initial project setup with README and ignore

app/services/routing/zone_service.py

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+
+import logging
+from typing import List, Dict, Any, Optional
+
+logger = logging.getLogger(__name__)
+
+class ZoneService:
+    """
+    Service to classify orders and riders into geographic zones.
+    Defaulting to Coimbatore logic as per user context.
+    """
+    
+    # Approximate Center of Coimbatore (Gandhipuram/Bus Stand area)
+    CENTER_LAT = 11.0168
+    CENTER_LON = 76.9558
+    
+    def __init__(self):
+        pass
+
+    def determine_zone(self, lat: float, lon: float, pincode: Optional[str] = None) -> str:
+        """
+        Determine the zone (North, South, East, West, etc.) based on coordinates.
+        """
+        if lat == 0 or lon == 0:
+            return "Unknown"
+
+        lat_diff = lat - self.CENTER_LAT
+        lon_diff = lon - self.CENTER_LON
+        
+        # Simple Quadrant Logic
+        # North: +Lat
+        # South: -Lat
+        # East: +Lon
+        # West: -Lon
+        
+        # Define a small central buffer (0.01 degrees ~ 1.1km)
+        buffer = 0.010
+        
+        is_north = lat_diff > buffer
+        is_south = lat_diff < -buffer
+        is_east = lon_diff > buffer
+        is_west = lon_diff < -buffer
+        
+        zone_parts = []
+        
+        if is_north: zone_parts.append("North")
+        elif is_south: zone_parts.append("South")
+        
+        if is_east: zone_parts.append("East")
+        elif is_west: zone_parts.append("West")
+        
+        if not zone_parts:
+            return "Central"
+            
+        return " ".join(zone_parts)
+
+    def group_by_zones(self, flat_orders: List[Dict[str, Any]], unassigned_orders: List[Dict[str, Any]] = None, fuel_charge: float = 2.5, base_pay: float = 30.0) -> Dict[str, Any]:
+        """
+        Group a flat list of optimized orders into Zones -> Riders -> Orders.
+        Calculates profit per order and per zone.
+        """
+        zones_map = {} # "North East": { "riders": { rider_id: [orders] } }
+        unassigned_orders = unassigned_orders or []
+        
+        # Merge both for initial processing if you want everything zoned
+        all_to_process = []
+        for o in flat_orders:
+            all_to_process.append((o, True))
+        for o in unassigned_orders:
+            all_to_process.append((o, False))
+
+        for order, is_assigned in all_to_process:
+            # 1. Extract Coords
+            try:
+                # Prefer Delivery location for zoning (where the customer is)
+                lat = float(order.get("deliverylat") or order.get("droplat") or 0)
+                lon = float(order.get("deliverylong") or order.get("droplon") or 0)
+                pincode = str(order.get("deliveryzip") or "")
+            except:
+                lat, lon, pincode = 0, 0, ""
+            
+            # 2. Get Zone
+            zone_name = self.determine_zone(lat, lon, pincode)
+            order["zone_name"] = zone_name
+            
+            # 3. Initialize Zone Bucket
+            if zone_name not in zones_map:
+                zones_map[zone_name] = {
+                    "riders_map": {}, 
+                    "total_orders": 0,
+                    "assigned_orders": 0,
+                    "unassigned_orders": [],
+                    "total_kms": 0.0,
+                    "total_profit": 0.0
+                }
+            
+            # 4. Add to Rider bucket within Zone
+            rider_id = order.get("userid") or order.get("_id")
+            
+            # Track kms and profit for this zone
+            try:
+                # 'actualkms' is preferred for delivery distance
+                dist = float(order.get("actualkms", order.get("previouskms", 0)))
+                zones_map[zone_name]["total_kms"] += dist
+                
+                # Individual charge for this order: Fixed Base + Variable Distance
+                order_amount = float(order.get("orderamount") or order.get("deliveryamount") or 0)
+                rider_payment = base_pay + (dist * fuel_charge)
+                profit = order_amount - rider_payment
+                
+                order["rider_charge"] = round(rider_payment, 2)
+                order["profit"] = round(profit, 2)
+                
+                # Profit-based classification (Order Type)
+                if profit <= 0:
+                    order["ordertype"] = "Loss"
+                elif profit <= 5:
+                    order["ordertype"] = "Risky"
+                elif profit <= 10:
+                    order["ordertype"] = "Economy"
+                else:
+                    order["ordertype"] = "Premium"
+                
+                zones_map[zone_name]["total_profit"] += profit
+            except:
+                pass
+
+            # If strictly unassigned order (no rider), put in unassigned
+            if not is_assigned:
+                zones_map[zone_name]["unassigned_orders"].append(order)
+            else:
+                str_rid = str(rider_id)
+                if str_rid not in zones_map[zone_name]["riders_map"]:
+                    zones_map[zone_name]["riders_map"][str_rid] = {
+                        "rider_details": {
+                            "id": str_rid,
+                            "name": order.get("username", "Unknown")
+                        },
+                        "orders": []
+                    }
+                zones_map[zone_name]["riders_map"][str_rid]["orders"].append(order)
+                zones_map[zone_name]["assigned_orders"] += 1
+            
+            zones_map[zone_name]["total_orders"] += 1
+
+        # 5. Restructure for API Response
+        output_zones = []
+        zone_metrics = []
+        
+        sorted_zone_names = sorted(zones_map.keys())
+        
+        for z_name in sorted_zone_names:
+            z_data = zones_map[z_name]
+            
+            # Flatten riders map
+            riders_list = []
+            for r_id, r_data in z_data["riders_map"].items():
+                riders_list.append({
+                    "rider_id": r_data["rider_details"]["id"],
+                    "rider_name": r_data["rider_details"]["name"],
+                    "orders_count": len(r_data["orders"]),
+                    "orders": r_data["orders"]
+                })
+            
+            # Create the flat metric summary
+            metrics = {
+                "zone_name": z_name,
+                "total_orders": z_data["total_orders"],
+                "assigned_orders": z_data["assigned_orders"],
+                "unassigned_orders_count": len(z_data["unassigned_orders"]),
+                "active_riders_count": len(riders_list),
+                "total_delivery_kms": round(z_data["total_kms"], 2),
+                "total_profit": round(z_data["total_profit"], 2)
+            }
+            
+            zone_metrics.append(metrics)
+            
+            # Create the detailed zone object with flattened metrics
+            zone_obj = {
+                "zone_name": z_name,
+                "total_orders": metrics["total_orders"],
+                "active_riders_count": metrics["active_riders_count"],
+                "assigned_orders": metrics["assigned_orders"],
+                "unassigned_orders_count": metrics["unassigned_orders_count"],
+                "total_delivery_kms": metrics["total_delivery_kms"],
+                "total_profit": metrics["total_profit"],
+                "riders": riders_list,
+                "unassigned_orders": z_data["unassigned_orders"]
+            }
+            
+            output_zones.append(zone_obj)
+            
+        return {
+            "detailed_zones": output_zones,
+            "zone_analysis": zone_metrics
+        }