Local Caching
Learn about local caching in Python.
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Local caching has the advantage of being (very) fast, as it does not require access to a remote cache over the network. Usually, caching works by storing cached data under a key that identifies it. This technique makes the Python dictionary the most obvious data structure for implementing a caching mechanism.
A simple cache using Python dictionary
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cache = {}cache['key'] = 'value'cache = {}def compute_length_or_read_in_cache(s):try:return cache[s]except KeyError:cache[s] = len(s)return cache[s]print("Foobar: ", compute_length_or_read_in_cache("foobar"))print('Cache: ', cache)print("Babaz: ", compute_length_or_read_in_cache("babaz"))print('Cache: ', cache)
Obviously, such a simple cache has a few drawbacks. First, its size is unbound, which means it can grow to a substantial size that can fill up the entire system memory. That would result in the death of either the process, or even the whole ...