[issue26827] PyObject *PyInit_myextention -> PyMODINIT_FUNC PyInit_myextention

2016-04-22 Thread Herbert
Herbert added the comment: The exact error was: ImportError: dynamic module does not define init function (PyInit_myextension) -- ___ Python tracker <rep...@bugs.python.org> <http://bugs.python.org/i

[issue26827] PyObject *PyInit_myextention -> PyMODINIT_FUNC PyInit_myextention

2016-04-22 Thread Herbert
New submission from Herbert: I think PyObject *PyInit_myextention(void) should be PyMODINIT_FUNC PyInit_myextention(void) on https://docs.python.org/3/howto/cporting.html#module-initialization-and-state It didn't work for me until I replaced this with a message in the about 'undefined

[issue25465] Pickle uses O(n) memory overhead

2015-11-09 Thread Herbert
Herbert added the comment: It may be fair to note that I have no swap installed on one of the machines, just 16GB of RAM, on which the 'crash' happens. Hence I'm not sure how this affects paging, I would think there is no paging if there is no swap. I can verify that the machine is 'stuck

[issue25465] Pickle uses O(n) memory overhead

2015-10-26 Thread Herbert
Herbert added the comment: Hi Eric, I would assume that for the right range-parameter (in my case 30 * 1000 ** 2), which just fits in memory, your system would also crash after a pickle.dump. That is, I had this behavior on two of my machine both running a Ubuntu setup though. Nevertheless

[issue25465] Pickle uses O(n) memory overhead

2015-10-25 Thread Herbert
Herbert added the comment: That sound reasonable regarding why O(n), but it does not explain why linux crashes (I've seen this on two ubuntu systems)if pickle runs out of memory. -- ___ Python tracker <rep...@bugs.python.org> <http://bugs.p

[issue25465] Pickle uses O(n) memory overhead

2015-10-23 Thread Herbert
Changes by Herbert <python-b...@prinsherbert.nl>: -- type: -> performance versions: +Python 3.4 ___ Python tracker <rep...@bugs.python.org> <http://bugs.pyt

[issue25465] Pickle uses O(n) memory overhead

2015-10-23 Thread Herbert
New submission from Herbert: I very often want to use pickle to store huge objects, such that I do not need to recalculate them again. However, I noticed that pickle uses O(n) (for n the object size in memory) amount of memory. That is, using python 3: data = {'%06d' % i: i for i