cached separately. For example, ``f(3)`` and ``f(3.0)`` will be treated
as distinct calls with distinct results.
+ The wrapped function is instrumented with a :func:`cache_parameters`
+ function that returns a new :class:`dict` showing the values for *maxsize*
+ and *typed*. This is for information purposes only. Mutating the values
+ has no effect.
+
To help measure the effectiveness of the cache and tune the *maxsize*
parameter, the wrapped function is instrumented with a :func:`cache_info`
function that returns a :term:`named tuple` showing *hits*, *misses*,
.. versionchanged:: 3.8
Added the *user_function* option.
+ .. versionadded:: 3.9
+ Added the function :func:`cache_parameters`
+
.. decorator:: total_ordering
Given a class defining one or more rich comparison ordering methods, this
# The user_function was passed in directly via the maxsize argument
user_function, maxsize = maxsize, 128
wrapper = _lru_cache_wrapper(user_function, maxsize, typed, _CacheInfo)
+ wrapper.cache_parameters = lambda : {'maxsize': maxsize, 'typed': typed}
return update_wrapper(wrapper, user_function)
elif maxsize is not None:
raise TypeError(
def decorating_function(user_function):
wrapper = _lru_cache_wrapper(user_function, maxsize, typed, _CacheInfo)
+ wrapper.cache_parameters = lambda : {'maxsize': maxsize, 'typed': typed}
return update_wrapper(wrapper, user_function)
return decorating_function
f_copy = copy.deepcopy(f)
self.assertIs(f_copy, f)
+ def test_lru_cache_parameters(self):
+ @self.module.lru_cache(maxsize=2)
+ def f():
+ return 1
+ self.assertEqual(f.cache_parameters(), {'maxsize': 2, "typed": False})
+
+ @self.module.lru_cache(maxsize=1000, typed=True)
+ def f():
+ return 1
+ self.assertEqual(f.cache_parameters(), {'maxsize': 1000, "typed": True})
+
@py_functools.lru_cache()
def py_cached_func(x, y):
--- /dev/null
+Add new cache_parameters() method for functools.lru_cache() to better support pickling.
\ No newline at end of file