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Python Celery Task Queues for Video Metadata Processing

DEV Community·ahmet gedik·26 days ago
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Why Background Processing for a Viral Video Vault ViralVidVault tracks viral videos across 7 European regions. The main cron pipeline needs to be fast -- fetch, score, store. But secondary tasks like thumbnail quality checks, deep metadata enrichment, and stale link removal are too slow for the critical path. Celery lets us offload this work to background workers. Celery Configuration # celery_app.py from celery import Celery app = Celery ( " viralvidvault " , broker = " redis://localhost:6379/0 " , backend = " redis://localhost:6379/1 " , ) app . conf . update ( task_serializer = " json " , result_serializer = " json " , accept_content = [ " json " ], timezone = " UTC " , task_acks_late = True , worker_prefetch_multiplier = 2 , task_soft_time_limit = 90 , task_time_limit = 120 , task_routes = { " tasks.score_virality_batch " : { " queue " : " scoring " }, " tasks.validate_thumbnails " : { " queue " : " thumbnails " }, " tasks.detect_dead_videos " : { " queue " : " cleanup " }, }, ) Enter fullscreen mode…

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