python philosophical question - strong vs duck typing

88888 Dihedral dihedral88888 at
Sat Jan 7 10:43:56 EST 2012

Terry Reedy於 2012年1月5日星期四UTC+8上午4時22分03秒寫道:
> On 1/4/2012 1:37 AM, Terry Reedy wrote:
> > On 1/3/2012 8:04 PM, Devin Jeanpierre wrote:
> >> [ An example of a simple dependently typed program:
> >> ]
> >
> > Just got it after a minute delay.
> A followup now that I have read it. Removing the 40 line comment, the 
> function itself is
> fun getitem{n,m:nat}(arr : array(int, n) ,
>   length : int(n), index : int m) : int =
>      if index < length then
>          arr[index]
>      else
>          ~1 (* -1, error *)
> where n,m are compiler variables used to define the dependent 
> (paramaterized) types array(int,n) and int(n)/ The double use of n means 
> that the compiler checks that length n of the array equals the length 
> passed.
> My response: in Python, there is no need to pass concrete collection 
> sizes because they are packaged with the collection at runtime as an 
> attribute. So:
> 1) In Python, there is no need for such checking. In addition, the 
> for-loop construct, 'for item in iterable:', removes the possibility of 
> indexing errors.
> 2) Python classes are, in a sense, or in effect, runtime dependent 
> types. While the formal implementation type of a 'list' is just 'list', 
> the effective computation type is 'mutable sequence of length n'. The 
> type of an iterator is 'read-only sequence of indefinite length'. I find 
> this an interesting way to look at Python.

Also it is easy to turn an indexed object to be an iterator by a
function decorator that returns a generator in the object level 
without declaring a new class from a class written by others.

Thus this can lead to  a decoupled design of software among many contributors
in an elegant way.  

I prefer a factorized decoupled blocks of modules to be completed 
by several programmers to build a package.  

> -- 
> Terry Jan Reed

More information about the Python-list mailing list