Learning Python

Lists

Our next stop on the built-in object tour is the Python list. Lists are Python’s most flexible ordered collection object type. Unlike strings, lists can contain any sort of object: numbers, strings, even other lists. Python lists do the work of most of the collection data structures you might have to implement manually in lower-level languages such as C. In terms of some of their main properties, Python lists are:

Ordered collections of arbitrary objects

From a functional view, lists are just a place to collect other objects, so you can treat them as a group. Lists also define a left-to-right positional ordering of the items in the list.

Accessed by offset

Just as with strings, you can fetch a component object out of a list by indexing the list on the object’s offset. Since lists are ordered, you can also do such tasks as slicing and concatenation.

Variable length, heterogeneous, arbitrarily nestable

Unlike strings, lists can grow and shrink in place (they’re variable length), and may contain any sort of object, not just one-character strings (they’re heterogeneous). Because lists can contain other complex objects, lists also support arbitrary nesting; you can create lists of lists of lists, and so on.

Of the category mutable sequence

In terms of our type category qualifiers, lists can be both changed in place (they’re mutable) and respond to all the sequence operations we saw in action on strings in the last section. In fact, sequence operations work the same on lists, so we won’t ...