在Python中,计算两个列表之间的差值的最佳方法是什么?
例子
A = [1,2,3,4]
B = [2,5]
A - B = [1,3,4]
B - A = [5]
在Python中,计算两个列表之间的差值的最佳方法是什么?
例子
A = [1,2,3,4]
B = [2,5]
A - B = [1,3,4]
B - A = [5]
当前回答
A = [1,2,3,4]
B = [2,5]
#A - B
x = list(set(A) - set(B))
#B - A
y = list(set(B) - set(A))
print x
print y
其他回答
简单的代码,让你与多个项目的差异,如果你想要:
a=[1,2,3,3,4]
b=[2,4]
tmp = copy.deepcopy(a)
for k in b:
if k in tmp:
tmp.remove(k)
print(tmp)
你可以做一个
list(set(A)-set(B))
and
list(set(B)-set(A))
如果你想要递归地深入到列表中的项目,我已经为python编写了一个包:https://github.com/erasmose/deepdiff
安装
从PyPi安装:
pip install deepdiff
如果你是Python3,你还需要安装:
pip install future six
示例使用
>>> from deepdiff import DeepDiff
>>> from pprint import pprint
>>> from __future__ import print_function
同一对象返回空
>>> t1 = {1:1, 2:2, 3:3}
>>> t2 = t1
>>> ddiff = DeepDiff(t1, t2)
>>> print (ddiff.changes)
{}
项目类型发生变化
>>> t1 = {1:1, 2:2, 3:3}
>>> t2 = {1:1, 2:"2", 3:3}
>>> ddiff = DeepDiff(t1, t2)
>>> print (ddiff.changes)
{'type_changes': ["root[2]: 2=<type 'int'> vs. 2=<type 'str'>"]}
某项的值已更改
>>> t1 = {1:1, 2:2, 3:3}
>>> t2 = {1:1, 2:4, 3:3}
>>> ddiff = DeepDiff(t1, t2)
>>> print (ddiff.changes)
{'values_changed': ['root[2]: 2 ====>> 4']}
项目添加和/或删除
>>> t1 = {1:1, 2:2, 3:3, 4:4}
>>> t2 = {1:1, 2:4, 3:3, 5:5, 6:6}
>>> ddiff = DeepDiff(t1, t2)
>>> pprint (ddiff.changes)
{'dic_item_added': ['root[5, 6]'],
'dic_item_removed': ['root[4]'],
'values_changed': ['root[2]: 2 ====>> 4']}
字符串的区别
>>> t1 = {1:1, 2:2, 3:3, 4:{"a":"hello", "b":"world"}}
>>> t2 = {1:1, 2:4, 3:3, 4:{"a":"hello", "b":"world!"}}
>>> ddiff = DeepDiff(t1, t2)
>>> pprint (ddiff.changes, indent = 2)
{ 'values_changed': [ 'root[2]: 2 ====>> 4',
"root[4]['b']:\n--- \n+++ \n@@ -1 +1 @@\n-world\n+world!"]}
>>>
>>> print (ddiff.changes['values_changed'][1])
root[4]['b']:
---
+++
@@ -1 +1 @@
-world
+world!
字符串差2
>>> t1 = {1:1, 2:2, 3:3, 4:{"a":"hello", "b":"world!\nGoodbye!\n1\n2\nEnd"}}
>>> t2 = {1:1, 2:2, 3:3, 4:{"a":"hello", "b":"world\n1\n2\nEnd"}}
>>> ddiff = DeepDiff(t1, t2)
>>> pprint (ddiff.changes, indent = 2)
{ 'values_changed': [ "root[4]['b']:\n--- \n+++ \n@@ -1,5 +1,4 @@\n-world!\n-Goodbye!\n+world\n 1\n 2\n End"]}
>>>
>>> print (ddiff.changes['values_changed'][0])
root[4]['b']:
---
+++
@@ -1,5 +1,4 @@
-world!
-Goodbye!
+world
1
2
End
类型变化
>>> t1 = {1:1, 2:2, 3:3, 4:{"a":"hello", "b":[1, 2, 3]}}
>>> t2 = {1:1, 2:2, 3:3, 4:{"a":"hello", "b":"world\n\n\nEnd"}}
>>> ddiff = DeepDiff(t1, t2)
>>> pprint (ddiff.changes, indent = 2)
{ 'type_changes': [ "root[4]['b']: [1, 2, 3]=<type 'list'> vs. world\n\n\nEnd=<type 'str'>"]}
列表的区别
>>> t1 = {1:1, 2:2, 3:3, 4:{"a":"hello", "b":[1, 2, 3]}}
>>> t2 = {1:1, 2:2, 3:3, 4:{"a":"hello", "b":[1, 2]}}
>>> ddiff = DeepDiff(t1, t2)
>>> pprint (ddiff.changes, indent = 2)
{ 'list_removed': ["root[4]['b']: [3]"]}
区别2:注意它不考虑顺序
>>> # Note that it DOES NOT take order into account
... t1 = {1:1, 2:2, 3:3, 4:{"a":"hello", "b":[1, 2, 3]}}
>>> t2 = {1:1, 2:2, 3:3, 4:{"a":"hello", "b":[1, 3, 2]}}
>>> ddiff = DeepDiff(t1, t2)
>>> pprint (ddiff.changes, indent = 2)
{ }
包含字典的列表:
>>> t1 = {1:1, 2:2, 3:3, 4:{"a":"hello", "b":[1, 2, {1:1, 2:2}]}}
>>> t2 = {1:1, 2:2, 3:3, 4:{"a":"hello", "b":[1, 2, {1:3}]}}
>>> ddiff = DeepDiff(t1, t2)
>>> pprint (ddiff.changes, indent = 2)
{ 'dic_item_removed': ["root[4]['b'][2][2]"],
'values_changed': ["root[4]['b'][2][1]: 1 ====>> 3"]}
如果顺序无关紧要,你可以简单地计算集合差值:
>>> set([1,2,3,4]) - set([2,5])
set([1, 4, 3])
>>> set([2,5]) - set([1,2,3,4])
set([5])
当查看in -operator的TimeComplexity时,在最坏的情况下它与O(n)一起工作。即使是集合。
因此,当比较两个数组时,最好情况下的TimeComplexity为O(n),最坏情况下为O(n²)。
另一种(但不幸的是更复杂)解决方案,在最好和最坏的情况下都适用于O(n):
# Compares the difference of list a and b
# uses a callback function to compare items
def diff(a, b, callback):
a_missing_in_b = []
ai = 0
bi = 0
a = sorted(a, callback)
b = sorted(b, callback)
while (ai < len(a)) and (bi < len(b)):
cmp = callback(a[ai], b[bi])
if cmp < 0:
a_missing_in_b.append(a[ai])
ai += 1
elif cmp > 0:
# Item b is missing in a
bi += 1
else:
# a and b intersecting on this item
ai += 1
bi += 1
# if a and b are not of same length, we need to add the remaining items
for ai in xrange(ai, len(a)):
a_missing_in_b.append(a[ai])
return a_missing_in_b
e.g.
>>> a=[1,2,3]
>>> b=[2,4,6]
>>> diff(a, b, cmp)
[1, 3]