# distutils.misc_util

numpy.distutils.misc_util.all_strings(lst)

  Return True if all items in lst are string objects.

numpy.distutils.misc_util.allpath(name)

  Convert a /-separated pathname to one using the OS’s path separator.

numpy.distutils.misc_util.appendpath(prefix, path)

numpy.distutils.misc_util.as_list(seq)

numpy.distutils.misc_util.blue_text(s)

numpy.distutils.misc_util.cyan_text(s)

numpy.distutils.misc_util.cyg2win32(path: str) → str

  Convert a path from Cygwin-native to Windows-native.

  Uses the cygpath utility (part of the Base install) to do the actual conversion. Falls back to returning the original path if this fails.

  Handles the default `/cygdrive` mount prefix as well as the `/proc/cygdrive` portable prefix, custom cygdrive prefixes such as `/` or `/mnt`, and absolute paths such as `/usr/src/` or `/home/username`

  Parameters:
    path str

      The path to convert

  Returns:
    converted_path str

      The converted path

  Notes

  Documentation for cygpath utility: https://cygwin.com/cygwin-ug-net/cygpath.html Documentation for the C function it wraps: https://cygwin.com/cygwin-api/func-cygwin-conv-path.html

numpy.distutils.misc_util.default_config_dict(name=None, parent_name=None, local_path=None)

  Return a configuration dictionary for usage in configuration() function defined in file setup_<name>.py.

numpy.distutils.misc_util.dict_append(d, **kws)

numpy.distutils.misc_util.dot_join(*args)

numpy.distutils.misc_util.exec_mod_from_location(modname, modfile)

  Use importlib machinery to import a module modname from the file modfile. Depending on the spec.loader, the module may not be registered in sys.modules.

numpy.distutils.misc_util.filter_sources(sources)

  Return four lists of filenames containing C, C++, Fortran, and Fortran 90 module sources, respectively.

numpy.distutils.misc_util.generate_config_py(target)

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

  Usage:

    config[‘py_modules’].append((packagename, ‘__config__’,generate_config_py))

numpy.distutils.misc_util.get_build_architecture()

numpy.distutils.misc_util.get_cmd(cmdname, _cache={})

numpy.distutils.misc_util.get_data_files(data)

numpy.distutils.misc_util.get_dependencies(sources)

numpy.distutils.misc_util.get_ext_source_files(ext)

numpy.distutils.misc_util.get_frame(level=0)

  Return frame object from call stack with given level.

numpy.distutils.misc_util.get_info(pkgname, dirs=None)

  Return an info dict for a given C library.

  The info dict contains the necessary options to use the C library.

  Parameters:
    pkgname str

      Name of the package (should match the name of the .ini file, without the extension, e.g. foo for the file foo.ini).

    dirs sequence, optional

      If given, should be a sequence of additional directories where to look for npy-pkg-config files. Those directories are searched prior to the NumPy directory.

  Returns:
    info dict

      The dictionary with build information.

  Raises:
    PkgNotFound

      If the package is not found.

  See also

  `Configuration.add_npy_pkg_config`, `Configuration.add_installed_library`
  `get_pkg_info`

  Examples

  To get the necessary information for the npymath library from NumPy:

      >>> npymath_info = np.distutils.misc_util.get_info('npymath')
      >>> npymath_info
      {'define_macros': [], 'libraries': ['npymath'], 'library_dirs':
      ['.../numpy/core/lib'], 'include_dirs': ['.../numpy/core/include']}

  This info dict can then be used as input to a `Configuration` instance:

      config.add_extension('foo', sources=['foo.c'], extra_info=npymath_info)

numpy.distutils.misc_util.get_language(sources)

  Determine language value (c,f77,f90) from sources

numpy.distutils.misc_util.get_lib_source_files(lib)

numpy.distutils.misc_util.get_mathlibs(path=None)

  Return the MATHLIB line from numpyconfig.h

numpy.distutils.misc_util.get_num_build_jobs()

  Get number of parallel build jobs set by the –parallel command line argument of setup.py If the command did not receive a setting the environment variable NPY_NUM_BUILD_JOBS is checked. If that is unset, return the number of processors on the system, with a maximum of 8 (to prevent overloading the system if there a lot of CPUs).

  Returns:
    out int

      number of parallel jobs that can be run

numpy.distutils.misc_util.get_numpy_include_dirs()

numpy.distutils.misc_util.get_pkg_info(pkgname, dirs=None)

  Return library info for the given package.

  Parameters:
    pkgname str

      Name of the package (should match the name of the .ini file, without the extension, e.g. foo for the file foo.ini).

    dirs sequence, optional

      If given, should be a sequence of additional directories where to look for npy-pkg-config files. Those directories are searched prior to the NumPy directory.

  Returns:
    pkginfo class instance

      The LibraryInfo instance containing the build information.

  Raises:
    PkgNotFound

      If the package is not found.

  See also

  `Configuration.add_npy_pkg_config`, `Configuration.add_installed_library`
  `get_info`

numpy.distutils.misc_util.get_script_files(scripts)

numpy.distutils.misc_util.gpaths(paths, local_path='', include_non_existing=True)

  Apply glob to paths and prepend local_path if needed.

numpy.distutils.misc_util.green_text(s)

numpy.distutils.misc_util.has_cxx_sources(sources)

  Return True if sources contains C++ files

numpy.distutils.misc_util.has_f_sources(sources)

  Return True if sources contains Fortran files

numpy.distutils.misc_util.is_local_src_dir(directory)

  Return true if directory is local directory.

numpy.distutils.misc_util.is_sequence(seq)

numpy.distutils.misc_util.is_string(s)

numpy.distutils.misc_util.mingw32()

  Return true when using mingw32 environment.

numpy.distutils.misc_util.minrelpath(path)

  Resolve and ‘.’ from path.

numpy.distutils.misc_util.njoin(*path)

  Join two or more pathname components + - convert a /-separated pathname to one using the OS’s path separator. - resolve and from path.

  Either passing n arguments as in njoin(‘a’,’b’), or a sequence of n names as in njoin([‘a’,’b’]) is handled, or a mixture of such arguments.

numpy.distutils.misc_util.red_text(s)

numpy.distutils.misc_util.sanitize_cxx_flags(cxxflags)

  Some flags are valid for C but not C++. Prune them.

numpy.distutils.misc_util.terminal_has_colors()

numpy.distutils.misc_util.yellow_text(s)