Run asynchronous distributed background tasks and scheduled jobs in Python.
npx skills add https://github.com/tuliosouza99/CartolaPy --skill taskiq
Please help me install this Agent Skill. Skill: taskiq Source: https://github.com/tuliosouza99/CartolaPy/tree/main/.agents/skills/taskiq Command: npx skills add https://github.com/tuliosouza99/CartolaPy --skill taskiq
Taskiq removes the complexity of running asynchronous, distributed background work in Python applications by providing brokers, workers, scheduling, and dependency injection so developers can offload long-running jobs and schedule recurring tasks reliably.
Set up a broker, declare an async task with @broker.task, start the broker in your app lifespan, and run a taskiq worker process to process queued jobs.
High-intent search queries and answers about installing and using this skill.
Running asynchronous background tasks in a FastAPI application involves setting up a broker, declaring tasks with a decorator, and starting a worker process. Taskiq integrates with FastAPI lifespans to manage worker startup and shutdown while offloading jobs like email sending or data processing.
Scheduling recurring cron-like jobs in Python asyncio services is supported through label and Redis-based scheduling mechanisms. This allows you to run periodic aggregation jobs and background pipelines across multiple worker nodes reliably without blocking the main event loop.
Yes, you can use dependency injection for task parameters in a Python task queue. Taskiq supports resolving FastAPI-style dependencies inside tasks using TaskiqDepends, allowing you to inject required services and parameters directly into your distributed background job functions.
Taskiq supports RabbitMQ and NATS brokers for distributed task queues, alongside Redis and InMemory options. These brokers enable asynchronous distributed background processing, allowing you to scale workers across multiple nodes for long-running jobs.
Testing async background tasks deterministically uses an InMemoryBroker pattern to execute jobs without external dependencies. This approach allows you to await tasks directly during test runs, ensuring predictable and reliable verification of your background processing logic.
InMemory brokers for background task queues are limited to single-process execution and do not support distributed scaling across multiple worker nodes. They are designed for testing and local development rather than production workloads, where RabbitMQ or Redis brokers are required for reliability.
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