Generators.

[Lie Ryan]

On 12/7/2009 7:22 AM, Jorge Cardona wrote:
> Hi,
>
> I was trying to create a function that receive a generator and return
> a list but that each elements were computed in a diferent core of my
> machine. I start using islice function in order to split the job in a
> way that if there is "n" cores each "i" core will compute the elements
> i,i+n,i+2n,..., but islice has a weird (to me) behavior, look:

it's nothing weird, python just do what you're telling it to:

transform all x in X with f(x)
> g = (f(x) for x in X)
then slice the result of that
> print(list(x for x in islice(g,0,None,2)))

what you want to do is to slice before you transform:
 >>> g = (x for x in islice(X, 0, None, 2))
 >>> print(list(f(x) for x in g))
eval: 0
eval: 2
eval: 4
eval: 6
eval: 8
[0, 2, 4, 6, 8]

> islice execute the function at the generator and drop the elements
> that aren't in the slice. I found that pretty weird, the way that i
> see generators is like an association between and indexing set (an
> iterator or another generator) and a computation that is made indexed
> by the indexing set, and islice is like a "transformation" on the
> indexing set,it doesn't matter the result of the function, the slice
> should act only on the indexing set, some other "transformation" like
> takewhile act on the result so, the execution it has to be made, but
> in the islice, or other "transformation" that act only in the indexing
> set, the function shouldn't be executed at each element, but only on
> that new set that result of the application of the "transformation" on
> the original set.

that seems like an extremely lazy evaluation, I don't know if even a 
true lazy language do that. Python is a strict language, with a few 
laziness provided by generators, in the end it's still a strict language.

> Well, it works for what i need, but is not very neat, and i think that
> there it should be a formal way to act on the base indexing iterator,
> such way exists? Is there a better approach to get what i need?

Reverse your operation.