Merge pull request 'fix/backend/veiwpoint-nodes-and-churches' (#38) from fix/backend/veiwpoint-nodes-and-churches into main

Reviewed-on: #38

.gitea/workflows/backend_run_lint.yaml

@@ -0,0 +1,34 @@
+on:
+  pull_request:
+    branches:
+      - main
+    paths:
+      - backend/**
+
+name: Run linting on the backend code
+
+jobs:
+  build:
+    name: Build
+    runs-on: ubuntu-latest
+    steps:
+
+    - uses: https://gitea.com/actions/checkout@v4
+
+    - name: Install dependencies
+      run: |
+        apt-get update && apt-get install -y python3 python3-pip
+        pip install pipenv        
+
+    - name: Install packages
+      run: |
+        ls -la
+        # only install dev-packages
+        pipenv install --categories=dev-packages
+        pipenv run pip freeze        
+
+      working-directory: backend
+
+    - name: Run linter
+      run: pipenv run pylint src
+      working-directory: backend

.gitea/workflows/backend_run_test.yaml

@@ -0,0 +1,33 @@
+on:
+  pull_request:
+    branches:
+      - main
+    paths:
+      - backend/**
+
+name: Run testing on the backend code
+
+jobs:
+  build:
+    name: Build
+    runs-on: ubuntu-latest
+    steps:
+
+    - uses: https://gitea.com/actions/checkout@v4
+
+    - name: Install dependencies
+      run: |
+        apt-get update && apt-get install -y python3 python3-pip
+        pip install pipenv        
+
+    - name: Install packages
+      run: |
+        ls -la
+        # install all packages, including dev-packages
+        pipenv install --dev
+        pipenv run pip freeze        
+      working-directory: backend
+
+    - name: Run Tests
+      run: pipenv run pytest src
+      working-directory: backend

.gitea/workflows/frontend_build-android.yaml

@@ -6,7 +6,7 @@ on:
       - frontend/**
 
 
-name: Build and release APK
+name: Build and release debug APK
 
 jobs:
   build:
@@ -55,7 +55,7 @@ jobs:
         ls -lah android
       working-directory: ./frontend
 
-    - run: flutter build apk --release --split-per-abi --build-number=${{ gitea.run_number }}
+    - run: flutter build apk --debug --split-per-abi --build-number=${{ gitea.run_number }}
       working-directory: ./frontend
 
     - name: Upload APKs to artifacts

.gitea/workflows/workflow_deploy-container.yaml

@@ -32,4 +32,4 @@ jobs:
     - name: Deploy to k8s
       run: |
         kubectl apply -k backend/deployment/overlays/${{ inputs.overlay }} --kubeconfig=kubeconfig
-        kubectl -n anyway-backend rollout restart deployment/anyway-backend-${{ inputs.overlay }}
+        kubectl -n anyway-backend rollout restart deployment/anyway-backend-${{ inputs.overlay }} --kubeconfig=kubeconfig

.vscode/launch.json

@@ -14,9 +14,9 @@
                 "DEBUG": "true"
             },
             "args": [
-                "--app-dir",
-                "src",
-                "main:app",
+                // "--app-dir",
+                // "src",
+                "src.main:app",
                 "--reload",
             ],
             "jinja": true,

.vscode/settings.json

@@ -0,0 +1,3 @@
+{
+    "cmake.ignoreCMakeListsMissing": true
+}

backend/.pylintrc

@@ -0,0 +1,2 @@
+[MAIN]
+max-line-length=240

backend/Pipfile

@@ -4,14 +4,19 @@ verify_ssl = true
 name = "pypi"
 
 [dev-packages]
+pylint = "*"
+pytest = "*"
+tomli = "*"
+httpx = "*"
+exceptiongroup = "*"
 
 [packages]
 numpy = "*"
 fastapi = "*"
 pydantic = "*"
-geopy = "*"
 shapely = "*"
 scipy = "*"
 osmpythontools = "*"
 pywikibot = "*"
 pymemcache = "*"
+fastapi-cli = "*"

backend/README.md

@@ -1,12 +1,37 @@
 # Backend
 
-This repository contains the backend code for the application. It utilizes FastAPI that allows to quickly create a RESTful API that exposes the endpoints of the route optimizer.
-
+This repository contains the backend code for the application. It utilizes **FastAPI** to quickly create a RESTful API that exposes the endpoints of the route optimizer.
 
 ## Getting Started
-- The code of the python application is located in the `src` directory.
-- Package management is handled with `pipenv` and the dependencies are listed in the `Pipfile`.
-- Since the application is aimed to be deployed in a container, the `Dockerfile` is provided to build the image.
+
+### Directory Structure
+- The code for the Python application is located in the `src` directory.
+- Package management is handled with **pipenv**, and the dependencies are listed in the `Pipfile`.
+- Since the application is designed to be deployed in a container, the `Dockerfile` is provided to build the image.
+
+### Setting Up the Development Environment
+
+To set up your development environment using **pipenv**, follow these steps:
+
+1. Install `pipenv` by running:
+    ```bash
+    sudo apt install pipenv
+    ```
+
+2. Create and activate a virtual environment:
+    ```bash
+    pipenv shell
+    ```
+
+3. Install the dependencies listed in the `Pipfile`:
+    ```bash
+    pipenv install
+    ```
+
+4. The virtual environment will be created under:
+    ```bash
+    ~/.local/share/virtualenvs/...
+    ```
 
 ### Deployment
 To deploy the backend docker container, we use kubernetes. Modifications to the backend are automatically pushed to a two-stage environment through the CI pipeline. See [deployment/README](deployment/README.md] for further information.

backend/src/constants.py

@@ -16,7 +16,7 @@ OSM_CACHE_DIR = Path(cache_dir_string)
 
 import logging
 # if we are in a debug session, set verbose and rich logging
-if os.getenv('DEBUG', False):
+if os.getenv('DEBUG', "false") == "true":
     from rich.logging import RichHandler
     logging.basicConfig(
         level=logging.DEBUG,

backend/src/main.py

@@ -1,14 +1,14 @@
 import logging
 from fastapi import FastAPI, Query, Body, HTTPException
 
-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 utils.optimizer import Optimizer
-from utils.refiner import Refiner
-from persistence import client as cache_client
+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 .utils.optimizer import Optimizer
+from .utils.refiner import Refiner
+from .persistence import client as cache_client
 
 
 logger = logging.getLogger(__name__)
@@ -63,7 +63,7 @@ def new_trip(preferences: Preferences, start: tuple[float, float], end: tuple[fl
     refined_tour = refiner.refine_optimization(landmarks, base_tour, preferences.max_time_minute, preferences.detour_tolerance_minute)
 
     linked_tour = LinkedLandmarks(refined_tour)
-    # upon creation of the trip, persistence of both the trip and its landmarks is ensured. Ca
+    # upon creation of the trip, persistence of both the trip and its landmarks is ensured
     trip = Trip.from_linked_landmarks(linked_tour, cache_client)
     return trip
 
@@ -84,4 +84,4 @@ def get_landmark(landmark_uuid: str) -> Landmark:
         landmark = cache_client.get(f"landmark_{landmark_uuid}")
         return landmark
     except KeyError:
-        raise HTTPException(status_code=404, detail="Landmark not found")
+        raise HTTPException(status_code=404, detail="Landmark not found")

backend/src/parameters/amenity_selectors.yaml

@@ -1,3 +1,6 @@
+# Tags were picked mostly arbitrarily, based on the OSM wiki and the OSM tags page.
+# See https://taginfo.openstreetmap.org for more inspiration.
+
 nature:
   leisure: park
   geological: ''
@@ -11,7 +14,24 @@ nature:
     - alpine_hut
     - viewpoint
     - zoo
-  waterway: waterfall
+    - resort
+    - picnic_site
+  water:
+    - pond
+    - lake
+    - river
+    - basin
+    - stream
+    - lagoon
+    - rapids
+  waterway:
+    - waterfall
+    - river
+    - canal
+    - dam
+    - dock
+    - boatyard
+
 
 shopping:
   shop:
@@ -23,10 +43,47 @@ sightseeing:
     - museum
     - attraction
     - gallery
+    - artwork
+    - aquarium
   historic: ''
   amenity:
     - planetarium
     - place_of_worship
     - fountain
+    - townhall
   water:
     - reflecting_pool
+  bridge:
+    - aqueduct
+    - viaduct
+    - boardwalk
+    - cantilever
+    - abandoned
+  building:
+    - church
+    - chapel
+    - mosque
+    - synagogue
+    - ruins
+    - temple
+    - government
+    - cathedral
+    - castle
+    - museum
+
+
+
+
+# to be used later on
+restauration:
+  shop:
+    - coffee
+    - bakery
+    - restaurant
+    - pastry
+  amenity:
+    - restaurant
+    - cafe
+    - ice_cream
+    - food_court
+    - biergarten

backend/src/parameters/landmark_parameters.yaml

@@ -1,11 +1,12 @@
 city_bbox_side: 7500 #m
 radius_close_to: 50
-church_coeff: 0.75
+church_coeff: 0.9
 nature_coeff: 1.25
 overall_coeff: 10
 tag_exponent: 1.15
 image_bonus: 10
 viewpoint_bonus: 15
-wikipedia_bonus: 6
+wikipedia_bonus: 4
+name_bonus: 3
 N_important: 40
 pay_bonus: -1

backend/src/parameters/optimizer_parameters.yaml

@@ -3,4 +3,4 @@ detour_corridor_width: 300
 average_walking_speed: 4.8
 max_landmarks: 10
 max_landmarks_refiner: 30
-overshoot: 1.8
+overshoot: 1.15

backend/src/persistence.py

@@ -1,7 +1,6 @@
 from pymemcache.client.base import Client
-from pymemcache import serde
 
-import constants
+from .constants import MEMCACHED_HOST_PATH
 
 
 class DummyClient:
@@ -16,13 +15,12 @@ class DummyClient:
         return self._data[key]
 
 
-if constants.MEMCACHED_HOST_PATH is None:
+if MEMCACHED_HOST_PATH is None:
     client = DummyClient()
 else:
     client = Client(
-        constants.MEMCACHED_HOST_PATH,
+        MEMCACHED_HOST_PATH,
         timeout=1,
         allow_unicode_keys=True,
-        encoding='utf-8',
-        serde=serde.pickle_serde
+        encoding='utf-8'
     )

backend/src/structs/landmark.py

@@ -5,7 +5,7 @@ from uuid import uuid4
 
 # Output to frontend
 class Landmark(BaseModel) :
-    
+
     # Properties of the landmark
     name : str
     type: Literal['sightseeing', 'nature', 'shopping', 'start', 'finish']
@@ -14,31 +14,39 @@ class Landmark(BaseModel) :
     osm_id : int
     attractiveness : int
     n_tags : int
-    image_url : Optional[str] = None                            # TODO future
+    image_url : Optional[str] = None
     website_url : Optional[str] = None
-    wikipedia_url : Optional[str] = None
     description : Optional[str] = None                          # TODO future
-    duration : Optional[int] = 0                                # TODO future
+    duration : Optional[int] = 0
     name_en : Optional[str] = None
 
     # Unique ID of a given landmark
-    uuid: str = Field(default_factory=uuid4)                    # TODO implement this ASAP
-    
+    uuid: str = Field(default_factory=uuid4)
+
     # Additional properties depending on specific tour
     must_do : Optional[bool] = False
     must_avoid : Optional[bool] = False
     is_secondary : Optional[bool] = False                       # TODO future   
-    
-    time_to_reach_next : Optional[int] = 0                      # TODO fix this in existing code
-    next_uuid : Optional[str] = None                            # TODO implement this ASAP
 
-    def __hash__(self) -> int:
-        return self.uuid.int
-    
+    time_to_reach_next : Optional[int] = 0
+    next_uuid : Optional[str] = None
+
     def __str__(self) -> str:
         time_to_next_str = f", time_to_next={self.time_to_reach_next}" if self.time_to_reach_next else ""
         is_secondary_str = f", secondary" if self.is_secondary else ""
         type_str = '(' + self.type + ')'
         if self.type in ["start", "finish", "nature", "shopping"] : type_str += '\t '
         return f'Landmark{type_str}: [{self.name} @{self.location}, score={self.attractiveness}{time_to_next_str}{is_secondary_str}]'
-    
+
+    def distance(self, value: 'Landmark') -> float:
+        return (self.location[0] - value.location[0])**2 + (self.location[1] - value.location[1])**2
+
+    def __hash__(self) -> int:
+        return hash(self.name)
+
+    def __eq__(self, value: 'Landmark') -> bool:
+        # eq and hash must be consistent
+        # in particular, if two objects are equal, their hash must be equal
+        # uuid and osm_id are just shortcuts to avoid comparing all the properties
+        # if they are equal, we know that the name is also equal and in turn the hash is equal
+        return self.uuid == value.uuid or self.osm_id == value.osm_id or (self.name == value.name and self.distance(value) < 0.001)

backend/src/structs/linked_landmarks.py

@@ -1,5 +1,5 @@
 from .landmark import Landmark
-from utils.get_time_separation import get_time
+from ..utils.get_time_separation import get_time
 
 class LinkedLandmarks:
     """
@@ -35,6 +35,7 @@ class LinkedLandmarks:
             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
 
         self._landmarks[-1].next_uuid = None
         self._landmarks[-1].time_to_reach_next = 0

backend/src/structs/trip.py

@@ -22,9 +22,10 @@ class Trip(BaseModel):
 
         # Store the trip in the cache
         cache_client.set(f"trip_{trip.uuid}", trip)
-        cache_client.set_many({f"landmark_{landmark.uuid}": landmark for landmark in landmarks}, expire=3600)
+        # make sure to await the result (noreply=False). Otherwise the cache might not be inplace when the trip is actually requested
+        cache_client.set_many({f"landmark_{landmark.uuid}": landmark for landmark in landmarks}, expire=3600, noreply=False)
         # is equivalent to:
         # for landmark in landmarks:
         #     cache_client.set(f"landmark_{landmark.uuid}", landmark, expire=3600)
 
-        return trip
+        return trip

backend/src/tester.py

@@ -1,12 +1,12 @@
 import logging
 import yaml
 
-from utils.landmarks_manager import LandmarkManager
-from utils.optimizer import Optimizer
-from utils.refiner import Refiner
-from structs.landmark import Landmark
-from structs.linked_landmarks import LinkedLandmarks
-from structs.preferences import Preferences, Preference
+from .utils.landmarks_manager import LandmarkManager
+from .utils.optimizer import Optimizer
+from .utils.refiner import Refiner
+from .structs.landmark import Landmark
+from .structs.linked_landmarks import LinkedLandmarks
+from .structs.preferences import Preferences, Preference
 
 
 logger = logging.getLogger(__name__)
@@ -22,8 +22,8 @@ def test(start_coords: tuple[float, float], finish_coords: tuple[float, float] =
     preferences = Preferences(
         sightseeing=Preference(type='sightseeing', score = 5),
         nature=Preference(type='nature', score = 5),
-        shopping=Preference(type='shopping', score = 5),
-        max_time_minute=100,
+        shopping=Preference(type='shopping', score = 0),
+        max_time_minute=30,
         detour_tolerance_minute=0
     )
 
@@ -74,6 +74,7 @@ def test(start_coords: tuple[float, float], finish_coords: tuple[float, float] =
 # test(tuple((48.8344400, 2.3220540)))       # Café Chez César 
 # test(tuple((48.8375946, 2.2949904)))       # Point random
 # test(tuple((47.377859, 8.540585)))         # Zurich HB
-# test(tuple((45.758217, 4.831814)))      # Lyon Bellecour
-test(tuple((48.5848435, 7.7332974)))      # Strasbourg Gare
+test(tuple((45.758217, 4.831814)))         # Lyon Bellecour
+# test(tuple((48.5848435, 7.7332974)))       # Strasbourg Gare
 # test(tuple((48.2067858, 16.3692340)))      # Vienne
+# test(tuple((48.2432090, 7.3892691)))         # Orschwiller 

backend/src/tests/test_main.py

@@ -0,0 +1,141 @@
+from fastapi.testclient import TestClient
+from typing import List
+import pytest
+from ..main import app
+from ..structs.landmark import Landmark
+
+
+@pytest.fixture()
+def client():
+    return TestClient(app)
+
+
+# Base test for checking if the API returns correct error code when no preferences are specified.
+def test_new_trip_invalid_prefs(client):
+    response = client.post(
+        "/trip/new",
+        json={
+            "preferences": {},
+            "start": [48.8566, 2.3522]
+            }
+        )
+    assert response.status_code == 422
+
+    
+# Test no. 1
+def test_turckheim(client):
+    duration_minutes = 15
+    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": [48.084588, 7.280405]
+            }
+        )
+    result = response.json()
+    landmarks = load_trip_landmarks(client, result['first_landmark_uuid'])
+
+    # checks :
+    assert response.status_code == 200  # check for successful planning
+    assert isinstance(landmarks, list)  # check that the return type is a list
+    assert duration_minutes*0.8 < int(result['total_time']) < duration_minutes*1.2
+    assert len(landmarks) > 2           # check that there is something to visit
+
+
+# Test no. 2
+def test_bellecour(client) :
+    duration_minutes = 35
+    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'])
+    osm_ids = landmarks_to_osmid(landmarks)
+
+    # checks :
+    assert response.status_code == 200  # check for successful planning
+    assert duration_minutes*0.8 < int(result['total_time']) < duration_minutes*1.2
+    assert 136200148 in osm_ids         # check for Cathédrale St. Jean in trip
+
+
+
+def landmarks_to_osmid(landmarks: List[Landmark]) -> list :
+    """
+    Convert the list of landmarks into a list containing their osm ids for quick landmark checking.
+    
+    Args :
+        landmarks (list): the list of landmarks
+    
+    Returns :
+        ids (list)      : the list of corresponding OSM ids
+    """
+    ids = []
+    for landmark in landmarks :
+        ids.append(landmark.osm_id)
+
+    return ids
+
+def fetch_landmark(client, landmark_uuid):
+    """
+    Fetch landmark data from the API based on the landmark UUID.
+
+    Args:
+        landmark_uuid (str): The UUID of the landmark.
+
+    Returns:
+        dict: Landmark data fetched from the API.
+    """
+    response = client.get(f"/landmark/{landmark_uuid}")
+
+    if response.status_code != 200:
+        raise Exception(f"Failed to fetch landmark with UUID {landmark_uuid}: {response.status_code}")
+    
+    json_data = response.json()
+    
+    if "detail" in json_data:
+        raise Exception(json_data["detail"])
+    
+    return json_data
+
+
+def load_trip_landmarks(client, first_uuid):
+    """
+    Load all landmarks for a trip using the response from the API.
+
+    Args:
+        first_uuid (str) : The first UUID of the landmark.
+
+    Returns:
+        landmarks (list) : An list containing all landmarks for the trip.
+    """
+    landmarks = []
+    next_uuid = first_uuid
+
+    while next_uuid is not None:
+        landmark_data = fetch_landmark(client, next_uuid)
+        landmarks.append(Landmark(**landmark_data)) # Create Landmark objects
+        next_uuid = landmark_data.get('next_uuid')  # Prepare for the next iteration
+
+    return landmarks
+
+
+
+
+# def test_new_trip_single_prefs(client):
+#     response = client.post(
+#         "/trip/new",
+#         json={
+#             "preferences": {"sightseeing": {"type": "sightseeing", "score": 1}, "nature": {"type": "nature", "score": 1}, "shopping": {"type": "shopping", "score": 1}, "max_time_minute": 360, "detour_tolerance_minute": 0},
+#             "start": [48.8566, 2.3522]
+#             }
+#         )
+#     assert response.status_code == 200
+
+
+# def test_new_trip_matches_prefs(client):
+#     # todo
+#     pass

backend/src/utils/get_time_separation.py

@@ -1,13 +1,14 @@
 import yaml
-from geopy.distance import geodesic
+from math import sin, cos, sqrt, atan2, radians
 
-import constants
+from ..constants import OPTIMIZER_PARAMETERS_PATH
 
-with constants.OPTIMIZER_PARAMETERS_PATH.open('r') as f:
+with OPTIMIZER_PARAMETERS_PATH.open('r') as f:
     parameters = yaml.safe_load(f)
     DETOUR_FACTOR = parameters['detour_factor']
     AVERAGE_WALKING_SPEED = parameters['average_walking_speed']
 
+EARTH_RADIUS_KM = 6373
 
 def get_time(p1: tuple[float, float], p2: tuple[float, float]) -> int:
     """
@@ -16,24 +17,34 @@ def get_time(p1: tuple[float, float], p2: tuple[float, float]) -> int:
     Args:
         p1 (Tuple[float, float]): Coordinates of the starting location.
         p2 (Tuple[float, float]): Coordinates of the destination.
-        detour (float): Detour factor affecting the distance.
-        speed (float): Walking speed in kilometers per hour.
 
-    Returns:
+        Returns:
         int: Time to travel from p1 to p2 in minutes.
     """
 
 
-    # Compute the straight-line distance in km
-    if p1 == p2 :
+    if p1 == p2:
         return 0
-    else: 
-        dist = geodesic(p1, p2).kilometers
+    else:
+        # Compute the distance in km along the surface of the Earth
+        # (assume spherical Earth)
+        # this is the haversine formula, stolen from stackoverflow
+        # in order to not use any external libraries
+        lat1, lon1 = radians(p1[0]), radians(p1[1])
+        lat2, lon2 = radians(p2[0]), radians(p2[1])
 
-    # Consider the detour factor for average cityto deterline walking distance (in km)
-    walk_dist = dist*DETOUR_FACTOR
+        dlon = lon2 - lon1
+        dlat = lat2 - lat1
+
+        a = sin(dlat / 2)**2 + cos(lat1) * cos(lat2) * sin(dlon / 2)**2
+        c = 2 * atan2(sqrt(a), sqrt(1 - a))
+
+        distance = EARTH_RADIUS_KM * c
+
+    # Consider the detour factor for average an average city
+    walk_distance = distance * DETOUR_FACTOR
 
     # Time to walk this distance (in minutes)
-    walk_time = walk_dist/AVERAGE_WALKING_SPEED*60
+    walk_time = walk_distance / AVERAGE_WALKING_SPEED * 60
 
     return round(walk_time)

backend/src/utils/landmarks_manager.py

@@ -1,20 +1,18 @@
-import math as m
+import math
 import yaml
 import logging
 
 from OSMPythonTools.overpass import Overpass, overpassQueryBuilder
 from OSMPythonTools.cachingStrategy import CachingStrategy, JSON
-from pywikibot import ItemPage, Site
-from pywikibot import config
-config.put_throttle = 0
-config.maxlag = 0
 
-from structs.preferences import Preferences, Preference
-from structs.landmark import Landmark
+from ..structs.preferences import Preferences
+from ..structs.landmark import Landmark
 from .take_most_important import take_most_important
-import constants
 
+from ..constants import AMENITY_SELECTORS_PATH, LANDMARK_PARAMETERS_PATH, OPTIMIZER_PARAMETERS_PATH, OSM_CACHE_DIR
 
+# silence the overpass logger
+logging.getLogger('OSMPythonTools').setLevel(level=logging.CRITICAL)
 
 
 class LandmarkManager:
@@ -30,10 +28,10 @@ class LandmarkManager:
 
     def __init__(self) -> None:
 
-        with constants.AMENITY_SELECTORS_PATH.open('r') as f:
+        with AMENITY_SELECTORS_PATH.open('r') as f:
             self.amenity_selectors = yaml.safe_load(f)
 
-        with constants.LANDMARK_PARAMETERS_PATH.open('r') as f:
+        with LANDMARK_PARAMETERS_PATH.open('r') as f:
             parameters = yaml.safe_load(f)
             self.max_bbox_side = parameters['city_bbox_side']
             self.radius_close_to = parameters['radius_close_to']
@@ -42,18 +40,19 @@ 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']
             self.N_important = parameters['N_important']
-            
-        with constants.OPTIMIZER_PARAMETERS_PATH.open('r') as f:
+
+        with OPTIMIZER_PARAMETERS_PATH.open('r') as f:
             parameters = yaml.safe_load(f)
             self.walking_speed = parameters['average_walking_speed']
             self.detour_factor = parameters['detour_factor']
 
         self.overpass = Overpass()
-        CachingStrategy.use(JSON, cacheDir=constants.OSM_CACHE_DIR)
+        CachingStrategy.use(JSON, cacheDir=OSM_CACHE_DIR)
 
 
     def generate_landmarks_list(self, center_coordinates: tuple[float, float], preferences: Preferences) -> tuple[list[Landmark], list[Landmark]]:
@@ -69,87 +68,44 @@ class LandmarkManager:
         preferences (Preferences): The user's preference settings that influence the landmark selection.
 
         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.
+        tuple[list[Landmark], list[Landmark]]:
+        - A list of all existing landmarks.
+        - A list of the most important landmarks based on the user's preferences.
         """
 
         max_walk_dist = (preferences.max_time_minute/2)/60*self.walking_speed*1000/self.detour_factor
         reachable_bbox_side = min(max_walk_dist, self.max_bbox_side)
 
-        L = []
+        # use set to avoid duplicates, this requires some __methods__ to be set in Landmark
+        all_landmarks = set()
+
         bbox = self.create_bbox(center_coordinates, reachable_bbox_side)
         # list for sightseeing
         if preferences.sightseeing.score != 0:
-            score_function = lambda score: int(score*10*preferences.sightseeing.score/5)   # self.count_elements_close_to(loc) +
-            L1 = self.fetch_landmarks(bbox, self.amenity_selectors['sightseeing'], preferences.sightseeing.type, score_function)
-            L += L1
+            score_function = lambda score: score * 10 * preferences.sightseeing.score / 5
+            current_landmarks = self.fetch_landmarks(bbox, self.amenity_selectors['sightseeing'], preferences.sightseeing.type, score_function)
+            all_landmarks.update(current_landmarks)
 
         # list for nature
         if preferences.nature.score != 0:
-            score_function = lambda score: int(score*10*self.nature_coeff*preferences.nature.score/5)   # self.count_elements_close_to(loc) +
-            L2 = self.fetch_landmarks(bbox, self.amenity_selectors['nature'], preferences.nature.type, score_function)
-            L += L2
+            score_function = lambda score: score * 10 * self.nature_coeff * preferences.nature.score / 5
+            current_landmarks = self.fetch_landmarks(bbox, self.amenity_selectors['nature'], preferences.nature.type, score_function)
+            all_landmarks.update(current_landmarks)
 
         # list for shopping
         if preferences.shopping.score != 0:
-            score_function = lambda score: int(score*10*preferences.shopping.score/5)   # self.count_elements_close_to(loc) +
-            L3 = self.fetch_landmarks(bbox, self.amenity_selectors['shopping'], preferences.shopping.type, score_function)
-            L += L3
+            score_function = lambda score: score * 10 * preferences.shopping.score / 5
+            current_landmarks = self.fetch_landmarks(bbox, self.amenity_selectors['shopping'], preferences.shopping.type, score_function)
+            # set time for all shopping activites :
+            for landmark in current_landmarks : landmark.duration = 45
+            all_landmarks.update(current_landmarks)
 
 
-        L = self.remove_duplicates(L)
-        # self.correct_score(L, preferences)
+        landmarks_constrained = take_most_important(all_landmarks, self.N_important)
+        self.logger.info(f'Generated {len(all_landmarks)} landmarks around {center_coordinates}, and constrained to {len(landmarks_constrained)} most important ones.')
 
-        L_constrained = take_most_important(L, self.N_important)
-        self.logger.info(f'Generated {len(L)} landmarks around {center_coordinates}, and constrained to {len(L_constrained)} most important ones.')
+        return all_landmarks, landmarks_constrained
 
-        return L, L_constrained
-
-
-    def remove_duplicates(self, landmarks: list[Landmark]) -> list[Landmark]:
-        """
-        Removes duplicate landmarks based on their names from the given list. Only retains the landmark with highest score
-
-        Parameters:
-        landmarks (list[Landmark]): A list of Landmark objects.
-
-        Returns:
-        list[Landmark]: A list of unique Landmark objects based on their names.
-        """
-
-        L_clean = []
-        names = []
-
-        for landmark in landmarks:
-            if landmark.name in names: 
-                continue  
-            else:
-                names.append(landmark.name)
-                L_clean.append(landmark)
-        
-        return L_clean
-        
-
-    def correct_score(self, landmarks: list[Landmark], preferences: Preferences) -> None:
-        """
-        Adjust the attractiveness score of each landmark in the list based on user preferences.
-
-        This method updates the attractiveness of each landmark by scaling it according to the user's preference score.
-        The score adjustment is computed using a simple linear transformation based on the preference score.
-
-        Args:
-            landmarks (list[Landmark]): A list of landmarks whose scores need to be corrected.
-            preferences (Preferences): The user's preference settings that influence the attractiveness score adjustment.
-        """
-
-        score_dict = {
-            preferences.sightseeing.type: preferences.sightseeing.score,
-            preferences.nature.type: preferences.nature.score,
-            preferences.shopping.type: preferences.shopping.score
-        }
-        for landmark in landmarks:
-            landmark.attractiveness = int(landmark.attractiveness * score_dict[landmark.type] / 5)        
 
 
     def count_elements_close_to(self, coordinates: tuple[float, float]) -> int:
@@ -172,7 +128,7 @@ class LandmarkManager:
 
         radius = self.radius_close_to
 
-        alpha = (180*radius) / (6371000*m.pi)
+        alpha = (180 * radius) / (6371000 * math.pi)
         bbox = {'latLower':lat-alpha,'lonLower':lon-alpha,'latHigher':lat+alpha,'lonHigher': lon+alpha}
 
         # Build the query to find elements within the radius
@@ -216,7 +172,7 @@ class LandmarkManager:
 
         # Convert distance to degrees
         lat_diff = half_side_length_km / 111  # 1 degree latitude is approximately 111 km
-        lon_diff = half_side_length_km / (111 * m.cos(m.radians(lat)))  # Adjust for longitude based on latitude
+        lon_diff = half_side_length_km / (111 * math.cos(math.radians(lat)))  # Adjust for longitude based on latitude
 
         # Calculate bbox
         min_lat = lat - lat_diff
@@ -248,134 +204,149 @@ class LandmarkManager:
         """
         return_list = []
 
+        if landmarktype == 'nature' : query_conditions = []
+        else : query_conditions = ['count_tags()>5']
+
         # caution, when applying a list of selectors, overpass will search for elements that match ALL selectors simultaneously
         # we need to split the selectors into separate queries and merge the results
         for sel in dict_to_selector_list(amenity_selector):
             self.logger.debug(f"Current selector: {sel}")
+
+            query_conditions = ['count_tags()>5']
+            element_types = ['way', 'relation']
+
+            if 'viewpoint' in sel :
+                query_conditions = []
+                element_types.append('node')
+
             query = overpassQueryBuilder(
                 bbox = bbox,
-                elementType = ['way', 'relation'],
+                elementType = element_types,
+                # selector can in principle be a list already,
+                # but it generates the intersection of the queries
+                # we want the union
                 selector = sel,
-                # conditions = [],
+                conditions = query_conditions,        # except for nature....
                 includeCenter = True,
                 out = 'body'
                 )
+            self.logger.debug(f"Query: {query}")
 
             try:
                 result = self.overpass.query(query)
             except Exception as e:
                 self.logger.error(f"Error fetching landmarks: {e}")
-                return
-            
+                continue
+
             for elem in result.elements():
 
-                name = elem.tag('name')                             # Add name
-                location = (elem.centerLat(), elem.centerLon())     # Add coordinates (lat, lon)
+                name = elem.tag('name')
+                location = (elem.centerLat(), elem.centerLon())
+                osm_type = elem.type()              # Add type: 'way' or 'relation'
+                osm_id = elem.id()                  # Add OSM id 
 
                 # TODO: exclude these from the get go
-                # skip if unprecise location
+                # handle unprecise and no-name locations
                 if name is None or location[0] is None:
-                    continue
+                    if osm_type == 'node' and 'viewpoint' in elem.tags().values(): 
+                        name = 'Viewpoint'
+                        name_en = 'Viewpoint'
+                        location = (elem.lat(), elem.lon())
+                    else : 
+                        continue
 
-                # skip if unused
-                # if 'disused:leisure' in elem.tags().keys():
-                #     continue
-                
                 # skip if part of another building
                 if 'building:part' in elem.tags().keys() and elem.tag('building:part') == 'yes':
                     continue
             
-                osm_type = elem.type()              # Add type: 'way' or 'relation'
-                osm_id = elem.id()                  # Add OSM id 
                 elem_type = landmarktype            # Add the landmark type as 'sightseeing, 
                 n_tags = len(elem.tags().keys())    # Add number of tags
                 score = n_tags**self.tag_exponent   # Add score
                 website_url = None
-                wikpedia_url = None
                 image_url = None
                 name_en = None
 
-                # remove specific tags
+                # Adjust scoring, browse through tag keys
                 skip = False
-                for tag in elem.tags().keys():
-                    if "pay" in tag:
-                        score += self.pay_bonus             # discard payment options for tags
+                for tag_key in elem.tags().keys():
+                    if "pay" in tag_key:
+                        # payment options are misleading and should not count for the scoring.
+                        score += self.pay_bonus
 
-                    if "disused" in tag:
-                        skip = True             # skip disused amenities
+                    if "disused" in tag_key:
+                        # skip disused amenities
+                        skip = True
                         break
 
-                    if "wiki" in tag:
-                        score += self.wikipedia_bonus             # wikipedia entries count more
-                        
-                    # if tag == "wikidata":
-                    #     Q = elem.tag('wikidata')
-                    #     site = Site("wikidata", "wikidata")
-                    #     item = ItemPage(site, Q)
-                    #     item.get()
-                    #     n_languages = len(item.labels)
-                    #     n_tags += n_languages/10
+                    if "name" in tag_key :
+                        score += self.name_bonus
 
-                    if "viewpoint" in tag:
-                        score += self.viewpoint_bonus
-                        duration = 10
+                    if "wiki" in tag_key:
+                        # wikipedia entries count more
+                        score += self.wikipedia_bonus
 
-                    if "image" in tag:
+                    if "image" in tag_key:
+                        # images must count more
                         score += self.image_bonus
 
                     if elem_type != "nature":
-                        if "leisure" in tag and elem.tag('leisure') == "park":
+                        if "leisure" in tag_key and elem.tag('leisure') == "park":
                             elem_type = "nature"
 
                     if landmarktype != "shopping":
-                        if "shop" in tag:
+                        if "shop" in tag_key:
                             skip = True
                             break
 
-                        if tag == "building" and elem.tag('building') in ['retail', 'supermarket', 'parking']:
+                        if tag_key == "building" and elem.tag('building') in ['retail', 'supermarket', 'parking']:
                             skip = True
                             break
-                    
-                    # Get additional information
-                    # if tag == 'wikipedia' :
-                    #     wikpedia_url = elem.tag('wikipedia')
-                    if tag in ['website', 'contact:website'] :
-                        website_url = elem.tag(tag)
-                    if tag == 'image' :
+
+                    # Extract image, website and english name
+                    if tag_key in ['website', 'contact:website']:
+                        website_url = elem.tag(tag_key)
+                    if tag_key == 'image':
                         image_url = elem.tag('image')
-                    if tag =='name:en' :
+                    if tag_key =='name:en':
                         name_en = elem.tag('name:en')
 
                 if skip:
                     continue
 
+                # Don't visit random apartments
+                if 'apartments' in elem.tags().values():
+                    continue
+
                 score = score_function(score)
-                if "place_of_worship" in elem.tags().values() :
-                    score = int(score*self.church_coeff)
-                    duration = 15
+                if "place_of_worship" in elem.tags().values():
+                    score = score * self.church_coeff
+                    duration = 10
+
+                if 'viewpoint' in elem.tags().values() :
+                    # viewpoints must count more
+                    score += self.viewpoint_bonus
+                    duration = 10
                 
-                elif "museum" in elem.tags().values() :
-                    score = int(score*self.church_coeff)
+                elif "museum" in elem.tags().values() or "aquarium" in elem.tags().values() or "planetarium" in elem.tags().values():
                     duration = 60
                 
-                else : 
+                else:
                     duration = 5
 
-                # Generate the landmark and append it to the list
+                # finally create our own landmark object
                 landmark = Landmark(
-                    name=name,
-                    type=elem_type,
-                    location=location,
-                    osm_type=osm_type,
-                    osm_id=osm_id,
-                    attractiveness=score,
-                    must_do=False,
-                    n_tags=int(n_tags),
-                    duration = duration, 
-                    name_en=name_en,
-                    image_url=image_url,
-                    # wikipedia_url=wikpedia_url,
-                    website_url=website_url
+                    name = name,
+                    type = elem_type,
+                    location = location,
+                    osm_type = osm_type,
+                    osm_id = osm_id,
+                    attractiveness = int(score),
+                    must_do = False,
+                    n_tags = int(n_tags),
+                    duration = int(duration),
+                    name_en = name_en,
+                    image_url = image_url,
+                    website_url = website_url
                 )
                 return_list.append(landmark)
         
@@ -399,7 +370,7 @@ def dict_to_selector_list(d: dict) -> list:
     for key, value in d.items():
         if type(value) == list:
             val = '|'.join(value)
-            return_list.append(f'{key}~"{val}"')
+            return_list.append(f'{key}~"^({val})$"')
         elif type(value) == str and len(value) == 0:
             return_list.append(f'{key}')
         else:

backend/src/utils/optimizer.py

@@ -3,11 +3,10 @@ import numpy as np
 
 from scipy.optimize import linprog
 from collections import defaultdict, deque
-from geopy.distance import geodesic
 
-from structs.landmark import Landmark
+from ..structs.landmark import Landmark
 from .get_time_separation import get_time
-import constants
+from ..constants import OPTIMIZER_PARAMETERS_PATH
 
     
 
@@ -27,7 +26,7 @@ class Optimizer:
     def __init__(self) :
 
         # load parameters from file
-        with constants.OPTIMIZER_PARAMETERS_PATH.open('r') as f:
+        with OPTIMIZER_PARAMETERS_PATH.open('r') as f:
             parameters = yaml.safe_load(f)
             self.detour_factor = parameters['detour_factor']
             self.average_walking_speed = parameters['average_walking_speed']
@@ -488,7 +487,7 @@ class Optimizer:
 
         # Raise error if no solution is found
         if not res.success :
-            raise ArithmeticError("No solution could be found, the problem is overconstrained. Please adapt your must_dos")
+            raise ArithmeticError("No solution could be found, the problem is overconstrained. Try with a longer trip (>30 minutes).")
 
         # If there is a solution, we're good to go, just check for connectiveness
         order, circles = self.is_connected(res.x)

backend/src/utils/refiner.py

@@ -2,11 +2,12 @@ import yaml, logging
 
 from shapely import buffer, LineString, Point, Polygon, MultiPoint, concave_hull
 from math import pi
+from typing import List
 
-from structs.landmark import Landmark
+from ..structs.landmark import Landmark
 from . import take_most_important, get_time_separation
 from .optimizer import Optimizer
-import constants
+from ..constants import OPTIMIZER_PARAMETERS_PATH
 
 
 
@@ -24,7 +25,7 @@ class Refiner :
         self.optimizer = optimizer
 
         # load parameters from file
-        with constants.OPTIMIZER_PARAMETERS_PATH.open('r') as f:
+        with OPTIMIZER_PARAMETERS_PATH.open('r') as f:
             parameters = yaml.safe_load(f)
             self.detour_factor = parameters['detour_factor']
             self.detour_corridor_width = parameters['detour_corridor_width']
@@ -133,6 +134,21 @@ class Refiner :
             i += 1
     
         return tour
+    
+    def integrate_landmarks(self, sub_list: List[Landmark], main_list: List[Landmark]) :
+        """
+        Inserts 'sub_list' of Landmarks inside the 'main_list' by leaving the ends untouched.
+        
+        Args: 
+            sub_list    : the list of Landmarks to be inserted inside of the 'main_list'.
+            main_list   : the original list with start and finish.
+
+        Returns:
+            the full list.
+        """
+        sub_list.append(main_list[-1])          # add finish back
+        return main_list[:-1] + sub_list        # create full set of possible landmarks
+
 
 
     def find_shortest_path_through_all_landmarks(self, landmarks: list[Landmark]) -> tuple[list[Landmark], Polygon]:
@@ -253,6 +269,11 @@ class Refiner :
         except :
             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 : 
+                Exception has occurred: AttributeError
+                'LineString' object has no attribute 'exterior'
+            """
 
 
         # reverse the xs and ys
@@ -315,26 +336,30 @@ class Refiner :
 
         self.logger.info(f"Using {len(minor_landmarks)} minor landmarks around the predicted path")
 
-        # full set of visitable landmarks
-        full_set = base_tour[:-1] + minor_landmarks   # create full set of possible landmarks (without finish)
-        full_set.append(base_tour[-1])                # add finish back
+        # Full set of visitable landmarks.
+        full_set = self.integrate_landmarks(minor_landmarks, base_tour)     # could probably be optimized with less overhead
 
-        # get a new tour
+        # Generate a new tour with the optimizer.
         new_tour = self.optimizer.solve_optimization(
             max_time = max_time + detour,
             landmarks = full_set, 
             max_landmarks = self.max_landmarks_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.")
             new_tour = base_tour
 
+        # If only one landmark, return it.
+        if len(new_tour) < 4 :
+            return new_tour
 
-        # Find shortest path using the nearest neighbor heuristic
+        # Find shortest path using the nearest neighbor heuristic.
         better_tour, better_poly = self.find_shortest_path_through_all_landmarks(new_tour)
 
-        # Fix the tour using Polygons if the path looks weird
+        # 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 :
             better_tour = self.fix_using_polygon(better_tour)
 

backend/src/utils/take_most_important.py

@@ -1,38 +1,16 @@
-from structs.landmark import Landmark
+from ..structs.landmark import Landmark
 
-def take_most_important(landmarks: list[Landmark], N_important) -> list[Landmark] :
-    L = len(landmarks)
-    L_copy = []
-    L_clean = []
-    scores = [0]*len(landmarks)
-    names = []
-    name_id = {}
+def take_most_important(landmarks: list[Landmark], n_important) -> list[Landmark]:
+    """
+    Given a list of landmarks, return the n_important most important landmarks
+    Parameters:
+    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
+    """
 
-    for i, elem in enumerate(landmarks) :
-        if elem.name not in names :
-            names.append(elem.name)
-            name_id[elem.name] = [i]
-            L_copy.append(elem)
-        else :
-            name_id[elem.name] += [i]
-            scores = []
-            for j in name_id[elem.name] :
-                scores.append(L[j].attractiveness)
-            best_id = max(range(len(scores)), key=scores.__getitem__)
-            t = name_id[elem.name][best_id]
-            if t == i :
-                for old in L_copy :
-                    if old.name == elem.name :
-                        old.attractiveness = L[t].attractiveness
-    
-    scores = [0]*len(L_copy)
-    for i, elem in enumerate(L_copy) :
-        scores[i] = elem.attractiveness
+    # Sort landmarks by attractiveness (descending)
+    sorted_landmarks = sorted(landmarks, key=lambda x: x.attractiveness, reverse=True)
 
-    res = sorted(range(len(scores)), key = lambda sub: scores[sub])[-(N_important-L):]
-
-    for i, elem in enumerate(L_copy) :
-        if i in res :
-            L_clean.append(elem)
-
-    return L_clean
+    return sorted_landmarks[:n_important]

frontend/.github/workflows/build_app_android.yaml

@@ -37,14 +37,13 @@ jobs:
           REF_NAME: ${{ github.ref_name }}
         run:
           # remove the 'v' prefix from the tag name
-          echo "VERSION_NAME=${REF_NAME//v}" >> $GITHUB_ENV
+          echo "BUILD_NAME=${REF_NAME//v}" >> $GITHUB_ENV
 
       - name: Load secrets from github
         run: |
-          echo "${{ secrets.ANDROID_SECRET_PROPERTIES }}" > secrets.properties
-          echo "${{ secrets.ANDROID_GOOGLE_PLAY_JSON }}" > google-key.json
-          # decode the base64 encoded google key
-          echo "${{ secrets.ANDROID_KEYSTORE_BASE64 }}" | base64 -d - > release.keystore
+          echo "${{ secrets.ANDROID_SECRET_PROPERTIES_BASE64 }}" | base64 -d > secrets.properties
+          echo "${{ secrets.ANDROID_GOOGLE_PLAY_JSON_BASE64 }}" | base64 -d > google-key.json
+          echo "${{ secrets.ANDROID_KEYSTORE_BASE64 }}" | base64 -d > release.keystore
         working-directory: android
 
       - name: Install fastlane
@@ -54,4 +53,6 @@ jobs:
       - name: Run fastlane lane
         run: bundle exec fastlane deploy_testing
         working-directory: android
-        # the environment variable VERSION_NAME is implicitly available
+        env:
+          BUILD_NUMBER: ${{ github.run_number }}
+          # BUILD_NAME is implicitly available

frontend/android/app/build.gradle

@@ -30,14 +30,19 @@ if (flutterVersionName == null) {
 
 
 def secretPropertiesFile = rootProject.file('secrets.properties')
+def fallbackPropertiesFile = rootProject.file('fallback.properties')
 def secretProperties = new Properties()
 
 if (secretPropertiesFile.exists()) {
     secretPropertiesFile.withReader('UTF-8') { reader ->
         secretProperties.load(reader)
     }
+} else if (fallbackPropertiesFile.exists()) {
+    fallbackPropertiesFile.withReader('UTF-8') { reader ->
+        secretProperties.load(reader)
+    }
 } else {
-    throw new GradleException("Secrets file secrets.properties not found")
+    throw new GradleException("Secrets file (secrets.properties, fallback.properties) not found")
 }
 
 

frontend/android/fallback.properties

@@ -1 +1,3 @@
+# This file mirrors the state of secrets.properties as a reference for the developer.
+# And as a fallback for build.gradle
 MAPS_API_KEY=Key

frontend/android/fastlane/Fastfile

@@ -5,22 +5,28 @@ default_platform(:android)
 
 platform :android do
 
-  desc "Deploy a new version as a preview version"
+  desc "Deploy a new version to closed testing"
   lane :deploy_testing do
-    version_name = ENV["VERSION_NAME"]
+    build_name = ENV["BUILD_NAME"]
+    build_number = ENV["BUILD_NUMBER"]
 
     sh(
       "flutter",
       "build",
       "appbundle",
       "--release",
-      "--build-name=#{version_name}",
+      "--build-name=#{build_name}",
+      "--build-number=#{build_number}",
       )
     
     upload_to_play_store(
       track: 'alpha',
       skip_upload_apk: true,
       skip_upload_changelogs: true,
+      aab: "../build/app/outputs/bundle/release/app-release.aab",
+      # this is the default output of flutter build ... --release
+      # in particular this the build folder lies in the flutter root folder
+      # this is the parent folder for the android folder
       )
   end
 
@@ -28,6 +34,7 @@ platform :android do
   lane :deploy_release do
     gradle(
       task: "clean assembleRelease",
+      # todo update to a flutter call
       properties: {
         # loaded from environment
         "android.injected.version.name" => ENV["VERSION_NAME"],
@@ -37,6 +44,10 @@ platform :android do
       track: "production",
       skip_upload_apk: true,
       skip_upload_changelogs: true,
+      aab: "../build/app/outputs/bundle/release/app-release.aab",
+      # this is the default output of flutter build ... --release
+      # in particular this the build folder lies in the flutter root folder
+      # this is the parent folder for the android folder
     )
   end
 end

frontend/lib/constants.dart

@@ -3,6 +3,7 @@ import 'package:flutter/material.dart';
 const String APP_NAME = 'AnyWay';
 
 String API_URL_BASE = 'https://anyway.anydev.info';
+String API_URL_DEBUG = 'https://anyway.anydev.info';
 String PRIVACY_URL = 'https://anydev.info/privacy';
 
 const String MAP_ID = '41c21ac9b81dbfd8';

frontend/lib/modules/current_trip_error_message.dart

@@ -0,0 +1,37 @@
+import 'package:anyway/structs/trip.dart';
+import 'package:auto_size_text/auto_size_text.dart';
+import 'package:flutter/material.dart';
+
+class CurrentTripErrorMessage extends StatefulWidget {
+  final Trip trip;
+  const CurrentTripErrorMessage({
+    super.key,
+    required this.trip,
+  });
+
+  @override
+  State<CurrentTripErrorMessage> createState() => _CurrentTripErrorMessageState();
+}
+
+class _CurrentTripErrorMessageState extends State<CurrentTripErrorMessage> {
+  @override
+  Widget build(BuildContext context) => Center(
+    child: Row(
+      mainAxisAlignment: MainAxisAlignment.center,
+      children: [
+        const Icon(
+          Icons.error_outline,
+          color: Colors.red,
+          size: 50,
+        ),
+        const Padding(
+          padding: EdgeInsets.only(left: 10),
+        ),
+        AutoSizeText(
+          'Error: ${widget.trip.errorDescription}',
+          maxLines: 3,
+        ),
+      ],
+    )
+  );
+}

frontend/lib/modules/current_trip_greeter.dart

@@ -1,111 +1,50 @@
-import 'dart:developer';
-
-import 'package:anyway/constants.dart';
-import 'package:anyway/structs/trip.dart';
+import 'package:flutter/material.dart';
 import 'package:auto_size_text/auto_size_text.dart';
 
-import 'package:flutter/material.dart';
+import 'package:anyway/pages/current_trip.dart';
+import 'package:anyway/structs/trip.dart';
 
-class Greeter extends StatefulWidget {
+
+class CurrentTripGreeter extends StatefulWidget {
   final Trip trip;
 
-  Greeter({
+  CurrentTripGreeter({
+    super.key,
     required this.trip,
   });
 
   @override
-  State<Greeter> createState() => _GreeterState();
+  State<CurrentTripGreeter> createState() => _CurrentTripGreeterState();
 }
 
 
-class _GreeterState extends State<Greeter> {
-  
-  Widget greeterBuilder (BuildContext context, Widget? child) {
-    final Shader textGradient = APP_GRADIENT.createShader(Rect.fromLTWH(0.0, 0.0, 200.0, 70.0));
-    TextStyle greeterStyle = TextStyle(
-      foreground: Paint()..shader = textGradient,
-      fontWeight: FontWeight.bold,
-      fontSize: 26
-    );
-
-    Widget topGreeter;
-
-    if (widget.trip.uuid != 'pending') {
-      topGreeter = FutureBuilder(
-        future: widget.trip.cityName,
-        builder: (BuildContext context, AsyncSnapshot<String> snapshot) {
-          if (snapshot.hasData) {
-            return AutoSizeText(
-              maxLines: 1,
-              'Welcome to ${snapshot.data}!',
-              style: greeterStyle
-            );
-          } else if (snapshot.hasError) {
-            log('Error while fetching city name');
-            return AutoSizeText(
-              maxLines: 1,
-              'Welcome to your trip!',
-              style: greeterStyle
-            );
-          } else {
-            return AutoSizeText(
-              maxLines: 1,
-              'Welcome to ...',
-              style: greeterStyle
-            );
-          }
-        }
-      );
-    } else {
-      // still awaiting the trip
-      // We can hopefully infer the city name from the cityName future
-      // Show a linear loader at the bottom and an info message above
-      topGreeter = Column(
-        mainAxisAlignment: MainAxisAlignment.end,
-        children: [
-          FutureBuilder(
-            future: widget.trip.cityName,
-            builder: (BuildContext context, AsyncSnapshot<String> snapshot) {
-              if (snapshot.hasData) {
-                return AutoSizeText(
-                  maxLines: 1,
-                  'Generating your trip to ${snapshot.data}...',
-                  style: greeterStyle
-                );
-              } else if (snapshot.hasError) {
-                // the exact error is shown in the central part of the trip overview. No need to show it here
-                return AutoSizeText(
-                  maxLines: 1,
-                  'Error while loading trip.',
-                  style: greeterStyle
-                  );
-              }
-              return AutoSizeText(
-                  maxLines: 1,
-                  'Generating your trip...',
-                  style: greeterStyle
-                  );
-            }
-          ),
-          Padding(
-            padding: EdgeInsets.all(5),
-            child: const LinearProgressIndicator()
-          )
-        ]
-      );
-    }
-
-    return Center(
-      child: topGreeter,
-    );
-  }
-
-
+class _CurrentTripGreeterState extends State<CurrentTripGreeter> {
   @override
-  Widget build(BuildContext context) {
-    return ListenableBuilder(
-      listenable: widget.trip,
-      builder: greeterBuilder,
-    );
-  }
+  Widget build(BuildContext context) => Center(
+    child: FutureBuilder(
+      future: widget.trip.cityName,
+      builder: (BuildContext context, AsyncSnapshot<String> snapshot) {
+        if (snapshot.hasData) {
+          return AutoSizeText(
+            maxLines: 1,
+            'Welcome to ${snapshot.data}!',
+            style: greeterStyle
+          );
+        } else if (snapshot.hasError) {
+          return AutoSizeText(
+            maxLines: 1,
+            'Welcome to your trip!',
+            style: greeterStyle
+          );
+        } else {
+          return AutoSizeText(
+            maxLines: 1,
+            'Welcome to ...',
+            style: greeterStyle
+          );
+        }
+      }
+    )
+  );
+
 }

frontend/lib/modules/current_trip_loading_indicator.dart

@@ -0,0 +1,60 @@
+import 'package:flutter/material.dart';
+import 'package:auto_size_text/auto_size_text.dart';
+
+import 'package:anyway/structs/trip.dart';
+import 'package:anyway/pages/current_trip.dart';
+
+class CurrentTripLoadingIndicator extends StatefulWidget {
+  final Trip trip;
+  const CurrentTripLoadingIndicator({
+    super.key,
+    required this.trip,
+  });
+
+  @override
+  State<CurrentTripLoadingIndicator> createState() => _CurrentTripLoadingIndicatorState();
+}
+
+class _CurrentTripLoadingIndicatorState extends State<CurrentTripLoadingIndicator> {
+  @override
+  Widget build(BuildContext context) => Center(
+    child: FutureBuilder(
+      future: widget.trip.cityName,
+      builder: (BuildContext context, AsyncSnapshot<String> snapshot) {
+        Widget greeter;
+        Widget loadingIndicator = const Padding(
+          padding: EdgeInsets.only(top: 10),
+          child: CircularProgressIndicator()
+        );
+
+        if (snapshot.hasData) {
+          greeter = AutoSizeText(
+            maxLines: 1,
+            'Generating your trip to ${snapshot.data}...',
+            style: greeterStyle,
+          );
+        } else if (snapshot.hasError) {
+          // the exact error is shown in the central part of the trip overview. No need to show it here
+          greeter = AutoSizeText(
+            maxLines: 1,
+            'Error while loading trip.',
+            style: greeterStyle,
+            );
+        } else {
+          greeter = AutoSizeText(
+            maxLines: 1,
+            'Generating your trip...',
+            style: greeterStyle,
+            );
+        }
+        return Column(
+          mainAxisAlignment: MainAxisAlignment.center,
+          children: [
+            greeter,
+            loadingIndicator,
+          ],
+        );
+      }
+    )
+  );
+}

frontend/lib/modules/current_trip_panel.dart

@@ -1,4 +1,6 @@
 import 'package:anyway/constants.dart';
+import 'package:anyway/modules/current_trip_error_message.dart';
+import 'package:anyway/modules/current_trip_loading_indicator.dart';
 import 'package:flutter/material.dart';
 
 import 'package:anyway/structs/trip.dart';
@@ -28,16 +30,36 @@ class _CurrentTripPanelState extends State<CurrentTripPanel> {
     return ListenableBuilder(
       listenable: widget.trip,
       builder: (context, child) {
-        if (widget.trip.uuid != 'pending' && widget.trip.uuid != 'error') {
+        if (widget.trip.uuid == 'error') {
+          return Align(
+              alignment: Alignment.topCenter,
+              child: SizedBox(
+                // reuse the exact same height as the panel has when collapsed
+                // this way the greeter will be centered when the panel is collapsed
+                height: MediaQuery.of(context).size.height * TRIP_PANEL_MIN_HEIGHT - 20,
+                child: CurrentTripErrorMessage(trip: widget.trip)
+              ),
+            );
+        } else if (widget.trip.uuid == 'pending') {
+            return Align(
+              alignment: Alignment.topCenter,
+              child: SizedBox(
+                // reuse the exact same height as the panel has when collapsed
+                // this way the greeter will be centered when the panel is collapsed
+                height: MediaQuery.of(context).size.height * TRIP_PANEL_MIN_HEIGHT - 20,
+                child: CurrentTripLoadingIndicator(trip: widget.trip),
+              ),
+            );
+        } else {
           return ListView(
             controller: widget.controller,
-            padding: const EdgeInsets.only(bottom: 30, left: 5, right: 5),
+            padding: const EdgeInsets.only(bottom: 30),
             children: [
               SizedBox(
                 // reuse the exact same height as the panel has when collapsed
                 // this way the greeter will be centered when the panel is collapsed
                 height: MediaQuery.of(context).size.height * TRIP_PANEL_MIN_HEIGHT - 20,
-                child: Greeter(trip: widget.trip),
+                child: CurrentTripGreeter(trip: widget.trip),
               ),
 
               const Padding(padding: EdgeInsets.only(top: 10)),
@@ -53,28 +75,6 @@ class _CurrentTripPanelState extends State<CurrentTripPanel> {
               Center(child: saveButton(widget.trip)),
             ],
           );
-        } else if(widget.trip.uuid == 'pending') {
-          return SizedBox(
-            // reuse the exact same height as the panel has when collapsed
-            // this way the greeter will be centered when the panel is collapsed
-            height: MediaQuery.of(context).size.height * TRIP_PANEL_MIN_HEIGHT - 20,
-            child: Greeter(trip: widget.trip)
-          );
-        } else {
-          return Row(
-            mainAxisAlignment: MainAxisAlignment.center,
-            children: [
-              const Icon(
-                Icons.error_outline,
-                color: Colors.red,
-                size: 50,
-              ),
-              Padding(
-                padding: const EdgeInsets.only(left: 10),
-                child: Text('Error: ${widget.trip.errorDescription}'),
-              ),
-            ],
-          );
         }
       }
     );

frontend/lib/modules/new_trip_button.dart

@@ -34,7 +34,7 @@ class _NewTripButtonState extends State<NewTripButton> {
         }
         return FloatingActionButton.extended(
           onPressed: onPressed,
-          icon: const Icon(Icons.add),
+          icon: const Icon(Icons.directions),
           label: AutoSizeText('Start planning!'),
         ); 
       }

frontend/lib/pages/current_trip.dart

@@ -6,6 +6,12 @@ import 'package:anyway/structs/trip.dart';
 import 'package:anyway/modules/current_trip_map.dart';
 import 'package:anyway/modules/current_trip_panel.dart';
 
+final Shader textGradient = APP_GRADIENT.createShader(Rect.fromLTWH(0.0, 0.0, 200.0, 70.0));
+TextStyle greeterStyle = TextStyle(
+  foreground: Paint()..shader = textGradient,
+  fontWeight: FontWeight.bold,
+  fontSize: 26
+);
 
 
 class TripPage extends StatefulWidget {
@@ -35,7 +41,7 @@ class _TripPageState extends State<TripPage> {
         maxHeight: MediaQuery.of(context).size.height * TRIP_PANEL_MAX_HEIGHT,
         // padding in this context is annoying: it offsets the notion of vertical alignment.
         // children that want to be centered vertically need to have their size adjusted by 2x the padding
-        padding: const EdgeInsets.only(top: 10),
+        padding: const EdgeInsets.all(10.0),
         // Panel snapping should not be disabled because it significantly improves the user experience
         // panelSnapping: false
         borderRadius: const BorderRadius.only(topLeft: Radius.circular(25), topRight: Radius.circular(25)),

frontend/lib/pages/new_trip_preferences.dart

@@ -63,7 +63,7 @@ class _NewTripPreferencesPageState extends State<NewTripPreferencesPage> {
       margin: const EdgeInsets.only(left: 10, right: 10, top: 10, bottom: 0),
       shadowColor: Colors.grey,
       child: ListTile(
-        leading: Icon(Icons.timer),
+        leading: preferences.maxTime.icon,
         title: Text(preferences.maxTime.description),
         subtitle: CupertinoTimerPicker(
           mode: CupertinoTimerPickerMode.hm,

frontend/lib/pages/settings.dart

@@ -61,9 +61,7 @@ class _SettingsPageState extends State<SettingsPage> {
                     return AlertDialog(
                       title: Text('Debug mode - use a custom API endpoint'),
                       content: TextField(
-                        decoration: InputDecoration(
-                          hintText: 'https://anyway-stg.anydev.info'
-                        ),
+                        controller: TextEditingController(text: API_URL_DEBUG),
                         onChanged: (value) {
                           setState(() {
                             API_URL_BASE = value;

frontend/lib/utils/fetch_trip.dart

@@ -38,10 +38,18 @@ fetchTrip(
   String dataString = jsonEncode(data);
   log(dataString);
 
-  final response = await dio.post(
-    "/trip/new",
-    data: data
-  );
+  late Response response;
+  try {
+     response = await dio.post(
+      "/trip/new",
+      data: data
+    );
+  } catch (e) {
+    trip.updateUUID("error");
+    trip.updateError(e.toString());
+    log(e.toString());
+    return;
+  }
 
   // handle errors
   if (response.statusCode != 200) {