Dear all, In [1], I have proposed a new keyword for scipy.linalg.lu function, with prospective name "p_indices" as a bool switch. This will have the effect of having the permutation matrix P in A = P L U decomposition returned as a vector of indices such as [3, 1, 2, 0] meaning first and fourth row is swapped. With this you can still compute A through L[P, :] @ U without allocating a very costly 2D matrix of 1s and 0s. In tall arrays, say 400x10, the resulting 2D array P is 400x400 and in the vector form this reduces to 400x1. Hence, the switch to control this behavior is done by a new keyword and I don't know if "p_indices" is a nice one (doesn't feel like it). I considered, return_indices, perm_as_1d, p_as_1d, p_as_vec and bunch more but either too many underscores or too verbose. Thus, I'd like to ask for either validation or new ideas. We should maybe ping the NumPy audience for this too as this has no counterpart in NumPy. Thanks, ilhan [1] : https://github.com/scipy/scipy/pull/18358