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+NumPy is a general-purpose array-processing package designed to
+efficiently manipulate large multi-dimensional arrays of arbitrary
+records without sacrificing too much speed for small multi-dimensional
+arrays.  NumPy is built on the Numeric code base and adds features
+introduced by numarray as well as an extended C-API and the ability to
+create arrays of arbitrary type which also makes NumPy suitable for
+interfacing with general-purpose data-base applications.
+
+There are also basic facilities for discrete fourier transform, basic
+linear algebra and random number generation.
+
+If you need to build numpy for debugging, set DEBUG=y. If you use
+software which is having problems with numpy's new relaxed strides
+checking, set NPY_RSC=0.
+
+It is highly recommended to install libraries implementing BLAS and
+LAPACK before installing numpy. You may choose between:
+   a) BLAS and LAPACK (unoptimized reference implementation, thus slow)
+   b) OpenBLAS (optimized, provides LAPACK too)
+   c) ATLAS and LAPACK (optimized), good to read README.ATLAS
+All these are available on SlackBuilds.org.
+
+If you want to use the UMFPACK library instead of SuperLU to solve
+unsymmetric sparse linear systems, then run this Slackbuild with
+NO_UMFPACK set to "no" and then install scikit-umfpack on top of
+scipy. In this context, UMFPACK is an optional dependency for
+numpy.
+
+IMPORTANT: The version installed by this SlackBuild does NOT include the
+           oldnumeric and numarray compatibility modules since
+           starting with version 1.9.0 these modules was removed by
+           the numpy developers.  If you need these compatibility
+           modules please consider the numpy-legacy SlackBuild which
+           is available for python2 only and does not conflict with this
+           installation of numpy.
+