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Submitted by Bryce on Tue, 03/19/2013 - 09:59
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It's been to long since I posted a solution to one of these challenges. How time flies when you're having fun.
Here's the problem:
If the numbers 1 to 5 are written out in words: one, two, three, four, five, then there are 3 + 3 + 5 + 4 + 4 = 19 letters used in total.
If all the numbers from 1 to 1000 (one thousand) inclusive were written out in words, how many letters would be used?
Here is the python code:
#!/usr/bin/env python ones = {'1': 'one', '2': 'two', '3': 'three', '4': 'four', '5': 'five', '6': 'six', '7': 'seven', '8': 'eight', '9': 'nine', '0': ''} tens = {'2': 'twenty', '3': 'thirty', '4': 'forty', '5': 'fifty', '6': 'sixty', '7': 'seventy', '8': 'eighty', '9': 'ninety'} teens = {'10': 'ten', '11': 'eleven', '12': 'twelve', '13': 'thriteen', '14': 'fourteen', '15': 'fifteen', '16': 'sixteen', '17': 'seventeen', '18': 'eighteen', '19': 'nineteen'} hundreds = {0: 0, 1: "onehundredand", 2: "twohundredand", 3: "threehundredand", 4: "fourhundredand", 5: "fivehundredand", 6: "sixhundredand", 7: "sevenhundredand", 8: "eighthundredand", 9: "ninehundredand" } if __name__ == "__main__": tot = 0 for h in xrange(10): for y in xrange(1,100): try: t,o = tuple(str(y)) if t is '1': tot += len("{h}{t}".format(h=hundreds[h], t=teens[t + o])) else: tot += len("{h}{t}{o}".format(h=hundreds[h], t=tens[t], o=ones[o])) except ValueError: tot += len("{h}{o}".format(h=hundreds[h], o=ones[str(y)])) tot += len('onethousand') print tot
Even though I wrote it, I still look at it and think "that's not mine." It's been a long time since I wrote a for loop within a for loop. There isn't anything wrong with it, it's just not my style. This time however I wasn't really able to come up with a solution that would allow me to break out of the two for loops.
The one part of the code that I was surprised "worked" war breaking up the digits by turning the number to a string then a tuple. This allowed me to easily test an exception. This exception will only be thrown 10% of the time. While exceptions might be expensive, the other 90% of the time the code hums along without using a conditional. Everything has costs, but I think that the cost of throwing an exception 10% of the time as opposed to testing a conditional 100% of the time is a cost I'm willing to accept.
I will admit that I did not code up another solution in a different programming language. While part of that is due to being lazy - it's good for the soul once and a while - I'm also not sure how I can code this up in a functional language. I'm sure it can be done, I just don't know how (If anyone has a link or idea please share it.) But because I do like to compare things I tweaked the code to run within python 3.3.0. The differences in time are so minimal that I'm not even going to post it. If you're really inspired you can read the python 3 code here.
Questions and comments welcomed. One quick side note to my readers: I'm getting married this year (Yay!) and a lot of my free time is spent juggling and planning. So I might not be blogging as frequently as usual. Thanks for your patience.
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Submitted by Bryce on Thu, 10/25/2012 - 09:12
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I'm not dead yet! I've just been insanely busy the last month or two with changing jobs and preparing my first programming presentation for BayPiggies and Silicon Valley Code Camp (which is a post for the near future). Both of these have kept me away from my blog. Let me make it up to you with a solution to project Euler problem #16.
The challenge is:
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 21000?
Let's start with some Python code:
#!/usr/bin/python print sum([int(i) for i in str(2 ** 1000)])
For this solution, using a more functional approach definitely reduced the code base. But one thing I was a little surprised about is that having a list comprehension within the sum function is actually faster than a generator expression. Usually one hears how generator expressions are preferred over list comprehensions because they are more efficient with memory, among other reasons. However, it's actually faster to give sum a list. One quick caveat, this whole sum and list comprehension thing applies to Python 2. The same seems to be also be true for Python 3, at least from the interpreter:
>>> import timeit >>> timeit.timeit("sum(int(x) for x in str(2 ** 1000))", number=1000) 0.11109958100132644 >>> timeit.timeit("sum([int(x) for x in str(2 ** 1000)])", number=1000) 0.09597363900684286 >>> timeit.timeit("sum(int(x) for x in str(2 ** 1000))", number=10000) 1.051396899012616 >>> timeit.timeit("sum([int(x) for x in str(2 ** 1000)])", number=10000) 0.9054670640034601 >>> timeit.timeit("sum(int(x) for x in str(2 ** 1000))", number=100000) 10.498383879996254 >>> timeit.timeit("sum([int(x) for x in str(2 ** 1000)])", number=100000) 8.992312036993098
On to the Haskell code:
Maybe it's just me and my Haskell/Python-centric brain, but I think the algorithm is simple enough to easily see the similarities and differences between the two languages. If I wanted to write the Haskell code to better match the Python code (syntactic differences aside), it would look like this: (inside the Haskell interpreter)
Even though this code may be easier to read for a Python programmer, it's not “good” Haskell code. It'll get the job done, but the map is obfuscated by the list comprehension. We can also adjust the Python code to make it resemble Haskell by using map:
print sum(map(int, str(2 ** 1000)))
But that might get you “dinged” because some people think that using map is “too functional” or “not Pythonic”, even if the code might be faster. I don't subscribe to that line of thinking...but that's a discussion for another time.
Times:
python – list comprehension : .032s
python – map : .030s
haskell – list ( interpreted) : .155s
haskell – map (interpreted) : .155s
haskell – list (compiled) : .006s
haskell – map (compiled) : .006s
As always, questions, comments, and complaints are encouraged. I hope everyone will forgive me for not posting for so long... sometimes life happens.
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Submitted by Bryce on Wed, 07/25/2012 - 09:45
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“The following iterative sequence is defined for the set of positive integers: n → n/2 (n is even) n → 3n + 1 (n is odd). Using the rule above and starting with 13, we generate the following sequence: 13 → 40 → 20 → 10 → 5 → 16 → 8 → 4 → 2 → 1. It can be seen that this sequence (starting at 13 and finishing at 1) contains 10 terms. Although it has not been proved yet (Collatz Problem), it is thought that all starting numbers finish at 1. Which starting number, under one million, produces the longest chain? NOTE: Once the chain starts the terms are allowed to go above one million.”
Not many of you may be aware of this, but about a year ago I wrote up a blog post that discussed Collatz chains in Haskell. You can find that post here: . Having some of the code already written made coming up with the solution easier. However, just because I had one function doesn't mean I had the whole problem licked. I still had a fair amount of work in front of me. Below is my code from the first attempt at a solution:
module Main where import Data.List chain' 1 = [1] chain' n | n <= 0 = [] | odd n = n : chain' (n * 3 + 1) main = do let seqx = map chain' [3..1000000]
This code appears to be logically correct but was incredibly slow - so slow that after over 2 minutes it still hadn’t completed. I admit I can be a little impatient with these things from time to time, but in this case something was obviously wrong.
I devised two optimizations:
- Reverse the order of the list. I will be more likely to find the number with the longest chain near 1,000,000 than 3.
- Use odd numbers only. This is based on the fact that in the chain' function an odd number gets multiplied right off the bat, whereas an even number is instantly divided by 2, and also on the assumption that a higher number will be more likely to have a longer chain. (I admit this was a complete experiment - I had no proof that it would work ahead of time, and knew it gave me the right answer only after the fact.)
The code then morphed into:
module Main where import Data.List chain' 1 = [1] chain' n | n <= 0 = [] | odd n = n : chain' (n * 3 + 1) main = do let seqx = map chain' [999999,999997..3]
The problem I ran into with this code was that I received stack overflow errors; my list of tuples holding another long list of int’s was taking up to much memory. I fixed this problem by computing the length of the list immediately after generating it. The new code looked like this:
import Data.List chain' 1 = [1] chain' n | n <= 0 = [] | odd n = n : chain' (n * 3 + 1) main = do let seqx = map (\x → (x , length $ chain' x ) [999999,999997..3]
This got me a result within the one minute time frame, but it still wasn't the right answer. Can you figure out why? Using the great code Jedai posted in the comments of my Apache log post, I was able to get my answer and finally complete the problem:
module Main where import Data.Tuple import Data.List (sortBy) import Data.Function (on) chain' 1 = [1] chain' n | n <= 0 = [] | odd n = n : chain' (n * 3 + 1) main = do let seqx = map (\x -> (x , length $ chain' x )) [999999,999997..3]

After figuring that out, getting the python answer was a breeze:
#!/usr/bin/python """Python solution for Project Euler problem #14.""" from itertools import imap def sequence(number): t_num = number count = 1 while(t_num > 1): if t_num % 2 == 0: t_num /= 2 else: t_num = (t_num * 3) + 1 count += 1 return (count, number) if __name__ == "__main__": print max(imap(sequence, xrange(999999,3,-2)))
Here are the speed numbers:
Haskell (complied) : 14.758s
Python : 18.537s
Haskell (runghc): 15.217s
I think the use of recursion in my Haskell code is affecting its speed of computation. As I learned from problem 12, I can use the State Monad again to speed things up. But I also learned from the comments of problem 12 that some people were able to substitute a scan or fold in the State Monad’s place. So I decided to shoot for one more solution. After studying up on scan and fold, and finding that neither was really what I wanted, I found iterate. Using iterate I was able to change the program to this:
module Main where import Data.Tuple import Data.Function (on) chain' n | n < 1 = 0 main = do let seqx = map (\x -> (x , chain' x )) [999999,999997..3]
The new chain' function doesn't read as cleanly as the old one, but it does remove the recursion I was talking about earlier. The computer gods rewarded my efforts by reducing the run times to these:
Haskell (complied) : 10.933s
Haskell (runghc): 11.744s
From 14.758 to 10.933 - almost 4 seconds taken off the clock! I think a speed up like that calls for some celebrating. Which is exactly what I'm going to do before I start on problem 15.
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Submitted by Bryce on Tue, 05/22/2012 - 09:48
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Problem thirteen from Project Euler is one of those problems that's so simple, I don't understand why it's in the double digits section. The problem reads: “Work out the first ten digits of the sum of the following one-hundred 50-digit numbers.”
It then proceeds to list 100 long numbers. I'm not going to paste them here because they are in the code solutions below and I don't want to clog up the “tubez” with more redundant information than I'm about to.
Enough of my jibber-jabber. Here is my Haskell solution first (trying to change things up here):
module Main where main = do where big_number = [ 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]
followed by my Python solution:
#!/usr/bin/python """ code solution for project euler's problem #13 in python. """ from __future__ import print_function def print_10(number): print(str(number)[0:10]) if __name__ == "__main__": big_number = [ 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] print_10(sum(big_number))
and to continue adding in the spice, I have included a solution in Scala:
def main (args : Array [String ]){ val big _number = List ("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") map {BigInt(_)} val sums = big _number sum println(su10) } }
Some of you may be wondering, “Why a Scala solution?” To which I respond, “Why not?” Because that's a little short, I'll add that it has something to do with Scala starting to gain traction in the industry and me seeing if I would like to get paid to program in it.
The solution, in all three languages, is pretty simple. The recipe essentially says, “Put all numbers into a list. Get the sum of that list, turn that number into a string, and get the first 10 characters of that string.”
Times:
Haskell (compiled) : real 0m0.004s
Haskell (runghc) : real 0m0.314s
Python : real 0m0.059s
Scala (compiled) : real 0m0.757s
For the most part it's pretty standard in these tests to see performance times such that Haskell (compiled) < Python < Haskell (runghc). Java and Perl usually fall somewhere between the Haskell (compiled) and Python, in that order. To see Scala be 2x slower than Haskell (runghc) was a shocker. The only thing that makes sense to me for the slowdown is having to use the BigInt library. That is probably the biggest thing I took away from these time tests - if I want to do REALLY large number crunching and performance DOES matter, JVM-based languages might not be the best option.
A few thoughts on Scala:
If I haven't stated it already in this blog, I should now give the disclaimer that I'm not a Java fan. I know it still has its loyal followers, but I'm not one of them. Moving on. This was my first time working with Scala, and I'd like to finally welcome Java to the 21st century. While doing some research on the Scala language itself I read that “the industry” was moving to replace Java with Scala. I welcome that change. Does that mean I “like” Scala? The honest answer is, to butcher the quote the appliances from the Flintstones, “Eh, it's a language.” Scala is definitely an improvement over Java – not really that hard to do in my opinion – but, the language still feels unpolished. One quick way to kill the interpreter in Scala is to type “Int” then hit the enter key. Instead of error-ing out, the interpreter does a great job of interpreting a crash test car hitting a cement wall (I had to restart the whole thing.) When I tried the same “technique” in the Python interpreter, I got as a response and for Haskell's interpreter I received “Not in scope: data constructor `Int'”. I also found Scala's function composition to be a little lacking when compared to Haskell. I wasn't able to cleanly change the BigInt data type to String, and then only print out ten characters without requiring three separate val's. Yes, I could have used one var instead, but that's beside the point. I will admit it could be my inexperience with the language showing, so if anyone knows a smoother way to do this in Scala please share it in the comments.
All that being said, I do like the way Scala is trying to handle the reducing of Java's dot notation, and I think it's starting to make strides in the right direction in other areas. I'm open to working with Scala more, and look forward to seeing how it evolves over the next few years.
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