你可以使用python-benedict，它是dict的子类。

安装:pip install python-benedict

from benedict import benedict

dict_you_want = benedict(your_dict).subset(keys=['firstname', 'lastname', 'email'])

它在GitHub上开源:https://github.com/fabiocaccamo/python-benedict

声明:我是这个库的作者。

我们也可以通过稍微更优雅的字典理解来实现这一点:

my_dict = {"a":1,"b":2,"c":3,"d":4}

filtdict = {k: v for k, v in my_dict.items() if k.startswith('a')}
print(filtdict)

给定你的原始字典orig和你感兴趣的键的条目集:

filtered = dict(zip(keys, [orig[k] for k in keys]))

这并不像delnan的答案那么好，但应该适用于每个感兴趣的Python版本。然而，它对原始字典中存在的每个键元素都是脆弱的。

代码1:

dict = { key: key * 10 for key in range(0, 100) }
d1 = {}
for key, value in dict.items():
    if key % 2 == 0:
        d1[key] = value

代码2:

dict = { key: key * 10 for key in range(0, 100) }
d2 = {key: value for key, value in dict.items() if key % 2 == 0}

代码3:

dict = { key: key * 10 for key in range(0, 100) }
d3 = { key: dict[key] for key in dict.keys() if key % 2 == 0}

所有代码段的性能都用timeit度量，使用number=1000，并为每段代码收集1000次。

对于python 3.6，三种过滤字典键的方式的性能几乎相同。对于python 2.7，代码3略快一些。

另一个选择:

content = dict(k1='foo', k2='nope', k3='bar')
selection = ['k1', 'k3']
filtered = filter(lambda i: i[0] in selection, content.items())

但你得到的是一个列表(Python 2)或一个迭代器(Python 3)，由filter()返回，而不是字典。

根据问题的标题，人们会期望在适当的地方过滤字典-几个答案建议了这样做的方法-仍然不明显的一个明显的方法是什么-我添加了一些时间:

import random
import timeit
import collections

repeat = 3
numbers = 10000

setup = ''
def timer(statement, msg='', _setup=None):
    print(msg, min(
        timeit.Timer(statement, setup=_setup or setup).repeat(
            repeat, numbers)))

timer('pass', 'Empty statement')

dsize = 1000
d = dict.fromkeys(range(dsize))
keep_keys = set(random.sample(range(dsize), 500))
drop_keys = set(random.sample(range(dsize), 500))

def _time_filter_dict():
    """filter a dict"""
    global setup
    setup = r"""from __main__ import dsize, collections, drop_keys, \
keep_keys, random"""
    timer('d = dict.fromkeys(range(dsize));'
          'collections.deque((d.pop(k) for k in drop_keys), maxlen=0)',
          "pop inplace - exhaust iterator")
    timer('d = dict.fromkeys(range(dsize));'
          'drop_keys = [k for k in d if k not in keep_keys];'
          'collections.deque('
              '(d.pop(k) for k in list(d) if k not in keep_keys), maxlen=0)',
          "pop inplace - exhaust iterator (drop_keys)")
    timer('d = dict.fromkeys(range(dsize));'
          'list(d.pop(k) for k in drop_keys)',
          "pop inplace - create list")
    timer('d = dict.fromkeys(range(dsize));'
          'drop_keys = [k for k in d if k not in keep_keys];'
          'list(d.pop(k) for k in drop_keys)',
          "pop inplace - create list (drop_keys)")
    timer('d = dict.fromkeys(range(dsize))\n'
          'for k in drop_keys: del d[k]', "del inplace")
    timer('d = dict.fromkeys(range(dsize));'
          'drop_keys = [k for k in d if k not in keep_keys]\n'
          'for k in drop_keys: del d[k]', "del inplace (drop_keys)")
    timer("""d = dict.fromkeys(range(dsize))
{k:v for k,v in d.items() if k in keep_keys}""", "copy dict comprehension")
    timer("""keep_keys=random.sample(range(dsize), 5)
d = dict.fromkeys(range(dsize))
{k:v for k,v in d.items() if k in keep_keys}""",
          "copy dict comprehension - small keep_keys")

if __name__ == '__main__':
    _time_filter_dict()

结果:

Empty statement 8.375600000000427e-05
pop inplace - exhaust iterator 1.046749841
pop inplace - exhaust iterator (drop_keys) 1.830537424
pop inplace - create list 1.1531293939999987
pop inplace - create list (drop_keys) 1.4512304149999995
del inplace 0.8008298079999996
del inplace (drop_keys) 1.1573763689999979
copy dict comprehension 1.1982901489999982
copy dict comprehension - small keep_keys 1.4407784069999998

因此，如果我们想要在适当的地方更新，似乎del是赢家-字典理解解决方案取决于正在创建的字典的大小，当然，删除一半的键已经太慢了-所以避免创建一个新的字典，如果你可以在适当的地方过滤。

编辑来解决@mpen的评论-我从keep_keys中计算了drop key(假设我们没有drop key) -我假设keep_keys/drop_keys是这个迭代的集合，或者会花很长时间。有了这些假设，del仍然更快——但要确定的是:如果你有一个(set, list, tuple)的下拉键，使用del