| .. -*- rest -*- | |
| .. vim:syntax=rest | |
| .. NB! Keep this document a valid restructured document. | |
| Building and installing NumPy | |
| +++++++++++++++++++++++++++++ | |
| :Authors: Numpy Developers <[email protected]> | |
| :Discussions to: [email protected] | |
| .. Contents:: | |
| PREREQUISITES | |
| ============= | |
| Building NumPy requires the following software installed: | |
| 1) For Python 2, Python__ 2.6.x or newer. | |
| For Python 3, Python__ 3.2.x or newer. | |
| On Debian and derivative (Ubuntu): python python-dev | |
| On Windows: the official python installer on Python__ is enough | |
| Make sure that the Python package distutils is installed before | |
| continuing. For example, in Debian GNU/Linux, distutils is included | |
| in the python-dev package. | |
| Python must also be compiled with the zlib module enabled. | |
| 2) nose__ (optional) 0.10.3 or later | |
| This is required for testing numpy, but not for using it. | |
| Python__ http://www.python.org | |
| nose__ http://somethingaboutorange.com/mrl/projects/nose/ | |
| Fortran ABI mismatch | |
| ==================== | |
| The two most popular open source fortran compilers are g77 and gfortran. | |
| Unfortunately, they are not ABI compatible, which means that concretely you | |
| should avoid mixing libraries built with one with another. In particular, | |
| if your blas/lapack/atlas is built with g77, you *must* use g77 when | |
| building numpy and scipy; on the contrary, if your atlas is built with | |
| gfortran, you *must* build numpy/scipy with gfortran. | |
| Choosing the fortran compiler | |
| ----------------------------- | |
| To build with g77: | |
| python setup.py build --fcompiler=gnu | |
| To build with gfortran: | |
| python setup.py build --fcompiler=gnu95 | |
| How to check the ABI of blas/lapack/atlas | |
| ----------------------------------------- | |
| One relatively simple and reliable way to check for the compiler used to | |
| build a library is to use ldd on the library. If libg2c.so is a dependency, | |
| this means that g77 has been used. If libgfortran.so is a dependency, | |
| gfortran has been used. If both are dependencies, this means both have been | |
| used, which is almost always a very bad idea. | |
| Building with ATLAS support | |
| =========================== | |
| Ubuntu 8.10 (Intrepid) | |
| ---------------------- | |
| You can install the necessary packages for optimized ATLAS with this | |
| command: | |
| sudo apt-get install libatlas-base-dev | |
| If you have a recent CPU with SIMD support (SSE, SSE2, etc...), you should | |
| also install the corresponding package for optimal performance. For | |
| example, for SSE2: | |
| sudo apt-get install libatlas3gf-sse2 | |
| *NOTE*: if you build your own atlas, Intrepid changed its default fortran | |
| compiler to gfortran. So you should rebuild everything from scratch, | |
| including lapack, to use it on Intrepid. | |
| Ubuntu 8.04 and lower | |
| --------------------- | |
| You can install the necessary packages for optimized ATLAS with this | |
| command: | |
| sudo apt-get install atlas3-base-dev | |
| If you have a recent CPU with SIMD support (SSE, SSE2, etc...), you should | |
| also install the corresponding package for optimal performance. For | |
| example, for SSE2: | |
| sudo apt-get install atlas3-sse2 | |
| Windows 64 bits notes | |
| ===================== | |
| Note: only AMD64 is supported (IA64 is not) - AMD64 is the version most | |
| people want. | |
| Free compilers (mingw-w64) | |
| -------------------------- | |
| http://mingw-w64.sourceforge.net/ | |
| To use the free compilers (mingw-w64), you need to build your own | |
| toolchain, as the mingw project only distribute cross-compilers | |
| (cross-compilation is not supported by numpy). Since this toolchain is | |
| still being worked on, serious compiler bugs can be expected. binutil 2.19 | |
| + gcc 4.3.3 + mingw-w64 runtime gives you a working C compiler (but the C++ | |
| is broken). gcc 4.4 will hopefully be able to run natively. | |
| This is the only tested way to get a numpy with a FULL blas/lapack (scipy | |
| does not work because of C++). | |
| MS compilers | |
| ------------ | |
| If you are familiar with MS tools, that's obviously the easiest path, and | |
| the compilers are hopefully more mature (although in my experience, they | |
| are quite fragile, and often segfault on invalid C code). The main drawback | |
| is that no fortran compiler + MS compiler combination has been tested - | |
| mingw-w64 gfortran + MS compiler does not work at all (it is unclear | |
| whether it ever will). | |
| For python 2.6, you need VS 2008. The freely available version does not | |
| contains 64 bits compilers (you also need the PSDK, v6.1). | |
| It is crucial to use the right MS compiler version. For python 2.6, you | |
| must use version 15. You can check the compiler version with cl.exe /?. | |