FAST Unique Combinations (from List With Duplicates) WITHOUT LOOKUPS
Solution 1:
Instead of post-processing/filtering your output, you can pre-process your input list. This way, you can avoid generating duplicates in the first place. Pre-processing involves either sorting (or using a collections.Counter
on) the input. One possible recursive realization is:
def subbags(bag, k):
a = sorted(bag)
n = len(a)
sub = []
def index_of_next_unique_item(i):
j = i + 1
while j < n and a[j] == a[i]:
j += 1
return j
def combinate(i):
if len(sub) == k:
yield tuple(sub)
elif n - i >= k - len(sub):
sub.append(a[i])
yield from combinate(i + 1)
sub.pop()
yield from combinate(index_of_next_unique_item(i))
yield from combinate(0)
bag = [1, 2, 3, 1, 2, 1]
k = 3
i = -1
print(sorted(bag), k)
print('---')
for i, subbag in enumerate(subbags(bag, k)):
print(subbag)
print('---')
print(i + 1)
Output:
[1, 1, 1, 2, 2, 3] 3
---
(1, 1, 1)
(1, 1, 2)
(1, 1, 3)
(1, 2, 2)
(1, 2, 3)
(2, 2, 3)
---
6
Requires some stack space for the recursion, but this + sorting the input should use substantially less time + memory than generating and discarding repeats.
Solution 2:
The current state-of-the-art inspired initially by a 50 than by a 100 reps bounties is at the moment (instead of a Python extension module written entirely in C):
An efficient algorithm and implementation that is better than the obvious
(set + combinations)
approach in the best (and average) case, and is competitive with it in the worst case.
It seems to be possible to fulfill this requirement using a kind of "fake it before you make it" approach. The current state-of-the-art is that there are two generator function algorithms available for solving the problem of getting unique combinations in case of a non-unique list. The below provided algorithm combines both of them what becomes possible because it seems to exist a threshold value for percentage of unique items in the list which can be used for appropriate switching between the two algorithms. The calculation of the percentage of uniqueness is done with so tiny amount of computation time that it even doesn't clearly show up in the final results due to common variation of the taken timing.
def iterFastUniqueCombos(lstList, comboSize, percUniqueThresh=60):
lstListSorted = sorted(lstList)
lenListSorted = len(lstListSorted)
percUnique = 100.0 - 100.0*(lenListSorted-len(set(lstListSorted)))/lenListSorted
lstComboCandidate = []
setUniqueCombos = set()
def idxNextUnique(idxItemOfList):
idxNextUniqueCandidate = idxItemOfList + 1
while (
idxNextUniqueCandidate < lenListSorted
and
lstListSorted[idxNextUniqueCandidate] == lstListSorted[idxItemOfList]
): # while
idxNextUniqueCandidate += 1
idxNextUnique = idxNextUniqueCandidate
return idxNextUnique
def combinate(idxItemOfList):
if len(lstComboCandidate) == sizeOfCombo:
yield tuple(lstComboCandidate)
elif lenListSorted - idxItemOfList >= sizeOfCombo - len(lstComboCandidate):
lstComboCandidate.append(lstListSorted[idxItemOfList])
yield from combinate(idxItemOfList + 1)
lstComboCandidate.pop()
yield from combinate(idxNextUnique(idxItemOfList))
if percUnique > percUniqueThresh:
from itertools import combinations
allCombos = combinations(lstListSorted, comboSize)
for comboCandidate in allCombos:
if comboCandidate in setUniqueCombos:
continue
yield comboCandidate
setUniqueCombos.add(comboCandidate)
else:
yield from combinate(0)
#:if/else
#:def iterFastUniqueCombos()
The below provided timings show that the above iterFastUniqueCombos()
generator function provides a clear advantage
over uniqueCombinations()
variant in case the list has less than 60 percent of unique elements and is not worse as
the on (set + combinations)
based uniqueCombinations()
generator function in the opposite case where it gets much faster than the iterUniqueCombos()
one (due to switching between
the (set + combinations)
and the (no lookups)
variant at 60% threshold for amount of unique elements in the list):
=========== sizeOfCombo: 6 sizeOfList: 48 noOfUniqueInList 1 percUnique 2
Combos: 12271512 print(len(list(combinations(lst,k)))) : 2.04968 seconds.
Combos: 1 print(len(list( iterUniqueCombos(lst,k)))) : 0.00011 seconds.
Combos: 1 print(len(list( iterFastUniqueCombos(lst,k)))) : 0.00008 seconds.
Combos: 1 print(len(list( uniqueCombinations(lst,k)))) : 3.61812 seconds.
========== sizeOfCombo: 6 sizeOfList: 48 noOfUniqueInList 48 percUnique 100
Combos: 12271512 print(len(list(combinations(lst,k)))) : 1.99383 seconds.
Combos: 12271512 print(len(list( iterUniqueCombos(lst,k)))) : 49.72461 seconds.
Combos: 12271512 print(len(list( iterFastUniqueCombos(lst,k)))) : 8.07997 seconds.
Combos: 12271512 print(len(list( uniqueCombinations(lst,k)))) : 8.11974 seconds.
========== sizeOfCombo: 6 sizeOfList: 48 noOfUniqueInList 27 percUnique 56
Combos: 12271512 print(len(list(combinations(lst,k)))) : 2.02774 seconds.
Combos: 534704 print(len(list( iterUniqueCombos(lst,k)))) : 1.60052 seconds.
Combos: 534704 print(len(list( iterFastUniqueCombos(lst,k)))) : 1.62002 seconds.
Combos: 534704 print(len(list( uniqueCombinations(lst,k)))) : 3.41156 seconds.
========== sizeOfCombo: 6 sizeOfList: 48 noOfUniqueInList 31 percUnique 64
Combos: 12271512 print(len(list(combinations(lst,k)))) : 2.03539 seconds.
Combos: 1114062 print(len(list( iterUniqueCombos(lst,k)))) : 3.49330 seconds.
Combos: 1114062 print(len(list( iterFastUniqueCombos(lst,k)))) : 3.64474 seconds.
Combos: 1114062 print(len(list( uniqueCombinations(lst,k)))) : 3.61857 seconds.
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