Standard Library

Standard Library

Python's standard library is vast. A few essential modules:

collections

Counter counts hashable objects:

from collections import Counter

words = ["apple", "banana", "apple", "cherry", "banana", "apple"]
c = Counter(words)
c["apple"]           # 3
c.most_common(2)     # [('apple', 3), ('banana', 2)]

defaultdict returns a default value for missing keys:

from collections import defaultdict

groups = defaultdict(list)
groups["a"].append(1)   # no KeyError

itertools

from itertools import chain, groupby, product, combinations

list(chain([1, 2], [3, 4]))       # [1, 2, 3, 4]
list(combinations("ABC", 2))      # [('A','B'), ('A','C'), ('B','C')]
list(product([0,1], repeat=2))    # [(0,0), (0,1), (1,0), (1,1)]

functools

from functools import reduce, lru_cache

reduce(lambda a, b: a + b, [1, 2, 3, 4])  # 10

@lru_cache(maxsize=None)
def fib(n):
    if n < 2: return n
    return fib(n-1) + fib(n-2)

The @lru_cache line is a decorator — the @ syntax wraps fib so that its return values are cached. After the first call to fib(10), subsequent calls with the same argument return instantly from the cache instead of recomputing.

Your Task

Implement most_common_words(text, n) that:

• Splits text into words (by spaces), lowercases all words
• Returns a list of the n most common words as (word, count) tuples, sorted by frequency (most frequent first)

Use collections.Counter.