Describe the difference between shallow copy and deep copy in Python. How to properly copy nested data structures? How does the copy module work?

Answer.

In Python, object copying can be shallow (shallow copy) and deep (deep copy). A shallow copy creates a new container, but nested objects are not copied; instead, references to the same objects are used. A deep copy recursively creates new copies of all nested objects, ensuring independence of the copy.

The copy module provides the methods copy() (shallow copy) and deepcopy() (deep copy):

import copy
original = [[1, 2], [3, 4]]
shallow = copy.copy(original)
deep = copy.deepcopy(original)

shallow[0][0] = 99
print(original)  # [[99, 2], [3, 4]] ← the original object has changed!
deep[1][1] = 42
print(original)  # [[99, 2], [3, 4]] - hasn't changed

Trick Question.

What is the difference between the operator list2 = list1 and using copy.copy(list1)?

Answer: The operator list2 = list1 creates a new reference to the same object. copy.copy(list1) makes a shallow copy, creating a new list object but with the same inner objects. For nested structures, shallow copying is not enough — a deep copy is needed.

Examples of real mistakes due to lack of knowledge of the subtleties of the topic.

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Story

When developing a REST API, data from the template was copied using normal assignment (data = template). The next request accidentally modified the "template" for all subsequent users since the same reference was used.

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Story

In the reporting module, data was copied using copy.copy(), even though the structure was nested (lists in dictionaries). Modifications in the copy unexpectedly reflected in the original data, causing errors in the statistics.

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Story

In one banking project, an incorrect copy of a complex nested object through copy.copy() (instead of deepcopy()) led to the loss of transaction history — new operations overwrote the old ones since the nested elements were shared.