Dynamically determine base classes on instantiation

Thomas Bach thbach at students.uni-mainz.de
Thu Aug 16 14:52:30 CEST 2012

On Thu, Aug 16, 2012 at 12:16:03AM +0000, Steven D'Aprano wrote:
> Some comments:
> 1) What you show are not "use cases", but "examples". A use-case is a 
> description of an actual real-world problem that needs to be solved. A 
> couple of asserts is not a use-case.

Thanks for the clarification on that one. So, here's the use-case: I'm
querying the crunchbase API which returns JSON data and is rather
poorly documented. I want to create a data model for the companies
listed on Crunchbase in order to be able to put the queried data in a
data-base. As I am too lazy to examine all the data by hand I thought
I automatize this. I thought that it would be nice to be able to pass
a function a parsed JSON object (AFAIK these are lists, dicts,
strings, ints, floats, strs in Python) and it returns me the type of
these objects. For the simple classes (str, int, float) this is quite
trivial: F('foo') should return `str' and F(8) should return `int'.

For a compound object like dict I would like it to return the data
fields with their type. Hence, F({'foo': 8}) should return 
{'foo': int}, and given that f = F({'foo': {'bar': 80}}) I would like
f to equal to {'foo': dict}, with the option to query the type of
'foo' via f.foo, where the latter should equal to {'bar': int}. So
far, this is not a complicated case. But, sometimes a data field on
returned data set is simply None. Thus, I want to extract the types from
another data set and merge the two.

So, my question (as far as I can see it, please correct me if I am
wrong) is less of the "How do I achieve this?"-kind, but more of the
"What is a clean design for this?"-kind. My intuitive thought was that
the `merge' function should be a part of the object returned from `F'.

> How about you tell us the problem, and we'll suggest a solution?

I can see your point. On the other hand, by expressing my thoughts you
can at least tell me that these are completely wrong and correct my
way of thinking this way.

> Consider your two examples:
> a = Foo(['a', 'list'])
> b = Foo({'blah': 8})
> According to your design:
> a is a Foo
> b is a Foo

I actually never said that. I simply wanted `a' and `b' to share the
same function (the `merge' function), I thought that the easiest way
to achieve this is by letting them share the same name-space. But, as
you show: …

> therefore a and b are the same type
> So far so good: this is perfectly normal object-oriented design.
> But you also have 
> a is a list, but not a dict
> b is a dict, but not a listn
> therefore a and b are different types
> So you contradict yourself: at the same time, a and b are both the same 
> and different types.

… I already made a mistake on the logical level.

> Instead, Foo should implement only the shared operations, and everything 
> else should be delegated to _obj.
> If you inherit from builtins, you cannot use automatic delegation on the 
> magic "double-underscore" (dunder) methods like __eq__, __len__, etc.
> See this thread here for one possible solution:
> http://www.velocityreviews.com/forums/t732798-automatic-delegation-in-python-3-a.html

OK, thanks for the hint. I will see how I'm going to put all this
stuff together.


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