Problem:
 Score : 500 points    Problem Statement We have N integers. The i -th number is A_i .  \{A_i\} is said to be pairwise coprime when GCD(A_i,A_j)=1 holds for every pair (i, j) such that 1\leq i < j \leq N .  \{A_i\} is said to be setwise coprime when \{A_i\} is not pairwise coprime but GCD(A_1,\ldots,A_N)=1 .  Determine if \{A_i\} is pairwise coprime, setwise coprime, or neither.  Here, GCD(\ldots) denotes greatest common divisor.      Constraints  2 \leq N \leq 10^6  1 \leq A_i\leq 10^6         Input Input is given from Standard Input in the following format:  N  A_1  \ldots  A_N       Output If \{A_i\} is pairwise coprime, print pairwise coprime ; if \{A_i\} is setwise coprime, print setwise coprime ; if neither, print not coprime .        Sample Input 1 3
3 4 5      Sample Output 1 pairwise coprime  GCD(3,4)=GCD(3,5)=GCD(4,5)=1 , so they are pairwise coprime.       Sample Input 2 3
6 10 15      Sample Output 2 setwise coprime  Since GCD(6,10)=2 , they are not pairwise coprime. However, since GCD(6,10,15)=1 , they are setwise coprime.       Sample Input 3 3
6 10 16      Sample Output 3 not coprime  GCD(6,10,16)=2 , so they are neither pairwise coprime nor setwise coprime.

Solution (Python):

"""

import numpy as np
i4 = np.int32
i8 = np.int64


def factorization(N):
    p = np.zeros(N + 1, i8)
    n_max = int(np.sqrt(N)) + 1
    p[0] = 1
    p[1] = 1
    for i in range(2, n_max):
        if p[i] == 0:
            j = i
            while j <= N:
                p[j] = i
                j += i
    for i in range(n_max, N + 1):
        if p[i] == 0:
            p[i] = i
    return p


def gcd(a, b):
    '''Computes the greatest common divisor of integers a and b using
    Euclid's Algorithm.
    '''
    while b != 0:
        a, b = b, a % b
    return a


def solve(A):
    a = np.sort(A)
    g = a[0]
    for i in range(1, a.shape[0]):
        g = gcd(a[i], g)
    if g > 1:
        return 2
    p_max = a[-1]
    p = factorization(p_max)
    primes_num = 0
    for i in range(2, p.shape[0]):
        if i == p[i]:
            primes_num += 1
    a_start = 0
    while a[a_start] == 1:
        a_start += 1
        if a_start == a.shape[0]:
            return 0
    a = a[a_start:]
    if len(a) > primes_num:
        return 1
    check = np.zeros(p_max + 1, i8)
    s = set()
    for d in a:
        while d > 1:
            x = p[d]
            s.add(x)
            d //= x

        while s:
            check[s.pop()] += 1

    if check.max() > 1:
        return 1
    else:
        return 0


def main(in_file):
    stdin = open(in_file)
    stdin.readline()
    A = np.array([int(x) for x in stdin.readline().split()])
    ans = solve(A)
    p = ['pairwise coprime', 'setwise coprime', 'not coprime']
    print(p[ans])


def main2():
    main('/dev/stdin')
"""
import os, sys
p = os.path.dirname(__file__)
pymain = os.path.join(p, "a.out")
if len(sys.argv) == 1:
    import subprocess
    if p == "":
        pymain = "./" + pymain
    subprocess.call(pymain)
else:
    import gzip, base64, stat
    gz = b'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'
    bin = gzip.decompress(base64.b64decode(gz))
    with open(pymain, "wb") as f:
        f.write(bin)
    os.chmod(pymain, 0o775)