[Numpy-discussion] Removing datetime support for 1.4.x series ?

[josef.pktd at gmail.com]

On Wed, Feb 3, 2010 at 12:16 PM, Christopher Barker
<Chris.Barker at noaa.gov> wrote:
> David Cournapeau wrote:
>> Just so that there is no confusion: it is only about removing it for
>> 1.4.x, not about removing datetime altogether. It seems that datetime in
>> 1.4.x has few users,
>
> Of course it has few users -- it's brand new!
>
>> whereas breaking ABI is a nuisance for many more
>> people. In particular, people who update NumPy 1.4.0 cannot use scipy or
>> matplotlib unless they build it by themselves as well - we are talking
>> about thousand of people at least assuming sourceforge numbers are accurate.
>
> Is it out of the question to make new builds of those?
>
> Anyway, ABI breakage will happen once in a while -- is it worse to do it
> now than any other time?
>
> Do people that don't want (or can't) upgrade scipy/mpl/whatever HAVE to
> upgrade numpy?

For example numpy 1.4 has improved nan-handling, which larry (a soon
to be released labeled array) relies on. I just asked Keith not to
make numpy 1.4 a hard requirement because I'm recommending to windows
users not to upgrade numpy. And we still don't have a warning on the
front page. (The recommendation on the pymvpa list was to switch to
Linux after a user tried numpy 1.4 with scipy 0.7.)

>
> For my part - I tried 1.4, found it broke a few things, so I downgraded.
> Then a bit later, we decided we needed to build a few things anyway, so
> have now gone to 1.4 and rebuilt scipy, and out own Cython extensions.
>
> changing it back means that I'd have to do that again -- not a huge
> deal, but that's what I meant by "the cat's out of the bag"

I also thought that if some packages start to be released for numpy
1.4.0, then it will be again messy if 1.4.1 is binary incompatible.
However, as David said the main problem are the large number of
version combinations for which binary distributions should be made
available. several versions of python, numpy, platforms.
numpy just doubled the requirement.

numpy is (or has become) too important for the entire ecosphere to
accidentally break binary compatibility without warning and
preparation.

Josef

>
> -Chris
>
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