NixReaperandClaude Sonnet 5
892f78016c
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Collections were bare stubs (name only) lazily created the moment a
movie's belongs_to_collection reference was seen. Adds a real
ingest_collection pipeline: TMDb's /collection/{id} for overview and
poster/backdrop artwork, plus ordered CollectionMovie membership --
linking only movies already ingested into Aurora, the same
never-fabricate-a-stub rule movie recommendations already follow.
get_or_create_collection now refreshes name/overview on an existing
stub instead of only creating, guarded so a bare movie-stub call
(overview=None) never clobbers real data a full ingestion already
filled in.
New POST /api/v1/admin/ingest/collection endpoint and
ingest_collection_task; GET /api/v1/collections/{id} needed no changes
since its read path (collection_service.py) already assembled the full
detail shape.
Co-Authored-By: Claude Sonnet 5 <[email protected]>
52 lines
1.3 KiB
Python
52 lines
1.3 KiB
Python
"""arq worker process entrypoint.
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Run with: `arq app.workers.worker.WorkerSettings`
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Workers scale independently of the API (section 1) — run as many worker
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processes/containers as needed; arq's Redis-backed queue coordinates them so
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each job is picked up by exactly one worker.
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"""
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from __future__ import annotations
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from arq.connections import RedisSettings
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from app.core.config import get_settings
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from app.core.logging import configure_logging, get_logger
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from app.workers.tasks import (
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download_artwork_task,
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ingest_collection_task,
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ingest_movie_task,
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ingest_person_task,
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ingest_season_task,
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ingest_series_task,
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)
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logger = get_logger(__name__)
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async def startup(ctx: dict) -> None:
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configure_logging()
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logger.info("worker_started")
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async def shutdown(ctx: dict) -> None:
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logger.info("worker_stopped")
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class WorkerSettings:
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functions = [
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ingest_movie_task,
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ingest_person_task,
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ingest_series_task,
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ingest_season_task,
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ingest_collection_task,
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download_artwork_task,
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]
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on_startup = startup
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on_shutdown = shutdown
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redis_settings = RedisSettings.from_dsn(get_settings().REDIS_URL)
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max_jobs = get_settings().WORKER_CONCURRENCY
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job_timeout = 300
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max_tries = 5
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