"""Parse Old Bailey Online XML (v7.2, figshare 10.15131/shef.data.4775434.v2) into one row per trial, with typed
persons, offences, verdicts, punishments and the defendant→offence→verdict→punishment joins; one row per session; one
row per Ordinary's Account. Verbatim TEI is kept in an `xml` column.

Usage: python parse_obo.py <xml_root> <out_dir> [--limit N] [--stats]

Conventions (see dataset card):
- persons.type is null when the source assigns no role (part-1 names tagged by GATE without a role).
- name = the person's own surface text (nested <persName> excluded); given/surname/gender/age/occupation/place/aliases
  come from <interp> children and persNameOccupation / persNamePlace / nameAlias joins (first value wins for interps —
  no repeated interp types were found in the corpus sample).
- <lb/> inside text: joined without a space (hyphenation-style breaks are the majority) unless the break sits between a
  word character and an upper-case letter, where a space is inserted.
- punishments: attached via defendantPunishment joins file-wide (part-1 sentences sit in a separate punishmentSummary
  div; a few joins point across trial divs — kept as the source has them, and the punishment row records the trial div
  it was found in). An in-trial punishment with no join anywhere is kept with defendant_ids = [].
- charges: criminalCharge joins; target ids that resolve to nothing in the trial are kept in `unresolved_ids`.
- sessions.summary_items: every <rs> outside a trialAccount div (offence/verdict/punishment/alias/occupation/crimeDate) with its
  category, text, containing div and joined ids — the 1670s–80s sessions record outcomes in supplementaryMaterial, not trials.
"""
import re, sys, json, collections
from pathlib import Path
from lxml import etree
import polars as pl

ROOT = Path(sys.argv[1]); OUT = Path(sys.argv[2]); OUT.mkdir(parents=True, exist_ok=True)
LIMIT = int(sys.argv[sys.argv.index("--limit") + 1]) if "--limit" in sys.argv else None
STATS = "--stats" in sys.argv
STRICT = etree.XMLParser(huge_tree=True)
LENIENT = etree.XMLParser(recover=True, huge_tree=True)
WS = re.compile(r"\s+")
ENC_RE = re.compile(rb'^<\?xml[^>]*encoding\s*=\s*["\']([A-Za-z0-9._-]+)["\']')

stats = collections.Counter(); warnings = []


def read_xml(path):
    """Return (root, verbatim_text). Decode with the declared encoding; parse strictly, fall back to recovery + warn."""
    raw = path.read_bytes()
    m = ENC_RE.match(raw[:200]); enc = m.group(1).decode() if m else "utf-8"
    if raw.startswith(b"\xef\xbb\xbf"): enc = "utf-8-sig"
    elif raw.startswith((b"\xff\xfe", b"\xfe\xff")): enc = "utf-16"
    try: text = raw.decode(enc)   # verbatim column must be lossless: no errors="replace"
    except (UnicodeDecodeError, LookupError) as e:
        raise SystemExit(f"{path.name}: cannot decode with declared encoding {enc!r}: {e}")
    try: root = etree.fromstring(raw, STRICT)
    except etree.XMLSyntaxError as e:
        root = etree.fromstring(raw, LENIENT); warnings.append(f"{path.name}: recovered parse ({str(e)[:80]})"); stats["recovered_parse"] += 1
    return root, text


def norm(s): return WS.sub(" ", s or "").strip()


def _collect(el, parts, skip_tag=None):
    if el.tag == "lb": parts.append("\x00")
    elif el.text: parts.append(el.text)
    for c in el:
        if not (skip_tag is not None and c.tag == skip_tag): _collect(c, parts, skip_tag)
        if c.tail: parts.append(c.tail)


def text_of(el, skip_tag=None):
    parts = []; _collect(el, parts, skip_tag)
    s = "".join(parts)
    s = re.sub(r"(\w)\x00(?=[A-Z])", r"\1 ", s).replace("\x00", "")
    return norm(s)


def interps(el):
    d = {}
    for i in el.findall("interp"): d.setdefault(i.get("type"), i.get("value"))
    return d


def parse_person(p):
    d = interps(p)
    has_nested = p.find(".//persName") is not None
    name = text_of(p, skip_tag="persName")
    if (has_nested or not name) and (d.get("given") or d.get("surname")): name = norm(f"{d.get('given') or ''} {d.get('surname') or ''}")
    if not name: name = text_of(p)
    return {"id": p.get("id"), "type": (p.get("type").replace("Name", "") if p.get("type") else None),
            "name": name, "given": d.get("given"), "surname": d.get("surname"), "gender": d.get("gender"), "age": d.get("age"),
            "occupation": d.get("occupation"), "place": None, "aliases": []}


def parse_rs(rs):
    d = interps(rs)
    return {**d, "id": rs.get("id"), "text": text_of(rs)}


trials, oas, sessions = [], [], []


def index_file(root):
    """File-level indexes: rs by id, persons by id (enriched from joins), places, joins by member id."""
    all_rs = {rs.get("id"): (rs, parse_rs(rs)) for rs in root.iter("rs") if rs.get("id")}
    all_place = {x.get("id"): text_of(x) for x in root.iter("placeName") if x.get("id")}
    pers_el = [p for p in root.iter("persName")]
    all_pers = {p.get("id"): parse_person(p) for p in pers_el if p.get("id")}
    joins = collections.defaultdict(list); by_member = collections.defaultdict(list)
    for j in root.iter("join"):
        res, targets = j.get("result"), j.get("targets", "").split()
        stats[f"join:{res}"] += 1; joins[res].append(targets)
        for t in targets: by_member[t].append((res, targets))
    for pid, per in all_pers.items():   # enrich persons from joins, once, file-wide
        for res, targets in by_member.get(pid, []):
            others = [t for t in targets if t != pid]
            if res == "persNameOccupation" and per["occupation"] is None:
                for t in others:
                    if t in all_rs: per["occupation"] = all_rs[t][1]["text"]
            elif res == "persNamePlace" and per["place"] is None:
                for t in others:
                    if t in all_place: per["place"] = all_place[t]
            elif res == "nameAlias":
                for t in others:
                    if t in all_rs and all_rs[t][1]["text"] not in per["aliases"]: per["aliases"].append(all_rs[t][1]["text"])
    return all_rs, all_place, all_pers, pers_el, joins, by_member


def parse_session(path):
    root, raw_text = read_xml(path)
    if root is None: stats["unparseable"] += 1; return
    session_id = path.stem
    all_rs, all_place, all_pers, pers_el, joins, by_member = index_file(root)
    rs_div = {}
    for rs in root.iter("rs"):
        if rs.get("id"):
            anc = next(rs.iterancestors("div1"), None); rs_div[rs.get("id")] = anc.get("id") if anc is not None else None
    body = root.find(".//body")
    div_types = collections.Counter(d.get("type") for d in root.iter("div1"))
    summary_items = []   # rs elements outside trialAccount divs (supplementaryMaterial / punishmentSummary / no div): early sessions record outcomes here
    for rs in root.iter("rs"):
        anc = next(rs.iterancestors("div1"), None)
        if rs.get("id") and (anc is None or anc.get("type") != "trialAccount"):
            d = all_rs[rs.get("id")][1]
            linked = sorted({t for res, targets in by_member.get(rs.get("id"), []) for t in targets if t != rs.get("id")})
            cat = d.get("offenceCategory") or d.get("verdictCategory") or d.get("punishmentCategory")
            sub = d.get("offenceSubcategory") or d.get("verdictSubcategory") or d.get("punishmentSubcategory")
            summary_items.append({"id": rs.get("id"), "type": rs.get("type"), "category": cat, "subcategory": sub, "text": d["text"],
                                  "found_in": anc.get("id") if anc is not None else None, "linked_ids": linked})
            stats[f"summary_item:{rs.get('type')}"] += 1
    sessions.append({"summary_items": summary_items, "session_id": session_id, "date": session_id[:8], "part": 1 if session_id[:8] <= "18341024" else 2,
                     "text": text_of(body) if body is not None else text_of(root), "xml": raw_text, "n_trials": div_types.get("trialAccount", 0),
                     "div_types": json.dumps(dict(div_types)), "persons": [all_pers[p.get("id")] if p.get("id") else parse_person(p) for p in pers_el],
                     "places": [text_of(x) for x in root.iter("placeName")], "obo_url": f"https://www.oldbaileyonline.org/browse.jsp?name={session_id}"})
    for div in root.iter("div1"):
        stats[f"div1:{div.get('type')}"] += 1
        if div.get("type") != "trialAccount": continue
        tid = div.get("id"); di = interps(div)
        persons = [all_pers[p.get("id")] if p.get("id") else parse_person(p) for p in div.iter("persName")]
        def_ids = [p["id"] for p in persons if p["type"] == "defendant" and p["id"]]   # source order
        def_set = set(def_ids)
        offences = [parse_rs(rs) for rs in div.iter("rs") if rs.get("type") == "offenceDescription"]
        verdicts = [parse_rs(rs) for rs in div.iter("rs") if rs.get("type") == "verdictDescription"]
        off_ids = {o["id"] for o in offences}; ver_ids = {v["id"] for v in verdicts}
        for o in offences:
            o["victim_ids"] = []; o["crime_date"] = None; o["place"] = None
            for res, targets in by_member.get(o["id"], []):
                others = [t for t in targets if t != o["id"]]
                if res == "offenceVictim": o["victim_ids"] += others
                elif res == "offencePlace":
                    for t in others:
                        if t in all_place: o["place"] = all_place[t]
                elif res == "offenceCrimeDate":
                    for t in others:
                        if t in all_rs: o["crime_date"] = all_rs[t][1]["text"]
        charges = []
        for targets in joins.get("criminalCharge", []):
            if not any(t in def_set for t in targets): continue
            unresolved = [t for t in targets if t not in def_set and t not in off_ids and t not in ver_ids]
            if unresolved: stats["charge_unresolved_targets"] += 1
            charges.append({"defendant_ids": [t for t in targets if t in def_set], "offence_ids": [t for t in targets if t in off_ids],
                            "verdict_ids": [t for t in targets if t in ver_ids], "unresolved_ids": unresolved})
        pun_rows = {}
        for d_id in def_ids:   # deterministic: defendant source order
            for res, targets in by_member.get(d_id, []):
                if res != "defendantPunishment": continue
                for t in targets:
                    if t in all_rs and all_rs[t][0].get("type") == "punishmentDescription":
                        row = pun_rows.setdefault(t, {**all_rs[t][1], "defendant_ids": [], "found_in": rs_div.get(t)})
                        if d_id not in row["defendant_ids"]: row["defendant_ids"].append(d_id)
                        if rs_div.get(t) not in (None, tid): stats["punishment_cross_trial"] += 1
        for rs in div.iter("rs"):   # every punishment whose text lives in this trial, with whatever defendants the joins name (possibly another trial's)
            pid = rs.get("id")
            if rs.get("type") == "punishmentDescription" and pid and pid not in pun_rows:
                joined = [t for res, targets in by_member.get(pid, []) if res == "defendantPunishment" for t in targets if t != pid and t in all_pers]
                pun_rows[pid] = {**parse_rs(rs), "defendant_ids": joined, "found_in": tid}
                if not joined: stats["punishment_unjoined"] += 1
                elif not any(j in def_set for j in joined): stats["punishment_text_here_defendant_elsewhere"] += 1
        trials.append({
            "trial_id": tid, "session_id": session_id, "date": di.get("date") or session_id[:8], "part": 1 if session_id[:8] <= "18341024" else 2,
            "text": text_of(div), "xml": etree.tostring(div, encoding="unicode"), "n_defendants": len(def_ids), "persons": persons,
            "offences": [{"id": o["id"], "category": o.get("offenceCategory"), "subcategory": o.get("offenceSubcategory"), "text": o["text"],
                          "crime_date": o["crime_date"], "place": o["place"], "victim_ids": o["victim_ids"]} for o in offences],
            "verdicts": [{"id": v["id"], "category": v.get("verdictCategory"), "subcategory": v.get("verdictSubcategory"), "text": v["text"]} for v in verdicts],
            "punishments": [{"id": p["id"], "category": p.get("punishmentCategory"), "subcategory": p.get("punishmentSubcategory"), "text": p["text"],
                             "defendant_ids": p["defendant_ids"], "found_in": p["found_in"]} for p in pun_rows.values()],
            "charges": charges, "places": [text_of(x) for x in div.iter("placeName")],
            "obo_url": f"https://www.oldbaileyonline.org/browse.jsp?div={tid}"})
        stats["trials"] += 1


def parse_oa(path):
    root, raw_text = read_xml(path)
    if root is None: stats["unparseable_oa"] += 1; return
    _, _, all_pers, pers_el, _, _ = index_file(root)
    div = root.find(".//div0"); di = interps(div) if div is not None else {}
    body = root.find(".//body")
    oas.append({"oa_id": path.stem, "date": di.get("date") or path.stem[2:10], "text": text_of(body) if body is not None else text_of(root), "xml": raw_text,
                "persons": [all_pers[p.get("id")] if p.get("id") else parse_person(p) for p in pers_el],
                "places": [text_of(x) for x in root.iter("placeName")], "obo_url": f"https://www.oldbaileyonline.org/browse.jsp?name={path.stem}"})
    stats["oa"] += 1


files = sorted((ROOT / "sessionsPapers").glob("*.xml"))
if LIMIT: files = files[::max(1, len(files) // LIMIT)][:LIMIT]
for i, f in enumerate(files):
    parse_session(f)
    if i % 200 == 0: print(f"{i}/{len(files)} {f.name} trials so far {stats['trials']}", flush=True)
oa_files = sorted((ROOT / "ordinarysAccounts").glob("*.xml"))
if LIMIT: oa_files = oa_files[:max(2, LIMIT // 5)]
for f in oa_files: parse_oa(f)

used = set()
for t in trials:   # source quirk: a few supplementary items share an id (e.g. s16980504-1) — suffix collision-safely and report
    base = t["trial_id"]
    if base in used:
        k = 2
        while f"{base}-dup{k}" in used: k += 1
        t["trial_id"] = f"{base}-dup{k}"; stats["dup_trial_id"] += 1; warnings.append(f"duplicate trial id {base} -> {t['trial_id']}")
    used.add(t["trial_id"])

PERSON = pl.Struct({"id": pl.Utf8, "type": pl.Utf8, "name": pl.Utf8, "given": pl.Utf8, "surname": pl.Utf8, "gender": pl.Utf8, "age": pl.Utf8,
                    "occupation": pl.Utf8, "place": pl.Utf8, "aliases": pl.List(pl.Utf8)})
SCHEMA = {
    "trial_id": pl.Utf8, "session_id": pl.Utf8, "date": pl.Utf8, "part": pl.Int8, "text": pl.Utf8, "xml": pl.Utf8, "n_defendants": pl.Int32,
    "persons": pl.List(PERSON),
    "offences": pl.List(pl.Struct({"id": pl.Utf8, "category": pl.Utf8, "subcategory": pl.Utf8, "text": pl.Utf8, "crime_date": pl.Utf8, "place": pl.Utf8, "victim_ids": pl.List(pl.Utf8)})),
    "verdicts": pl.List(pl.Struct({"id": pl.Utf8, "category": pl.Utf8, "subcategory": pl.Utf8, "text": pl.Utf8})),
    "punishments": pl.List(pl.Struct({"id": pl.Utf8, "category": pl.Utf8, "subcategory": pl.Utf8, "text": pl.Utf8, "defendant_ids": pl.List(pl.Utf8), "found_in": pl.Utf8})),
    "charges": pl.List(pl.Struct({"defendant_ids": pl.List(pl.Utf8), "offence_ids": pl.List(pl.Utf8), "verdict_ids": pl.List(pl.Utf8), "unresolved_ids": pl.List(pl.Utf8)})),
    "places": pl.List(pl.Utf8), "obo_url": pl.Utf8,
}
df = pl.from_dicts(trials, schema=SCHEMA); assert df["trial_id"].n_unique() == df.height
df.write_parquet(OUT / "trials.parquet", compression="zstd")
oa = pl.from_dicts(oas, schema={"oa_id": pl.Utf8, "date": pl.Utf8, "text": pl.Utf8, "xml": pl.Utf8, "persons": pl.List(PERSON), "places": pl.List(pl.Utf8), "obo_url": pl.Utf8})
oa.write_parquet(OUT / "ordinarys_accounts.parquet", compression="zstd")
ses = pl.from_dicts(sessions, schema={"session_id": pl.Utf8, "date": pl.Utf8, "part": pl.Int8, "text": pl.Utf8, "xml": pl.Utf8, "n_trials": pl.Int32, "div_types": pl.Utf8,
                                      "persons": pl.List(PERSON), "places": pl.List(pl.Utf8),
                                      "summary_items": pl.List(pl.Struct({"id": pl.Utf8, "type": pl.Utf8, "category": pl.Utf8, "subcategory": pl.Utf8, "text": pl.Utf8, "found_in": pl.Utf8, "linked_ids": pl.List(pl.Utf8)})),
                                      "obo_url": pl.Utf8})
ses.write_parquet(OUT / "sessions.parquet", compression="zstd")
print("\nwrote", df.shape, "trials;", ses.shape, "sessions;", oa.shape, "OA")
(OUT / "parse_warnings.txt").write_text("\n".join(warnings))
if warnings: print(f"{len(warnings)} parse warnings -> {OUT / 'parse_warnings.txt'}")
if STATS:
    for k, v in sorted(stats.items()): print(f"  {k:32s} {v}")
    g = df.filter(pl.col("verdicts").list.eval(pl.element().struct.field("category") == "guilty").list.any())
    print("guilty trials:", g.height, "| guilty with 0 punishments:", g.filter(pl.col("punishments").list.len() == 0).height)
    print("trials with 0 offences:", df.filter(pl.col("offences").list.len() == 0).height, "| 0 charges:", df.filter(pl.col("charges").list.len() == 0).height,
          "| punishments with no defendant:", df.explode("punishments").filter(pl.col("punishments").struct.field("defendant_ids").list.len() == 0).height)