Project Euler Problem 1

February 10, 2015

Project Euler is a collection of math problems intended for computer solution, and is one of the inspirations for Programming Praxis. The first problem on Project Euler, which also regularly appears on lists of phone interview questions, asks you to:

Find the sum of all the multiples of 3 or 5 below 1000.

Your task is to write a program that solves Problem 1 for arbitrary n; since the problem is simple, you must provide at least three fundamentally different solutions. When you are finished, you are welcome to read or run a suggested solution, or to post your own solution or discuss the exercise in the comments below.

Pages: 1 2

6 Responses to “Project Euler Problem 1”

  1. Three ways…
    (1) Brute force overall entries and summing them!
    (2) Brute force summing muliples of 5, multiples of 3 and removing duplicate multiples of 15…
    (3) Same as 2 but using formulae to compute sum – no need to brute force…

    sub bf {
    my $n = shift;
    my $t = 0;
    $t+= $_ foreach grep { !($_ % 3) || !($_ % 5) } 1..($n-1);
    return $t;
    }

    sub x {
    my $n = shift;
    return _x($n,3)+_x($n,5)-_x($n,15);
    }

    sub _x {
    my($n,$f)=@_;
    my $s = 0;
    my $t = 0;
    while($t<$n) {
    $s+=$t;
    $t+=$f;
    }
    return $s;
    }

    sub yy {
    my $n = shift;
    return _y($n,3)+_y($n,5)-_y($n,15);
    }

    sub _y {
    my($n,$f)=@_;
    $n = int (($n-1)/$f);
    return $f * ($n+1)*$n/2;
    }

    printf "%7d %20d %20d %20d\n", $_, bf($_), x($_), yy($_) foreach @ARGV;

  2. Rutger said

    My solution in Python.
    Easy to extend, just add your own function as long as it starts with “solve_” and returns the result as an int.

    #project euler 1
    import time
    
    # naive solution, iterate through all numbers
    def solve_brute_force(up_until):
    	result = 0
    	for i in range(up_until):
    		if (not i % 3) or (not i % 5):
    			result += i
    	return result
    
    # Wheeled, jumps from one number %3 or %5 to the next
    def solve_wheel_multiples(up_until):
    	i = 0
    	first_numbers = []
    	for i in range(0, 3*5+1):
    		if (not i % 3) or (not i % 5):
    			first_numbers.append(i)
    	wheel = []
    	for i in range(1,len(first_numbers)):
    		wheel.append(first_numbers[i] - first_numbers[i-1])
    	result = 0
    	idx = 0
    	len_wheel = len(wheel) #no need to copute it each iteration
    	number_mod3_or_mod5 = 0
    	while number_mod3_or_mod5 < up_until:
    		result += number_mod3_or_mod5
    		number_mod3_or_mod5 += wheel[idx]
    		idx = (idx + 1) % len_wheel
    	return result
    
    # Math, sum(1/2(n*(n+1)) * k) where n = #k < up_until, for k in 3,5 minus 15
    def solve_plain_math(up_until):
    	num_3 = (up_until-1) / 3 
    	x = (num_3 * (num_3+1))/2
    	num_5 = (up_until-1) / 5 
    	y = (num_5 * (num_5+1))/2
    	num_15 = (up_until-1) / 15 
    	z = (num_15 * (num_15+1))/2
    	return x*3 + y*5 - z*15
    
    # iterate through each solve methods dynamically (Python rocks :) !!)
    for method in [method for method in dir() if method.startswith("solve_")]:
    	print "\nRunning method:", method
    	start_time = time.time()
    	up_until = 1000
    	print locals()[method](up_until)
    	print "Run time (s):", time.time() - start_time
    
  3. Rutger said

    Above code outputs for n = 1000:

    Running method: solve_brute_force
    233168
    Run time (s): 0.0

    Running method: solve_plain_math
    233168
    Run time (s): 0.0

    Running method: solve_wheel_multiples
    233168
    Run time (s): 0.0

    ——————————————————–

    For n = 10000000:

    Running method: solve_brute_force
    23333331666668
    Run time (s): 1.47399997711

    Running method: solve_plain_math
    23333331666668
    Run time (s): 0.0

    Running method: solve_wheel_multiples
    23333331666668
    Run time (s): 0.986999988556

  4. Paul said
    def euler1a(): # simple
        return sum(i for i in range(1000) if i % 3 == 0 or i % 5 == 0)
    
    def euler1b(): # with sieve
        sieve = [0] * 1000
        sieve[3::3] = [1] * len(sieve[3::3])
        sieve[5::5] = [1] * len(sieve[5::5])
        return sum(i for i, s in enumerate(sieve) if s)
            
    def euler1c(): # with Gaussian sum
        def sumg(start, stop, inc):
            n = (stop - start) // inc + 1
            return n * start + inc * n * (n - 1) // 2
        return sumg(3, 999, 3) + sumg(5, 999, 5) - sumg(15, 999, 15)
    
  5. mcmillhj said

    Similar solution using Gauss’s summation formula in SML:

    fun sumMultiples3and5LessThanN n =
        let fun gaussian n = (n * (n + 1)) div 2
        in
                3 * gaussian(n div 3)
            +  5 * gaussian(n div 5)
            - 15 * gaussian(n div 15)
        end
    
  6. Jussi Piitulainen said

    Only two ways but they are more different. I suppose the sampling method
    is O(sample size) space, while the gambling method is O(1) space, but the
    sample size can be considered a constant. These count 0 as a multiple.

    import random
    
    def sampling(three = 3, five = 5, thousand = 1000, size = 500):
        sample = random.sample(range(thousand + 1), size)
        count = sum(1 for m in sample if (m % three == 0 or m % five == 0))
        return (count / size) * thousand
    
    def gambling(three = 3, five = 5, thousand = 1000, size = 500):
        count = sum(1 for m in ( random.randrange(thousand + 1)
                                 for _ in range(size) )
                    if (m % three == 0 or m % five == 0))
        return (count / size) * thousand
    
    if __name__ == '__main__':
        print('science says', sorted((sampling() for _ in range(11)))[5])
        print('gambler says', sorted((gambling() for _ in range(11)))[5])
    

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