I've got, what I think is a valid solution to problem 2 of Project Euler (finding all even numbers in the Fibonacci sequence up to 4,000,000). This works for lower numbers, but crashes when I run it with 4,000,000. I understand that this is computationally difficult, but shouldn't it just take a long time to compute rather than crash? Or is there an issue in my code?
import functools
def fib(limit):
sequence = []
for i in range(limit):
if(i < 3):
sequence.append(i)
else:
sequence.append(sequence[i-1] + sequence[i-2])
return sequence
def add_even(x, y):
if(y % 2 == 0):
return x + y
return x + 0
print(functools.reduce(add_even,fib(4000000)))
The problem is about getting the Fibonacci numbers that are smaller than 4000000. Your code tries to find the first 4000000 Fibonacci values instead. Since Fibonacci numbers grow exponentially, this will reach numbers too large to fit in memory.
You need to change your function to stop when the last calculated value is more than 4000000.
Another possible improvement is to add the numbers as you are calculating them instead of storing them in a list, but this won't be necessary if you stop at the appropriate time.
Related
I'm new to both Python and StackOverflow so I apologise if this question has been repeated too much or if it's not a good question. I'm doing a beginner's Python course and one of the tasks I have to do is to make a function that finds the next prime number after a given input. This is what I have so far:
def nextPrime(n):
num = n + 1
for i in range(1, 500):
for j in range(2, num):
if num%j == 0:
num = num + 1
return num
When I run it on the site's IDE, it's fine and everything works well but then when I submit the task, it says the runtime was too long and that I should optimise my code. But I'm not really sure how to do this, so would it be possible to get some feedback or any suggestions on how to make it run faster?
When your function finds the answer, it will continue checking the same number hundreds of times. This is why it is taking so long. Also, when you increase num, you should break out of the nested loop to that the new number is checked against the small factors first (which is more likely to eliminate it and would accelerate progress).
To make this simpler and more efficient, you should break down your problem in areas of concern. Checking if a number is prime or not should be implemented in its own separate function. This will make the code of your nextPrime() function much simpler:
def nextPrime(n):
n += 1
while not isPrime(n): n += 1
return n
Now you only need to implement an efficient isPrime() function:
def isPrime(x):
p,inc = 2,1
while p*p <= x:
if x % p == 0: return False
p,inc = p+inc,2
return x > 1
Looping from 1 to 500, especially because another loop runs through it, is not only inefficient, but also confines the range of the possible "next prime number" that you're trying to find. Therefore, you should make use of while loop and break which can be used to break out of the loop whenever you have found the prime number (of course, if it's stated that the number is less than 501 in the prompt, your approach totally makes sense).
Furthermore, you can make use of the fact that you only need check the integers less than or equal to the square root of the designated integer (which in python, is represented as num**0.5) to determine if that integer is prime, as the divisors of the integers always come in pair and the largest of the smaller divisor is always a square root, if it exists.
What I'm trying to figure out is when I run this code for smaller numbers it returns the list just fine, but for larger numbers (I would call this small in the context of what I'm working on.) like 29996299, it will run for a long time, I've waited for 45 minutes with no results and had to end up killing the program. What I was wondering was whether there was a more efficient way to handle numbers whose scale was larger than 4 or 5 digits. I've tested a few permutations of the range function to see if there was a better way to handle the limits of the list I want to produce but nothing seems to have any effect on the amount of time it takes to do the computation. I'm new to python and am not that experienced as a programmer. Thank you for your time.
ran the program again before submitting this post and it took an hour and a half or so.
function of the program is to take the User selected number, use it to generate a lower bound, find all primes between the bound and input and append to list, then generate a secound upper bound and find all primes and then append to list, to create a list that extends forwards and backwards from the initial number.
the program works like I expect it to but not as quickly as I need it to since the numbers I'm going to be dealing with are going to get large quickly, almost doubling at each phase.
initial_num = input("Please enter a number. ")
lower_1 = int(initial_num) - 1000
upper_1 = int(initial_num)
list_1 = []
for num in range(lower_1,upper_1):
if num > 1:
for i in range(2,num):
if (num % i) == 0:
break
else:
list_1.append(num)
lower_2 = list_1[-1]
upper_2 = list_1[-1] + 2000
list_2 = []
for num in range(lower_2,upper_2 +1):
if num > 1:
for i in range(2,num):
if (num % i) == 0:
break
else:
list_2.append(num)
list_3 = list_1 + list_2[1:]
print list_3
You can use a more efficient algorithm to generate the entire list of prime numbers up to N. This is the Sieve of Erathostenes. Please have a look at the linked article, it even includes an example pseudocode. The basic idea of the algorithm is:
maintain L, a list of potentially prime numbers (initially all numbers from 2 to N)
pick the next prime number (p) as the first element of L (intially 2)
remove all numbers that are a multiple of p, up to N, since they cannot be prime
repeat from step 2
At the end you are left with a list of prime numbers.
An implementation in Pyhton from here
def eratosthenes2(n):
multiples = set()
for i in range(2, n+1):
if i not in multiples:
yield i
multiples.update(range(i*i, n+1, i))
print(list(eratosthenes2(100)))
To reduce memory consumpution you could consider usgin a bitset, storing one bit for each number. That should reduce memory usage by between 32 - 64 times. A bitset implementation is available for python here.
I'm relatively new to the python world, and the coding world in general, so I'm not really sure how to go about optimizing my python script. The script that I have is as follows:
import math
z = 1
x = 0
while z != 0:
x = x+1
if x == 500:
z = 0
calculated = open('Prime_Numbers.txt', 'r')
readlines = calculated.readlines()
calculated.close()
a = len(readlines)
b = readlines[(a-1)]
b = int(b) + 1
for num in range(b, (b+1000)):
prime = True
calculated = open('Prime_Numbers.txt', 'r')
for i in calculated:
i = int(i)
q = math.ceil(num/2)
if (q%i==0):
prime = False
if prime:
calculated.close()
writeto = open('Prime_Numbers.txt', 'a')
num = str(num)
writeto.write("\n" + num)
writeto.close()
print(num)
As some of you can probably guess I'm calculating prime numbers. The external file that it calls on contains all the prime numbers between 2 and 20.
The reason that I've got the while loop in there is that I wanted to be able to control how long it ran for.
If you have any suggestions for cutting out any clutter in there could you please respond and let me know, thanks.
Reading and writing to files is very, very slow compared to operations with integers. Your algorithm can be sped up 100-fold by just ripping out all the file I/O:
import itertools
primes = {2} # A set containing only 2
for n in itertools.count(3): # Start counting from 3, by 1
for prime in primes: # For every prime less than n
if n % prime == 0: # If it divides n
break # Then n is composite
else:
primes.add(n) # Otherwise, it is prime
print(n)
A much faster prime-generating algorithm would be a sieve. Here's the Sieve of Eratosthenes, in Python 3:
end = int(input('Generate primes up to: '))
numbers = {n: True for n in range(2, end)} # Assume every number is prime, and then
for n, is_prime in numbers.items(): # (Python 3 only)
if not is_prime:
continue # For every prime number
for i in range(n ** 2, end, n): # Cross off its multiples
numbers[i] = False
print(n)
It is very inefficient to keep storing and loading all primes from a file. In general file access is very slow. Instead save the primes to a list or deque. For this initialize calculated = deque() and then simply add new primes with calculated.append(num). At the same time output your primes with print(num) and pipe the result to a file.
When you found out that num is not a prime, you do not have to keep checking all the other divisors. So break from the inner loop:
if q%i == 0:
prime = False
break
You do not need to go through all previous primes to check for a new prime. Since each non-prime needs to factorize into two integers, at least one of the factors has to be smaller or equal sqrt(num). So limit your search to these divisors.
Also the first part of your code irritates me.
z = 1
x = 0
while z != 0:
x = x+1
if x == 500:
z = 0
This part seems to do the same as:
for x in range(500):
Also you limit with x to 500 primes, why don't you simply use a counter instead, that you increase if a prime is found and check for at the same time, breaking if the limit is reached? This would be more readable in my opinion.
In general you do not need to introduce a limit. You can simply abort the program at any point in time by hitting Ctrl+C.
However, as others already pointed out, your chosen algorithm will perform very poor for medium or large primes. There are more efficient algorithms to find prime numbers: https://en.wikipedia.org/wiki/Generating_primes, especially https://en.wikipedia.org/wiki/Sieve_of_Eratosthenes.
You're writing a blank line to your file, which is making int() traceback. Also, I'm guessing you need to rstrip() off your newlines.
I'd suggest using two different files - one for initial values, and one for all values - initial and recently computed.
If you can keep your values in memory a while, that'd be a lot faster than going through a file repeatedly. But of course, this will limit the size of the primes you can compute, so for larger values you might return to the iterate-through-the-file method if you want.
For computing primes of modest size, a sieve is actually quite good, and worth a google.
When you get into larger primes, trial division by the first n primes is good, followed by m rounds of Miller-Rabin. If Miller-Rabin probabilistically indicates the number is probably a prime, then you do complete trial division or AKS or similar. Miller Rabin can say "This is probably a prime" or "this is definitely composite". AKS gives a definitive answer, but it's slower.
FWIW, I've got a bunch of prime-related code collected together at http://stromberg.dnsalias.org/~dstromberg/primes/
I am writing a code to find the largest prime factor of a very large number.
Problem 3 of Project Euler :
What is the largest prime factor of the number 600851475143 ?
I coded it in C...but the data type long long int is not sufficient enough to hold the value .
Now, I have rewritten the code in Python. How can I reduce the time taken for execution (as it is taking a considerable amount of time)?
def isprime(b):
x=2
while x<=b/2:
if(b%x)==0:
return 0
x+=1
return 1
def lpf(a):
x=2
i=2
while i<=a/2:
if a%i==0:
if isprime(i)==1:
if i>x:
x=i
print(x)
i+=1
print("final answer"+x)
z=600851475143
lpf(z)
There are many possible algorithmic speed ups. Some basic ones might be:
First, if you are only interested in the largest prime factor, you should check for them from the largest possible ones, not smallest. So instead of looping from 2 to a/2 try to check from a downto 2.
You could load the database of primes instead of using isprime function (there are dozens of such files in the net)
Also, only odd numbers can be primes (except for 2) so you can "jump" 2 values in each iteration
Your isprime checker could also be speededup, you do not have to look for divisiors up to b/2, it is enough to check to sqrt(b), which reduces complexity from O(n) to O(sqrt(n)) (assuming that modulo operation is constant time).
You could use the 128 int provided by GCC: http://gcc.gnu.org/onlinedocs/gcc/_005f_005fint128.html . This way, you can continue to use C and avoid having to optimize Python's speed. In addition, you can always add your own custom storage type to hold numbers bigger than long long in C.
I think you're checking too many numbers (incrementing by 1 and starting at 2 in each case). If you want to check is_prime by trial division, you need to divide by fewer numbers: only odd numbers to start (better yet, only primes). You can range over odd numbers in python the following way:
for x in range(3, some_limit, 2):
if some_number % x == 0:
etc.
In addition, once you have a list of primes, you should be able to run through that list backwards (because the question asks for highest prime factor) and test if any of those primes evenly divides into the number.
Lastly, people usually go up to the square-root of a number when checking trial division because anything past the square-root is not going to provide new information. Consider 100:
1 x 100
2 x 50
5 x 20
10 x 10
20 x 5
etc.
You can find all the important divisor information by just checking up to the square root of the number. This tip is useful both for testing primes and for testing where to start looking for a potential divisor for that huge number.
First off, your two while loops only need to go up to the sqrt(n) since you will have hit anything past that earlier (you then need to check a/i for primeness as well). In addition, if you find the lowest number that divides it, and the result of the division is prime, then you have found the largest.
First, correct your isprime function:
def isprime(b):
x=2
sqrtb = sqrt(b)
while x<=sqrtb:
if(b%x)==0:
return 0
x+=1
return 1
Then, your lpf:
def lpf(a):
x=2
i=2
sqrta = sqrt(a)
while i<=sqrt(a):
if a%i==0:
b = a//i # integer
if isprime(b):
return b
if isprime(i):
x=i
print(x)
i+=1
return x
I had an overflow error with this program here!, I realized the mistake of that program. I cannot use range or xrange when it came to really long integers. I tried running the program in Python 3 and it works. My code works but then responds after several times. Hence in order to optimize my code, I started thinking of strategies for the optimizing the code.
My problem statement is A number is called lucky if the sum of its digits, as well as the sum of the squares of its digits is a prime number. How many numbers between A and B are lucky?.
I started with this:
squarelist=[0,1,4,9,16,25,36,49,64,81]
def isEven(self, n):
return
def isPrime(n):
return
def main():
t=long(raw_input().rstrip())
count = []
for i in xrange(t):
counts = 0
a,b = raw_input().rstrip().split()
if a=='1':
a='2'
tempa, tempb= map(int, a), map(int,b)
for i in range(len(b),a,-1):
tempsum[i]+=squarelist[tempb[i]]
What I am trying to achieve is since I know the series is ordered, only the last number changes. I can save the sum of squares of the earlier numbers in the list and just keep changing the last number. This does not calculate the sum everytime and check if the sum of squares is prime. I am unable to fix the sum to some value and then keep changing the last number.How to go forward from here?
My sample inputs are provided below.
87517 52088
72232 13553
19219 17901
39863 30628
94978 75750
79208 13282
77561 61794
I didn't get what you want to achieve with your code at all. This is my solution to the question as I understand it: For all natural numbers n in a range X so that a < X < b for some natural numbers a, b with a < b, how many numbers n have the property that the sum of its digits and the sum of the square of its digits in decimal writing are both prime?
def sum_digits(n):
s = 0
while n:
s += n % 10
n /= 10
return s
def sum_digits_squared(n):
s = 0
while n:
s += (n % 10) ** 2
n /= 10
return s
def is_prime(n):
return all(n % i for i in xrange(2, n))
def is_lucky(n):
return is_prime(sum_digits(n)) and is_prime(sum_digits_squared(n))
def all_lucky_numbers(a, b):
return [n for n in xrange(a, b) if is_lucky(n)]
if __name__ == "__main__":
sample_inputs = ((87517, 52088),
(72232, 13553),
(19219, 17901),
(39863, 30628),
(94978, 75750),
(79208, 13282),
(77561, 61794))
for b, a in sample_inputs:
lucky_number_count = len(all_lucky_numbers(a, b))
print("There are {} lucky numbers between {} and {}").format(lucky_number_count, a, b)
A few notes:
The is_prime is the most naive implementation possible. It's still totally fast enough for the sample input. There are many better implementations possible (and just one google away). The most obvious improvement would be skipping every even number except for 2. That alone would cut calculation time in half.
In Python 3 (and I really recommend using it), remember to use //= to force the result of the division to be an integer, and use range instead of xrange. Also, an easy way to speed up is_prime is Python 3's #functools.lru_cache.
If you want to save some lines, calculate the sum of digits by casting them to str and back to int like that:
def sum_digits(n):
return sum(int(d) for d in str(a))
It's not as mathy, though.