What value do I use in a slicing range to include the last value in a numpy array?

Question

Imagine some numpy array, e.g. x = np.linspace(1,10).

x[i:j] gives me a view into x for the range [i,j). I love that I can also do x[i:-k] which excludes the last k elements.

However, in order to include the last element I need to do x[i:].

My question is this: How do I combine these two notations if I for instance need to loop over k.

Say that I want to do this:

l = list()
for k in [5,4,3,2,1]:
    l.append(x[:-k])
l.append(x[:])

What annoys me is that last line. In this simple example of course it doesn't do much of a difference, but sometimes this becomes much more annoying. What I miss is something more DRY-like.

The following snippet course does NOT yield the desired result, but represents the style of code I seek:

l = list()
for k in [5,4,3,2,1,0]:
    l.append(x[:-k])

Answer 1

It's a bit of a pain, but since -0 is the same as 0, there is no easy solution.

One way to do it would be:

l = list()
for k in [5,4,3,2,1,0]:
    l.append(x[:-k or None])

This is because when k is 0, -k or None is None, and x[:None] will do what you want. For other values of k, -k or None will be -k.

I am not sure if I like it myself though.