LeetCode 高频题详细题解 2025 升级，数学算法模板 + 大厂真题助你备战面试

def beautifulSubsets(nums, k):
    from collections import defaultdict
    count = 
    path = []
    
    def dfs(index):
        nonlocal count
        count += 
        for i in range(index, len(nums)):
            if nums[i] - k in path or nums[i] + k in path:
                continue
            path.append(nums[i])
            dfs(i + )
            path.pop()
    
    dfs()
    return count -   # 减去空集

def predict_markov(t, initial_state, transition_matrix):
    state = initial_state.copy()
    for _ in range(t):
        new_state = [0.0, 0.0, 0.0]
        for i in range():
            for j in range():
                new_state[i] += state[j] * transition_matrix[j][i]
        state = new_state
    return state[] > 0.5

class MyHashMap:
    def __init__(self):
        self.size = 
        self.buckets = [[] for _ in range(self.size)]
    
    def hash(self, key):
        return key % self.size
    
    def put(self, key, value):
        bucket = self.buckets[self.hash(key)]
        for i, (k, v) in enumerate(bucket):
            if k == key:
                bucket[i] = (key, value)
                return
        bucket.append((key, value))
    
    def get(self, key):
        bucket = self.buckets[self.hash(key)]
        for k, v in bucket:
            if k == key:
                return v
        return -
    
    def remove(self, key):
        bucket = self.buckets[self.hash(key)]
        for i, (k, v) in enumerate(bucket):
            if k == key:
                del bucket[i]
                return