PCEP Control Flow, Loops, Lists and Logic Practice Question
This PCEP practice question tests your understanding of control flow, loops, lists and logic. Examine the command output carefully: the correct answer depends on what the output actually shows, not on general recall alone. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
A data analyst writes a Python script to double each element in a matrix without altering the original. The code is:
original = [[1,2,3],[4,5,6]]
copy = original
for i in range(len(original)):
for j in range(len(original[i])):
copy[i][j] *= 2
print(original)
The output shows [[2,4,6],[8,10,12]], meaning the original was also changed. Which single modification to the line 'copy = original' ensures the original matrix remains unchanged?
Replace `copy = original` with `copy = original[:]`
Why wrong: This creates a shallow copy; inner lists are still shared, so modifications affect original.
B
Replace `copy = original` with `import copy; copy = copy.deepcopy(original)`
deepcopy creates independent copies of all nested objects.
C
Replace `copy = original` with `copy = list(original)`
Why wrong: Similar to slicing, list() creates a shallow copy.
D
Replace the nested loop with a list comprehension: `copy = [[x*2 for x in row] for row in original]`
Why wrong: This is a correct solution, but it replaces the entire loop, not just the copy assignment line. The question asks for a modification to that specific line.
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Replace `copy = original` with `import copy; copy = copy.deepcopy(original)`
Option B is correct because `copy.deepcopy()` creates a fully independent copy of the nested list structure. In Python, assignment (`copy = original`) only copies the reference to the outer list, so modifying elements through `copy` also modifies `original`. Shallow copies (like `original[:]` or `list(original)`) copy the outer list but still share references to the inner lists, so changes to inner elements affect both. Only `deepcopy` recursively duplicates all nested objects, ensuring the original matrix remains unchanged.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
✗
Replace `copy = original` with `copy = original[:]`
Why it's wrong here
This creates a shallow copy; inner lists are still shared, so modifications affect original.
✓
Replace `copy = original` with `import copy; copy = copy.deepcopy(original)`
Why this is correct
deepcopy creates independent copies of all nested objects.
Related concept
Read the scenario before looking for a memorised answer.
✗
Replace `copy = original` with `copy = list(original)`
Why it's wrong here
Similar to slicing, list() creates a shallow copy.
✗
Replace the nested loop with a list comprehension: `copy = [[x*2 for x in row] for row in original]`
Why it's wrong here
This is a correct solution, but it replaces the entire loop, not just the copy assignment line. The question asks for a modification to that specific line.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Python Institute often tests the distinction between shallow and deep copy in nested structures, and the trap here is that candidates assume `original[:]` or `list(original)` create a full independent copy, not realizing that inner lists are still shared references.
Trap categories for this question
Similar concept trap
Similar to slicing, list() creates a shallow copy.
Detailed technical explanation
How to think about this question
Python's `copy.deepcopy` uses a recursive algorithm that traverses every object in the container, creating new copies of mutable objects (like lists) while preserving immutable objects (like integers) by reference. This is essential when dealing with nested data structures such as matrices, JSON trees, or configuration dictionaries, where shallow copies would lead to unintended side effects. In real-world applications, failing to use deepcopy can cause subtle bugs in data pipelines where original data must remain pristine for audit trails or rollback operations.
KKey Concepts to Remember
Read the scenario before looking for a memorised answer.
Find the constraint that changes the correct option.
Eliminate answers that are true in general but not in this case.
TExam Day Tips
→Watch for words such as best, first, most likely and least administrative effort.
→Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A practitioner preparing for the PCEP exam encounters this exact type of scenario on the job. The correct answer here is not the most general option — it is the best answer for the specific constraint described. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Real exam questions reward reading the full scenario before eliminating options, because the constraint defines which answer fits.
What to study next
Got this wrong? Here's your next step.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Control Flow, Loops, Lists and Logic — This question tests Control Flow, Loops, Lists and Logic — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Replace `copy = original` with `import copy; copy = copy.deepcopy(original)` — Option B is correct because `copy.deepcopy()` creates a fully independent copy of the nested list structure. In Python, assignment (`copy = original`) only copies the reference to the outer list, so modifying elements through `copy` also modifies `original`. Shallow copies (like `original[:]` or `list(original)`) copy the outer list but still share references to the inner lists, so changes to inner elements affect both. Only `deepcopy` recursively duplicates all nested objects, ensuring the original matrix remains unchanged.
What should I do if I get this PCEP question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Question Discussion
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