[Numpy-discussion] Error building numpy (1.5.1 and 1.6.1rc3) with python2.7 debug
Fri Aug 5 18:37:56 CDT 2011
On Sat, Jul 16, 2011 at 22:45, Bruce Southey <email@example.com> wrote:
> On Sat, Jul 16, 2011 at 4:34 AM, Sandro Tosi <firstname.lastname@example.org> wrote:
>> while preparing a test upload for 1.6.1rc3 in Debian, I noticed that
>> it gets an error when building blas with python 2.7 in the debug
>> flavor, the build log is at . It's also been confirmed it fails
>> also with 1.5.1 
>>  http://people.debian.org/~morph/python-numpy_1.6.1~rc3-1_amd64.build
>>  http://bugs.debian.org/cgi-bin/bugreport.cgi?bug=634012
>> I think it might be a toolchain change in Debian (since 1.5.1 was
>> built successfully and now it fails), but could you please give me a
>> hand in debugging the issue?
>> Thanks in advance,
>> Sandro Tosi (aka morph, morpheus, matrixhasu)
>> My website: http://matrixhasu.altervista.org/
>> Me at Debian: http://wiki.debian.org/SandroTosi
>> NumPy-Discussion mailing list
> What do you mean by 'python2.7 debug'?
> Numpy 1.6.1rc's and earlier build and install with Python 2.7 build in
> debug mode ($ ./configure --with-pydebug
> ) on 64-bit Fedora 14 and 15. But, if I can follow you build process
> (should be the plain 'python setup.py build' to be useful) I think
> numpy is not finding the correct blas/lapack/atlas libraries so either
> you may need a site.cfg for that system or install those in the Linux
> standard locations such as /usr/lib64.
> You should probably try building without blas, lapack and atlas etc.:
> BLAS=None LAPACK=None ATLAS=None python setup.py build
It's not a matter of not finding the headers: the same build process
succeeds if run using gfortran-4.5 while fails if run with
gfortran-4.6 , it's likely that gcc is more strict now and something
needs to be adapted in numpy.
Has someone successfully built numpy with gcc 4.6 ?
Sandro Tosi (aka morph, morpheus, matrixhasu)
My website: http://matrixhasu.altervista.org/
Me at Debian: http://wiki.debian.org/SandroTosi
More information about the NumPy-Discussion