About indexing and slicing

At the beginning of this chapter, we saw slicing applied on strings. Slicing, in general, applies to a sequence: tuples, lists, strings, and so on. With lists, slicing can also be used for assignment. I've almost never seen this used in professional code, but still, you know you can. Could you slice dictionaries or sets? I hear you scream, Of course not!. Excellent; I see we're on the same page here, so let's talk about indexing.

There is one characteristic about Python indexing I haven't mentioned before. I'll show you by way of an example. How do you address the last element of a collection? Let's see:

>>> a = list(range(10))  # `a` has 10 elements. Last one is 9.
>>> a
[0, 1, 2, 3, 4, 5, 6, 7, 8, 9]
>>> len(a)  # its length is 10 elements
10
>>> a[len(a) - 1]  # position of last one is len(a) - 1
9
>>> a[-1]  # but we don't need len(a)! Python rocks!
9
>>> a[-2]  # equivalent to len(a) - 2
8
>>> a[-3]  # equivalent to len(a) - 3
7

If the list a has 10 elements, because of the 0-index positioning system of Python, the first one is at position 0 and the last one is at position 9. In the preceding example, the elements are conveniently placed in a position equal to their value: 0 is at position 0, 1 at position 1, and so on.

So, in order to fetch the last element, we need to know the length of the whole list (or tuple, or string, and so on) and then subtract 1. Hence: len(a) - 1. This is so common an operation that Python provides you with a way to retrieve elements using negative indexing. This proves very useful when you do data manipulation. Here's a nice diagram about how indexing works on the string "HelloThere" (which is Obi-Wan Kenobi sarcastically greeting General Grievous):

Trying to address indexes greater than 9 or smaller than -10 will raise an IndexError, as expected.