如何按特定键的值对词典列表进行排序?鉴于:

[{'name': 'Homer', 'age': 39}, {'name': 'Bart', 'age': 10}]

按名称排序时,应为:

[{'name': 'Bart', 'age': 10}, {'name': 'Homer', 'age': 39}]

当前回答

a = [{'name':'Homer', 'age':39}, ...]

# This changes the list a
a.sort(key=lambda k : k['name'])

# This returns a new list (a is not modified)
sorted(a, key=lambda k : k['name']) 

其他回答

如@Claudiu对@monojohnny在本回答的评论部分所示,给出:

list_to_be_sorted = [
                      {'name':'Homer', 'age':39}, 
                      {'name':'Milhouse', 'age':10}, 
                      {'name':'Bart', 'age':10} 
                    ]

按关键字“age”、“name”对词典列表进行排序(如SQL语句ORDER BY age,name),可以使用:

newlist = sorted( list_to_be_sorted, key=lambda k: (k['age'], k['name']) )

或者,同样

import operator
newlist = sorted( list_to_be_sorted, key=operator.itemgetter('age','name') )

打印(新列表)

〔{‘name’:‘Bart’,‘age’:10},{‘ame’:‘Milhouse’,‘age’:10〕,{‘name’:‘Homer’,‘age’:39}〕

您必须实现自己的比较函数,该函数将通过名称键的值来比较字典。参见PythonInfo Wiki中的排序迷你如何

a = [{'name':'Homer', 'age':39}, ...]

# This changes the list a
a.sort(key=lambda k : k['name'])

# This returns a new list (a is not modified)
sorted(a, key=lambda k : k['name']) 

sorted()函数接受key=参数

newlist = sorted(list_to_be_sorted, key=lambda d: d['name']) 

或者,您可以使用operator.itemgetter而不是自己定义函数

from operator import itemgetter
newlist = sorted(list_to_be_sorted, key=itemgetter('name')) 

为完整起见,添加reverse=True以降序排序

newlist = sorted(list_to_be_sorted, key=itemgetter('name'), reverse=True)

使用Pandas包是另一种方法,尽管其大规模运行时比其他人提出的更传统的方法慢得多:

import pandas as pd

listOfDicts = [{'name':'Homer', 'age':39}, {'name':'Bart', 'age':10}]
df = pd.DataFrame(listOfDicts)
df = df.sort_values('name')
sorted_listOfDicts = df.T.to_dict().values()

下面是一个小列表和一个大(100k+)的字典列表的一些基准值:

setup_large = "listOfDicts = [];\
[listOfDicts.extend(({'name':'Homer', 'age':39}, {'name':'Bart', 'age':10})) for _ in range(50000)];\
from operator import itemgetter;import pandas as pd;\
df = pd.DataFrame(listOfDicts);"

setup_small = "listOfDicts = [];\
listOfDicts.extend(({'name':'Homer', 'age':39}, {'name':'Bart', 'age':10}));\
from operator import itemgetter;import pandas as pd;\
df = pd.DataFrame(listOfDicts);"

method1 = "newlist = sorted(listOfDicts, key=lambda k: k['name'])"
method2 = "newlist = sorted(listOfDicts, key=itemgetter('name')) "
method3 = "df = df.sort_values('name');\
sorted_listOfDicts = df.T.to_dict().values()"

import timeit
t = timeit.Timer(method1, setup_small)
print('Small Method LC: ' + str(t.timeit(100)))
t = timeit.Timer(method2, setup_small)
print('Small Method LC2: ' + str(t.timeit(100)))
t = timeit.Timer(method3, setup_small)
print('Small Method Pandas: ' + str(t.timeit(100)))

t = timeit.Timer(method1, setup_large)
print('Large Method LC: ' + str(t.timeit(100)))
t = timeit.Timer(method2, setup_large)
print('Large Method LC2: ' + str(t.timeit(100)))
t = timeit.Timer(method3, setup_large)
print('Large Method Pandas: ' + str(t.timeit(1)))

#Small Method LC: 0.000163078308105
#Small Method LC2: 0.000134944915771
#Small Method Pandas: 0.0712950229645
#Large Method LC: 0.0321750640869
#Large Method LC2: 0.0206089019775
#Large Method Pandas: 5.81405615807