changed to no dev when building the docker image

- 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.

.gitea/workflows/backend_run_test.yaml

@@ -18,17 +18,17 @@ jobs:
     - name: Install dependencies
       run: |
         apt-get update && apt-get install -y python3 python3-pip
-        pip install pipenv        
+        pip install uv        
 
     - name: Install packages
       run: |
         ls -la
         # install all packages, including dev-packages
-        pipenv install --dev
+        uv sync
       working-directory: backend
 
     - name: Run Tests
-      run: pipenv run pytest src --html=report.html --self-contained-html --log-cli-level=DEBUG
+      run: uv run pytest src --html=report.html --self-contained-html --log-cli-level=DEBUG
       working-directory: backend
 
     - name: Upload HTML report

LICENSE.md

@@ -0,0 +1,30 @@
+# License
+
+## Proprietary License
+
+All code and resources in this repository are the property of AnyDev. The software and related documentation are provided solely for use with services provided by AnyDev. Redistribution, modification, or use of this software outside of its intended service is strictly prohibited without explicit permission.
+
+### Copyright © 2024 AnyDev
+
+All rights reserved.
+
+### Restrictions
+
+- You may not modify, distribute, copy, or reverse engineer any part of this codebase.
+- This software is licensed for use solely in conjunction with services provided by AnyDev.
+- Any commercial use of this software is strictly prohibited without explicit written consent from AnyDev.
+
+## Third-Party Dependencies
+
+This project uses third-party dependencies, which are subject to their respective licenses.
+
+- Python backend dependencies: fastapi, pydantic, numpy, shapely, etc. – Licensed under their respective licenses.
+- Flutter frontend dependencies: Cupertino Icons, sliding_up_panel, http, etc. – Licensed under their respective licenses.
+
+Please refer to each project's documentation for the specific terms and conditions.
+
+## OpenStreetMap Data Usage
+
+This project uses data derived from **OpenStreetMap**. OpenStreetMap data is available under the [Open Database License (ODbL)](https://www.openstreetmap.org/copyright). We comply with the ODbL license, and some of the data displayed in the service may be derived from OpenStreetMap sources. We do not redistribute raw OpenStreetMap data; instead, it is processed and transformed before being used in our services.
+
+More information about OpenStreetMap data usage can be found [here](https://www.openstreetmap.org/copyright).

backend/.gitignore

@@ -1,6 +1,9 @@
 # osm-cache
 cache_XML/
 
+# secrets
+*secrets.yaml
+
 # Byte-compiled / optimized / DLL files
 __pycache__/
 *.py[cod]
@@ -9,6 +12,9 @@ __pycache__/
 # C extensions
 *.so
 
+# Pytest reports
+report.html
+
 # Distribution / packaging
 .Python
 build/

backend/.python-version

@@ -0,0 +1 @@
+3.12.9

backend/Dockerfile

@@ -1,11 +1,29 @@
-FROM python:3.11-slim
+FROM python:3.12-slim-bookworm
 
+# The installer requires curl (and certificates) to download the release archive
+RUN apt-get update && apt-get install -y --no-install-recommends curl ca-certificates
+
+# Download the latest installer
+ADD https://astral.sh/uv/install.sh /uv-installer.sh
+
+# Run the installer then remove it
+RUN sh /uv-installer.sh && rm /uv-installer.sh
+
+# Ensure the installed binary is on the `PATH`
+ENV PATH="/root/.local/bin/:$PATH"
+
+# Set the working directory
 WORKDIR /app
-COPY Pipfile Pipfile.lock .
 
-RUN pip install pipenv
+# Copy uv files
-RUN pipenv install --deploy --system
+COPY pyproject.toml pyproject.toml
+COPY uv.lock uv.lock
+COPY .python-version .python-version
 
+# Sync the venv
+RUN uv sync --frozen --no-cache --no-dev
+
+# Copy application files
 COPY src src
 
 EXPOSE 8000
@@ -17,4 +35,4 @@ ENV MEMCACHED_HOST_PATH=none
 ENV LOKI_URL=none
 
 # explicitly use a string instead of an argument list to force a shell and variable expansion
-CMD fastapi run src/main.py --port 8000 --workers $NUM_WORKERS
+CMD uv run fastapi run src/main.py --port 8000 --workers $NUM_WORKERS

backend/Pipfile

@@ -1,27 +0,0 @@
-[[source]]
-url = "https://pypi.org/simple"
-verify_ssl = true
-name = "pypi"
-
-[dev-packages]
-pylint = "*"
-pytest = "*"
-tomli = "*"
-httpx = "*"
-exceptiongroup = "*"
-pytest-html = "*"
-typing-extensions = "*"
-dill = "*"
-
-[packages]
-numpy = "*"
-fastapi = "*"
-pydantic = "*"
-shapely = "*"
-pymemcache = "*"
-fastapi-cli = "*"
-scikit-learn = "*"
-loki-logger-handler = "*"
-pulp = "*"
-scipy = "*"
-requests = "*"

backend/main.py

@@ -0,0 +1,6 @@
+def main():
+    print("Hello from backend!")
+
+
+if __name__ == "__main__":
+    main()

backend/pyproject.toml

@@ -0,0 +1,55 @@
+[project]
+name = "backend"
+version = "0.1.0"
+description = "Add your description here"
+readme = "README.md"
+requires-python = ">=3.12"
+dependencies = [
+    "annotated-types==0.7.0 ; python_full_version >= '3.8'",
+    "anyio==4.8.0 ; python_full_version >= '3.9'",
+    "certifi==2024.12.14 ; python_full_version >= '3.6'",
+    "charset-normalizer==3.4.1 ; python_full_version >= '3.7'",
+    "click==8.1.8 ; python_full_version >= '3.7'",
+    "fastapi==0.115.7 ; python_full_version >= '3.8'",
+    "fastapi-cli==0.0.7 ; python_full_version >= '3.8'",
+    "h11==0.14.0 ; python_full_version >= '3.7'",
+    "httptools==0.6.4",
+    "idna==3.10 ; python_full_version >= '3.6'",
+    "joblib==1.4.2 ; python_full_version >= '3.8'",
+    "loki-logger-handler==1.1.0 ; python_full_version >= '2.7'",
+    "markdown-it-py==3.0.0 ; python_full_version >= '3.8'",
+    "mdurl==0.1.2 ; python_full_version >= '3.7'",
+    "numpy==2.2.2 ; python_full_version >= '3.10'",
+    "pulp==2.9.0 ; python_full_version >= '3.7'",
+    "pydantic==2.10.6 ; python_full_version >= '3.8'",
+    "pydantic-core==2.27.2 ; python_full_version >= '3.8'",
+    "pygments==2.19.1 ; python_full_version >= '3.8'",
+    "pymemcache==4.0.0 ; python_full_version >= '3.7'",
+    "python-dotenv==1.0.1",
+    "pyyaml==6.0.2",
+    "requests==2.32.3 ; python_full_version >= '3.8'",
+    "rich==13.9.4 ; python_full_version >= '3.8'",
+    "rich-toolkit==0.13.2 ; python_full_version >= '3.8'",
+    "scikit-learn==1.6.1 ; python_full_version >= '3.9'",
+    "scipy==1.15.1 ; python_full_version >= '3.10'",
+    "shapely==2.0.6 ; python_full_version >= '3.7'",
+    "shellingham==1.5.4 ; python_full_version >= '3.7'",
+    "sniffio==1.3.1 ; python_full_version >= '3.7'",
+    "starlette==0.45.3 ; python_full_version >= '3.9'",
+    "threadpoolctl==3.5.0 ; python_full_version >= '3.8'",
+    "typer==0.15.1 ; python_full_version >= '3.7'",
+    "typing-extensions==4.12.2 ; python_full_version >= '3.8'",
+    "urllib3==2.3.0 ; python_full_version >= '3.9'",
+    "uvicorn[standard]==0.34.0 ; python_full_version >= '3.9'",
+    "uvloop==0.21.0",
+    "watchfiles==1.0.4",
+    "websockets==14.2",
+]
+
+[dependency-groups]
+dev = [
+    "httpx>=0.28.1",
+    "ipykernel>=6.30.0",
+    "pytest>=8.4.1",
+    "pytest-html>=4.1.1",
+]

backend/src/landmarks/cluster_manager.py

@@ -8,8 +8,8 @@ from pydantic import BaseModel
 
 from ..overpass.overpass import Overpass, get_base_info
 from ..structs.landmark import Landmark
-from .get_time_distance import get_distance
+from ..utils.get_time_distance import get_distance
-from .utils import create_bbox
+from ..utils.bbox import create_bbox
 
 
 
@@ -103,7 +103,7 @@ class ClusterManager:
             out = out
         )
         except Exception as e:
-            self.logger.error(f"Error fetching clusters: {e}")
+            self.logger.warning(f"Error fetching clusters: {e}")
 
         if result is None :
             self.logger.debug(f"Found no {cluster_type} clusters, overpass query returned no datapoints.")
@@ -146,7 +146,7 @@ class ClusterManager:
                     self.valid = False
 
             else :
-                self.logger.debug(f"Detected 0 {cluster_type} clusters.")
+                self.logger.debug(f"Found 0 {cluster_type} clusters.")
                 self.valid = False
 
 
@@ -242,18 +242,16 @@ class ClusterManager:
                                                   out = 'ids center tags'
                                                   )
             except Exception as e:
-                self.logger.error(f"Error fetching clusters: {e}")
+                self.logger.warning(f"Error fetching clusters: {e}")
                 continue
 
             if result is None :
-                self.logger.error(f"Error fetching clusters: {e}")
+                self.logger.warning(f"Error fetching clusters: query result is None")
                 continue
 
             for elem in result:
-                osm_type = elem.get('type')
+                # Get basic info
-
+                id, coords, name = get_base_info(elem, elem.get('type'), with_name=True)
-                id, coords, name = get_base_info(elem, osm_type, with_name=True)
-
                 if name is None or coords is None :
                     continue
 
@@ -261,7 +259,7 @@ class ClusterManager:
                 if  d < min_dist :
                     min_dist = d
                     new_name = name             # add name
-                    osm_type = osm_type     # add type: 'way' or 'relation'
+                    osm_type = elem.get('type') # add type: 'way' or 'relation'
                     osm_id = id                 # add OSM id
 
         return Landmark(

backend/src/landmarks/landmarks_manager.py

@@ -4,10 +4,9 @@ import yaml
 
 from ..structs.preferences import Preferences
 from ..structs.landmark import Landmark
-from .take_most_important import take_most_important
 from .cluster_manager import ClusterManager
 from ..overpass.overpass import Overpass, get_base_info
-from .utils import create_bbox
+from ..utils.bbox import create_bbox
 
 from ..constants import AMENITY_SELECTORS_PATH, LANDMARK_PARAMETERS_PATH, OPTIMIZER_PARAMETERS_PATH
 
@@ -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)
@@ -55,7 +54,12 @@ class LandmarkManager:
         self.logger.info('LandmakManager successfully initialized.')
 
 
-    def generate_landmarks_list(self, center_coordinates: tuple[float, float], preferences: Preferences) -> tuple[list[Landmark], list[Landmark]]:
+    def generate_landmarks_list(
+            self,
+            center_coordinates: tuple[float, float],
+            preferences: Preferences,
+            allow_clusters: bool = True
+            ) -> list[Landmark] :
         """
         Generate and prioritize a list of landmarks based on user preferences.
 
@@ -63,16 +67,17 @@ class LandmarkManager:
         and current location. It scores and corrects these landmarks, removes duplicates, and then selects the most important
         landmarks based on a predefined criterion.
 
-        Args:
+        Parameters :
             center_coordinates (tuple[float, float]): The latitude and longitude of the center location around which to search.
             preferences (Preferences): The user's preference settings that influence the landmark selection.
+            allow_clusters (bool, optional) : If set to False, no clusters will be fetched. Mainly used for the option to fetch landmarks nearby.
 
         Returns:
         tuple[list[Landmark], list[Landmark]]:
         - A list of all existing landmarks.
         - A list of the most important landmarks based on the user's preferences.
         """
-        self.logger.debug('Starting to fetch landmarks...')
+        self.logger.info(f'Starting to fetch landmarks around {center_coordinates}...')
         max_walk_dist = int((preferences.max_time_minute/2)/60*self.walking_speed*1000/self.detour_factor)
         radius = min(max_walk_dist, int(self.max_bbox_side/2))
 
@@ -89,6 +94,7 @@ class LandmarkManager:
             all_landmarks.update(current_landmarks)
             self.logger.info(f'Found {len(current_landmarks)} sightseeing landmarks')
 
+            if allow_clusters :
             # special pipeline for historic neighborhoods
                 neighborhood_manager = ClusterManager(bbox, 'sightseeing')
                 historic_clusters = neighborhood_manager.generate_clusters()
@@ -113,16 +119,19 @@ class LandmarkManager:
                 landmark.duration = 30
             all_landmarks.update(current_landmarks)
 
+            if allow_clusters :
                 # special pipeline for shopping malls
                 shopping_manager = ClusterManager(bbox, 'shopping')
                 shopping_clusters = shopping_manager.generate_clusters()
                 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 sorted(all_landmarks, key=lambda x: x.attractiveness, reverse=True)
     
-        return all_landmarks, landmarks_constrained
 
     def set_landmark_score(self, landmark: Landmark, landmarktype: str, preference_level: int) :
         """
@@ -197,7 +206,7 @@ class LandmarkManager:
                     out = 'ids center tags'
                     )
             except Exception as e:
-                self.logger.error(f"Error fetching landmarks: {e}")
+                self.logger.debug(f"Failed to fetch landmarks, proceeding without: {str(e)}")
                 continue
 
             return_list += self._to_landmarks(result, landmarktype, preference_level)
@@ -236,6 +245,17 @@ class LandmarkManager:
                 continue
 
             tags = elem.get('tags')
+            n_tags=len(tags)
+
+            # Skip this landmark if not suitable
+            if tags.get('building:part') is not None :
+                continue
+            if tags.get('disused') is not None :
+                continue
+            if tags.get('boundary') is not None :
+                continue
+            if tags.get('shop') is not None and landmarktype != 'shopping' :
+                continue
 
             # Convert this to Landmark object
             landmark = Landmark(name=name,
@@ -244,57 +264,36 @@ class LandmarkManager:
                                 osm_id=id,
                                 osm_type=osm_type,
                                 attractiveness=0,
-                                n_tags=len(tags))
+                                n_tags=n_tags)
 
-            # self.logger.debug('added landmark.')
+            # Extract useful information for score calculation later down the road.
+            landmark.image_url = tags.get('image')
+            landmark.website_url = tags.get('website')
+            landmark.wiki_url = tags.get('wikipedia')
+            landmark.name_en = tags.get('name:en')
 
-            # Browse through tags to add information to landmark.
+            # Check for place of worship
-            for key, value in tags.items():
+            if tags.get('place_of_worship') is not None :
-
-                # Skip this landmark if not suitable.
-                if key == 'building:part' and value == 'yes' :
-                    break
-                if 'disused:' in key :
-                    break
-                if 'boundary:' in key :
-                    break
-                if 'shop' in key and landmarktype != 'shopping' :
-                    break
-                # if value == 'apartments' :
-                #     break
-
-                # Fill in the other attributes.
-                if key == 'image' :
-                    landmark.image_url = value
-                if key == 'website' :
-                    landmark.website_url = value
-                if value == 'place_of_worship' :
                     landmark.is_place_of_worship = True
-                if key == 'wikipedia' :
+                    landmark.name_en = tags.get('place_of_worship')
-                    landmark.wiki_url = value
-                if key == 'name:en' :
-                    landmark.name_en = value
-                if 'building:' in key or 'pay' in key :
-                    landmark.n_tags -= 1
 
-                # Set the duration.
+            # Set the duration. Needed for the optimization.
-                if value in ['museum', 'aquarium', 'planetarium'] :
+            if tags.get('amenity') in ['aquarium', 'planetarium'] or tags.get('tourism') in ['aquarium', 'museum', 'zoo']:
                 landmark.duration = 60
-                elif value == 'viewpoint' :
+            elif tags.get('tourism') == 'viewpoint' :
                 landmark.is_viewpoint = True
                 landmark.duration = 10
-                elif value == 'cathedral' :
+            elif tags.get('building') == 'cathedral' :
                 landmark.is_place_of_worship = False
                 landmark.duration = 10
 
-            else:
+            # Compute the score and add landmark to the list.
             self.set_landmark_score(landmark, landmarktype, preference_level)
             landmarks.append(landmark)
 
-            continue
-
         return landmarks
 
+
 def dict_to_selector_list(d: dict) -> list:
     """
     Convert a dictionary of key-value pairs to a list of Overpass query strings.

backend/src/landmarks/landmarks_router.py

@@ -0,0 +1,123 @@
+"""Main app for backend api"""
+import logging
+import time
+import random
+from fastapi import HTTPException, APIRouter
+
+from ..structs.landmark import Landmark
+from ..structs.preferences import Preferences, Preference
+from .landmarks_manager import LandmarkManager
+
+
+# Setup the logger and the Landmarks Manager
+logger = logging.getLogger(__name__)
+manager = LandmarkManager()
+
+
+# Initialize the API router
+router = APIRouter()
+
+
+@router.post("/get/landmarks")
+def get_landmarks(
+    preferences: Preferences,
+    start: tuple[float, float],
+) -> list[Landmark]:
+    """
+    Function that returns all available landmarks given some preferences and a start position.
+
+    Args:
+        preferences : the preferences specified by the user as the post body
+        start       : the coordinates of the starting point
+    Returns: 
+        list[Landmark] : The full list of fetched landmarks
+    """
+    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")
+
+    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_time = time.time()
+
+    # Generate the landmarks from the start location
+    landmarks = manager.generate_landmarks_list(
+        center_coordinates = start,
+        preferences = preferences
+    )
+
+    if len(landmarks) == 0 :
+        raise HTTPException(status_code=500, detail="No landmarks were found.")
+
+    t_generate_landmarks = time.time() - start_time
+    logger.info(f'Fetched {len(landmarks)} landmarks in  \t: {round(t_generate_landmarks,3)} seconds')
+    
+    return landmarks
+
+
+@router.post("/get-nearby/landmarks/{lat}/{lon}")
+def get_landmarks_nearby(
+    lat: float,
+    lon: float
+) -> list[Landmark] :
+    """
+    Suggests nearby landmarks based on a given latitude and longitude.
+
+    This endpoint returns a curated list of up to 5 landmarks around the given geographical coordinates. It uses fixed preferences for
+    sightseeing, shopping, and nature, with a maximum time constraint of 30 minutes to limit the number of landmarks returned.
+
+    Args:
+        lat (float): Latitude of the user's current location.
+        lon (float): Longitude of the user's current location.
+
+    Returns:
+        list[Landmark]: A list of selected nearby landmarks.
+    """
+    logger.info(f'Fetching landmarks nearby ({lat}, {lon}).')
+
+    # Define fixed preferences:
+    prefs = Preferences(
+        sightseeing = Preference(
+            type='sightseeing',
+            score=5
+        ),
+        shopping = Preference(
+            type='shopping',
+            score=2
+        ),
+        nature = Preference(
+            type='nature',
+            score=5
+        ),
+        max_time_minute=30,
+        detour_tolerance_minute=0,
+    )
+
+    # Find the landmarks around the location
+    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 8 - 12 landmarks from there
+    if len(landmarks_around) > 8 :
+        n_imp = random.randint(2,5)
+        rest = random.randint(8 - n_imp, min(12, len(landmarks_around))-n_imp)
+
+        print(f'len = {len(landmarks_around)}\nn_imp = {n_imp}\nrest = {rest}')
+        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/logging_config.py

@@ -33,14 +33,14 @@ def configure_logging():
         # silence the chatty logs loki generates itself
         logging.getLogger('urllib3.connectionpool').setLevel(logging.WARNING)
         # no need for time since it's added by loki or can be shown in kube logs
-        logging_format = '%(name)s - %(levelname)s - %(message)s'
+        logging_format = '%(name)-55s - %(levelname)-7s - %(message)s'
 
     else:
         # if we are in a debug (local) session, set verbose and rich logging
         from rich.logging import RichHandler
         logging_handlers = [RichHandler()]
         logging_level = logging.DEBUG if is_debug else logging.INFO
-        logging_format = '%(asctime)s - %(name)s - %(levelname)s - %(message)s'
+        logging_format = '%(asctime)s - %(name)-55s - %(levelname)-7s - %(message)s'
 
 
 

backend/src/main.py

@@ -1,20 +1,18 @@
 """Main app for backend api"""
-
 import logging
-import time
 from contextlib import asynccontextmanager
-from fastapi import FastAPI, HTTPException, BackgroundTasks, Query
+from fastapi import FastAPI, HTTPException
 
 from .logging_config import configure_logging
-from .structs.landmark import Landmark, Toilets
+from .structs.landmark import Landmark
-from .structs.preferences import Preferences
 from .structs.linked_landmarks import LinkedLandmarks
 from .structs.trip import Trip
-from .utils.landmarks_manager import LandmarkManager
+from .landmarks.landmarks_manager import LandmarkManager
-from .utils.toilets_manager import ToiletsManager
+from .toilets.toilets_router import router as toilets_router
+from .optimization.optimization_router import router as optimization_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
 
 
@@ -37,109 +35,22 @@ async def lifespan(app: FastAPI):
 app = FastAPI(lifespan=lifespan)
 
 
-@app.post("/trip/new")
-def new_trip(preferences: Preferences,
-             start: tuple[float, float],
-             end: tuple[float, float] | None = None, 
-             background_tasks: BackgroundTasks = None) -> Trip:
-    """
-    Main function to call the optimizer.
 
-    Args:
+# Fetches the global list of landmarks given preferences and start/end coordinates. Two routes
-        preferences : the preferences specified by the user as the post body
+# Call with "/get/landmarks/" for main entry point of the trip generation pipeline.
-        start       : the coordinates of the starting point
+# Call with "/get-nearby/landmarks/" for the NEARBY feature.
-        end         : the coordinates of the finishing point
+app.include_router(landmarks_router)
-    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.")
 
-    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',
+# Optimizes the trip given preferences. Second step in the main trip generation pipeline
-                            type='finish',
+# Call with "/optimize/trip"
-                            location=(end[0], end[1]),
+app.include_router(optimization_router)
-                            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 :
+# Fetches toilets near given coordinates.
-        raise HTTPException(status_code=500, detail="No landmarks were found.")
+# Call with "/get/toilets" for fetching toilets around coordinates
+app.include_router(toilets_router)
 
-    # 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:
-        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 TimeoutError as te :
-        logger.error(f'Refiner failed : {str(te)} Using base tour.')
-        refined_tour = base_tour
-    except Exception as exc :
-        raise HTTPException(status_code=500, detail=f"An unexpected error occurred: {str(exc)}") from exc
-
-    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.debug('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
@@ -158,6 +69,7 @@ def get_trip(trip_uuid: str) -> Trip:
         trip = cache_client.get(f"trip_{trip_uuid}")
         return trip
     except KeyError as exc:
+        logger.error(f"Failed to fetch trip with UUID {trip_uuid}: {str(exc)}")
         raise HTTPException(status_code=404, detail="Trip not found") from exc
 
 
@@ -176,32 +88,46 @@ def get_landmark(landmark_uuid: str) -> Landmark:
         landmark = cache_client.get(f"landmark_{landmark_uuid}")
         return landmark
     except KeyError as exc:
+        logger.error(f"Failed to fetch landmark with UUID {landmark_uuid}: {str(exc)}")
         raise HTTPException(status_code=404, detail="Landmark not found") from exc
 
 
-@app.post("/toilets/new")
+@app.post("/trip/recompute-time/{trip_uuid}/{removed_landmark_uuid}")
-def get_toilets(location: tuple[float, float] = Query(...), radius: int = 500) -> list[Toilets] :
+def update_trip_time(trip_uuid: str, removed_landmark_uuid: str) -> Trip:
     """
-    Endpoint to find toilets within a specified radius from a given location.
+    Updates the reaching times of a given trip when removing a landmark.
-
-    This endpoint expects the `location` and `radius` as **query parameters**, not in the request body.
 
     Args:
-        location (tuple[float, float]): The latitude and longitude of the location to search from.
+        landmark_uuid (str) : unique identifier for a Landmark.
-        radius (int, optional): The radius (in meters) within which to search for toilets. Defaults to 500 meters.
 
     Returns:
-        list[Toilets]: A list of Toilets objects that meet the criteria.
+        (Landmark)          : the corresponding Landmark.
     """
-    if location is None:
+    # First, fetch the trip in the cache.
-        raise HTTPException(status_code=406, detail="Coordinates not provided or invalid")
-    if not (-90 <= location[0] <= 90 or -180 <= location[1] <= 180):
-        raise HTTPException(status_code=422, detail="Start coordinates not in range")
-
-    toilets_manager = ToiletsManager(location, radius)
-
     try:
-        toilets_list = toilets_manager.generate_toilet_list()
+        trip = cache_client.get(f'trip_{trip_uuid}')
-        return toilets_list
     except KeyError as exc:
-        raise HTTPException(status_code=404, detail="No toilets found") from exc
+        logger.error(f"Failed to update trip with UUID {trip_uuid} (trip not found): {str(exc)}")
+        raise HTTPException(status_code=404, detail='Trip not found') from exc
+
+    landmarks = []
+    next_uuid = trip.first_landmark_uuid
+
+    # Extract landmarks
+    try :
+        while next_uuid is not None:
+            landmark = cache_client.get(f'landmark_{next_uuid}')
+            # Filter out the removed landmark.
+            if next_uuid != removed_landmark_uuid :
+                landmarks.append(landmark)
+            next_uuid = landmark.next_uuid  # Prepare for the next iteration
+    except KeyError as exc:
+        logger.error(f"Failed to update trip with UUID {trip_uuid} : {str(exc)}")
+        raise HTTPException(status_code=404, detail=f'landmark {next_uuid} not found') from exc
+
+    # Re-link every thing and compute times again
+    linked_tour = LinkedLandmarks(landmarks)
+    trip = Trip.from_linked_landmarks(linked_tour, cache_client)
+
+    return trip
+

backend/src/optimization/optimization_router.py

@@ -0,0 +1,141 @@
+"""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 ..structs.trip import Trip
+from ..overpass.overpass import fill_cache
+from ..cache import client as cache_client
+from ..constants import OPTIMIZER_PARAMETERS_PATH
+
+
+# Setup the Logger, Optimizer and Refiner
+logger = logging.getLogger(__name__)
+optimizer = Optimizer()
+refiner = Refiner(optimizer=optimizer)
+
+
+# Initialize the API router
+router = APIRouter()
+
+
+@router.post("/optimize/trip")
+def optimize_trip(
+        preferences: Preferences,
+        landmarks: list[Landmark],
+        start: tuple[float, float],
+        end: tuple[float, float] | None = None,
+        background_tasks: BackgroundTasks = None
+    ) -> Trip:
+    """
+    Main function to call the optimizer.
+
+    Args:
+        preferences (Preferences)   : the preferences specified by the user as the post body.
+        start (tuple[float, float]) : the coordinates of the starting point.
+        end tuple[float, float]     : the coordinates of the finishing point.
+        backgroud_tasks (BackgroundTasks) : necessary to fill the cache after the trip has been returned.
+    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 len(landmarks) == 0 :
+        raise HTTPException(status_code=406, detail="No landmarks provided for computing the trip.")
+    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.")
+
+    # Start the timer
+    start_time = time.time()
+
+    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',
+        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
+    )
+    
+    # From the parameters load the length at which to truncate the landmarks list.
+    with OPTIMIZER_PARAMETERS_PATH.open('r') as f:
+            parameters = yaml.safe_load(f)
+            n_important = parameters['N_important']
+
+    # Truncate to the  most important landmarks for a shorter list
+    landmarks_short = landmarks[:n_important]
+
+    # insert start and finish to the shorter landmarks list
+    landmarks_short.insert(0, start_landmark)
+    landmarks_short.append(end_landmark)
+
+    # 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
+    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'Optimized a trip of {trip.total_time} minutes with {len(refined_tour)} landmarks in {round(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
+

backend/src/optimization/optimizer.py

@@ -257,7 +257,6 @@ class Optimizer:
         Returns:
             None: This function modifies the `prob` object by adding L-2 equality constraints in-place.
         """
-        # FIXME: weird 0 artifact in the coefficients popping up
         # Loop through rows 1 to L-2 to prevent stacked ones
         for i in range(1, L-1):
             # Add the constraint that sums across each "row" or "block" in the decision variables
@@ -590,7 +589,7 @@ class Optimizer:
         try :
             prob.solve(pl.PULP_CBC_CMD(msg=False, timeLimit=self.time_limit+1, gapRel=self.gap_rel))
         except Exception as exc :
-            raise Exception(f"No solution found: {exc}") from exc
+            raise Exception(f"No solution found: {str(exc)}") from exc
         status = pl.LpStatus[prob.status]
         solution = [pl.value(var) for var in x]  # The values of the decision variables (will be 0 or 1)
 
@@ -598,7 +597,7 @@ class Optimizer:
 
         # Raise error if no solution is found. FIXME: for now this throws the internal server error
         if status != 'Optimal' :
-            self.logger.error("The problem is overconstrained, no solution on first try.")
+            self.logger.warning("The problem is overconstrained, no solution on first try.")
             raise ArithmeticError("No solution could be found. Please try again with more time or different preferences.")
 
         # If there is a solution, we're good to go, just check for connectiveness
@@ -608,7 +607,7 @@ class Optimizer:
         while circles is not None :
             i += 1
             if i == self.max_iter :
-                self.logger.error(f'Timeout: No solution found after {self.max_iter} iterations.')
+                self.logger.warning(f'Timeout: No solution found after {self.max_iter} iterations.')
                 raise TimeoutError(f"Optimization took too long. No solution found after {self.max_iter} iterations.")
 
             for circle in circles :
@@ -618,12 +617,13 @@ class Optimizer:
             try :
                 prob.solve(pl.PULP_CBC_CMD(msg=False, timeLimit=self.time_limit, gapRel=self.gap_rel))
             except Exception as exc :
-                raise Exception(f"No solution found: {exc}") from exc
+                self.logger.warning("No solution found: {str(exc)")
+                raise Exception(f"No solution found: {str(exc)}") from exc
 
             solution = [pl.value(var) for var in x]
 
             if pl.LpStatus[prob.status] != 'Optimal' :
-                self.logger.error("The problem is overconstrained, no solution after {i} cycles.")
+                self.logger.warning("The problem is overconstrained, no solution after {i} cycles.")
                 raise ArithmeticError("No solution could be found. Please try again with more time or different preferences.")
 
             circles = self.is_connected(solution)

backend/src/optimization/refiner.py

@@ -6,7 +6,6 @@ from shapely import buffer, LineString, Point, Polygon, MultiPoint, concave_hull
 
 from ..structs.landmark import Landmark
 from ..utils.get_time_distance import get_time
-from ..utils.take_most_important import take_most_important
 from .optimizer import Optimizer
 from ..constants import OPTIMIZER_PARAMETERS_PATH
 
@@ -238,7 +237,7 @@ class Refiner :
             if self.is_in_area(area, landmark.location) and landmark.name not in visited_names:
                 second_order_landmarks.append(landmark)
 
-        return take_most_important(second_order_landmarks, int(self.max_landmarks_refiner*0.75))
+        return sorted(second_order_landmarks, key=lambda x: x.attractiveness, reverse=True)[:int(self.max_landmarks_refiner*0.75)]
 
 
     # Try fix the shortest path using shapely
@@ -278,7 +277,7 @@ class Refiner :
             better_tour_poly = concave_hull(MultiPoint(coords))  # Create concave hull with "core" of tour leaving out start and finish
             xs, ys = better_tour_poly.exterior.xy
             """ 
-            ERROR HERE : 
+            FIXED : ERROR HERE : 
                 Exception has occurred: AttributeError
                 'LineString' object has no attribute 'exterior'
             """
@@ -356,7 +355,7 @@ class Refiner :
 
         # If unsuccessful optimization, use the base_tour.
         if new_tour is None:
-            self.logger.warning("No solution found for the refined tour. Returning the initial tour.")
+            self.logger.warning("Refiner failed: No solution found during second stage optimization.")
             new_tour = base_tour
 
         # If only one landmark, return it.
@@ -369,6 +368,7 @@ class Refiner :
         # Fix the tour using Polygons if the path looks weird.
         # Conditions : circular trip and invalid polygon.
         if base_tour[0].location == base_tour[-1].location and not better_poly.is_valid :
+            self.logger.debug("Tours might be funky, attempting to correct with polygons")
             better_tour = self.fix_using_polygon(better_tour)
 
         return better_tour

backend/src/overpass/caching_strategy.py

@@ -1,3 +1,4 @@
+"""Module defining the handling of cache data from Overpass requests."""
 import os
 import json
 import hashlib
@@ -61,7 +62,7 @@ class JSONCache(CachingStrategyBase):
         return None
 
     def set(self, key, value):
-        """Save the JSON data as an ElementTree to the cache."""
+        """Save the JSON data in the cache."""
         filename = self._filename(key)
         try:
             # Write the JSON data to the cache file
@@ -94,7 +95,7 @@ class JSONCache(CachingStrategyBase):
 
     def close(self):
         """Cleanup method, if needed."""
-        pass
+
 
 class CachingStrategy:
     """
@@ -107,6 +108,7 @@ class CachingStrategy:
 
     @classmethod
     def use(cls, strategy_name='JSON', **kwargs):
+        """Define the caching strategy to use."""
         if cls.__strategy:
             cls.__strategy.close()
 
@@ -119,10 +121,12 @@ class CachingStrategy:
 
     @classmethod
     def get(cls, key):
+        """Get the data from the cache."""
         return cls.__strategy.get(key)
 
     @classmethod
     def set(cls, key, value):
+        """Save the data in the cache."""
         cls.__strategy.set(key, value)
 
     @classmethod

backend/src/overpass/overpass.py

@@ -1,5 +1,6 @@
 """Module allowing connexion to overpass api and fectch data from OSM."""
 import os
+import time
 import urllib
 import math
 import logging
@@ -59,13 +60,11 @@ class Overpass :
             return Overpass._filter_landmarks(cached_responses, bbox)
 
         # If there is no cached data, fetch all from Overpass.
-        elif not cached_responses :
+        if not cached_responses :
             query_str = Overpass.build_query(bbox, osm_types, selector, conditions, out)
             self.logger.debug(f'Query string: {query_str}')
             return self.fetch_data_from_api(query_str)
 
-        # Hybrid cache: some data from Overpass, some data from cache.
-        else :
         # Resize the bbox for smaller search area and build new query string.
         non_cached_bbox = Overpass._get_non_cached_bbox(non_cached_cells, bbox)
         query_str = Overpass.build_query(non_cached_bbox, osm_types, selector, conditions, out)
@@ -96,9 +95,10 @@ class Overpass :
                 return elements
 
         except urllib.error.URLError as e:
-            self.logger.error(f"Error connecting to Overpass API: {e}")
+            self.logger.error(f"Error connecting to Overpass API: {str(e)}")
-            raise ConnectionError(f"Error connecting to Overpass API: {e}") from e
+            raise ConnectionError(f"Error connecting to Overpass API: {str(e)}") from e
         except Exception as exc :
+            self.logger.error(f"unexpected error while fetching data from Overpass: {str(exc)}")
             raise Exception(f'An unexpected error occured: {str(exc)}') from exc
 
 
@@ -122,7 +122,7 @@ class Overpass :
                 self.caching_strategy.set(cache_key, elements)
                 self.logger.debug(f'Cache set for {cache_key}')
         except urllib.error.URLError as e:
-            raise ConnectionError(f"Error connecting to Overpass API: {e}") from e
+            raise ConnectionError(f"Error connecting to Overpass API: {str(e)}") from e
         except Exception as exc :
             raise Exception(f'An unexpected error occured: {str(exc)}') from exc
 
@@ -153,7 +153,7 @@ class Overpass :
             - If no conditions are provided, the query will just use the `selector` to filter the OSM 
             elements without additional constraints.
         """
-        query = '[out:json];('
+        query = '[out:json][timeout:20];('
 
         # convert the bbox to string.
         bbox_str = f"({','.join(map(str, bbox))})"
@@ -388,7 +388,7 @@ def get_base_info(elem: dict, osm_type: OSM_TYPES, with_name=False) :
     if with_name :
         name = elem.get('tags', {}).get('name')
         return osm_id, coords, name
-    else :
+
     return osm_id, coords
 
 
@@ -399,18 +399,27 @@ def fill_cache():
     """
     overpass = Overpass()
 
+    n_files = 0
+    total = 0
+
+    overpass.logger.info('Trip successfully returned, starting to fill cache.')
+
     with os.scandir(OSM_CACHE_DIR) as it:
         for entry in it:
             if entry.is_file() and entry.name.startswith('hollow_'):
-
+                total += 1
                 try :
                     # Read the whole file content as a string
-                    with open(entry.path, 'r') as f:
+                    with open(entry.path, 'r', encoding='utf-8') as f:
                         # load data and fill the cache with the query and key
                         json_data = json.load(f)
                         overpass.fill_cache(json_data)
+                        n_files += 1
+                        time.sleep(1)
                     # Now delete the file as the cache is filled
                     os.remove(entry.path)
 
                 except Exception as exc :
-                    overpass.logger.error(f'An error occured while parsing file {entry.path} as .json file')
+                    overpass.logger.error(f'An error occured while parsing file {entry.path} as .json file: {str(exc)}')
+
+    overpass.logger.info(f"Successfully filled {n_files}/{total} cache files.")

backend/src/parameters/amenity_selectors.yaml

@@ -72,6 +72,7 @@ sightseeing:
     # - castle
     # - museum
 
+
 museums:
   tourism:
     - museum

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

@@ -6,4 +6,5 @@ max_landmarks_refiner: 20
 overshoot: 0.0016
 time_limit: 1
 gap_rel: 0.025
-max_iter: 40
+max_iter: 80
+N_important: 60

backend/src/structs/landmark.py

@@ -1,8 +1,7 @@
 """Definition of the Landmark class to handle visitable objects across the world."""
-
 from typing import Optional, Literal
 from uuid import uuid4, UUID
-from pydantic import BaseModel, ConfigDict, Field
+from pydantic import BaseModel, Field
 
 
 # Output to frontend
@@ -50,7 +49,8 @@ class Landmark(BaseModel) :
     image_url : Optional[str] = None
     website_url : Optional[str] = None
     wiki_url : Optional[str] = None
-    description : Optional[str] = None                          # TODO future
+    # keywords: Optional[dict] = {}
+    # description : Optional[str] = None
     duration : Optional[int] = 5
     name_en : Optional[str] = None
 
@@ -69,6 +69,7 @@ class Landmark(BaseModel) :
     is_viewpoint : Optional[bool] = False
     is_place_of_worship : Optional[bool] = False
 
+
     def __str__(self) -> str:
         """
         String representation of the Landmark object.
@@ -122,26 +123,3 @@ class Landmark(BaseModel) :
         return (self.uuid == value.uuid or
                 self.osm_id == value.osm_id or
                 (self.name == value.name and self.distance(value) < 0.001))
-
-
-class Toilets(BaseModel) :
-    """
-    Model for toilets. When false/empty the information is either false either not known.
-    """
-    location : tuple
-    wheelchair : Optional[bool] = False
-    changing_table : Optional[bool] = False
-    fee : Optional[bool] = False
-    opening_hours : Optional[str] = ""
-
-
-    def __str__(self) -> str:
-        """
-        String representation of the Toilets object.
-
-        Returns:
-            str: A formatted string with the toilets location.
-        """
-        return f'Toilets @{self.location}'
-
-    model_config = ConfigDict(from_attributes=True)

backend/src/structs/linked_landmarks.py

@@ -2,6 +2,7 @@
 
 from .landmark import Landmark
 from ..utils.get_time_distance import get_time
+from ..utils.description import description_and_keywords
 
 class LinkedLandmarks:
     """
@@ -35,18 +36,23 @@ class LinkedLandmarks:
         Create the links between the landmarks in the list by setting their 
         .next_uuid and the .time_to_next attributes.
         """
-
         # Mark secondary landmarks as such
         self.update_secondary_landmarks()
 
-
         for i, landmark in enumerate(self._landmarks[:-1]):
+            # Set uuid of the next landmark
             landmark.next_uuid = self._landmarks[i + 1].uuid
+
+            # Adjust time to reach and total time
             time_to_next = get_time(landmark.location, self._landmarks[i + 1].location)
             landmark.time_to_reach_next = time_to_next
             self.total_time += time_to_next
             self.total_time += landmark.duration
 
+            # Fill in the keywords and description. GOOD IDEA, BAD EXECUTION, tags aren't available anymore at this stage
+            # landmark.description, landmark.keywords = description_and_keywords(tags)
+
+
         self._landmarks[-1].next_uuid = None
         self._landmarks[-1].time_to_reach_next = 0
 

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/structs/toilets.py

@@ -0,0 +1,26 @@
+"""Definition of the Toilets class."""
+from typing import Optional
+from pydantic import BaseModel, ConfigDict
+
+
+class Toilets(BaseModel) :
+    """
+    Model for toilets. When false/empty the information is either false either not known.
+    """
+    location : tuple
+    wheelchair : Optional[bool] = False
+    changing_table : Optional[bool] = False
+    fee : Optional[bool] = False
+    opening_hours : Optional[str] = ""
+
+
+    def __str__(self) -> str:
+        """
+        String representation of the Toilets object.
+
+        Returns:
+            str: A formatted string with the toilets location.
+        """
+        return f'Toilets @{self.location}'
+
+    model_config = ConfigDict(from_attributes=True)

backend/src/tests/test_invalid_input.py

@@ -19,30 +19,50 @@ def invalid_client():
         ([48.8566, 2.3522], {}, 422),
 
         # Invalid cases: incomplete preferences.
-        ([48.084588, 7.280405], {"sightseeing": {"type": "nature", "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": "nature", "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": "nature", "score": 5},
+        ([91, 181], {"sightseeing": {"type": "sightseeing", "score": 5},
                      "nature": {"type": "nature", "score": 5},
                      "shopping": {"type": "shopping", "score": 5},
                     }, 422),
-        ([-91, 181], {"sightseeing": {"type": "nature", "score": 5},
+        ([-91, 181], {"sightseeing": {"type": "sightseeing", "score": 5},
                      "nature": {"type": "nature", "score": 5},
                      "shopping": {"type": "shopping", "score": 5},
                     }, 422),
-        ([91, -181], {"sightseeing": {"type": "nature", "score": 5},
+        ([91, -181], {"sightseeing": {"type": "sightseeing", "score": 5},
                      "nature": {"type": "nature", "score": 5},
                      "shopping": {"type": "shopping", "score": 5},
                     }, 422),
-        ([-91, -181], {"sightseeing": {"type": "nature", "score": 5},
+        ([-91, -181], {"sightseeing": {"type": "sightseeing", "score": 5},
                      "nature": {"type": "nature", "score": 5},
                      "shopping": {"type": "shopping", "score": 5},
                     }, 422),
@@ -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_main.py

@@ -1,345 +0,0 @@
-"""Collection of tests to ensure correct implementation and track progress. """
-import time
-from fastapi.testclient import TestClient
-import pytest
-
-from .test_utils import load_trip_landmarks, log_trip_details
-from ..main import app
-
-@pytest.fixture(scope="module")
-def client():
-    """Client used to call the app."""
-    return TestClient(app)
-
-
-def test_turckheim(client, request):    # pylint: disable=redefined-outer-name
-    """
-    Test n°1 : Custom test in Turckheim to ensure small villages are also supported.
-
-    Args:
-        client:
-        request:
-    """
-    start_time = time.time()  # Start timer
-    duration_minutes = 20
-
-    response = client.post(
-        "/trip/new",
-        json={
-            "preferences": {"sightseeing": {"type": "sightseeing", "score": 5},
-            "nature": {"type": "nature", "score": 0},
-            "shopping": {"type": "shopping", "score": 0},
-            "max_time_minute": duration_minutes,
-            "detour_tolerance_minute": 0},
-            "start": [48.084588, 7.280405]
-            # "start": [45.74445023349939, 4.8222687890538865]
-            # "start": [45.75156398104873, 4.827154464827647]
-            }
-        )
-    result = response.json()
-    landmarks = load_trip_landmarks(client, result['first_landmark_uuid'])
-
-
-    # Get computation time
-    comp_time = time.time() - start_time
-
-    # Add details to report
-    log_trip_details(request, landmarks, result['total_time'], duration_minutes)
-
-    # for elem in landmarks :
-    #     print(elem)
-
-    # checks :
-    assert response.status_code == 200  # check for successful planning
-    assert isinstance(landmarks, list)  # check that the return type is a list
-    assert len(landmarks) > 2           # check that there is something to visit
-    assert comp_time < 30, f"Computation time exceeded 30 seconds: {comp_time:.2f} seconds"
-    assert duration_minutes*0.8 < result['total_time'], f"Trip too short: {result['total_time']} instead of {duration_minutes}"
-    assert duration_minutes*1.2 > result['total_time'], f"Trip too long: {result['total_time']} instead of {duration_minutes}"
-    # assert 2!= 3
-
-def test_bellecour(client, request) :   # pylint: disable=redefined-outer-name
-    """
-    Test n°2 : Custom test in Lyon centre to ensure proper decision making in crowded area.
-    
-    Args:
-        client:
-        request:
-    """
-    start_time = time.time()  # Start timer
-    duration_minutes = 120
-
-
-    response = client.post(
-        "/trip/new",
-        json={
-            "preferences": {"sightseeing": {"type": "sightseeing", "score": 5},
-                            "nature": {"type": "nature", "score": 5},
-                            "shopping": {"type": "shopping", "score": 5},
-                            "max_time_minute": duration_minutes,
-                            "detour_tolerance_minute": 0},
-            "start": [45.7576485, 4.8330241]
-            }
-        )
-    result = response.json()
-    landmarks = load_trip_landmarks(client, result['first_landmark_uuid'])
-
-    # Get computation time
-    comp_time = time.time() - start_time
-
-    # Add details to report
-    log_trip_details(request, landmarks, result['total_time'], duration_minutes)
-
-    # for elem in landmarks :
-    #     print(elem)
-
-    # checks :
-    assert response.status_code == 200  # check for successful planning
-    assert comp_time < 30, f"Computation time exceeded 30 seconds: {comp_time:.2f} seconds"
-    assert duration_minutes*0.8 < result['total_time'], f"Trip too short: {result['total_time']} instead of {duration_minutes}"
-    assert duration_minutes*1.2 > result['total_time'], f"Trip too long: {result['total_time']} instead of {duration_minutes}"
-
-def test_cologne(client, request) :   # pylint: disable=redefined-outer-name
-    """
-    Test n°3 : Custom test in Cologne to ensure proper decision making in crowded area.
-    
-    Args:
-        client:
-        request:
-    """
-    start_time = time.time()  # Start timer
-    duration_minutes = 240
-
-    response = client.post(
-        "/trip/new",
-        json={
-            "preferences": {"sightseeing": {"type": "sightseeing", "score": 5},
-                            "nature": {"type": "nature", "score": 5},
-                            "shopping": {"type": "shopping", "score": 5},
-                            "max_time_minute": duration_minutes,
-                            "detour_tolerance_minute": 0},
-            "start": [50.942352665, 6.957777972392]
-            }
-        )
-    result = response.json()
-    landmarks = load_trip_landmarks(client, result['first_landmark_uuid'])
-
-    # Get computation time
-    comp_time = time.time() - start_time
-
-    # Add details to report
-    log_trip_details(request, landmarks, result['total_time'], duration_minutes)
-
-    # for elem in landmarks :
-    #     print(elem)
-
-    # checks :
-    assert response.status_code == 200  # check for successful planning
-    assert comp_time < 30, f"Computation time exceeded 30 seconds: {comp_time:.2f} seconds"
-    assert duration_minutes*0.8 < result['total_time'], f"Trip too short: {result['total_time']} instead of {duration_minutes}"
-    assert duration_minutes*1.2 > result['total_time'], f"Trip too long: {result['total_time']} instead of {duration_minutes}"
-
-
-def test_strasbourg(client, request) :   # pylint: disable=redefined-outer-name
-    """
-    Test n°4 : Custom test in Strasbourg to ensure proper decision making in crowded area.
-    
-    Args:
-        client:
-        request:
-    """
-    start_time = time.time()  # Start timer
-    duration_minutes = 180
-
-    response = client.post(
-        "/trip/new",
-        json={
-            "preferences": {"sightseeing": {"type": "sightseeing", "score": 5},
-                            "nature": {"type": "nature", "score": 5},
-                            "shopping": {"type": "shopping", "score": 5},
-                            "max_time_minute": duration_minutes,
-                            "detour_tolerance_minute": 0},
-            "start": [48.5846589226, 7.74078715721]
-            }
-        )
-    result = response.json()
-    landmarks = load_trip_landmarks(client, result['first_landmark_uuid'])
-
-    # Get computation time
-    comp_time = time.time() - start_time
-
-    # Add details to report
-    log_trip_details(request, landmarks, result['total_time'], duration_minutes)
-
-    # for elem in landmarks :
-    #     print(elem)
-
-    # checks :
-    assert response.status_code == 200  # check for successful planning
-    assert comp_time < 30, f"Computation time exceeded 30 seconds: {comp_time:.2f} seconds"
-    assert duration_minutes*0.8 < result['total_time'], f"Trip too short: {result['total_time']} instead of {duration_minutes}"
-    assert duration_minutes*1.2 > result['total_time'], f"Trip too long: {result['total_time']} instead of {duration_minutes}"
-
-
-def test_zurich(client, request) :   # pylint: disable=redefined-outer-name
-    """
-    Test n°5 : Custom test in Zurich to ensure proper decision making in crowded area.
-    
-    Args:
-        client:
-        request:
-    """
-    start_time = time.time()  # Start timer
-    duration_minutes = 180
-
-    response = client.post(
-        "/trip/new",
-        json={
-            "preferences": {"sightseeing": {"type": "sightseeing", "score": 5},
-                            "nature": {"type": "nature", "score": 5},
-                            "shopping": {"type": "shopping", "score": 5},
-                            "max_time_minute": duration_minutes,
-                            "detour_tolerance_minute": 0},
-            "start": [47.377884227, 8.5395114066]
-            }
-        )
-    result = response.json()
-    landmarks = load_trip_landmarks(client, result['first_landmark_uuid'])
-
-    # Get computation time
-    comp_time = time.time() - start_time
-
-    # Add details to report
-    log_trip_details(request, landmarks, result['total_time'], duration_minutes)
-
-    # for elem in landmarks :
-    #     print(elem)
-
-    # checks :
-    assert response.status_code == 200  # check for successful planning
-    assert comp_time < 30, f"Computation time exceeded 30 seconds: {comp_time:.2f} seconds"
-    assert duration_minutes*0.8 < result['total_time'], f"Trip too short: {result['total_time']} instead of {duration_minutes}"
-    assert duration_minutes*1.2 > result['total_time'], f"Trip too long: {result['total_time']} instead of {duration_minutes}"
-
-
-def test_paris(client, request) :   # pylint: disable=redefined-outer-name
-    """
-    Test n°6 : Custom test in Paris (les Halles) centre to ensure proper decision making in crowded area.
-    
-    Args:
-        client:
-        request:
-    """
-    start_time = time.time()  # Start timer
-    duration_minutes = 200
-
-    response = client.post(
-        "/trip/new",
-        json={
-            "preferences": {"sightseeing": {"type": "sightseeing", "score": 5},
-                            "nature": {"type": "nature", "score": 0},
-                            "shopping": {"type": "shopping", "score": 5},
-                            "max_time_minute": duration_minutes,
-                            "detour_tolerance_minute": 0},
-            "start": [48.85468881798671, 2.3423925755998374]
-            }
-        )
-    result = response.json()
-    landmarks = load_trip_landmarks(client, result['first_landmark_uuid'])
-
-    # Get computation time
-    comp_time = time.time() - start_time
-
-    # Add details to report
-    log_trip_details(request, landmarks, result['total_time'], duration_minutes)
-
-    # for elem in landmarks :
-    #     print(elem)
-
-    # checks :
-    assert response.status_code == 200  # check for successful planning
-    assert comp_time < 30, f"Computation time exceeded 30 seconds: {comp_time:.2f} seconds"
-    assert duration_minutes*0.8 < result['total_time'], f"Trip too short: {result['total_time']} instead of {duration_minutes}"
-    assert duration_minutes*1.2 > result['total_time'], f"Trip too long: {result['total_time']} instead of {duration_minutes}"
-
-
-def test_new_york(client, request) :   # pylint: disable=redefined-outer-name
-    """
-    Test n°7 : Custom test in New York to ensure proper decision making in crowded area.
-    
-    Args:
-        client:
-        request:
-    """
-    start_time = time.time()  # Start timer
-    duration_minutes = 600
-
-    response = client.post(
-        "/trip/new",
-        json={
-            "preferences": {"sightseeing": {"type": "sightseeing", "score": 5},
-                            "nature": {"type": "nature", "score": 5},
-                            "shopping": {"type": "shopping", "score": 5},
-                            "max_time_minute": duration_minutes,
-                            "detour_tolerance_minute": 0},
-            "start": [40.72592726802, -73.9920434795]
-            }
-        )
-    result = response.json()
-    landmarks = load_trip_landmarks(client, result['first_landmark_uuid'])
-
-    # Get computation time
-    comp_time = time.time() - start_time
-
-    # Add details to report
-    log_trip_details(request, landmarks, result['total_time'], duration_minutes)
-
-    # for elem in landmarks :
-    #     print(elem)
-
-    # checks :
-    assert response.status_code == 200  # check for successful planning
-    assert comp_time < 30, f"Computation time exceeded 30 seconds: {comp_time:.2f} seconds"
-    assert duration_minutes*0.8 < result['total_time'], f"Trip too short: {result['total_time']} instead of {duration_minutes}"
-    assert duration_minutes*1.2 > result['total_time'], f"Trip too long: {result['total_time']} instead of {duration_minutes}"
-
-
-def test_shopping(client, request) :   # pylint: disable=redefined-outer-name
-    """
-    Test n°8 : Custom test in Lyon centre to ensure shopping clusters are found.
-    
-    Args:
-        client:
-        request:
-    """
-    start_time = time.time()  # Start timer
-    duration_minutes = 240
-
-    response = client.post(
-        "/trip/new",
-        json={
-            "preferences": {"sightseeing": {"type": "sightseeing", "score": 0},
-                            "nature": {"type": "nature", "score": 0},
-                            "shopping": {"type": "shopping", "score": 5},
-                            "max_time_minute": duration_minutes,
-                            "detour_tolerance_minute": 0},
-            "start": [45.7576485, 4.8330241]
-            }
-        )
-    result = response.json()
-    landmarks = load_trip_landmarks(client, result['first_landmark_uuid'])
-
-    # Get computation time
-    comp_time = time.time() - start_time
-
-    # Add details to report
-    log_trip_details(request, landmarks, result['total_time'], duration_minutes)
-
-    # for elem in landmarks :
-    #     print(elem)
-
-    # checks :
-    assert response.status_code == 200  # check for successful planning
-    assert comp_time < 30, f"Computation time exceeded 30 seconds: {comp_time:.2f} seconds"
-    assert duration_minutes*0.8 < result['total_time'], f"Trip too short: {result['total_time']} instead of {duration_minutes}"
-    assert duration_minutes*1.2 > result['total_time'], f"Trip too long: {result['total_time']} instead of {duration_minutes}"

backend/src/tests/test_nearby.py

@@ -0,0 +1,46 @@
+"""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], 200),    # Lyon, France
+        ([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
+    """
+    Test n°1 : Verify handling of invalid input.
+
+    Args:
+        client:
+        request:
+    """
+    response = client.post(f"/get-nearby/landmarks/{location[0]}/{location[1]}")
+    suggestions = response.json()
+
+    # checks :
+    assert response.status_code == status_code  # check for successful planning
+    assert isinstance(suggestions, list)  # check that the return type is a list
+    assert len(suggestions) > 0

backend/src/tests/test_toilets.py

@@ -3,7 +3,7 @@
 from fastapi.testclient import TestClient
 import pytest
 
-from ..structs.landmark import Toilets
+from ..structs.toilets import Toilets
 from ..main import app
 
 
@@ -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

@@ -0,0 +1,81 @@
+"""Collection of tests to ensure correct implementation and track progress."""
+import time
+from fastapi.testclient import TestClient
+import pytest
+
+from .test_utils import load_trip_landmarks, log_trip_details
+from ..structs.preferences import Preferences, Preference
+from ..main import app
+
+
+@pytest.fixture(scope="module")
+def client():
+    """Client used to call the app."""
+    return TestClient(app)
+
+
+@pytest.mark.parametrize(
+    "sightseeing, shopping, nature, max_time_minute, start_coords, end_coords",
+    [
+        # Edge cases
+        (0, 0, 5, 240, [45.7576485, 4.8330241], None),                  # Lyon, Bellecour - test shopping only
+        
+        # Realistic
+        (5, 0, 0, 20, [48.0845881, 7.2804050], None),                   # Turckheim
+        (5, 5, 5, 120, [45.7576485, 4.8330241], None),                  # Lyon, Bellecour
+        (5, 2, 5, 240, [50.9423526, 6.9577780], None),                  # Cologne, centre
+        (3, 5, 0, 180, [48.5846589226, 7.74078715721], None),           # Strasbourg, 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
+    ]
+)
+def test_trip(client, request, sightseeing, shopping, nature, max_time_minute, start_coords, end_coords):
+
+    start_time = time.time()  # Start timer
+
+    prefs = Preferences(
+        sightseeing=Preference(type='sightseeing', score=sightseeing),
+        shopping=Preference(type='shopping', score=shopping),
+        nature=Preference(type='nature', score=nature),
+        max_time_minute=max_time_minute,
+        detour_tolerance_minute=0,
+    )
+    start = start_coords
+    end = end_coords
+
+    # Step 1: request the list of landmarks in the vicinty of the starting point
+    response = client.post(
+        "/get/landmarks",
+        json={
+            "preferences": prefs.model_dump(),
+            "start": start_coords,
+            "end": end_coords,
+            }
+        )
+    landmarks = response.json()
+
+    # Step 2: Feed the landmarks to the optimizer to compute the trip
+    response = client.post(
+        "/optimize/trip",
+        json={
+            "preferences": prefs.model_dump(),
+            "landmarks": landmarks,
+            "start": start,
+            "end": end,
+            }
+        )
+    result = response.json()
+    landmarks = load_trip_landmarks(client, result['first_landmark_uuid'])
+
+    # Get computation time
+    comp_time = time.time() - start_time
+
+    # Add details to report
+    log_trip_details(request, landmarks, result['total_time'], prefs.max_time_minute)
+
+    # checks :
+    assert response.status_code == 200  # check for successful planning
+    assert comp_time < 30, f"Computation time exceeded 30 seconds: {comp_time:.2f} seconds"
+    assert prefs.max_time_minute*0.8 < result['total_time'], f"Trip too short: {result['total_time']} instead of {prefs.max_time_minute}"
+    assert prefs.max_time_minute*1.2 > result['total_time'], f"Trip too long: {result['total_time']} instead of {prefs.max_time_minute}"

backend/src/tests/test_utils.py

@@ -1,10 +1,12 @@
 """Helper methods for testing."""
+import time
 import logging
+from functools import wraps
 from fastapi import HTTPException
-from pydantic import ValidationError
 
-from ..structs.landmark import Landmark
 from ..cache import client as cache_client
+from ..structs.landmark import Landmark
+from ..structs.preferences import Preferences, Preference
 
 
 def landmarks_to_osmid(landmarks: list[Landmark]) -> list[int] :
@@ -39,7 +41,7 @@ def fetch_landmark(landmark_uuid: str):
     try:
         landmark = cache_client.get(f'landmark_{landmark_uuid}')
         if not landmark :
-            logger.warning(f'Cache miss for landmark UUID: {landmark_uuid}')
+            logger.error(f'Cache miss for landmark UUID: {landmark_uuid}')
             raise HTTPException(status_code=404, detail=f'Landmark with UUID {landmark_uuid} not found in cache.')
 
         # Validate that the fetched data is a dictionary
@@ -92,3 +94,34 @@ def log_trip_details(request, landmarks: list[Landmark], duration: int, target_d
     request.node.trip_details = trip_string
     request.node.trip_duration = str(duration)              # result['total_time']
     request.node.target_duration = str(target_duration)
+
+
+
+
+def trip_params(
+    sightseeing: int,
+    shopping: int,
+    nature: int,
+    max_time_minute: int,
+    start_coords: tuple[float, float] = None,
+    end_coords: tuple[float, float] = None,
+):
+    def decorator(test_func):
+        @wraps(test_func)
+        def wrapper(client, request):
+            prefs = Preferences(
+                sightseeing=Preference(type='sightseeing', score=sightseeing),
+                shopping=Preference(type='shopping', score=shopping),
+                nature=Preference(type='nature', score=nature),
+                max_time_minute=max_time_minute,
+                detour_tolerance_minute=0,
+            )
+
+            start = start_coords
+            end = end_coords
+
+            # Inject into test function
+            return test_func(client, request, prefs, start, end)
+
+        return wrapper
+    return decorator

backend/src/toilets/toilets_manager.py

@@ -2,8 +2,8 @@
 import logging
 
 from ..overpass.overpass import Overpass, get_base_info
-from ..structs.landmark import Toilets
+from ..structs.toilets import Toilets
-from .utils import create_bbox
+from ..utils.bbox import create_bbox
 
 
 # silence the overpass logger
@@ -65,7 +65,7 @@ class ToiletsManager:
         try:
             result = self.overpass.fetch_data_from_api(query_str=query)
         except Exception as e:
-            self.logger.error(f"Error fetching landmarks: {e}")
+            self.logger.error(f"Error fetching toilets: {e}")
             return None
 
         toilets_list = self.to_toilets(result)

backend/src/toilets/toilets_router.py

@@ -0,0 +1,42 @@
+"""API entry point for fetching toilet locations."""
+
+from fastapi import HTTPException, APIRouter, Query
+
+from .toilets_manager import ToiletsManager
+from ..structs.toilets import Toilets
+
+
+# Initialize the API router
+router = APIRouter()
+
+
+@router.post("/get/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.
+
+    This endpoint expects the `location` and `radius` as **query parameters**, not in the request body.
+
+    Args:
+        location (tuple[float, float]): The latitude and longitude of the location to search from.
+        radius (int, optional): The radius (in meters) within which to search for toilets. Defaults to 500 meters.
+
+    Returns:
+        list[Toilets]: A list of Toilets objects that meet the criteria.
+    """
+    if location is None:
+        raise HTTPException(status_code=406, detail="Coordinates not provided or invalid")
+    if not (-90 <= location[0] <= 90 or -180 <= location[1] <= 180):
+        raise HTTPException(status_code=422, detail="Start coordinates not in range")
+
+    toilets_manager = ToiletsManager(location, radius)
+
+    try :
+        toilets_list = toilets_manager.generate_toilet_list()
+    except KeyError as exc:
+        raise HTTPException(status_code=404, detail="No toilets found") from exc
+
+    return toilets_list

backend/src/utils/description.py

@@ -0,0 +1,123 @@
+"""Add more information about the landmarks by writing a short description and keywords. """
+
+
+def description_and_keywords(tags: dict):
+    """
+    Generates a description and a set of keywords for a given landmark based on its tags.
+
+    Params:
+        tags (dict): A dictionary containing metadata about the landmark, including its name,
+                importance, height, date of construction, and visitor information.
+
+    Returns:
+        description (str): A string description of the landmark.
+        keywords (dict): A dictionary of keywords with fields such as 'importance', 'height',
+                    'place_type', and 'date'.
+    """
+    # Extract relevant fields
+    name = tags.get('name')
+    importance = tags.get('importance', None)
+    n_visitors = tags.get('tourism:visitors', None)
+    height = tags.get('height')
+    place_type = get_place_type(tags)
+    date = get_date(tags)
+
+    if place_type is None :
+        return None, None
+
+    # Start the description.
+    if importance is None :
+        if len(tags.keys()) < 5 :
+            return None, None
+        if len(tags.keys()) < 10 :
+            description = f"{name} is a well known {place_type}."
+        elif len(tags.keys()) < 17 :
+            importance = 'national'
+            description = f"{name} is a {place_type} of national importance."
+        else :
+            importance = 'international'
+            description = f"{name} is an internationally famous {place_type}."
+    else :
+        description = f"{name} is a {place_type} of {importance} importance."
+
+    if height is not None and date is not None :
+        description += f" This {place_type} was constructed in {date} and is ca. {height} meters high."
+    elif height is not None :
+        description += f" This {place_type} stands ca. {height} meters tall."
+    elif date is not None:
+        description += f" It was constructed in {date}."
+
+    # Format the visitor number
+    if n_visitors is not None :
+        n_visitors = int(n_visitors)
+        if n_visitors < 1000000 :
+            description += f" It welcomes {int(n_visitors/1000)} thousand visitors every year."
+        else :
+            description += f" It welcomes {round(n_visitors/1000000, 1)} million visitors every year."
+
+    # Set the keywords.
+    keywords = {"importance": importance,
+                "height": height,
+                "place_type": place_type,
+                "date": date}
+
+    return description, keywords
+
+
+def get_place_type(tags):
+    """
+    Determines the type of the place based on available tags such as 'amenity', 'building',
+    'historic', and 'leisure'. The priority order is: 'historic' > 'building' (if not generic) > 
+    'amenity' > 'leisure'.
+
+    Params:
+        tags (dict): A dictionary containing metadata about the place.
+
+    Returns:
+        place_type (str): The determined type of the place, or None if no relevant type is found.
+    """
+    amenity = tags.get('amenity', None)
+    building = tags.get('building', None)
+    historic = tags.get('historic', None)
+    leisure = tags.get('leisure')
+
+    if historic and historic != "yes":
+        return historic
+    if building and building not in ["yes", "civic", "government", "apartments", "residential", "commericial", "industrial", "retail", "religious", "public", "service"]:
+        return building
+    if amenity:
+        return amenity
+    if leisure:
+        return leisure
+
+
+    return None
+
+
+def get_date(tags):
+    """
+    Extracts the most relevant date from the available tags, prioritizing 'construction_date',
+    'start_date', 'year_of_construction', and 'opening_date' in that order.
+
+    Params:
+        tags (dict): A dictionary containing metadata about the place.
+
+    Returns:
+        date (str): The most relevant date found, or None if no date is available.
+    """
+    construction_date = tags.get('construction_date', None)
+    opening_date = tags.get('opening_date', None)
+    start_date = tags.get('start_date', None)
+    year_of_construction = tags.get('year_of_construction', None)
+
+    # Prioritize based on availability
+    if construction_date:
+        return construction_date
+    if start_date:
+        return start_date
+    if year_of_construction:
+        return year_of_construction
+    if opening_date:
+        return opening_date
+
+    return None

backend/src/utils/take_most_important.py

@@ -1,17 +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) -> list[Landmark]:
-    """
-    Given a list of landmarks, return the n_important most important landmarks
-    Args:
-    landmarks: list[Landmark] - list of landmarks
-    n_important: int - number of most important landmarks to return
-    Returns:
-    list[Landmark] - list of the n_important most important landmarks
-    """
-
-    # Sort landmarks by attractiveness (descending)
-    sorted_landmarks = sorted(landmarks, key=lambda x: x.attractiveness, reverse=True)
-
-    return sorted_landmarks[:n_important]

status

@@ -0,0 +1,48 @@
+error: wrong number of arguments, should be from 1 to 2
+usage: git config [<options>]
+
+Config file location
+    --[no-]global         use global config file
+    --[no-]system         use system config file
+    --[no-]local          use repository config file
+    --[no-]worktree       use per-worktree config file
+    -f, --[no-]file <file>
+                          use given config file
+    --[no-]blob <blob-id> read config from given blob object
+
+Action
+    --[no-]get            get value: name [value-pattern]
+    --[no-]get-all        get all values: key [value-pattern]
+    --[no-]get-regexp     get values for regexp: name-regex [value-pattern]
+    --[no-]get-urlmatch   get value specific for the URL: section[.var] URL
+    --[no-]replace-all    replace all matching variables: name value [value-pattern]
+    --[no-]add            add a new variable: name value
+    --[no-]unset          remove a variable: name [value-pattern]
+    --[no-]unset-all      remove all matches: name [value-pattern]
+    --[no-]rename-section rename section: old-name new-name
+    --[no-]remove-section remove a section: name
+    -l, --[no-]list       list all
+    --[no-]fixed-value    use string equality when comparing values to 'value-pattern'
+    -e, --[no-]edit       open an editor
+    --[no-]get-color      find the color configured: slot [default]
+    --[no-]get-colorbool  find the color setting: slot [stdout-is-tty]
+
+Type
+    -t, --[no-]type <type>
+                          value is given this type
+    --bool                value is "true" or "false"
+    --int                 value is decimal number
+    --bool-or-int         value is --bool or --int
+    --bool-or-str         value is --bool or string
+    --path                value is a path (file or directory name)
+    --expiry-date         value is an expiry date
+
+Other
+    -z, --[no-]null       terminate values with NUL byte
+    --[no-]name-only      show variable names only
+    --[no-]includes       respect include directives on lookup
+    --[no-]show-origin    show origin of config (file, standard input, blob, command line)
+    --[no-]show-scope     show scope of config (worktree, local, global, system, command)
+    --[no-]default <value>
+                          with --get, use default value when missing entry
+