Python functools Exercises With Answers

What does lru_cache do?

1. Sorts the arguments
2. Caches results by argument valuescorrect
3. Runs the function in parallel
4. Deletes old functions

Answer: Caches results by argument values

Why: Repeated calls with the same arguments can reuse a stored result.

What does partial return?

1. The result of calling the function
2. A class
3. A new callable with some arguments fixedcorrect
4. A list of arguments

Answer: A new callable with some arguments fixed

Why: partial stores arguments and waits for the remaining ones.

What does reduce do?

1. Sorts an iterable
2. Creates a dictionary
3. Folds an iterable into one valuecorrect
4. Removes duplicates

Answer: Folds an iterable into one value

Why: reduce applies a two-argument function cumulatively.

What does this code print?

from functools import partial
def power(base, exponent):
    return base ** exponent
square = partial(power, exponent=2)
print(square(5))

1. 10
2. 5
3. 25correct
4. 7

Answer: 25

Why: partial fixes exponent to 2, so the call becomes power(5, 2).

Complete the cache decorator import.

from functools import ____

Answer: lru_cache

Why: lru_cache is the memoization decorator in functools.

Complete the function that fixes an argument.

from functools import partial
def power(base, exponent):
    return base ** exponent
square = ____(power, exponent=2)

Answer: partial

Why: partial creates a specialized callable.

Complete the folding function.

from functools import reduce
print(____(lambda a, b: a + b, [1, 2, 3], 0))

Answer: reduce

Why: reduce combines values from left to right.

Complete the cache size argument.

from functools import lru_cache
@lru_cache(____=None)
def square(n):
    return n * n

Answer: maxsize

Why: maxsize=None lets the cache grow without a fixed limit.

What does the program output?

from functools import lru_cache
@lru_cache(maxsize=None)
def f(n):
    return n * 2
print(f(2) + f(2))

Answer: 8

Why: Both calls return four, so the sum is eight; the second call reuses the cached result.

What appears on the screen?

from functools import partial
def add(a, b):
    return a + b
add5 = partial(add, 5)
print(add5(3))

Answer: 8

Why: partial fixes the first argument to five, so the result is eight.

What is printed?

from functools import reduce
print(reduce(lambda a, b: a * b, [2, 3, 4]))

Answer: 24

Why: The multiplication folds to twenty-four.

What is the output?

from functools import lru_cache
@lru_cache(maxsize=None)
def f(n):
    return n + 1
f(1)
f(1)
print(f.cache_info().hits)

Answer: 1

Why: The second call is a cache hit, so hits is one.