Getting the difference (delta) between two lists of dictionaries
Asked Answered
E

4

36

I have the following Python data structures:

data1 = [{'name': u'String 1'}, {'name': u'String 2'}]
data2 = [{'name': u'String 1'}, {'name': u'String 2'}, {'name': u'String 3'}]

I'm looking for the best way to get the delta between the two lists. Is there anything in Python that's as convenient as the JavaScript Underscore.js (_.difference) library?

Eudo answered 3/11, 2013 at 16:51 Comment(0)
D
34

Use itertools.filterfalse:

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'}]
Dogwood answered 3/11, 2013 at 16:59 Comment(1)
That's ifilterfalse on python2.Lovejoy
C
39

How about this:

>>> [x for x in data2 if x not in data1]
[{'name': u'String 3'}]

Edit:

If you need symmetric difference you can use :

>>> [x for x in data1 + data2 if x not in data1 or x not in data2]

or

>>> [x for x in data1 if x not in data2] + [y for y in data2 if y not in data1]

One more edit

You can also use sets:

>>> 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)
Chiromancy answered 3/11, 2013 at 16:57 Comment(4)
What happens if data1 contains items not in data2?Dogwood
As @LutzHorn pointed out, this is equivalent to set(data2) - set(data1) (except dicts are unhashable). @Eudo asked for the delta which would be sets' symmetric difference, so the correct answer is @LutzHorn 's.Prau
@LutzHorn _.difference is not symmetric so output will be the same.Chiromancy
Thanks chaps - Both of the above suggestions seem to work for me and produce the same results. Is there any benefit of using either one?Eudo
D
34

Use itertools.filterfalse:

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'}]
Dogwood answered 3/11, 2013 at 16:59 Comment(1)
That's ifilterfalse on python2.Lovejoy
O
20

In case you want the difference recursively, I have written a package for python: https://github.com/seperman/deepdiff

Installation

Install from PyPi:

pip install deepdiff

Example usage

Importing

>>> from deepdiff import DeepDiff
>>> from pprint import pprint
>>> from __future__ import print_function # In case running on Python 2

Same object returns empty

>>> t1 = {1:1, 2:2, 3:3}
>>> t2 = t1
>>> print(DeepDiff(t1, t2))
{}

Type of an item has changed

>>> 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}}}

Value of an item has changed

>>> 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}}}

Item added and/or removed

>>> 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}}}

String difference

>>> 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'}}}

String difference 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

Type change

>>> 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]}}}

List difference

>>> 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}}

List difference 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}}}

List difference ignoring order or duplicates: (with the same dictionaries as above)

>>> 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)
{}

List that contains dictionary:

>>> 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}}}

Sets:

>>> 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]']}

Named Tuples:

>>> 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}}}

Custom objects:

>>> 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}}}

Object attribute added:

>>> t2.c = "new attribute"
>>> pprint(DeepDiff(t1, t2))
{'attribute_added': ['root.c'],
 'values_changed': {'root.b': {'newvalue': 2, 'oldvalue': 1}}}
Oeildeboeuf answered 27/9, 2014 at 20:50 Comment(2)
Amazing library. How this feature set is not in Python standard library - I will never know ;)Essayistic
Haha. Thanks @TonySepia! Maybe one day it will be in the standard library... I guess I could submit a proposal...Oeildeboeuf
R
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
Rowlandson answered 25/2, 2015 at 3:7 Comment(1)
you have to know that data2 has more data to set up 'delta'Essam

© 2022 - 2024 — McMap. All rights reserved.