collections: Counter, defaultdict, deque

Counter: counting without boilerplate

The standard library exists so you do not rewrite, and re-debug, the same chores in every project. Counting things and grouping things are the two most common data chores in working Python, and this unit's collections module turns each into a line or two.

Counting things in Python for Beginners took four lines: check if the key exists, initialize it, increment. collections.Counter does it in one:

from collections import Counter

votes = ["cat", "dog", "cat", "bird", "cat"]
tally = Counter(votes)
# Counter({'cat': 3, 'dog': 1, 'bird': 1})

A Counter is a dict (it subclasses dict, inheritance from lesson 3-4 in the wild), with extras:

• tally.most_common(2) gives the top two (item, count) pairs.
• Missing keys return 0 instead of raising KeyError.
• Feed it any iterable: a list, a string, a generator from unit 4.

defaultdict and deque

defaultdict is a dict that invents a default value for missing keys. Pass it the factory to use, like list or int:

from collections import defaultdict

groups = defaultdict(list)
groups["fruit"].append("apple")   # no KeyError, a fresh [] appears

That kills the if key not in d: d[key] = [] dance forever, and it is the standard tool for grouping.

deque (say "deck", short for double-ended queue) stores its items so that both ends are directly reachable. As a result, appendleft and popleft take the same tiny, fixed amount of time no matter how many items the deque holds. A plain list cannot offer that: list.pop(0) must shift every remaining element one slot left, so its cost grows with the length of the list. Use a deque whenever you need a queue, like breadth-first search in the Data Structures course. (Unit 9 turns this kind of cost reasoning into a formal habit.)