python philosophical question - strong vs duck typing
88888 Dihedral
dihedral88888 at googlemail.com
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:
> >> http://codepad.org/eLr7lLJd ]
> >
> > 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
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