我想取两个列表,并找出出现在这两个列表中的值。
a = [1, 2, 3, 4, 5]
b = [9, 8, 7, 6, 5]
returnMatches(a, b)
例如,将返回[5]。
我想取两个列表,并找出出现在这两个列表中的值。
a = [1, 2, 3, 4, 5]
b = [9, 8, 7, 6, 5]
returnMatches(a, b)
例如,将返回[5]。
当前回答
>>> s = ['a','b','c']
>>> f = ['a','b','d','c']
>>> ss= set(s)
>>> fs =set(f)
>>> print ss.intersection(fs)
**set(['a', 'c', 'b'])**
>>> print ss.union(fs)
**set(['a', 'c', 'b', 'd'])**
>>> print ss.union(fs) - ss.intersection(fs)
**set(['d'])**
其他回答
可以使用itertools。产品。
>>> common_elements=[]
>>> for i in list(itertools.product(a,b)):
... if i[0] == i[1]:
... common_elements.append(i[0])
快捷方式:
list(set(a).intersection(set(b)))
你要复印一份吗?如果不是,也许你应该使用集合:
>>> set([1, 2, 3, 4, 5]).intersection(set([9, 8, 7, 6, 5]))
set([5])
you can | for set union and & for set intersection.
for example:
set1={1,2,3}
set2={3,4,5}
print(set1&set2)
output=3
set1={1,2,3}
set2={3,4,5}
print(set1|set2)
output=1,2,3,4,5
curly braces in the answer.
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。