2.7中两个方法的时间比较显示它们实际上是相同的:

>>> setup_string = "a = sorted(dict({2:3, 1:89, 4:5, 3:0}).items())"
>>> timeit.timeit(stmt="[(k, val) for k, val in a]", setup=setup_string, number=10000)
0.003599141953657181

>>> setup_string = "from collections import OrderedDict\n"
>>> setup_string += "a = OrderedDict({1:89, 2:3, 3:0, 4:5})\n"
>>> setup_string += "b = a.items()"
>>> timeit.timeit(stmt="[(k, val) for k, val in b]", setup=setup_string, number=10000)
0.003581275490432745 

或者用熊猫，

演示:

>>> d={'B':1,'A':2,'C':3}
>>> df=pd.DataFrame(d,index=[0]).sort_index(axis=1)
   A  B  C
0  2  1  3
>>> df.to_dict('int')[0]
{'A': 2, 'B': 1, 'C': 3}
>>> 

See:

这方面的文档 整只熊猫的记录

dictionary = {1:[2],2:[],5:[4,5],4:[5],3:[1]}

temp=sorted(dictionary)
sorted_dict = dict([(k,dictionary[k]) for i,k in enumerate(temp)])

sorted_dict:
         {1: [2], 2: [], 3: [1], 4: [5], 5: [4, 5]}

在这里，我找到了一些最简单的解决方案，使用pprint按键对python字典进行排序。 如。

>>> x = {'a': 10, 'cd': 20, 'b': 30, 'az': 99} 
>>> print x
{'a': 10, 'b': 30, 'az': 99, 'cd': 20}

但是当使用pprint时，它将返回排序后的dict

>>> import pprint 
>>> pprint.pprint(x)
{'a': 10, 'az': 99, 'b': 30, 'cd': 20}

from operator import itemgetter
# if you would like to play with multiple dictionaries then here you go:
# Three dictionaries that are composed of first name and last name.
user = [
    {'fname': 'Mo', 'lname': 'Mahjoub'},
    {'fname': 'Abdo', 'lname': 'Al-hebashi'},
    {'fname': 'Ali', 'lname': 'Muhammad'}
]
#  This loop will sort by the first and the last names.
# notice that in a dictionary order doesn't matter. So it could put the first name first or the last name first. 
for k in sorted (user, key=itemgetter ('fname', 'lname')):
    print (k)

# This one will sort by the first name only.
for x in sorted (user, key=itemgetter ('fname')):
    print (x)

我发现对字典进行排序的一个简单方法是，根据要排序的字典的排序键:值项创建一个新字典。 如果你想对dict ={}排序，使用相关的方法检索它的所有项，使用sorted()函数对它们排序，然后创建新字典。

下面是使用字典理解的代码:

sorted_dict = {k:v for k,v in sorted(dict.items())}