PyPy is an amazing project, but if you're really writing performance sensitive code then relying on the heuristics of a JIT is a dangerous game. There are also a lot of things that PyPy's JIT just can't realistically optimize.

Just because something generates native code does not mean it "runs as fast as C". Semantics of a particular language can force it to do more job without any chance to optimize that away.

For example, if you modify C compiler to make integer operations clamp at min/max rather than overflowing, it will always be times slower than original at number crunching, and there would be no way to overcome that.