ch_part2_is_it_optimal.py

def consistent_hashing_same_allocations(
    n: int,
    urls: List[str],
    ch_cls: ConsistentHashing,
) -> float:
    ch = ch_cls(server_ids={random_str() for _ in range(n)})
    allocs = {url: ch.key_lookup(key=url) for url in urls}
    ch.add_server(server_id=random_str())
    return sum(
        allocs[url] == ch.key_lookup(key=url)
        for url in urls
    ) / len(urls)


def run_exp(
    ns: Sequence[int],
    experiment_cnt: int,
    ch_cls: Type[ConsistentHashing],
) -> pd.DataFrame:
    return pd.DataFrame(
        dict(
            n=n,
            idx_experiment=idx_experiment,
            same_alloc=consistent_hashing_same_allocations(
                n=n,
                urls=urls,
                ch_cls=ch_cls,
            ),
        )
        for n in ns
        for idx_experiment in range(experiment_cnt)
    )