I think generally people who care about performance don't tend to write their code in Python to begin with, so the culture of python is much less performance sensitive than is typical even among other interpreted languages like perl, php, ruby or javascript. The people who do need performance, but are still using python, tend to rely on native libraries doing significant numerical calculations, and many of these libraries are not compatible with PyPy. The escape hatch there is to offload more and more of the computation into the native runtime rather than to optimize the python performance.
