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

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Reviewed-on: #38
This commit is contained in:
Helldragon67 2024-11-18 16:09:19 +00:00
commit 881f6a901d
20 changed files with 907 additions and 517 deletions
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34
.gitea/workflows/backend_run_lint.yaml Normal file
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@ -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

33
.gitea/workflows/backend_run_test.yaml Normal file
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@ -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

6
.vscode/launch.json vendored
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@ -14,9 +14,9 @@
"DEBUG": "true"
},
"args": [
"--app-dir",
"src",
"main:app",
// "--app-dir",
// "src",
"src.main:app",
"--reload",
],
"jinja": true,

2
backend/.pylintrc Normal file
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@ -0,0 +1,2 @@
[MAIN]
max-line-length=240

5
backend/Pipfile
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@ -4,6 +4,11 @@ verify_ssl = true
name = "pypi"
[dev-packages]
pylint = "*"
pytest = "*"
tomli = "*"
httpx = "*"
exceptiongroup = "*"
[packages]
numpy = "*"

1038
backend/Pipfile.lock generated
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0
backend/src/__init__.py Normal file
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16
backend/src/main.py
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@ -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__)

5
backend/src/parameters/landmark_parameters.yaml
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@ -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

2
backend/src/parameters/optimizer_parameters.yaml
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@ -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

14
backend/src/persistence.py
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@ -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,
timeout = 1,
allow_unicode_keys = True,
encoding = 'utf-8',
serde = serde.pickle_serde
MEMCACHED_HOST_PATH,
timeout=1,
allow_unicode_keys=True,
encoding='utf-8'
)

3
backend/src/structs/linked_landmarks.py
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@ -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

20
backend/src/tester.py
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@ -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

0
backend/src/tests/__init__.py Normal file
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141
backend/src/tests/test_main.py Normal file
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@ -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

4
backend/src/utils/get_time_separation.py
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@ -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']

87
backend/src/utils/landmarks_manager.py
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@ -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:
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 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
@ -248,59 +266,66 @@ 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

6
backend/src/utils/optimizer.py
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@ -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']

6
backend/src/utils/refiner.py
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@ -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']

2
backend/src/utils/take_most_important.py
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@ -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]:
"""