It’s surprising how many problems can be expressed as mathematical optimization problems and often convex problems that can be efficiently solved. CVXPY is an open source Python-embedded modeling language for convex optimization problems. It’s maintained by academics at Stanford University and offers a batteries-included install for several open source and commercial solvers. The documentation includes many examples which should inspire developers to use it. It’s particularly useful for prototyping solutions even though commercially licensed solvers, such Gurobi or IBM CPLEX, may be required. In most cases though, it suffices by itself. However, the same group has written many extension packages such as DCCP and related software such as CVXOPT based on recent advances in optimization.
