How to generate unique(!) arrays/lists/sequences of uniformly distributed randoms

Let‘s say I generate a pack, i.e. an one dimensional array of 10 random numbers with a random generator. Then I generate another array of 10 random numbers. I do this X times. How can I generate unique arrays, that even after a trillion generations, there is no array which is equal to another?

In one array, the elements can be duplicates. The array just has to differ from the other arrays with at least one different element from all its elements.

Is there any numpy method for this? Is there some special algorithm which works differently by exploring some space for the random generation? I don’t know.

One easy answer would be to write the arrays to a file and check if they were generated already, but the I/O operations on a subsequently bigger file needs way too much time.