routesapi/run_simulation.py

import json
import logging
import asyncio
from app.services.core.assignment_service import AssignmentService
from app.services.routing.route_optimizer import RouteOptimizer
from app.core.arrow_utils import save_optimized_route_parquet

# Setup logging
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)

# Load Environment Variables
try:
    from dotenv import load_dotenv
    load_dotenv()
    print("✅ Loaded .env file")
except ImportError:
    print("⚠️ python-dotenv not installed, skipping .env load")

async def run_simulation():
    print("🚀 Starting Logic Simulation (High Efficiency Mode + K-wMeans)...")
    
    # 1. Load Orders (using route.json as source)
    try:
        with open('route.json', 'r') as f:
            route_data = json.load(f)
    except FileNotFoundError:
        print("❌ route.json not found.")
        return
    
    raw_orders = route_data.get('details', [])
    # Strip assignment data to simulate fresh orders
    clean_orders = []
    for o in raw_orders:
        o_copy = o.copy()
        for key in ['userid', 'step', 'cumulativekms', 'eta']:
            o_copy.pop(key, None)
        clean_orders.append(o_copy)
        
    print(f"📦 Loaded {len(clean_orders)} orders.")

    # 2. Mock Riders
    # Using the 5 rider fleet as agreed
    rider_ids = [753, 883, 1114, 1271, 1116, 1096, 897, 950, 1272, 1133] # Full Active Riders List
    # Rider Starting Locations (Based on "Mostly Available Location")
    # Coordinates approximated for Coimbatore areas
    rider_locations = {
        1116: (11.0067, 76.9558), # VIVEK ANANDAN: RS PURAM
        1096: (11.0450, 76.9000), # NARAYANASAMY: VADAVALI
        897:  (11.0430, 76.9380), # VARUN EDWARD: KAVUNDAMPALAYAM
        950:  (11.0330, 76.9800), # JAYASABESH: GANAPATHY
        1114: (11.0450, 77.0000), # TAMILAZHAGAN: GANDHIMA NAGAR
        883:  (11.0200, 77.0000), # RAJAN: PEELAMEDU
        1272: (10.9950, 77.0000), # MUTHURAJA: RAMANATHAPURAM
        753:  (11.0000, 77.0300), # MANIKANDAN: SINGANALLUR
        1133: (11.0067, 76.9558), # THATCHINAMOORTHI: RS PURAM (Covering Kavundampalayam to Kovaipudur)
        1271: (11.0067, 76.9558)  # Legacy ID for Thatchinamoorthi
    }

    riders = []
    for i, rid in enumerate(rider_ids):
        lat, lon = rider_locations.get(rid, (11.0168, 76.9558)) # Default to Central if unknown
        riders.append({
            "userid": rid,
            "status": "idle",
            "onduty": 1,
            "latitude": str(lat),
            "longitude": str(lon)
        })

    # 3. Run Assignment
    assignment_service = AssignmentService()
    try:
        assignments, unassigned_orders = assignment_service.assign_orders(clean_orders, riders)
    except Exception as e:
        print(f"❌ Error during assignment: {e}")
        import traceback
        traceback.print_exc()
        return

    # 4. Generate Output (Mirroring API Logic)
    optimizer = RouteOptimizer()
    
    output_details = []
    distribution = {}
    assigned_count = 0
    
    # Prepare async tasks
    tasks = []
    task_rids = []
    
    for rid, orders in assignments.items():
        if not orders: continue
        distribution[rid] = len(orders)
        assigned_count += len(orders)
        
        # Optimize Route & Add Metrics (Cumulative KMS, Step, etc.)
        mock_rider = next((r for r in riders if r["userid"] == rid), None)
        start_coords = None
        if mock_rider:
            start_coords = (float(mock_rider['latitude']), float(mock_rider['longitude']))

        tasks.append(optimizer.optimize_provider_payload(orders, start_coords=start_coords))
        task_rids.append(rid)

    # Run tasks
    if tasks:
        results = await asyncio.gather(*tasks)
        
        for rid, optimized_route in zip(task_rids, results):
            mock_rider = next((r for r in riders if r["userid"] == rid), {})
            r_name = mock_rider.get("username", "")
            r_contact = mock_rider.get("contactno", "")
            
            total_kms = 0
            if optimized_route:
                try:
                    total_kms = max([float(o.get("cumulativekms", 0)) for o in optimized_route])
                except:
                    total_kms = sum([float(o.get("actualkms", o.get("kms", 0))) for o in optimized_route])

            for o in optimized_route:
                o['userid'] = rid
                o['username'] = r_name
                o['rider'] = r_name
                o['ridercontactno'] = r_contact
                o['riderkms'] = str(round(total_kms, 2))
                output_details.append(o)

    # 5. Zone Processing
    fuel_charge = 2.5
    base_pay = 30.0
    from app.services.routing.zone_service import ZoneService
    zone_service = ZoneService()
    zone_data = zone_service.group_by_zones(output_details, unassigned_orders, fuel_charge=fuel_charge, base_pay=base_pay)
    
    # 6. Save output.json
    output_data = {
        "message": "Success",
        "status": True,
        "details": output_details,
        "zone_summary": zone_data["zone_analysis"],
        "zones": zone_data["detailed_zones"],
        "meta": {
            "total_orders": len(clean_orders),
            "total_riders": len(rider_ids),
            "assigned_orders": assigned_count,
            "unassigned_orders": len(unassigned_orders),
            "total_profit": round(sum(z["total_profit"] for z in zone_data["zone_analysis"]), 2),
            "unassigned_details": [
                {"id": o.get("orderid") or o.get("_id"), "reason": o.get("unassigned_reason")}
                for o in unassigned_orders
            ],
            "distribution_summary": distribution
        }
    }
    
    with open('output.json', 'w') as f:
        json.dump(output_data, f, indent=4)
        
    # Apache Arrow / Parquet Export
    try:
        save_optimized_route_parquet(output_details, 'output.parquet')
        print("📊 Also saved results to output.parquet (Apache Arrow format)")
    except Exception as e:
        print(f"⚠️ Could not save Parquet: {e}")
        
    print("✅ Simulation Complete. Saved to output.json")
    print("📊 Distribution Summary:")
    print(json.dumps(distribution, indent=4))

if __name__ == "__main__":
    asyncio.run(run_simulation())