Day 32: Confusing Shallow vs Deep Copy

 

🐍 Python Mistakes Everyone Makes ❌

Day 32: Confusing Shallow vs Deep Copy

Copying data structures in Python looks simple—but it can silently break your code if you don’t understand what’s really being copied.

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❌ The Mistake

Assuming copy() (or slicing) creates a fully independent copy.

a = [[1, 2], [3, 4]]
b = a.copy()

b[0].append(99)

print(a)

👉 Surprise: a changes too.

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❌ Why This Fails

• copy() creates a shallow copy

• Only the outer list is duplicated

• Inner (nested) objects are shared

• Modifying nested data affects both lists

So even though a and b look separate, they still point to the same inner lists.

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✅ The Correct Way

Use a deep copy when working with nested objects.

import copy

a = [[1, 2], [3, 4]]
b = copy.deepcopy(a)

b[0].append(99)

print(a)

👉 Now a remains unchanged.

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🧠 Simple Rule to Remember

✔ Shallow copy → shares inner objects
✔ Deep copy → copies everything recursively

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🔑 Key Takeaways

• Not all copies are equal in Python

• Nested data requires extra care

• Use deepcopy() when independence matters

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Understanding this distinction prevents hidden bugs that are extremely hard to debug later 🧠⚠️