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优化键列表的字典成员资格的性能

[英]Optimize the performance of dictionary membership for a list of Keys

 原文  2015-04-24 05:28:26  9   3    python/ performance/ list/ python-2.7/ dictionary

问题描述

I am trying to write a code which should return true if any element of list is present in a dictionary. 我正在尝试编写一个代码，如果列表中存在任何list元素，则该代码应该返回true。 Performance of this piece is really important. 这件作品的表现非常重要。 I know I can just loop over list and break if I find the first search hit. 我知道如果我找到第一个搜索命中，我可以循环遍历列表并中断。 Is there any faster or more Pythonic way for this than given below? 有没有更快或更多的Pythonic方式比下面给出的？ 

for x in someList:
     if x in someDict:
           return True
return False

EDIT: I am using Python 2.7 . 编辑：我使用的是Python 2.7 。 My first preference would be a faster method. 我的第一个偏好是更快的方法。

3 个解决方案

解决方案1
 38 已采纳  2015-04-24 05:30:16

Use of builtin any can have some performance edge over two loops 使用内置任何一个可以在两个循环上具有一些性能优势 

any(x in someDict for x in someList)

but you might need to measure your mileage. 但你可能需要衡量你的里程数。 If your list and dict remains pretty static and you have to perform the comparison multiple times, you may consider using set 如果您的列表和字典仍然非常静态，并且您必须多次执行比较，则可以考虑使用set 

someSet = set(someList) 
someDict.viewkeys() & someSet

Note Python 3.X, by default returns views rather than a sequence, so it would be straight forward when using Python 3.X 注意 Python 3.X默认返回视图而不是序列，所以在使用Python 3.X时它会很简单 

someSet = set(someList) 
someDict.keys() & someSet

In both the above cases you can wrap the result with a bool to get a boolean result 在上述两种情况下，您都可以使用bool包装结果以获得布尔结果 

bool(someDict.keys() & set(someSet ))

Heretic Note 异端音符

My curiosity got the better of me and I timed all the proposed solutions. 我的好奇心让我变得更好，我计划了所有提议的解决方案。 It seems that your original solution is better performance wise. 您的原始解决方案似乎更好的性能。 Here is the result 这是结果

Sample Randomly generated Input 样本随机生成的输入 

def test_data_gen():
    from random import sample
    for i in range(1,5):
        n = 10**i
        population = set(range(1,100000))
        some_list = sample(list(population),n)
        population.difference_update(some_list)
        some_dict = dict(zip(sample(population,n),
                             sample(range(1,100000),n)))
        yield "Population Size of {}".format(n), (some_list, some_dict), {}

The Test Engine 测试引擎

I rewrote the Test Part of the answer as it was messy and the answer was receiving quite a decent attention. 我重写了答案的测试部分，因为它很混乱，答案得到了相当不错的关注。 I created a timeit compare python module and moved it onto github 我创建了一个timeit compare python模块并将其移动到github上

The Test Result 测试结果 

Timeit repeated for 10 times
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
======================================
Test Run for Population Size of 10
======================================
|Rank  |FunctionName         |Result    |Description
+------+---------------------+----------+-----------------------------------------------
|     1|foo_nested           |0.000011  |Original OPs Code
+------+---------------------+----------+-----------------------------------------------
|     2|foo_ifilter_any      |0.000014  |any(ifilter(some_dict.__contains__, some_list))
+------+---------------------+----------+-----------------------------------------------
|     3|foo_ifilter_not_not  |0.000015  |not not next(ifilter(some_dict.__contains__...
+------+---------------------+----------+-----------------------------------------------
|     4|foo_imap_any         |0.000018  |any(imap(some_dict.__contains__, some_list))
+------+---------------------+----------+-----------------------------------------------
|     5|foo_any              |0.000019  |any(x in some_dict for x in some_list)
+------+---------------------+----------+-----------------------------------------------
|     6|foo_ifilter_next     |0.000022  |bool(next(ifilter(some_dict.__contains__...
+------+---------------------+----------+-----------------------------------------------
|     7|foo_set_ashwin       |0.000024  |not set(some_dct).isdisjoint(some_lst)
+------+---------------------+----------+-----------------------------------------------
|     8|foo_set              |0.000047  |some_dict.viewkeys() & set(some_list )
======================================
Test Run for Population Size of 100
======================================
|Rank  |FunctionName         |Result    |Description
+------+---------------------+----------+-----------------------------------------------
|     1|foo_ifilter_any      |0.000071  |any(ifilter(some_dict.__contains__, some_list))
+------+---------------------+----------+-----------------------------------------------
|     2|foo_nested           |0.000072  |Original OPs Code
+------+---------------------+----------+-----------------------------------------------
|     3|foo_ifilter_not_not  |0.000073  |not not next(ifilter(some_dict.__contains__...
+------+---------------------+----------+-----------------------------------------------
|     4|foo_ifilter_next     |0.000076  |bool(next(ifilter(some_dict.__contains__...
+------+---------------------+----------+-----------------------------------------------
|     5|foo_imap_any         |0.000082  |any(imap(some_dict.__contains__, some_list))
+------+---------------------+----------+-----------------------------------------------
|     6|foo_any              |0.000092  |any(x in some_dict for x in some_list)
+------+---------------------+----------+-----------------------------------------------
|     7|foo_set_ashwin       |0.000170  |not set(some_dct).isdisjoint(some_lst)
+------+---------------------+----------+-----------------------------------------------
|     8|foo_set              |0.000638  |some_dict.viewkeys() & set(some_list )
======================================
Test Run for Population Size of 1000
======================================
|Rank  |FunctionName         |Result    |Description
+------+---------------------+----------+-----------------------------------------------
|     1|foo_ifilter_not_not  |0.000746  |not not next(ifilter(some_dict.__contains__...
+------+---------------------+----------+-----------------------------------------------
|     2|foo_ifilter_any      |0.000746  |any(ifilter(some_dict.__contains__, some_list))
+------+---------------------+----------+-----------------------------------------------
|     3|foo_ifilter_next     |0.000752  |bool(next(ifilter(some_dict.__contains__...
+------+---------------------+----------+-----------------------------------------------
|     4|foo_nested           |0.000771  |Original OPs Code
+------+---------------------+----------+-----------------------------------------------
|     5|foo_set_ashwin       |0.000838  |not set(some_dct).isdisjoint(some_lst)
+------+---------------------+----------+-----------------------------------------------
|     6|foo_imap_any         |0.000842  |any(imap(some_dict.__contains__, some_list))
+------+---------------------+----------+-----------------------------------------------
|     7|foo_any              |0.000933  |any(x in some_dict for x in some_list)
+------+---------------------+----------+-----------------------------------------------
|     8|foo_set              |0.001702  |some_dict.viewkeys() & set(some_list )
======================================
Test Run for Population Size of 10000
======================================
|Rank  |FunctionName         |Result    |Description
+------+---------------------+----------+-----------------------------------------------
|     1|foo_nested           |0.007195  |Original OPs Code
+------+---------------------+----------+-----------------------------------------------
|     2|foo_ifilter_next     |0.007410  |bool(next(ifilter(some_dict.__contains__...
+------+---------------------+----------+-----------------------------------------------
|     3|foo_ifilter_any      |0.007491  |any(ifilter(some_dict.__contains__, some_list))
+------+---------------------+----------+-----------------------------------------------
|     4|foo_ifilter_not_not  |0.007671  |not not next(ifilter(some_dict.__contains__...
+------+---------------------+----------+-----------------------------------------------
|     5|foo_set_ashwin       |0.008385  |not set(some_dct).isdisjoint(some_lst)
+------+---------------------+----------+-----------------------------------------------
|     6|foo_imap_any         |0.011327  |any(imap(some_dict.__contains__, some_list))
+------+---------------------+----------+-----------------------------------------------
|     7|foo_any              |0.011533  |any(x in some_dict for x in some_list)
+------+---------------------+----------+-----------------------------------------------
|     8|foo_set              |0.018313  |some_dict.viewkeys() & set(some_list )
Timeit repeated for 100 times
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
======================================
Test Run for Population Size of 10
======================================
|Rank  |FunctionName         |Result    |Description
+------+---------------------+----------+-----------------------------------------------
|     1|foo_nested           |0.000098  |Original OPs Code
+------+---------------------+----------+-----------------------------------------------
|     2|foo_ifilter_any      |0.000124  |any(ifilter(some_dict.__contains__, some_list))
+------+---------------------+----------+-----------------------------------------------
|     3|foo_ifilter_not_not  |0.000131  |not not next(ifilter(some_dict.__contains__...
+------+---------------------+----------+-----------------------------------------------
|     4|foo_imap_any         |0.000142  |any(imap(some_dict.__contains__, some_list))
+------+---------------------+----------+-----------------------------------------------
|     5|foo_ifilter_next     |0.000151  |bool(next(ifilter(some_dict.__contains__...
+------+---------------------+----------+-----------------------------------------------
|     6|foo_any              |0.000158  |any(x in some_dict for x in some_list)
+------+---------------------+----------+-----------------------------------------------
|     7|foo_set_ashwin       |0.000186  |not set(some_dct).isdisjoint(some_lst)
+------+---------------------+----------+-----------------------------------------------
|     8|foo_set              |0.000496  |some_dict.viewkeys() & set(some_list )
======================================
Test Run for Population Size of 100
======================================
|Rank  |FunctionName         |Result    |Description
+------+---------------------+----------+-----------------------------------------------
|     1|foo_ifilter_any      |0.000661  |any(ifilter(some_dict.__contains__, some_list))
+------+---------------------+----------+-----------------------------------------------
|     2|foo_ifilter_not_not  |0.000677  |not not next(ifilter(some_dict.__contains__...
+------+---------------------+----------+-----------------------------------------------
|     3|foo_nested           |0.000683  |Original OPs Code
+------+---------------------+----------+-----------------------------------------------
|     4|foo_ifilter_next     |0.000684  |bool(next(ifilter(some_dict.__contains__...
+------+---------------------+----------+-----------------------------------------------
|     5|foo_imap_any         |0.000762  |any(imap(some_dict.__contains__, some_list))
+------+---------------------+----------+-----------------------------------------------
|     6|foo_any              |0.000854  |any(x in some_dict for x in some_list)
+------+---------------------+----------+-----------------------------------------------
|     7|foo_set_ashwin       |0.001291  |not set(some_dct).isdisjoint(some_lst)
+------+---------------------+----------+-----------------------------------------------
|     8|foo_set              |0.005018  |some_dict.viewkeys() & set(some_list )
======================================
Test Run for Population Size of 1000
======================================
|Rank  |FunctionName         |Result    |Description
+------+---------------------+----------+-----------------------------------------------
|     1|foo_ifilter_any      |0.007585  |any(ifilter(some_dict.__contains__, some_list))
+------+---------------------+----------+-----------------------------------------------
|     2|foo_nested           |0.007713  |Original OPs Code
+------+---------------------+----------+-----------------------------------------------
|     3|foo_set_ashwin       |0.008256  |not set(some_dct).isdisjoint(some_lst)
+------+---------------------+----------+-----------------------------------------------
|     4|foo_ifilter_not_not  |0.008526  |not not next(ifilter(some_dict.__contains__...
+------+---------------------+----------+-----------------------------------------------
|     5|foo_any              |0.009422  |any(x in some_dict for x in some_list)
+------+---------------------+----------+-----------------------------------------------
|     6|foo_ifilter_next     |0.010259  |bool(next(ifilter(some_dict.__contains__...
+------+---------------------+----------+-----------------------------------------------
|     7|foo_imap_any         |0.011414  |any(imap(some_dict.__contains__, some_list))
+------+---------------------+----------+-----------------------------------------------
|     8|foo_set              |0.019862  |some_dict.viewkeys() & set(some_list )
======================================
Test Run for Population Size of 10000
======================================
|Rank  |FunctionName         |Result    |Description
+------+---------------------+----------+-----------------------------------------------
|     1|foo_imap_any         |0.082221  |any(imap(some_dict.__contains__, some_list))
+------+---------------------+----------+-----------------------------------------------
|     2|foo_ifilter_any      |0.083573  |any(ifilter(some_dict.__contains__, some_list))
+------+---------------------+----------+-----------------------------------------------
|     3|foo_nested           |0.095736  |Original OPs Code
+------+---------------------+----------+-----------------------------------------------
|     4|foo_set_ashwin       |0.103427  |not set(some_dct).isdisjoint(some_lst)
+------+---------------------+----------+-----------------------------------------------
|     5|foo_ifilter_next     |0.104589  |bool(next(ifilter(some_dict.__contains__...
+------+---------------------+----------+-----------------------------------------------
|     6|foo_ifilter_not_not  |0.117974  |not not next(ifilter(some_dict.__contains__...
+------+---------------------+----------+-----------------------------------------------
|     7|foo_any              |0.127739  |any(x in some_dict for x in some_list)
+------+---------------------+----------+-----------------------------------------------
|     8|foo_set              |0.208228  |some_dict.viewkeys() & set(some_list )
Timeit repeated for 1000 times
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
======================================
Test Run for Population Size of 10
======================================
|Rank  |FunctionName         |Result    |Description
+------+---------------------+----------+-----------------------------------------------
|     1|foo_nested           |0.000953  |Original OPs Code
+------+---------------------+----------+-----------------------------------------------
|     2|foo_ifilter_any      |0.001134  |any(ifilter(some_dict.__contains__, some_list))
+------+---------------------+----------+-----------------------------------------------
|     3|foo_ifilter_not_not  |0.001213  |not not next(ifilter(some_dict.__contains__...
+------+---------------------+----------+-----------------------------------------------
|     4|foo_ifilter_next     |0.001340  |bool(next(ifilter(some_dict.__contains__...
+------+---------------------+----------+-----------------------------------------------
|     5|foo_imap_any         |0.001407  |any(imap(some_dict.__contains__, some_list))
+------+---------------------+----------+-----------------------------------------------
|     6|foo_any              |0.001535  |any(x in some_dict for x in some_list)
+------+---------------------+----------+-----------------------------------------------
|     7|foo_set_ashwin       |0.002252  |not set(some_dct).isdisjoint(some_lst)
+------+---------------------+----------+-----------------------------------------------
|     8|foo_set              |0.004701  |some_dict.viewkeys() & set(some_list )
======================================
Test Run for Population Size of 100
======================================
|Rank  |FunctionName         |Result    |Description
+------+---------------------+----------+-----------------------------------------------
|     1|foo_ifilter_any      |0.006209  |any(ifilter(some_dict.__contains__, some_list))
+------+---------------------+----------+-----------------------------------------------
|     2|foo_ifilter_next     |0.006411  |bool(next(ifilter(some_dict.__contains__...
+------+---------------------+----------+-----------------------------------------------
|     3|foo_ifilter_not_not  |0.006657  |not not next(ifilter(some_dict.__contains__...
+------+---------------------+----------+-----------------------------------------------
|     4|foo_nested           |0.006727  |Original OPs Code
+------+---------------------+----------+-----------------------------------------------
|     5|foo_imap_any         |0.007562  |any(imap(some_dict.__contains__, some_list))
+------+---------------------+----------+-----------------------------------------------
|     6|foo_any              |0.008262  |any(x in some_dict for x in some_list)
+------+---------------------+----------+-----------------------------------------------
|     7|foo_set_ashwin       |0.012260  |not set(some_dct).isdisjoint(some_lst)
+------+---------------------+----------+-----------------------------------------------
|     8|foo_set              |0.046773  |some_dict.viewkeys() & set(some_list )
======================================
Test Run for Population Size of 1000
======================================
|Rank  |FunctionName         |Result    |Description
+------+---------------------+----------+-----------------------------------------------
|     1|foo_ifilter_not_not  |0.071888  |not not next(ifilter(some_dict.__contains__...
+------+---------------------+----------+-----------------------------------------------
|     2|foo_ifilter_next     |0.072150  |bool(next(ifilter(some_dict.__contains__...
+------+---------------------+----------+-----------------------------------------------
|     3|foo_nested           |0.073382  |Original OPs Code
+------+---------------------+----------+-----------------------------------------------
|     4|foo_ifilter_any      |0.075698  |any(ifilter(some_dict.__contains__, some_list))
+------+---------------------+----------+-----------------------------------------------
|     5|foo_set_ashwin       |0.077367  |not set(some_dct).isdisjoint(some_lst)
+------+---------------------+----------+-----------------------------------------------
|     6|foo_imap_any         |0.090623  |any(imap(some_dict.__contains__, some_list))
+------+---------------------+----------+-----------------------------------------------
|     7|foo_any              |0.093301  |any(x in some_dict for x in some_list)
+------+---------------------+----------+-----------------------------------------------
|     8|foo_set              |0.177051  |some_dict.viewkeys() & set(some_list )
======================================
Test Run for Population Size of 10000
======================================
|Rank  |FunctionName         |Result    |Description
+------+---------------------+----------+-----------------------------------------------
|     1|foo_nested           |0.701317  |Original OPs Code
+------+---------------------+----------+-----------------------------------------------
|     2|foo_ifilter_next     |0.706156  |bool(next(ifilter(some_dict.__contains__...
+------+---------------------+----------+-----------------------------------------------
|     3|foo_ifilter_any      |0.723368  |any(ifilter(some_dict.__contains__, some_list))
+------+---------------------+----------+-----------------------------------------------
|     4|foo_ifilter_not_not  |0.746650  |not not next(ifilter(some_dict.__contains__...
+------+---------------------+----------+-----------------------------------------------
|     5|foo_set_ashwin       |0.776704  |not set(some_dct).isdisjoint(some_lst)
+------+---------------------+----------+-----------------------------------------------
|     6|foo_imap_any         |0.832117  |any(imap(some_dict.__contains__, some_list))
+------+---------------------+----------+-----------------------------------------------
|     7|foo_any              |0.881777  |any(x in some_dict for x in some_list)
+------+---------------------+----------+-----------------------------------------------
|     8|foo_set              |1.665962  |some_dict.viewkeys() & set(some_list )
Timeit repeated for 10000 times
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
======================================
Test Run for Population Size of 10
======================================
|Rank  |FunctionName         |Result    |Description
+------+---------------------+----------+-----------------------------------------------
|     1|foo_nested           |0.010581  |Original OPs Code
+------+---------------------+----------+-----------------------------------------------
|     2|foo_ifilter_any      |0.013512  |any(ifilter(some_dict.__contains__, some_list))
+------+---------------------+----------+-----------------------------------------------
|     3|foo_imap_any         |0.015321  |any(imap(some_dict.__contains__, some_list))
+------+---------------------+----------+-----------------------------------------------
|     4|foo_ifilter_not_not  |0.017680  |not not next(ifilter(some_dict.__contains__...
+------+---------------------+----------+-----------------------------------------------
|     5|foo_ifilter_next     |0.019334  |bool(next(ifilter(some_dict.__contains__...
+------+---------------------+----------+-----------------------------------------------
|     6|foo_any              |0.026274  |any(x in some_dict for x in some_list)
+------+---------------------+----------+-----------------------------------------------
|     7|foo_set_ashwin       |0.030881  |not set(some_dct).isdisjoint(some_lst)
+------+---------------------+----------+-----------------------------------------------
|     8|foo_set              |0.053605  |some_dict.viewkeys() & set(some_list )
======================================
Test Run for Population Size of 100
======================================
|Rank  |FunctionName         |Result    |Description
+------+---------------------+----------+-----------------------------------------------
|     1|foo_nested           |0.070194  |Original OPs Code
+------+---------------------+----------+-----------------------------------------------
|     2|foo_ifilter_not_not  |0.078524  |not not next(ifilter(some_dict.__contains__...
+------+---------------------+----------+-----------------------------------------------
|     3|foo_ifilter_any      |0.079499  |any(ifilter(some_dict.__contains__, some_list))
+------+---------------------+----------+-----------------------------------------------
|     4|foo_imap_any         |0.087349  |any(imap(some_dict.__contains__, some_list))
+------+---------------------+----------+-----------------------------------------------
|     5|foo_ifilter_next     |0.093970  |bool(next(ifilter(some_dict.__contains__...
+------+---------------------+----------+-----------------------------------------------
|     6|foo_any              |0.097948  |any(x in some_dict for x in some_list)
+------+---------------------+----------+-----------------------------------------------
|     7|foo_set_ashwin       |0.130725  |not set(some_dct).isdisjoint(some_lst)
+------+---------------------+----------+-----------------------------------------------
|     8|foo_set              |0.480841  |some_dict.viewkeys() & set(some_list )
======================================
Test Run for Population Size of 1000
======================================
|Rank  |FunctionName         |Result    |Description
+------+---------------------+----------+-----------------------------------------------
|     1|foo_ifilter_any      |0.754491  |any(ifilter(some_dict.__contains__, some_list))
+------+---------------------+----------+-----------------------------------------------
|     2|foo_ifilter_not_not  |0.756253  |not not next(ifilter(some_dict.__contains__...
+------+---------------------+----------+-----------------------------------------------
|     3|foo_ifilter_next     |0.771382  |bool(next(ifilter(some_dict.__contains__...
+------+---------------------+----------+-----------------------------------------------
|     4|foo_nested           |0.787152  |Original OPs Code
+------+---------------------+----------+-----------------------------------------------
|     5|foo_set_ashwin       |0.818520  |not set(some_dct).isdisjoint(some_lst)
+------+---------------------+----------+-----------------------------------------------
|     6|foo_imap_any         |0.902947  |any(imap(some_dict.__contains__, some_list))
+------+---------------------+----------+-----------------------------------------------
|     7|foo_any              |1.001810  |any(x in some_dict for x in some_list)
+------+---------------------+----------+-----------------------------------------------
|     8|foo_set              |2.012781  |some_dict.viewkeys() & set(some_list )
=======================================
Test Run for Population Size of 10000
=======================================
|Rank  |FunctionName         |Result     |Description
+------+---------------------+-----------+-----------------------------------------------
|     1|foo_imap_any         |10.071469  |any(imap(some_dict.__contains__, some_list))
+------+---------------------+-----------+-----------------------------------------------
|     2|foo_any              |11.127034  |any(x in some_dict for x in some_list)
+------+---------------------+-----------+-----------------------------------------------
|     3|foo_set              |18.881414  |some_dict.viewkeys() & set(some_list )
+------+---------------------+-----------+-----------------------------------------------
|     4|foo_nested           |8.731133   |Original OPs Code
+------+---------------------+-----------+-----------------------------------------------
|     5|foo_ifilter_not_not  |9.019190   |not not next(ifilter(some_dict.__contains__...
+------+---------------------+-----------+-----------------------------------------------
|     6|foo_ifilter_next     |9.189966   |bool(next(ifilter(some_dict.__contains__...
+------+---------------------+-----------+-----------------------------------------------
|     7|foo_set_ashwin       |9.363886   |not set(some_dct).isdisjoint(some_lst)
+------+---------------------+-----------+-----------------------------------------------
|     8|foo_ifilter_any      |9.442759   |any(ifilter(some_dict.__contains__, some_list))

And a Graphical Comparison from the above referred module 以及上述模块的图形比较

在此输入图像描述在此输入图像描述在此输入图像描述在此输入图像描述

Conclusion 结论

Premature optimization is evil. 过早优化是邪恶的。 It is evident that none of the solutions have optimal performance when the test domain varies. 很明显，当测试域变化时，没有一种解决方案具有最佳性能。 Depending on population size and frequency of iteration, performance of solutions varies considerably. 根据人口规模和迭代频率，解决方案的性能差异很大。 The result again speaks out about the fact that in Python, one should ensure that the code should be readable rather than ensuring that the code is either nifty or optimized for performance for certain cases, but then it may not be scalable. 结果再次说明了这样一个事实，即在Python中，应该确保代码应该是可读的，而不是确保代码对于某些情况的性能是好的或优化的，但是它可能不是可伸缩的。

Note There were some doubts on why not using ifilter performs better than the rest 注意有一些疑问为什么不使用ifilter比其他更好

"In Abhit's answer, he timed the different approaches and found that ifilter/next was not the fastest; any idea why this would be the case? " “在Abhit的回答中，他定时采用不同的方法，发现ifilter / next不是最快的;任何想法为什么会出现这种情况？”

It is a known fact that in python, there is an overhead when calling C functions, and if the population size is low but the frequency of iteration is high, the accumulation of C function call overhead would slowly show up. 众所周知，在python中，调用C函数时会产生开销，如果填充大小但迭代频率很高，则C函数调用开销的累积会慢慢显现。 As can be seen in the graphs, where population size is low but iteration is high, using ifilter, performance deviates considerably. 从图中可以看出，在人口规模较小但迭代率较高的情况下，使用ifilter，性能会有很大差异。

解决方案2
 10  2015-04-24 05:39:01

The cleanest and fastest way is to use any() and itertools.ifilter() : 最干净，最快捷的方法是使用any（）和itertools.ifilter（） ： 

any(ifilter(someDict.__contains__, someList))

This code uses: 此代码使用：

  • a bound method, someDict.__contains__ as the predicate 一个绑定方法， someDict.__contains__作为谓词
  • the ifilter() itertool lazily scans for a true result at C speed ifilter（） itertool懒惰地以C速度扫描真实结果
  • the any() built-in drives the filter to find a single matching occurrence or to return False if the iterator is exhausted. any（）内置驱动过滤器以查找单个匹配事件，或者如果迭代器用尽则返回False 。

You could also use itertools.imap() instead of ifilter() . 您也可以使用itertools.imap（）而不是ifilter（） 。

解决方案3
 4  2015-04-24 05:30:09

s = set(someList)
return bool(s.intersection(someDict.keys()))

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