Packaging (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 setup command from numpy.distutils.core. A useful 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 NumPy Distutils - Users Guide.

Modules in numpy.distutils

misc_util

get_numpy_include_dirs()
dict_append(d, **kws)
appendpath(prefix, path)
allpath(name) Convert a /-separated pathname to one using the OS’s path separator.
dot_join(*args)
generate_config_py(target) Generate config.py file containing system_info information used during building the package.
get_cmd(cmdname[, _cache])
terminal_has_colors()
red_text(s)
green_text(s)
yellow_text(s)
blue_text(s)
cyan_text(s)
cyg2win32(path)
all_strings(lst) Return True if all items in lst are string objects.
has_f_sources(sources) Return True if sources contains Fortran files
has_cxx_sources(sources) Return True if sources contains C++ files
filter_sources(sources) Return four lists of filenames containing C, C++, Fortran, and Fortran 90 module sources, respectively.
get_dependencies(sources)
is_local_src_dir(directory) Return true if directory is local directory.
get_ext_source_files(ext)
get_script_files(scripts)
class numpy.distutils.misc_util.Configuration(package_name=None, parent_name=None, top_path=None, package_path=None, **attrs) [source]

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 Configuration instance.

todict() [source]

Return a dictionary compatible with the keyword arguments of distutils setup function.

Examples

>>> setup(**config.todict())                           
get_distribution() [source]

Return the distutils distribution object for self.

get_subpackage(subpackage_name, subpackage_path=None, parent_name=None, caller_level=1) [source]

Return list of subpackage configurations.

Parameters:
subpackage_name : str or None

Name of the subpackage to get the configuration. ‘*’ in subpackage_name is handled as a wildcard.

subpackage_path : str

If None, then the path is assumed to be the local path plus the subpackage_name. If a setup.py file is not found in the subpackage_path, then a default configuration is used.

parent_name : str

Parent name.

add_subpackage(subpackage_name, subpackage_path=None, standalone=False) [source]

Add a sub-package to the current Configuration instance.

This is useful in a setup.py script for adding sub-packages to a package.

Parameters:
subpackage_name : str

name of the subpackage

subpackage_path : str

if given, the subpackage path such as the subpackage is in subpackage_path / subpackage_name. If None,the subpackage is assumed to be located in the local path / subpackage_name.

standalone : bool
add_data_files(*files) [source]

Add data files to configuration data_files.

Parameters:
files : sequence

Argument(s) can be either

  • 2-sequence (<datadir prefix>,<path to data file(s)>)
  • paths to data files where python datadir prefix defaults to package dir.

Notes

The form of each element of the files sequence is very flexible allowing many combinations of where to get the files from the package and where they should ultimately be installed on the system. The most basic usage is for an element of the files argument sequence to be a simple filename. This will cause that file from the local path to be installed to the installation path of the self.name package (package path). The file argument can also be a relative path in which case the entire relative path will be installed into the package directory. Finally, the file can be an absolute path name in which case the file will be found at the absolute path name but installed to the package path.

This basic behavior can be augmented by passing a 2-tuple in as the file argument. The first element of the tuple should specify the relative path (under the package install directory) where the remaining sequence of files should be installed to (it has nothing to do with the file-names in the source distribution). The second element of the tuple is the sequence of files that should be installed. The files in this sequence can be filenames, relative paths, or absolute paths. For absolute paths the file will be installed in the top-level package installation directory (regardless of the first argument). Filenames and relative path names will be installed in the package install directory under the path name given as the first element of the tuple.

Rules for installation paths:

  1. file.txt -> (., file.txt)-> parent/file.txt
  2. foo/file.txt -> (foo, foo/file.txt) -> parent/foo/file.txt
  3. /foo/bar/file.txt -> (., /foo/bar/file.txt) -> parent/file.txt
  4. *.txt -> parent/a.txt, parent/b.txt
  5. foo/*.txt`` -> parent/foo/a.txt, parent/foo/b.txt
  6. */*.txt -> (*, */*.txt) -> parent/c/a.txt, parent/d/b.txt
  7. (sun, file.txt) -> parent/sun/file.txt
  8. (sun, bar/file.txt) -> parent/sun/file.txt
  9. (sun, /foo/bar/file.txt) -> parent/sun/file.txt
  10. (sun, *.txt) -> parent/sun/a.txt, parent/sun/b.txt
  11. (sun, bar/*.txt) -> parent/sun/a.txt, parent/sun/b.txt
  12. (sun/*, */*.txt) -> parent/sun/c/a.txt, parent/d/b.txt

An additional feature is that the path to a data-file can actually be a function that takes no arguments and returns the actual path(s) to the data-files. This is useful when the data files are generated while building the package.

Examples

Add files to the list of data_files to be included with the package.

>>> self.add_data_files('foo.dat',
...     ('fun', ['gun.dat', 'nun/pun.dat', '/tmp/sun.dat']),
...     'bar/cat.dat',
...     '/full/path/to/can.dat')                   

will install these data files to:

<package install directory>/
 foo.dat
 fun/
   gun.dat
   nun/
     pun.dat
 sun.dat
 bar/
   car.dat
 can.dat

where <package install directory> is the package (or sub-package) directory such as ‘/usr/lib/python2.4/site-packages/mypackage’ (‘C: Python2.4 Lib site-packages mypackage’) or ‘/usr/lib/python2.4/site- packages/mypackage/mysubpackage’ (‘C: Python2.4 Lib site-packages mypackage mysubpackage’).

add_data_dir(data_path) [source]

Recursively add files under data_path to data_files list.

Recursively add files under data_path to the list of data_files to be installed (and distributed). The data_path can be either a relative path-name, or an absolute path-name, or a 2-tuple where the first argument shows where in the install directory the data directory should be installed to.

Parameters:
data_path : seq or str

Argument can be either

  • 2-sequence (<datadir suffix>, <path to data directory>)
  • path to data directory where python datadir suffix defaults to package dir.

Notes

Rules for installation paths:

foo/bar -> (foo/bar, foo/bar) -> parent/foo/bar
(gun, foo/bar) -> parent/gun
foo/* -> (foo/a, foo/a), (foo/b, foo/b) -> parent/foo/a, parent/foo/b
(gun, foo/*) -> (gun, foo/a), (gun, foo/b) -> gun
(gun/*, foo/*) -> parent/gun/a, parent/gun/b
/foo/bar -> (bar, /foo/bar) -> parent/bar
(gun, /foo/bar) -> parent/gun
(fun/*/gun/*, sun/foo/bar) -> parent/fun/foo/gun/bar

Examples

For example suppose the source directory contains fun/foo.dat and fun/bar/car.dat:

>>> self.add_data_dir('fun')                       
>>> self.add_data_dir(('sun', 'fun'))              
>>> self.add_data_dir(('gun', '/full/path/to/fun'))

Will install data-files to the locations:

<package install directory>/
  fun/
    foo.dat
    bar/
      car.dat
  sun/
    foo.dat
    bar/
      car.dat
  gun/
    foo.dat
    car.dat
add_include_dirs(*paths) [source]

Add paths to configuration include directories.

Add the given sequence of paths to the beginning of the include_dirs list. This list will be visible to all extension modules of the current package.

add_headers(*files) [source]

Add installable headers to configuration.

Add the given sequence of files to the beginning of the headers list. By default, headers will be installed under <python- include>/<self.name.replace(‘.’,’/’)>/ directory. If an item of files is a tuple, then its first argument specifies the actual installation location relative to the <python-include> path.

Parameters:
files : str or seq

Argument(s) can be either:

  • 2-sequence (<includedir suffix>,<path to header file(s)>)
  • path(s) to header file(s) where python includedir suffix will default to package name.
add_extension(name, sources, **kw) [source]

Add extension to configuration.

Create and add an Extension instance to the ext_modules list. This method also takes the following optional keyword arguments that are passed on to the Extension constructor.

Parameters:
name : str

name of the extension

sources : seq

list of the sources. The list of sources may contain functions (called source generators) which must take an extension instance and a build directory as inputs and return a source file or list of source files or None. If None is returned then no sources are generated. If the Extension instance has no sources after processing all source generators, then no extension module is built.

include_dirs :
define_macros :
undef_macros :
library_dirs :
libraries :
runtime_library_dirs :
extra_objects :
extra_compile_args :
extra_link_args :
extra_f77_compile_args :
extra_f90_compile_args :
export_symbols :
swig_opts :
depends :

The depends list contains paths to files or directories that the sources of the extension module depend on. If any path in the depends list is newer than the extension module, then the module will be rebuilt.

language :
f2py_options :
module_dirs :
extra_info : dict or list

dict or list of dict of keywords to be appended to keywords.

Notes

The self.paths(…) method is applied to all lists that may contain paths.

add_library(name, sources, **build_info) [source]

Add library to configuration.

Parameters:
name : str

Name of the extension.

sources : sequence

List of the sources. The list of sources may contain functions (called source generators) which must take an extension instance and a build directory as inputs and return a source file or list of source files or None. If None is returned then no sources are generated. If the Extension instance has no sources after processing all source generators, then no extension module is built.

build_info : dict, optional

The following keys are allowed:

  • depends
  • macros
  • include_dirs
  • extra_compiler_args
  • extra_f77_compile_args
  • extra_f90_compile_args
  • f2py_options
  • language
add_scripts(*files) [source]

Add scripts to configuration.

Add the sequence of files to the beginning of the scripts list. Scripts will be installed under the <prefix>/bin/ directory.

add_installed_library(name, sources, install_dir, build_info=None) [source]

Similar to add_library, but the specified library is installed.

Most C libraries used with distutils are only used to build python extensions, but libraries built through this method will be installed so that they can be reused by third-party packages.

Parameters:
name : str

Name of the installed library.

sources : sequence

List of the library’s source files. See add_library for details.

install_dir : str

Path to install the library, relative to the current sub-package.

build_info : dict, optional

The following keys are allowed:

  • depends
  • macros
  • include_dirs
  • extra_compiler_args
  • extra_f77_compile_args
  • extra_f90_compile_args
  • f2py_options
  • language
Returns:
None

Notes

The best way to encode the options required to link against the specified C libraries is to use a “libname.ini” file, and use get_info to retrieve the required options (see add_npy_pkg_config for more information).

add_npy_pkg_config(template, install_dir, subst_dict=None) [source]

Generate and install a npy-pkg config file from a template.

The config file generated from template is installed in the given install directory, using subst_dict for variable substitution.

Parameters:
template : str

The path of the template, relatively to the current package path.

install_dir : str

Where to install the npy-pkg config file, relatively to the current package path.

subst_dict : dict, optional

If given, any string of the form @key@ will be replaced by subst_dict[key] in the template file when installed. The install prefix is always available through the variable @prefix@, since the install prefix is not easy to get reliably from setup.py.

Notes

This works for both standard installs and in-place builds, i.e. the @prefix@ refer to the source directory for in-place builds.

Examples

config.add_npy_pkg_config('foo.ini.in', 'lib', {'foo': bar})

Assuming the foo.ini.in file has the following content:

[meta]
Name=@foo@
Version=1.0
Description=dummy description

[default]
Cflags=-I@prefix@/include
Libs=

The generated file will have the following content:

[meta]
Name=bar
Version=1.0
Description=dummy description

[default]
Cflags=-Iprefix_dir/include
Libs=

and will be installed as foo.ini in the ‘lib’ subpath.

paths(*paths, **kws) [source]

Apply glob to paths and prepend local_path if needed.

Applies glob.glob(…) to each path in the sequence (if needed) and pre-pends the local_path if needed. Because this is called on all source lists, this allows wildcard characters to be specified in lists of sources for extension modules and libraries and scripts and allows path-names be relative to the source directory.

get_config_cmd() [source]

Returns the numpy.distutils config command instance.

get_build_temp_dir() [source]

Return a path to a temporary directory where temporary files should be placed.

have_f77c() [source]

Check for availability of Fortran 77 compiler.

Use it inside source generating function to ensure that setup distribution instance has been initialized.

Notes

True if a Fortran 77 compiler is available (because a simple Fortran 77 code was able to be compiled successfully).

have_f90c() [source]

Check for availability of Fortran 90 compiler.

Use it inside source generating function to ensure that setup distribution instance has been initialized.

Notes

True if a Fortran 90 compiler is available (because a simple Fortran 90 code was able to be compiled successfully)

get_version(version_file=None, version_variable=None) [source]

Try to get version string of a package.

Return a version string of the current package or None if the version information could not be detected.

Notes

This method scans files named __version__.py, <packagename>_version.py, version.py, and __svn_version__.py for string variables version, __version__, and <packagename>_version, until a version number is found.

make_svn_version_py(delete=True) [source]

Appends a data function to the data_files list that will generate __svn_version__.py file to the current package directory.

Generate package __svn_version__.py file from SVN revision number, it will be removed after python exits but will be available when sdist, etc commands are executed.

Notes

If __svn_version__.py existed before, nothing is done.

This is intended for working with source directories that are in an SVN repository.

make_config_py(name='__config__') [source]

Generate package __config__.py file containing system_info information used during building the package.

This file is installed to the package installation directory.

get_info(*names) [source]

Get resources information.

Return information (from system_info.get_info) for all of the names in the argument list in a single dictionary.

Other modules

system_info.get_info(name[, notfound_action]) notfound_action: 0 - do nothing 1 - display warning message 2 - raise error
system_info.get_standard_file(fname) Returns a list of files named ‘fname’ from 1) System-wide directory (directory-location of this module) 2) Users HOME directory (os.environ[‘HOME’]) 3) Local directory
cpuinfo.cpu
log.set_verbosity(v[, force])
exec_command 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 <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.

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 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.

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Licensed under the 3-clause BSD License.
https://docs.scipy.org/doc/numpy-1.16.1/reference/distutils.html