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translation: Add Python and Java code for EN version (#1345)
* Add the intial translation of code of all the languages * test * revert * Remove * Add Python and Java code for EN version
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en/codes/python/chapter_backtracking/subset_sum_ii.py
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52
en/codes/python/chapter_backtracking/subset_sum_ii.py
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"""
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File: subset_sum_ii.py
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Created Time: 2023-06-17
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Author: krahets (krahets@163.com)
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"""
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def backtrack(
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state: list[int], target: int, choices: list[int], start: int, res: list[list[int]]
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):
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"""Backtracking algorithm: Subset Sum II"""
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# When the subset sum equals target, record the solution
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if target == 0:
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res.append(list(state))
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return
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# Traverse all choices
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# Pruning two: start traversing from start to avoid generating duplicate subsets
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# Pruning three: start traversing from start to avoid repeatedly selecting the same element
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for i in range(start, len(choices)):
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# Pruning one: if the subset sum exceeds target, end the loop immediately
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# This is because the array is sorted, and later elements are larger, so the subset sum will definitely exceed target
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if target - choices[i] < 0:
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break
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# Pruning four: if the element equals the left element, it indicates that the search branch is repeated, skip it
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if i > start and choices[i] == choices[i - 1]:
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continue
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# Attempt: make a choice, update target, start
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state.append(choices[i])
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# Proceed to the next round of selection
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backtrack(state, target - choices[i], choices, i + 1, res)
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# Retract: undo the choice, restore to the previous state
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state.pop()
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def subset_sum_ii(nums: list[int], target: int) -> list[list[int]]:
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"""Solve Subset Sum II"""
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state = [] # State (subset)
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nums.sort() # Sort nums
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start = 0 # Start point for traversal
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res = [] # Result list (subset list)
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backtrack(state, target, nums, start, res)
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return res
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"""Driver Code"""
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if __name__ == "__main__":
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nums = [4, 4, 5]
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target = 9
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res = subset_sum_ii(nums, target)
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print(f"Input array nums = {nums}, target = {target}")
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print(f"All subsets equal to {target} res = {res}")
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