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Python functools cache() Function

The Python cache() function specifies the application performance by storing the results determined by the program. Similarly, caching involves storing values computed during function calls for future reuse, this is known as memorization.

We can perform repetitive operations on large datasets. By using caching results, we can minimize the time and cost of executing the calculations repeatedly on the datasets.

Following is the syntax for the cache() function.

@functools.cache()

The cache() decorator doesn't accept any parameters.

This function returns the cached version of the decorated function.

In the example below, the factorial function calculates the factorial of a number using cache() function and results the cached value.

import functools
@functools.cache
def fact(x):
    if x == 0:
        return 1
    else:
        return x * fact(x - 1)
print(fact(29))  
print(fact(6)) 

The result is generated as follows −

8841761993739701954543616000000
720

We are now using the square function, which calculates the square of a number using the cache() function. If the function is called with the same argument again, it returns the cached result instead of recalculating the program.

import functools
@functools.cache
def fact(x):
    return x * fact(x-1) if x else 1
print(fact(20))
print(fact(20)) #stored result, no need for recalculation 

The code is generated as follows −

2432902008176640000
2432902008176640000

Here, we are finding the fibonacci function, which calculates the Fibonacci number for a given input using the cache() function.

import functools
@functools.cache
def fib(x):
    if x <= 1:
        return x
    return fib(x - 1) + fib(x - 2)
print(fib(20))  
print(fib(10)) 

The output is obtained as follows −

6765
55

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