Ok so I'm having trouble actually suppressing this thing. The problem is that to detect whether umfpack is present we try to build the UmfpackContect() object: try: from scipy.sparse.linalg.dsolve import umfpack UmfpackContext = umfpack.UmfpackContext()except: UmfpackContext = None The constructor raises an ImportError, which we duly catch (although that line should really specify the error type, but whatever). Unfortunately, the UmfpackContext class has a destructor (__del__) which then tries to delete some objects that were never created and raises an AttributeError — which, since we are already in a try: except: clause, gets ignored, hence the message to stderr. Basically this is a bug in scipy I think? The standard approach is to temporarily redirect stderr to /dev/null, and this works interactively: In [1]: from scipy.sparse.linalg.dsolve import umfpack In [2]: try: UC = umfpack.UmfpackContext()except ImportError: print 'hello' ...: hello Exception AttributeError: "'UmfpackContext' object has no attribute '_symbolic'" in <bound method UmfpackContext.__del__ of <scipy.sparse.linalg.dsolve.umfpack.umfpack.UmfpackContext object at 0x103938250>> ignored In [3]: import sys, os In [4]: null = open(os.devnull, 'w') In [5]: null.write('hello!') In [6]: sys.stdout.write('hello!') hello! In [7]: sys.stderr.write('hello') hello In [8]: sys.stderr = null In [9]: sys.stderr.write('hello') In [10]: try: UC = umfpack.UmfpackContext()except ImportError: print 'hello' ....: hello In [11]: sys.stderr = sys.__stderr__ In [12]: sys.stderr.write('hello') hello However, doing this in the code doesn't work, even when I try to flush the redirected stderr! (I'm not even sure that makes sense!) sys.stderr = open(os.devnull, 'w')try: from scipy.sparse.linalg.dsolve import umfpack UmfpackContext = umfpack.UmfpackContext()except: UmfpackContext = Nonefinally: sys.stderr.flush() sys.stderr = sys.__stderr__ Thoughts/ideas? On Fri, Oct 4, 2013 at 10:54 PM, Juan Nunez-Iglesias <jni.soma@gmail.com>wrote:

Thanks! Although in this case I was using pip install *and* it was on an EC2 micro instance so I only have 1 CPU. =)

But it is noted and very useful going forward. =)

On Fri, Oct 4, 2013 at 10:32 PM, Ralf Gommers <ralf.gommers@gmail.com>wrote:

...

On Fri, Oct 4, 2013 at 1:33 PM, Juan Nunez-Iglesias <jni.soma@gmail.com>wrote:

...

On Fri, Oct 4, 2013 at 8:59 PM, Johannes Schönberger <jsch@demuc.de>wrote:

...

Are you sure you have SWIG installed?

I wasn't and I didn't. =)

Bloody hell scipy takes a long time to build. =)

$ time python setup.py build_ext -i real 12m6.843s user 6m3.244s sys 0m13.124s

$ time ../Bento/bentomaker build -i -j # -j == parallel build (on 4 cores here) real 1m46.466s user 2m54.628s sys 0m10.900s

Blame distutils (and start using Bento) :)

Ralf

...

Juan.

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