Packaging

NumPy provides enhanced distutils functionality to make it easier to build and install sub-packages, auto-generate code, and extension modules that use Fortran-compiled libraries. A useful Configuration <misc_util.Configuration> class is also provided in numpy.distutils.misc_util that can make it easier to construct keyword arguments to pass to the setup function (by passing the dictionary obtained from the todict() method of the class). More information is available in the distutils-user-guide.

The choice and location of linked libraries such as BLAS and LAPACK as well as include paths and other such build options can be specified in a site.cfg file located in the NumPy root repository or a .numpy-site.cfg file in your home directory. See the site.cfg.example example file included in the NumPy repository or sdist for documentation.

Modules in numpy.distutils

• distutils.misc_util

.. autosummary:: 
    :toctree:generated/
    ccompiler
    ccompiler_opt
    cpuinfo.cpu
    core.Extension
    exec_command
    log.set_verbosity
    system_info.get_info
    system_info.get_standard_file

Configuration class

Building installable C libraries

Conventional C libraries (installed through add_library) are not installed, and are just used during the build (they are statically linked). An installable C library is a pure C library, which does not depend on the python C runtime, and is installed such that it may be used by third-party packages. To build and install the C library, you just use the method add_installed_library instead of add_library, which takes the same arguments except for an additional install_dir argument

.. hidden in a comment so as to be included in refguide but not rendered documentation
  >>> import numpy.distutils.misc_util
  >>> config = np.distutils.misc_util.Configuration(None, '', '.')
  >>> with open('foo.c', 'w') as f: pass

>>> config.add_installed_library('foo', sources=['foo.c'], install_dir='lib')

npy-pkg-config files

To make the necessary build options available to third parties, you could use the npy-pkg-config mechanism implemented in numpy.distutils. This mechanism is based on a .ini file which contains all the options. A .ini file is very similar to .pc files as used by the pkg-config unix utility

[meta]
Name: foo
Version: 1.0
Description: foo library

[variables]
prefix = /home/user/local
libdir = ${prefix}/lib
includedir = ${prefix}/include

[default]
cflags = -I${includedir}
libs = -L${libdir} -lfoo

Generally, the file needs to be generated during the build, since it needs some information known at build time only (e.g. prefix). This is mostly automatic if one uses the Configuration method add_npy_pkg_config. Assuming we have a template file foo.ini.in as follows

[meta]
Name: foo
Version: @version@
Description: foo library

[variables]
prefix = @prefix@
libdir = ${prefix}/lib
includedir = ${prefix}/include

[default]
cflags = -I${includedir}
libs = -L${libdir} -lfoo

and the following code in setup.py

>>> config.add_installed_library('foo', sources=['foo.c'], install_dir='lib')
>>> subst = {'version': '1.0'}
>>> config.add_npy_pkg_config('foo.ini.in', 'lib', subst_dict=subst)

This will install the file foo.ini into the directory package_dir/lib, and the foo.ini file will be generated from foo.ini.in, where each @version@ will be replaced by subst_dict['version']. The dictionary has an additional prefix substitution rule automatically added, which contains the install prefix (since this is not easy to get from setup.py).

Reusing a C library from another package

Info are easily retrieved from the get_info function in numpy.distutils.misc_util:

>>> info = np.distutils.misc_util.get_info('npymath')
>>> config.add_extension('foo', sources=['foo.c'], extra_info=info)
<numpy.distutils.extension.Extension('foo') at 0x...>

An additional list of paths to look for .ini files can be given to get_info.

Conversion of .src files

NumPy distutils supports automatic conversion of source files named <somefile>.src. This facility can be used to maintain very similar code blocks requiring only simple changes between blocks. During the build phase of setup, if a template file named <somefile>.src is encountered, a new file named <somefile> is constructed from the template and placed in the build directory to be used instead. Two forms of template conversion are supported. The first form occurs for files named <file>.ext.src where ext is a recognized Fortran extension (f, f90, f95, f77, for, ftn, pyf). The second form is used for all other cases. See templating.