Develop Reference

Prime checker including non primes

I am trying to solve Project Euler number 7.
By listing the first six prime numbers: 2, 3, 5, 7, 11, and 13, we can see that the 6th prime is 13.
What is the 10 001st prime number?
First thing that came into my mind was using length of list. This was very ineffective solution as it took over a minute. This is the used code.
def ch7():
primes = []
x = 2
while len(primes) != 10001:
for i in range(2, x):
if x % i == 0:
break
else:
primes.append(x)
x += 1
print(primes[-1])
ch7()
# Output is: 104743.
This works well but I wanted to reach faster solution. Therefore I did a bit of research and found out that in order to know if a number is a prime, we need to test whether it is divisible by any number up to its square root e.g. in order to know if 100 is a prime we dont need to divide it by every number up to 100, but only up to 10.
When I implemented this finding weird thing happened. The algorithm included some non primes. To be exact 66 of them. This is the adjusted code:
import math
primes = []
def ch7():
x = 2
while len(primes) != 10001:
for i in range(2, math.ceil(math.sqrt(x))):
if x % i == 0:
break
else:
primes.append(x)
x += 1
print(primes[-1])
ch7()
# Output is 104009
This solution takes under a second but it includes some non primes. I used math.ceil() in order to get int instead of float but I figured it should not be a problem since it still tests by every int up to square root of x.
Thank you for any suggestions.

Your solution generates a list of primes, but doens't use that list for anything but extracting the last element. We can toss that list, and cut the time of the code in half by treating 2 as a special case, and only testing odd numbers:
def ch7(limit=10001): # assume limit is >= 1
prime = 2
number = 3
count = 1
while count < limit:
for divisor in range(3, int(number ** 0.5) + 1, 2):
if number % divisor == 0:
break
else: # no break
prime = number
count += 1
number += 2
return prime
print(ch7())
But if you're going to collect a list of primes, you can use that list to get even more speed out of the program (about 10% for the test limits in use) by using those primes as divisors instead of odd numbers:
def ch7(limit=10001): # assume limit is >= 1
primes = [2]
number = 3
while len(primes) < limit:
for prime in primes:
if prime * prime > number: # look no further
primes.append(number)
break
if number % prime == 0: # composite
break
else: # may never be needed but prime gaps can be arbitrarily large
primes.append(number)
number += 2
return primes[-1]
print(ch7())
BTW, your second solution, even with the + 1 fix you mention in the comments, comes up with one prime beyond the correct answer. This is due to the way your code (mis)handles the prime 2.

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.

Making a prime generator

This is supposed to be a prime generator. I try running this but it doesn't print out the integers. The program will also end right away. I don't know if its running
def prime_gen():
start = 1
while start:
if start % start == 0:
print(start)
start += 1

First what is a prime? A number that have no divisors but itself.
The easy way is to load that numbers, starting by two and check if that number can't be divided by all the previous ones, if its so then you got a new one; you can make it a generator by using yield instead of return
def prime_gen():
primes = [2]
yield 2
n = 3
while True:
for p in primes:
if n % p == 0:
n += 1
break
else:
primes.append(n)
yield n
Example:
pg = prime_gen()
next(pg)
2
next(pg)
3
next(pg)
5
next(pg)
7
next(pg)
11

You have 2 main issues here:
Your algorithm doesn't calculate primes - it runs infinitely (while start), and prints a number when number % number == 0 (aka number modulo number) which is always true. So this is an infinite loop printing the numbers from 1 up.
you never call prime_gen() which is why the program doesn't do anything.
You have created a function but did not call it.
for a nice way of calculating primes, take a look at Sieve of Eratosthenes (Wikipedia).

You can do something like:
def prime_gen(limit):
current = 2 # 1 is not exactly prime
primes = []
while current <= limit:
isPrime = True
for p in primes:
if current % p == 0:
isPrime = False
break
if isPrime:
primes.append(current)
print current, ", ",
current += 1
return primes

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

Finding the largest prime number "within" a number

For this question, I need to find the largest prime number within a larger number. For the purpose of the example, let's say the larger number is "123456789", then some of the numbers I would have to check are 12, 456, 234567, etc.
I wrote some Python code to figure this out, but it is running very slow for the number I am trying to check. The actual number I am working with is about 10000 digits, so there are a lot of numbers I need to look at. Here is my code:
num = "123456789"
def isPrime(n):
# 0 and 1 are not primes
if n < 2:
return False
# 2 is the only even prime number
if n == 2:
return True
# all other even numbers are not primes
if not n & 1:
return False
# range starts with 3 and only needs to go up the squareroot of n
# for all odd numbers
for x in range(3, long(n**0.5)+1, 2):
if n % x == 0:
return False
return True
def largestPrime():
largest = 2
for i in range(0,len(num)):
for j in range(i+1,len(num)):
if isPrime(long(num[i:j])):
if long(num[i:j]) > largest:
largest =long(num[i:j])
print largest
def main():
largestPrime()
main()
I'm pretty sure this code gives the correct answer, but as I said, it's really slow. Can anyone help me figure out how to speed this up?
Thanks for any help!

I'd probably use the strategy of starting with the total number of digits and seeing if that's prime. Then keep decreasing the digits by one while shifting over to the left to see if that's prime. Let me explain with an example:
123456789
First check the 9-digit number: 123456789
Then check the 8-digit numbers: 23456789, 12345678
Then Check the 7-digit numbers: 3456789, 2345678, 1234567
etc.

One problem I see is that for some large numbers you are going to be testing the same number many times. For example for '123456712345671234567', your code will test '1234567' 3 times. I suggest you make a set that contains no duplicates, then run your prime test on each number. I also think that sorting the numbers is a good idea because we can stop after the first prime is found.
Next if you are dealing with large numbers (e.g. 10000 digits), I suggest using a statistical primality test. Below I made a Miller-Rabin primality test using pseudocode from wikipedia.
I have pretty much rewritten your code :P
import random
num = '3456647867843652345683947582397589235623896514759283590867843652345683947582397589235623896514759283590784235876867843652345683947582397589235623896514759283590784235876867843652345683947582397589235623896514759283590784235876867843652345683947582397589235623896514759283590784235876867843652345683947582397589235623896514759283590784235876867843652345683947582397589235623896514759283590784235876867843652345683947582397589235623896514759283590784235876784235876324650'
def probablyPrime(num, k):
"""Using Miller-Rabin primality test"""
if num == 2 or num == 3:
return True
if num < 2:
return False
if not num & 1:
return False
# find s and d such that n−1 = (2**s)*d with d odd
d = (num-1) >> 1
s = 1
while not (d & 1):
d = d >> 1
s += 1
# run k times
for _ in range(k):
a = random.randint(2, num-2)
x = pow(a, d, num) # more efficient than x = a**d % num
if not (x == 1 or x == num-1):
for _ in range(s-1):
x = (x**2) % num
if x == 1:
return False
if x == num-1:
break
if not x == num-1:
return False
return True
def largestPrime(num):
num_list = set([])
for i in range(0,len(num)+1):
for j in range(i+1,len(num)+1):
inum = int(num[i:j])
# Don't append numbers that have already appeared
if inum not in num_list:
num_list.add(inum)
# Convert to list and sort
num_list = list(num_list)
num_list.sort(reverse=True)
for num in num_list:
print('Checking ' + str(num))
if probablyPrime(num,100):
print('\n' + str(num) + ' is probably the largest prime!')
return
largestPrime(num)
Another way to improve speed might be python's multiprocessing package.

Code:
def isprime(n):
if n == 2:
return str(n)+" is the biggest prime"
if n % 2 == 0:
return isprime(n-1) #not prime, check again for next biggest number
max = n**0.5+1
i = 3
while i <= max:
if n % i == 0:
return isprime(n-1) #not prime, check again for next biggest number
i+=2
return str(n)+" is the biggest prime"
print "Testing 7:",isprime(7)
print "Testing 23:",isprime(23)
print "Testing 2245:",isprime(2245)
print "Testing 222457:",isprime(222457)
print "Testing 727245628:",isprime(727245628)
Output:
>>>
Testing 7: 7 is the biggest prime
Testing 23: 23 is the biggest prime
Testing 2245: 2243 is the biggest prime
Testing 222457: 222437 is the biggest prime
Testing 727245628: 727245613 is the biggest prime