import os
import pickle
import logging
from datetime import datetime
from typing import Dict, Any

logger = logging.getLogger(__name__)

HISTORY_FILE = "rider_history.pkl"

class RiderHistoryService:
    def __init__(self, history_file: str = HISTORY_FILE):
        self.history_file = history_file
        self.history = self._load_history()

    def _load_history(self) -> Dict[int, Dict[str, float]]:
        """Load history from pickle file."""
        if not os.path.exists(self.history_file):
            return {}
        
        try:
            with open(self.history_file, 'rb') as f:
                return pickle.load(f)
        except Exception as e:
            logger.error(f"Failed to load rider history: {e}")
            return {}

    def _save_history(self):
        """Save history to pickle file."""
        try:
            with open(self.history_file, 'wb') as f:
                pickle.dump(self.history, f)
        except Exception as e:
            logger.error(f"Failed to save rider history: {e}")

    def update_rider_stats(self, rider_id: int, distance_km: float, order_count: int):
        """Update cumulative stats for a rider."""
        rider_id = int(rider_id)
        if rider_id not in self.history:
            self.history[rider_id] = {
                "total_km": 0.0,
                "total_orders": 0,
                "last_updated": datetime.now().isoformat()
            }
        
        self.history[rider_id]["total_km"] += distance_km
        self.history[rider_id]["total_orders"] += order_count
        self.history[rider_id]["last_updated"] = datetime.now().isoformat()
        
        # Auto-save on update
        self._save_history()

    def get_rider_score(self, rider_id: int) -> float:
        """
        Get a score representing the rider's historical 'load' (KMs).
        Higher Score = More KMs driven recently.
        """
        rider_id = int(rider_id)
        stats = self.history.get(rider_id, {})
        return stats.get("total_km", 0.0)

    def get_preferred_assignment_type(self, rider_id: int, all_rider_scores: Dict[int, float]) -> str:
        """
        Determine if rider should get 'Long' or 'Short' routes based on population average.
        """
        score = self.get_rider_score(rider_id)
        if not all_rider_scores:
            return "ANY"
            
        avg_score = sum(all_rider_scores.values()) / len(all_rider_scores)
        
        # If rider has driven LESS than average, prefer LONG routes (Risky)
        if score < avg_score:
            return "LONG"
        # If rider has driven MORE than average, prefer SHORT routes (Economy)
        else:
            return "SHORT"