Here is an R function that produces a Metropolis-Hastings sample for the univariate log-target f when the later is defined outside as another function. And when using a Gaussian random walk with scale one as proposal. (Inspired from a X validated question.)
The function is definitely not optimal, crashes for values of T larger than 580 (unless one modifies the stack size), and operates the most basic version of a Metropolis-Hastings algorithm. But as a codegolf challenge (on a late plane ride), this was a fun exercise.