L2 · Working engineerPython internals~4 min · 4 tests#56

map, filter and reduce in Python

Use map(), filter() and functools.reduce() together: double every number, keep the evens and multiply them all. Functional Python with live tests.

The problem

Return a tuple of three results computed from nums:

every number doubled — using map
only the even numbers — using filter
the product of all numbers — using functools.reduce

For an empty list, the product is 1.

Examples

Example 1

Input

functional([1, 2, 3, 4, 5])

Expected output

([2, 4, 6, 8, 10], [2, 4], 120)

Example 2
Input
```
functional([3])
```
Expected output
```
([6], [], 3)
```

+ 2 hidden tests on Submit — reduce needs an initial value.

Edge cases to ask about

Empty list (reduce initial value)
Zero in the product

Hints

0/3

How an interviewer scores this

0/9

1. Understand the problemRestate it, ask about edge cases and input size.
2. Write a brute-force solutionCorrect first, clever later.
3. Get the correct outputautoAll visible examples pass.
4. Analyse time complexityautoCommit to a Big-O in the Complexity Lab.
5. Analyse space complexityautoExtra memory, not the input.
6. Identify the bottleneckautoMeasure your code — where does it bend?
7. OptimiseUsually: a set or dict instead of a scan.
8. Explain why it worksSay it out loud to Solvi.
9. Test the edge casesautoSubmit passes every hidden test.

Python 3.13 · functional

def functional(nums):
    """Return (doubled, evens, product) using map, filter and reduce."""
    # Write your solution here
    pass

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Complexity Lab

What does this cost as n grows?

Interviewers score the analysis as much as the code. Commit to an answer first — then check it, and read why.

Time complexity of the optimal solution

Space complexity (extra memory)

Pick both to reveal the answer.

From brute force to optimal

The progression an interviewer wants to hear, one step at a time.

Approach	Time	Space	Idea
map / filter / reduce	O(n)	O(n)	map and filter are lazy iterators — wrap in list().

Walkthrough of the optimal approach (try it yourself first)

map and filter return lazy iterators in Python 3, so wrap them in list(). reduce moved to functools and needs an initial value (1 for a product) or it raises TypeError on an empty list — that is what the hidden test checks.

Most Python style guides prefer comprehensions over map/filter with lambdas; say so.

Complexity: O(n) time, O(n) space. Each function makes one pass; the two lists can hold n items.

Reveal the reference solution

from functools import reduce

def functional(nums):
    doubled = list(map(lambda x: x * 2, nums))
    evens = list(filter(lambda x: x % 2 == 0, nums))
    product = reduce(lambda a, b: a * b, nums, 1)
    return doubled, evens, product

Follow-ups interviewers ask

Rewrite all three with comprehensions and math.prod.

Frequently asked interview questions

Core interview concepts, complexities, and follow-ups scored by hiring teams.

What is the time complexity of map, filter and reduce in Python?

The optimal solution runs in O(n) time and O(n) auxiliary space. Each function makes one pass; the two lists can hold n items.

What follow-up questions do interviewers ask about map, filter and reduce in Python?

Rewrite all three with comprehensions and math.prod.