Python in-memory cache with time to live

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

ttl is the time to live in seconds.

In case you don't want to use any 3rd libraries, you can add one more parameter to your expensive function: ttl_hash=None. This new parameter is so-called "time sensitive hash", its the only purpose is to affect lru_cache.

For example:

from functools import lru_cacheimport time@lru_cache()def my_expensive_function(a, b, ttl_hash=None):    del ttl_hash  # to emphasize we don't use it and to shut pylint up    return a + b  # horrible CPU load...def get_ttl_hash(seconds=3600):    """Return the same value withing `seconds` time period"""    return round(time.time() / seconds)# somewhere in your code...res = my_expensive_function(2, 2, ttl_hash=get_ttl_hash())# cache will be updated once in an hour

You can use the expiringdict module:

The core of the library is ExpiringDict class which is an ordered dictionary with auto-expiring values for caching purposes.

In the description they do not talk about multithreading, so in order not to mess up, use a Lock.