Decorators caching - with cache - lru_cache

• By adding the lru_cache decorator we can tell Python to cache the result and save on computation time.

import functools

@functools.lru_cache()
def compute(x, y):
    print(f"Called with {x} and {y}")
    # some long computation here
    return x+y

if __name__ == "__main__":
    print(compute(2, 3))
    print(compute(3, 4))
    print(compute(2, 3))

Called with 2 and 3
5
Called with 3 and 4
7
5

from with_lru_cache import compute

def test_compute(capsys):
    assert compute(2, 3) == 5
    out, err = capsys.readouterr()
    assert err == ''
    assert out == 'Called with 2 and 3\n'

    assert compute(3, 4) == 7
    out, err = capsys.readouterr()
    assert err == ''
    assert out == 'Called with 3 and 4\n'

    assert compute(2, 3) == 5
    out, err = capsys.readouterr()
    assert err == ''
    assert out == '' # compute is not called!