Update route_optimizer/green_route_optimizer.py

route_optimizer/green_route_optimizer.py

@@ -4,24 +4,45 @@ import math
 
 class GreenRouteOptimizer:
     """
-    A simple placeholder class for route optimization.
-    In real-world apps, integrate APIs like Google Maps or OpenRouteService for real routes.
+    Green Route Optimizer class.
+    Provides route optimization and recommends the most eco-friendly route.
     """
 
+    # Approximate emission factors (kg CO2 per km)
+    EMISSION_FACTORS = {
+        "driving": 0.21,   # example: car
+        "cycling": 0.0,    # bicycles produce zero direct emissions
+        "walking": 0.0     # walking produces zero direct emissions
+    }
+
     def __init__(self):
         pass
 
     def optimize(self, start, end, mode="driving"):
         """
-        Returns a mock optimized route result.
-        Replace this with real API calls if needed.
+        Returns a mock optimized route for a given transport mode.
+        Uses Euclidean distance as a simple approximation.
         """
-        distance_km = math.dist(start, end)  # Euclidean distance (approximation)
+        distance_km = math.dist(start, end)
         optimized_route = {
             "start": start,
             "end": end,
             "mode": mode,
             "optimized_distance_km": round(distance_km, 2),
-            "estimated_emission_kg": round(distance_km * 0.21, 3)  # example emission factor
+            "estimated_emission_kg": round(distance_km * self.EMISSION_FACTORS.get(mode, 0.21), 3)
         }
         return optimized_route
+
+    def recommend_green_routes(self, start, end):
+        """
+        Recommends the greenest route among driving, cycling, and walking.
+        Returns a sorted list by estimated emissions.
+        """
+        routes = []
+        for mode in self.EMISSION_FACTORS.keys():
+            route = self.optimize(start, end, mode)
+            routes.append(route)
+
+        # Sort routes by estimated emissions (ascending)
+        routes_sorted = sorted(routes, key=lambda x: x["estimated_emission_kg"])
+        return routes_sorted