如何解决Python3 functools lru_cache RuntimeError
from functool import lru_cache
@lru_cache
def fibonacci(n):
"""0,1,2,3,5,8,13,21,34
"""
if n == 0:
yield 0
elif n == 1:
yield 1
else:
yield next(fibonacci(n - 1)) + next(fibonacci(n - 2))
如果我使用@lru_cache
装饰器调用此函数,如下所示:
for x in range(10):
print(next(fibonacci(x)))
我得到:
StopIteration
The above exception was the direct cause of the following exception:
RuntimeError: generator raised StopIteration
我已经做了很多搜索,但我不知道该如何解决。没有装饰器,一切正常。
解决方法
如果您确实想缓存并因此重用生成器迭代器,请确保它们确实支持该迭代器。就是说,使他们不仅产生结果,而且反复产生结果。例如:
@lru_cache
def fibonacci(n):
"""0,1,2,3,5,8,13,21,34
"""
if n == 0:
while True:
yield 0
elif n == 1:
while True:
yield 1
else:
result = next(fibonacci(n - 1)) + next(fibonacci(n - 2))
while True:
yield result
测试:
>>> for x in range(10):
print(next(fibonacci(x)))
0
1
1
2
3
5
8
13
21
34
,
您可以使用备忘录装饰器
参考:Can I memoize a Python generator?的Jasmijn回答
代码
from itertools import tee
from types import GeneratorType
Tee = tee([],1)[0].__class__
def memoized(f):
cache={}
def ret(*args):
if args not in cache:
cache[args]=f(*args)
if isinstance(cache[args],(GeneratorType,Tee)):
# the original can't be used any more,# so we need to change the cache as well
cache[args],r = tee(cache[args])
return r
return cache[args]
return ret
@memoized
def Fibonacci(n):
"""0,34
"""
if n == 0:
yield 0
elif n == 1:
yield 1
else:
yield next(fibonacci_mem(n - 1)) + next(fibonacci_mem(n - 2))
计时测试
摘要
测试n从1到20 orig:原始代码 lru:使用lru缓存 记忆:使用记忆修饰器
每种算法的3次运行以秒为单位
结果表明,lru_cache技术提供了最快的运行时间(即较短的时间)
n: 1 orig: 0.000008,lru 0.000006,mem: 0.000015
n: 10 orig: 0.000521,lru 0.000024,mem: 0.000057
n: 15 orig: 0.005718,lru 0.000013,mem: 0.000035
n: 20 orig: 0.110947,lru 0.000014,mem: 0.000040
n: 25 orig: 1.503879,lru 0.000018,mem: 0.000042
计时测试代码
from itertools import tee
from types import GeneratorType
from functools import lru_cache
Tee = tee([],r = tee(cache[args])
return r
return cache[args]
return ret
def fibonacci(n):
"""0,34
"""
if n == 0:
yield 0
elif n == 1:
yield 1
else:
yield next(fibonacci(n - 1)) + next(fibonacci(n - 2))
@memoized
def fibonacci_mem(n):
"""0,34
"""
if n == 0:
yield 0
elif n == 1:
yield 1
else:
yield next(fibonacci_mem(n - 1)) + next(fibonacci_mem(n - 2))
@lru_cache
def fibonacci_cache(n):
"""0,34
"""
if n == 0:
while True:
yield 0
elif n == 1:
while True:
yield 1
else:
result = next(fibonacci_cache(n - 1)) + next(fibonacci_cache(n - 2))
while True:
yield result
from timeit import timeit
cnt = 3
for n in [1,10,15,20,25]:
t_orig = timeit(lambda:next(fibonacci(n)),number = cnt)
t_mem = timeit(lambda:next(fibonacci_mem(n)),number = cnt)
t_cache = timeit(lambda:next(fibonacci_cache(n)),number = cnt)
print(f'n: {n} orig: {t_orig:.6f},lru {t_cache:.6f},mem: {t_mem:.6f}')
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