Question

让＆＃39;假设字典A中有一个键，而字典B中有10亿个键

在算法上，查找操作是O（1）

但是，根据字典大小查找不同的实际时间（程序执行时间）？

onekey_stime = time.time()
print one_key_dict.get('firstkey')
onekey_dur = time.time() - onekey_stime

manykeys_stime = time.time()
print manykeys_dict.get('randomkey')
manykeys_dur = time.time() - manykey_stime

我会看到onekey_dur和manykeys_dur之间的时差吗？

Answer 1

在一个小型和大型字典的测试中非常相同：

In [31]: random_key = lambda: ''.join(np.random.choice(list(string.ascii_letters), 20))

In [32]: few_keys = {random_key(): np.random.random() for _ in xrange(100)}

In [33]: many_keys = {random_key(): np.random.random() for _ in xrange(1000000)}

In [34]: few_lookups = np.random.choice(few_keys.keys(), 50)

In [35]: many_lookups = np.random.choice(many_keys.keys(), 50)

In [36]: %timeit [few_keys[k] for k in few_lookups]
100000 loops, best of 3: 6.25 µs per loop

In [37]: %timeit [many_keys[k] for k in many_lookups]
100000 loops, best of 3: 7.01 µs per loop

编辑：对你来说，@ ShadowRanger - 错过的查找也非常接近：

In [38]: %timeit [few_keys.get(k) for k in many_lookups]
100000 loops, best of 3: 7.99 µs per loop

In [39]: %timeit [many_keys.get(k) for k in few_lookups]
100000 loops, best of 3: 8.78 µs per loop

Python字典：大小影响时间？

1 个答案: