Generating random vectors of Euclidean norm <= 1 in Python?

More specifically, given a natural number d, how can I generate random vectors in R^d such that each vector x has Euclidean norm <= 1?

Generating random vectors via numpy.random.rand(1,d) is no problem, but the likelihood of such a random vector having norm <= 1 is predictably bad for even not-small d. For example, even for d = 10 about 0.2% percent of such random vectors have appropriately small norm. So that seems like a silly solution.

EDIT: Re: Walter's comment, yes, I'm looking for a uniform distribution over vectors in the unit ball in R^d.