Implement backend API for landmarks, trip optimization, and toilet locations

- Added landmarks_router.py to handle landmark retrieval based on user preferences and location.
- Implemented optimization_router.py for trip optimization, including handling preferences and landmarks.
- Created toilets_router.py to fetch toilet locations within a specified radius from a given location.
- Enhanced error handling and logging across all new endpoints.
- Generated a comprehensive report.html for test results and environment details.

backend/src/landmarks/landmarks_manager.py

@@ -4,7 +4,6 @@ import yaml
 
 from ..structs.preferences import Preferences
 from ..structs.landmark import Landmark
-from ..utils.take_most_important import take_most_important
 from .cluster_manager import ClusterManager
 from ..overpass.overpass import Overpass, get_base_info
 from ..utils.bbox import create_bbox
@@ -23,7 +22,7 @@ class LandmarkManager:
     church_coeff: float     # coeff to adjsut score of churches
     nature_coeff: float       # coeff to adjust score of parks
     overall_coeff: float        # coeff to adjust weight of tags
-    n_important: int        # number of important landmarks to consider
+    # n_important: int        # number of important landmarks to consider
 
 
     def __init__(self) -> None:
@@ -42,7 +41,7 @@ class LandmarkManager:
             self.wikipedia_bonus = parameters['wikipedia_bonus']
             self.viewpoint_bonus = parameters['viewpoint_bonus']
             self.pay_bonus = parameters['pay_bonus']
-            self.n_important = parameters['N_important']
+            # self.n_important = parameters['N_important']
 
         with OPTIMIZER_PARAMETERS_PATH.open('r') as f:
             parameters = yaml.safe_load(f)
@@ -60,7 +59,7 @@ class LandmarkManager:
             center_coordinates: tuple[float, float],
             preferences: Preferences,
             allow_clusters: bool = True
-            ) -> tuple[list[Landmark], list[Landmark]]:
+            ) -> list[Landmark] :
         """
         Generate and prioritize a list of landmarks based on user preferences.
 
@@ -127,13 +126,12 @@ class LandmarkManager:
                 all_landmarks.update(shopping_clusters)
 
 
-        landmarks_constrained = take_most_important(all_landmarks, self.n_important)
-
         # DETAILS HERE
         # self.logger.info(f'All landmarks generated : {len(all_landmarks)} landmarks around {center_coordinates}, and constrained to {len(landmarks_constrained)} most important ones.')
         self.logger.info(f'Found {len(all_landmarks)} landmarks in total.')
 
-        return all_landmarks, landmarks_constrained
+        return sorted(all_landmarks, key=lambda x: x.attractiveness, reverse=True)
+    
 
     def set_landmark_score(self, landmark: Landmark, landmarktype: str, preference_level: int) :
         """

backend/src/landmarks/landmarks_router.py

@@ -6,7 +6,7 @@ from fastapi import HTTPException, APIRouter
 
 from ..structs.landmark import Landmark
 from ..structs.preferences import Preferences, Preference
-from ..landmarks.landmarks_manager import LandmarkManager
+from .landmarks_manager import LandmarkManager
 
 
 # Setup the logger and the Landmarks Manager
@@ -14,7 +14,7 @@ logger = logging.getLogger(__name__)
 manager = LandmarkManager()
 
 
-# Start the router
+# Initialize the API router
 router = APIRouter()
 
 
@@ -48,7 +48,7 @@ def get_landmarks(
     start_time = time.time()
 
     # Generate the landmarks from the start location
-    landmarks, _ = manager.generate_landmarks_list(
+    landmarks = manager.generate_landmarks_list(
         center_coordinates = start,
         preferences = preferences
     )
@@ -62,7 +62,7 @@ def get_landmarks(
     return landmarks
 
 
-@router.post("/landmarks/get-nearby/{lat}/{lon}")
+@router.post("/get-nearby/landmarks/{lat}/{lon}")
 def get_landmarks_nearby(
     lat: float,
     lon: float
@@ -81,6 +81,7 @@ def get_landmarks_nearby(
         list[Landmark]: A list of selected nearby landmarks.
     """
     logger.info(f'Fetching landmarks nearby ({lat}, {lon}).')
+
     # Define fixed preferences:
     prefs = Preferences(
         sightseeing = Preference(
@@ -100,18 +101,23 @@ def get_landmarks_nearby(
     )
 
     # Find the landmarks around the location
-    _, landmarks_around = manager.generate_landmarks_list(
+    landmarks_around = manager.generate_landmarks_list(
         center_coordinates = (lat, lon),
         preferences = prefs,
         allow_clusters=False,
     )
+
     if len(landmarks_around) == 0 :
         raise HTTPException(status_code=500, detail="No landmarks were found.")
 
-    # select 5 landmarks from there
+    # select 8 - 12 landmarks from there
-    if len(landmarks_around) > 6 :
+    if len(landmarks_around) > 8 :
-        landmarks_around = landmarks_around[:2] + random.sample(landmarks_around[3:], 2)
+        n_imp = random.randint(2,5)
+        rest = random.randint(8 - n_imp, min(12, len(landmarks_around))-n_imp)
 
-    logger.info(f'Found {len(landmarks_around)} landmarks nearby ({lat}, {lon}).')
+        print(f'len = {len(landmarks_around)}\nn_imp = {n_imp}\nrest = {rest}')
-    logger.debug('Suggested landmarks :\n\t' + '\n\t'.join(f'{landmark}' for landmark in landmarks_around))
+        landmarks_around = landmarks_around[:n_imp] + random.sample(landmarks_around[n_imp:], rest)
+    
+    logger.info(f'Found {len(landmarks_around)} landmarks to suggest nearby ({lat}, {lon}).')
+    # logger.debug('Suggested landmarks :\n\t' + '\n\t'.join(f'{landmark}' for landmark in landmarks_around))
     return landmarks_around

backend/src/main.py

@@ -1,22 +1,18 @@
 """Main app for backend api"""
 import logging
-import time
-import random
 from contextlib import asynccontextmanager
-from fastapi import FastAPI, HTTPException, BackgroundTasks
+from fastapi import FastAPI, HTTPException
 
 from .logging_config import configure_logging
 from .structs.landmark import Landmark
-from .structs.preferences import Preferences, Preference
 from .structs.linked_landmarks import LinkedLandmarks
 from .structs.trip import Trip
 from .landmarks.landmarks_manager import LandmarkManager
-from .toilets.toilets_route import router as toilets_router
+from .toilets.toilets_router import router as toilets_router
-from .optimization.optimization_routes import router as optimization_router
+from .optimization.optimization_router import router as optimization_router
-from .landmarks.landmarks_routes import router as landmarks_router
+from .landmarks.landmarks_router import router as landmarks_router, get_landmarks_nearby
 from .optimization.optimizer import Optimizer
 from .optimization.refiner import Refiner
-from .overpass.overpass import fill_cache
 from .cache import client as cache_client
 
 
@@ -40,118 +36,21 @@ app = FastAPI(lifespan=lifespan)
 
 
 
-app.include_router(toilets_router)
+# Fetches the global list of landmarks given preferences and start/end coordinates. Two routes
-app.include_router(optimization_router)
+# Call with "/get/landmarks/" for main entry point of the trip generation pipeline.
+# Call with "/get-nearby/landmarks/" for the NEARBY feature.
 app.include_router(landmarks_router)
 
 
-@app.post("/trip/new")
+# Optimizes the trip given preferences. Second step in the main trip generation pipeline
-def new_trip(
+# Call with "/optimize/trip"
-    preferences: Preferences,
+app.include_router(optimization_router)
-    start: tuple[float, float],
-    end: tuple[float, float] | None = None,
-    background_tasks: BackgroundTasks = None
-) -> Trip:
-    """
-    Main function to call the optimizer.
 
-    Args:
-        preferences : the preferences specified by the user as the post body
-        start       : the coordinates of the starting point
-        end         : the coordinates of the finishing point
-    Returns: 
-        (uuid) : The uuid of the first landmark in the optimized route
-    """
-    if preferences is None:
-        raise HTTPException(status_code=406, detail="Preferences not provided or incomplete.")
-    if (preferences.shopping.score == 0 and
-        preferences.sightseeing.score == 0 and
-        preferences.nature.score == 0) :
-        raise HTTPException(status_code=406, detail="All preferences are 0.")
-    if start is None:
-        raise HTTPException(status_code=406, detail="Start coordinates not provided")
-    if not (-90 <= start[0] <= 90 or -180 <= start[1] <= 180):
-        raise HTTPException(status_code=422, detail="Start coordinates not in range")
-    if end is None:
-        end = start
-        logger.info("No end coordinates provided. Using start=end.")
 
-    logger.info(f"Requested new trip generation. Details:\n\tCoordinates: {start}\n\tTime: {preferences.max_time_minute}\n\tSightseeing: {preferences.sightseeing.score}\n\tNature: {preferences.nature.score}\n\tShopping: {preferences.shopping.score}")
+# Fetches toilets near given coordinates.
+# Call with "/get/toilets" for fetching toilets around coordinates
+app.include_router(toilets_router)
 
-    start_landmark = Landmark(name='start',
-                              type='start',
-                              location=(start[0], start[1]),
-                              osm_type='start',
-                              osm_id=0,
-                              attractiveness=0,
-                              duration=0,
-                              must_do=True,
-                              n_tags = 0)
-
-    end_landmark = Landmark(name='finish',
-                            type='finish',
-                            location=(end[0], end[1]),
-                            osm_type='end',
-                            osm_id=0,
-                            attractiveness=0,
-                            duration=0,
-                            must_do=True,
-                            n_tags=0)
-
-    start_time = time.time()
-
-    # Generate the landmarks from the start location
-    landmarks, landmarks_short = manager.generate_landmarks_list(
-        center_coordinates = start,
-        preferences = preferences
-    )
-
-    if len(landmarks) == 0 :
-        raise HTTPException(status_code=500, detail="No landmarks were found.")
-
-    # insert start and finish to the landmarks list
-    landmarks_short.insert(0, start_landmark)
-    landmarks_short.append(end_landmark)
-
-    t_generate_landmarks = time.time() - start_time
-    logger.info(f'Fetched {len(landmarks)} landmarks in  \t: {round(t_generate_landmarks,3)} seconds')
-    start_time = time.time()
-
-    # First stage optimization
-    try:
-        base_tour = optimizer.solve_optimization(preferences.max_time_minute, landmarks_short)
-    except Exception as exc:
-        logger.error(f"Trip generation failed: {str(exc)}")
-        raise HTTPException(status_code=500, detail=f"Optimization failed: {str(exc)}") from exc
-
-    t_first_stage = time.time() - start_time
-    start_time = time.time()
-
-    # Second stage optimization
-    # TODO : only if necessary (not enough landmarks for ex.)
-    try :
-        refined_tour = refiner.refine_optimization(landmarks, base_tour,
-                                               preferences.max_time_minute,
-                                               preferences.detour_tolerance_minute)
-    except Exception as exc :
-        logger.warning(f"Refiner failed. Proceeding with base trip {str(exc)}")
-        refined_tour = base_tour
-
-    t_second_stage = time.time() - start_time
-
-    logger.debug(f'First stage optimization\t: {round(t_first_stage,3)} seconds')
-    logger.debug(f'Second stage optimization\t: {round(t_second_stage,3)} seconds')
-    logger.info(f'Total computation time\t: {round(t_first_stage + t_second_stage,3)} seconds')
-    linked_tour = LinkedLandmarks(refined_tour)
-
-    # upon creation of the trip, persistence of both the trip and its landmarks is ensured.
-    trip = Trip.from_linked_landmarks(linked_tour, cache_client)
-    logger.info(f'Generated a trip of {trip.total_time} minutes with {len(refined_tour)} landmarks in {round(t_generate_landmarks + t_first_stage + t_second_stage,3)} seconds.')
-    logger.info('Detailed trip :\n\t' + '\n\t'.join(f'{landmark}' for landmark in refined_tour))
-
-    background_tasks.add_task(fill_cache)
-
-    return trip
 
 
 #### For already existing trips/landmarks

backend/src/optimization/optimization_router.py

@@ -1,19 +1,20 @@
-"""Main app for backend api"""
+"""API entry point for the trip optimization."""
+
 import logging
 import time
 import yaml
 from fastapi import HTTPException, APIRouter, BackgroundTasks
 
+from .optimizer import Optimizer
+from .refiner import Refiner
 from ..structs.landmark import Landmark
 from ..structs.preferences import Preferences
 from ..structs.linked_landmarks import LinkedLandmarks
 from ..utils.take_most_important import take_most_important
 from ..structs.trip import Trip
-from ..optimization.optimizer import Optimizer
-from ..optimization.refiner import Refiner
 from ..overpass.overpass import fill_cache
 from ..cache import client as cache_client
-from ..constants import LANDMARK_PARAMETERS_PATH
+from ..constants import OPTIMIZER_PARAMETERS_PATH
 
 
 # Setup the Logger, Optimizer and Refiner
@@ -22,7 +23,7 @@ optimizer = Optimizer()
 refiner = Refiner(optimizer=optimizer)
 
 
-# Start the router
+# Initialize the API router
 router = APIRouter()
 
 
@@ -66,7 +67,8 @@ def optimize_trip(
 
     logger.info(f"Requested new trip generation. Details:\n\tCoordinates: {start}\n\tTime: {preferences.max_time_minute}\n\tSightseeing: {preferences.sightseeing.score}\n\tNature: {preferences.nature.score}\n\tShopping: {preferences.shopping.score}")
 
-    start_landmark = Landmark(name='start',
+    start_landmark = Landmark(
+        name='start',
         type='start',
         location=(start[0], start[1]),
         osm_type='start',
@@ -74,9 +76,11 @@ def optimize_trip(
         attractiveness=0,
         duration=0,
         must_do=True,
-                              n_tags = 0)
+        n_tags = 0
+    )
 
-    end_landmark = Landmark(name='finish',
+    end_landmark = Landmark(
+        name='finish',
         type='finish',
         location=(end[0], end[1]),
         osm_type='end',
@@ -84,10 +88,11 @@ def optimize_trip(
         attractiveness=0,
         duration=0,
         must_do=True,
-                            n_tags=0)
+        n_tags=0
+    )
     
     # From the parameters load the length at which to truncate the landmarks list.
-    with LANDMARK_PARAMETERS_PATH.open('r') as f:
+    with OPTIMIZER_PARAMETERS_PATH.open('r') as f:
             parameters = yaml.safe_load(f)
             n_important = parameters['N_important']
 

backend/src/parameters/landmark_parameters.yaml

@@ -7,5 +7,4 @@ tag_exponent: 1.15
 image_bonus: 1.1
 viewpoint_bonus: 10
 wikipedia_bonus: 1.25
-N_important: 60
 pay_bonus: -1

backend/src/parameters/optimizer_parameters.yaml

@@ -7,3 +7,4 @@ overshoot: 0.0016
 time_limit: 1
 gap_rel: 0.025
 max_iter: 80
+N_important: 60

backend/src/structs/preferences.py

@@ -1,7 +1,7 @@
 """Defines the Preferences used as input for trip generation."""
 
 from typing import Optional, Literal
-from pydantic import BaseModel
+from pydantic import BaseModel, field_validator
 
 
 class Preference(BaseModel) :
@@ -15,6 +15,13 @@ class Preference(BaseModel) :
     type: Literal['sightseeing', 'nature', 'shopping', 'start', 'finish']
     score: int          # score could be from 1 to 5
 
+    @field_validator("type")
+    @classmethod
+    def validate_type(cls, v):
+        if v not in {'sightseeing', 'nature', 'shopping', 'start', 'finish'}:
+            raise ValueError(f"Invalid type: {v}")
+        return v
+
 
 # Input for optimization
 class Preferences(BaseModel) :

backend/src/tests/test_invalid_input.py

@@ -19,15 +19,35 @@ def invalid_client():
         ([48.8566, 2.3522], {}, 422),
 
         # Invalid cases: incomplete preferences.
-        ([48.084588, 7.280405], {"sightseeing": {"type": "sightseeing", "score": 5}, # no shopping
+        ([48.084588, 7.280405], {"sightseeing": {"type": "sightseeing", "score": 5},    # no shopping pref
                                  "nature": {"type": "nature", "score": 5},
                                  }, 422),
-        ([48.084588, 7.280405], {"sightseeing": {"type": "sightseeing", "score": 5}, # no nature
+        ([48.084588, 7.280405], {"sightseeing": {"type": "sightseeing", "score": 5},    # no nature pref
                                  "shopping": {"type": "shopping", "score": 5},
                                  }, 422),
-        ([48.084588, 7.280405], {"nature": {"type": "nature", "score": 5},      # no sightseeing
+        ([48.084588, 7.280405], {"nature": {"type": "nature", "score": 5},              # no sightseeing pref
                                  "shopping": {"type": "shopping", "score": 5},
                                  }, 422),
+        ([48.084588, 7.280405], {"sightseeing": {"type": "nature", "score": 1},         # mixed up preferences types. TODO: i suggest reducing the complexity by remove the Preference object.
+                                 "nature": {"type": "shopping", "score": 1},
+                                 "shopping": {"type": "shopping", "score": 1},
+                                 }, 422),
+        ([48.084588, 7.280405], {"doesnotexist": {"type": "sightseeing", "score": 2},   # non-existing preferences types
+                                 "nature": {"type": "nature", "score": 2},
+                                 "shopping": {"type": "shopping", "score": 2},
+                                 }, 422),
+        ([48.084588, 7.280405], {"sightseeing": {"type": "sightseeing", "score": 3},    # non-existing preferences types
+                                 "nature": {"type": "doesntexisteither", "score": 3},
+                                 "shopping": {"type": "shopping", "score": 3},
+                                 }, 422),
+        ([48.084588, 7.280405], {"sightseeing": {"type": "sightseeing", "score": -1},   # negative preference value
+                                 "nature": {"type": "doesntexisteither", "score": 4},
+                                 "shopping": {"type": "shopping", "score": 4},
+                                 }, 422),
+        ([48.084588, 7.280405], {"sightseeing": {"type": "sightseeing", "score": 10},   # too high preference value
+                                 "nature": {"type": "doesntexisteither", "score": 4},
+                                 "shopping": {"type": "shopping", "score": 4},
+                                 }, 422),
 
         # Invalid cases: unexisting coords
         ([91, 181], {"sightseeing": {"type": "sightseeing", "score": 5},
@@ -53,7 +73,7 @@ def test_input(invalid_client, start, preferences, status_code):   # pylint: dis
     Test new trip creation with different sets of preferences and locations.
     """
     response = invalid_client.post(
-        "/trip/new",
+        "/get/landmarks",
         json ={
             "preferences": preferences,
             "start": start

backend/src/tests/test_nearby.py

@@ -1,22 +1,32 @@
 """Collection of tests to ensure correct implementation and track progress of the get_landmarks_nearby feature. """
+
 from fastapi.testclient import TestClient
 import pytest
 
 from ..main import app
 
+
 @pytest.fixture(scope="module")
 def client():
     """Client used to call the app."""
     return TestClient(app)
 
 
-
-
 @pytest.mark.parametrize(
     "location,status_code",
     [
-        ([45.7576485, 4.8330241], 2000),     # Lyon, Bellecour.
+        ([45.7576485, 4.8330241], 200),    # Lyon, France
-        ([41.4020572, 2.1818985], 2000),       # Barcelona
+        ([41.4020572, 2.1818985], 200),    # Barcelona, Spain
+        ([59.3293, 18.0686], 200),         # Stockholm, Sweden
+        ([43.6532, -79.3832], 200),        # Toronto, Canada
+        ([38.7223, -9.1393], 200),         # Lisbon, Portugal
+        ([6.5244, 3.3792], 200),           # Lagos, Nigeria
+        ([17.3850, 78.4867], 200),         # Hyderabad, India
+        ([30.0444, 31.2357], 200),         # Cairo, Egypt
+        ([50.8503, 4.3517], 200),          # Brussels, Belgium
+        ([35.2271, -80.8431], 200),        # Charlotte, USA
+        ([10.4806, -66.9036], 200),        # Caracas, Venezuela
+        ([9.51074, -13.71118], 200),       # Conakry, Guinea
     ]
 )
 def test_nearby(client, location, status_code):    # pylint: disable=redefined-outer-name
@@ -27,9 +37,7 @@ def test_nearby(client, location, status_code):    # pylint: disable=redefined-o
         client:
         request:
     """
-    response = client.post(f"/landmarks/get-nearby/{location[0]}/{location[1]}")
+    response = client.post(f"/get-nearby/landmarks/{location[0]}/{location[1]}")
-    print(response)
-    print(response.json())
     suggestions = response.json()
 
     # checks :

backend/src/tests/test_toilets.py

@@ -30,12 +30,13 @@ def test_invalid_input(client, location, radius, status_code):    # pylint: disa
         request:
     """
     response = client.post(
-        "/toilets/new",
+        "/get/toilets",
         params={
             "location": location,
             "radius": radius
         }
     )
+    print(response.json())
 
     # checks :
     assert response.status_code == status_code
@@ -58,11 +59,12 @@ def test_no_toilets(client, location, status_code):    # pylint: disable=redefin
         request:
     """
     response = client.post(
-        "/toilets/new",
+        "/get/toilets",
         params={
             "location": location
         }
     )
+    print(response.json())
     toilets_list = [Toilets.model_validate(toilet) for toilet in response.json()]
 
     # checks :
@@ -87,12 +89,14 @@ def test_toilets(client, location, status_code):    # pylint: disable=redefined-
         request:
     """
     response = client.post(
-        "/toilets/new",
+        "/get/toilets",
         params={
             "location": location,
             "radius" : 600
         }
     )
+
+    print(response.json())
     toilets_list = [Toilets.model_validate(toilet) for toilet in response.json()]
 
     # checks :

backend/src/tests/test_trip_generation.py

@@ -23,9 +23,9 @@ def client():
         # Realistic
         (5, 0, 0, 20, [48.0845881, 7.2804050], None),                   # Turckheim
         (5, 5, 5, 120, [45.7576485, 4.8330241], None),                  # Lyon, Bellecour
-        (5, 5, 5, 240, [50.9423526, 6.9577780], None),                  # Cologne, centre
+        (5, 2, 5, 240, [50.9423526, 6.9577780], None),                  # Cologne, centre
-        (5, 5, 5, 180, [48.5846589226, 7.74078715721], None),           # Strasbourg, centre
+        (3, 5, 0, 180, [48.5846589226, 7.74078715721], None),           # Strasbourg, centre
-        (5, 5, 5, 180, [47.377884227, 8.5395114066], None),             # Zurich, centre
+        (2, 4, 5, 180, [47.377884227, 8.5395114066], None),             # Zurich, centre
         (5, 0, 5, 200, [48.85468881798671, 2.3423925755998374], None),  # Paris, centre
         (5, 5, 5, 600, [40.72592726802, -73.9920434795], None),         # New York, Lower Manhattan
     ]

backend/src/toilets/toilets_router.py

@@ -1,16 +1,20 @@
-"""Defines the endpoint for fetching toilet locations."""
+"""API entry point for fetching toilet locations."""
+
 from fastapi import HTTPException, APIRouter, Query
 
-from ..structs.toilets import Toilets
 from .toilets_manager import ToiletsManager
+from ..structs.toilets import Toilets
 
 
-# Define the API router
+# Initialize the API router
 router = APIRouter()
 
 
-@router.post("/toilets/new")
+@router.post("/get/toilets")
-def get_toilets(location: tuple[float, float] = Query(...), radius: int = 500) -> list[Toilets] :
+def get_toilets(
+        location: tuple[float, float] = Query(...),
+        radius: int = 500
+    ) -> list[Toilets] :
     """
     Endpoint to find toilets within a specified radius from a given location.
 

backend/src/utils/take_most_important.py

@@ -1,24 +0,0 @@
-"""Helper function to return only the major landmarks from a large list."""
-from ..structs.landmark import Landmark
-
-def take_most_important(
-    landmarks: list[Landmark],
-    n_important: int
-) -> list[Landmark]:
-    """
-    Given a list of landmarks, return the most important landmarks based on their attractiveness.
-    
-    Args:
-        landmarks (list[Landmark]): List of landmarks that needs to be truncated
-        n_important (int): Number of most important landmarks to return
-    
-    Returns:
-        list[Landmark]: List of the n_important most important landmarks
-    """
-    if n_important == 0 :
-        raise ValueError('Number of landmarks to keep cannot be zero.')
-
-    # Sort landmarks by attractiveness (descending)
-    sorted_landmarks = sorted(landmarks, key=lambda x: x.attractiveness, reverse=True)
-
-    return sorted_landmarks[:n_important]