Python in-memory cache with time to live

Question

I have multiple threads running the same process that need to be able to to notify each other that something should not be worked on for the next n seconds its not the end o

Answer 1

The OP is using python 2.7 but if you're using python 3, ExpiringDict mentioned in the accepted answer is currently, well, expired. The last commit to the github repo was June 17, 2017 and there is an open issue that it doesn't work with Python 3.5

As of September 1, 2020, there is a more recently maintained project cachetools.

pip install cachetools

from cachetools import TTLCache

cache = TTLCache(maxsize=10, ttl=360)
cache['apple'] = 'top dog'
...
>>> cache['apple']
'top dog'
... after 360 seconds...
>>> cache['apple']
KeyError exception thrown

ttl is the time to live in seconds.

Answer 2

I know this is a little old, but for those who are interested in no third-party dependencies, this is a minor wrapper around the builtin functools.lru_cache (I noticed Javier's similar answer after writing this, but figured I post it anyway since this doesn't require Django):

import functools
import time


def time_cache(max_age, maxsize=128, typed=False):
    """Least-recently-used cache decorator with time-based cache invalidation.

    Args:
        max_age: Time to live for cached results (in seconds).
        maxsize: Maximum cache size (see `functools.lru_cache`).
        typed: Cache on distinct input types (see `functools.lru_cache`).
    """
    def _decorator(fn):
        @functools.lru_cache(maxsize=maxsize, typed=typed)
        def _new(*args, __time_salt, **kwargs):
            return fn(*args, **kwargs)

        @functools.wraps(fn)
        def _wrapped(*args, **kwargs):
            return _new(*args, **kwargs, __time_salt=int(time.time() / max_age))

        return _wrapped

    return _decorator

And its usage:

@time_cache(10)
def expensive(a: int):
    """An expensive function."""
    time.sleep(1 + a)


print("Starting...")
expensive(1)
print("Again...")
expensive(1)
print("Done")

NB this uses time.time and comes with all its caveats. You may want to use time.monotonic instead if available/appropriate.