On 2/14/23 15:07, Dino wrote:
Here's my problem today. I am using a dict() to implement a quick and
dirty in-memory cache.
I am stopping adding elements when I am reaching 1000 elements (totally
arbitrary number), but I would like to have something slightly more
sophisticated to free up space for newer and potentially more relevant
entries.
I am thinking of the Least Recently Used principle, but how to implement
that is not immediate. Before I embark on reinventing the wheel, is
there a tool, library or smart trick that will allow me to remove
elements with LRU logic?
It depends here how fancy you want to get. If you really need the
behavior of a size-limited cache and you expect there to be a lot of
churn, then you'll probably want a combination of data structures...
e.g. a dict-like thing for quick hashed lookups (means your "keys" need
to be hashable) and a doubly-linked list for ordering so you can quickly
move a hit to the most-recent position - and maybe you want to keep
cache stats as well.
Do look at functools if that well-tested standard library module fits
your needs. If you need, or are motivated (as a learning experience?) to
roll your own, my memory tells me the RealPython crew did a tutorial on
implementing an LRU cache, might be worth a look (not sure if this is
one of the all-free ones, or one of the
must-be-a-paid-subscriber-to-get-the-advanced-stuff ones.
--
https://mail.python.org/mailman/listinfo/python-list
