Efficiently generating a large array of biased coin flips

I am looking for a high-performance Python solution to the following problem:

Flip a biased coin n times so that the probability of heads (=1) is equal to a given probability p. n is in the millions.

I suspect there can be a very efficient numpy-based solution.