.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

.vscode/launch.json

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

backend/.pylintrc

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

backend/Pipfile

@@ -4,6 +4,11 @@ verify_ssl = true
 name = "pypi"
 
 [dev-packages]
+pylint = "*"
+pytest = "*"
+tomli = "*"
+httpx = "*"
+exceptiongroup = "*"
 
 [packages]
 numpy = "*"

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__)

backend/src/parameters/landmark_parameters.yaml

@@ -1,11 +1,12 @@
 city_bbox_side: 7500 #m
 radius_close_to: 50
-church_coeff: 0.5
+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/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/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=15,
+        shopping=Preference(type='shopping', score = 0),
+        max_time_minute=30,
         detour_tolerance_minute=0
     )
 
@@ -74,7 +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((45.758217, 4.831814)))         # Lyon Bellecour
 # test(tuple((48.5848435, 7.7332974)))       # Strasbourg Gare
 # test(tuple((48.2067858, 16.3692340)))      # Vienne
-test(tuple((48.084588, 7.280405)))         # Turckheim 
+# 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

@@ -1,9 +1,9 @@
 import yaml
 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']

backend/src/utils/landmarks_manager.py

@@ -5,10 +5,11 @@ import logging
 from OSMPythonTools.overpass import Overpass, overpassQueryBuilder
 from OSMPythonTools.cachingStrategy import CachingStrategy, JSON
 
-from structs.preferences import Preferences
-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)
@@ -27,10 +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']
@@ -39,18 +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]]:
@@ -202,18 +204,29 @@ 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 = ['count_tags()>5'],
+                conditions = query_conditions,        # except for nature....
                 includeCenter = True,
                 out = 'body'
                 )
@@ -229,18 +242,23 @@ class LandmarkManager:
 
                 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:
+                    if osm_type == 'node' and 'viewpoint' in elem.tags().values(): 
+                        name = 'Viewpoint'
+                        name_en = 'Viewpoint'
+                        location = (elem.lat(), elem.lon())
+                    else : 
                         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
@@ -248,60 +266,67 @@ class LandmarkManager:
                 image_url = None
                 name_en = None
 
-                # Adjust scoring
+                # Adjust scoring, browse through tag keys
                 skip = False
-                for tag in elem.tags().keys():
-                    if "pay" in tag:
+                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:
+                    if "disused" in tag_key:
                         # skip disused amenities
                         skip = True
                         break
 
-                    if "wiki" in tag:
+                    if "name" in tag_key :
+                        score += self.name_bonus
+
+                    if "wiki" in tag_key:
                         # wikipedia entries count more
                         score += self.wikipedia_bonus
 
-                    if "viewpoint" in tag:
-                        # viewpoints must count more
-                        score += self.viewpoint_bonus
-                        duration = 10
-
-                    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
 
                     # Extract image, website and english name
-                    if tag in ['website', 'contact:website']:
-                        website_url = elem.tag(tag)
-                    if tag == 'image':
+                    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 = 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() or "aquarium" in elem.tags().values() or "planetarium" in elem.tags().values():
                     duration = 60
                 

backend/src/utils/optimizer.py

@@ -4,9 +4,9 @@ import numpy as np
 from scipy.optimize import linprog
 from collections import defaultdict, deque
 
-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
 
     
 
@@ -26,7 +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']

backend/src/utils/refiner.py

@@ -4,10 +4,10 @@ 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
 
 
 
@@ -25,7 +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']

backend/src/utils/take_most_important.py

@@ -1,4 +1,4 @@
-from structs.landmark import Landmark
+from ..structs.landmark import Landmark
 
 def take_most_important(landmarks: list[Landmark], n_important) -> list[Landmark]:
     """