Discretization size and Recurrence period of numpy uniform

My queries are regarding the generation of the uniform random number generator using numpy.random.uniform on [0,1).

a) Does this implementation involve a uniform step-size, i.e. are the universe of possibilities {0,a,2a,...,Na} where (N+1)a = 1 and a is constant?

b) If the above is true, then what's the value of this step-size? I noticed that the value of numpy.nextafter(x,y) keeps on changing depending upon x. Hence my question regarding whether a uniform step-size was used to implement numpy.random.uniform.

c) If the step-size is not uniform, then what would be the best way to figure out the number of unique values that numpy.random.uniform(low=0, high=1) can take?

d) What's the recurrence period of numpy.random.uniform, i.e. after how many samplings will I see my original number again? For maximum efficiency, this should be equal to the number of unique values.

I tried looking up the source code at Github but didn't find anything directly interpretable there.