Deep Copy vs. Shallow Copy: Fundamental Methods for Python Object Replication

In Python, there are three methods for object copying: assignment, shallow copy, and deep copy. Their behavioral differences affect object independence, especially for nested mutable objects where clear distinctions are necessary. Assignment: A new variable points to the original object reference, sharing the same object. Modifying either variable will affect the original object (e.g., `b.append(4)` in a list causes `a` to also be modified). Shallow copy: Methods like `copy.copy()`, which only copy the outer layer. Nested objects within remain shared with the original object (e.g., modifying a sublist in a list affects the original list). Deep copy: `copy.deepcopy()`, which recursively copies all levels, resulting in complete independence. Modifications to both inner and outer layers do not affect the original object. Applicable scenarios: Assignment is suitable for simple immutable objects; shallow copy handles single-layer nesting; deep copy addresses multi-layer nesting. Common misunderstandings: Assignment, shallow copy, and deep copy have similar effects on immutable objects; confusing shallow and deep copies; needing deep copy for nested structures. Understanding the differences between the three can prevent unintended modifications and ensure code reliability.