On Tue, 20 Oct 2009 14:45:49 -0700, Zac Burns wrote: > My preference would be that failIfEqual checks both != and ==. This is > practical, and would benefit almost all use cases. If "!=" isn't "not > ==" (IEEE NaNs I hear is the only known use case)
numpy uses == and != as element-wise operators: >>> import numpy >>> a = numpy.array([10, 20, 30, 40]) >>> b = numpy.array([10, 20, 31, 40]) >>> a==b array([ True, True, False, True], dtype=bool) >>> a!=b array([False, False, True, False], dtype=bool) >>> not a!=b Traceback (most recent call last): File "<stdin>", line 1, in <module> ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all() > then those could simply not use this method. I'm not so sure this is a good idea. Python specifically treats == and != as independent. There's no reason to think that a class must have both, or that it's an error if it defines == without !=, or even that they are reflections of each other. numpy doesn't, and that's a pretty huge counter-example. > It would not surprise me if changing this would bring to light many > existing bugs. It would surprise me. -- Steven -- http://mail.python.org/mailman/listinfo/python-list
