[SciPy-dev] Best ways to set default values consistent within a module

[David Cournapeau]

Francesc Altet wrote:
> El ds 09 de 06 del 2007 a les 19:46 +0900, en/na David Cournapeau va
> escriure:
>> Hi,
>>
>>     I have a question concerning default values for scipy functions. 
>> Basically, I have a class which have a significant number of function, 
>> several private, several private, and they provide different levels of 
>> the same functionality, with similar arguments with default values.
>>
>> class foo:
>>     def foo1(level = def1, dim = def2):
>>        pass
>>     def foo2(level = def1, dim = def2):
>>        pass
>>    
>> What is the best way to maintain the default values consistent ? What I 
>> do for now is to set the default values from global variables; another 
>> way is to use the syntax *args, **kw, but I don't really like it myself, 
>> because then you do not know what the values when doing help foo.foo1 (I 
>> found this really annoying in matplotlib docstrings, for example).
>
> Well, if you can afford requiring Python 2.4 or higher in your
> application, one possibility is to use decorators.  For example,
> consider this:
>
> ------------------------- prova.py ---------------------------------
> def add_dflts():
>     def decorator(func):
>         def wrapper(hello, k=1, level="lvl1", dim=3):
>             return func(hello, k, level, dim)
>         wrapper.__name__ = func.__name__
>         wrapper.__dict__ = func.__dict__
>         wrapper.__doc__ = func.__doc__
>         return wrapper
>     return decorator
>
> @add_dflts()
> def test(hello, k, level, dim):
>     "Hello test"
>     print hello, k, level, dim
>
> test("Hello!", k=2)
> ---------------------------------------------------------------------
>
> Importing this on ipython gives:
>
> In [1]:import prova
> Hello! 2 lvl1 3
>
> So, the decorated test() function honors the defaults stated in the
> decorator.  Also, you can see how the doc string is conveniently updated
> as well:
>
> In [2]:prova.test?
> Type:           function
> Base Class:     <type 'function'>
> String Form:    <function test at 0xb76a341c>
> Namespace:      Interactive
> File:           /tmp/prova.py
> Definition:     prova.test(hello, k=1, level='lvl1', dim=3)
> Docstring:
>     Hello test
Mm. how is this different than "classic" function factory ? Depending on 
2.4 features is a no-no anyway, because this code is meant to be used in 
scipy. Well, I will think about using function generators, but this 
sounds a bit overkill for what I want to do.

>
> As Phillip Eby says in www.ddj.com/184406073  (a strongly recommended
> read):
>
Argh, it made me realize that I was using some python2.4 specific 
features in my code already :)

cheers,

David