Viktor Barzin b9f576ae2b Stream-process listings as IDs arrive via asyncio.Queue ... Replace the sequential fetch-all-then-process pipeline with a streaming architecture where listing processing starts as soon as IDs become available from each subquery. A producer task fetches pages and enqueues new IDs (filtered inline against DB), while 20 consumer workers process listings concurrently from the queue. - Add ListingRepository.get_listing_ids() for fast ID-only projection - Refactor listing_tasks.py: remove get_ids_to_process/dump_listings_and_monitor, replace with unified producer/worker/monitor pipeline - Apply same pattern to CLI path in listing_fetcher.py - Remove 'filtering' phase from frontend, show combined fetch+process metrics - Add fetching_done flag to TaskResult for phase transition tracking		2026-02-06 23:43:54 +00:00
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listing_tasks.py	Stream-process listings as IDs arrive via asyncio.Queue	2026-02-06 23:43:54 +00:00
task_state.py	migrate background tasks to celery	2025-06-22 21:18:52 +00:00