added dataclass

backend/app/main.py

@@ -1,5 +1,5 @@
 from src.optimizer import solve_optimization
-from src.optimizer import landmark
+from src.optimizer import Landmark
 from fastapi import FastAPI
 
 app = FastAPI()
@@ -12,18 +12,18 @@ def main(max_steps: int, print_details: bool):
     #max_steps = 16
 
 
-    # Initialize all landmarks (+ start and goal). Order matters here
-    landmarks = []
-    landmarks.append(landmark("départ", -1, (0, 0)))
-    landmarks.append(landmark("tour eiffel", 99, (0,2)))                           # PUT IN JSON
-    landmarks.append(landmark("arc de triomphe", 99, (0,4)))
-    landmarks.append(landmark("louvre", 99, (0,6)))
-    landmarks.append(landmark("montmartre", 99, (0,10)))
-    landmarks.append(landmark("concorde", 99, (0,8)))
-    landmarks.append(landmark("arrivée", -1, (0, 0)))
+    # Initialize all Landmarks (+ start and goal). Order matters here
+    Landmarks = []
+    Landmarks.append(Landmark("départ", -1, (0, 0)))
+    Landmarks.append(Landmark("tour eiffel", 99, (0,2)))                           # PUT IN JSON
+    Landmarks.append(Landmark("arc de triomphe", 99, (0,4)))
+    Landmarks.append(Landmark("louvre", 99, (0,6)))
+    Landmarks.append(Landmark("montmartre", 99, (0,10)))
+    Landmarks.append(Landmark("concorde", 99, (0,8)))
+    Landmarks.append(Landmark("arrivée", -1, (0, 0)))
 
 
-    visiting_order = solve_optimization(landmarks, max_steps, print_details)
+    visiting_order = solve_optimization(Landmarks, max_steps, print_details)
 
     #return visiting_order
 

backend/app/src/optimizer.py

@@ -1,14 +1,15 @@
 from scipy.optimize import linprog
 import numpy as np
 from scipy.linalg import block_diag
+from dataclasses import dataclass
 
 
 # Defines the landmark class (aka some place there is to visit)
-class landmark :
-    def __init__(self, name: str, attractiveness: int, loc: tuple):
-        self.name = name
-        self.attractiveness = attractiveness
-        self.loc = loc
+@dataclass
+class Landmark :
+    name : str
+    attractiveness : int
+    loc : tuple
 
 # Convert the solution of the optimization into the list of edges to follow. Order is taken into account
 def untangle(resx: list) :