Home > Article > Backend Development > Shallow copy and deep copy in python
Before we talk about what deep and shallow copies are, let’s first look at this phenomenon:
a = ['scolia', 123, [], ] b = a[:] b[2].append(666) print a print b
Why do I only modify b, but it affects a? I have seen what I said in my previous article: all the memory references are stored in the sequence.
So, when we modify the empty list inside through b, we are actually modifying the same object in the memory, so it will affect a.
a = ['scolia', 123, [], ] b = a[:] print id(a), id(a[0]), id(a[1]), id(a[2]) print id(b), id(b[0]), id(b[1]), id(b[2])
The code is verified correctly, so although a and b are two different objects, the references inside are both the same. This is the so-called new object, old content.
However, shallow copy is not just that, look below:
a = ['scolia', 123, [], ] b = a[:] b[1] = 666 print a print b
What is going on here? What's going on?
Students who have read my instructions on variable assignment in Python will know: For immutable data types such as strings and numbers, modification is equivalent to reassignment. Here it is equivalent to refreshing the reference.
Verify the code:
a = ['scolia', 123, [], ] b = a[:] b[1] = 666 print id(a), id(a[0]), id(a[1]), id(a[2]) print id(b), id(b[0]), id(b[1]), id(b[2])
It seems that it is correct.
The above mentioned are shallow copies. To sum up, shallow copies only copy a series of references. When we modify the modifiable data type of the copied object, the references are not changed, so Will affect the original object. When modifying an unmodifiable object, a new object is created and the reference is refreshed. Therefore, the reference to the original object is different, and the result is different.
Method to create a shallow copy:
1. Slicing operation
2. Use the list() factory function to create a new object . (b = list(a))
So a deep copy means re-creating the objects referenced inside and generating a new series of references.
Basically, it is like this, but for unmodifiable objects such as strings and numbers, it seems a bit wasteful to create a new copy. Anyway, when you want to modify it, you will create a new object and refresh the reference. of. So it doesn't matter if you still use the original reference, it can also achieve the purpose of saving memory.
Look at the code verification:
from copy import deepcopy a = ['scolia', 123, [], ] b = deepcopy(a) b[1] = 666 print id(a), id(a[0]), id(a[1]), id(a[2]) print id(b), id(b[0]), id(b[1]), id(b[2])
Verified correctly .
Creation of deep copy:
1. Just like the code example, it can only be created through the deepcopy() method of the built-in copy module .
Okay, let’s stop here for the issue of deep and shallow copying. If there are any mistakes or need to be added, we will continue later.
The above article provides an in-depth understanding of shallow copy and deep copy in python. This is all the content shared by the editor. I hope it can give you a reference, and I also hope that everyone will support the PHP Chinese website.
For more articles related to shallow copy and deep copy in python, please pay attention to the PHP Chinese website!