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6 Cool Things You Can Do With The Functools Module - Pybites

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In this article let’s look at the functools Standard Library module and 6 cool things you can do with it (be warned, a lot of decorators are coming your way! 😍) … You can use the @cache decorator (formerly called @lru_cache) as a “simple lightweight unbounded function cache”. The classic example is calculating a Fibonacci series where the intermediate results are cached, speeding up the calculation significantly: On my system this code takes 0.02s to complete. 😎 However if I comment the @cache decorator it takes 28.30s because of all the repeated calculations! 😱 Hence caching is especially useful and crucial for tasks with expensive repeat computations. New to caching? Check out our YouTube video. You can do the same for properties using @cached_property. Using the @total_ordering decorator you can write the __eq__() dunder and one of __lt__(), __le__(), __gt__(), or __ge__(), so only two, and it will provide the other ones automatically for you. Less code, nice automation. As per t

In this article let’s look at the functools Standard Library module and 6 cool things you can do with it (be warned, a lot of decorators are coming your way! 😍) … 1. Cache (“memoize”) things You can use the @cache decorator (formerly called @lru_cache ) as a “simple lightweight unbounded function cache”. The classic example is calculating a Fibonacci series where the intermediate results are cached, speeding up the calculation significantly: from functools import cache @cache def fibonacci(n: int) -> int: if n <= 1: return n return fibonacci(n - 1) + fibona

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6 Cool Things You Can Do With The Functools Module - Pybites

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