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[파이썬] itertools 라이브러리 사용법 (순열 조합)(permutations combinations) – Python 문법

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[파이썬] itertools 라이브러리 사용법 (순열, 조합)(permutations, combinations)

오늘은 파이썬 라이브러리 중 하나인 itertools에 대해 알아보겠습니다~!

알고리즘을 풀면 조합과 순열 개념이 자주 등장하는데요,

itertools 라이브러리를 이용하면 조합과 순열을 쉽게 구할 수 있답니당.

itertools : 효율적인 루핑을 위한 이터레이터를 만드는 함수

itertools에는 여러가지 함수들이 많이 있는데, 그 중 조합형 이터레이터인

– combinations()

– combinations_with_replacement()

– product()

– permutations()

에 대해 알아봅시다.

combinations(iterable, r) : iterable에서 원소 개수가 r개인 조합 뽑기

from itertools import combinations l = [1,2,3] for i in combinations(l,2): print(i) ”’ 출력 결과: (1, 2) (1, 3) (2, 3) ”’

파이썬 공식문서에 따르면 입력 iterable의 순서에 따라 사전식 순서로 방출됩니다. 따라서, 입력 iterable이 정렬되어있으면, 조합 튜플이 정렬된 순서로 생성됩니다.

combinations_with_replacement(iterable,r) : iterable에서 원소 개수가 r개인 중복 조합 뽑기

from itertools import combinations_with_replacement l = [‘A’, ‘B’, ‘C’] for i in combinations_with_replacement(l,2): print(i) ”’ 출력결과: (‘A’, ‘A’) (‘A’, ‘B’) (‘A’, ‘C’) (‘B’, ‘B’) (‘B’, ‘C’) (‘C’, ‘C’) ”’

permutations(iterable,r=None) : iterable에서 원소 개수가 r개인 순열 뽑기

from itertools import permutations l = [‘A’, ‘B’, ‘C’] for i in permutations(l): #r을 지정하지 않거나 r=None으로 하면 최대 길이의 순열이 리턴된다! print(i) ”’ 출력결과: (‘A’, ‘B’, ‘C’) (‘A’, ‘C’, ‘B’) (‘B’, ‘A’, ‘C’) (‘B’, ‘C’, ‘A’) (‘C’, ‘A’, ‘B’) (‘C’, ‘B’, ‘A’) ”’

product(*iterables, repeat=1) : 여러 iterable의 데카르트곱 리턴

product는 다른 함수와 달리 인자로 여러 iterable을 넣어줄 수 있고 그 친구들간의 모든 짝을 지어서 리턴합니다.

from itertools import product l1 = [‘A’, ‘B’] l2 = [‘1’, ‘2’] for i in product(l1,l2,repeat=1): #l1과 l2의 모든 쌍을 지어 리턴한다 print(i) ”’ 출력결과: (‘A’, ‘1’) (‘A’, ‘2’) (‘B’, ‘1’) (‘B’, ‘2’) ”’ for i in product(l1,repeat=3): #product(l1,l1,l1,repeat=1)과 동일한 출력 print(i) ”’ 출력결과: (‘A’, ‘A’, ‘A’) (‘A’, ‘A’, ‘B’) (‘A’, ‘B’, ‘A’) (‘A’, ‘B’, ‘B’) (‘B’, ‘A’, ‘A’) (‘B’, ‘A’, ‘B’) (‘B’, ‘B’, ‘A’) (‘B’, ‘B’, ‘B’) ”’

조합, 순열이 필요한 문제에 꼭 적용해보세요!

[Python] itertools 조합 / 순열 사용법

파이썬 itertools 모듈에는 많은 함수들이 있다. ( 파이썬 itertools 공식문서 )

그 중에서도 조합 / 순열 함수인 아래 4가지 함수에 대해서 알아보자.

combinations ( ) combinations_with_replacement ( ) product ( ) permutations ( )

combinations(iterable, r)

iterable에서 원소 개수가 r개인 조합 뽑기

from itertools import combinations if __name__ == ‘__main__’ : iterator = [ 1 , 2 , 3 , 4 ] for i in combinations ( iterator , 3 ) : print ( i )

출력 결과 ( 1 , 2 , 3 ) ( 1 , 2 , 4 ) ( 1 , 3 , 4 ) ( 2 , 3 , 4 )

combinations_with_replacement(iterable,r)

iterable에서 원소 개수가 r개인 중복 조합 뽑기

from itertools import combinations_with_replacement if __name__ == ‘__main__’ : iterator = [ 1 , 2 , 3 , 4 ] for i in combinations_with_replacement ( iterator , 2 ) : print ( i )

출력 결과 ( 1 , 1 ) ( 1 , 2 ) ( 1 , 3 ) ( 1 , 4 ) ( 2 , 2 ) ( 2 , 3 ) ( 2 , 4 ) ( 3 , 3 ) ( 3 , 4 ) ( 4 , 4 )

permutations(iterable,r)

iterable에서 원소 개수가 r개인 순열 뽑기

from itertools import permutations if __name__ == ‘__main__’ : iterator = [ 1 , 2 , 3 , 4 ] for i in permutations ( iterator , 2 ) : print ( i )

출력 결과 ( 1 , 2 ) ( 1 , 3 ) ( 1 , 4 ) ( 2 , 1 ) ( 2 , 3 ) ( 2 , 4 ) ( 3 , 1 ) ( 3 , 2 ) ( 3 , 4 ) ( 4 , 1 ) ( 4 , 2 ) ( 4 , 3 )

product(*iterables, repeat=1)

여러 iterable의 데카르트곱 반환

from itertools import product if __name__ == ‘__main__’ : iterator1 = [ ‘A’ , ‘B’ , ‘C’ ] iterator2 = [ ‘1’ , ‘2’ , ‘3’ ] for i in product ( iterator1 , iterator2 , repeat = 1 ) : print ( i )

Python Itertools

Python’s Itertool is a module that provides various functions that work on iterators to produce complex iterators. This module works as a fast, memory-efficient tool that is used either by themselves or in combination to form iterator algebra.

For example, let’s suppose there are two lists and you want to multiply their elements. There can be several ways of achieving this. One can be using the naive approach i.e by iterating through the elements of both the list simultaneously and multiply them. And another approach can be using the map function i.e by passing the mul operator as a first parameter to the map function and Lists as the second and third parameter to this function. Let’s see the time taken by each approach.

Python3

import operator import time L1 = [ 1 , 2 , 3 ] L2 = [ 2 , 3 , 4 ] t1 = time.time() a, b, c = map (operator.mul, L1, L2) t2 = time.time() print ( “Result:” , a, b, c) print ( “Time taken by map function: %.6f” % (t2 – t1)) t1 = time.time() print ( “Result:” , end = ” ” ) for i in range ( 3 ): print (L1[i] * L2[i], end = ” ” ) t2 = time.time() print ( ”

Time taken by for loop: %.6f” % (t2 – t1))

Output:

Result: 2 6 12 Time taken by map function: 0.000005 Result: 2 6 12 Time taken by for loop: 0.000014

In the above example, it can be seen that the time taken by the map function is approximately half than the time taken by for loop. This shows that itertools are fast, memory-efficient tools.

Different types of iterators provided by this module are:

Infinite iterators

Iterator in Python is any Python type that can be used with a ‘for in loop’. Python lists, tuples, dictionaries, and sets are all examples of inbuilt iterators. But it is not necessary that an iterator object has to exhaust, sometimes it can be infinite. Such types of iterators are known as Infinite iterators.

Python provides three types of infinite iterators:

count(start, step): This iterator starts printing from the “start” number and prints infinitely. If steps are mentioned, the numbers are skipped else step is 1 by default. See the below example for its use with for in loop.

Example:

Python3

import itertools for i in itertools.count( 5 , 5 ): if i = = 35 : break else : print (i, end = ” ” )

Output:

5 10 15 20 25 30

cycle(iterable): This iterator prints all values in order from the passed container. It restarts printing from the beginning again when all elements are printed in a cyclic manner.

Example 1:

Python3

import itertools count = 0 for i in itertools.cycle( ‘AB’ ): if count > 7 : break else : print (i, end = ” ” ) count + = 1

Output:

A B A B A B A B

Example 2: Using the next function.

Python3

import itertools l = [ ‘Geeks’ , ‘for’ , ‘Geeks’ ] iterators = itertools.cycle(l) for i in range ( 6 ): print ( next (iterators), end = ” ” )

Combinatoric iterators

Output:

Geeks for Geeks Geeks for Geeks

repeat(val, num): This iterator repeatedly prints the passed value an infinite number of times. If the optional keyword num is mentioned, then it repeatedly prints num number of times.

Example:

Python3

import itertools print ( “Printing the numbers repeatedly : ” ) print ( list (itertools.repeat( 25 , 4 )))

Output:

Printing the numbers repeatedly : [25, 25, 25, 25]
Combinatoric iterators

The recursive generators that are used to simplify combinatorial constructs such as permutations, combinations, and Cartesian products are called combinatoric iterators.

In Python there are 4 combinatoric iterators:

Product(): This tool computes the cartesian product of input iterables. To compute the product of an iterable with itself, we use the optional repeat keyword argument to specify the number of repetitions. The output of this function is tuples in sorted order.

Example:

Python3

from itertools import product print ( “The cartesian product using repeat:” ) print ( list (product([ 1 , 2 ], repeat = 2 ))) print () print ( “The cartesian product of the containers:” ) print ( list (product([ ‘geeks’ , ‘for’ , ‘geeks’ ], ‘2’ ))) print () print ( “The cartesian product of the containers:” ) print ( list (product( ‘AB’ , [ 3 , 4 ])))

Output:

The cartesian product using repeat: [(1, 1), (1, 2), (2, 1), (2, 2)] The cartesian product of the containers: [(‘geeks’, ‘2’), (‘for’, ‘2’), (‘geeks’, ‘2’)] The cartesian product of the containers: [(‘A’, 3), (‘A’, 4), (‘B’, 3), (‘B’, 4)]
Permutations(): Permutations() as the name speaks for itself is used to generate all possible permutations of an iterable. All elements are treated as unique based on their position and not their values. This function takes an iterable and group_size, if the value of group_size is not specified or is equal to None then the value of group_size becomes the length of the iterable.

Example:

Python3

from itertools import permutations print ( “All the permutations of the given list is:” ) print ( list (permutations([ 1 , ‘geeks’ ], 2 ))) print () print ( “All the permutations of the given string is:” ) print ( list (permutations( ‘AB’ ))) print () print ( “All the permutations of the given container is:” ) print ( list (permutations( range ( 3 ), 2 )))

Output:

All the permutations of the given list is: [(1, ‘geeks’), (‘geeks’, 1)] All the permutations of the given string is: [(‘A’, ‘B’), (‘B’, ‘A’)] All the permutations of the given container is: [(0, 1), (0, 2), (1, 0), (1, 2), (2, 0), (2, 1)]
Combinations(): This iterator prints all the possible combinations(without replacement) of the container passed in arguments in the specified group size in sorted order.

Example:

Python3

from itertools import combinations print ( “All the combination of list in sorted order(without replacement) is:” ) print ( list (combinations([ ‘A’ , 2 ], 2 ))) print () print ( “All the combination of string in sorted order(without replacement) is:” ) print ( list (combinations( ‘AB’ , 2 ))) print () print ( “All the combination of list in sorted order(without replacement) is:” ) print ( list (combinations( range ( 2 ), 1 )))

Output:

All the combination of list in sorted order(without replacement) is: [(‘A’, 2)] All the combination of string in sorted order(without replacement) is: [(‘A’, ‘B’)] All the combination of list in sorted order(without replacement) is: [(0, ), (1, )]
Combinations_with_replacement(): This function returns a subsequence of length n from the elements of the iterable where n is the argument that the function takes determining the length of the subsequences generated by the function. Individual elements may repeat itself in combinations_with_replacement function.

Example:

Python3

from itertools import combinations_with_replacement print ( “All the combination of string in sorted order(with replacement) is:” ) print ( list (combinations_with_replacement( “AB” , 2 ))) print () print ( “All the combination of list in sorted order(with replacement) is:” ) print ( list (combinations_with_replacement([ 1 , 2 ], 2 ))) print () print ( “All the combination of container in sorted order(with replacement) is:” ) print ( list (combinations_with_replacement( range ( 2 ), 1 )))

Output:

All the combination of string in sorted order(with replacement) is: [(‘A’, ‘A’), (‘A’, ‘B’), (‘B’, ‘B’)] All the combination of list in sorted order(with replacement) is: [(1, 1), (1, 2), (2, 2)] All the combination of container in sorted order(with replacement) is: [(0, ), (1, )]
Terminating iterators

Terminating iterators are used to work on the short input sequences and produce the output based on the functionality of the method used.

Different types of terminating iterators are:

accumulate(iter, func): This iterator takes two arguments, iterable target and the function which would be followed at each iteration of value in target. If no function is passed, addition takes place by default. If the input iterable is empty, the output iterable will also be empty.

Example:

Python3

import itertools import operator li1 = [ 1 , 4 , 5 , 7 ] print ( “The sum after each iteration is : ” , end = “”) print ( list (itertools.accumulate(li1))) print ( “The product after each iteration is : ” , end = “”) print ( list (itertools.accumulate(li1, operator.mul))) print ( “The sum after each iteration is : ” , end = “”) print ( list (itertools.accumulate(li1))) print ( “The product after each iteration is : ” , end = “”) print ( list (itertools.accumulate(li1, operator.mul)))

Output:

The sum after each iteration is : [1, 5, 10, 17] The product after each iteration is : [1, 4, 20, 140] The sum after each iteration is : [1, 5, 10, 17] The product after each iteration is : [1, 4, 20, 140]
chain(iter1, iter2..): This function is used to print all the values in iterable targets one after another mentioned in its arguments.

Example:

Python3

import itertools li1 = [ 1 , 4 , 5 , 7 ] li2 = [ 1 , 6 , 5 , 9 ] li3 = [ 8 , 10 , 5 , 4 ] print ( “All values in mentioned chain are : ” , end = “”) print ( list (itertools.chain(li1, li2, li3)))

Output:

All values in mentioned chain are : [1, 4, 5, 7, 1, 6, 5, 9, 8, 10, 5, 4]
chain.from_iterable(): This function is implemented similarly as a chain() but the argument here is a list of lists or any other iterable container.

Example:

Python3

import itertools li1 = [ 1 , 4 , 5 , 7 ] li2 = [ 1 , 6 , 5 , 9 ] li3 = [ 8 , 10 , 5 , 4 ] li4 = [li1, li2, li3] print ( “All values in mentioned chain are : ” , end = “”) print ( list (itertools.chain.from_iterable(li4)))

Output:

All values in mentioned chain are : [1, 4, 5, 7, 1, 6, 5, 9, 8, 10, 5, 4]
compress(iter, selector): This iterator selectively picks the values to print from the passed container according to the boolean list value passed as other arguments. The arguments corresponding to boolean true are printed else all are skipped.

Example:

Python3

import itertools print ( “The compressed values in string are : ” , end = “”) print ( list (itertools.compress( ‘GEEKSFORGEEKS’ , [ 1 , 0 , 0 , 0 , 0 , 1 , 0 , 0 , 1 , 0 , 0 , 0 , 0 ])))

Output:

The compressed values in string are : [‘G’, ‘F’, ‘G’]
dropwhile(func, seq): This iterator starts printing the characters only after the func. in argument returns false for the first time.

Example:

Python3

import itertools li = [ 2 , 4 , 5 , 7 , 8 ] print ( “The values after condition returns false : ” , end = “”) print ( list (itertools.dropwhile( lambda x : x % 2 = = 0 , li)))

Output:

The values after condition returns false : [5, 7, 8]
filterfalse(func, seq): As the name suggests, this iterator prints only values that return false for the passed function.

Example:

Python3

import itertools li = [ 2 , 4 , 5 , 7 , 8 ] print ( “The values that return false to function are : ” , end = “”) print ( list (itertools.filterfalse( lambda x : x % 2 = = 0 , li)))

Output:

The values that return false to function are : [5, 7]
islice(iterable, start, stop, step): This iterator selectively prints the values mentioned in its iterable container passed as argument. This iterator takes 4 arguments, iterable container, starting pos., ending position and step.

Example:

Python3

import itertools li = [ 2 , 4 , 5 , 7 , 8 , 10 , 20 ] print ( “The sliced list values are : ” , end = “”) print ( list (itertools.islice(li, 1 , 6 , 2 )))

Output:

The sliced list values are : [4, 7, 10]
starmap(func., tuple list): This iterator takes a function and tuple list as argument and returns the value according to the function from each tuple of the list.

Example:

Python3

import itertools li = [ ( 1 , 10 , 5 ), ( 8 , 4 , 1 ), ( 5 , 4 , 9 ), ( 11 , 10 , 1 ) ] print ( “The values acc. to function are : ” , end = “”) print ( list (itertools.starmap( min , li)))

Output:

The values acc. to function are : [1, 1, 4, 1]
takewhile(func, iterable): This iterator is the opposite of dropwhile(), it prints the values till the function returns false for 1st time.

Example:

Python3

import itertools li = [ 2 , 4 , 6 , 7 , 8 , 10 , 20 ] print ( “The list values till 1st false value are : ” , end = “”) print ( list (itertools.takewhile( lambda x : x % 2 = = 0 , li )))

Output:

The list values till 1st false value are : [2, 4, 6]
tee(iterator, count):- This iterator splits the container into a number of iterators mentioned in the argument.

Example:

Python3

import itertools li = [ 2 , 4 , 6 , 7 , 8 , 10 , 20 ] iti = iter (li) it = itertools.tee(iti, 3 ) print ( “The iterators are : ” ) for i in range ( 0 , 3 ): print ( list (it[i]))

Output:

The iterators are : [2, 4, 6, 7, 8, 10, 20] [2, 4, 6, 7, 8, 10, 20] [2, 4, 6, 7, 8, 10, 20]
zip_longest( iterable1, iterable2, fillval): This iterator prints the values of iterables alternatively in sequence. If one of the iterables is printed fully, the remaining values are filled by the values assigned to fillvalue.

Example:

Python3

import itertools print ( “The combined values of iterables is : ” ) print ( * (itertools.zip_longest( ‘GesoGes’ , ‘ekfrek’ , fillvalue = ‘_’ )))

Output:

The combined values of iterables is : (‘G’, ‘e’) (‘e’, ‘k’) (‘s’, ‘f’) (‘o’, ‘r’) (‘G’, ‘e’) (‘e’, ‘k’) (‘s’, ‘_’)

So you have finished reading the 파이썬 itertools topic article, if you find this article useful, please share it. Thank you very much. See more: 파이썬 itertools cycle, 파이썬 itertools chain, 파이썬 itertools combinations, Itertools, 파이썬 itertools product, 파이썬 itertools groupby, Import itertools, 파이썬 tee

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itertools â í¨ì¨ì ì¸ ë£¨íì ìí ì´í°ë ì´í°ë¥¼ ë§ëë í¨ì — Python 3.8.13 ë¬¸ì

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itertools â í¨ì¨ì ì¸ ë£¨íì ìí ì´í°ë ì´í°ë¥¼ ë§ëë í¨ì — Python 3.8.13 ë¬¸ì