In Python, I would like to solve a collection of problems, that are all solvable via MOSEK's conic optimization solvers (ExpCone, SOCP, etc.)
I have tried CVXPY. I get very robust and reliable results, however, the problem formulation times are quite expensive. I am looking for an efficient alternative.
To this end, given that I only use MOSEK, I thought maybe I don't need CVXPY (i.e., I won't switch between solvers, happy just with MOSEK).
Hence, I found the MOSEK API for Python, but it looks less intuitive than CVXPY to formulate disciplined optimization problems. There is also MOSEK Fusion, which looks simpler, but I don't really understand what the difference is.
Hence, I am wondering: given that I need to only use MOSEK, cannot afford large problem-formulation times, and also do not know the MOSEK API but am familiar with CVXPY, what would you recommend me? Which option is the most reasonable one for me?