Collections

Overview

• In addition to the native data structures, Python also includes a collections module in the Standard Library

Collection	Description
namedtuple()	factory function for creating tuple subclasses with named fields
deque	list-like container with fast appends and pops on either end
ChainMap	dict-like class for creating a single view of multiple mappings
Counter	dict subclass for counting hashable objects
OrderedDict	dict subclass that remembers the order entries were added
defaultdict	dict subclass that calls a factory function to supply missing values
UserDict	wrapper around dictionary objects for easier dict subclassing
UserList	wrapper around list objects for easier list subclassing
UserString	wrapper around string objects for easier string subclassing

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OrderedDict Collection

• Ordered Dictionaries work almost exactly like the native dict data structure, with one enhancement: they maintain the order of the items added to them
• Is not a native data structure, need to import

>>> from collections import OrderedDict

>>> od = OrderedDict()
>>> od["apples"] = 5
>>> od["pears"] = 2
>>> od["oranges"] = 9

>>> od["pears"]
2

>>> od["bananas"] = 12

>>> od
OrderedDict([('apples', 5), ('pears', 2), ('oranges', 9), ('bananas', 12)])

This OrderedDict worked just like the dict data structure with the following differences:
1. We did have to import it before we could use it
2. We added the key-value pairs to it incrementally, to demonstrate how it maintains the order in which they were added
3. When you look at the contents of the OrderedDict it looks a little different OrderedDict(<list of tuples>)

Index