[Numpy-discussion] Warning on http://scipy.org/ about binary incompatibility ?
Thu Jan 28 08:01:13 CST 2010
On Thu, Jan 28, 2010 at 1:39 AM, David Cournapeau <firstname.lastname@example.org> wrote:
> Charles R Harris wrote:
>> On Wed, Jan 27, 2010 at 6:20 PM, David Cournapeau <email@example.com
>> <mailto:firstname.lastname@example.org>> wrote:
>> email@example.com <mailto:firstname.lastname@example.org> wrote:
>> > Can we/someone add a warning on the front page http://scipy.org/
>> > (maybe under news for numpy download) about incompatibility of the
>> > binaries on sourceforge of scipy <=0.7.1 with numpy 1.4.0 ?
>> It seems that it will be quite difficult to fix the issue without
>> removing something (I tried to use datetime as user types, but this
>> opened a can of worms), so I am (quite reluctantly ) coming to the
>> conclusion we should just bite the bullet and change the ABI number (so
>> that importing anything will fail instead of crashing randomly).
>> Something like numpy 220.127.116.11, which would just have a different ABI
>> number than 1.4.0, without anything else.
>> Why do you think it would be better to make this change in 1.4 rather
>> than 1.5?
> Because then any extension fails to import with a clear message instead
> of crashing as it does now. It does not matter much if you know the
> crash is coming from an incompatible ABI, but it does if you don't :)
I thought we could get away with a small binary incompatibility,
without rebuilding everything. I'm using matplotlib although not
extensively and it didn't crash in a while. (I don't remember which
version of scipy I used for the last time when I had a crashing
I just tried to build h5py which does not import at all with 1.4.0,
but I only get compiler errors about using headers only with Visual
C++ and conflicting types for 'ssize_t' .
Is there a way to find out which extensions use the binary
incompatible part. Since it took a long time to confirm the ABI
breakage, I would think it's not in a heavily used part. Although, I'm
not sure since I had to rebuild for example most scikits with 1.4
either because of the cython issue or because of this.
Personally, I would remove the ABI breakage for 1.4.1, I rather have a
working SciPy than a new "experimental" feature.
That's my opinion as a consumer of binary distributions.
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