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Right up until you have to implement, debug, or enchance these lower-level packages yourself. Then suddenly * 95% of your users can't contribute or even unders

Right up until you have to implement, debug, or enchance these lower-level packages yourself. Then suddenly * 95% of your users can't contribute or even understand what's going on, because they don't understand the language it's written in * even if you do understand, you have to write in a much less expressive language (you came using Python for a reason, but end up doing all the hard work in C) * performance gets lots at the boundary between the languages (which is why Julia nearly always outperforms Numpy) * error messages and bugs often fall through the crack of the two languages The fundamental argument "you can just use Python, you just have to write all the hard stuff in not-Python" is very strange to me.

coldtea 6y ago
>Right up until you have to implement, debug, or enchance these lower-level packages yourself That's the very benefit of a larger ecosystem: you don't. Whereas with a smaller ecosystem, you often do. >95% of your users can't contribute or even understand what's going on, because they don't understand the language it's written in That's even more of a problem with Julia, since the code written in Julia will be unfamiliar to both first level users (much much fewer use Julia than Python) and to library developers (fewer know Julian than C/C++, which such Python libs are written in).