Python's shades of Copy

Depth copy

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

import copy # ######### 数字、字符串 ######### n1  = 123 # n1 = "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))

For dictionaries, tuples, and lists, the change in memory address is different when assigning, shallow copy, and deep copy.

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

>>> n1 = {"K1": "Zhangshan", "K2": 123, "K3": ["Lisi", 456]}

>>> N2 = N1

>>> Print ID (n1)

11195200

>>> Print ID (n2)

11195200

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

>>> n1 = {"K1": "Zhangshan", "K2": 123, "K3": ["Lisi", 456]}

>>> n3 = copy.copy (N1)

>>> Print ID (n1)

11267952

>>> Print ID (n3)

11151792

>>> Print ID (n1[' K3 ') # #查看内存地址相同

139853825328696

>>> Print ID (n3[' K3 ') # #查看内存地址相同

139853825328696

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Deep Copy , recreate all the data in memory (excluding the last layer, that is, Python's internal optimization of strings and numbers)

>>> Import Copy

>>> n1 = {"K1": "Zhangshan", "K2": 123, "K3": ["Lisi", 456]}

>>> N4 = copy.deepcopy (n1)

>>> Print ID (n1)

11193264

>>> Print ID (n4)

11249664

>>> Print ID (n1[' K3 ') # #查看内存地址不同

139853635849824

>>> Print ID (n2[' K3 ') # #查看内存地址不同

139853635827256

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Python's shades of Copy