Why Doesn\'t Updating a Shallow Copy of a Python Dictionary Change the Original?

Why Shallow Copy Dictionary Doesn't Update Original

When dealing with data structures, understanding the nuances of copying is crucial. Python offers two primary copy methods: shallow and deep copying. This article delves into the difference in these techniques, specifically examining why updating a shallow copy does not impact the original dictionary.

Python's Shallow Copy

dict.copy() performs a shallow copy of a dictionary, meaning it creates a new reference to the same content. The contents are not duplicated by value but instead share the same memory reference.

Consider the example:

original = dict(a=1, b=2)
new = original.copy()
new.update({'c': 3})

After the shallow copy, any changes made to the new reference (new) will alter the original dictionary (original) because they point to the same underlying data. In the example, adding 'c': 3 to the shallow copy also updates the original dictionary.

Understanding Deep Copy vs. Shallow Copy

Where shallow copying only creates new references to existing data, deep copying creates entirely new objects. The contents are duplicated recursively. This ensures that any modifications made to the new reference do not affect the original.

Using copy.deepcopy() performs a deep copy. In this case, any changes made to the new reference (c) will not impact the original dictionary (a).

Conclusion

Shallow copying in Python involves creating new references to existing data, while deep copying creates entirely new objects with duplicated contents. Understanding this distinction is essential when dealing with complex data structures, as it determines how modifications to one object impact the others.

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