Files
euler-project/problems/013_problem/013_problem.py
2020-08-02 21:06:44 -04:00

281 lines
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Python

# # Problem 13:
#
# [Euler Project #13](https://projecteuler.net/problem=13)
#
#
# > Work out the first ten digits of the sum of the following one-hundred 50-digit numbers.
#
# > 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
#
#
# ---
import os
import pprint
import time # Typically imported for sleep function, to slow down execution in terminal.
import typing
import decorators # Typically imported to compute execution duration of functions.
import math
import numpy
# ### Import the data table above. Let's be lazy and use the nice multi-cursor feature of the code editor.
numbers = [ '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'
]
# Data Prep
# - Firstly, this data input creates a list which have cells of the ```string``` data type.
# - The strings should be parsed into type ```int``` at some point.
#
# ### Solution Approach
# Can we just employ old-school arithmetic by summing the integers by columns, right to left, <br>
# carrying over anything greater than *9* to the next column?
# loop over all 50 numbers in the input to convert the string
# into a list of characters, still as tpye: string
for row in range(len(numbers)):
numbers[row] = list(numbers[row])
# loop across the newly formed list to convert the string
# character into an integer
for digit in range(len(numbers[row])):
numbers[row][digit] = int(numbers[row][digit])
# time to employ the "old math" by running down the columns
# and summing... Dont forget to carry-over!
# Let's store the sums into a list...
solution_digits=[]
column_carryover = 0
print(len(numbers))
print(len(numbers[0]))
for places in range(len(numbers[0])):
# initialize the column sum
places = len(numbers[0])-places-1
#print(places)
column_sum = 0
for term in range(len(numbers)):
#print("row=",term,", column=",places)
column_sum+=numbers[term][places]
column_sum+=column_carryover
print(column_sum)
column_carryover=0
column_sum_element = int(list(str(column_sum))[-1])
solution_digits.append(column_sum_element)
column_sum *= 0.1
column_carryover = column_sum.__trunc__()
solution_digits.append(column_carryover)
print(solution_digits)
solution_digits.reverse()
string=""
for i in solution_digits[:10]:
string+=str(i)
print("The solution is ",string)