Seeding random number generators in parallel programs

I am studing the multiprocessing module of Python. I have two cases:

Ex. 1

def Foo(nbr_iter):
    for step in xrange(int(nbr_iter)) :
        print random.uniform(0,1)
...

from multiprocessing import Pool

if __name__ == "__main__":
    ...
    pool = Pool(processes=nmr_parallel_block)
    pool.map(Foo, nbr_trial_per_process)

Ex 2. (using numpy)

 def Foo_np(nbr_iter):
     np.random.seed()
     print np.random.uniform(0,1,nbr_iter)

In both cases the random number generators are seeded in their forked processes.

Why do I have to do the seeding explicitly in the numpy example, but not in the Python example?