L1 · FoundationsList basics~1 min · 4 tests

Sum a List Without sum()

Add up a Python list with a loop and an accumulator instead of sum(), then compare with the built-in. O(n) basics with live test cases in your browser.

The problem

Return the total of all numbers in nums without using sum().

Examples

Example 1
Input
```
list_total([1, 2, 3, 4])
```
Expected output
```
10
```
Example 2
Input
```
list_total([-1, 1])
```
Expected output
```
0
```

+ 2 hidden tests on Submit.

Edge cases to ask about

Empty list
Floats
Negatives

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 · list_total

def list_total(nums):
    """Total of nums without sum()."""
    # Write your solution here
    pass

⌘/Ctrl + Enter runs the examples

Your code runs in real CPython inside your browser — nothing is sent anywhere. The first run downloads the interpreter (about 6 MB, once). Your code is saved on this device as you type.

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 measure your code against the optimal one at growing input sizes.

Time complexity of the optimal solution

Space complexity (extra memory)

Pick both to reveal the answer.

Measure it

Runs the function on inputs of size 250 up to 16,000 and records the time and peak memory. Slow solutions stop early — a short curve is itself the answer.

From brute force to optimal

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

Approach	Time	Space	Idea
Accumulator loop	O(n)	O(1)

Walkthrough of the optimal approach (try it yourself first)

An accumulator starting at 0, updated once per element. The built-in sum() does the same in C, so it's faster — but the interviewer wants to see the loop.

Complexity: O(n) time, O(1) space. One addition per element.

Reveal the reference solution

def list_total(nums):
    total = 0
    for x in nums:
        total += x
    return total

Follow-ups interviewers ask

Sum only the even-indexed elements.

Frequently asked interview questions

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

What is the time complexity of Sum a List Without sum() in Python?

The optimal solution runs in O(n) time and O(1) auxiliary space. One addition per element.

What follow-up questions do interviewers ask about Sum a List Without sum()?

Sum only the even-indexed elements.