有一个简单的方法:

d = {2:3, 1:89, 4:5, 3:0}

s = {k : d[k] for k in sorted(d)}

s

Out[1]: {1: 89, 2: 3, 3: 0, 4: 5} 

来自Python的集合库文档:

>>> from collections import OrderedDict

>>> # regular unsorted dictionary
>>> d = {'banana': 3, 'apple':4, 'pear': 1, 'orange': 2}

>>> # dictionary sorted by key -- OrderedDict(sorted(d.items()) also works
>>> OrderedDict(sorted(d.items(), key=lambda t: t[0]))
OrderedDict([('apple', 4), ('banana', 3), ('orange', 2), ('pear', 1)])

>>> # dictionary sorted by value
>>> OrderedDict(sorted(d.items(), key=lambda t: t[1]))
OrderedDict([('pear', 1), ('orange', 2), ('banana', 3), ('apple', 4)])

>>> # dictionary sorted by length of the key string
>>> OrderedDict(sorted(d.items(), key=lambda t: len(t[0])))
OrderedDict([('pear', 1), ('apple', 4), ('orange', 2), ('banana', 3)])

找到了另一种方法:

import json
print json.dumps(d, sort_keys = True)

乌利希期刊指南: 1. 这也可以对嵌套对象进行排序(谢谢@DanielF)。 2. Python字典是无序的，因此只适用于打印或赋值给STR。

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]}

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 

以下是建议解决方案的性能:

from collections import OrderedDict
from sortedcontainers import SortedDict
import json

keys = np.random.rand(100000)
vals = np.random.rand(100000)

d = dict(zip(keys, vals))

timeit SortedDict(d)
#45.8 ms ± 780 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)

timeit sorted(d.items())
#91.9 ms ± 707 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)

timeit OrderedDict(sorted(d.items(), key=lambda x: x[0]))
#93.7 ms ± 1.52 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)

timeit dict(sorted(dic.items()))
#113 ms ± 824 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)

timeit OrderedDict(sorted(dic.items()))
#122 ms ± 2.65 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)

timeit json.dumps(d, sort_keys=True)
#259 ms ± 9.42 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)

如我们所见，格兰特·詹克斯的解决方案是目前为止最快的。