Python: How to perform PCA with promax rotation?

How can I perform PCA in python, from SVD and eigenvalue decomposition with promax rotation? I've implemented a function that returns a rotation matrix such that the rotated loadings are and the rotated left singular vectors are . How can I get the equivalent for an oblique promax rotation? A numpy-based solution would be great