Greetings Pavel, > Suppose, I have some resource-intensive tasks implemented as > functions in Python. Those are called repeatedly in my program. > It's guranteed that a call with the same arguments always produces > the same return value. I want to cache the arguments and return > values and in case of repititive call immediately return the > result without doing expensive calculations.
Great problem description. Thank you for being so clear. [I snipped sample code...] This is generically called memoization. > Do you like this design or maybe there's a better way with > Python's included batteries? In Python, there's an implementation available for you in the functools module. It's called lru_cache. LRU means 'Least Recently Used'. > I'd also like to limit the size of the cache (in MB) and get rid > of old cached data. Don't know how yet. You can also limit the size of the lru_cache provided by the functools module. For this function, the size is calculated by number of entries--so you will need to figure out memory size to cache entry count. Maybe others who have used functools.lru_cache can help you with how they solved the problem of mapping entry count to memory usage. Good luck, -Martin [0] https://docs.python.org/3/library/functools.html#functools.lru_cache -- Martin A. Brown http://linux-ip.net/ -- https://mail.python.org/mailman/listinfo/python-list
