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fix: blog post frontmatter to build #20

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Merged
q1zhen merged 1 commit into from
Jun 25, 2025
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fix: blog post frontmatter to build #20

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10 changes: 10 additions & 0 deletions src/content/blog/2025-06-20/index.md
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---
title: "Placeholder"
author: "Unknown"
date: "Jun 20, 2025"
description: "Placeholder content"
latex: true
pdf: true
---

Content coming soon.
2 changes: 1 addition & 1 deletion src/content/blog/2025-06-23/index.md
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Expand Up @@ -36,7 +36,7 @@ class PriorityQueue:
二叉堆的平衡性使其成为工业级应用的首选，尤其适合高频数据更新场景。

## 手撕二叉堆实现（代码核心部分）
二叉堆本质是完全二叉树，满足堆序性：父节点值始终大于或等于子节点值（最大堆）。其底层使用数组存储，索引映射关系为：父节点索引 $parent(i) = \lfloor (i-1)/2 \rfloor$，左子节点 $left\\_child(i) = 2i+1$，右子节点 $right\\_child(i) = 2i+2$。这种结构避免了指针开销，内存访问高效。
二叉堆本质是完全二叉树，满足堆序性：父节点值始终大于或等于子节点值（最大堆）。其底层使用数组存储，索引映射关系为：父节点索引 \( parent(i) = \lfloor (i-1)/2 \rfloor \)，左子节点 \( \text{left\_child}(i) = 2i+1 \)，右子节点 \( \text{right\_child}(i) = 2i+2 \)。这种结构避免了指针开销，内存访问高效。

关键操作包括上浮（Heapify Up）和下沉（Heapify Down）。上浮用于插入后维护堆结构，从新元素位置向上比较并交换，直至满足堆性质。以下 Python 代码实现上浮逻辑：

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