numpy (matrix solver) - python vs. matlab

[Eelco]

There is linalg.pinv, which computes a pseudoinverse based on SVD that
works on all matrices, regardless of the rank of the matrix. It merely
approximates A*A.I = I as well as A permits though, rather than being
a true inverse, which may not exist.

Anyway, there are no general answers for this kind of thing. In all
non-textbook problems I can think of, the properties of your matrix
are highly constrained by the problem you are working on; which
additional tests are required to check for corner cases thus depends
on the problem. Often, if you have found an elegant solution to your
problem, no such corner cases exist. In that case, MATLAB is just
wasting your time with its automated checks.