[Numpy-discussion] Should arr.diagonal() return a copy or a view? (1.7 compatibility issue)
Dag Sverre Seljebotn
d.s.seljebotn at astro.uio.no
Wed May 23 16:01:36 EDT 2012
On 05/23/2012 10:00 PM, Dag Sverre Seljebotn wrote:
> On 05/23/2012 07:29 PM, Travis Oliphant wrote:
>>
>> On May 23, 2012, at 8:02 AM, Olivier Delalleau wrote:
>>
>>> 2012/5/23 Nathaniel Smith<njs at pobox.com<mailto:njs at pobox.com>>
>>>
>>> On Wed, May 23, 2012 at 6:06 AM, Travis Oliphant
>>> <travis at continuum.io<mailto:travis at continuum.io>> wrote:
>>> > I just realized that the pull request doesn't do what I thought
>>> it did which
>>> > is just add the flag to warn users who are writing to an array
>>> that is a
>>> > view when it used to be a copy. It's more cautious and also
>>> "copies" the
>>> > data for 1.7.
>>> >
>>> > Is this really a necessary step? I guess it depends on how many
>>> use-cases
>>> > there are where people are relying on .diagonal() being a copy.
>>> Given that
>>> > this is such an easy thing for people who encounter the warning
>>> to fix their
>>> > code, it seems overly cautious to *also* make a copy (especially
>>> for a rare
>>> > code-path like this --- although I admit that I don't have any
>>> reproducible
>>> > data to support that assertion that it's a rare code-path).
>>> >
>>> > I think we have a mixed record of being cautious (not cautious
>>> enough in
>>> > some changes), but this seems like swinging in the other
>>> direction of being
>>> > overly cautious on a minor point.
>>>
>>> The reason this isn't a "minor point" is that if we just switched it
>>> then it's possible that existing, working code would start returning
>>> incorrect answers, and the only indication would be some console spew.
>>> I think that such changes should be absolutely verboten for a library
>>> like numpy. I'm already paranoid enough about my own code!
>>>
>>> That's why people up-thread were arguing that we just shouldn't risk
>>> the change at all, ever.
>>>
>>> I admit to some ulterior motive here: I'd like to see numpy be able to
>>> continue to evolve, but I am also, like I said, completely paranoid
>>> about fundamental libraries changing under me. So this is partly my
>>> attempt to find a way to make a potentially "dangerous" change in a
>>> responsible way. If we can't learn to do this, then honestly I think
>>> the only responsible alternative going forward would be to never
>>> change any existing API except in trivial ways (like removing
>>> deprecated functions).
>>>
>>> Basically my suggestion is that every time we alter the behaviour of
>>> existing, working code, there should be (a) a period when that
>>> existing code produces a warning, and (b) a period when that existing
>>> code produces an error. For a change like removing a function, this is
>>> easy. For something like this diagonal change, it's trickier, but
>>> still doable.
>>>
>>>
>>> /agree with Nathaniel. Overly cautious is good!
>>>
>>
>> Then are you suggesting that we need to back out the changes to the
>> casting rules as well, because this will also cause code to stop
>> working. This is part of my point. We are not being consistently cautious.
>
> Two wrongs doesn't make one right?
>
> I'd think the inconvenience to users is mostly "per unwarned breakage",
> so that even one unwarned breakage less translates into fewer minutes
> wasted for users scratching their heads.
>
> In the end it's a tradeoff between inconvenience to NumPy developers and
> inconvenience to NumPy users -- not inconveniencing the developers
> further is an argument for not being consistent; but for diagonal() the
> work is already done.
...and, I missed the point about a future-compatible fix implying
double-copy.
Dag
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