When working with data structures like lists and dictionaries in Python, understanding how to copy data is crucial for managing and manipulating it effectively. Python offers two types of copying mechanisms: shallow copying and deep copying. These methods differ in how they handle the copying of nested objects and their references.
A shallow copy creates a new object, but it inserts references into it to the objects found in the original. In other words, the new object is a copy of the outermost structure, but it contains references to the same elements as the original. Changes to the elements within the copied object will be reflected in the original and vice versa.
You can create a shallow copy using:
copy
module’s copy()
function.copy()
method for lists.copy.copy()
original_list
is affected by changes made to shallow_copy_list
because both lists share the same nested list.copy.copy()
method, changes to the nested list in shallow_copy_list
reflect in original_list
.A deep copy creates a new object and recursively copies all objects found within the original. This means that not only the outermost object but also all nested objects are duplicated. As a result, changes made to the deep copy will not affect the original object, and vice versa.
You can create a deep copy using:
copy
module’s deepcopy()
function.copy.deepcopy()
deep_copy_list
do not affect original_list
because all nested objects are copied independently.Understanding the difference between shallow and deep copying in Python is essential for managing data structures effectively. Shallow copying duplicates the outermost object and keeps references to nested objects, while deep copying creates entirely new instances of all nested objects. By choosing the appropriate copying method, you can control how changes to copied objects affect the original data and optimize performance based on your needs