  SnapVX is a high-performance Python solver for convex optimization problems
defined on networks. For these problems, it provides a fast and scalable
solution with guaranteed global convergence. SnapVX combines the capabilities
of two open source software packages: Snap.py and CVXPY. Snap.py is a large
scale graph processing library, and CVXPY provides a general modeling framework
for small-scale subproblems. SnapVX offers a customizable yet easy-to-use
interface with out-of-the-box functionality. Based on the Alternating Direction
Method of Multipliers (ADMM), it is able to efficiently store, analyze, and
solve large optimization problems from a variety of different applications.
Documentation, examples, and more can be found on the SnapVX website at
http://snap.stanford.edu/snapvx.
