  We present a simple algorithm that perfectly samples configurations from the
unique Gibbs measure of a spin system on a potentially infinite graph $G$. The
sampling algorithm assumes strong spatial mixing together with subexponential
growth of $G$. It produces a finite window onto a perfect sample from the Gibbs
distribution. The run-time is linear in the size of the window.
