Range is too large Python - python

I'm trying to find the largest prime factor of the number x, Python gives me the error that the range is too large. I've tried using x range but I get an OverflowError: Python int too large to convert to C long
x = 600851475143
maxPrime = 0
for i in range(x):
isItPrime = True
if (x%i == 0):
for prime in range(2,i-1):
if (i%prime == 0):
isItPrime = False
if (isItPrime == True):
if (i > maxPrime):
maxPrime = i;
print maxPrime

In old (2.x) versions of Python, xrange can only handle Python 2.x ints, which are bound by the native long integer size of your platform. Additionally, range allocates a list with all numbers beforehand on Python 2.x, and is therefore unsuitable for large arguments.
You can either switch to 3.x (recommended), or a platform where long int (in C) is 64 bit long, or use the following drop-in:
import itertools
range = lambda stop: iter(itertools.count().next, stop)
Equivalently, in a plain form:
def range(stop):
i = 0
while i < stop:
yield i
i += 1

This is what I would do:
def prime_factors(x):
factors = []
while x % 2 == 0:
factors.append(2)
x /= 2
i = 3
while i * i <= x:
while x % i == 0:
x /= i
factors.append(i)
i += 2
if x > 1:
factors.append(x)
return factors
>>> prime_factors(600851475143)
[71, 839, 1471, 6857]
It's pretty fast and I think it's right. It's pretty simple to take the max of the factors found.
2017-11-08
Returning to this 5 years later, I would use yield and yield from plus faster counting over the prime range:
def prime_factors(x):
def diver(x, i):
j = 0
while x % i == 0:
x //= i
j += 1
return x, [i] * j
for i in [2, 3]:
x, vals = diver(x, i)
yield from vals
i = 5
d = {5: 2, 1: 4}
while i * i <= x:
x, vals = diver(x, i)
yield from vals
i += d[i % 6]
if x > 1:
yield x
list(prime_factors(600851475143))
The dict {5: 2, 1: 4} uses the fact that you don't have to look at all odd numbers. Above 3, all numbers x % 6 == 3 are multiples of 3, so you need to look at only x % 6 == 1 and x % 6 == 5, and you can hop between these by alternately adding 2 and 4, starting from 5.

The accepted answer suggests a drop-in replacement for xrange, but only covers one case. Here is a more general drop-in replacement.
def custom_range(start=0,stop=None,step=1):
'''xrange in python 2.7 fails on numbers larger than C longs.
we write a custom version'''
if stop is None:
#handle single argument case. ugly...
stop = start
start = 0
i = start
while i < stop:
yield i
i += step
xrange=custom_range

I would definitely stick with xrange since creating a list between 0 and what looks like a number rivaled by infinity would be taxing for memory. xrange will generate only the numbers when asked. For the number too large problem, you might want to try a "long". This can be achieved by writing a L on the end of the number. I made my own version to test it out. I put in a small sleep as to not destroy my computer into virtually a while(1) loop. I was also impatient to see the program come to a complete end, so I put in print statements
from time import sleep
x = 600851475143L
maxPrime = 0
for i in xrange(1,x):
isItPrime = True
if (x%i) == 0:
for prime in xrange(2,i-1):
if (i%prime) == 0:
isItPrime = False
break
if isItPrime:
maxPrime = i
print "Found a prime: "+str(i)
sleep(0.0000001)
print maxPrime
Hope this helps!
EDIT:
I also did a few more edits to yield this version. It is fairly efficient and I checked quite a few numbers this program provides (it seems to check out so far):
from time import sleep
x = 600851475143L
primes = []
for i in xrange(2,x):
isItPrime = True
for prime in primes:
if (i%prime) == 0:
isItPrime = False
break
if isItPrime:
primes.append(i)
print "Found a prime: "+str(i)
sleep(0.0000001)
print primes[-1]

Very uneficient code, that's not the best way of getting dividers, I've done it with a for and range, but I can't execute it because of the long variables, so I decided to implement it with a for using a while, and increment a counter by myself.
For 32 bit int like 13195:
# The prime factors of 13195 are 5, 7, 13 and 29.
# What is the largest prime factor of the number 600851475143 ?
i = 13195
for j in xrange(2, i, 1):
if i%j == 0:
i = i/j
print j
Good way for longer numbers:
# The prime factors of 13195 are 5, 7, 13 and 29.
# What is the largest prime factor of the number 600851475143 ?
i = 600851475143
j = 2
while i >= j:
if i%j == 0:
i = i/j
print j
j = j+1
The last prime is the last printed value.

Another implementation for python 2 range():
import itertools
import operator
def range(*args):
"""Replace range() builtin with an iterator version."""
if len(args) == 0:
raise TypeError('range() expected 1 arguments, got 0')
start, stop, step = 0, args[0], 1
if len(args) == 2: start, stop = args
if len(args) == 3: start, stop, step = args
if step == 0:
raise ValueError('range() arg 3 must not be zero')
iters = itertools.count(start, step)
pred = operator.__ge__ if step > 0 else operator.__le__
for n in iters:
if pred(n, stop): break
yield n

Related

finding the smallest prime factors of a number using python [duplicate]

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

how can i check if number entered is prime and if not find its prime factors in python? [duplicate]

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

Strange output when trying to find prime numbers Python

Ok, so I admittedly am kind of a noob, and I've been going through a course on udemy for programming. The problem is asking to write a function that finds all the prime numbers up to the number given. So I started writing the following code to extract the numbers that are not even, as well as the numbers not evenly divisible by 3 just to start:
def count_primes(num):
num_list5 = []
for i in range(num + 1):
print(i)
if i % 2 != 0 or i % 3 != 0:
num_list5.append(i)
return num_list5
When I call the function with a number of 100 like:
count_primes(100)
In the output, I get the num_list5 showing all the numbers in the range except for 6 and multiples of 6:
[1, 2, 3, 4, 5, 7, 8, 9, 10, 11, 13, 14 ...]
Its like the if statement is doing an AND operation here... because 6 would be divisible by 2 AND 3. Is this a bug or something? Or am I not understanding and/or operations correctly?
What's weird is that it was working at one point and after making a change and reverting it, it started doing this...
I'm using VSCode and Jupyter notebooks and tried both Python 3.8.5 64-bit and 3.9.4 64-bit on Ubuntu 20.04
i % 2 != 0 or i % 3 != 0 is equal to not (i % 2 == 0 and i % 3 == 0) (De Morgan's laws)
It should be i % 2 != 0 and i % 3 != 0
If you are looking to generate all primes less than num, you should loop over all numbers j less than i and check if i%j is zero rather than just 2 and 3.
def count_primes(num):
num_list5 = []
for i in range(2, num + 1): # start at 2 because 1 and zero are not primes
print(i)
for j in range(2, i):
if i%j == 0:
break
else:
num_list5.append(i)
return num_list5
if __name__ == "__main__":
n = 100
print(count_primes(n))
Note that using Sieve of Eratosthenes method, this can be done more efficiently:
import math
def count_primes_sieve(num):
num_list5 = [False, False] + [True]*(num - 1)
for i in range(2, math.ceil(math.sqrt(num)) + 1):
if num_list5[i]:
j = i * i
while j < len(num_list5):
num_list5[j] = False
j += i
return [i for i, p in enumerate(num_list5) if p]
if __name__ == "__main__":
n = 100
print(count_primes_sieve(n))
We know some facts about prime numbers which you can use in your program. Negative numbers, 0 and 1 are not prime. 2 is the only even prime. A prime number only has itself and 1 as factors. From multiplication we know that if a x b = c then one of a, b is <= sqrt(c). That last fact helps us cut down the number of trial divisors we have to test. We can test for a prime by looking for a number that divides the target but is not the target itself or 1. If we find such a number then the target is not prime.
Here is some pseudocode to help:
function isPrime(num)
// 1, 0, negatives not prime.
if (num < 2)
return false
end if
// 2 is the only even prime.
if (num MOD 2 = 0)
return (num = 2)
end if
// Try odd factors up to square root.
limit <- 1 + sqrt(num)
for (test <- 3; test < limit; test <- test + 2)
if (num MOD test = 0)
// Not prime, we have found a factor.
return false
end if
end for
// If we get this far then num is prime.
return true
end function
After figuring out the propositional math and de Morgan's Law as someone pointed out, I was able to come up with a pretty simple solution using or and mod operators and only goes through a the sequence once:
def count_primes(num):
num_list5 = []
for i in range(2, num + 1):
if i == 2 or i == 3 or i == 5 or i == 7:
num_list5.append(i)
if not (i % 2 == 0 or i % 3 == 0 or i % 5 == 0 or i % 7 == 0):
num_list5.append(i)
return num_list5
print(count_primes(100))

Basic prime number generator in Python

Just wanted some feedback on my prime number generator. e.g. is it ok, does it use to much resources etc. It uses no libraries, it's fairly simple, and it is a reflection of my current state of programming skills, so don't hold back as I want to learn.
def prime_gen(n):
primes = [2]
a = 2
while a < n:
counter = 0
for i in primes:
if a % i == 0:
counter += 1
if counter == 0:
primes.append(a)
else:
counter = 0
a = a + 1
print primes
There are a few optimizations thar are common:
Example:
def prime(x):
if x in [0, 1]:
return False
if x == 2:
return True
for n in xrange(3, int(x ** 0.5 + 1)):
if x % n == 0:
return False
return True
Cover the base cases
Only iterate up to the square root of n
The above example doesn't generate prime numbers but tests them. You could adapt the same optimizations to your code :)
One of the more efficient algorithms I've found written in Python is found in the following question ans answer (using a sieve):
Simple Prime Generator in Python
My own adaptation of the sieve algorithm:
from itertools import islice
def primes():
if hasattr(primes, "D"):
D = primes.D
else:
primes.D = D = {}
def sieve():
q = 2
while True:
if q not in D:
yield q
D[q * q] = [q]
else:
for p in D[q]:
D.setdefault(p + q, []).append(p)
del D[q]
q += 1
return sieve()
print list(islice(primes(), 0, 1000000))
On my hardware I can generate the first million primes pretty quickly (given that this is written in Python):
prologic#daisy
Thu Apr 23 12:58:37
~/work/euler
$ time python foo.py > primes.txt
real 0m19.664s
user 0m19.453s
sys 0m0.241s
prologic#daisy
Thu Apr 23 12:59:01
~/work/euler
$ du -h primes.txt
8.9M primes.txt
Here is the standard method of generating primes adapted from the C# version at: Most Elegant Way to Generate Prime Number
def prime_gen(n):
primes = [2]
# start at 3 because 2 is already in the list
nextPrime = 3
while nextPrime < n:
isPrime = True
i = 0
# the optimization here is that you're checking from
# the number in the prime list to the square root of
# the number you're testing for primality
squareRoot = int(nextPrime ** .5)
while primes[i] <= squareRoot:
if nextPrime % primes[i] == 0:
isPrime = False
i += 1
if isPrime:
primes.append(nextPrime)
# only checking for odd numbers so add 2
nextPrime += 2
print primes
You start from this:
def prime_gen(n):
primes = [2]
a = 2
while a < n:
counter = 0
for i in primes:
if a % i == 0:
counter += 1
if counter == 0:
primes.append(a)
else:
counter = 0
a = a + 1
print primes
do you really need the else branch? No.
def prime_gen(n):
primes = [2]
a = 2
while a < n:
counter = 0
for i in primes:
if a % i == 0:
counter += 1
if counter == 0:
primes.append(a)
a = a + 1
print primes
Do you need the counter? No!
def prime_gen(n):
primes = [2]
a = 2
while a < n:
for i in primes:
if a % i == 0:
primes.append(a)
break
a = a + 1
print primes
Do you need to check for i larger that sqrt(a)? No.
def prime_gen(n):
primes = [2]
a = 3
while a < n:
sqrta = sqrt(a+1)
for i in primes:
if i >= sqrta:
break
if a % i == 0:
primes.append(a)
break
a = a + 1
print primes
Do you really want to manually increase a?
def prime_gen(n):
primes = [2]
for a in range(3,n):
sqrta = sqrt(a+1)
for i in primes:
if i >= sqrta:
break
if a % i == 0:
primes.append(a)
break
This is some basic refactoring that should automatically flow out of your fingers.
Then you test the refactored code, see that it is buggy and fix it:
def prime_gen(n):
primes = [2]
for a in range(3,n):
sqrta = sqrt(a+1)
isPrime = True
for i in primes:
if i >= sqrta:
break
if a % i == 0:
isPrime = False
break
if(isPrime):
primes.append(a)
return primes
And finally you get rid of the isPrime flag:
def prime_gen(n):
primes = [2]
for a in range(3,n):
sqrta = sqrt(a+1)
for i in primes:
if i >= sqrta:
primes.append(a)
break
if a % i == 0:
break
return primes
now you believe you're done. Then suddenly a friend of yours point out that for a even you are checking i >= sqrta for no reason. (Similarly for a mod 3 == 0 numbers, but then branch-prediction comes in help.)
Your friend suggest you to check a % i == 0 before:
def prime_gen(n):
primes = [2]
for a in range(3,n):
sqrta = sqrt(a+1)
for i in primes:
if a % i == 0:
break
if i >= sqrta:
primes.append(a)
break
return primes
now you're done and grateful to your brillant friend!
You can use Python yield statement to generate one item at the time. Son instead of get all items at once you will iterate over generator and get one item at the time. This minimizes your resources.
Here an example:
from math import sqrt
from typing import Generator
def gen(num: int) -> Generator[int, None, None]:
if 2 <= num:
yield 2
yield from (
i
for i in range(3, num + 1, 2)
if all(i % x != 0 for x in range(3, int(sqrt(i) + 1)))
)
for x in gen(100):
print(x, end=", ")
Output:
2, 3, 5, 7, 11, 13, 17, 19, 23, 29, 31, 37, 41, 43, 47, 53, 59, 61, 67, 71, 73, 79, 83, 89, 97,
I made improvements on the solution proposed my jimifiki
import math #for finding the sqare root of the candidate number
def primes(n):
test = [3] #list of primes new candidates are tested against
found = [5] #list of found primes, which are not being tested against
c = 5 #candidate number, starting at five
while c < n: #upper bound, largest candidate will be this or 1 bigger
p = True #notes the possibility of c to be prime
c += 2 #increase candidate by 2, avoiding all even numbers
for a in test: #for each item in test
if c % a == 0: #check if candidate is divisible
p = False #since divisible cannot be prime
break #since divisible no need to continue checking
if p: #true only if not divisible
if found[0] > math.sqrt(c): #is samallest in found > sqrt of c
found.append(c) #if so c is a prime, add it to the list
else: #if not, it's equal and we need to start checking for it
test.append(found.pop(0)) #move pos 0 of found to last in test
return([2] + test + found) #after reaching limit returns 2 and both lists
The biggest improvement is not checking for even numbers and checking the square root only if the number is not divisible, the latter really adds up when numbers get bigger. The reason we don't need to check for the square root is, that the test list only contains numbers smaller than the square root. This is because we add the next number only when we get to the first non-prime not divisible by any of the numbers in test. This number is always the square of the next biggest prime which is also the smallest number in found. The use of the boolean "p" feels kind of spaghetty to me so there might be room for improvement.
Here's a pretty efficient prime number generator that I wrote a while back that uses the Sieve of Eratosthenes:
#!/usr/bin/env python2.7
def primeslt(n):
"""Finds all primes less than n"""
if n < 3:
return []
A = [True] * n
A[0], A[1] = False, False
for i in range(2, int(n**0.5)+1):
if A[i]:
j = i**2
while j < n:
A[j] = False
j += i
return [num for num in xrange(n) if A[num]]
def main():
i = ''
while not i.isdigit():
i = raw_input('Find all prime numbers less than... ')
print primeslt(int(i))
if __name__ == '__main__':
main()
The Wikipedia article (linked above) explains how it works better than I could, so I'm just going to recommend that you read that.
I have some optimizations for the first code which can be used when the argument is negative:
def is_prime(x):
if x <=1:
return False
else:
for n in xrange(2, int(x ** 0.5 + 1)):
if x % n == 0:
return False
return True
print is_prime(-3)
Being Python, it usually better to return a generator that will return an infinite sequence of primes rather than a list.
ActiveState has a list of older Sieve of Eratosthenes recipes
Here is one of them updated to Python 2.7 using itertools count with a step argument which did not exist when the original recipe was written:
import itertools as it
def sieve():
""" Generate an infinite sequence of prime numbers.
"""
yield 2
D = {}
for q in it.count(3, 2): # start at 3 and step by odds
p = D.pop(q, 0)
if p:
x = q + p
while x in D: x += p
D[x] = p # new composite found. Mark that
else:
yield q # q is a new prime since no composite was found
D[q*q] = 2*q
Since it is a generator, it is much more memory efficient than generating an entire list. Since it locates composite, it is computationally efficient as well.
Run this:
>>> g=sieve()
Then each subsequent call returns the next prime:
>>> next(g)
2
>>> next(g)
3
# etc
You can then get a list between boundaries (i.e., the Xth prime from the first to the X+Y prime...) by using islice:
>>> tgt=0
>>> tgt, list(it.islice(sieve(), tgt, tgt+10))
(0, [2, 3, 5, 7, 11, 13, 17, 19, 23, 29])
>>> tgt=1000000
>>> tgt, list(it.islice(sieve(), tgt, tgt+10))
(1000000, [15485867, 15485917, 15485927, 15485933, 15485941, 15485959, 15485989, 15485993, 15486013, 15486041])
To Get the 100th prime number:
import itertools
n=100
x = (i for i in itertools.count(1) if all([i%d for d in xrange(2,i)]))
print list(itertools.islice(x,n-1,n))[0]
To get prime numbers till 100
import itertools
n=100
x = (i for i in xrange(1,n) if all([i%d for d in xrange(2,i)]))
for n in x:
print n
you can do it this way also to get the primes in a dictionary in python
def is_prime(a):
count = 0
counts = 0
k = dict()
for i in range(2, a - 1):
k[count] = a % i
count += 1
for j in range(len(k)):
if k[j] == 0:
counts += 1
if counts == 0:
return True
else:
return False
def find_prime(f, g):
prime = dict()
count = 0
for i in range(int(f), int(g)):
if is_prime(i) is True:
prime[count] = i
count += 1
return prime
a = find_prime(20,110)
print(a)
{0: 23, 1: 29, 2: 31, 3: 37, 4: 41, 5: 43, 6: 47, 7: 53, 8: 59, 9: 61, 10: 67, 11:
71, 12: 73, 13: 79, 14: 83, 15: 89, 16: 97, 17: 101, 18: 103, 19: 107, 20: 109}

Python prime number code running slow

I am trying to solve the problem mentioned here: https://www.spoj.pl/problems/PRIME1/
I am also giving the description below.
Peter wants to generate some prime numbers for his cryptosystem. Help him! Your task is to generate all prime numbers between two given numbers!
Input
The input begins with the number t of test cases in a single line (t<=10). In each of the next t lines there are two numbers m and n (1 <= m <= n <= 1000000000, n-m<=100000) separated by a space.
Output
For every test case print all prime numbers p such that m <= p <= n, one number per line, test cases separated by an empty line.`
My code is as below. I am thinking remove method on list is very slow.
import sys
import math
num = int(sys.stdin.readline());
indices = []
maxrange = 2
while(num > 0):
a,b = sys.stdin.readline().split(" ");
a = int(a)
b = int(b)
if(a < 2):
a = 2
indices.append((a,b))
if(b > maxrange):
maxrange= b
num = num - 1
val = int(math.sqrt(maxrange)+1)
val2 = int(math.sqrt(val)+1)
checks = range(2,val2)
for i in range(2,val2):
for j in checks:
if(i!= j and j%i == 0):
checks.remove(j)
primes = range(2,val)
for i in checks:
for j in primes:
if(i != j and j%i == 0):
primes.remove(j)
primes2 = range(2,maxrange)
for i in primes:
for j in primes2:
if(j != i and j%i == 0):
primes2.remove(j)
for (a,b) in indices:
for p in primes2:
if(a<= p and b >= p):
print p
if(p > b):
break
print
I think python list remove is very slow. My code is correct but I am getting timelimit exceeded. can someone help me improve this code.
A primality testing function will perform best. There's pseudocode on the Miller-Rabin wikipedia page
Instead of removing the element that is not a prime, why not replace it with some sentinel value, perhaps -1 or None? Then when printing, just print the values that aren't sentinels.
Use a list of length (n-m), and then the index for number i is x[m+i].
remove() isn't slow in the grand scheme of things, it's just that the code calls it a LOT.
As dappawit suggests, rather than modifying the list, change the value in the list so you know that it isn't a valid number to use.
I also see that when you generate the set of prime numbers, you use range(2,maxrange) which is okay, but not efficient if the lower bound is much greater than 2. You'll be wasting computing time on generating primes that aren't even relevant to the problem space. If nothing else, keep track of minrange as well as maxrange.
A bug with your original code is that you use range(2,maxrange). That means maxrange is not in the list of numbers considered. Try 3 5 as input for a and b to see the bug.
range(2,maxrange+1) fixes the problem.
Another bug in the code is that you modify the original sequence:
From Python docs - for-statement
It is not safe to modify the sequence being iterated over in the loop (this can only happen for mutable sequence types, such as lists). If you need to modify the list you are iterating over (for example, to duplicate selected items) you must iterate over a copy. The slice notation makes this particularly convenient:
My python skills are rudimentary, but this seems to work:
Old:
primes2 = range(2,maxrange)
for i in primes:
for j in primes2:
if(j != i and j%i == 0):
primes2.remove(j)
for (a,b) in indices:
for p in primes2:
if(a<= p and b >= p):
New:
primes2 = array.array('L', range(minrange,maxrange+1))
for i in primes:
for j in primes2:
if(j != i and j%i == 0):
primes2[j-minrange] = 0
for (a,b) in indices:
for p in primes2:
if (p != 0):
if(a<= p and b >= p):
You could also skip generating the set of prime numbers and just test the numbers directly, which would work if the sets of numbers you have to generate prime numbers are not overlapping (no work duplication).
enter link description here
Here's a deterministic variant of the Miller–Rabin primality test for small odd integers in Python:
from math import log
def isprime(n):
assert 1 < n < 4759123141 and n % 2 != 0, n
# (n-1) == 2**s * d
s = 0
d = n-1
while d & 1 == 0:
s += 1
d >>= 1
assert d % 2 != 0 and (n-1) == d*2**s
for a in [2, 7, 61]:
if not 2 <= a <= min(n-1, int(2*log(n)**2)):
break
if (pow(a, d, n) != 1 and
all(pow(a, d*2**r, n) != (n-1) for r in xrange(s))):
return False
return True
The code intent is to be an executable pseudo-code.

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