In Python, the concepts of deep copy and shallow copy are crucial when dealing with mutable objects, such as lists or dictionaries, especially when these objects contain other mutable objects. Understanding the difference between these two types of copying is essential for managing how data is stored and manipulated in memory.
Shallow Copy
A shallow copy creates a new compound object and then, to the extent possible, inserts references into it to the objects found in the original. This means that the new object itself is a distinct entity, but it contains references to the original elements rather than copies of them. Therefore, changes made to the contents of the shallow copy can affect the original object if those contents are mutable objects.
For example, if you have a list of lists and perform a shallow copy, the new list will be a new object, but the sublists will be the same objects that exist in the original list. Modifying any mutable objects in the shallow copy will reflect in the original object because both the original and the copy refer to the same mutable elements[1][2][7].
Deep Copy
A deep copy, on the other hand, creates a new compound object and then, recursively, inserts copies into it of the objects found in the original. This means that not only is the new compound object distinct, but all of its elements are distinct copies as well. Changes made to the deep copy do not affect the original object, as they are completely independent of each other.
This type of copy is useful when you need to work with a copy of an object without affecting the original object, even if changes are made to nested objects. For instance, using a deep copy on a list of lists results in a new list with new sublists, so changes to the sublists of the copy will not affect the sublist...
