A heap is a special type of data structure that is a complete binary tree and also an ordered data structure. In a heap, the value of each node must be greater than or equal to (or less than or equal to) the value of its child nodes, this is known as the heap property of a heap structure. Based on the heap property, a heap can be divided into a max heap and a min heap.<\/p>\n
In a max heap, the parent node’s value is greater than or equal to its child node’s value, while in a min heap, the parent node’s value is smaller than or equal to its child node’s value. This means that in a max heap, the root node’s value is the largest, and in a min heap, the root node’s value is the smallest.<\/p>\n
Heaps are commonly used to implement algorithms such as Priority Queue and Heap Sort. In Python, you can use the built-in heapq module to work with heap data structures. This module provides functions like heapify() to convert a list into a heap, heappush() to insert an element into the heap, and heappop() to remove and return the smallest (or largest) element from the heap.<\/p>\n","protected":false},"excerpt":{"rendered":"
A heap is a special type of data structure that is a complete binary tree and also an ordered data structure. In a heap, the value of each node must be greater than or equal to (or less than or equal to) the value of its child nodes, this is known as the heap property […]<\/p>\n","protected":false},"author":14,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_import_markdown_pro_load_document_selector":0,"_import_markdown_pro_submit_text_textarea":"","footnotes":""},"categories":[1],"tags":[],"class_list":["post-28313","post","type-post","status-publish","format-standard","hentry","category-uncategorized"],"yoast_head":"\n