Journey to Master Python (WIP)

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Functools module

Memoization

Functools module supports memoization through lru_cache decorator. This way you dont need to write memoization code.

In the example adding the decorator @lru_cache does the needful. You can also see the cache details with cache_info

lru_cache Decorator

import time
from functools import lru_cache
def fibonacci(n):
    if n < 2:
        return n
    return fibonacci(n-1) + fibonacci(n-2)
@lru_cache(maxsize=128)
def fibonacci_cached(n):
    if n < 2:
        return n
    return fibonacci_cached(n-1) + fibonacci_cached(n-2)
time1 = time.time()
print(f'35 Fibonocci number is {fibonacci(35)}')
time2 = time.time()
print(f'Total time taken is {(time2-time1)*1000}ms')
time1 = time.time()
print(f'35 Fibonocci number is {fibonacci_cached(35)}')
time2 = time.time()
print(f'Total time taken is {(time2-time1)*1000 }ms')
print(f'{fibonacci_cached.cache_info()}')

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8/12 Functools Module

Functools module

Memoization

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