On 2013-06-13, dieter wrote: >> ... Anyway, my real question is how to go about debugging memory leak >> problems in Python, particularly for a long running server process >> written with Twisted. I'm not sure how to use heapy or guppy, and >> objgraph doesn't tell me enough to locate the problem. > > Analysing memory leaks is really difficult: huge amounts of data is > involved and usually, it is almost impossible to determine which of the > mentioned objects are leaked and which are rightfully in use. In > addition, long running Python processes usually have degrading memory > use - due to memory fragmentation. There is nothing you can do against > this. > > Therefore: if the leak seems to be small, it may be much more advicable > to restart your process periodically (during times where a restart does > not hurt much) rather than try to find (and fix) the leaks. Only when > the leak is large enough that it would force you to too frequent > restarts, a deeper analysis may be advicable (large leaks are easier to > locate as well).
Am I the only one who thinks this is terrible advice? -- Real (i.e. statistical) tennis and snooker player rankings and ratings: http://www.statsfair.com/ -- http://mail.python.org/mailman/listinfo/python-list
