Method 1:
If you turned on logging at the start of celery workers, they record the time taken to complete each task.
$ celery worker -l info -A your_app --logfile celery.log
This will lead to the creation of such magazines.
[2016-06-04 13:21:30,749: INFO/MainProcess] Task sig.add[a8b648eb-9674-44f0-90bd-71cfebe22f2f] succeeded in 0.00979363399983s: 3
[2016-06-04 13:21:30,973: INFO/MainProcess] Received task: sig.add[7fd422e6-8f48-4dd2-90de-e213afbedc38]
[2016-06-04 13:21:30,982: WARNING/Worker-2] called by small_task. LOL {'signal': <Signal: Signal>, 'result': 3, 'sender': <@task: sig.add of tasks:0x7fdf33146c50>}
, succeeded in. , , [, : , , , .
$ grep ' succeeded in ' celery.log | awk -F'[ :\[]' '{print $9, $13}' | sort
awk: warning: escape sequence `\[' treated as plain `['
sig.add 0.00775764500031s
sig.add 0.00802627899975s
sig.foo 12.00813863099938s
sig.foo 15.00871706100043s
sig.foo 12.00979363399983s
, add , foo .
2:
task_prerun_handler, task_postrun_handler , / . , , -.
from time import time
from celery.signals import task_prerun, task_postrun
tasks = {}
task_avg_time = {}
Average = namedtuple('Average', 'cum_avg count')
@task_prerun.connect
def task_prerun_handler(signal, sender, task_id, task, args, kwargs):
tasks[task_id] = time()
@task_postrun.connect
def task_postrun_handler(signal, sender, task_id, task, args, kwargs, retval, state):
try:
cost = time() - tasks.pop(task_id)
except KeyError:
cost = None
if not cost:
return
try:
cum_avg, count = task_avg_time[task.name]
new_count = count + 1
new_avg = ((cum_avg * count) + cost) / new_count
task_avg_time[task.name] = Average(new_avg, new_count)
except KeyError:
task_avg_time[task.name] = Average(cost, 1)
: fooobar.com/questions/956362/...