Just for the sake of comprehensiveness, I ran your Python benchmark through 
the Numba JIT library (which uses the same underlying LLVM infrastructure 
that Julia does) and on my computer the Python code is faster than Julia by 
68%. Vanilla CPython is terrible for this kind of simple explicit loop 
code, but Numba and other JIT libraries largely solve that issue with 
minimal effort as long as the code is simple enough. That by no means 
solves all of Python's issues in the context of numerical programming and 
I'm sure the Julia benchmark could be improved as others have already 
mentioned, but benchmarking Python this way isn't necessarily 
representative of how a performance-conscious programmer would reasonably 
approach a problem of this kind.

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