persistence for recurring api calls

backend/src/utils/landmarks_manager.py

@@ -15,10 +15,6 @@ from .take_most_important import take_most_important
 import constants
 
 
-SIGHTSEEING = 'sightseeing'
-NATURE = 'nature'
-SHOPPING = 'shopping'
-
 
 
 class LandmarkManager:
@@ -74,25 +70,25 @@ class LandmarkManager:
         # list for sightseeing
         if preferences.sightseeing.score != 0:
             score_function = lambda loc, n_tags: int((self.count_elements_close_to(loc) + ((n_tags**1.2)*self.tag_coeff) )*self.church_coeff)  
-            L1 = self.fetch_landmarks(bbox, self.amenity_selectors['sightseeing'], SIGHTSEEING, score_function)
-            self.correct_score(L1, preferences.sightseeing)
+            L1 = self.fetch_landmarks(bbox, self.amenity_selectors['sightseeing'], preferences.sightseeing.type, score_function)
             L += L1
 
         # list for nature
         if preferences.nature.score != 0:
             score_function = lambda loc, n_tags: int((self.count_elements_close_to(loc) + ((n_tags**1.2)*self.tag_coeff) )*self.park_coeff)  
-            L2 = self.fetch_landmarks(bbox, self.amenity_selectors['nature'], NATURE, score_function)
-            self.correct_score(L2, preferences.nature)
+            L2 = self.fetch_landmarks(bbox, self.amenity_selectors['nature'], preferences.nature.type, score_function)
             L += L2
 
         # list for shopping
         if preferences.shopping.score != 0:
             score_function = lambda loc, n_tags: int(self.count_elements_close_to(loc) + ((n_tags**1.2)*self.tag_coeff))
-            L3 = self.fetch_landmarks(bbox, self.amenity_selectors['shopping'], SHOPPING, score_function)
-            self.correct_score(L3, preferences.shopping)
+            L3 = self.fetch_landmarks(bbox, self.amenity_selectors['shopping'], preferences.shopping.type, score_function)
             L += L3
 
+
         L = self.remove_duplicates(L)
+        self.correct_score(L, preferences)
+
         L_constrained = take_most_important(L, self.N_important)
         self.logger.info(f'Generated {len(L)} landmarks around {center_coordinates}, and constrained to {len(L_constrained)} most important ones.')
 
@@ -123,7 +119,7 @@ class LandmarkManager:
         return L_clean
         
 
-    def correct_score(self, landmarks: list[Landmark], preference: Preference):
+    def correct_score(self, landmarks: list[Landmark], preferences: Preferences) -> None:
         """
         Adjust the attractiveness score of each landmark in the list based on user preferences.
 
@@ -132,20 +128,16 @@ class LandmarkManager:
 
         Args:
             landmarks (list[Landmark]): A list of landmarks whose scores need to be corrected.
-            preference (Preference): The user's preference settings that influence the attractiveness score adjustment.
-
-        Raises:
-            TypeError: If the type of any landmark in the list does not match the expected type in the preference.
+            preferences (Preferences): The user's preference settings that influence the attractiveness score adjustment.
         """
 
-        if len(landmarks) == 0:
-            return
-        
-        if landmarks[0].type != preference.type:
-            raise TypeError(f"LandmarkType {preference.type} does not match the type of Landmark {landmarks[0].name}")
-
-        for elem in landmarks:
-            elem.attractiveness = int(elem.attractiveness*preference.score/5)     # arbitrary computation
+        score_dict = {
+            preferences.sightseeing.type: preferences.sightseeing.score,
+            preferences.nature.type: preferences.nature.score,
+            preferences.shopping.type: preferences.shopping.score
+        }
+        for landmark in landmarks:
+            landmark.attractiveness = int(landmark.attractiveness * score_dict[landmark.type] / 5)        
 
 
     def count_elements_close_to(self, coordinates: tuple[float, float]) -> int:
@@ -310,7 +302,7 @@ class LandmarkManager:
                         if "leisure" in tag and elem.tag('leisure') == "park":
                             elem_type = "nature"
 
-                    if landmarktype != SHOPPING:
+                    if landmarktype != "shopping":
                         if "shop" in tag:
                             skip = True
                             break