from typing import Dict, List, Optional
from pathlib import Path
import pandas as pd
from datetime import datetime
from app.config import settings
from app.utils.logger import get_logger

logger = get_logger(__name__)


class DataService:
    def __init__(self):
        self.data_path: Path = settings.DATA_PATH_RESOLVED
        self._price_data: Dict[str, pd.DataFrame] = {}
        self._battery_data: Optional[pd.DataFrame] = None
        self._loaded: bool = False

    async def initialize(self):
        logger.info(f"Loading data from {self.data_path}")
        self._load_price_data()
        self._load_battery_data()
        self._loaded = True
        logger.info("Data loaded successfully")

    def _load_price_data(self):
        if not self.data_path.exists():
            logger.warning(f"Data path {self.data_path} does not exist")
            return

        prices_file = self.data_path / "electricity_prices.parquet"
        if prices_file.exists():
            df = pd.read_parquet(prices_file)
            logger.info(f"Loaded price data: {len(df)} total rows from {prices_file}")

            if "region" in df.columns:
                for region in ["FR", "BE", "DE", "NL", "UK"]:
                    region_df = df[df["region"] == region].copy()
                    if len(region_df) > 0:
                        self._price_data[region] = region_df
                        logger.info(f"Loaded {region} price data: {len(region_df)} rows")
            else:
                logger.warning("Price data file does not contain 'region' column")
        else:
            logger.warning(f"Price data file not found: {prices_file}")

    def _load_battery_data(self):
        battery_path = self.data_path / "battery_capacity.parquet"
        if battery_path.exists():
            self._battery_data = pd.read_parquet(battery_path)
            logger.info(f"Loaded battery data: {len(self._battery_data)} rows")
        else:
            logger.warning(f"Battery data file not found: {battery_path}")

    def get_latest_prices(self) -> Dict[str, Dict]:
        result = {}
        for region, df in self._price_data.items():
            if len(df) > 0:
                latest = df.iloc[-1].to_dict()
                result[region] = {
                    "timestamp": latest.get("timestamp"),
                    "day_ahead_price": latest.get("day_ahead_price", 0),
                    "real_time_price": latest.get("real_time_price", 0),
                    "volume_mw": latest.get("volume_mw", 0),
                }
        return result

    def get_price_history(
        self, region: str, start: Optional[str] = None, end: Optional[str] = None, limit: int = 1000
    ) -> List[Dict]:
        if region not in self._price_data:
            return []

        df = self._price_data[region].copy()

        if "timestamp" in df.columns:
            df = df.sort_values("timestamp")

            if start:
                df = df[df["timestamp"] >= start]
            if end:
                df = df[df["timestamp"] <= end]

        df = df.tail(limit)

        return df.to_dict("records")

    def get_battery_states(self) -> List[Dict]:
        if self._battery_data is None or len(self._battery_data) == 0:
            return []

        latest_by_battery = self._battery_data.groupby("battery_id").last().reset_index()

        result = []
        for _, row in latest_by_battery.iterrows():
            result.append(
                {
                    "timestamp": row.get("timestamp"),
                    "battery_id": row.get("battery_id"),
                    "capacity_mwh": row.get("capacity_mwh", 0),
                    "charge_level_mwh": row.get("charge_level_mwh", 0),
                    "charge_rate_mw": row.get("charge_rate_mw", 0),
                    "discharge_rate_mw": row.get("discharge_rate_mw", 0),
                    "efficiency": row.get("efficiency", 0.9),
                }
            )
        return result

    def get_arbitrage_opportunities(self, min_spread: Optional[float] = None) -> List[Dict]:
        if min_spread is None:
            min_spread = settings.ARBITRAGE_MIN_SPREAD

        opportunities = []
        latest_prices = self.get_latest_prices()

        regions = list(latest_prices.keys())
        for i in range(len(regions)):
            for j in range(i + 1, len(regions)):
                region_a = regions[i]
                region_b = regions[j]

                price_a = latest_prices[region_a].get("real_time_price", 0)
                price_b = latest_prices[region_b].get("real_time_price", 0)

                if price_a > 0 and price_b > 0:
                    spread = abs(price_a - price_b)
                    if spread >= min_spread:
                        if price_a < price_b:
                            buy_region, sell_region = region_a, region_b
                            buy_price, sell_price = price_a, price_b
                        else:
                            buy_region, sell_region = region_b, region_a
                            buy_price, sell_price = price_b, price_a

                        opportunities.append(
                            {
                                "timestamp": datetime.utcnow(),
                                "buy_region": buy_region,
                                "sell_region": sell_region,
                                "buy_price": buy_price,
                                "sell_price": sell_price,
                                "spread": spread,
                                "volume_mw": 100,
                            }
                        )

        return opportunities

    def get_dashboard_summary(self) -> Dict:
        latest_prices = self.get_latest_prices()

        total_volume = sum(p.get("volume_mw", 0) for p in latest_prices.values())
        avg_price = (
            sum(p.get("real_time_price", 0) for p in latest_prices.values()) / len(latest_prices)
            if latest_prices
            else 0
        )

        arbitrage = self.get_arbitrage_opportunities()
        battery_states = self.get_battery_states()

        avg_battery_charge = 0
        if battery_states:
            avg_battery_charge = sum(
                b.get("charge_level_mwh", 0) / b.get("capacity_mwh", 1) for b in battery_states
            ) / len(battery_states)

        return {
            "latest_timestamp": datetime.utcnow(),
            "total_volume_mw": total_volume,
            "avg_realtime_price": avg_price,
            "arbitrage_count": len(arbitrage),
            "battery_count": len(battery_states),
            "avg_battery_charge": avg_battery_charge,
        }