Illustration of deep and shallow copy in Python (in layman's terms)

I. Shallow and deep copy

assignment operation

l1 = [1, 2, 3, [22, 33]]
l2 = l1
(666)

print(l1) # [1, 2, 3, [22, 33], 666]
print(l2) # [1, 2, 3, [22, 33], 666]

Illustration:

Attention:l2 = l1is a pointer, an assignment, and has nothing to do with shades of copy.

Shallow copy

The list is actually slots, each storing the memory address of the object.

precedent1. Adding elements to a large list
l1 = [1, 2, 3, [22, 33]]
l2 = ()
# Or the following, which is also a shallow copy
# import copy
# l2 = (l1)
(666)

print(l1) # [1, 2, 3, [22, 33], 666]
print(l2) # [1, 2, 3, [22, 33]]

precedent2. Adding elements to a small list
l1 = [1, 2, 3, [22, 33]]
l2 = ()
l1[-1].append(666)

print(l1) # [1, 2, 3, [22, 33, 666]]
print(l2) # [1, 2, 3, [22, 33, 666]]、

precedent3. commander-in-chief (military)l1The first element of the list is changed to6
l1 = [1, 2, 3, [22, 33]]
l2 = ()
l1[0] = 6

print(l1) # [6, 2, 3, [22, 33]]
print(l2) # [1, 2, 3, [22, 33]]

Illustration:

Example 1

Example 2

Example 3

Summary:

Shallow copy: A new space is created in memory to hold the copied list, but the contents of the list still follows the memory address of the previous object.

Attention:

In slicing, if it is a full cut, it is a shallow copy.

Deep copy

import copy
l1 = [1, 2, 3, [22, 33]]
l2 = (l1)
(666)
print(l1) # [1, 2, 3, [22, 33], 666]
print(l2) # [1, 2, 3, [22, 33]]

Illustration:

The essence is shown below:

But python has an optimization for deep copy that recreates a copy of the mutable datatypes in memory, while the immutable datatypes follow the previous one, so it looks like the following in memory:

Summary:

Deep copy: it opens a new space in memory and creates a new copy of the original list and the mutable datatypes inside the list, while the immutable datatypes are kept as they were before.

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