New submission from Martin Panter: Revision 32bfc81111b6 added test.test_random.MersenneTwister_TestBasicOps.test_choices_algorithms(), which runs the following code:
n = 13132817 # 13 million self.gen.choices(range(n), [1]*n, k=10000) When I build Python with the “--with-pydebug” configure option on x86-64 Linux, this call uses over 1.2 GB of memory. My computer only has 2 GiB, so it tends to slow down the whole operating system and/or trigger Linux’s out-of-memory killler. Especially if other tests are run concurrently. Is it practical to reduce the magnitude of the test parameters, or optimize the implementation to use less memory? If not, perhaps we could hook into the mechanism that other tests use when the allocate large blocks of memory, to cause them to be skipped in low-memory situations. ---------- components: Tests messages: 281185 nosy: martin.panter, rhettinger priority: normal severity: normal status: open title: test_choices_algorithms() in test_random uses lots of memory type: resource usage versions: Python 3.6, Python 3.7 _______________________________________ Python tracker <rep...@bugs.python.org> <http://bugs.python.org/issue28743> _______________________________________ _______________________________________________ Python-bugs-list mailing list Unsubscribe: https://mail.python.org/mailman/options/python-bugs-list/archive%40mail-archive.com
