I never called it a strength; I simply don't care how fast Python is because I don't need to. Reasoning about what is going on under the hood with Python is just easier than Julia - if it needs to be fast, it's a fast external library being used.

This is really a minor issue stemming from the relative maturity of the languages - if Julia becomes more established I would hope usage of external libraries which don't offer a performance advantage (ie everything besides C and Fortran) eventually gets replaced with native packages to preserve the sanity of the users.