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Found 20 Skills
Expert Django and Celery guidance for asynchronous task processing. Use when designing background tasks, configuring workers, handling retries and errors, optimizing task performance, implementing periodic tasks, or setting up production monitoring. Follows Celery best practices with Django integration patterns.
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.
Full Sentry SDK setup for Python. Use when asked to "add Sentry to Python", "install sentry-sdk", "setup Sentry in Python", or configure error monitoring, tracing, profiling, logging, metrics, crons, or AI monitoring for Python applications. Supports Django, Flask, FastAPI, Celery, Starlette, AIOHTTP, Tornado, and more.
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.
factory_boy test data generation specialist. Covers Factory, DjangoModelFactory, SQLAlchemyModelFactory, all field declarations (Faker, LazyAttribute, Sequence, SubFactory, RelatedFactory, post_generation, Trait, Maybe, Dict, List), batch creation, pytest integration, and Celery task testing patterns. USE WHEN: user mentions "factory_boy", "test factory", "DjangoModelFactory", "SQLAlchemyModelFactory", asks about "test data generation", "factory traits", "SubFactory", "factory fixtures". DO NOT USE FOR: pytest internals - use `pytest`; Django setup - use `pytest-django`; Hypothesis property testing - use `pytest` with Hypothesis
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.
Python background job patterns including task queues, workers, and event-driven architecture. Use when implementing async task processing, job queues, long-running operations, or decoupling work from request/response cycles.
Expert Django developer specializing in Async Views, Django Ninja (FastAPI-like), and HTMX patterns for modern full-stack apps.