efficiently sample sequences of consecutive integers that terminate in the same number from a numpy array?

Suppose I have the following numpy array:

Space = np.arange(7) 

Question: How could I generate a set of N samples from Space such that:

1. Each sample consist only of increasing or decreasing consecutive numbers
2. The sampling is done with replacement so the sample need not be monotonically increasing or decreasing.
3. Each sample ends with a 6 or 0, and
4. There is no limitation on the length of the samples (however each sample terminates once a 6 or 0 has been selected).

In essence I'm creating a markov reward process via numpy sampling (There is probably a more efficient packet for this, but i'm not sure what it would be.) For example if N = 3, a possible sampled set would look something like this.

Sample = [[1,0],[4, 3, 4, 5, 6],[4, 3, 2, 1, 2, 1, 0]]

I can accomplish this with something not very elegant like this:

N = len(Space)
Set = []
for i in range(3):
    X = np.random.randint(N)
    if (X == 0) | (X==6):
        Set.append(X)
    else:
        Sample = []
        while (X !=0) & (X != 6):
            Next = np.array([X-1, X+1])
            X = np.random.choice(Next)
            Sample.append(X)
        Set.append(Sample)
return(Set)

But I was wondering what a more efficient/pythonic way to go about this type of sampling, perhaps without so many loops? Or alternatively if there are better python libraries for this sort of thing? Thanks.