Is there a way to solve yB = c without computing the right inverse?
You can transpose the equation and then use linalg.solve.
I would like to solve an equation of the form yB = c, where y is my unknown (possibly a matrix). However the B matrix is not well conditioned, and I would like to have a method similar to numpy.linalg.solve in order to maintain the numerical accuracy of the solution.  
I have tried to simply use the inverse of B, with numpy.linalg.inv, to find the solution y = cB^-1 as well as using the pseudo-inverse (numpy.linalg.pinv), but they prooved to be not accurate enough...
I have also looked into the QR decomposition, since numpy provides the method for it, in order to adapt it to the right inverse case, but here I struggle with the algebra.
Is there an accurate way to solve this equation ? Or is there an equivalent to numpy.linalg.solve for the right inverse ?