LINPACK_D is a Python library which solves systems of linear equations for a variety of matrix types and storage modes, by Jack Dongarra, Jim Bunch, Cleve Moler, Pete Stewart.
MATLAB already provides a wide set of linear equation solvers. This (partial) set of LINPACK routines is provided just for testing and comparison.
LINPACK has officially been superseded by the LAPACK library. The LAPACK library uses more modern algorithms and code structure. However, the LAPACK library can be extraordinarily complex; what is done in a single LINPACK routine may correspond to 10 or 20 utility routines in LAPACK. This is fine if you treat LAPACK as a black box. But if you wish to learn how the algorithm works, or to adapt it, or to convert the code to another language, this is a real drawback. This is one reason I still keep a copy of LINPACK around.
Versions of LINPACK in various arithmetic precisions are available through the NETLIB web site.
The computer code and data files described and made available on this web page are distributed under the GNU LGPL license.
LINPACK_D is available in a C version and a C++ version and a FORTRAN77 version and a FORTRAN90 version and a MATLAB version and a Python version.
CONDITION, a Python library which implements methods of computing or estimating the condition number of a matrix.
TEST_MAT, a Python library which defines test matrices.
WATHEN, a Python library which compares storage schemes (full, banded, sparse triplet, sparse) and solution strategies (A\x, Linpack, conjugate gradient) for linear systems involving the Wathen matrix, which can arise when solving a problem using the finite element method (FEM).
Original FORTRAN77 version by Jack Dongarra, Jim Bunch, Cleve Moler, Pete Stewart. Python version by John Burkardt.
You can go up one level to the Python source codes.