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  • Sorting a meta-list by first element of children lists in Python

    - by thismachinechills
    I have a list, root, of lists, root[child0], root[child1], etc. I want to sort the children of the root list by the first value in the child list, root[child0][0], which is an int. Example: import random children = 10 root = [[random.randint(0, children), "some value"] for child in children] I want to sort root from greatest to least by the first element of each of it's children. I've taken a look at some previous entries that used sorted() and a lamda function I'm entirely unfamiliar with, so I'm unsure of how to apply that to my problem. Appreciate any direction that can by given Thanks

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  • Python 3: Recursivley find if number is even

    - by pythonhack
    I am writing a program that must find if a number is even or not. It needs to follow this template. I can get it to find if a number is even or not recursively (call function and subtract 2, base case zero), but I am having a hard time following this template, based on how the isEven function is called in the main function. Any help would be greatly appreciated. Write a recursive function called isEven that finds whether a number is even or not: def isEven() #recursivley determine whether number is even or not def main(): number=int(input(“Enter a number : “)) if (isEven(number)): print(“Number is even”) else: print(“Number is not even”) main() Thank you! Appreciate it.

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  • threading in Python taking up too much CPU

    - by KevinShaffer
    I wrote a chat program and have a GUI running using Tkinter, and to go and check when new messages have arrived, I create a new thread so Tkinter keeps doing its thing without locking up while the new thread goes and grabs what I need and updates the Tkinter window. This however becomes a huge CPU hog, and my guess is that it has to do somehow with the fact that the Thread is started and never really released when the function is done. Here's the relevant code (it's ugly and not optimized at the moment, but it gets the job done, and itself does not use too much processing power, as when I run it not threaded, it doesn't take up much CPU but it locks up Tkinter) Note: This is inside of a class, hence the extra tab. def interim(self): threading.Thread(target=self.readLog).start() self.after(5000,self.interim) def readLog(self): print 'reading' try: length = len(str(self.readNumber)) f = open('chatlog'+str(myport),'r') temp = f.readline().replace('\n','') while (temp[:length] != str(self.readNumber)) or temp[0] == '<': temp = f.readline().replace('\n','') while temp: if temp[0] != '<': self.updateChat(temp[length:]) self.readNumber +=1 else: self.updateChat(temp) temp = f.readline().replace('\n','') f.close() Is there a way to better manage the threading so I don't consume 100% of the CPU very quickly?

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  • Python 3 order of testing undetermined

    - by user578598
    string='a' p=0 while (p <len(string)) & (string[p]!='c') : p +=1 print ('the end but the process already died ') while (p <1) & (string[p]!='c') : IndexError: string index out of range I want to test a condition up to the end of a string (example string length=1) why are both parts of the and executed is the condition is already false! as long as p < len(string). the second part does not even need executing. if it does a lot of performance can be lost

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  • Ideas for student parallel programming project

    - by chi42
    I'm looking to do a parallel programming project in C (probably using pthreads or maybe OpenMP) for a class. It will done by a group of about four students, and should take about 4 weeks. I was thinking it would be interesting to attack some NP-complete problem with a more complex algorithm like a genetic algo with simulated annealing, but I'm not sure if it would be a big enough project. Anyone knew of any cool problems that could benefit from a parallel approach?

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  • Understanding VS2010 C# parallel profiling results

    - by Haggai
    I have a program with many independent computations so I decided to parallelize it. I use Parallel.For/Each. The results were okay for a dual-core machine - CPU utilization of about 80%-90% most of the time. However, with a dual Xeon machine (i.e. 8 cores) I get only about 30%-40% CPU utilization, although the program spends quite a lot of time (sometimes more than 10 seconds) on the parallel sections, and I see it employs about 20-30 more threads in those sections compared to serial sections. Each thread takes more than 1 second to complete, so I see no reason for them to work in parallel - unless there is a synchronization problem. I used the built-in profiler of VS2010, and the results are strange. Even though I use locks only in one place, the profiler reports that about 85% of the program's time is spent on synchronization (also 5-7% sleep, 5-7% execution, under 1% IO). The locked code is only a cache (a dictionary) get/add: bool esn_found; lock (lock_load_esn) esn_found = cache.TryGetValue(st, out esn); if(!esn_found) { esn = pData.esa_inv_idx.esa[term_idx]; esn.populate(pData.esa_inv_idx.datafile); lock (lock_load_esn) { if (!cache.ContainsKey(st)) cache.Add(st, esn); } } lock_load_esn is a static member of the class of type Object. esn.populate reads from a file using a separate StreamReader for each thread. However, when I press the Synchronization button to see what causes the most delay, I see that the profiler reports lines which are function entrance lines, and doesn't report the locked sections themselves. It doesn't even report the function that contains the above code (reminder - the only lock in the program) as part of the blocking profile with noise level 2%. With noise level at 0% it reports all the functions of the program, which I don't understand why they count as blocking synchronizations. So my question is - what is going on here? How can it be that 85% of the time is spent on synchronization? How do I find out what really is the problem with the parallel sections of my program? Thanks.

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  • Parallel For Loop - Problems when adding to a List - Possible .Net Bugs

    - by Kevin Crowell
    I am having some issues involving Parallel for loops and adding to a List. The problem is, the same code may generate different output at different times. I have set up some test code below. In this code, I create a List of 10,000 int values. 1/10th of the values will be 0, 1/10th of the values will be 1, all the way up to 1/10th of the values being 9. After setting up this List, I setup a Parallel for loop that iterates through the list. If the current number is 0, I add a value to a new List. After the Parallel for loop completes, I output the size of the list. The size should always be 1,000. Most of the time, the correct answer is given. However, I have seen 3 possible incorrect outcomes occur: The size of the list is less than 1,000 An IndexOutOfRangeException occurs @ doubleList.Add(0.0); An ArgumentException occurs @ doubleList.Add(0.0); The message for the ArgumentException given was: Destination array was not long enough. Check destIndex and length, and the array's lower bounds. What could be causing the errors? Is this a .Net bug? Is there something I can do to prevent this from happening? Please try the code for yourself. If you do not get an error, try it a few times. Please also note that you probably will not see any errors using a single-core machine. using System; using System.Collections.Generic; using System.Threading.Tasks; namespace ParallelTest { class Program { static void Main(string[] args) { List<int> intList = new List<int>(); List<double> doubleList = new List<double>(); for (int i = 0; i < 250; i++) { intList.Clear(); doubleList.Clear(); for (int j = 0; j < 10000; j++) { intList.Add(j % 10); } Parallel.For(0, intList.Count, j => { if (intList[j] == 0) { doubleList.Add(0.0); } }); if (doubleList.Count != 1000) { Console.WriteLine("On iteration " + i + ": List size = " + doubleList.Count); } } Console.WriteLine("\nPress any key to exit."); Console.ReadKey(); } } }

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  • parallel java libraries

    - by jetru
    I'm looking for Java libraries/applications which are parallel and feature objects that can be queried in parallel. That is, there is/are objects in which multiple types of operations can be made from different threads and these will be synchronized. It would be helpful if someone could ideas of where I could find such applications as well. EDIT: Actually, language doesn't matter so much, so C++, Python, anything is welcome

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  • Parallel For Loop - Problems when adding to a List

    - by Kevin Crowell
    I am having some issues involving Parallel for loops and adding to a List. The problem is, the same code may generate different output at different times. I have set up some test code below. In this code, I create a List of 10,000 int values. 1/10th of the values will be 0, 1/10th of the values will be 1, all the way up to 1/10th of the values being 9. After setting up this List, I setup a Parallel for loop that iterates through the list. If the current number is 0, I add a value to a new List. After the Parallel for loop completes, I output the size of the list. The size should always be 1,000. Most of the time, the correct answer is given. However, I have seen 3 possible incorrect outcomes occur: The size of the list is less than 1,000 An IndexOutOfRangeException occurs @ doubleList.Add(0.0); An ArgumentException occurs @ doubleList.Add(0.0); The message for the ArgumentException given was: Destination array was not long enough. Check destIndex and length, and the array's lower bounds. What could be causing the errors? Is this a .Net bug? Is there something I can do to prevent this from happening? Please try the code for yourself. If you do not get an error, try it a few times. Please also note that you probably will not see any errors using a single-core machine. using System; using System.Collections.Generic; using System.Threading.Tasks; namespace ParallelTest { class Program { static void Main(string[] args) { List<int> intList = new List<int>(); List<double> doubleList = new List<double>(); for (int i = 0; i < 250; i++) { intList.Clear(); doubleList.Clear(); for (int j = 0; j < 10000; j++) { intList.Add(j % 10); } Parallel.For(0, intList.Count, j => { if (intList[j] == 0) { doubleList.Add(0.0); } }); if (doubleList.Count != 1000) { Console.WriteLine("On iteration " + i + ": List size = " + doubleList.Count); } } Console.WriteLine("\nPress any key to exit."); Console.ReadKey(); } } }

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  • Project Euler 10: (Iron)Python

    - by Ben Griswold
    In my attempt to learn (Iron)Python out in the open, here’s my solution for Project Euler Problem 10.  As always, any feedback is welcome. # Euler 10 # http://projecteuler.net/index.php?section=problems&id=10 # The sum of the primes below 10 is 2 + 3 + 5 + 7 = 17. # Find the sum of all the primes below two million. import time start = time.time() def primes_to_max(max): primes, number = [2], 3 while number < max: isPrime = True for prime in primes: if number % prime == 0: isPrime = False break if (prime * prime > number): break if isPrime: primes.append(number) number += 2 return primes primes = primes_to_max(2000000) print sum(primes) print "Elapsed Time:", (time.time() - start) * 1000, "millisecs" a=raw_input('Press return to continue')

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  • What's wrong with relative imports in Python?

    - by Oddthinking
    I recently upgraded versions of pylint, a popular Python style-checker. It has gone ballistic throughout my code, pointing out places where I import modules in the same package, without specifying the full package path. The new error message is W0403. W0403: Relative import %r, should be %r Used when an import relative to the package directory is detected. Example For example, if my packages are structured like this: /cake /__init__.py /icing.py /sponge.py /drink and in the sponge package I write: import icing instead of import cake.icing I will get this error. While I understand that not all Pylint messages are of equal importance, and I am not afraid to dismiss them, I don't understand why such a practice is considered a poor idea. I was hoping someone could explain the pitfalls, so I could improve my coding style rather than (as I currently plan to do) turning off this apparently spurious warning.

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  • Project Euler 15: (Iron)Python

    - by Ben Griswold
    In my attempt to learn (Iron)Python out in the open, here’s my solution for Project Euler Problem 15.  As always, any feedback is welcome. # Euler 15 # http://projecteuler.net/index.php?section=problems&id=15 # Starting in the top left corner of a 2x2 grid, there # are 6 routes (without backtracking) to the bottom right # corner. How many routes are their in a 20x20 grid? import time start = time.time() def factorial(n): if n == 0: return 1 else: return n * factorial(n-1) rows, cols = 20, 20 print factorial(rows+cols) / (factorial(rows) * factorial(cols)) print "Elapsed Time:", (time.time() - start) * 1000, "millisecs" a=raw_input('Press return to continue')

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  • Project Euler 9: (Iron)Python

    - by Ben Griswold
    In my attempt to learn (Iron)Python out in the open, here’s my solution for Project Euler Problem 9.  As always, any feedback is welcome. # Euler 9 # http://projecteuler.net/index.php?section=problems&id=9 # A Pythagorean triplet is a set of three natural numbers, # a b c, for which, # a2 + b2 = c2 # For example, 32 + 42 = 9 + 16 = 25 = 52. # There exists exactly one Pythagorean triplet for which # a + b + c = 1000. Find the product abc. import time start = time.time() product = 0 def pythagorean_triplet(): for a in range(1,501): for b in xrange(a+1,501): c = 1000 - a - b if (a*a + b*b == c*c): return a*b*c print pythagorean_triplet() print "Elapsed Time:", (time.time() - start) * 1000, "millisecs" a=raw_input('Press return to continue')

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  • Compound assignment operators in Python's Numpy library

    - by Leonard
    The "vectorizing" of fancy indexing by Python's numpy library sometimes gives unexpected results. For example: import numpy a = numpy.zeros((1000,4), dtype='uint32') b = numpy.zeros((1000,4), dtype='uint32') i = numpy.random.random_integers(0,999,1000) j = numpy.random.random_integers(0,3,1000) a[i,j] += 1 for k in xrange(1000): b[i[k],j[k]] += 1 Gives different results in the arrays 'a' and 'b' (i.e. the appearance of tuple (i,j) appears as 1 in 'a' regardless of repeats, whereas repeats are counted in 'b'). This is easily verified as follows: numpy.sum(a) 883 numpy.sum(b) 1000 It is also notable that the fancy indexing version is almost two orders of magnitude faster than the for loop. My question is: "Is there an efficient way for numpy to compute the repeat counts as implemented using the for loop in the provided example?"

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  • Project Euler 5: (Iron)Python

    - by Ben Griswold
    In my attempt to learn (Iron)Python out in the open, here’s my solution for Project Euler Problem 5.  As always, any feedback is welcome. # Euler 5 # http://projecteuler.net/index.php?section=problems&id=5 # 2520 is the smallest number that can be divided by each # of the numbers from 1 to 10 without any remainder. # What is the smallest positive number that is evenly # divisible by all of the numbers from 1 to 20? import time start = time.time() def gcd(a, b): while b: a, b = b, a % b return a def lcm(a, b): return a * b // gcd(a, b) print reduce(lcm, range(1, 20)) print "Elapsed Time:", (time.time() - start) * 1000, "millisecs" a=raw_input('Press return to continue')

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  • Project Euler 8: (Iron)Python

    - by Ben Griswold
    In my attempt to learn (Iron)Python out in the open, here’s my solution for Project Euler Problem 8.  As always, any feedback is welcome. # Euler 8 # http://projecteuler.net/index.php?section=problems&id=8 # Find the greatest product of five consecutive digits # in the following 1000-digit number import time start = time.time() number = '\ 73167176531330624919225119674426574742355349194934\ 96983520312774506326239578318016984801869478851843\ 85861560789112949495459501737958331952853208805511\ 12540698747158523863050715693290963295227443043557\ 66896648950445244523161731856403098711121722383113\ 62229893423380308135336276614282806444486645238749\ 30358907296290491560440772390713810515859307960866\ 70172427121883998797908792274921901699720888093776\ 65727333001053367881220235421809751254540594752243\ 52584907711670556013604839586446706324415722155397\ 53697817977846174064955149290862569321978468622482\ 83972241375657056057490261407972968652414535100474\ 82166370484403199890008895243450658541227588666881\ 16427171479924442928230863465674813919123162824586\ 17866458359124566529476545682848912883142607690042\ 24219022671055626321111109370544217506941658960408\ 07198403850962455444362981230987879927244284909188\ 84580156166097919133875499200524063689912560717606\ 05886116467109405077541002256983155200055935729725\ 71636269561882670428252483600823257530420752963450' max = 0 for i in xrange(0, len(number) - 5): nums = [int(x) for x in number[i:i+5]] val = reduce(lambda agg, x: agg*x, nums) if val > max: max = val print max print "Elapsed Time:", (time.time() - start) * 1000, "millisecs" a=raw_input('Press return to continue')

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  • Python or C server hosting for indie development

    - by Richard Fabian
    I've written a lot of the game, but it's singleplayer. Now we want to join up and play together. I want to host it like an MMO, but haven't got any personal ability to host (no static IPs or direct access to a reasonable router that will allow me to port forward) so I wondered if there were any free / very cheap hosting solutions for people developing games that need to develop their MMO side. In my case it's a world server for a 2D game where the world map can be changed by the players. So, GAE sounds expensive, as there would be quite a few updates per second (I heard they bill for data updates but not for download, but can't find refernce to billing anywhere on the FAQs) I'd prefer to be able to write the server in python as that's what the game is written in (with pygame), but C is fine, and maybe even better as it might prompt me to write some more performant world generator code ;)

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  • Project Euler 2: (Iron)Python

    - by Ben Griswold
    In my attempt to learn (Iron)Python out in the open, here’s my solution for Project Euler Problem 2.  As always, any feedback is welcome. # Euler 2 # http://projecteuler.net/index.php?section=problems&id=2 # Find the sum of all the even-valued terms in the # Fibonacci sequence which do not exceed four million. # Each new term in the Fibonacci sequence is generated # by adding the previous two terms. By starting with 1 # and 2, the first 10 terms will be: # 1, 2, 3, 5, 8, 13, 21, 34, 55, 89, ... # Find the sum of all the even-valued terms in the # sequence which do not exceed four million. import time start = time.time() total = 0 previous = 0 i = 1 while i <= 4000000: if i % 2 == 0: total +=i # variable swapping removes the need for a temp variable i, previous = previous, previous + i print total print "Elapsed Time:", (time.time() - start) * 1000, "millisecs" a=raw_input('Press return to continue')

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  • PHP developer wanting to learn python

    - by dclowd9901
    I'm pretty familiar at this point with PHP (Javascript, too), up to the point of OOP in PHP, and am looking to branch out my knowledge. I'm looking at Python next, but a lot of it is a bit alien to me as a PHP developer. I'm less concerned about learning the language itself. I'm positive there's plenty of good resources, documentation and libraries to help me get the code down. I'm less sure about the technical aspects of how to set up a dev environment, unit testing and other more mundane details that are very important, aid in rapid development, but aren't as widely covered. Are there any good resources out there for this?

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  • Project Euler 16: (Iron)Python

    - by Ben Griswold
    In my attempt to learn (Iron)Python out in the open, here’s my solution for Project Euler Problem 16.  As always, any feedback is welcome. # Euler 16 # http://projecteuler.net/index.php?section=problems&id=16 # 2^15 = 32768 and the sum of its digits is # 3 + 2 + 7 + 6 + 8 = 26. # What is the sum of the digits of the number 2^1000? import time start = time.time() print sum([int(i) for i in str(2**1000)]) print "Elapsed Time:", (time.time() - start) * 1000, "millisecs" a=raw_input('Press return to continue')

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  • Project Euler 7: (Iron)Python

    - by Ben Griswold
    In my attempt to learn (Iron)Python out in the open, here’s my solution for Project Euler Problem 7.  As always, any feedback is welcome. # Euler 7 # http://projecteuler.net/index.php?section=problems&id=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 10001st prime number? import time start = time.time() def nthPrime(nth): primes = [2] number = 3 while len(primes) < nth: isPrime = True for prime in primes: if number % prime == 0: isPrime = False break if (prime * prime > number): break if isPrime: primes.append(number) number += 2 return primes[nth - 1] print nthPrime(10001) print "Elapsed Time:", (time.time() - start) * 1000, "millisecs" a=raw_input('Press return to continue')

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  • Finding the html tag value with Python [on hold]

    - by MrWho
    Consider a html page, which contains a line like below: file: 'http://google.com/video.mp4' I want to search for google.com/video.mp4 in that file and save it in a variable.I want to code it with python. Shortly, I want to elicit a link from a html page, so I need to get the link by using regular expressions or the other techniques in which I'm asking about. PS: What should I exactly try to clarify?it's really annoying that the administrators don't even say what is exactly unclear about the question, they've just learned to close or on hold the topics!

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  • Project Euler 13: (Iron)Python

    - by Ben Griswold
    In my attempt to learn (Iron)Python out in the open, here’s my solution for Project Euler Problem 13.  As always, any feedback is welcome. # Euler 13 # http://projecteuler.net/index.php?section=problems&id=13 # Work out the first ten digits of the sum of the # following one-hundred 50-digit numbers. import time start = time.time() number_string = '\ 37107287533902102798797998220837590246510135740250\ 46376937677490009712648124896970078050417018260538\ 74324986199524741059474233309513058123726617309629\ 91942213363574161572522430563301811072406154908250\ 23067588207539346171171980310421047513778063246676\ 89261670696623633820136378418383684178734361726757\ 28112879812849979408065481931592621691275889832738\ 44274228917432520321923589422876796487670272189318\ 47451445736001306439091167216856844588711603153276\ 70386486105843025439939619828917593665686757934951\ 62176457141856560629502157223196586755079324193331\ 64906352462741904929101432445813822663347944758178\ 92575867718337217661963751590579239728245598838407\ 58203565325359399008402633568948830189458628227828\ 80181199384826282014278194139940567587151170094390\ 35398664372827112653829987240784473053190104293586\ 86515506006295864861532075273371959191420517255829\ 71693888707715466499115593487603532921714970056938\ 54370070576826684624621495650076471787294438377604\ 53282654108756828443191190634694037855217779295145\ 36123272525000296071075082563815656710885258350721\ 45876576172410976447339110607218265236877223636045\ 17423706905851860660448207621209813287860733969412\ 81142660418086830619328460811191061556940512689692\ 51934325451728388641918047049293215058642563049483\ 62467221648435076201727918039944693004732956340691\ 15732444386908125794514089057706229429197107928209\ 55037687525678773091862540744969844508330393682126\ 18336384825330154686196124348767681297534375946515\ 80386287592878490201521685554828717201219257766954\ 78182833757993103614740356856449095527097864797581\ 16726320100436897842553539920931837441497806860984\ 48403098129077791799088218795327364475675590848030\ 87086987551392711854517078544161852424320693150332\ 59959406895756536782107074926966537676326235447210\ 69793950679652694742597709739166693763042633987085\ 41052684708299085211399427365734116182760315001271\ 65378607361501080857009149939512557028198746004375\ 35829035317434717326932123578154982629742552737307\ 94953759765105305946966067683156574377167401875275\ 88902802571733229619176668713819931811048770190271\ 25267680276078003013678680992525463401061632866526\ 36270218540497705585629946580636237993140746255962\ 24074486908231174977792365466257246923322810917141\ 91430288197103288597806669760892938638285025333403\ 34413065578016127815921815005561868836468420090470\ 23053081172816430487623791969842487255036638784583\ 11487696932154902810424020138335124462181441773470\ 63783299490636259666498587618221225225512486764533\ 67720186971698544312419572409913959008952310058822\ 95548255300263520781532296796249481641953868218774\ 76085327132285723110424803456124867697064507995236\ 37774242535411291684276865538926205024910326572967\ 23701913275725675285653248258265463092207058596522\ 29798860272258331913126375147341994889534765745501\ 18495701454879288984856827726077713721403798879715\ 38298203783031473527721580348144513491373226651381\ 34829543829199918180278916522431027392251122869539\ 40957953066405232632538044100059654939159879593635\ 29746152185502371307642255121183693803580388584903\ 41698116222072977186158236678424689157993532961922\ 62467957194401269043877107275048102390895523597457\ 23189706772547915061505504953922979530901129967519\ 86188088225875314529584099251203829009407770775672\ 11306739708304724483816533873502340845647058077308\ 82959174767140363198008187129011875491310547126581\ 97623331044818386269515456334926366572897563400500\ 42846280183517070527831839425882145521227251250327\ 55121603546981200581762165212827652751691296897789\ 32238195734329339946437501907836945765883352399886\ 75506164965184775180738168837861091527357929701337\ 62177842752192623401942399639168044983993173312731\ 32924185707147349566916674687634660915035914677504\ 99518671430235219628894890102423325116913619626622\ 73267460800591547471830798392868535206946944540724\ 76841822524674417161514036427982273348055556214818\ 97142617910342598647204516893989422179826088076852\ 87783646182799346313767754307809363333018982642090\ 10848802521674670883215120185883543223812876952786\ 71329612474782464538636993009049310363619763878039\ 62184073572399794223406235393808339651327408011116\ 66627891981488087797941876876144230030984490851411\ 60661826293682836764744779239180335110989069790714\ 85786944089552990653640447425576083659976645795096\ 66024396409905389607120198219976047599490197230297\ 64913982680032973156037120041377903785566085089252\ 16730939319872750275468906903707539413042652315011\ 94809377245048795150954100921645863754710598436791\ 78639167021187492431995700641917969777599028300699\ 15368713711936614952811305876380278410754449733078\ 40789923115535562561142322423255033685442488917353\ 44889911501440648020369068063960672322193204149535\ 41503128880339536053299340368006977710650566631954\ 81234880673210146739058568557934581403627822703280\ 82616570773948327592232845941706525094512325230608\ 22918802058777319719839450180888072429661980811197\ 77158542502016545090413245809786882778948721859617\ 72107838435069186155435662884062257473692284509516\ 20849603980134001723930671666823555245252804609722\ 53503534226472524250874054075591789781264330331690' total = 0 for i in xrange(0, 100 * 50 - 1, 50): total += int(number_string[i:i+49]) print str(total)[:10] print "Elapsed Time:", (time.time() - start) * 1000, "millisecs" a=raw_input('Press return to continue')

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