我有以下Python数据结构：
data1 = [{'name': u'String 1'}, {'name': u'String 2'}]
data2 = [{'name': u'String 1'}, {'name': u'String 2'}, {'name': u'String 3'}]
我正在寻找获取两个列表之间差异的最佳方法。在Python中是否有像JavaScript Underscore.js (_.difference)库一样方便的工具？
获取两个字典列表之间的差异（增量）
35
- user1513388
4个回答
38
这个怎么样：
>>> [x for x in data2 if x not in data1]
[{'name': u'String 3'}]
编辑:
如果您需要对称差集，可以使用：
>>> [x for x in data1 + data2 if x not in data1 or x not in data2]
>>> [x for x in data1 if x not in data2] + [y for y in data2 if y not in data1]
另外一次编辑
你也可以使用集合：
>>> from functools import reduce
>>> s1 = set(reduce(lambda x, y: x + y, [x.items() for x in data1]))
>>> s2 = set(reduce(lambda x, y: x + y, [x.items() for x in data2]))
>>> s2.difference(s1)
>>> s2.symmetric_difference(s1)
- zero323
4
34
import itertools
r = list(itertools.filterfalse(lambda x: x in data1, data2))
+ list(itertools.filterfalse(lambda x: x in data2, data1))
assert r == [{'name': 'String 3'}]
- user1907906
1
5这是针对Python2的ifilterfalse。 - vegai
20
如果您需要递归地获取差异，我编写了一个用于Python的软件包：
https://github.com/seperman/deepdiff安装
从PyPi安装：
pip install deepdiff
使用示例
导入
>>> from deepdiff import DeepDiff
>>> from pprint import pprint
>>> from __future__ import print_function # In case running on Python 2
同一对象返回空
>>> t1 = {1:1, 2:2, 3:3}
>>> t2 = t1
>>> print(DeepDiff(t1, t2))
{}
项目类型已更改
>>> t1 = {1:1, 2:2, 3:3}
>>> t2 = {1:1, 2:"2", 3:3}
>>> pprint(DeepDiff(t1, t2), indent=2)
{ 'type_changes': { 'root[2]': { 'newtype': <class 'str'>,
'newvalue': '2',
'oldtype': <class 'int'>,
'oldvalue': 2}}}
某个项的值已经改变
>>> t1 = {1:1, 2:2, 3:3}
>>> t2 = {1:1, 2:4, 3:3}
>>> pprint(DeepDiff(t1, t2), indent=2)
{'values_changed': {'root[2]': {'newvalue': 4, 'oldvalue': 2}}}
已添加和/或删除项目
>>> 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)
{'dic_item_added': ['root[5]', 'root[6]'],
'dic_item_removed': ['root[4]'],
'values_changed': {'root[2]': {'newvalue': 4, 'oldvalue': 2}}}
字符串差异
>>> 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, indent = 2)
{ 'values_changed': { 'root[2]': {'newvalue': 4, 'oldvalue': 2},
"root[4]['b']": { 'newvalue': 'world!',
'oldvalue': 'world'}}}
字符串差异 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, indent = 2)
{ 'values_changed': { "root[4]['b']": { 'diff': '--- \n'
'+++ \n'
'@@ -1,5 +1,4 @@\n'
'-world!\n'
'-Goodbye!\n'
'+world\n'
' 1\n'
' 2\n'
' End',
'newvalue': 'world\n1\n2\nEnd',
'oldvalue': 'world!\n'
'Goodbye!\n'
'1\n'
'2\n'
'End'}}}
>>>
>>> print (ddiff['values_changed']["root[4]['b']"]["diff"])
---
+++
@@ -1,5 +1,4 @@
-world!
-Goodbye!
+world
1
2
End
类型变换
>>> 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, indent = 2)
{ 'type_changes': { "root[4]['b']": { 'newtype': <class 'str'>,
'newvalue': 'world\n\n\nEnd',
'oldtype': <class 'list'>,
'oldvalue': [1, 2, 3]}}}
>>> t1 = {1:1, 2:2, 3:3, 4:{"a":"hello", "b":[1, 2, 3, 4]}}
>>> t2 = {1:1, 2:2, 3:3, 4:{"a":"hello", "b":[1, 2]}}
>>> ddiff = DeepDiff(t1, t2)
>>> pprint (ddiff, indent = 2)
{'iterable_item_removed': {"root[4]['b'][2]": 3, "root[4]['b'][3]": 4}}
列表差异2：
>>> 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, 3]}}
>>> ddiff = DeepDiff(t1, t2)
>>> pprint (ddiff, indent = 2)
{ 'iterable_item_added': {"root[4]['b'][3]": 3},
'values_changed': { "root[4]['b'][1]": {'newvalue': 3, 'oldvalue': 2},
"root[4]['b'][2]": {'newvalue': 2, 'oldvalue': 3}}}
- 忽略顺序或重复项的列表差异：（与上面相同的字典）
>>> 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, 3]}}
>>> ddiff = DeepDiff(t1, t2, ignore_order=True)
>>> print (ddiff)
{}
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, indent = 2)
{ 'dic_item_removed': ["root[4]['b'][2][2]"],
'values_changed': {"root[4]['b'][2][1]": {'newvalue': 3, 'oldvalue': 1}}}
集合：
>>> t1 = {1, 2, 8}
>>> t2 = {1, 2, 3, 5}
>>> ddiff = DeepDiff(t1, t2)
>>> pprint (DeepDiff(t1, t2))
{'set_item_added': ['root[3]', 'root[5]'], 'set_item_removed': ['root[8]']}
命名元组：
>>> from collections import namedtuple
>>> Point = namedtuple('Point', ['x', 'y'])
>>> t1 = Point(x=11, y=22)
>>> t2 = Point(x=11, y=23)
>>> pprint (DeepDiff(t1, t2))
{'values_changed': {'root.y': {'newvalue': 23, 'oldvalue': 22}}}
自定义对象：
>>> class ClassA(object):
... a = 1
... def __init__(self, b):
... self.b = b
...
>>> t1 = ClassA(1)
>>> t2 = ClassA(2)
>>>
>>> pprint(DeepDiff(t1, t2))
{'values_changed': {'root.b': {'newvalue': 2, 'oldvalue': 1}}}
新增了对象属性：
>>> t2.c = "new attribute"
>>> pprint(DeepDiff(t1, t2))
{'attribute_added': ['root.c'],
'values_changed': {'root.b': {'newvalue': 2, 'oldvalue': 1}}}
- Seperman
2
1惊人的库。为什么这个功能集不在Python标准库中，我永远不会知道 ;) - tonysepia
3哈哈，谢谢@TonySepia！也许有一天它会成为标准库...我想我可以提交一个提案... - Seperman
2
data1 = [{'name': u'String 1'}, {'name': u'String 2'}]
data2 = [{'name': u'String 1'}, {'name': u'String 2'}, {'name': u'String 3'}]
delta = list({dict2['name'] for dict2 in data2} -
{dict1['name'] for dict1 in data1})
delta_dict = [{'name': value} for value in delta]
print delta_dict
- Saksham Varma
1
你必须知道data2有更多的数据来设置“delta”。 - sk8asd123
网页内容由stack overflow 提供, 点击上面的可以查看英文原文，
原文链接
原文链接
data1包含了data2中没有的项会发生什么？ - user1907906set(data2) - set(data1)（除了字典是不可哈希的）。@user1513388要求的增量将是集合的对称差异，因此正确答案是@LutzHorn的。 - ThinkChaos