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Add background jobs to Django with Celery, moving work such as email delivery and PDF generation outside web requests. Covers scheduled runs, retries, linked or parallel tasks, monitoring, and tests, with Redis or RabbitMQ carrying task messages.
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Use when integrating Celery with Django - task definition and calling, django-celery-beat scheduling, worker deployment, Flower monitoring, testing tasks, batch processing, or choosing between cron and beat
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Move slow Python operations into background jobs so requests can return promptly. Use task queues and workers, the processes that execute queued work, with retry rules, duplicate handling, time limits, and persistent job status.
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Run background tasks in Python with Celery. Use when a user asks to process tasks asynchronously, schedule periodic jobs, run background workers, build task queues in Python, or offload heavy processing from web requests.
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Use when running background tasks with Celery - worker and broker configuration (Redis, RabbitMQ), task routing by name vs queue, chains/groups/chords, retry patterns (autoretry_for, retry_backoff), acks_late semantics, failure detection, and monitoring with Flower
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Use when working with Celery — celery worker management, task monitoring, queue routing, Flower dashboard analysis, and task result tracking.
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Django + Celery async task patterns — configuration, task design, beat scheduling, retries, canvas workflows, monitoring, and testing. Use when adding background jobs, scheduled tasks, or async processing to a Django app.
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Expert in background job processing with Bull/BullMQ (Redis), Celery, and cloud queues. Implements retries, scheduling, priority queues, and worker management. Use for async task processing, email campaigns, report generation, batch operations. Activate on "background job", "async task", "queue", "worker", "BullMQ", "Celery". NOT for real-time WebSocket communication, synchronous API calls, or simple setTimeout operations.
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Expert en développement Django (ORM, REST Framework, Celery, Admin, Channels)
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Backend Python Specialist IA — Expert en développement backend Python (FastAPI, Django, SQLAlchemy, Celery, async, type safety)
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Expert in background job processing with Bull/BullMQ (Redis), Celery, and cloud queues. Implements retries, scheduling, priority queues, and worker management. Use for async task processing, email campaigns, report generation, batch operations. Activate on "background job", "async task", "queue", "worker", "BullMQ", "Celery". NOT for real-time WebSocket communication, synchronous API calls, or simple setTimeout operations.
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Master Django 5.x with async views, DRF, Celery, and Django Channels. Build scalable web applications with proper architecture, testing, and deployment. Use PROACTIVELY for Django development, ORM optimization, or complex Django patterns.
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RAG-specific best practices for LlamaIndex, ChromaDB, and Celery workers. Covers ingestion, retrieval, embeddings, and performance.
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Server-specific best practices for FastAPI, Celery, and Pydantic. Extends python-skills with framework-specific patterns.
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Async communication patterns using message brokers and task queues. Use when building event-driven systems, background job processing, or service decoupling. Covers Kafka (event streaming), RabbitMQ (complex routing), NATS (cloud-native), Redis Streams, Celery (Python), BullMQ (TypeScript), Temporal (workflows), and event sourcing patterns.
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Operate a running Guaardvark: GPU and VRAM state, plugin start/stop, logs, Celery tasks, the Interconnector sync to other machines, overnight RAG autoresearch, and infographics. Use when the user asks what is using the GPU, why a job is stuck, to start or stop ComfyUI/Audio Foundry/Swarm, to sync another box, to run autoresearch, or to make an infographic.
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实现异步任务 / 消息队列 / 定时任务 / 后台 worker 时使用。覆盖 RabbitMQ / Kafka / Redis Streams / Bull / Celery / Sidekiq / Spring @Async / Temporal。融合 At-least-once + 幂等 + 死信 + Outbox 模式。
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Auto-activate for litestar_queues, QueuePlugin, QueueConfig, WorkerConfig, QueueService, @task, QueuedBackgroundTask, QueueEventsConfig, or SQLSpecBackendConfig. Not for litestar-saq, Celery, or Dramatiq.
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Auto-activate for litestar_saq, SAQPlugin, SAQConfig, QueueConfig, TaskQueues, CronJob, litestar workers run, background jobs, schedules, or SAQ UI. Not for litestar-queues, Celery, RQ, or Dramatiq.
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Structured logging conventions for DraftForge backend (Django/Celery/Daphne) and frontend (React). This skill should be used when adding log statements, creating new modules, debugging with logs, or reviewing logging patterns. Covers structlog usage, system/subsystem taxonomy, required fields, log levels, and Grafana query patterns.
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Domine Django 5.x com views assíncronas, DRF, Celery e Django Channels. Construa aplicações web escaláveis com arquitetura apropriada, testes e deployment.
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Master Django 5.x with async views, DRF, Celery, and Django Channels. Build scalable web applications with proper architecture, testing, and deployment. Use PROACTIVELY for Django development, ORM optimization, or complex Django patterns.
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Designs background job processing systems with queue integration (BullMQ/Celery), job definitions, retry policies, exponential backoff, idempotent execution, and monitoring hooks. Use when implementing "background jobs", "task queues", "async processing", or "job workers".
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