Don't know why but gc.garbage is empty list.

On Sunday, February 15, 2015 at 1:04:15 PM UTC+2, Graham Dumpleton wrote:
>
> If the objects cannot be reclaimed due to Python objects cycles where 
> objects have __del__() methods, they simply are not able to be reclaimed.
>
> You can try:
>
>     import gc
>     gc.collect()
>
> but will likely have little effect.
>
> I would suggest you also read:
>
> http://christian.hofstaedtler.name/blog/2013/01/gc-garbage.html
>
> Graham
>
> On 15/02/2015, at 10:00 PM, Paul Royik <[email protected] <javascript:>> 
> wrote:
>
> Can I force cleaning memory after algorithm has finished?
>
> On Sunday, February 15, 2015 at 12:53:30 PM UTC+2, Graham Dumpleton wrote:
>>
>>
>> On 15/02/2015, at 9:41 PM, Paul Royik <[email protected]> wrote:
>>
>> I reduced possibility by restricting very long and complex expressions.
>>
>> Code, that I use is simple.
>>
>> class TimeLimit(object):
>>     def __init__(self, timeout=60):
>>         self.timeout = timeout
>>         self.end = None
>>
>>     def check_timeout(self):
>>         if self.end and time.time() > self.end:
>>             raise TimeoutException
>>         else:
>>             self.start()
>>
>>     def start(self):
>>         if not self.end:
>>             self.end = time.time() + self.timeout
>>
>> class MainClass(object):
>>   def __init__(self):
>>        self.timer = TimeLimit()
>>         algo(timer)
>>
>>
>> def algo(timer):
>>     do_something()
>>     external()
>>     timer.check_timeout()
>>     algo(timer)
>>
>>
>> Which ultimately is no different to what was being done with the 
>> decorator.
>>
>> If external() can run a lot longer than the timeout, either way is not 
>> going to be much use. It is only going to be of much use if external() is 
>> always a short call and on subsequent calls you are simply calling it with 
>> different arguments.
>>
>> I debugged code thoroughly and it works as expected. And as shown memory 
>> is not drastically increased during execution, but later. Is that possible 
>> that reasong in apache conf? Or I need to look for problem in code? I have 
>> no clue where to search as everything works. Is it possible to see memory 
>> usage somehow on localhost (I'm under Windows)?
>>
>>
>> It is unlikely to be the Apache configuration. It is more likely that 
>> after finishing the execution of the algorithm, the algorithm isn't 
>> clearing out any working data structures it creates when it is doing 
>> calculations and they are persisting in memory. Subsequent calls simply add 
>> more memory each time and so it grows in that way.
>>
>> There are various reasons that Python objects cannot be reclaimed and 
>> will keep using memory.
>>
>> There aren't really great tools for tracking that sort of stuff down.
>>
>> Graham
>>
>> On Sunday, February 15, 2015 at 12:31:36 PM UTC+2, Graham Dumpleton wrote:
>>>
>>>
>>> On 15/02/2015, at 9:26 PM, Paul Royik <[email protected]> wrote:
>>>
>>> Yes. External library could run long (although I reduced this 
>>> possibility).
>>>
>>>
>>> How have you reduced possibility?
>>>
>>> So, what should I do with locking threads? Is it resolvable?
>>>
>>>
>>> No idea. It isn't my code. I can only highlight what looks suspicious in 
>>> the log output.
>>>
>>> I'm just now playing with code on stackoverflow. People suggested to 
>>> create class instead of decorator and pass its instance in all functions. I 
>>> did as they proposed and it worked.
>>>
>>>
>>> Since you don't provide the code for that, I can't comment.
>>>
>>> However, with the flow of time I see increase in memory.
>>> So, now nobody access site.
>>>
>>> I ran command ps -u simamura -o pid,rss,command | awk '{print 
>>> $0}{sum+=$2} END {print "Total", sum/1024, "MB"}' and see 200 MB.
>>> Then I invoke integral calculator, while it works above command shows 
>>> 200 MB.
>>> Calculator finished, I check memory - still 200 MB. In 10-15 minutes 
>>> (remember nobody access the site) I see 240 MB.
>>>
>>> In result, memory increased from 130 MB (memory immediately after server 
>>> restart) to 435 MB in 10 hours.
>>>
>>> How can I resolve this issue? I feel that in another 12 hours webfaction 
>>> will kill the process, because I memomy will be over limit.
>>>
>>>
>>> Have you tried adding print() debug statements to your code to track 
>>> through what is being called and to determine whether your code is doing 
>>> what is expected?
>>>
>>> Graham
>>>
>>> On Sunday, February 15, 2015 at 12:12:39 PM UTC+2, Graham Dumpleton 
>>> wrote:
>>>>
>>>>
>>>> On 15/02/2015, at 9:03 PM, Paul Royik <[email protected]> wrote:
>>>>
>>>> How do you know that it runs too long?
>>>>
>>>>
>>>> In explained the log output previously and what was happening.
>>>>
>>>> If you go back far enough in the logs even before what you provided you 
>>>> will see some messages like:
>>>>
>>>> [Fri Feb 06 12:39:06.254056 2015] [wsgi:info] [pid 9731:tid 
>>>> 140178879313664] mod_wsgi (pid=9731): Daemon process request time limit 
>>>> exceeded, stopping process 'localhost:20241'.
>>>> [Fri Feb 06 12:39:06.254108 2015] [wsgi:info] [pid 9731:tid 
>>>> 140179136616192] mod_wsgi (pid=9731): Shutdown requested 'localhost:20241'.
>>>> [Fri Feb 06 12:39:06.286339 2015] [wsgi:info] [pid 9731:tid 
>>>> 140179136616192] mod_wsgi (pid=9731): Dumping stack trace for active 
>>>> Python 
>>>> threads.
>>>> [Fri Feb 06 12:39:06.286359 2015] [wsgi:info] [pid 9731:tid 
>>>> 140179136616192] mod_wsgi (pid=9731): Thread 140178316318464 executing 
>>>> file 
>>>> "/usr/local/lib/python2.7/threading.py", line 147, in acquire
>>>> [Fri Feb 06 12:39:06.286363 2015] [wsgi:info] [pid 9731:tid 
>>>> 140179136616192] mod_wsgi (pid=9731): called from file 
>>>> "/home/simamura/lib/python2.7/sympy/core/compatibility.py", line 851, in 
>>>> wrapper,
>>>> [Fri Feb 06 12:39:06.286366 2015] [wsgi:info] [pid 9731:tid 
>>>> 140179136616192] mod_wsgi (pid=9731): called from file 
>>>> "/home/simamura/lib/python2.7/sympy/core/cache.py", line 89, in wrapper,
>>>> [Fri Feb 06 12:39:06.286369 2015] [wsgi:info] [pid 9731:tid 
>>>> 140179136616192] mod_wsgi (pid=9731): called from file 
>>>> "/home/simamura/lib/python2.7/sympy/core/operations.py", line 127, in 
>>>> _matches_commutative,
>>>> [Fri Feb 06 12:39:06.286372 2015] [wsgi:info] [pid 9731:tid 
>>>> 140179136616192] mod_wsgi (pid=9731): called from file 
>>>> "/home/simamura/lib/python2.7/sympy/core/mul.py", line 808, in matches,
>>>> [Fri Feb 06 12:39:06.286375 2015] [wsgi:info] [pid 9731:tid 
>>>> 140179136616192] mod_wsgi (pid=9731): called from file 
>>>> "/home/simamura/lib/python2.7/sympy/core/add.py", line 358, in 
>>>> _matches_simple,
>>>> [Fri Feb 06 12:39:06.286378 2015] [wsgi:info] [pid 9731:tid 
>>>> 140179136616192] mod_wsgi (pid=9731): called from file 
>>>> "/home/simamura/lib/python2.7/sympy/core/operations.py", line 127, in 
>>>> _matches_commutative,
>>>>
>>>> So it says that request time limit was exceeded.
>>>>
>>>> This is followed by stack dumps for what all the request threads were 
>>>> doing.
>>>>
>>>> In the part you did show, they both are stuck in:
>>>>
>>>> [Sat Feb 14 19:58:00.261118 2015] [wsgi:info] [pid 12528:tid 
>>>> 139862016030464] mod_wsgi (pid=12528): Thread 139861715523328 executing 
>>>> file "/usr/local/lib/python2.7/threading.py", line 147, in acquire
>>>> [Sat Feb 14 19:58:00.261120 2015] [wsgi:info] [pid 12528:tid 
>>>> 139862016030464] mod_wsgi (pid=12528): called from file 
>>>> "/home/simamura/lib/python2.7/sympy/core/compatibility.py", line 851, in 
>>>> wrapper,
>>>> [Sat Feb 14 19:58:00.261122 2015] [wsgi:info] [pid 12528:tid 
>>>> 139862016030464] mod_wsgi (pid=12528): called from file 
>>>> "/home/simamura/lib/python2.7/sympy/core/cache.py", line 89, in wrapper,
>>>> [Sat Feb 14 19:58:00.261125 2015] [wsgi:info] [pid 12528:tid 
>>>> 139862016030464] mod_wsgi (pid=12528): called from file 
>>>> "/home/simamura/lib/python2.7/sympy/core/mul.py", line 373, in _gather,
>>>> [Sat Feb 14 19:58:00.261127 2015] [wsgi:info] [pid 12528:tid 
>>>> 139862016030464] mod_wsgi (pid=12528): called from file 
>>>> "/home/simamura/lib/python2.7/sympy/core/mul.py", line 98, in flatten,
>>>>
>>>> That is, they are both waiting on a thread lock.
>>>>
>>>> This suggests to me that the code isn't possibly dealing with locking 
>>>> properly, or a lock is held for a very long time while in some certain 
>>>> section and blocking other threads from running and so why they are 
>>>> delayed 
>>>> and take so long.
>>>>
>>>> No more than 300 seconds as I wrote in conf file (socket-timeout and 
>>>> request-timeout).
>>>>
>>>> I can not control it thoroughly.
>>>> def algo():
>>>>   do_something()
>>>>   invoke_external_library() # this could run slighlty longer, so 
>>>> timeout is not precise
>>>>   check_timeout()
>>>>   algo()
>>>>
>>>>
>>>> So the thing that takes the unpredictable amount of time and you need 
>>>> to interrupt is not even your code?
>>>>
>>>> Graham
>>>>
>>>> On Sunday, February 15, 2015 at 11:36:05 AM UTC+2, Graham Dumpleton 
>>>> wrote:
>>>>>
>>>>> So we are back the fact that your requests are still running too long 
>>>>> and however you have set up the timeout check isn't working.
>>>>>
>>>>> Have you added print() debug statements in your code to validate that 
>>>>> the die on timeout check is even being run regularly?
>>>>>
>>>>> To be able to distinguish each request thread, you can include the 
>>>>> output of threading.currentThread() on the print statements.
>>>>>
>>>>> Graham
>>>>>
>>>>> On 15/02/2015, at 8:19 PM, Paul Royik <[email protected]> wrote:
>>>>>
>>>>> [Sat Feb 14 19:58:00.261309 2015] [wsgi:info] [pid 12528:tid 
>>>>> 139862016030464] mod_wsgi (pid=12528): called from file 
>>>>> "/home/simamura/lib/python2.7/mod_wsgi/server/__init__.py", line 1137, in 
>>>>> handle_request.
>>>>> [Sat Feb 14 19:58:05.245850 2015] [wsgi:info] [pid 12528:tid 
>>>>> 139861541500672] mod_wsgi (pid=12528): Aborting process 'localhost:20241'.
>>>>> [Sat Feb 14 19:58:05.245889 2015] [wsgi:info] [pid 12528:tid 
>>>>> 139861541500672] mod_wsgi (pid=12528): Exiting process 'localhost:20241'.
>>>>> [Sun Feb 15 01:58:05.352861 2015] [wsgi:error] [pid 11272:tid 
>>>>> 139862014424832] [client 127.0.0.1:48193] Truncated or oversized 
>>>>> response headers received from daemon process 'localhost:20241': 
>>>>> /home/simamura/webapps/django_math/express/htdocs/calculators, referer: 
>>>>> http://www.emathhelp.net/calculators/calculus-2/integral-calculator/
>>>>> [Sun Feb 15 01:58:05.352890 2015] [wsgi:error] [pid 11272:tid 
>>>>> 139862015223552] [client 127.0.0.1:48563] Truncated or oversized 
>>>>> response headers received from daemon process 'localhost:20241': 
>>>>> /home/simamura/webapps/django_math/express/htdocs/calculators, referer: 
>>>>> http://www.emathhelp.net/calculators/calculus-2/integral-calculator/
>>>>> [Sun Feb 15 01:58:05.352958 2015] [wsgi:error] [pid 11272:tid 
>>>>> 139861948524288] [client 127.0.0.1:48240] Truncated or oversized 
>>>>> response headers received from daemon process 'localhost:20241': 
>>>>> /home/simamura/webapps/django_math/express/htdocs/calculators, referer: 
>>>>> http://www.emathhelp.net/calculators/calculus-2/integral-calculator/
>>>>> [Sun Feb 15 01:58:05.352992 2015] [wsgi:error] [pid 11272:tid 
>>>>> 139862015489792] [client 127.0.0.1:48440] Truncated or oversized 
>>>>> response headers received from daemon process 'localhost:20241': 
>>>>> /home/simamura/webapps/django_math/express/htdocs/calculators, referer: 
>>>>> http://www.emathhelp.net/calculators/calculus-2/integral-calculator/
>>>>> [Sun Feb 15 01:58:05.353008 2015] [wsgi:error] [pid 11666:tid 
>>>>> 139862014957312] [client 127.0.0.1:48329] Truncated or oversized 
>>>>> response headers received from daemon process 'localhost:20241': 
>>>>> /home/simamura/webapps/django_math/express/htdocs/calculators, referer: 
>>>>> http://www.emathhelp.net/calculators/calculus-2/integral-calculator/
>>>>> [Sun Feb 15 01:58:05.353015 2015] [wsgi:error] [pid 11272:tid 
>>>>> 139862014691072] [client 127.0.0.1:48620] Truncated or oversized 
>>>>> response headers received from daemon process 'localhost:20241': 
>>>>> /home/simamura/webapps/django_math/express/htdocs/calculators, referer: 
>>>>> http://www.emathhelp.net/calculators/calculus-2/integral-calculator/
>>>>> [Sun Feb 15 01:58:05.353081 2015] [wsgi:error] [pid 11272:tid 
>>>>> 139861949323008] [client 127.0.0.1:48778] Truncated or oversized 
>>>>> response headers received from daemon process 'localhost:20241': 
>>>>> /home/simamura/webapps/django_math/express/htdocs/calculators, referer: 
>>>>> http://www.emathhelp.net/calculators/calculus-2/integral-calculator/
>>>>> [Sun Feb 15 01:58:05.353081 2015] [wsgi:error] [pid 11666:tid 
>>>>> 139861948790528] [client 127.0.0.1:48735] Truncated or oversized 
>>>>> response headers received from daemon process 'localhost:20241': 
>>>>> /home/simamura/webapps/django_math/express/htdocs/calculators, referer: 
>>>>> http://www.emathhelp.net/calculators/calculus-2/integral-calculator/
>>>>> [Sun Feb 15 01:58:05.353096 2015] [wsgi:error] [pid 11666:tid 
>>>>> 139862015223552] [client 127.0.0.1:48792] Truncated or oversized 
>>>>> response headers received from daemon process 'localhost:20241': 
>>>>> /home/simamura/webapps/django_math/express/htdocs/calculators, referer: 
>>>>> http://www.emathhelp.net/calculators/calculus-2/integral-calculator/
>>>>> [Sun Feb 15 01:58:05.972993 2015] [wsgi:info] [pid 24792:tid 
>>>>> 139862016030464] mod_wsgi (pid=12528): Process 'localhost:20241' has 
>>>>> died, 
>>>>> deregister and restart it.
>>>>> [Sun Feb 15 01:58:06.081051 2015] [wsgi:info] [pid 24792:tid 
>>>>> 139862016030464] mod_wsgi (pid=12528): Process 'localhost:20241' has been 
>>>>> deregistered and will no longer be monitored.
>>>>> [Sun Feb 15 01:58:06.081333 2015] [wsgi:info] [pid 23028:tid 
>>>>> 139862016030464] mod_wsgi (pid=23028): Starting process 'localhost:20241' 
>>>>> with threads=10.
>>>>> [Sun Feb 15 01:58:06.163910 2015] [wsgi:info] [pid 23028:tid 
>>>>> 139862016030464] mod_wsgi (pid=23028): Python home /usr/local.
>>>>> [Sun Feb 15 01:58:06.163937 2015] [wsgi:info] [pid 23028:tid 
>>>>> 139862016030464] mod_wsgi (pid=23028): Initializing Python.
>>>>> [Sun Feb 15 01:58:06.534740 2015] [wsgi:info] [pid 23028:tid 
>>>>> 139862016030464] mod_wsgi (pid=23028): Attach interpreter ''.
>>>>> [Sun Feb 15 01:58:06.549849 2015] [wsgi:info] [pid 23028:tid 
>>>>> 139862016030464] mod_wsgi (pid=23028): Imported 'mod_wsgi'.
>>>>> [Sun Feb 15 01:58:06.549942 2015] [wsgi:info] [pid 23028:tid 
>>>>> 139862016030464] mod_wsgi (pid=23028, process='localhost:20241', 
>>>>> application=''): Loading WSGI script 
>>>>> '/home/simamura/webapps/django_math/express/handler.wsgi'.
>>>>> [Sun Feb 15 02:06:36.476939 2015] [core:info] [pid 11272:tid 
>>>>> 139861948524288] [client 127.0.0.1:56156] AH00128: File does not 
>>>>> exist: /home/simamura/webapps/math_root/browserconfig.xml
>>>>>
>>>>>
>>>>> And that's all.
>>>>>
>>>>> On Sunday, February 15, 2015 at 10:11:25 AM UTC+2, Graham Dumpleton 
>>>>> wrote:
>>>>>>
>>>>>> Provide me with the logging from a period before the restart until a 
>>>>>> period after.
>>>>>>
>>>>>> The log can be very informative if you know what to look for.
>>>>>>
>>>>>> Graham
>>>>>>
>>>>>> On 15/02/2015, at 6:43 PM, Paul Royik <[email protected]> wrote:
>>>>>>
>>>>>> I actually have custom error 500 page. This means, that when Django 
>>>>>> throws error, custom page should be shown.
>>>>>> But it is not the case. Standard white-background apache page is 
>>>>>> shown.
>>>>>> So, I think that problem is not in Django exception. Otherwise Django 
>>>>>> would show custom page, which is not the case.
>>>>>> In logs I saw only that server was restarted.
>>>>>> Can I somehow tune logging, so that real error is written?
>>>>>>
>>>>>> On Sunday, February 15, 2015 at 2:44:50 AM UTC+2, Graham Dumpleton 
>>>>>> wrote:
>>>>>>>
>>>>>>>
>>>>>>> On 15/02/2015, at 10:53 AM, Paul Royik <[email protected]> wrote: 
>>>>>>>
>>>>>>> > I already tried this approach. 
>>>>>>> > 
>>>>>>> > It seems good. 
>>>>>>> > But when I tested it on server, by simultaneously executing page 
>>>>>>> on two different computers, it gave me 500 error. 
>>>>>>> > 
>>>>>>> > How this can be explained? Again something with apache? Logs 
>>>>>>> didn't show anything. But I noticed again serious memory usage. And 
>>>>>>> this 
>>>>>>> happens only when I use code for limiting time. 
>>>>>>>
>>>>>>>
>>>>>>> Some tips for you about ensuring you get the best help. 
>>>>>>>
>>>>>>> Stop discarding the message content for the message you are replying 
>>>>>>> to. It can be frustrating to have to keep going back to old messages to 
>>>>>>> see 
>>>>>>> what was said originally and what you may be following up to, 
>>>>>>> especially 
>>>>>>> when on a phone. When asking questions on mailing list, let the person 
>>>>>>> you 
>>>>>>> are asking questions of decide what can be discarded from the message 
>>>>>>> chain 
>>>>>>> as they will know better what should be kept in the message to provide 
>>>>>>> easy 
>>>>>>> access to important information for context. 
>>>>>>>
>>>>>>> When you reply to say you are have a new error, provide the actual 
>>>>>>> code you were using exactly at the time you had the error. Saves the 
>>>>>>> person 
>>>>>>> who is helping you having to go back and ask for it if it is unclear 
>>>>>>> what 
>>>>>>> code you were using. 
>>>>>>>
>>>>>>> Your messages here and on StackOverflow show that you play around 
>>>>>>> with the example code I am giving you and I have reduced confidence you 
>>>>>>> were running with the code I suggested at the time of the problem you 
>>>>>>> are 
>>>>>>> now relating to. 
>>>>>>>
>>>>>>> If you are getting 500 errors and nothing is being logged, it is 
>>>>>>> because Django is capturing the exception and converting it to a 
>>>>>>> generic 
>>>>>>> 500 error response page. Configure Django to send you emails with the 
>>>>>>> details of the exceptions. If you are on a local system, then set 
>>>>>>> DEBUG=True in the Django settings so the details of the error are shown 
>>>>>>> in 
>>>>>>> response that goes back to the browser. 
>>>>>>>
>>>>>>> As to the code, I did test it this time, including under mod_wsgi 
>>>>>>> with 20 request threads and hitting it with concurrent and successive 
>>>>>>> requests with a benchmarking tool. I saw no issues and it appeared to 
>>>>>>> behave as I would expect. 
>>>>>>>
>>>>>>> So in a test2.py file I had: 
>>>>>>>
>>>>>>> import time 
>>>>>>> import functools 
>>>>>>> import threading 
>>>>>>>
>>>>>>> def time_limit(seconds): 
>>>>>>>     def decorator(func): 
>>>>>>>         func.info = threading.local() 
>>>>>>>         def check_timeout(): 
>>>>>>>             if time.time() > func.info.end_time: 
>>>>>>>                 raise RuntimeError('timeout') 
>>>>>>>
>>>>>>>         func.check_timeout = check_timeout 
>>>>>>>
>>>>>>>         @functools.wraps(func) 
>>>>>>>         def wrapper(*args, **kwargs): 
>>>>>>>             print 'hasattr counter', hasattr(func.info, 'counter') 
>>>>>>>             if not hasattr(func.info, 'counter'): 
>>>>>>>                 print 'init counter to 0' 
>>>>>>>                 func.info.counter = 0 
>>>>>>>             if func.info.counter == 0: 
>>>>>>>                 func.info.end_time = time.time() + seconds 
>>>>>>>             print 'counter', func.info.counter 
>>>>>>>             func.info.counter += 1 
>>>>>>>             try: 
>>>>>>>                 return func(*args, **kwargs) 
>>>>>>>             finally: 
>>>>>>>                 func.info.counter -= 1 
>>>>>>>
>>>>>>>         return wrapper 
>>>>>>>
>>>>>>>     return decorator 
>>>>>>>
>>>>>>> @time_limit(5) 
>>>>>>> def algorithm(limit, nest=0): 
>>>>>>>     algorithm.check_timeout() 
>>>>>>>     print 'sleep' 
>>>>>>>     time.sleep(1.0) 
>>>>>>>     if nest == limit: 
>>>>>>>         print 'return' 
>>>>>>>         return 
>>>>>>>     algorithm(limit, nest+1) 
>>>>>>>
>>>>>>> In serial2.py I had a straight serialised test: 
>>>>>>>
>>>>>>> from test2 import algorithm 
>>>>>>>
>>>>>>> try: 
>>>>>>>     algorithm(3) 
>>>>>>> except RuntimeError: 
>>>>>>>     print 'timeout' 
>>>>>>>
>>>>>>> try: 
>>>>>>>     algorithm(10) 
>>>>>>> except RuntimeError: 
>>>>>>>     print 'timeout' 
>>>>>>>
>>>>>>> try: 
>>>>>>>     algorithm(10) 
>>>>>>> except RuntimeError: 
>>>>>>>     print 'timeout' 
>>>>>>>
>>>>>>> And then in hello2.wsgi I had it used by a WSGI application. 
>>>>>>>
>>>>>>> from test2 import algorithm 
>>>>>>>
>>>>>>> def application(environ, start_response): 
>>>>>>>     status = '200 OK' 
>>>>>>>     output = b'Hello World!' 
>>>>>>>
>>>>>>>     algorithm(1) 
>>>>>>>
>>>>>>>     response_headers = [('Content-type', 'text/plain'), 
>>>>>>>                         ('Content-Length', str(len(output)))] 
>>>>>>>     start_response(status, response_headers) 
>>>>>>>
>>>>>>>     return [output] 
>>>>>>>
>>>>>>> In the latter case I ran mod_wsgi-express against it as: 
>>>>>>>
>>>>>>> mod_wsgi-express start-server hello2.wsgi --port 8002 --threads=20 
>>>>>>>
>>>>>>> and then hit it with ab as: 
>>>>>>>
>>>>>>> ab -n 100 -c 15 http://localhost:8002/ 
>>>>>>>
>>>>>>> In this case it wasn't designed to timeout anything, but that should 
>>>>>>> not be a concern as the counter initialisation is still being tested. 
>>>>>>>
>>>>>>> Do note that if you did cut and paste that last code, I did change 
>>>>>>> the exception type. 
>>>>>>>
>>>>>>> Anyway, the best thing to do is setup Django so that it provides the 
>>>>>>> details of the exception it captured but then effectively discarded 
>>>>>>> because 
>>>>>>> it converted it to a 500 page. 
>>>>>>>
>>>>>>
>>>>>
>>>> -- 
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>>>>
>>>>
>>>>
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