juliengrenier

from operator import mul
def euler8(digits, n=4):
    i = 0
    _max = 0
    while i <= len(digits)-n:
        _r = reduce(mul, [int(x) for x in digits[i:i+n]])
        if _r > _max:
            _max = _r

        i += 1

juliengrenier

def genprimes(upto):
    primes = {}
    q = 2
    i = 0
    while i < upto:
        if q not in primes:
            yield q
            i += 1
            primes[q*q] = [q]
        else:

juliengrenier

def retry_task(name, max_retries=3, ignore_result=True, queue="celery", countdown=10, exceptions=[]):
    """
        This decorator allows you to retry a celery task if it raised an exception of type defined in <exceptions>.
        Tasks are also wrapped by a commit_on_success decorator to avoid incomplete data in the database.

         arguments are :
            name:   The name of the task
            max_retries: The number of retries before giving up [default: 3]
            ignore_result: Should celery ignores the result [default: True]
            queue: The queue name [default: "celery"]

juliengrenier

function randomRange(lowerBound, upperBound){
    return lowerBound + Math.random() * (upperBound-lowerBound);
}
function draw() {
    var canvas = document.getElementById("canvas");
    var c = canvas.getContext("2d");
    
    function drawBranch(l, direction) {
          c.save();
          c.fillRect(-1, 0, 2, -l);

juliengrenier

class NullProxy(object):
    """Pretend you have a model object with three attributes:

    class Person(object):
        name = String(40)
        age = Integer()
        email = Email()

    And have a sub-class adding extra attributes:

juliengrenier

str = 'a string'
binary_representation = ''.join([bin(ord(c))[2:].zfill(8) for c in str])

juliengrenier

str = '01001000011000010111000001110000011110010010000001001110011001010111011100100000010110010110010101100001011100100111001100100001'
print ''.join([chr(int(str[i:i+8],2)) for i in range(len(str)) if i % 8 ==0])