How Can I Efficiently Copy Nested Lists in Python Without Affecting the Original?

Copying Nested Lists Efficiently in Python

In Python, copying a nested list can be tricky due to its mutable nature. Modifying one list will affect the original list if shallow copying techniques are employed. To overcome this limitation, it is essential to understand the nuances of list copying in Python and opt for a method that ensures independence of the copied list.

Consider the example of a 1D list:

a = [1, 2]
b = a[:]

In this scenario, shallow copying is sufficient, as modifying b does not affect a. However, the same approach fails when working with 2D or nested lists:

a = [[1, 2], [3, 4]]
b = a[:]

Modifying b in this case will also affect a. To create a truly independent copy of the nested list, one must delve into deeper levels of copying.

Solution: Deep Copying Using copy.deepcopy()

Python's copy module provides a robust solution for deep copying nested lists with its deepcopy() function. Unlike shallow copying, this function recursively iterates through the nested structure, creating independent copies at every level:

import copy
b = copy.deepcopy(a)

With deepcopy() in place, modifying b will not impact the original list a. This technique ensures that the two lists are separate and can be manipulated independently, addressing the issue of nested list modification.

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