Question

Since I’m starting to get the hang of Python, I’m starting to test my newly acquired Python skills on some problems on projecteuler.net.

Anyways, at some point, I ended up making a function for getting a list of all primes up until a number ‘n’.

Here’s how the function looks atm:

def primes(n):
    """Returns list of all the primes up until the number n."""

    # Gather all potential primes in a list.
    primes = range(2, n + 1)
    # The first potential prime in the list should be two.
    assert primes[0] == 2
    # The last potential prime in the list should be n.
    assert primes[-1] == n

    # 'p' will be the index of the current confirmed prime.
    p = 0
    # As long as 'p' is within the bounds of the list:
    while p < len(primes):
        # Set the candidate index 'c' to start right after 'p'.
        c = p + 1
        # As long as 'c' is within the bounds of the list:
        while c < len(primes):
            # Check if the candidate is divisible by the prime.
            if(primes[c] % primes[p] == 0):
                # If it is, it isn't a prime, and should be removed.
                primes.pop(c)
            # Move on to the next candidate and redo the process.
            c = c + 1
        # The next integer in the list should now be a prime, 
        # since it is not divisible by any of the primes before it. 
        # Thus we can move on to the next prime and redo the process.
        p = p + 1       
    # The list should now only contain primes, and can thus be returned.
    return primes

It seems to work fine, although one there’s one thing that bothers me.
While commenting the code, this piece suddenly seemed off:

# Check if the candidate is divisible by the prime.
if(primes[c] % primes[p] == 0):
    # If it is, it isn't a prime, and should be removed from the list.
    primes.pop(c)
# Move on to the next candidate and redo the process.
c += 1

If the candidate IS NOT divisible by the prime we examine the next candidate located at ‘c + 1’. No problem with that.

However, if the candidate IS divisible by the prime, we first pop it and then examine the next candidate located at ‘c + 1’.
It struck me that the next candidate, after popping, is not located at ‘c + 1’, but ‘c’, since after popping at ‘c’, the next candidate “falls” into that index.

I then thought that the block should look like the following:

# If the candidate is divisible by the prime:
if(primes[c] % primes[p] == 0):
    # If it is, it isn't a prime, and should be removed from the list.
    primes.pop(c)
# If not:
else:
    # Move on to the next candidate.
    c += 1

This above block seems more correct to me, but leaves me wondering why the original piece apparently worked just fine.

So, here are my questions:

After popping a candidate which turned out not be a prime, can we assume, as it is in my original code, that the next candidate is NOT divisible by that same prime?

If so, why is that?

Would the suggested “safe” code just do unnecessary checks on the candidates which where skipped in the “unsafe” code?

PS:

I’ve tried writing the above assumption as an assertion into the ‘unsafe’ function, and test it with n = 100000. No problems occurred. Here’s the modified block:

# If the candidate is divisible by the prime:
if(primes[c] % primes[p] == 0):
    # If it is, it isn't a prime, and should be removed.
    primes.pop(c)
    # If c is still within the bounds of the list:
    if c < len(primes):
        # We assume that the new candidate at 'c' is not divisible by the prime.
        assert primes[c] % primes[p] != 0
# Move on to the next candidate and redo the process.
c = c + 1

Answer 1

It fails for much bigger numbers. The first prime is 71, for that the candidate can fail. The smallest failing candidate for 71 is 10986448536829734695346889 which overshadows the number 10986448536829734695346889 + 142.

def primes(n, skip_range=None):
    """Modified "primes" with the original assertion from P.S. of the question.
    with skipping of an unimportant huge range.
    >>> primes(71)
    [2, 3, 5, 7, 11, 13, 17, 19, 23, 29, 31, 37, 41, 43, 47, 53, 59, 61, 67, 71]
    >>> # The smallest failing number for the first failing prime 71:
    >>> big_n = 10986448536829734695346889
    >>> primes(big_n + 2 * 71, (72, big_n))
    Traceback (most recent call last):
    AssertionError
    """
    if not skip_range:
        primes = list(range(2, n + 1))
    else:
        primes = list(range(2, skip_range[0]))
        primes.extend(range(skip_range[1], n + 1))
    p = 0
    while p < len(primes):
        c = p + 1
        while c < len(primes):
            if(primes[c] % primes[p] == 0):
                primes.pop(c)
                if c < len(primes):
                    assert primes[c] % primes[p] != 0
            c = c + 1
        p = p + 1
    return primes

# Verify that it can fail.
aprime = 71   # the first problematic prime 
FIRST_BAD_NUMBERS = (
        10986448536829734695346889, 11078434793489708690791399,
        12367063025234804812185529, 20329913969650068499781719,
        30697401499184410328653969, 35961932865481861481238649,
        40008133490686471804514089, 41414505712084173826517629,
        49440212368558553144898949, 52201441345368693378576229)

for bad_number in FIRST_BAD_NUMBERS:
    try:
        primes(bad_number + 2 * aprime, (aprime + 1, bad_number))
        raise Exception('The number {} should fail'.format(bad_number))
    except AssertionError:
        print('{} OK. It fails as is expected'.format(bad_number))

I solved these numbers by a complicated algorithm like a puzzle by searching possible remainders of n modulo small primes. The last simple step was to get the complete n (by chinese remainder theorem in three lines of Python code). I know all 120 basic solutions smaller than primorial(71) = 2 * 3 * 5 * 7 * 11 * 13 * 17 * 19 * 23 * 29 * 31 * 37 * 41 * 43 * 47 * 53 * 59 * 61 * 67 * 71 repeated periodically by all multiples of this number. I rewrote the algorithm many times for every decade of tested primes because for every decade was the solution much slower than for the previous. Maybe I find a smaller solution with the same algorithm for primes 73 or 79 in acceptable time.

---

Edit:

I would like to find also a complete silent fail of the unsafe original function. Maybe exists some candidate composed from different primes. This way of solution would only postpone the final outcome for later. Every step would be much more and more expensive for time and resources. Therefore only numbers composed from one or two primes are attractive.

I expect that only two solutions the hidden candidate c are good: c = p ** n or c = p1 * p ** n or c = p1 ** n1 * p ** n where p and p1 are primes and n is a power greater than 1. The primes function fails if c - 2 * p is divisible by no prime smaller than p and if all number between c-2n and c are divisible by any prime smaller than p. The variant p1*p**n requires also that the same c had failed before for p1 (p1 < p) as we already know infinite number of such candidates.

EDIT: I found a smaller example of failure: number 121093190175715194562061 for the prime 79. (which is about ninety times less than for 71) I can’t continue by the same algorithm to find smaller examples because all 702612 basic solutions took more than 30 hours for the prime 79 on my laptop.

I also verified it for all candidates smaller than 400000000 (4E10) and for all relevant primes, that no candidate will fail the assertion in the question. Until you have terabytes of memory and thousands years of time, the assertion in the algorithm will pass, because your time complexity is O((n / log(n)) ^2) or very similar.