Scientific Python tips and tricks
scottsievert.github.io
scottsievert.github.io
I went all the way to MinGW, but fell apart at the fortran stuff.
Then, I'd use `pip install numpy scipy` (since numpy is a scipy dependency).
numpy.distutils.system_info.BlasNotFoundError: Blas (http://www.netlib.org/blas/) libraries not found. Directories to search for the libraries can be specifies in the numpy/distutils/site.cfg file (section [blas]) or by setting the BLAS environment variable.
I know this isn't stackoverflow, so no further info needed.
Needless to say, going down the netlib.org/blas/ is quite brutal on windows...
>>> import scipy
>>> scipy.test()
Running unit tests for scipy
NumPy version 1.8.1
NumPy is installed in C:\Python27\lib\site-packages\numpy
SciPy version 0.14.0rc2
SciPy is installed in C:\Python27\lib\site-packages\scipy
Python version 2.7.6 (default, Nov 10 2013, 19:24:24) [MSC
v.1500 64 bit (AMD64)]
nose version 1.3.3
....
Ran 16575 tests in 136.936s
OK (KNOWNFAIL=277, SKIP=1181)
<nose.result.TextTestResult run=16575 errors=0 failures=0>
Have you tried using Christoph Gohlke's pre-compiled binaries[1]? Here's the list of libraries I have installed [2].Also don't customize any install paths; leave it everything as default (e.g., C:\Python27). I've long gave up trying to keep my root folder under control; now it's a festival of Ruby, MinGW, Vagrant, etc.
This is the only way to install python libraries under Windows without pulling your hair out. Any other way is truly a nightmare. That's why I use Linux whenever possible for most of my coding.
I hear you on the Linux business, and that's what I use at home and elsewhere, but it's not an option at the office.