八大排序四大查询,哈希表,树的遍历,哈夫曼,多叉树,python+typescript版本
问题描述不够清晰,"八大排序四大查询"通常指的是数据库中的事务处理,"哈夫曼编码"与"多叉树"则不是常见的计算机术语,可能是特定领域的知识。"哈夫曼"通常指的是哈夫曼树,一种特定类型的二叉树,用于信源编码(数据压缩)。"多叉树"是每个节点有多于两个子节点的树。
如果你是在寻找如何在Python和TypeScript中实现这些概念,请提供具体的需求或问题。例如,排序算法可以用Python实现,如下:
# 冒泡排序
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
# 选择排序
def selection_sort(arr):
n = len(arr)
for i in range(n):
min_idx = i
for j in range(i+1, n):
if arr[j] < arr[min_idx]:
min_idx = j
arr[i], arr[min_idx] = arr[min_idx], arr[i]
return arr
# 插入排序
def insertion_sort(arr):
n = len(arr)
for i in range(1, n):
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
# 快速排序
def quicksort(arr):
if len(arr) <= 1:
return arr
pivot = arr[len(arr) // 2]
left = [x for x in arr if x < pivot]
middle = [x for x in arr if x == pivot]
right = [x for x in arr if x > pivot]
return quicksort(left) + middle + quicksort(right)
# 使用示例
arr = [3, 6, 8, 10, 1, 2, 1]
print("Bubble Sort:", bubble_sort(arr))
print("Selection Sort:", selection_sort(arr))
print("Insertion Sort:", insertion_sort(arr))
print("Quick Sort:", quicksort(arr))
对于查询操作,可以使用Python中的字典来实现简单的键值对查找。
# 查询操作示例
data = {
"name": "Alice",
"age": 30,
"city": "New York"
}
# 查询
name = data.get("name")
age = data.get("age")
city = data.get("city")
print(f"Name: {name}, Age: {age}, City: {city}")
对于哈夫曼编码,可以使用下面的Python代码实现:
# 哈夫曼编码
from collections import Counter
def huffman_codes(s):
freq = Counter(s)
tree = dict()
for char, freq in freq.items():
tree[char] = [freq, None, None]
queue = [x for x in tree.values()]
while len(queue) > 1:
queue.sort()
a = queue.pop(0)
b = queue.pop(0)
parent = [a[0] + b[0], a, b]
queue.append(parent)
def traverse(dic, char):
curr = dic
while curr[1] or curr[2]:
if not curr[1]:
char += '0'
curr =
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