More precisely, modern CPUs are so much faster than network or file I/O that if your program has to wait on I/O, the CPU is going to sit idle most of the time a

More precisely, modern CPUs are so much faster than network or file I/O that if your program has to wait on I/O, the CPU is going to sit idle most of the time anyway, so trying to optimize CPU time is pointless. The GP's use case is an example: he's capturing HTTP headers, so the bottleneck is network I/O, not CPU. So Python for his use case is, as he says, plenty fast. For use cases where CPU is the bottleneck, such as numeric simulations, Python users reach for something like numpy, where all the CPU intensive stuff is being done in C extensions, not Python bytecode.