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Add comprehensive logging to Celery tasks and listing processor

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This commit is contained in:
Viktor Barzin 2026-02-02 23:01:13 +00:00
parent 33ae5c91a2
commit 3267adca66
2 changed files with 269 additions and 107 deletions
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60
crawler/listing_processor.py
View file

@ -13,6 +13,9 @@ from repositories.listing_repository import ListingRepository
logger = logging.getLogger("uvicorn.error")
# Also use celery task logger for visibility in worker output
celery_logger = logging.getLogger("celery.task")
class ListingProcessor:
semaphore: asyncio.Semaphore
@ -36,15 +39,16 @@ class ListingProcessor:
for step in self.process_steps:
if await step.needs_processing(listing_id):
async with self.semaphore:
step_name = step.__class__.__name__
try:
listing = await step.process(listing_id)
logger.debug(f"[{listing_id}] {step_name} completed")
except Exception as e:
logger.error(f"Failed to process {listing_id=}: {e}")
logger.error(f"[{listing_id}] {step_name} failed: {e}")
celery_logger.error(f"[{listing_id}] {step_name} failed: {e}")
return None
return listing
async def listing_exists(self, listing_id: int) -> bool: ...
class Step:
listing_repository: ListingRepository
@ -65,19 +69,23 @@ class FetchListingDetailsStep(Step):
existing_listings = await self.listing_repository.get_listings(
only_ids=[listing_id]
)
if (existing_listings) == 0:
if len(existing_listings) == 0:
return True
return False
async def process(self, listing_id: int) -> Listing:
logger.debug(f"Fetching details for {listing_id=}")
logger.debug(f"[{listing_id}] Fetching property details from API")
celery_logger.info(f"[{listing_id}] Fetching details...")
existing_listings = await self.listing_repository.get_listings(
only_ids=[listing_id]
)
now = datetime.now()
if len(existing_listings) > 0:
# listing exists, do not refresh
logger.debug(f"[{listing_id}] Already exists, skipping refresh")
return existing_listings[0]
listing_details = await detail_query(listing_id)
furnish_type_str = listing_details["property"].get("letFurnishType", "unknown")
@ -124,7 +132,12 @@ class FetchListingDetailsStep(Step):
additional_info=listing_details,
)
await self.listing_repository.upsert_listings([listing])
logger.debug(f"Completed fetching details for {listing_id=}")
celery_logger.info(
f"[{listing_id}] Details fetched: £{listing.price}, "
f"{listing.number_of_bedrooms}BR, {listing.agency}"
)
logger.debug(f"[{listing_id}] Details fetch complete")
# TODO: dump to filesystem
return listing
@ -140,7 +153,8 @@ class FetchImagesStep(Step):
return len(listing.floorplan_image_paths) == 0
async def process(self, listing_id: int) -> Listing:
logger.debug(f"Fetching images for {listing_id=}")
logger.debug(f"[{listing_id}] Fetching floorplan images")
existing_listings = await self.listing_repository.get_listings(
only_ids=[listing_id]
)
@ -152,6 +166,12 @@ class FetchImagesStep(Step):
all_floorplans = listing.additional_info.get("property", {}).get(
"floorplans", []
)
if len(all_floorplans) == 0:
logger.debug(f"[{listing_id}] No floorplans available")
return listing
downloaded = 0
client_timeout = aiohttp.ClientTimeout(total=30)
for floorplan_obj in all_floorplans:
url = floorplan_obj["url"]
@ -169,8 +189,12 @@ class FetchImagesStep(Step):
with open(floorplan_path, "wb") as f:
f.write(await response.read())
listing.floorplan_image_paths.append(str(floorplan_path))
downloaded += 1
await self.listing_repository.upsert_listings([listing])
logger.debug(f"Completed fetching images for {listing_id=}")
celery_logger.info(f"[{listing_id}] Downloaded {downloaded} floorplan images")
logger.debug(f"[{listing_id}] Image fetch complete")
return listing
@ -188,11 +212,19 @@ class DetectFloorplanStep(Step):
return listings[0].square_meters is None
async def process(self, listing_id: int) -> Listing:
logger.debug(f"Running floorplan detection for {listing_id=}")
logger.debug(f"[{listing_id}] Running OCR on floorplans")
listings = await self.listing_repository.get_listings(only_ids=[listing_id])
if len(listings) == 0:
raise ValueError(f"Listing {listing_id} does not exist")
listing = listings[0]
if len(listing.floorplan_image_paths) == 0:
logger.debug(f"[{listing_id}] No floorplan images to process")
listing.square_meters = 0
await self.listing_repository.upsert_listings([listing])
return listing
sqms = []
for floorplan_path in listing.floorplan_image_paths:
async with self.ocr_semaphore:
@ -201,9 +233,15 @@ class DetectFloorplanStep(Step):
)
if estimated_sqm is not None:
sqms.append(estimated_sqm)
max_sqm = max(sqms, default=0) # try once, if we fail, keep as 0
# if max_sqm is not None:
listing.square_meters = max_sqm
await self.listing_repository.upsert_listings([listing])
logger.debug(f"Completed running floorplan detection for {listing_id=}")
if max_sqm > 0:
celery_logger.info(f"[{listing_id}] OCR detected {max_sqm} sqm")
else:
logger.debug(f"[{listing_id}] OCR: no square meters detected")
logger.debug(f"[{listing_id}] OCR complete")
return listing

316
crawler/tasks/listing_tasks.py
View file

@ -1,5 +1,6 @@
import asyncio
import logging
import time
from typing import Any
from celery import Task
from celery.schedules import crontab
@ -9,6 +10,8 @@ from config.scraper_config import ScraperConfig
from listing_processor import ListingProcessor
from models.listing import Listing, QueryParameters
from rec.query import create_session, listing_query
from rec.exceptions import CircuitBreakerOpenError, ThrottlingError
from rec.throttle_detector import get_throttle_metrics, reset_throttle_metrics
from repositories.listing_repository import ListingRepository
from database import engine
from services.query_splitter import QuerySplitter, SubQuery
@ -16,6 +19,16 @@ from utils.redis_lock import redis_lock
logger = logging.getLogger("uvicorn.error")
# Also configure a celery-specific logger that always outputs to stdout
celery_logger = logging.getLogger("celery.task")
if not celery_logger.handlers:
handler = logging.StreamHandler()
handler.setFormatter(logging.Formatter(
"%(asctime)s [%(levelname)s] %(name)s: %(message)s"
))
celery_logger.addHandler(handler)
celery_logger.setLevel(logging.INFO)
SCRAPE_LOCK_NAME = "scrape_listings"
@ -23,12 +36,18 @@ SCRAPE_LOCK_NAME = "scrape_listings"
def dump_listings_task(self: Task, parameters_json: str) -> dict[str, Any]:
with redis_lock(SCRAPE_LOCK_NAME) as acquired:
if not acquired:
logger.warning("Another scrape job is already running, skipping this execution")
msg = "Another scrape job is already running, skipping this execution"
logger.warning(msg)
celery_logger.warning(msg)
self.update_state(state="SKIPPED", meta={"reason": "Another scrape job is running"})
return {"status": "skipped", "reason": "another_job_running"}
celery_logger.info(f"Acquired lock: {SCRAPE_LOCK_NAME}")
logger.info(f"Acquired lock: {SCRAPE_LOCK_NAME}")
parsed_parameters = QueryParameters.model_validate_json(parameters_json)
celery_logger.info(f"Starting scrape with parameters: {parsed_parameters}")
self.update_state(state="Starting...", meta={"progress": 0})
asyncio.run(dump_listings_full(task=self, parameters=parsed_parameters))
return {"progress": 0}
@ -50,46 +69,91 @@ async def dump_listings_full(
*, task: Task, parameters: QueryParameters
) -> list[Listing]:
"""Fetches all listings, images as well as detects floorplans"""
start_time = time.time()
celery_logger.info("=" * 60)
celery_logger.info("PHASE 1: Initializing listing fetch")
celery_logger.info("=" * 60)
repository = ListingRepository(engine)
task.update_state(state="Identifying missing listings", meta={"progress": 0})
celery_logger.info("Querying Rightmove API to identify new listings...")
ids_to_process = await get_ids_to_process(
parameters=parameters, repository=repository, task=task
)
celery_logger.info(f"Found {len(ids_to_process)} new listings to process")
logger.info(f"Found {len(ids_to_process)} listings to process")
if len(ids_to_process) == 0:
elapsed = time.time() - start_time
celery_logger.info(f"No new listings found. Completed in {elapsed:.1f}s")
task.update_state(
state="No new listings found",
meta={"progress": 1, "processed": 0, "total": 0, "message": "All listings are up to date"},
)
return []
celery_logger.info("=" * 60)
celery_logger.info("PHASE 2: Processing listings (fetch details, images, OCR)")
celery_logger.info("=" * 60)
listing_processor = ListingProcessor(repository)
celery_logger.info(f"Starting processing {len(ids_to_process)} listings")
logger.info(f"Starting processing {len(ids_to_process)} listings")
return await dump_listings_and_monitor(
result = await dump_listings_and_monitor(
task=task, listing_processor=listing_processor, missing_ids=ids_to_process
)
elapsed = time.time() - start_time
celery_logger.info("=" * 60)
celery_logger.info(f"COMPLETED: Processed {len(result)} listings in {elapsed:.1f}s")
celery_logger.info("=" * 60)
return result
async def dump_listings_and_monitor(
*, task: Task, listing_processor: ListingProcessor, missing_ids: set[int]
) -> list[Listing]:
task_progress = {missing_id: 0 for missing_id in missing_ids}
processed_count = 0
failed_count = 0
start_time = time.time()
async def process(missing_id: int) -> Listing | None:
nonlocal processed_count, failed_count
listing = await listing_processor.process_listing(missing_id)
task_progress[missing_id] = 1
if listing is not None:
processed_count += 1
else:
failed_count += 1
return listing
async def monitor() -> None:
last_progress = 0
while (progress := sum(task_progress.values())) < len(missing_ids):
progress_ratio = round(progress / len(missing_ids), 2)
logger.error(
f"Task progress: {progress_ratio * 100}% ({progress} out of {len(missing_ids)})"
)
# Log every 10% progress or at least every update
if progress_ratio >= last_progress + 0.1 or progress == 1:
elapsed = time.time() - start_time
rate = progress / elapsed if elapsed > 0 else 0
eta = (len(missing_ids) - progress) / rate if rate > 0 else 0
celery_logger.info(
f"Progress: {progress_ratio * 100:.0f}% "
f"({progress}/{len(missing_ids)}) "
f"| Elapsed: {elapsed:.0f}s "
f"| Rate: {rate:.1f}/s "
f"| ETA: {eta:.0f}s"
)
last_progress = progress_ratio
task.update_state(
state=f"Progress: {progress_ratio * 100}% ({progress} out of {len(missing_ids)})",
state=f"Processing: {progress_ratio * 100:.0f}% ({progress}/{len(missing_ids)})",
meta={"progress": progress_ratio, "processed": progress, "total": len(missing_ids)},
)
await asyncio.sleep(1)
@ -97,7 +161,11 @@ async def dump_listings_and_monitor(
processed_listings = await asyncio.gather(
*[process(id) for id in missing_ids], *[monitor()]
)
filtered_listings = [l for l in processed_listings if l is not None]
filtered_listings = [listing for listing in processed_listings if listing is not None]
celery_logger.info(
f"Processing complete: {processed_count} successful, {failed_count} failed"
)
return filtered_listings
@ -149,115 +217,171 @@ async def get_ids_to_process(
config = ScraperConfig.from_env()
splitter = QuerySplitter(config)
# Reset throttle metrics
reset_throttle_metrics()
def on_progress(phase: str, message: str) -> None:
task.update_state(state=message, meta={"phase": phase})
celery_logger.info(f"[{phase}] {message}")
async with create_session(config) as session:
# Phase 1 & 2: Split and probe queries
task.update_state(
state="Analyzing query and splitting by price bands...",
meta={"phase": "splitting", "progress": 0},
)
subqueries = await splitter.split(parameters, session, on_progress)
celery_logger.info("Starting query splitting and probing...")
total_estimated = splitter.calculate_total_estimated_results(subqueries)
logger.info(
f"Split into {len(subqueries)} subqueries, "
f"estimated {total_estimated} total results"
)
try:
async with create_session(config) as session:
# Phase 1 & 2: Split and probe queries
task.update_state(
state="Analyzing query and splitting by price bands...",
meta={"phase": "splitting", "progress": 0},
)
subqueries = await splitter.split(parameters, session, on_progress)
# Phase 3: Fetch all pages for each subquery
task.update_state(
state=f"Fetching listings from {len(subqueries)} subqueries...",
meta={
"phase": "fetching",
"subqueries": len(subqueries),
"estimated_results": total_estimated,
},
)
semaphore = asyncio.Semaphore(config.max_concurrent_requests)
identifiers: set[int] = set()
async def fetch_subquery(sq: SubQuery) -> list[dict[str, Any]]:
"""Fetch all pages for a single subquery."""
results: list[dict[str, Any]] = []
# Calculate how many pages we need based on estimated results
estimated = sq.estimated_results or 0
if estimated == 0:
return results
# Fetch pages up to max_pages_per_query or until no more results
page_size = parameters.page_size
max_pages = min(
config.max_pages_per_query,
(estimated // page_size) + 1,
total_estimated = splitter.calculate_total_estimated_results(subqueries)
celery_logger.info(
f"Query split complete: {len(subqueries)} subqueries, "
f"~{total_estimated} estimated total results"
)
logger.info(
f"Split into {len(subqueries)} subqueries, "
f"estimated {total_estimated} total results"
)
for page_id in range(1, max_pages + 1):
async with semaphore:
await asyncio.sleep(config.request_delay_ms / 1000)
try:
result = await listing_query(
page=page_id,
channel=parameters.listing_type,
min_bedrooms=sq.min_bedrooms,
max_bedrooms=sq.max_bedrooms,
radius=parameters.radius,
min_price=sq.min_price,
max_price=sq.max_price,
district=sq.district,
page_size=page_size,
max_days_since_added=parameters.max_days_since_added,
furnish_types=parameters.furnish_types or [],
session=session,
)
results.append(result)
# Phase 3: Fetch all pages for each subquery
task.update_state(
state=f"Fetching listings from {len(subqueries)} subqueries...",
meta={
"phase": "fetching",
"subqueries": len(subqueries),
"estimated_results": total_estimated,
},
)
# Check if we've received all results
properties = result.get("properties", [])
if len(properties) < page_size:
# No more results on next page
celery_logger.info(f"Fetching pages from {len(subqueries)} subqueries...")
semaphore = asyncio.Semaphore(config.max_concurrent_requests)
identifiers: set[int] = set()
completed_subqueries = 0
total_pages_fetched = 0
async def fetch_subquery(sq: SubQuery) -> list[dict[str, Any]]:
"""Fetch all pages for a single subquery."""
nonlocal completed_subqueries, total_pages_fetched
results: list[dict[str, Any]] = []
# Calculate how many pages we need based on estimated results
estimated = sq.estimated_results or 0
if estimated == 0:
completed_subqueries += 1
return results
# Fetch pages up to max_pages_per_query or until no more results
page_size = parameters.page_size
max_pages = min(
config.max_pages_per_query,
(estimated // page_size) + 1,
)
for page_id in range(1, max_pages + 1):
async with semaphore:
await asyncio.sleep(config.request_delay_ms / 1000)
try:
result = await listing_query(
page=page_id,
channel=parameters.listing_type,
min_bedrooms=sq.min_bedrooms,
max_bedrooms=sq.max_bedrooms,
radius=parameters.radius,
min_price=sq.min_price,
max_price=sq.max_price,
district=sq.district,
page_size=page_size,
max_days_since_added=parameters.max_days_since_added,
furnish_types=parameters.furnish_types or [],
session=session,
config=config,
)
results.append(result)
total_pages_fetched += 1
# Check if we've received all results
properties = result.get("properties", [])
if len(properties) < page_size:
# No more results on next page
break
except CircuitBreakerOpenError as e:
celery_logger.error(f"Circuit breaker open: {e}")
break
except Exception as e:
if "GENERIC_ERROR" in str(e):
# Reached end of results
logger.debug(
f"Max page for {sq.district}: {page_id - 1}"
except ThrottlingError as e:
celery_logger.warning(
f"Throttling on {sq.district} page {page_id}: {e}"
)
break
except Exception as e:
if "GENERIC_ERROR" in str(e):
# Reached end of results
logger.debug(
f"Max page for {sq.district}: {page_id - 1}"
)
break
logger.warning(
f"Error fetching page {page_id} for {sq.district}: {e}"
)
break
logger.warning(
f"Error fetching page {page_id} for {sq.district}: {e}"
)
break
return results
completed_subqueries += 1
return results
# Fetch all subqueries concurrently
all_results = await asyncio.gather(
*[fetch_subquery(sq) for sq in subqueries]
)
# Fetch all subqueries concurrently
all_results = await asyncio.gather(
*[fetch_subquery(sq) for sq in subqueries]
)
# Extract identifiers from all results
for subquery_results in all_results:
for response_json in subquery_results:
if not response_json:
continue
if response_json.get("totalAvailableResults", 0) == 0:
continue
for property_data in response_json.get("properties", []):
identifier = property_data.get("identifier")
if identifier:
identifiers.add(identifier)
celery_logger.info(
f"Fetch complete: {total_pages_fetched} pages from "
f"{completed_subqueries} subqueries"
)
# Extract identifiers from all results
for subquery_results in all_results:
for response_json in subquery_results:
if not response_json:
continue
if response_json.get("totalAvailableResults", 0) == 0:
continue
for property_data in response_json.get("properties", []):
identifier = property_data.get("identifier")
if identifier:
identifiers.add(identifier)
except CircuitBreakerOpenError as e:
celery_logger.error(f"Circuit breaker prevented query: {e}")
# Log throttle metrics
metrics = get_throttle_metrics()
if metrics.total_requests > 0:
celery_logger.info(metrics.summary())
return set()
finally:
# Log throttle metrics
metrics = get_throttle_metrics()
if metrics.total_requests > 0:
celery_logger.info(f"API Stats: {metrics.total_requests} requests, "
f"avg {metrics.average_response_time:.2f}s, "
f"{metrics.total_throttling_events} throttled")
celery_logger.info(f"Found {len(identifiers)} unique listing IDs from API")
logger.info(f"Found {len(identifiers)} unique listings")
# Filter out listings already in the database
all_listing_ids = {l.id for l in await repository.get_listings()}
celery_logger.info("Checking database for existing listings...")
all_listing_ids = {listing.id for listing in await repository.get_listings()}
new_ids = identifiers - all_listing_ids
celery_logger.info(
f"Filtering: {len(identifiers)} total, "
f"{len(all_listing_ids)} existing in DB, "
f"{len(new_ids)} new to process"
)
task.update_state(
state=f"Found {len(new_ids)} new listings to process",
meta={