"""
Normalize scraped hotel data → backend hotels.json seeder schema.
Outputs to scraped_data/hotels_international.json (separate from VN hotels).
"""

import json
import logging
import re
import os
from typing import Optional

from scripts.scrapers.config import PATHS

logger = logging.getLogger(__name__)

# Default vendor ID for scraped hotels (system vendor)
DEFAULT_VENDOR_ID = "000000000000000000000001"

HOTEL_AMENITY_NORMALIZE = {
    "wifi": "Free WiFi",
    "wi-fi": "Free WiFi",
    "internet": "Free WiFi",
    "pool": "Swimming Pool",
    "swimming": "Swimming Pool",
    "gym": "Gym",
    "fitness": "Gym",
    "spa": "Spa",
    "restaurant": "Restaurant",
    "bar": "Bar",
    "parking": "Parking",
    "airport": "Airport Shuttle",
    "shuttle": "Airport Shuttle",
    "breakfast": "Breakfast Included",
    "air conditioning": "Air Conditioning",
    "ac": "Air Conditioning",
    "front desk": "24-hour Front Desk",
    "24-hour": "24-hour Front Desk",
    "laundry": "Laundry Service",
    "concierge": "Concierge",
    "business": "Business Center",
    "meeting": "Meeting Rooms",
    "room service": "Room Service",
}


def _slugify(text: str) -> str:
    text = text.lower().strip()
    text = re.sub(r"[^\w\s-]", "", text)
    text = re.sub(r"[\s_-]+", "-", text)
    return text[:80]


def _normalize_amenities(raw_amenities: list) -> list:
    """Normalize amenity strings to standardized names."""
    normalized = set()
    for amenity in raw_amenities:
        if not amenity:
            continue
        lower = amenity.lower()
        matched = False
        for keyword, standard in HOTEL_AMENITY_NORMALIZE.items():
            if keyword in lower:
                normalized.add(standard)
                matched = True
                break
        if not matched and len(amenity) > 2:
            normalized.add(amenity.title())
    return sorted(list(normalized))[:15]  # Cap at 15 amenities


def _convert_price_to_vnd(price_usd: Optional[float], exchange_rate: float = 25000) -> int:
    """Convert USD price/night to VND."""
    if not price_usd:
        return 1_000_000  # Default ~$40/night in VND
    return int(price_usd * exchange_rate)


def normalize_hotel(raw: dict, index: int) -> Optional[dict]:
    """
    Convert raw scraped hotel dict to backend hotels.json schema entry.
    Returns None if minimum required fields are missing.
    """
    name = (raw.get("name") or "").strip()
    if not name or len(name) < 3:
        return None

    dest_id = raw.get("destination_id", "unknown")
    city = raw.get("city", "")
    country = raw.get("country", "")
    exchange_rate = raw.get("exchange_rate", 25000)

    lat = raw.get("lat")
    lon = raw.get("lon")
    if lat is None or lon is None:
        # Skip hotels without coordinates (can't display on map)
        return None

    star_rating = raw.get("star_rating") or 3
    star_rating = min(max(int(star_rating), 1), 5)

    rating = raw.get("rating")
    if rating is not None:
        try:
            rating = float(rating)
            if rating > 5:
                rating = round(rating / 2, 1)
            rating = round(min(max(rating, 1.0), 5.0), 1)
        except (TypeError, ValueError):
            rating = 3.5
    else:
        rating = 3.5

    price_usd = raw.get("price_per_night")
    lowest_price_vnd = _convert_price_to_vnd(price_usd, exchange_rate)

    amenities = _normalize_amenities(raw.get("amenities") or [])
    images = raw.get("images") or []
    if not images:
        images = []  # No placeholder images

    hotel_type = raw.get("property_type") or "HOTEL"

    # Build locationId reference (will be created as new location)
    location_id = f"loc_{_slugify(city)}_001"

    return {
        "hotelID": f"hotel_{dest_id}_{index:03d}",
        "vendorId": DEFAULT_VENDOR_ID,
        "locationId": location_id,
        "city": city,
        "country": country,
        "name": name,
        "slug": _slugify(name),
        "hotelType": hotel_type,
        "starRating": star_rating,
        "address": (raw.get("address") or f"{city}, {country}").strip(),
        "latitude": float(lat),
        "longitude": float(lon),
        "description": (raw.get("description") or f"Welcome to {name} in {city}.").strip(),
        "shortDescription": f"{star_rating}-star {hotel_type.lower().replace('_', ' ')} in {city}",
        "phone": raw.get("phone") or "",
        "email": "",
        "website": raw.get("website") or "",
        "images": images[:5],
        "amenities": amenities,
        "policies": {
            "cancellation": "Free cancellation up to 24 hours before check-in",
            "pets": False,
            "smoking": False,
        },
        "approvalStatus": "APPROVED",
        "status": "ACTIVE",
        "featured": rating >= 4.0 and star_rating >= 4,
        "verified": True,
        "averageRating": rating,
        "totalReviews": raw.get("reviews_count") or 0,
        "totalRooms": 50,
        "lowestPrice": lowest_price_vnd,
        "createdAt": "2026-01-01T00:00:00Z",
        "updatedAt": "2026-01-01T00:00:00Z",
        "_source": raw.get("source", "unknown"),
    }


def save_hotels(scraped_cities: list) -> dict:
    """
    Process all scraped hotel data, normalize, deduplicate by name+city,
    and save to hotels_international.json.
    """
    output_path = PATHS["hotels_backend"]
    os.makedirs(os.path.dirname(output_path), exist_ok=True)

    # Load existing if any
    existing = []
    if os.path.exists(output_path):
        with open(output_path, "r", encoding="utf-8") as f:
            existing = json.load(f)

    existing_keys = {(h["name"].lower(), h.get("city", "").lower()) for h in existing}

    added = 0
    skipped = 0
    index_start = len(existing)

    for city_data in scraped_cities:
        raw_hotels = city_data.get("hotels", [])
        city_name = city_data.get("city", "")

        for i, raw in enumerate(raw_hotels):
            key = (raw.get("name", "").lower(), city_name.lower())
            if key in existing_keys:
                skipped += 1
                continue

            normalized = normalize_hotel(raw, index_start + added)
            if normalized is None:
                skipped += 1
                continue

            existing.append(normalized)
            existing_keys.add(key)
            added += 1

    with open(output_path, "w", encoding="utf-8") as f:
        json.dump(existing, f, ensure_ascii=False, indent=2)

    stats = {
        "total_hotels": len(existing),
        "added": added,
        "skipped": skipped,
        "output_file": output_path,
    }
    logger.info(f"Hotel save: +{added} added, {skipped} skipped → {len(existing)} total → {output_path}")
    return stats