I think I agree... cython support for decorators would probably be the
best approach.

On Sat, Jun 21, 2008 at 11:51 AM, Dag Sverre Seljebotn
<[EMAIL PROTECTED]> wrote:
> rahul garg wrote:
>> On Sat, Jun 21, 2008 at 12:28 PM, Stefan Behnel <[EMAIL PROTECTED]>
>> wrote:
>>
>>> Hi,
>>>
>>> rahul garg wrote:
>>> > I was thinking of providing a "prange" which defaults to xrange when
>>> running
>>> > on interpreter.
>>> > The reason I like the prange construct, is that we can easily add lets
>>> say
>>> > thread-local variables or reduction variables.
>>> > for i in prange(i, threadlocal=[myvar1,myvar2],reduction=[red1,red2]):
>>> #loop
>>> > body
>>>
>>> You could easily do that with a
>>>
>>>    with thread_each(iterable, threadlocal=...):
>>>        ...
>>>
>>> syntax, too, and IMHO it looks much better (minus a better name for
>>> "thread_each" ;)
>>>
>>> And it might even be possible to support this in plain Python one day.
>>
>>
>> Well the problem is that how does it run as a loop on the interpreter?
>> If its to run as a loop on the interpreter, there must be a loop statement
>> somewhere potentially.
>> What about adopting it to :
>> for i in thread_each(iterator,threadlocal=...):
>>
>> This is uglier than with thread_each() but has a simple serial
>> implementation.
>> Thoughts?
>
> Jumping into this thread at a random spot...
>
> In dev1 days for SAGE a @parallel decorator for functions was
> demonstrated. So:
>
> P> @parallel
> P> def f(x): return 2*x
> ...
> P> f([1,2,3])
> [2, 4, 6]
>
> Where each of the multiplications would happen in parallel using
> PyProcessing. However, I don't think any Cython support is really needed
> for this (except for decorator support :-)).
>
> So: I like PyProcessing but there's no need to build anything into Cython
> for that. A parallel decorator could work for OpenMP though (at least if
> the function is also declared inline etc.)
>
> Dag Sverre
>
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