Python base assignment/deep copy/shallow copy

First, whether it's an assignment or a depth copy, it's a distinction between values that might change, that is, for numbers, for strings, it's meaningless to assign values.

So, let's get to those mutable like List set Dict tuple ... To be explored.

Assignment value:

There are two ways to modify N:

1 assigning values directly to n

>>> n=[1,2]>>> g=n>>> ID (n)140529062430792>>>  ID (g)140529062430792>>> n=[1,3]>>> g[1, 2]>>> ID (n) 140529062430920>>> ID (g)140529062430792

2 Assigning a value to an element of n

>>> n=[1,2]>>> g=n>>> ID (n)140529062430728>>>  ID (g)140529062430728>>> n[1]=3>>> g[1, 3]>>> ID (n) 140529062430728>>> ID (g)140529062430728

Shallow copy

>>> Import copy>>> name=[' Tong ', ' Yang '
>>> N=[1,name]
>>> g=copy.copy (N)
>>> g
[1, [' Tong ', ' Yang ']
>>> ID (N)
140529062259976
>>> ID (g)
140529062259848# two variables (n and g) have different addresses

When modifying the element of the name of N:

>>> name[1]='Hua'>>>n[1, ['Tong','Hua']]>>>g[1, ['Tong','Hua']]>>>ID (n)140529062259976>>>ID (g)140529062259848#the values of N and G are the same, and the memory address has not changed

　　shallow copy will only copy one layer, so the values of N and G have changed in the example above .

Deep copy

>>> name=['Tong','Yang']>>> n=[1, name]>>> g=copy.deepcopy (n)>>>g[1, ['Tong','Yang']] #g的第二个元素已经不是变量name了. >>>ID (n)140529062430728>>>ID (g)140529062259976#n differs from G's address

When you modify the element of name:

 >>> name[1]= " hua   '  >>> 

　　Deep copy will copy all layers, and the values of the variables will be directly output to replace the variables.

This article refers to the following: http://www.cnblogs.com/wupeiqi/articles/5133343.html

Python base assignment/deep copy/shallow copy