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> I don’t think the productivity gap is as large as the performance gap anymore. It's impossible to make a general statement like this. Every project has a d

• dkersten 8y ago
  Sure it’s a bit over-general. Having said that, when I write bad C++ code t still typically runs faster than decent Python code, for typical use cases. I also don’t find the productivity loss of using C++, as a language (I mean, I’d still be more productive using django than a c++ web framework, just because django is super comprehensive), isn’t all that great. Also, when I need performance in C++, I have a lot more options than in Python and even on core data structures I have options (eg in Python I have a list, in c++ I have linked lists, vectors, deques, destructive versions of these, arrays, trees... memory pooled versions, cache line aligned versions, parallel versions etc). Don’t get me wrong, for many use cases where Python is often used, like web development, I’d much rather use and be more productive in Python, but I disagree with the premise that Python is so much more productive than C++ that the performance overhead is negligible. Even if in most cases the cost is worth it. It’s worth noting a counter to my argument though and that is for data analysis, Python is largely just glue between libraries that are implemented in C, so the performance difference here is largely negligible.