Python面试题【数据结构和算法部分131-160】

Python面试题【数据结构和算法部分131-160】

Python面试题【数据结构和算法部分131-160】

  1. 问题:在Python中如何实现一个优先队列?
    答案:
python 复制代码
    import heapq

    class PriorityQueue:
        def __init__(self):
            self._queue = []
            self._index = 0

        def push(self, item, priority):
            heapq.heappush(self._queue, (-priority, self._index, item))
            self._index += 1

        def pop(self):
            return heapq.heappop(self._queue)[-1]
  1. 问题:如何在Python中实现一个循环数组?
    答案:
python 复制代码
    class CircularArray:
        def __init__(self, size):
            self.array = [None] * size
            self.size = size
            self.head = 0

        def get(self, index):
            return self.array[(self.head + index) % self.size]

        def set(self, index, value):
            self.array[(self.head + index) % self.size] = value

        def rotate(self, shift):
            self.head = (self.head + shift) % self.size
  1. 问题:如何在Python中检查一个数是否是快乐数?
    答案:
python 复制代码
    def is_happy(n):
        seen = set()
        while n != 1 and n not in seen:
            seen.add(n)
            n = sum(int(i)**2 for i in str(n))
        return n == 1
  1. 问题:Python中如何实现计数排序?
    答案:
python 复制代码
    def counting_sort(arr):
        count = [0] * (max(arr) + 1)
        for num in arr:
            count[num] += 1
        i = 0
        for num, freq in enumerate(count):
            for _ in range(freq):
                arr[i] = num
                i += 1
        return arr
  1. 问题:如何在Python中找到所有可能的排列组合?
    答案:
python 复制代码
    from itertools import permutations

    def get_permutations(arr):
        return list(permutations(arr))
  1. 问题:在Python中如何实现希尔排序?
    答案:
python 复制代码
    def shell_sort(arr):
        n = len(arr)
        gap = n // 2
        while gap > 0:
            for i in range(gap, n):
                temp = arr[i]
                j = i
                while j >= gap and arr[j - gap] > temp:
                    arr[j] = arr[j - gap]
                    j -= gap
                arr[j] = temp
            gap //= 2
        return arr
  1. 问题:在Python中如何实现最小生成树算法?
    答案:

    可以使用Kruskal或Prim算法实现最小生成树。这些算法通过选择边的方式来构造树,以确保树的权重总和最小,且不形成环。

  2. 问题:如何在Python中实现KMP字符串匹配算法?
    答案:

    KMP算法通过计算一个"部分匹配"表来改善匹配过程,减少比较的次数。

  3. 问题:在Python中如何实现冒泡排序?
    答案:

python 复制代码
    def bubble_sort(arr):
        n = len(arr)
        for i in range(n):
            for j in range(0, n-i-1):
                if arr[j] > arr[j+1]:
                    arr[j], arr[j+1] = arr[j+1], arr[j]
        return arr
  1. 问题:在Python中如何实现基数排序?
    答案:
python 复制代码
    def radix_sort(arr):
        RADIX = 10
        placement = 1
        max_digit = max(arr)

        while placement < max_digit:
            buckets = [[] for _ in range(RADIX)]
            for i in arr:
                tmp = int((i / placement) % RADIX)
                buckets[tmp].append(i)
            a = 0
            for b in range(RADIX):
                buck = buckets[b]
                for i in buck:
                    arr[a] = i
                    a += 1
            placement *= RADIX
        return arr
  1. 问题:如何在Python中实现深度优先搜索(DFS)用于图的遍历?
    答案:
python 复制代码
    def dfs(graph, start, visited=None):
        if visited is None:
            visited = set()
        visited.add(start)
        for next in graph[start] - visited:
            dfs(graph, next, visited)
        return visited
  1. 问题:在Python中如何使用广度优先搜索(BFS)找到图中从起点到终点的最短路径?
    答案:
python 复制代码
    from collections import deque

    def bfs_shortest_path(graph, start, goal):
        explored = set()
        queue = deque([(start, [start])])
        while queue:
            current, path = queue.popleft()
            if current == goal:
                return path
            for next in graph[current]:
                if next not in explored:
                    explored.add(next)
                    queue.append((next, path + [next]))
        return None
  1. 问题:如何在Python中检测有向图中的环?
    答案:
python 复制代码
    def detect_cycle(graph):
        WHITE, GRAY, BLACK = 0, 1, 2
        color = {u: WHITE for u in graph}
        
        def dfs(node):
            if color[node] == GRAY:
                return True
            if color[node] == BLACK:
                return False
            color[node] = GRAY
            for neighbour in graph[node]:
                if dfs(neighbour):
                    return True
            color[node] = BLACK
            return False
        
        for node in graph:
            if color[node] == WHITE:
                if dfs(node):
                    return True
        return False
  1. 问题:如何在Python中实现Floyd-Warshall算法?
    答案:
python 复制代码
    def floyd_warshall(weights):
        V = len(weights)
        dist = list(map(lambda i: list(map(lambda j: j, i)), weights))
        for k in range(V):
            for i in range(V):
                for j in range(V):
                    dist[i][j] = min(dist[i][j], dist[i][k] + dist[k][j])
        return dist
  1. 问题:如何在Python中实现Dijkstra算法?
    答案:
python 复制代码
    import heapq

    def dijkstra(graph, start):
        min_dist = {vertex: float('infinity') for vertex in graph}
        min_dist[start] = 0
        pq = [(0, start)]
        
        while pq:
            current_dist, current_vertex = heapq.heappop(pq)
            
            if current_dist > min_dist[current_vertex]:
                continue
            
            for neighbor, weight in graph[current_vertex].items():
                distance = current_dist + weight
                
                if distance < min_dist[neighbor]:
                    min_dist[neighbor] = distance
                    heapq.heappush(pq, (distance, neighbor))
                    
        return min_dist
  1. 问题:如何在Python中找出数组中的第k个最大元素?
    答案:
python 复制代码
    import heapq

    def findKthLargest(nums, k):
        return heapq.nlargest(k, nums)[-1]
  1. 问题:在Python中如何实现并查集?
    答案:
python 复制代码
    class UnionFind:
        def __init__(self, size):
            self.root = [i for i in range(size)]
        
        def find(self, x):
            while x != self.root[x]:
                x = self.root[x]
            return x
        
        def union(self, x, y):
            rootX = self.find(x)
            rootY = self.find(y)
            if rootX != rootY:
                self.root[rootY] = rootX
        
        def connected(self, x, y):
            return self.find(x) == self.find(y)
  1. 问题:如何在Python中实现二叉搜索树的插入操作?
    答案:
python 复制代码
    class TreeNode:
        def __init__(self, val=0, left=None, right=None):
            self.val = val
            self.left = left
            self.right = right

    def insert_into_bst(root, val):
        if not root:
            return TreeNode(val)
        if val < root.val:
            root.left = insert_into_bst(root.left, val)
        else:
            root.right = insert_into_bst(root.right, val)
        return root
  1. 问题:如何在Python中实现二叉树的后序遍历?
    答案:
python 复制代码
    def postorder_traversal(root):
        result = []
        if root:
            result += postorder_traversal(root.left)
            result += postorder_traversal(root.right)
            result.append(root.val)
        return result
  1. 问题:如何在Python中找到未排序数组中的最长连续序列?
    答案:
python 复制代码
    def longest_consecutive(nums):
        num_set = set(nums)
        longest = 0
        for num in num_set:
            if num - 1 not in num_set:
                current_num = num
                current_streak = 1
                
                while current_num + 1 in num_set:
                    current_num += 1
                    current_streak += 1
                
                longest = max(longest, current_streak)
        
        return longest
  1. 问题:在Python中如何实现线性查找?
    答案:
python 复制代码
    def linear_search(arr, x):
        for i in range(len(arr)):
            if arr[i] == x:
                return i
        return -1
  1. 问题:如何在Python中实现插入排序算法?
    答案:
python 复制代码
    def insertion_sort(arr):
        for i in range(1, len(arr)):
            key = arr[i]
            j = i - 1
            while j >= 0 and key < arr[j]:
                arr[j + 1] = arr[j]
                j -= 1
            arr[j + 1] = key
        return arr
  1. 问题:在Python中如何实现选择排序算法?
    答案:
python 复制代码
    def selection_sort(arr):
        for i in range(len(arr)):
            min_idx = i
            for j in range(i+1, len(arr)):
                if arr[min_idx] > arr[j]:
                    min_idx = j
            arr[i], arr[min_idx] = arr[min_idx], arr[i]
        return arr
  1. 问题:如何在Python中找到数组中的峰值元素?
    答案:
python 复制代码
    def find_peak_element(nums):
        left, right = 0, len(nums) - 1
        while left < right:
            mid = (left + right) // 2
            if nums[mid] > nums[mid + 1]:
                right = mid
            else:
                left = mid + 1
        return left
  1. 问题:在Python中如何实现桶排序算法?
    答案:
python 复制代码
    def bucket_sort(arr):
        max_value = max(arr)
        size = max_value // len(arr)
        buckets = [[] for _ in range(size)]
        for i in range(len(arr)):
            j = arr[i] // size
            if j != size:
                buckets[j].append(arr[i])
            else:
                buckets[size - 1].append(arr[i])
        for i in range(size):
            insertion_sort(buckets[i])
        result = []
        for i in range(size):
            result = result + buckets[i]
        return result
  1. 问题:如何在Python中实现计算一个数的幂?
    答案:
python 复制代码
    def power(x, n):
        if n == 0:
            return 1
        elif n % 2 == 0:
            return power(x, n // 2) ** 2
        else:
            return x * power(x, n // 2) ** 2
  1. 问题:在Python中如何在一个包含从0到n的整数的数组中找到缺失的数字?
    答案:
python 复制代码
    def missing_number(nums):
        n = len(nums)
        expected_sum = n * (n + 1) // 2
        actual_sum = sum(nums)
        return expected_sum - actual_sum
  1. 问题:在Python中如何实现二叉树的前序遍历?
    答案:
python 复制代码
    def preorder_traversal(root):
        result = []
        if root:
            result.append(root.val)
            result += preorder_traversal(root.left)
            result += preorder_traversal(root.right)
        return result
  1. 问题:如何在Python中实现一个简单的散列表?
    答案:
python 复制代码
    class HashTable:
        def __init__(self, size):
            self.size = size
            self.table = [None] * size
        
        def hash_function(self, key):
            return key % self.size
        
        def insert(self, key, value):
            hash_index = self.hash_function(key)
            self.table[hash_index] = value
        
        def get(self, key):
            hash_index = self.hash_function(key)
            return self.table[hash_index]
  1. 问题:在Python中如何找到第n个斐波那契数?
    答案:
python 复制代码
    def fibonacci(n):
        a, b = 0, 1
        for _ in range(n):
            a, b = b, a + b
        return a
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