Optimize your python code with lru cache tutorial
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lru (least recently used) cache is a technique used to store frequently accessed data in memory to speed up operations by reducing the need to repeatedly compute or fetch the same data. python provides a built-in `functools.lru_cache` decorator that can be used to easily implement this caching mechanism.
here is a step-by-step tutorial on how to optimize your python code using `lru_cache`:
1. import the `lru_cache` decorator from the `functools` module:
2. define a function that performs a computationally expensive task or fetches data:
3. decorate the function with `lru_cache` to enable caching:
4. call the cached function with the desired input:
in this example, the `fibonacci_cached` function will automatically cache the results of previous function calls, avoiding redundant computations for the same input. the `maxsize=none` argument specifies that the cache can grow indefinitely.
by using `lru_cache`, you can significantly improve the performance of your python code, especially for functions with repetitive or recursive computations. make sure to analyze your specific use case and adjust the caching parameters accordingly for optimal results.
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