使用new_list=my_list时,对new_list的任何修改都会每次更改my_list。为什么会出现这种情况,以及如何克隆或复制列表以防止出现这种情况?
当前回答
还有另一种方法可以复制一个直到现在才列出的列表:添加一个空列表:l2=l+[]。
我用Python 3.8测试了它:
l = [1,2,3]
l2 = l + []
print(l,l2)
l[0] = 'a'
print(l,l2)
这不是最好的答案,但它奏效了。
其他回答
让我惊讶的是,这还没有被提及,所以为了完整起见。。。
您可以使用“splat operator”:*执行列表解包,这也将复制列表的元素。
old_list = [1, 2, 3]
new_list = [*old_list]
new_list.append(4)
old_list == [1, 2, 3]
new_list == [1, 2, 3, 4]
这种方法的明显缺点是它仅在Python 3.5+中可用。
尽管从时间上看,这似乎比其他常用方法表现得更好。
x = [random.random() for _ in range(1000)]
%timeit a = list(x)
%timeit a = x.copy()
%timeit a = x[:]
%timeit a = [*x]
#: 2.47 µs ± 38.1 ns per loop (mean ± std. dev. of 7 runs, 100000 loops each)
#: 2.47 µs ± 54.6 ns per loop (mean ± std. dev. of 7 runs, 100000 loops each)
#: 2.39 µs ± 58.2 ns per loop (mean ± std. dev. of 7 runs, 100000 loops each)
#: 2.22 µs ± 43.2 ns per loop (mean ± std. dev. of 7 runs, 100000 loops each)
deepcopy选项是唯一适用于我的方法:
from copy import deepcopy
a = [ [ list(range(1, 3)) for i in range(3) ] ]
b = deepcopy(a)
b[0][1]=[3]
print('Deep:')
print(a)
print(b)
print('-----------------------------')
a = [ [ list(range(1, 3)) for i in range(3) ] ]
b = a*1
b[0][1]=[3]
print('*1:')
print(a)
print(b)
print('-----------------------------')
a = [ [ list(range(1, 3)) for i in range(3) ] ]
b = a[:]
b[0][1]=[3]
print('Vector copy:')
print(a)
print(b)
print('-----------------------------')
a = [ [ list(range(1, 3)) for i in range(3) ] ]
b = list(a)
b[0][1]=[3]
print('List copy:')
print(a)
print(b)
print('-----------------------------')
a = [ [ list(range(1, 3)) for i in range(3) ] ]
b = a.copy()
b[0][1]=[3]
print('.copy():')
print(a)
print(b)
print('-----------------------------')
a = [ [ list(range(1, 3)) for i in range(3) ] ]
b = a
b[0][1]=[3]
print('Shallow:')
print(a)
print(b)
print('-----------------------------')
导致输出:
Deep:
[[[1, 2], [1, 2], [1, 2]]]
[[[1, 2], [3], [1, 2]]]
-----------------------------
*1:
[[[1, 2], [3], [1, 2]]]
[[[1, 2], [3], [1, 2]]]
-----------------------------
Vector copy:
[[[1, 2], [3], [1, 2]]]
[[[1, 2], [3], [1, 2]]]
-----------------------------
List copy:
[[[1, 2], [3], [1, 2]]]
[[[1, 2], [3], [1, 2]]]
-----------------------------
.copy():
[[[1, 2], [3], [1, 2]]]
[[[1, 2], [3], [1, 2]]]
-----------------------------
Shallow:
[[[1, 2], [3], [1, 2]]]
[[[1, 2], [3], [1, 2]]]
-----------------------------
菲利克斯已经给出了一个很好的答案,但我想我应该对各种方法进行速度比较:
10.59秒(105.9µs/itn)-copy.depcopy(旧列表)10.16秒(101.6µs/itn)-纯Python Copy()方法使用deepcopy复制类1.488秒(14.88µs/itn)-纯Python Copy()方法不复制类(仅dicts/lists/tuples)0.325秒(3.25µs/itn)-对于old_list:new_list.append(项目)中的项目0.217秒(2.17µs/itn)-[i代表old_list](列表理解)0.186秒(1.86µs/itn)-复制副本(old_list)0.075秒(0.75µs/itn)-列表(旧列表)0.053秒(0.53µs/itn)-新列表=[];新列表扩展(旧列表)0.039秒(0.39µs/itn)-old_list[:](列表切片)
所以最快的是列表切片。但请注意,与copy.deepcopy()和python版本不同,copy.copy()、list[:]和list(list)不会复制列表中的任何列表、字典和类实例,因此如果原始列表发生变化,它们也会在复制的列表中发生变化,反之亦然。
(如果有人感兴趣或想提出任何问题,以下是脚本:)
from copy import deepcopy
class old_class:
def __init__(self):
self.blah = 'blah'
class new_class(object):
def __init__(self):
self.blah = 'blah'
dignore = {str: None, unicode: None, int: None, type(None): None}
def Copy(obj, use_deepcopy=True):
t = type(obj)
if t in (list, tuple):
if t == tuple:
# Convert to a list if a tuple to
# allow assigning to when copying
is_tuple = True
obj = list(obj)
else:
# Otherwise just do a quick slice copy
obj = obj[:]
is_tuple = False
# Copy each item recursively
for x in xrange(len(obj)):
if type(obj[x]) in dignore:
continue
obj[x] = Copy(obj[x], use_deepcopy)
if is_tuple:
# Convert back into a tuple again
obj = tuple(obj)
elif t == dict:
# Use the fast shallow dict copy() method and copy any
# values which aren't immutable (like lists, dicts etc)
obj = obj.copy()
for k in obj:
if type(obj[k]) in dignore:
continue
obj[k] = Copy(obj[k], use_deepcopy)
elif t in dignore:
# Numeric or string/unicode?
# It's immutable, so ignore it!
pass
elif use_deepcopy:
obj = deepcopy(obj)
return obj
if __name__ == '__main__':
import copy
from time import time
num_times = 100000
L = [None, 'blah', 1, 543.4532,
['foo'], ('bar',), {'blah': 'blah'},
old_class(), new_class()]
t = time()
for i in xrange(num_times):
Copy(L)
print 'Custom Copy:', time()-t
t = time()
for i in xrange(num_times):
Copy(L, use_deepcopy=False)
print 'Custom Copy Only Copying Lists/Tuples/Dicts (no classes):', time()-t
t = time()
for i in xrange(num_times):
copy.copy(L)
print 'copy.copy:', time()-t
t = time()
for i in xrange(num_times):
copy.deepcopy(L)
print 'copy.deepcopy:', time()-t
t = time()
for i in xrange(num_times):
L[:]
print 'list slicing [:]:', time()-t
t = time()
for i in xrange(num_times):
list(L)
print 'list(L):', time()-t
t = time()
for i in xrange(num_times):
[i for i in L]
print 'list expression(L):', time()-t
t = time()
for i in xrange(num_times):
a = []
a.extend(L)
print 'list extend:', time()-t
t = time()
for i in xrange(num_times):
a = []
for y in L:
a.append(y)
print 'list append:', time()-t
t = time()
for i in xrange(num_times):
a = []
a.extend(i for i in L)
print 'generator expression extend:', time()-t
Python 3.6计时
下面是使用Python 3.6.8的计时结果。请记住,这些时间是相对的,而不是绝对的。
我坚持只做浅层复制,还添加了一些在Python 2中不可能的新方法,例如list.copy()(Python 3切片的等价物)和两种形式的列表解包(*new_list,=list和new_list=[*list]):
METHOD TIME TAKEN
b = [*a] 2.75180600000021
b = a * 1 3.50215399999990
b = a[:] 3.78278899999986 # Python 2 winner (see above)
b = a.copy() 4.20556500000020 # Python 3 "slice equivalent" (see above)
b = []; b.extend(a) 4.68069800000012
b = a[0:len(a)] 6.84498999999959
*b, = a 7.54031799999984
b = list(a) 7.75815899999997
b = [i for i in a] 18.4886440000000
b = copy.copy(a) 18.8254879999999
b = []
for item in a:
b.append(item) 35.4729199999997
我们可以看到,Python 2的获胜者仍然表现出色,但并没有远远超过Python 3 list.copy(),特别是考虑到后者的出色可读性。
黑马是拆包和重新包装方法(b=[*a]),它比原始切片快约25%,比其他拆包方法(*b,=a)快两倍多。
b=a*1的表现也出奇地好。
请注意,这些方法不会为列表以外的任何输入输出等效结果。它们都适用于可切片对象,少数适用于任何可迭代对象,但只有copy.copy()适用于更一般的Python对象。
以下是相关方的测试代码(此处的模板):
import timeit
COUNT = 50000000
print("Array duplicating. Tests run", COUNT, "times")
setup = 'a = [0,1,2,3,4,5,6,7,8,9]; import copy'
print("b = list(a)\t\t", timeit.timeit(stmt='b = list(a)', setup=setup, number=COUNT))
print("b = copy.copy(a)\t", timeit.timeit(stmt='b = copy.copy(a)', setup=setup, number=COUNT))
print("b = a.copy()\t\t", timeit.timeit(stmt='b = a.copy()', setup=setup, number=COUNT))
print("b = a[:]\t\t", timeit.timeit(stmt='b = a[:]', setup=setup, number=COUNT))
print("b = a[0:len(a)]\t\t", timeit.timeit(stmt='b = a[0:len(a)]', setup=setup, number=COUNT))
print("*b, = a\t\t\t", timeit.timeit(stmt='*b, = a', setup=setup, number=COUNT))
print("b = []; b.extend(a)\t", timeit.timeit(stmt='b = []; b.extend(a)', setup=setup, number=COUNT))
print("b = []; for item in a: b.append(item)\t", timeit.timeit(stmt='b = []\nfor item in a: b.append(item)', setup=setup, number=COUNT))
print("b = [i for i in a]\t", timeit.timeit(stmt='b = [i for i in a]', setup=setup, number=COUNT))
print("b = [*a]\t\t", timeit.timeit(stmt='b = [*a]', setup=setup, number=COUNT))
print("b = a * 1\t\t", timeit.timeit(stmt='b = a * 1', setup=setup, number=COUNT))
Python的习惯用法是newList=oldList[:]
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