a = [1,2,3,4,5]
b = [1,3,5,6]
c = a and b
print c

实际输出:[1,3,5,6] 预期输出:[1,3,5]

如何在两个列表上实现布尔AND操作(列表交集)?


如果顺序不重要,你不需要担心重复,那么你可以使用set intersection:

>>> a = [1,2,3,4,5]
>>> b = [1,3,5,6]
>>> list(set(a) & set(b))
[1, 3, 5]

如果布尔与是指同时出现在两个列表中的项,例如交集,那么你应该看看Python的set和frozenset类型。


从较大的集合中创建一个集合:

_auxset = set(a)

然后,

c = [x for x in b if x in _auxset]

会做你想做的(保留b的顺序,而不是a的顺序——不一定能同时保留两者),而且动作要快。(使用a中的if x作为列表理解中的条件也可以工作,并且避免了构建_auxset的需要,但不幸的是,对于相当长的列表,它会慢得多)。

如果你想对结果进行排序,而不是保持列表的顺序,一个更整洁的方法可能是:

c = sorted(set(a).intersection(b))

如果你将两个列表中较大的一个转换为一个集合,你可以使用intersection()获得该集合与任何可迭代对象的交集:

a = [1,2,3,4,5]
b = [1,3,5,6]
set(a).intersection(b)

a = [1,2,3,4,5]
b = [1,3,5,6]
c = list(set(a).intersection(set(b)))

应该像做梦一样工作。并且,如果可以的话,使用集合而不是列表来避免所有这些类型更改!


对我来说,使用列表推导式是一个非常明显的方法。不确定性能如何,但至少能保持列表。

[x for x in a if x in b]

或者"所有在A中的x值,如果x值在B中"


下面是一些Python 2 / Python 3代码,用于为基于列表和基于集的方法生成时间信息,以查找两个列表的交集。

纯粹的列表理解算法是O(n²),因为在列表上进行搜索是一个线性搜索。基于集合的算法是O(n),因为集合搜索是O(1),集合创建是O(n)(将集合转换为列表也是O(n))。因此,对于足够大的n,基于集合的算法更快,但对于较小的n,创建集合的开销使它们比纯列表比较算法慢。

#!/usr/bin/env python

''' Time list- vs set-based list intersection
    See http://stackoverflow.com/q/3697432/4014959
    Written by PM 2Ring 2015.10.16
'''

from __future__ import print_function, division
from timeit import Timer

setup = 'from __main__ import a, b'
cmd_lista = '[u for u in a if u in b]'
cmd_listb = '[u for u in b if u in a]'

cmd_lcsa = 'sa=set(a);[u for u in b if u in sa]'

cmd_seta = 'list(set(a).intersection(b))'
cmd_setb = 'list(set(b).intersection(a))'

reps = 3
loops = 50000

def do_timing(heading, cmd, setup):
    t = Timer(cmd, setup)
    r = t.repeat(reps, loops)
    r.sort()
    print(heading, r)
    return r[0]

m = 10
nums = list(range(6 * m))

for n in range(1, m + 1):
    a = nums[:6*n:2]
    b = nums[:6*n:3]
    print('\nn =', n, len(a), len(b))
    #print('\nn = %d\n%s %d\n%s %d' % (n, a, len(a), b, len(b)))
    la = do_timing('lista', cmd_lista, setup) 
    lb = do_timing('listb', cmd_listb, setup) 
    lc = do_timing('lcsa ', cmd_lcsa, setup)
    sa = do_timing('seta ', cmd_seta, setup)
    sb = do_timing('setb ', cmd_setb, setup)
    print(la/sa, lb/sa, lc/sa, la/sb, lb/sb, lc/sb)

输出

n = 1 3 2
lista [0.082171916961669922, 0.082588911056518555, 0.0898590087890625]
listb [0.069530963897705078, 0.070394992828369141, 0.075379848480224609]
lcsa  [0.11858987808227539, 0.1188349723815918, 0.12825107574462891]
seta  [0.26900982856750488, 0.26902294158935547, 0.27298116683959961]
setb  [0.27218389511108398, 0.27459001541137695, 0.34307217597961426]
0.305460649521 0.258469975867 0.440838458259 0.301898526833 0.255455833892 0.435697630214

n = 2 6 4
lista [0.15915989875793457, 0.16000485420227051, 0.16551494598388672]
listb [0.13000702857971191, 0.13060092926025391, 0.13543915748596191]
lcsa  [0.18650484085083008, 0.18742108345031738, 0.19513416290283203]
seta  [0.33592700958251953, 0.34001994132995605, 0.34146714210510254]
setb  [0.29436492919921875, 0.2953648567199707, 0.30039691925048828]
0.473793098554 0.387009751735 0.555194537893 0.540689066428 0.441652573672 0.633583767462

n = 3 9 6
lista [0.27657914161682129, 0.28098297119140625, 0.28311991691589355]
listb [0.21585917472839355, 0.21679902076721191, 0.22272896766662598]
lcsa  [0.22559309005737305, 0.2271728515625, 0.2323150634765625]
seta  [0.36382699012756348, 0.36453008651733398, 0.36750602722167969]
setb  [0.34979605674743652, 0.35533690452575684, 0.36164689064025879]
0.760194128313 0.59330170819 0.62005595016 0.790686848184 0.61710008036 0.644927481902

n = 4 12 8
lista [0.39616990089416504, 0.39746403694152832, 0.41129183769226074]
listb [0.33485794067382812, 0.33914685249328613, 0.37850618362426758]
lcsa  [0.27405810356140137, 0.2745978832244873, 0.28249192237854004]
seta  [0.39211201667785645, 0.39234519004821777, 0.39317893981933594]
setb  [0.36988520622253418, 0.37011313438415527, 0.37571001052856445]
1.01034878821 0.85398540833 0.698928091731 1.07106176249 0.905302334456 0.740927452493

n = 5 15 10
lista [0.56792402267456055, 0.57422614097595215, 0.57740211486816406]
listb [0.47309303283691406, 0.47619009017944336, 0.47628307342529297]
lcsa  [0.32805585861206055, 0.32813096046447754, 0.3349759578704834]
seta  [0.40036201477050781, 0.40322518348693848, 0.40548801422119141]
setb  [0.39103078842163086, 0.39722800254821777, 0.43811702728271484]
1.41852623806 1.18166313332 0.819398061028 1.45237674242 1.20986133789 0.838951479847

n = 6 18 12
lista [0.77897095680236816, 0.78187918663024902, 0.78467702865600586]
listb [0.629547119140625, 0.63210701942443848, 0.63321495056152344]
lcsa  [0.36563992500305176, 0.36638498306274414, 0.38175487518310547]
seta  [0.46695613861083984, 0.46992206573486328, 0.47583580017089844]
setb  [0.47616910934448242, 0.47661614418029785, 0.4850609302520752]
1.66818870637 1.34819326075 0.783028414812 1.63591241329 1.32210827369 0.767878297495

n = 7 21 14
lista [0.9703209400177002, 0.9734041690826416, 1.0182771682739258]
listb [0.82394003868103027, 0.82625699043273926, 0.82796716690063477]
lcsa  [0.40975093841552734, 0.41210508346557617, 0.42286920547485352]
seta  [0.5086359977722168, 0.50968098640441895, 0.51014018058776855]
setb  [0.48688101768493652, 0.4879908561706543, 0.49204087257385254]
1.90769222837 1.61990115188 0.805587768483 1.99293236904 1.69228211566 0.841583309951

n = 8 24 16
lista [1.204819917678833, 1.2206029891967773, 1.258256196975708]
listb [1.014998197555542, 1.0206191539764404, 1.0343101024627686]
lcsa  [0.50966787338256836, 0.51018595695495605, 0.51319599151611328]
seta  [0.50310111045837402, 0.50556015968322754, 0.51335406303405762]
setb  [0.51472997665405273, 0.51948785781860352, 0.52113485336303711]
2.39478683834 2.01748351664 1.01305257092 2.34068341135 1.97190418975 0.990165516871

n = 9 27 18
lista [1.511646032333374, 1.5133969783782959, 1.5639569759368896]
listb [1.2461750507354736, 1.254518985748291, 1.2613379955291748]
lcsa  [0.5565330982208252, 0.56119203567504883, 0.56451296806335449]
seta  [0.5966339111328125, 0.60275578498840332, 0.64791703224182129]
setb  [0.54694414138793945, 0.5508568286895752, 0.55375313758850098]
2.53362406013 2.08867620074 0.932788243907 2.76380331728 2.27843203069 1.01753187594

n = 10 30 20
lista [1.7777848243713379, 2.1453688144683838, 2.4085969924926758]
listb [1.5070111751556396, 1.5202279090881348, 1.5779800415039062]
lcsa  [0.5954139232635498, 0.59703707695007324, 0.60746097564697266]
seta  [0.61563014984130859, 0.62125110626220703, 0.62354087829589844]
setb  [0.56723213195800781, 0.57257509231567383, 0.57460403442382812]
2.88774814689 2.44791645689 0.967161734066 3.13413984189 2.6567803378 1.04968299523

使用2GHz的单核机器和2GB的RAM在Debian风格的Linux上运行Python 2.6.6 (Firefox在后台运行)生成。

这些数字只是一个粗略的指南,因为各种算法的实际速度受到两个源列表中元素的比例的不同影响。


使用过滤器和lambda运算符可以实现函数式的方法。

list1 = [1,2,3,4,5,6]

list2 = [2,4,6,9,10]

>>> list(filter(lambda x:x in list1, list2))

[2, 4, 6]

编辑:它过滤掉了同时存在于list1和list中的x,集差异也可以使用:

>>> list(filter(lambda x:x not in list1, list2))
[9,10]

python3 filter返回一个过滤器对象,用list封装它返回输出列表。


这是一个示例,当您需要在结果中的每个元素出现的次数应该与它在两个数组中显示的次数相同。

def intersection(nums1, nums2):
    #example:
    #nums1 = [1,2,2,1]
    #nums2 = [2,2]
    #output = [2,2]
    #find first 2 and remove from target, continue iterating

    target, iterate = [nums1, nums2] if len(nums2) >= len(nums1) else [nums2, nums1] #iterate will look into target

    if len(target) == 0:
            return []

    i = 0
    store = []
    while i < len(iterate):

         element = iterate[i]

         if element in target:
               store.append(element)
               target.remove(element)

         i += 1


    return store

这可能是晚了,但我只是认为我应该分享的情况下,你需要手动做(显示工作-哈哈)或当你需要所有元素出现尽可能多的次数或当你也需要它是唯一的。

请注意,还为它编写了测试。



    from nose.tools import assert_equal

    '''
    Given two lists, print out the list of overlapping elements
    '''

    def overlap(l_a, l_b):
        '''
        compare the two lists l_a and l_b and return the overlapping
        elements (intersecting) between the two
        '''

        #edge case is when they are the same lists
        if l_a == l_b:
            return [] #no overlapping elements

        output = []

        if len(l_a) == len(l_b):
            for i in range(l_a): #same length so either one applies
                if l_a[i] in l_b:
                    output.append(l_a[i])

            #found all by now
            #return output #if repetition does not matter
            return list(set(output))

        else:
            #find the smallest and largest lists and go with that
            sm = l_a if len(l_a)  len(l_b) else l_b

            for i in range(len(sm)):
                if sm[i] in lg:
                    output.append(sm[i])

            #return output #if repetition does not matter
            return list(set(output))

    ## Test the Above Implementation

    a = [1, 1, 2, 3, 5, 8, 13, 21, 34, 55, 89]
    b = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13]
    exp = [1, 2, 3, 5, 8, 13]

    c = [4, 4, 5, 6]
    d = [5, 7, 4, 8 ,6 ] #assuming it is not ordered
    exp2 = [4, 5, 6]

    class TestOverlap(object):

        def test(self, sol):
            t = sol(a, b)
            assert_equal(t, exp)
            print('Comparing the two lists produces')
            print(t)

            t = sol(c, d)
            assert_equal(t, exp2)
            print('Comparing the two lists produces')
            print(t)

            print('All Tests Passed!!')

    t = TestOverlap()
    t.test(overlap)


你也可以使用计数器!它不会保留顺序,但会考虑副本:

>>> from collections import Counter
>>> a = [1,2,3,4,5]
>>> b = [1,3,5,6]
>>> d1, d2 = Counter(a), Counter(b)
>>> c = [n for n in d1.keys() & d2.keys() for _ in range(min(d1[n], d2[n]))]
>>> print(c)
[1,3,5]

这样可以得到两个列表的交集,也可以得到公共重复项。

>>> from collections import Counter
>>> a = Counter([1,2,3,4,5])
>>> b = Counter([1,3,5,6])
>>> a &= b
>>> list(a.elements())
[1, 3, 5]

这里的大多数解决方案都不考虑列表中元素的顺序,而是将列表视为集合。另一方面,如果希望找到两个列表中包含的一个最长子序列,则可以尝试以下代码。

def intersect(a, b):
    if a == [] or b == []: 
        return []
    inter_1 = intersect(a[1:], b)
    if a[0] in b:
        idx = b.index(a[0])
        inter_2 = [a[0]] + intersect(a[1:], b[idx+1:])        
        if len(inter_1) <= len(inter_2):
            return inter_2
    return inter_1

对于a=[1,2,3]和b=[3,1,4,2],返回[1,2]而不是[1,2,3]。注意,这样的子序列不是唯一的,因为[1],[2],[3]都是a=[1,2,3]和b=[3,2,1]的解。


你也可以使用numpy.intersect1d(ar1, ar2)。 它返回两个数组中唯一且已排序的值。


在这种情况下,你有一个列表的列表地图很方便:

>>> lists = [[1, 2, 3], [2, 3, 4], [2, 3, 5]]
>>> set(lists.pop()).intersection(*map(set, lists))
{2, 3}

适用于类似的迭代对象:

>>> lists = ['ash', 'nazg']
>>> set(lists.pop()).intersection(*map(set, lists))
{'a'}

如果列表是空的,Pop会爆炸,所以你可能想要在一个函数中进行包装:

def intersect_lists(lists):
    try:
        return set(lists.pop()).intersection(*map(set, lists))
    except IndexError: # pop from empty list
        return set()

当我们使用tuple时,我们想要交叉

a=([1,2,3,4,5,20], [8,3,9,5,1,4,20])

for i in range(len(a)):

    b=set(a[i-1]).intersection(a[i])
print(b)
{1, 3, 4, 5, 20}