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On Sat, Feb 14, 2015 at 2:36 PM, Georg Brandl <g.brandl@gmx.net> wrote:

> In the case of int, there is a good reason for this behavior - bool. In python,
\> we want True + True == 2\. In numpy, where binary operations preserve
\> subclasses, you have
\>
\>>>> import numpy
\>>>> numpy.bool\_(1) + numpy.bool\_(1)
\> True

I don't think numpy.bool\_ subclasses some class like numpy.int\_.

And numpy.bool\_ subclasses don't preserve type in addition:

>>> import numpy

>>> class Bool(numpy.bool\_):

... pass

...

>>> numpy.bool\_.mro()

\[, , \]

>>> Bool(1) + Bool(1)

True

>>> type(\_)

So there goes my theory. :-)

I think all these examples just highlight the need for a clear guidance when self.\_\_class\_\_() can be called in base classes to construct instances of derived classes.

Apparently numpy has it both ways. One way for scalars (see above) and the other for arrays:

>>> class Array(numpy.ndarray):

... pass

...

>>> a = Array(1)

>>> a\[0\] = 1

>>> a+a

Array(\[ 2.\])