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Check if a number can be formed by sum of a number and its reverse

I want to check if a given number can be formed by another number say b and reverse(b). For example 12 == 6+6, 22 == 11 + 11 and 121 == 29+92. One thing I have figured out is if the number is multiple of 11 or it is an even number less than 20, then it can be formed. I tried to implement this below:
num = 121
if num%11==0:
print('Yes')
else:
if num%2==0 and num<20:
print('Yes')
else:
for j in range(11,(int(num)//2)+1):
if j+int(str(j)[::-1])==num:
print('Yes')
break
However, if the condition goes into the for loop, it gives TLE. Can any other conditions be given?
Update: If the reversed number has trailing zeroes, it should be removed and then added. For example: 101 == 100+1. I am looking for an optimized form of my code. Or I think I am missing some conditions which can take O(1) time, similar to the condition if num%11==0: print('Yes')

All the previous answers are not really a check. It's more a brute force try and error.
So let's do it a little bit smarter.
We start with a number, for example 246808642. we can reduce the problem to the outer 2 place values at the end and start of the number. Let us call this values A and B at the front and Y and Z on the back. the rest, in the middle, is Π. So our number looks now ABΠYZ with A = 2, B = 4, Π = 68086, Y = 4 and Z = 2. (one possible pair of numbers to sum up for this is 123404321). Is A equal to 1, this is only possible for a sum greater 10 (An assumption, but i guess it works, some proof would be nice!).
so if it is a one, we know that the second last number is one greater by the carry over. So we ignore A for the moment and compare B to Z, because they should be the same because both are the result of the addition of the same two numbers. if so, we take the remaining part Π and reduce Y by one (the carry over from the outer addition), and can start again at the top of this chart with Π(Y-1). Only a carry over can make B one bigger than Z, if it's so, we can replace B by one and start with 1Π(Y-1) at the top. B-1!=Z and B!=Z, we can stop, this isnt possible for such a number which is the sum of a number and its reversed.
If A != 1, we do everything similiar as before but now we use A instead of B. (I cut this here. The answer is long enough.)
The code:
import time
def timing(f):
def wrap(*args, **kwargs):
time1 = time.time()
ret = f(*args, **kwargs)
time2 = time.time()
print('{:s} function took {:.3f} ms'.format(f.__name__, (time2-time1)*1000.0))
return ret
return wrap
#timing
def check(num):
num = str(num)
if (int(num) < 20 and int(num)%2 == 0) or (len(num) ==2 and int(num)%11 == 0):
return print('yes')
if len(num) <= 2 and int(num)%2 != 0:
return print('no')
# get the important place values of the number x
A = num[0]
B = num[1]
remaining = num[2:-2]
Y = num[-2]
Z = num[-1]
# check if A = 1
if A == '1':
# A = 1
# check if B == Z
if B == Z:
# so the outest addition matches perfectly and no carry over from inner place values is involved
# reduce the last digit about one and check again.
check(remaining + (str(int(Y)-1) if Y != '0' else '9'))
elif int(B)-1 == int(Z):
# so the outest addition matches needs a carry over from inner place values to match, so we add to
# to the remaining part of the number a leading one
# we modify the last digit of the remaining place values, because the outest had a carry over
check('1' + remaining + (str(int(Y)-1) if Y != '0' else '9'))
else:
print("Not able to formed by a sum of a number and its reversed.")
else:
# A != 1
# check if A == Z
if A == Z:
# so the outest addition matches perfectly and no carry over from inner place values is involved
check(B + remaining + Y)
elif int(A) - 1 == int(Z):
# so the outest addition matches needs a carry over from inner place values to match, so we add to
# to the remaining part of the number a leading one
# we modify the last digit of the remaining place values, because the outest had a carry over
check('1' + B + remaining + Y)
else:
print("Not able to formed by a sum of a number and its reversed.")
#timing
def loop_check(x):
for i in range(x + 1):
if i == int(str(x - i)[::-1]) and not str(x - i).endswith("0"):
print('yes, by brute force')
break
loop_check(246808642)
check(246808642)
Result:
yes, by brute force
loop_check function took 29209.069 ms
Yes
check function took 0.000 ms
And another time we see the power of math. Hope this work for you!

You can brute force it like this:
def reverse_digits(n):
return int(str(n)[::-1])
def sum_of_reversed_numbers(num):
for i in range(num + 1):
if i == reverse_digits(num - i):
return i, num - i
return None
print("Yes" if sum_of_reversed_numbers(num) else "No")

Can you provide the constraints of the problem?
Here is something you can try:
i = 0
j = num
poss = 0
while(i<=j):
if(str(i)==str(j)[::-1]):
poss = 1
break
i+=1
j-=1
if(poss):
print("Yes")
else:
print("No")

You can do it without str slicing:
def reverse(n):
r = 0
while n != 0:
r = r*10 + int(n%10)
n = int(n/10)
return r
def f(n):
for i in range(n + 1):
if i + reverse(i) == n:
return True
return False
print('Yes' if f(101) else 'No')
#Yes

The basic idea of my solution is that you first generate a mapping of digits to the digits that could make them up, so 0 can be made by either 0+0 or 1+9, 2+8 etc. (but in that case there's a carried 1 you have to keep in mind on the next step). Then you start at the smallest digit, and use that code to check each possible way to form the first digit (this gives you candidates for the first and last digit of the number that sums with its reverse to give you the input number). Then you move on the second digit and try those. This code could be greatly improved by checking both the last and the first digit together, but it's complicated by the carried 1.
import math
candidates = {}
for a in range(10):
for b in range(10):
# a, b, carry
candidates.setdefault((a + b) % 10, []).append((a, b, (a + b) // 10))
def sum_of_reversed_numbers(num):
# We reverse the digits because Arabic numerals come from Arabic, which is
# written right-to-left, whereas English text and arrays are written left-to-right
digits = [int(d) for d in str(num)[::-1]]
# result, carry, digit_index
test_cases = [([None] * len(digits), 0, 0)]
if len(digits) > 1 and str(num).startswith("1"):
test_cases.append(([None] * (len(digits) - 1), 0, 0))
results = []
while test_cases:
result, carry, digit_index = test_cases.pop(0)
if None in result:
# % 10 because if the current digit is a 0 but we have a carry from
# the previous digit, it means that the result and its reverse need
# to actually sum to 9 here so that the +1 carry turns it into a 0
cur_digit = (digits[digit_index] - carry) % 10
for a, b, new_carry in candidates[cur_digit]:
new_result = result[::]
new_result[digit_index] = a
new_result[-(digit_index + 1)] = b
test_cases.append((new_result, new_carry, digit_index + 1))
else:
if result[-1] == 0 and num != 0: # forbid 050 + 050 == 100
continue
i = "".join(str(x) for x in result)
i, j = int(i), int(i[::-1])
if i + j == num:
results.append((min(i, j), max(i, j)))
return results if results else None
We can check the above code by pre-calculating the sums of all numbers from 0 to 10ⁿ and their reverse and storing them in a dict of lists called correct (a list because there's many ways to form the same number, eg. 11+11 == 02 + 20), which means we have the correct answers for 10ⁿ⁻¹ we can use to check the above function. Btw, if you're doing this a lot with small numbers, this pre-calculating approach is faster at the expense of memory.
If this code prints nothing it means it works (or your terminal is broken :) )
correct = {}
for num in range(1000000):
backwards = int(str(num)[::-1])
components = min(num, backwards), max(num, backwards)
summed = num + backwards
correct.setdefault(summed, []).append(components)
for i in range(100000):
try:
test = sum_of_reversed_numbers(i)
except Exception as e:
raise Exception(i) from e
if test is None:
if i in correct:
print(i, test, correct.get(i))
elif sorted(test) != sorted(correct[i]):
print(i, test, correct.get(i))

Stole the idea from #Doluk. I was asked this question in a test today. I couldn't solve it then. With Doluk's idea and thinking seriously on it below is a decision tree kind for one level of recursion. I might be wrong as I haven't ran this algorithm.
Let n be the number, we want to check if special
case 1: leading number is not 1
case 1a: no carry over from inner addition
abcdefgh
hgfedcba
x x => (a+h) < 10
if both ends are same in n, strip both sides by one digit and recurse
case 1b: carry over from inner addition
1
abcdefgh
hgfedcba
(x+1)......(x) => (a+h+1) < 10
if left end is 1 greater than right end in n, strip both sides by one digit, add digit 1 on the left and recurse
case 2: leading number is 1
case 2a: no carry over from inner addition
1 1
abcdefgh
hgfedcba
1x x => (a+h) >= 10
strip - if second and last digit are same, strip two digits from left and one from right, from the remaining number minus 1 and recurse.
case 2b: carry over from inner addition
case 2bi: a+h = 9
11
abcdefgh
hgfedcba
10......9
strip - two from left and one from right and recurse.
case 2bj: a+h >= 10
11 1
abcdefgh
hgfedcba
1(x+1)......x
strip - two from left and one from right and subtract 1 from number and recurse.

In my question, they gave me an array of numbers and they asked me to find numbers which of them are special (Which can be formed by the sum and reverse of that number).
My brute force solution was to iterate from 0 to 1000000 and insert them into the set and last check for each element in the set.
Time Complexity: O(n)
Space Complexity: O(n)
where n is the highest number allowed.

How to avoid lists when analyzing order for palindromes?

Just want to apologize in advance for the general coding and logic gore you might encounter while reading this. I recently discovered Project Euler and thought it was fun. I've made it a point to not only find the answer, but make a generic function that could find the answer for any similar case given the appropriate input. For instance, problem number 4, involving palindromes, which can be seen here: https://projecteuler.net/problem=4
Essentially what I did was found a way to multiply every possible combination of numbers given a number of digits, n, then found products that were palindromes. However, anything above 3 digits just takes way too long to process. I believe this is because I used the list() function to take advantage of indexing to determine whether the product was a palindrome. Is there another way to do something of this nature? I feel like this is shoving a square through a circular hole.
Here's the function in question.
def palindrome(n):
number = 0
for i in range(0,n):
number = number + 9 * pow(10, i)
a = pow(10, n - 1) - 1
b = pow(10, n - 1)
while a * b < number * number:
a = a + 1
b = a
while b <= number:
c = a * b
b = b + 1
digits = list(str(int(c)))
lastdigits = digits[::-1]
numdigits = len(digits)
middle = int((numdigits - (numdigits % 2)) / 2) - 1
if numdigits > 1 and digits[:middle + 1] == lastdigits[:middle + 1] and digits[0] == digits[-1] == '9' and numdigits == 2 * n:
print(c)

"Find the largest palindrome made from the product of two 3-digit numbers."
3-digit numbers would be anything from 100 - 999. One thing about the largest product is guaranteed: The two operands must be as large as possible.
Thus, it would make sense to step through a loop starting from the largest number (999) to the smallest (100). We can append palindromes to a list and then later return the largest one.
When you calculate a product, convert it to a string using str(...). Now, checking for palindromes is easy thanks to python's string splicing. A string is a palindrome if string == string[::-1], where string[::-1] does nothing but return a reversed copy of the original.
Implementing these strategies, we have:
def getBiggestPalindrome():
max_palindrome = -1
for i in range(999, 99, -1):
for j in range(999, i - 1, -1):
prod = i * j
str_prod = str(prod)
if str_prod == str_prod[::-1] and prod > max_palindrome:
print(prod)
max_palindrome = prod
return max_palindrome
getBiggestPalindrome()
And, this returns
>>> getBiggestPalindrome()
906609
Note that you can use the range function to generate values from start, to end, with step. The iteration stops just before end, meaning the last value would be 100.

Efficient algorithm to find the count of numbers that are divisible by a number without a remainder in a range

Let's say I have two numbers: 6 and 11 and I am trying to find how many numbers between this range are divisible by 2 (3, in this case).
I have this simple code right now:
def get_count(a, b, m):
count = 0
for i in range(a, b + 1):
if i % m == 0:
count += 1
return count
Its order of growth is linear, O(N), I believe.
I was wondering if there is a faster algorithm with a constant O(1) performance, or a mathematical formula.
I don't expect a direct answer. The name of such an algorithm would be awesome.
Thank you.

((b - b%m) - a)//m+1 seems to work for me. I doubt it has a name. Another formula that seems to work is (b//m) - ((a-1)//m).
Sample python3 program:
def get_count(a, b, m):
return (((b - (b % m)) - a) // m) + 1
for i in range(5, 8):
for j in range(10, 13):
print(get_count(i, j, 2), end=" ")
print()

You are counting even numbers. Let's write o for odd, E for even.
If the sequence has an even count of numbers, it is either oEoE...oE or EoEo...Eo, i.e. one half of numbers is always even. If there is odd count of numbers, you can check the first number (or last one) separately and the rest is the known case discussed first.
def count_even(start, end):
# assert start <= end
len = end - start
len2, r = divmod(len, 2)
if r and start % 2 == 0:
len2 += 1
return len2

To find the count of all numbers between 0 and n that are divisible by two. you can use the bitwise operation called right shift;
c = a >> 1;
10 >> 1 is equivalent to floor(10/2)
You can subtract the two resultant numbers and get numbers between any range.
This will work in O(1). Hope this helps.

Equal or higher multiple of a number, Python

I have been challenged with designing a code which validates a GTIN-8 code. I have looked on how to find the equal or higher multiple of a 10 and I have had no success so far, hope you guys can help me!
Here is a small piece of code, I need to find the equal or higher multiple of 10.
NewNumber = (NewGtin_1 + Gtin_2 + NewGtin_3 + Gtin_4 + NewGtin_5 + Gtin_6 + NewGtin_7)
print (NewNumber)

If you mean find the smallest multiple of 10 that is greater than or equal to your number, try
def round_up_by_10s(num):
return -((-num) // 10) * 10
That works for positive and negative numbers, integer or float, in Python 2.x or Python 3.x. It also avoids an if statement and can be written as a one-liner. For a float number it returns a float: surround the return value with an int(...) if you want the returned value to always be an integer.
If you mean find the smallest number that is a multiple of your number and of 10, try
def lcm10(num):
return (10 // gcd(num, 10)) * num

Generally speaking You can find multiples with the modulo operation:
if number % 10 == 0:
do something

I'm guessing you what the smallest multiple of 10 that is higher or equal than NewNumber. If that's the case, do:
last_digit = NewNumber % 10
bigger = NewNumber - last_digit
if last_digit != 0:
bigger += 10
Also, you shouldn't use capital letters to start variable names, those are usually used for classes only.

Trying using this:
# method 1 for integers
n = NewNumber / 10 * 10
if n < NewNumber: n += 10
# method 2 for floats, decimals
import math
n = math.ceil(NewNumber / 10) * 10

Project Euler 5 in Python - How can I optimize my solution?

I've recently been working on Project Euler problems in Python. I am fairly new to Python, and still somewhat new as a programmer.
In any case, I've ran into a speed-related issue coding a solution for problem #5. The problem is,
"2520 is the smallest number that can be divided by each of the numbers from 1 to 10 without any remainder. What is the smallest positive number that is evenly divisible by all of the numbers from 1 to 20?"
I've checked around some, and I haven't been able to find anything on this problem pertaining to Python specifically. There were some completed scripts, but I want to avoid looking at other's code in full, if possible, instead wanting to improve my own.
The code I have written runs successfully for the example of 2520 and the range 1 to 10, and should be directly modifiable to work with the question. However, upon running it, I do not get an answer. Presumably, it is a very high number, and the code is not fast enough. Printing the current number being checked seems to support this, reaching several million without getting an answer.
The code, in it's current implementation is as follows:
rangemax = 20
def div_check(n):
for i in xrange(11,rangemax+1):
if n % i == 0:
continue
else:
return False
return True
if __name__ == '__main__':
num = 2
while not div_check(num):
print num
num += 2
print num
I have already made a couple changes which I think should help the speed. For one, for a number to be divisible by all numbers 1 to 20, it must be even, as only even numbers are divisible by 2. Hence, I can increment by 2 instead of 1. Also, although I didn't think of it myself, I found someone point out that a number divisible by 11 to 20 is divisible by 1 to 10. (Haven't checked that one, but it seems reasonable)
The code still, however is not fast enough. What optimisations, either programmatic, or mathematics, can I make to make this code run faster?
Thanks in advance to any who can help.

Taking the advice of Michael Mior and poke, I wrote a solution. I tried to use a few tricks to make it fast.
Since we need a relatively short list of numbers tested, then we can pre-build the list of numbers rather than repeatedly calling xrange() or range().
Also, while it would work to just put the numbers [1, 2, 3, ..., 20] in the list, we can think a little bit, and pull numbers out:
Just take the 1 out. Every integer is evenly divisible by 1.
If we leave the 20 in, there is no need to leave the 2 in. Any integer evenly divisible by 20 is evenly divisible by 2 (but the reverse might not be true). So we leave the 20 and take out the 2, the 4, and the 5. Leave the 19, as it's prime. Leave the 18, but now we can take out the 3 and the 6. If you repeat this process, you wind up with a much shorter list of numbers to try.
We start at 20 and step numbers by 20, as Michael Mior suggested. We use a generator expression inside of all(), as poke suggested.
Instead of a while loop, I used a for loop with xrange(); I think this is slightly faster.
The result:
check_list = [11, 13, 14, 16, 17, 18, 19, 20]
def find_solution(step):
for num in xrange(step, 999999999, step):
if all(num % n == 0 for n in check_list):
return num
return None
if __name__ == '__main__':
solution = find_solution(20)
if solution is None:
print "No answer found"
else:
print "found an answer:", solution
On my computer, this finds an answer in under nine seconds.
EDIT:
And, if we take advice from David Zaslavsky, we realize we can start the loop at 2520, and step by 2520. If I do that, then on my computer I get the correct answer in about a tenth of a second.
I made find_solution() take an argument. Try calling find_solution(2520).

My first answer sped up the original calculation from the question.
Here's another answer that solves it a different way: just find all the prime factors of each number, then multiply them together to go straight to the answer. In other words, this automates the process recommended by poke in a comment.
It finishes in a fraction of a second. I don't think there is a faster way to do this.
I did a Google search on "find prime factors Python" and found this:
http://www.stealthcopter.com/blog/2009/11/python-factors-of-a-number/
From that I found a link to factor.py (written by Mike Hansen) with some useful functions:
https://gist.github.com/weakish/986782#file-factor-py
His functions didn't do quite what I wanted, so I wrote a new one but used his pull_prime_factors() to do the hard work. The result was find_prime_factors() which returns a list of tuples: a prime number, and a count. For example, find_prime_factors(400) returns [(2,4), (5,2)] because the prime factors of 400 are: (2*2*2*2)*(5*5)
Then I use a simple defaultdict() to keep track of how many we have seen so far of each prime factor.
Finally, a loop multiplies everything together.
from collections import defaultdict
from factor import pull_off_factors
pf = defaultdict(int)
_primes = [2,3,5,7,11,13,17,19,23,29]
def find_prime_factors(n):
lst = []
for p in _primes:
n = pull_off_factors(n, p, lst)
return lst
def find_solution(low, high):
for num in xrange(low, high+1):
lst = find_prime_factors(num)
for n, count in lst:
pf[n] = max(pf[n], count)
print "prime factors:", pf
solution = 1
for n, count in pf.items():
solution *= n**count
return solution
if __name__ == '__main__':
solution = find_solution(1, 20)
print "answer:", solution
EDIT: Oh wow, I just took a look at #J.F. Sebastian's answer to a related question. His answer does essentially the same thing as the above code, only far more simply and elegantly. And it is in fact faster than the above code.
Least common multiple for 3 or more numbers
I'll leave the above up, because I think the functions might have other uses in Project Euler. But here's the J.F. Sebastian solution:
def gcd(a, b):
"""Return greatest common divisor using Euclid's Algorithm."""
while b:
a, b = b, a % b
return a
def lcm(a, b):
"""Return lowest common multiple."""
return a * b // gcd(a, b)
def lcmm(*args):
"""Return lcm of args."""
return reduce(lcm, args)
def lcm_seq(seq):
"""Return lcm of sequence."""
return reduce(lcm, seq)
solution = lcm_seq(xrange(1,21))
print "lcm_seq():", solution
I added lcm_seq() but you could also call:
lcmm(*range(1, 21))

Since your answer must be divisible by 20, you can start at 20 and increment by 20 instead of by two. In general, you can start at rangemax and increment by rangemax. This reduces the number of times div_check is called by an order of magnitude.

Break down the number as a prime factorization.
All primes less than 20 are:
2,3,5,7,11,13,17,19
So the bare minimum number that can be divided by these numbers is:
2*3*5*7*11*13*17*19
Composites:
4,6,8,9,10,12,14,15,16,18,20 = 2^2, 2*3, 2^3, 3^2, 2*5, 2^2*3, 2*7, 3*5, 2*3^2, 2^2*5
Starting from the left to see which factors needed:
2^3 to build 4, 8, and 16
3 to build 9
Prime factorization: 2^4 * 3^2 * 5 * 7 * 11 * 13 * 17 * 19 = 232,792,560

I got the solution in 0.066 milliseconds (only 74 spins through a loop) using the following procedure:
Start with smallest multiple for 1, which = 1. Then find the smallest multiple for the next_number_up. Do this by adding the previous smallest multiple to itself (smallest_multiple = smallest_multiple + prev_prod) until next_number_up % smallest_multiple == 0. At this point smallest_multiple is the correct smallest multiple for next_number_up. Then increment next_number_up and repeat until you reach the desired smallest_multiple (in this case 20 times). I believe this finds the solution in roughly n*log(n) time (though, given the way numbers seem to work, it seems to complete much faster than that usually).
For example:
1 is the smallest multiple for 1
Find smallest multiple for 2
Check if previous smallest multiple works 1/2 = .5, so no
previous smallest multiple + previous smallest multiple == 2.
Check if 2 is divisible by 2 - yes, so 2 is the smallest multiple for 2
Find smallest multiple for 3
Check if previous smallest multiple works 2/3 = .667, so no
previous smallest multiple + previous smallest multiple == 4
Check if 4 is divisible by 3 - no
4 + previous smallest multiple == 6
Check if 6 is divisible by 3 - yes, so 6 is the smallest multiple for 3
Find smallest multiple for 4
Check if previous smallest multiple works 6/4 = 1.5, so no
previous smallest multiple + previous smallest multiple == 12
Check if 12 is divisble by 4 - yes, so 12 is the smallest multiple for 4
repeat until 20..
Below is code in ruby implementing this approach:
def smallestMultiple(top)
prod = 1
counter = 0
top.times do
counter += 1
prevprod = prod
while prod % counter != 0
prod = prod + prevprod
end
end
return prod
end

List comprehensions are faster than for loops.
Do something like this to check a number:
def get_divs(n):
divs = [x for x in range(1,20) if n % x == 0]
return divs
You can then check the length of the divs array to see if all the numbers are present.

Two different types of solutions have been posted here. One type uses gcd calculations; the other uses prime factorization. I'll propose a third type, which is based on the prime factorization approach, but is likely to be much faster than prime factorization itself. It relies on a few simple observations about prime powers -- prime numbers raised to some integral exponent. In short, it turns out that the least common multiple of all numbers below some number n is equal to the product of all maximal prime powers below n.
To prove this, we begin by thinking about the properties that x, the least common multiple of all numbers below n, must have, and expressing them in terms of prime powers.
x must be a multiple of all prime powers below n. This is obvious; say n = 20. 2, 2 * 2, 2 * 2 * 2, and 2 * 2 * 2 * 2 are all below 20, so they all must divide x. Likewise, 3 and 3 * 3 are both below n and so both must divide x.
If some number a is a multiple of the prime power p ** e, and p ** e is the maximal power of p below n, then a is also a multiple of all smaller prime powers of p. This is also quite obvious; if a == p * p * p, then a == (p * p) * p.
By the unique factorization theorem, any number m can be expressed as a multiple of prime powers less than m. If m is less than n, then m can be expressed as a multiple of prime powers less than n.
Taken together, the second two observations show that any number x that is a multiple of all maximal prime powers below n must be a common multiple of all numbers below n. By (2), if x is a multiple of all maximal prime powers below n, it is also a multiple of all prime powers below n. So by (3), it is also a multiple of all other numbers below n, since they can all be expressed as multiples of prime powers below n.
Finally, given (1), we can prove that x is also the least common multiple of all numbers below n, because any number less than x could not be a multiple of all maximal prime powers below n, and so could not satisfy (1).
The upshot of all this is that we don't need to factorize anything. We can just generate primes less than n!
Given a nicely optimized sieve of eratosthenes, one can do that very quickly for n below one million. Then all you have to do is find the maximal prime power below n for each prime, and multiply them together.
prime_powers = [get_max_prime_power(p, n) for p in sieve(n)]
result = reduce(operator.mul, prime_powers)
I'll leave writing get_max_prime_power as an exercise. A fast version, combined with the above, can generate the lcm of all numbers below 200000 in 3 seconds on my machine.
The result is a 86871-digit number!

This solution ran pretty quickly for me (imports numpy).
t0 = time.time()
import numpy
ints = numpy.array(range(1,21))
primes = [2,3,5,7,11,13,17,19] # under 20
facts = []
for p in primes:
counter = 0
nums = ints
while any(nums % p == 0):
nums = nums / float(p)
counter += 1
facts.append(counter)
facts = numpy.array(facts)
mults = primes**facts
ans = 1
for m in mults:
ans = m * ans
t1 =time.time()
perf = t1 - t0
print "Problem 5\nAnswer:",ans, "runtime:", perf, "seconds"
"""Problem 5
Answer: 232792560 runtime: 0.00505399703979 seconds"""

Here i have also done using prime factorization way.
#!/usr/bin/env python
import math
def is_prime(num):
if num > 1:
if num == 2:
return True
if num%2 == 0:
return False
for i in range(3, int(math.sqrt(num))+1, 2):
if num%i == 0:
return False
return True
return False
def lcm(number):
prime = []
lcm_value = 1
for i in range(2,number+1):
if is_prime(i):
prime.append(i)
final_value = []
for i in prime:
x = 1
while i**x < number:
x = x + 1
final_value.append(i**(x-1))
for j in final_value:
lcm_value = j * lcm_value
return lcm_value
if __name__ == '__main__':
print lcm(20)
After checking how much time it has taken, it was not bad at all.
root#l-g6z6152:~/learn/project_euler# time python lcm.py
232792560
real 0m0.019s
user 0m0.008s
sys 0m0.004s

I wrote a solution to euler5 that:
Is orders of magnitude faster than most of the solutions here when n=20 (though not all respondents report their time) because it uses no imports (other than to measure time for this answer) and only basic data structures in python.
Scales much better than most other solutions. It will give the answer for n=20 in 6e-05 seconds, or for n=100 in 1 millisec, faster than most of the responses for n=20 listed here.
import time
a=time.clock() # set timer
j=1
factorlist=[]
mydict={}
# change second number to desired number +1 if the question were changed.
for i in range(2,21,1):
numberfactors=[]
num=i
j=2
# build a list of the prime factors
for j in range(j,num+1,1):
counter=0
if i%j==0:
while i%j==0:
counter+=1
numberfactors.append(j)
i=i/j
# add a list of factors to a dictionary, with each prime factor as a key
if j not in mydict:
mydict[j] = counter
# now, if a factor is already present n times, including n times the factor
# won't increase the LCM. So replace the dictionary key with the max number of
# unique factors if and only if the number of times it appears is greater than
# the number of times it has already appeared.
# for example, the prime factors of 8 are 2,2, and 2. This would be replaced
# in the dictionary once 16 were found (prime factors 2,2,2, and 2).
elif mydict[j] < counter:
mydict[j]=counter
total=1
for key, value in mydict.iteritems():
key=int(key)
value=int(value)
total=total*(key**value)
b=time.clock()
elapsed_time=b-a
print total, "calculated in", elapsed_time, "seconds"
returns:
232792560 calculated in 6e-05 seconds
# does not rely on heuristics unknown to all users, for instance the idea that
# we only need to include numbers above 10, etc.
# For all numbers evenly divisible by 1 through 100:
69720375229712477164533808935312303556800 calculated in 0.001335 seconds

Here is program in C language. Cheers
#include <stdio.h>
#include <stdlib.h>
//2520 is the smallest number that can be divided by each of the numbers from 1 to 10 without any remainder.
//What is the smallest positive number that is evenly divisible by all of the numbers from 1 to 20?
bez_ost(int q)
{
register br=0;
for( register i=1;i<=20;i++)
if(q%i==0)
br++;
if(br==20)
return 1;
return 0;
}
int main()
{
register j=20;
register ind=0;
while(ind!=1)
{
j++;
if(bez_ost(j))
break;
}
fprintf(stdout,"\nSmallest positive number that is evenlu divisible by all of the numbers from 1 to 20 is: %d\n\a",j);
system("Pause");
}

I've had the same problem. The algorithm seems to be quite slow, but it does work nonetheless.
result = list()
xyz = [x for x in range(11, 21)]
number = [2520]
count = 0
while len(result) == 0:
for n in number:
print n
for x in xyz:
if n % x == 0:
count += 1
elif n % x != 0:
count = 0
break
if count == 10:
result.append(number[0])
elif count != 10:
number[0] += 1
print result
This was the algorithm I made.

How about this? The required number is, after all, the LCM of the given numbers.
def lcm(a,b):
lcm1 = 0
if a == b:
lcm1 = a
else:
if a > b:
greater = a
else:
greater = b
while True:
if greater % a == 0 and greater % b == 0:
lcm1 = greater
break
greater += 1
return lcm1
import time
start_time = time.time()
list_numbers = list(range(2,21))
lcm1 = lcm(list_numbers[0],list_numbers[1])
for i in range(2,len(list_numbers)):
lcm1 = lcm(lcm1,list_numbers[i])
print(lcm1)
print('%0.5f'%(time.time()-start_time))
This code took a full 45 s to get the answer to the actual question! Hope it helps.

import time
primes = [11,13,17,19]
composites = [12,14,15,16,18,20]
def evenlyDivisible(target):
evenly = True
for n in composites:
if target % n > 0:
evenly = False
break
return evenly
step = 1
for p in primes:
step *= p
end = False
number = 0
t1 = time.time()
while not end:
number += step
if evenlyDivisible(number):
end = True
print("Smallest positive evenly divisible number is",number)
t2 = time.time()
print("Time taken =",t2-t1)
Executed in 0.06 seconds

Here is my Python solution, it has 12 iteration so compiled quite fast:
smallest_num = 1
for i in range (1,21):
if smallest_num % i > 0: # If the number is not divisible by i
for k in range (1,21):
if (smallest_num * k) % i == 0: # Find the smallest number divisible by i
smallest_num = smallest_num * k
break
print (smallest_num)

Here's an observation on this problem. Ultimately, it takes 48 iterations to find the solution.
Any number that is divisible by all of the numbers from 1..20 must be divisible by the product of the primes in that range, namely 2, 3, 5, 7, 11, 13, 17, and 19. It cannot be smaller than the product of these primes, so let's use that number, 232,792,560, as the increment, rather than 20, or 2,520, or some other number.
As it turns out, 48 * 232,792,560 is divisible by all numbers 1..20. By the way, the product of all of the non-primes between 1..20 is 66. I haven't quite figured out the relationship between 48 and 66 in this context.

up = int(input('Upper limit: '))
number = list(range(1, up + 1))
n = 1
for i in range(1, up):
n = n * number[i]
for j in range(i):
if number[i] % number[j] == 0:
n = n / number[j]
number[i] = number[i] / number[j]
print(n)

How I can reduce the complexity of this
num = 1
found = False
while not found:
count =0
for i in range(1, 21):
if num %i == 0:
count+=1
if count ==10:
print(num)
found = True
num+=1

Here is the code in C++ to find the solution for this question.
What we have to do is to run a loop from 1 until we got that number so just iterate through the loop and once the number get evenly divisble(remainder 0) flag value dont get change and flag remains 1 and we got that number and break through outer loop and print the answer
#include <bits/stdc++.h>
using namespace std;
int main()
{
ios_base::sync_with_stdio(false);
cin.tie(NULL);
int i,j,flag=1;
for(i=1;;i++) //iterate until we got the number
{
flag=1;
for(j=2;j<=20;j++) //check form 1 to 20 for that number
{
if(i%j!=0) //if the number is not evenly divisible we break loop and
{
flag=0;break; // initilize flag as 0 i.e. that number is not what we want
}
}
if(flag==1) //if any number we got that is evenly divisible i.e. flag value doesnt change we got that number we break through the loop and print the answer
break;
} // after ending of the loop as we jump to next number make flag also 1 again so that again inner loop conditions apply on it
cout<<i;
return 0;
}

A typescript variant that seems to be relatively quick, leveraging recursion and known facts.
describe(`2520 is the smallest number that can be divided by each of the numbers from 1 to 10 without any remainder.
What is the smallest positive number that is evenly divisible by all of the numbers from 1 to 20?`,
() => {
it("prooves the example: 10", () => smallestWithoutRemainder(10).should.be.equal(2520));
it("prooves 1", () => smallestWithoutRemainder(1).should.be.equal(1));
it("prooves 2", () => smallestWithoutRemainder(2).should.be.equal(2));
it("prooves 3", () => smallestWithoutRemainder(3).should.be.equal(6));
it("prooves 4", () => smallestWithoutRemainder(4).should.be.equal(12));
it("prooves 5", () => smallestWithoutRemainder(5).should.be.equal(60));
it("prooves 6", () => smallestWithoutRemainder(6).should.be.equal(60));
it("prooves 7", () => smallestWithoutRemainder(7).should.be.equal(420));
it("prooves 8", () => smallestWithoutRemainder(8).should.be.equal(840));
it("prooves 9", () => smallestWithoutRemainder(9).should.be.equal(2520));
it("prooves 12", () => smallestWithoutRemainder(12).should.be.equal(27720));
it("prooves 20", () => smallestWithoutRemainder(20).should.be.equal(232792560));
it("prooves 30", () => smallestWithoutRemainder(30).should.be.equal(2329089562800));
it("prooves 40", () => smallestWithoutRemainder(40).should.be.equal(5342931457063200));
});
let smallestWithoutRemainder = (end: number, interval?: number) => {
// What do we know?
// - at 10, the answer is 2520
// - can't be smaller than the lower multiple of 10
// - must be an interval of the lower multiple of 10
// so:
// - the interval and the start should at least be divisable by 'end'
// - we can recurse and build on the results before it.
if (!interval) interval = end;
let count = Math.floor(end / 10);
if (count == 1) interval = 2520;
else if (count > 1) interval = smallestWithoutRemainder((count - 1) * 10, interval);
for (let i = interval; true; i += interval) {
let failed = false;
for (let j = end; j > 1; j--) {
if (i % j != 0) {
failed = true;
break;
}
}
if (!failed) return i;
}
}

I think this the answer:
primes = [11, 13, 17, 19]
result = 2520
for i in primes:
result *= i
print (result * 2)