另一种更实用的方法是检查列表1 (lst1)和列表2 (lst2)是否相等，其中对象的深度为1，并保持顺序:

all(i == j for i, j in zip(lst1, lst2))   

我更喜欢基于集合的答案，但这里有一个不管怎样都有用的答案

[x for x in a if x in b]

一个快速的性能测试显示卢茨的解决方案是最好的:

import time

def speed_test(func):
    def wrapper(*args, **kwargs):
        t1 = time.time()
        for x in xrange(5000):
            results = func(*args, **kwargs)
        t2 = time.time()
        print '%s took %0.3f ms' % (func.func_name, (t2-t1)*1000.0)
        return results
    return wrapper

@speed_test
def compare_bitwise(x, y):
    set_x = frozenset(x)
    set_y = frozenset(y)
    return set_x & set_y

@speed_test
def compare_listcomp(x, y):
    return [i for i, j in zip(x, y) if i == j]

@speed_test
def compare_intersect(x, y):
    return frozenset(x).intersection(y)

# Comparing short lists
a = [1, 2, 3, 4, 5]
b = [9, 8, 7, 6, 5]
compare_bitwise(a, b)
compare_listcomp(a, b)
compare_intersect(a, b)

# Comparing longer lists
import random
a = random.sample(xrange(100000), 10000)
b = random.sample(xrange(100000), 10000)
compare_bitwise(a, b)
compare_listcomp(a, b)
compare_intersect(a, b)

这是我的机器上的结果:

# Short list:
compare_bitwise took 10.145 ms
compare_listcomp took 11.157 ms
compare_intersect took 7.461 ms

# Long list:
compare_bitwise took 11203.709 ms
compare_listcomp took 17361.736 ms
compare_intersect took 6833.768 ms

显然，任何人工性能测试都应该持保留态度，但由于set().intersection()答案至少与其他解决方案一样快，而且也是最易读的，因此它应该是这个常见问题的标准解决方案。

a = [1, 2, 3, 4, 5]
b = [9, 8, 7, 6, 5]

lista =set(a)
listb =set(b)   
print listb.intersection(lista)   
returnMatches = set(['5']) #output 

print " ".join(str(return) for return in returnMatches ) # remove the set()   

 5        #final output 

我使用了下面的方法，它对我很有效:

group1 = [1, 2, 3, 4, 5]
group2 = [9, 8, 7, 6, 5]

for k in group1:
    for v in group2:
        if k == v:
            print(k)

在你的例子中，这会输出5。可能不是很好的性能。

快捷方式:

list(set(a).intersection(set(b)))