Python深度复制与浅复制

2017-05-17  本文已影响0人  开罗酒吧

原文链接:http://www.python-course.eu/deep_copy.php

The difference between shallow and deep copying is only relevant for compound objects, which are objects containing other objects, like lists or class instances.

>>> colours1 = ["red", "green"]
>>> colours2 = colours1
>>> colours2 = ["rouge", "vert"]
>>> print colours1
['red', 'green']

In the example above a simple list is assigned to colours1. In the next step we assign colour1 to colours2. After this, a new list is assigned to colours2. A new memory location had been allocated for colours2, because we have assigned a complete new list to this variable.

>> colours1 = ["red", "green"]
>>> colours2 = colours1
>>> colours2[1] = "blue"
>>> colours1
['red', 'blue']

colours1 and colours2 share the same memory

shallow copy:using [:]

>>> list1 = ['a','b','c','d']
>>> list2 = list1[:]
>>> list2[1] = 'x'
>>> print list2
['a', 'x', 'c', 'd']
>>> print list1
['a', 'b', 'c', 'd']
>>> 

But as soon as a list contains sublists, we have the same difficulty, i.e. just pointers to the sublists.

>>> lst1 = ['a','b',['ab','ba']]
>>> lst2 = lst1[:]
shallow_copy_4.png

Using the Method deepcopy from the Module copy

A solution to the described problems is to use the module "copy". This module provides the method "copy", which allows a complete copy of a arbitrary list, i.e. shallow and other lists.

The following script uses our example above and this method:

from copy import deepcopy

lst1 = ['a','b',['ab','ba']]

lst2 = deepcopy(lst1)

lst2[2][1] = "d"
lst2[0] = "c";

print lst2
print lst1

If we save this script under the name of deep_copy.py and if we call the script with "python deep_copy.py", we will receive the following output:

$ python deep_copy.py 
['c', 'b', ['ab', 'd']]
['a', 'b', ['ab', 'ba']]
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