Python collections Examples

Short, runnable programs that show python collections module in action. Read the explanation, press Run, then change the code and try your own ideas. New to the topic? Start with the Python collections Module lesson.

1The most common words in a review

split() makes a list of words, Counter tallies them, and most_common(3) gives the top three. Words with equal counts keep the order in which they first appeared.

The most common words in a review

from collections import Counter

review = "great food great service but slow service and great price"
words = review.split()
counts = Counter(words)
print(counts.most_common(3))
print(len(counts), "different words out of", len(words))

Expected output[('great', 3), ('service', 2), ('food', 1)]
7 different words out of 10

2What is still missing from an order?

Subtracting counters keeps only positive amounts, which is exactly the shortfall. subtract() is the version that keeps zeros and negatives, so it shows the surplus too.

What is still missing from an order?

from collections import Counter

stock = Counter({"apples": 5, "pears": 2})
order = Counter({"apples": 3, "pears": 4, "plums": 6})
missing = order - stock
print(missing)
print(sorted(missing))
stock.subtract(order)
print(stock)

Expected outputCounter({'plums': 6, 'pears': 2})
['pears', 'plums']
Counter({'apples': 2, 'pears': -2, 'plums': -6})

3Unique pages per visitor with defaultdict(set)

A set ignores duplicates, so asha visiting /home twice is stored once. Sorting the keys and the sets keeps the output stable.

Unique pages per visitor with defaultdict(set)

from collections import defaultdict

visits = [("asha", "/home"), ("ben", "/home"), ("asha", "/cart"),
          ("asha", "/home"), ("ben", "/pay")]
pages = defaultdict(set)
for user, page in visits:
    pages[user].add(page)
for user in sorted(pages):
    print(user, sorted(pages[user]))

Expected outputasha ['/cart', '/home']
ben ['/home', '/pay']

4A print queue that shares the printer

A job that needs more than two pages prints two, then goes to the back of the line. popleft() and append() are both fast on a deque.

A print queue that shares the printer

from collections import deque

jobs = deque([("report.pdf", 3), ("photo.png", 1), ("invoice.pdf", 2)])
while jobs:
    name, pages = jobs.popleft()
    if pages > 2:
        print("printing 2 pages of", name)
        jobs.append((name, pages - 2))
    else:
        print("finished", name)

Expected outputprinting 2 pages of report.pdf
finished photo.png
finished invoice.pdf
finished report.pdf

5A rolling average of the last 3 readings

deque(maxlen=3) forgets the oldest reading as soon as a fourth arrives, so the average always covers only the latest three.

A rolling average of the last 3 readings

from collections import deque

window = deque(maxlen=3)
for temp in [20, 22, 21, 25, 30, 28]:
    window.append(temp)
    print(temp, list(window), round(sum(window) / len(window), 1))

Expected output20 [20] 20.0
22 [20, 22] 21.0
21 [20, 22, 21] 21.0
25 [22, 21, 25] 22.7
30 [21, 25, 30] 25.3
28 [25, 30, 28] 27.7

6Employee records with namedtuple

Fields are read by name in max() and in the filter. _replace() builds a promoted copy, and _asdict() shows it as a dict ready for JSON.

Employee records with namedtuple

from collections import namedtuple

Employee = namedtuple("Employee", ["name", "team", "salary"])
staff = [Employee("Asha", "dev", 70000), Employee("Ben", "ops", 52000),
         Employee("Cara", "dev", 64000)]
top = max(staff, key=lambda e: e.salary)
print(top.name, top.salary)
promoted = top._replace(salary=top.salary + 5000)
print(promoted)
print(promoted._asdict())
print([e.name for e in staff if e.team == "dev"])

Expected outputAsha 70000
Employee(name='Asha', team='dev', salary=75000)
{'name': 'Asha', 'team': 'dev', 'salary': 75000}
['Asha', 'Cara']

Practise next

Python collections Module exercises → Back to the lesson

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