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

Darren Dale dsdale24@gmail....
Thu Feb 4 06:42:38 CST 2010


On Thu, Feb 4, 2010 at 3:21 AM, Francesc Alted <faltet@pytables.org> wrote:
> A Thursday 04 February 2010 08:46:01 Charles R Harris escrigué:
>> > Perhaps one way to articulate my perspective is the following:
>> >
>> > There are currently 2 groups of NumPy users:
>> >
>> >  1)  those who have re-compiled all of their code for 1.4.0
>> >  2)  those who haven't
>>
>> I think David has a better grip on that. There really are a lot of people
>> who depend on binaries, and those binaries in turn depend on numpy. I would
>> even say those folks are a majority, they are those who download the Mac
>>  and Windows versions of numpy.
>
> Yes, I think this is precisely the problem: people that are used to fetch
> binaries and want to use new NumPy, will be forced to upgrade all the other
> binary packages that depends on it.  And these binary packagers (including me)
> are being forced to regenerate their binaries as soon as possible if they
> don't want their users to despair.  I'm not saying that regenerating binaries
> is not possible, but that would require a minimum of anticipation.  I'd be
> more comfortable with ABI-breaking releases to be announced at least with 6
> months of anticipation.
>
> Then, a user is not likely going to change its *already* working environment
> until all the binary packages he depends on (scipy, matplotlib, pytables,
> h5py, numexpr, sympy...) have been *all* updated for dealing with the new ABI
> numpy, and that could be really a long time.  With this (and ironically), an
> attempt to quickly introduce a new feature (in this case datetime, but it
> could have been whatever) in a release for allowing wider testing and
> adoption, will almost certainly result in a release that takes much longer to
> spread widely, and what is worst, generating a large frustration among users.

Also, there was some discussion about wanting to make some other
changes in numpy that would break ABI once, but allow new dtypes in
the future without additional ABI breakage. Since ABI breakage is so
disruptive, could we try to coordinate so a number of them can happen
all at once, with plenty of warning to the community? Then this
change, datetime, and hasobject can all be handled at the same time,
and it could/should be released as numpy-2.0. Then when when numpy for
py-3.0 is ready, which will presumably require ABI breakage, it could
be called numpy-3.0.

Darren


More information about the NumPy-Discussion mailing list