WGH*_*WGH 22 python caching lru functools python-decorators
我怎样才能使@functools.lru_cache装饰器忽略一些关于缓存键的函数参数?
例如,我有一个如下所示的函数:
def find_object(db_handle, query):
# (omitted code)
return result
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如果我lru_cache像这样应用装饰器,db_handle将包含在缓存键中.因此,如果我尝试使用相同query但不同的函数调用该函数db_handle,它将再次执行,我想避免.我只想lru_cache考虑query参数.
Yan*_*ann 11
使用cachetools,您可以编写:
from cachetools import cached
from cachetools.keys import hashkey
from random import randint
@cached(cache={}, key=lambda db_handle, query: hashkey(query))
def find_object(db_handle, query):
print("processing {0}".format(query))
return query
queries = list(range(5))
queries.extend(range(5))
for q in queries:
print("result: {0}".format(find_object(randint(0, 1000), q)))
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我至少有一个非常丑陋的解决方案。包装db_handle在一个始终等于的对象中,并在函数内展开它。
它需要一个带有大量辅助函数的装饰器,这使得堆栈跟踪非常混乱。
class _Equals(object):
def __init__(self, o):
self.obj = o
def __eq__(self, other):
return True
def __hash__(self):
return 0
def lru_cache_ignoring_first_argument(*args, **kwargs):
lru_decorator = functools.lru_cache(*args, **kwargs)
def decorator(f):
@lru_decorator
def helper(arg1, *args, **kwargs):
arg1 = arg1.obj
return f(arg1, *args, **kwargs)
@functools.wraps(f)
def function(arg1, *args, **kwargs):
arg1 = _Equals(arg1)
return helper(arg1, *args, **kwargs)
return function
return decorator
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