Re: Addition of "pyprocessing" module to standard lib.

The inclusion of the processing module does not exclude the potential  
to also use or one day include MPI bindings.

The goal is to add a module with a "known" API and semantics which  
allows programmer using cPython to easily take advantage of multple  
cores  (and as a side benefit, machines).

In theory - one could also use MPI within an application using the  
processing module as a communications/message passing system.

-Jesse

On May 13, 2008, at 9:23 PM, Tom Pinckney <thomaspinckney3 <at> gmail.com>  
wrote:

> Why not use MPI? It's cross platform, cross language and very widely  
> supported already. And there're Python bindings already.
>
> On May 13, 2008, at 8:52 PM, Jesse Noller wrote:
>
>> I am looking for any questions, concerns or benchmarks python-dev has
>> regarding the possible inclusion of the pyprocessing module to the
>> standard library - preferably in the 2.6 timeline.  In March, I began
>> working on the PEP for the inclusion of the pyprocessing (processing)
>> module into the python standard library[1]. The original email to the
>> stdlib-sig can be found here, it includes a basic overview of the
>> module:
>>
>> http://mail.python.org/pipermail/stdlib-sig/2008-March/000129.html
>>
>> The processing module mirrors/mimics the API of the threading  
>> module -
>> and with simple import/subclassing changes depending on the code,
>> allows you to leverage multi core machines via an underlying forking
>> mechanism. The module also supports the sharing of data across groups
>> of networked machines - a feature obviously not part of the core
>> threading module, but useful in a distributed environment.
>>
>> As I am trying to finish up the PEP, I want to see if I can address
>> any questions or include any other useful data (including benchmarks)
>> in the PEP prior to publishing it. I am also intending to include
>> basic benchmarks for both the processing module against the threading
>> module as a comparison.
>>
>> -Jesse
>>
>> [1] Processing page: http://pyprocessing.berlios.de/
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