New submission from Sebastian Berg: In NumPy we decided some time ago that if you have a multi dimensional buffer, shaped for example 1x10, then this buffer should be considered both C- and F-contiguous. Currently, some buffers which can be used validly in a contiguous fashion are rejected.
CPython does not support this currently possibly creating smaller nuisance if/once we change it fully in NumPy, see for example https://github.com/numpy/numpy/issues/5085 I have attached a patch which should (sorry I did not test this at all yet) relax the checks as much as possible. I think this is right, but we did some subtle breaks in user code (mostly cython code) when we first tried changing it, and while numpy arrays may be more prominently C/F-contiguous, compatibility issues with libraries checking for contiguity explicitly and then requesting a strided buffer are very possible. If someone could give me a hint about adding tests, that would be great. Also I would like to add a small note to the PEP in any case regarding this subtlety, in the hope that more code will take care about such subtleties. ---------- components: Library (Lib) files: relaxed-strides-checking.patch keywords: patch messages: 227113 nosy: seberg priority: normal severity: normal status: open title: Memoryviews require more strict contiguous checks then necessary type: enhancement Added file: http://bugs.python.org/file36663/relaxed-strides-checking.patch _______________________________________ Python tracker <rep...@bugs.python.org> <http://bugs.python.org/issue22445> _______________________________________ _______________________________________________ Python-bugs-list mailing list Unsubscribe: https://mail.python.org/mailman/options/python-bugs-list/archive%40mail-archive.com
