232 lines
8.8 KiB
Python
232 lines
8.8 KiB
Python
import asyncio
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import itertools
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import logging
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from typing import Any
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from celery import Task
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from celery.schedules import crontab
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from celery_app import app
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from config.schedule_config import SchedulesConfig
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from listing_processor import ListingProcessor
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from models.listing import Listing, QueryParameters
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from rec.districts import get_districts
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from rec.query import listing_query
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from repositories.listing_repository import ListingRepository
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from database import engine
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from services import image_fetcher, floorplan_detector
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from utils.redis_lock import redis_lock
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logger = logging.getLogger("uvicorn.error")
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SCRAPE_LOCK_NAME = "scrape_listings"
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@app.task(bind=True, pydantic=True)
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def dump_listings_task(self: Task, parameters_json: str) -> dict[str, Any]:
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with redis_lock(SCRAPE_LOCK_NAME) as acquired:
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if not acquired:
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logger.warning("Another scrape job is already running, skipping this execution")
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self.update_state(state="SKIPPED", meta={"reason": "Another scrape job is running"})
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return {"status": "skipped", "reason": "another_job_running"}
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logger.info(f"Acquired lock: {SCRAPE_LOCK_NAME}")
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parsed_parameters = QueryParameters.model_validate_json(parameters_json)
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self.update_state(state="Starting...", meta={"progress": 0})
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asyncio.run(dump_listings_full(task=self, parameters=parsed_parameters))
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return {"progress": 0}
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async def async_dump_listings_task(parameters_json: str) -> dict[str, Any]:
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with redis_lock(SCRAPE_LOCK_NAME) as acquired:
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if not acquired:
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logger.warning("Another scrape job is already running, skipping this execution")
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return {"status": "skipped", "reason": "another_job_running"}
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logger.info(f"Acquired lock: {SCRAPE_LOCK_NAME}")
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parsed_parameters = QueryParameters.model_validate_json(parameters_json)
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await dump_listings_full(task=Task(), parameters=parsed_parameters)
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return {"progress": 0}
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async def dump_listings_full(
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*, task: Task, parameters: QueryParameters
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) -> list[Listing]:
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"""Fetches all listings, images as well as detects floorplans"""
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repository = ListingRepository(engine)
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task.update_state(state="Identifying missing listings", meta={"progress": 0})
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ids_to_process = await get_ids_to_process(
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parameters=parameters, repository=repository, task=task
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)
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logger.info(f"Found {len(ids_to_process)} listings to process")
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listing_processor = ListingProcessor(repository)
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logger.info(f"Starting processing {len(ids_to_process)} listings")
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return await dump_listings_and_monitor(
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task=task, listing_processor=listing_processor, missing_ids=ids_to_process
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)
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async def dump_listings_and_monitor(
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*, task: Task, listing_processor: ListingProcessor, missing_ids: set[int]
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) -> list[Listing]:
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task_progress = {missing_id: 0 for missing_id in missing_ids}
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async def process(missing_id: int) -> Listing | None:
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listing = await listing_processor.process_listing(missing_id)
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task_progress[missing_id] = 1
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return listing
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async def monitor() -> None:
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while (progress := sum(task_progress.values())) < len(missing_ids):
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progress_ratio = round(progress / len(missing_ids), 2)
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logger.error(
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f"Task progress: {progress_ratio * 100}% ({progress} out of {len(missing_ids)})"
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)
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task.update_state(
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state=f"Progress: {progress_ratio * 100}% ({progress} out of {len(missing_ids)})",
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meta={"progress": progress_ratio, "processed": progress, "total": len(missing_ids)},
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)
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await asyncio.sleep(1)
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processed_listings = await asyncio.gather(
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*[process(id) for id in missing_ids], *[monitor()]
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)
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filtered_listings = [l for l in processed_listings if l is not None]
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return filtered_listings
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@app.on_after_finalize.connect
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def setup_periodic_tasks(sender, **kwargs):
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"""Register periodic tasks from environment configuration."""
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try:
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config = SchedulesConfig.from_env()
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except ValueError as e:
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logger.error(f"Failed to load schedule configuration: {e}")
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return
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for schedule in config.get_enabled_schedules():
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logger.info(
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f"Registering periodic task: {schedule.name} at {schedule.hour}:{schedule.minute}"
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)
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sender.add_periodic_task(
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crontab(
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minute=schedule.minute,
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hour=schedule.hour,
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day_of_week=schedule.day_of_week,
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),
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dump_listings_task.s(schedule.to_query_parameters().model_dump_json()),
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name=schedule.name,
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)
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async def get_ids_to_process(
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*,
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parameters: QueryParameters,
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repository: ListingRepository,
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task: Task,
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) -> set[int]:
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semaphore = asyncio.Semaphore(5) # if too high, rightmove drops connections
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districts = await get_valid_districts_to_scrape(parameters.district_names)
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task.update_state(state="Fetching listings to scrape", meta={"progress": 0})
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json_responses: list[list[dict[str, Any]]] = await asyncio.gather(
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*[
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_fetch_listings_with_semaphore(
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task=task, semaphore=semaphore, parameters=parameters, district=district
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)
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for district in districts.keys()
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],
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)
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json_responses_flat = list(itertools.chain.from_iterable(json_responses))
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logger.debug(f"Total listings fetched {len(json_responses_flat)}")
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identifiers: set[int] = set()
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for response_json in json_responses_flat:
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if response_json == {}:
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continue
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if response_json["totalAvailableResults"] == 0:
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continue
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for property in response_json["properties"]:
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identifier = property["identifier"]
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identifiers.add(identifier)
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# if listing is already in db, do not fetch details again
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all_listing_ids = {l.id for l in await repository.get_listings()}
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all_ids = all_listing_ids.union(identifiers)
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return all_ids
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async def get_valid_districts_to_scrape(
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district_names: set[str] | None,
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) -> dict[str, str]:
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if district_names:
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districts = {
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district: locid
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for district, locid in get_districts().items()
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if district in district_names
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}
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else:
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districts = get_districts()
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return districts
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async def _fetch_listings_with_semaphore(
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*,
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task: Task,
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semaphore: asyncio.Semaphore,
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parameters: QueryParameters,
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district: str,
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) -> list[dict[str, Any]]:
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result = []
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# split the price in N bands to avoid the 1.5k capping by rightmove
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# basically instead of 1 query with price between 1k and 5k that is capped at 1500 results
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# we do 10 queries each with an increment in price range so we send more queries but each
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# has a smaller chance of returning more than 1.5k results
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number_of_steps = 10
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price_step = parameters.max_price // number_of_steps
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for step in range(number_of_steps):
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task.update_state(
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state=f"Fetching listings ({step} out of {number_of_steps})",
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meta={"progress": step / number_of_steps},
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)
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min_price = step * price_step
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max_price = (step + 1) * price_step
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logger.debug(
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f"Step {step} of {number_of_steps} with {min_price=} and {max_price=}"
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)
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for num_bedrooms in range(parameters.min_bedrooms, parameters.max_bedrooms + 1):
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for page_id in range(
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1,
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3, # seems like all searches stop at 1500 entries (page_id * page_size)
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):
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logger.debug(f"Processing {page_id=} for {district=}")
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async with semaphore:
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try:
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listing_query_result = await listing_query(
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page=page_id,
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channel=parameters.listing_type,
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# min_bedrooms=parameters.min_bedrooms,
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# max_bedrooms=parameters.max_bedrooms,
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min_bedrooms=num_bedrooms,
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max_bedrooms=num_bedrooms,
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radius=parameters.radius,
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min_price=min_price,
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max_price=max_price,
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district=district,
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page_size=parameters.page_size,
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max_days_since_added=parameters.max_days_since_added,
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furnish_types=parameters.furnish_types or [],
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)
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except Exception as e:
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if "GENERIC_ERROR" in str(e): # Too big page id
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logger.debug(f"Max page id for {district=}: {page_id-1}")
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break
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raise e
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result.append(listing_query_result)
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return result
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