How can I improve caching performance in my Python library?
An example of an AI chatbot conversation about optimizing caching in Python libraries.
How can I improve caching performance in my Python library?
You can improve caching performance by using libraries like functools.lru_cache or implementing a custom caching mechanism.
What are the benefits of using functools.lru_cache?
functools.lru_cache provides automatic caching of function results, reducing computation time for repeated calls with the same arguments.
Are there any downsides to using caching?
Yes, caching can increase memory usage and may lead to stale data if not managed properly.
How can I clear the cache when needed?
You can clear the cache by calling the cache_clear() method on the cached function.
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