[ Avaa Bypassed ]

"""
An enhanced distutils, providing support for Fortran compilers, for BLAS,
LAPACK and other common libraries for numerical computing, and more.

Public submodules are::

    misc_util
    system_info
    cpu_info
    log
    exec_command

For details, please see the *Packaging* and *NumPy Distutils User Guide*
sections of the NumPy Reference Guide.

For configuring the preference for and location of libraries like BLAS and
LAPACK, and for setting include paths and similar build options, please see
``site.cfg.example`` in the root of the NumPy repository or sdist.

"""

import warnings

# Must import local ccompiler ASAP in order to get
# customized CCompiler.spawn effective.
from . import ccompiler
from . import unixccompiler

from .npy_pkg_config import *

warnings.warn("\n\n"
    "  `numpy.distutils` is deprecated since NumPy 1.23.0, as a result\n"
    "  of the deprecation of `distutils` itself. It will be removed for\n"
    "  Python >= 3.12. For older Python versions it will remain present.\n"
    "  It is recommended to use `setuptools < 60.0` for those Python versions.\n"
    "  For more details, see:\n"
    "    https://numpy.org/devdocs/reference/distutils_status_migration.html \n\n",
    DeprecationWarning, stacklevel=2
)
del warnings

# If numpy is installed, add distutils.test()
try:
    from . import __config__
    # Normally numpy is installed if the above import works, but an interrupted
    # in-place build could also have left a __config__.py.  In that case the
    # next import may still fail, so keep it inside the try block.
    from numpy._pytesttester import PytestTester
    test = PytestTester(__name__)
    del PytestTester
except ImportError:
    pass


def customized_fcompiler(plat=None, compiler=None):
    from numpy.distutils.fcompiler import new_fcompiler
    c = new_fcompiler(plat=plat, compiler=compiler)
    c.customize()
    return c

def customized_ccompiler(plat=None, compiler=None, verbose=1):
    c = ccompiler.new_compiler(plat=plat, compiler=compiler, verbose=verbose)
    c.customize('')
    return c