Description
Solve convex optimization problems from Python with numerical routines for linear, quadratic, and cone-based models. It helps researchers and engineers compute decisions under mathematical constraints.
This is a scientific computing library, not a general calculator. Results depend on the model, scaling, solver settings, and input data, so important decisions should validate solutions independently.