My Python Backtracking solution use O(n) space

  • 0
    class Solution(object):
        def solveNQueens(self, n):
            :type n: int
            :rtype: List[List[str]]
            if not n:
                return [[]]
            self.res = []
            self.n = n
            for i in range(n):
                select = [True for j in range(n)]
                select[i] = False
                self.dfs(select, i, [i])
            return self.res
        def dfs(self, select, prev, valuelist):
            # print valuelist
            if len(valuelist) == self.n:
                temp = []
                for i in range(self.n):
                    row = ['.' for j in range(self.n)]
                    pos = valuelist[i]
                    row[pos] = 'Q'
            for i in range(self.n):
                if select[i] and self.diagnol(valuelist, i):
                    newlist = select[:]
                    newlist[i] = False
                    self.dfs(newlist, i, valuelist + [i])
        def diagnol(self, valuelist, pos):
            length = len(valuelist)
            l = length
            for x in valuelist:
                if pos == x - l or pos == x + l:
                    return False
                l -= 1
            return True

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