如何在Python中加速此任务

import multiprocessing as mp

def square(x):
    return x * x

if __name__ == "__main__":
    with mp.Pool(mp.cpu_count()) as pool:
        results = pool.map(square, range(10))
    print(results)

from concurrent.futures import ProcessPoolExecutor

def square(x):
    return x * x

if __name__ == "__main__":
    with ProcessPoolExecutor(max_workers=mp.cpu_count()) as executor:
        results = list(executor.map(square, range(10)))
    print(results)

pip install cython

# example.pyx
def square(int x):
    return x * x

cythonize -i example.pyx

import example

print(example.square(10))

pip install numba

from numba import njit

@njit
def square(x):
    return x * x

print(square(10))

import numpy as np

arr = np.array([1, 2, 3, 4, 5])
result = arr ** 2
print(result)

numbers = [1, 2, 3, 4, 5]
set_numbers = set(numbers)

if 3 in set_numbers:
    print("Found")

from functools import lru_cache

@lru_cache(maxsize=None)
def fibonacci(n):
    if n < 2:
        return n
    return fibonacci(n-1) + fibonacci(n-2)

print(fibonacci(10))