python functool.lru_cache

store the results of expensive function calls and return the cached result when the same inputs occur again

• decorator to optimize performance-intensive functions

• Limited and Predictable Input Variance

• Repetitive Computations with Identical Inputs

from functools import partial, lru_cache
import numpy as np

@lru_cache(maxsize=128)
def expensive_computation(x, y):
    return np.sum(np.power(np.arange(x), y))

partial_compute = partial(
    expensive_computation, y=2)

# Usage
result1 = partial_compute(1000000)
result2 = partial_compute(1000000) #Cached result

print(f"Result 1: {result1}")
print(f"Result 2: {result2}")
# Result 1: 333332833333500000
# Result 2: 333332833333500000