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计算 Python 列表中真布尔值的数量

[英]Counting the number of True Booleans in a Python List

I have a list of Booleans:我有一个布尔列表:

[True, True, False, False, False, True]

and I am looking for a way to count the number of True in the list (so in the example above, I want the return to be 3 .) I have found examples of looking for the number of occurrences of specific elements, but is there a more efficient way to do it since I'm working with Booleans?我正在寻找一种方法来计算列表中True的数量(因此在上面的示例中,我希望返回值为3 。)我找到了寻找特定元素出现次数的示例,但是有因为我正在使用布尔值,所以有更有效的方法吗? I'm thinking of something analogous to all or any .我正在考虑类似于allany的东西。

True is equal to 1 . True等于1

>>> sum([True, True, False, False, False, True])
3

list has a count method: list有一个count方法:

>>> [True,True,False].count(True)
2

This is actually more efficient than sum , as well as being more explicit about the intent, so there's no reason to use sum :这实际上比sum更有效,并且对意图更明确,因此没有理由使用sum

In [1]: import random

In [2]: x = [random.choice([True, False]) for i in range(100)]

In [3]: %timeit x.count(True)
970 ns ± 41.1 ns per loop (mean ± std. dev. of 7 runs, 1000000 loops each)

In [4]: %timeit sum(x)
1.72 µs ± 161 ns per loop (mean ± std. dev. of 7 runs, 100000 loops each)

If you are only concerned with the constant True , a simple sum is fine.如果您只关心常量True ,那么简单的sum就可以了。 However, keep in mind that in Python other values evaluate as True as well.但是,请记住,在 Python 中,其他值也评估为True A more robust solution would be to use the bool builtin:更强大的解决方案是使用bool内置:

>>> l = [1, 2, True, False]
>>> sum(bool(x) for x in l)
3

UPDATE: Here's another similarly robust solution that has the advantage of being more transparent:更新:这是另一个同样强大的解决方案,其优点是更加透明:

>>> sum(1 for x in l if x)
3

PS Python trivia: True could be true without being 1. Warning: do not try this at work! PS Python 琐事: True可能为真而不是 1。警告:不要在工作中尝试这个!

>>> True = 2
>>> if True: print('true')
... 
true
>>> l = [True, True, False, True]
>>> sum(l)
6
>>> sum(bool(x) for x in l)
3
>>> sum(1 for x in l if x)
3

Much more evil:更邪恶:

True = False

You can use sum() :您可以使用sum()

>>> sum([True, True, False, False, False, True])
3

After reading all the answers and comments on this question, I thought to do a small experiment.看完这个问题的所有答案和评论后,我想做一个小实验。

I generated 50,000 random booleans and called sum and count on them.我生成了 50,000 个随机布尔值并调用sum并对它们进行count

Here are my results:这是我的结果:

>>> a = [bool(random.getrandbits(1)) for x in range(50000)]
>>> len(a)
50000
>>> a.count(False)
24884
>>> a.count(True)
25116
>>> def count_it(a):
...   curr = time.time()
...   counting = a.count(True)
...   print("Count it = " + str(time.time() - curr))
...   return counting
... 
>>> def sum_it(a):
...   curr = time.time()
...   counting = sum(a)
...   print("Sum it = " + str(time.time() - curr))
...   return counting
... 
>>> count_it(a)
Count it = 0.00121307373046875
25015
>>> sum_it(a)
Sum it = 0.004102230072021484
25015

Just to be sure, I repeated it several more times:可以肯定的是,我又重复了几次:

>>> count_it(a)
Count it = 0.0013530254364013672
25015
>>> count_it(a)
Count it = 0.0014507770538330078
25015
>>> count_it(a)
Count it = 0.0013344287872314453
25015
>>> sum_it(a)
Sum it = 0.003480195999145508
25015
>>> sum_it(a)
Sum it = 0.0035257339477539062
25015
>>> sum_it(a)
Sum it = 0.003350496292114258
25015
>>> sum_it(a)
Sum it = 0.003744363784790039
25015

And as you can see, count is 3 times faster than sum .正如您所看到的, countsum快 3 倍。 So I would suggest to use count as I did in count_it .所以我建议像我在count_it所做的那样使用count

Python version: 3.6.7 Python版本:3.6.7
CPU cores: 4 CPU核心:4
RAM size: 16 GB内存大小:16 GB
OS: Ubuntu 18.04.1 LTS操作系统:Ubuntu 18.04.1 LTS

Just for completeness' sake ( sum is usually preferable), I wanted to mention that we can also use filter to get the truthy values.为了完整起见( sum通常更可取),我想提到我们也可以使用filter来获取真实值。 In the usual case, filter accepts a function as the first argument, but if you pass it None , it will filter for all "truthy" values.在通常情况下, filter接受一个函数作为第一个参数,但如果你传递它None ,它将过滤所有“真实”值。 This feature is somewhat surprising, but is well documented and works in both Python 2 and 3.这个特性有点令人惊讶,但有很好的文档记录并且可以在 Python 2 和 3 中使用。

The difference between the versions, is that in Python 2 filter returns a list, so we can use len :版本之间的区别在于,在 Python 2 中filter返回一个列表,因此我们可以使用len

>>> bool_list = [True, True, False, False, False, True]
>>> filter(None, bool_list)
[True, True, True]
>>> len(filter(None, bool_list))
3

But in Python 3, filter returns an iterator, so we can't use len , and if we want to avoid using sum (for any reason) we need to resort to converting the iterator to a list (which makes this much less pretty):但是在 Python 3 中, filter返回一个迭代器,所以我们不能使用len ,如果我们想避免使用sum (出于任何原因),我们需要将迭代器转换为一个列表(这使得它不那么漂亮) :

>>> bool_list = [True, True, False, False, False, True]
>>> filter(None, bool_list)
<builtins.filter at 0x7f64feba5710>
>>> list(filter(None, bool_list))
[True, True, True]
>>> len(list(filter(None, bool_list)))
3

It is safer to run through bool first.首先通过bool运行更安全。 This is easily done:这很容易做到:

>>> sum(map(bool,[True, True, False, False, False, True]))
3

Then you will catch everything that Python considers True or False into the appropriate bucket:然后,您将把 Python 认为是 True 或 False 的所有内容都捕获到适当的存储桶中:

>>> allTrue=[True, not False, True+1,'0', ' ', 1, [0], {0:0}, set([0])]
>>> list(map(bool,allTrue))
[True, True, True, True, True, True, True, True, True]

If you prefer, you can use a comprehension:如果您愿意,可以使用理解式:

>>> allFalse=['',[],{},False,0,set(),(), not True, True-1]
>>> [bool(i) for i in allFalse]
[False, False, False, False, False, False, False, False, False]

I prefer len([b for b in boollist if b is True]) (or the generator-expression equivalent), as it's quite self-explanatory.我更喜欢len([b for b in boollist if b is True]) (或等效的生成器表达式),因为它是不言自明的。 Less 'magical' than the answer proposed by Ignacio Vazquez-Abrams.比 Ignacio Vazquez-Abrams 提出的答案更“神奇”。

Alternatively, you can do this, which still assumes that bool is convertable to int, but makes no assumptions about the value of True: ntrue = sum(boollist) / int(True)或者,您可以这样做,它仍然假设 bool 可转换为 int,但不对 True 的值做任何假设: ntrue = sum(boollist) / int(True)

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