Understanding the functools Module in Python
functools â Higher-order functions and operations on callable objects 🔗
The functools module in Python provides tools for working with higher-order functions, which are functions that can take other functions as arguments or return them as results. Key features of the module include decorators for caching function results, transforming methods into properties, and creating partial functions. Notable functions include @functools.cache, which offers a simple caching mechanism, @functools.cached_property for caching method results, and @functools.lru_cache for a more advanced caching solution with size limits. Other functions in the module help with creating single-dispatch generic functions and simplifying comparison operations in classes. Overall, functools enhances the efficiency and functionality of Python functions and methods.
What is the purpose of the functools module?
The functools module provides tools for working with higher-order functions, allowing for caching, property transformation, and other functional programming techniques.
What does the @functools.lru_cache decorator do?
The @functools.lru_cache decorator caches the results of function calls to avoid redundant calculations, saving up to a specified number of recent calls.
How does @functools.cached_property work?
@functools.cached_property transforms a method into a property that computes its value once and caches it, making it efficient for expensive computations that do not change.