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一个快速而不科学的基准:import time
def make_string(c, n):
return c * n
def make_tuple(el, n):
return (el,) * n
def hashtest(gen, n):
# First compute how long generation alone takes
gen_time = time.perf_counter()
for x in range(n):
gen()
gen_time = time.perf_counter() - gen_time
# Then compute how long hashing and generation takes
hash_and_gen_time = time.perf_counter()
for x in range(n):
hash(gen())
hash_and_gen_time = time.perf_counter() - hash_and_gen_time
# Return the two
return (hash_and_gen_time, gen_time)
for gen in (make_string, make_tuple):
for obj_length in (10000, 20000, 40000):
t = f"{gen.__name__} x {obj_length}"
# Using `b'hello'.decode()` here to avoid any cached hash shenanigans
hash_and_gen_time, gen_time = hashtest(
lambda: gen(b"hello".decode(), obj_length), 10000
)
hash_time = hash_and_gen_time - gen_time
print(t, hash_time, obj_length / hash_time)
输出make_string x 10000 0.23490356100000004 42570.66158311665
make_string x 20000 0.47143921999999994 42423.284172241765
make_string x 40000 0.942087403 42458.905482254915
make_tuple x 10000 0.45578034300000025 21940.393335480014
make_tuple x 20000 0.9328520900000008 21439.62608263008
make_tuple x 40000 1.8562772150000004 21548.505620158674
基本上说哈希序列是字符串或元组,是线性时间,但是哈希字符串比散列组快得多。
import time
s = ('x' * 500_000_000)
t0 = time.perf_counter()
a = hash(s)
t1 = time.perf_counter()
print(t1 - t0)
t0 = time.perf_counter()
b = hash(s)
t2 = time.perf_counter()
assert a == b
print(t2 - t0)
输出0.26157095399999997
1.201999999977943e-06
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