When working with objects in Python, you may often need to create copies of them to modify or manipulate without affecting the original object. There are two common techniques for creating copies of objects in Python: shallow copy and deep copy.
Shallow Copy:
A shallow copy creates a new object but does not create new copies of the nested objects within it. This means that the new object contains references to the same nested objects as the original object. To create a shallow copy of an object in Python, you can use the `copy` module's `copy()` function.
Here's an example of creating a shallow copy of a list:
```python
import copy
original_list = [1, 2, [3, 4]]
shallow_copy_list = copy.copy(original_list)
original_list[2][0] = 5
print(original_list) # Output: [1, 2, [5, 4]]
print(shallow_copy_list) # Output: [1, 2, [5, 4]]
```
As you can see from the example, when we modify the nested list in the original list, the same modification reflects in the shallow copy list as well. This is because the shallow copy only creates a new list object, but it still shares the same references to nested objects.
Deep Copy:
In contrast, a deep copy creates a new object and recursively creates new copies of all the nested objects within it. This means that the new object contains entirely new copies of the nested objects, independent of the original object. To create a deep copy of an object in Python, you can use the `copy` module's `deepcopy()` function.
Here's an example of creating a deep copy of a list:
```python
import copy
original_list = [1, 2, [3, 4]]
deep_copy_list = copy.deepcopy(original_list)
original_list[2][0] = 5
print(original_list) # Output: [1, 2, [5, 4]]
print(deep_copy_list) # Output: [1, 2, [3, 4]]
```
In this example, when we modify the nested list in the original list, the deep copy list remains unaffected. This is because the deep copy creates entirely new copies of all the nested objects.
In summary, when creating copies of objects in Python, you can use shallow copy if you only need to create a new object with the same references to nested objects, or use deep copy if you need entirely independent copies of all nested objects. Understanding these techniques is essential for effectively managing and manipulating objects in your Python programs.
