duck typing assert

Andriy Kornatskyy andriy.kornatskyy at live.com
Thu Nov 8 20:29:10 CET 2012


Ian,

Thank you for the comments.

There is definitely a room for improvement, however there are limits. One of them is related to decorator that replaces decorated method arguments with something like *args, **kwargs. Here is an example.

def x():
    def decorate(m):
        def x(*args, **kwargs):
            pass
        return x
    return decorate

class Foo(object):

    @x
    def bar(self, a):
        pass

Another one challenge is related to inheritance, or even more complex case: multiple inheritance. I do not believe there is a need to scan whole hierarchy, better apply checks separately, the assert will be more readable.

class IFoo(object):
    def foo(self):
        pass

class IBar(IFoo):
    def bar(self):
        pass

class Bar(IBar):
    def foo(self):
        pass

    def bar(self):
        pass

assert looks(Bar).like(IBar)
assert looks(Bar).like(IFoo)


I agree, special methods __?__ should not be considered private... but what is right: know which one are special (how about some custom? e.g. __ctx__) or enforce check for it by explicitly asking for such check?

# 1
assert looks(Foo).like(IFoo, notice=['__len__'])
# 2
assert looks(Foo, notice=['__len__']).like(IFoo)

I believe if IFoo.foo is decorated as property, it must remain property, otherwise you need exclude it from checks, thus this way you pay code reviewer attention to that.

Thanks.

Andriy Kornatskyy


----------------------------------------
> From: ian.g.kelly at gmail.com
> Date: Thu, 8 Nov 2012 11:34:45 -0700
> Subject: Re: duck typing assert
> To: python-list at python.org
>
> On Thu, Nov 8, 2012 at 10:30 AM, Andriy Kornatskyy
> <andriy.kornatskyy at live.com> wrote:
> >
> > People who come from strongly typed languages that offer interfaces often are confused by lack of one in Python. Python, being dynamic typing programming language, follows duck typing principal. It can as simple as this:
> >
> > assert looks(Foo).like(IFoo)
> >
> > The post below shows how programmer can assert duck typing between two Python classes:
> >
> > mindref.blogspot.com/2012/11/python-duck-typing-assert.html
> >
> > Comments or suggestions are welcome.
>
> Overall, it looks potentially useful to me. Looking over the
> wheezy.core.introspection source, it appears to ignore special method
> names. For example, if you do:
>
> class IFoo(object):
> def __len__(self):
> pass
>
> class Foo(object):
> pass
>
> assert looks(Foo).like(IFoo)
>
> I would expect this to fail, but judging from the code it would not,
> as it ignores all names starting with '_'. That makes some sense for
> private names (but on the other hand, why would you declare private
> names in an interface unless you want to enforce their presence?), but
> names like __len__ should not be considered private.
>
> Another comment I have is on properties, and descriptors in general.
> Does this allow something declared as a property to be implemented as
> a simple class attribute, and vice versa? Or can something declared
> as a property be implemented with some custom descriptor class? I
> think the answer is "no" to both, as the check it performs is
> "t2.__class__ is not t.__class__". I assert though that in general
> the type of a descriptor (that is not a simple class attribute) is not
> as important in duck testing as its API -- and all descriptors have
> basically the same API of __get__, __set__, and __delete__.
> --
> http://mail.python.org/mailman/listinfo/python-list
 		 	   		  


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