
Hi,
After more investigation, I found that there already exist a way to suppress those message on posix system. So I reused it in the PR. That way, it was faster, but prevent change in that area. So there is less change of breaking other syste:
https://github.com/numpy/numpy/pull/4081
But it remove the stdout when we run this command:
numpy.distutils.system_info.get_info("blas_opt")
But during compilation, we still have the info about what is found:
atlas_blas_threads_info: Setting PTATLAS=ATLAS Setting PTATLAS=ATLAS customize Gnu95FCompiler Found executable /usr/bin/gfortran customize Gnu95FCompiler customize Gnu95FCompiler using config compiling '_configtest.c':
/* This file is generated from numpy/distutils/system_info.py */ void ATL_buildinfo(void); int main(void) { ATL_buildinfo(); return 0; }
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -O2 -fPIC
compile options: '-c' gcc: _configtest.c gcc -pthread _configtest.o -L/usr/lib64/atlas -lptf77blas -lptcblas -latlas -o _configtest success! removing: _configtest.c _configtest.o _configtest Setting PTATLAS=ATLAS FOUND: libraries = ['ptf77blas', 'ptcblas', 'atlas'] library_dirs = ['/usr/lib64/atlas'] language = c define_macros = [('ATLAS_INFO', '"\"3.8.3\""')] include_dirs = ['/usr/include']
FOUND: libraries = ['ptf77blas', 'ptcblas', 'atlas'] library_dirs = ['/usr/lib64/atlas'] language = c define_macros = [('ATLAS_INFO', '"\"3.8.3\""')] include_dirs = ['/usr/include']
non-existing path in 'numpy/lib': 'benchmarks' lapack_opt_info: lapack_mkl_info: mkl_info: libraries mkl,vml,guide not found in ['/opt/lisa/os_v2/common/Canopy_64bit/User/lib', '/usr/local/lib64', '/usr/local/lib', '/usr/lib64', '/usr/lib'] NOT AVAILABLE
NOT AVAILABLE
atlas_threads_info: Setting PTATLAS=ATLAS libraries ptf77blas,ptcblas,atlas not found in /opt/lisa/os_v2/common/Canopy_64bit/User/lib libraries lapack_atlas not found in /opt/lisa/os_v2/common/Canopy_64bit/User/lib libraries ptf77blas,ptcblas,atlas not found in /usr/local/lib64 libraries lapack_atlas not found in /usr/local/lib64 libraries ptf77blas,ptcblas,atlas not found in /usr/local/lib libraries lapack_atlas not found in /usr/local/lib libraries lapack_atlas not found in /usr/lib64/atlas numpy.distutils.system_info.atlas_threads_info Setting PTATLAS=ATLAS Setting PTATLAS=ATLAS FOUND: libraries = ['lapack', 'ptf77blas', 'ptcblas', 'atlas'] library_dirs = ['/usr/lib64/atlas'] language = f77 define_macros = [('ATLAS_INFO', '"\"3.8.3\""')] include_dirs = ['/usr/include']
FOUND: libraries = ['lapack', 'ptf77blas', 'ptcblas', 'atlas'] library_dirs = ['/usr/lib64/atlas'] language = f77 define_macros = [('ATLAS_INFO', '"\"3.8.3\""')] include_dirs = ['/usr/include']
Frédéric
On Fri, Nov 22, 2013 at 4:26 PM, Frédéric Bastien nouiz@nouiz.org wrote:
I didn't forgot this, but I got side tracked. Here is the Theano code I would like to try to use to replace os.system:
https://github.com/Theano/Theano/blob/master/theano/misc/windows.py
But I won't be able to try this before next week.
Fred
On Fri, Nov 15, 2013 at 5:49 PM, David Cournapeau cournape@gmail.com wrote:
On Fri, Nov 15, 2013 at 7:41 PM, Robert Kern robert.kern@gmail.com wrote:
On Fri, Nov 15, 2013 at 7:28 PM, David Cournapeau cournape@gmail.com wrote:
On Fri, Nov 15, 2013 at 6:21 PM, Charles R Harris charlesr.harris@gmail.com wrote:
Sure, give it a shot. Looks like subprocess.Popen was intended to replace os.system in any case.
Except that output is not 'real time' with straight Popen, and doing so reliably on every platform (cough - windows - cough) is not completely trivial. You also have to handle buffered output, etc... That code is very fragile, so this would be quite a lot of testing to change, and I am not sure it worths it.
It doesn't have to be "real time". Just use .communicate() and print out the stdout and stderr to their appropriate streams after the subprocess finishes.
Indeed, it does not have to be, but that's useful for debugging compilation issues (not so much for numpy itself, but for some packages which have files that takes a very long time to build, like scipy.sparsetools or bottleneck).
That's a minor point compared to the potential issues when building on windows, though.
David
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