[Numpy-discussion] Making NumPy accessible to everyone (or no-one) (was Numpy-discussion Digest, Vol 19, Issue 44)
Fri Apr 11 03:57:31 CDT 2008
On Thu, Apr 10, 2008 at 3:55 AM, Stéfan van der Walt <firstname.lastname@example.org>
> Hi Joe, all
> On 10/04/2008, Joe Harrington <email@example.com> wrote:
> > > Absolutely. Let's please standardize on:
> > > import numpy as np
> > > import scipy as sp
> > I hope we do NOT standardize on these abbreviations. While a few may
> > have discussed it at a sprint, it hasn't seen broad discussion
Valid point... Travis did a wonderful job of summarizing that sprint and
posting to the list. However, the N vs. np discussion was missed.
> Namespaces throttle the amount of information with which the user is
> presented, and well thought through design leads to logical, intuitive
> segmentation of functionality.
> > Namespaces add characters to code that have a high redundancy factor.
> > This means they pollute code, make it slow and inaccurate to read, and
> > making learning harder. Lines get longer and may wrap if they contain
> > several calls. It is harder while visually scanning code to
> > distinguish the function name if it's adjacent to a bunch of other
> > text, particularly if that text appears commonly in the nearby code.
I think namespaces are one of the crown-jewels that make python more
attractive to scientists (not programmers) over Matlab. Even if they don't
realize it yet. :)
I think a lot of researchers would spend less time debugging their code if
they were using python with namespaces instead of adding this:
in all of their Matlab code! Or other path manipulation.
We certainly need a better discover mechanism for users to find functions
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