added pep8 example

backend/src/landmarks_manager.py

@@ -111,6 +111,15 @@ def take_most_important(L: List[Landmark]) -> List[Landmark] :
 
 # Remove duplicate elements and elements with low score
 def remove_duplicates(L: List[Landmark]) -> List[Landmark] :
+    """
+    Removes duplicate landmarks based on their names from the given list.
+
+    Parameters:
+    L (List[Landmark]): A list of Landmark objects.
+
+    Returns:
+    List[Landmark]: A list of unique Landmark objects based on their names.
+    """
     L_clean = []
     names = []
 
@@ -180,124 +189,6 @@ def create_bbox(coordinates: Tuple[float, float], side_length: int) -> Tuple[flo
 
     return min_lat, min_lon, max_lat, max_lon
 
-# Generates the list of landmarks for a given Landmarktype. Needs coordinates, a list of amenities and the corresponding LandmarkType
-def get_landmarks_coords(coordinates: Tuple[float, float], list_amenity: list, landmarktype: LandmarkType) -> List[Landmark]:
-
-    # Read the parameters from the file
-    with open (os.path.dirname(os.path.abspath(__file__)) + '/parameters/landmarks_manager.params', "r") as f :
-        parameters = json.loads(f.read())
-        tag_coeff = parameters['tag coeff']
-        park_coeff = parameters['park coeff']
-        church_coeff = parameters['church coeff']
-        radius = parameters['radius close to']
-        bbox_side = parameters['city bbox side']
-    
-    # Generate a bbox around current coordinates
-    bbox = create_bbox(coordinates, bbox_side)
-
-    # Initialize some variables
-    overpass = Overpass()
-    N = 0
-    L = []
-
-    for amenity in list_amenity :
-        query = overpassQueryBuilder(bbox=bbox, elementType=['way', 'relation'], selector=amenity, includeCenter=True, out='body')
-        result = overpass.query(query)
-        N += result.countElements()
-
-        for elem in result.elements():
-
-            name = elem.tag('name')                             # Add name, decode to ASCII
-            location = (elem.centerLat(), elem.centerLon())     # Add coordinates (lat, lon)
-
-            # Skip if unprecise location
-            if name is None or location[0] is None:
-                continue
-
-            # Skip if unused
-            if 'disused:leisure' in elem.tags().keys():
-                    continue
-            
-            else :
-                osm_type = elem.type()              # Add type : 'way' or 'relation'
-                osm_id = elem.id()                  # Add OSM id 
-                elem_type = landmarktype            # Add the landmark type as 'sightseeing
-                n_tags = len(elem.tags().keys())    # Add number of tags
-                
-                # Add score of given landmark based on the number of surrounding elements. Penalty for churches as there are A LOT
-                if amenity == "'amenity'='place_of_worship'" :
-                    score = int((count_elements_within_radius(location, radius) + n_tags*tag_coeff )*church_coeff)  
-                elif amenity == "'leisure'='park'" :
-                    score = int((count_elements_within_radius(location, radius) + n_tags*tag_coeff )*park_coeff)  
-                else :
-                    score = count_elements_within_radius(location, radius) + n_tags*tag_coeff
-                
-                if score is not None :
-                    # Generate the landmark and append it to the list
-                    landmark = Landmark(name=name, type=elem_type, location=location, osm_type=osm_type, osm_id=osm_id, attractiveness=score, must_do=False, n_tags=n_tags)
-                    L.append(landmark)
-
-    return L
-
-def get_landmarks_nominatim(city_country: str, list_amenity: list, landmarktype: LandmarkType) -> List[Landmark] :
-    
-    # Read the parameters from the file
-    with open (os.path.dirname(os.path.abspath(__file__)) + '/parameters/landmarks_manager.params', "r") as f :
-        parameters = json.loads(f.read())
-        tag_coeff = parameters['tag coeff']
-        park_coeff = parameters['park coeff']
-        church_coeff = parameters['church coeff']
-        radius = parameters['radius close to']
-    
-    overpass = Overpass()
-    nominatim = Nominatim()
-    areaId = nominatim.query(city_country).areaId()
-    
-    # Initialize some variables
-    N = 0
-    L = []
-
-    for amenity in list_amenity :
-        query = overpassQueryBuilder(area=areaId, elementType=['way', 'relation'], selector=amenity, includeCenter=True, out='body')
-        result = overpass.query(query)
-        N += result.countElements()
-
-        for elem in result.elements():
-
-            name = elem.tag('name')                             # Add name
-            location = (elem.centerLat(), elem.centerLon())     # Add coordinates (lat, lon)
-
-            # skip if unprecise location
-            if name is None or location[0] is None:
-                continue
-
-            # skip if unused
-            if 'disused:leisure' in elem.tags().keys():
-                    continue
-            
-            else :
-                osm_type = elem.type()              # Add type : 'way' or 'relation'
-                osm_id = elem.id()                  # Add OSM id 
-                elem_type = landmarktype            # Add the landmark type as 'sightseeing
-                n_tags = len(elem.tags().keys())    # Add number of tags
-                
-                # Add score of given landmark based on the number of surrounding elements. Penalty for churches as there are A LOT
-                if amenity == "'amenity'='place_of_worship'" :
-                    score = int((count_elements_within_radius(location, radius) + n_tags*tag_coeff )*church_coeff)  
-                elif amenity == "'leisure'='park'" :
-                    score = int((count_elements_within_radius(location, radius) + n_tags*tag_coeff )*park_coeff)  
-                else :
-                    score = count_elements_within_radius(location, radius) + n_tags*tag_coeff
-
-                if score is not None :
-                    # Generate the landmark and append it to the list
-                    landmark = Landmark(name=name, type=elem_type, location=location, osm_type=osm_type, osm_id=osm_id, attractiveness=score, must_do=False, n_tags=n_tags)
-                    L.append(landmark)
-
-    return L
-
-
-
 
 def get_landmarks(list_amenity: list, landmarktype: LandmarkType, city_country: str = None, coordinates: Tuple[float, float] = None) -> List[Landmark] :
     

backend/src/parameters/landmarks_manager.params

@@ -2,7 +2,7 @@
   "city bbox side" : 10,
   "radius close to" : 27.5,
   "church coeff" : 0.6,
-  "park coeff" : 1.4,
+  "park coeff" : 1.5,
   "tag coeff" : 100,
   "N important" : 30
 }

backend/src/tester.py

@@ -80,7 +80,7 @@ def test4(coordinates: tuple[float, float]) -> List[Landmark]:
 
     landmarks, landmarks_short = generate_landmarks(preferences=preferences, city_country=city_country, coordinates=coordinates)
 
-    #write_data(landmarks)
+    write_data(landmarks)
 
 
     start = Landmark(name='start', type=LandmarkType(landmark_type='start'), location=(48.8375946, 2.2949904), osm_type='start', osm_id=0, attractiveness=0, must_do=True, n_tags = 0)