This is a rather simple and appealing method after von Neumann. Assume that we are looking at an interval $x\in [a,b]$, this being the domain of the PDF $p(x)$. Suppose also that the largest value our distribution function takes in this interval is $M$, that is $$\begin{equation*} p(x) \le M \hspace{1cm} x\in [a,b]. \end{equation*}$$ Then we generate a random number $x$ from the uniform distribution for $x\in [a,b]$ and a corresponding number $s$ for the uniform distribution between $[0,M]$. If $$\begin{equation*} p(x) \ge s, \end{equation*}$$ we accept the new value of $x$, else we generate again two new random numbers $x$ and $s$ and perform the test in the latter equation again.