Building From Source on Mac OSX¶
These instructions describe how to build NumPy and SciPy libraries from source.
If you just want to use NumPy or SciPy, install pre-built binaries as described in Installing the SciPy Stack.
Apple ships its own version of Python with OS X. However, we strongly recommend installing the official Python distribution.
Alternatively, use Python from one of the OS X package managers (Homebrew, MacPorts, Fink).
Apple’s Developer Tools¶
Apple’s Developer Tools provide a number of key libraries, particularly the vecLib Framework , which includes the BLAS and LAPACK libraries for optimizing matrix and vector operations. The most recent version should be included on your OS X installation CD. Ensure that all components are installed by choosing customize when available during the install process and selecting all optional packages - at least the X11 development tools and (on OS X 10.6 or lower) the 10.4 SDK.
Though virtually any commercial C/C++ compiler may be used with SciPy, OS X comes with GNU C compilers pre-installed. The only thing missing is the GNU FORTRAN compiler.
We recommend gfortran; this is a free, open source, F95 compiler. We suggest you use the following binaries:
- For Snow Leopard : https://cran.r-project.org/bin/macosx/tools/gfortran-4.2.3.pkg
- For Lion : http://r.research.att.com/gfortran-lion-5666-3.pkg (for Xcode 4.1)
- Later versions : http://r.research.att.com/tools/gcc-42-5666.3-darwin11.pkg (for Xcode 4.2 or higher) (also available through Homebrew)
See this site for the most recent links.
Unless you are building from released source packages, the Cython compiler is also needed.
This section notes only things specific to one version of OS X or Python. The build instructions in Obtaining and Building NumPy and SciPy apply to all versions.
OS X 10.7 (Lion) and 10.8 (Mountain Lion)¶
The default C compiler on (Mountain) Lion is llvm-gcc-4.2, which has so far proven to be problematic (up to scipy 0.12.0). We recommend to use gcc-4.2, or alternatively clang. The Fortran flag “-ff2c” has been reported to be necessary.
If you have the older version of XCode installed (4.1), then before building with gcc, do:
$ export CC=gcc-4.2 $ export CXX=g++-4.2 $ export FFLAGS=-ff2c
gcc-4.2 is not included with the current version of XCode (4.2). So, if you have that version of XCode then before building with gcc, the easiest thing is to do:
$ export CC=clang $ export CXX=clang++ $ export FFLAGS=-ff2c
Alternatively, you may try installing gcc-4.2 manually, and then using the environment variables in the prior block.
On OS X 10.6 and higher the default gcc version is 4.2. From Python 2.7 the python.org installers are all built with that compiler. Python 2.6 however was built with gcc 4.0. For gcc the correct version should be picked up automatically by distutils; for C++ code (only in SciPy) you should ensure that g++ and c++ default to 4.0:
$ export CC=/usr/bin/gcc-4.0 $ export CXX=/usr/bin/g++-4.0
A more permanent way to achieve this is to create symlinks
$ ln -s /usr/bin/g++-4.0 g++ $ ln -s /usr/bin/g++-4.0 c++
in a directory and add that to the front of your PATH.
Obtaining and Building NumPy and SciPy¶
You may install NumPy and SciPy either by checking out the source files from the Git repositories, or unpacking them from a source archive file from Obtaining NumPy & SciPy libraries. If you choose the latter, simply expand the archive (generally a gzipped tar file), otherwise check out the following branches from the repository:
$ git clone https://github.com/numpy/numpy.git $ git clone https://github.com/scipy/scipy.git
Both NumPy and SciPy are built as follows:
$ python setup.py build $ python setup.py install
The above applies to the official Python distribution, which is 32-bit only for 2.6 while 32/64-bit bundles are available for 2.7 and 3.x. For alternative 64-bit Pythons (either from Apple or home-built) on Snow Leopard, you may need to extend your build flags to specify the architecture by setting LDFLAGS and FFLAGS.
Note that with distutils (setup.py) given build flags like LDFLAGS do not extend but override the defaults, so you have to specify all necessary flags. Only try this if you know what you’re doing!
After a successful build, you may try running the built-in unit tests for SciPy:
$ python >>> import numpy as np >>> np.test('full') >>> import scipy >>> scipy.test()
Be sure not to import numpy or scipy while you’re in the numpy/scipy source tree. Change directory first.
If you have any problems installing SciPy on your Mac based on these instructions, please check the scipy-users and scipy-dev mailing list archives for possible solutions. If you are still stuck, feel free to join scipy-users for further assistance. Please have the following information ready:
- Your OS version
- The versions of gcc and gfortran and where you obtained gfortran
- $ gcc --version
- $ gfortran --version
- The versions of numpy and scipy that you are trying to install
- The full output of $ python setup.py build