Stefan Krah added the comment: We overlooked one thing. Since hashing is defined in terms of tobytes(), the equality-hash invariant is now broken:
>>> from _testbuffer import ndarray >>> x = ndarray([1,2,3], shape=[3], format='f') >>> y = ndarray([1,2,3], shape=[3], format='B') >>> a = memoryview(x) >>> b = memoryview(y) >>> a == b True >>> hash(a) == hash(b) False >>> This is one problem with the new equality definition. It puts "memoryview" firmly into array territory. I'm not saying that's wrong, I even think it was the intention of the PEP authors to have a zero copy "arrayview". Both array.array and numpy.array sidestep the issue by not being hashable. I don't really see a way around all this except doing slow element-wise hashing. ---------- resolution: fixed -> status: closed -> open _______________________________________ Python tracker <rep...@bugs.python.org> <http://bugs.python.org/issue15573> _______________________________________ _______________________________________________ Python-bugs-list mailing list Unsubscribe: http://mail.python.org/mailman/options/python-bugs-list/archive%40mail-archive.com
