L2 · Working engineerStacks & queues~6 min · 4 tests#41

Implement a Stack in Python

Build a Stack class with push, pop, peek, is_empty and size on a Python list, all O(1). Learn LIFO and why list.pop(0) would be the wrong end.

The problem

Implement a Stack (last in, first out):

push(x) adds to the top
pop() removes and returns the top, or None if empty
peek() returns the top without removing it, or None
is_empty() and size()

Examples

Example 1

Input

run_ops(Stack, [], [["push", 10], ["push", 20], ["push", 30], ["pop"]])

Expected output

[None, None, None, 30]

Example 2

Input

run_ops(Stack, [], [["push", 1], ["peek"], ["size"], ["pop"], ["is_empty"]])

Expected output

[None, 1, 1, 1, True]

+ 2 hidden tests on Submit — empty stack.

Edge cases to ask about

Pop from empty
Peek on empty
Mixed types

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 · Stack

class Stack:
    def __init__(self):
        pass

    def push(self, x):
        pass

    def pop(self):
        pass

    def peek(self):
        pass

    def is_empty(self):
        pass

    def size(self):
        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 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
List, top at index 0	O(n) push/pop	O(n)	insert(0)/pop(0) shift every element.
bestList, top at the end	O(1) push/pop	O(n)	append() and pop() work on the end.

Walkthrough of the optimal approach (try it yourself first)

Use a list and treat its end as the top: append to push, pop() to pop, [-1] to peek — all O(1). Using the front (insert(0, x), pop(0)) would be O(n) per operation, because every element shifts.

Complexity: O(1) time, O(n) space. append() and pop() on the END of a Python list are amortised O(1); the stack stores n items.

Reveal the reference solution

class Stack:
    def __init__(self):
        self._items = []

    def push(self, x):
        self._items.append(x)

    def pop(self):
        return self._items.pop() if self._items else None

    def peek(self):
        return self._items[-1] if self._items else None

    def is_empty(self):
        return not self._items

    def size(self):
        return len(self._items)

Follow-ups interviewers ask

Add get_min() in O(1) (min-stack).
Make it thread-safe.

Frequently asked interview questions

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

What is the time complexity of Implement a Stack in Python?

The optimal solution runs in O(1) time and O(n) auxiliary space. append() and pop() on the END of a Python list are amortised O(1); the stack stores n items.

What is the brute-force approach, and how do you optimise it?

List, top at index 0: O(n) push/pop time, O(n) space. insert(0)/pop(0) shift every element. List, top at the end: O(1) push/pop time, O(n) space. append() and pop() work on the end.

What follow-up questions do interviewers ask about Implement a Stack in Python?

Add get_min() in O(1) (min-stack). Make it thread-safe.