#!/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)

        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()