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Is this the remaining major hurdle toward getting mega-libraries like SciPy, pandas, and BioPython to work? Or will the C API in PyPy always be less performant than CPython?

If more people start using PyPy for ad-hoc data analysis, it could help nudge it out of its niche into the mainstream.

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Yes, the remaining part is a hurdle, but hopefully not a very big one. The interface will always be slower, but hopefully you won't have to interact with it much (you almost never do with scipy). We have a cunning plan on how to make the numpy interface faster though, stay tuned [To recap: generic-cpython-extension-border-crossing will always be slower, btu maybe we can do hacks for numpy]

Thanks for all the hard work you guys put in! Seriously, I'm hoping for the best. Glad you're thinking about numpy too.

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