The Python Standard Library: Data Structures

This chapter covers two modules related to memory management in Python.

Python includes several standard programming data structures, such as list, tuple, dict, and set, as part of its built-in types. Many applications do not require other structures, but when they do, the standard library provides powerful and well-tested versions that are ready to use.

The collections module includes implementations of several data structures that extend those found in other modules. For example, Deque is a double-ended queue that allows the addition or removal of items from either end. The defaultdict is a dictionary that responds with a default value if a key is missing, while OrderedDict remembers the sequence in which items are added to it. And namedtuple extends the normal tuple to give each member item an attribute name in addition to a numeric index.

For large amounts of data, an array may make more efficient use of memory than a list. Since the array is limited to a single data type, it can use a more compact memory representation than a general purpose list. At the same time, arrays can be manipulated using many of the same methods as a list, so it may be possible to replace lists with arrays in an application without a lot of other changes.

Sorting items in a sequence is a fundamental aspect of data manipulation. Python's list includes a sort() method, but sometimes it is more efficient to maintain a list in sorted order without resorting it each time its contents are changed. The functions in heapq modify the contents of a list while preserving the sort order of the list with low overhead.

Another option for building sorted lists or arrays is bisect. It uses a binary search to find the insertion point for new items and is an alternative to repeatedly sorting a list that changes frequently.

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