.
Tests: +25 Checks test_merge_resolve, +7 test_genotype, +8 genetics.test.ts,
neuer Extract- und Ingest-Test, e2e GOHOME-ROW. Alles grün.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
GerbilManager import tooling (FEAT-8b)
One-off migration tooling (Python, no third-party deps) that turns Julian's wife's hand-built spreadsheets into normalised JSON for review and, later, import. This is not product code — it lives outside the app and is run manually.
See the format analysis in FEAT-8a-format-spec.md (Pam's hive workspace).
What it does
extract.py runs stages 1–2 of the pipeline:
- Extract (stage 1)
- 10 Stammbaum pedigree charts → animals (name, DOB, death, Farbschlag, genotype, breeder, positionally-reconstructed parent links, photos).
- Wurfchronik litter chronicle → litters (date, dam, sire, Wurfstärke, sex breakdown, Zuchtnummer, notes). Columns are read by header row because the two sheets use different schemas.
- Embedded photos (
xl/media) →output/photos/<animal-slug>/, mapped to the animal by drawing anchor position.
- Dedup + review (stage 2)
- Merge animals on
normalise(call-name) + DOB, with the Zucht as discriminator (Julian's ruling: Wurfchronik[brackets]≡ Stammbaumof/von <line>suffix — both are the breeding line; same name+DOB but different Zucht stays two animals). - Match animals onto Wurfchronik litters (
litterRef) via DOB + (Vater, Mutter) — the Pam-validated build order (chronicle litters are canonical). - Emit a German-language
output/review-report.mdfor the breeder to verify (merges, conflicts, ambiguous/incomplete entries, unmapped genotype tokens, litter data-quality warnings). - Nothing is loaded into the database — stage 3 (API load) is separate and waits on DATA-2 + FEAT-1b phase 2.
- Merge animals on
Wurfchronik column semantics (Julian, authoritative)
A Wurfbezeichnung · B Geburtsdatum · C Mutter · D Vater ([…] = Zucht,
& = multiple sires) · E survivedToGoHome (Tabelle1 only, unlabeled —
detected positionally) · F Wurfstärke → totalBorn · G breakdown
Männchen,Weibchen,TG,s → males/females/stillborn/diedLater (s = died
after birth, before Abgabe) · last column → note. Validation: E should
equal F − TG − s; mismatches become German warnings in the review report
(data-quality signal, not an import blocker). A few Tabelle2 rows shift these
columns — they are read value-adaptively and flagged with a warning.
Genotypes are mapped to the frozen 8-locus contract (A C D E G P Sp Re) while
preserving everything: genotype.mapped8locus, genotype.rawGenotype (verbatim),
genotype.unmappedTokens (e.g. the Uw locus, markers WFNZ/WP/DP). A -
(unknown second allele) maps to ?.
Run
cd tools/import
python extract.py # xlsx → animals.json / litters.json
python extract.py --stammbaeume "<dir>" --wurfchronik "<file.xlsx>"
python extract_docx.py # Wurfchronik-Detail.docx → docx_*.json
python extract_contracts.py # Abgabeverträge (.docx) → contracts.json
python merge_and_resolve.py # → resolved_import.json (DB-ready)
Requires Python 3 (zero third-party deps). Re-runnable / idempotent — re-run
when more files arrive (Wurfchronik Teil2+, new charts, or new contracts).
extract_contracts.py scans the breeder's sale-contract share
(\\truenas\…\Verträge, ~1.4k .docx) and emits one record per contract
(buyer, animal call-names, Farbschlag, dates, price, source filename). It skips
the blank template, Abstammungsnachweis/Geburtsurkunde documents, and any
file that is not a readable .docx. merge_and_resolve.py then conservatively
folds contracts into the resolved data: buyers become receiver Contacts, and
unambiguously matched gerbils get ReceiverContactId / GoHomeDate /
Status=GivenAway (only where not already set), with a provenance history line.
Ambiguous / unmatched animals are counted and skipped, never guessed.
Output (tools/import/output/, git-ignored except the report)
| File | Contents |
|---|---|
animals.json |
deduped animals with genotype, parentRefs, photos, sourceFiles |
litters.json |
litters from the Wurfchronik |
docx_animals.json / docx_litters.json |
Wurfchronik-Detail.docx rows |
contracts.json |
one record per Abgabevertrag (buyer, animals, dates, price) |
resolved_import.json |
merged DB-ready payload consumed by IngestResolvedService |
photos/<slug>/… |
extracted, anchor-mapped images |
review-report.md |
human review deliverable (committed) |
Files
xlsx_util.py— dependency-free.xlsxreader (zip + XML): shared strings, cells by reference, image/drawing anchors.genotype.py— genotype notation parser → 8-locus mapping + raw + unmapped.extract.py— the pipeline (stages 1–2).