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Indexing and Slicing
Because strings are defined as ordered collections of characters, we can access their components by position. In Python, characters in a string are fetched by indexing—providing the numeric offset of the desired component in square brackets after the string. You get back the one-character string at the specified position.
As in the C language, Python offsets start at 0 and end at one less than the length of the string. Unlike C, however, Python also lets you fetch items from sequences such as strings using negative offsets. Technically, a negative offset is added to the length of a string to derive a positive offset. You can also think of negative offsets as counting backward from the end. The following interaction demonstrates:
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>>> S = 'spam'
>>> S[0], S[−2] # Indexing from front or end
('s', 'a')
>>> S[1:3], S[1:], S[:−1] # Slicing: extract a section
('pa', 'pam', 'spa')
The first line defines a four-character string and assigns it the name S. The next line indexes it in two ways: S[0] fetches the item at offset 0 from the left (the one-character string 's'), and S[−2] gets the item at offset 2 back from the end (or equivalently, at offset (4 + (–2)) from the front). Offsets and slices map to cells as shown in Figure 7-1.[20]
Figure 7-1. Offsets and slices: positive offsets start from the left end (offset 0 is the first item), and negatives count back from the right end (offset −1 is the last item). Either kind of offset can be used to give positions in indexing and slicing operations.
The last line in the preceding example demonstrates slicing, a generalized form of indexing that returns an entire section, not a single item. Probably the best way to think of slicing is that it is a type of parsing (analyzing structure), especially when applied to strings—it allows us to extract an entire section (substring) in a single step. Slices can be used to extract columns of data, chop off leading and trailing text, and more. In fact, we’ll explore slicing in the context of text parsing later in this chapter.
The basics of slicing are straightforward. When you index a sequence object such as a string on a pair of offsets separated by a colon, Python returns a new object containing the contiguous section identified by the offset pair. The left offset is taken to be the lower bound (inclusive), and the right is the upper bound (noninclusive). That is, Python fetches all items from the lower bound up to but not including the upper bound, and returns a new object containing the fetched items. If omitted, the left and right bounds default to 0 and the length of the object you are slicing, respectively.
For instance, in the example we just saw, S[1:3] extracts the items at offsets 1 and 2: it grabs the second and third items, and stops before the fourth item at offset 3. Next, S[1:] gets all items beyond the first—the upper bound, which is not specified, defaults to the length of the string. Finally, S[:−1] fetches all but the last item—the lower bound defaults to 0, and −1 refers to the last item, noninclusive.
This may seem confusing at first glance, but indexing and slicing are simple and powerful tools to use, once you get the knack. Remember, if you’re unsure about the effects of a slice, try it out interactively. In the next chapter, you’ll see that it’s even possible to change an entire section of another object in one step by assigning to a slice (though not for immutables like strings). Here’s a summary of the details for reference:
- Indexing (S[i]) fetches components at offsets:
- The first item is at offset 0.
- Negative indexes mean to count backward from the end or right.
- S[0] fetches the first item.
- S[−2] fetches the second item from the end (like S[len(S)−2]).
- Slicing (S[i:j]) extracts contiguous sections of sequences:
- The upper bound is noninclusive.
- Slice boundaries default to 0 and the sequence length, if omitted.
- S[1:3] fetches items at offsets 1 up to but not including 3.
- S[1:] fetches items at offset 1 through the end (the sequence length).
- S[:3] fetches items at offset 0 up to but not including 3.
- S[:−1] fetches items at offset 0 up to but not including the last item.
- S[:] fetches items at offsets 0 through the end—this effectively performs a top-level copy of S.
The last item listed here turns out to be a very common trick: it makes a full top-level copy of a sequence object—an object with the same value, but a distinct piece of memory (you’ll find more on copies in Chapter 9). This isn’t very useful for immutable objects like strings, but it comes in handy for objects that may be changed in-place, such as lists.
In the next chapter, you’ll see that the syntax used to index by offset (square brackets) is used to index dictionaries by key as well; the operations look the same but have different interpretations.
Extended slicing: the third limit and slice objects
In Python 2.3 and later, slice expressions have support for an optional third index, used as a step (sometimes called a stride). The step is added to the index of each item extracted. The full-blown form of a slice is now X[I:J:K], which means “extract all the items in X, from offset I through J−1, by K.” The third limit, K, defaults to 1, which is why normally all items in a slice are extracted from left to right. If you specify an explicit value, however, you can use the third limit to skip items or to reverse their order.
For instance, X[1:10:2] will fetch every other item in X from offsets 1–9; that is, it will collect the items at offsets 1, 3, 5, 7, and 9. As usual, the first and second limits default to 0 and the length of the sequence, respectively, so X[::2] gets every other item from the beginning to the end of the sequence:
>>> S = 'abcdefghijklmnop'
>>> S[1:10:2]
'bdfhj'
>>> S[::2]
'acegikmo'
You can also use a negative stride. For example, the slicing expression "hello"[::−1] returns the new string "olleh"—the first two bounds default to 0 and the length of the sequence, as before, and a stride of −1 indicates that the slice should go from right to left instead of the usual left to right. The effect, therefore, is to reverse the sequence:
>>> S = 'hello'
>>> S[::−1]
'olleh'
With a negative stride, the meanings of the first two bounds are essentially reversed. That is, the slice S[5:1:−1] fetches the items from 2 to 5, in reverse order (the result contains items from offsets 5, 4, 3, and 2):
>>> S = 'abcedfg'
>>> S[5:1:−1]
'fdec'
Skipping and reversing like this are the most common use cases for three-limit slices, but see Python’s standard library manual for more details (or run a few experiments interactively). We’ll revisit three-limit slices again later in this book, in conjunction with the for loop statement.
Later in the book, we’ll also learn that slicing is equivalent to indexing with a slice object, a finding of importance to class writers seeking to support both operations:
>>> 'spam'[1:3] # Slicing syntax
'pa'
>>> 'spam'[slice(1, 3)] # Slice objects
'pa'
>>> 'spam'[::-1]
'maps'
>>> 'spam'[slice(None, None, −1)]
'maps'
Why You Will Care: Slices
Throughout this book, I will include common use case sidebars (such as this one) to give you a peek at how some of the language features being introduced are typically used in real programs. Because you won’t be able to make much sense of real use cases until you’ve seen more of the Python picture, these sidebars necessarily contain many references to topics not introduced yet; at most, you should consider them previews of ways that you may find these abstract language concepts useful for common programming tasks.
For instance, you’ll see later that the argument words listed on a system command line used to launch a Python program are made available in the argv attribute of the built-in sys module:
# File echo.py
import sys
print(sys.argv)
% python echo.py −a −b −c
['echo.py', '−a', '−b', '−c']
Usually, you’re only interested in inspecting the arguments that follow the program name. This leads to a very typical application of slices: a single slice expression can be used to return all but the first item of a list. Here, sys.argv[1:] returns the desired list, ['−a', '−b', '−c']. You can then process this list without having to accommodate the program name at the front.
Slices are also often used to clean up lines read from input files. If you know that a line will have an end-of-line character at the end (a \n newline marker), you can get rid of it with a single expression such as line[:−1], which extracts all but the last character in the line (the lower limit defaults to 0). In both cases, slices do the job of logic that must be explicit in a lower-level language.
Note that calling the line.rstrip method is often preferred for stripping newline characters because this call leaves the line intact if it has no newline character at the end—a common case for files created with some text-editing tools. Slicing works if you’re sure the line is properly terminated.
