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I'm currently working through the Project Euler Problems using HackerRank to evaluate the code and I'm stuck on the 7th Problem.

"""
    By listing the first six prime numbers: 2, 3, 5, 7, 11, and 13, we can see that the 6th prime is 13.

    What is the 10 001st prime number?

"""
import pytest

def find_primes(limit):
    nums = [True] * (limit+1)
    nums[0] = nums[1] = False

    for (i, is_prime) in enumerate(nums):
        if is_prime:
            yield i
            for n in range(i*i, limit+1, i):
                nums[n] = False

def find_n_prime(n):
    for i in range(n, (n*n)+1, n):
        primes = list(find_primes(i))
        if len(primes) >= n:
            return primes[n-1]

def test_find_n_primes():
    assert find_n_prime(2) == 3
    assert find_n_prime(3) == 5

    assert find_n_prime(10) == 29
    assert find_n_prime(15) == 47
    assert find_n_prime(81) == 419

    assert find_n_prime(941) == 7417
    assert find_n_prime(1000) == 7919

    assert find_n_prime(10001) == 104743

The code only completes the first test case on hackerRank and fails for #2 test case and times out for the rest.

How can I improve the Code ?

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1 Answer 1

10
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Upper bound for p_n

There is a known upper bound for the n-th prime.

It means that you don't need any loop inside find_n_prime, and you don't need to check if len(primes) >= n either.

import pytest
from math import log, ceil

def find_primes(limit):
    nums = [True] * (limit + 1)
    nums[0] = nums[1] = False

    for (i, is_prime) in enumerate(nums):
        if is_prime:
            yield i
            for n in range(i * i, limit + 1, i):
                nums[n] = False

def upper_bound_for_p_n(n):
    if n < 6:
        return 100
    return ceil(n * (log(n) + log(log(n))))

def find_n_prime(n):
    primes = list(find_primes(upper_bound_for_p_n(n)))
    return primes[n - 1]

It calculates the 100000th prime in less than 230ms on my computer, compared to 1.5s for your code.

itertools.islice

Another possible optimization would be to use itertools.isclice to get the n-th prime out of the find_primes generator, without converting it to a list.

from itertools import islice

def find_n_prime(n):
    primes = find_primes(upper_bound_for_p_n(n))
    return next(islice(primes, n - 1, n))
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1
  • \$\begingroup\$ If the upper bound is \$U\$ then the running time of Eratosphenes' sieve is \$O(U \lg \lg U)\$. If you really want overkill, Meissel-Lehmer with an intelligent interpolation search should be \$O(U^{0.67+\epsilon} \lg U)\$. Maybe considerably better if you can cache and reuse subcomputations. \$\endgroup\$ Apr 24, 2018 at 15:12

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