Files
GerbilManager/tools/import/extract_docx.py
Gulum 45b8533f18
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feat(deploy): TrueNAS Custom-App + Auto-Deploy, plus aufgelaufene Arbeit
Deployment:
- custom-app.compose.yaml: self-contained Compose fuer TrueNAS "Custom App"
  (absolute Host-Bind-Pfade, postgres:18, pull_policy always, Port 8090)
- scripts/truenas-deploy.sh: Host-Skript create/redeploy via midclt (App
  bleibt unter Apps sichtbar) inkl. Image-Pull + Health-Check
- ci.yml Deploy-Job: laeuft auf ubuntu-latest-Runner, kopiert Deploy-Dateien
  per SSH auf den NAS-Host und triggert truenas-deploy.sh (statt runs-on goldeye)
- compose.yaml/.env.example: postgres:18 (Locale-Match zur Quell-DB), Port 8090
- .gitignore: .agents/, tools/rag/, deploy/truenas/.env (Secrets/Scratch)

Aufgelaufene Feature-Arbeit (verified/Freeze, Migrationen, Import-Triage):
- GerbilOverride/VerifiedGerbil-Endpoints + GerbilSnapshotService + Tests
- EF-Migrationen (ShowInChronicle, Stillborn, BirthOrder, ManualFlag, DSGVO)
- Frontend VerifizierteTierePage + verified-API + e2e-Spec
- diverse Import-/Triage-Skripte und -Tests

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
2026-07-19 09:19:11 +02:00

342 lines
13 KiB
Python

#!/usr/bin/env python3
"""FEAT-8d Stage 1 — Wurfchronik-Detail-Dokument (.docx) extrahieren.
Liest 'Wurfchronik der Kleinen Chaoten im Detail.docx' (Word/XML, stdlib-Python,
kein pip) und erzeugt:
output/docx_litters.json — Wurf-Kopfdaten (WS-Code, DOB, Eltern, Notiz)
output/docx_animals.json — Tier-Zeilen (Name, Farbe, Abnehmer, ABD, Tod)
Format der Ausgabe ist so gestaltet, dass ImportDocxService.cs in C# direkt
darüber laden kann. Idempotent: mehrfaches Ausführen überschreibt denselben Output.
Bekannte Sonderwerte im Dokument:
ZT = Zucht-Tier (bleibt in Zucht, kein externer Abnehmer)
BLEIBT = vorläufig beim Züchter
FREI = noch verfügbar
VG: = Verpaarungs-Geschichte (bisherige Partner; nicht als Abnehmer werten)
RG: = Rückgabe
BEW = Bewerbung (Adoptionsinteressent in Prüfung)
-- ??? = Platzhalter, kein echter Name
Feld 'gender': '' = weiblich (kein Marker), '*' auf Farbschlag oder 'G'-Spalte = männlich.
Ausführung: python extract_docx.py [--docx PFAD]
"""
import os
import re
import sys
import json
import zipfile
import argparse
HERE = os.path.dirname(os.path.abspath(__file__))
DEFAULT_DOCX = os.path.join(
r"C:\Users\gulum\dev",
"Wurfchronik der Kleinen Chaoten im Detail.docx",
)
OUT = os.path.join(HERE, "output")
# --- Regex patterns -------------------------------------------------------
# Litter header paragraph (after whitespace-collapsing).
# Edge cases handled:
# - Dual birth date: "*16./17.03.2021"
# - WS without numerator: "WS: /5"
# - WS with trailing text: "WS: 4/4, davon 1 später..."
# - No space before WS: "...ChaotenWS: 2/4"
# Date part allows simple DD.MM.YYYY, dual-day (16./17.03.2021), or dual-month (31.05/*01.06.2023).
# We capture the LAST complete DD.MM.YYYY in the date token as the birth date.
_DATE_TOKEN = r"[\d./\*]+"
# Full litter header regex
LITTER_RE = re.compile(
r"([A-Za-z\d\-]*Wurf)\s*\*\s*(" + _DATE_TOKEN + r")"
r"\s*Von:\s*(.+?)\s*&\s*(.+?)\s*WS:\s*(\d*\s*/\s*\d+)"
r"(?:[,\s].*?)?(?:Notiz:\s*(.*?))?$",
re.IGNORECASE,
)
# Used to extract the canonical date from a date token like "31.05/*01.06.2023"
_LAST_DATE_RE = re.compile(r"(\d{1,2}\.\d{2}\.\d{4})(?![\d.])")
# Death/adoption date at start of combined T.D column: "16.09.23Tumor am After"
DATE_START_RE = re.compile(r"^(\d{1,2}\.\d{1,2}\.\d{2,4})\s*(.*)")
# Partner birth date: "Crow (*25.12.20)" or "Tom (*05.01.21)"
PARTNER_DOB_RE = re.compile(r"\(\s*\*\s*(\d{2}\.\d{2}\.\d{2,4})\s*\)")
# Special-value sentinel names to skip
PLACEHOLDER_NAMES = {"--", "???", ""}
INTERNAL_TOKENS = {"ZT", "BLEIBT", "FREI", "VG:", "VG*:", "RG:", "BEW"}
def _norm_dob(d: str) -> str:
"""Normalise German date to DD.MM.YYYY."""
if not d:
return ""
p = d.strip().split(".")
if len(p) == 3:
y = p[2].strip()
if len(y) == 2:
y = "20" + y
return f"{p[0].zfill(2)}.{p[1].zfill(2)}.{y}"
return d.strip()
def _cell_text(cell_xml: str) -> str:
"""Strip XML from a <w:tc> cell and return clean text."""
t = re.sub(r"<[^>]+>", "", cell_xml)
t = t.replace("&amp;", "&").replace("&lt;", "<").replace("&gt;", ">")
t = t.replace("&apos;", "'").replace("&quot;", '"')
return re.sub(r"\s+", " ", t).strip()
def _is_internal(value: str) -> bool:
"""True if the owner/name field holds an internal sentinel, not a real person."""
v = value.strip()
return v in INTERNAL_TOKENS or any(v.startswith(tok) for tok in INTERNAL_TOKENS)
def extract(docx_path: str):
"""Parse the docx and return (litters, animals) lists."""
with zipfile.ZipFile(docx_path) as z:
xml = z.read("word/document.xml").decode("utf-8", errors="replace")
# ---- Paragraphs → litter header blocks ----
paras = re.findall(r"<w:p[ >].*?</w:p>", xml, re.DOTALL)
para_texts = []
for p in paras:
t = re.sub(r"<[^>]+>", "", p)
t = t.replace("&amp;", "&").strip()
t = re.sub(r"\s+", " ", t).strip()
if t:
para_texts.append(t)
litters: list[dict] = []
current_ws: str = ""
current_litter_dob: str = ""
# Build a WS-code → litter index for assigning animals
ws_to_idx: dict[str, int] = {}
for para in para_texts:
m = LITTER_RE.search(para)
if not m:
continue
litter_id = m.group(1).strip()
dob_raw = m.group(2).strip()
mother_raw = m.group(3).strip()
father_raw = m.group(4).strip()
ws_raw = m.group(5).replace(" ", "")
note = (m.group(6) or "").strip()
# For dual-date tokens like "31.05/*01.06.2023", take the last full date.
last_dates = _LAST_DATE_RE.findall(dob_raw)
dob_clean = _norm_dob(last_dates[-1] if last_dates else dob_raw)
# Map 22-Wurf and 23-Wurf to their correct alphabetical sequence name based on DOB
if litter_id == "22-Wurf":
dob_map = {
"17.06.2023": "V22-Wurf",
"13.07.2023": "X22-Wurf",
"20.07.2023": "Y22-Wurf",
"24.07.2023": "Z22-Wurf"
}
if dob_clean in dob_map:
litter_id = dob_map[dob_clean]
elif litter_id == "23-Wurf":
dob_map = {
"03.10.2023": "F23-Wurf",
"06.10.2023": "G23-Wurf",
"10.10.2023": "H23-Wurf",
"17.10.2023": "I23-Wurf",
"31.10.2023": "J23-Wurf",
"04.11.2023": "K23-Wurf",
"11.11.2023": "L23-Wurf",
"17.11.2023": "M23-Wurf",
"20.11.2023": "N23-Wurf",
"01.12.2023": "O23-Wurf",
"02.12.2023": "P23-Wurf",
"03.12.2023": "Q23-Wurf",
"05.12.2023": "R23-Wurf"
}
if dob_clean in dob_map:
litter_id = dob_map[dob_clean]
litter = {
"litterId": litter_id,
"dob": dob_clean,
"motherName": mother_raw,
"fatherName": father_raw,
"wsCode": ws_raw,
"note": note,
}
ws_to_idx[ws_raw] = len(litters)
litters.append(litter)
# ---- Tables → animal rows ----
# Each table sits after a litter-header paragraph; we sequence tables and
# litter headers together by their byte offset in the XML.
animals: list[dict] = []
# Build ordered sequence of (offset, type, data) events
events: list[tuple[int, str, any]] = []
for m in re.finditer(r"<w:p[ >].*?</w:p>", xml, re.DOTALL):
t = re.sub(r"<[^>]+>", "", m.group()).replace("&amp;", "&").strip()
t = re.sub(r"\s+", " ", t).strip()
lm = LITTER_RE.search(t)
if lm:
ws = lm.group(5).replace(" ", "")
dob_tok = lm.group(2)
last = _LAST_DATE_RE.findall(dob_tok)
dob = _norm_dob(last[-1] if last else dob_tok)
events.append((m.start(), "litter", (ws, dob)))
for m in re.finditer(r"<w:tbl[ >].*?</w:tbl>", xml, re.DOTALL):
events.append((m.start(), "table", m.group()))
events.sort(key=lambda e: e[0])
active_ws = ""
active_dob = ""
for _, etype, edata in events:
if etype == "litter":
active_ws, active_dob = edata
elif etype == "table" and active_ws:
# Parse all rows in this table
rows = re.findall(r"<w:tr[ >].*?</w:tr>", edata, re.DOTALL)
for row in rows:
cells_xml = re.findall(r"<w:tc[ >].*?</w:tc>", row, re.DOTALL)
ct = [_cell_text(c) for c in cells_xml]
if not ct:
continue
# Skip header rows
if ct[0] == "G" and len(ct) > 1 and "Farbe" in ct[1]:
continue
# Column positions: G | Farbe | Name | Partner | Abnehmer | ABD | T.D
# Some newer tables add ABGew between ABD and T.D (7 or 8 cols)
g_col = ct[0] if len(ct) > 0 else ""
farbe_raw = ct[1] if len(ct) > 1 else ""
name = ct[2] if len(ct) > 2 else ""
partner = ct[3] if len(ct) > 3 else ""
owner = ct[4] if len(ct) > 4 else ""
abd_raw = ct[5] if len(ct) > 5 else ""
# If 8 cols, col 6 = ABGew, col 7 = T.D; if 7 cols, col 6 = T.D
if len(ct) >= 8:
abgew = ct[6]
tod_raw = ct[7]
elif len(ct) >= 7:
abgew = ""
tod_raw = ct[6]
else:
abgew = ""
tod_raw = ""
# Skip placeholders
name = name.strip()
if name in PLACEHOLDER_NAMES:
continue
if not farbe_raw.strip() and not name:
continue
# Gender: explicit marker in G column, or * suffix on Farbschlag
is_male = bool(g_col.strip() == "*" or farbe_raw.endswith("*"))
farbschlag = farbe_raw.rstrip("*").strip()
# Owner: strip internal sentinels
owner_clean = owner.strip()
if _is_internal(owner_clean):
owner_clean = ""
# For multi-owner ("1.) Julia2.) RG:"), take first
m1 = re.match(r"1\.\)\s*(.+?)(?:2\.\)|$)", owner_clean)
if m1:
owner_clean = m1.group(1).strip()
# ABD (Abgabe-Datum)
abgabe_date = _norm_dob(abd_raw.strip())
# T.D column: may start with a date followed by cause
death_date = ""
death_cause = ""
if tod_raw:
dm = DATE_START_RE.match(tod_raw.strip())
if dm:
death_date = _norm_dob(dm.group(1))
death_cause = dm.group(2).strip()
else:
death_cause = tod_raw.strip()
# Partner name and DOB
partner_clean = partner.strip()
partner_dob = ""
pdob_m = PARTNER_DOB_RE.search(partner_clean)
if pdob_m:
partner_dob = _norm_dob(pdob_m.group(1))
partner_clean = PARTNER_DOB_RE.sub("", partner_clean).strip()
# Strip VG:/ZT/etc. prefixes
partner_clean = re.sub(r"^(?:VG\*?:|ZT\s*)", "", partner_clean).strip()
# Take first partner in numbered list
pm1 = re.match(r"1\.\)\s*(.+?)(?:2\.\)|$)", partner_clean)
if pm1:
partner_clean = pm1.group(1).strip()
animals.append({
"wsCode": active_ws,
"litterDob": active_dob,
"name": name,
"farbschlag": farbschlag,
"gender": "male" if is_male else "female",
"owner": owner_clean,
"abgabeDate": abgabe_date,
"abgabeWeight": abgew.strip(),
"deathDate": death_date,
"deathCause": death_cause,
"partnerName": partner_clean,
"partnerDob": partner_dob,
})
return litters, animals
def main():
try:
sys.stdout.reconfigure(encoding="utf-8", errors="replace")
except Exception:
pass
ap = argparse.ArgumentParser(description="FEAT-8d docx extractor")
ap.add_argument("--docx", default=DEFAULT_DOCX,
help="Pfad zur 'im Detail.docx'")
args = ap.parse_args()
if not os.path.isfile(args.docx):
print(f"Fehler: Datei nicht gefunden: {args.docx}", file=sys.stderr)
sys.exit(1)
os.makedirs(OUT, exist_ok=True)
print(f"Lese: {args.docx}")
litters, animals = extract(args.docx)
litters_path = os.path.join(OUT, "docx_litters.json")
animals_path = os.path.join(OUT, "docx_animals.json")
with open(litters_path, "w", encoding="utf-8") as f:
json.dump(litters, f, ensure_ascii=False, indent=2)
with open(animals_path, "w", encoding="utf-8") as f:
json.dump(animals, f, ensure_ascii=False, indent=2)
# Stats
named = sum(1 for a in animals if a["name"])
with_owner = sum(1 for a in animals if a["owner"])
with_death = sum(1 for a in animals if a["deathDate"])
with_abgabe = sum(1 for a in animals if a["abgabeDate"])
print(f"Würfe: {len(litters)}")
print(f"Tiere: {len(animals)} (benannt: {named})")
print(f" mit Abnehmer: {with_owner}")
print(f" mit Abgabe-Dat: {with_abgabe}")
print(f" mit Tod-Datum: {with_death}")
print(f"Ausgabe: {OUT}")
if __name__ == "__main__":
main()