[Numpy-discussion] Created NumPy 1.7.x branch
fperez.net at gmail.com
Mon Jun 25 22:38:24 EDT 2012
On Mon, Jun 25, 2012 at 6:39 PM, Travis Oliphant <travis at continuum.io> wrote:
> On Jun 25, 2012, at 7:21 PM, Fernando Perez wrote:
> For context, consider that for many years, the word "gratuitous" has been used in a non-derogatory way in the Python ecosystem to describe changes to semantics and syntax that don't have benefits significant enough to offset the pain it will cause to existing users. That's why I used the word. I am not trying to be derogatory. I am trying to be clear that we need to respect existing users of NumPy more than we have done from 1.5 to 1.7 in the enthusiasm to make changes.
For reference, here's the (long) thread where this came to be:
It's worth noting that at the time, the discussion was for an addition
to *scipy*, not to numpy. I don't know when things were moved over to
> Working on the NumPy code base implies respecting the conventions that are already in place --- not just disregarding them and doing whatever we want. I'm not really sure why I have to argue the existing users point of view so much recently. I would hope that all of us would have the perspective that the people who have adopted NumPy deserve to be treated with respect. The changes that grate on me are the ones that seem to take lightly existing users of NumPy.
I certainly appreciate the need to not break user habits/code, as we
struggle with the very same issue in IPython all the time. And
obviously at this point numpy is 'core infrastructure' enough that
breaking backwards compatibility in any way should be very strongly
discouraged (things were probably a bit different back in 2009).
>> 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.
> I'm trying very hard to be fair --- especially to changes like this. What grates me are changes that affect our user base in a negative way --- specifically by causing code that used to work to no longer work or create alterations to real conventions. This kind of change is just not acceptable if we can avoid it. I'm really trying to understand why others do not feel so strongly about this, but I'm not persuaded by what I've heard so far.
I just want to note that I'm not advocating for *any*
backwards-compatibility breakage in numpy at this point... I was just
providing context for a discussion that happened back in 2009, and in
the scipy list. I certainly feel pretty strongly at this point about
the importance of preserving working code *today*, given the role of
numpy at the 'root node' of the scipy ecosystem tree and the size of
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