You would like pypy+numpy+scipy so that you could write fast
python-only algorithms and still use the existing libraries. I
suppose this is a perfectly reasonable usecase, and indeed
the current plan does not focus on this.
Yes. That is exactly what I want.
However, I'd like to underline that to write fast python-only algorithms,
you most probably still need a fast numpy in the way it is written right now
(unless you want to write your algorithms without using numpy at all)
I make very little use of numpy itself other than as the way to use scipy; I
tend to write python-only algorithms that don't use numpy. As Peter Cock says
in his own reply, a little bit of slowdown in regular numpy use compared to
CPython would be fine, though a LOT of slowdown could be a problem.
Now, I'm not saying I'm typical. I have no idea how typical I am, though it
sounds like Peter Cock is in a similar boat. I'm sure I'd benefit from doing
more with numpy. But I simply cannot do without scipy, or accessing equivalent
functionality by using R or another package. I'd much rather use scipy and see
its capabilities grow than use R.
From my own bias, I'd assume that what would benefit the scientific community
most is scipy integration first, and a faster numpy second. Scipy simply
provides too many tools that are absolutely essential.
The project for providing a common interface to IronPython, etc. sounded
extremely promising in that regard -- it makes enormous sense to me that all
different versions of python should have a way to access scipy, even if custom
code that uses numpy is a little bit slower. My main concern is that the glue
to frequently-called scipy functions such as scipy.stats.stats.chisqprob
wouldn't be so much slower that my overall script isn't benefiting from PyPy.
Obviously, I understand that this is an open-source project and people develop
what they are interested in. I'm just giving my individual perspective, for
whatever it may be worth.
--
Gary Robinson
CTO
Emergent Discovery, LLC
personal email: gary...@me.com
work email: grobin...@emergentdiscovery.com
Company: http://www.emergentdiscovery.com
Blog:http://www.garyrobinson.net
On Oct 19, 2011, at 7:57 AM, Antonio Cuni wrote:
On 19/10/11 13:42, Antonio Cuni wrote:
I'm not sure to interpret your sentence correctly.
Are you saying that you would still want a pypy+numpy+scipy, even if it ran
things slower than CPython? May I ask why?
ah sorry, I think I misunderstood your email.
You would like pypy+numpy+scipy so that you could write fast python-only
algorithms and still use the existing libraries. I suppose this is a
perfectly reasonable usecase, and indeed the current plan does not focus on
this.
However, I'd like to underline that to write fast python-only algorithms,
you most probably still need a fast numpy in the way it is written right now
(unless you want to write your algorithms without using numpy at all). If we
went to the slow-but-scipy-compatible approach, any pure python algorithm
which interfaces with numpy arrays would be terribly slow.
ciao,
Anto
___
pypy-dev mailing list
pypy-dev@python.org
http://mail.python.org/mailman/listinfo/pypy-dev
