How Can I Independently Copy Nested Lists in Python?

Copying Nested Lists: Achieving Independence in Data Manipulation

In Python, copying one-dimensional lists is straightforward using the slicing assignment operator ([ : ]). However, this method fails to preserve data independence when dealing with nested lists (2D or higher). The issue arises from the interconnected memory references established during the initial assignment.

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

Modifications made to b will inadvertently propagate to a because the references, not the values, are duplicated. To circumvent this problem, Python offers a specialized utility for deep copying: the copy.deepcopy() function.

import copy
b = copy.deepcopy(a)

Unlike the slicing method, copy.deepcopy() traverses the nested structure recursively, creating new objects entirely separate from the original. This ensures that any alterations to b remain isolated, preserving the integrity of a.

By employing copy.deepcopy(), you can confidently replicate nested lists, safeguarding data independence and enabling unparalleled flexibility in data manipulation.

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