Deep and latent copies in Python

>>> a = [' Ace ', [' age ',10]]>>> b = a[:]>>> c = List (a) >>> for item in a: ...     Print (ID (item))     ... 140281621219736140281621134800>>> for item in B:    print (ID (item))     ... 140281621219736140281621134800>>> for item in C:    print (ID (item))     ... 140281621219736140281621134800

As you can see, the centralized copy here is just a pointer-like reference. Change to try?

>>> b[0] = ' bog ' >>> b[' bog ', [' age ', 10]]>>> a[' Ace ', [' age ', 10]]>>> c[' Ace ', [' age ' , 10]]>>> c[0] = ' cat ' >>> a[' Ace ', [' age ', 10]]>>> b[' bog ', [' age ', 10]]>>> c[' cat ', [ ' Age ', 10]]

AI, it's changed. Changing the list?

>>> a[' Ace ', [' age ', 10]]>>> b[' bog ', [' age ', 10]]>>> c[' cat ', [' age ', 10]]>>> a[1][ 1] = ' ago ' >>> a[' Ace ', [' Age ', ' ago ']]>>> b[' bog ', [' Age ', ' ago ']]>>> c[' cat ', [' Age ', ' ago '] >>> b[1][1] = ' agy ' >>> a[' Ace ', [' age ', ' agy ']]>>> b[' bog ', [' age ', ' agy ']]>>> c[' Cat ', [' age ', ' agy ']]>>> c[1][1] = ' cat! ' >>> a[' Ace ', [' age ', ' cat! '] >>> b[' bog ', [' age ', ' cat! '] >>> c[' cat ', [' age ', ' cat! ']

Emma, it's all changed. What a situation!

Haha, here's a summary!

found that the name string IDs in the list are different, but the age list IDs are the same.

This is because the strings in Python cannot be modified, so when you rename Tom and Anny, you re-create a ' tom ' and ' Anny ' object, replacing the old ' Jack ' object.

This explains that shallow copy (shallow copy), which duplicates the object, but still uses references to the elements in the object.

That deep copy is also playing full-time from memory space to open a new address to save a copy spicy!

How to use it?

>>> import copy>>> D = copy.deepcopy (a) >>> for item in a: ...     Print (ID (a))     ... 140281621133432140281621133432>>> for item in D:    print (ID (item))     ... 140281621219736140281621159160

see! It's not the same.

Deep and latent copies in Python