"""
Wiktionary Verification Script (v2 - with corrected title building)
Verifies that entries sourced from Wiktionary actually exist on Wiktionary
by querying the MediaWiki API.

Key fixes from v1:
- Preserve trailing dashes for reconstruction forms (PIE, Semitic, etc.)
- Use "Proto-Hellenic" instead of "Proto-Greek" for grk-pro
- Batch queries (up to 50 titles per API call) for efficiency
"""

import csv
import json
import random
import sys
import time
from pathlib import Path

# Force UTF-8 output on Windows
if sys.platform == "win32":
    sys.stdout.reconfigure(encoding="utf-8", errors="replace")
    sys.stderr.reconfigure(encoding="utf-8", errors="replace")

import requests

LEXICON_DIR = Path(r"C:\Users\alvin\hf-ancient-scripts\data\training\lexicons")
API_URL = "https://en.wiktionary.org/w/api.php"
SAMPLE_SIZE = 20
RATE_LIMIT = 0.5  # seconds between API requests

# Wiktionary requires a proper User-Agent header per their API policy
SESSION = requests.Session()
SESSION.headers.update({
    "User-Agent": "AncientScriptsVerifier/1.0 (https://github.com/; academic research) python-requests",
})

# Mapping from ISO code to Wiktionary reconstruction namespace language name
# NOTE: grk-pro uses "Proto-Hellenic" on Wiktionary, NOT "Proto-Greek"
RECONSTRUCTION_LANGS = {
    "ine-pro": "Proto-Indo-European",
    "sem-pro": "Proto-Semitic",
    "ccs-pro": "Proto-Kartvelian",
    "dra-pro": "Proto-Dravidian",
    "grk-pro": "Proto-Hellenic",
}

# Human-readable names for all languages
LANG_NAMES = {
    "hit": "Hittite",
    "uga": "Ugaritic",
    "phn": "Phoenician",
    "ave": "Avestan",
    "peo": "Old Persian",
    "xpg": "Phrygian",
    "xle": "Lemnian",
    "cms": "Messapic",
    "elx": "Elamite",
    "ett": "Etruscan",
    "xcr": "Carian",
    "xlc": "Lycian",
    "xld": "Lydian",
    "xlw": "Luwian",
    "xrr": "Raetic",
    "xur": "Urartian",
    "txb": "Tocharian B",
    "xto": "Tocharian A",
    "xhu": "Hurrian",
    "ine-pro": "Proto-Indo-European",
    "sem-pro": "Proto-Semitic",
    "ccs-pro": "Proto-Kartvelian",
    "dra-pro": "Proto-Dravidian",
    "grk-pro": "Proto-Greek (Proto-Hellenic on Wiktionary)",
}


def load_wiktionary_entries(lang_code: str) -> list[dict]:
    """Load entries from a TSV where Source contains 'wiktionary'."""
    tsv_path = LEXICON_DIR / f"{lang_code}.tsv"
    entries = []
    with open(tsv_path, "r", encoding="utf-8") as f:
        reader = csv.DictReader(f, delimiter="\t")
        for row in reader:
            src = row.get("Source", "")
            if "wiktionary" in src.lower():
                entries.append(row)
    return entries


def build_wiktionary_title(word: str, lang_code: str) -> str:
    """Build the Wiktionary page title for a given word and language.

    For reconstruction languages, uses Reconstruction: namespace.
    IMPORTANT: Trailing dashes are PRESERVED for reconstruction forms,
    as Wiktionary uses them in page titles (e.g., h₃rewk- not h₃rewk).
    """
    clean = word.strip()

    if lang_code in RECONSTRUCTION_LANGS:
        lang_name = RECONSTRUCTION_LANGS[lang_code]
        # Remove leading * only. Keep trailing - (Wiktionary uses it!)
        stem = clean.lstrip("*").strip()
        return f"Reconstruction:{lang_name}/{stem}"

    # For regular languages, use the word directly
    # Remove leading hyphens (morphological prefix markers)
    clean = clean.lstrip("-")
    return clean


def query_wiktionary_batch(titles: list[str]) -> dict[str, bool]:
    """Query Wiktionary API for up to 50 titles at once.
    Returns dict mapping title -> exists (bool).
    """
    results = {}
    for i in range(0, len(titles), 50):
        batch = titles[i:i + 50]
        params = {
            "action": "query",
            "titles": "|".join(batch),
            "format": "json",
        }
        try:
            resp = SESSION.get(API_URL, params=params, timeout=15)
            resp.raise_for_status()
            data = resp.json()
            pages = data.get("query", {}).get("pages", {})

            # Track normalization mapping
            normalized = {}
            for n in data.get("query", {}).get("normalized", []):
                normalized[n["to"]] = n["from"]

            for page_id, page_info in pages.items():
                api_title = page_info.get("title", "")
                exists = int(page_id) != -1 and "missing" not in page_info
                orig_title = normalized.get(api_title, api_title)
                results[orig_title] = exists
                results[api_title] = exists

        except Exception as e:
            for t in batch:
                results[t] = False
            print(f"    API error for batch: {e}")

        if i + 50 < len(titles):
            time.sleep(RATE_LIMIT)

    return results


def verify_language(lang_code: str, rng: random.Random) -> dict:
    """Verify a sample of entries for one language."""
    entries = load_wiktionary_entries(lang_code)
    if not entries:
        return {
            "lang": lang_code,
            "lang_name": LANG_NAMES.get(lang_code, lang_code),
            "total_entries": 0,
            "sampled": 0,
            "verified": 0,
            "not_found": 0,
            "verification_rate": 0,
            "results": [],
        }

    sample_size = min(SAMPLE_SIZE, len(entries))
    sample = rng.sample(entries, sample_size)

    # Build titles
    word_to_title = {}
    for entry in sample:
        word = entry["Word"]
        title = build_wiktionary_title(word, lang_code)
        word_to_title[word] = title

    # Batch query
    unique_titles = list(set(word_to_title.values()))
    existence_map = query_wiktionary_batch(unique_titles)

    # Build results
    results = []
    for entry in sample:
        word = entry["Word"]
        title = word_to_title[word]
        exists = existence_map.get(title, False)
        results.append({
            "original_word": word,
            "query_title": title,
            "exists": exists,
        })

    verified = sum(1 for r in results if r["exists"])
    not_found = sum(1 for r in results if not r["exists"])

    return {
        "lang": lang_code,
        "lang_name": LANG_NAMES.get(lang_code, lang_code),
        "total_entries": len(entries),
        "sampled": sample_size,
        "verified": verified,
        "not_found": not_found,
        "verification_rate": verified / sample_size * 100 if sample_size > 0 else 0,
        "results": results,
    }


def main():
    rng = random.Random(42)

    # Discover all languages with wiktionary sources
    all_langs = []
    for tsv in sorted(LEXICON_DIR.glob("*.tsv")):
        lang_code = tsv.stem
        with open(tsv, "r", encoding="utf-8") as f:
            content = f.read()
        if "\twiktionary" in content.lower():
            all_langs.append(lang_code)

    print(f"Found {len(all_langs)} languages with Wiktionary sources: {', '.join(all_langs)}")
    print(f"Sampling up to {SAMPLE_SIZE} entries per language")
    print("=" * 100)

    all_results = []
    total_sampled = 0
    total_verified = 0
    total_not_found = 0
    flagged_words = []

    for i, lang_code in enumerate(all_langs):
        print(f"\n[{i+1}/{len(all_langs)}] Verifying {lang_code} ({LANG_NAMES.get(lang_code, '?')})...")
        result = verify_language(lang_code, rng)
        all_results.append(result)

        total_sampled += result["sampled"]
        total_verified += result["verified"]
        total_not_found += result["not_found"]

        for r in result["results"]:
            if not r["exists"]:
                flagged_words.append({
                    "lang": lang_code,
                    "lang_name": LANG_NAMES.get(lang_code, lang_code),
                    "word": r["original_word"],
                    "query_title": r["query_title"],
                })

        # Progress
        print(f"  Total entries: {result['total_entries']}, Sampled: {result['sampled']}, "
              f"Verified: {result['verified']}, Not found: {result['not_found']} "
              f"({result['verification_rate']:.0f}% verified)")
        if result["not_found"] > 0:
            missing = [r for r in result["results"] if not r["exists"]]
            for m in missing[:5]:
                print(f"    NOT FOUND: '{m['original_word']}' (queried as: '{m['query_title']}')")
            if len(missing) > 5:
                print(f"    ... and {len(missing) - 5} more")

    # === SUMMARY ===
    print("\n" + "=" * 100)
    print("SUMMARY")
    print("=" * 100)
    print(f"\nTotal languages checked: {len(all_langs)}")
    print(f"Total entries sampled: {total_sampled}")
    print(f"Total verified on Wiktionary: {total_verified}")
    print(f"Total NOT found: {total_not_found}")
    if total_sampled > 0:
        print(f"Overall verification rate: {total_verified / total_sampled * 100:.1f}%")

    print("\n" + "-" * 100)
    print("PER-LANGUAGE BREAKDOWN (sorted by verification rate)")
    print("-" * 100)
    header = f"{'Lang':<10} {'Name':<42} {'Total':<8} {'Sampled':<9} {'Verified':<9} {'Not Found':<10} {'Rate':<8}"
    print(header)
    print("-" * 100)
    for r in sorted(all_results, key=lambda x: x["verification_rate"]):
        print(f"{r['lang']:<10} {r['lang_name']:<42} {r['total_entries']:<8} {r['sampled']:<9} "
              f"{r['verified']:<9} {r['not_found']:<10} {r['verification_rate']:.0f}%")

    # Categorize results
    high_confidence = [r for r in all_results if r["verification_rate"] >= 80]
    medium_confidence = [r for r in all_results if 40 <= r["verification_rate"] < 80]
    low_confidence = [r for r in all_results if r["verification_rate"] < 40]

    print("\n" + "=" * 100)
    print("INTERPRETATION")
    print("=" * 100)

    if high_confidence:
        print(f"\nHIGH CONFIDENCE (>=80% verified) - {len(high_confidence)} languages:")
        print("  These entries are strongly validated as real Wiktionary content.")
        for r in sorted(high_confidence, key=lambda x: -x["verification_rate"]):
            print(f"    {r['lang']:<10} {r['lang_name']:<40} {r['verification_rate']:.0f}%")

    if medium_confidence:
        print(f"\nMEDIUM CONFIDENCE (40-79% verified) - {len(medium_confidence)} languages:")
        print("  Many entries verified, but some may use different transliteration/spelling conventions.")
        print("  The unverified entries may still be real but use non-standard forms.")
        for r in sorted(medium_confidence, key=lambda x: -x["verification_rate"]):
            print(f"    {r['lang']:<10} {r['lang_name']:<40} {r['verification_rate']:.0f}%")

    if low_confidence:
        print(f"\nLOW CONFIDENCE (<40% verified) - {len(low_confidence)} languages:")
        print("  These may be from Wiktionary appendices/categories rather than individual pages,")
        print("  or use significantly different transliteration conventions than Wiktionary page titles.")
        for r in sorted(low_confidence, key=lambda x: -x["verification_rate"]):
            print(f"    {r['lang']:<10} {r['lang_name']:<40} {r['verification_rate']:.0f}%")

    if flagged_words:
        print("\n" + "-" * 100)
        print(f"ALL FLAGGED WORDS NOT FOUND ON WIKTIONARY ({len(flagged_words)} total)")
        print("-" * 100)
        current_lang = None
        for fw in flagged_words:
            if fw["lang"] != current_lang:
                current_lang = fw["lang"]
                print(f"\n  [{fw['lang']}] {fw['lang_name']}:")
            print(f"    word='{fw['word']}'  queried='{fw['query_title']}'")

    # Save detailed results
    output_path = Path(r"C:\Users\alvin\hf-ancient-scripts\wiktionary_verification_results.json")
    with open(output_path, "w", encoding="utf-8") as f:
        json.dump({
            "summary": {
                "total_languages": len(all_langs),
                "total_sampled": total_sampled,
                "total_verified": total_verified,
                "total_not_found": total_not_found,
                "overall_verification_rate": total_verified / total_sampled * 100 if total_sampled > 0 else 0,
            },
            "per_language": all_results,
            "flagged_words": flagged_words,
        }, f, indent=2, ensure_ascii=False)
    print(f"\nDetailed results saved to: {output_path}")


if __name__ == "__main__":
    main()