Yet, numpy exists for python, so why can't you use it in a comparison? Why can't you use libraries for languages? The python approach is all about gluing bits

Yet, numpy exists for python, so why can't you use it in a comparison? Why can't you use libraries for languages? The python approach is all about gluing bits together, not staying within a pure walled garden. Also, python is not an implementation of python. These benchmarks are always funny, because real systems use different components, yet the benchmarks stick to some fake, non-real-world way of measuring. Oh, the garbage collection in java pauses for multiple seconds soemtimes... but it's not slow because we ignore that in our benchmarks. Oh, it's not fast the first time, because the jit hasn't warmed up? Let's ignore that in our benchmarks too. Um... yeah. Good one. This benchmark is also flawed to since people would probably use numexpr in the real world. Which is much faster than plain numpy. So python would be even faster than they say. Mercurial(hg) is now faster than git. Git is written by great C hackers (including Linus no less), and yet hg is faster than git. See the facebook benchmarks for evidence. Using the right tool for the job can mean using multiple languages together for where they are best. Want clarity and performance? Then C/asm + python is an ok combination.