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RPython is not intended for humans to write programs in, it's for implementing interpreters. If you're after a faster Python, you should use PyPy not RPython.

Numba gives you JIT compilation annotations for parallel vector operations--it's a little bit like OpenMP for Python, in a way.

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I just look forward to have a proper JIT as part of regular Python, as PyPy still seems to be an underdog, and JIT research for dynamic languages on GraalVM and OpenJ9 seems more focused on Ruby, hence why I kind of hope that Julia puts some pressure into the eco-system.

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