为什么这两个代码的运行时间不同?

时间:2019-07-12 18:03:58

标签: python trie

我正在解决leetcode上的一个问题,并且注意到两个几乎相似的代码在不同的运行时,这两个代码之间的唯一区别是,在其中一个中,我创建了res数组作为Solution类实例变量,而在另一个中,res数组是临时。 下面是区别,慢了将近1.6倍 enter image description here

我尝试了多次,但时差仍然存在吗? 有人可以帮我知道原因吗?

代码1:

class Solution(object):
    def __init__(self):
        self.res = []

    def dfs(self,node,i,j,board,path):
        if not node:
            return
        if node.isComplete:
            self.res.append(path)
            #since we have already added this word we remove it from our trie.
            node.isComplete = False
        if i<0 or j<0 or i>=len(board) or j>=len(board[0]):
            return

        tmp = board[i][j]
        nextNode = node.children.get(tmp)
        board[i][j]='#'
        self.dfs(nextNode,i+1,j,board,path+tmp)
        self.dfs(nextNode,i-1,j,board,path+tmp)
        self.dfs(nextNode,i,j+1,board,path+tmp)
        self.dfs(nextNode,i,j-1,board,path+tmp)
        board[i][j]=tmp


    def findWords(self, board, words):
        trie = Trie()
        for w in words:
            trie.insert(w)
        root = trie.root
        for i in xrange(len(board)):
            for j in xrange(len(board[0])):
                self.dfs(root,i,j,board,"")
        return self.res

        """
        :type board: List[List[str]]
        :type words: List[str]
        :rtype: List[str]
        """

代码2:

class Solution(object):
    def findWords(self, board, words):
        res = []
        trie = Trie()
        node = trie.root
        for w in words:
            trie.insert(w)
        for i in xrange(len(board)):
            for j in xrange(len(board[0])):
                self.dfs(board, node, i, j, "", res)
        return res

    def dfs(self, board, node, i, j, path, res):
        if node.isWord:
            res.append(path)
            node.isWord = False
        if i < 0 or i >= len(board) or j < 0 or j >= len(board[0]):
            return 
        tmp = board[i][j]
        node = node.children.get(tmp)
        if not node:
            return 
        board[i][j] = "#"
        self.dfs(board, node, i+1, j, path+tmp, res)
        self.dfs(board, node, i-1, j, path+tmp, res)
        self.dfs(board, node, i, j-1, path+tmp, res)
        self.dfs(board, node, i, j+1, path+tmp, res)
        board[i][j] = tmp

0 个答案:

没有答案