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# Time Complexity: O(N^(T/M))
# N = number of candidates, T = target, M = smallest candidate
# The recursion tree has a maximum depth of T/M, and each level explores up to N choices.
# Space Complexity: O(T/M)
# For the recursion stack and the current combination. Excluding the space required for the output list.
class Solution:
def combinationSum(self, candidates: List[int], target: int) -> List[List[int]]:
answer = []
def backtrack(index, curr, tot_sum):
# Base case
if tot_sum == target:
answer.append(curr.copy())
return
# Pruning
if tot_sum > target:
return
for i in range(index, len(candidates)):
# Choose
curr.append(candidates[i])
# Explore
tot_sum += candidates[i]
backtrack(i, curr, tot_sum)
tot_sum -= candidates[i]
# Backtrack
curr.pop()
backtrack(0, [], 0)
return answer
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