"Python trail 13" Python's deep-shade copy

Depth copy

One, number and string

For numbers and strings, assignments, shallow copies, and deep copies are meaningless because they always point to the same memory address.

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importcopy# ######### 数字、字符串 #########n1 =123# n1 = "i am alex age 10"print(id(n1))# ## 赋值 ##n2 =n1print(id(n2))# ## 浅拷贝 ##n2 =copy.copy(n1)print(id(n2)) # ## 深拷贝 ##n3 =copy.deepcopy(n1)print(id(n3))

Second, other basic data types

For dictionaries, Ganso, and lists, the changes in the memory address of the assignment, the shallow copy, and the deep copy are different.

1. Assign Value

assignment , just create a variable that points to the original memory address, such as:

123	n1  =   { "K1" :  "WU" ,  "K2" :  123 ,  "K3" : [ "Alex"   456 ]}     n2  =   n1

　　

2. Shallow copy

Shallow copy , creating only the first layer of data in memory

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

3. Deep copy

deep copy , recreate all the data in memory (excluding the last layer, i.e., Python's internal optimization of strings and numbers)

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

"Python trail 13" Python's deep-shade copy