Hi,
Does anyone know how to use __metaclass__ specification alongside
inheritance from boost python classes? This code illustrates the problem:
import abc
> from scitbx.lstbx import normal_eqns
>
class Refinery(object):
> __metaclass__ = abc.ABCMeta
> pass
>
class AdaptLstbx(Refinery, normal_eqns.non_linear_ls):
> pass
The result is
Traceback (most recent call last):
> File "<stdin>", line 1, in <module>
> File "/usr/lib/python2.7/abc.py", line 87, in __new__
> cls = super(ABCMeta, mcls).__new__(mcls, name, bases, namespace)
> TypeError: Error when calling the metaclass bases
> metaclass conflict: the metaclass of a derived class must be a
> (non-strict) subclass of the metaclasses of all its bases
The real Refinery is a class that has one method that must be supplied by a
concrete subclass. I like the idea of making it impossible to instantiate a
base Refinery rather than relying on e.g. raise NotImplementedError() in
that method definition. This is what ABCMeta would give me, if only I could
get it to work here. Google found me some answers that require me to know
the __metaclass__ of the bases (as suggested by the error message),
but normal_eqns.non_linear_ls.__metaclass__ does not exist.
I don't terribly mind the raise NotImplementedError() alternative, but I
thought that if I can easily use ABCMeta, I'd like to.
Cheers
-- David
