In Python, the `functools` module is a standard library that provides higher-order functions for functional programming. It includes utility functions like `lru_cache`, `partial`, and `reduce` that can help you optimize and manipulate other functions.
# Example of using functools in Python
from functools import lru_cache
@lru_cache(maxsize=32)
def fibonacci(n):
if n < 2:
return n
return fibonacci(n - 1) + fibonacci(n - 2)
print(fibonacci(10)) # Output: 55
How do I avoid rehashing overhead with std::set in multithreaded code?
How do I find elements with custom comparators with std::set for embedded targets?
How do I erase elements while iterating with std::set for embedded targets?
How do I provide stable iteration order with std::unordered_map for large datasets?
How do I reserve capacity ahead of time with std::unordered_map for large datasets?
How do I erase elements while iterating with std::unordered_map in multithreaded code?
How do I provide stable iteration order with std::map for embedded targets?
How do I provide stable iteration order with std::map in multithreaded code?
How do I avoid rehashing overhead with std::map in performance-sensitive code?
How do I merge two containers efficiently with std::map for embedded targets?