glmnet actually does a slightly different check than just a "n" vs "p" comparison like this. It invokes method 1 (covariance method) if p <= 500. The covariance method keeps track of a matrix of covariances C(i,j) for every feature i and every active feature j. And under the hood, C is allocated as a pxp matrix (even though we use much less memory than that usually); this was done out of simplicity because it's very hard to write clever data structures in Fortran. So even when n >> p, if p is also large, this is not a viable default option on most machines.
https://github.com/civisanalytics/python-glmnet/blob/813c06f5fcc9604d8e445bd4992f53c4855cc7cb/glmnet/linear.py#L288-L293
glmnetactually does a slightly different check than just a "n" vs "p" comparison like this. It invokes method 1 (covariance method) if p <= 500. The covariance method keeps track of a matrix of covariances C(i,j) for every feature i and every active feature j. And under the hood, C is allocated as a pxp matrix (even though we use much less memory than that usually); this was done out of simplicity because it's very hard to write clever data structures in Fortran. So even when n >> p, if p is also large, this is not a viable default option on most machines.Anyways, I'd suggest changing to