Question 1

How to set up periodic tasks in Machinery?

Accepted Answer

Use the RegisterPeriodicTask method with a cron expression and task signature. The README provides examples for scheduling tasks, groups, chains, and chords using standard cron syntax, making it easy to automate recurring jobs.

Question 2

Machinery vs Celery: which is better for Go projects?

Accepted Answer

Machinery is native to Go, offering seamless integration and idiomatic APIs, while Celery is Python-based. For Go applications, Machinery avoids inter-language overhead, but Celery might be preferable if you're already in a Python ecosystem with more third-party extensions.

Question 3

Can I monitor task progress in Machinery?

Accepted Answer

Yes, by configuring a result backend like Redis, you can check task states (e.g., PENDING, SUCCESS) using asyncResult.GetState() or inspect pending tasks with server.GetBroker().GetPendingTasks() specifically for Redis broker, as mentioned in the Keeping Results section.

Question 4

How to handle errors in Machinery workflows?

Accepted Answer

Configure retry counts and timeouts in task signatures, and set custom error handlers on workers using SetErrorHandler. The Error Handling section shows how to define error callbacks for tasks and groups to manage failures gracefully.

Question 5

Does Machinery support task prioritization?

Accepted Answer

No, Machinery does not natively support task priorities; tasks are processed in FIFO order based on the queue. For priority handling, you would need to implement separate queues with different routing keys or use broker-specific features outside Machinery.

Question 6

What are the performance trade-offs with Machinery?

Accepted Answer

Performance depends heavily on the chosen broker—Redis and AMQP can handle high throughput, but JSON serialization adds overhead. The README suggests tuning prefetch counts for long-running tasks and using efficient backends to minimize latency.

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