Real Python: Shallow vs Deep Copying of Python Objects

Python's assignment binds variables to objects, not creating copies, unlike some languages. This distinction is crucial for mutable objects. Shallow copying creates a new object but shares nested objects, leading to potential issues. Deep copying recursively duplicates all objects for complete independence. The `copy` module provides `copy()` for shallow and `deepcopy()` for deep copies. Custom classes can define their copying behavior using `__copy__()` and `__deepcopy__()`. Objects are classified as scalar (indivisible) or composite (containers). Composite objects can be mutable (changeable) or immutable (unchangeable). Mutability impacts copying strategies; immutable objects benefit from re-use, while mutable objects might require deep copies to avoid unintended modifications. Understanding these concepts is vital for managing complex data structures effectively. The article emphasizes the importance of copying for defensive programming and creating independent data snapshots. Choosing between shallow and deep copying depends on the specific needs of your application.