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 <[EMAIL PROTECTED]>
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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