Function Memoizing

Caches can also be used to store function calls, as a way of memoize.

Because this is dict based, any function calls must have hashable arguments & keywords. Better to not cache than to blow up entirely.

Example

import faste

@faste.decor.rr_cache()
def takes_long(*args):
    time.sleep(5)
    return args

takes_long("a", "b", "c")
# waits 5 seconds before returning ("a", "b", "c",)

takes_long("a", "b", "c")
# returns ("a", "b", "c",) immediately

takes_long.clear_cache()
takes_long("a", "b", "c")
# waits 5 seconds before returning ("a", "b", "c",)

Cache Decorators

faste.decor.rr_cache(max_size=128)

Random Replacement cache decorator, implementing faste.caches.RRCache

Keyword Arguments:  max_size (int) – max cache size

faste.decor.lru_cache(max_size=128)

Least Recently Used cache decorator, implementing faste.caches.LRUCache

Keyword Arguments:  max_size – max cache size

faste.decor.lfu_cache(max_size=128)

Least Frequently Used cache decorator, implementing faste.caches.LFUCache

Keyword Arguments:  max_size – max cache size

faste.decor.timed_cache(timeout, max_size=128)

Time based decorator, implementing faste.caches.TimeoutCache

Parameters:

• timeout (int) – Cache key timeout
• max_size (int) – (keyword) max size.