wkta

import os
from time import sleep
import random

DISP_WIDTH = 96
DISP_HEIGHT = 32
NB_MAX_CHAR_GEN=64

class MovingChar():
    def __init__(self , display):

wkta

import pygame
from time import sleep
import random
import sys

BLACK = ( 0, 0, 0)
NB_PIX_BATCH = 64
DISP_WIDTH = 640
DISP_HEIGHT = 480
REFR_RATE = 0.008

wkta

from __future__ import print_function
import sys

def printMultiples(k, sup_bound):
    map(print, [ k*i for i in xrange(1,1+(sup_bound/k) ) ] )

if (len(sys.argv)<3 ):
    print("this program prints multiples of k up to a cernain bound")
    print("usage: python "+sys.argv[0]+" k sup_bound")
    sys.exit(1)

wkta

import pygame
from time import sleep

#replace this by some cool sound effect & music !
SFX = 'alrighty.wav'
MUSIC = '4sequence.mp3'

# init pygame ; load n play a sound effect
pygame.init()
soundObj = pygame.mixer.Sound('alrighty.wav')

wkta

import pygame
from pygame.locals import *
import sys
from time import sleep

# init. pygame libr; create the screen and diplays a help message in the console
pygame.init() 
DISPLAYSURF = pygame.display.set_mode((640, 480))
src_color = pygame.Color('antiquewhite3')
targ_color = pygame.Color('yellow')

wkta

import random
import pygame
from pygame.locals import *

def generateRandColorObj():
    return pygame.Color(
        random.randint(0,255), random.randint(0,255), random.randint(0,255), 255 )

def addSquare(start_pos, end_pos, color ):
    square_list.append( (start_pos, end_pos, color))    

wkta

import time
current_milli_time = lambda: int(round(time.time() * 1000))

# we use the Factory Design Pattern, RngCreator is the abstract class
class RngCreator(object):
    def createRng(self):
        raise NotImplementedError("Please Implement this method")
    def inputParams(self, p_dict):
        raise NotImplementedError("Please Implement this method")

wkta

import random
# This code implements the so-called "descent method" which is a kind of NEIGHBOR SEARCH METHOD 
# often used in optimization.
# I apply it to the simple problem of finding the minimum value in a huge random matrix
# I count the nb of values tested to show how this kind of search is efficient in practice

# I initiale a random matrix and compute the global min. value on-the-fly to know
# if the descent method eventually succeeds in finding it.
N = 128 ; M = 128
MAX_VAL = 255

wkta

# this program draws a random TREE-LIKE shape, inspired by L-Systems
import pygame
from time import sleep
import random
import sys
DISP_WIDTH = 640
DISP_HEIGHT = 480

def randPeriod():
    return random.choice((1, 16,  64) ) #determines the slope with wich the emerging branch grows

wkta

import random
import pygame
from pygame.locals import *
SCREEN_W = 640
SCREEN_H = 480

def refeshFunction():
    DISPLAYSURF.fill(  pygame.Color('antiquewhite3') )
    # draws the paddle
    rect_rep_paddle =\