Lisandro Dalcin wrote:
> Perhaps the reason for this is simple:
> few Python core developers are involved in scientific computing and do
> not have a clear idea of what it is needed for this.
Perhaps true, but.....
I imagine one of the issues that the python-dev crowd has is that they
don't want to add features solely for the scientific computing crowd.
Indeed, they don't need to. The features are there in numpy, everyone
who uses numpy has access to them.
The reason I want to have these features in the standard library is that
there are a lot of good uses for them outside the scientific computing
community, and, in particular, for interaction between scientific
computing and more general purpose packages (GUI toolkits, Image
processing, web frameworks, who knows?)
Specifically, this is useful stuff for exchanging data with PIL,
wxPython (two specific uses I have), and Matplotlib could really use it
with all of its back-ends (TK, GTK, QT, etc....).
In addition, I don't think it's on the table at the moment, but an n-d
array has a lot of use well outside of number crunching. I've introduced
a handful of users to numpy just to get access to a nice n-d object
array type for completely no-numeric uses.
Off to go post on python-dev.....
-Chris
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Christopher Barker, Ph.D.
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