pip-install-ghxuqwgs/numpy_78e94bf2b6094bf9a1f3d92042f9bf46/doc/source/reference/distutils.rst

**********************************
Packaging (:mod:`numpy.distutils`)
**********************************

.. module:: numpy.distutils

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. To use features of NumPy
distutils, use the :func:`setup <core.setup>` command from
:mod:`numpy.distutils.core`. A useful :class:`Configuration
<misc_util.Configuration>` class is also provided in
:mod:`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 NumPy Distutils Users Guide in
``<site-packages>/numpy/doc/DISTUTILS.txt``.


.. index::
   single: distutils


Modules in :mod:`numpy.distutils`
=================================

misc_util
---------

.. module:: numpy.distutils.misc_util

.. autosummary::
   :toctree: generated/

   get_numpy_include_dirs
   dict_append
   appendpath
   allpath
   dot_join
   generate_config_py
   get_cmd
   terminal_has_colors
   red_text
   green_text
   yellow_text
   blue_text
   cyan_text
   cyg2win32
   all_strings
   has_f_sources
   has_cxx_sources
   filter_sources
   get_dependencies
   is_local_src_dir
   get_ext_source_files
   get_script_files


.. class:: Configuration(package_name=None, parent_name=None, top_path=None, package_path=None, **attrs)

    Construct a configuration instance for the given package name. If
    *parent_name* is not None, then construct the package as a
    sub-package of the *parent_name* package. If *top_path* and
    *package_path* are None then they are assumed equal to
    the path of the file this instance was created in. The setup.py
    files in the numpy distribution are good examples of how to use
    the :class:`Configuration` instance.

    .. automethod:: todict

    .. automethod:: get_distribution

    .. automethod:: get_subpackage

    .. automethod:: add_subpackage

    .. automethod:: add_data_files

    .. automethod:: add_data_dir

    .. automethod:: add_include_dirs

    .. automethod:: add_headers

    .. automethod:: add_extension

    .. automethod:: add_library

    .. automethod:: add_scripts

    .. automethod:: add_installed_library

    .. automethod:: add_npy_pkg_config

    .. automethod:: paths

    .. automethod:: get_config_cmd

    .. automethod:: get_build_temp_dir

    .. automethod:: have_f77c

    .. automethod:: have_f90c

    .. automethod:: get_version

    .. automethod:: make_svn_version_py

    .. automethod:: make_config_py

    .. automethod:: get_info

Other modules
-------------

.. currentmodule:: numpy.distutils

.. autosummary::
   :toctree: generated/

   system_info.get_info
   system_info.get_standard_file
   cpuinfo.cpu
   log.set_verbosity
   exec_command

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::

  >>> 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).  npy-pkg-config files can also be
installed at the same location as used for numpy, using the path returned from
`get_npy_pkg_dir` function.

Reusing a C library from another package
----------------------------------------

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

  >>> info = get_info('npymath')
  >>> config.add_extension('foo', sources=['foo.c'], extra_info=**info)

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 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.

.. index::
   single: code generation

Fortran files
-------------

This template converter will replicate all **function** and
**subroutine** blocks in the file with names that contain '<...>'
according to the rules in '<...>'. The number of comma-separated words
in '<...>' determines the number of times the block is repeated. What
these words are indicates what that repeat rule, '<...>', should be
replaced with in each block. All of the repeat rules in a block must
contain the same number of comma-separated words indicating the number
of times that block should be repeated. If the word in the repeat rule
needs a comma, leftarrow, or rightarrow, then prepend it with a
backslash ' \'. If a word in the repeat rule matches ' \\<index>' then
it will be replaced with the <index>-th word in the same repeat
specification. There are two forms for the repeat rule: named and
short.


Named repeat rule
^^^^^^^^^^^^^^^^^

A named repeat rule is useful when the same set of repeats must be
used several times in a block. It is specified using <rule1=item1,
item2, item3,..., itemN>, where N is the number of times the block
should be repeated. On each repeat of the block, the entire
expression, '<...>' will be replaced first with item1, and then with
item2, and so forth until N repeats are accomplished. Once a named
repeat specification has been introduced, the same repeat rule may be
used **in the current block** by referring only to the name
(i.e. <rule1>.


Short repeat rule
^^^^^^^^^^^^^^^^^

A short repeat rule looks like <item1, item2, item3, ..., itemN>. The
rule specifies that the entire expression, '<...>' should be replaced
first with item1, and then with item2, and so forth until N repeats
are accomplished.


Pre-defined names
^^^^^^^^^^^^^^^^^

The following predefined named repeat rules are available:

- <prefix=s,d,c,z>

- <_c=s,d,c,z>

- <_t=real, double precision, complex, double complex>

- <ftype=real, double precision, complex, double complex>

- <ctype=float, double, complex_float, complex_double>

- <ftypereal=float, double precision, \\0, \\1>

- <ctypereal=float, double, \\0, \\1>


Other files
-----------

Non-Fortran files use a separate syntax for defining template blocks
that should be repeated using a variable expansion similar to the
named repeat rules of the Fortran-specific repeats. The template rules
for these files are:

1. "/\**begin repeat "on a line by itself marks the beginning of
   a segment that should be repeated.

2. Named variable expansions are defined using #name=item1, item2, item3,
   ..., itemN# and placed on successive lines. These variables are
   replaced in each repeat block with corresponding word. All named
   variables in the same repeat block must define the same number of
   words.

3. In specifying the repeat rule for a named variable, item*N is short-
   hand for item, item, ..., item repeated N times. In addition,
   parenthesis in combination with \*N can be used for grouping several
   items that should be repeated. Thus, #name=(item1, item2)*4# is
   equivalent to #name=item1, item2, item1, item2, item1, item2, item1,
   item2#

4. "\*/ "on a line by itself marks the end of the the variable expansion
   naming. The next line is the first line that will be repeated using
   the named rules.

5. Inside the block to be repeated, the variables that should be expanded
   are specified as @name@.

6. "/\**end repeat**/ "on a line by itself marks the previous line
   as the last line of the block to be repeated.