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Within the scope of a linked C library, this is true. But when your Python code is shuttling chunks of data between libraries it's less so. Pure Julia has the a
by jacques_chester 7y ago
Within the scope of a linked C library, this is true. But when your Python code is shuttling chunks of data between libraries it's less so. Pure Julia has the advantage that it can perform global optimisations that Python-wrapping-C can't.
- mlthoughts2018 7y agoI disagree. In practice the things I can do between Cython, llvmlite and numba are very low effort, wide reach optimizations. Practically, I have never found a case when a feature of Julia would have made this much easier for me. As a result, the tradeoff of Julia continues to be 100% focused on the switching costs, infrastructure maturity, drop in equivalents of well worn Python libraries, etc.