或更简洁
if set(L) & set(M):
# there is an intersection
else:
# no intersection
如果您确实需要True
或False
bool(set(L) & set(M))
经过一段时间后,这似乎也是尝试的好选择
m_set=set(M)
any(x in m_set for x in L)
如果M或L中的项目不可散列,则必须使用效率较低的方法,例如
any(x in M for x in L)
以下是100个商品列表的一些时间安排。在没有交集的情况下,使用集合的速度要快得多,在有交集的情况下,使用集合的速度要慢一些。
M=range(100)
L=range(100,200)
timeit set(L) & set(M)
10000 loops, best of 3: 32.3 µs per loop
timeit any(x in M for x in L)
1000 loops, best of 3: 374 µs per loop
timeit m_set=frozenset(M);any(x in m_set for x in L)
10000 loops, best of 3: 31 µs per loop
L=range(50,150)
timeit set(L) & set(M)
10000 loops, best of 3: 18 µs per loop
timeit any(x in M for x in L)
100000 loops, best of 3: 4.88 µs per loop
timeit m_set=frozenset(M);any(x in m_set for x in L)
100000 loops, best of 3: 9.39 µs per loop
# Now for some random lists
import random
L=[random.randrange(200000) for x in xrange(1000)]
M=[random.randrange(200000) for x in xrange(1000)]
timeit set(L) & set(M)
1000 loops, best of 3: 420 µs per loop
timeit any(x in M for x in L)
10 loops, best of 3: 21.2 ms per loop
timeit m_set=set(M);any(x in m_set for x in L)
1000 loops, best of 3: 168 µs per loop
timeit m_set=frozenset(M);any(x in m_set for x in L)
1000 loops, best of 3: 371 µs per loop