oliphant at ee.byu.edu
Fri Feb 4 14:32:06 EST 2005
>> O.K. I can see that there are several out there who belive that
>> SciPy is sufficiently hard to install that they are concerned about
>> requiring it for their math-using packages (despite the provided
>> binary distributions, and the work that continues on making it easier
>> to install). I'm
> This sort of leads back to the original point, that is, putting
> something in the Python Standard Library. I suspect that for most
> scientists and engineers if they have to install anything extra at all
> to use arrays practially, they really don't care if it is in the core
> or not. The current Numeric (or numarray) is a fairly straightforward
> install now and if the issue is having users avoid this extra install,
> putting a reduced functionality array package in the core is not going
> to address this issue. On the other hand, it is likely to have the
> general Python community more likely to use arrays as an interchange
> format, which is a separate benefit (a point I stressed at the last
> scipy conference).
As Perry suggested, I personally don't care whether it is in the Python
core or not. The only reason I ever wanted to put it into the core is
because of the PIL. When I asked the creator of the PIL, why he did not
use Numeric Python, his response was that it wasn't in the core.
Right now, I think we would benefit if the basic multidimensional array
object were in the core. It would be nicer if we could agree on how
basic operations were to behave so math could be done with them, and put
that in there as well.
Perry makes a great point about the benefit of using arrays as an
interchange format... There are people out there who use the array
object in Python for just that. It would be great if there was one
multidimensional array object used by the entire Python community for
applications requiring such a structure, but it wouldn't remove the need
for "more stuff" to do science and so my interest in getting such an
object into the Python core has waned considerably over the years.
I'm more interested now in uniting a fractured community (or at least
making interoperability easier).
More information about the NumPy-Discussion