Shallow vs. Deep Copy in Python Dictionaries: Why Doesn\'t `copy()` Update the Original?

Understanding Shallow and Deep Copying: Why Dictionary Shallow Copy Doesn't Update Original

When working with data structures in Python, it's crucial to understand the difference between shallow and deep copying. Shallow copying creates a new reference to the original data structure, while deep copying creates a completely new data structure with isolated content.

Let's examine the behavior of shallow copying in dictionaries. In the example provided:

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

Calling copy() on the dictionary original creates a new mapping object, new, that references the same content as original. This is known as shallow copying. When new is updated with {'c': 3}, only new is affected. Both original and new reference the same underlying data structure.

Representation after shallow copy:

original: |  {a: 1, b: 2}   |
new:     |  {a: 1, b: 2}   |

However, when shallow copying a mutable data structure, like a list:

original = [1, 2, 3]
new = original

Modifying the new list (new.append(4)) modifies the original list (original) as well.

Representation after shallow copy for lists:

original: |  [1, 2, 3]  |
new:     |  [1, 2, 3]  |

The key distinction between shallow and deep copying lies in how they handle nested data structures. Deep copying recursively copies all content by value, creating completely isolated data structures:

import copy
c = copy.deepcopy(a)

Representation after deep copy:

original: |  {a: [1, 2, 3]}  |
c:        |  {a: [1, 2, 3]}  |

In summary, shallow copying references the original data structure, while deep copying creates an entirely new, isolated structure. This distinction becomes especially important when modifying mutable data structures.

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