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Benchmark huey beside the other queues - #91
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- benchmarks/huey_app.py hands echo tasks to the huey Redis storage, which keeps results in the huey.results hash the cleanup already names. - The consumer runs as one process with one thread, like the celery and dramatiq workers, and is stopped after a sentinel task proves the drain. - The footnote lists huey with the queues that read one message at a time. - The generated chart is left untouched; regenerate it with benchmarks/chart.py from a run on an idle machine.
Measured on an idle machine: threadmill 9,960 tasks/s, dramatiq 7,177, huey 6,038, celery 2,280, django-tasks-db 2,065, django-tasks-rq 82. Four of the five earlier rows land within 6% of the previous chart; threadmill measured 9,960 against 11,977, which is the queue that coverage tracing and start-cost quantization hit hardest.
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The comparison benchmarks cover Celery, dramatiq, django-tasks-db and django-tasks-rq, but not huey. Huey is a widely used lightweight queue, so the throughput chart should rank it beside the others.
benchmarks/huey_app.pywith aRedisHueyapp, an echo task and a sentinel task.--graceful-signal=TERMmakes SIGTERM stop it gracefully.huey.*queue, results, schedule and counter keys in the queue cleanup.One thing to review: the threadmill row measures 9,960 tasks/s against 11,977 in the previous chart. It is the row that coverage tracing and the one-second start cost hit hardest, because its worker runs in-process and its drain is only about 8 seconds. The other four earlier rows reproduce within 6%.