automatically save a trip when it is first created

LICENSE.md

@@ -1,30 +0,0 @@
-# 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

@@ -1,9 +1,6 @@
 # osm-cache
 cache_XML/
 
-# secrets
-*secrets.yaml
-
 # Byte-compiled / optimized / DLL files
 __pycache__/
 *.py[cod]

backend/landmarks.json

@@ -1,363 +0,0 @@
-[
-    {
-        "name": "Chinatown",
-        "type": "shopping",
-        "location": [
-            45.7554934,
-            4.8444852
-        ],
-        "osm_type": "way",
-        "osm_id": 996515596,
-        "attractiveness": 129,
-        "n_tags": 0,
-        "image_url": null,
-        "website_url": null,
-        "wiki_url": null,
-        "keywords": {},
-        "description": null,
-        "duration": 30,
-        "name_en": null,
-        "uuid": "285d159c-68ee-4b37-8d71-f27ee3d38b02",
-        "must_do": false,
-        "must_avoid": false,
-        "is_secondary": false,
-        "time_to_reach_next": 0,
-        "next_uuid": null,
-        "is_viewpoint": false,
-        "is_place_of_worship": false
-    },
-    {
-        "name": "Galeries Lafayette",
-        "type": "shopping",
-        "location": [
-            45.7627107,
-            4.8556833
-        ],
-        "osm_type": "way",
-        "osm_id": 1069872743,
-        "attractiveness": 197,
-        "n_tags": 11,
-        "image_url": null,
-        "website_url": "http://www.galerieslafayette.com/",
-        "wiki_url": null,
-        "keywords": null,
-        "description": null,
-        "duration": 30,
-        "name_en": null,
-        "uuid": "28f1bc30-10d3-4944-8861-0ed9abca012d",
-        "must_do": false,
-        "must_avoid": false,
-        "is_secondary": false,
-        "time_to_reach_next": 0,
-        "next_uuid": null,
-        "is_viewpoint": false,
-        "is_place_of_worship": false
-    },
-    {
-        "name": "Muji",
-        "type": "shopping",
-        "location": [
-            45.7615971,
-            4.8543781
-        ],
-        "osm_type": "way",
-        "osm_id": 1044165817,
-        "attractiveness": 259,
-        "n_tags": 14,
-        "image_url": null,
-        "website_url": "https://www.muji.com/fr/",
-        "wiki_url": null,
-        "keywords": null,
-        "description": null,
-        "duration": 30,
-        "name_en": "Muji",
-        "uuid": "957f86a5-6c00-41a2-815d-d6f739052be4",
-        "must_do": false,
-        "must_avoid": false,
-        "is_secondary": false,
-        "time_to_reach_next": 0,
-        "next_uuid": null,
-        "is_viewpoint": false,
-        "is_place_of_worship": false
-    },
-    {
-        "name": "HEMA",
-        "type": "shopping",
-        "location": [
-            45.7619133,
-            4.8565239
-        ],
-        "osm_type": "way",
-        "osm_id": 1069872750,
-        "attractiveness": 156,
-        "n_tags": 9,
-        "image_url": null,
-        "website_url": "https://fr.westfield.com/lapartdieu/store/HEMA/www.hema.fr",
-        "wiki_url": null,
-        "keywords": null,
-        "description": null,
-        "duration": 30,
-        "name_en": null,
-        "uuid": "8dae9d3e-e4c4-4e80-941d-0b106e22c85b",
-        "must_do": false,
-        "must_avoid": false,
-        "is_secondary": false,
-        "time_to_reach_next": 0,
-        "next_uuid": null,
-        "is_viewpoint": false,
-        "is_place_of_worship": false
-    },
-    {
-        "name": "Cordeliers",
-        "type": "shopping",
-        "location": [
-            45.7622752,
-            4.8337998
-        ],
-        "osm_type": "node",
-        "osm_id": 5545183519,
-        "attractiveness": 813,
-        "n_tags": 0,
-        "image_url": null,
-        "website_url": null,
-        "wiki_url": null,
-        "keywords": {},
-        "description": null,
-        "duration": 30,
-        "name_en": null,
-        "uuid": "ba02adb5-e28f-4645-8c2d-25ead6232379",
-        "must_do": false,
-        "must_avoid": false,
-        "is_secondary": false,
-        "time_to_reach_next": 0,
-        "next_uuid": null,
-        "is_viewpoint": false,
-        "is_place_of_worship": false
-    },
-    {
-        "name": "Halles de Lyon Paul Bocuse",
-        "type": "shopping",
-        "location": [
-            45.7628282,
-            4.8505601
-        ],
-        "osm_type": "relation",
-        "osm_id": 971529,
-        "attractiveness": 272,
-        "n_tags": 12,
-        "image_url": null,
-        "website_url": "https://www.halles-de-lyon-paulbocuse.com/",
-        "wiki_url": "fr:Halles de Lyon-Paul Bocuse",
-        "keywords": {
-            "importance": "national",
-            "height": null,
-            "place_type": "marketplace",
-            "date": null
-        },
-        "description": "Halles de Lyon Paul Bocuse is a marketplace of national importance.",
-        "duration": 30,
-        "name_en": null,
-        "uuid": "bbd50de3-aa91-425d-90c2-d4abfd1b4abe",
-        "must_do": false,
-        "must_avoid": false,
-        "is_secondary": false,
-        "time_to_reach_next": 0,
-        "next_uuid": null,
-        "is_viewpoint": false,
-        "is_place_of_worship": false
-    },
-    {
-        "name": "Grand Bazar",
-        "type": "shopping",
-        "location": [
-            45.7632141,
-            4.8361975
-        ],
-        "osm_type": "way",
-        "osm_id": 82399951,
-        "attractiveness": 93,
-        "n_tags": 7,
-        "image_url": null,
-        "website_url": null,
-        "wiki_url": null,
-        "keywords": null,
-        "description": null,
-        "duration": 30,
-        "name_en": null,
-        "uuid": "3de9131c-87c5-4efb-9fa8-064896fb8b29",
-        "must_do": false,
-        "must_avoid": false,
-        "is_secondary": false,
-        "time_to_reach_next": 0,
-        "next_uuid": null,
-        "is_viewpoint": false,
-        "is_place_of_worship": false
-    },
-    {
-        "name": "Shopping Area",
-        "type": "shopping",
-        "location": [
-            45.7673452,
-            4.8438683
-        ],
-        "osm_type": "node",
-        "osm_id": 0,
-        "attractiveness": 156,
-        "n_tags": 0,
-        "image_url": null,
-        "website_url": null,
-        "wiki_url": null,
-        "keywords": {},
-        "description": null,
-        "duration": 30,
-        "name_en": null,
-        "uuid": "df2482a8-7e2e-4536-aad3-564899b2fa65",
-        "must_do": false,
-        "must_avoid": false,
-        "is_secondary": false,
-        "time_to_reach_next": 0,
-        "next_uuid": null,
-        "is_viewpoint": false,
-        "is_place_of_worship": false
-    },
-    {
-        "name": "Cour Oxyg\u00e8ne",
-        "type": "shopping",
-        "location": [
-            45.7620905,
-            4.8568873
-        ],
-        "osm_type": "way",
-        "osm_id": 132673030,
-        "attractiveness": 63,
-        "n_tags": 5,
-        "image_url": null,
-        "website_url": null,
-        "wiki_url": null,
-        "keywords": null,
-        "description": null,
-        "duration": 30,
-        "name_en": null,
-        "uuid": "ed134f76-9a02-4bee-9c10-78454f7bc4ce",
-        "must_do": false,
-        "must_avoid": false,
-        "is_secondary": false,
-        "time_to_reach_next": 0,
-        "next_uuid": null,
-        "is_viewpoint": false,
-        "is_place_of_worship": false
-    },
-    {
-        "name": "P\u00f4le de Commerces et de Loisirs Confluence",
-        "type": "shopping",
-        "location": [
-            45.7410414,
-            4.8171031
-        ],
-        "osm_type": "way",
-        "osm_id": 440270633,
-        "attractiveness": 259,
-        "n_tags": 14,
-        "image_url": null,
-        "website_url": "https://www.confluence.fr/",
-        "wiki_url": null,
-        "keywords": null,
-        "description": null,
-        "duration": 30,
-        "name_en": null,
-        "uuid": "dd7e2f5f-0e60-4560-b903-e5ded4b6e36a",
-        "must_do": false,
-        "must_avoid": false,
-        "is_secondary": false,
-        "time_to_reach_next": 0,
-        "next_uuid": null,
-        "is_viewpoint": false,
-        "is_place_of_worship": false
-    },
-    {
-        "name": "Grand H\u00f4tel-Dieu",
-        "type": "shopping",
-        "location": [
-            45.7586955,
-            4.8364597
-        ],
-        "osm_type": "relation",
-        "osm_id": 300128,
-        "attractiveness": 546,
-        "n_tags": 22,
-        "image_url": null,
-        "website_url": "https://grand-hotel-dieu.com",
-        "wiki_url": "fr:H\u00f4tel-Dieu de Lyon",
-        "keywords": {
-            "importance": "international",
-            "height": null,
-            "place_type": "building",
-            "date": "C17"
-        },
-        "description": "Grand H\u00f4tel-Dieu is an internationally famous building. It was constructed in C17.",
-        "duration": 30,
-        "name_en": null,
-        "uuid": "a91265a8-ffbd-44f7-a7ab-3ff75f08fbab",
-        "must_do": false,
-        "must_avoid": false,
-        "is_secondary": false,
-        "time_to_reach_next": 0,
-        "next_uuid": null,
-        "is_viewpoint": false,
-        "is_place_of_worship": false
-    },
-    {
-        "name": "Westfield La Part-Dieu",
-        "type": "shopping",
-        "location": [
-            45.761331,
-            4.855676
-        ],
-        "osm_type": "way",
-        "osm_id": 62338376,
-        "attractiveness": 546,
-        "n_tags": 22,
-        "image_url": null,
-        "website_url": "https://fr.westfield.com/lapartdieu",
-        "wiki_url": "fr:La Part-Dieu (centre commercial)",
-        "keywords": null,
-        "description": null,
-        "duration": 30,
-        "name_en": null,
-        "uuid": "7d60316f-d689-4fcf-be68-ffc09353b826",
-        "must_do": false,
-        "must_avoid": false,
-        "is_secondary": false,
-        "time_to_reach_next": 0,
-        "next_uuid": null,
-        "is_viewpoint": false,
-        "is_place_of_worship": false
-    },
-    {
-        "name": "Ainay",
-        "type": "shopping",
-        "location": [
-            45.7553105,
-            4.8312084
-        ],
-        "osm_type": "node",
-        "osm_id": 5545126047,
-        "attractiveness": 132,
-        "n_tags": 0,
-        "image_url": null,
-        "website_url": null,
-        "wiki_url": null,
-        "keywords": {},
-        "description": null,
-        "duration": 30,
-        "name_en": null,
-        "uuid": "ad214f3d-a4b9-4078-876a-446caa7ab01c",
-        "must_do": false,
-        "must_avoid": false,
-        "is_secondary": false,
-        "time_to_reach_next": 0,
-        "next_uuid": null,
-        "is_viewpoint": false,
-        "is_place_of_worship": false
-    }
-]

backend/src/main.py

@@ -1,16 +1,17 @@
 """Main app for backend api"""
+
 import logging
 import time
 from contextlib import asynccontextmanager
-from fastapi import FastAPI, HTTPException, BackgroundTasks
+from fastapi import FastAPI, HTTPException, BackgroundTasks, Query
 
 from .logging_config import configure_logging
-from .structs.landmark import Landmark
+from .structs.landmark import Landmark, Toilets
 from .structs.preferences import Preferences
 from .structs.linked_landmarks import LinkedLandmarks
 from .structs.trip import Trip
-from .landmarks.landmarks_manager import LandmarkManager
+from .utils.landmarks_manager import LandmarkManager
-from .toilets.toilet_routes import router as toilets_router
+from .utils.toilets_manager import ToiletsManager
 from .optimization.optimizer import Optimizer
 from .optimization.refiner import Refiner
 from .overpass.overpass import fill_cache
@@ -36,10 +37,6 @@ async def lifespan(app: FastAPI):
 app = FastAPI(lifespan=lifespan)
 
 
-
-app.include_router(toilets_router)
-
-
 @app.post("/trip/new")
 def new_trip(preferences: Preferences,
              start: tuple[float, float],
@@ -69,8 +66,6 @@ def new_trip(preferences: Preferences,
         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}")
-
     start_landmark = Landmark(name='start',
                               type='start',
                               location=(start[0], start[1]),
@@ -92,7 +87,6 @@ def new_trip(preferences: Preferences,
                             n_tags=0)
 
     start_time = time.time()
-
     # Generate the landmarks from the start location
     landmarks, landmarks_short = manager.generate_landmarks_list(
         center_coordinates = start,
@@ -114,7 +108,6 @@ def new_trip(preferences: Preferences,
     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
@@ -126,21 +119,22 @@ def new_trip(preferences: Preferences,
         refined_tour = refiner.refine_optimization(landmarks, base_tour,
                                                preferences.max_time_minute,
                                                preferences.detour_tolerance_minute)
-    except Exception as exc :
+    except TimeoutError as te :
-        logger.warning(f"Refiner failed. Proceeding with base trip {str(exc)}")
+        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)
 
+    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)
 
@@ -163,7 +157,6 @@ 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
 
 
@@ -182,45 +175,32 @@ 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("/trip/recompute-time/{trip_uuid}/{removed_landmark_uuid}")
+@app.post("/toilets/new")
-def update_trip_time(trip_uuid: str, removed_landmark_uuid: str) -> Trip:
+def get_toilets(location: tuple[float, float] = Query(...), radius: int = 500) -> list[Toilets] :
     """
-    Updates the reaching times of a given trip when removing a landmark.
+    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:
-        landmark_uuid (str) : unique identifier for a Landmark.
+        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:
-        (Landmark)          : the corresponding Landmark.
+        list[Toilets]: A list of Toilets objects that meet the criteria.
     """
-    # First, fetch the trip in the cache.
+    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 :
-        trip = cache_client.get(f'trip_{trip_uuid}')
+        toilets_list = toilets_manager.generate_toilet_list()
+        return toilets_list
     except KeyError as exc:
-        logger.error(f"Failed to update trip with UUID {trip_uuid} (trip not found): {str(exc)}")
+        raise HTTPException(status_code=404, detail="No toilets found") from 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/optimizer.py

@@ -257,6 +257,7 @@ 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
@@ -589,15 +590,15 @@ 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: {str(exc)}") from exc
+            raise Exception(f"No solution found: {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)
 
-        self.logger.debug("First results are out. Looking out for circles and correcting...")
+        self.logger.debug("First results are out. Looking out for circles and correcting.")
 
         # Raise error if no solution is found. FIXME: for now this throws the internal server error
         if status != 'Optimal' :
-            self.logger.warning("The problem is overconstrained, no solution on first try.")
+            self.logger.error("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
@@ -607,7 +608,7 @@ class Optimizer:
         while circles is not None :
             i += 1
             if i == self.max_iter :
-                self.logger.warning(f'Timeout: No solution found after {self.max_iter} iterations.')
+                self.logger.error(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 :
@@ -617,13 +618,12 @@ class Optimizer:
             try :
                 prob.solve(pl.PULP_CBC_CMD(msg=False, timeLimit=self.time_limit, gapRel=self.gap_rel))
             except Exception as exc :
-                self.logger.warning("No solution found: {str(exc)")
+                raise Exception(f"No solution found: {exc}") from 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.warning("The problem is overconstrained, no solution after {i} cycles.")
+                self.logger.error("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

@@ -278,7 +278,7 @@ 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
             """ 
-            FIXED : ERROR HERE : 
+            ERROR HERE : 
                 Exception has occurred: AttributeError
                 'LineString' object has no attribute 'exterior'
             """
@@ -356,7 +356,7 @@ class Refiner :
 
         # If unsuccessful optimization, use the base_tour.
         if new_tour is None:
-            self.logger.warning("Refiner failed: No solution found during second stage optimization.")
+            self.logger.warning("No solution found for the refined tour. Returning the initial tour.")
             new_tour = base_tour
 
         # If only one landmark, return it.
@@ -369,7 +369,6 @@ 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

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

@@ -1,6 +1,5 @@
 """Module allowing connexion to overpass api and fectch data from OSM."""
 import os
-import time
 import urllib
 import math
 import logging
@@ -53,22 +52,22 @@ class Overpass :
         # Retrieve cached data and identify missing cache entries
         cached_responses, non_cached_cells = self._retrieve_cached_data(overlapping_cells, osm_types, selector, conditions, out)
 
-        self.logger.debug(f'Cache hit for {len(overlapping_cells)-len(non_cached_cells)}/{len(overlapping_cells)} quadrants.')
+        self.logger.info(f'Cache hit for {len(overlapping_cells)-len(non_cached_cells)}/{len(overlapping_cells)} quadrants.')
 
         # If there is no missing data, return the cached responses after filtering.
         if not non_cached_cells :
             return Overpass._filter_landmarks(cached_responses, bbox)
 
         # If there is no cached data, fetch all from Overpass.
-        if not cached_responses :
+        elif 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)
-        self.logger.debug(f'Query string: {query_str}')
             non_cached_responses = self.fetch_data_from_api(query_str)
             return Overpass._filter_landmarks(cached_responses, bbox) + non_cached_responses
 
@@ -95,10 +94,9 @@ class Overpass :
                 return elements
 
         except urllib.error.URLError as e:
-            self.logger.error(f"Error connecting to Overpass API: {str(e)}")
+            self.logger.error(f"Error connecting to Overpass API: {e}")
-            raise ConnectionError(f"Error connecting to Overpass API: {str(e)}") from e
+            raise ConnectionError(f"Error connecting to Overpass API: {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 +120,7 @@ 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: {str(e)}") from e
+            raise ConnectionError(f"Error connecting to Overpass API: {e}") from e
         except Exception as exc :
             raise Exception(f'An unexpected error occured: {str(exc)}') from exc
 
@@ -153,7 +151,7 @@ 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][timeout:20];('
+        query = '[out:json];('
 
         # convert the bbox to string.
         bbox_str = f"({','.join(map(str, bbox))})"
@@ -388,7 +386,7 @@ 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
 
 
@@ -399,25 +397,18 @@ def fill_cache():
     """
     overpass = Overpass()
 
-    n_files = 0
-    total = 0
-
     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', encoding='utf-8') as f:
+                    with open(entry.path, 'r') 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: {str(exc)}')
+                    overpass.logger.error(f'An error occured while parsing file {entry.path} as .json file')
-
-    overpass.logger.info(f"Successfully filled {n_files}/{total} cache files.")

backend/src/parameters/amenity_selectors.yaml

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

backend/src/parameters/landmark_parameters.yaml

@@ -1,11 +1,12 @@
 max_bbox_side: 4000   #m
 radius_close_to: 50
-church_coeff: 0.75
+church_coeff: 0.55
-nature_coeff: 1.6
+nature_coeff: 1.4
 overall_coeff: 10
 tag_exponent: 1.15
 image_bonus: 1.1
-viewpoint_bonus: 10
+viewpoint_bonus: 5
 wikipedia_bonus: 1.25
+name_bonus: 3
 N_important: 60
 pay_bonus: -1

backend/src/parameters/optimizer_parameters.yaml

@@ -5,5 +5,5 @@ max_landmarks: 10
 max_landmarks_refiner: 20
 overshoot: 0.0016
 time_limit: 1
-gap_rel: 0.025
+gap_rel: 0.05
-max_iter: 80
+max_iter: 40

backend/src/structs/landmark.py

@@ -1,7 +1,8 @@
 """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, Field
+from pydantic import BaseModel, ConfigDict, Field
 
 
 # Output to frontend
@@ -49,8 +50,7 @@ class Landmark(BaseModel) :
     image_url : Optional[str] = None
     website_url : Optional[str] = None
     wiki_url : Optional[str] = None
-    keywords: Optional[dict] = {}
+    description : Optional[str] = None                          # TODO future
-    description : Optional[str] = None
     duration : Optional[int] = 5
     name_en : Optional[str] = None
 
@@ -69,7 +69,6 @@ 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.
@@ -123,3 +122,26 @@ 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/toilets.py

@@ -1,26 +0,0 @@
-"""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_main.py

@@ -31,9 +31,9 @@ def test_turckheim(client, request):    # pylint: disable=redefined-outer-name
             "shopping": {"type": "shopping", "score": 0},
             "max_time_minute": duration_minutes,
             "detour_tolerance_minute": 0},
-            "start": [48.084588, 7.280405]
+            # "start": [48.084588, 7.280405]
             # "start": [45.74445023349939, 4.8222687890538865]
-            # "start": [45.75156398104873, 4.827154464827647]
+            "start": [45.75156398104873, 4.827154464827647]
             }
         )
     result = response.json()
@@ -46,6 +46,8 @@ def test_turckheim(client, request):    # pylint: disable=redefined-outer-name
     # 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

backend/src/tests/test_toilets.py

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

backend/src/tests/test_utils.py

@@ -1,6 +1,7 @@
 """Helper methods for testing."""
 import logging
 from fastapi import HTTPException
+from pydantic import ValidationError
 
 from ..structs.landmark import Landmark
 from ..cache import client as cache_client
@@ -38,7 +39,7 @@ def fetch_landmark(landmark_uuid: str):
     try:
         landmark = cache_client.get(f'landmark_{landmark_uuid}')
         if not landmark :
-            logger.error(f'Cache miss for landmark UUID: {landmark_uuid}')
+            logger.warning(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

backend/src/toilets/toilet_routes.py

@@ -1,38 +0,0 @@
-"""Defines the endpoint for fetching toilet locations."""
-from fastapi import HTTPException, APIRouter, Query
-
-from ..structs.toilets import Toilets
-from .toilets_manager import ToiletsManager
-
-
-# Define the API router
-router = APIRouter()
-
-
-@router.post("/toilets/new")
-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/cluster_manager.py

@@ -1,6 +1,6 @@
 """Find clusters of interest to add more general areas of visit to the tour."""
 import logging
-from typing import Literal, Tuple
+from typing import Literal
 
 import numpy as np
 from sklearn.cluster import DBSCAN
@@ -8,8 +8,8 @@ from pydantic import BaseModel
 
 from ..overpass.overpass import Overpass, get_base_info
 from ..structs.landmark import Landmark
-from ..utils.get_time_distance import get_distance
+from .get_time_distance import get_distance
-from ..utils.bbox import create_bbox
+from .utils import create_bbox
 
 
 
@@ -33,7 +33,7 @@ class Cluster(BaseModel):
     """
     type: Literal['street', 'area']
     importance: int
-    centroid: Tuple[float, float]
+    centroid: tuple
     # start: Optional[list] = None      # for later use if we want to have streets as well
     # end: Optional[list] = None
 
@@ -103,7 +103,7 @@ class ClusterManager:
             out = out
         )
         except Exception as e:
-            self.logger.warning(f"Error fetching clusters: {e}")
+            self.logger.error(f"Error fetching clusters: {e}")
 
         if result is None :
             self.logger.debug(f"Found no {cluster_type} clusters, overpass query returned no datapoints.")
@@ -178,12 +178,11 @@ class ClusterManager:
 
             # Calculate the centroid as the mean of the points
             centroid = np.mean(current_cluster, axis=0)
-            centroid = tuple((round(centroid[0], 7), round(centroid[1], 7)))
 
             if self.cluster_type == 'shopping' :
-                score = len(current_cluster)*3
+                score = len(current_cluster)*2
             else :
-                score = len(current_cluster)*15
+                score = len(current_cluster)*8
             locations.append(Cluster(
                 type='area',
                 centroid=centroid,
@@ -216,7 +215,7 @@ class ClusterManager:
         """
 
         # Define the bounding box for a given radius around the coordinates
-        bbox = create_bbox(cluster.centroid, 300)
+        bbox = create_bbox(cluster.centroid, 1000)
         
         # Query neighborhoods and shopping malls
         selectors = ['"place"~"^(suburb|neighborhood|neighbourhood|quarter|city_block)$"']
@@ -224,10 +223,10 @@ class ClusterManager:
         if self.cluster_type == 'shopping' :
             selectors.append('"shop"="mall"')
             new_name = 'Shopping Area'
-            t = 30
+            t = 40
         else :
             new_name = 'Neighborhood'
-            t = 20
+            t = 15
 
         min_dist = float('inf')
         osm_id = 0
@@ -239,28 +238,30 @@ class ClusterManager:
                 result = self.overpass.send_query(bbox = bbox,
                                                   osm_types = osm_types,
                                                   selector = sel,
-                                                  out = 'ids center tags'
+                                                  out = 'ids center'
                                                   )
             except Exception as e:
-                self.logger.warning(f"Error fetching clusters: {e}")
+                self.logger.error(f"Error fetching clusters: {e}")
                 continue
 
             if result is None :
-                self.logger.warning(f"Error fetching clusters: query result is None")
+                self.logger.error(f"Error fetching clusters: {e}")
                 continue
 
             for elem in result:
-                # Get basic info
+                osm_type = elem.get('type')
-                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
 
                 d = get_distance(cluster.centroid, coords)
                 if  d < min_dist :
                     min_dist = d
-                    new_name = name             # add name
+                    new_name = name
-                    osm_type = elem.get('type') # add type: 'way' or 'relation'
+                    osm_type = osm_type     # Add type: 'way' or 'relation'
-                    osm_id = id                 # add OSM id
+                    osm_id = id             # Add OSM id
 
         return Landmark(
             name=new_name,

backend/src/utils/landmarks_manager.py

@@ -4,10 +4,10 @@ import yaml
 
 from ..structs.preferences import Preferences
 from ..structs.landmark import Landmark
-from ..utils.take_most_important import take_most_important
+from .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
+from .utils import create_bbox
 
 from ..constants import AMENITY_SELECTORS_PATH, LANDMARK_PARAMETERS_PATH, OPTIMIZER_PARAMETERS_PATH
 
@@ -39,6 +39,7 @@ class LandmarkManager:
             self.overall_coeff = parameters['overall_coeff']
             self.tag_exponent = parameters['tag_exponent']
             self.image_bonus = parameters['image_bonus']
+            self.name_bonus = parameters['name_bonus']
             self.wikipedia_bonus = parameters['wikipedia_bonus']
             self.viewpoint_bonus = parameters['viewpoint_bonus']
             self.pay_bonus = parameters['pay_bonus']
@@ -146,8 +147,6 @@ class LandmarkManager:
             score *= self.wikipedia_bonus
         if landmark.is_place_of_worship :
             score *= self.church_coeff
-        if landmark.is_viewpoint :
-            score *= self.viewpoint_bonus
         if landmarktype == 'nature' :
             score *= self.nature_coeff
 
@@ -197,12 +196,12 @@ class LandmarkManager:
                     out = 'ids center tags'
                     )
             except Exception as e:
-                self.logger.debug(f"Failed to fetch landmarks, proceeding without: {str(e)}")
+                self.logger.error(f"Error fetching landmarks: {e}")
                 continue
 
             return_list += self._to_landmarks(result, landmarktype, preference_level)
 
-        # self.logger.debug(f"Fetched {len(return_list)} landmarks of type {landmarktype} in {bbox}")
+        self.logger.debug(f"Fetched {len(return_list)} landmarks of type {landmarktype} in {bbox}")
 
         return return_list
 
@@ -246,6 +245,8 @@ class LandmarkManager:
                                 attractiveness=0,
                                 n_tags=len(tags))
 
+            # self.logger.debug('added landmark.')
+
             # Browse through tags to add information to landmark.
             for key, value in tags.items():
 
@@ -266,7 +267,7 @@ class LandmarkManager:
                     landmark.image_url = value
                 if key == 'website' :
                     landmark.website_url = value
-                if value == 'place_of_worship' :
+                if key == 'place_of_worship' :
                     landmark.is_place_of_worship = True
                 if key == 'wikipedia' :
                     landmark.wiki_url = value
@@ -275,7 +276,6 @@ class LandmarkManager:
                 if 'building:' in key or 'pay' in key :
                     landmark.n_tags -= 1
 
-
                 # Set the duration.
                 if value in ['museum', 'aquarium', 'planetarium'] :
                     landmark.duration = 60
@@ -286,138 +286,14 @@ class LandmarkManager:
                     landmark.is_place_of_worship = False
                     landmark.duration = 10
 
-            landmark.description, landmark.keywords = self.description_and_keywords(tags)
+            else:
                 self.set_landmark_score(landmark, landmarktype, preference_level)
                 landmarks.append(landmark)
 
             continue
 
-
         return landmarks
 
-
-    def description_and_keywords(self, 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 = self.get_place_type(tags)
-        date = self.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(self, data):
-        """
-        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:
-            data (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 = data.get('amenity', None)
-        building = data.get('building', None)
-        historic = data.get('historic', None)
-        leisure = data.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(self, data):
-        """
-        Extracts the most relevant date from the available tags, prioritizing 'construction_date',
-        'start_date', 'year_of_construction', and 'opening_date' in that order.
-
-        Params:
-            data (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 = data.get('construction_date', None)
-        opening_date = data.get('opening_date', None)
-        start_date = data.get('start_date', None)
-        year_of_construction = data.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
-
-
 def dict_to_selector_list(d: dict) -> list:
     """
     Convert a dictionary of key-value pairs to a list of Overpass query strings.

backend/src/utils/toilets_manager.py

@@ -2,8 +2,8 @@
 import logging
 
 from ..overpass.overpass import Overpass, get_base_info
-from ..structs.toilets import Toilets
+from ..structs.landmark import Toilets
-from ..utils.bbox import create_bbox
+from .utils 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 toilets: {e}")
+            self.logger.error(f"Error fetching landmarks: {e}")
             return None
 
         toilets_list = self.to_toilets(result)

status

@@ -1,48 +0,0 @@
-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
-