random numpy array whose values are between -1 and 1 and sum to 1

what is the best way to create a NumPy array x of a given size with values randomly (and uniformly?) spread between -1 and 1, and that also sum to 1 ?

I tried 2*np.random.rand(size)-1 and np.random.uniform(-1,1,size) based on the discussion here, but if I take a transformation approach, by re-scaling both methods by their sum afterwards, x/=np.sum(x), this ensures the elements sum to 1, but: there are elements in the array that are suddenly much greater or less than 1 (>1, <-1) which is not wanted.