156 lines
6.2 KiB
Python
156 lines
6.2 KiB
Python
import asyncio
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import importlib
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import itertools
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import json
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import logging
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import pathlib
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from typing import Any
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from listing_processor import ListingProcessor
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from rec.query import listing_query, QueryParameters
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from rec.districts import get_districts
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from repositories import ListingRepository
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from tqdm.asyncio import tqdm
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from data_access import Listing
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from models import Listing as modelListing
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dump_images_module = importlib.import_module("3_dump_images")
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detect_floorplan_module = importlib.import_module("4_detect_floorplan")
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logger = logging.getLogger("uvicorn.error")
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async def dump_listings_full(
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parameters: QueryParameters,
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repository: ListingRepository,
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data_dir: pathlib.Path = pathlib.Path("data/rs/"),
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) -> list[modelListing]:
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"""Fetches all listings, images as well as detects floorplans"""
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new_listings = await dump_listings(parameters, repository, data_dir)
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logger.debug(f"Upserted {len(new_listings)} new listings")
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# logger.debug("Starting to fetch floorplans")
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# await dump_images_module.dump_images(repository, image_base_path=data_dir)
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# logger.debug("Completed fetching floorplans")
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# logger.debug("Starting floorplan detection")
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# await detect_floorplan_module.detect_floorplan(repository)
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# logger.debug("Completed floorplan detection")
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# refresh listings
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listings = await repository.get_listings(parameters) # this can be better
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new_listings = [l for l in listings if l.id in new_listings]
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return new_listings
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async def dump_listings(
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parameters: QueryParameters,
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repository: ListingRepository,
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data_dir: pathlib.Path = pathlib.Path("data/rs/"),
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) -> list[modelListing]:
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if parameters.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 parameters.district_names
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}
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else:
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districts = get_districts()
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logger.debug("Valid districts to scrape:", districts.keys())
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semaphore = asyncio.Semaphore(5) # if too high, rightmove drops connections
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json_responses: list[list[dict[str, Any]]] = await tqdm.gather(
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*[
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_fetch_listings_with_semaphore(semaphore, parameters, district)
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for district in districts.keys()
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],
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desc="Fetching listings",
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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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listings: list[Listing] = []
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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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listing = Listing(identifier, data_dir=data_dir, _listing_object=property)
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listings.append(listing)
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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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missing_listing = [
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listing for listing in listings if listing.identifier not in all_listing_ids
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]
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missing_ids = [listing.identifier for listing in missing_listing]
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missing_ids = [missing_ids[0]]
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listing_processor = ListingProcessor(repository)
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logger.info(f"Starting processing {len(missing_listing)} new listings")
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processed_listings = await tqdm.gather(
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*[listing_processor.process_listing(id) for id in missing_ids]
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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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async def _fetch_listings_with_semaphore(
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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 = 1
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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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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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async def dump_listings_to_fs(listings: list[Listing]) -> None:
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for listing in tqdm(listings, desc="Dumping listings to FS"):
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listing.dump_listing()
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# if not listing.path_detail_json().exists():
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with open(listing.path_detail_json(), "w") as f:
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json.dump(listing._details_object, f, indent=4)
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