.. -*- rest -*-

NumPy Distutils - Users Guide
=============================

:Author: Pearu Peterson <pearu@cens.ioc.ee>
:Discussions to: scipy-dev@scipy.org
:Created: October 2005
:Revision: $LastChangedRevision: 4645 $
:SVN source: $HeadURL: http://svn.scipy.org/svn/numpy/tags/1.1.1/numpy/doc/DISTUTILS.txt $

.. contents::

SciPy structure
'''''''''''''''

Currently SciPy project consists of two packages:

- NumPy (previously called SciPy core) --- it provides packages like:

  + numpy.distutils - extension to Python distutils
  + numpy.f2py - a tool to bind Fortran/C codes to Python
  + numpy.core - future replacement of Numeric and numarray packages
  + numpy.lib - extra utility functions
  + numpy.testing - numpy-style tools for unit testing
  + etc

- SciPy --- a collection of scientific tools for Python.

The aim of this document is to describe how to add new tools to SciPy.


Requirements for SciPy packages
'''''''''''''''''''''''''''''''

SciPy consists of Python packages, called SciPy packages, that are
available to Python users via the ``scipy`` namespace. Each SciPy package
may contain other SciPy packages. And so on. Therefore, the SciPy 
directory tree is a tree of packages with arbitrary depth and width. 
Any SciPy package may depend on NumPy packages but the dependence on other
SciPy packages should be kept minimal or zero.

A SciPy package contains, in addition to its sources, the following
files and directories:

  + ``setup.py`` --- building script
  + ``info.py``  --- contains documentation and import flags
  + ``__init__.py`` --- package initializer
  + ``tests/`` --- directory of unittests

Their contents are described below.

The ``setup.py`` file
'''''''''''''''''''''

In order to add a Python package to SciPy, its build script (``setup.py``) 
must meet certain requirements. The most important requirement is that the 
package define a ``configuration(parent_package='',top_path=None)`` function 
which returns a dictionary suitable for passing to 
``numpy.distutils.core.setup(..)``. To simplify the construction of 
this dictionary, ``numpy.distutils.misc_util`` provides the 
``Configuration`` class, described below.

SciPy pure Python package example
---------------------------------

Below is an example of a minimal ``setup.py`` file for a pure Scipy package::

  #!/usr/bin/env python
  def configuration(parent_package='',top_path=None):
      from numpy.distutils.misc_util import Configuration
      config = Configuration('mypackage',parent_package,top_path)
      return config

  if __name__ == "__main__":
      from numpy.distutils.core import setup
      #setup(**configuration(top_path='').todict())
      setup(configuration=configuration)

The arguments of the ``configuration`` function specifiy the name of
parent SciPy package (``parent_package``) and the directory location
of the main ``setup.py`` script (``top_path``).  These arguments, 
along with the name of the current package, should be passed to the
``Configuration`` constructor.

The ``Configuration`` constructor has a fourth optional argument,
``package_path``, that can be used when package files are located in
a different location than the directory of the ``setup.py`` file. 

Remaining ``Configuration`` arguments are all keyword arguments that will
be used to initialize attributes of ``Configuration``
instance. Usually, these keywords are the same as the ones that
``setup(..)`` function would expect, for example, ``packages``,
``ext_modules``, ``data_files``, ``include_dirs``, ``libraries``,
``headers``, ``scripts``, ``package_dir``, etc.  However, the direct
specification of these keywords is not recommended as the content of
these keyword arguments will not be processed or checked for the
consistency of SciPy building system.

Finally, ``Configuration`` has ``.todict()`` method that returns all
the configuration data as a dictionary suitable for passing on to the
``setup(..)`` function.

``Configuration`` instance attributes
-------------------------------------

In addition to attributes that can be specified via keyword arguments
to ``Configuration`` constructor, ``Configuration`` instance (let us
denote as ``config``) has the following attributes that can be useful
in writing setup scripts:

+ ``config.name`` - full name of the current package. The names of parent
  packages can be extracted as ``config.name.split('.')``.

+ ``config.local_path`` - path to the location of current ``setup.py`` file.

+ ``config.top_path`` - path to the location of main ``setup.py`` file.

``Configuration`` instance methods
----------------------------------

+ ``config.todict()`` --- returns configuration dictionary suitable for
  passing to ``numpy.distutils.core.setup(..)`` function.

+ ``config.paths(*paths) --- applies ``glob.glob(..)`` to items of
  ``paths`` if necessary. Fixes ``paths`` item that is relative to
  ``config.local_path``.

+ ``config.get_subpackage(subpackage_name,subpackage_path=None)`` ---
  returns a list of subpackage configurations. Subpackage is looked in the
  current directory under the name ``subpackage_name`` but the path
  can be specified also via optional ``subpackage_path`` argument.
  If ``subpackage_name`` is specified as ``None`` then the subpackage
  name will be taken the basename of ``subpackage_path``.
  Any ``*`` used for subpackage names are expanded as wildcards.

+ ``config.add_subpackage(subpackage_name,subpackage_path=None)`` ---
  add SciPy subpackage configuration to the current one. The meaning
  and usage of arguments is explained above, see
  ``config.get_subpackage()`` method.

+ ``config.add_data_files(*files)`` --- prepend ``files`` to ``data_files``
  list. If ``files`` item is a tuple then its first element defines
  the suffix of where data files are copied relative to package installation
  directory and the second element specifies the path to data
  files. By default data files are copied under package installation
  directory. For example,

  ::

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

  will install data files to the following locations

  ::

    <installation path of config.name package>/
      foo.dat
      fun/
        gun.dat
	pun.dat
        sun.dat
      bar/
        car.dat
      can.dat 

  Path to data files can be a function taking no arguments and
  returning path(s) to data files -- this is a useful when data files
  are generated while building the package. (XXX: explain the step
  when this function are called exactly) 

+ ``config.add_data_dir(data_path)`` --- add directory ``data_path``
  recursively to ``data_files``. The whole directory tree starting at
  ``data_path`` will be copied under package installation directory.
  If ``data_path`` is a tuple then its first element defines
  the suffix of where data files are copied relative to package installation
  directory and the second element specifies the path to data directory.
  By default, data directory are copied under package installation
  directory under the basename of ``data_path``. For example,
 
  ::

    config.add_data_dir('fun')  # fun/ contains foo.dat bar/car.dat
    config.add_data_dir(('sun','fun'))
    config.add_data_dir(('gun','/full/path/to/fun'))

  will install data files to the following locations 

  ::

    <installation path of config.name package>/
      fun/
         foo.dat
         bar/
            car.dat
      sun/
         foo.dat
         bar/
            car.dat
      gun/
         foo.dat
         bar/
            car.dat

+ ``config.add_include_dirs(*paths)`` --- prepend ``paths`` to
  ``include_dirs`` list. This list will be visible to all extension
  modules of the current package.

+ ``config.add_headers(*files)`` --- prepend ``files`` to ``headers``
  list. By default, headers will be installed under 
  ``<prefix>/include/pythonX.X/<config.name.replace('.','/')>/``
  directory. If ``files`` item is a tuple then it's first argument
  specifies the installation suffix relative to
  ``<prefix>/include/pythonX.X/`` path.  This is a Python distutils
  method; its use is discouraged for NumPy and SciPy in favour of
  ``config.add_data_files(*files)``.

+ ``config.add_scripts(*files)`` --- prepend ``files`` to ``scripts``
  list. Scripts will be installed under ``<prefix>/bin/`` directory.

+ ``config.add_extension(name,sources,*kw)`` --- create and add an
  ``Extension`` instance to ``ext_modules`` list. The first argument 
  ``name`` defines the name of the extension module that will be
  installed under ``config.name`` package. The second argument is
  a list of sources. ``add_extension`` method takes also keyword
  arguments that are passed on to the ``Extension`` constructor.
  The list of allowed keywords is the following: ``include_dirs``,
  ``define_macros``, ``undef_macros``, ``library_dirs``, ``libraries``,
  ``runtime_library_dirs``, ``extra_objects``, ``extra_compile_args``,
  ``extra_link_args``, ``export_symbols``, ``swig_opts``, ``depends``,
  ``language``, ``f2py_options``, ``module_dirs``, ``extra_info``.

  Note that ``config.paths`` method is applied to all lists that
  may contain paths. ``extra_info`` is a dictionary or a list
  of dictionaries that content will be appended to keyword arguments.
  The list ``depends`` 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.

  The list of sources may contain functions ('source generators')
  with a pattern ``def <funcname>(ext, build_dir): return
  <source(s) or None>``. If ``funcname`` returns ``None``, no sources
  are generated. And if the ``Extension`` instance has no sources
  after processing all source generators, no extension module will
  be built. This is the recommended way to conditionally define
  extension modules. Source generator functions are called by the
  ``build_src`` command of ``numpy.distutils``.

  For example, here is a typical source generator function::

    def generate_source(ext,build_dir):
        import os
        from distutils.dep_util import newer
        target = os.path.join(build_dir,'somesource.c')
        if newer(target,__file__):
            # create target file
        return target

  The first argument contains the Extension instance that can be
  useful to access its attributes like ``depends``, ``sources``,
  etc. lists and modify them during the building process.
  The second argument gives a path to a build directory that must
  be used when creating files to a disk.

+ ``config.add_library(name, sources, **build_info)`` --- add
  a library to ``libraries`` list. Allowed keywords arguments
  are ``depends``, ``macros``, ``include_dirs``,
  ``extra_compiler_args``, ``f2py_options``. See ``.add_extension()``
  method for more information on arguments.

+ ``config.have_f77c()`` --- return True if Fortran 77 compiler is
  available (read: a simple Fortran 77 code compiled succesfully). 

+ ``config.have_f90c()`` --- return True if Fortran 90 compiler is
  available (read: a simple Fortran 90 code compiled succesfully). 

+ ``config.get_version()`` --- return version string of the current package,
  ``None`` if version information could not be detected. This methods
  scans files ``__version__.py``, ``<packagename>_version.py``,
  ``version.py``, ``__svn_version__.py`` for string variables
  ``version``, ``__version__``, ``<packagename>_version``.

+ ``config.make_svn_version_py()`` --- appends a data function to
  ``data_files`` list that will generate ``__svn_version__.py`` file
  to the current package directory. The file will be removed from
  the source directory when Python exits.

+ ``config.get_build_temp_dir()`` --- return a path to a temporary
  directory. This is the place where one should build temporary
  files.

+ ``config.get_distribution()`` --- return distutils ``Distribution``
  instance.

+ ``config.get_config_cmd()`` --- returns ``numpy.distutils`` config
  command instance.

+ ``config.get_info(*names)`` ---

Template files
--------------

XXX: Describe how files with extensions ``.f.src``, ``.pyf.src``,
``.c.src``, etc. are pre-processed by the ``build_src`` command.

Useful functions in ``numpy.distutils.misc_util``
-------------------------------------------------

+ ``get_numpy_include_dirs()`` --- return a list of NumPy base
  include directories. NumPy base include directories contain
  header files such as ``numpy/arrayobject.h``, ``numpy/funcobject.h``
  etc. For installed NumPy the returned list has length 1
  but when building NumPy the list may contain more directories,
  for example, a path to ``config.h`` file that
  ``numpy/base/setup.py`` file generates and is used by ``numpy``
  header files.

+ ``append_path(prefix,path)`` --- smart append ``path`` to ``prefix``.

+ ``gpaths(paths, local_path='')`` --- apply glob to paths and prepend
  ``local_path`` if needed.

+ ``njoin(*path)`` --- join pathname components + convert ``/``-separated path
  to ``os.sep``-separated path and resolve ``..``, ``.`` from paths.
  Ex. ``njoin('a',['b','./c'],'..','g') -> os.path.join('a','b','g')``.

+ ``minrelpath(path)`` --- resolves dots in ``path``.

+ ``rel_path(path, parent_path)`` --- return ``path`` relative to ``parent_path``.

+ ``def get_cmd(cmdname,_cache={})`` --- returns ``numpy.distutils``
  command instance.

+ ``all_strings(lst)``

+ ``has_f_sources(sources)``

+ ``has_cxx_sources(sources)``

+ ``filter_sources(sources)`` --- return ``c_sources, cxx_sources,
  f_sources, fmodule_sources``

+ ``get_dependencies(sources)``

+ ``is_local_src_dir(directory)``

+ ``get_ext_source_files(ext)``

+ ``get_script_files(scripts)``

+ ``get_lib_source_files(lib)``

+ ``get_data_files(data)``

+ ``dot_join(*args)`` --- join non-zero arguments with a dot.

+ ``get_frame(level=0)`` --- return frame object from call stack with given level.

+ ``cyg2win32(path)``

+ ``mingw32()`` --- return ``True`` when using mingw32 environment.

+ ``terminal_has_colors()``, ``red_text(s)``, ``green_text(s)``,
  ``yellow_text(s)``, ``blue_text(s)``, ``cyan_text(s)``

+ ``get_path(mod_name,parent_path=None)`` --- return path of a module
  relative to parent_path when given. Handles also ``__main__`` and
  ``__builtin__`` modules.

+ ``allpath(name)`` --- replaces ``/`` with ``os.sep`` in ``name``.

+ ``cxx_ext_match``, ``fortran_ext_match``, ``f90_ext_match``,
  ``f90_module_name_match``

``numpy.distutils.system_info`` module
--------------------------------------

+ ``get_info(name,notfound_action=0)``
+ ``combine_paths(*args,**kws)``
+ ``show_all()``

``numpy.distutils.cpuinfo`` module
----------------------------------

+ ``cpuinfo``

``numpy.distutils.log`` module
------------------------------

+ ``set_verbosity(v)``


``numpy.distutils.exec_command`` module
---------------------------------------

+ ``get_pythonexe()``
+ ``find_executable(exe, path=None)``
+ ``exec_command( command, execute_in='', use_shell=None, use_tee=None, **env )``

The ``info.py`` file
''''''''''''''''''''

Scipy package import hooks assume that each package contains a
``info.py`` file.  This file contains overall documentation about the package
and variables defining the order of package imports, dependency
relations between packages, etc.

On import, the following information will be looked for in ``info.py``:

__doc__
  The documentation string of the package.

__doc_title__
  The title of the package. If not defined then the first non-empty 
  line of ``__doc__`` will be used.

__all__
  List of symbols that package exports. Optional.

global_symbols
  List of names that should be imported to numpy name space. To import
  all symbols to ``numpy`` namespace, define ``global_symbols=['*']``.

depends
  List of names that the package depends on. Prefix ``numpy.``
  will be automatically added to package names. For example,
  use ``testing`` to indicate dependence on ``numpy.testing``
  package. Default value is ``[]``.

postpone_import
  Boolean variable indicating that importing the package should be
  postponed until the first attempt of its usage. Default value is ``False``.
  Depreciated.

The ``__init__.py`` file
''''''''''''''''''''''''

To speed up the import time and minimize memory usage, numpy
uses ``ppimport`` hooks to transparently postpone importing large modules,
which might not be used during the Scipy session. In order to
have access to the documentation of all Scipy packages, including 
postponed packages, the docstring from ``info.py`` is imported
into ``__init__.py``.

The header of a typical ``__init__.py`` is::

  #
  # Package ... - ...
  #

  from info import __doc__
  ...

  from numpy.testing import NumpyTest
  test = NumpyTest().test

The ``tests/`` directory
''''''''''''''''''''''''

Ideally, every Python code, extension module, or subpackage in Scipy
package directory should have the corresponding ``test_<name>.py``
file in ``tests/`` directory.  This file should define classes
derived from ``NumpyTestCase`` (or from ``unittest.TestCase``) class
and have names starting with ``test``. The methods of these classes
which names start with ``bench``, ``check``, or ``test``, are passed
on to unittest machinery. In addition, the value of the first optional
argument of these methods determine the level of the corresponding
test. Default level is 1.

A minimal example of a ``test_yyy.py`` file that implements tests for
a Scipy package module ``numpy.xxx.yyy`` containing a function
``zzz()``, is shown below::

  import sys
  from numpy.testing import *

  set_package_path()
  # import xxx symbols
  from xxx.yyy import zzz
  restore_path()

  #Optional:
  set_local_path()
  # import modules that are located in the same directory as this file.
  restore_path()

  class test_zzz(NumpyTestCase):
      def check_simple(self, level=1):
          assert zzz()=='Hello from zzz'
      #...

  if __name__ == "__main__":
      NumpyTest().run()

``NumpyTestCase`` is derived from ``unittest.TestCase`` and it
basically only implements an additional method ``measure(self,
code_str, times=1)``.

Note that all classes that are inherited from ``TestCase`` class, are
picked up by the test runner when using ``testoob``.

``numpy.testing`` module provides also the following convenience
functions::

  assert_equal(actual,desired,err_msg='',verbose=1)
  assert_almost_equal(actual,desired,decimal=7,err_msg='',verbose=1)
  assert_approx_equal(actual,desired,significant=7,err_msg='',verbose=1)
  assert_array_equal(x,y,err_msg='')
  assert_array_almost_equal(x,y,decimal=6,err_msg='')
  rand(*shape) # returns random array with a given shape

``NumpyTest`` can be used for running ``tests/test_*.py`` scripts.
For instance, to run all test scripts of the module ``xxx``, execute
in Python:

  >>> NumpyTest('xxx').test(level=1,verbosity=1)

or equivalently,

  >>> import xxx
  >>> NumpyTest(xxx).test(level=1,verbosity=1)

To run only tests for ``xxx.yyy`` module, execute:

  >>> NumpyTest('xxx.yyy').test(level=1,verbosity=1)

To take the level and verbosity parameters for tests from
``sys.argv``, use ``NumpyTest.run()`` method (this is supported only
when ``optparse`` is installed).

Extra features in NumPy Distutils
'''''''''''''''''''''''''''''''''

Specifing config_fc options for libraries in setup.py script
------------------------------------------------------------

It is possible to specify config_fc options in setup.py scripts.
For example, using

  config.add_library('library',
                     sources=[...],
                     config_fc={'noopt':(__file__,1)})

will compile the ``library`` sources without optimization flags.

It's recommended to specify only those config_fc options in such a way
that are compiler independent.

Getting extra Fortran 77 compiler options from source 
-----------------------------------------------------

Some old Fortran codes need special compiler options in order to
work correctly. In order to specify compiler options per source
file, ``numpy.distutils`` Fortran compiler looks for the following
pattern::

  CF77FLAGS(<fcompiler type>) = <fcompiler f77flags>

in the first 20 lines of the source and use the ``f77flags`` for
specified type of the fcompiler (the first character ``C`` is optional). 

TODO: This feature can be easily extended for Fortran 90 codes as
well. Let us know if you would need such a feature.
