本文整理匯總了Python中_functools._lru_cache_wrapper方法的典型用法代碼示例。如果您正苦於以下問題：Python _functools._lru_cache_wrapper方法的具體用法？Python _functools._lru_cache_wrapper怎麽用？Python _functools._lru_cache_wrapper使用的例子？那麽, 這裏精選的方法代碼示例或許可以為您提供幫助。您也可以進一步了解該方法所在類_functools的用法示例。
在下文中一共展示了_functools._lru_cache_wrapper方法的2個代碼示例，這些例子默認根據受歡迎程度排序。您可以為喜歡或者感覺有用的代碼點讚，您的評價將有助於係統推薦出更棒的Python代碼示例。
示例1: lru_cache
# 需要導入模塊: import _functools [as 別名]
# 或者: from _functools import _lru_cache_wrapper [as 別名]
def lru_cache(maxsize=128, typed=False):
"""Least-recently-used cache decorator.
If *maxsize* is set to None, the LRU features are disabled and the cache
can grow without bound.
If *typed* is True, arguments of different types will be cached separately.
For example, f(3.0) and f(3) will be treated as distinct calls with
distinct results.
Arguments to the cached function must be hashable.
View the cache statistics named tuple (hits, misses, maxsize, currsize)
with f.cache_info(). Clear the cache and statistics with f.cache_clear().
Access the underlying function with f.__wrapped__.
See: http://en.wikipedia.org/wiki/Cache_algorithms#Least_Recently_Used
"""
# Users should only access the lru_cache through its public API:
# cache_info, cache_clear, and f.__wrapped__
# The internals of the lru_cache are encapsulated for thread safety and
# to allow the implementation to change (including a possible C version).
# Early detection of an erroneous call to @lru_cache without any arguments
# resulting in the inner function being passed to maxsize instead of an
# integer or None.
if maxsize is not None and not isinstance(maxsize, int):
raise TypeError('Expected maxsize to be an integer or None')
def decorating_function(user_function):
wrapper = _lru_cache_wrapper(user_function, maxsize, typed, _CacheInfo)
return update_wrapper(wrapper, user_function)
return decorating_function 示例2: lru_cache
# 需要導入模塊: import _functools [as 別名]
# 或者: from _functools import _lru_cache_wrapper [as 別名]
def lru_cache(maxsize=128, typed=False):
"""Least-recently-used cache decorator.
If *maxsize* is set to None, the LRU features are disabled and the cache
can grow without bound.
If *typed* is True, arguments of different types will be cached separately.
For example, f(3.0) and f(3) will be treated as distinct calls with
distinct results.
Arguments to the cached function must be hashable.
View the cache statistics named tuple (hits, misses, maxsize, currsize)
with f.cache_info(). Clear the cache and statistics with f.cache_clear().
Access the underlying function with f.__wrapped__.
See: http://en.wikipedia.org/wiki/Cache_algorithms#Least_Recently_Used
"""
# Users should only access the lru_cache through its public API:
# cache_info, cache_clear, and f.__wrapped__
# The internals of the lru_cache are encapsulated for thread safety and
# to allow the implementation to change (including a possible C version).
# Early detection of an erroneous call to @lru_cache without any arguments
# resulting in the inner function being passed to maxsize instead of an
# integer or None. Negative maxsize is treated as 0.
if isinstance(maxsize, int):
if maxsize < 0:
maxsize = 0
elif maxsize is not None:
raise TypeError('Expected maxsize to be an integer or None')
def decorating_function(user_function):
wrapper = _lru_cache_wrapper(user_function, maxsize, typed, _CacheInfo)
return update_wrapper(wrapper, user_function)
return decorating_function