[Numpy-discussion] Created NumPy 1.7.x branch
Mon Jun 25 19:21:31 CDT 2012
On Mon, Jun 25, 2012 at 5:10 PM, Travis Oliphant <email@example.com> wrote:
> You are still missing the point that there was already a choice that was
> made in the previous class --- made in Numeric actually.
> You made a change to that. It is the change that is 'gratuitous'.
As someone who played a role in that change (by talking with Chuck
about it, I didn't do the actual hard work), I'd like to pitch in.
I think it's unfair to use the word gratuitous here, which is defined as:
Uncalled for; lacking good reason; unwarranted.
It is true that the change happened to not consider enough the reasons
that existed for the previous state of affairs, but it's *not* true
that there were no good reasons for it. Calling something gratuitous
is fairly derogatory, as it implies that it was done without any
thinking whatsoever, and that was most certainly not the case here.
It was a deliberate and considered change for what were *thought* to
be good reasons.
It's possible that, had there been feedback from you at the time,
those reasons would have been appreciated as not being sufficient to
make the change, or that a different solution would have been arrived
But to say that there were no good reason is unfair to those who did
spend the time thinking about the problem, and who thought the reasons
they had found were indeed good ones.
That particular issue was simply one of the best examples of what
happens in a project when there are not enough eyes to provide
feedback on its evolution: even with the best intentions, the few
doing the work may make changes that might not have gone through with
more input from others. But the alternative was to paralyze numpy
completely, which I think would have been a worse outcome.
I know that this particular issue grates you quite a bit, but I urge
you to be fair in your appreciation of how it came to be: through the
work of well-intentioned and thoughtful (but not omniscient) people
when you weren't participating actively in numpy development.
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