Two part question:
Trying to determine the largest prime factor of 600851475143, I found this program online that seems to work. The problem is, I'm having a hard time figuring out how it works exactly, though I understand the basics of what the program is doing. Also, I'd like if you could shed some light on any method you may know of finding prime factors, perhaps without testing every number, and how your method works.
Here's the code that I found online for prime factorization [NOTE: This code is incorrect. See Stefan's answer below for better code.]:
n = 600851475143
i = 2
while i * i < n:
while n % i == 0:
n = n / i
i = i + 1
print(n)
#takes about ~0.01secs
Why is that code so much faster than this code, which is just to test the speed and has no real purpose other than that?
i = 1
while i < 100:
i += 1
#takes about ~3secs
This question was the first link that popped up when I googled "python prime factorization".
As pointed out by #quangpn88, this algorithm is wrong (!) for perfect squares such as n = 4, 9, 16, ... However, #quangpn88's fix does not work either, since it will yield incorrect results if the largest prime factor occurs 3 or more times, e.g., n = 2*2*2 = 8 or n = 2*3*3*3 = 54.
I believe a correct, brute-force algorithm in Python is:
def largest_prime_factor(n):
i = 2
while i * i <= n:
if n % i:
i += 1
else:
n //= i
return n
Don't use this in performance code, but it's OK for quick tests with moderately large numbers:
In [1]: %timeit largest_prime_factor(600851475143)
1000 loops, best of 3: 388 µs per loop
If the complete prime factorization is sought, this is the brute-force algorithm:
def prime_factors(n):
i = 2
factors = []
while i * i <= n:
if n % i:
i += 1
else:
n //= i
factors.append(i)
if n > 1:
factors.append(n)
return factors
Ok. So you said you understand the basics, but you're not sure EXACTLY how it works. First of all, this is a great answer to the Project Euler question it stems from. I've done a lot of research into this problem and this is by far the simplest response.
For the purpose of explanation, I'll let n = 20. To run the real Project Euler problem, let n = 600851475143.
n = 20
i = 2
while i * i < n:
while n%i == 0:
n = n / i
i = i + 1
print (n)
This explanation uses two while loops. The biggest thing to remember about while loops is that they run until they are no longer true.
The outer loop states that while i * i isn't greater than n (because the largest prime factor will never be larger than the square root of n), add 1 to i after the inner loop runs.
The inner loop states that while i divides evenly into n, replace n with n divided by i. This loop runs continuously until it is no longer true. For n=20 and i=2, n is replaced by 10, then again by 5. Because 2 doesn't evenly divide into 5, the loop stops with n=5 and the outer loop finishes, producing i+1=3.
Finally, because 3 squared is greater than 5, the outer loop is no longer true and prints the result of n.
Thanks for posting this. I looked at the code forever before realizing how exactly it worked. Hopefully, this is what you're looking for in a response. If not, let me know and I can explain further.
It looks like people are doing the Project Euler thing where you code the solution yourself. For everyone else who wants to get work done, there's the primefac module which does very large numbers very quickly:
#!python
import primefac
import sys
n = int( sys.argv[1] )
factors = list( primefac.primefac(n) )
print '\n'.join(map(str, factors))
For prime number generation I always use the Sieve of Eratosthenes:
def primes(n):
if n<=2:
return []
sieve=[True]*(n+1)
for x in range(3,int(n**0.5)+1,2):
for y in range(3,(n//x)+1,2):
sieve[(x*y)]=False
return [2]+[i for i in range(3,n,2) if sieve[i]]
In [42]: %timeit primes(10**5)
10 loops, best of 3: 60.4 ms per loop
In [43]: %timeit primes(10**6)
1 loops, best of 3: 1.01 s per loop
You can use Miller-Rabin primality test to check whether a number is prime or not. You can find its Python implementations here.
Always use timeit module to time your code, the 2nd one takes just 15us:
def func():
n = 600851475143
i = 2
while i * i < n:
while n % i == 0:
n = n / i
i = i + 1
In [19]: %timeit func()
1000 loops, best of 3: 1.35 ms per loop
def func():
i=1
while i<100:i+=1
....:
In [21]: %timeit func()
10000 loops, best of 3: 15.3 us per loop
If you are looking for pre-written code that is well maintained, use the function sympy.ntheory.primefactors from SymPy.
It returns a sorted list of prime factors of n.
>>> from sympy.ntheory import primefactors
>>> primefactors(6008)
[2, 751]
Pass the list to max() to get the biggest prime factor: max(primefactors(6008))
In case you want the prime factors of n and also the multiplicities of each of them, use sympy.ntheory.factorint.
Given a positive integer n, factorint(n) returns a dict containing the
prime factors of n as keys and their respective multiplicities as
values.
>>> from sympy.ntheory import factorint
>>> factorint(6008) # 6008 = (2**3) * (751**1)
{2: 3, 751: 1}
The code is tested against Python 3.6.9 and SymPy 1.1.1.
"""
The prime factors of 13195 are 5, 7, 13 and 29.
What is the largest prime factor of the number 600851475143 ?
"""
from sympy import primefactors
print(primefactors(600851475143)[-1])
def find_prime_facs(n):
list_of_factors=[]
i=2
while n>1:
if n%i==0:
list_of_factors.append(i)
n=n/i
i=i-1
i+=1
return list_of_factors
Isn't largest prime factor of 27 is 3 ??
The above code might be fastest,but it fails on 27 right ?
27 = 3*3*3
The above code returns 1
As far as I know.....1 is neither prime nor composite
I think, this is the better code
def prime_factors(n):
factors=[]
d=2
while(d*d<=n):
while(n>1):
while n%d==0:
factors.append(d)
n=n/d
d+=1
return factors[-1]
Another way of doing this:
import sys
n = int(sys.argv[1])
result = []
for i in xrange(2,n):
while n % i == 0:
#print i,"|",n
n = n/i
result.append(i)
if n == 1:
break
if n > 1: result.append(n)
print result
sample output :
python test.py 68
[2, 2, 17]
The code is wrong with 100. It should check case i * i = n:
I think it should be:
while i * i <= n:
if i * i = n:
n = i
break
while n%i == 0:
n = n / i
i = i + 1
print (n)
My code:
# METHOD: PRIME FACTORS
def prime_factors(n):
'''PRIME FACTORS: generates a list of prime factors for the number given
RETURNS: number(being factored), list(prime factors), count(how many loops to find factors, for optimization)
'''
num = n #number at the end
count = 0 #optimization (to count iterations)
index = 0 #index (to test)
t = [2, 3, 5, 7] #list (to test)
f = [] #prime factors list
while t[index] ** 2 <= n:
count += 1 #increment (how many loops to find factors)
if len(t) == (index + 1):
t.append(t[-2] + 6) #extend test list (as much as needed) [2, 3, 5, 7, 11, 13...]
if n % t[index]: #if 0 does else (otherwise increments, or try next t[index])
index += 1 #increment index
else:
n = n // t[index] #drop max number we are testing... (this should drastically shorten the loops)
f.append(t[index]) #append factor to list
if n > 1:
f.append(n) #add last factor...
return num, f, f'count optimization: {count}'
Which I compared to the code with the most votes, which was very fast
def prime_factors2(n):
i = 2
factors = []
count = 0 #added to test optimization
while i * i <= n:
count += 1 #added to test optimization
if n % i:
i += 1
else:
n //= i
factors.append(i)
if n > 1:
factors.append(n)
return factors, f'count: {count}' #print with (count added)
TESTING, (note, I added a COUNT in each loop to test the optimization)
# >>> prime_factors2(600851475143)
# ([71, 839, 1471, 6857], 'count: 1472')
# >>> prime_factors(600851475143)
# (600851475143, [71, 839, 1471, 6857], 'count optimization: 494')
I figure this code could be modified easily to get the (largest factor) or whatever else is needed. I'm open to any questions, my goal is to improve this much more as well for larger primes and factors.
In case you want to use numpy here's a way to create an array of all primes not greater than n:
[ i for i in np.arange(2,n+1) if 0 not in np.array([i] * (i-2) ) % np.arange(2,i)]
Check this out, it might help you a bit in your understanding.
#program to find the prime factors of a given number
import sympy as smp
try:
number = int(input('Enter a number : '))
except(ValueError) :
print('Please enter an integer !')
num = number
prime_factors = []
if smp.isprime(number) :
prime_factors.append(number)
else :
for i in range(2, int(number/2) + 1) :
"""while figuring out prime factors of a given number, n
keep in mind that a number can itself be prime or if not,
then all its prime factors will be less than or equal to its int(n/2 + 1)"""
if smp.isprime(i) and number % i == 0 :
while(number % i == 0) :
prime_factors.append(i)
number = number / i
print('prime factors of ' + str(num) + ' - ')
for i in prime_factors :
print(i, end = ' ')
This is my python code:
it has a fast check for primes and checks from highest to lowest the prime factors.
You have to stop if no new numbers came out. (Any ideas on this?)
import math
def is_prime_v3(n):
""" Return 'true' if n is a prime number, 'False' otherwise """
if n == 1:
return False
if n > 2 and n % 2 == 0:
return False
max_divisor = math.floor(math.sqrt(n))
for d in range(3, 1 + max_divisor, 2):
if n % d == 0:
return False
return True
number = <Number>
for i in range(1,math.floor(number/2)):
if is_prime_v3(i):
if number % i == 0:
print("Found: {} with factor {}".format(number / i, i))
The answer for the initial question arrives in a fraction of a second.
Below are two ways to generate prime factors of given number efficiently:
from math import sqrt
def prime_factors(num):
'''
This function collectes all prime factors of given number and prints them.
'''
prime_factors_list = []
while num % 2 == 0:
prime_factors_list.append(2)
num /= 2
for i in range(3, int(sqrt(num))+1, 2):
if num % i == 0:
prime_factors_list.append(i)
num /= i
if num > 2:
prime_factors_list.append(int(num))
print(sorted(prime_factors_list))
val = int(input('Enter number:'))
prime_factors(val)
def prime_factors_generator(num):
'''
This function creates a generator for prime factors of given number and generates the factors until user asks for them.
It handles StopIteration if generator exhausted.
'''
while num % 2 == 0:
yield 2
num /= 2
for i in range(3, int(sqrt(num))+1, 2):
if num % i == 0:
yield i
num /= i
if num > 2:
yield int(num)
val = int(input('Enter number:'))
prime_gen = prime_factors_generator(val)
while True:
try:
print(next(prime_gen))
except StopIteration:
print('Generator exhausted...')
break
else:
flag = input('Do you want next prime factor ? "y" or "n":')
if flag == 'y':
continue
elif flag == 'n':
break
else:
print('Please try again and enter a correct choice i.e. either y or n')
Since nobody has been trying to hack this with old nice reduce method, I'm going to take this occupation. This method isn't flexible for problems like this because it performs loop of repeated actions over array of arguments and there's no way how to interrupt this loop by default. The door open after we have implemented our own interupted reduce for interrupted loops like this:
from functools import reduce
def inner_func(func, cond, x, y):
res = func(x, y)
if not cond(res):
raise StopIteration(x, y)
return res
def ireducewhile(func, cond, iterable):
# generates intermediary results of args while reducing
iterable = iter(iterable)
x = next(iterable)
yield x
for y in iterable:
try:
x = inner_func(func, cond, x, y)
except StopIteration:
break
yield x
After that we are able to use some func that is the same as an input of standard Python reduce method. Let this func be defined in a following way:
def division(c):
num, start = c
for i in range(start, int(num**0.5)+1):
if num % i == 0:
return (num//i, i)
return None
Assuming we want to factor a number 600851475143, an expected output of this function after repeated use of this function should be this:
(600851475143, 2) -> (8462696833 -> 71), (10086647 -> 839), (6857, 1471) -> None
The first item of tuple is a number that division method takes and tries to divide by the smallest divisor starting from second item and finishing with square root of this number. If no divisor exists, None is returned.
Now we need to start with iterator defined like this:
def gener(prime):
# returns and infinite generator (600851475143, 2), 0, 0, 0...
yield (prime, 2)
while True:
yield 0
Finally, the result of looping is:
result = list(ireducewhile(lambda x,y: div(x), lambda x: x is not None, iterable=gen(600851475143)))
#result: [(600851475143, 2), (8462696833, 71), (10086647, 839), (6857, 1471)]
And outputting prime divisors can be captured by:
if len(result) == 1: output = result[0][0]
else: output = list(map(lambda x: x[1], result[1:]))+[result[-1][0]]
#output: [2, 71, 839, 1471]
Note:
In order to make it more efficient, you might like to use pregenerated primes that lies in specific range instead of all the values of this range.
You shouldn't loop till the square root of the number! It may be right some times, but not always!
Largest prime factor of 10 is 5, which is bigger than the sqrt(10) (3.16, aprox).
Largest prime factor of 33 is 11, which is bigger than the sqrt(33) (5.5,74, aprox).
You're confusing this with the propriety which states that, if a number has a prime factor bigger than its sqrt, it has to have at least another one other prime factor smaller than its sqrt. So, with you want to test if a number is prime, you only need to test till its sqrt.
def prime(n):
for i in range(2,n):
if n%i==0:
return False
return True
def primefactors():
m=int(input('enter the number:'))
for i in range(2,m):
if (prime(i)):
if m%i==0:
print(i)
return print('end of it')
primefactors()
Another way that skips even numbers after 2 is handled:
def prime_factors(n):
factors = []
d = 2
step = 1
while d*d <= n:
while n>1:
while n%d == 0:
factors.append(d)
n = n/d
d += step
step = 2
return factors
import math
class Solution:
def countSquares(self, N):
list = []
count = 0
for i in range(1,(int)(math.sqrt(N))):
square = i ** 2
list.append(square)
count = count + 1
return count
I am trying to count the number of perfect squares that are less than a given 'N'.
For example, if N = 9, the output is 2. Because only 1 & 4 are the perfect squares present.
list(map(lambda x:x*x, range(1,1+int(math.sqrt(n-1)))))
I think this should do it.
math.ceil(math.sqrt(n)) - 1
math.sqrt will output the square root of the current number.
math.ceil converts that number into the next whole number.
- 1 gives you the previous whole number, which is also the (inclusive) count of whole numbers which can be squared to a number less than n.
If you need to get the list of the square roots instead of the count the modifications are simple.
list(range(1, math.ceil(math.sqrt(n))))
In this case - 1 doesn't need to be performed so range ends with the correct number.
count = 0
for i in range(1, X):
#...
count = count + 1
ends with count == X - 1. Therefore, you don't really need a loop. You also never actually use the list, so storing it will slow down the program further.
sq = math.sqrt(N)
if math.floor(sq) < sq <= math.ceil(sq):
return int(sq)
return int(sq) - 1
Try this:
import math
class Solution:
def countSquares(self, N):
n = math.floor(math.sqrt(N))
if n * n == N:
return n - 1
else:
return n
The following code contains a mistake that can trigger an infinite loop, I can not figure out how to get the second print statement to run, I am sure it is something simple to fix it, but just can't see it.
def smallest_prime_factor(x):
"""Returns the smallest prime number that is a divisor of x"""
# Start checking with 2, then move up one by one
n = 2
while n <= x:
if x % n == 0:
x += 1
return n
print(smallest_prime_factor(12)) # should be 2
print(smallest_prime_factor(15)) # should be 3
Instead of increasing value for x which is the number for which you are trying to find the smallest prime number factor, you need to increase n that is the factor. Also, if n divides x, then you need to return n else you need to increment the value of n outside the if block.
Try this code:
def smallest_prime_factor(x):
"""Returns the smallest prime number that is a divisor of x"""
# Start checking with 2, then move up one by one
n = 2
while n <= x:
if x % n == 0:
return n
n += 1
Also to optimize it more, you just need to run while loop till the square root of a number to find it's prime number factor, else the number itself is the prime factor.
So this is the optimized version of the above code:
def smallest_prime_factor(x):
"""Returns the smallest prime number that is a divisor of x"""
# Start checking with 2, then move up one by one
n = 2
while n*n <= x:
if x % n == 0:
return n
n += 1
return x
you get in an infinite loop because you do not change the value of n if the return condition it is not met, as you can see the return condition is met only if your number x is a multiple of 2, you have to change :
if x % n == 0:
x += 1
with:
while n <= x:
if x % n == 0:
return x
n += 1
to optimize your code you can search for a number prime n to divide x that is less than int(math.sqrt(x) + 1):
import math
def smallest_prime_factor(x):
"""Returns the smallest prime number that is a divisor of x"""
# Start checking with 2, then move up one by one
n = 2
max_n = int(math.sqrt(x) + 1)
while n < max_n:
if x % n == 0:
return n
n += 1
return x
even better you could use the Sieve of Eratosthenes to generate fast the prime numbers and test against your x:
# Sieve of Eratosthenes
# Code by David Eppstein, UC Irvine, 28 Feb 2002
# http://code.activestate.com/recipes/117119/
def gen_primes(y):
""" Generate an infinite sequence of prime numbers.
"""
# Maps composites to primes witnessing their compositeness.
# This is memory efficient, as the sieve is not "run forward"
# indefinitely, but only as long as required by the current
# number being tested.
#
D = {}
# The running integer that's checked for primeness
q = 2
while q < y:
if q not in D:
# q is a new prime.
# Yield it and mark its first multiple that isn't
# already marked in previous iterations
#
yield q
D[q * q] = [q]
else:
# q is composite. D[q] is the list of primes that
# divide it. Since we've reached q, we no longer
# need it in the map, but we'll mark the next
# multiples of its witnesses to prepare for larger
# numbers
#
for p in D[q]:
D.setdefault(p + q, []).append(p)
del D[q]
def smallest_prime_factor(x):
"""Returns the smallest prime number that is a divisor of x"""
# Start checking with 2, then move up one by one
return next((i for i in gen_primes(int(math.sqrt(x) + 1)) if x % i == 0), x)
This is my solution to Project Euler Problem 3. I have written this code for Project Euler but if I put in "49" i get "49". What seems to be the problem?
n = 600851475143
i = 2
while (i * i < n):
while (n % i == 0):
n = n / i
i = i + 1
print (n)
I'm assuming you meant set n = 49.
Your outer while loop checks the condition i * i < n, which is not true for i == 7, so the outer loop breaks as soon as it hits 7. Change the < to <=.
However, your code isn't correct in the first place-- perhaps something like this is what you meant?
n = 600851475143
i = 2
factors = []
while (i <= n):
while (n % i == 0):
n = n / i
factors.append(i)
i = i + 1
print factors
You're printing n you want to print i...
Probably the fastest way to solve it by finding all the prime factors and then return the max.
Brute force solution took me less then 1 sec
I'm assuming you mean n = 49.
Your code isn't right, but the error is small -- change the < to <= and it works for Project Euler #3.
The problem of the code not working for squares such as 49 still remains though. Here is a modified piece of code that should work for squares as well.
n = 49
i = 2
while i * i <= n:
while n % i == 0:
x = n
n = n / i
i = i + 1
if n == 1:
print x
else:
print n
finding factors of N only need to check upto √N.
First basic solution:-
value of N never change
find factors upto √N & store biggest factor.
from math import sqrt
ans = -1
n = input() #or directly put
for i in range(2,int(sqrt(n))+1):
while (n%i==0):
if i > ans:
ans = i
print(ans)
Little optimized solution:-
if we change value of N, it iterate less than previous method.
only need to check % (modulus) of N with primes.
if have prime numbers list, then check/iterate with that only
unless, ignoring even numbers check numbers like 9,15,21... is prime or not, is worthless so...
excluding 2 all prime is odd.
so after check N with 2, check N with only odd numbers.
find factors upto √N & store biggest factor.
when get factor, divide N until N no have that factor
find the next factor do same process, until N become 1 (no have any factors)
from math import sqrt
ans = 2
n = input() #or directly put
while (n%2 == 0):
n /= 2
i = 3
while n > 1:
while (n%i == 0):
ans = i
n /= i
i += 2
print(ans)
find prime factors and return largest obviously
from math import sqrt
def is_prime(n):
if n ==2:return True
if n<2:return False
if n%2==0:return False
for i in range(3,int(sqrt(n))+1,2):
if n%i == 0:
return False;
return True;
n = 600851475143
i = n
while(i>1):
if is_prime(i) and is_prime(i) and n%i==0:
print(i);
break
i = i-1;
Your code is written assuming there are more than one factor, but in the case of n=49, it turns out that it has only one factor that is 7. So you can add a line checking whether it has more than one factor, or if not then it should be printed.
I'm trying to solve the 12th problem on Project Euler. I can calculate the number that has over 500 divisors in almost 4 minutes. How can i make it faster? Here's the attempt;
import time
def main():
memo={0:0,1:1}
i=2
n=200
while(1):
if len(getD(getT(i)))>n:
break
i+=1
print(getT(i))
#returns the nth triangle number
def getT(n):
if not n in memo:
memo[n]=n+getT(n-1)
return memo[n]
#returns the list of the divisors
def getD(n):
divisors=[n]
for i in xrange(1,int((n/2)+1)):
if (n/float(i))%1==0:
divisors.append(i)
return divisors
startTime=time.time()
main()
print(time.time()-startTime)
You don't need an array to store the triangle numbers. You can use a single int because you are checking only one value. Also, it might help to use the triangle number formula:n*(n+1)/2 where you find the nth triangle number.
getD also only needs to return a single number, as you are just looking for 500 divisors, not the values of the divisors.
However, your real problem lies in the n/2 in the for loop. By checking factor pairs, you can use sqrt(n). So only check values up to sqrt(n). If you check up to n/2, you get a very large number of wasted tests (in the millions).
So you want to do the following (n is the integer to find number of divisors of, d is possible divisor):
make sure n/d has no remainder.
determine whether to add 1 or 2 to your number of divisors.
Using a decorator (courtesy of activestate recipes) to save previously calculated values, and using a list comprehension to generate the devisors:
def memodict(f):
""" Memoization decorator for a function taking a single argument """
class memodict(dict):
def __missing__(self, key):
ret = self[key] = f(key)
return ret
return memodict().__getitem__
#memodict
def trinumdiv(n):
'''Return the number of divisors of the n-th triangle number'''
numbers = range(1,n+1)
total = sum(numbers)
return len([j for j in range(1,total+1) if total % j == 0])
def main():
nums = range(100000)
for n in nums:
if trinumdiv(n) > 200:
print n
break
Results:
In [1]: %cpaste
Pasting code; enter '--' alone on the line to stop or use Ctrl-D.
:def main():
: nums = range(10000)
: for n in nums:
: if trinumdiv(n) > 100:
: print 'Found:', n
: break
:
:startTime=time.time()
:main()
:print(time.time()-startTime)
:--
Found: 384
1.34229898453
and
In [2]: %cpaste
Pasting code; enter '--' alone on the line to stop or use Ctrl-D.
:def main():
: nums = range(10000)
: for n in nums:
: if trinumdiv(n) > 200:
: print 'Found:', n
: break
:
:startTime=time.time()
:main()
:print(time.time()-startTime)
:--
Found: 2015
220.681169033
A few comments.
As Quincunx writes, you only need to check the integer range from 1..sqrt(n) which would translate into something like this for i in xrange(1, sqrt(n) + 1): .... This optimization alone vastly speeds up things.
You can use the triangle number formula (which I didn't know until just now, thank you Quincunx), or you can use another approach for finding the triangle numbers than recursion and dictionary lookups. You only need the next number in the sequence, so there is no point in saving it. Function calls involves significant overhead in Python, so recursion is usually not recommended for number crunching. Also, why the cast to float, I didn't quite get that ?
I see that you are already using xrange instead of range to build the int stream. I assume you know that xrange is faster because it is implemented as a generator function. You can do that too. This makes things a lot smoother as well.
I've tried to do just that, use generators, and the code below finds the 500th triangle number in ~16sec on my machine (YMMV). But I've also used a neat trick to find the divisors, which is the quadratic sieve.
Here is my code:
def triangle_num_generator():
""" return the next triangle number on each call
Nth triangle number is defined as SUM([1...N]) """
n = 1
s = 0
while 1:
s += n
n += 1
yield s
def triangle_num_naive(n):
""" return the nth triangle number using the triangle generator """
tgen = triangle_num_generator()
ret = 0
for i in range(n):
ret = tgen.next()
return ret
def divisor_gen(n):
""" finds divisors by using a quadrativ sieve """
divisors = []
# search from 1..sqrt(n)
for i in xrange(1, int(n**0.5) + 1):
if n % i is 0:
yield i
if i is not n / i:
divisors.insert(0, n / i)
for div in divisors:
yield div
def divisors(n):
return [d for d in divisor_gen(n)]
num_divs = 0
i = 1
while num_divs < 500:
i += 1
tnum = triangle_num_naive(i)
divs = divisors(tnum)
num_divs = len(divs)
print tnum # 76576500
Running it produces the following output on my humble machine:
morten#laptop:~/documents/project_euler$ time python pr012.py
76576500
real 0m16.584s
user 0m16.521s
sys 0m0.016s
Using the triangle formula instead of the naive approach:
real 0m3.437s
user 0m3.424s
sys 0m0.000s
I made a code for the same task. It is fairly fast. I used a very fast factor-finding algorithm to find the factors of the number. I also used (n^2 + n)/2 to find the triangle numbers. Here is the code:
from functools import reduce
import time
start = time.time()
n = 1
list_divs = []
while len(list_divs) < 500:
tri_n = (n*n+n)/2 # Generates the triangle number T(n)
list_divs = list(set(reduce(list.__add__,([i, int(tri_n//i)] for i in range(1, int(pow(tri_n, 0.5) + 1)) if tri_n % i == 0)))) # this is the factor generator for any number n
n+=1
print(tri_n, time.time() - start)
It completes the job in 15 seconds on an OK computer.
Here is my answer which solves in about 3 seconds. I think it could be made faster by keeping track of the divisors or generating a prime list to use as divisors... but 3 seconds was quick enough for me.
import time
def numdivisors(triangle):
factors = 0
for i in range(1, int((triangle ** 0.5)) + 1):
if triangle % i == 0:
factors += 1
return factors * 2
def maxtriangledivisors(max):
i = 1
triangle = 0
while i > 0:
triangle += i
if numdivisors(triangle) >= max:
print 'it was found number', triangle,'triangle', i, 'with total of ', numdivisors(triangle), 'factors'
return triangle
i += 1
startTime=time.time()
maxtriangledivisors(500)
print(time.time()-startTime)
Here is another solution to the problem.In this i use Sieve of Eratosthenes to find the primes then doing prime factorisation.
Applying the below formula to calculate number of factors of a number:
total number of factors=(n+1)*(m+1).....
where number=2^n*3^n.......
My best time is 1.9 seconds.
from time import time
t=time()
a=[0]*100
c=0
for i in range(2,100):
if a[i]==0:
for j in range(i*i,100,i):
continue
a[c]=i
c=c+1
print(a)
n=1
ctr=0
while(ctr<=1000):
ctr=1
triang=n*(n+1)/2
x=triang
i=0
n=n+1
while(a[i]<=x):
b=1
while(x%a[i]==0):
b=b+1
x=x//a[i];
i=i+1
ctr=ctr*b
print(triang)
print("took time",time()-t)