Complete Python Interview Guide
Questions
What is the difference between a shallow copy and a deep copy in Python?
The Scenario
You are a backend engineer at a social media company. You are writing a new service that needs to make a copy of a nested data structure. You are not sure whether to use a shallow copy or a deep copy.
The Challenge
Explain the difference between a shallow copy and a deep copy in Python. What are the pros and cons of each approach, and which one would you choose for this use case?
A junior engineer might not be aware of the difference between a shallow copy and a deep copy. They might just use the `copy()` method without considering the implications of using a shallow copy on a nested data structure.
A senior engineer would be able to provide a detailed explanation of the differences between a shallow copy and a deep copy. They would also be able to explain the trade-offs between each approach and would have a clear recommendation for which one to use in this use case.
Step 1: Understand the Key Differences
| Feature | Shallow Copy | Deep Copy |
|---|---|---|
| Copying | Creates a new object, but inserts references to the original objects. | Creates a new object and recursively copies all the objects inside it. |
| Mutability | If you modify an object in the copy, it will also be modified in the original. | If you modify an object in the copy, it will not be modified in the original. |
| Performance | Faster than a deep copy. | Slower than a shallow copy. |
Step 2: Choose the Right Tool for the Job
For our use case, we should use a deep copy. This is because we are working with a nested data structure, and we want to make sure that the copy is completely independent of the original.
Step 3: Code Examples
Here are some code examples that show the difference between the two approaches:
Shallow Copy:
import copy
old_list = [[1, 2, 3], [4, 5, 6], [7, 8, 9]]
new_list = copy.copy(old_list)
old_list[1][1] = 'X'
print(old_list) # [[1, 2, 3], [4, 'X', 6], [7, 8, 9]]
print(new_list) # [[1, 2, 3], [4, 'X', 6], [7, 8, 9]]As you can see, when we modify the nested list in the old list, it is also modified in the new list.
Deep Copy:
import copy
old_list = [[1, 2, 3], [4, 5, 6], [7, 8, 9]]
new_list = copy.deepcopy(old_list)
old_list[1][1] = 'X'
print(old_list) # [[1, 2, 3], [4, 'X', 6], [7, 8, 9]]
print(new_list) # [[1, 2, 3], [4, 5, 6], [7, 8, 9]]As you can see, when we modify the nested list in the old list, it is not modified in the new list.
Practice Question
You are working with a list of objects and you want to create a new list with the same objects, but in a different order. Which of the following would be the most efficient?