python lru cache ttl
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title: implementing python lru cache with time-to-live (ttl)
introduction:
caching is a technique commonly used in computer science to store frequently accessed data in memory, reducing the need to recompute or retrieve the data from its original source. python's functools module provides a built-in decorator called lru_cache (least recently used cache), which helps in implementing a cache with limited size. however, it doesn't provide a built-in way to set a time-to-live (ttl) for cached items. in this tutorial, we'll explore how to implement an lru cache with ttl using a custom decorator.
prerequisites:
make sure you have a basic understanding of python and its decorators.
implementation:
we'll create a custom decorator named lru_cache_ttl that extends the functionality of functools.lru_cache. the extended functionality includes the ability to set a ttl for cached items.
explanation:
conclusion:
implementing an lru cache with time-to-live adds a valuable dimension to caching, allowing developers to control the lifespan of cached items. by combining the principles of least recently used caching with a ttl mechanism, you can optimize the performance of your python applications efficiently.
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