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#!/usr/bin/env python3
"""Build the reproducible, source-level OOD set from a Tatoeba export.

The export is intentionally not committed. The resulting JSONL contains the
selected text plus source IDs and hashes so the published set can be audited.
"""
import argparse
import hashlib
import json
import tarfile
import urllib.request
from collections import Counter, defaultdict
from datetime import date
from pathlib import Path

SOURCE_URL = "https://downloads.tatoeba.org/exports/sentences.tar.bz2"
SOURCE_SHA256 = "8117f33886e94c3d371f1f13d0efa120a8172d67eb7006b2656c444c012645d0"
SOURCE_RELEASE = "2026-07-18 export (archive last-modified date)"
TOTAL_PER_CLASS = 8772
LANGUAGES = {
    "afr": "Afrikaans", "ara": "Arabic", "asm": "Assamese", "ben": "Bengali",
    "bul": "Bulgarian", "cat": "Catalan", "ces": "Czech", "cmn": "Mandarin Chinese",
    "dan": "Danish", "deu": "German", "ell": "Greek", "epo": "Esperanto",
    "eus": "Basque", "fin": "Finnish", "fra": "French", "gle": "Irish",
    "glg": "Galician", "hau": "Hausa", "heb": "Hebrew", "hin": "Hindi",
    "hrv": "Croatian", "hun": "Hungarian", "hye": "Armenian", "ind": "Indonesian",
    "isl": "Icelandic", "ita": "Italian", "jpn": "Japanese", "kor": "Korean",
    "lit": "Lithuanian", "lvs": "Latvian", "mar": "Marathi", "mkd": "Macedonian",
    "mon": "Mongolian", "nld": "Dutch", "nno": "Norwegian Nynorsk",
    "nob": "Norwegian Bokmal", "pol": "Polish", "por": "Portuguese",
    "ron": "Romanian", "rus": "Russian", "slk": "Slovak", "slv": "Slovenian",
    "spa": "Spanish", "srp": "Serbian", "swe": "Swedish", "swh": "Swahili",
    "tat": "Tatar", "tha": "Thai", "tur": "Turkish", "ukr": "Ukrainian",
    "vie": "Vietnamese", "yid": "Yiddish",
}


def normalize(text):
    return " ".join(text.split()).strip()


def digest(text):
    return hashlib.sha256(text.encode("utf-8")).hexdigest()


def bucket(text):
    size = len(text.encode("utf-8"))
    if size <= 32:
        return "short"
    if size <= 96:
        return "medium"
    return "long"


def add_candidate(heaps, lang, capacity, source_id, text):
    """Keep the lexicographically smallest stable hashes per language."""
    import heapq

    text_hash = digest(text)
    key = (text_hash, str(source_id))
    heap = heaps[lang]
    item = (key[0], key[1], text)
    if len(heap) < capacity:
        heapq.heappush(heap, (-int(key[0], 16), key[1], text))
    elif int(key[0], 16) < -heap[0][0]:
        heapq.heapreplace(heap, (-int(key[0], 16), key[1], text))


def download(path):
    if path.exists():
        return
    path.parent.mkdir(parents=True, exist_ok=True)
    urllib.request.urlretrieve(SOURCE_URL, path)


def sha256_file(path):
    h = hashlib.sha256()
    with path.open("rb") as f:
        for block in iter(lambda: f.read(1024 * 1024), b""):
            h.update(block)
    return h.hexdigest()


def main():
    parser = argparse.ArgumentParser()
    parser.add_argument("--source", type=Path, required=True)
    parser.add_argument("--output", type=Path, required=True)
    parser.add_argument("--manifest", type=Path, required=True)
    args = parser.parse_args()

    actual_sha256 = sha256_file(args.source)
    if actual_sha256 != SOURCE_SHA256:
        raise SystemExit(f"source checksum mismatch: {actual_sha256} != {SOURCE_SHA256}")

    targets = {"eng": TOTAL_PER_CLASS}
    non_english = sorted(LANGUAGES)
    base, remainder = divmod(TOTAL_PER_CLASS, len(non_english))
    targets.update({lang: base + (i < remainder) for i, lang in enumerate(non_english)})
    heaps = defaultdict(list)
    seen_rows = 0
    with tarfile.open(args.source, "r:bz2") as archive:
        member = archive.extractfile("sentences.csv")
        if member is None:
            raise SystemExit("sentences.csv missing from source archive")
        for raw in member:
            seen_rows += 1
            if seen_rows == 1:
                continue
            parts = raw.decode("utf-8").rstrip("\n").split("\t", 2)
            if len(parts) != 3:
                continue
            source_id, lang, raw_text = parts
            if lang not in targets:
                continue
            text = normalize(raw_text)
            encoded = text.encode("utf-8")
            if not 3 <= len(text) <= 276 or len(encoded) > 256:
                continue
            if not any(ch.isalpha() for ch in text):
                continue
            add_candidate(heaps, lang, targets[lang] * 4, source_id, text)

    rows = []
    used_text_hashes = set()
    for lang in ["eng", *non_english]:
        candidates = sorted(heaps[lang], key=lambda item: (item[0] * -1, item[1]))
        label = "EN" if lang == "eng" else "NOT-EN"
        selected = 0
        for _, source_id, text in candidates:
            text_hash = digest(text)
            if text_hash in used_text_hashes:
                continue
            used_text_hashes.add(text_hash)
            rows.append({
                "id": f"tatoeba-{source_id}-{lang}",
                "text": text,
                "label": label,
                "language": "en" if lang == "eng" else lang,
                "language_name": "English" if lang == "eng" else LANGUAGES[lang],
                "category": bucket(text),
                "source": "Tatoeba",
                "source_release": SOURCE_RELEASE,
                "source_id": source_id,
                "source_url": f"https://tatoeba.org/en/sentences/show/{source_id}",
                "text_sha256": digest(text),
                "utf8_bytes": len(text.encode("utf-8")),
            })
            selected += 1
            if selected == targets[lang]:
                break
        if selected != targets[lang]:
            raise SystemExit(f"not enough unique rows for {lang}: {selected}/{targets[lang]}")

    if len(rows) != TOTAL_PER_CLASS * 2:
        raise SystemExit(f"wrong row count: {len(rows)}")
    if len({row["text_sha256"] for row in rows}) != len(rows):
        raise SystemExit("duplicate normalized text hashes found")
    counts = Counter(row["language"] for row in rows)
    if counts["en"] != TOTAL_PER_CLASS or len(counts) != 53:
        raise SystemExit(f"wrong composition: {counts}")

    args.output.parent.mkdir(parents=True, exist_ok=True)
    with args.output.open("w", encoding="utf-8") as f:
        for row in rows:
            f.write(json.dumps(row, ensure_ascii=False, sort_keys=True) + "\n")

    manifest = {
        "dataset_name": "en-or-not OOD set",
        "created": str(date.today()),
        "source": {
            "name": "Tatoeba sentence export",
            "url": SOURCE_URL,
            "release": SOURCE_RELEASE,
            "sha256": actual_sha256,
            "license": "CC-BY 2.0",
        },
        "selection": {
            "seed": "sha256(text)",
            "total_examples": len(rows),
            "english_examples": counts["en"],
            "non_english_examples": len(rows) - counts["en"],
            "non_english_languages": sorted(LANGUAGES),
            "language_counts": dict(sorted(counts.items())),
            "max_utf8_bytes": 256,
            "filters": ["3-276 Unicode characters", "3-256 UTF-8 bytes", "contains a letter", "normalized whitespace"],
        },
        "exclusion_boundary": {
            "documented_training_sources": [
                "Project Gutenberg collections",
                "papluca/language-identification",
                "oscar-corpus/oscar (optional)",
            ],
            "guarantee": "source-level exclusion only; zero lexical overlap with undisclosed training artifacts is not guaranteed",
        },
    }
    args.manifest.write_text(json.dumps(manifest, ensure_ascii=False, indent=2) + "\n", encoding="utf-8")
    print(json.dumps({"rows": len(rows), "languages": len(counts), "sha256": actual_sha256}, indent=2))


if __name__ == "__main__":
    main()