Discussion on best practices for advanced caching - please join

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I have tried adding the cachetools TTLCache on top. So far this seems to speed things up even more.

So updating the _get_data of the above example with

from cachetools import cached, TTLCache

@cached(cache=TTLCache(maxsize=1024, ttl=600))
def _get_data(value):
    value_str = str(value)
    if value_str in cache:
        return cache[value_str]
    else:
        print("loading data", value)
        time.sleep(1)

        df = pd.DataFrame(np.random.randint(0, 100, size=(100, 4)), columns=list("ABCD"))
        cache[value_str] = df
        print("data loaded")
        return df

I will need to figure out how to get things working globally. Right now I think it’s working for a session.