L2 · Working engineerPython internals~4 min · 2 tests#64

Shallow Copy vs Deep Copy in Python

See the difference between copy.copy and copy.deepcopy on nested lists: a shallow copy shares inner objects, a deep copy does not. Proved by tests.

The problem

Write make_copies(original) that returns a tuple (shallow, deep):

shallow — a shallow copy (new outer list, shared inner lists)
deep — a deep copy (everything independent)

The test mutates an inner list of the original afterwards and checks which copy sees the change.

Examples

Example 1

Input

probe(make_copies)

Expected output

([1, 2, 99], [1, 2], False, False)

+ 1 hidden test on Submit.

Edge cases to ask about

Flat vs nested lists
Copy is not the same object

How the tests call your code

These helpers run before your code. The test inputs above call them.

def probe(make_copies):
    original = [[1, 2], [3, 4]]
    shallow, deep = make_copies(original)
    original[0].append(99)
    return (shallow[0], deep[0], shallow is original, deep is original)

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 · make_copies

def make_copies(original):
    """Return (shallow_copy, deep_copy)."""
    # Write your solution here
    pass

⌘/Ctrl + Enter runs the examples

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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
copy.copy / copy.deepcopy	O(n) / O(total size)	same	list(x) and x[:] are also shallow copies.

Walkthrough of the optimal approach (try it yourself first)

A shallow copy (copy.copy, list(x), x[:]) is a new outer list holding the same inner objects — mutate an inner list and both see it. A deep copy (copy.deepcopy) recursively copies every nested object, so the copies are fully independent.

For flat lists of immutable values (ints, strings) the two behave the same.

Complexity: O(n) time, O(n) space. A shallow copy copies the n outer references; a deep copy walks and copies every nested object.

Reveal the reference solution

import copy

def make_copies(original):
    return copy.copy(original), copy.deepcopy(original)

Follow-ups interviewers ask

How does deepcopy handle cycles?
Customise copying with deepcopy.

Frequently asked interview questions

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

What is the time complexity of Shallow Copy vs Deep Copy in Python?

The optimal solution runs in O(n) time and O(n) auxiliary space. A shallow copy copies the n outer references; a deep copy walks and copies every nested object.

What follow-up questions do interviewers ask about Shallow Copy vs Deep Copy in Python?

How does deepcopy handle cycles? Customise copying with __deepcopy__.