Python每日一练(20230416)

简介: Python每日一练(20230416)

1. 有效数字


有效数字(按顺序)可以分成以下几个部分:


  1. 一个 小数 或者 整数
  2.    (可选)一个 'e' 或 'E' ,后面跟着一个 整数

小数(按顺序)可以分成以下几个部分:

   (可选)一个符号字符('+' 或 '-')

   下述格式之一:

       至少一位数字,后面跟着一个点 '.'

       至少一位数字,后面跟着一个点 '.' ,后面再跟着至少一位数字

       一个点 '.' ,后面跟着至少一位数字

整数(按顺序)可以分成以下几个部分:

   (可选)一个符号字符('+' 或 '-')

   至少一位数字


部分有效数字列举如下:

   ["2", "0089", "-0.1", "+3.14", "4.", "-.9", "2e10", "-90E3", "3e+7", "+6e-1", "53.5e93", "-123.456e789"]


部分无效数字列举如下:

   ["abc", "1a", "1e", "e3", "99e2.5", "--6", "-+3", "95a54e53"]

给你一个字符串 s ,如果 s 是一个 有效数字 ,请返回 true 。


示例 1:

输入:s = "0"

输出:true


示例 2:

输入:s = "e"

输出:false


示例 3:

输入:s = "."

输出:false


示例 4:

输入:s = ".1"

输出:true


提示:

   1 <= s.length <= 20

   s 仅含英文字母(大写和小写),数字(0-9),加号 '+' ,减号 '-' ,或者点 '.' 。

以下程序实现了这一功能,请你填补空白处内容:

```python

class Solution(object):
    def isNumber(self, s):
        s = s.strip()
        ls, pos = len(s), 0
        if ls == 0:
            return False
        if s[pos] == '+' or s[pos] == '-':
            pos += 1
        isNumeric = False
        while pos < ls and s[pos].isdigit():
            pos += 1
            isNumeric = True
        _____________________________;
        elif pos < ls and s[pos] == 'e' and isNumeric:
            isNumeric = False
            pos += 1
            if pos < ls and (s[pos] == '+' or s[pos] == '-'):
                pos += 1
            while pos < ls and s[pos].isdigit():
                pos += 1
                isNumeric = True
        if pos == ls and isNumeric:
            return True
        return False
# %%
s = Solution()
print(s.isNumber(s = "0"))
```

出处:

https://edu.csdn.net/practice/25740860

代码:

class Solution(object):
    def isNumber(self, s):
        s = s.strip()
        ls, pos = len(s), 0
        if ls == 0:
            return False
        if s[pos] == '+' or s[pos] == '-':
            pos += 1
        isNumeric = False
        while pos < ls and s[pos].isdigit():
            pos += 1
            isNumeric = True
        if pos < ls and s[pos] == '.':
            pos += 1
            while pos < ls and s[pos].isdigit():
                pos += 1
                isNumeric = True
        elif pos < ls and s[pos] == 'e' and isNumeric:
            isNumeric = False
            pos += 1
            if pos < ls and (s[pos] == '+' or s[pos] == '-'):
                pos += 1
            while pos < ls and s[pos].isdigit():
                pos += 1
                isNumeric = True
        if pos == ls and isNumeric:
            return True
        return False
# %%
s = Solution()
print(s.isNumber(s = "0"))
print(s.isNumber(s = "e"))
print(s.isNumber(s = "."))
print(s.isNumber(s = ".1"))


输出:

True

False

False

True


2. 二叉树的最大深度

给定一个二叉树,找出其最大深度。


二叉树的深度为根节点到最远叶子节点的最长路径上的节点数。

说明: 叶子节点是指没有子节点的节点。

示例:

给定二叉树 [3,9,20,null,null,15,7],

    3

   / \

  9  20

/  \

15   7

返回它的最大深度 3 。

出处:

https://edu.csdn.net/practice/25740861

代码:


class TreeNode:
     def __init__(self, x):
         self.val = x
         self.left = None
         self.right = None
def listToTree(lst: list) -> TreeNode:
    if not lst:
        return None
    root = TreeNode(lst[0])
    queue = [root]
    i = 1
    while i < len(lst):
        node = queue.pop(0)
        if lst[i] is not None:
            node.left = TreeNode(lst[i])
            queue.append(node.left)
        i += 1
        if i < len(lst) and lst[i] is not None:
            node.right = TreeNode(lst[i])
            queue.append(node.right)
        i += 1
    return root
class Solution:
    def maxDepth(self, root: TreeNode) -> int:
        if root is None:
            return 0
        maxdepth = max(self.maxDepth(root.left),self.maxDepth(root.right)) + 1
        return maxdepth
# %%
s = Solution()
null = None
nums = [3,9,20,null,null,15,7]
root = listToTree(nums)
print(s.maxDepth(root))



输出:

3

代码2:DFS

class TreeNode:
     def __init__(self, x):
         self.val = x
         self.left = None
         self.right = None
def listToTree(lst: list) -> TreeNode:
    if not lst:
        return None
    root = TreeNode(lst[0])
    queue = [root]
    i = 1
    while i < len(lst):
        node = queue.pop(0)
        if lst[i] is not None:
            node.left = TreeNode(lst[i])
            queue.append(node.left)
        i += 1
        if i < len(lst) and lst[i] is not None:
            node.right = TreeNode(lst[i])
            queue.append(node.right)
        i += 1
    return root
class Solution:
    def maxDepth(self, root: TreeNode):
        if not root:
            return 0
        depth = []
        def dfs(node, nodes=[]):
            if not node:
                return
            nodes.append(node.val)
            if node.left or node.right:
                dfs(node.left, nodes)
                dfs(node.right, nodes)
            else:
                depth.append(len(nodes))
            nodes.pop()
        dfs(root)
        return max(depth)
# %%
s = Solution()
null = None
nums = [3,9,20,null,null,15,7]
root = listToTree(nums)
print(s.maxDepth(root))





3. 单词搜索


给定一个 m x n 二维字符网格 board 和一个字符串单词 word 。如果 word 存在于网格中,返回 true ;否则,返回 false 。


单词必须按照字母顺序,通过相邻的单元格内的字母构成,其中“相邻”单元格是那些水平相邻或垂直相邻的单元格。同一个单元格内的字母不允许被重复使用。


示例 1:


image.jpeg

image.jpeg



输入:board = [["A","B","C","E"],["S","F","C","S"],["A","D","E","E"]], word = "ABCCED"

输出:true

示例 2:

56b7681c631f1e73b77fe9a7475033ea.jpeg

输入:board = [["A","B","C","E"],["S","F","C","S"],["A","D","E","E"]], word = "SEE"

输出:true

示例 3:

输入:board = [["A","B","C","E"],["S","F","C","S"],["A","D","E","E"]], word = "ABCB"

输出:false



提示:

   m == board.length

   n = board[i].length

   1 <= m, n <= 6

   1 <= word.length <= 15

   board 和 word 仅由大小写英文字母组成


进阶:你可以使用搜索剪枝的技术来优化解决方案,使其在 board 更大的情况下可以更快解决问题?

出处:

https://edu.csdn.net/practice/25740862

代码:


class Solution(object):
    def exist(self, board, word):
        """
        :type board: List[List[str]]
        :type word: str
        :rtype: bool
        """
        check_board = [[True] * len(board[0]) for _ in range(len(board))]
        for i in range(len(board)):
            for j in range(len(board[0])):
                if board[i][j] == word[0] and check_board:
                    check_board[i][j] = False
                    res = self.check_exist(check_board, board, word, 1, len(word), i, j)
                    if res:
                        return True
                    check_board[i][j] = True
        return False
    def check_exist(self, check_board, board, word, index, ls, row, col):
        if index == ls:
            return True
        for temp in [(0, 1),(0, -1),(1, 0),(-1, 0)]:
            curr_row = row + temp[0]
            curr_col = col + temp[1]
            if curr_row >= 0 and curr_row < len(board) and curr_col >= 0 and curr_col < len(board[0]):
                if check_board[curr_row][curr_col] and board[curr_row][curr_col] == word[index]:
                    check_board[curr_row][curr_col] = False
                    res = self.check_exist(check_board, board, word, index + 1, len(word), curr_row, curr_col)
                    if res:
                        return res
                    check_board[curr_row][curr_col] = True
        return False
if __name__ == "__main__":
    s = Solution()
    print (s.exist(board = [["A","B","C","E"],["S","F","C","S"],["A","D","E","E"]], word = "ABCCED"))


输出:

True

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