Python heapq.heappush() Method

heapq.heappush() function inserts an element into a heap while maintaining the heap property. It is commonly used to build and manage min-heaps, priority queues and other heap-based data structures.

Example: The following example inserts elements into a heap using heappush().

import heapq

h = []
heapq.heappush(h, 10)
heapq.heappush(h, 5)
heapq.heappush(h, 20)

print(h)

[5, 10, 20]

Explanation: heapq.heappush() inserts each element into h and automatically rearranges the heap so that the smallest element remains at index 0.

Syntax

heapq.heappush(heap, item)

Parameters:

• heap: The heap list where the element will be inserted.
• item: The value to be added to the heap.

Examples

Example 1: This example shows how heappush() maintains the min-heap property while inserting multiple values. The smallest element is always placed at the root of the heap.

import heapq

h = []
heapq.heappush(h, 5)
heapq.heappush(h, 1)
heapq.heappush(h, 8)
heapq.heappush(h, 3)

print(h)

[1, 3, 8, 5]

Explanation: Each call to heapq.heappush() inserts a value into h and rearranges the heap so that the minimum element stays at index 0.

Example 2: Since heapq implements a min-heap, we can simulate a max-heap by inserting negative values.

import heapq

h = []
for x in [5, 1, 8, 3]:
    heapq.heappush(h, -x)

print([-x for x in h])

[8, 3, 5, 1]

Explanation: Negative values are inserted using heapq.heappush(). The heap is maintained on negative numbers, and [-x for x in h] converts them back to positive values.

Example 3: This example uses tuples where the first value represents the priority and the second value represents the task.

import heapq

pq = []
heapq.heappush(pq, (2, "Task A"))
heapq.heappush(pq, (1, "Task B"))
heapq.heappush(pq, (3, "Task C"))

print(pq)

[(1, 'Task B'), (2, 'Task A'), (3, 'Task C')]

Explanation: heapq.heappush() orders the tuples based on the first element (priority). The task with the lowest priority value appears at the root of the heap.