Implement backend API for landmarks, trip optimization, and toilet locations
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- Added landmarks_router.py to handle landmark retrieval based on user preferences and location.
- Implemented optimization_router.py for trip optimization, including handling preferences and landmarks.
- Created toilets_router.py to fetch toilet locations within a specified radius from a given location.
- Enhanced error handling and logging across all new endpoints.
- Generated a comprehensive report.html for test results and environment details.
This commit is contained in:
2025-07-13 17:43:24 +02:00
parent 54bc9028ad
commit b0f9d31ee2
15 changed files with 1235 additions and 217 deletions

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"""Main app for backend api"""
import logging
import time
import random
from fastapi import HTTPException, APIRouter
from ..structs.landmark import Landmark
from ..structs.preferences import Preferences, Preference
from .landmarks_manager import LandmarkManager
# Setup the logger and the Landmarks Manager
logger = logging.getLogger(__name__)
manager = LandmarkManager()
# Initialize the API router
router = APIRouter()
@router.post("/get/landmarks")
def get_landmarks(
preferences: Preferences,
start: tuple[float, float],
) -> list[Landmark]:
"""
Function that returns all available landmarks given some preferences and a start position.
Args:
preferences : the preferences specified by the user as the post body
start : the coordinates of the starting point
Returns:
list[Landmark] : The full list of fetched landmarks
"""
if preferences is None:
raise HTTPException(status_code=406, detail="Preferences not provided or incomplete.")
if (preferences.shopping.score == 0 and
preferences.sightseeing.score == 0 and
preferences.nature.score == 0) :
raise HTTPException(status_code=406, detail="All preferences are 0.")
if start is None:
raise HTTPException(status_code=406, detail="Start coordinates not provided")
if not (-90 <= start[0] <= 90 or -180 <= start[1] <= 180):
raise HTTPException(status_code=422, detail="Start coordinates not in range")
logger.info(f"Requested new trip generation. Details:\n\tCoordinates: {start}\n\tTime: {preferences.max_time_minute}\n\tSightseeing: {preferences.sightseeing.score}\n\tNature: {preferences.nature.score}\n\tShopping: {preferences.shopping.score}")
start_time = time.time()
# Generate the landmarks from the start location
landmarks = manager.generate_landmarks_list(
center_coordinates = start,
preferences = preferences
)
if len(landmarks) == 0 :
raise HTTPException(status_code=500, detail="No landmarks were found.")
t_generate_landmarks = time.time() - start_time
logger.info(f'Fetched {len(landmarks)} landmarks in \t: {round(t_generate_landmarks,3)} seconds')
return landmarks
@router.post("/get-nearby/landmarks/{lat}/{lon}")
def get_landmarks_nearby(
lat: float,
lon: float
) -> list[Landmark] :
"""
Suggests nearby landmarks based on a given latitude and longitude.
This endpoint returns a curated list of up to 5 landmarks around the given geographical coordinates. It uses fixed preferences for
sightseeing, shopping, and nature, with a maximum time constraint of 30 minutes to limit the number of landmarks returned.
Args:
lat (float): Latitude of the user's current location.
lon (float): Longitude of the user's current location.
Returns:
list[Landmark]: A list of selected nearby landmarks.
"""
logger.info(f'Fetching landmarks nearby ({lat}, {lon}).')
# Define fixed preferences:
prefs = Preferences(
sightseeing = Preference(
type='sightseeing',
score=5
),
shopping = Preference(
type='shopping',
score=2
),
nature = Preference(
type='nature',
score=5
),
max_time_minute=30,
detour_tolerance_minute=0,
)
# Find the landmarks around the location
landmarks_around = manager.generate_landmarks_list(
center_coordinates = (lat, lon),
preferences = prefs,
allow_clusters=False,
)
if len(landmarks_around) == 0 :
raise HTTPException(status_code=500, detail="No landmarks were found.")
# select 8 - 12 landmarks from there
if len(landmarks_around) > 8 :
n_imp = random.randint(2,5)
rest = random.randint(8 - n_imp, min(12, len(landmarks_around))-n_imp)
print(f'len = {len(landmarks_around)}\nn_imp = {n_imp}\nrest = {rest}')
landmarks_around = landmarks_around[:n_imp] + random.sample(landmarks_around[n_imp:], rest)
logger.info(f'Found {len(landmarks_around)} landmarks to suggest nearby ({lat}, {lon}).')
# logger.debug('Suggested landmarks :\n\t' + '\n\t'.join(f'{landmark}' for landmark in landmarks_around))
return landmarks_around