d expects to load the same
                   libraries at run-time.
                   In NumPy 1.21+ on macOS, 'accelerate' (Apple's Accelerate BLAS
                   library) is in the default build-time search order after
                   'openblas'.

                Examples
                --------
                >>> import numpy as np
                >>> np.show_config()
                blas_opt_info:
                    language = c
                    define_macros = [('HAVE_CBLAS', None)]
                    libraries = ['openblas', 'openblas']
                    library_dirs = ['/usr/local/lib']
                """
                from numpy.core._multiarray_umath import (
                    __cpu_features__, __cpu_baseline__, __cpu_dispatch__
                )
                for name,info_dict in globals().items():
                    if name[0] == "_" or type(info_dict) is not type({}): continue
                    print(name + ":")
                    if not info_dict:
                        print("  NOT AVAILABLE")
                    for k,v in info_dict.items():
                        v = str(v)
                        if k == "sources" and len(v) > 200:
                            v = v[:60] + " ...\n... " + v[-60:]
                        print("    %s = %s" % (k,v))

                features_found, features_not_found = [], []
                for feature in __cpu_dispatch__:
                    if __cpu_features__[feature]:
                        features_found.append(feature)
                    else:
                        features_not_found.append(feature)

                print("Supported SIMD extensions in this NumPy install:")
                print("    baseline = %s" % (','.join(__cpu_baseline__)))
                print("    found = %s" % (','.join(features_found)))
                print("    not found = %s" % (','.join(features_not_found)))

                    N)