import os
import re
import asyncio
import httpx
import json
from typing import List, Optional
from pydantic import BaseModel
from pathlib import Path
from datetime import datetime, timedelta


class Building(BaseModel):
    """Single building footprint"""
    id: int
    geometry: List[List[float]]  # [[lon, lat], ...]
    height: float  # meters
    levels: Optional[int] = None
    building_type: Optional[str] = None
    material: Optional[str] = None  # Detected material type
    tags: dict = {}  # Store all OSM tags for material detection


class OSMCache:
    """Local cache for OSM data with expiry"""

    CACHE_EXPIRY_DAYS = 30

    def __init__(self, cache_type: str):
        self.data_path = Path(os.environ.get('RFCP_DATA_PATH', './data'))
        self.cache_path = self.data_path / 'osm' / cache_type
        self.cache_path.mkdir(parents=True, exist_ok=True)

    def _get_cache_key(self, min_lat: float, min_lon: float, max_lat: float, max_lon: float) -> str:
        """Generate cache key from bbox (rounded to 0.01 degree grid)"""
        return f"{min_lat:.2f}_{min_lon:.2f}_{max_lat:.2f}_{max_lon:.2f}"

    def _get_cache_file(self, cache_key: str) -> Path:
        return self.cache_path / f"{cache_key}.json"

    def get(self, min_lat: float, min_lon: float, max_lat: float, max_lon: float) -> Optional[dict]:
        """Get cached data if available and not expired"""
        cache_key = self._get_cache_key(min_lat, min_lon, max_lat, max_lon)
        cache_file = self._get_cache_file(cache_key)

        if not cache_file.exists():
            return None

        try:
            data = json.loads(cache_file.read_text())

            # Check expiry
            cached_at = datetime.fromisoformat(data.get('_cached_at', '2000-01-01'))
            if datetime.now() - cached_at > timedelta(days=self.CACHE_EXPIRY_DAYS):
                return None

            return data.get('data')

        except Exception as e:
            print(f"[OSMCache] Failed to read cache: {e}")
            return None

    def set(self, min_lat: float, min_lon: float, max_lat: float, max_lon: float, data):
        """Save data to cache"""
        cache_key = self._get_cache_key(min_lat, min_lon, max_lat, max_lon)
        cache_file = self._get_cache_file(cache_key)

        try:
            cache_data = {
                '_cached_at': datetime.now().isoformat(),
                '_bbox': [min_lat, min_lon, max_lat, max_lon],
                'data': data
            }
            cache_file.write_text(json.dumps(cache_data))

        except Exception as e:
            print(f"[OSMCache] Failed to write cache: {e}")

    def clear(self):
        """Clear all cached data"""
        for f in self.cache_path.glob("*.json"):
            f.unlink()

    def get_size_mb(self) -> float:
        """Get cache size in MB"""
        total = sum(f.stat().st_size for f in self.cache_path.glob("*.json"))
        return total / (1024 * 1024)


class BuildingsService:
    """
    OpenStreetMap buildings via Overpass API with local caching.
    """

    OVERPASS_URLS = [
        "https://overpass-api.de/api/interpreter",
        "https://overpass.kumi.systems/api/interpreter",
    ]
    DEFAULT_LEVEL_HEIGHT = 3.0  # meters per floor
    DEFAULT_BUILDING_HEIGHT = 9.0  # 3 floors if unknown

    def __init__(self):
        self.cache = OSMCache('buildings')
        self._memory_cache: dict[str, List[Building]] = {}
        self._max_cache_size = 50

    @staticmethod
    def _safe_int(value) -> Optional[int]:
        """Safely parse int from OSM tag (handles '1a', '2-3', '5+', etc.)"""
        if not value:
            return None
        try:
            return int(value)
        except (ValueError, TypeError):
            match = re.search(r'\d+', str(value))
            if match:
                return int(match.group())
            return None

    @staticmethod
    def _safe_float(value) -> Optional[float]:
        """Safely parse float from OSM tag (handles '10 m', '~12', '10m')"""
        if not value:
            return None
        try:
            cleaned = str(value).lower().replace('m', '').replace('~', '').strip()
            return float(cleaned)
        except (ValueError, TypeError):
            match = re.search(r'[\d.]+', str(value))
            if match:
                return float(match.group())
            return None

    def _bbox_key(self, min_lat: float, min_lon: float, max_lat: float, max_lon: float) -> str:
        """Generate memory cache key for bbox"""
        return f"{min_lat:.2f}_{min_lon:.2f}_{max_lat:.2f}_{max_lon:.2f}"

    async def fetch_buildings(
        self,
        min_lat: float, min_lon: float,
        max_lat: float, max_lon: float,
        use_cache: bool = True
    ) -> List[Building]:
        """Fetch buildings in bounding box from OSM, using cache if available"""
        bbox_key = self._bbox_key(min_lat, min_lon, max_lat, max_lon)

        # Check memory cache
        if use_cache and bbox_key in self._memory_cache:
            return self._memory_cache[bbox_key]

        # Check disk cache (OSMCache with expiry)
        if use_cache:
            cached = self.cache.get(min_lat, min_lon, max_lat, max_lon)
            if cached is not None:
                print(f"[Buildings] Cache hit for bbox")
                buildings = [Building(**b) for b in cached]
                self._memory_cache[bbox_key] = buildings
                return buildings

        # Fetch from Overpass API with retry
        print(f"[Buildings] Fetching from Overpass API...")

        query = f"""
        [out:json][timeout:30];
        (
          way["building"]({min_lat},{min_lon},{max_lat},{max_lon});
          relation["building"]({min_lat},{min_lon},{max_lat},{max_lon});
        );
        out body;
        >;
        out skel qt;
        """

        data = None
        max_retries = 3
        for attempt in range(max_retries):
            url = self.OVERPASS_URLS[attempt % len(self.OVERPASS_URLS)]
            try:
                timeout = 60.0 * (attempt + 1)  # 60s, 120s, 180s
                async with httpx.AsyncClient(timeout=timeout) as client:
                    response = await client.post(url, data={"data": query})
                    response.raise_for_status()
                    data = response.json()
                    break
            except Exception as e:
                print(f"[Buildings] Overpass attempt {attempt + 1}/{max_retries} failed ({url}): {e}")
                if attempt < max_retries - 1:
                    wait_time = 2 ** attempt  # 1s, 2s
                    print(f"[Buildings] Retrying in {wait_time}s...")
                    await asyncio.sleep(wait_time)
                else:
                    print(f"[Buildings] All {max_retries} attempts failed")
                    return []

        buildings = self._parse_overpass_response(data)

        # Save to disk cache
        if buildings:
            self.cache.set(min_lat, min_lon, max_lat, max_lon,
                           [b.model_dump() for b in buildings])

        # Memory cache with size limit
        if len(self._memory_cache) >= self._max_cache_size:
            oldest = next(iter(self._memory_cache))
            del self._memory_cache[oldest]
        self._memory_cache[bbox_key] = buildings

        return buildings

    def _parse_overpass_response(self, data: dict) -> List[Building]:
        """Parse Overpass JSON response into Building objects"""
        buildings = []

        # Build node lookup
        nodes = {}
        for element in data.get("elements", []):
            if element["type"] == "node":
                nodes[element["id"]] = (element["lon"], element["lat"])

        # Process ways (building footprints)
        for element in data.get("elements", []):
            if element["type"] != "way":
                continue

            tags = element.get("tags", {})
            if "building" not in tags:
                continue

            geometry = []
            for node_id in element.get("nodes", []):
                if node_id in nodes:
                    geometry.append(list(nodes[node_id]))

            if len(geometry) < 3:
                continue

            height = self._estimate_height(tags)

            material_str = None
            if "building:material" in tags:
                material_str = tags["building:material"]
            elif "building:facade:material" in tags:
                material_str = tags["building:facade:material"]

            buildings.append(Building(
                id=element["id"],
                geometry=geometry,
                height=height,
                levels=self._safe_int(tags.get("building:levels")),
                building_type=tags.get("building"),
                material=material_str,
                tags=tags
            ))

        return buildings

    def _estimate_height(self, tags: dict) -> float:
        """Estimate building height from OSM tags"""
        if "height" in tags:
            h = self._safe_float(tags["height"])
            if h is not None and h > 0:
                return h

        if "building:levels" in tags:
            levels = self._safe_int(tags["building:levels"])
            if levels is not None and levels > 0:
                return levels * self.DEFAULT_LEVEL_HEIGHT

        building_type = tags.get("building", "yes")
        type_heights = {
            "house": 6.0,
            "residential": 12.0,
            "apartments": 18.0,
            "commercial": 12.0,
            "industrial": 8.0,
            "warehouse": 6.0,
            "garage": 3.0,
            "shed": 2.5,
            "roof": 3.0,
            "church": 15.0,
            "cathedral": 30.0,
            "hospital": 15.0,
            "school": 12.0,
            "university": 15.0,
            "office": 20.0,
            "retail": 6.0,
        }

        return type_heights.get(building_type, self.DEFAULT_BUILDING_HEIGHT)

    def point_in_building(self, lat: float, lon: float, building: Building) -> bool:
        """Check if point is inside building footprint (ray casting)"""
        x, y = lon, lat
        polygon = building.geometry
        n = len(polygon)
        inside = False

        j = n - 1
        for i in range(n):
            xi, yi = polygon[i]
            xj, yj = polygon[j]

            if ((yi > y) != (yj > y)) and (x < (xj - xi) * (y - yi) / (yj - yi) + xi):
                inside = not inside
            j = i

        return inside

    def line_intersects_building(
        self,
        lat1: float, lon1: float, height1: float,
        lat2: float, lon2: float, height2: float,
        building: Building
    ) -> Optional[float]:
        """Check if line segment intersects building.
        Returns distance along path where intersection occurs, or None."""
        from app.services.terrain_service import TerrainService

        num_samples = 20
        for i in range(num_samples):
            t = i / num_samples
            lat = lat1 + t * (lat2 - lat1)
            lon = lon1 + t * (lon2 - lon1)
            height = height1 + t * (height2 - height1)

            if self.point_in_building(lat, lon, building):
                if height < building.height:
                    dist = t * TerrainService.haversine_distance(lat1, lon1, lat2, lon2)
                    return dist

        return None


# Singleton instance
buildings_service = BuildingsService()