hello-algo/codes/python/chapter_heap/heap.py
2023-10-19 16:21:51 +08:00

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"""
File: heap.py
Created Time: 2023-02-23
Author: Krahets (krahets@163.com)
"""
import sys
from pathlib import Path
sys.path.append(str(Path(__file__).parent.parent))
from modules import print_heap
import heapq
def test_push(heap: list, val: int, flag: int = 1):
heapq.heappush(heap, flag * val) # 元素入堆
print(f"\n元素 {val} 入堆后")
print_heap([flag * val for val in heap])
def test_pop(heap: list, flag: int = 1):
val = flag * heapq.heappop(heap) # 堆顶元素出堆
print(f"\n堆顶元素 {val} 出堆后")
print_heap([flag * val for val in heap])
"""Driver Code"""
if __name__ == "__main__":
# 初始化小顶堆
min_heap, flag = [], 1
# 初始化大顶堆
max_heap, flag = [], -1
print("\n以下测试样例为大顶堆")
# Python 的 heapq 模块默认实现小顶堆
# 考虑将“元素取负”后再入堆,这样就可以将大小关系颠倒,从而实现大顶堆
# 在本示例中flag = 1 时对应小顶堆flag = -1 时对应大顶堆
# 元素入堆
test_push(max_heap, 1, flag)
test_push(max_heap, 3, flag)
test_push(max_heap, 2, flag)
test_push(max_heap, 5, flag)
test_push(max_heap, 4, flag)
# 获取堆顶元素
peek: int = flag * max_heap[0]
print(f"\n堆顶元素为 {peek}")
# 堆顶元素出堆
test_pop(max_heap, flag)
test_pop(max_heap, flag)
test_pop(max_heap, flag)
test_pop(max_heap, flag)
test_pop(max_heap, flag)
# 获取堆大小
size: int = len(max_heap)
print(f"\n堆元素数量为 {size}")
# 判断堆是否为空
is_empty: bool = not max_heap
print(f"\n堆是否为空 {is_empty}")
# 输入列表并建堆
# 时间复杂度为 O(n) ,而非 O(nlogn)
min_heap = [1, 3, 2, 5, 4]
heapq.heapify(min_heap)
print("\n输入列表并建立小顶堆后")
print_heap(min_heap)