anyway/backend/src/main.py
kscheidecker 6921ab57f8
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added more structure
2025-06-21 18:54:42 +02:00

270 lines
10 KiB
Python

"""Main app for backend api"""
import logging
import time
import random
from contextlib import asynccontextmanager
from fastapi import FastAPI, HTTPException, BackgroundTasks
from .logging_config import configure_logging
from .structs.landmark import Landmark
from .structs.preferences import Preferences, Preference
from .structs.linked_landmarks import LinkedLandmarks
from .structs.trip import Trip
from .landmarks.landmarks_manager import LandmarkManager
from .toilets.toilet_routes import router as toilets_router
from .optimization.optimizer import Optimizer
from .optimization.refiner import Refiner
from .overpass.overpass import fill_cache
from .cache import client as cache_client
logger = logging.getLogger(__name__)
manager = LandmarkManager()
optimizer = Optimizer()
refiner = Refiner(optimizer=optimizer)
@asynccontextmanager
async def lifespan(app: FastAPI):
"""Function to run at the start of the app"""
logger.info("Setting up logging")
configure_logging()
yield
logger.info("Shutting down logging")
app = FastAPI(lifespan=lifespan)
app.include_router(toilets_router)
@app.post("/trip/new")
def new_trip(preferences: Preferences,
start: tuple[float, float],
end: tuple[float, float] | None = None,
background_tasks: BackgroundTasks = None) -> Trip:
"""
Main function to call the optimizer.
Args:
preferences : the preferences specified by the user as the post body
start : the coordinates of the starting point
end : the coordinates of the finishing point
Returns:
(uuid) : The uuid of the first landmark in the optimized route
"""
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")
if end is None:
end = start
logger.info("No end coordinates provided. Using start=end.")
logger.info(f"Requested new trip generation. Details:\n\tCoordinates: {start}\n\tTime: {preferences.max_time_minute}\n\tSightseeing: {preferences.sightseeing.score}\n\tNature: {preferences.nature.score}\n\tShopping: {preferences.shopping.score}")
start_landmark = Landmark(name='start',
type='start',
location=(start[0], start[1]),
osm_type='start',
osm_id=0,
attractiveness=0,
duration=0,
must_do=True,
n_tags = 0)
end_landmark = Landmark(name='finish',
type='finish',
location=(end[0], end[1]),
osm_type='end',
osm_id=0,
attractiveness=0,
duration=0,
must_do=True,
n_tags=0)
start_time = time.time()
# Generate the landmarks from the start location
landmarks, landmarks_short = manager.generate_landmarks_list(
center_coordinates = start,
preferences = preferences
)
if len(landmarks) == 0 :
raise HTTPException(status_code=500, detail="No landmarks were found.")
# insert start and finish to the landmarks list
landmarks_short.insert(0, start_landmark)
landmarks_short.append(end_landmark)
t_generate_landmarks = time.time() - start_time
logger.info(f'Fetched {len(landmarks)} landmarks in \t: {round(t_generate_landmarks,3)} seconds')
start_time = time.time()
# First stage optimization
try:
base_tour = optimizer.solve_optimization(preferences.max_time_minute, landmarks_short)
except Exception as exc:
logger.error(f"Trip generation failed: {str(exc)}")
raise HTTPException(status_code=500, detail=f"Optimization failed: {str(exc)}") from exc
t_first_stage = time.time() - start_time
start_time = time.time()
# Second stage optimization
# TODO : only if necessary (not enough landmarks for ex.)
try :
refined_tour = refiner.refine_optimization(landmarks, base_tour,
preferences.max_time_minute,
preferences.detour_tolerance_minute)
except Exception as exc :
logger.warning(f"Refiner failed. Proceeding with base trip {str(exc)}")
refined_tour = base_tour
t_second_stage = time.time() - start_time
logger.debug(f'First stage optimization\t: {round(t_first_stage,3)} seconds')
logger.debug(f'Second stage optimization\t: {round(t_second_stage,3)} seconds')
logger.info(f'Total computation time\t: {round(t_first_stage + t_second_stage,3)} seconds')
linked_tour = LinkedLandmarks(refined_tour)
# upon creation of the trip, persistence of both the trip and its landmarks is ensured.
trip = Trip.from_linked_landmarks(linked_tour, cache_client)
logger.info(f'Generated a trip of {trip.total_time} minutes with {len(refined_tour)} landmarks in {round(t_generate_landmarks + t_first_stage + t_second_stage,3)} seconds.')
logger.info('Detailed trip :\n\t' + '\n\t'.join(f'{landmark}' for landmark in refined_tour))
background_tasks.add_task(fill_cache)
return trip
#### For already existing trips/landmarks
@app.get("/trip/{trip_uuid}")
def get_trip(trip_uuid: str) -> Trip:
"""
Look-up the cache for a trip that has been previously generated using its identifier.
Args:
trip_uuid (str) : unique identifier for a trip.
Returns:
(Trip) : the corresponding trip.
"""
try:
trip = cache_client.get(f"trip_{trip_uuid}")
return trip
except KeyError as exc:
logger.error(f"Failed to fetch trip with UUID {trip_uuid}: {str(exc)}")
raise HTTPException(status_code=404, detail="Trip not found") from exc
@app.get("/landmark/{landmark_uuid}")
def get_landmark(landmark_uuid: str) -> Landmark:
"""
Returns a Landmark from its unique identifier.
Args:
landmark_uuid (str) : unique identifier for a Landmark.
Returns:
(Landmark) : the corresponding Landmark.
"""
try:
landmark = cache_client.get(f"landmark_{landmark_uuid}")
return landmark
except KeyError as exc:
logger.error(f"Failed to fetch landmark with UUID {landmark_uuid}: {str(exc)}")
raise HTTPException(status_code=404, detail="Landmark not found") from exc
@app.post("/trip/recompute-time/{trip_uuid}/{removed_landmark_uuid}")
def update_trip_time(trip_uuid: str, removed_landmark_uuid: str) -> Trip:
"""
Updates the reaching times of a given trip when removing a landmark.
Args:
landmark_uuid (str) : unique identifier for a Landmark.
Returns:
(Landmark) : the corresponding Landmark.
"""
# First, fetch the trip in the cache.
try:
trip = cache_client.get(f'trip_{trip_uuid}')
except KeyError as exc:
logger.error(f"Failed to update trip with UUID {trip_uuid} (trip not found): {str(exc)}")
raise HTTPException(status_code=404, detail='Trip not found') from exc
landmarks = []
next_uuid = trip.first_landmark_uuid
# Extract landmarks
try :
while next_uuid is not None:
landmark = cache_client.get(f'landmark_{next_uuid}')
# Filter out the removed landmark.
if next_uuid != removed_landmark_uuid :
landmarks.append(landmark)
next_uuid = landmark.next_uuid # Prepare for the next iteration
except KeyError as exc:
logger.error(f"Failed to update trip with UUID {trip_uuid} : {str(exc)}")
raise HTTPException(status_code=404, detail=f'landmark {next_uuid} not found') from exc
# Re-link every thing and compute times again
linked_tour = LinkedLandmarks(landmarks)
trip = Trip.from_linked_landmarks(linked_tour, cache_client)
return trip
# TODO: get stuff to do nearby. The idea is to have maybe thhe 3 best things to do within 500m and 2 hidden gems.
@app.post("/landmarks/get-nearby/{lat}/{lon}")
def get_landmarks_nearby(lat: float, lon: float) -> list[Landmark] :
# preferences = {"sightseeing": {"type": "sightseeing", "score": 0},
# "nature": {"type": "nature", "score": 0},
# "shopping": {"type": "shopping", "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 = 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),
allow_clusters=False
)
if len(landmarks_around) == 0 :
raise HTTPException(status_code=500, detail="No landmarks were found.")
# select 5 landmarks from there
if len(landmarks_around) > 6 :
landmarks_around = landmarks_around[:2] + random.sample(landmarks_around[3:], 2)
logger.info('Suggested landmarks :\n\t' + '\n\t'.join(f'{landmark}' for landmark in landmarks_around))
return landmarks_around