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python code is not running.I am calculating prime factors of a number (project euler problem - 3)

I am trying to calculate prime factors of a number in python python 3.8.2 32bit (when i pass 35 in code its output should be 7,and so on).But for some reason the program does not return any answer (when i click run the cmd does not output anything).But when i run this javascript, the exact same code works there. (Previously i had an array(list) to which i would append prime factors and at last i would pop the last element which worked for smaller numbers , but for really large numbers i would get a Memory error,so i converted it to use only one variable which will be updated for every while loop). What is going on here ??
My code is :
import math
# Computes only prime factors of n
def compute(n):
arr = 0
# Checks if n is divisible by 2, and if it is divisible,returns 2 because there will be no any other
# prime factor.
if n % 2 == 0:
return 2
# Now that 2 is eliminated we only check for odd numbers upto (square root of n)+1
for i in range(1, round(math.sqrt(n)) + 1, 2):
while n % i == 0:
arr = n/i
n /= i
return str(arr)
print(compute(81))
I am a newbie in python so plz tell me if i have made any silly mistakes.
Ty.

For numbers that are not divisible by 2, your code runs into an infinite loop at
while n%i == 0
For numbers that are divisible by 2, your function returns 2. The execution of the return statement exits the function.
Even if you change the while in while n%i == 0 to if n% == 0 the function will not work.
You will have to restructure your code.
An easy fix would be to check for all factors of a number till n/2 + 1 and return the factors (in a list) that are prime (which can be checked using a separate isprime function.
def isprime(n):
for x in range(2,n//2+1):
if n%x==0:
return False
return True
def compute(n):
arr = []
for i in range(2, n//2+1):
if n % i == 0:
if isprime(i):
arr.append(i)
return arr

If you want all prime factors (which i guess) you shouldn't return values before you have all prime factors in a list for example.
And with this programm you only check once for a 2. But 4 has 2*2. Put it in a loop.

So this code saves all prime factors in a list:
from math import sqrt, ceil
def get_prime_factors(n):
prime_factors = []
while n > 1:
for i in range (2, ceil(sqrt(n))+1):
if n % i == 0:
possible_prime_number = i
while True:
for j in range(2, possible_prime_number//2-1):
if possible_prime_number % j == 0:
possible_prime_number //= j
break
prime_factors.append(possible_prime_number)
n //= possible_prime_number
break
return prime_factors
if you only want the highest one replace return prime_factors with return max(prime_factors)

OK. I think counting upto 600 billion is ridiculous(considering that i am on a 32 bit system). So here is the final code that i am setteling on which gives answer in acceptable time upto 99 million, without using any array and only 1 for loop.
from math import ceil
# Computes only prime factors of n
def compute(n):
arr = 0
# Checks if n is divisible by 2, and if it is divisible,sets arr =2
if n % 2 == 0:
arr = 2
# Now that 2 is eliminated we only check for odd numbers upto (square root of n)+1
for i in range(1, ceil(n/2) + 1, 2):
if n % i == 0:
arr = i
n //= i
return str(arr)
print(compute(999999999))
P.S.:- If you see any possible improvement in my code plz tell me.

Why doesn't my prime factorizer terminate?

Using python. The 'print' step in my prime factorizer works, but it never returns 1, and the list isn't generated either. Where is my program getting stuck?
from math import ceil, floor, sqrt
primeList = []
primeFactorList = []
def primeList(x):
primeList = [2]
for n in range(2,x):
for p in primeList:
if n%p == 0:
break
elif p == primeList[-1]:
primeList.append(n)
return(primeList)
# Generates list of prime numbers less than x
def primeFactorizer(x):
primeFactorList = []
while x != 1:
for p in primeList(x):
if x%p == 0:
primeFactorList.append(p)
x = x/p
print(x)
break
return(primeFactorList)
# Generates list of (possibly duplicate) prime factors of x
print(primeFactorizer(36))

primeListreturns primes up to but less than x.
If x in primeFactorizer is a prime number, x%p is never true inside the for-loop, therefore x never changes.
Forget about the primes and test every number for factorization:
def factorize(number):
factors = []
for factor in range(2, number + 1):
while number % factor == 0:
factors.append(factor)
number //= factor
print(number)
if number == 1:
break
return factors
print(factorize(36))

Summation of primes : Using Generator vs w/o Generator

Project Euler 10th problem:
Find the sum of all the primes below two million.
Well I came up with two solutions :
USING GENERATOR FUNCTION
def gen_primes():
n = 2
primes = []
while True:
for p in primes:
if n % p == 0:
break
else:
primes.append(n)
yield n
n += 1
flag = True
sum=0
p=gen_primes()
while flag:
prime=p.__next__()
if prime > 2000000:
flag = False
else:
sum+=prime
print(sum)
W/O GENERATOR
def prime(number):
if number ==1:
return -1
else:
for a in (range(1,int(number**0.5)+1))[::2]:
if number%a==0 and a!=1:
return False
else:
return True
count=2
for i in (range(1,2000000))[::2]:
if prime(i)==True and i!=1:
count+=i
else:
continue
print(count)
Surprisingly, the latter (w/o g) takes 7.4 seconds whereas the former (using g) takes around 10 minutes !!!
Why is it so? Thought the generator would perform better because of fewer steps.

Your generator is doing a lot of unnecessary work. It checks all primes up to n when it only needs to check primes up to the square root of n. Here is a modified version of your generator function with the unnecessary work removed:
from time import time
t = time()
def gen_primes():
primes = []
yield 2
n = 3
while True:
is_prime = True
upper_limit = n ** .5
for p in primes:
if n % p == 0:
is_prime = False
break
elif p > upper_limit:
break
if is_prime:
primes.append(n)
yield n
n += 2 # only need to check divisibility by odd numbers
sum = 0
for prime in gen_primes():
if prime > 2_000_000:
break
else:
sum += prime
print("time:", time() - t)
print(sum)
This takes 2.3 seconds on my computer. The version without the generator takes 4.8 seconds on my computer.
If you're interested in a much more efficient algorithm for finding prime numbers, check out the Sieve of Eratosthenes.
https://en.wikipedia.org/wiki/Sieve_of_Eratosthenes

Here's a rework of your generator code that's almost twice as fast as the non-generator code. Similar to #DanielGiger's solution (+1) but attempts to be simpler and possibly a hair faster. It uses multiple squaring instead of a single square root (may or may not win out) and doesn't need a boolean flag:
def gen_primes():
yield 2
primes = [2]
number = 3
while True:
for prime in primes:
if prime * prime > number:
yield number
primes.append(number)
break
if number % prime == 0:
break
number += 2
total = 0
generator = gen_primes()
while True:
prime = next(generator)
if prime > 2_000_000:
break
total += prime
print(total)
Here's an equivalent rework of your non-generator code that also attempts to be simpler and just a hair faster. My rule of thumb is to deal with 2 and less as special cases and then write a clean odd divisor check:
def is_prime(number):
if number < 2:
return False
if number % 2 == 0:
return number == 2
for divisor in range(3, int(number**0.5) + 1, 2):
if number % divisor == 0:
return False
return True
total = 2
for i in range(3, 2_000_000, 2):
if is_prime(i):
total += i
print(total)
Also, your code generates an entire range of numbers and then throws away the even numbers -- we can use the third argument to range() to generate only the odd numbers in the first place.
In the end, the use of a generator has nothing to do with the general performance of your two solutions. You can rewrite your second solution as a generator:
def gen_primes():
yield 2
number = 3
while True:
for divisor in range(3, int(number**0.5) + 1, 2):
if number % divisor == 0:
break
else: # no break
yield number
number += 2
The difference between the two solutions is one uses only primes as trial divisors (at the cost of storage) and the other uses odd numbers (pseudoprimes) as trial divisors (with no storage cost). Time-wise, the one that does fewer trial divisions, wins.

efficient ways of finding the largest prime factor of a number

I'm doing this problem on a site that I found (project Euler), and there is a question that involves finding the largest prime factor of a number. My solution fails at really large numbers so I was wondering how this code could be streamlined?
""" Find the largest prime of a number """
def get_factors(number):
factors = []
for integer in range(1, number + 1):
if number%integer == 0:
factors.append(integer)
return factors
def test_prime(number):
prime = True
for i in range(1, number + 1):
if i!=1 and i!=2 and i!=number:
if number%i == 0:
prime = False
return prime
def test_for_primes(lst):
primes = []
for i in lst:
if test_prime(i):
primes.append(i)
return primes
################################################### program starts here
def find_largest_prime_factor(i):
factors = get_factors(i)
prime_factors = test_for_primes(factors)
print prime_factors
print find_largest_prime_factor(22)
#this jams my computer
print find_largest_prime_factor(600851475143)
it fails when using large numbers, which is the point of the question I guess. (computer jams, tells me I have run out of memory and asks me which programs I would like to stop).
************************************ thanks for the answer. there was actually a couple bugs in the code in any case. so the fixed version of this (inefficient code) is below.
""" Find the largest prime of a number """
def get_factors(number):
factors = []
for integer in xrange(1, number + 1):
if number%integer == 0:
factors.append(integer)
return factors
def test_prime(number):
prime = True
if number == 1 or number == 2:
return prime
else:
for i in xrange(2, number):
if number%i == 0:
prime = False
return prime
def test_for_primes(lst):
primes = []
for i in lst:
if test_prime(i):
primes.append(i)
return primes
################################################### program starts here
def find_largest_prime_factor(i):
factors = get_factors(i)
print factors
prime_factors = test_for_primes(factors)
return prime_factors
print find_largest_prime_factor(x)

From your approach you are first generating all divisors of a number n in O(n) then you test which of these divisors is prime in another O(n) number of calls of test_prime (which is exponential anyway).
A better approach is to observe that once you found out a divisor of a number you can repeatedly divide by it to get rid of all of it's factors. Thus, to get the prime factors of, say 830297 you test all small primes (cached) and for each one which divides your number you keep dividing:
830297 is divisible by 13 so now you'll test with 830297 / 13 = 63869
63869 is still divisible by 13, you are at 4913
4913 doesn't divide by 13, next prime is 17 which divides 4913 to get 289
289 is still a multiple of 17, you have 17 which is the divisor and stop.
For further speed increase, after testing the cached prime numbers below say 100, you'll have to test for prime divisors using your test_prime function (updated according to #Ben's answer) but go on reverse, starting from sqrt. Your number is divisible by 71, the next number will give an sqrt of 91992 which is somewhat close to 6857 which is the largest prime factor.

Here is my favorite simple factoring program for Python:
def factors(n):
wheel = [1,2,2,4,2,4,2,4,6,2,6]
w, f, fs = 0, 2, []
while f*f <= n:
while n % f == 0:
fs.append(f)
n /= f
f, w = f + wheel[w], w+1
if w == 11: w = 3
if n > 1: fs.append(n)
return fs
The basic algorithm is trial division, using a prime wheel to generate the trial factors. It's not quite as fast as trial division by primes, but there's no need to calculate or store the prime numbers, so it's very convenient.
If you're interested in programming with prime numbers, you might enjoy this essay at my blog.

My solution is in C#. I bet you can translate it into python. I've been test it with random long integer ranging from 1 to 1.000.000.000 and it's doing good. You can try to test the result with online prime calculator Happy coding :)
public static long biggestPrimeFactor(long num) {
for (int div = 2; div < num; div++) {
if (num % div == 0) {
num \= div
div--;
}
}
return num;
}

The naive primality test can be improved upon in several ways:
Test for divisibility by 2 separately, then start your loop at 3 and go by 2's
End your loop at ceil(sqrt(num)). You're guaranteed to not find a prime factor above this number
Generate primes using a sieve beforehand, and only move onto the naive way if you've exhausted the numbers in your sieve.
Beyond these easy fixes, you're going to have to look up more efficient factorization algorithms.

Use a Sieve of Eratosthenes to calculate your primes.
from math import sqrt
def sieveOfEratosthenes(n):
primes = range(3, n + 1, 2) # primes above 2 must be odd so start at three and increase by 2
for base in xrange(len(primes)):
if primes[base] is None:
continue
if primes[base] >= sqrt(n): # stop at sqrt of n
break
for i in xrange(base + (base + 1) * primes[base], len(primes), primes[base]):
primes[i] = None
primes.insert(0,2)
return filter(None, primes)

The point to prime factorization by trial division is, the most efficient solution for factorizing just one number doesn't need any prime testing.
You just enumerate your possible factors in ascending order, and keep dividing them out of the number in question - all thus found factors are guaranteed to be prime. Stop when the square of current factor exceeds the current number being factorized. See the code in user448810's answer.
Normally, prime factorization by trial division is faster on primes than on all numbers (or odds etc.), but when factorizing just one number, to find the primes first to test divide by them later, will might cost more than just going ahead with the increasing stream of possible factors. This enumeration is O(n), prime generation is O(n log log n), with the Sieve of Eratosthenes (SoE), where n = sqrt(N) for the top limit N. With trial division (TD) the complexity is O(n1.5/(log n)2).
Of course the asymptotics are to be taken just as a guide, actual code's constant factors might change the picture. Example, execution times for a Haskell code derived from here and here, factorizing 600851475149 (a prime):
2.. 0.57 sec
2,3,5,... 0.28 sec
2,3,5,7,11,13,17,19,... 0.21 sec
primes, segmented TD 0.65 sec first try
0.05 sec subsequent runs (primes are memoized)
primes, list-based SoE 0.44 sec first try
0.05 sec subsequent runs (primes are memoized)
primes, array-based SoE 0.15 sec first try
0.06 sec subsequent runs (primes are memoized)
so it depends. Of course factorizing the composite number in question, 600851475143, is near instantaneous, so it doesn't matter there.

Here is an example in JavaScript
function largestPrimeFactor(val, divisor = 2) {
let square = (val) => Math.pow(val, 2);
while ((val % divisor) != 0 && square(divisor) <= val) {
divisor++;
}
return square(divisor) <= val
? largestPrimeFactor(val / divisor, divisor)
: val;
}

I converted the solution from #under5hell to Python (2.7x). what an efficient way!
def largest_prime_factor(num, div=2):
while div < num:
if num % div == 0 and num/div > 1:
num = num /div
div = 2
else:
div = div + 1
return num
>> print largest_prime_factor(600851475143)
6857
>> print largest_prime_factor(13195)
29

Try this piece of code:
from math import *
def largestprime(n):
i=2
while (n>1):
if (n % i == 0):
n = n/i
else:
i=i+1
print i
strinput = raw_input('Enter the number to be factorized : ')
a = int(strinput)
largestprime(a)

Old one but might help
def isprime(num):
if num > 1:
# check for factors
for i in range(2,num):
if (num % i) == 0:
return False
return True
def largest_prime_factor(bignumber):
prime = 2
while bignumber != 1:
if bignumber % prime == 0:
bignumber = bignumber / prime
else:
prime = prime + 1
while isprime(prime) == False:
prime = prime+1
return prime
number = 600851475143
print largest_prime_factor(number)

I Hope this would help and easy to understand.
A = int(input("Enter the number to find the largest prime factor:"))
B = 2
while (B <(A/2)):
if A%B != 0:
B = B+1
else:
A = A/B
C = B
B = 2
print (A)

This code for getting the largest prime factor, with nums value of prime_factor(13195) when I run it, will return the result in less than a second.
but when nums value gets up to 6digits it will return the result in 8seconds.
Any one has an idea of what is the best algorithm for the solution...
def prime_factor(nums):
if nums < 2:
return 0
primes = [2]
x = 3
while x <= nums:
for i in primes:
if x%i==0:
x += 2
break
else:
primes.append(x)
x += 2
largest_prime = primes[::-1]
# ^^^ code above to gets all prime numbers
intermediate_tag = []
factor = []
# this code divide nums by the largest prime no. and return if the
# result is an integer then append to primefactor.
for i in largest_prime:
x = nums/i
if x.is_integer():
intermediate_tag.append(x)
# this code gets the prime factors [29.0, 13.0, 7.0, 5.0]
for i in intermediate_tag:
y = nums/i
factor.append(y)
print(intermediate_tag)
print(f"prime factor of {nums}:==>",factor)
prime_factor(13195)
[455.0, 1015.0, 1885.0, 2639.0]
prime factor of 13195:==> [29.0, 13.0, 7.0, 5.0]

Beginner looking for advice/help on this code (Python) [duplicate]

I was having issues in printing a series of prime numbers from one to hundred. I can't figure our what's wrong with my code.
Here's what I wrote; it prints all the odd numbers instead of primes:
for num in range(1, 101):
for i in range(2, num):
if num % i == 0:
break
else:
print(num)
break

You need to check all numbers from 2 to n-1 (to sqrt(n) actually, but ok, let it be n).
If n is divisible by any of the numbers, it is not prime. If a number is prime, print it.
for num in range(2,101):
prime = True
for i in range(2,num):
if (num%i==0):
prime = False
if prime:
print (num)
You can write the same much shorter and more pythonic:
for num in range(2,101):
if all(num%i!=0 for i in range(2,num)):
print (num)
As I've said already, it would be better to check divisors not from 2 to n-1, but from 2 to sqrt(n):
import math
for num in range(2,101):
if all(num%i!=0 for i in range(2,int(math.sqrt(num))+1)):
print (num)
For small numbers like 101 it doesn't matter, but for 10**8 the difference will be really big.
You can improve it a little more by incrementing the range you check by 2, and thereby only checking odd numbers. Like so:
import math
print 2
for num in range(3,101,2):
if all(num%i!=0 for i in range(2,int(math.sqrt(num))+1)):
print (num)
Edited:
As in the first loop odd numbers are selected, in the second loop no
need to check with even numbers, so 'i' value can be start with 3 and
skipped by 2.
import math
print 2
for num in range(3,101,2):
if all(num%i!=0 for i in range(3,int(math.sqrt(num))+1, 2)):
print (num)

I'm a proponent of not assuming the best solution and testing it. Below are some modifications I did to create simple classes of examples by both #igor-chubin and #user448810. First off let me say it's all great information, thank you guys. But I have to acknowledge #user448810 for his clever solution, which turns out to be the fastest by far (of those I tested). So kudos to you, sir! In all examples I use a values of 1 million (1,000,000) as n.
Please feel free to try the code out.
Good luck!
Method 1 as described by Igor Chubin:
def primes_method1(n):
out = list()
for num in range(1, n+1):
prime = True
for i in range(2, num):
if (num % i == 0):
prime = False
if prime:
out.append(num)
return out
Benchmark: Over 272+ seconds
Method 2 as described by Igor Chubin:
def primes_method2(n):
out = list()
for num in range(1, n+1):
if all(num % i != 0 for i in range(2, num)):
out.append(num)
return out
Benchmark: 73.3420000076 seconds
Method 3 as described by Igor Chubin:
def primes_method3(n):
out = list()
for num in range(1, n+1):
if all(num % i != 0 for i in range(2, int(num**.5 ) + 1)):
out.append(num)
return out
Benchmark: 11.3580000401 seconds
Method 4 as described by Igor Chubin:
def primes_method4(n):
out = list()
out.append(2)
for num in range(3, n+1, 2):
if all(num % i != 0 for i in range(2, int(num**.5 ) + 1)):
out.append(num)
return out
Benchmark: 8.7009999752 seconds
Method 5 as described by user448810 (which I thought was quite clever):
def primes_method5(n):
out = list()
sieve = [True] * (n+1)
for p in range(2, n+1):
if (sieve[p]):
out.append(p)
for i in range(p, n+1, p):
sieve[i] = False
return out
Benchmark: 1.12000012398 seconds
Notes: Solution 5 listed above (as proposed by user448810) turned out to be the fastest and honestly quiet creative and clever. I love it. Thanks guys!!
EDIT: Oh, and by the way, I didn't feel there was any need to import the math library for the square root of a value as the equivalent is just (n**.5). Otherwise I didn't edit much other then make the values get stored in and output array to be returned by the class. Also, it would probably be a bit more efficient to store the results to a file than verbose and could save a lot on memory if it was just one at a time but would cost a little bit more time due to disk writes. I think there is always room for improvement though. So hopefully the code makes sense guys.
2021 EDIT: I know it's been a really long time but I was going back through my Stackoverflow after linking it to my Codewars account and saw my recently accumulated points, which which was linked to this post. Something I read in the original poster caught my eye for #user448810, so I decided to do a slight modification mentioned in the original post by filtering out odd values before appending the output array. The results was much better performance for both the optimization as well as latest version of Python 3.8 with a result of 0.723 seconds (prior code) vs 0.504 seconds using 1,000,000 for n.
def primes_method5(n):
out = list()
sieve = [True] * (n+1)
for p in range(2, n+1):
if (sieve[p] and sieve[p]%2==1):
out.append(p)
for i in range(p, n+1, p):
sieve[i] = False
return out
Nearly five years later, I might know a bit more but I still just love Python, and it's kind of crazy to think it's been that long. The post honestly feels like it was made a short time ago and at the time I had only been using python about a year I think. And it still seems relevant. Crazy. Good times.

Instead of trial division, a better approach, invented by the Greek mathematician Eratosthenes over two thousand years ago, is to sieve by repeatedly casting out multiples of primes.
Begin by making a list of all numbers from 2 to the maximum desired prime n. Then repeatedly take the smallest uncrossed number and cross out all of its multiples; the numbers that remain uncrossed are prime.
For example, consider the numbers less than 30. Initially, 2 is identified as prime, then 4, 6, 8, 10, 12, 14, 16, 18, 20, 22, 24, 26, 28 and 30 are crossed out. Next 3 is identified as prime, then 6, 9, 12, 15, 18, 21, 24, 27 and 30 are crossed out. The next prime is 5, so 10, 15, 20, 25 and 30 are crossed out. And so on. The numbers that remain are prime: 2, 3, 5, 7, 11, 13, 17, 19, 23, and 29.
def primes(n):
sieve = [True] * (n+1)
for p in range(2, n+1):
if (sieve[p]):
print p
for i in range(p, n+1, p):
sieve[i] = False
An optimized version of the sieve handles 2 separately and sieves only odd numbers. Also, since all composites less than the square of the current prime are crossed out by smaller primes, the inner loop can start at p^2 instead of p and the outer loop can stop at the square root of n. I'll leave the optimized version for you to work on.

break ends the loop that it is currently in. So, you are only ever checking if it divisible by 2, giving you all odd numbers.
for num in range(2,101):
for i in range(2,num):
if (num%i==0):
break
else:
print(num)
that being said, there are much better ways to find primes in python than this.
for num in range(2,101):
if is_prime(num):
print(num)
def is_prime(n):
for i in range(2, int(math.sqrt(n)) + 1):
if n % i == 0:
return False
return True

The best way to solve the above problem would be to use the "Miller Rabin Primality Test" algorithm. It uses a probabilistic approach to find if a number is prime or not. And it is by-far the most efficient algorithm I've come across for the same.
The python implementation of the same is demonstrated below:
def miller_rabin(n, k):
# Implementation uses the Miller-Rabin Primality Test
# The optimal number of rounds for this test is 40
# See http://stackoverflow.com/questions/6325576/how-many-iterations-of-rabin-miller-should-i-use-for-cryptographic-safe-primes
# for justification
# If number is even, it's a composite number
if n == 2:
return True
if n % 2 == 0:
return False
r, s = 0, n - 1
while s % 2 == 0:
r += 1
s //= 2
for _ in xrange(k):
a = random.randrange(2, n - 1)
x = pow(a, s, n)
if x == 1 or x == n - 1:
continue
for _ in xrange(r - 1):
x = pow(x, 2, n)
if x == n - 1:
break
else:
return False
return True

Igor Chubin's answer can be improved. When testing if X is prime, the algorithm doesn't have to check every number up to the square root of X, it only has to check the prime numbers up to the sqrt(X). Thus, it can be more efficient if it refers to the list of prime numbers as it is creating it. The function below outputs a list of all primes under b, which is convenient as a list for several reasons (e.g. when you want to know the number of primes < b). By only checking the primes, it saves time at higher numbers (compare at around 10,000; the difference is stark).
from math import sqrt
def lp(b)
primes = [2]
for c in range(3,b):
e = round(sqrt(c)) + 1
for d in primes:
if d <= e and c%d == 0:
break
else:
primes.extend([c])
return primes

My way of listing primes to an entry number without too much hassle is using the property that you can get any number that is not a prime with the summation of primes.
Therefore, if you divide the entry number with all primes below it, and it is not evenly divisible by any of them, you know that you have a prime.
Of course there are still faster ways of getting the primes, but this one already performs quite well, especially because you are not dividing the entry number by any number, but quite only the primes all the way to that number.
With this code I managed on my computer to list all primes up to 100 000 in less than 4 seconds.
import time as t
start = t.clock()
primes = [2,3,5,7]
for num in xrange(3,100000,2):
if all(num%x != 0 for x in primes):
primes.append(num)
print primes
print t.clock() - start
print sum(primes)

A Python Program function module that returns the 1'st N prime numbers:
def get_primes(count):
"""
Return the 1st count prime integers.
"""
result = []
x=2
while len(result) in range(count):
i=2
flag=0
for i in range(2,x):
if x%i == 0:
flag+=1
break
i=i+1
if flag == 0:
result.append(x)
x+=1
pass
return result

A simpler and more efficient way of solving this is storing all prime numbers found previously and checking if the next number is a multiple of any of the smaller primes.
n = 1000
primes = [2]
for i in range(3, n, 2):
if not any(i % prime == 0 for prime in primes):
primes.append(i)
print(primes)
Note that any is a short circuit function, in other words, it will break the loop as soon as a truthy value is found.

we can make a list of prime numbers using sympy library
import sympy
lower=int(input("lower value:")) #let it be 30
upper=int(input("upper value:")) #let it be 60
l=list(sympy.primerange(lower,upper+1)) #[31,37,41,43,47,53,59]
print(l)

Here's a simple and intuitive version of checking whether it's a prime in a RECURSIVE function! :) (I did it as a homework assignment for an MIT class)
In python it runs very fast until 1900. IF you try more than 1900, you'll get an interesting error :) (Would u like to check how many numbers your computer can manage?)
def is_prime(n, div=2):
if div> n/2.0: return True
if n% div == 0:
return False
else:
div+=1
return is_prime(n,div)
#The program:
until = 1000
for i in range(until):
if is_prime(i):
print i
Of course... if you like recursive functions, this small code can be upgraded with a dictionary to seriously increase its performance, and avoid that funny error.
Here's a simple Level 1 upgrade with a MEMORY integration:
import datetime
def is_prime(n, div=2):
global primelist
if div> n/2.0: return True
if div < primelist[0]:
div = primelist[0]
for x in primelist:
if x ==0 or x==1: continue
if n % x == 0:
return False
if n% div == 0:
return False
else:
div+=1
return is_prime(n,div)
now = datetime.datetime.now()
print 'time and date:',now
until = 100000
primelist=[]
for i in range(until):
if is_prime(i):
primelist.insert(0,i)
print "There are", len(primelist),"prime numbers, until", until
print primelist[0:100], "..."
finish = datetime.datetime.now()
print "It took your computer", finish - now , " to calculate it"
Here are the resuls, where I printed the last 100 prime numbers found.
time and date: 2013-10-15 13:32:11.674448
There are 9594 prime numbers, until 100000
[99991, 99989, 99971, 99961, 99929, 99923, 99907, 99901, 99881, 99877, 99871, 99859, 99839, 99833, 99829, 99823, 99817, 99809, 99793, 99787, 99767, 99761, 99733, 99721, 99719, 99713, 99709, 99707, 99689, 99679, 99667, 99661, 99643, 99623, 99611, 99607, 99581, 99577, 99571, 99563, 99559, 99551, 99529, 99527, 99523, 99497, 99487, 99469, 99439, 99431, 99409, 99401, 99397, 99391, 99377, 99371, 99367, 99349, 99347, 99317, 99289, 99277, 99259, 99257, 99251, 99241, 99233, 99223, 99191, 99181, 99173, 99149, 99139, 99137, 99133, 99131, 99119, 99109, 99103, 99089, 99083, 99079, 99053, 99041, 99023, 99017, 99013, 98999, 98993, 98981, 98963, 98953, 98947, 98939, 98929, 98927, 98911, 98909, 98899, 98897] ...
It took your computer 0:00:40.871083 to calculate it
So It took 40 seconds for my i7 laptop to calculate it. :)

# computes first n prime numbers
def primes(n=1):
from math import sqrt
count = 1
plist = [2]
c = 3
if n <= 0 :
return "Error : integer n not >= 0"
while (count <= n - 1): # n - 1 since 2 is already in plist
pivot = int(sqrt(c))
for i in plist:
if i > pivot : # check for primae factors 'till sqrt c
count+= 1
plist.append(c)
break
elif c % i == 0 :
break # not prime, no need to iterate anymore
else :
continue
c += 2 # skipping even numbers
return plist

You are terminating the loop too early. After you have tested all possibilities in the body of the for loop, and not breaking, then the number is prime. As one is not prime you have to start at 2:
for num in xrange(2, 101):
for i in range(2,num):
if not num % i:
break
else:
print num
In a faster solution you only try to divide by primes that are smaller or equal to the root of the number you are testing. This can be achieved by remembering all primes you have already found. Additionally, you only have to test odd numbers (except 2). You can put the resulting algorithm into a generator so you can use it for storing primes in a container or simply printing them out:
def primes(limit):
if limit > 1:
primes_found = [(2, 4)]
yield 2
for n in xrange(3, limit + 1, 2):
for p, ps in primes_found:
if ps > n:
primes_found.append((n, n * n))
yield n
break
else:
if not n % p:
break
for i in primes(101):
print i
As you can see there is no need to calculate the square root, it is faster to store the square for each prime number and compare each divisor with this number.

How about this? Reading all the suggestions I used this:
prime=[2]+[num for num in xrange(3,m+1,2) if all(num%i!=0 for i in range(2,int(math.sqrt(num))+1))]
Prime numbers up to 1000000
root#nfs:/pywork# time python prime.py
78498
real 0m6.600s
user 0m6.532s
sys 0m0.036s

Adding to the accepted answer, further optimization can be achieved by using a list to store primes and printing them after generation.
import math
Primes_Upto = 101
Primes = [2]
for num in range(3,Primes_Upto,2):
if all(num%i!=0 for i in Primes):
Primes.append(num)
for i in Primes:
print i

Here is the simplest logic for beginners to get prime numbers:
p=[]
for n in range(2,50):
for k in range(2,50):
if n%k ==0 and n !=k:
break
else:
for t in p:
if n%t ==0:
break
else:
p.append(n)
print p

n = int(input())
is_prime = lambda n: all( n%i != 0 for i in range(2, int(n**.5)+1) )
def Prime_series(n):
for i in range(2,n):
if is_prime(i) == True:
print(i,end = " ")
else:
pass
Prime_series(n)
Here is a simplified answer using lambda function.

def function(number):
for j in range(2, number+1):
if all(j % i != 0 for i in range(2, j)):
print(j)
function(13)

for i in range(1, 100):
for j in range(2, i):
if i % j == 0:
break
else:
print(i)

Print n prime numbers using python:
num = input('get the value:')
for i in range(2,num+1):
count = 0
for j in range(2,i):
if i%j != 0:
count += 1
if count == i-2:
print i,

def prime_number(a):
yes=[]
for i in range (2,100):
if (i==2 or i==3 or i==5 or i==7) or (i%2!=0 and i%3!=0 and i%5!=0 and i%7!=0 and i%(i**(float(0.5)))!=0):
yes=yes+[i]
print (yes)

min=int(input("min:"))
max=int(input("max:"))
for num in range(min,max):
for x in range(2,num):
if(num%x==0 and num!=1):
break
else:
print(num,"is prime")
break

This is a sample program I wrote to check if a number is prime or not.
def is_prime(x):
y=0
if x<=1:
return False
elif x == 2:
return True
elif x%2==0:
return False
else:
root = int(x**.5)+2
for i in xrange (2,root):
if x%i==0:
return False
y=1
if y==0:
return True

n = int(raw_input('Enter the integer range to find prime no :'))
p = 2
while p<n:
i = p
cnt = 0
while i>1:
if p%i == 0:
cnt+=1
i-=1
if cnt == 1:
print "%s is Prime Number"%p
else:
print "%s is Not Prime Number"%p
p+=1

Using filter function.
l=range(1,101)
for i in range(2,10): # for i in range(x,y), here y should be around or <= sqrt(101)
l = filter(lambda x: x==i or x%i, l)
print l

for num in range(1,101):
prime = True
for i in range(2,num/2):
if (num%i==0):
prime = False
if prime:
print num

f=0
sum=0
for i in range(1,101):
for j in range(1,i+1):
if(i%j==0):
f=f+1
if(f==2):
sum=sum+i
print i
f=0
print sum

The fastest & best implementation of omitting primes:
def PrimeRanges2(a, b):
arr = range(a, b+1)
up = int(math.sqrt(b)) + 1
for d in range(2, up):
arr = omit_multi(arr, d)

Here is a different approach that trades space for faster search time. This may be fastest so.
import math
def primes(n):
if n < 2:
return []
numbers = [0]*(n+1)
primes = [2]
# Mark all odd numbers as maybe prime, leave evens marked composite.
for i in xrange(3, n+1, 2):
numbers[i] = 1
sqn = int(math.sqrt(n))
# Starting with 3, look at each odd number.
for i in xrange(3, len(numbers), 2):
# Skip if composite.
if numbers[i] == 0:
continue
# Number is prime. Would have been marked as composite if there were
# any smaller prime factors already examined.
primes.append(i)
if i > sqn:
# All remaining odd numbers not marked composite must be prime.
primes.extend([i for i in xrange(i+2, len(numbers), 2)
if numbers[i]])
break
# Mark all multiples of the prime as composite. Check odd multiples.
for r in xrange(i*i, len(numbers), i*2):
numbers[r] = 0
return primes
n = 1000000
p = primes(n)
print "Found", len(p), "primes <=", n

Adding my own version, just to show some itertools tricks v2.7:
import itertools
def Primes():
primes = []
a = 2
while True:
if all(itertools.imap(lambda p : a % p, primes)):
yield a
primes.append(a)
a += 1
# Print the first 100 primes
for _, p in itertools.izip(xrange(100), Primes()):
print p