Python deep copy of different data types

Deep copy

1. Numbers and strings

For numbers and strings, there is no actual change in assignment, shallow copy, and deep copy, because after these operations, the number or string still points to the same memory address.

import copy
# ######### 数字、字符串 #########
n1 = 123
# n1 = "i am alex age 10"
print(id(n1))
# ## 赋值 ##
n2 = n1
print(id(n2))
# ## 浅拷贝 ##
n2 = copy.copy(n1)
print(id(n2))
  
# ## 深拷贝 ##
n3 = copy.deepcopy(n1)
print(id(n3))

2. Other basic data types

For dictionaries, ancestors, and lists, the memory address changes are different when assigning, shallow copying and deep copying.

1. Assignment

Assignment just creates a variable that points to the original memory address, such as:

n1 = {
    
    "k1": "wu", "k2": 123, "k3": ["alex", 456]}
  
n2 = n1

2. Shallow copy

Shallow copy, only the first layer of data is created in memory

'''
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'''
import copy
  
n1 = {
    
    "k1": "wu", "k2": 123, "k3": ["alex", 456]}
  
n3 = copy.copy(n1)

3. Deep copy

Deep copy, recreate all the data in the memory (excluding the last layer, namely: python internal optimization of strings and numbers)

'''
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'''
import copy
  
n1 = {
    
    "k1": "wu", "k2": 123, "k3": ["alex", 456]}
  
n4 = copy.deepcopy(n1)