`functools`

The Python functools module provides higher-order functions and tools for working with callable objects.

This module allows you to work with functions in a functional programming style, offering utilities that modify or extend the behavior of functions and methods in Python.

Here’s an example:

>>> import functools

>>> double = functools.partial(lambda x, y: x * y, x=2)
>>> double(5)
10

Key Features

Provides tools for creating partial functions
Supports function memoization with lru_cache
Offers decorators for method caching
Includes utilities for comparing and ordering

Frequently Used Classes and Functions

Object	Type	Description
`functools.partial`	Function	Returns a new callable object that behaves like the original function with specified arguments
`@functools.lru_cache`	Decorator	Caches function calls with a Least Recently Used (LRU) cache strategy
`functools.reduce()`	Function	Performs a cumulative computation on a sequence of elements
`@functools.singledispatch`	Decorator	Transforms a function into a single-dispatch generic function.

Examples

Create a partial function that computes powers of 3:

>>> from functools import partial

>>> cube = partial(lambda x, y: x**y, y=3)
>>> cube(4)
64

Use reduce() to compute the product of a list:

>>> from functools import reduce
>>> reduce(lambda x, y: x * y, [1, 2, 3, 4])
24

Common Use Cases

Creating functions with fixed arguments for repeated use
Optimizing recursive functions with caching
Transforming comparison functions for sorting
Performing cumulative operations on data collections

Real-World Example

Suppose you have a recursive function that calculates Fibonacci numbers, and you want to optimize it by using caching to avoid redundant calculations:

>>> from functools import lru_cache

>>> @lru_cache(maxsize=128)
... def fibonacci(n):
...     if n < 2:
...         return n
...     return fibonacci(n-1) + fibonacci(n-2)
...

>>> fibonacci(100)
354224848179261915075

Here, the @lru_cache decorator significantly improves the performance of the Fibonacci function by storing the results of previously computed values, avoiding the need to recompute them.

functools