don't know if it's documented on the book but nevertheless there has been a few times it popped up on this group. As output is buffered, especially on Windows but on unixes flavoured OSes as well, the "printed" output should be limited. Of course it never has been a real issue because if you need to return something you shouldn't NEVER EVER use print. And because you should be already accustomed to NEVER EVER using print in any web2py application, first because print doesn't get you anything and second because if you need huge prints you're probably sidestepping a correct usage of the logging library. Anyhow, I'll submit right away a PR on the book with a solid note about it.
On Monday, February 29, 2016 at 7:41:41 PM UTC+1, Boris Aramis Aguilar Rodríguez wrote: > > Hi, there is an issue driving me crazy with the web2py scheduler: > > If you return something that has a huge size then it will always timeout; > even if the scheduler task correctly finishes. Let me explain with an > example: > > def small_test(): > s = 's'*1256018 > another_s = s > #print s > #print another_s > #print 'FINISHED PROCESS' > return dict(s = s, another_s = another_s, f = 'finished') > > small_test is the function to execute, as you can see a string full of 's' > 1256018 times is. Simple > > So when you enqueue the scheduler every time the output is the same: > http://prnt.sc/a9iarj (screenshot of the TIMEOUT) > > As you can see from the screenshot, the process actually finished; while > logging the scheduler output shows the following: > > DEBUG:web2py.scheduler.PRTALONENETLAPP-SRV#24475: work to do 1405 > DEBUG:web2py.scheduler.PRTALONENETLAPP-SRV#24475: new scheduler_run > record > INFO:web2py.scheduler.PRTALONENETLAPP-SRV#24475:new task 1405 > "small_test" portal/default.small_test > DEBUG:web2py.scheduler.PRTALONENETLAPP-SRV#24475: new task allocated: > portal/default.small_test > DEBUG:web2py.scheduler.PRTALONENETLAPP-SRV#24475: task starting > DEBUG:web2py.scheduler.PRTALONENETLAPP-SRV#24475: task started > DEBUG:web2py.scheduler.PRTALONENETLAPP-SRV#24475: new task report: > COMPLETED > DEBUG:web2py.scheduler.PRTALONENETLAPP-SRV#24475: result: {"s": > "ssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssss$ > DEBUG:web2py.scheduler.PRTALONENETLAPP-SRV#24475:........recording > heartbeat (RUNNING) > DEBUG:web2py.scheduler.PRTALONENETLAPP-SRV#24475:........recording > heartbeat (RUNNING) > DEBUG:web2py.scheduler.PRTALONENETLAPP-SRV#24475:........recording > heartbeat (RUNNING) > DEBUG:web2py.scheduler.PRTALONENETLAPP-SRV#24475:........recording > heartbeat (RUNNING) > DEBUG:web2py.scheduler.PRTALONENETLAPP-SRV#24475:........recording > heartbeat (RUNNING) > DEBUG:web2py.scheduler.PRTALONENETLAPP-SRV#24475: freeing workers that > have not sent heartbeat > DEBUG:web2py.scheduler.PRTALONENETLAPP-SRV#24475:........recording > heartbeat (RUNNING) > DEBUG:web2py.scheduler.PRTALONENETLAPP-SRV#24475:........recording > heartbeat (RUNNING) > DEBUG:web2py.scheduler.PRTALONENETLAPP-SRV#24475:........recording > heartbeat (RUNNING) > DEBUG:web2py.scheduler.PRTALONENETLAPP-SRV#24475:........recording > heartbeat (RUNNING) > DEBUG:web2py.scheduler.PRTALONENETLAPP-SRV#24475:........recording > heartbeat (RUNNING) > DEBUG:web2py.scheduler.PRTALONENETLAPP-SRV#24475: freeing workers that > have not sent heartbeat > DEBUG:web2py.scheduler.PRTALONENETLAPP-SRV#24475:........recording > heartbeat (RUNNING) > DEBUG:web2py.scheduler.PRTALONENETLAPP-SRV#24475:........recording > heartbeat (RUNNING) > DEBUG:web2py.scheduler.PRTALONENETLAPP-SRV#24475:........recording > heartbeat (RUNNING) > DEBUG:web2py.scheduler.PRTALONENETLAPP-SRV#24475:........recording > heartbeat (RUNNING) > DEBUG:web2py.scheduler.PRTALONENETLAPP-SRV#24475:........recording > heartbeat (RUNNING) > DEBUG:web2py.scheduler.PRTALONENETLAPP-SRV#24475: freeing workers that > have not sent heartbeat > DEBUG:web2py.scheduler.PRTALONENETLAPP-SRV#24475:........recording > heartbeat (RUNNING) > DEBUG:web2py.scheduler.PRTALONENETLAPP-SRV#24475: task timeout > DEBUG:web2py.scheduler.PRTALONENETLAPP-SRV#24475: recording task report > in db (TIMEOUT) > DEBUG:web2py.scheduler.PRTALONENETLAPP-SRV#24475: status TIMEOUT, > stop_time 2016-02-29 11:56:52.393706, run_result {"s": > "sssssssssssssssssssssssssss$ > INFO:web2py.scheduler.PRTALONENETLAPP-SRV#24475:task completed (TIMEOUT) > DEBUG:web2py.scheduler.PRTALONENETLAPP-SRV#24475:looping... > INFO:web2py.scheduler.PRTALONENETLAPP-SRV#24475:nothing to do > > > > As you can see there is a TaskReport object in the queue with a COMPLETED > status (I know this because I read the scheduler.py code of web2py) So I'm > pretty sure the task finishes quite fast but then it hangs. > > So I did another test, that doesn't directly use the scheduler but only > calls the executor method from the scheduler and usess process; just like > the scheduler would: > > from gluon.scheduler import Task > from gluon.scheduler import executor > t = Task(app='portal', function='small_test', timeout = 120) > import logging > logging.getLogger().setLevel(logging.DEBUG) > import multiprocessing > queue = multiprocessing.Queue(maxsize = 1) > out = multiprocessing.Queue() > t.task_id = 123 > t.uuid = 'asdfasdf' > p = multiprocessing.Process(target=executor, args=(queue, t, out)) > p.start() > p.join(timeout = 120) > p.is_alive() > > > when the join finishes waiting (2 minutes) if you check for p.is_alive() > it always returns True; but when you do a queue.get() and then instantly > check for p.is_alive() the process finishes!!!!! > > So i noticed the problem is from multiprocessing library, due to the fact > that it can't handle lots of data from a queue (which seems kind of strange > for my case, but I don't know how it is implemented); anyways i found this > bug: http://bugs.python.org/issue8237 and http://bugs.python.org/issue8426 > > The interesting part is it is actually documented (I didn't knew that): > > https://docs.python.org/2/library/multiprocessing.html#multiprocessing-programming > > But in my current implementation this will happen quite often, I'll work > on a work-around but I would really like that web2py scheduler could handle > large data output from my processes for me, but well that is my wish and I > would like to have some guidance on this issue and avoid a work-around. > > Anyway, this should be documented somewhere in web2py too (that probably > could had saved me a week of code reading and debugging); or it should be > managed somehow (I wouldn't naturally expect an output limit besides the > database implementation). > -- Resources: - http://web2py.com - http://web2py.com/book (Documentation) - http://github.com/web2py/web2py (Source code) - https://code.google.com/p/web2py/issues/list (Report Issues) --- You received this message because you are subscribed to the Google Groups "web2py-users" group. 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